New Technology-Based Firms in the New Millennium : Funding: an Enduring Problem [1 ed.] 9780857243744, 9780857243737

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NEW TECHNOLOGY-BASED FIRMS IN THE NEW MILLENNIUM VOLUME VIII

New Technology-Based Firms in the New Millennium Volume VII: The Production and Distribution of Knowledge (2009) Ray Oakey, Aard Groen, Gary Cook and Peter van der Sijde New Technology-Based Firms in the New Millennium Volume VI (2008) Aard Groen, Ray Oakey, Peter van der Sijde and Gary Cook New Technology-Based Firms in the New Millennium Volume V (2006) Aard Groen, Ray Oakey, Peter van der Sijde and Saleema Kauser New Technology-Based Firms in the New Millennium Volume IV (2005) Wim During, Ray Oakey and Saleema Kauser New Technology-Based Firms in the New Millennium Volume III (2004) Wim During, Ray Oakey and Saleema Kauser New Technology-Based Firms in the New Millennium Volume II (2002) Ray Oakey, Wim During and Saleema Kauser New Technology-Based Firms in the New Millennium Volume I (2001) Wim During, Ray Oakey and Saleema Kauser

NEW TECHNOLOGY-BASED FIRMS IN THE NEW MILLENNIUM VOLUME VIII

EDITED BY

RAY OAKEY Manchester Business School, Manchester, UK

AARD GROEN University of Twente, Enschede, The Netherlands

GARY COOK University of Liverpool Management School, Liverpool, UK

PETER VAN DER SIJDE VU University Amsterdam, Amsterdam, The Netherlands

United Kingdom  North America  Japan India  Malaysia  China

Emerald Group Publishing Limited Howard House, Wagon Lane, Bingley BD16 1WA, UK First edition 2010 Copyright r 2010 Emerald Group Publishing Limited Reprints and permission service Contact: [email protected] No part of this book may be reproduced, stored in a retrieval system, transmitted in any form or by any means electronic, mechanical, photocopying, recording or otherwise without either the prior written permission of the publisher or a licence permitting restricted copying issued in the UK by The Copyright Licensing Agency and in the USA by The Copyright Clearance Center. No responsibility is accepted for the accuracy of information contained in the text, illustrations or advertisements. The opinions expressed in these chapters are not necessarily those of the Editor or the publisher. British Library Cataloguing in Publication Data A catalogue record for this book is available from the British Library ISBN: 978-0-85724-373-7 ISSN: 1876-0228 (Series)

Emerald Group Publishing Limited, Howard House, Environmental Management System has been certified by ISOQAR to ISO 14001:2004 standards Awarded in recognition of Emerald’s production department’s adherence to quality systems and processes when preparing scholarly journals for print

Contents

Contributors

vii

1.

Introduction Ray Oakey and Gary Cook

1

2.

Defining University Spin-Offs Teresa Hogan and Quan Zhou

7

3.

Entrepreneurial-Innovative University Services: A Way to Integrate in the University’s Third Mission Mo´nica Arroyo-Va´zquez, Peter van der Sijde and Fernando Jime´nez-Sa´ez

4.

5.

6.

7.

8.

Linking Innovation and Entrepreneurship in Higher Education: A Study of Swedish Schools of Entrepreneurship A˚sa Lindholm Dahlstrand and Eva Berggren How Useful is the Stage Model Theory in Explaining the Capital Structure of Venture Capital-Backed and Non-Venture Capital-Backed Firms? Teresa Hogan and Elaine Hutson Who You are and What You do: The Role of Entrepreneurial Human Capital in the Demand and Supply of External Finance of High-Tech Start-Ups Panagiotis Ganotakis

25

35

51

69

Financing New Ventures: Attitudes Towards Public Innovation Support Charlotte Norrman and Magnus Klofsten

89

Small Firm Expectations from Acquisition in the ICT Industry: A Conceptual Framework for Stakeholder Analysis Caren Weinberg, Tim Minshall and Elizabeth Garnsey

111

vi 9.

10.

11.

12.

13.

14.

Contents Entrepreneurs’ Communicative Behaviour in Technology-Based versus Service-Based Businesses — A Resource Dependence Perspective Pia Ulvenblad

133

Knowledge-Intensive Entrepreneurship and the Voice-of-the-Consumer Basil G. Englis, Paula D. Englis, Aard Groen and Peter van der Sijde

147

Going Public: A Growth Opportunity for ‘Research-Intensive’ Companies. The El.En. Group Case Antonio Corvino, Giulia Romano and Ettore Spadafora

159

What are High-Technology Firms and What Drives Their Performance? Martin A. Sims and Nicholas O’Regan

173

Implementing Open Innovation: Challenges in Linking Strategic and Operational Factors for Large Firms Working with HTSFs Tim Minshall, Letizia Mortara and Johann Jakob Napp Forms of Market Orientation in French Young High-Technology Firms: A Typology Ste´phanie Petzold-Dumeynieux

189

211

Contributors

Mo´nica Arroyo-Va´zquez

INGENIO (CSIC-UPV), Universidad Polite´cnica de Valencia, Valencia, Spain

Eva Berggren

School of Business and Engineering, Halmstad University, Halmstad, Sweden

Antonio Corvino

Department of Business Administration, University of Foggia, Foggia, Italy

A˚sa Lindholm Dahlstrand

Centre for Innovation, Entrepreneurship and Learning Research, Halmstad University, Halmstad, Sweden

Paula D. Englis

Campbell School of Business, Berry College, Mount Berry, GA, USA

Basil G. Englis

Campbell School of Business, Berry College, Mount Berry, GA, USA

Panagiotis Ganotakis

Aston Business School, Aston University, Birmingham, UK

Elizabeth Garnsey

Institute for Manufacturing, University of Cambridge, Cambridge, UK

Aard Groen

University of Twente, Enschede, The Netherlands

Teresa Hogan

Dublin City University Business School, Dublin, Ireland

Elaine Hutson

Michael Smurfit Graduate Business School, University College Dublin, Co. Dublin, Ireland

Magnus Klofsten

Department of Management and Engineering, Linko¨ping University, Linko¨ping, Sweden

Tim Minshall

Institute for Manufacturing, University of Cambridge, Cambridge, UK

viii

Contributors

Letizia Mortara

Institute for Manufacturing, University of Cambridge, Cambridge, UK

Johann Jakob Napp

Institute for Manufacturing, University of Cambridge, Cambridge, UK

Charlotte Norrman

Department of Management and Engineering, Linko¨ping University, Linko¨ping, Sweden

Nicholas O’Regan

University of the West of England, Bristol, UK

Ste´phanie PetzoldDumeynieux

Bordeaux Management School, Talence, France

Giulia Romano

Department of Business Administration, University of Foggia, Foggia, Italy

Fernando Jime´nez-Sa´ez

INGENIO (CSIC-UPV), Universidad Polite´cnica de Valencia, Valencia, Spain

Martin A. Sims

University of Hertfordshire, Hatfield, UK

Ettore Spadafora

Department of Business Administration ‘‘Egidio Giannessi’’, University of Pisa, Pisa, Italy

Pia Ulvenblad

School of Business and Engineering, Halmstad University, Halmstad, Sweden

Peter van der Sijde

VU University Amsterdam, Amsterdam, The Netherlands

Caren Weinberg

Institute for Manufacturing, University of Cambridge, Cambridge, UK

Quan Zhou

Dublin City University Business School, Dublin, Ireland

Chapter 1

Introduction Ray Oakey and Gary Cook

The chapters of this volume have been derived from the best papers presented at the annual International High Technology Small Firms Conference held in Manchester in May 2007, a gathering occurring alternately in Manchester at Manchester Business School in the United Kingdom and at the University of Twente in the Netherlands. This latest contribution, volume eight, is part of a unique overall sequence of edited books that began in 1994 as New Technology-Based Firms in the 1990s. When writing the preface to the sixth volume of the ‘new millennium’ part of this series in 2008, we observed that government policy had shifted in the new millennium towards an emphasis on growth led by consumption underpinned by borrowing, to the neglect of our ability to produce. We subsequently sounded a warning that ‘y in the medium term, such economic growth based on borrowing will be difficult to sustain, at personal, corporate or national government levels. Thus, in the future, the governments of the Western developed nations must return to the business of supporting productive industries that allow us to sell our goods and services to other countries in order to pay for what we buy from them, thus creating a balanced world economic system’. The ensuing two years have not only dramatically shown the potency of that warning, but also profoundly changed the context within which policy towards the productive sector of the economy, and high technology small firms in particular, is now to be framed. Companies in almost all countries face credit rationing, with new small high risk firms being less favoured, as lenders either focus investment in established medium technology firms with a track record or suspend investment completely during the recession. Consumers, even if not creditconstrained, are more focused on retrenchment. Governments in most developed countries are faced with the tricky balancing act of reducing huge budget deficits while attempting to sustain weak and fragile recoveries. The United Kingdom exemplifies these trends, and in addition has seen a profound political shift with the ousting of the Labour government after 13 years in office, to be replaced by a

New Technology Based Firms in the New Millennium, Volume VIII Edited by R. Oakey, A. Groen, G. Cook and P. van der Sijde r 2010 Emerald Group Publishing Limited. All rights reserved.

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Ray Oakey and Gary Cook

Conservative–Liberal coalition government, which none of the political pundits predicted. The new administration has pinned its colours firmly to the ‘spending cuts mast’, ushering in severe reductions in public spending and placing its faith in the ability and willingness of private enterprise to propel the economy forward free from the burden of ‘big government’. The ‘axe’ of expenditure cuts is poised above the university sector in the United Kingdom, prompting concern that, by reducing expenditure, the government may be consuming the ‘seed corn’ of our future prosperity, whereas other developed country governments perceive a greater need to escape recession by investing in the production and dissemination of knowledge through their systems of higher education. This last point links to another warning raised in the preface to the sixth volume that developing economies, most notably China and India, are continuing on a path of rapid technological ‘catch-up’ and, indeed, are increasingly serious contenders in the knowledge-based economy. These events throw into sharp relief the need to improve our understanding of the processes which support invention and innovation, together with the start-up and survival of new technology-based firms. In addition, serious academic enquiry is also needed into the effectiveness of policy in these areas and how policy may be improved, both in terms of our better understanding of hightechnology entrepreneurship, and an impartial yet critical evaluation of past policy interventions. The chapters of the current volume continue a long-standing contribution to these endeavours, representing the best papers from our 2007 conference in Manchester. They fall into a number of key topic areas comprising ‘Promoting entrepreneurship through university-based programmes’, ‘The financing of new technology-based firms’, ‘‘Start-up strategies’ and ‘Drivers of superior performance’.

The Papers Promoting Entrepreneurship Through University-Based Programmes In Chapter 2, providing a contextual introduction to the issue of university spin-offs, Hogan and Quan Zhou seek to construct a better definition of what the term ‘spinoff’ should consist. After a wide-ranging review of previous attempts to define and classify aspects of the spin-off process, the authors offer their own ‘three-point’ checklist which seeks to clarify and define the ‘spin-off’ process. In conclusion, their paper seeks to assess the advantages and drawbacks of the system they recommend. This initial paper in this section is welcome since it illustrates that not only do academics differ over how to assist the ‘spin-off’ process, but they also often do not agree on how this process is to be defined. Arroyo-Va´zquez, van der Sijde and Jime´nez Sa´ez, in Chapter 3, argue that there needs to be an integrated approach to both encouragement of entrepreneurship and business support if the potential of entrepreneurial universities and their linked science parks are to be fully realised. They build a model of such an integrated

Introduction

3

approach based around four key processes: entrepreneurship support; creating an entrepreneurship culture; support for business launches and business development support. The underpinnings of each of these four key processes are developed in detail, leading to a rich template which identified how an array of stakeholders ought to be contributing to the overall system of entrepreneurship and business support. They demonstrate the applicability and utility of this framework by using it to analyse the case of the Polytechnic University of Valencia and its linked science parks, identifying some areas where resource gaps could be filled and improvements made. In Chapter 4, Lindholm Dahlstrand and Berggren analyse the similarities and differences between two cohorts of students, one graduating from a school of entrepreneurship and the other from an innovator–entrepreneur programme. This is directly relevant to the policy question of how best to promote entrepreneurship in general and academic entrepreneurship in particular. Their key conclusion is that a specific entrepreneurship education does positively influence the likelihood of entrepreneurial behaviour. Some key results emerge. Students who completed entrepreneurship courses exhibited significantly higher interest in starting a business and were much more likely actually to do so following graduation from their programme. However, the different structures of individual courses result in substantially variable results. Students from one programme, the entrepreneurship programme at the Chalmers School of Entrepreneurship, were much more likely to seek to establish a business exploiting someone else’s innovation than the other two programmes, reflecting the fact that Chalmers makes the greatest distinction between innovation and entrepreneurship. Graduates from the entrepreneurship programmes were more disposed to be active in seeking out new business opportunities and were thus more likely to become serial entrepreneurs.

The Financing of New Technology-Based Firms In Chapter 5, Hogan and Hutson explore the applicability of the conventional stage models of financing to the case of software firms. They split their sample into two groups, those backed by venture capital and those not. In neither case does the stage model describe financing behaviour well, although it fits the ‘non-venture capital backed group’ somewhat better. The ‘venture capital backed firms’ were particularly distinguished by the extent to which they relied on external sources at all stages of development from the ‘seed capital stage’ to ‘sustained growth’. Contrary to the conventional wisdom, these software firms experienced their most acute funding gap, not at start-up as is typical for new technology-based firms, but at the commercialisation stage. This was attributed to the relatively short lead times for product development in high-technology ventures. Given the evident shortage of bank financing at this stage in particular, there was a particular policy implication here, as well as the general point that since the new technology-based firms were a heterogeneous group, a ‘one size fits all’ policy approach was unlikely to succeed.

4

Ray Oakey and Gary Cook

Ganotakis, in Chapter 6, examines the influence of a number of entrepreneur and firm-specific factors on both demand for, and supply of, start-up finance to high-tech start-ups. This contrasts with the literature on this subject which has generally only considered either demand or supply in isolation. He found that more highly educated entrepreneurs were more likely to apply for external finance, while larger and older entrepreneurial teams were more likely to receive such finance. Otherwise, human capital does not seem to exert a significant influence on the likelihood of receiving external finance. Ganotakis finds no support for the theory that there are ‘discouraged potential borrowers’ or supply constraints caused by the founder’s poor human capital affecting the flow of finance to high-tech start-ups. He does find that there are supply constraints related to market imperfections because suppliers of external finance tend to put great weight on the quality and viability of the proposal; it is important that entrepreneurs carefully prepare and competently deliver sound business plans. In Chapter 7, Norrman and Klofsten investigate attitudes towards public innovation support for the financing of new high-technology ventures in Sweden. By means of an extensive survey of successful and unsuccessful applicants for support provided by the Swedish Innovation Centre (SIC), they measure the extent to which public sector support aids new venture formation. They discover that overall there is substantial support among new venture entrepreneurs for the involvement of the public sector. However, the authors also find that such support, while welcome, is not adequate to meet the needs of new venture entrepreneurs, especially for the process of developing a new product and launching it into the market place. In Chapter 8, Weinberg, Minshall and Garnsey explore an important, but underresearched, area of high technology small firm development, namely the impact of acquisition activity, whereby technology-based small firms are often aggressively acquired by unusually larger counterparts. This phenomenon is critical to any consideration of high technology small firm finance since it is usually the need for additional technological and financial resources, in the absence of other loan- or equity-based alternatives, which leads expanding high technology small firms down the acquisition route in order to fund survival and/or growth. The authors make the point that most research on acquisitions of this type is viewed from the acquirer’s perspective and not that of the seller. In an attempt to ameliorate the high level of acquisition failure in this area, the authors construct a framework that measure the degree of fit between the various stakeholders objectives, both prior to, and after the acquisition.

Start-Up Strategies Ulvenblad, in Chapter 9, begins this sub-section on start-ups by addressing the question of how firms construct communication strategies while still in the start-up phase, in order to help establish the business and compensate for a lack of ‘track

Introduction

5

record’. Her analysis works within a resource-dependence framework and is based on four case studies, two involving technology start-ups and two involving service-sector start-ups. A key differentiator between these two types of firms is that the technology start-ups faced a more severe problem of attracting finance to support an extended product development phase. The service start-ups, by contrast, had placed more emphasis on establishing a reputation on which they could trade. Accordingly, the technology start-ups placed more emphasis on creating the appearance of a substantial and competent business, in order to be more attractive to would-be investors. The service companies, however, relied more on developing networks within which they could create visibility for the company. In Chapter 10, Englis et al. explore how the ‘voice of the consumer’ can be integrated into the process of opportunity recognition and exploitation. Having provided an illustrative case study of an initially unsuccessful launch and then successful relaunch of paperbackswap.com, the authors argue that a focus on identifying and delivering consumer benefits through integrating the voice of the consumer is likely to result in greater success for high-tech start-ups. This stands in contrast to the typical ‘technology-push’ approach of such firms. Understanding the benefits that a technology will yield for consumers is essential in assessing the potential commercial value of an innovation. This process does not stop at launch, however, but continues to bring benefits if embedded into the firm’s continuous improvement efforts, helping to identify and then evaluate improvements. In contrast to research concerning large and established firms, research on how to incorporate the ‘voice of the consumer’ and the benefits of doing this for high-tech start-ups is very rare, a gap the authors argue, is important to address. Corvino, Romano and Spadafora, in Chapter 11, explore the option of ‘going public’ for research-intensive high-technology companies. With the support of evidence from an Italian case study, they show how ‘going public’ permitted their case study firm to obtain the financial resources necessary of increase its size, based on a strong investment in R&D. The authors identify three factors that aid a successful outcome of the process of ‘going public’, namely solving the problem of the firm’s credibility, the acceptance by entrepreneurs of the need to ‘go public and resisting the fear of loss of control that inevitably accompanies the dilution of the founders’ share ownership. Overall, they show how their case study firm has substantially benefited from ‘going public’.

Drivers of Superior Performance In Chapter 12, Sims and O’Regan consider a classic strategic question, namely what drives firm performance? Their contribution in relation to high-tech firms is to propose and apply an input-based definition of what constitutes a high-tech firm, rather than relying on Standard Industrial Classification (SIC) codes, which have well-known flaws, before moving on to assess the causes of differential performance. Within any SIC defined industry there will be differences in the innovative

6

Ray Oakey and Gary Cook

performance of technology-intensive firms. Their input-based index was based on four dimensions: expenditure on R&D; the use of innovation; creativity and capabilities. These factors were further decomposed into constituent factors. Their results, based on 197 SMEs in the fabrication and electronics sectors, showed considerable variation among sub-sectors of these two ‘high-tech’ industries in terms of mean firm scores on their input-based high-tech index. They include that highertech firms tend to be more agile than their lower-technology counterparts and also to become more agile as they mature. Minshall, Mortara and Napp, in Chapter 13, report on a series of case studies that explore the problems of linking operational and strategic issues when implementing an open innovation approach. Following a review of relevant literature, the authors map the strategic and operational issues experienced by multinational companies when seeking to introduce an open innovation system in which high technology small firms are also involved. Three broad common problems were identified as ‘Intellectual property management’, ‘Expectation management’ and ‘Skills development’. The chapter concludes with an exploration of the skills required in order to make collaborations between multinational firms and high-technology small firms more effective. Finally in Chapter 14, Petzold-Dumeynieux examines the forms of market orientation displayed by French young high technology small firms. After arguing that marketing in high technology small firms is a poorly understood process, on the basis of a survey results from 101 young small French high technology small firms, the author proceeds to construct a typology in which three types of market orientation are identified based on four factors that differentiate the market orientation types.

Chapter 2

Defining University Spin-Offs Teresa Hogan and Quan Zhou

Introduction The role of the university in the 21st century is rapidly changing, reflecting a growing interest in the commercialisation of university knowledge among scholars and policymakers. University spin-offs (USOs) represent one mechanism for commercialising knowledge that are attracting considerable attention because of their potential to (a) enhance local economic development, (b) assist universities in their major mission of teaching and research and (c) generate high-performance firms (Shane, 2004). Indeed, one study by Bray and Lee (2000), based on a small US sample, found that on average, technology transfer offices earned a higher return from equity stakes in their USOs, even allowing for a 50% failure rate, than from the average licensing agreement. The growing commercial interest in USOs is being matched by increasing scholarly attention. A search using the keywords ‘university’ and ‘spin-off’ in the research database Ebsco revealed that there were 94 relevant articles published between 2004 and 2006, compared to a total of 96 from the period 1967 to 2003. Despite growing interest in USOs, there is no universally accepted definition of the concept and significant variation exists across studies (Pirnay, Surlemont, & Nlemvo, 2003). As a result, empirical evidence is ambiguous and comparability is limited (Shane, 2004). Three examples show how the lack of a universal definition leads to ambiguity and incomparability. Firstly, take the example of MIT, which is widely cited in the USO literature. The Bank Boston study (1997) recorded 4000 MIT spinoffs employing a total of 1.1 million people worldwide in 1994. In the report, they included all the companies created by MIT graduates, even if the founders had graduated 10 years prior to setting up their companies. It is likely that many of the firms had little connection with MIT by 1997. Hence, the number of USOs cited in the Bank Boston study is likely to be exaggerated. Secondly, a lack of comparability

New Technology Based Firms in the New Millennium, Volume VIII Edited by R. Oakey, A. Groen, G. Cook and P. van der Sijde r 2010 Emerald Group Publishing Limited. All rights reserved.

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Teresa Hogan and Quan Zhou

is evident in findings from two reports on USOs in Japan. An OECD (2003) study reported that only six firms were spun-off from Japanese universities in 2000, while a study by Kondo (2004) found that more than 100 USOs were created annually in Japan between 2000 and 2003. Spin-offs in the OECD report refer to companies formed to commercialise university intellectual property, while Kondo (2004) uses the term to refer to all companies that received ‘management resources’ from ‘mother universities’. Thirdly, two studies from the same government department in Canada provide uncomparable results due to lack of consistency. Bordt and Earl (2004) noted that the number of USOs in Canada increased 3.5 times from 384, recorded in the Survey of Intellectual Property Commercialisation in the Higher Education Sector (SIPCHES) in 2001, to 1350 reported in the Survey of Electronic Commerce and Technology (SECT) in 2003. However, spin-offs in SIPCHES were required to have administrative links with their universities while those in SECT were not. The definition in the SECT report was very broad. Some companies (e.g. campus laundry service, parking lots), which typically would not be listed as universities spin-offs, were reported as spin-offs in SECT. These disparities indicate that there is clearly a need for a universally accepted definition of USOs, as well as a classification system that distinguishes between the different types of USOs that exist. This chapter provides a detailed review of existing definitions of USO based on an examination of key journal articles, books, government and international organisation reports and conference papers produced over the past 20 years. It identifies and assesses three key criteria used to define USOs. The first relates to the knowledge base of the spin-off which may be codified or tacit. The second relates to the background of the founder(s) which might include any one or a number of the following: researchers, surrogate entrepreneurs or students. The third concerns the relationship between the university and the spin-off. This can be examined in terms of the assistance provided by universities which might include the following: finance, knowledge, human and/or physical capital. Resulting from this analysis, the chapter proposes three conditions that a USO should fulfil. The conditions are tested on a portfolio of 41 companies associated with Invent, an incubator and university commercialisation gateway, based at Dublin City University (DCU) in Ireland. The structure of the chapter is as follows. The next section looks at prior definitions of USOs, while the third section looks at prior classifications systems with the aim of identifying common criteria. The fourth section attempts a synthesis and introduces a three-point checklist for identifying USOs. The fifth section pilot tests the checklist using the client portfolio of Invent, and introduces our definition of USOs. The final section concludes with a discussion of the advantages and disadvantages of using the three-point checklist.

What is a University Spin-Off? The aim of this literature review is to identify common criteria from the definitions employed in (a) key studies of USOs and (b) classification studies on USOs. Before

Defining University Spin-Offs

9

proceeding, it is necessary to differentiate between two terms which are used interchangeably in the literature, namely, ‘the university spin-off’ and ‘the university spin-out’.

Spin-Off or Spin-Out? There is a difference between the terms ‘spin-off’ and ‘spin-out’. A ‘spin-off’ company, is started by employees who leave their mother organisation but, maintains loose ties with this mother organisation (Klepper, 2001; Koster, 2004; Development Bank of Japan, 2005). The term ‘spin-out’ is used to refer to a company that does not have a direct link with the mother organisation, and the choice of forming a new company is made by the employee(s), not the employer (Hulsink & Elfring, 2004; Koster, 2004; Franco & Mitchell, 2005; Development Bank of Japan, 2005). Koster (2004) differentiates between (a) start-up companies, (b) spin-out companies and (c) spin-off companies using a resource-based perspective, depicted in Figure 1. The Development Bank of Japan (2005) also differentiates between ‘spin-outs’ and ‘spin-offs’ in terms of the support they get from the parent organisation and the commercialisation risk involved. Considering the links between the USOs and the universities, the term ‘spin-off’ is more applicable in describing companies that are supported by universities.

Existing Definitions of USOs Earlier researchers tended to adopt a broader definition of USOs. For example, Rappert, Webster, and Charles (1999, p. 874) define USOs as ‘firms whose products or services develop out of technology-based ideas or scientific technical know-how generated in a university setting by a member of faculty, staff or student who founded (or co-founded with others) the firm. The individual or individuals may either leave the university to start a company or start the company while still inside the university’. This full Spin-offs Parental support

none

Start-up

Spin-outs

no

yes Resource sharing

Figure 1: Spin-offs versus spin-outs. Source: Koster (2004).

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Teresa Hogan and Quan Zhou

definition includes companies formed to develop both (a) technical know-how and (b) IP-protected technology. Weatherston (1995) and Pirnay et al. (2003) use similar definitions. More recently, researchers have favoured a narrow definition of the USO. The common characteristic of such narrow definitions is ‘IP protection’. For example, Shane (2004, p. 4) defines a USO as ‘A new company founded to exploit a piece of intellectual property created in an academic institution’. Similar definitions can be found in Nicolaou and Birley (2003), Lockett and Wright (2005), Coster and Butler (2005) and Walter, Auer, and Ritter (2006). Lockett and Wright (2005), exclude all companies that are not based on technology assigned licences from universities. Narrow definitions have also been developed by international research organisations such as the OECD and interest groups such as the Association of University Technology Managers (AUTM). The OECD (2003, p. 263) defines an IP-based spinoff from a Public Research Organisation (PRO) as ‘a new firm whose start-up includes a substantial contribution of knowledge recently developed in a PRO; and this knowledge is protected by IPRs that are either licensed or transferred to the firm’. Note that the OECD refers to publicly funded researcher institutions as well as universities.1 Again, AUTM (2001) uses a ‘conservative’ definition and only counts companies that are dependent on technology licences acquired from a university or research institution. Finally, Bray and Lee (2000, p. 386) define the USO as ‘a start up company formed to develop and commercialize the technology, and the university takes equity in the start-up’. This is the narrowest definition since it explicitly points out the university’s position as taking an equity stake in the start-up. Table 1 presents the definitions employed including 16 key international studies in the United States, the United Kingdom, the rest of Europe and Japan. It highlights the diversity in the definitions in use. Nonetheless, links between USOs and their parent organisation make USOs different from other start-up companies. Such collaboration with a parent university may afford the USO access to resources (e.g. funding, human expertise, R&D) particularly at the time of foundation. Ndonzuau, Pirnay, and Surlemont (2002) identify three collaborative relationships between universities and USOs. Universities provide financial resources in the form of equity, knowledge (intangible resources) in the form of patented technology, as well as access to some university facilities, equipment and raw materials (material resources). In addition, most USOs also have access to human resources from their universities. The stylised version of the USO is where an academic leaves a university post to set up a company to commercialise his or her own research. Table 1 also identifies the link(s) that exist between the USO and the parent organisation, delineated by resource type: (a) financial, (b) knowledge, (c) human capital and (d) equipment/materials, as specified in the definition employed in each study. Thus, only two studies — Bray and Lee (2000)

1. PROs include ‘(i) all research-performing universities, both public and private; (ii) research laboratories and agencies operated and fully funded by the government; (iii) other research organisations that receive a significant share of their total funding from public sources’ (OECD, 2003, p. 75).

Shane (2004)

Bray and Lee (2000)

Carayannis et al. (1998)

Smilor, Gibson, and Dietrich (1990)

Authors/Year

Definitions

‘(1) the founder was a faculty member, staff member, or student who left the university to start a company or who started the company while still affiliated with the university; and/or (2) a technology or technology-based idea developed within the university. The companies in the study represent a range of technologies and tend to be growth oriented’ (p. 63). ‘A new company that is formed by individuals who were former employees of a parent organisation and around a core technology that originated at a parent organisation and that was then transferred to the new company’ (p. 1). ‘a start up company formed to develop and commercialize the technology, and the university takes equity in the startup’ (p. 386). ‘A new company founded to exploit a piece of intellectual property created in an academic institution’ (p. 4).

Table 1: Definitions of USOs.

US

US

US

US

Country

No

Yes

No

No

Financial

Yes

Yes

Yes

Yes

Knowledge Based

No

No

Yes

Yes

Human Resource

Type of Resource Link

No

No

No

No

Equipment Based

Defining University Spin-Offs 11

Definitions

‘firms that have been spun off from academic departments or research centres within a university with the aim of commercializing technology invented at the university’ (p. 444). Rappert et al. (1999) ‘firms whose products or services develop out of technology-based ideas or scientific technical know-how generated in a university setting by a member of faculty, staff or student who founded (or co-founded with others) the firm. The individual or individuals may either leave the university to start a company or start the company while still inside the university’ (p. 874). Nicolaou and Birley ‘(1) the transfer of a core technology from (2003) an academic institution into a new company and (2) the founding member(s) may include the inventor academic(s) who may or may not be currently affiliated with the academic institution’ (p. 333).

Libaers et al. (2006)

Authors/Year

Table 1: (Continued )

No

No

No

UK

UK

Financial US

Country

Yes

Yes

Yes

Knowledge Based

Yes

Yes

No

Human Resource

Type of Resource Link

No

No

No

Equipment Based

12 Teresa Hogan and Quan Zhou

Steffensen, Rogers, and Speakman (1999)

McQueen and Wallmark (1982)

Wright et al. (2006)

Lockett and Wright (2005)

Coster and Butler (2005)

‘high technology ventures that originated from research work in a university, resulting in the generation of intellectual property and, usually, the subsequent involvement of key researchers’ (p. 535). ‘new ventures that are dependent upon licensing or assignment of the institution’s intellectual property for initiation’ (p. 1044). ‘a start-up company whose formation is dependent on the formal transfer of intellectual property rights from the university and in which the university holds an equity stake’ (p. 481). ‘(1) the company founder or founders have to come from a university (faculty, staff or student); (2) the activity of the company has to be based on technical ideas generated in the university environment; and (3) the transfer from the university to the company has to be direct and not via an intermediate employment somewhere’ (p. 307). ‘a new company that is formed (1) by individuals who were former employees of the parent organisation. (2) a core technology that is transferred from parent organisation’ (p. 93). Norway

Sweden

UK

UK

UK

No

No

Yes

No

No

Yes

Yes

Yes

Yes

Yes

Yes

Yes

No

No

Yes

No

No

No

No

No

Defining University Spin-Offs 13

Walter et al. (2006)

Kondo (2004)

Pirnay et al. (2003)

Klofsten and JonesEvans (2000)

Authors/Year

Table 1: (Continued ) Country

‘The formation of new firm or Sweden organisation to exploit the results of the university research’ (p. 300). ‘new firms created to exploit commercially Belgium some knowledge, technology or research results developed within a university’ (p. 356). ‘A newly founded company that has Japan received some management resources from a university or universities’ (p. 39). ‘business ventures that are founded by one Germany or more academics who choose to work in the private sector (at least part-time) and transfer a core technology from the parent organisation’ (p. 544).

Definitions

No

Not obvious

No

No

Financial

Yes

Not obvious

Yes

Yes

Knowledge Based

Yes

Not obvious

No

No

Human Resource

Type of Resource Link

No

Not obvious

No

No

Equipment Based

14 Teresa Hogan and Quan Zhou

Defining University Spin-Offs

15

and Wright, Lockett, Clarysse, and Binks (2006) — require the parent organisation to share financial resources with the USO in order to satisfy their definition. In all studies sharing is specified. Earlier studies have placed greater importance on the role of university personnel in the formation of spin-offs. Only three of the nine studies published after 2000 specify the involvement of university staff or students in the transfer process. This may reflect an increased sophistication of technology transfer policy and processes over the past decade designed to facilitate the transfer of technology without the direct involvement of the original researcher in company formation.

Taxonomies of USOs An alternative approach to defining the USO as a single entity is to recognise multiple forms. These empirically inducted classifications or taxonomies are useful in identifying key and common criteria. Classification systems tend to focus on the role of the founder and the origin of the technology. One of the first classification systems was provided by Carayannis, Rogers, Kurihara, and Allbritton (1998), who identified five different kinds of USO based on a sample of just seven companies including the following: (1) The founder of the spin-off company was an employee of the parent organisation, but the technology was not transferred from the parent organisation; (2) The core technology of the spin-off company originated in the parent organisation, but the founder of the spin-off company did not transfer from the parent organisation; (3) The founder of the spin-off company created the core technology of the spin-off company, but not while employed by the parent organisation; (4) The founder of the spin-off company was not employed by the parent organisation, nor did the core technology originate at the parent company, but the spin-off company used certain resources from the parent company; (5) The core technology and the founder(s) came from the parent organisation, and the founder continued to work for the parent organisation (Carayannis et al., 1998, p. 4). Pirnay et al. (2003) have proposed a typology of USOs based on the status of the individuals involved in new firm formation (e.g. researchers and students), or the nature of the spin-off activity (e.g. product or service oriented). They identified four kinds of spin-offs: (a) academic product-oriented spin-offs, (b) academic service-oriented spin-offs, (c) student product-oriented spin-offs and (d) student service-oriented spin-offs. This typology, however, ignores the role of surrogate entrepreneurs, which has become increasingly important in the spin-off process. Nicolaou and Birley (2003) use a trichotomous system which is based on the affiliation of the inventor to the university. If the inventor/academic leaves the university to start a company, the resulting company is termed an ‘orthodox’ spin-off. If the inventor remains in the university, holding a part-time position in the new company, then the

16

Teresa Hogan and Quan Zhou

company is classified as a ‘hybrid’ spin-off. If the inventor has no involvement in the creation of the new company, the company is referred to as a ‘technology’ spin-off. Hindle and Yencken (2004) have also classified public research spin-offs in terms of their relationship with parent organisations. They suggested four types of research based spin-off companies: (1) Direct research spin-offs created to exploit IP arising out of a research institute; (2) Technology transfer companies founded to exploit the university’s tacit knowledge and know-how. The core product/service of the company usually does not have any formal legal protection; (3) Start-up or indirect spin-off company, set up by university staff or students based on the experience acquired at the university, but without formal links with the university (e.g. IP licensing); (4) Spin-in (to existing company) derived from university knowledge, which can operate either outside or inside the existing company. The European Commission (2002) introduced the concepts of ‘primary’ spin-offs and ‘secondary’ spin-offs. It found that only top research universities in Europe have sufficient resources to promote and develop spin-off companies. The term ‘secondary’ spin-off was coined to describe USOs based on intellectual property brought in from another institution, and or adaptations of existing technology. This distinction is important because it breaks the technology link between the USO and the parent organisation.

Defining USOs: What Matters? In our review of the prior studies, we identify three issues that need to be addressed in defining a USO. These are: (1) The knowledge transferred to the USO; (2) The individuals involved in the venture creation; (3) The links between the university and the spin-off company. The Knowledge Transferred to the USO Two types of knowledge are likely to be transferred to USOs. One is codified knowledge, which refers to the most visible output of research activities. This knowledge can be easily imitated and should be protected by legal contract. The other type of knowledge is tacit which incorporates personal experience, accumulated from research activities (Pirnay et al., 2003). More specifically, Hindle and Yencken (2004, p. 794) define codified/explicit knowledge as follows: (1) The published knowledge based on the science or engineering involved in the ‘discovery’; (2) New knowledge, contained in patents, copyrights, registered designs, etc.;

Defining University Spin-Offs

17

(3) The codified content of postgraduate or undergraduate training in entrepreneurship and/or technology management. However, tacit knowledge inputs can be just as important as codified knowledge and include: (1) The ability to find ideas that can be converted into opportunities; (2) Technology and scientific background brought to new ventures by the ongoing involvement of the original inventors; (3) Familiarity with the particular product/industry sector; (4) Entrepreneurial experience in start-up management, fund raising as well as access to business networks. The transfer of codified knowledge to a new company often involves the transfer of an inventor’s tacit knowledge, except in the case of off-the-shelf inventions (e.g. pharmaceutical drug’s formulation) (Lowe, 2006). In some cases, a USO may involve knowledge brought in by the university from another institution (European Commission, 2002).

The Individuals Involved in Founding the Spin-Off A researcher can become an academic entrepreneur and set up a new company or, alternatively, a university can find an external entrepreneur with business experience to manage a new company. Students are also included because they are different from researchers or surrogate entrepreneurs. Student start-ups are more likely to be seen as part of students’ entrepreneurial experience in preparation for their working career (Rasmussen, Moen, & Gulbrandsen, 2006). However, students might use the knowledge gained on their programme of study, entrepreneurial training from the university and the university’s support service in setting up their companies. Earlier definitions of USOs restricted the role of founder to university researchers and students. However, surrogate entrepreneurs can also set up USOs (Radosevich, 1995; Franklin, Wright, & Lockett, 2001) in instances where the university offers a technology to a company set up by an external entrepreneur who will start a new company to exploit the technology. Thus, prior association within a university (whether as a student or employee) is no longer a necessary condition for USO founders.

Links Between Universities and Spin-Off Companies The university may be an important resource for the USO. This resource sharing can be classified as financial, knowledge based, human capital based and/or equipment based. The university can take an equity stake in the USO, licence the technology to the USO and take a royalty, or provide seed funds and loans. Therefore, this

18

Teresa Hogan and Quan Zhou

financial link represents the university’s control and economic interest in the USOs. Universities are more likely to support the new venture creation process if their benefit is protected. The knowledge link refers to the ‘knowledge’ base of the USO. Knowledge that is transferable from the university can be either ‘codified’ or ‘tacit’. The human resource link refers to the individuals involved in creating the venture, where the founder or employee(s) might come from the parent university. The equipment link refers to resources the USO can access from the university (e.g. library, laboratories, office space). Based on our analysis we propose a checklist for identifying/selecting USO. This checklist contains the following three conditions: Condition 1. The university should receive formal compensation from the new company. By receiving compensation from the USO, the university creates close links to their spin-offs, and this is a more profit-oriented relationship. Otherwise, the relationship between the company and the university is comparatively loose. Condition 2. USOs must receive knowledge from the parent university. This knowledge might have formal IP protection, or it can be experience gained from the university. If a company does not receive any knowledge from the university, then it is not a USO. Condition 3. The founder of the company can be a university employee, a university student, an entrepreneur from outside of the university or a team comprising any combination of the above. This checklist reflects the common interest of the firm and university, which involves revenue generation. It also shows the difference between USOs and other start-up companies, since the USO depends on the university’s knowledge. In the next section, we test our checklist.

Applying the Checklist The objective of the study was to examine a population of firms to identify a subset of spin-offs using the checklist. The study examined a portfolio of companies linked to Invent which is a wholly owned subsidiary of DCU with responsibility for commercialising its intellectual property. The centre manager identified 41 companies with links to Invent at the time of the study in spring 2007. Table 2 shows the classification of DCU/Invent client companies. Firstly, only 27 of the 41 companies were actually based in Invent, while 14 companies appeared on an Invent network listing but had no links to the university in terms of knowledge transfer and/or founding personnel. The remaining 27 companies included (a) Invent client companies (16), (b) individual clients availing of the incubating service (7) and (c) spin-in companies seeking to develop R&D links with DCU (4). Of the remaining twenty-seven companies, just seven companies had direct links with DCU. A short questionnaire was designed and sent to the founders of the seven

Defining University Spin-Offs

19

Table 2: Classification of DCU/Invent companies. Description Invent Companies in which Invent has an company equity stake Spin-in Companies interested in developing R&D links with DCU Concept Individuals with feasibility plans desk seeking to move to the next stage of development Virtual Companies that are not based in clients Invent, but are interested in the services, expertise and network potential of Invent

Companies with Companies with Invent Links DCU Links 16

4

4

2

7

1

14

0

short-listed companies. The aim of the questionnaire was to try to identify the links between DCU/Invent and these companies. The companies were asked questions concerning the founders’ background, their relationship with DCU and the technology’s link to DCU. Table 3 shows the details for the seven companies. Of the seven companies that were linked to DCU, three companies (GSS, 2XL and Slidepath) were identified as USOs according to our conditions. Firstly, DCU holds equity stakes in these companies. In this way, DCU can claim financial compensation if these companies are successful. Secondly, all three companies transferred knowledge that originated or was developed in DCU. GSS was based on technology developed in a DCU Research Centre, while the other two companies are based on experience/know-how gained in DCU. GSS and Slidepath fit most of the existing definitions because they are typical spin-off companies: (1) they are founded by academics; (2) the university has an equity stake; (3) they have strong IP protection (patent) and (4) they are technology based, while 2XL offers a sports conference and sports training service based on experience and know-how gained during the founder’s time at the University. Under most definitions, it would not be classed as a USO for two reasons: (1) it was not based on technology but on know-how and experience in the area of sport science, nutrition and training and (2) it was founded by students rather than academics, although student founders are included in our definition. However, since DCU has an equity stake in 2XL, it meets our first condition. Two of the four companies, not classified as USOs, are spin-in companies. Impedans and Lexas are looking for potential technology from DCU, but they are not involved in commercialising such technology as yet. DCU will take an equity stake only when these companies find a suitable technology and decide to develop it jointly with DCU. Therefore, they do not satisfy Condition 1 at present. However, in the spin-off literature, many definitions state that a USO should be a ‘new’ firm. From this point of view, Impedans and Lexas are joint ventures rather than USOs. Phive is based on research at

Founder Background

Lexas

Slidepath

Icora Ltd.

Phive

Impedans

Company’s Core Business

IP Protection

Equity Stake Support from DCU

DCU staff and Technology-based previous DCU service-oriented research student company Manager outside Technology-based DCU product-oriented company

Experience/ know-how gained in DCU Looking for suitable technology

Experience/knowhow related to public funded research at DCU Experience/knowhow gained in DCU

Looking for suitable technology

Patent-pending and nondisclosure agreement Non-disclosure agreement Copyright/trade mark Patent

No

Yes

Yes

Spinoffs?

Facilities, employees Facilities No, will have in the future

Yes

No

Yes

Not now Under Training in negotiation entrepreneurship and technology management No Brand name, No facilitates, network

Technology-based Technology Patent Yes Facilitates (e.g. product-oriented developed in office space, lab) company DCU Non-technologyExperience/knowCopyright/trade Yes Facilitates, network based servicehow gained in mark oriented company DCU Technology-based Seeking strong IP Will file patent No, will have Facilitates, brand product-oriented generation in as the business in the future name company collaboration with opportunity DCU grows

Type of Company

Previous experienced manager, current DCU staff Technology-based A full-time lecturer at DCU product-oriented and private company sector manager Taught Technology-based postgraduate product-oriented student at DCU company

GSS Sensor DCU researcher Solutions Ltd. 2XL Sports DCU research Ltd. student

Company Name

Table 3: Classification of USOs in Invent DCU.

20 Teresa Hogan and Quan Zhou

Defining University Spin-Offs

21

DCU and was set up in 2005. They have a prototype but the relevant financial agreement is still under negotiation. Because of the lack of financial compensation, Phive is not considered a USO. Icora was founded by two DCU students and the company is based on technology developed in their final year project. DCU does not have any ownership claim on the technology, and there is no licence or equity agreement between DCU and the company. Therefore, Icora is not defined as a USO since it does not meet all three conditions. Based on our analysis, we propose the following definition: A USO is a firm created to exploit knowledge developed in a university which is based on a financial agreement between the firm and the university, irrespective of whether academic staff or students are involved in the venture creating process.

Conclusion It is widely accepted that USOs are important conduits of knowledge transfer in society and that the number of USOs is generally on the increase, with many governments actively encouraging their formation. However, there is no universally accepted definition of a USO, which makes measuring their prevalence and impact on economic activity difficult. In addition to this ambiguity, the lack of a clear definition also leads to incomparability. Early definitions were rather general such that any company with links to a university, including all campus-based companies and all companies formed by current and former staff and graduates, were classified as USOs. A narrower definition typically requires that there is a legal agreement on the transfer of technology from the university to the company. However, narrow definitions also have limitations as they underestimate the transfer of knowledge from the university to society. This is because they exclude all companies that are formed on the basis of experience and know-how gained in a university environment, or what are regarded as knowledge-intensive companies. While the choice between a narrow or broad definition should be determined by the nature and scope of the study, it is important that researchers make this choice explicit so that it is clear what is included (or not included) in their definition. This allows practitioners better access to research findings and facilitates comparison. The use of our checklist ensures that researchers are explicit about the three core conditions for defining USOs. Based on the checklist, we define a USO as a firm created to exploit knowledge developed in a university which is based on a financial agreement between the firm and the university, irrespective of whether academic staff or students are involved in the venture creation process. This definition includes knowledge-intensive companies if the university has received compensation for the knowledge transferred. It would typically include knowledge-intensive companies that receive financial injections from the parent university. Thus, knowledge-intensive companies in which the university has no equity stake are excluded under this definition. The definition does not require the founders to have a link with the university as it includes surrogate entrepreneurs. The key advantage of the definition is that it is unambiguous and easy to implement using a three-point checklist. It emphasises the economic returns from USOs by attempting

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to measure all income accruing to the university from knowledge transfer. It includes all companies covered by licensing agreements, and knowledge-intensive companies in which the university has an equity stake. However, it does not capture the full level of knowledge transfer from the university embodied in new firms, since knowledgeintensive companies, in which the university has no financial participation, are excluded. Therefore, our proposed definition could be classed as a narrow definition.

References Association of University Technology Managers (AUTM). (2001). AUTM licensing survey. 2001 Survey Summary, Northbrook, IL. Bank Boston. (1997). MIT: The impact of innovation. A Bank Boston Economics Department Special Report, Boston, MA. Bordt, M., & Earl, L. (2004). Public sector technology transfer in Canada, 2003. SIEID Working Paper Series, Catalogue No. 88F0006XIE Ottawa: Statistics Canada Catalogue No. 88F0006XIE- No.018. Bray, M. J., & Lee, J. N. (2000). University revenues from technology transfer: Licensing fees vs. equity positions. Journal of Business Venturing, 15, 385–392. Carayannis, E. G., Rogers, E. M., Kurihara, K., & Allbritton, M. M. (1998). High-technology spin-offs from government R&D laboratories and research universities. Technovation, 18, 1–11. Coster, R. D., & Butler, C. (2005). Assessment of proposals for new technology ventures in the UK: Characteristics of university spin-off companies. Technovation, 25, 535–543. Development Bank of Japan. (2005). Japan’s innovation capacity and polices for commercialising new technologies: Using curve-outs to create new industries. Development Bank of Japan Research Report No. 53, Economic and Industrial Research Department, Tokyo. European Commission. (2002). University spin-outs in Europe: Overview and good practice, innovation and participation of SMEs’ programme. Luxembourg: Directorate-General for Enterprise. Franco, A. M., & Mitchell, M. F. (2005). Covenants not to compete. Labor Mobility and Industry Dynamics. University of Iowa Memo. Franklin, S. J., Wright, M., & Lockett, A. (2001). Academic and surrogate entrepreneurs in university spin-out companies. Journal of Technology Transfer, 26, 127–141. Hindle, K., & Yencken, J. (2004). Public research commercialisation, entrepreneurship and new technology based firms: An integrated model. Technovation, 24, 793–803. Hulsink, W., & Elfring, T. (2004). Entrepreneurs, new technology firms and networks: Experiences from lone starters, spin-offs and incubatees in the Dutch ICT industry 1990–2000. In: W. During, T. Oakey & S. Kauser (Eds), New technology-based firms in the new millennium (Vol. III, pp. 69–87). Oxford: Elsevier Ltd. Klepper, S. (2001). Employee startups in high-tech industries. Industrial and Corporate Change, 10, 639–674. Klofsten, M., & Jones-Evans, D. (2000). Comparing academic entrepreneurship in Europe — The case of Sweden and Ireland. Small Business Economics, 14, 299–309. Kondo, M. (2004). University spin-offs in Japan: From university-industry collaboration to university-industry crossover. Tech Monitor, 37–43. Koster, S. (2004). Spin-off firms and individual start-ups. Are they really different? 44th ERSA Conference, Porto.

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Libaers, D., Meyer, M., & Geuna, A. (2006). The role of university spinout companies in an emerging technology: The case of nanotechnology. Journal of Technology Transfer, 31, 443–450. Lockett, A., & Wright, M. (2005). Resources, capabilities, risk capital and the creation of university spin-out companies. Research Policy, 34, 1043–1057. Lowe, R. A. (2006). Who develops a university invention? The impact of tacit knowledge and licensing policies. The Journal of Technology Transfer, 31, 415–429. McQueen, D. H., & Wallmark, J. T. (1982). Spin-off companies from Chalmers university of technology. Technovation, 1, 305–315. Ndonzuau, F. N., Pirnay, F., & Surlemont, B. (2002). A stage model of academic spin-off creation. Technovation, 22, 281–289. Nicolaou, N., & Birley, S. (2003). Academic networks in a trichotomous categorisation of university spinouts. Journal of Business Venturing, 18, 333–359. OECD (2003). Turning science into business: Patenting and licensing at public research organizations. Paris: OECD. Pirnay, F., Surlemont, B., & Nlemvo, F. (2003). Toward a typology of university spin-offs. Small Business Economics, 21, 355–369. Radosevich, R. (1995). A model for entrepreneurial spin-offs from public technology sources. International Journal of Technology Management, 10, 879–893. Rappert, B., Webster, A., & Charles, D. (1999). Making sense of diversity and reluctance: Academic — industrial relations and intellectual property. Research Policy, 28, 873–890. Rasmussen, E., Moen, Ø., & Gulbrandsen, M. (2006). Initiatives to promote commercialization of university knowledge. Technovation, 26, 518–533. Shane, S. (2004). Academic entrepreneurship: University spinoffs and wealth creation. Cheltenhan, UK: Edward Elgar. Smilor, R. W., Gibson, D. V., & Dietrich, G. B. (1990). University spin-out companies: Technology start-ups from UT-Austin. Journal of Business Venturing, 5, 63–76. Steffensen, M., Rogers, E. M., & Speakman, K. (1999). Spin-offs from research centers at a research university. Journal of Business Venturing, 15, 93–111. Walter, A., Auer, M., & Ritter, T. (2006). The impact of network capabilities and entrepreneurial orientation on university spin-off performance. Journal of Business Venturing, 21, 541–567. Weatherston, J. (1995). Academic entrepreneurs: Is a spin-off company too risky? 40th International Council on Small Business, Sydney. Wright, M., Lockett, A., Clarysse, B., & Binks, M. (2006). University spin-out companies and venture capital. Research Policy, 35, 481–501.

Chapter 3

Entrepreneurial-Innovative University Services: A Way to Integrate in the University’s Third Mission Mo´nica Arroyo-Va´zquez, Peter van der Sijde and Fernando Jime´nez-Sa´ez

Introduction The so-called ‘Third Mission’ of the university is under debate for the last 20–30 years (Laredo, 2007) and this mission has received a wide variety of interpretations. In this chapter we adhere to execution of activities that contribute to the economic and social development of its territory. This new idea of the university as an entrepreneurial one requires a reorientation of its strategy to cope with the challenges imposed by its new task towards society. In this sense, the Entrepreneurship Support Programmes (ESPs), as university services, are a central element in the fulfilment of the aims and objectives of any entrepreneurial university, as those that combine and integrate the traditional activities of education and research with the contribution to the economic and social development (Etzkowitz, 1998; Goddard, 1998). The ESP services consist, for example, of programmes that promote entrepreneurship in all the fields; they support the creation of new innovative companies with a scientific or technologic base; they support the development of university spin-off and training related to the creation and management of companies; and they promote university–company relationship and interaction between other factors (Arroyo-Va´zquez & van der Sijde, 2008). The reorientation of the strategy of the university into an entrepreneurial one involves also a strategy with regard to the university’s ‘entrepreneurial’ services, which have to adapt to the new demands and needs of the university’s ‘new’ users, entrepreneurs and companies as well as university staff members.

New Technology Based Firms in the New Millennium, Volume VIII Edited by R. Oakey, A. Groen, G. Cook and P. van der Sijde r 2010 Emerald Group Publishing Limited. All rights reserved.

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In this chapter, we describe the role of the IDEAS Institute in the process of transformation of the UPV into an entrepreneurial one.

Theoretical Framework The study of the entrepreneurial universities’ success has produced an extensive collection of literature on the characteristics of these universities and the way in which they could convert successfully into entrepreneurial ones. Some of these works are by O’Shea, Allen, Morse, O’Gorman, and Roche (2007), Etzkowitz (1983, 2004), Clark (1998), Tornatzky, Waugaman, and Gray (2002) and others. The entrepreneurial university can be understood as a flexible organisation that interacts with its social and economic environment, continuously adapting to changes. Therefore, to attend properly to the demands of the society and to be recognised as entrepreneurial university, it is necessary to transform not just the aims and strategies of the university but also its climate and culture. This transformation of the traditional university towards an entrepreneurial one has been studied by Clark with regard to European universities (Clark, 1998) as well as universities worldwide (Clark, 2004). Clark identified the following important conditions that need to be realised:     

A stimulated heartland A strengthened steering core A diversified funding base An extended developmental periphery An integrated entrepreneurial climate

A university office with a task to stimulate, support and realise such a transformation of a university into an entrepreneurial one needs to work on each of these five dimensions. An office as intended with the extended developmental periphery needs to create a basis for innovation inside the university to work on the characteristics (conditions) that are connected with an entrepreneurial university. In this sense, the connections between a flexible organisation that interacts with its social and economic surroundings adapting to the changes and looking for additional funding and the integrated entrpreneurial culture (Clark, 1998) is key for a university service that wants to implement innovation in its processes. These extrapolations of the definition of entrepreneurial university to the one of innovative university service is in perfect tuning with the four typical conditions of the services sector identified in the literature (Evangelista & Sirilli, 1995), which have implications to define and analyse the innovation in services:  The close interaction between knowledge production and its further application (Chang, Yang, & Chen, 2009). This fact involves that a large part of innovation in services activities are mainly oriented towards the adaptation of those services to the users’ needs.

A Way to Integrate in the University’s Third Mission

27

 The intensive content in information of the activities of services and of production. This factor confers huge importance on the generation and use of the information technologies in the activities of innovation of the companies of services.  Human resources are a basic factor of competitiveness.  The importance of the organisational factors in the performance of the companies. Each time more evidence becomes available for the innovative activity in services of this nature (Gallouj, 1998; Sundbo & Gallouj, 1998; Miles, 1994; Teece, 1996). The management of ESP as an innovative service in the frame of an entrepreneurial university requires incorporating and adopting these characteristics, influencing conveniently the appearances mentioned and having in account the needs and characteristics of the Third Mission of the university.

Innovative University Services to Manage Entrepreneurial Universities We recognise two critical tasks related to the entrepreneurial culture within the entrepreneurial university that are closely related to its Third Mission. The first one is the Entrepreneurship Encouragement (EE) defined as ‘dynamisation’ (Castro et al. 2001) (and entrepreneurial culture building process) among the involved stakeholders (always including entrepreneurs) as well as the promotion of research and teaching activities in entrepreneurship and related fields. In this definition we want to point out that ‘dynamisation’ is understood as the induced behavioural change that ‘moves someone to do something’. According to these authors two activities must be promoted in the ‘dynamisation’ process: awareness and motivation on the one hand and the provision of facilities on the other. The second critical task is the Business Development Support (BDS). We define it as the process that encompasses the opportunity search and recognition, opportunity development, business start-up and business development and growth. We argue that these two tasks must be developed jointly, within an integrating framework since many stakeholders are involved in both and the different activities of each task can benefit from a synergic stream among them, therefore improving the whole EE&BDS process. Arroyo-Va´zquez and van der Sijde (2008) developed this integrating approach constructed around four main pillars reflecting those activities and tools that may help implement this approach. The model must be taken into account under a generic consideration, and it needs to be adapted and rearranged in each case in order to make it operational. This proposal of EE&BDS integrating model is shown in Figure 1. It depicts on the one hand, the different areas that we have to promote in order to achieve an integrating process and, on the other, the activities that we have to carry out in each one. The authors show that the proposed model could yield optimum results when stakeholders take on their assigned roles. However, to achieve these results and the objective aims of the Third Mission, it is necessary that stakeholders agree and interact with each other. This requires delicate stakeholder management, balancing the interests of the internal and external stakeholders of the Third Mission and building a university service with the characteristics of an innovative service that allows the appropriate management of the EE&BDS model.

Incubator & Facilities

Business Monitoring

Business Launch Support

Support Programmes

Technological Services

Entrepreneurship Culture

Business Opportunities Search

Figure 1: The EE&BDS model.

R&D Development Network

Business Development Support

Entrepreneurship Encourage & Business Support

Entrepreneurship Support

Business Plan Awareness

Access to funds

Commercial Network

28 Mo´nica Arroyo-Va´zquez et al.

Research Teaching

A Way to Integrate in the University’s Third Mission

29

Table 1: Entrepreneurial and innovative service characteristics. Scope

Characteristics

Entrepreneurial

Alternative research for funding Flexible organization

Entrepreneurial/Innovative

Interaction with the surroundings Integrated entrepreneurial culture

Innovative

Adaptation to the users’ needs Use of IT Training and training of human resources

The characteristics that identify these services have to deal with the duality of the entrepreneurial-innovative university. Table 1 shows the already mentioned characteristics, indicating whether they correspond to entrepreneurial, innovative or both services.

The Case of the IDEAS Institute of the Polytechnic University of Valencia as an Entrepreneurial and Innovative Service The IDEAS Institute, created in 1992, is the office of the Polytechnic University of Valencia responsible for the creation and development of innovative and technologybased companies. From its creation, this office has been continuously adapting to the needs of its users, inside and outside of the university. The evolution of the IDEAS Institute over 18 years of its existence has followed a path that has allowed gradual transition and incorporation of new services in response to university needs. The mission of the IDEAS Institute is to encourage and develop entrepreneurship at the university, create awareness and promote dynamisation in the university community, and support the creation and development of innovative and technologybased companies — all in accordance with the ‘third’ mission of the UPV as an entrepreneurial university (IDEAS Institute 2006, 2007). The current organisational structure of IDEAS Institute is depicted in Figure 2, which shows the differentiation between the management of IDEAS and its relation with the university and university offices, and the services rendered to entrepreneurs and companies. Regarding the resources, the IDEAS Institute receives funding from the UPV. However, as innovative and entrepreneurial office, it has to explore new avenues for additional funding. For this activity, the Institute has a project manager whose task is to scout funding through subsidies, collaborations, agreements, etc. In 2007 the IDEAS Institute explored sponsorship as a financial source. As a result, the current financial structure of the service is divided equally in three sources of funding: finance by its own university, projects and collaboration, and sponsorships.

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Figure 2: Organisational structure of IDEAS Institute. Source: IDEAS Institute (2006, 2007). With regard to the flexibility of the services, the IDEAS objective is to help an entrepreneur with all its available means. For instance, the office as part of the university is able to tap into the PR resources and promote the entrepreneurial culture within and outside the university by developing programmes open to university staff as well as entrepreneurs. The flexibility should also consider the services loaned. Sure enough, the entrepreneurs always have different problems for which they explore different solutions and, in most cases, innovative solutions. The IDEAS Institute tries to constantly develop its services and adapt them to the needs of its users. Finally, the IDEAS Institute can be considered as an entrepreneurial and innovative office stimulating entrepreneurship in the broadest sense (Table 2).

Conclusions Clark sets the pathway to create an entrepreneurial university: Indicating that it must fulfil five lines of actions. In this chapter we focused on the IDEAS Institute that can be characterised as the implementation process of the extended developmental periphery of the UPV. This extended developmental periphery has both an inwardoriented task (to stimulate and contribute to an entrepreneurial climate in UPV) as well as an outward-oriented task (business creation and service to companies). This combination requires special ‘Janus’ competencies (training of human resources), and in this sense this chapter can be viewed as an extension of Clark’s view, to be able to deal with the internal stakeholder(s), the UPV and the schools and institutes of UPV, and the external stakeholders, the institutional environment of UPV. To be able to interact with both tipes of stakeholders the IDEAS Institute must behave as flexible organisation that serves both internal and external stakeholders and applies new ICT means to communicate with them. By balancing the interest

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Table 2: Implementation of characteristics of innovative and entrepreneurial services at IDEAS Institute. Characteristic Entrepreneurial university service

Application to the Case of the IDEAS Institute Diversified funding base

Flexible organization

Interaction with the environment (extended developmental periphery)

Integrated entrepreneurial culture

Innovative university service

Adaptation to its users’ needs

Communication (use of IT)

Funding not only of the UPV, but also:  From projects, collaborations and subsidies  By sponsorship of (other) agencies and companies The organisational structure, the timetable and the services have been more flexible in order to adapt it to the users needs, on the one hand, and allow the interaction with the rest of agents and the generation of new processes and procedures, on the other. Collaboration with agents in the environment such as:  Public entities  Companies and business associations  Financial entities and investors  Scientific parks, technologies and universities Fostering of creativity, commitment and innovation in the form to attend to the entrepreneurs and companies. To attend to the requests of the service, currently exists an integrated entrepreneurial culture in the people that offers the service and that has been fruit of a process carried out from the start of the programme. The IDEAS Institute has a set of services that evolves constantly to adapt itself to the needs of the users. The philosophy is not ‘this is what we offer’, but ‘what the entrepreneur needs are and how can be satisfied.’ New services are constantly arising from the needs of entrepreneurs and companies. From the beginning the use of IT is considered essential. IDEAS has implemented online services, has

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Mo´nica Arroyo-Va´zquez et al.

Table 2: (Continued ) Characteristic

Application to the Case of the IDEAS Institute

Training human resources

software for entrepreneurs support, has developed a virtual commercial centre to innovative companies, TV magazines, tools for videoconferencing, implementation of the last trends (web 2.0, interactive blogs, etc.) as a means to communicate with its constituencies. The team of the IDEAS Institute receives constant training related with its activities. In addition to the continuous training offered by the university, IDEAS Institute promotes the support to conferences, presentations and courses in its domain.

(adaptation to its users’ needs) of both constituencies the IDEAS Institute is able to generate funds internally and externally for its activities — in other words, ‘legitimacy’ is generated within both constituencies, securing funding (Clark: ‘diversified funding base’). The extended developmental periphery as outlined by Clark is an important instrument in the transformation into an entrepreneurial university. We state that, based on this single case of the IDEAS Institute of UPV, the role of such an organisation cannot be overestimated: an extended developmental periphery needs to balance the interest of the internal and external constituencies, and not only serve the internal university constituency. This requires that such an organisation is flexible and needs to gain legitimacy from both for its ‘raison d’eˆtre’: contributing to the entrepreneurial culture of the university through encouragement and stimulation of entrepreneurship, ESPs and services to the entrepreneurship and business world outside the university. The results of the IDEAS Institute show that this is not only possible, but highly appreciated internally and externally.

References Arroyo-Va´zquez, M., & van der Sijde, P. C. (2008). Entrepreneurship encouragement and business development support at universities and science parks. Industry and Higher Education, 22(1), 37–48. Castro-Martı´ nez, E., Ferna´ndez de Lucio, I., Gutie´rrez-Gracia, A., & An˜o´n, M. J. (2001). La estrategia de dinamizacio´n en la cooperacio´n investigacio´n-empresa: desarrollo conceptual y

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aplicaciones. IX Seminario Latino-Iberoamericano de Gestio´n Tecnolo´gica (ALTEC) Proceedings. San Jose´, Costa Rica. Chang, Y. C., Yang, P. Y., & Chen, M. H. (2009). The determinants of academic research commercial performance: Towards an organizational ambidexterity perspective. Research Policy, 38(6), 936–946. Clark, B. (2004). Delineating the character of the entrepreneurial university. Higher Education Policy (17), 355–370. Clark, B. (1998). Creating entrepreneurial universities: Organizational pathways of transformation. Oxford: Pergamon Press. Etzkowitz, H. (1983). Entrepreneurial scientists and entrepreneurial universities in American academic science. Minerva, 1(2–3), 198–233. Etzkowitz, H. (1998). The norms of entrepreneurial science: Cognitive effects of the new university-industry linkages. Research Policy, 27(8), 823–833. Evangelista, R., & Sirilli, G. (1995). Measuring innovation in services. Research Evaluation, 5(3), 207–215. Gallouj, F. (1998). Innovation in reverse services and the reverse product cycle. S14S Topical Paper No. 5, STEP Group. Gallouj, F. (1998). Innovating in reverse: Services and the reverse productcycle. European Journal of Innovation Management, 1(3), 123–138. Goddard, J. (1998). The role of universities in regional development. Working paper for CREColumbus, UNESCO, Paris, 1 de agosto de 1998. IDEAS. (2006). Annual Report 2006. Valencia, 2007. IDEAS (2007). Annual Report 2007. Valencia, 2008. Laredo, P. (2007). Revisiting the third mission of universities: Towards a renewed categorization of university activities. Higher Education Policy, 20, 441–456. Miles, I. (1994). Innovation in services: Part 2 — Sectoral and industrial studies of innovation. In: M. Dodgson & R. Rothwell (Eds), The handbook of industrial innovation (pp. 243–256). Gran Bretan˜a: Edward Elgar. O’Shea, R. P., Allen, T. J., Morse, K. P., O’Gorman, C. Y., & Roche, F. (2007). Delineating the anatomy of an entrepreneurial university: The Massachusetts Institute of Technology experience. R&D Management, 37(1), 1–16. Sundbo, J., & Gallouj, F. (1998). Innovation as a loosely coupled system in services. SI4S Topical Paper No. 4. STEP Group, Oslo. Teece, D. J. (1996). Firm organization, industrial structure and technological innovation. Journal of Economic Behaviour and Organization, 32(2), 193–224. Tornatzky, L. G., Waugaman, P. G., & Gray, D. O. (2002). Innovation U: New University roles in the knowledge economy. North Carolina: Southern Growth Policies Board.

Chapter 4

Linking Innovation and Entrepreneurship in Higher Education: A Study of Swedish Schools of Entrepreneurship A˚sa Lindholm Dahlstrand and Eva Berggren

Introduction This chapter focuses on Swedish university students studying entrepreneurship and establishing new firms. It is well known that the establishment of new firms is important for economic growth, innovation and job creation. For quite some time, public debate and policy initiatives, as well as research, have focused on how to improve growth of new firms. More than 30 years of entrepreneurship research reveal, however, that differences in personality traits provide little explanation of why some entrepreneurs are more successful than others. Instead, it is suggested that it is the behaviour of individuals that make them entrepreneurial, and that this behaviour is influenced by experience and learning (Gustafsson, 2004; Politis, 2005). The question is thus whether entrepreneurship education will influence the entrepreneurial behaviour of students. One main concern among different policy makers has been to create favourable conditions for academic entrepreneurship. To achieve this, research-based new academic firms and seed financing have been focused on. As a response, Swedish universities are acting to contribute to the creation of new firms. Many universities encourage academic spin-offs; some have set up incubators, and some have established programmes for entrepreneurship education and learning. The role of student entrepreneurs has been acknowledged as one of the main processes of academic entrepreneurship. Some universities focus on training future innovatorentrepreneurs, while others separate innovation from entrepreneurship. In, for example, Chalmers School of Entrepreneurship (CSE), ideas based on advanced

New Technology Based Firms in the New Millennium, Volume VIII Edited by R. Oakey, A. Groen, G. Cook and P. van der Sijde r 2010 Emerald Group Publishing Limited. All rights reserved.

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A˚sa Lindholm Dahlstrand and Eva Berggren

university research are used as projects where the students can train and learn entrepreneurship. Some of these projects are later spun off as new firms, while other students of the school use their knowledge to set up new firms based on other ideas. Lindholm Dahlstrand (2008) found that university spin-offs created by external entrepreneurs have the highest growth of all Swedish new technology-based firms. Possibly, these founders are able to combine the ‘best of two worlds’, that is, both commercial knowledge and advanced technical research. It is also possible that the professional entrepreneur holds an advantage over the innovator-entrepreneur when it comes to establishing new high-growth firms. A school of entrepreneurship might have the potential to create professional environments and encourage entrepreneurial learning, influencing the entrepreneurial behaviour of its students. This chapter focuses on two groups of university students establishing new firms. The first is the ‘educated professional entrepreneur’, the second the ‘educated innovator entrepreneur’. The ‘educated professional entrepreneur’ is a former student who has learned to become an entrepreneur in a formal school of entrepreneurship. The ‘educated innovator entrepreneur’ is a former university student with a degree in innovation engineering. The start-up of a new business can be seen as a process including two sub-processes, discovery and exploitation (Shane & Venkataraman, 2000). The discovery and development of idea, or opportunity, usually continues when its realization and exploitation has begun (Davidsson, 2006). Even if the processes partly run in parallel, the development of ideas usually starts before the exploitation. By separating innovators from entrepreneurs, and by supplying (external) ideas to professional entrepreneurs, it is possible that the startup and exploitation process can be improved. One way to describe the start-up process could be as systematic steps as in Klofsten’s eight cornerstones (Davidsson & Klofsten, 2003) or Delmar and Shane (2003) process steps, both including the two sub-processes of discovery and exploitation. In this chapter we would like to explore and analyse, as suggested by Sarasvathy (2001), another way of handling the start-up process as a more experimental and flexible approach. Sarasvathy discusses causation and effectuation as two ways of handling the start-up process, where causation is based on the logic of prediction, while effectuation is built on the logic of control. Causation is about selecting between means to create the presumed effect, while effectuation implies that the entrepreneur starts with the resources available and figures out possible effects that can be achieved by these means, trying to make the most out of the currently available resources. The effectuation process works incrementally and iteratively and starts with affordable loss rather than expected returns. Sarasvathy describes effectuation as an alternative to the conventional textbook approach to establishing a new business. Which approach is most successful could depend on many factors, where the characteristics of the idea, that is, the innovation, is one and the characteristics of the individual, that is, the entrepreneur, are another. Factors such as the stage of the development of the venture and the environment are further circumstances that should be considered (Davidsson, 2006). Samuelsson (2004) has shown that the startup processes are different for imitative and innovative ideas. Delmar and Shane

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37

(2003) found some evidence that following the ‘right’ order would result in a better performance, but since this is in a context dominated by imitative ideas, it could be presumed to involve less uncertainty (Gustafsson, 2004). Even if developing a business idea starts in an individual’s mind, Johannisson (2000) argues that entrepreneurship should be looked upon as a collective social game rather than an individual phenomenon. All firms will need an ‘organizing context’ that will help the entrepreneur to cope with uncertainty. The concept of networking could be seen as especially important during the start-up phase of a new venture (Johannisson, 2000). If schools of entrepreneurship are able to create favourable conditions for networking, this could be an important contribution to the start-up process. Another potential contribution is linked to the so-called liabilities of newness. Stinchcombe (1965) showed that the risk for closure was highest for new businesses and that this risk decreased with growing age, when the entrepreneur had learned to cope with the liability of newness. A new business has to overcome both internal and external obstacles (Aldrich & Auster, 1986) and a lack of track record in both directions, both parts having to relay on relations with strangers. For young individuals, both their age and their lack of a track record could be looked upon with suspicion by those older and more established. Here the track record could possibly be improved by participating in a school of entrepreneurship. Not only do young entrepreneurs suffer from liabilities of newness (Stinchcombe, 1965; Aldrich & Auster, 1986), but they usually also have limited experience and capital of their own, fewer possibilities to obtain financing from others and lack a competent personal network. In line with this, Gibb (1997) has suggested that a way to compensate for their weakness is to create learning partnerships within the network environment. For young entrepreneurs short of resources, access to a supporting network through their education could enable students to create, develop and expand their firms. Lacking a track record of their own, they are able to get credibility among customers and investors through entrepreneurship schools or incubators connected to universities. Thus, there are several potential advantages for students participating in formal schools of entrepreneurship and learning to become ‘educated professional entrepreneurs’. The lack of resources and a track record is a problem for all new firms, but could be expected to be worse for young entrepreneurs. The exploitation process includes the creation of resources and business legitimacy in the eyes of others. But even in the discovery process a competent experienced network could be of the greatest importance. The resource-based view (Penrose, 1959) focuses more on the resources that will help the business to perform better. Skills and capabilities are part of these. The network of entrepreneurs plays several important roles, one of them being to supplement limited resources. The traditional view of entrepreneurs as resourceful individuals has changed to an image of entrepreneurs as a collective phenomenon (Johannisson, 2000). Entrepreneurship could also be understood as a continuous learning process, an ability that is built up over time (Politis, 2005). Entrepreneurs starting their first venture are called novice entrepreneurs, while those with previous start-up experience

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are called habitual entrepreneurs (Westhead & Wright, 1998). Samuelsson (2004) found that previous start-up experience is important for survival, especially for innovative ideas, which demand a higher competence. According to Shane (2000), the entrepreneurs’ ability to discover opportunities is related to their prior knowledge. To gain start-up experience might constitute important learning in an entrepreneurship education. Possibly, this is something to take advantage of in future entrepreneurial activities. This might also be something that differentiates the ‘educated professional’ from the ‘educated innovator’ entrepreneur.

Aim and Scope In order to explore whether entrepreneurship education influences the entrepreneurial behaviour of students, this chapter focuses on two groups of university students establishing new firms. The first is the ‘education professional entrepreneur’, the second is the ‘educated innovator entrepreneur’. The ‘educated professional entrepreneur’ is a former student who has learned to become an entrepreneur in a formal school of entrepreneurship. The ‘educated innovator entrepreneur’ is a former university student with a degree in innovation engineering. The chapter analyses the different characteristics of these student entrepreneurs and their views of company creation. The focus is not on the question whether entrepreneurship can be learnt, but instead if entrepreneurship education can make individuals behave more entrepreneurially. Questions dealt with include: Do different forms of entrepreneurship training result in different company creation processes? Are the trained entrepreneurs able to use what they have learnt with a view to establishing companies?

Method The chapter is based on an empirical sample of almost 300 former entrepreneurship students. These students have been selected from three Swedish universities: the School of Entrepreneurship at Chalmers University of Technology (CSE), the University of Gothenburg (GU) and Halmstad University (HH). Two of these (Chalmers and Gothenburg) have formal schools of entrepreneurship, while Halmstad University has instead focused on an innovation engineering programme (see the fourth section below)). With assistance from the universities a postal questionnaire was distributed to 591 former students, out of whom 50%, or 294 individuals, answered (Table 1). These answers are used to analyse the differences between the entrepreneurs and the educations. The three schools represented in the sample exemplify both differences and similarities. One major difference is how long the educational programmes have existed. CSE was established as a 1-year Master’s programme in 1997. Thus, the first students graduated in 1998. Between 1998 and 2006, 152 students graduated. It was

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39

Table 1: Sample distribution.

Postal questionnaire Graduation year Answers Active response rate (%)

Total

CSE

GU

HH

591

140 1998–2006 70 50

85 2001–2006 41 48

366 2001–2006 183 50

294 50

possible to find the address of 140 of these former students, and 70 have answered our postal questionnaire (after two reminders). At the University of Gothenburg, the formal school of entrepreneurship started in 2000, as a 1-year Master’s programme at the School of Business, Economics and Law. The first graduates finished their education in 2001. Out of the total number of 89 former students, 85 could be identified and received a postal questionnaire. With two reminders this resulted in a response rate of 41 individuals, or 48%. The Innovation Engineering programme at Halmstad University is the oldest of the three sub-samples, starting as early as 1979. It is a 3-year Bachelors programme, which can be extended with a fourth year. This is not a formal school of entrepreneurship, and the studies focus on innovation and renewal. Since 1979 about 1300 students have graduated from this programme. In order to compare this group of graduates with the two groups from CSE and GU, we decided to only include graduates who were awarded their degrees between 2001 and 2006. This resulted in a population of 366 identified individuals. After sending a postal questionnaire and two reminders, this resulted in 183 usable answers. Thus, summarizing these responses leads to a usable sample of 294 individuals graduating between 1998 and 2006. Out of these 111 (38%) have a degree from a formal school of entrepreneurship, and 183 from an innovation-focused engineering programme. However, the graduates from the CSE also usually have an engineering background (4 years), while the students at the University of Gothenburg have a more mixed background. Actually, almost 40% of our respondents had a degree in business before they started the 1-year education to become professional entrepreneurs. Out of the questionnaire respondents, 77 are females and 217 are males. Their age ranged from 22 to 53, with a mean of 29 years. They had an average of 5 years’ work experience. The questionnaire included 34 questions, asking about the respondents’ (A) education and work experience, (B) own company formation experience, (C) networking, cooperation and financing and (D) view of business opportunities. In this first round of analysing our sample, we are primarily interested in questions about why the students wanted to study entrepreneurship, if and why they have created new firms and from where the business ideas originated. We are also interested in finding out whether and how the respondents feel that the entrepreneurship education has been useful for them. In fifth and seventh sections, we will describe the different characteristics between the groups of former students and analyse whether their education has affected their views and behaviour regarding

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new firm creation and entrepreneurial activities. In doing so, we provide some statistical testing using a few of the variables included in our questionnaire.

The Three Schools Chalmers University of Technology (CSE) was established in 1997, when a 1-year Master’s programme in entrepreneurship for engineering students was initiated. Since then the programme has been extended to 2 years, including both elective and compulsory courses, as well as an innovation project and a Master’s thesis. Courses such as Intellectual Property Strategies, Technology-Based Entrepreneurship, Design of Technological Innovations and Markets, etc., are studied. A total of 15–20 students are recruited each year. This is based on interviews where traits and abilities, for example, motivation, teamwork, responsibility, leadership and communication, are analysed. Ideas based on advanced university research are used for projects where the students can train and learn entrepreneurship. CSE is creating a network with innovative individuals, universities and firms interested in developing and commercializing early stage technology-based ideas with high market potential. The earlystage high-tech ideas are provided from researchers and innovators who can follow their idea grow in partnership with the student team and an international network for support with coaching and advice. A collaboration agreement is signed between the school and the provider of the idea. CSE is both an educational platform and a pre-incubator, and most students start a legal company during the year. The University of Gothenburg (GU) started a formal school of entrepreneurship in 2000, as a 1-year Master’s programme at the School of Business, Economics and Law. Business ideas are suggested from students or others, such as companies, entrepreneurs and researchers who will get assistance from the students to develop their ideas. A committee judges the commercial potential of the proposed business ideas, and suitable ideas are selected as student projects. The students have different backgrounds and previous Bachelor degrees. They work in small teams to develop new ideas and write business plans. They are supervised and coached by experienced professionals both from academia and from business. Four courses are included in the educational programme, Entrepreneurship in Theory and Practice, Strategy & Market, Resource Management, and Project Work and Intrapreneurship, in addition to work with the business plan. The academic examination is a combined business plan and Master’s thesis and sometimes also a new growing company. The aims are combined, both to develop the student’s entrepreneurial ability and to establish a new business. The aim of the school is that the graduates should be able to identify business opportunities, start a business or work as an entrepreneur in an existing company. By interviews their engagement, motivation and entrepreneurial skills are judged and used for the recruitment of 15 students each year. The Innovation Engineering programme at Halmstad University (HH) started in 1979 and was, because of its focus on innovation and product development projects, at that point unique in Sweden. The students work with projects to find solutions to

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41

industrial problems and to cooperate with established companies. The programme provides both technical and business knowledge. The first 2 years include studies in engineering skills such as maths, mechanics, electronics, design, product development and manufacturing, combined with business skills such as accounting, marketing, promotion and business development. The third year the students mainly work with their thesis, focusing on developing an idea into a product. The students have access to work space with prototype machinery, metal and modelling. It is a 3-year Bachelors programme, with an optional fourth year focusing on industrial management and innovation. The students have been acknowledged for their success in patent applications and establishing new companies. Graduates employed in existing companies mostly work with product development, project/production management or system selling. There are no courses in ‘entrepreneurship’, nor is the word used in the marketing of the programme. The focal point is clearly on innovation and product development, providing a broad technical and commercial base for managing the innovation process.

What Characterizes the Entrepreneurial Types? This section will provide a basic overview of the respondents in our sample. First, we will describe the similarities and differences between respondents graduating from the three different schools. The former students are compared with respect to the motives for their chosen education, their main occupation today and the source of the business idea (for the former students that had actually started a company). Second, we would like to argue that there are some main differences between the ‘educated professional entrepreneur’ and the ‘educated innovator entrepreneur’. In Table 2 the motives for the choice of an entrepreneurship education are summarized for the three sub-samples. Not surprisingly, the respondents from the HH group (which is not a formal entrepreneurship education) score lower than the other two when asked about the importance of wanting to know more about the topic (i.e. entrepreneurship) and the wish to start a company. We found that these motives were indeed the most highly ranked for students from CSE and GU. The Table 2: Motives for the choice of an entrepreneurship education. Mean

I wish to start a company I want to learn more about the topic I want to try a business idea Easy credits

CSE

GU

HH

4.45 4.24 1.63 1.04

4.38 4.26 2.47 1.34

3.17 3.89 1.63 1.35

Note: The answers were measured on a 5-point scale where 1 suggested ‘do not agree’ and 5 suggested ‘do fully agree’.

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wish to start a company ranks highest (mean 4.45 and 4.38, respectively), and the second strongest motive was to learn more about the subject (mean 4.24 and 4.23). Testing the differences in a one-way ANOVA shows that there are significant differences between the motives for the respondents in the groups (all significant at 0.01). A post hoc Tukey HSD test (Table 3) shows that for the two motives considered the most important (the wish to start a company and the wish to learn more about the topic) there are significant differences between the ‘educated professional entrepreneurs’ (the respondents from CSE/GU) and the ‘educated innovator entrepreneur’ (HH). Thus, it can be concluded that the motives to learn more about the subject and/or to start a company significantly differ between the ‘educated professional entrepreneurs’ and the ‘educated innovator entrepreneur’. Two additionally interesting things can be noted in Table 3. First, the students at GU, who have the freedom to suggest their own business ideas, tend to rank the motive to try a business idea significantly higher than the other former students do. Looking at the former students’ current activities and positions, there are also huge differences between the two groups. As can be seen in Table 4, the former students from CSE and from GU are today running their own companies to a much higher extent than do former students from HH. Among the ‘educated professional entrepreneurs’ 42% run their own business (full- or part-time), while the Table 3: Multiple comparisons of motives mean difference (Tukey HSD test). Motive (in Declining Order of Importance)

Standard Error

Significance

0.074 1.276* 1.201*

0.223 0.161 0.198

0.941 0.000 0.000

2. Learn more CSE–GU CSE–HH GU–HH

 0.021 0.349* 0.370**

0.188 0.135 0.167

0.993 0.027 0.070

3. Try a business idea CSE–GU CSE–HH GU–HH

 0.847* 0.001 0.848*

0.205 0.146 0.182

0.000 1.000 0.000

4. Easy credits CSE–GU CSE–HH GU–HH

 0.297**  0.305*  0.008

0.136 0.097 0.120

0.075 0.005 0.998

1. Start a company CSE–GU CSE–HH GU–HH

Mean Difference

Note: (*) Mean difference is significant at the 0.005 level; (**) mean difference is significant at the 0.1 level.

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43

Table 4: Main activity today. Total (n, %) Employed Self-employed Combination Studying Other

205 50 18 13 8

Total

294

(70) (17) (6) (4) (3)

CSE (n, %) 38 26 4 2 70

(54) (37) (6) (3) –

GU (n, %) 23 12 5 1 41

(56) (29) (12) (2) –

HH (n, %) 144 12 9 10 8

(79) (7) (5) (5) (4)

183

corresponding figure for the ‘educated innovator entrepreneur’ is only 12%. It is more common for the ‘educated innovator entrepreneur’ to hold positions as employed in some other organization (79%). Among the ‘educated professional entrepreneurs’ only 55% have an employment in a firm that is not their own. One critical difference in the design of entrepreneurial education seems to be related to the question of whether or not it is possible and recommendable to differentiate between innovators and entrepreneurs. As described above, CSE tends to separate innovation from entrepreneurship; ideas and innovations from university research are used to be further developed and commercialized by the entrepreneurship students. Some of these projects are later spun off as new firms, whereas other CSE students use their knowledge as ‘educated professional entrepreneurs’ to set up new firms based on other ideas. The education of the HH students instead focuses on the creation of innovations, which in turn may be used as the basis for new firm creation, that is, the training of future innovator-entrepreneurs. Table 5 makes it clear that the students tend to use different sources of ideas when setting up their own firms, and that the importance of these sources differs between the students. In total, the former students were asked about the importance of 10 different sources of ideas,1 but only the four most important motives for each group have been included in the table. The table shows that it is only the CSE students who tend to use university research and external inventors as main sources of business ideas. This clearly differentiates this education from the other two,2 which is very likely a result of the design of the education programme. Instead, the GU and HH students show similarities when it comes to the ranking of important sources of ideas; in both groups private ideas and the respondents’ own university studies are highly

1. The low means could be explained by the answers being spread out over the 10 fixed alternatives. 2. The only significant differences (at the 0.05 level) between CSE and the other two are found in the importance of using university research as sources of ideas. There are also significant differences between CSE and HH when it comes to the importance of external inventors, and between CSE and GU significant differences are found for the importance of private ideas and the respondents’ own university studies. There are, however, no significant differences between former GU and HH students.

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Table 5: The importance of different sources of business ideas (among former students who run their own firms). Ranking 1 2 3 4

CSE University research (2.44) External inventor (2.40) Private idea (2.20) Customer contact (2.00)

GU Private idea (3.67) Own university studies (3.00) Customer contact (2.71) Employment (1.90)

HH Private idea (2.89) Customer contact (2.70) Own university studies (2.52) Supplier (1.78)

Note: The answers were measured on a 5-point scale where 1 suggested ‘not at all important’ and 5 suggested ‘highest importance’.

ranked. Thus, while CSE seems to distinguish between innovators and entrepreneurs, this is not the case for the other two schools.3 Even though there are some grounds for separating the students into ‘educated professional entrepreneur’ and ‘educated innovator entrepreneur’, it is necessary to remember that both the former GU students and the former HH students are to a great extent exploring their own ideas, and thus combine the two roles of innovators and entrepreneurs. The CSE and GU schools both create meeting points for external ideas and students interested in helping to develop and commercialize new ideas. The students are supplied with the business idea and an exclusive network which they work with during their Master’s year. The students in these two groups already have a basic university degree and have chosen the entrepreneurial education as a supplement. The HH students, on the other hand, have chosen a 3-year programme focusing on innovation and product development and are more oriented toward the technical than the commercial aspect of innovative activity. After their studies, the HH students are primarily employed in other organizations than their own firms. This indicates that the focus of CSE and GU is on ‘learning to become an entrepreneur’ (i.e. a business focus) while the HH education focuses instead on ‘learning to become entrepreneurial’ (i.e. a focus on renewal). Students from CSE and GU can be seen as a professional group of graduate entrepreneurs who have received intensive training and support with a clear business focus. The focus of HH students is instead on innovation, and their objective is renewal rather than the creation of new firms for the exploitation of an idea.

3. The GU school provides the students with ideas to be developed. These ideas have usually not originated from university research, but are instead based on external ideas or the students’ own ideas. Since the students explore these ideas during their education, and the companies they are running are usually established after their education, it is likely that this will result in a higher ranking of both ‘private idea’ and ‘own university studies’, that is, even if the original source came from an external innovator.

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45

Will Different Forms of Entrepreneurship Training Result in Different Views on Company Development? In this section the three schools are grouped into two groups of entrepreneurs: the first is the ‘educated professional entrepreneur’ (EPE), the second is the ‘educated innovator entrepreneur’ (EIE). The focus is on whether the differences between these student entrepreneurs will result in different views on company development. The assumption is that both the background and the studies will influence the development of the new firms created. One way of analysing the views on company development is to study how the former students reflect on business opportunities; see Table 6. In total, the respondents were asked to reflect upon 10 different statements about their own behaviour. The results show that there are substantial differences between the EPEs and the EIEs. For 8 of the 10 reflections in Table 6, there are statistically significant differences between the two groups. The main difference between the two groups seems to lie in that the EPE continually searches and reflects on (new) business opportunities, while for the EIE it is not the opportunities but other factors (e.g. finding resources and transfer ideas) that are in focus. For example, the EPEs search to a greater extent actively for business opportunities, regarding the discovery of new opportunities as a Table 6: Reflections on business opportunities.

I am actively searching for new business opportunities One opportunity leads to others I often realize opportunities To find business opportunities is a learning process I like to reflect upon new business ideas New business opportunities often appear when solving a specific problem It is important that the business idea represents a concept that can develop over time New business opportunities appear normally due to market or technology changes The problem is not to find new opportunities but to find the necessary resources The problem is not to find new opportunities but to transfer my ideas to others

EPE

EIE

T-Test p*

3.56

2.63

0.00

3.93 3.08 3.88

3.29 2.19 3.47

0.00 0.00 0.01

4.03 3.57

3.47 3.27

0.00 0.01

3.74

3.92

–

3.64

3.55

–

3.06

3.40

0.02

2.14

2.74

0.00

Note: A 5-point scoring system was employed, ranging from ‘1 ¼ do not agree’ to ‘5 ¼ do fully agree’. (*) Difference significant at 0.05 level. Bold font shows the significant differences connected to the theory of Sarasvathy.

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learning process, and thinking that one new idea leads to others. Moreover, the EPEs also think that they realize their ideas more often and that they have fewer problems to convey their ideas to others. As seen in Table 7, the two groups of entrepreneurs also differ in the way they themselves reflect on new business creation. There are significant differences for 7 of the 12 reflections in Table 7. In particular, the EPEs and the EIEs tend to have different views when it comes to the uncertainty of new firm formation processes. There is a significant difference in how the individuals in the two different groups perceive risky situations. The EPEs show a significantly higher preference for welcoming uncertain situations with a view to making use of these events in the future. They also prefer informal methods to get market information. The EIEs, on the other hand, try to avoid insecure situations and prefer accurate market plans. This would suggest that the EPEs are more likely to prefer effectual reasoning in the business creation process compared to the EIEs. However, the EIEs show a significantly higher preference for effectuation, when it comes to proceeding from what they can afford to lose. The EPEs were found to score higher on having goaloriented relations and trying to maximize the profit of the opportunity, which can be Table 7: Reflections on the ‘‘creation of a new firm’’.

I prefer to have goal-oriented relations with stakeholders I prioritize maximizing the profit of the opportunity I prefer informal methods to get market information I prefer flexible goals, depending on available resources I prefer informal relations with stakeholder I create a market by identifying interested stakeholders I welcome insecure situations I meet a market demand and satisfy it I start from what I can afford to lose when realizing a business opportunity I prefer to have fixed goals and go for their results I try to avoid insecure situations I prefer accurate market plans

EPE

EIE

t-Test p*

3.81

3.54

*

3.66

3.32

*

3.53

3.23

*

3.39

3.24

3.27 3.09

3.14 2.89

3.05 3.33 2.63

2.70 3.45 3.33

3.30

3.32

2.63 2.70

3.37 3.00

*

*

* *

Note: A 5-point scoring system was employed, ranging from ‘1 ¼ do not agree’ to ‘5 ¼ do fully agree’. (*) Difference significant at 0.05 level. Bold font shows the significant differences connected to the theory of Sarasvathy.

Linking Innovation and Entrepreneurship in Higher Education

47

related to causation reasoning. The result shows differences between the two groups with regard to their preferences for effectual decision-making, but both groups seem to mix effectuation and causation approaches.

Are the Trained Entrepreneurs Able to Use what they have Learnt with a View to Establishing New Companies? Already when describing the characteristics of the schools and the former students, it was concluded that there were more EPE students who were running their own companies. Among the ‘educated professional entrepreneurs’ 42% are currently running companies they have established on their own, while only 12% of the EIEs are doing so. However, many more of the former students have acquired the experience of creating new firms. There are 50 former students from CSE with startup experience (71% of the respondents), 21 former students from GU (51% of the respondents) and 23 from HH (13% of the respondents). Thus, there is a tendency that the EPE students experiment with start-up activities to a much higher extent, while the EIEs instead tend to remain in business with the companies they create. This is further underlined when comparing the number of firms created by the former students. For CSE the 70 respondents have created 105 firms (i.e. on average 1.5 firm/student), the GU students 41 firms (0.83 firm/student) and the HH students 34 firms (0.19 firm/student). This indicates that the EPEs are habitual entrepreneurs to a higher extent.4 When asked about the major benefits of their education, the EPEs score higher on all aspects measured in Table 8. The former students of the formal entrepreneurship schools (EPE) consider the education to have contributed with personal and financial connections, interaction with university researchers and external innovators, as well as other cooperation partners. The ‘educated professional entrepreneurs’ in general acknowledge the benefits of the entrepreneurship education positively when it comes to factors of importance to starting-up. The findings show that the education innovator entrepreneurs acknowledge less benefit from the education in factors known to contribute to start-ups. Moreover, the former EPE students consider the education itself to have contributed positively to the start-up of their firms (a mean of 3.15 on a 5-point scale). The corresponding figure for the EIE students is 1.74.5 A tentative regression was run in order to explore what it is that influences the differences in start-up rate. Both the education itself and the motive to choose an entrepreneurship education were found to contribute to the start-up frequency. The

4. Looking only at the students with start-up experience, the corresponding figures show a mean of 2.1 companies per student (146/71) for EPEs and 1.5 (34/23) for EIEs. 5. This figure could partly be explained by the fact that significantly fewer of the EIE students have actually started companies.

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Table 8: Important benefits of the entrepreneurship education.

General knowledge Important personal contacts Special knowledge Contributed to starting up Contact with co-operators Contact with financiers Contact with university researchers Contact with customers

EPE

EIE

t-Test p

4.36 3.67 3.42 3.15 3.17 2.72 2.48 2.07

3.93 2.85 2.36 1.74 2.63 1.88 1.96 1.87

0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.10

Note: A 5-point scoring system was employed, ranging from ‘1 ¼ do not agree’ to ‘5 ¼ do fully agree’.

results indicate that participating in a formal school of entrepreneurship contributes significantly to the start-up rate (coefficient ¼ 0.261, significant at 0.000), and that the benefits of the education itself have actually contributed more (coefficient ¼ 0.569, significant 0.000) than the motive to chose the education because one wishes to start a company (coefficient ¼ 0.091, significant at 0.05). These three variables gained an adjusted R2 value of 0.588 when used to explain the variance in start-up formation.

Conclusion and Implications The results of this study strongly suggest that professional entrepreneurship education influences the entrepreneurial behaviour of students. Students who choose to participate in a formal school of entrepreneurship seem especially to benefit from what they have learnt with regard to exploiting opportunities and creating new firms. EPEs learning entrepreneurship in these schools seem to focus on goal-oriented profit maximization, while the latter (EIEs) tend to avoid insecure situations and start from what they themselves think they can afford to lose when realizing a business opportunity. It is also clear from the results of this study that the EPEs tend to reflect on and continuously search for new business opportunities, while the EIEs instead focus on how to find necessary resources and how to transfer their ideas to others. There are clear differences between how the two groups show a mixture of causation and effectuation reasoning. According to Sarasvathy (2001), both approaches can occur simultaneously. The EPEs have learned the conventional start-up steps in their education but are, on the other hand, to a larger extent experienced habitual entrepreneurs. How these and other factors, such as the characteristics of the idea, the individual, the environment or the stage of development, influence the preference for effectuation-based start-up processes will be worth further examination.

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Another important finding of this study is that the ‘educated professional entrepreneurs’ to a higher extent tend to be habitual entrepreneurs (Westhead & Wright, 1998; Politis, 2005) and to create a higher number of new firms. Instead, the ‘educated innovator entrepreneur’ tend to take on employment in other organizations, perhaps to work as ‘internal entrepreneurs’ or ‘intrapreneurs’. Even so, the results also indicate that there might be a sub-group of habitual entrepreneurs creating a high number of new firms among the ‘educated innovator entrepreneur’. This sub-group is worth further attention in future studies. One of the most important conclusions of this study is that both the participation in a formal school of entrepreneurship and the benefits of the education contribute to business start-up. Even though many students choose an entrepreneurship education because they want to start their own firm, our results indicate that the type of entrepreneurial education is more important than this motivation. In other words, the results suggest that the fact that EPEs create a relatively high number of new firms is influenced by the education, and not only by the fact that these individuals have an already existing interest in starting a business. Even so, it should be remembered that the students analysed in our sample might be predisposed toward entrepreneurship and have expressed their interest in becoming entrepreneurs by their choice of education. Thus, it would be interesting for future research to complement this study by adding some control group to the analysis. Another area for further research is to compare and analyse the development and performance of the firms created by the entrepreneurs. From the preliminary findings of this study, it seems as if the ‘educated innovator entrepreneur’ are more persistent in developing the firms they create, while the ‘educated professional entrepreneurs’ instead tend to habitually establish new firms, perhaps instead of staying with the firm when it develops and grows. We hope to be able to get back to this question and analyse it when these newly created firms have had some time to develop and mature.

Acknowledgements The authors want to express their gratitude to the Knowledge Foundation (KKstiftelsen) for providing the financial support which has made this study possible. They also gratefully acknowledge the support of the FSF organization, as well as the help received from the three universities and their former students. Finally, they are very happy to belong to the KEEN research group of Halmstad University and to RIDE at Chalmers University. Valuable comments and ideas have been generated by members of both these research centres.

References Aldrich, H., & Auster, E. R. (1986). Even dwarfs started small: Liabilities of age and size and their strategic implications. Research in Organizational Behaviour, 8, 165–198.

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Davidsson, P. (2006). The entrepreneurial process. In: S. Carter & D. Jones-Evans (Eds), Enterprise and small business: Principles, practice and policy (pp. 129–151). Harlow: Pearson. Davidsson, P., & Klofsten, M. (2003). The business platform: Developing an instrument to gauge and to assist the development of young firms. Journal of Small Business Management, 41(1), 1–26. Delmar, F., & Shane, S. (2003). Does the order of organizing activities matter for new venture performance?. In: W. D. Bygrave, C. G. Brush & P. Davidsson, et al. (Eds), Frontiers of entrepreneurship 2003. Wellesley, MA: Babson College. Gibb, A. (1997). Small firms’ training and competitiveness. International Small Business Journal, 15(3), 13–29. Gustafsson, V. (2004). Entrepreneurial decision-making. JIBS dissertation series no. 022, Jo¨nko¨ping University. Johannisson, B. (2000). Networking and entrepreneurial growth. In: D. Sexton & H. Landstro¨m (Eds), The Blackwell handbook of entrepreneurship (pp. 368–386). Oxford: Blackwell. Lindholm Dahlstrand, A˚. (2008). University knowledge transfer and the role of academic spin-offs. In: J. Potter (Ed.), Entrepreneurship and higher education (pp. 235–254). Paris: OECD Publication. Penrose, E. T. (1959). The theory of the growth of the firm. Oxford: Basil Blackwell. Politis, D. (2005). The process of entrepreneurial learning: A conceptual framework. Entrepreneurship Theory and Practice, 29(4), 399–424. Samuelsson, M. (2004). Creating new ventures. JIBS dissertation series no. 20, Jo¨nko¨ping University. Sarasvathy, S. D. (2001). Causation and effectuation: Toward a theoretical shift from economic inevitability to entrepreneurial contingency. Academy of Management Review, 26(2), 243–263. Shane, S. (2000). Prior knowledge and the discovery of entrepreneurial opportunities. Organization Science, 11(4), 448–469. Shane, S., & Venkataraman, S. (2000). The promise of entrepreneurship as a field of research. Academy of Management Review, 25(1), 217–226. Stinchcombe, A. (1965). Social structure and organizations. In: J. March (Ed.), Handbook of organizations (pp. 142–193). Chicago: Rand McNally. Westhead, P., & Wright, M. (1998). Novice, portfolio, and serial founders. Journal of Business Venturing, 13(3), 173–204.

Chapter 5

How Useful is the Stage Model Theory in Explaining the Capital Structure of Venture Capital-Backed and Non-Venture Capital-Backed Firms? Teresa Hogan and Elaine Hutson

Introduction Policymakers have long supported the development of venture capital markets on the basis that venture capital fills a perceived gap in the availability of early stage seed capital funding for new technology-based firms (NTBFs).1 Support from policymakers, however, has not been matched by academic research on NTBF financing. This is a major concern because NTBF financing is not well understood. The theoretical focus of this chapter is the life cycle or stage model of financing, which has proved the dominate paradigm in the analysis of financing in NTBFs. It is particularly relevant to this study, as the stage model is explicitly endorsed by venture capitalists who structure deals in phases in order to effectively monitor the investee firm’s progress (Sahlman, 1990). Using data gathered via a survey of a sample of NTBFs in the Irish software product sector, we address two research questions. First, how closely does the capital structure of venture capital-backed firms and non-venture capital-backed firms reflect the predictions of the life cycle model? We provide a breakdown of the capital structure of venture capital-backed and non-venture capital-backed firms at various

1. NTBFs are defined by Little (1977) as independent ventures less than 25 years old that supply a product or service based on the exploitation of an invention or technological innovation.

New Technology Based Firms in the New Millennium, Volume VIII Edited by R. Oakey, A. Groen, G. Cook and P. van der Sijde r 2010 Emerald Group Publishing Limited. All rights reserved.

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stages in their development, by dividing the sample firms into four age categories: start-up (o2 years), commercialisation (2–4 years), growth (5–9 years) and maturity (W10 years). Second, to what extent is the early stage funding of venture capitalbacked and non-venture capital-backed firms linked to key events in their formation? We present an event history analysis of the start-up stage of software product firms. The events are: first beta product, recruitment of first employee(s), receipt of first revenue from consulting activities, receipt of first revenue from product sales, and first external funding of any kind. While we examine the timing of all of these startup stage events, we focus our analysis on the impact of two events — product lead times and receipt of first consulting revenues — on the funding of venture capitalbacked and non-venture capital-backed software product firms. Product lead times in the software development sector are shorter than in other high-technology sectors such as electronics or biotechnology, and the investment requirement involves primarily human rather than physical capital. As product lead times in the software product sector are relatively short, and costly physical capital is generally not needed, external funding may not be required to fund product development. In addition, start-up software firms also have the option to undertake consulting contracts to finance product development; this is referred to in the literature as the ‘soft start’ model of financing (Bullock, 1983). In our event history analysis, we also seek to examine whether the sample firms were able to fund product development without obtaining external funding, and to what extent product development was financed via the use of consulting revenues. The Irish software sector provides an excellent laboratory for the analysis of financing in venture capital-backed versus non-venture capital-backed firms. The venture capital market in Ireland grew rapidly from the mid-1990s, and its focus was the burgeoning software sector. The amount invested by venture capitalist in Irish companies rose from h32 million in 1979 to over a quarter of a billion euro in 2000, and remained at this level even after the technology stock crash in the early 2000s (Irish Venture Capital Association (IVCA), 2006). Further, the Irish government, through Enterprise Ireland — the state agency responsible for supporting the development of indigenous industry — is a major investor in venture capital funds. The rationale for government participation is to bridge a perceived gap in the availability of early stage seed capital funding, and to support the development of the venture capital industry (Enterprise Ireland, 2003). Enterprise Ireland (2006) reported that 83% of the money invested in their Seed and Venture Capital Programme over the period 2001–2005 went to start-up companies. This compares with a European average of 38% and a US average of 29% for start-up stage venture capital investment during the same period. There is no doubt that the relatively high proportion of venture capital funding channelled to start-ups in Ireland is a result of government participation. Mulcahy (2005) estimates that the government accounted for 17% of total venture capital funds raised in Ireland over the period 1998–2003, compared to a European average of 7%. The main beneficiary of this policy has been the indigenous information technology (IT) industry, and in particular the software sector, which until recently had very little competition from emerging technology sectors (such as healthcare and biotechnology) for funds. The investment portfolios

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53

of Irish venture capitalists remain dominated by software companies, which attracted 60% of their total investment funds in 2005 (IVCA, 2006). The remainder of the chapter is structured as follows. The next section presents an overview of the literature on NTBFs and the stage model. In the third section, the survey methodology is discussed and summary data on the characteristics of the sample are presented. Our findings are discussed in the fourth section, in two subsections: first, capital structure by stage, and second, key events in the formation process. The final section summarises and concludes.

Theoretical Background The stage model has dominated the academic and practical literature on the financing of NTBFs. The model holds that stages in the firm’s development are paralleled by changes in its financial structure and access to finance. In a large-scale study of high-technology firms, Roberts (1991, p. 125) pointed out that: The new technology-based firm evolves through a succession of several stages of corporate growth and parallel development in its finance. The time during which a company can be classified in a particular phase varies widely among firms and the dividing line between phases is at best fuzzy. Yet the relative stage of evolution does strongly influence the type and amount both of capital required and especially of capital available. Acceptance of the model in the technology sector is demonstrated by the structuring of venture capital deals into stages or rounds. Nesheim’s (2000) popular handbook High Tech Start-up breaks down the capital formation process into 14 stages, from the idea phase through to initial public offering (IPO). Roberts (1991) identified four stages in the financial life cycle of NTBFs: seed, start-up, early growth and sustained growth. These are presented in Table 1, which we have adapted to include the primary sources of financing available and the potential financial problems encountered at each stage.

The Four Stages of Financial Life Cycle NTBFs differ from the general population of start-ups in that they are characterised by an intensive period of research and development (Kazanjian, 1988; Kazanjian & Drazin, 1990) at the so-called ‘seed’ stage. In order to develop the product, the founder commits limited personal funds, assumes the risk of failure and puts in time and effort (so-called ‘sweat equity’). This phase is funded primarily by the founder’s personal savings and those of friends and family. The seed stage is followed by prototype development and testing at start-up. It is likely that the founder’s personal

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Table 1: The financial life cycle of the new technology-based firm. Stage Seed  Concentrated R&D resulting in product idea  First test for commercial viability Start-up  Prototype development design and redesign  Targeting reference customers

Early growth  Foothold in the market  Sales growth  Move towards profitability  Large commercialisation costs

Source of Finance

Potential Problems

 3Fs: founders, family and friends  Research grants/equity

 Undercapitalisation

As above plus:  Overdrafts, bank loans  Leasing  Private investors  Venture capital  Seed funds

 Undercapitalisation  Finance gap  Loss of control

As above plus:  Retained profits  Trade credit  Longer term finance from financial institutions  Supplier/buyers  New market issue

As above plus:  Maintaining ROI

As above

 Maintaining ROI

Sustained growth

Note: This table is derived from Roberts (1991). In addition, potential problems encountered at each stage are flagged.

funds will be exhausted during this stage, and some source of outside funding is usually necessary. This is because NTBFs tend to be characterised by long product lead times. There is limited evidence on NTBF financing at start-up, but it suggests that this stage is financed mainly by the founders, followed by friends and family, and then by private investors (Roberts, 1991). In the United Kingdom, Moore (1994) reported that NTBFs raised only 7% of initial funding from banks, compared with 24% for SMEs in general, suggesting that NTBFs face greater problems in debt markets than their counterparts in other sectors at start-up. If private equity or venture capital is unavailable, the NTBF is likely to face serious financial constraints, and undercapitalisation at start-up has been linked to poor growth performance (Lumme, Kauranen, & Autio, 1994; Moore, 1994). The ‘early growth’ or commercialisation stage marks the end of product development, and at this stage the firm begins to establish a foothold in the market.

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55

The risk of failure recedes as sales revenues increase and retained profits become an increasingly important source of finance. By the time the NTBF reaches the ‘sustained growth’ stage, it will have diversified its products and markets. The firm’s investment decisions and financing requirements will not differ substantially from those of other successful large companies. Despite its practical appeal, the stage model has attracted much criticism. One of the fundamental criticisms is it treats NTBFs as a homogenous group, whereas NTBFs are in fact highly diverse. For this reason our sample comprises software product firms, for which we provide a breakdown of the sources of finance at the different stages in their development. In this context, is the stage model applicable to software product firms in general, and does it hold for both venture capital-backed and non-venture capitalbacked firms? The model has also been criticised for implicitly assuming that all firms pass uniformly through these predetermined stages (Gibb & Davies, 1991; O’Farrell & Hitchens, 1987). Other researchers view new firm development as stochastic rather than as a linear sequence as the stage model implies (Gersick, 1994; Katz, 1993; Reynolds & Miller, 1992). In a rare empirical test of the stage model for SMEs, Reynolds and Miller (1992) examined the sequencing of four events: principal’s commitment, first hire, first financing and first sales. They found little support for a linear and sequential formation process. In the second part of our study, we examine the sequencing of key events in the formation process of venture capital-backed and non-venture capital-backed software product firms. The analysis focuses on funding at the start-up stage, as it is often said that NTBFs can face greater financial constraints at this stage than the general population of new firm start-ups. We seek to establish whether there is any systematic relation between product lead times and two events in the start-up phase, namely receipt of external funding and receipt of consulting revenues. The stage model predicts that NTBFs are primarily self-financing at the start-up phase in their evolution. Product lead times, however, may affect the firm’s ability to finance this phase internally. The longer the product lead time, the more likely firms will require external financing (Oakey, 1995; Roberts, 1991). In the software sector, product lead times are generally shorter than in other high-technology sectors, and capital requirements are relatively low (Oakey, 1995). Prior analysis has found, contrary to the stage model’s predictions, that software product firms were just as likely to secure finance in advance of producing their first beta product as they were to receive funds subsequently (Hogan & Hutson, 2006). On average, firms produced their first beta product in a median of 12 months and acquired their first external funds a median of 3 months later, but this timing difference is not statistically significant. This suggests that the software product firm may be able to produce its first beta product without having to first secure external funds. In this chapter, we investigate whether there is a difference between the timing of these two events in venture capital-backed and non-venture capital-backed firms. In other words, are venture capital-backed firms more likely to receive funding prior to producing their first betas than non-venture capital-backed firms?

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Cash earned from consulting activities or provided by potential suppliers and customers is an important source of new product development financing at the start-up stage in NTBFs. Bullock (1983) suggests that many begin life as ‘soft starts’; founders can choose a low-risk service-orientated ‘soft’ start-up entry strategy and ‘harden’ over time to become product-orientated ventures. PricewaterhouseCoopers (1999) demonstrated that Bullock’s (1983) ‘soft start’ description is particularly pertinent in Ireland, where many software product companies start out providing bespoke development and consulting services to businesses before going on to develop software products. The ‘soft start’ model would be more apt for non-venture capital-backed firms than the venture capital-backed firms. We investigate whether non-venture capital-backed firms are more likely to use consulting revenues to finance the product development phase than their venture capital-backed counterparts.

Methodology and Sample Characteristics In Ireland — as in other countries — the majority of start-ups in the software sector are service firms. Software product firms are those that are primarily involved in the development and commercialisation of their own products. A database of indigenous software companies was compiled specifically for this study and took over a year to complete. Using various sources (National Software Directory, Software Association of Ireland), we found that there were more than 1000 indigenous software companies in Ireland in 2001. Of these, we identified 257 as software product companies. The survey design was based on self-administered questionnaires using the tailored design method (Dillman, 1976, 2000). The response rate was just under 46%. The majority (71%) of the sample firms were active in the diverse and fragmented ‘applications’ segment of the software product market. Applications can be targeted at specific industry sectors such as banking, education and training, telecommunications and health, but ‘applications’ also include functional software such as accounting, word processing, payroll and e-mail software. According to HotOrigin (2002), the financial services sector was the main target for indigenous software firms, followed by the telecommunications and high-technology sectors. The next highest concentration of indigenous software product firms was in the ‘systems’ segment. This category incorporates a wide range of products, including operating systems, network management and distributed computing. Eighteen firms (15% of the sample) were involved in developing systems software. Of the remaining 16 companies, 7 (6%) were developing data management software, 6 (5%) were developing enterprise software and 3 (2.5%) were involved in the development of programming languages and tools such as Java and C + + , as well as security tools. Of the 117 firms that responded, 110 provided information on their capital structure and their shareholders, enabling the sample to be split into venture capitalbacked and non-venture capital-backed firms. The number of venture capital-backed

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57

and non-venture capital-backed firms is similar: 56 of the 110 (51%) for which capital structure data are available had not received venture capital backing, and 54 (49%) were funded by venture capitalists. Table 2 summarises the age and size distribution of the sample firms. Panel A shows that the youngest firm was less than a year old, and the oldest was 27 years. The average age was under 6 years (5.8 years), and the median was 4 years. The venture capital-backed firms were younger than the non-venture capitalbacked; the mean age (at the time of the survey) of the former was 4.8 years (median 3.5), and the latter group was on average 6.7 years old (median 5). Two measures of size are provided: employment (Panel B) and sales turnover (Panel C). Panel B shows employment data for 108 firms that provided information for 2002. Total employment in the full sample is 2609, or an average of 26 employees per firm (median 12.5). The venture capital-backed firms employed over twice as

Table 2: Age and size distribution for venture capital-backed and non-venture capital-backed firms. Venture Capital-Backed (n ¼ 54) Panel A: age (years) Mean Median Minimum Maximum

Non-Venture Capital-Backed (n ¼ 56)

Total (n ¼ 110)

4.8 3.5 1 19

6.7 5 0 27

5.8 4 0 27

Panel B: size (employment) Total 1755.0 Mean 32.5 Median 20.5 Minimum 0.0 Maximum 200.0

854.0 15.8 8.5 0.0 140.0

2609.0 24.1 13.5 0.0 200.0

Panel C: size (turnover) Pre-revenue oh127,000 h127,000–634,999 h635,000–1,269,999 h1,270,000–3,809,999 Wh3,810,000

Number

%

Number

%

Number

%

12 1 15 7 11 6 52

23.1 1.9 28.8 13.5 21.2 11.5

9 12 11 10 11 3 56

16.1 21.4 19.7 17.9 19.6 5.4

21 13 26 17 22 9 108

19.4 12.0 24.1 15.7 20.4 8.3

Note: Turnover figures were requested in Irish punts, as euro notes and coins were not introduced until 2002, but we report our findings in euro only.

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many people as the non-venture capital-backed firms; the former employed 1755 people, giving an average of 32.5 employees per firm, and the latter a total of 854 people, which is 16 employees per firm. Most respondent firms were relatively small when size is measured by sales. Almost one-third turned over less than h127,000, and 55.5% had sales less than h635,000. Twenty-nine percent of firms had a turnover of greater than h1,270,000, and only 8% had a turnover of greater than h3,810,000. There was little difference between the two groups except that the venture capitalbacked group had a higher proportion of firms recording both no turnover and turnover of more than h3,810,000.

Results The results are presented in two parts. Part one presents the capital structure of venture capital-backed and non-venture capital-backed firms. The survey respondents were asked to provide information on current sources of funding: internal (savings, consulting revenues and retained earnings) and external (bank debt, venture capital, private investors and government grants). Capital structure is classified by stage of development by dividing the sample firms into four age categories: start-up (o2 years), commercialisation (2–4 years), growth (5–9 years) and maturity (W10 years). The time bands for the start-up, commercialisation and growth stages for our sample software product firms are based on estimates provided by the National Software Directorate (1997). The description of the four stages is based on Roberts (1991), with one exception — Roberts (1991) does not include a ‘mature’ stage in his model. The description of the mature phase comes from traditional financing stage model theory as outlined by Weston and Brigham (1970), and the time band is taken from Berger and Udell (1998). Part two examines differences in the sequencing of formation events and is based on the work of Reynolds and Miller (1992), with the addition of events specific to software development — consulting revenues and beta production. Survey respondents were asked to identify their firm’s formation date and to supply dates for key events in the formation process relative to the formation date. These events were development of first beta product, recruitment of first employee(s), receipt of first revenues from consulting activities and product sales, and first external funding.

Capital Structure Table 3 provides summary capital structure information at each stage for the 96 firms in the sample that provided detailed funding information. Due to the well-known difficulty of persuading owner-managers to reveal financial data, this information was requested in percentage form. Panel A presents the average figures for the sample overall, Panel B provides a breakdown for the non-venture capital-backed firms and Panel C provides details for the venture capital-backed firms. Columns [3]–[6] present

43.0 10.0

9.5 10.0 14.0

12

46

20

18

96

[3]

Savings

55

21.5

35.5 50.0

36.0 23.5

25.5

12.5

17.5

25.0

3.0

17.0

46.0

18.0

8.5

2.5

[5]

32.5

19.0

20.0

28.0

13.5

27.0

[4]

Consulting Retained Revenues Profits

72.0

85.5

81.0

50.0

87.0

50.0

76.0

55.5

32.0

72.5

[6]

Total Internal

Internal Sources of Financing (%)

Panel B: Non-venture capital-backed firms [A] Start-up 10 51.5 (o2 years) [B] Commercialisation 20 20.0 (2–4 years) [C] Growth 10 9.5 (5–9 years) [D] Maturity 15 12.0 (W10 years)

Panel A: Full sample [A] Start-up (o2 years) [B] Commercialisation (2–4 years) [C] Growth (5–9 years) [D] Maturity (W10 years)

Number of Firms

Table 3: Sources of finance at different stages.

5.0

5.0

8.0

6.5

0.0

4.0

5.0

6.5

3.0

0.0

[7]

Bank Loans

0.0

0.0

0.0

0.0

0.0

28.0

11.0

28.0

38.0

13.0

[8]

Venture Capital

16.0

5.5

2.5

31.5

9.5

11.0

5.0

3.0

18.5

10.0

[9]

Private Investors

7.0

4.0

8.5

12.0

3.5

7.0

3.0

7.0

8.5

4.5

[10]

Government Grants

External Sources of Financing (%)

28.0

14.5

19.0

50

13.0

50.0

24.0

44.5

68.0

27.5

[11]

Total External

Venture Capital-Backed and Non-Venture Capital-Backed Firms? 59

Number of Firms

41

Panel C: Venture capital-backed firms [A] Start-up 2 (o2 years) [B] Commercialisation 26 (2–4 years) 10 [C] Growth (5–9 years) [D] Maturity 3 (W10 years)

Table 3: (Continued )

19.0 0.0

9.5 0 11.0

10.0

2.5

4.0

0.0

[4]

5.0

26.5

1.0

5.0

0.0

[5]

Consulting Retained Revenues Profits

0.0

[3]

Savings

20.0

26.5

29.5

17.5

0.0

[6]

Total Internal

Internal Sources of Financing (%)

2.5

8.5

5.0

1.0

0.0

[7]

Bank Loans

65.0

65.0

56.0

67.5

78.5

[8]

Venture Capital

7.0

0.0

4.0

8.0

13

[9]

Private Investors

5.5

0

5.5

6.0

8.5

[10]

Government Grants

External Sources of Financing (%)

80.0

73.5

70.5

82.5

100.0

[11]

Total External

60 Teresa Hogan and Elaine Hutson

Venture Capital-Backed and Non-Venture Capital-Backed Firms?

61

the proportion of total financing obtained from internal sources, including personal savings [3], consulting revenues [4] and retained profits [5], whilst column [6] shows the total internal financing. Columns [7]–[11] provide information on external sources, including bank loans [7], venture capital [8], private/angel capital [9] and government grants [10], whilst column [11] presents total external financing. Rows [A]–[D] delineate the results for the four age bands representing different stages in the life cycle of the software product firm: start-up (o2 years), commercialisation (2–4 years), growth (5–9 years) and maturity (W10 years). The average figures for the full sample show a 50/50 divide between internal and external sources of finance. A mere 4% of finance was provided by banks, and the remaining outside finance (46%) consisted of private equity and government grants. The average figures mask a substantial difference between the capital structures of venture capital-backed and non-venture capital-backed firms. In contrast to the 50/50 split between internal and external funding for the sample overall, Panel B shows that non-venture capital-backed firms were much more dependent on internal sources than their venture capital-backed counterparts (Panel C). On average, the non-venture capital-backed firms financed 72% of their capital requirement from internal sources of funds, compared to 20% for venture capitalbacked firms. Venture capital, as expected, was clearly the key difference between the two groups, accounting for 65% of all funding for the venture capital-backed subsample. The financing hierarchy for the non-venture capital-backed group was similar to the sample overall — internal, outside equity, and then debt. For the venture capital-backed firms, outside equity comprises the vast majority of financing, followed by internal finance, and lastly, debt. Interesting patterns emerge when the two sub-samples aged. Internal finance remains the dominant source of finance for the non-venture capital-backed firms irrespective of age, with retained profits taking over from savings in the growth and mature phases. The exception to the absolute dominance of internal sources of finance occurs for firms between 2 and 4 years old. This indicates that the critical funding stage for software product firms is not at start-up but rather at the commercialisation stage. At this stage, only half of the financing requirement for non-venture capital-backed firms was provided by internal sources, and money from private investors (32%) and government grants (12%) take up the slack. This suggests that considerable resources must be mobilised for the commercialisation effort in software product firms, as start-up funds and savings have run down and sales have not yet taken off. Retained profits were essentially absent from the venture capital-backed firms except for those over 10 years old, whereas retained profits comprise a very high proportion of financing for the non-venture capital-backed group in both the growth and mature phases of their development (36% and 50%, respectively). Another major difference between the two groups is the near absence of savings for the venture capital-backed cohort, and the presence of savings as a source of finance even among the older non-venture capital-backed group. As previously discussed in Hogan and Hutson (2005), consulting revenues were an important source of funds

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Teresa Hogan and Elaine Hutson

for software firms, and the ability for these software product firms to earn money from consulting work gives them considerable financial flexibility. Comparing the two sub-samples, it is clear that consulting revenues are a much more important source of financing for the non-venture capital-backed firms, representing 25% of overall funding compared to 11% for the venture capital-backed sub-sample. Consulting revenues appear to play a critical part in financing on an ongoing basis when venture capital is absent.

The Formation Process Table 4 reports the timing of the following key events in the start-up process of software product firms: development of first product beta, recruitment of first employee(s), receipt of first revenues from consulting activities and product sales, and first external funding. External funding covers all sources of external funding including bank finance, private equity, venture capital and government grants. Panel A presents the average figures for the sample overall, Panel B provides a breakdown for the non-venture capital-backed firms, and Panel C provides details for the venture capital-backed firms. The time periods are calculated from the month of formation. Some firms, however, reported not having attainted particular milestones, and this information is recorded in column [6]. All but 4 firms had recruited their first employee, while 20 non-venture capital-backed firms had not acquired any external funding. The mean and median number of months from start-up to the attainment of each milestone appear in columns [1] and [2], respectively. All of the means exceed the medians, indicating right skewness in the data; therefore, the discussion of the summary statistics will concentrate on medians rather than means. The median time to first product beta for the overall sample was 12 months, which was well after the firms earned their first consulting revenues in month 3 or hired their first employee in month 4. First external funding was obtained just a half month after the production of first beta — a median of 12.5 months after start-up. First product revenues were earned a median of 2 months after first product beta, in month 14. The non-venture capital-backed firms reached all milestones (with the exception of external funding) before the venture capital-backed cohort. The median time to first product beta for non-venture capital-backed firms was 10 months, followed by first product revenue in month 12, and lastly, first external funding a median of 14.5 months after formation. These firms hired their first employees and earned their first revenues from consulting activities concurrently, a median of 2 months after formation. It took the venture capital-backed firms longer to reach each of these milestones with the exception of external funding. However, the t-test results in Panel D indicate that, with the exception of consulting revenues, there are no significant differences in the timing of the events between the two cohorts. The non-venture capital-backed firms earned their first revenues from consulting earlier than the venture capital-backed firms (p ¼ 0.013). This suggests that the

0.525 0.153 0.013 0.944 0.334

0 0 0 1 0

0 0 0 0 0

0 0 0 0 0

Minimum

[3]

79 28 33 78 112

88 135 27 91 156

88 135 33 91 156

Maximum

[4]

53 53 41 45 52

49 51 44 46 32

102 104 85 91 84

Total Attaining Milestone

[5]

1 1 12 9 0

5 3 10 8 22

6 4 22 17 22

Milestone Not (Yet) Attained

[6]

1 0 2

1 1 1 1 1

1 1 2 1 3

Missing

[7]

Note: Column [6] — ‘Milestone not yet attained’: firms were asked to tick a ‘not applicable’ box if their business had not yet reached the particular milestone.

Panel D:t-tests (p-values) (a) Prototype (b) Employee (c) Consulting revenue (d) Product revenues (e) External funding

12 4 6 14 11.5

Panel C: VC-backed (n ¼ 54) (a) Prototype (b) Employee (c) Consulting revenue (d) Product revenues (e) External funding

18 6 8.5 19 18

10 2 2 12 14.5

Panel B: non-VC-backed (n ¼ 55) (a) Prototype 16 (b). Employee 11 (c) Consulting revenue 4.5 (d) Product revenues 18.5 (e) External funding 24

Median

Mean

12 4 3 14 12.5

[2]

[1]

17.0 8 6.5 19 20

Panel A: full sample (a) Prototype (b) Employee (c) Consulting revenue (d) Product revenues (e) External funding

Time to first

Table 4: Timing of key events in the start-up stage in VC and non-VC-backed firms (monthly analysis) (n ¼ 109).

Venture Capital-Backed and Non-Venture Capital-Backed Firms? 63

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non-venture capital-backed firms are more likely to be ‘soft starts’ insofar as they start earning revenues from consulting at an earlier age than their venture capital-backed counterparts. Interestingly, beta production does not appear to take significantly longer in venture capital-backed software firms than in non-venture capital-backed firms; beta production for the former is a median of 2 months later (month 12) than in their non-venture capital-backed counterparts. However, the t-test (p ¼ 0.55) shows that this difference in timing is not significant. This is an important finding, because as already noted, product lead times are shorter in software development than in other high-tech sectors and therefore would appear to have less impact on financing requirements. It suggests that product lead times are not a key determinant of whether or not software development firms seek venture capital. Further analysis points to differences between the two sub-samples in the sequencing of beta production and external funding. Looking at Table 4 it is clear that non-venture capital-backed firms fund beta production using internal funds only, with first funding arriving a median of 4.5 months after completion of first beta product, while their venture capital-backed counterparts receive their first funding half a month before their first beta product appears. Table 5 shows the sequencing of beta production and first external funding in the overall sample and in the two subsamples. Row A of Table 5 shows the number of firms that produced their first beta and received their first injection of funds in the same month. Row B shows the number of firms that either had produced a beta before attracting funding or had not secured

Table 5: The sequencing of first beta and first external funding. Full sample (N ¼ 109) Number (A) Beta and external funding concurrently (B) Beta before funding or without funding (C) Funding before beta or without prototype (D) No beta and no external funding Total Missing/insufficient data Independent sample test Mann–Whitney U z ¼  3.154 p ¼ 0.002

%

VC-backed (N ¼ 54) Number

%

Non-VC-backed (N ¼ 55) Number

%

4

3.8

2

4.0

2

3.7

56

53.8

20

40.0

36

66.7

41

39.4

28

56.0

13

24.1

3

2.9

0.0

3

5.5

104 5

100

0.0 50 4

100

54 1

100

Venture Capital-Backed and Non-Venture Capital-Backed Firms?

65

external funding at the time the study was undertaken (i.e. firms that ticked milestone ‘unattained’ in the questionnaire). These refer to the 22 firms in column [6] in Table 4. Effectively, ‘non-attained’ signifies that the firm produced its beta before attracting external funding. Similarly, row C shows the number of companies that had secured funding before developing their first beta product or that had not developed their first beta product at the time the survey was completed.2 Table 5 confirms the findings from Table 4. Overall, 56 of the 104 firms for which we have data (53.8%) developed their first beta product prior to attracting any external funding. This pattern is much more evident in the non-venture capitalbacked firms, where 36 out of 54 firms (66.7%) had developed their first beta product before obtaining external funding. The corresponding figure for the venture capitalbacked firms is 20 (40%). Consequently, 56% of the venture capital-backed firms, compared to 24% of the non-venture capital-backed firms, had succeeded in securing external funds prior to developing their first beta product. The test statistics for the sequencing of the key events are also presented in Table 5. In order to maximise the number of observations, the data were transferred from continuous to categorical, otherwise the 22 non-venture capital-backed firms that had no external funding of any kind would have to be excluded. Thus, firms that had developed their first product beta before receiving external funding, or were yet to receive external funding, are combined as category 1 (row B), and those that had accessed funding before product beta or had yet to produce their first beta are denoted category 0. The independent sample test confirms that difference in the sequencing of the two events across venture capital-backed and non-venture capital-backed firms is highly significantly (p ¼ 0.02). This finding is consistent with the tendency for non-venture capital-backed firms to earn revenues from consulting earlier than their venture capital-backed counterparts. Since non-venture capital-backed firms are less like to secure external funding for product development, they are more likely to use revenues from consulting activities to fund product development. This evidence suggests that the difference in the pattern of funding in the two cohorts is evident even at start-up, when the nonventure capital group tend to substitute internal sources for external sources of funds. This pattern is also evident from the stage analysis of capital structure in nonventure capital-backed firms (Table 3), which showed that consulting revenues accounted for 32.5% of total funding in this group at start-up. The comparable figure for the venture capital-backed firms was zero. However, it should be noted that there were only two venture capital-backed firms in this stage classification. Nonetheless, a comparison of financing for both groups over the other three stages indicates that consulting revenues were consistently a more important source of funding for the non-venture capital-backed firms.

2. There were insufficient data available to determine the sequencing of the event in three cases; this is where firms supplied yearly data only and where the events in question occurred in the same year. No information was available for two firms.

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Conclusion The stage model remains the dominant model for the analysis of NTBF financing. One of the fundamental criticisms of the stage model, however, is that it treats NTBFs as a homogenous group. In this chapter we have demonstrated that, even within a narrow sub-sector of NTBFs, there is considerable within-group variation in the pattern of financing over the various stages of development, and in the timing and sequencing of key events at the start-up stage. Overall, non-venture capitalbacked NTBFs in the software product sector tend to follow the traditional life cycle model of financing, with internal sources dominating external sources of funding at both the start-up and mature stages of their development. Savings and consulting revenues — which are the most important sources at start-up — are replaced by retained profits at the mature stage as predicted by the stage model. In contrast, the venture capital-backed firms follow the financial life cycle typical of NTBFs at commercialisation, but remain highly dependent on external sources of funding throughout their life cycle, sourcing on average 80% of their financing requirements externally. The comparable figure for the non-venture capital-backed firms is 28%. Therefore, neither group fits the stage model of financing for NTBFs. The start-up stage is of particular interest, since policymakers believe that the gap in the market for funds appears at this stage. However, not all NTBFs are the same. Although venture capital-backed firms tend to make greater use of external funding at this time, there is no difference in the product lead times between venture capitalbacked and non-venture capital-backed firms. The software sector may be unique among high-technology sectors in this respect because software products have rather short lead times — the median lead time in our sample was 12 months. The analysis in this chapter has suggested that software product firms are more likely to experience a funding gap post-product development — in the commercialisation stage. Even the non-venture capital-backed firms need to draw on external funds to finance the commercialisation stage of their development. Only half of their financing requirement at this stage was provided by internal sources, and money from private investors (32%) and government grants (12%) took up the slack. It has already been suggested that a greater dependence on external sources at this stage may reflect the depletion of ownership sources of funds and/or the requirements of getting the product to market. Nevertheless, there is clearly a need for further analysis of the financing requirements of software firms at this stage in their development. This is of concern because banks do not appear to be a major provider of funds to either group at this post-start-up phase in their development. Prior research confirms that the founders of software product firms in Ireland perceive greater information asymmetries in debt markets than in venture capital markets (Hogan & Hutson, 2005). This may reflect the Anglo-Saxon banking system in Ireland. Consulting revenue is an important source of funding for software product firms in general. It is the most important source of internal funding for the venture capital-backed firms and represents 11% of total funding for this cohort. Consulting revenue is, however, a much more important source of finance for the non-venture

Venture Capital-Backed and Non-Venture Capital-Backed Firms?

67

capital-backed group and represents 25% of total funding. In addition, non-venture capital-backed firms get involved in consulting significantly earlier than their venture capital-backed counterparts. Non-venture capital-backed firms received their first revenues from consulting a median of 2 months after formation, which was a median of 4 months before their venture capital-backed counterparts. This is consistent with a ‘soft start’ strategy that favours internal sources of funding over external sources. Overall, the combination of short product lead times and opportunities to undertake consulting activities to fund development shows that software entrepreneurs have considerable financial flexibility at start-up.

References Berger, A. N., & Udell, G. F. (1998). The economics of small business finance; the role of private equity and debt markets in the finance growth cycle. Journal of Banking and Finance, 22, 613–673. Bullock, M. (1983). Academic enterprise, industrial innovation and the development of high technology financing in the United States. London: Brand Brothers and Co.. Dillman, D. (1976). Mail and telephone surveys. New York: Wiley. Dillman, D. (2000). Mail and internet survey. New York: Wiley. Enterprise Ireland (2003). Annual Report Dublin. Dublin, Ireland: Enterprise Ireland. Enterprise Ireland (2006). Seed and Venture Capital Programme 2000–2006 Report. Dublin, Ireland: Enterprise Ireland. Gersick, C. (1994). Pacing strategic change: The case of new venture. Academy of Management Journal, 37, 9–45. Gibb, A. A., & Davies, L. G. (1991). Methodological problems in the development and testing of a growth model of business enterprise development. In: A. A. Gibb & L. G. Davies (Eds), Recent research in entrepreneurship (pp. 286–321). Aldershot, UK: Avebury. Hogan, T., & Hutson, E. (2005). Capital structure in new technology-based firms: Evidence from the Irish software sector. Journal of Global Finance, 15(3), 369–387. Hogan, T., & Hutson, E. (2006). The relation between key events in the development phase and the financial structure of NTBFs in the software sector. International Entrepreneurship and Management Journal, 2(2), 56–72. HotOrigin. (2002). Ireland’s software cluster: Innovation — The fuel for international success. A Report on the Indigenous Software Sector in the Republic and Northern Ireland. Dublin, Ireland: HotOrigin. Irish Venture Capital Association (IVCA) (2006). The economic impact of venture capital in Ireland — 2005. Dublin, Ireland: IVCA. Katz, J. A. (1993). The dynamics of organisational emergence: A contemporary group formation perspective. Entrepreneurship, Theory and Practice, 17(2), 97–110. Kazanjian, R. K. (1988). Relation of dominant problems to stages of growth in technologybased new ventures. Academy of Management Journal, 31, 257–279. Kazanjian, R. K., & Drazin, R. (1990). A stage contingent model of design and growth for technology based new ventures. Journal of Business Venturing, 5, 137–150. Little, A. D. (1977). New technology-based firms in the United Kingdom and the Federal Republic of Germany. London: Wilton House.

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Lumme, A., Kauranen, I., & Autio, E. (1994). The growth and funding mechanisms of new technology-based firms: A comparative study between the United Kingdom and Finland. In: R. Oakey (Ed.), New technology-based firmed in the 1990s (pp. 81–92). London: Paul Chapman. Moore, B. (1994). Financial constraints to the growth and development of small high technology firms. In: A. Hughes & D. J. Storey (Eds), Finance and the small firm. London: Routledge. Mulcahy, D. (2005). Angels and IPO: Policies for sustainable equity financing of Irish small businesses. Dublin, Ireland: The Policy Institute, Trinity College Dublin. National Software Directorate (NSD) (1997). The financing of high-technology start-ups. Dublin, Ireland: National Software Directorate. Nesheim, J. L. (2000). High tech start-up. New York: The Free Press. Oakey, R. P. (1995). High-technology new firms: Variable barriers to growth. London: Paul Chapman. O’Farrell, D., & Hitchens, M. W. N. (1987). Alternative theories of small firm growth: A critical review. Research Paper no. 15. Edinburgh: Department of Town and Country Planning, Heriot Watt University Edinburgh. PricewaterhouseCoopers (1999). Strategic development of internationally traded service industries throughout Ireland: Software. Dublin, Ireland: Enterprise Ireland. Reynolds, P., & Miller, B. (1992). New firm gestation: Conception, birth, and implications for research. Journal of Business Venturing, 7, 405–417. Roberts, E. B. (1991). Entrepreneurs in high technology; lessons from MIT and beyond. New York: Oxford University Press. Sahlman, W. A. (1990). The structure and governance of venture capital organisations. Journal of Financial Economics, 27(2), 473–521. Weston, J. F., & Brigham, E. F. (1970). Managerial finance (3rd ed.). Fort Worth, TX: Dryden Press.

Chapter 6

Who You are and What You do: The Role of Entrepreneurial Human Capital in the Demand and Supply of External Finance of High-Tech Start-Ups Panagiotis Ganotakis

Introduction The existence of adequate financial capital at start-up as well as during the lifetime of a firm is considered to be vital not only for its survival but also for its effective trading and growth, as it can act as a buffer against unforeseen difficulties (Cooper, Gimeno-Gascon, & Woo, 1994; Chandler & Hanks, 1998; Venkataraman & Van de Ven, 1998; Cassar, 2004). Inadequate or inappropriate capital structure is often the most common reason for a large proportion of small business failures (Chaganti, DeCarolis, & Deeds, 1995). In the case of new technology–based firms (hereafter NTBFs), the access to financial capital is even more crucial. Further to the direct effect it has on their own viability and performance, it also exerts a wide indirect effect on the economy of a country in regards to job creation, competitiveness and economic growth. NTBFs are considered to be major conduits for translating scientific knowledge into commercial products and services, and they play a crucial role in the development and diffusion of innovative products at the base of the competitiveness of a country’s economy (Storey & Tether, 1998; Hogan & Hutson, 2005). Therefore, it is important for the factors that determine whether high-tech start-ups are able to access appropriate external sources of finance to be investigated. The existence of a financial gap in the United Kingdom, especially for the case of small and medium enterprises (SMEs) and NTBFs, has been a subject of debate for

New Technology Based Firms in the New Millennium, Volume VIII Edited by R. Oakey, A. Groen, G. Cook and P. van der Sijde r 2010 Emerald Group Publishing Limited. All rights reserved.

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some time. Theoretically, the existence of such a gap has been seen for some (e.g. Evans & Jovanovic, 1989) as the cause of capital market imperfections (supply constraints), whereas arguments also exist that a large part of it is self-imposed by the entrepreneurs themselves (demand constraints), due to their unwillingness to apply for external finance (Kon & Storey, 2003). This suggests that distinctive characteristics of high-tech entrepreneurs are expected to be closely related to the success of the company as they influencethe organizational and strategic decisions at the start-up stages and through the company’s life (Feeser & Willard, 1990; Gimeno, Folta, Cooper, & Woo, 1997; Casson, 2005). The existing literature on firms’ access to financial sources at the start-up stage has been almost entirely concerned with the criteria and processes that providers of external finance use (by using data obtained from investors) in order to decide whether or not to supply finance. The methodologies used in these studies have been criticized in a number of ways. First of all, as mentioned in the work by Shepherd (1999) and Silva (2004), such studies rely predominantly on the accuracy of the providers of finance introspection, which can produce invalid results.1 Second, the majority of these studies tend to focus on the criteria used by the suppliers of finance while very little is known about the characteristics of the entrepreneurs that apply (or do not apply) for external finance, irrespective of whether they receive it, and they in most cases focus almost exclusively on single sources of firm financing (Storey, 1994; Mason & Harrison, 1996; Boocock & Woods, 1997). Finally, even where the same source was analysed, the results do not always support each other (e.g. for the United Kingdom, see Storey (1994) and Deakins & Hussain (1991, 1994)). This chapter overcomes these limitations by following suggestions from the human capital theory (Becker, 1964; Preisendo¨rfer & Voss, 1990; Colombo & Grilli, 2005; Ganotakis, 2008); the nature and the combination of skills of those entrepreneurs (or entrepreneurial team) who apply for external finance as well as the characteristics of those who obtain external finance are jointly investigated. This allows to test whether the supply and the demand of finance can be related to the entrepreneurs’ characteristics and the level of presence of each one in a founding team.2 Moreover, the chapter addresses the differences (if any) in the demand and supply of external finance across a spectrum of sources of financing used by NTBFs, namely external equity, bank debt and governmental support. External equity is here defined as the finance received from venture capitalists, business angels and corporate

1. Some of the limitations included retrospective reporting (e.g. Tyebjee & Bruno, 1984), hypothetical cases (e.g. Zacharakis & Meyer, 1998), which was criticized as it relied on hypothetical ventures and environments rather on actual proposals, and taping verbal protocols (e.g. Hall & Hofer, 1993) criticized for relying on self-reported data. 2. In the literature a similar approach was taken by Grilli (2005) and Astebro (2002). However, both were carried out for access to bank debt alone; none of them was for the case of the United Kingdom (Italy and the United States, respectively), and they were limited to firms operating in the software and the small business sector, respectively.

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ventures; bank debt includes bank loans and overdrafts, while governmental support includes finance received from the major sources of financial assistance available to NTBFs, for example, SMART, Loan Guarantee Scheme, EU programmes (e.g. FRAMEWORK), etc. Drivers, criteria and motivation to finance a project (supply) can be very different depending on the provider and its point of view. A bank might be interested in collateral, venture capitalists in the exit perspectives, a governmental body in the level of job creation, R&D spillovers, etc. The same arguments can be used for the demand, in that motivation, objectives and rationale are very different if you are seeking a bank loan, equity or subsidies. The financial literature has produced a number of papers that both theoretically and empirically examine which kind of firms in equilibrium would use debt versus equity finance. Myers (1977), Myers and Majluf (1984), Jensen and Meckling (1976) and Jensen (1986) identify factors such as information asymmetry and agency costs that could affect a firm’s ability and choice of external versus internal and debt versus equity financing. A number of papers also examine the usage of bank versus debt finance (Rajan, 1992). However, most of the factors previously documented to affect equilibrium facing choice have been based on controlling for differences across firms in terms of sales growth, volatility, asset size, asset tangibility, existing debt levels, etc. This framework is clearly not applicable to the start-up decision of NTBFs. Also, most of this literature is focused exclusively on the demand or on the supply side but not on both simultaneously. This chapter, on the other hand, tests the factors that affect the demand and supply (1) for external finance in general and (2) for each of the aforementioned sources of finance individually. This makes it possible to test if significant differences exist across the different sources due to the different requirements and the different nature of the financial support. To the author’s knowledge, this is the first comparative study that estimates and compares the factors that most affect the likelihood of a firm to apply and also receive funds from different sources of external financing. The chapter is structured as follows. The next section presents the main testable hypotheses and the factors that are expected to have an impact on the ability of a high-tech start-up to access external finance. Section ‘Model Specification’ describes the econometric method, the data set and the variable specification. Section ‘Empirical Results’ reports the results of the empirical analysis. A final section concludes.

Testable Hypotheses on the Factors Affecting Access of a High-Tech Start-Up to External Finance Evans and Jovanovic (1989) argue that the capital market is imperfect and entrepreneurs face liquidity constraints. As a result of the ‘financial gap’, they use a sub-optimal amount of capital to start up their business with potentially negative effect on the survival of their firms. Later, Cressy (1996) argued that the correlation

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that Evans and Jovanovic (1989) observed between financial capital and survival is demand driven as firms self-select for funds on the basis of the human capital endowments of the founders, with more qualified founders being more likely to borrow. That would mean that qualified entrepreneurs will be more likely to apply for external finance and are also the more likely to receive it. This theory would implicitly suggest that a ‘skill gap’ could exist and that could be as dangerous as the ‘financial gap’. In order to investigate the presence of a skill versus a financial gap, the human capital theory is applied (Becker, 1964; Preisendo¨rfer & Voss, 1990; Colombo & Grilli, 2005; Ganotakis, 2008) which allows for the investigation of whether the investment entrepreneurs made on their own education, training and experience exert a significant impact on the demand and supply of external finance. In particular, the chapter differentiates between general and specific human capital. General human capital (e.g. entrepreneurial age) refers to skills that can be transferred to other jobs in the economy. On the contrary, specific human capital (e.g. technical, business education; commercial, managerial experience) refers to skills specific to a certain job (or position) that can have no effect if transferred to other firm, that is, they might not be transferred to other occupations. The sections that follow present the testable hypotheses for the effect that entrepreneurial as well as other firm’s characteristics are expected to have on the supply and the demand for external finance.

Education and Past Experience A substantial literature has argued that educational attainment can be an important factor in contributing to lower levels of failure reported in high-tech firms (Roberts, 1991; Storey & Tether, 1998; Almus & Nerlinger, 1999). Education also provides the entrepreneur with a sufficient start in knowledge and confidence for success in the new venture. Firms with highly educated entrepreneurs may find it easier to attract external finance, as it is very likely that this is noticed by providers of external finance (Storey, 1994; Mason & Harrison, 1996; Boocock & Woods, 1997). Moreover, higher levels of education itself and especially business education can provide technology entrepreneurs with an advantage over their blue-collar counterparts when applying for external funds, as they are better equipped to prepare loan applications and to negotiate with investment firms/institutes (Oakey, 1984). Contrary to the supply for external finance, the effect that high levels of education might have on the demand for external finance is not obvious. On the one hand, it is more likely that highly educated entrepreneurs will have the ability to identify potential opportunities for growth and also find ways of taking advantage of them. That means that it will be more likely for their firms to grow and therefore apply for external finance in order to finance that growth. On the other hand, entrepreneurs with higher levels of human capital than the average are more likely to have already accumulated the necessary financial capital through better paid previous employment

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(Xu, 1998; Asterbo & Bernhardt, 2002), with no need for external finance. Therefore, although no clear hypothesis can be provided for the effect that education has on the demand for external finance, the following hypothesis can be made for the supply of external finance: Hypothesis 1. High levels of education (in both technical and business disciplines) have a positive effect on the ability of a firm to attract external finance. The skills that a management team has acquired through experience appear in the literature to be of major importance to venture capitalists, business angels and banks in order to invest in a firm (MacMillan, Seigel, & Subba Narasimha, 1985; Sweeting, 1991; Muzyka, Birley, & Leleux, 1996). More specifically the main areas of experience viewed in the literature as important for external investors are managerial, commercial and technical experience. Shepherd, Douglas, and Shanley (2000), for example, argue that a firm will be regarded investment ready from external investors if it is considered to be management ready, market ready and technology ready. Each of these areas is argued to be crucial for the financial success of a firm and, as such, they are considered by investors. A new firm will be regarded ‘management ready’ if the management team has the necessary skills and knowledge that would allow it to manage production, marketing, human resources and finances. To achieve that, the team will collectively have to have qualifications and experience (management acumen) across the range of business and technology areas that are needed. Similarly, a new firm will be considered ‘technology ready’ if prototypes have been built and tested and if the new product/service can be mass produced at a unit cost that allows sufficient profit at the envisioned price level. Finally, a new firm will be regarded as ‘market ready’ if the new product has been tested against the needs of the target customer and found to be in substantial demand by the target market at the proposed price level. Management readiness is directly linked not only to the education (business/ management) but also to the experience of the entrepreneurial team, as are the other two firm readiness areas. For example, it is not possible to achieve technology readiness without the founding team having the appropriate technical expertise, and market readiness will not be achieved without the team having the appropriate commercial experience (see among the others Boocock & Woods, 1997; Feeney, Haines, & Riding, 1999; Siegel, Siegel, & MacMillan, 1988). Evidence on the impact of managerial experience on the supply of finance was found to be important by external finance providers such as bank managers (Fletcher, 1995), venture capitalists (Wright & Robbie, 1996) and business angels (Harrison & Mason, 2002). Also, entrepreneurs that have same-sector experience will be expected to have higher levels of performance in their entrepreneurial role as they will have professional experience in the same sector that will provide them with knowledge on the market, and technological and competitive environment in which the new firm will operate (Grilli, 2005). That has been recognized by a number of external finance providers. As a result, the management’s same-sector experience has been proved to be one of the main factors for investing in a firm (MacMillan et al., 1985;

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Muzyka et al., 1996; Harrison & Mason, 2002). Therefore, the following hypothesis is formulated concerning the supply of external finance: Hypothesis 2a. Managerial, commercial, technical and same-sector experience have a positive effect on the ability of a firm to attract external finance. Moving to the demand for external finance, a number of researchers have identified certain values and goals of entrepreneurs as the most important factors that determine strategic and therefore financial decisions. For example, Kotey and Meredith (1997), Chell, Howorth, and Brearley (1991) and Vickery (1987) divided founders into two categories according to their personal values and examined their strategic preferences and financial decisions. They identified and characterized ‘entrepreneurs’ as those founders that adopted proactive strategies that involved initiative taking and adoption of management practices, and were associated with the use of all resources including external finance which can provide a firm with a leading edge over its competitors and enable them to maximize returns. On the other hand, founders described as ‘reactive strategists’, ‘caretakers’ or ‘parsimonious’ were identified to be risk averse and to rely on internal equity as a source of finance that would allow them to maintain control of their firm. Entrepreneurial values such as competence, achievement, responsibility, innovation and creativity (Kotey & Meredith, 1997; Silver, 1988) are expected to be higher in teams where high human capital exists as founders will have higher levels of knowledge about the market and technological environment and more belief in their managerial abilities and the future performance of their firm (Grilli, 2005). Human capital characteristics that have been proved to have a positive effect on the growth and performance of firms are expected to affect also the demand for external finance. Such characteristics include commercial (marketing, finance, human resource), managerial and to a less extent technical experience (Gimeno et al., 1997; Bruderl & Preisendo¨rfer, 2000; Ganotakis, 2008). It is expected that entrepreneurial ability is going to be higher in teams where the above human capital variables exist as that will cause reduction in the uncertainty about a firm’s post-entry performance; founders will have higher levels of knowledge about the market and technological environment and more belief in their managerial abilities (Grilli, 2005). As a result, entrepreneurial teams with specific human capital skills are expected to be more likely to apply for external finance. Finally, it can be argued that entrepreneurs with same-sector previous experience are likely to have developed relationships with more appropriate providers of external finance in their previous occupation. That means that it will be easier for them to receive but it can also make them more confident to apply for external finance. This leads us to formulate the following hypothesis concerning the demand for external finance: Hypothesis 2b. Commercial, technical, managerial and same-sector experience in a founding team will be expected to have a positive effect also on the willingness of a firm to apply for external finance.

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Other Entrepreneurial Characteristics Concerning the number of founders that start a firm, it is reasonable to expect that the greater the number of founders, the higher the start-up financial capital and the less the need to apply for external finance (Grilli, 2005). At the same time it is possible that a large team is a proxy for and an indicator of an ambitious large project with growth potential that is more likely to seek external finance. On the supply side, the higher financial start-up capital can be seen from potential investors as collateral. Also, a firm with relatively more owners may imply a greater variety of complementary skills (Almus & Nerlinger, 1999) and it may also proxy for a deeper commitment to a successful firm, both of which will make them more attractive investment proposals (Astebro & Bernhardt, 2003).3 The higher the average age of the entrepreneurial team, the more likely they have accumulated the necessary financial capital through more years of working experience. The personal accumulated wealth can serve as a substitute for external finance, so the likelihood of them applying for external finance will be lower than for younger entrepreneurs (Astebro & Berhhardt, 2003). On the supply side, it is more likely that older entrepreneurs invest higher levels of financial capital in the firm at start-up, which means that higher levels of collateral can be available. Older entrepreneurs are also more likely to have higher levels of human and social capital in comparison to younger entrepreneurs. All the above characteristics can have a positive influence on the decision of both bank institutes and external equity providers. Therefore, we formulate the following hypothesis: Hypothesis 3. The larger and the older the founding team, the more likely it receives external finance but the less likely it applies for it.

Other Control Factors Other control factors reflecting firm-specific characteristics are included in the analysis such as whether a firm belongs to the manufacturing sector and whether it is founded in a science park. From the demand side for external finance, as the manufacturing sector is more capital intensive than the service sector (Porter, 1980), entrepreneurs operating in such sectors are expected to be in more need of a higher start-up financial capital which will make them more likely to apply for external finance. For the supply for external finance, the case is not that clear. On the one hand, manufacturing firms are more likely to have higher levels of tangible assets in their structure due to the need for production equipment and inventories. That can serve

3. That was the case in a study of Bas in the United Kingdom by Mason and Harrison (1994), where it was found that investment in single founder firms was rare.

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as collateral which in turn can serve as a control of adverse selection and moral hazard problems that are generated by information asymmetries (Parker, 2002). On the other hand, in high-tech sectors some assets might be too specific. That can reduce their resale value (Fiet, 1995), and consequently they would not be able to be used as collateral. Further to that, high-tech manufacturing start-ups can be regarded as riskier investment proposals as they can require a longer period for R&D, often for an innovative but untested commercial product than traditional start-ups (Oakey, 2003). The following hypothesis is therefore formulated: Hypothesis 4. Start-up firms operating in the manufacturing sector are more likely to apply but less likely to receive external finance.

Model Specification The Econometric Model The first aim of this chapter is to investigate the factors that affect the access of NTBFs to external sources of finance while trying to differentiate between the demand and the supply sides of accessing external finance. The most straightforward way to model the firm’s demand for external finance is by specifying a dichotomous variable y1i equal to 1 if a firm seeks external finance and 0 if it does not. Similarly another dichotomous variable y2i can be used to indicate whether a firm managed to receive external finance (1) or not (0). These two variables reflect the observed characteristics of the demand and the supply of external finance and can be modelled by two latent variables y1i and y2i as in Eq. (1): y1i ¼ b01 w1i þ e1i y2i ¼ b02 w2i þ e2i

ð1Þ

where the vector w1i includes firm- and entrepreneurial-specific determinants of the demand for external finance and vector w2i comprises variables that indicate whether a number of entrepreneurial and firm characteristics meet the requirements of the providers of external finance. e1i and e2i are normal standard distributed error terms; i ¼ 1, 2, y, N. Unfortunately, information on whether the company has applied for external finance irrespective of whether the company has received external finance was not available.4 Information was available only on those companies that have obtained

4. In terms of the four possible combinations — applied and received (y1i ¼ 1 and y2i ¼ 1), applied and not received (y1i ¼ 1 and y2i ¼ 0), not applied and received (y1i ¼ 0 and y2i ¼ 1), and not applied and not received (y1i ¼ 0 and y2i ¼ 0) — the last three are indistinguishable, one of which is unlikely. In other words, the only information about the two binary variables is whether both equal 1, and the remaining possible outcomes cannot be distinguished from each other.

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external finance. Basically, only w1i and w2i and yi ¼ y1iy2i are observed. This prevents direct estimation of the demand equation in Eq. (1). In such case and given that the actors involved in the decision-making process (supply and demand) are not the same, the Poirier model based on partial observability (see Poirier, 1980) turns out to be the most appropriate specification. The Poirier model assumes that the two probit equations in Eq. (1) can be indirectly estimated jointly by maximum likelihood where the likelihood function of the model reduces to L¼

Y

 Y  F2 ðb01 w1 ; b02 w2 ; rÞ 1  F2 ðb01 w1 ; b02 w2 ; rÞ

i:yi ¼1

(2)

i:yi ¼0

where F2 is the bivariate standard normal cumulative distribution function and r the correlation coefficient between the two disturbances. The probability that the ith high-tech company will apply for an external source of finance at start-up and will be successful in the application will be given by Prob½ yi ¼ 1 ¼ Prob½y1i 40; y2i 40 ¼ Prob½e1i 4  b01 w1i ; e2i 4  b02 w2i  ¼ F2 ðb01 w1i ; b02 w2i ; rÞ

ð3Þ

Conversely, the probability that the ith high-tech start-up will not have access to external finance will be given by 1  Prob[ y1 ¼ 1]. This set-up allows for the estimation of the supply and demand equation for external finance as in Eq. (1). Poirier (1980) also shows that in order for the model to work, a necessary condition is that at least one variable that is contained in one of the variable vectors (either w1 or w2) is not included in the other. The variable chosen for this purpose is discussed in the following section.

The Data Set The data used in this study are the result of a unique postal survey carried out in the United Kingdom between March and June 2005 over a sample of firms that are independently owned (i.e. the founder(s) owns at least 50% of the company), do not belong to a group, are less than 25 years old and belong to a high-technology sector. Following Butchard (1987), high-technology sectors were defined as those sectors with the highest proportion of scientists and engineers in R&D activities and with the highest R&D intensity (measured as R&D expenditure both over sales and over value added), in relation to the rest of the sectors. The information used to identify the key sectors was sourced from the OECD (STAN Indicators), the ONS (MA-14 report on R&D in the UK business) and the Department of Trade and Industry (DTI) — now Department for Business, Enterprise and Regulatory Reform (the Department of Trade and Industry (2003) ‘Innovation Report’ and various scoreboards). The sectors that were identified as high technology from both manufacturing and services were pharmaceutical, aerospace, electrical equipment, TV, radio,

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communications equipment, medical equipment and computer equipment, telecommunications, software, R&D in natural science and engineering and technical testing and analysis. For each sector 15.76% of the sector population stratified and calibrated by age and size was randomly extracted, leading to an original sample of 4000 companies.5 Data were gathered by first calling each entrepreneur to explain the purpose of the research and to ask whether they would have liked to participate. Following the call, a postal questionnaire was sent out. If no response was received within 2 weeks, the company was contacted again via telephone and a reminder with another copy of the questionnaire was sent. Of the original sample of 4000 companies, a representative by sector and firm size sub-sample of 412 firms was derived (10.3% response rate) providing information on 751 entrepreneurs operating in 243 manufacturing and 169 service high-tech firms.

The Variable Specification The questionnaire was designed to contain a number of questions on entrepreneurs’ characteristics, financial structure, financial sources at start-up as well as a number of other firms’ characteristics. This information was used to model the determinants of the demand for external finance at start-up (w1 and w2 in Eq. (1)). Their definition and the sign of the impact they are expected to exert on the supply and the demand for external finance (at start-up) are listed in Table 1. The same variables are going to be specified in both the supply and the demand equations of Eq. (1) apart from the variable that captures whether a firm was located at a science park at start-up. This variable is omitted from the demand (but not the supply) side in order to meet the unequal information set condition required by the partial observability bivariate probit model (a similar approach was taken by Grilli (2005) in his study of Italian start-ups). As Westhead and Batstone (1998, 1999) found, in the United Kingdom, science park firms make rare use of business advice and planning and financial advice and support or access finance directly from the science park itself. Moreover, science park managers appear to be poorly perceived with regards to providing information or creating links with the nearby university that can have a reverse effect on their ability to become investment ready (Westhead & Batstone, 1998). Consequently, for the majority of the incubated firms the access to external finance is likely not to be due to better information about financial products that can be available from the park. Rather it is more likely to be an effect of the environment of the science park that can provide a firm with higher perceived credibility, and also

5. Size of firms was divided in seven categories according to employment size (0–4, 5–9, 10–19, 20–49, 50–99, 100–249, W250), and age was divided in four (o2, 2–4, 5–10 and 11–25 years). The size categories were defined after considering the definitions of firms’ size provided by the EU Commission Recommendation 2003/361/EC and the Office of National Statistics PA1003_2004, ‘UK Business: Activity, Size and Location — 2004.

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Table 1: Independent variables: description and expected sign. Name 1 Technical education 2 Business education 3 Sector experience 4 Technical experience 5 Commercial experience 6 Managerial experience 7 Founders 8 Entrepreneurial age 9 Industry sector 10 Science park

Description 0–5: 0, None; 1, Higher National Certificate; 2, Higher National Diploma; 3, Degree; 4, Masters; 5, PhD 0–5: 0, None; 1, Higher National Certificate; 2, Higher National Diploma; 3, Degree; 4, Masters; 5, PhD, MBA Average number of founders with previous sector experience different than current Average number of founders with experience in a technical role (R&D, engineering, manufacturing, IT) Average number of founders with experience in a commercial role (marketing, sales, finance, HR) Average number of founders with experience in a managerial position Number of founders at start-up Average age of an entrepreneurial team Dummy variable whether a company belongs to the manufacturing sector (1/0) Dummy variable whether the firm was located at a science park at start-up (1/0)

Demand

Supply

No prediction

+

No prediction

+





+

+

+

+

+

+

 

+ +

+



N/A

+

of the cooperation agreements with larger companies (corporate venture capitalists) that can be created due to the science park’s environment.

Empirical Results Access to External Finance in General Table 2 presents the results of the bivariate probit model with partial observability divided into the supply and demand equations for external finance in general. Starting from the entrepreneurial human capital variables and the demand side, it is found that entrepreneurial teams with either high technical or business formal educational skills (theoretically more qualified entrepreneurs) are more likely to make the decision to apply for external finance. This does not support the argument that educated entrepreneurs are less likely to apply for external finance being better able to gather the financial capital needed to start up a firm due to relatively higher paid past employment (see Grilli, 2005). On the contrary, it seems that higher human capital increases the likelihood of applying to external sources of finance perhaps due to

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Table 2: Demand for and supply of external finance: bivariate probit. Variables Constant Technical education Business education Sector experience Technical experience Commercial experience Managerial experience Founders Entrepreneurial age Industry sector Science park Rho (1, 2) N

Demand

Supply

 0.847*** 0.172*** 0.107*  0.003 0.00915*** 0.0147*** 0.00285  0.148  0.138 0.68*** –

 7.427***  0.116 0.033 0.00284  0.0147 0.0115 0.00255 0.406** 2.229***  0.733* 0.903 0.99***

339

339

***Significant at the 1% level; **significant at the 5% level; *significant at the 10% level.

a better ability to identify potential opportunities for growth and to be able to take advantage of these opportunities at a larger scale. This also might reflect a possible higher confidence in relation to lower skilled entrepreneurs for their ability to succeed. On the supply side, the bivariate probit model shows that none of the specific human capital variables (education or experience) appears to have a significant effect on the ability of a firm to attract external finance. This does not support Hypotheses 1 or 2a and shows that even though highly qualified entrepreneurs are more likely to apply for external finance, their skills have no impact on their firms accessing external funds. The specific human capital variables that capture the experience in functional areas are an important factor in explaining the decision of a founding team to apply for external finance. In fact, both variables that capture technical and commercial experience have a significant and positive effect. This result provides support for most part of Hypothesis 2b, showing that the entrepreneurial team’s level and type of experience have a positive effect on the likelihood of a firm applying for external finance at start-up. The number of founders as well as the entrepreneurial age have the expected negative signs in the demand equation; however, none of them appears to be significant. On the supply side it is found that the higher the number of founders, the easier it is for them to receive external finance, and the same was found for older entrepreneurial teams. These results confirm Hypothesis 3 that the larger and the older the founding team, the more likely it is to receive external finance but less likely to apply for it. Entrepreneurs that operate in the high-tech manufacturing sectors were found to be more likely to seek external finance. This is likely to be due to the manufacturing

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sector being more capital intensive than the service sector. On the other hand, in line with Hypothesis 4, it was found that although it is more likely that manufacturing firms will apply for external finance, it is less likely that they will receive it. The empirical evidence also suggests that lone, relatively younger entrepreneurs operating in manufacturing sectors face higher constraints in accessing external finance in relation to the rest of the entrepreneurs. Due to their young age and being the only founders of the firm, it is more likely that their human, social and financial capital will not be as high as that of older entrepreneurs. Not all the skills that external finance providers prefer to exist in order to invest in a firm are present in a one-man band firm. Finally, whether a firm was incubated at start-up was not found to have a significant effect on accessing external finance. Of the three theoretical positions on the factors that affect the demand and supply for external finance, the Kon and Storey (2003) theory on the existence of discouraged borrowers is not supported by the empirical evidence as it was found that highly educated entrepreneurs were more likely to apply for external finance in relation to less educated ones. While both education and experience are found to have a significant effect on the demand for external finance, none of the six specific human capital variables was found to exert a significant impact on the supply of external finance. This does not support the Cressy’s proposition (Cressy, 1996) on the existence of a skill gap and a supply constraint driven by the entrepreneur’s specific education and experience. The fact that entrepreneurs’ specific education and experience have an effect on the demand but not on the supply of external finance seems to support the theoretical propositions of Evans and Jovanovic (1989). The significance of the number of founders and the team’s entrepreneurial age in the supply equation can be read as further evidence of capital market imperfections. While older entrepreneurs might be facilitated by having already established a reputation in the industry with other companies as well as with suppliers of finance, larger teams tend to have higher levels of internal equity at start-up. This would support the proposition that providers of finance tend to invest in firms that have started with high levels of internal equity and collateral while putting less emphasis on the entrepreneurs’ human capital.

Access to Equity, Bank Debt and Governmental Support A further aim of this chapter is to investigate which entrepreneurial and firm variables are more likely to assist a firm in applying and also receiving external finance from different sources, namely external equity, bank debt or governmental support. As a result, three bivariate probit models with partial observability were performed for each financial source. The results are reported in Table 3.

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Table 3: Demand and supply of bank finance, external equity and governmental support. Variables

Bank Debt Demand

Constant  3.462* Technical 0.091 education Business education 0.017 Sector experience 0.00215 Technical 0.0177** experience Commercial 0.0135*** experience Managerial 0.000656 experience Founders  0.263 Entrepreneurial age 0.489 Industry sector 0.794*** Science park –

po0.1;

**

po0.05;

 3.816  0.039

Demand  1.813 0.044

Governmental Support

Supply

Demand

 2.57 0.0894

0.5 0.0114

Supply 1.6 0.434**

0.0534  0.219 0.334 0.0860  0.123  0.00277 0.00685  0.00987 0.00828  0.0072  0.012  0.01 0.0206  0.0153 0.00403  0.00914 0.00382 0.326* 0.935* 0.0797 0.428

0.99***

Rho(1, 2) N *

Supply

External Equity

0.0171*  0.00842  0.0185** 0.0065

0.0019

0.183  0.196  0.00647 1.0434 0.546  0.831 – 0.368  0.997*** 339

0.0173  0.199  0.258  1.153 –

0.00869  0.0122  0.512  0.799 1.949*  1.094

0.99***

***

po0.01.

Starting with the access on bank debt (bank loan and/or overdraft), it is found that firms that have a large proportion of entrepreneurs with either technical or commercial experience in their teams are more likely to apply for bank finance as do firms that operate in the manufacturing sector. On the supply side, none of the human capital variables are significant. This result is in line with that of Storey (1994); although based on a single probit model (supply side) estimates, he found that the entrepreneurial human capital had no effect on the access to bank finance and neither did the sector (manufacturing/services) that a firm operated in. It is also found that bank managers tend to provide debt finance to firms that are founded by a relatively larger number of founders and also to firms whose entrepreneurs are relatively older. These results are consistent with those presented in section ‘Access to External Finance in General’. The main reason is that bank debt is the most frequently accessed source of external finance, and it is likely that the modelling of the demand and supply of external finance is dominated by its influence. For the case of external equity (here defined as the finance received from venture capitalists, business angels and corporate ventures), it is found that firms with high levels of commercial experience in their teams are more likely to apply for external finance. No variable was found to have a significant effect on the ability of a firm to .

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attract external equity,6 suggesting that entrepreneurs’ specific education and experience are not a discriminating factor in supplying external equity. Factors other than the ones specified are likely to affect the demand and the supply of external equity. For example, Mason and Rogers (1997) and later Mason and Harrison (2002) found that business angels first look at whether there is a fit between their own personal investment criteria that include stage (e.g. start-up, growth), industry sector and location. Industry preferences in general have to do with whether a particular business angel has familiarity with the industry that a proposed firm operates in. Geographical limitations have to do with the need of business angels to be in a position to monitor and become involved in the management and development of their investee ventures and also as proximity, and involvement provides a mechanism for managing moral hazard. However, while industry sector is business angel specific, no information exists on their geographical proximity to the company. Moreover, it can also be a case that even when firms meet the criteria, they simply might have their application rejected due to idiosyncrasies of the financial provider that was approached. That could be the case of a venture capitalist not able to finance an eligible/suitable project because it has already committed its entire portfolio on other projects (Tyebjee & Bruno, 1984). For the case of both general and specific access (bank loan and external equity) to external finance, the Evans and Jovanovic (1989) proposition cannot be rejected, suggesting that capital market imperfections are a higher constraint than entrepreneurs’ characteristics in the supply of external finance. Finally, governmental support is defined as any finance received from the major sources of financial assistance available to NTBF such as SMART, DTI programmes, Loan Guarantee Scheme and EU programmes (FRAMEWORK). On the demand side, it was found that firms that have a high proportion of entrepreneurs with commercial experience are less likely to apply for governmental support. When this result is compared across the source of financing, it emerges that although firms with a high proportion of commercial experience in their entrepreneurial team are more likely to apply for bank debt or external equity, they are less likely to apply for governmental support. On the supply side, it was found that the presence of a high formal technical qualification has a significant effect on the ability of a firm to receive governmental

6. External equity is here defined as the finance received from venture capitalists, business angels and corporate ventures. It could be argued that the investment criteria of the three types of equity investors could be significantly different, but when jointly modelled such differences might not be picked up. This possibility was disregarded on the grounds that a number of studies have shown that similar criteria are used to a certain extent by all types of external equity investors (Mason & Harrison, 1994; Siegel et al., 2003; Manigart, Wright, Robbie, Desbrieres, & De Waele, 1997; Hogan & Hutson, 2005; Weber & Weber, 2005). On the other hand, a limited number of companies have reported having used any of the three sources of external finance. As a result, any further disaggregations by source of external equity would not be statistically meaningful.

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support. Technical qualification can be interpreted as an indication for the technological innovativeness of a product/service of a firm which is the main requirement of R&D awards such as the SMART, SPUR, EUREKA, etc. Only for some of them, that is, SMART and SPUR, also the qualifications and experience of the management team seem to appear as a requirement. Finally, it appears that firms operating in the manufacturing sector are more likely to receive governmental funding. This reflects the fact that manufacturing firms are more likely to comply with the requirements of governmental programmes.

Conclusions This chapter has explored the role of human capital in the likelihood of a firm applying for and receiving external finance in general and also the likelihood of applying and receiving bank debt, external equity and governmental support individually. For the case of general external finance, it was found that highly educated entrepreneurs in either a technical or business discipline were more likely to apply for external finance. Firms with high levels of either technical or commercial experience in their founding teams were also more likely to apply for external finance as were manufacturing firms. On the supply side, it was found that none of the specific human capital variables (education and experience) significantly affect the supply of external finance, while firms with larger and older entrepreneurial teams are more likely to receive external finance whereas manufacturing firms are not. Apart from disentangling supply and demand for general external finance, this chapter has also investigated the factors that affect the access of high-tech start-up firms to external equity, bank finance and governmental support. That was done by identifying whether the factors that appear to have a significant effect on the ability of a firm to access each financial source are the result of the demand or supply for each source of external finance. It was found that an entrepreneurial team with high levels of commercial or technical experience and operating in the manufacturing sector was more likely to apply for bank debt. On the other hand, those firms formed with relative older and larger in size entrepreneurial teams were more likely to receive bank debt. In firms where a high level of commercial experience was present, it was more likely that an application to external equity would be made. None of the human capital variables appeared to have a significant effect on the supply of external equity. Starting with the theoretical positions on the factors that affect the demand and supply for general external finance, results showed that neither the theory of Kon and Storey (2003) on the existence of discouraged borrowers nor that of Cressy (1996) on the existence of supply constraints based on the founders’ human capital was supported. The theoretical position by Evans and Jovanovic (1989) on the existence of supply constraints due to market imperfections rather than to human capital characteristics was supported not only in the model for the general access to external finance, but also in the more specific access to bank loans and external equity.

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Finally, it has emerged that governmental support is targeted mainly to manufacturing firms and firms whose entrepreneurs have high technical education. The latter is believed to be a proxy for product uniqueness, which is the most important criterion applied for provision of support. However, none of the specific human capital variables related to business, managerial or commercial skills were found to matter in order for support to be provided. This can be one of the reasons for the results derived by Smallbone, North, Vickers, and McCarthy (2000) on 40 SMART award winner entrepreneurs. Although these entrepreneurs reported were successful in reaching technical objectives (creating, e.g., a working prototype), they often met serious constraints when trying to commercialize the product, which can be due to the lack of managerial/commercial skills and the failure of governmental programmes to take account of this need. This suggests that the simple provision of funds from the government might not be enough to guarantee the success of these firms and the existence of support for the aforementioned skills should also be considered within such programmes. The above results can be of interest and have practical implications to both present and future entrepreneurs. They suggest that at the start-up stage, if the founder(s) of a high-technology firm (especially in the manufacturing sector) intends to market an innovative, technologically advanced product, then they stand a good chance of receiving funds from government-sponsored programmes, once they apply for it, especially at the research and development stage. Relatively young entrepreneurs and/or individuals who are interested in starting a firm by themselves and intend to apply for bank debt at the start-up stage are more likely to face higher constraints than others, unless they are able to provide some forms of collateral. If collateral is not available, then they should try to start the firm with another individual, preferably with considerable experience. Finally, as none of the specific human capital variables seemed to be important in order for external equity or bank debt to be provided, it appears that what providers of finance put more attention on is the viability of the investment proposal, and therefore entrepreneurs who approach these sources should put significant effort first in choosing suitable investors and second in presenting their case convincingly.

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Chapter 7

Financing New Ventures: Attitudes Towards Public Innovation Support Charlotte Norrman and Magnus Klofsten

Introduction In the international arena, there is an ongoing debate over the lack of newly started businesses in general and over how to obtain sustainable growth in these businesses in particular. Policy-makers in Europe have sought to ease this problem of paucity of new firm’s start-ups, which is mainly caused by a lack of financial resources for new innovative ideas as problematic (European Commission (2007–2013); Groen, Jenniskens, & van der Sijde, 2005). Consequently, during the latest decade, there has been an increase in the number of public sector financial schemes designed to promote entrepreneurship in very early-stage businesses (COM, 2005, 2006). These efforts have, however, escaped criticism. Those who promote public financing believe that with the right tools and governance this type of support is an important complement to the private sector financial market (Oakey, 2003). However, bankers and venture capitalists often state that the main issue is not the lack of available capital but the inability of entrepreneurs to convince investors of the merits of their business ideas (Mason & Harrison, 2002). There have also been arguments against the socioeconomic efficiency (Storey, 1994). The financial aspects of the entrepreneurial process have, by tradition, been focused on the efficiency of venture capital and equity-based financing, while the unit of analysis is commonly the firm (Klofsten, Jonsson, & Simo´n, 1999). This research has, in various studies, explored the supply of capital as well as those ventures and now it is deployed in obtaining such capital (cf. Nouira, 2005). Studies that have evaluated governmental policies towards entrepreneurial support cover areas such as ‘success factors’ in regional innovation systems, ‘public support measures’ and the ‘effectiveness of small and medium sized enterprises (SME)

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policies’. Most of these studies have been focused on small firms, while some also include consideration of new ventures. As an example, Cooke, Roper, and Wylie (2003) argue that any regional innovation system must take a more functional approach (i.e. by creating a regionalised network of incubators, science parks and venture capital). Rye (2002) argues that public R&D support seems to be more important for SMEs than for larger firms. According to Hart and Scott (1994), public support, although only one of the several finding sources available, seems to be particularly successful and cost-effective in increasing employment among small firms. Wren and Storey (2002), however, argue that public support has been more effective in medium-sized firms when compared to their smaller counterparts. Other studies on this topic tend to concentrate on more general policy issues and are directed towards evaluation (cf. Mosselman, Prince, & Kemp, 2004; Storey, 2000). Commonly, the needs, attitudes and motivations of the entrepreneurs are seen as highly important (Nouira, Klofsten, & Lindholm-Dahlstrand, 2005). However, studies dealing with sole inventor entrepreneurs, and their attempts to obtain access to resources when commercialising their ideas, are few (Meyer, 2003). When studying support systems it is of importance to regard both supply and demand sides of the system, and one way to do this is to use a holistic perspective. Such an approach has been used in studies of financial gaps and financial constrains (cf. Nouira, 2005). Furthermore, Lambrecht and Pirnay (2005) investigate both perspectives in their study of SME firms, but as far as we have experienced the research using this approach towards public innovation support, concerning the earliest stages of venture development, seems to be limited. This chapter is one part of a larger research project focusing on public innovation support of new ventures. Until now, we have studied the selection strategies of a public support system, where factors such as legal form and type of industry emerged as important (Norrman, Klofsten, & Sundin, 2007). Also the degree of knowledge intensity seems to be important to success in obtaining public sector innovation support (Norrman, Klofsten, & Bergek, 2005). Furthermore, we have studied the performance of the system and found that there is a difference between the limited number of firms that gained innovation support and those that were rejected. However, a limitation of our earlier empirical work is that it was based on secondary data from different sources, in which the variables were fixed, thus not allowing us to create our own variables. A second limitation was that the main focus of this secondary data has been on the supply side of the support system, on which there is already good knowledge. This imbalance implies that our knowledge of the applicant’s points of view, in case of attitudes towards public support and their needs of such support, is limited. In order to create efficient support instrument, both policy-makers and entrepreneurs need good knowledge about how any given support system works (OECD, 2004). From other studies concerning support schemes such as small business training (Gibb, 1987) and incubator support (Lindholm-Dahlstrand & Klofsten, 2002), it is shown that there often is mismatch access between supply and demand concerning the support and its content. The aim of this chapter is to investigate if there is a gap between the supply and demand sides of public innovation

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support systems. We believe in the appropriateness of using a holistic approach since it can capture the potential mismatch addressed above. Such an approach takes into account the entrepreneur, his or her attitudes and ideas, and the environment that influences the entrepreneurial process (Bygrave & Timmons, 1992; Klofsten, 1992; Roininen, 2006). Regarding the increasing faith in societal intervention to assist firm development — from both academic and practitioner viewpoints — we believe that there is a need for more research that focuses on the receivers of public innovation support in the earliest stages of new venture support.

Research Object and Method This chapter is based on a survey of idea owners who have applied for public innovation support from the Sweden Innovation Centre (SIC) Swedish support scheme that was available from 1994 to 2003. According to this scheme, it supported ‘innovators in their absolute earliest phases of development with financial capital, advice and networks’ (SIC, 2002, p. 24). The main objective of SIC scheme was ‘to create a better innovation climate in Sweden’ y ‘in which people’s attitudes to innovators become positive, and where it is easy for an innovator to receive help to develop his or her concept into a commercialised product or service’ (SIC, 2002, p. 24). The SIC system was broadly aiming at supporting the development of ideas concerning both practical consumer products and more advanced techniques for industrial and societal purposes (SIC, 2004). Financial support was intended to cover the costs of product development, IPR and marketing activities, while other costs such as salaries were not covered. The finance provided could be described as swift and of low risk for the applicants, since loans were written off if the project failed. For more information about the SIC scheme, see appendix. This research is based on questionnaires sent out to all individuals who, according to the diary system of SIC, applied for finance in case of conditional loans during its final years from 2002 to 2003. The sample hence includes both rejected and supported cases. In total, 1034 questionnaires were sent out since all obvious duplicates were removed. Of these, 215 were returned due to them being wrongly addressed. Of the remaining 819, 294 or 36% were returned, of which 277 were properly completed, a response rate of 34%. The first part of the questionnaire considered basic facts about the applicant. The second part consisted of 16 statements, where we investigated the attitudes of the applicants by giving them fixed alternatives on a seven-degree Likert scale ranging from ‘fully agree’ to ‘fully disagree’. These attitude questions addressed items such as the support per se, network provision, motivation, credibility and factors that are coupled to the project, market and finance. Since, especially during the latest years of the SIC scheme, it was not obvious to an applicant if the money came from SIC or the regional development actor ALMI, or both, this joint funding was addressed as ‘public sector support’ within the questionnaire. Finally, there were two ‘open-ended’ questions where we asked the respondent to provide three advantages of the SIC

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system and three suggestions for improvement of public support activities. The fact that this issue strongly engaged the people involved is obvious. About 72% of the returned questionnaires had comments on one or both of these ‘open-ended’ questions. It is also worth mentioning that we, during data collection, received many phone calls, e-mails and postscripts to the questionnaires with comments, experiences and observations from both innovators and entrepreneurs that were both satisfied and very upset. These answers have been analysed through quantitative analysis using SPSS 14.0. Significances have been estimated by chi square tests and linear regressions. Concerning the ‘open-ended’ questions we have counted frequencies for the most common statements, and subjected them to quantitative analysis in order to capture, reproduce and analyse the information received.

Sources of Error and Limitations The size of the sample is a source of error, and according to Rodeghier (1996) the number of cases for each category ought to exceed 50 in order to minimise statistical errors. In this survey a crucial variable is the support or rejection of an application. The number of supported application according to the respondents’ own responses is 195, and the number of rejected is 50. The number of cases is at the minimum required by Rodeghier, which is a weakness. Regarding the support rate, support in the case of innovation subsidies and support from earlier years have been included. This is because we assume that if the respondents consider their applications as supported, this will have affected their attitudes towards public support. Moreover, we cannot be sure that all respondents have been able to distinguish between different sources of finance since SIC and ALMI have been merged. Furthermore, in some regions regional funds have been used to boost the finance from SIC and ALMI (Norrman, 2006). Any impact on the results caused by these problems was explored, but this did not cause the results to differ. According to Heckman, Ichimura, and Todd (1997), there are four possible sources of systematic errors within quantitative research that can occur when estimating programme impact. These are (1) incompatible definitions of the dependent variable, (2) unequal economic circumstances for the observed groups of cases, (3) incompatible populations for the observed groups, and (4) the existence of non-observable variables which govern self-selection into the programme for one of the observed groups, making it non-compatible with the other group. As far as we can tell, the first two points are eliminated by the design of the survey and by the rules for application. The fourth point is eliminated by the fact that all the ventures surveyed are self-selected to the scheme by the fact that they have filed an application. The third point might be of some relevance, but since, as described above, the respondents have used their own estimation of support or rejection, we consider this point to be irrelevant. Non-response is another potential error when surveys are conducted (Rodeghier, 1996). To investigate this, we have compared the group that completed their questionnaires to the group of non-respondents. Analysis was made through

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cross-tabulation of the variable sent in/not sent in with a number of variables within the conditional loan diary database. According to this analysis, there was no significant difference between the two groups in terms of gender or type of industry. There was a significant difference according to firm type ( p ¼ 0.003), which resulted from this fall that sample analysed; the number of sole proprietors was larger, and the number of limited companies was lower than expected. One implication of this tendency might be that the answers reflect the attitudes of independent inventors to a larger degree than expected. Finally, there is a significant difference according to the variable support/reject ( p ¼ 0.000). The number of supported cases (according to the SIC conditional loan diary) is approximately 9 percentage points higher in our sample than in the SIC conditional loan diary in total for the investigated years. This might imply that the attitudes given are more positive than those for all firms, since it is reasonable to expect that supported respondents are more satisfied than those who were rejected.

Support in Theory and Practise In this section we discuss what results can be expected from a public support scheme that direct its support to early-stage innovative ideas, that is, the programme theory (cf. Hjalmarsson & Johansson, 2003), and how this harmonises with the needs of the ventures applying for support. The scheme studied addressed finance, advice and networks as the three main types of support. However, there were, apart from the above-cited purpose, no clearly stated detailed and measurable goals indicating exactly what the scheme was supposed to achieve. This is, from an evaluation point of view, problematic, but far from rare (Hjalmarsson & Johansson, 2003; Storey, 2000). Furthermore, although the main goal of SIC was to provide financial support for commercialisation of new venture ideas, in this study the focus was on other aspects of support (i.e. what the money has been used for and the value that the support has created for those who have obtained the support). Moreover, in addition to the intentions of SIC, from the academic literature, we have added and discussed three more factors that are shown to be of importance for early-stage ventures, namely ‘motivation or driving force’, ‘credibility or legitimacy’ and ‘investment readiness’.

Motivation What motivates the entrepreneur is a subject that has been fairly well studied over the years. One of the most cited studies is ‘The Achieving Society’ (McClelland, 1961), which argues that the entrepreneur is primarily motivated by his need for achievement. Other early sources add reasons, such as ‘the need to make money’, ‘be one’s own boss’ and ‘self-realisation’, as motives for entrepreneurship (Dahme´n, 1950; Roberts & Wainer, 1971). The issue of motivation, or the driving force, of the

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entrepreneur continues to be regarded as key success factor (Davidsson & Klofsten, 2003). It is argued that entrepreneurs are driven by intrinsic factors (i.e. ownership, control, responsibility and psychological rewards) and extrinsic factors (i.e. tangible rewards such as finance) (Choo & Wong, 2006; Naffziger, Hornsby, & Kuratko, 1994). Accordingly public support in the form of innovation finance for promising ideas might be judged an extrinsic motivation factor. By gaining support of an application, the entrepreneur receives confirmation (i.e. reward) to assist his or her continuing struggle. However, we have noted that there is little research on motivation factors in so far as their impact on public innovation support. This question is touched upon in an earlier study conducted by Klofsten et al. (1999), which indicated that public support towards early-stage enterprises, even in the case of small sums of capital, increased the motivation of entrepreneurs. The importance of this factor is further discussed in our previous research on this project (Norrman et al., 2007). To learn more about public innovation support as motivation factor, the following hypothesis was proposed: Hypothesis 1. Public innovation support directed to new ventures increases the motivation of the supported entrepreneur(s).

Credibility One of the barriers faced by early-stage ventures is the lack of credibility or legitimacy as seen by customers or financiers (Birley & Norburn, 1985; Klofsten & Lindholm-Dahlstrand, 2000; Storey & Tether, 1998; Van de Ven, 1993; Zimmerman & Zeitz, 2002). Credibility is put forward as crucial to new ventures in their attempts to gain resources (Birley & Norburn, 1985; Storey & Tether, 1998) and to overcome the ‘liability of newness’ (Zimmerman & Zeitz, 2002). In our previous research we found that credibility could be coupled to factors such as legal form, industry and knowledge intensity (Norrman, 2005). Credibility is also shown to be an important factor when networks are formed during the start-up stage of a new venture (Birley & Norburn, 1985). It is also shown that credibility can be improved by publicly funded grants (Klofsten et al., 1999; Lerner, 2002). To investigate if this trend holds also for this study, a second hypothesis was proposed: Hypothesis 2. Public innovation support directed to new ventures increases the credibility of the supported entrepreneurs and their ventures with external actors.

Network In the marketing information about the SIC support scheme, ‘networks’ were put forward as one of the three main tasks that the scheme was concerned to achieve. Also within this research, the surrounding context of the entrepreneur is regarded as

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important. Olofsson (1979) concluded that it is important that firms strive to make contact with partners and customers at an early stage in their development since this decreases uncertainty. The importance of already having good relations with customers when the firm is started was put forward by Utterback and Reitberger (1982) in the early 1980s. Van de Ven (1993, p. 214) argues that ‘new technologies are seldom if ever developed by a single firm alone in the vacuum of an institutional environment’. In a more recent study, Ramachandran and Sougata (2006) proposed the ability to establish networks as a first critical point in the new venture formation process. Since the lack of start-up capital is often a major problem for the new entrepreneur, the networking can be used to acquire funding (Ramachandran & Sougata, 2006; Winborg, 2003). Furthermore, the new venture has to find advisors, and recruit board members and employees. Hence, being able to establish contacts with surrounding actors is of importance to the entrepreneur (Birley, 1985). Public support systems, especially those that express networking as one of their main tasks, ought to strive to promote the networking process, by taking the role of mediator between the supported ventures and other crucial actors (Rye, 2002). The issue of enlargement of the networks of supported firms is therefore put up as our third hypothesis: Hypothesis 3. Public innovation support, directed at new ventures, enlarges the network of the supported entrepreneurs.

Business Development It is argued that the ‘demand side’ contributes to the equity gap in early-stage growth businesses (Mason & Harrison, 2001). Mason and Harrison (2002) argue that one important barrier to investment by venture capitalists is the lack of proper business opportunities for investment, and difficulties in negotiating with the entrepreneurs. They therefore suggest that entrepreneurs should be educated in understanding the advantages of taking on external equity-based capital by striving to be ‘investment ready’ before they turn to the investors. Such an approach is concerned with business development and incorporates (1) the entrepreneurs’ attitudes to equity-based finance, (2) the way of presenting their offer, in both written and oral forms, and (3) the match between the investor and the venture invested in (Mason & Harrison, 2001). Following the arguments of Mason and Harrison, it is important to improve the attitudes of early-stage entrepreneurs. This is also suggested by North, Smallbone, and Vickers (2001) who state that ‘one of the tasks of innovation support should be to encourage attitudinal change on the part of owner-managers with respect to external finance’ (p. 309). Although far from all applications for money from the SIC scheme can be expected to aspire to obtain equity-based venture capital, it is likely to assume that all of them are in the need of some kind of additional finance. In addition to SIC funding, many other sources of external finance had been applied for. The SIC support process was designed in steps, starting with innovation subsidies and

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continued through loans. We do not know if all applicants for loans also applied for subsidies, but we do know from our research on the conditional loan database that the average number of applications per person was 1.4, which entails that more than one application per venture has been common (Norrman, 2005). Since repetition is crucial to learning this SIC type of innovation, funding can be regarded as part of a training process aimed at attaining investment readiness. In Norrman (2005), it is questioned whether the SIC system really helped develop the supported firms by making them more ready for investments. This question is therefore posed into our last hypothesis: Hypothesis 4. Public innovation support, directed to new ventures, has in general a positive effect on the business development of the supported entrepreneurs and their ventures. Finally, we address the question of whether the applying ventures really obtained what they demanded when they applied for public innovation support. Previous research shows that mismatches between demand and supply are common (Gibb, 1987; Lindholm-Dahlstrand & Klofsten, 2002). We are interested in whether this also holds in the case of SIC. These issues will be investigated through the above hypotheses and through a qualitative analysis of ‘open-ended’ questions, where the questioned applicants have had an opportunity to record what they regard as the major advantages or drawbacks of the SIC system.

Data and Results In this section we present and discuss our results in the light of the theory and their context in terms of our hypotheses.

On Motivation (H1) Since the difference between supported and rejected ventures is significant, and since the mean is positive, we regard this hypothesis as corroborated (see Table 1). The open-ended questions produced comments such as ‘the money gives an optimistic conviction to the project’, ‘the money gives motivation’ and ‘the size of the sum is not essential, but to gain verification and trust in our ability to commercialize the product gives mental stimulation’. When the variable ‘motivation’ was run during linear regression against capital using functions, namely ‘marketing measures’, ‘product development’ and ‘IPR activities’, a positive correlation between motivation and support for product development and IPR activities was shown (see appendix; Tables 2 and 3). Even though the business platform theory shows that the driving force of an entrepreneur is the factor that is often at a high level already from the outset, there is, as far as we have experienced, no literature that argues the case that measures

Mean 0.89 1.25  0.8  0.67  0.42  1.90  0.28 0.02  1.72

 0.79  0.55  1.92

 0.3  0.03  1.57  0.25 0.03  1.46

Variable

H1: Motivation Supported Rejected

H2: Credibility Supported Rejected

(a) To financiers Supported Rejected

(b) To customers Supported Rejected

H3: Networking Supported Rejected

H4: Business development Supported Rejected

0.000

0.001

0.000

0.000

0.000

0.000

Significance

Interpretation

The ability of increasing the business development of the supported venture is rather low

Network provision by the scheme studied is rather low even among supported ventures

Rejected applicants did, in a larger degree than expected, fully disagree with the proposition that public innovation support had increased their credibility with customers. The supported firms were less clear cut and ranged from partly disagree to fully agree in larger degree than expected

Rejected applicants did, in a larger degree than expected, fully disagree with the proposition that public innovation support had increased their credibility with financiers, and enhanced the possibilities of getting finance from other sources. The supported firms were less clear cut and ranged from neutral to fully agree in larger extent than expected

The ability of increasing the credibility of the supported venture is rather low concerning credibility towards financiers as well as towards customers

Public support from the scheme studied seems to be of some importance, as factor motivation for those that were supported

Table 1: Results from attitude questions that were coupled to our hypothesis.

Financing New Ventures: Attitudes Towards Public Innovation Support 97

Mean  0.15 0.09  1.09 0.18 0.43  0.83

1.21 1.61  0.53

 0.15 0.18  1.63

 0.03 0.24  1.27

Variable

(a) Attitudes towards external finance Supported Rejected

(b) Ability to present the offer Supported Rejected

(c) Development of the project idea Supported Rejected

(d) Knowledge of market Supported Rejected

(e) Knowledge of sources of finance Supported Rejected

Table 1: (Continued )

0.000

0.000

0.000

0.000

0.000

Significance

Rejected applicants did, to a larger degree than expected, fully disagree with the proposition that public innovation support had increased their knowledge about sources of finance. The supported firms were less clear cut and ranged from partly disagree to fully agree to a larger degree than expected

Rejected applicants did, to a larger degree than expected, fully disagree with the proposition that public innovation support had increased their knowledge of their market. The supported firms were less clear cut and ranged from partly disagree to fully agree to a larger extent than expected

Rejected applicants did, to a larger degree than expected, fully disagree while the supported firms did agree to a larger extent than expected to the proposition that public innovation support had helped them to develop and clarify their idea

Supported applicants were more positive, while those rejected were more negative than expected to the proposition that the process to apply for finance from the public support scheme had helped them to improve the presentation of their offer

Rejected applicants did, in a larger degree than expected, fully disagree with the proposition that contacts with the public support scheme have made them more likely to take on external finance

Interpretation

98 Charlotte Norrman and Magnus Klofsten

a

2.28

2.26

2.04

(II) Soft loan conditions

(III) Support irrespective of firm type

(IV) Finance in combination with qualified advice

The mean ranges from 3 (fully agree) to –3 (fully disagree); 0, neutral.

0.000

1.35a 1.61 0.14

(I) The support was crucial Supported Rejected

–

–

–

0.001

 0.33  0.09  1.42

(f) Knowledge of how to run the project Supported Rejected

The majority of the applicants agreed or fully agreed to the proposition that finance should be given in combination with qualified advice, while no difference was found with support or rejection

The majority of the applicants agreed or fully agreed to the proposition that soft loans should be granted irrespective of the legal form of the firm; no difference was found due to support or rejection

The majority of the applicants agreed or fully agreed to the proposition that soft loan conditions are highly important, while no difference was found due to support or rejection

Supported applicants ranged from not agree to fully agree, while the rejected firms to a larger degree than expected had ticked the alternative ‘not at all agree’ to the proposition that the support was crucial for the project

Rejected applicants did, to a larger degree than expected, fully disagree with the proposition that public innovation support had increased their knowledge about how to run the project. The supported firms were less clear cut and ranged from not agree to fully agree to a larger degree than expected

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Table 2: Sample characteristics. Gender Industry Product/service Education Firm liability, application Firm liability now Commercialisation Localities Visions Development, employees Development, turnover

Females, 27; males, 250 ICT, 46; machinery, 27; vehicles and related technologies, 22 66 products, 191 products and services, 10 solely on services No university, 109; undergraduate university, 132; postgraduated, 34 Limited company, 117; sole proprietorship, 114 Limited company, 124; sole proprietorship, 55 Commercialised in some way, 135 Business localities, 102; science park/incubator, 29; owner’s residence, 125; more than one locality, 14 Will not run a firm, 24; 1 employee, 94; up to 10 employees, 48; 11–50 employees, 16; W50, 16 Increased number, 47; unchanged, 134; decreased, 37 Increased, 90; unchanged, 93; decreased, 43

Table 3: Detected correlations between attitudes and using areas. Dependent Variablea

Significance

Direction

H1: Motivation

IPR ( p ¼ 0.005) PD ( p ¼ 0.042)

Positive Positive

H2: Credibility

IPR ( p ¼ 0.005) PD ( p ¼ 0.036) IPR (p ¼ 0.016) PD (p ¼ 0.016) IPR (p ¼ 0.008)

Positive Positive Positive Positive Positive

(a) Attitudes external finance (b) Ability to present the offer (c) Development of the project idea (e) Knowledge of sources of finance (f) Knowledge of how to run the project

IPR ( p ¼ 0.009) PD ( p ¼ 0.031) PD (p ¼ 0.048) PD (p ¼ 0.049) PD (p ¼ 0.008) IPR (p ¼ 0.036) IPR (p ¼ 0.000)

Positive Positive Positive Positive Positive Positive Positive

The support was crucial

IPR ( p ¼ 0.016)

Positive

(a) To customers (b) To financiers H4: Business development

a

Linear regression, coefficient matrix with attitude questions as dependent variables.

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designed to strengthen an entrepreneur’s motivation might be damaging (Klofsten, 1992). External finance is, according to Choo and Wong (2006), an example of an extrinsic type of reward, which according to them has a prominent role in buttressing entrepreneurial intentions. Our results also support the findings of Klofsten et al. (1999), which show that small sums of capital directed at new ventures encourage entrepreneurs to continue their work.

On Credibility (H2) Also in this case of public innovation support increasing the credibility of entrepreneurs, the difference between supported and rejected ventures was significant (Table 1). Although the supported ventures were less negative than those rejected, the mean of the supported firms remains a weak corroborate of the hypothesis. We therefore consider the second hypothesis to be rejected. However, it appears that the variable was positively correlated using functions. Both IPR activities and product development came out as significant against credibility to financiers, and for credibility to customers IPR activities came out as significant (Table 3; appendix). Credibility is sparsely mentioned within the open-ended questions, and when mentioned, it is in connection to finance. Klofsten et al. (1999) were able to show that small sums of publicly funded grants increased the credibility of the recipient towards other financiers. However, these findings were not supported by this study. The mean among the supported firms was close to zero, which implies that no effect is estimated. We have also measured if public innovation support has increased the credibility of recipients with customers, but here the mean was also negative for the supported firms. A possible explanation of this result is that much of the support was given to ventures in the very early stages of their development. Furthermore, the average support rate for the SIC scheme was 57% (Norrman et al., 2007), which is a rather high figure compared to venture capital, where the support rate usually is a couple of per cents (Fredriksen, 1997). It is therefore likely to be assumed that potential investors do not consider the selection made by SIC as a guarantee of a good investment. There might be a possibility that ventures that, through the finance obtained from SIC, have been able to obtain a patent have increased their possibilities of getting additional capital. The correlation between credibility and support on IPR activities was significant, and maybe an indication of this. However, we have not been able to investigate if money for IPR activities, in fact, has resulted in granted patents. It is argued that credibility is an important factor for the enhancement of the networking process (i.e. the function of opening doors) (Ali & Birley, 1998). Ali and Birley argue that ‘association’ is a way to acquire credibility. This can be illustrated by the following example. If a new entrepreneur is recommended by his or her business advisor to contact a person in the advisors’ network, with the request to give this new contact the advisors’ regards, the chance for the new entrepreneur to acquire

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help is increased. This is partly because the new contact, if the entrepreneur is refused, risks his or her relationship with both the new entrepreneur and, more importantly, his or her advisor friend.

On Improved Networks (H3) Results show that this hypothesis also must be rejected (Table 1). According to respondents, the SIC scheme cannot be said to have enlarged the networks of the supported firms. From the responses to the ‘open-ended’ questions, we can conclude that in a few cases the SIC scheme was acknowledged to have ‘opened doors’ and to have ‘supplied contacts’. However, the number of suggestions for improvement is more than three times as large, which indicates that the desire for networking has been larger than its supply (Table 4; appendix). About 20 years ago, Birley (1985) argued that networks are initially crucial for the development of a new venture. She showed that entrepreneurs commonly were unaware of what resources are available in the region, and argued that increasing the entrepreneur’s awareness of the availability of formal resources was important. According to the results of this investigation, there is plenty of room for improvement in this area. However, we Table 4: Results from the open-ended questions. Advantages of the SIC Scheme

Frequency

Matter for Improvements

Frequency

SIC gave good advice

44

37

SIC had a good way of handling the applications/ meeting the applicants

60

SIC were complicated and not swift Information asymmetry between the applicant and SIC (our interpretation) More advice is demanded Better quality of the advice is demanded Lack of long-term commitment More money is demanded More support like the SIC scheme is demanded More network is demanded

SIC forced you to think SIC were a prerequisite to start-up SIC had good conditions SIC were directed to early stages SIC trusted the applicant

SIC gave network

8 71 49 5 13

6

31

38 40 28 43 25

20

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must admit, not least from our own experience, that establishing networks is hard work, which requires both resources and devotion.

On Business Development Enhancement (H4) If all variables of business development enhancement measure are taken together, the hypothesis must be rejected, since the mean rate for the supported firms is close to zero, which means that no effect was estimated (Table 1). Also this variable was investigated concerning functional use of capital, and the result shows that product development and IPR activities were more positively associated (Table 3; appendix). When analysis dealt individually with these measures, all except ‘development of the product idea’ were close to zero or negative. This shows that although the SIC scheme, according to its uses, has not been recognised as having an overall impact, it has contributed to the development of project ideas. This impact may be caused by the way in which the scheme has allocated financing. The largest part of the funding was spent on product development and protection (IPR activities), while only a minor part was allocated to marketing activities. All money was paid out against factual costs of purchased services. Qualified advice and activities undertaken in these areas can thereby be assumed to have improved and developed the products. However, there is no necessary causal link between a brilliant product and success in the marketplace (Heydebreck, Klofsten, & Maier, 2000).

On the Issue of Mismatch Accessing new markets with new products takes time, and the process is associated with high risks. Thus, marketing may require a long-term commitment from financiers (Lindstro¨m & Olofsson, 2001; Oakey, 2003). A lack of long-term commitment is a rather common remark in the answers of the ‘open-ended’ questions. A probable explanation to this, as mentioned above, is that most of the SIC money was dedicated to development and protection of the product. The applicants were then left on their own with the great challenge of taking their product to the market. Potential knowledge of marketing techniques is a significant weakness in technology-based firms (cf. Westhead & Storey, 1997). A lack of marketing capability is another commonly referred characteristic (Mason & Harrison, 2001; Oakey, 2003; Westhead & Storey, 1997). We cannot know what kind of advice was supplied to assisted firms, or if it was directed to issues related to marketing or product development and/or product protection. However, to the open-ended question that addressed suggestions for improvement, one reply noted: ‘To reach the market includes at least three types of professions; innovators, constructors and marketing managers — how many master all of these?’ y ‘Marketing support is needed y the marketing part is the most complicated’. y ‘Marketing support — financial support is good, but not enough

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when a new product is launched’ y ‘Lots of projects are wound up due to a lack of entrepreneurial knowledge — entrepreneurship education is needed’. Hence, we can conclude that there is some evidence of a demand for more advice concerning marketing issues. However, not all external advice is of indisputable good quality (Hjalmarsson & Johansson, 2003; Lambrecht & Pirnay, 2005). Lambrecht and Pirnay (2005) point out a number of shortcomings concerning external advice (e.g. that the consultants suffer from capability constraints; that they serve their own interests; and that they give generic advice instead of tailored and put the venture into a dependency relationship). Some of these shortcomings have been observed in this investigation. The attitude questions show that a majority agree or fully agree to our proposition that financial support ought to be combined with qualified advice. In the final ‘openended’ questions, 44 of the respondents noted that the advice from SIC was good (Table 4; appendix). However, there were also requests for more advice and for advice of better quality. A large part of respondents who put down ‘good advice’ as an advantage asked for both more advice and increased quality of the advice. Furthermore, in section ‘Introduction’ we argued that a holistic approach is of importance and the demand for such wider approach can be found in the suggestions for improvement from the open-ended questions of our questionnaire: ‘Commonly it feels like public innovation support is aiming to be politically correct rather than focused on the market’ y ‘I think that those that judged the projects would have benefited from closer contact with the applicants when judging the market potential of the product’. It cannot be denied that some of the negative comments are due to other reasons such as personal chemistry or information asymmetry. Information asymmetry is in fact indicated within a number of answers to the ‘open-ended’ questions (e.g. comments such as ‘Commonly the founder knows more than the financier’, y ‘Unfortunately you neither understood the technique nor the market of our product’ y ‘They turned us down since we didn’t give them our classified construction drawings’). In the literature the concept is explained as an obstacle that emerges when two parties, in this case the inventor/entrepreneur and the support scheme management, have obtained separate knowledge of each other’s status and potential (Shane & Cable, 2002). This is a commonly referred problem (Berggren, Olofsson, & Silver, 2000; Carpenter & Petersen, 2002; Harding, 2002; Lerner, 2002; Shane & Cable, 2002). There are many explanations given for the occurrence of information asymmetry. For example, entrepreneurs might be reluctant to display too many details since they fear that surrendering such information might benefit competitors (Berggren et al., 2000). A probable explanation for such confidentiality might be that either they had occasions when they had revealed too much information in the past or they had taken the advice of patent consultants regarding confidentiality too seriously. However, this problem is not one-sided, since the applicant for funding can, from the investor’s point of view, be regarded as overoptimistic since the full potential of a product under development is not made clear to the investor (Shane & Cable, 2002). Furthermore, it is often argued that innovators or entrepreneurs resist external ownership and carefully preserve their independence (Berggren et al., 2000; Cressy & Olofsson, 1997; Harding, 2002; Lindstro¨m & Olofsson, 2001; North et al., 2001).

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Another observation is that supported ventures agreed to a large degree that the support was crucial to the realisation of the project. Within the open-ended questions, such remarks were made by 71 respondents (Table 4; appendix). Furthermore, most of the respondents fully agreed with the proposition that it is of high importance that public innovation support is given to early-stage ideas. Taken together, our results expose a number of problems within the support scheme studied. Since the aim of the scheme was to provide finance, advice, networks and the commercialisation ideas, one would have expected to find a positive impact on supported firms, at least concerning their ability to create networks, since such activities are rather inexpensive to conduct, compared to other activities. Although the scheme strived to create a better innovation climate for helping innovators to commercialise their products, the analysis shows that the main focus was put on product development and the intellectual property protection of products. It is also in these areas that the competence of the scheme seems to have been strongest. In order to support an application, the scheme made three important stipulations: first, the idea was to be new; second, it was to be technology or intellectually advanced; and third, it had to be commercialisable (SIC). From interviews with the SIC officials (Norrman et al., 2007), we know that the third condition ‘commercialisable’ was only put into practice during the later years of the scheme. However, it seems that more could have been done. Our findings show that there was a gap between the support given and the support demanded, which supports the findings of other studies (Hjalmarsson & Johansson, 2003). This gap is exemplified through issues concerning marketing. New ventures are often oriented towards product development, but for them to sustain, their products have to gain the acceptance of customers (Klofsten, 1992). It is therefore crucial that a large enough market is defined at an early stage. This, to us, implies that product development has to be market driven. If the market is neglected, and the venture focuses solely on this development of its new technique, there is a risk that money and time are invested in vain. It is indisputable that several ventures that received support managed to commercialise their products (SIC, 2004). However, it has been shown that the costs per job generated were rather high (Norrman and Bager-Sjo¨gren, 2010 in press).

Conclusions The aim of this chapter has been to investigate if there is a gap between the supply of and demand for public financial support for innovation. This has involved surveying the attitudes of innovators and entrepreneurs that have applied for public innovation support. The results of this survey have been compared to the aims of the support scheme and the findings of other academic studies, regarding public support schemes. From this study the following two major conclusions can be drawn:  Public financial support increases the motivation of new venture entrepreneurs, a finding that is also supported by other empirical studies such as Klofsten et al. (1999) and Choo and Wong (2006).

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 Public financial support has a positive effect on new venture idea/product development. This is in line with the work of Rye (2002), which argues that public support is important to the success of small firm development projects. The major implications of this study are that first there is a demand for public innovation support for early-stage ideas per se and that the support given was regarded as essential for the implementation of the supported projects. Furthermore, it has been shown that the support given does not fully meet the demands of the applicants. The system has been focused on products and their development and protection, which implies that ventures experience severe problems when attempting to bridge the gap between product and market. This gap implies that there is room for more research in this area, using different methodological approaches focused on different support measures directed at various stages of new firm development in order to develop best practise on how this gap can be bridged. We argue that, in order to be able to succeed in supporting new ventures, it is crucial to have a holistic approach that considers both the development and protection of the product and its market. One way to adopt this holistic approach is to consider suggestions for improvements that are provided by the participants of this survey. According to these comments, marketing support should be the main target of public innovation support. Furthermore, since we know that accessing new markets with new products involves high risk and cost (Lindstro¨m & Olofsson, 2001; Oakey, 2003), in line with Oakey (2003), we therefore argue that the long-term commitment of financiers is important. Klofsten et al. (1999) argue that also small sums of finance are crucial for new ventures, ironically, it seems, from the single inventor/entrepreneur point of view, that the most prioritised issue is the issue of getting the idea financed at all and the design of the optimal support system therefore, from their point of view, is of secondary priority. This supports the arguments of North et al. (2001) that public innovation support should focus on the basic needs of the users.

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Lambrecht, J., & Pirnay, F. (2005). An evaluation of public support measures for private external consultancies to SMEs in the Walloon Region of Belgium. Entrepreneurship & Regional Development, 17(2), 89–108. Lerner, J. (2002). When bureaucrats meet entrepreneurs: The design of effective public venture capital programmes. Economic Journal, 112(477), F73. Lindholm-Dahlstrand, A˚., & Klofsten, M. (2002). Growth and innovation support in Swedish science parks and incubators. Oxford: Elsevier Science. Lindstro¨m, G., & Olofsson, C. (2001). Early stage financing of NTBFs: An analysis of contributions from support actors. Venture Capital: An International Journal of Entrepreneurial Finance, 3, 151–168. Mason, C. M., & Harrison, R. T. (2001). ‘Investment readiness’: A critique of government proposals to increase the demand for venture capital. Regional Studies, 35, 663–668. Mason, C. M., & Harrison, R. T. (2002). Barriers to investment in the informal venture capital sector. Entrepreneurship & regional development, 14, 271–287. McClelland, E. (1961). The achieving society. New York: D. Van Nostrand Company Inc. Meyer, M. (2003). Academic entrepreneurs or entrepreneurial academics? Research-based ventures and public support mechanisms. R&D Management, 33(2), 107–115. Mosselman, M., Prince, Y., & Kemp, R. (2004). Review of the methodologies to measure effectiveness of state aid to SMEs. Final Report to the European Commission. Naffziger, D. W., Hornsby, J. S., & Kuratko, D. F. (1994). A proposed research model of entrepreneurial motivation. Entrepreneurship Theory & Practice, 18(3), 29–42. Norrman, C. (2005). Publicly financed support of technology-based ventures Linko¨ping studies in science and technology. Licentiate thesis, no. 1219, LiU-Tek-Lic, Linko¨ping University, Linko¨ping, Sweden. Norrman, C. (2006). Innovationsbidrag och Villkorsla˚n: Statistiska data om SICs innovationsbidrag och villkorsla˚n mellan a˚ren 1994 och 2003. IMIE Working Paper Series. Issue 78. Linko¨ping University, Department of Management and Engineering, Linko¨ping, Sweden. Norrman, C., & Bager-Sjo¨gren, L. (in press). Entrepreneurship policy to support new innovative ventures: Is it effective? International Small Business Journal. Norrman, C., Klofsten, M., & Bergek, A. (2005). Public innovation support and innovative ideas. Babson Kauffman Entrepreneurship Research Conference, June, Babson College, Boston, MA. Norrman, C., Klofsten, M., & Sundin, E. (2007). Which new venture ideas get public sector innovation support? A study of early stage financing from a supply side perspective. In: New technology-based firms in the new millennium V. Oxford: Elsevier. North, D., Smallbone, D., & Vickers, I. (2001). Public sector support for innovating SMEs. Small Business Economics, 16, 303–317. Nouira, S. (2005). Early-stage finance — Exploring the financial context of small and young knowledge-intensive firms. Department of Management and Economics, LiU-TEK-LIC2005:74, Linko¨ping University, Linko¨ping, Sweden. Nouira, S., Klofsten, M., & Lindholm-Dahlstrand, A˚. (2005). The logic of the entrepreneur: Implications of the entrepreneur’s perception of early-stage financing. International Journal of Entrepreneurship & Innovation, 6(2), 85–89. Oakey, R. P. (2003). Funding innovation and growth in UK new technology-based firms: Some observations on contributions from the public and private sectors. Venture Capital: An International Journal of Entrepreneurial Finance, 5, 161–179. OECD. (2004). Evaluation of SME policies and programmes. 2nd OECD Conference of Ministers Responsible for Small and Medium-sized Enterprises (SMEs), OECD, Istanbul, Turkey, June 3–5, 2004.

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Olofsson, C. (1979). Fo¨retagets exploatering av sina marknadsrelationer. En studie av produktutveckling. Forskningsrapport, Nr 91. Linko¨pings Universitet, Ekonomiska Institutionen, Linko¨ping, Sweden. Ramachandran, K., & Sougata, R. (2006). Networking and new venture resource strategies: A study of information technology start-ups. The Journal of Entrepreneurship, 15(2), 145–168. Roberts, E. B., & Wainer, H. A. (1971). Some characteristics of technical entrepreneurs. IEEE Transactions on Engineering Management, EM-18(3), 100–109. Rodeghier, M. (1996). Surveys with confidence. Chicago: SPSS Inc. Roininen, S. (2006). The start-up process of academic spin-offs and non-academic ventures. Lulea˚: Department of Business Administration and Social Sciences, Entrepreneurship, Lulea˚ University. Rye, M. (2002). Evaluating the impact of public support on commercial research and development projects. Evaluation, 8(2), 227–248. Shane, S., & Cable, D. (2002). Network ties, reputation, and the financing of new ventures. Management Science, 48, 364. SIC. (2002). Stiftelsen Innovationscentrum 2002 (Sweden Innovation Centre 2002). Stiftelsen Innovationscentrum, Stockholm. SIC. (2004). 10 a˚r med Stiftelsen Innovationscentrum (10 years with Sweden Innovation Centre). Stiftelsen Innovationscentrum, 1–15, Stockholm. SIC Na¨ring a˚t Goda ide´er-Anso¨kan om villkorsla˚n. Stiftelsen Innovationscentrum (Sweden Innovation Centre) information brochure/application form, Stockholm. Storey, D. (2000). Six steps to heaven: Evaluating the impact of public policies to support small business in developed economies. In: D. Sexton & H. Landstrom (Eds). The Blackwell handbook of entrepreneurship. Oxford: Blackwell Publishing. Storey, D. J. (1994). Understanding the small business sector. London: Routledge. Storey, D. J., & Tether, B. S. (1998). New technology-based firms in the European Union: An introduction. Research Policy, 26(9), 933–946. Utterback, J. M., & Reitberger, G. (1982). Technology and industrial innovation in Sweden — A study of new technology-based firms. Cambridge, MA: MIT-CPA (CPA/82-061A). Van de Ven, A. H. (1993). The development of an infrastructure for entrepreneurship. Journal of Business Venturing, 8, 211–230. Westhead, P., & Storey, D. J. (1997). Financial constraints on the growth of high technology small firms in the United Kingdom. Applied Financial Economics, 7, 197–201. Winborg, J. (2003). Pengar a¨r inte alltid lo¨sningen (Money is not always the solution). Sma˚fo¨retaget och kapitalet, Svensk forskning kring sma˚ fo¨retags finansiering, SNS Fo¨rlag Kristianstad, pp. 29–44. Wren, C., & Storey, D. J. (2002). Evaluating the effect of soft business support upon small firm performance. Oxford Economic Papers, 54, 334–365. Zimmerman, M. A., & Zeitz, G. J. F. (2002). Beyond survival: Achieving new venture growth by building legitimacy. Academy of Management Review, 27(3), 414–431.

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Appendix. About SIC At its inception, the SIC established funds of Mh56.7, which was received from the public foundations of employees to help support new innovative projects (Prop. 1993/94:206). In total, SIC allocated Mh122 during the programme period, since its original fund was expanded through returns from capital investments. SIC administrated three types of financial support for new firms and private individuals:  Innovation subsidy — a financial grant of approximately h4000  Conditional loan — a ‘soft’ type of loan (maximum h43,000)  Scholarship — used for special issues To get the application for a conditional loan supported, the project or idea had to fulfil the following three conditions: (1) it had to be new and firms were not allowed to be older than three years to qualify, (2) it had to be able to be commercialised and (3) it had to be technically or intellectually advanced (SIC, 2002, 2004; and interviews). Approximately two thirds of the funding was during the years set aside for measures related to development and the protection of products, with the rest focusing on supporting commercialisation, marketing measures and other activities such as help with negotiation (SIC, 2004). The overall support rate for all projects, irrespective of firm type, was approximately 57% (Norrman, 2006). Today the SIC system is inherited by another governmentally financed support actor — the ALMI. Taken together, SIC allocated about Mh3.3 on conditional loans to the ventures in our sample. Of these, Mh2.35 (68%) were put on product development (125 cases), kh385 (11%) on IPR (93 cases), kh435 (13%) on commercialisation (76 cases) and kh274 (8%, 63 cases) on other measures (whereof a large part in fact was dedicated to initial type search (ITS) screening procedures, which belongs to the IPR category). On average: supported ventures have gained support on 2.2 out of the above 4 areas.

Chapter 8

Small Firm Expectations from Acquisition in the ICT Industry: A Conceptual Framework for Stakeholder Analysis Caren Weinberg, Tim Minshall and Elizabeth Garnsey

Introduction The buyers’ perspective of mergers and acquisitions (M&A) has been heavily researched, yet it has produced surprisingly few prescriptive findings. Given the limited amount of prior research from the sellers’ perspective, inductive methods appear to be the most appropriate to research this phenomenon (Eisenhardt, 1989; Yin, 2003; Miles & Huberman, 1994). Using the model outlined by Carlile and Christensen (2005), the overall goal of the project reported here is to build a theoretical framework based on empirical observations. This will eventually facilitate the examination of this phenomenon and enhance knowledge as well as theory building for further research. As a first step towards new theory building, this chapter proposes a conceptual framework which focuses on the M&A process for high-technology small firms (HTSFs). It begins with a review of current M&A literature and identifies some of the weaknesses in current research. Suggestions as to how to deal with this gap are explored. The relevant dimensions and variables for building a framework are outlined in section ‘Conceptual Framework for Theory Building’, which is then applied in a case profile of a young Cambridge (UK) firm from the Information and Communications Technology (ICT) sector in section ‘Case Study — Applying the Framework’. The chapter concludes with a brief synopsis of this initial case study analysis, outlining how the framework can be applied to the larger context of theory building.

New Technology Based Firms in the New Millennium, Volume VIII Edited by R. Oakey, A. Groen, G. Cook and P. van der Sijde r 2010 Emerald Group Publishing Limited. All rights reserved.

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In summary, by researching the acquisition process concentrating on the small firm, and more specifically, sellers’ expectations, we may gain useful insight into how and why various stakeholders in HTSFs approach acquisition. Thus, an analysis of the alignment of these expectations may well afford new perspectives, not yet identified by those concentrating on large firms and/or the post-acquisition process alone. A conceptual framework has been proposed to aid in the formulation of hypotheses.

The Significance of High-Technology Small Firms Government agencies and prominent researchers have identified HTSFs as major contributors to the economic success of the nation (DTI, 1998, 2001; Storey, 1994). Similar sources have also noted that in the United Kingdom, firms tend to remain small and few have grown to global proportions (DTI, 2002; Harding, 2003). Since one of the primary growth paths of HTSFs is through acquisition, examining how acquisitions take place and what makes them successful should help explain why many HTSFs have not grown as much as they could.1

Mergers and Acquisitions — Are they Important? For owners of new firms, acquisition is a primary means of securing returns from an enterprise. More generally, M&A have been studied for over 30 years as they were considered a key technology driver even before 1856, when the local telegraph exchanges in the United States merged to form Western Union. Government influences, deregulation, globalisation and the desire for economies of scale as well as the introduction of new technologies have fuelled the M&A phenomenon worldwide (Andrade, Mitchell, & Stafford, 2001). Competition and the need for innovation were noted by Baumol (2004) as the rationale behind firms pursuing acquisition strategies. He refers to revolutionary breakthroughs coming predominantly from small entrepreneurial firms and sees acquisition as a way for large firms to ‘internalize the externalities’. Waves of acquisition have been tracked as far back as the 18th century (Buckley & Ghauri, 2003). Some refer to M&A activity as ‘episodic’, following the wave patterns that tend to cluster around particular industries (Andrade et al., 2001). Cartwright and Price (2003) identified the most recent wave of M&A activity worldwide as starting in 1997 with 37,000 global transactions valued at close to US$3.5 trillion prior to the demise of the technology bubble which peaked in 2000 (Thomson Financial, 2006). M&A volumes continued to decline until 2003 when the trend was

1. Acquisition does not necessarily mean end of growth; it can be perceived as growth through the acquiring company.

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Figure 1: UK M&A activity 1997–2005. reversed, and have been on the rise since. Deloitte & Touche projected 30% year-onyear growth of M&A activity in 2006 (D&TCF, 2006). Patterns in the United Kingdom closely mirror those found globally. As shown in Figure 1, both deal values and deal volumes hit a low point in 2003 but have been increasing (KPMG, 2005). ‘2005 proved a bumper year for UK M&A with the market growing by about a third of 2004 in deal value terms. [y] the UK remaining one of the most attractive markets for foreign buyers and with UK corporates leading the way in scouring worldwide growth opportunities’, according to David Brooks, head of M&A at Grant Thornton Corporate Finance (Grant Thornton, 2006, p. 6). Because of their vast number, the mergers and acquisitions will affect a growing number of firms, people and economies. Cartwright and Price (2003) found that in the past 5 years over half of the US and EU senior managers had been involved in a merger or acquisition. Based on these volumes, the merger and acquisition process should be well understood. This does not appear to be the case, and researchers in the area of M&A such as King, Dalton, Daily, and Covin (2004) have called for additional theory development and changes to M&A research methods. They believe that the methods used to date have not been conclusive or produced useful prescriptive outcomes.

Small Firms — The Sellers’ Perspective Most studies of M&A have approached M&A research from the perspective of the buyer, as opposed to the seller or target. They have examined corporate finance,

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capital markets, strategy, organisational theory, corporate culture and human resource management. However, they tend to underestimate or even ignore the seller’s perspective. This is true with regard to both how firms cope with acquisition scenarios and how they review their outcomes. There has been a distinct lack of research from the perspective of the seller. We identified only two works concentrating specifically on the point of view of the seller, those of Melissa Graebner and Kathleen Eisenhardt (Graebner & Eisenhardt, 2004; Graebner, 2004). The former looks at acquired leaders (managers of acquired firms) and how they create value in the integration of technology firms, and the latter is an extensive examination through case studies of sellers’ choices in entrepreneurial acquisitions. Graebner and Eisenhardt link the occurrence of acquisitions with expansion hurdles and personal motivations to pursue acquisition. They analyse the effects of ‘high combination potential’ and ‘organisational rapport’ in 12 cases. They have determined that more potential is generated when buyers and sellers have common goals and make acquisition decisions consistent with joint long-term value creation. Congruent with the conclusions of those researching from the buyers’ perspective, Graebner and Eisenhardt observe that the sellers’ perspective is ‘complex, varied and significant’ and suggest avenues for more balanced and accurate research of acquisition. In addition, they assert that the buyers’ perspective alone is insufficient to provide explanations for many aspects of M&A, and are hopeful that further investigation of the sellers’ perspective could lead to new models and theories.

Success and Failure There are varying definitions of failure, and no single standpoint is recognised in connection with acquisitions (Bruner, 2001). Regardless of the perspective, researchers have agreed that there are difficulties surrounding concrete and valid findings with regard to M&A and neither outcomes nor profitability can be certain (Lubatkin, 1983). It was noted that 25% of managers perceived the outcomes of M&A deals to be unsuccessful and an additional 20% as ‘so-so’ (Hunt, 1988; Hunt, Lees, Grumbar, & Vivian, 1987). Datta, Narayanan, and Pinches (1992) reported that ‘on average’ acquiring firms did not realise significant returns, and Galpin and Herndon (2000) reported that managers of newly merged companies tend to grade their own financial performance as ‘C  ’. Researchers have increasingly focused on the percentage of failures in M&A. Kitching (1967), Porter (1987), Cartwright and Cooper (1995), and Marks and Mirvis (2001), for example, have estimated failure rates ranging from 20% to 80%. Even more dramatic, Lajoux (1998) studied over 7000 M&A between 1965 and 1997 and reported 40–80% failed to meet projected targets. Risberg (2003) questions the exact magnitude of the phenomenon and the basis on which many

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researches make these claims. ‘[y] one universal lesson has become obvious: making a deal ‘‘work’’ is one of the hardest tasks in the business’ (Perry & Herd, 2004, p. 12). Despite decades of research and empirical knowledge, mergers and acquisitions do not necessarily contribute to improved performance, nor are they the best way to obtain needed resources. However, internal or organic growth, while providing resources quickly, continues to prove difficult for small firms even with external investment (Capron, 1999; Block & MacMillan, 1993), and research in analogous areas, such as licensing and alliances, presents evidence that these are equally challenging options (e.g. Das & Teng, 1998; Inkpen & Beamish, 1997; Pisano, 1990; Teece, 1986). Nevertheless, mergers and acquisitions continue to take place and research proliferates. What we hope to achieve is a new perspective that can aid the investigation of this phenomenon and identify a more meaningful or useful specification of the outcome of new firm growth followed by acquisition than ‘success’. Success measures raise the question of success for whom. Growth is not necessarily a full measure of value created and captured by an enterprise, since, for example, some small firms are more profitable than those that have grown larger. Increasingly, there is interest in the value created by a new firm (Bowman & Ambrosini, 2000). Firms engage in both value creation and value capture but there are many different kinds of value. Moreover, entrepreneurial innovation often creates value that is not captured for the firm or its owners. These are among the issues we hope to elucidate. Can M&A Success be Identified? Having looked mostly at the large firm outcomes in the acquisition process, typical tools for analysis consist of accounting and stock market–based measures of performance. In most instances, the effects on financial performance have been shown to be either insignificant or negative. In addition, it was noted by King et al. (2004) that most post-acquisition research only includes stock market event studies, ignoring the potential effects of M&A on other relevant criteria. Many HTSFs are too early in their financial cycle to have this type of measurable metrics. Furthermore, once a small firm (seller) has been absorbed into the buying firm, it becomes increasingly difficult to identify independent financial variables for analysis. In their meta-analysis of post-acquisition performance, King et al. (2004) found that empirical research has not consistently identified grounds for predicting success. They reviewed the most commonly researched variables of post-acquisition performance and found many inconsistencies. Hitt and others have attempted to support a theoretical rationale that recognises synergy resulting in the sum of two firms after acquisition being greater than their individual parts (i.e. 1 + 1W2) (Capron, Dussauge, & Mitchell, 1998; Hitt, Harrison, Ireland, & Best, 1998). Yet, they have not suggested tangible metrics to support this equation. King et al. (2004) also noted that significant variances or contradictions may be due to variables that have not yet been identified. They pointed out several M&A theorists who apply non-financial concepts such as ‘parenting advantage

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(Campbell, Goold, & Alexander, 1995), complementary resources (Harrison, Hitt, Hoskisson, & Ireland, 2001), or absorptive capacity (Zahra & George, 2002) as core to their models’ (King et al., 2004, p. 196). These concepts are used to identify effects that are more tangible and represent variables that are considered essential and must be aligned for synergy or success to be achieved. Their concept of ‘inconclusiveness’ of M&A research regarding performance findings supports earlier works such as those of Haspeslagh and Jemison (1991) and others, who continue to comment that there were too few explanatory conditions in M&A research to allow the outcome or performance to be consistently predictable (Hitt et al., 1998). The reasoning behind M&A in general was questioned by Pablo and Javidan (2004, p. xiv). They discussed the prevalence of the phenomenon as one where ‘corporations and executives are obviously in love with M&A’s’. But is this true for founders and investors as well? It could be argued that outcomes are not only difficult to predict or quantify, but that they are also relative. Depending on how success is measured, and by whom, the answers may vary. Thus, it seems inappropriate to ignore the potential influence of the various stakeholders and the alignment of their expectations when examining questions relating to the success or failure of M&A.

Expectations as an Indicator The main stakeholders considered in existing M&A research are the buyers.2 Their incentive to pursue acquisition includes rapid diversification into new markets to take advantage of growth opportunities and economies of scope (Vermeulen & Barkema, 2001), expansion of product lines, elimination of competition and economies of scale (Zollo & Singh, 2000). Access to new technology (Ahuja & Katila, 2001; Graebner & Eisenhardt, 2004), entrance to international markets (Vermeulen & Barkema, 2001) and the necessity for reorganisation (Davis & Stout, 1992) have also been identified as leading incentives. Jensen (1993) assumed that individual stakeholders were motivated by self-interest and that high-ranking corporate officers may pursue paths for the good of the public shareholders, but not necessarily in the best interest of the individual owners (Jensen & Meckling, 1994). Positions of power and control with regard to information were researched by O’Donnell (2000), while others addressed the relationships present in M&A (Graebner & Eisenhardt, 2004; Lane, Cannelloa, & Lubatkin, 1998). This difference between parties based on asymmetric information goes against more traditional economic models that assumed parties in a transaction have perfect information and

2. The majority of acquisition research focuses on post-acquisition scenarios and tends to approach the subject looking at the acquiring as opposed to the acquired entity, that is, the buyers’ perspective as opposed to the sellers’.

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that the concept of self-interest is not entirely determined by economic incentives (Granovetter, 1985) or primarily motivated by financial gains (Barney & Hesterly, 1996; Hirsch, Michaels, & Friedman, 1990). Behavioural scientists identified non-financial rewards as significant motivators for entrepreneurs (Cyert & March, 1963; Simon, 1955). Though generally observing large firms, Penrose (1959) believed expectations, more than ‘objective facts’, to be the key antecedents to managerial behaviour.3 Garnsey has adopted Penrose’s large firm theories and applied the resource-based perspective to HTSFs (1995, 1998): by looking at both internal and external influences, a useful model can be constructed with which one can begin to understand the processes in small firms. Inherent characteristics of individuals and the relationships between these individuals are paramount. Drawing from this and other similar approaches (Amit & Schoemaker, 1993; Barney, 1986; Barney & Zajac, 1994; Lei, Hitt, & Bettis, 1996; Schoemaker, 1992), this study attempts to understand the alignment of stakeholders and their expectations in the acquisition process.

Conceptual Framework for Theory Building Theory-Building Process — Building Blocks There are several approaches to theory building including functionalist, interpretivist and structuralist. The similarities and differences among paradigms were reviewed by Gioia and Pitre (1990) who concluded that multi-paradigm perspectives provide more comprehensive views by accounting for differences and recognising ‘the multifaceted nature of organisational reality’ (Burrell & Morgan, 1979). For the purpose of our study we use a combination of methods, and this chapter represents the analysis of relevant theories and variables for putting together a framework (see Figure 2). To develop this framework, semi-structured interviews with industry experts were held in addition to the literature review. These included Cambridge (UK)-based venture capital firms, corporate investors, small business authorities and entrepreneurs. Included were individuals both experienced and not experienced in the actual acquisition process. Insights were gathered based on concepts from Delphi methodology concerning the use of expert opinion. The objective of this process was to obtain a reliable consensus of opinion on the subject of HTSFs and M&A (Linstone & Turoff, 1975).

3. Deakins and Philpott (1994) emphasise the desire for independence and autonomy as a strong driver for entrepreneurial start-ups where their principals do not want these benefits to be lessened when their small firms are merged or acquired.

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SELECTING A TOPIC • What are the issues? • What are the research questions?

REVIEWING LITERATURE

• What do we know?

FINDING A GAP

• What is missing?

PUTTING A FRAMEWORK TOGETHER • What are the relevant theories and variables?

FORMULATING HYPOTHESES

DESIGNING RESEARCH

• What are data? • Where to find data? • How to measure data?

Figure 2: Initial steps towards theory building — functional paradigm (based on Gioia & Pitre, 1990, p. 593). Dimensions The expert interviews provided extensive background for the development of the conceptual framework. The consensus supported the identification of a threedimensional framework taking into account the existence of diverse stakeholders, their opinions with regard to expectations as well as those expectations over time. These three dimensions were identified as fundamentally essential to our research and make up the building blocks of a conceptual framework which is outlined in the following sub-sections. Each dimension has an inherent set of criteria specific to the framework and it is applied through the probing of informants in a more interpretive manner. It is felt that this combination will enhance creative theory building as suggested by Weick (1989). Stakeholders At an early stage in the investigation of this phenomenon, it became evident that there is not a single relevant perspective in acquisition scenarios, but many pertinent ones. Internal and external stakeholders have different perspectives with regard to M&A. As stated by Murray and Lott (1995), investors are motivated by the value appreciation of their shares and safe exit strategies. However, there are examples where pressures from investors cause companies to sell or go public earlier than might have been advisable or desired by the management team, often to the detriment of the firm. Often cited as the originator of agency theory, Smith (1776) discussed the issue of ownership and control in firms. He believed that people’s attitudes and actions were dependent on whose money they were looking after, their own or that of others. Berle and Means (1932) attempted to identify the sources of conflict when ownership and control of large corporations began to be held separately, finding that divergent or misaligned interests among the different parties were important. In the 1970s the role of information, incomplete and asymmetric, held by the different stakeholders was investigated (Akerlof, 1970; Ross, 1973). For example, Oakey states that ‘joint owners tend to have a greater propensity to view the firm, from the outset, in terms of ways in which their shares can rapidly maximise returns (usually implying a ‘‘grow to sell’’ approach), than do individual entrepreneurs’ (2003, p. 684). Venture capitalists look for strong teams, and founders themselves often group with friends or associates from previous places of employment or institutions such as army or university. Within these groupings,

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Figure 3: Stakeholders. however, each stakeholder may have different views on what the firms’ goals are. Having multiple owners means more people need to buy in to, as well as benefit from, any chosen exit strategy. Granstand and Sjolander (1990) feel this motivates multiple owner groups to pursue maximum monetary returns and often pushes them towards deals with global giants offering larger rewards. Thus, the comprehensive stakeholder perspective was initiated to encompass the potentially varying standpoints of the different parties concerned. The stakeholders identified for the purpose of this framework include founders, managers, investors and, depending on the scope of the case, others who were (or would be) involved in the decision process leading to acquisition such as consultants. To obtain the full picture, representatives from the buyer’s side are also included in the interview process, but their expectations generally differ from those of the seller (see Figure 3). Expectations Taking into account numerous M&A theories based on large firm research discussed above, an endless list of expectations considered by individuals involved in the acquisition process as ‘important’ could be identified. There are, however, a relatively small group of potential outcomes that are consistently referred to by HTSF stakeholders. These include personal gains, return on investments, company growth and technology diffusion. For example, stakeholders who were not anxious to pursue acquisition enjoyed a particular lifestyle with the current structure of the company, thus making acquisition less attractive. Cases of companies entering into financial difficulties were discussed in the expert interviews. Breaking even as well as trying to protect loyal employees who had been instrumental in building the company appeared important. Thus, these factors were added to the potential expectation list as depicted in Figure 4.

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Wealth (Personal) ROI Survival / Breakeven Life Style / Fun People(Interesting Jobs) Growth Technology

Figure 4: Expectations.

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Figure 5: Three dimensions. Expectations and stakeholders compromise the first two dimensions of the conceptual framework. The potentially changing expectations of these stakeholders, pre- and postacquisition, led us to surmise that introducing a third dimension to this framework was compulsory, not simply helpful, this being the element of time (Figure 5). Time In their paper on the role of time in theory building, George and Jones (2000) pointed out that time is often included as a boundary condition — as opposed to recognising that it may play a more central role. Particularly to support ontologically accurate descriptions of phenomenon, specific elements must be present. These

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include answers to the what, how and why as well as who, where and when. Time directly impacts the basic elements of theory building — what, how and why (Kaplan, 1964; Dubin, 1976, 1978; Whetten, 1989). In addition to identifying the impact of past, present and future in individual psychological constructs, Karniol and Ross (1996) have appropriated them to those of organisations as well. They identify the relationship between the past and the present as well as to the imagined future as a ‘two-way street’ having ‘reciprocal motivational connections between people’s goals and recollections’ (Karniol & Ross, 1996, p. 607). In acquisition scenarios, expectations are formed by past achievements as well as future expectations. Bandura (1982) identifies a firm’s perceived capabilities of overcoming current difficulties as being based on previous experiences and the anticipation of future influences, thus fundamentally affecting motivation and actions at any given time. Baron and Hannan (2002) note that the way in which founders of HTSFs address strategy in early stages continues to affect their firms’ long-term development, emphasising the importance of taking a wider perspective when reviewing any single phenomenon. Motivations change, and in order to properly review a phenomenon one must then be able to incorporate those changes into any comprehensive model. Williamson approached opportunism as a stable tendency; however, it should be recognised that individuals’ desire to act opportunistically is a state of mind that can change, often and rapidly (1975, 1985). Weick pointed out the importance of ‘simultaneous parallel processing’ elements of building theory, as opposed to sequential or linear processing (1989, p. 519). It was noted that time also has various ramifications on the framework. Time can be represented both as snapshots or points in time where we capture data and as absolute time, that is, the months or years that different processes take and the changes that occur over those periods of time: 1. Snapshots — For the purpose of our model, three distinct activities were identified as snapshots for data capture. They are (i) the point in time where acquisition begins to be actively considered (t  1), (ii) the point in time when acquisition takes place (t0) and (iii) the initial stocktaking when one is able to reflect on the acquisition process and reflect on the alignment of expected outcomes to actual ones (t1). These points have been identified as expectations, realisation and outcome (ERO; see Figure 6). An important aspect of this dimension is that these points are snapshots in the life cycle. They represent a moment in time — but one must keep in mind that firms are dynamic and changing between these points. To fully understand the dynamics of HTSFs, it is essential to understand both the pre- and post-acquisition dynamics. The expectations which are held prior to acquisition even being considered as well as those held following the completion of integration with an acquiring firm. Refer to Figure 7. 2. Absolute time — Time between each static stage of the ERO framework is also relevant. The framework maps duration of time: (i) time from inception to beginning of expected acquisition, (ii) the period over which acquisition is researched or negotiated up to realisation and (iii) the time after realisation until a

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Figure 7: Expanded time snapshots for ERO framework. measurable outcome (refer to Figure 8). This allows us to compare the case studies, understanding the different durations: When did the E stage occur? How long did it take to get to R and then to O? Thus, this enables a better understanding of the evolution between the ERO stages.

Application of the Conceptual Framework Though the building blocks of the conceptual framework, stakeholders, expectations and time, were validated with industry experts, to test its soundness as a research tool it has been applied to an actual case study of a Cambridge-based HTSF in the ICT sector. The following represents this application in the form of a concrete case study.

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Case Study — Applying the Framework Cambridge-Based Research Cambridge (UK) has over 1500 technology-based companies and is recognised as having one of the highest levels of entrepreneurship in Europe (EC, 2006). The 2006 Cambridge Technopole Report identified Cambridge as one of the world’s leading high-technology business clusters (Herriot & Minshall, 2006, p. 11). On average, 25% of UK venture capital investments are focused on Cambridge companies (Library House WilmerHale & BDO Stoy Hayward, 2006). New firms grow in specific business environments, the features of which have a major impact on their prospects. Hence, we aim to examine a group of Cambridgebased firms in a specific sector. This allows us to focus comparisons on firms’ experience rather than sectoral difference. The sector identified as of particular interest for more in-depth examination is the ICT sector in Cambridge. Information and Communication Technology The evolution of the ICT marketplace worldwide has called for new rules of engagement. Whereas previously the market only aimed to connect two people over a simple line, the new market is forcing suppliers and operators to continuously introduce innovative media, entertainment, gaming, interaction and data services over IP networks. They have been forced to identify and cope with shifting service offerings — in a quickly changing and increasingly competitive consumer-driven marketplace. This calls for innovative solutions on every level including technology, IT architecture, applications, content, billing, provisioning, service management and an ever-growing platform of expectations. With a well-established international technology consultancy network in Cambridge, local companies have for decades adapted leading scientific and technological knowledge to meet commercial requirements. This has played a significant role in the expansion of ICT as an identified industry cluster in Cambridge. Cambridge also reflects the evolution of the world market, growing initially in areas of computing and networking, breeding companies such as ACORN and encompassing a strong silicon base with the likes of CSR and ARM.

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By concentrating at this stage on the ICT sector, it is believed that the elements of the framework will strengthen ‘replication logic’. Outcomes can then be tested for generalised ability across sectors. The next stage was to identify a Cambridge-based company within the ICT sector for initial review and testing of this conceptual framework. A Cambridge-based HTSF (TechCo for our purposes) was acquired by a multinational ICT firm, referred to here as BigCo. We were able to observe the acquisition progression and to hold several discussions with people over a 6-month period, having the unique opportunity to obtain information from the individual stakeholders during the acquisition process.

TechCo — Cambridge-Based HTSF Specialising in application protocols and silicon for mobile devices, TechCo was spun out of a Cambridge-based technology consultancy as a wholly owned subsidiary in the late 1990s. In 2007, TechCo was purchased by a global communication company with a division focused on mobile devices for cellular and wireless systems. Prior to acquiring TechCo, BigCo was just one of the many silicon vendors and handset manufactures in the wireless industry that TechCo supplied with various IP. In 2006 it became known that TechCo was short of cash and BigCo made a strategic decision to purchase the company and its assets. This enabled BigCo to ensure continued availability of potentially critical elements in their mobile devices as well as access to TechCo’s application software which was in the final stages of development. Expectations of TechCo’s stakeholders including the original founders, an investor, a top manager, a financial consultant and BigCo’s integration team were collected through semi-structured interviews and numerous secondary sources. The outcomes have been introduced into the ERO conceptual framework (see Figure 9), and initial observations have been made. TechCo Background Prior to being acquired in 2007, TechCo flourished in Cambridge and held a strong market position. The company had a distinctive culture of innovation and the founders were committed to providing both an interesting work environment and cutting edge solutions to their customers. Publicly traded since 2000, the founders’ intent was to grow organically and become a worldclass player. Being acquired was not seen as necessary or productive, and over the years several offers were dismissed without consideration. As illustrated in Figure 9, company growth and a content workforce were the main aims of the internal stakeholders of TechCo. Investors and financial consultants were satisfied with comfortable returns, and the company maintained year-on-year revenue and manpower growth. The sheer breadth and depth of their customer base afforded TechCo market dominance. In March 2006 a leading news source announced that TechCo’s new

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Figure 9: TechCo’s initial expectations. solutions were better than previous solutions as well as better than any others available in the market. Continuous reports of successful developments and the growing reputation of their new product line continued well in 2006. Though they managed to maintain market position and growth through the difficult years after the bubble, in 2006 TechCo was taken by surprise when revenues from traditional product lines nearing end of life diminished faster than their replacement products were able to generate new revenues. Several high cost lines in their budget, mostly associated with 3G development, were not drawing profits as quickly as expected, and this insecure financial position left them vulnerable. The stakeholders became increasingly aware that they needed to change policy or face bankruptcy. Over a period of 18 months, TechCo investigated possible scenarios, one of them being acquisition by a large firm. Other options included breaking up the company and selling off some of the parts or raising additional public funds. Management focus shifted from growth and wanting to ‘rule the world’ to protecting personnel. Being publicly traded, protecting shareholder assets was essential; nevertheless, maintaining an interesting work environment and retaining their staff were seen as equally important as TechCo was considered a family. For an investor and the financial consultant, expectations shifted from wanting a return on their investment to simply wanting to be able to minimise or control losses by avoiding liquidation. A large number of potential acquisition partners were reviewed. TechCo’s preference would have been for a local entity to acquire them. Unfortunately, none were in a position to do so. BigCo, however, had been very happy with TechCo as a supplier and made it clear that they believed there was something special in the company culture that they intended to maintain and promised no immediate redundancies.

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ERO Framework The founders and management team were accustomed to functioning as a ‘whole system’ using ‘family solutions’ with common ethos and generally in agreement about decisions. Despite the fact that they never expected to be acquired, once it became a necessity, their expectation to protect people in an interesting environment was aligned. Initially taking a backseat and letting BigCo manage the acquisition process, TechCo’s CEO and co-founder realised that staff were looking to him for leadership. ‘At first I made a big mistake — TechCo employees needed my endorsement; I needed to take ownership of the process’. At the point where he took a more active role in facilitating the integration process it became easier, ensuring smoother integration and a more content workforce. One of the founders stated that ‘having to be acquired was a failure — but the acquisition by BigCo has proved to be a B + . The actual acquisition itself couldn’t have been better once we got over the psychological impact; our big expectations have been met. Life is good. Most people have interesting jobs with opportunity’. Coming from a culture ‘not hot on defined roles and responsibilities’, some of the more senior staff found it difficult to deal with changes in ‘seniority’ — as their positions became much more defined with a large corporate structure now in place. One senior manager interviewed left soon after the acquisition was completed. Initially benefiting from a ‘fun’ working environment, his feeling was he ‘didn’t want to wait around for the dust to settle’. He believed that he would have to spend several years carving out a new place for himself and dealing with administration of the acquisition rather than focusing on development which was his passion. In addition, TechCo’s external financial consultants were not retained past the acquisition closure. So, though they had played a pivotal role in TechCo’s management for many years, the acquisition ended their tenure and their expectations were not met. These cases, however, were exceptions and not the norm. Analysis Buyer expectations lay in obtaining both technology and an outstanding technical team with robust development skills, capable of working to tighter schedules than BigCo developers traditionally adhered to. In order to preserve these assets, it is crucial for BigCo to align with TechCo’s expectations of interesting work and retention of jobs. These expectations are compatible, and their alignment appears essential. From Figure 10, it is possible to see the progression of stakeholders’ expectations over time. Initial expectations and those that remain the same from the previous period are depicted with an X, those that change with an O and those stakeholders removed from the process are represented by the symbol ‘ ¼ ’. In this way, it is possible to see that founders’ expectations have been aligned at all three stages of the ERO framework. By charting absolute time of the TechCo acquisition process, as in Figure 11, one can see that TechCo had been expanding for over 10 years and had very few setbacks since inception. Faced with financial difficulties, they considered acquisition and reviewed a good number of potential buyers over 18 months. When BigCo actually made an offer, there was a very short period, measurable in weeks, before it was accepted. It has not yet been a year since the acquisition. Integration is on schedule

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Figure 11: TechCo’s absolute timeline. and appears to be running smoothly from both the buyers’ and the sellers’ perspective. One of the co-founders stated: ‘y all the big things work, some of the little ones suck — but they aren’t the important ones. These are differences people just need to get used to, people don’t like change — but they do like their jobs and BigCo opened lots of doors for interesting development opportunities and projects’. Initial review of the ERO framework for this acquisition has highlighted some interesting aspects regarding the alignment of expectations. It is felt that applying ERO to additional cases for cross-case analysis will aid the theory-building process.

Next Steps Using the ERO framework, multiple case studies will be developed based on standard techniques for theory building (Yin, 2003; Eisenhardt, 1989). Data collection, analysis and the subsequent stage of theory building will be performed using firms identified through the initial interview process as depicted in Figure 12 (Gioia & Pitre, 1990). Primary case information will be gathered through semistructured interviews. Archival data, websites, publications and other materials provided by the participants will be used as secondary sources (Yin, 2003). Pre- and post-acquisition perspectives will be gathered from the various seller– stakeholder points of view. The buyers’ perspective will also be included to broaden

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• Show how the theory is refined, supported or disconfirmed • Show what it tells the scientific community and the practitioners

Figure 12: Secondary steps towards theory building — functional paradigm (based on Gioia & Pitre, 1990). the analysis in each case. This multiple case method follows a ‘replication logic’ comparable to that used in multiple experiments, considered more robust and generalisable than single case studies (Eisenhardt, 1989). The collected body of case studies will provide a starting point from which to draw cross-case conclusions and build a theoretical framework. The framework will be strengthened with broader data analysis to enhance internal and external validity.

Conclusion Seller–stakeholder’s pre-acquisition expectations may well influence a firm’s ability to realise its full post-acquisition potential. To date, acquisition-related research has concentrated on the buyer’s perspective, and numerous researchers have examined M&A by looking at corporate finance, capital markets, strategy, organisational theory, corporate culture and human resource management. They have tended to pay little attention to or leave out all together the seller’s perspective, which we view as a critical factor in the equation. The ERO framework outlined here aims to enrich this body of knowledge by allowing one to determine the alignment of HTSF stakeholder expectations pre- and post-acquisition. Addressing this gap will lead to insights that are of potential interest to both academia and industry. This research is designed to provide insight for both potential buying and selling firms as well as for the investment community and policy-makers.

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Chapter 9

Entrepreneurs’ Communicative Behaviour in Technology-Based versus Service-Based Businesses — A Resource Dependence Perspective Pia Ulvenblad

From previous research we know that entrepreneurs often suffer from liability of newness as they lack a ‘track record’ for the business (Aldrich, 1999; Aldrich & Fiol, 1994; Lounsbury & Glynn, 2001; Shepherd, Douglas, & Shanely, 2000; Stinchcombe, 1965). Hence, they have to ‘draw on alternative forms of communication’ (Aldrich & Fiol, 1994, p. 652). Further, we know that entrepreneurs need to act as if the business is already ongoing (Gartner, Bird, & Starr, 1992), but it is not fully clear how they are to accomplish this. Entrepreneurs communicate their visions and intentions in business plans (Delmar & Shane, 2004; Karlsson, 2005). They communicate to create credibility and to obtain finance. Hitt, Ireland, Camp, and Sexton (2001) state that entrepreneurs need to act strategically regarding communication. One way to do this could be to use a story-telling strategy (Lounsbury & Glynn, 2001; O’Connor, 2002) or a talking strategy (Wickham, 2006). Another way could be to ‘do as a duckling’ (Mattsson, 2007) — act cool on the surface and paddle furiously below. The aim of this chapter is to compare communicative behaviour in technologybased and service-based businesses, to enhance the understanding of how entrepreneurs can overcome the liability of newness and generate credibility for their businesses. This chapter contributes to previous research in several ways. First, it advances the understanding of how entrepreneurs in technology-based and service-based businesses use communication in the start-up phase of the business. Several activities have to be carried out by the entrepreneur to accomplish a start-up, some of them being of a more instrumental character (Delmar & Shane, 2004; Hormozi, 2004; Karlsson, 2005) and others of a more relational character (Aldrich & Fiol, 1994; Gaglio, Cecchini, & Winter, 1998; Lounsbury & Glynn, 2001; Mattsson, 2007).

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Communication is an act of interaction that is incorporated both in activities that have a more instrumental character, such as writing a business plan, and naturally in activities with a more relational character, such as talking to presumptive stakeholders. Since communication has been seen as important in every step of business development (Roodt, 2005), it also deserves to be highlighted in advancing the understanding of entrepreneurial strategies in the start-up phase. Second, the chapter gives empirical examples of alternative ways of communication in early startup phases. Gartner, Bird, and Starr (1992) propose that entrepreneurs talk and act as if the business is already ongoing. Aldrich and Fiol (1994) argue that, since entrepreneurs often lack a previous ‘track record’ in their businesses, they need to draw on alternative forms of communication. However, empirical studies have been limited, so the present study makes a contribution in this research area. Third, the study furthers the understanding of strategic communication in the start-up phase of the business by relating the communication strategies to business characteristics of technology-based and service-based businesses. The chapter proceeds as follows. First a framework is presented to enhance the understanding of entrepreneurial communication strategies. Afterwards, the method, with details of the data collection and data analysis, is described. Four cases analysing the communicative behaviour for each business are presented and followed by a discussion of the empirical and theoretical analysis. Finally conclusions, implications and future directors for research are discussed.

Theoretical Framework — A Resource Dependence Perspective and Communicative Behaviour A Resource Dependence Perspective To enhance the understanding of entrepreneurial communication strategies in the start-up phase of the business, a resource dependence perspective is presented. Resources can be categorized in several ways. Penrose (1959), one of the pioneers in the resource-based view, and the subsequent work of, for example, Wernerfelt (1984) and Barney (1991), have brought the individual, the entrepreneur and especially resources within the business into focus. The process school of the resource-based view focuses on processes and activities and internal strategic capabilities (Tucker, Meyer, & Westerman, 1996). Furthermore, capabilities are based on developing, carrying and exchanging information through the business’s human capital (Tucker et al., 1996). Grant (1991, p. 122) defined such capabilities as ‘complex patterns of coordination and cooperation between people, and between people and (tangible) resources’. Baum, Locke, and Smith (2001) and Lee, Lee, and Pennings (2001) found that new businesses’ internal capabilities are the primary determinants of the businesses’ performance. One of the intangible resources could be a business reputation (Deephouse, 2000). A positive reputation creates advantages in order to obtain, for example, financial capital.

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In the present study we know that new businesses often lack a ‘track record’ and suffer from liability of newness (Aldrich, 1999; Aldrich & Fiol, 1994; Lounsbury & Glynn, 2001; Shepherd et al., 2000; Stinchcombe, 1965). They must therefore act as if the business is already ongoing (Gartner et al., 1992), draw on alternative forms of communication (Aldrich & Fiol, 1994) and search for surrogate means to establish a positive reputation (Hitt et al., 2001). With a focus on communicative behaviour, we also know that someone has to react to the communication. Grant (1991, p. 122) talks about ‘patterns of coordination and cooperation between people’ and this is also what the dependence is centred on. As an entrepreneur, one has to interact with people and organizations to obtain resources, and thus one will also depend on these people and organizations. Pfeffer and Salancik (1978) point to this dependence in several ways. Organizations require resources from the external environment to survive, which means that the entrepreneurs have to interact with others to get these resources. There is always a judgement by outsiders involved: ‘y the acceptability of the organization and its activities is ultimately judged by those outside the organization’ (ibid., p. 11). Further, the focus is on exchange, and this may consist of ‘monetary or physical resources, information or social legitimacy’ (ibid., p. 43). In determining the dependence of one organization on another, there are three critical factors according to Pfeffer and Salancik (1978): (i) the importance of the resource, (ii) the discretion over the resource’s allocation and use, and (iii) the number of alternatives available. The organization has different possibilities to respond to external control and constraints. Pfeffer (1981) thinks organizations can acquire control over resources so that either their dependence on other organizations decreases or others become more dependent on them. Pfeffer and Salancik (1978, p. 11) propose that ‘the organization can and does manipulate, influence and create acceptability for itself and its activities’ and present different strategies to do this. Since communicative behaviour is central in the present study, it is relevant to see how the authors relate to the subject of communication strategy. ‘The common element in our consideration of strategies for developing a negotiated environment is communication. Both the need for and feasibility of interfirm communication is the single best predictor of interfirm activity’ (Pfeffer & Salancik, 1978, p. 183). Further, since the environment must be relied upon to provide support, the communicative behaviour also needs to be adjusted and adapted in order to suit the external environment. This is called behaviour interdependence, as the activities are themselves dependent on the actions of another social actor (ibid.). Although there is some external control of the organization, it is possible to respond to the situation. Organizations can also respond to pressures from the environment by acceding to the demands of some interests, avoiding the demands of others, establishing relationships with some coalitions and avoiding them with others etc. The placing of environmental groups’ representatives in, for example, advisory boards could also be a way to meet the external constraints. ‘Beliefs about products and services are created y’ (Pfeffer & Salancik, 1978, p. 101), and therefore the challenge is to communicate the business idea as interesting

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and attracting, so external actors like financiers will be interested in seeing more of the business and hopefully interacting with the entrepreneur, particularly through providing financial capital.

Communicative Behaviour ‘Communication is not just about relating information. It is also about eliciting action on the part of the receiver. It is not so much about getting people to know things as about getting them to do things’ (Wickham, 2006, p. 324). When entrepreneurs communicate with potential stakeholders they are eager to get action, such as provision of financial capital, but they are also, as a first step, eager to make an impression regarding the business. Gaglio et al. (1998) found, for example, that entrepreneurs are aware of how to create an impression of their business, but they prefer to manipulate such areas as communication, office location and dress before manipulating the symbolic dimensions of technology. However, it is not clear how the entrepreneurs manipulate communication. Communication is also a dynamic process involving a reciprocal flow of information that has been shown to be important in every phase of business development (Roodt, 2005). Baum, Locke, and Kirkpatrick (1998) found among other things that communication of the business vision has a significant impact on the organizational performance, especially in entrepreneurial businesses. To manage the vision is found to be an entrepreneurial behaviour (Sadler-Smith, Hampson, Chaston, & Badger, 2003). It is not clear from the study whether this has to do with communication. However, it could be related to communication, since one way to manage vision in the study is to identify customer needs. Entrepreneurs in the start-up phase need to communicate with different stakeholders to create legitimacy for the businesses. Since they often lack track records, they must draw on alternative forms of communication. One way to communicate could be to use a ‘story-telling strategy’. This is used by entrepreneurs who think of their business as a stage with different actors and different roles, proposes Wickham (2006). It can be related to Goffman (1959/1974) who has described acting as being in a scene, in the social interaction between individuals. Lounsbury and Glynn (2001) propose a framework that they call ‘cultural entrepreneurship’. They think that entrepreneurs can use stories as a way to create a new identity for the business and build legitimacy with key stakeholders. O’Connor (2002) studied high-technology start-ups and found that entrepreneurs create several different types of stories, some of which are contradictory. She also found that stories can both create legitimacy and help the founder to induce others to give resources to the business (ibid.). Mattsson (2007) identified six categories of communicative strategies: to go (i) from being no one to being someone, (ii) from small to big, (iii) from inexperienced to experienced, (iv) from one role to another role, (v) from being alone to being a network member and (vi) from silence to communication.

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Method To meet the aim of the chapter and enhance our empirically based understanding regarding entrepreneurs’ communicative behaviours, this study is based on four case studies which include interviews with six entrepreneurs. Two of the cases are technology-based (Software with respondent Alan and Event with respondents Dana and Doris) and two are service-based (Picture with respondent Eric and Strategy with respondents Franc and Filip). All four cases are situated in incubator environments. As this chapter represents one part of a larger project, the empirical findings in the interviews are especially related to resource dependence and communicative behaviour in the four cases. The data were collected during autumn 2006 and spring 2007. In-depth interviews were conducted with the six entrepreneurs. The interviews were carried out as stories focused on the business start-up and further development. The entrepreneurs were, among other things, asked to recall their growth orientation, how they started their businesses, what they did to communicate their intentions, what activities they engaged in, which actors were central etc. The interviews were tape-recorded and transcribed word for word to capture every nuance in the stories. The interviews lasted from 1 to 1.5 h. Besides the interviews, observations, studies of both business plans and PowerPoint presentations have been conducted together with other documents, homepages etc. related to each one of the businesses. The analysis of the empirical material was conducted stepwise. After the transcriptions of the interviews, the tapes were listened to once more, in order (i) to make margin notes of expressions and (ii) to identify general patterns in the expressions of all the six interviewees before concentrating on each one of them. The next step was to focus on each one of the interviews, seeking to understand the specific expression of the entrepreneurs based on whether the business is technologybased or service-based. The last step was to match the empirical findings with the frame of reference — using resource dependence theory to further the understanding of entrepreneurial communication. There are advantages as well as shortcomings in a study based on stories. The advantages of collecting data through stories are that details are revealed in the stories. The empirical nearness makes it easier to understand nuances in the stories of the entrepreneur. However, there are also shortcomings with the approach, one being that it involves stories. It could be argued that the entrepreneurs do not describe what happened. To meet these shortcomings, this study encompasses several meetings with the entrepreneurs, as a way to create trust between the entrepreneur and the researcher.

Resource Dependence and Communicative Behaviour in Four Newly Started Businesses The first two cases in the following presentation are technology-based (Software and Event) and the last two cases are service-based (Picture and Strategy).

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Software Software started as a research idea. Alan, who is the managing director, thought of making contact with a researcher and innovator, and they started together to develop the business. This process began in spring 2005, and in December 2005 they registered their formal business as a legal entity. During 2006 Alan initiated a contact with a former board colleague who was involved in an incubator. The colleague was interested, they made a presentation for him, and this gave them the opportunity to get finance from the incubator and also a location in the incubator area near a university. The business idea is to develop advanced technical products in the software area. From two persons and one product initially, they went to five employees, ten students working with projects and 18 products by the beginning of 2007. Alan has a university education in business economics and experience from both start-ups and liquidation of a business. He also has work experience from coaching entrepreneurs in the emergent phase of business development. With the experience from coaching other entrepreneurs, he has learned the importance of asking customers what they want in the start-up phase of the business. This is usually a missing part of business plans, he thinks. In the starting process of Software they were determined to make a thorough market investigation including interviews with potential customers, and Alan believes this was also a signal for financiers that the business was interesting to take part in. As they are working with a new emission of shares, Alan says it is important to think about communication. They need money to further develop the business into a selling organization. We are working with a new issue of shares; then it is important for the financiers — what do we earn? Alan thinks there is a big difference between explaining the products for people who know technology and doing so for those who do not, and this is a challenge. It is better to limit the talk about techniques in some cases. You have to think about who you are talking to y. Alan also says that publication is important because, if financiers have read about the business in a positive way, it will be easier to get the first contact and get them involved in the business. The company, he continues, has about a hundred product ideas. This work will continue stepwise depending on the customers’ need for the products. We have been listening to needs all the time since the start, Alan says. It was important for Alan to get a homepage at an early stage, but this was especially important for displaying competence and professionalism, to be able to attract financiers and other stakeholders. He worked with highlighting research as a foundation of the business. This was also something he knew would interest

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financiers. He soon placed an advisory board with experienced consultants on the homepage. The company wanted to be seen as big in its smallness from the start and not as a garage business, so the site was enhanced to look as if there were more people, but they did not lie. The focus in presentations of the business is the products and product development. Alan continues to highlight the research basis in the products and to work with being professional. During board meetings Alan is the driving force. He is eager to adapt to part-owners’ wishes while still keeping the focus on the process of developing a selling organization.

Event Dana, who is the managing director of Event, and Doris planned their business during the completion of an engineering project for educational purposes in 2002/2003. After this period they gradually developed their business from part-time to full-time involvement in the summer of 2004. In February 2004 they got the opportunity to move into an incubator related to a university where they still are located. In the beginning of 2006 they formally started Event as a legal entity. Their business idea is to develop and construct electrical components and products. They both have a university education in engineering and experiences from different types of enterprises. According to Dana the process of starting the business has incorporated a lot of marketing activities, directed to stakeholders like customers and financiers. Dana and Doris have been working actively to show stakeholders that they are competent in what they are doing. From the start they have had a need for both financial resources and business development competence. They understood that the business was going global as the Swedish market was too small for the product. An initial difficulty was the financing. One solution to the problem was, as Doris explains it: We got a contact with Daniel Brown who has been working a lot in industries. He works as a coach. He also got into the business and thanks to this we got finance. Dana also points out that this legitimacy with Daniel in the board gave them opportunities that she thinks would have been harder without him. When you are sitting in negotiations you see that when you say something yourself it is not the same as when Daniel says something. Legitimacy is important — you notice that. Another difficulty has been to explain the technology for non-technicians. Doris says that they sometimes felt as if they had to use another language to communicate with both financiers and other external stakeholders. Both Dana and Doris are in a way perfectionists, according to themselves. They have understood that it is often a matter of playing a role when they introduce their business. Further, Doris thinks

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that they have been working a lot with creating professionalism. It is important for them, and she says that if they are going to introduce themselves, they do so in an impressive way. Dana continues that being professional and acquiring legitimacy means not only having a location, a homepage in English and so on — it is a question of time, and she thinks that the time factor is crucial. It is a result of continuity for Dana: they refused to give up their intentions to start and develop a business. She says that the longer you exist, the more legitimacy you get. The focus in presentation of their business is on the product. In the business plan they also have written about the external actors that are important in testing their products. Further, they have been elaborating upon different types of presentations. Once they made a public appearance as a kind of show. We made a show with music y then we went in and told our story in a different way. Dana is not sure about what it gave them to make that appearance, but she noticed that after the presentation they obtained a new financier for the business. She also observed that people remembered them afterwards and were interested in what had become of the business since the last time. In the beginning of 2007 they applied for more financial resources and tried to carry out a new issue of shares, but they failed. In May 2007 Dana and Doris were still struggling for finance and they have both decided to look for employment outside the business to earn their living. They have contact with important actors testing their products, but it takes time. The time factor is crucial in the business, and they need acceptance from the important actors.

Picture Eric formally started his business Picture in the beginning of 2006. The business is located in an incubator related to a university, which Eric is very happy about. He thinks this has given him the opportunity to get legitimization and a place to meet customers that is not in his own home, to become someone in a context and to get a lower cost situation in the emerging phase of the business. His business idea is to supply customers with pedagogical e-learning programmes for different needs. He has a university education in computer pedagogy and also practical experience as a teacher. He sees cooperative partners as the first step in the growing process of the business. This is also what he has been working with from the start. As Eric did not have a natural network in the new city, the development of network contacts is something that has been preoccupying him as one of the most important activities. It has been important to be seen and to create new contacts that eventually can lead to new contacts and so on. The networks — it is often they that give you new contacts.

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During the process of starting the business, Eric has been working a lot with activities that make him visible in the business arena. A name for the firm, a homepage and visiting cards were the first signs of the business. Parallel with these activities, he wrote the first business plan and communicated it both to financiers and in network meetings. In the start-up it was important to talk and work as if the business was already ongoing. He tells that in the earliest phase, when he had his first PowerPoint presentations for stakeholders, he caught himself thinking: It was almost as if the business was running already. He took up a new role, and one of the most important themes in this role was to get the first customer — a reference customer that would help him to open new doors. He got his first reference customer and is continuing the work. In May 2007 Eric is working part-time to earn his living and part-time to further develop the business. He thinks it is a good complementary arrangement and he can develop his network even more.

Strategy Franc started a business in 2003 on a small scale beside his work with estates. In January 2006 he moved into an incubator located near a university and started his cooperation with Filip. The planning of a mutual business took place over almost 1.5 years before the start-up. They work as partners under the same trademark Strategy but each has his own customers. The business idea is to provide strategic help (e.g. strategic analysis and market analysis) for businesses in various environments. Franc and Filip have higher education in market communication and leadership, and former experience from both teaching and work as leaders. The process of starting the business encompassed numerous activities. As both Franc and Filip have education in communication, they think a lot about how they communicate their intentions and their business idea. It was important early to be regarded both as a business and as businessmen. It was also important to be able to earn their living, and one thing that helped them at the start was the location in the incubator, says Filip. It was a way to get resources to the business without having to pay everything by yourself. Beside visible things like a homepage and visiting cards, it was important to have a strategy that could be seen. One of these strategies was to have a telephone with a landline subscription. Filip tells about his initial strategy to make himself visible as a businessman. In every situation that presented an opportunity for a business interaction, he asked questions and then he had to introduce himself. When you have been at a meeting, asking a question, you can always refer to this incident, Filip

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continues. It is always good to refer to something or someone about which there is prior knowledge. network makes it possible to refer back to something. We met at the network meeting y. Franc, talking about customers and stakeholders, proposes that what you expect is what you get — this is what they have worked with regarding communication. He thinks that presenting the firm is a lot like going into an expected role and that if the customers expect a role, then they should get it. It is also important to make a visible display of competence. It is important that someone sees you and thinks you are good, says Franc. A way to do this is to be seen acting in different settings. Nobody is buying my company, they are buying me.

Analysis Based on the stories, both similarities and differences regarding communicative behaviour and resource dependence have been identified. What communicative behaviour do the entrepreneurs have when responding to the external environment, and how can this be understood? All six of them are aware of the importance of communication, as also Gaglio et al. (1998) found in their study. The respondents all work with communication but in different ways. In the technology-based organizations, Alan, Dana and Doris focus on product development. They need to get acceptance for their ideas and they need finance. All three of them have concentrated on communicating competence and business size to external actors in the early phase of the business. Alan emphasized, for example, the amount of people active within the business as an indicator of size, and he soon put an advisory board on the homepage as an indicator of competence related to the business. Dana and Doris have been working actively to show stakeholders that they are competent in what they are doing. Since time is a crucial factor, they need to be considered competent and professional from an early stage, and this might be enhanced by their having initially created an image of being bigger than they actually are. In the service-based organizations, we also find the will to appear bigger than they are. However, their communication strategies are rather connected with the location (Eric) and with the landline telephone subscription (Filip). The exchange between different organizations could be ‘monetary or physical resources, information or social legitimacy’ (Pfeffer & Salancik, 1978, p. 43). In the technology-based organizations, financial resources are important in the product development process, so the monetary exchange is obvious here. Although servicebased organizations also have a financial resource need in the start-up phase of the business, the focus is not on product development. In the service-based organization, it is possible to start with your service and sell your service. Franc expresses it by saying that nobody buys his company, they buy him. In a technology-based

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organization, there is a time factor that is crucial in the product development. This we can see both in Software, struggling to transform the organization into a selling organization, and in Event, having failed in its search for more financial resources and waiting to get the products tested. Regarding physical resources, the technologybased organizations are also more dependent on the environment, as they need suppliers who can provide material etc. Physical resources in terms of, for example, location have been provided in the four cases, as all of them are located in business incubator environments. In the service-based organizations, it has been important to communicate through a networking strategy and to be visible as a businessman. Eric, Franc and Filip have, all three of them, been working with the creation of new contacts. The networks make it possible to refer back to something, thinks Filip. Eric says that the networks often provide new contacts. This networking plays a special role for the two service-based organizations in the study. The exchange here may be mainly for social legitimacy, although it might also yield a monetary exchange between two potential partners in the future. Although the respondents in the two service-based organizations more often imply that networks are important, and take part in network activities, there is no doubt that networking also has importance for the entrepreneurs in the technologybased organizations. However, the networking activities in these cases are more about contacting financiers or someone who has contact with financiers. In all of the cases, there are expressions of dependence. Pfeffer and Salancik (1978) think that organizations require resources from the external environment to survive, and this means that the entrepreneurs have to interact with others to get these resources. In determining the dependence of one organization on another, there are three critical factors according to the authors: (i) the importance of the resource, (ii) the discretion over the resource allocation and use, and (iii) the number of alternatives available (ibid.). For the technology-based organizations, the financial resources have a high degree of importance. The service-based organizations also have a clear need for financial resources, but it is possible for the entrepreneurs in these organizations to start with the service they are providing. In both technologybased and service-based organizations, there are needs for the resource of external competence. This can be obtained from the board of directors or by interacting with external actors in, for example, networks. The entrepreneurs in the technology-based organizations have expressed difficulties with explaining to external actors what they are doing. They say there is a big difference between explaining the products for people who know technology and doing so for those who do not (Alan). They have sometimes felt as if they had to use another language to communicate the technology (Dana). In some cases the changing of roles for adapting to the environment is obvious since the entrepreneurs use communication as a strategic tool for adaptation. Alan, for example, is eager to adapt to part-owners’ wishes. Organizations can respond to pressures from the environment by avoiding the demands of some parties and acceding to the demands of others. This can be considered easy for service-based organizations that are working with networks. If they do not want to accede to the demands of one network, they can avoid it and go to

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another network to create new contacts. However, for technology-based organizations that are in the start-up phase and suffer from liability of newness, this is not so easy regarding financial resources. ‘Interdependence is the reason why nothing comes out quite the way one wants it to. Any event that depends on more than a single causal agent is an outcome based on interdependent agents’ (Pfeffer & Salancik, 1978, p. 40). Both internal (Barney, 1991; Penrose, 1959; Tucker et al., 1996; Wernerfelt, 1984) and external resources are important in business development. Communication is one of the internal resources related to human capital and is defined as an important capability (Tucker et al., 1996; Roodt, 2005). In the present study, the entrepreneurs use this capability strategically to cope with the external environment that they are dependent on.

Conclusions, Implications and Research Challenges The aim of this chapter has been to compare communicative behaviour in technology-based and service-based businesses, in order to enhance the understanding of how entrepreneurs can overcome the liability of newness and acquire credibility for their businesses. The entrepreneurs are all dependent on the external environment, and they focus on different communication strategies to deal with the dependence. The results of the study show that entrepreneurs in the technology-based organizations focus on communicating competence and size in the start-up phase of the business. In the service-based organizations the entrepreneurs focus more on communication through a networking strategy and on being visible as businessmen. The results will have implications for entrepreneurs learning different ways of communication in the start-up phase of their businesses. Communication has been shown to be important in every step of business development — especially in the startup phase of the business when the entrepreneur lacks a ‘track record’. There will also be practical implications for both entrepreneurial education and business incubator activities. A focus on communicative behaviour might enhance the possibilities for entrepreneurs to attract potential stakeholders earlier than they otherwise would. A research challenge is to further the understanding of strategic communication in the start-up phase of the business by continuing to relate entrepreneurial communication strategies to different factors in the entrepreneur’s background and the present situation. These could be previous experience and education, growth orientation, business characteristics etc.

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Barney, J. B. (1991). Firm resources and sustained competitive advantage. Journal of Management, 19, 99–120. Baum, J. R., Locke, E. A., & Kirkpatrick, S. A. (1998). A longitudinal study of the relation of vision and vision communication to venture growth in entrepreneurial firms. Journal of Applied Psychology, 83(1), 43–54. Baum, J. R., Locke, E. A., & Smith, K. G. (2001). A multi-dimensional model of venture growth. Academy of Management Journal, 44(2), 292–303. Deephouse, D. L. (2000). Media reputation as a strategic resource: An integration of mass communication and resource-based theories. Journal of Management, 26(6), 1091–1112. Delmar, F., & Shane, S. (2004). Legitimating first: Organizing activities and the survival of new ventures. Journal of Business Venturing, 19, 385–410. Gaglio, C. M., Cecchini, M., & Winter, S. (1998). Gaining legitimacy: The symbolic use of technology by new ventures. In: P. D. Reynolds (Ed.), Frontiers of entrepreneurship research (pp. 203–215). Wellesley, MA: Babson College. Gartner, W. B., Bird, B. J., & Starr, J. A. (1992). Acting as if: Differentiating entrepreneurial from organizational behaviour. Entrepreneurship, Theory and Practice, 16(3), 13–31. Goffman, E. (1959/1974). Jaget och maskerna (The presentation of self in everyday life). Stockholm, Sweden: Prisma. Grant, R. M. (1991). The resource-based theory of competitive compensation: Implications for strategy and formulation. California Management Review, 33, 115–135. Hitt, M. A., Ireland, R. D., Camp, S. M., & Sexton, D. L. (2001). Guest editors’ introduction to the special issue: Strategic entrepreneurship: Entrepreneurial strategies for wealth creation. Strategic Management Journal, 22, 479–491. Hormozi, A. M. (2004). Becoming an entrepreneur: How to start a small business. International Journal of Management, 21(3), 278–285. Karlsson, T. (2005). Business plans in new ventures, an institutional perspective. Doctoral dissertation, JIBS, Jo¨nko¨ping, Sweden. Lee, C., Lee, K., & Pennings, J. M. (2001). Internal capabilities, external networks, and performance: A study on technology-based ventures. Special issue: Strategic entrepreneurship: Entrepreneurial strategies for wealth creation. Strategic Management Journal, 22, 615–640. Lounsbury, M., & Glynn, M. A. (2001). Cultural entrepreneurship: Stories, legitimacy, and the acquisition of resources. Strategic Management Journal, 22, 545–564. Mattsson, P. I. (2007). Doing as a duckling — Entrepreneurial strategies to cope with liability of newness in a communicative way. Paper presented at the 2007 SMS Conference, Catania, Italy, 23–25 May. O’Connor, E. (2002). Storied business: Typology, intertextuality, and traffic in entrepreneurial narrative. The Journal of Business Communication, 39(1), 36–54. Penrose, E. T. (1959). The theory of the growth of the firm. Oxford: Basil Blackwell. Pfeffer, J. (1981). Power in organizations. Cambridge: Marshfield. Pfeffer, J., & Salancik, G. R. (1978). The external control of organizations: A resource dependence perspective. New York: Harper & Row. Roodt, J. (2005). Self-employment and the required skills. Management Dynamics, 14(4), 18–33. Sadler-Smith, E., Hampson, Y., Chaston, I., & Badger, B. (2003). Managerial behavior; entrepreneurial style, and small firm performance. Journal of Small Business Management, 41(1), 47–67. Shepherd, D. A., Douglas, E. J., & Shanely, M. (2000). New venture survival: Ignorance, external shocks, and risk reduction strategies. Journal of Business Venturing, 15, 393–410.

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Chapter 10

Knowledge-Intensive Entrepreneurship and the Voice-of-the-Consumer Basil G. Englis, Paula D. Englis, Aard Groen and Peter van der Sijde

Introduction The founder of paperbackswap.com, Bobby Swarthout, developed the idea for his venture while he was a college student. As a student on a limited budget, he had become tired of paying high prices for textbooks. So he developed and launched an online textbook swapping service. Along with a small group of students, he managed to assemble a group of 12 colleges and universities across the United States to participate in textbook swapping. However, after a few months, very few students had used the site. By listening to the potential customers who chose not to participate, Bobby found out that there were too many easy substitutes for the swapping service (e.g. bookstore returns, half.com, efollett, etc.). These alternatives offered either greater convenience or cash in return for used books (especially appealing to students who did not pay for their books themselves), or other appealing features. However, Mr. Swarthout believed in his concept and also listened to the ‘voice-of-the-consumer’ (VOC) and moved his business idea into different consumer/product space: that of paperback books. Along with a few lead users attracted to his original idea, he refined the original idea, gathered resources (an angel who invested in the business) and added technological capabilities. One year later he launched paperbackswap.com. From inception, the firm embraced the VOC as the key tool in driving product development and improvement efforts. For paperbackswap.com listening to the VOC has become part of a closed-loop system where inputs from consumers are analysed and product improvements developed in

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response and where the loop is closed by listening to how consumers respond to product changes. The following examples help illustrate how paperbackswap.com integrates VOC into its product development efforts. For example, as with many online services there is a ‘learning curve’ for users, many of whom are not the most sophisticated Internet or computer users. Recognizing this, the company instituted a ‘tour guide’ programme where highly committed members of the online ‘swap community’ volunteer as helpers for new users. These tour guides contact new users who wish to be helped, walk them through the system and answer any questions the new user may have. Data reveal that the tour guide system has resulted in a higher conversion rate of new contacts into active bookswappers. A broad range of services offered by paperbackswap.com have been directly influenced by VOC feedback. These range from book discussion forums to live chat to book journals where members share their reviews and comments about books they have read. At the core of the business is a crucial technological approach that has served to greatly simplify the users’ task in swapping books. For users to swap books easily over wide distances, they must use the mail system. In order to simplify this process, the founder of paperbackswap.com developed the technology needed to develop a database of ‘International Standard Book Numbers (ISBNs)’, integrate this into a second database that contains the dimensions and weight of the books and tie both to an output system that produces a wrapper using standard paper in the user’s printer. The user folds along the dotted lines and tapes the wrapper around the book. The process whereby the wrapper is printed provides a seamless connection between return and delivery addresses as well as printing the correct postage on the pieces of paper that provide the book wrapper. While the products being swapped are ‘old school’, the software technology behind paperbackswap.com is sophisticated, knowledge-intensive and has several patents pending. As a high-tech knowledgeintensive business, paperbackswap.com has grown to be a leader in the industry and continues to grow at a rapid rate — this online community has been doubling in size every 6 months. What can other high-tech knowledge-intensive start-ups learn from paperbackswap.com and its experience with the VOC? Many high-tech knowledge-intensive entrepreneurial firms tend to focus on their technological capabilities and to develop products that are typically taken to the market using a ‘push’ strategy. In doing so, the firm and its downstream value-chain members push their technology into the marketplace with scarcely a thought of the consumer until after the product is in the hands of the user (Workman, 1994). The need to bring the consumer’s voice into the start-up firm has seldom been discussed. Although some studies have examined the general construct of market orientation (Narver & Slater, 1990; Kohli & Jaworski, 1990) and related this to firm performance, a focus on the market is not necessarily synonymous with the VOC. Many firms, especially upstream members of a value chain, tend to view their customers as those firms to whom they sell their products. This perspective relies on value-chain intermediaries to act as ‘interpreters’ of the desires and needs of the enduser. A true VOC orientation involves integrating a consumer orientation throughout the firm (regardless of the firm’s position in the value chain). Innovation

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should be viewed as a continuous process that operated in response to emerging consumer needs so that the firm leads rather than follows the industry (e.g. Sheth, Sisodia, & Sharma, 2000). High-tech knowledge-intensive entrepreneurial firms who listen to the VOC throughout the start-up process should be more successful since they are more able to (1) understand how their technical capabilities translate into consumer benefits, (2) develop products that reflect this understanding and (3) better align their value chains to deliver these benefits. This chapter explores the role of the VOC in the start-up process for high-tech knowledge-intensive firms. Specifically, we describe how high-tech start-up firms have integrated the VOC throughout the start-up process of opportunity recognition, preparation for exploitation and opportunity exploitation. First, we will provide a review of the literature VOC and knowledge-intensive entrepreneurship. Then, we highlight different techniques and tools for capturing the VOC across the three stages of the entrepreneurial process. Specifically, we focus on how start-ups with limited experience and resources are able to integrate the VOC into the firm’s systems and processes and to thereby develop more effective product offerings. Finally, we propose a research agenda and offer some practical suggestions for start-up firms.

Literature Review Voice-of-the-Consumer The VOC can be a unique resource for high-tech knowledge-intensive firms that generally tend to be technology oriented and not consumer oriented (Miles & Darroch, 2006). While such firms often have very sophisticated understanding of their technological capabilities, these tend to be understood as attributes of actual or potential products. Instead they need to be understood in terms of the benefits that these attributes can deliver to users. These are not always apparent and it is here that an active programme for assessing the VOC can have a critical competitive advantage. In providing a means of connecting product features and attributes to user benefits, the VOC brings a different kind of knowledge into the firm that other firms may not have, and may not be able to imitate. Thus, VOC can be an important area of resource-based advantage (Barney, 1991). A large body of research supports the need to have unique resources as critical to a firm’s success — particularly for start-ups (Florin, Lubatkin, & Schulze, 2003; Yli-Renko, Autio, & Sapienza, 2001; Tsai & Ghoshal, 1998). From a resource-based view of the firm, if the firm can develop resources like the VOC that are valuable, rare, inimitable and nonsubstitutable, then these could lead to a sustainable competitive advantage (Barney, 1991; Conner, 1991). As noted by Morris, Schindehutte, and LaForge (2002), a consumer orientation in an entrepreneurial context should involve marketing efforts that emphasize three dimensions: customer equity, visceral relationships and emotional experience. Customer equity reflects the firm’s attitude towards the consumer and refers to the

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view that the primary value of a customer1 to the firm is across its lifetime, not situated in a single transaction. A customer equity perspective requires that the firm develop a knowledge base of changing consumer preferences, which helps the firm to anticipate and respond to changes in its current customer base and potentially to expand to new consumer segments. Visceral relationships reflect the depth of connection, at a fundamental level of identity, between the firm and the customer (e.g. many users have a strong personal bond with myspace.com and the online community it serves). A hallmark of a strong visceral relationship is that it is highly interactive. The final dimension is the nature and intensity of the emotional experience (see also Fournier, 1998 for a discussion of the quality of emotional experience and consumer bonding with brands). The firm and the customer have a deeply felt sense of purpose and conviction, reflecting a different level of commitment and resulting in a sense of authenticity that underlies the customer experience (e.g. Harley–Davidson; Fournier, Sensiper, McAlexander, & Schouten, 2001). While this is important in conceptualizing the customer–firm relationship, it leaves open the following questions: (1) What kind of insight into consumer behaviour is needed at which stage of entrepreneurial development? (2) What methods are best suited to developing these insights? (3) What benefits accrue to firms that successfully integrate the VOC into their innovation processes?

The Entrepreneurial Process and VOC The start-up process for high-tech knowledge-intensive firms has received considerable attention from researchers in the field of marketing, strategic management and entrepreneurship (e.g. Oviatt & McDougall, 1995; Knight & Cavusgil, 1996; Harveston, 2000; Saarenketo, 2002; Wakkee, 2004). Opportunities are considered knowledge-intensive when knowledge is the most important element in the development of the offering (Grant, 1996). The more knowledge-intensive a firm is, the more likely it is able to leverage its core technology to gain some form of competitive advantage (Dunning, 1988). Research has also shown that small firms can overcome the disadvantage of small size and liability of newness through their distinctive product or use of a unique core technology to produce the product (Cavusgil & Knight, 1997; Englis, Wakkee, & van der Sijde, 2007; Harveston, 2000). Typically the technological knowledge needed to create a high-tech venture is highly specialized. Using a model of pre-venture phase development, Van der Veen and Wakkee (2004) argue that entrepreneurship is the process of (1) recognizing opportunities, (2) preparing these for exploitation and (3) exploiting them in order to create value without regard of the resources they currently control. This is illustrated

1. Throughout, we make the following distinctions: consumer is used to refer to the end-user in the market whether or not this person or entity has purchased a product from the firm. Customer is used to refer to individuals or entities who have purchased products or services from the firm.

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VOC

VOC

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Figure 1: The entrepreneurial process. Source: Adapted from Van der Veen and Wakkee (2004). in Figure 1; our work adds as we extend previous research to focus on the role of the VOC in the entrepreneurial process. Although shown as sequentially organized, the three stages in the process (opportunity recognition, preparation and exploitation) are highly dynamic and iterative (Ropo & Hunt, 1995). The three stages may be overlapping, and feedback loops exist both within the three stages and between them. Thus, throughout the entrepreneurial process, changes may require actions or decisions to be rethought. Indeed, Bygrave and Hofer (1991) note that the entrepreneurial process is holistic and its course is influenced by a number of variables including the needs of the consumer. The next section will discuss each stage of the process and the potential impact of the VOC.

Opportunity Recognition: The Role of the VOC The first stage of the entrepreneurial process is opportunity recognition. Not surprisingly, when dealing with high-tech ventures, scientific discoveries are often the start-up point of the opportunity recognition process. These scientific discoveries only become innovations when they or their applications are introduced to the market and when these can result in the creation of profit or wealth (Guth & Ginsberg, 1990) or have an impact on the market (Wiklund, 1998). For technology firms, the opportunity recognition process most often takes the form of a new technology that is pushed into the marketplace. By matching resources and perceived needs of consumers, the entrepreneur develops an initial idea into a viable business opportunity (Long & McMullan, 1984; Bhave, 1994; Puhakka, 2002). However, many entrepreneurs guess if their product/service will meet the needs of customers — as Bobby Swarthout did with his original textbook swapping business. Bringing the VOC into the opportunity recognition phase of the entrepreneurial process is essential to providing an answer to the question of whether or not an opportunity exists. Understanding how the user of the technology will benefit from its use is critical to understanding the true value of the technology. This should be the starting point in developing a business model for commercializing the technology. By viewing the relationship with the customer as long term, it is an opportunity to start building

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the relationship. Thus, the firm will start building customer equity — the beginning of a long-term relationship, with the customer viewed as a firm asset. The VOC may also help to narrow the recognition process to more feasible ideas and decrease the amount of time before the entrepreneur can move to the next stage of the development. Through interaction with members of the value chain and listening to the voice of consumer, the entrepreneur analyses the competitive environment, refines the initial idea and develops a clear understanding of the value (if any) of the idea (Van der Veen & Wakkee, 2004). The decision to commercialize (or not) should flow from this process. In this sense, the relationship with the VOC is highly interactive where the firm identifies with consumers and their needs at a fundamental level. To develop the idea into a full-fledged business opportunity, the entrepreneur proactively searches for specific information and assesses required resources (and potential resource providers). Once the entrepreneur decides whether the opportunity is sufficiently developed, the venture will then move to the exploitation stage. Proposition 1a. During the opportunity recognition stage, high-tech start-ups that engage the VOC are more likely to view consumers as an asset and begin to build long-term relationships with consumers than high-tech firms that do not engage the VOC. Proposition 1b. During the opportunity recognition stage, high-tech start-ups that engage the VOC to help define and narrow the ‘gap’ in product/service offerings will adopt a ‘pull’ strategy, while high-tech firms that do not engage the VOC are more likely to ‘push’ strategy for the product/service.

Preparation for Exploitation: The Role of the VOC During the preparation stage, the business idea is translated through exchange with the market into a concrete business concept. Developing the necessary resource base and knowledge-related capabilities are the most important steps in this process (i.e. Brush, Greene, Hart, & Haller, 2001). Knowledge-related capabilities are produced through learning processes that span the organizations’ boundaries. They determine how the initial idea will be transformed into the offering that will be introduced in the market (Penrose, 1959). This contrasts with the opportunity recognition process. Here the idea was developed into a full-fledged opportunity through mental processing of the desirability and feasibility and some early contact with the VOC. However, in the preparation stage the entrepreneur starts collecting the venture’s resources in a much more systematic matter engaging many contacts outside the firm. Clearly, this process requires knowledge related to the technology, the market and the resource base (i.e. human, organizational and financial resources). Technological knowledge relates to the feasibility of the offering in terms of functionality and application. It also includes knowledge embedded in research facilities and

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knowledge embedded in human resources (Nonaka & Takeuchi, 1995). The market knowledge taps into VOC and beyond to legislative and cultural issues and the socioeconomic and technological landscape of the market (Van der Veen & Wakkee, 2004). Knowledge about building the resource base is needed to ensure that an organization can be created and move from the mind of the entrepreneur into a functioning firm. The voice of the customer may be the most important source of market knowledge for high-tech knowledge-intensive firms during this stage of development as the product offering will now take its final shape. Often the specific product that can be developed from a technological capability can take many forms. Consider, for example, the user interface that might be developed for an MP3 audio player; there are countless ways of providing control of and access to digitized music. A hallmark of Apple’s iPod interface is its ease of use, a feature yet to be successfully imitated by Apple’s competition and a clear competitive advantage (e.g. Jade & Marsal, 2005). This reflects a deep understanding of what young consumers would desire in an MP3 player. The result for Apple has been a ‘market pull’ where consumers demand not just portable digital music (easy to copy) but also the ease of use of the iPod interface (difficulty to duplicate). The powerful connection that can result from successful integration of the VOC during the opportunity recognition stage and throughout product development can dramatically increase the lifetime value of each customer. Today, there are numerous iPod versions available for customers and many iPod owners have also purchased video iPods. Similarly, many iPod owners are eagerly awaiting the release of Apple’s iPhone. The iPhone’s main technological advance is its user interface and not the core cell phone, camera or iPod technologies (New Media Age, 2007). Many products and services have a shortened ‘shelf life’ or a window of opportunity to reap profits from a given innovation (Workman, 1994). Thus, the firm will engage the VOC asset base and build customer equity to guide decisions and keep a close watch on changing consumer preferences. The firm may engage lead or heavy users in testing beta versions of the product or service before it enters the market to assess the viability of the idea. Thus, the flow of information is two-way with end-users actively engaged in a process of co-development and co-design of the product or service. This flow of information and the VOC view of the firm lead to a deeply felt sense of purpose and conviction on both sides that serves to differentiate the firm. Proposition 2a. During the exploitation preparation stage, high-tech firms that engage the VOC are more likely to focus on building customer equity (i.e. building databases to track customer preferences, etc.) than high-tech firms that do not engage the VOC. Proposition 2b. During the exploitation preparation stage, high-tech firms that engage the VOC are more likely to use co-development methods for their products and services, where end-users are actively engaged in the development process than high-tech firms that do not engage the VOC.

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Opportunity Exploitation: The Role of the VOC In the opportunity exploitation stage, the high-tech firm has now created marketable products or services and exchange processes between the firm and its customers become more important. For firms that have not engaged the VOC, this is the stage where they first begin to connect with the consumer. It is more likely that these firms may realize that an appropriate resource base to exploit the opportunity is not viable or that the product/service offering does not resonate with the consumer. Likewise, the demand for the product or service may be insufficient for profitable exploitation. In these cases, the business concept may be revised or even abandoned (Herron & Sapienza, 1992). For firms that engage the VOC early in the entrepreneurial process, it is likely that they will move forward having discovered problems through the VOC much earlier. As the product or service is readied for full market introduction, supporting marketing efforts are engaged (branding, packaging, advertising, training materials, etc.). A key goal of this stage of development is to evaluate the effectiveness of different elements of the communications mix in conveying appropriate information about what the product/technology can do. A critical issue to successful marketing introduction and customer satisfaction is that consumers’ expectations are in line with what the product/technology can deliver. The key question that VOC can help firms to address is: ‘to what extent does the product/technology provide benefits that match consumers’ ideal solution set?’ Most product offerings are ‘imperfect’ solutions to a consumer’s problem, and it is important for firms to understand this and calibrate product claims accordingly. For firms that move forward in the opportunity exploitation process, market exchange will increase to a higher level. As the market matures, firms will continue to add new or improved products and services to the market and/or improve internal operations. The opportunity exploitation process leads to value creation in terms of choice for customers, financial gain, knowledge, incremental innovation, etc. (Autio, Sapienza, & Almeida, 2000). As operational issues become critical and the focus shifts to maintenance of initial success, however, it becomes even more important for firms to listen to the VOC: consumer preferences are constantly changing. For firms that embraced the VOC early in the entrepreneurial process, the role of customer equity will continue to be monitored closely and the firm will continue to build dynamic knowledge of changing customer preferences. Traditional start-ups will tend to focus on the VOC as an expense rather than an investment (Workman, 1994). The VOC-led firm will focus on developing extensive customer interactions. These firms are likely to invest in technologies to reduce transactional costs such as databases, voice-response technologies and Internet-based communication tools (i.e. e-mail, blogs, etc.). Firms that listen to the VOC are more likely to integrate it throughout their value chain to facilitate product creation (e.g. Dell computers), pricing (e.g. priceline.com), distribution and fulfilment (e.g. online purchases delivered to the home via FedEx, UPS, DHL, etc.) and communication (e-mail systems).

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The relationship between the firm and the VOC will continue to be dyadic, and new product/service introductions may be based on engaging the customer at a deep level (e.g. Apple, MySpace, Volkswagon). As the product/service expands, the firm will continue to have a different level of commitment to the nature of the customer experience than firms which do not view VOC as an asset. Proposition 3a. During the opportunity exploitation stage, high-tech firms that do not engage the VOC are more likely to fail than high-tech firms that do engage the VOC. Proposition 3b. During the opportunity exploitation stage, high-tech firms that engage the VOC are more likely to invest in technologies and production process to integrate VOC throughout their value chain than high-tech firms that do not engage the VOC.

Proposition 3c. During the opportunity exploitation stage, high-tech firms that engage the VOC are likely to have a different level of commitment to the nature of the customer experience than high-tech firms that do not engage the VOC, leading to higher levels of performance. Table 1 summarizes the role of the VOC across the entrepreneurial process. Table 1: Summary of role of VOC in entrepreneurial process. Role of Voice-of-the-Consumer Opportunity recognition

 VOC defines ‘gap’ in product/service offerings  VOC narrows product/service focus

Preparation for exploitation

 VOC-engaged firm focuses on the needs, wants and resources of customers as the starting point of the business planning process  VOC involved in ‘co-creation’ — products are developed and improved in collaboration with key consumer groups  VOC involved in aspects of the design, production and consumption of the product or service

Opportunity exploitation

 Firm uses databases and ongoing analysis of customer needs to create better and more customized products to meet VOC  VOC integrated throughout firm value chain to facilitate product creation (e.g. Dell computers), pricing (e.g. priceline.com), distribution and fulfilment (e.g. online purchases delivered to the home via FedEx, UPS, DHL, etc.) and communication (e-mail systems)

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Conclusion In this chapter we examined how the role of the VOC can impact the start-up processes of high-tech knowledge-intensive firms. Specifically, we describe how high-tech start-up firms can integrate the VOC throughout the start-up process of opportunity recognition, preparation for exploitation and opportunity exploitation. There is a paucity of research that explores the entrepreneurial process and the VOC for start-ups — particularly high-tech knowledge-intensive start-ups. Most research focuses on large firms (i.e. Sheth et al., 2000) with few exceptions (cf. Morris et al., 2002). To address this gap in the literature, this chapter focused on how high-tech start-ups with limited experience and available resources can engage the VOC by viewing the customer as an asset with a lifetime relationship to the firm, creating a connection to the customer that is deep and enduring, and committing to creating a customer experience that reflects authenticity and the dyadic nature of the relationship. Our research focused on the engagement of the VOC across the start-up process. The main contribution of our study concerns our focus on the period leading up to the launch of the firm. Previous studies have usually examined established firms (i.e. Morris et al., 2002). Many high-tech start-ups operate in industries that are characterized by high levels of knowledge intensity and shorter life cycles. These firms both require and generate highly specialized market knowledge from consumers. Firms which engage the VOC are able to transform knowledge through different interactions and leverage this knowledge within the firm to recognize opportunities, create product and service offerings which meet the needs or are co-created and expand externally into the marketplace to gain a competitive advantage worldwide. Engaging the VOC affects firm activities in relation to opportunity recognition, preparation and exploitation a great deal (Deo & Blomstermo, 2000). To reflect the impact of the VOC, we formulated a series of propositions that form a framework that helps us understand the entrepreneurial process. Our research on the entrepreneurial start-up process has several implications. Like other new ventures, high-tech knowledge-intensive start-ups have limited time and resources. Therefore, they need to develop strategies that enable them to create, obtain and leverage VOC knowledge efficiently and effectively. Firms must be aware that during each of the three phases of the entrepreneurial start-up process, different knowledge needs exist that the VOC can help to answer. Future research is needed to examine the extent to which the propositions formulated above accurately describe the role of the VOC in the entrepreneurial process. These empirical investigations should include start-ups from different hightech knowledge-intensive industries. Other research could be conducted to extend this contribution outside the science-based (high-tech) sectors of industry.

References Autio, E., Sapienza, H. J., & Almeida, J. G. (2000). Effects of age at entry, knowledge intensity, and imitability on international growth. Academy of Management Journal, 43(5), 909–924.

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Barney, J. (1991). Firm resources and sustained competitive advantage. Journal of Management, 17(1), 99–120. Bhave, M. P. (1994). A process model of venture creation. Journal of Business Venturing, 9(3), 223–242. Brush, C. G., Greene, P. G., Hart, M. M., & Haller, H. S. (2001). From initial idea to unique advantage: The entrepreneurial challenge of constructing a resource base. Academy of Management Executive, 15(1), 64–78. Bygrave, W. D., & Hofer, C. W. (1991). Theorizing about entrepreneurship. Entrepreneurship Theory and Practice, 16, 13–22. Cavusgil, S. T., & Knight, G. A. (1997). Explaining an emerging phenomenon for international marketing: Global orientation and the born-global firm. Working Paper. East Lansing, MI: Michigan State University CIBER. Conner, K. (1991). A historical comparison of resource-based theory and five schools of thought within industrial organization economics: Do we have a new theory of the firm? Journal of Management, 17(1), 121–155. Deo Sharma, D., & Blomstermo, A. (2000). The internationalization process of born globals: A network view. International Business Review, 12(6), 739–753. Dunning, J. H. (1988). The eclectic paradigm of international production: A restatement and some possible extensions. Journal of International Business Studies, 19(1), 1–32. Englis, P. D., Wakkee, I. A. M., & van der Sijde, P. (2007). Knowledge and networks in the global startup process. International Journal of Knowledge Management Studies, 1(3/4), 497–514. Florin, J., Lubatkin, M., & Schulze, W. (2003). A social capital model of high growth ventures. Academy of Management Journal, 46(3), 374–384. Fournier, S. (1998). Consumers and their brands: Developing relationship theory in consumer research. Journal of Consumer Research, 24(March), 343–373. Fournier, S., Sensiper, S., McAlexander, J., & Schouten, J. (2001). Building brand community on the Harley–Davidson posse ride. Harvard Business School Case 9-501-009. Boston, MA: Harvard Business School Publishing. Grant, R. M. (1996). Toward a knowledge-based theory of the firm. Strategic Management Journal, 17, 109–122. Guth, W. D., & Ginsberg, A. (1990). Corporate entrepreneurship. Strategic Management Journal, 11, 5–15. Harveston, P. D. (2000). Synoptic versus incremental internationalization: An examination of born global and gradual globalizing firms. Unpublished doctoral dissertation, Memphis, TN: The University of Memphis. Herron, L., & Sapienza, H. J. (1992). The entrepreneur and the initiation of new venture launch activities. Entrepreneurship Theory and Practice, 17(1), 49–55. Jade, K., & Marsal, K. (2005). Apple fails to patent iPod interface. Apple Insider, August 9. Available at http://www.appleinsider.com/articles/05/08/09/applefails_to_patent_ipodinterface.html Knight, G. A., & Cavusgil, S. T. (1996). The born global firm: A challenge to traditional internationalization theory. In: S. T. Cavusgil & T. K. Madsen (Eds), Export internationalizing research — Enrichment and challenges. Advances in international marketing (pp. 11–26). New York: JAI Press. Kohli, A. K., & Jaworski, B. J. (1990). Market orientation: The construct, research propositions, and managerial implications. Journal of Marketing, 54(April), 1–18. Long, W., & McMullan, W. E. (1984). Mapping the new venture opportunity process. In: Frontiers of entrepreneurship research (pp. 567–590). Wellesley, MA: Babson College.

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Miles, M., & Darroch, J. (2006). Large firms, entrepreneurial marketing processes, and the cycle of competitive advantage. European Journal of Marketing, 40(5/6), 485–502. Morris, M. H., Schindehutte, M., & LaForge, R. W. (2002). Entrepreneurial marketing: A construct for integrating emerging entrepreneurship and marketing perspectives. Journal of Marketing Theory and Practice, 10, 1–18. Narver, J. C., & Slater, S. F. (1990). The effect of a market orientation on business profitability. Journal of Marketing, 54(October), 20–35. New Media Age. (2007). NMA futures — User interfaces: Farewell to the keyboard. New Media Age, March 22, p. S.17. Nonaka, I., & Takeuchi, H. (1995). The knowledge creating company. New York: Oxford University Press. Oviatt, B. M., & McDougall, P. P. (1995). Global start-ups: Entrepreneurs on a worldwide stage. Academy of Management Executive, 9(2), 30–43. Penrose, E. T. (1959). The theory of the growth of the firm. New York: Wiley. Puhakka, V. (2002). Entrepreneurial business opportunity recognition; relationships between intellectual and social capital, environmental dynamism, opportunity recognition behaviour, and performance. PhD thesis, University of Vaasa, Finland. Ropo, A., & Hunt, J. G. (1995). Entrepreneurial processes as virtuous and vicious spirals in a changing opportunity structure: A paradoxical perspective. Entrepreneurship Theory and Practice, 19(3), 91–111. Saarenketo, S. (2002). Born globals — Internationalization of small and medium-sized knowledge-intensive firms. Doctoral dissertation, Lappeenranta University of Technology, Finland. Sheth, J. N., Sisodia, R. S., & Sharma, A. (2000). The antecedents and consequences of customer-centric marketing. Journal of Academy of Marketing Science, 28(1), 55–66. Tsai, W., & Ghoshal, S. (1998). Social capital and value creation: The role of intrafirm networks. Academy of Management Journal, 41(4), 464–477. Van der Veen, M., & Wakkee, I. A. M. (2004). Understanding entrepreneurship. In: D. S. Watkins (Ed.), Annual review of progress in entrepreneurship research: Volume 2, 2002–2003 (pp. 114–152). Brussels: European Foundation for Management Development. Wakkee, I. (2004). Starting global, an entrepreneurship-in-networks approach. Doctoral dissertation, NIKOS, University of Twente, The Netherlands. Wiklund, W. W. J. (1998). Small firm growth and performance: Entrepreneurship and beyond. Doctoral dissertation, Jo¨nko¨ping International Business School, Jo¨nko¨ping. Workman, J. P., Jr. (1994). Marketing’s limited role in new product development in one computer systems firm. Journal of Marketing Research, 30(4), 405–421. Yli-Renko, H., Autio, E., & Sapienza, H. (2001). Social capital, knowledge acquisition, and knowledge exploitation in young technology-based firms. Strategic Management Journal, 22(6/7), 587–614.

Chapter 11

Going Public: A Growth Opportunity for ‘Research-Intensive’ Companies The El.En. Group Case Antonio Corvino, Giulia Romano and Ettore Spadafora

Theoretical Background An Outline of Corporate Strategy and Management Innovation The success of a firm is usually characterized by a constant re-thinking of its strategic model. Considerable entrepreneurial tension is involved in achieving competitive excellence, and the achievement of a right balance between the different elements that form a corporate strategy (e.g. economic perspective and social acceptability) (Coda, 1988). In particular, innovative companies must be driven by a strategic approach that is focused on effective investments and a continuous learning (Coda, 1988; Bertini, 1991; Bianchi Martini, 2001). Thus, for these types of firms, the availability of financial resources, with which to support the company’s strategic model, is essential. Indeed, on the one hand, the company’s strategic model ensures competitive advantage, while, on the other hand, corporate finance is crucial in order to fund the company’s distinctive competences (Kay, 1993; Prahalad & Hamel, 1990). When adopting a strategic perspective, in ‘research-intensive’ sectors, the business risk is considerable, and successful distinctive competences can be applied to the production of goods in other related sectors. As a consequence, companies often implement a diversification strategy in order to be successful in the long term. This strategy often concerns value chain sharing among these related businesses with which the company operates (Ramanujam & Varadarajan, 1989; Fuller & Pitt, 1995). In particular, a diversification strategy might take advantage of synergies that result from sharing

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distribution networks, R&D results, post-sale services and so on (Rappaport, 1986). Such diversifications can cause not only smaller production costs or greater revenues, but also substantial coordination costs (Porter, 1987; Chatterjee & Wernerfelt, 1991). In addition, a company’s size is a key factor for determining competitiveness in ‘research-intensive’ sectors, because markets for these companies are usually worldwide. Thus, through a diversification strategy, a parent company could create several strategic subsidiary business units, each one focused on a particular product or market, or alternatively, it could establish a corporate group, in order to increase its presence in other ‘competitive arenas’. The controlled companies could also benefit from some smaller costs or greater revenues, because of the presence of their equity-based relationships. These benefits, such as ‘parenting advantage’ (Campbell, Goold, & Alexander, 1995), are well known. Nevertheless, besides the creation of ‘parenting advantage’, the top management should constantly monitor and improve such advantages. In particular, innovation is a powerful means through which firms effectively can pursue long-lasting advantages. From a strategic perspective, innovation takes on an entrepreneurial meaning by providing a new way of competing in the sector in which a firm operates (Markides, 1997). In other words, innovation may be viewed as a means by which a firm does something different from its rivals (Drucker, 1985). However, in addition to strategic innovation, an important role can be played by management innovation. New approaches to management, which distinguish the firm from its competitors, can deliver a sustainable competitive advantage. In particular, the creation of a competitive advantage depends on one or more of the following conditions (Hamel, 2006): 1. a challenge launched to the generally accepted management norms of the sector; 2. the systematic nature of the innovation in the firm; 3. a long-standing programme of management innovation in the firm.

Access Issue for SME Innovative Companies The access to financial resources is a big issue for small companies. A lack of capital is frequently due to internal obstacles (e.g. fear of dilution of family power and, consequently, of company identity loss and information asymmetries between inside and outside shareholders) and external financial market features (e.g. low trust of SME, few institutional investors that seek to invest in SME). In particular, small growing firms have, from a financial point of view, some ‘prominent features’ (Cornell & Shapiro, 1988). On the one hand, they have a large ‘appetite for cash’ in order to attempt growth through the exploitation of risky opportunities that occur. On the other hand, they have difficulties in formulating competent financial plans that adequately sell their growth options. The market has therefore many difficulties in evaluating such plans since frequently there are no obvious benchmarks, and there is more uncertainty about future prospects of a new

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innovative company than a more mature firm. This difficulty in valuing growth potential intensifies the ‘credibility problem’ and increases the potential for conflict between managers, investors and non-investor stakeholders (Cornell & Shapiro, 1988). According to the pecking order theory (Narayanan, 1988; Myers & Majluf, 1984), a company should consider external capital investment only if there is no other way in which to finance growth. Information asymmetries often lead companies to prefer self-financing and bank debt to equity financing (in particular by venture capitalists or by going public). While, in general, investors are less informed than the investment-seeking companies, that is, seeking to go public, in particular, innovative companies with a pioneering business technology have to face a greater credibility problem during the ‘going public’ phase. As a matter of fact, according to Maksimovic and Pichler (2001, p. 459), ‘a pioneering firm that invests early may gain an advantage in the product market. However, the firm faces the risk that it does not have the winning technology and may be subsequently forced out by rivals who turn out to have a better technology’. Market evidence shows that equity funding is an exception rather than the rule in funding small firms’ growth. In particular, in Italy, the stock market traditionally has had a limited role in corporate funding (Pagano, Panetta, & Zingales, 1998). However, recent research has shown that there is an increasing number of Italian companies that currently could be listed on the stock exchange (Pellizzoni, 2002; Franzosi & Pellizzoni, 2003). As an alternative to going public, an owner can sell equity to a large external shareholder, such as a venture capital fund (Chemmanur & Fulghieri, 1999). However, in these cases the owner may meet both an over-monitoring risk (Pagano & Ro¨ell, 1998) and a need to find an exit, in order to liquidate a venture capital stake in the near to medium term (Black & Gilson, 1998). In addition to the cost, another factor that influences the choice of corporate funding in Italian companies is ‘political’ in nature, that is, an unwillingness to accept a loss of corporate control (Melis, 2000), although in recent years, Italian entrepreneurs have started to change their attitude towards the stock markets. To help innovative fast-growing SMEs to finance their growth, as happened in other European countries (Susi, 2002), in Italy, a capital market especially for these firms (the Nuovo Mercato) was created in 1999. This step facilitated better access to capital for a higher number of new ventures. As said by Ravasi and Marchisio, ‘the positive experience of some ‘‘pioneers’’ has helped to overcome the widespread mistrust of entrepreneurs and small-business owners and triggered an imitation effect that has brought an increasing number of companies to open their capital to the financial markets’ (2003, p. 383). Chemmanur and Fulghieri (1999) have found that companies go public more frequently in periods when stocks of companies operating in the same industry are overvalued (i.e. a high market-to-book ratio), in order to catch a ‘window of opportunity’. These periods are also known as ‘hot market periods’ (Ibbotson & Jaffe, 1975; Ritter, 1984). Thus, according to Ravasi and Marchisio (2003) in the

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Italian context, and to Corvin and Harris (2001) with reference to the United States, smaller and riskier firms are more likely to list on stock markets especially dedicated to innovative growing companies where many of their industry peers are listed. Pagano et al. (1998, p. 41) have highlighted that ‘a high market-to-book ratio may alternatively indicate that rational investors place a high valuation on the future growth opportunities in the industry. If these growth opportunities require large investments, companies will be induced to go public in order to raise the necessary funding’. However, these authors believe that in the Italian case for the period 1982– 1992, companies ‘do not go public to finance subsequent investment and growth, but rather to rebalance their accounts’ (Pagano et al., 1998, p. 61). Therefore, Italian companies, on average, seem to have not used the stock market to finance investments in core activities. Similar results are found for Sweden and Spain (Rydqvist & Ho¨gholm, 1995; Planell, 1995). On the contrary and more recently, Kim and Weisbach (2005) found that firms around the world use equity markets to raise capital for investment. In Italy, as in many other countries, at the end of 1990s the ‘new economic boom’ generated a ‘hot market period’ and induced, thanks to a greater credibility problem, many innovative companies to go public. From 1999 to 2004, 45 companies were listed on the New Market, which comprised more than 15% of all the companies that were listed on the Milan Stock Exchange in 2001 (Table 1). At the moment, only 35 of these companies remain listed, while 6 of them were delisted due to failure or liquidation. As summarized in Pagano et al. (1998), many studies analyse the main costs and benefits of the decision to go public. These models show empirical predictions on the variables affecting the probability of an initial public offering (IPO). Some of them predict that smaller, younger or high-tech companies are less likely to go public because of the possibility of rejection and for moral hazard (Leland & Pyle, 1977; Chemmanur & Fulghieri, 1995), considerable fixed direct costs, administrative expenses and fees (Ritter, 1987) and a loss of confidentiality on a companies’ competitive advantage (Campbell, 1979; Yosha, 1995).

Table 1: Companies listed on Nuovo Mercato and on Milan Stock Exchange as a whole from 1999 to 2004. Year

Listed Companies (Nuovo Mercato)

Listed Companies (Milan Stock Exchange)

Nuovo Mercato on Milan Stock Exchange (%)

1999 2000 2001 2002 2003 2004

6 40 45 45 43 40

270 295 294 295 279 278

2.22 13.56 15.31 15.25 15.41 14.39

Source: Borsa Italiana.

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On the contrary, other studies have argued that smaller companies seeking substantial investment are more likely to go public because of stock market monitoring (Holmstro¨m & Tirole, 1993; Pagano & Ro¨ell, 1998) and the possibility of accessing an alternative source of finance to obtain greater bargaining power with banks (Krips Newman, 1985; Rajan, 1992). Moreover, recent researches show that the benefits of IPOs are broader and richer than commonly thought. According to Ravasi and Marchisio (2003), besides the automatic inflow of capital, there are other benefits, such as an improved visibility, credibility, prestige and trustworthiness, and an increase in the number of strategic opportunities that the company can select from. They affirm that ‘going public may increase the number of strategic opportunities that the company can select from, as it opens up a broader range of possibilities for establishing and reinforcing partnerships and alliances’ (2003, p. 392).

Research Goals and Methodology This chapter aims to identify the conditions that can support the going public decision of an innovative SME, which has the aim of using an IPO to finance growth. In other words, we wonder what are the circumstances which make going public a growth opportunity for a research-intensive company. We explore these issues with the help of El.En. Group, a research-intensive Italian organization, active in the design and production of high-tech laser sources and systems for medical, industrial, aesthetic, scientific and cultural heritage conservation applications. The El.En. Group represents an interesting case study for investigation because of its strategic model that includes also the going public option. El.En. was founded as a small innovative company, and its financial strategy was, since the outset, uncommon in Italy. Following Eisenhardt’s (1989) suggestions, we combined different multiple data collection methods. In particular, we adopted two main collection methods: analysis of archival sources and in-depth interviews. We examined financial statements, articles about the El.En. Group published in newspapers and magazines, financial analysts’ reports, the IPO informative prospectus and so on. We then conducted in-depth interviews with people who had participated in the listing process. In particular, we interviewed El.En.’s CEO (Mr. Andrea Cangioli), the El.En. founder and Scientific Committee President (Prof. Leonardo Masotti) and the Scientific Committee Secretary (Mr. Stefano Frosini). The interviews were conducted by a team comprised of at least two interviewers since team interviews allowed us complementary insights (Eisenhardt, 1989). According to Ravasi and Marchisio (2003), our tentative reconstruction of the case was later submitted to our interviewees, in order to ensure reliability and to refine our emerging framework. We adopted an iterative process with a certain degree of overlap, between data analysis and collection (Glaser & Strauss, 1967; Eisenhardt, 1989). For instance, although we tried to analyse most documents before interviews, some relevant archival sources were brought to our attention during the interviews. This approach allowed us not only to compare different sources, but also to test and refine our conceptual framework.

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The El.En. Case Study An Overview of the Firm El.En. was founded in 1981 from an idea of a university professor (Leonardo Masotti, professor of electronic engineering at the University of Florence) and one of his students (Gabriele Clementi, the current president) as a small ‘research-intensive’ company. The company’s strategic model has been based, since its inception, on product innovation through the application of highly skilled human resources. After creating its first medical laser system in 1983, the company has developed its technological know-how over subsequent years. El.En. produces laser systems designed and created for application in various sectors; in particular, it designs, produces and trades the following products on a worldwide basis:  medical laser equipment used in dermatology, surgery, aesthetics, physiotherapy, dentistry and gynaecology;  industrial laser systems for applications ranging from the cutting, marking and welding of metals, wood, plastics and glass to the decorating of leather and fabric and the conservative restoration of works of art. Starting from 1989, El.En. developed its diversified production capabilities, while expanding its capacity. The development of new business activities was accomplished through both the acquisition and establishment of companies focused on specific business areas. By going public in 2000, El.En. obtained significant financial resources, thus allowing the company to increase its size, invest in R&D to develop new laser applications and strengthen its presence in new markets. In April 2002, the Group secured its own niche in the field of medical laser devices with the acquisition of Cynosure, one of the most important American companies in the sector. The next year, El.En. took over another American company, Lasercut, specializing in the production of industrial laser devices for cutting die boards and metals. In addition, in May 2003, the Group acquired Asclepion, the dermatological business unit of the Carl Zeiss Meditec in Germany. Today, El.En. Group is the leader in Europe and one of the most important international players in the production and trading of laser for medical and industrial applications. It produces optical equipment and assembles the final products. Moreover, it offers to its customers after-sale assistance and the sale of spare parts. The El.En. Group’s production process is a particularly interesting case. The high value-added and technology-intensive activities (such as the production of optical cavities for laser sources, the manipulation mechanical systems of the light bundle, the management software of the laser system and the testing) are carried out ‘in house’. These production activities represent a fundamental source of El.En. Group’s competitive advantage. Consequently, the activities of the researchers of the four research centres of the Group, as well as the annual investments in R&D, are exclusively focused on the identification of new development opportunities for their

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high value-added activities. Conversely, low value-added activities (such as the wiring and the mechanical assembly) are outsourced to local suppliers. Therefore, each of these companies originates a value-based network, because some activities of the value chain are carried out by other independent companies. One of the El.En.’s strengths is its worldwide presence. After recent acquisitions, the size of the Italian market has decreased, with a strong growth of sales abroad and in particular in the US market. An important role in such a growth has been played by the trading network, which is the result of acquisitions or strategic alliances with traders located in El.En. main markets. El.En. acquired directly local traders to reduce the emergent transaction costs of the supplier–customer relationship (Williamson, 1975, 1985). El.En S.p.a. (the Group holding) produces and sells laser sources and laser systems (both medical and industrial). Further, it supplies post-sale services based on specific spare parts. As a consequence of maintaining a post-sales structure, some El.En Group’s companies can benefit from a reduction in differentiation costs. Moreover, they can benefit from lower financial costs and greater bargaining power with financiers, due to the centralized financial function (Ansoff, 1965). The key aspects of the El.En Group’s strategic model are the following: (a) development of its offer through new products and services (e.g. new instruments for the physiotherapy or cultural heritage conservation applications); (b) acquisitions and alliances aimed to strengthen its competences and market position; (c) an effective sales network, due to investments in marketing (e.g. advertising, fairs, sponsorships); (d) a human resources development process, by means of the continuous training of employees and the hiring of specialized human resources; (e) adoption of incentive systems, in order to align employees’ interests to those of the Group; (f) R&D investments to support process and product innovation. With regard to innovations, and especially to management innovations, top managers took some decisions, which have allowed the Group to be, over the years, truly different from their competitors. In particular, in El.En., at least two management breakthroughs can be identified. The first management innovation was regarding the organizational structure at corporate level. El.En. adopted a unique organization model: centralization of a crucial activity (namely R&D), which was carried out by the four manufacturing firms of the Group. These firms were characterized by a high degree of autonomy and were in competition with one another, in terms of generation of research ideas and development of profitable products. As a result, in the Group there was the simultaneous presence of four ‘entrepreneurial souls’. The underlying motivation behind that choice was the pursuit of a wide range of product lines, which is viewed as crucial, especially in markets such as the United States. The importance of increasing the number of product lines is confirmed, for example, by the four small distribution networks of El.En. Group in countries like Germany, which are in charge of selling different products with different brands. Consequently, the economies of scale were not exploited, as well as the economies of scope. Multinational groups with a number of business units generally centralize several activities (e.g. accounting, public relations, legal services). In the high-tech

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sectors, large companies grasp the economic advantages deriving from centralized research laboratories, whose results are useful for many business units (Grant, 2006). Indeed, the American competitors of El.En. (co-leaders with it in the laser system business) moved in that direction. The lack of a group culture confirms fostering the development of ‘independent souls’ in the Group. An organizational issue strictly linked to the adopted multicentrality concerns the coordination between those ‘souls’ that do not go along the same entrepreneurial path. The coordination in El.En. is achieved by a complex mechanism of mediation, managed at corporate level (‘actions and reactions’, using the words of the CFO of the Group), and not, as it happens in several multinational groups, by a set of specific procedures. The second management innovation has a multidisciplinary approach to business activities, and, related to this, the search for and the merger of a wide set of different high-level competencies. This approach allows El.En. to carry out all the value-added activities that are fundamental for the final quality of the product. Differently, El.En. Group competitors have focused on few core competencies; as a consequence, they concentrate their efforts on few value-added activities, outsourcing the others.

Going Public to Finance Growth Strategies El.En. was founded as a small ‘research-intensive’ company to transform the research ideas and results of Prof. Masotti and Mr Clementi into products. Initially, it was a ‘societa` in nome collettivo’ (partnership) with two charter members: Mr Clementi, the current president, and Mrs Bazzocchi, Prof. Masotti’s wife. To set up the company, the partners needed a significant inflow of cash, which was obtained by taking a bank loan. However, since its origin, El.En. was characterized by a broad ‘opening up’ of the equity capital since its founders thought that innovative companies needed financial resources to sustain innovation and to develop innovative products. Thus, they allowed access to the company’s risk capital minority partners. As a matter of fact, in 1989 El.En. was converted into a ‘societa` a responsabilita` limitata’ (a limited liability company). Until 1992, the minority shareholders held about 10% of El.En. capital. After 1992, following acquisitions, El.En. looked for a new shareholder. Consequently, Andrea Cangioli, the current CEO, became a shareholder of El.En. holding when he acquired about 33% of its equity. Over about 10 years the company continuously increased its size both through acquisitions in Italy and abroad and through internal growth. In April 1996, El.En. was converted into a ‘societa` per azioni’ (i.e. joint stock company). In May 2000, Mr Clementi, one of El.En. founders, during the ‘new economy’ boom, when considering how to mitigate the low credibility problem of high-tech SMEs, had the idea of going public by listing El.En. on ‘Nuovo Mercato’, that had been created the previous year. The El.En. management preferred going public, instead of raising equity privately from a venture capital fund, not only to exploit ‘hot market’ opportunities, but also

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in order to avoid the over-monitoring risk, and to avoid the typical short-termist view that venture capital funds usually adopt. In May 2000, Banca Toscana, a regional Italian bank, became one of the El.En. Group’s shareholders, with about 14% of El.En. Group’s capital. Before and after going public, El.En. Group’s capital was held by eight significant shareholders (each one holding more than 2% of share capital). In particular, after the listing process, Banca Toscana maintained more than 10% of El.En. share capital and has remained as a shareholder since 2006. Through going public the El.En. Group aimed to consolidate its position in the market, and to expand itself in areas where it had an insufficient presence (such as the US market), by means of strengthening its commercial structure and distribution network. The El.En. Group was listed on Nuovo Mercato in December 2000. Part of the offer emanated from Banca Toscana that sold part of the shares (i.e. 26% of the shares offered), while the rest (i.e. 74%) came from El.En. new shares issue. By going public El.En. raised h25.9 million of cash, minus direct listing expenses of around 6% of the capital raised. With the funds raised from the IPO El.En. Group acquired Cynosure, one of its competitors and one of the most important American companies in the laser sector. Later, El.En. acquired further companies abroad, in the United States, Germany and Japan. As stated by the management of El.En., being listed was very expensive. In addition to the direct costs, there were many others costs due, for example, to the top management being involved in ‘road shows’ and other time-consuming procedures involving, for example, reporting and information requirements. Even though the management believed that company stocks were undervalued, in December 2005, the Group listed Cynosure on the NASDAQ Exchange, confirming their trust in the going public process. The listing of Cynosure allowed El.En. Group to obtain additional financial resources with which to develop their American business, and to improve the Group’s ability to make new investments. At the end of 2006, El.En. Group had more than 400 employees throughout the world (Table 2).

Table 2: A summary of consolidated financial data of El.En. Group.

Revenues EBITDA Net income Total assets Total equity Number of employees

2006

2005

2004

2003

2002

2001

2000

154.372 10.676 1.638 169.841 119.732 418

118.343 14.888 24.704 168.872 124.123 548

94.519 9.858 5.441 89.974 52.261 431

68.195 4.970 599 75.221 49.949 347

54.138 6.855 2.863 76.674 51.767 299

27.844 3.809 2.634 59.662 46.757 162

25.955 7.188 3.529 57.959 45.562 123

Source: El.En., Consolidated Report, 2000–2006 (h million).

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Discussion The El.En. case suggests that going public could be a relevant opportunity for a hightechnology, rapidly expanding, small company that needs to obtain liquidity, while improving its visibility and image. The case shows, however, that the conditions which make going public a growth opportunity for a research-intensive company are informed by the following criteria: 1. credibility problems; 2. a fear of a change in the company control; 3. the aims that lead to the going public choice. Although many high-tech companies throughout the world did not live through the ‘new economy’ crisis in the early 2000s, thanks to the ‘new economy boom’ and the consequent establishment of financial markets dedicated to SMEs, many small innovative firms reduced their credibility problem, and went public easily, by obtaining the needed financial resources. Thus, with reference to point 1, it is clear that the contribution of financial markets especially dedicated to innovative SMEs and the presence of institutional investors willing to support and trust in fast-growing strategic model are essential to buttress credibility. With reference to point 2, since the success of an innovative SME depends necessarily on the exploitation of development opportunities, the fear of a change in company control often represents a great obstacle to the development of an SME. Innovative SMEs usually have many financial problems because their shareholders prefer to reduce growth possibility instead of opening their company’s equity up to external shareholders. For a ‘research-intensive’ company, finance is one of the most important factors that supports the company’s distinctive competences. Therefore, the availability of financial resources is a critical issue, because its acquisition allows competitive advantage. This case study shows that entrepreneurial initiative led the shareholders to an ‘opening up’ of the company to equity capital involvement. In fact, since setting up, the El.En. founders have welcomed new shareholders. This feature made El.En. a unique case among Italian firms. Finally, in relation to point 3, in many cases companies consider going public as a solution to their financial problems rather than for exploiting strategic opportunities. Therefore, in these cases, going public only can be an opportunity for the top management to finance, but not to develop, their company. Development implies the identification and implementation of a company’s strategic model that is able to deliver success in the long term. The El.En. Group case suggests that, referring to ‘research-intensive’ SMEs, success in the long term is due to a winning strategic model, together with an innovative finance strategy (which leads to going public on two stock exchanges). As Mr Cangioli stated, during the company’s growth, distinctive competences have been

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a very important strategic driver, thus enabling renewable competitive advantage, over their direct rivals in competitive arenas.

Conclusive Remarks The El.En. case suggests that going public could be an appropriate opportunity for a high-technology, rapidly expanding, small company that needs to obtain financial resources to support its growth strategies. However, this case shows that three conditions render going public a more viable growth opportunity for a researchintensive company. These conditions are related to the following aspects: a reduction of credibility problems, through investors willing to support successful SMEs and dedicated financial markets, a change in the minds of entrepreneurs that allow an increasing access of new shareholders and an appropriate strategic model that include the going public decision to support growth strategies and the innovation processes.

Acknowledgements Although this chapter is the outcome of joint work of the three authors, Antonio Corvino wrote sections ‘‘An Outline of Corporate Strategy and Management Innovation’’ and ‘‘Discussion’’; Giulia Romano wrote sections ‘‘Access Issue for SME Innovative Companies’’, ‘‘Research Goals and Methodology,’’ and ‘‘Going Public to Finance Growth Strategies’’; and Ettore Spadafora wrote sections ‘‘An Overview of the Firm’’ and ‘‘Conclusive Remarks.’’

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Chapter 12

What are High-Technology Firms and What Drives Their Performance? Martin A. Sims and Nicholas O’Regan

Introduction Technology is defined by Krajewski and Ritzman (2000, p. 17) as ‘the know-how, physical things, and procedures used to produce products and services’. Over the past two decades, the development of high-technology-based firms has been actively encouraged by governments and development agencies (Westhead & Storey, 1994) as a source of competitive advantage. In many cases, small high-technology-based firms have effectively exploited market opportunities. This has been helped by the emergence of generic technologies, most notably information technology that is knowledge intensive rather than capital and labour intensive (Rothwell, 1994, p. 12). Such technologies have been effectively used to open up new market niches for small- and medium-sized firms (SMEs). Accordingly, high-technology firms have become well established as sources of both competitiveness and employment creation (Oakey, 1991). From an academic perspective, the trend in the establishment of high-technology firms has been paralleled by the number of empirical studies investigating their success in aspects such as innovation potential (Acs & Audretsch, 1987; Monck, Porter, Quintas, Storey, & Wynarczyk, 1988) and growth potential (Phillips, Kirchhoff, & Brown, 1991). However, to date there is no commonly accepted definition of a high-technology firm (Goss & Vozikis, 1994). Instead, all firms are classified at the industry level which tends to be all inclusive rather than firm specific. In other words, the overall industrial classification of an industrial sector, such as heavy engineering, might be perceived as low technology orientated whereas some firms within this sector may have leading edge high-technology products and/or processes. Accordingly, this study examines the appropriateness of existing industrial

New Technology Based Firms in the New Millennium, Volume VIII Edited by R. Oakey, A. Groen, G. Cook and P. van der Sijde r 2010 Emerald Group Publishing Limited. All rights reserved.

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classification methodologies and seeks to develop a ‘high-technology footprint’ underpinned by a number of input criteria. The chapter is structured as follows. First, we consider current methods of firm classification with reference to high-technology firms. Second, we examine hightechnology firms from an input perspective. Third, a brief description of agility is provided. Next, we identify ‘high-technology’ firms and consider a range of attributes as a surrogate measure for agility. Finally we compare the degree of agility in the derived high-technology sectors with that of the remaining sectors.

High-Technology Firms High-technology firms play an enormous role in the economic growth of many countries. This leads to the question — what is a high-technology firm? The standard industrial classification (SIC) provides an industrial classification code for all firms, both service and manufacturing. Arguably, the selection of high-technology-based firms using the SIC can be fraught with difficulties as the boundaries between classifications tend to be arbitrary, and few attempts have been made to update the classification to bring it into line with modern day business. For example, a perusal of the SIC categories suggests that categories such as ‘electro medical equipment’ are high technology in orientation whereas categories such as ‘Office machinery and supplies’ do not readily indicate the degree of high technology inherent in the companies under this heading. Accordingly, the identification of high-technology firms from existing SIC classification is fraught with difficulty. The more commonly accepted approach is to define high technology based on the degree of expenditure on R&D as a percentage of sales greater than 5% (Balkin, Markman, & Gomez-Mejia, 2000). This has gained currency as the accepted approach to identifying high-tech companies. Following further refinements, an ‘enhanced’ classification method emerged that takes into account the creativity and skills of the workforce and focussing on the levels of R&D expenditure rather than the results of that spending. This ‘enhanced’ definition places an unduly high emphasis on the use of R&D as the main driver of high technology and innovation (see Mowery & Rosenberg, 1989). This approach tends to focus on product innovation to the exclusion of process innovation. In addition, it is arguable whether the definition applies to small hightechnology-based firms that often lack a structured R&D approach. Other contributions to the literature contend that high-technology firms tend to have employees who are highly educated, have a large proportion of their assets tied up in intellectual human capital and do not have as much capital-intensive investment as traditional-type firms (Milkovich, Gerhart, & Hannon, 1991). Accordingly, the literature on the classification of ‘high-technology’ firms presents a mixed picture. In an effort to establish a working definition of high-technology firms, we focus on an input-based approach using the more commonly accepted

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surrogate measures of high technology: R&D, capabilities and innovation (see Jovanovic & MacDonald, 1994).

Developing an ‘Input’-Based High-Technology Footprint The extant literature sees creativity as the foundation of innovation and high technology (Scott & Bruce, 1994; Van de Ven, 1986). Amabile, Conti, Coon, Lazenby, and Herron (1996, p. 1154) contend that ‘all innovation begins with creative ideas y creativity by individuals and teams is a starting point for innovation; the first is a necessary but not sufficient condition for the second’. From the perspective of this chapter, we are interested in the use of creativity in the development of differentiated products. The literature is unambiguous in stating that differentiated products lead to high performance (Song & Montoya-Weiss, 2001), in particular by providing a competitive edge by meeting customer demands (Sethi, Smith, & Park, 2001; Song & Montoya-Weiss, 2001). Following from the above, we used four factors to capture the essence of high-technology firms from an input perspective: a. b. c. d.

degree of emphasis on and investment in R&D innovation creativity capabilities

Following the identification of high-technology firms based on the inputs approach outlined, we then sought to ascertain if the degree of agility in the derived high-technology sectors is higher than the degree of agility in the remaining sectors. The following sections will examine each of these factors in greater detail.

Degree of Emphasis on Research & Development One of the principal means of identifying high-technology firms is based on the degree of R&D activity measured in expenditure terms compared to sales levels (Parthasarthy & Hammond, 2002). The association between the degree of R&D expenditure and innovation is clearly shown in previous studies (see Deeds, 2001; Greve, 2003; Parthasarthy & Hammond, 2002). However, this presupposes that all innovation arises from formalised R&D systems, whereas arguably high levels of R&D expenditure do not always translate into new products. We derived the following research question: Do high-technology firms place a higher emphasis on research and development compared with low-technology firms? Each company’s commitment to R&D was established by calculating their expenditure as a proportion of total sales, and the relationship between R&D expenditure and the number of full time employees.

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Innovation Innovation and its importance is widely covered in the literature (Porter & Ketels, 2003; Deshpande´ & Farley, 1999) and is generally considered to be the driver of competitive advantage when effectively implemented (Ernst, 2002; Burgelman, Christensen, & Wheelwright, 2004; Miller & Morris, 1998) as well as the retention and/or gaining of competitive advantage (Hult, Hurley, & Knight, 2004; Hitt, Hoskisson, & Kim, 1997; Stuart, 2000; Edler, Fireder, & Reger, 2002). Others see innovation as a pivotal activity in the quest for competitive advantage for companies of all sizes (Sethi et al., 2001). A review of the literature indicates that there is no commonly accepted definition of innovation (Kim & Oh, 2002; Roehrich, 2004). Many studies look at innovation in terms of inputs such as expenditure on R&D (Cordero, 1990), while others see it as a continuous process involving various organisational functions and activities (Cormican & O’Sullivan, 2004, p. 820). A more focussed definition is propounded by Ahuja and Lampart (2001) as inventions that have been patented. Accordingly, innovation is generally accepted as the conversion of R&D activity into new products or processes. We derived the following research question: Do high-technology firms place a higher emphasis on innovation compared with lowtechnology firms? Respondents were asked to rate the importance of the following three practices/ tools to describe innovation: innovation as a competitive factor, innovation and organisational direction and being first to the market.

Creativity The stage preceding innovation involves the use of creativity to ‘spark’ the ideas for innovation (Amabile et al., 1996) and the subsequent development of new products/ product differentiation (Song & Montoya-Weiss, 2001). A review of the literature suggests that creativity is generally seen as the conceptualisation of new ideas by individuals or teams (Amabile, 1988). However, it must be stressed that there is no one accepted definition of creativity (Shalley, Gilson, & Blum, 2000). The capacity to innovate is a crucial activity in all firms (Zaltman, Duncan, & Holbek, 1973; Hurley & Hult, 1998). This is also known as absorptive capacity (Cohen & Levinthal, 1990) and refers to the ability to effectively adopt or implement new ideas, processes or products (Hurley & Hult, 1998). Arguably, manufacturing has changed dramatically and is no longer based on using standard equipment and techniques. This implies the need to adapt and to be creative in meeting external demands. Accordingly, we derived the following research question: Do high-technology firms place a higher emphasis on creativity compared with lowtechnology firms? Respondents were asked to rate the importance of the following three practices/ tools: the introduction of new products, the degree of staff creativity and the ability to customise products.

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Capabilities Capabilities are defined by Dosi, Nelson, and Winter (2002) as ‘the know-how that enables organisations to perform and extend their characteristic ‘‘output’’ actions’. Oakey and Mukhar (1999) contend that output or performance orientations are important determinants of high-technology firms. Adapting to operating environment conditions can include activities such as new or modified products and/or services as well as production processes (Eisenhardt & Martin, 2000). The literature suggests that to maintain competitive advantage, firms need to develop capabilities to improve the core business processes (Danneels, 2002; Eisenhardt & Martin, 2000; Helfat & Ruthbitschek, 2000; Winter, 2003; Zollo & Winter, 2002; Zott, 2003). For example, Zollo and Winter (2002, p. 340) see dynamic capabilities as ‘a learned and stable pattern of collective activity through which the organisation systematically generates and modifies its operating routines in pursuit of improved effectiveness’. On the other hand, Teece, Pisano, and Shuen (1997, p. 516) define a dynamic capability as the unique ability of the firm to ‘integrate, build and reconfigure internal and external competences to address rapidly changing environments’. On a broadly similar vein, Eisenhardt and Martin (2000, p. 1107) see dynamic capabilities as the ‘organisational and strategic routines by which firms achieve new resource configurations as markets emerge, collide, split, evolve, and die’. From the perspective of this chapter, capabilities are important as they relate closely with innovation. This means that capabilities need to be continuously under review. However, to date, there is a dearth of research focussing on innovation capability in SMEs. Accordingly, we derived the following research question: Do high-technology firms place a higher emphasis on capabilities compared with lowtechnology firms? Respondents were asked to rate the importance of the following two practices/ tools: staff competencies and the use of state-of-the-art technology.

Agility Reference is commonly made in the literature to the dynamic environment (D’Aveni, 1999) and the consequential increasing need for value chain reconfiguration to attain, regain or retain competitive advantage (Christopher & Towill, 2000). Organisational agility is arguably the most important means of attaining competitive advantage in today’s dynamic environment (Goldman & Nagel, 1993; Gunasekaran, 1998). But what is agility? The literature definitions centre on agility as the capability to both survive and enhance performance in a period of intense change (see Preiss et al., 1996). Yusuf, Sarhardi, and Gunasekaran (1999, p. 37) provide a comprehensive definition of agility as the ‘successful exploitation of competitive bases (speed, flexibility, innovation pro-activity, quality and profitability) through the integration of reconfigurable resources and best practices in a knowledge-rich environment to

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Table 1: Attributes of agility. Core Practices

Attributes

Environmental scanning

Frequency of management accounts production Prediction of future trends Minimising downtime Responsiveness of operations

Institutional positioning

Re-evaluation of decisions Flexibility of operations Speed of response Superior flexibility

Responding

Avoidance of problems Ability to customise on demand

provide customer-driven products and services in a fast changing market environment’. This led us to derive the following research question: Are high-technology firms more agile than other firms? The literature propounds a number of attributes of agility. For example, Gerwin (1993) suggests that flexibility is a key attribute while others focus on speed of adaptation to changing market conditions (Goldman & Nagel, 1993; Swink & Hegarty, 1998; Yusuf et al., 1999). However, Overby et al. (2006) see agility as much more than flexibility, and envision radical changes rather than simply being flexible in dealing with a given environmental situation. This implies that the following core practices are central to the concept of agility: environmental scanning (Prahalad & Hamel, 1990), institutional positioning (Yusuf et al., 1999; Goldman & Nagel, 1993) and responding to the market environment Huang (1999). We developed an agility footprint/score to measure a firm’s propensity to be agile, by gathering attitudinal data from 10 attributes depicted in Table 1 and mapping them to the three ‘core practices’.

Data Collection We used a self-reported postal survey to collect data for three reasons. First, to test the series of propositions advanced above, we required a large number of observations in our data set. We chose sectors that are perceived as being technology orientated such as electronics and IT/software development (Rothwell & Zegveld, 1982). Second, self-reporting was preferred to alternative methods because the overall length of the questionnaire and associated costs ruled out telephone and personal interviews respectively. Third, there is a strong prior support for using self-reporting in this type of research (Ramanujam & Venkatraman, 1987; Pearce & Robinson, 1987; McKiernan & Morris, 1994; Kargar & Parnell, 1996; Shrader, Chacko,

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Herrmann, & Mulford, 2004). Furthermore in organisational studies, surveys are the dominant tool for collecting data (Podsokoff & Organ, 1986). Cooper (1984) found that new product performance is largely driven by the strategic approach adopted by the top management of the organisation. We used managerial perceptions as the basis of the study, as they shape to a significant degree the strategic behaviour of the firm. This is consistent with Chattopadhyay, Glick, Miller, and Huber (1999) and Spanos and Lioukas (2001).

The Sample The initial sample for this study consisted of 1,000 randomly selected manufacturing SMEs operating in the United Kingdom’s fabrication and electronics sectors. The database proved less accurate than expected. After firms that did not match the selection criteria were deleted, the effective sample size was 702 firms. The sample selected comprised engineering and electronics firms. The reasons for focusing on the fabrication/electronics sectors follow. First, both sectors are economically and strategically important. Second, the already large and significant population of electronic/fabrication SMEs, 15,000 in total (DTI, 2000). Third, the difference between the product life cycles of the two sectors, a key contingency factor (Hofer, 1975). Fourth, changes in organisational categorisations and/or paradigms are often established using SMEs (Klepper, 1996). Our exploratory interviews with the Managing Directors of six firms indicated that firms from the electronics and engineering sectors could be further categorised into the following sub-sectors:      

Electronic production Mechanical engineering production Electrical engineering production IT/Software development Distribution/Service Other manufacturing

This study, therefore, uses these sub-sector categories. The sample was selected randomly according to sector and size band specifications using the European Commission’s EC/DTI’s definition of SMEs — a firm employing up to 250 people. In the absence of a uniformly accepted definition of SMEs, we have opted for the definition used in the official statistics of the EC, that is to say, the most broadly used measure of SME classification in the EC.

Responses We received 197 valid responses — a 27% response rate. This is relatively high as typical response rates for studies addressing strategic issues are 10–12%

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(Geletkanycz, 1997, p. 622; Koch & McGrath, 1996). Contact prior to the dispatch of the questionnaire and follow-up calls probably account for the high response. The potential impact of non-response bias was assessed using a T-test to compare the means for the sample of 26 CEOs who participated in the short telephone survey with the means for the main sample. The differences were statistically insignificant. We also used a T-test to examine the difference between early and late informants’ response to key questions. This provides an effective test for assessing non-response bias because late respondents are likely to respond in a manner similar to nonrespondents (Armstrong & Overton, 1977; Lambert & Harrington, 1990). Our extensive analysis suggests that non-response is not a serious problem and should not affect our conclusions.

Data Analysis The respondents to the survey instruments categorised their respective firms as belonging to one of the following sub-sectors: electronic production, mechanical engineering production, electrical engineering production, IT/software development, distribution/service and other manufacturing. The literature contends that R&D activity, innovation, creativity and capabilities are important drivers of performance in high-technology firms. In this regard, we sought to establish an objective ‘measure’ of these concepts that ultimately drives high-technology activity in companies. To this end a technology footprint was derived using multi-correlate ranking based on the following recognised drivers of high technology: 1. R&D activity — companies were ranked in terms of their R&D expenditure as a percentage of sales and expenditure per FTE. 2. Innovation — a combination of the following three measures was derived to create an objective measure of innovation: the degree of use and importance of (a) innovation as a competitive factor, (b) innovation and organisational direction and (c) being first to the market. 3. Creativity/Capabilities — a combination of (a) staff creativity, (b) staff competencies, (c) ability to customise on demand, (d) the introduction of new products and (e) the use of state-of-the-art technology. Each firm was awarded a ranking that reflected the two measures of R&D expenditure outlined above. The sub-sector average ranking was then calculated as depicted in Table 2. The same method was used to calculate the sector average ranking for both innovation and creativity/capabilities. A low ‘ranking’ average number indicates that firms in that sector were ranked ‘highest’ or with a 1, and the higher average ranking numbers means that firms in these sectors were more towards ‘lowest’. It can be seen, for example from Table 2 that the IT/software sector, with an average score of 78, was the sector with the highest R&D investment and the highest emphasis on innovation. IT/Software was ranked fourth in terms of creativity and capabilities. Thus, IT/software received a total ‘inputs ranking’ of 6.

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Table 2: Summary of technology footprint. Sector Electronics Mechanical Electrical IT/Software Distribution Other

Average R&D Score 132 164 133 78 178 177

(2) (4) (3) (1) (6) (5)

Average Innovation Score 263 337 267 217 320 326

(2) (6) (3) (1) (4) (5)

Average Creativity and Capabilities Score 286 300 268 290 336 278

(3) (5) (1) (4) (6) (2)

Total 7 15 7 6 16 12

Table 3: Correlation analysis — between high technology and its drivers for each sector. Sectors

Electronics Mechanical Electrical IT/Software Distribution Other Overall

Drivers R&D/ Innovation

Innovation/Creativity and Capabilities

R&D and Creativity/ Capabilities

N

0.4355 0.4101 0.5556 0.5075  0.0595 0.2966 0.4071

0.4996 0.5897 0.6632 0.7224 0.7285 0.6806 0.5889

0.5054 0.3182 0.0749 0.2133 0.1215 0.0840 0.2893

33 86 11 15 23 29 197

An analysis of Table 2 indicates that electronics, electrical and IT/software are the three industrial sectors with the highest level of drivers of high technology with a significant gap between them and the three remaining sectors. Having highlighted three ‘high-technology’ industrial sectors, consideration was given to the relationship between each of the drivers for each sector. The results are depicted in Table 3. An analysis of Table 3 indicates a strong correlation between innovation and creativity/capability. In all sectors, the innovation/creativity linkage is very strong (i.e. better than 99% confidence level in all cases). This is consistent with the contention by Amabile et al. (1996) that all innovation begins with creative ideas and creativity by individuals and teams is a starting point for innovation. The analysis also depicts a strong correlation between creativity and innovation for all firms in the sectors examined (0.5889) and between R&D and innovation (0.4071), whereas the correlation between R&D and creativity is less strong (0.2893). In the sectors focussing on manufacturing (i.e. all sectors with the exception of distribution), the

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Table 4: Positional ranking — showing examples of firms with highest and lowest technology ranking scores. Firm ‘A’

Firm ‘Z’

Input drivers R&D to sales R&D to full-time employees Innovation and competition Innovation and organisation First to market Staff creativity Staff competencies Customise products on demand Introduce new products State-of-the-art technology

4 4 1 1 1 1 28 1 47 1

110 17 185 192 192 187 175 188 189 172

Total score

89

1607

correlation between R&D expenditure and innovation is strong with electrical and IT/software demonstrating particularly strong linkages. In developing the ‘input technology footprint’ we ranked each of the firms in terms of the 10 variables contained within the 3 ‘technology drivers’ outlined above. The best score that a firm could achieve is 10 (where a firm is ranked first in each of the 10 areas). On the other hand, the least favourable score (where a firm achieved the least rank for each variable) is 1970 (where a firm is ranked 197th on all 10 times). Table 3 shows, by way of explanation, the positional ranking in each of the 10 areas for the ‘best’ firm (A) and the firm with the least technology ranking score (Z). Having ranked the sample by ‘technology footprint score’, the sector-based counts of firms in the upper and lower quartiles of the ranking are depicted in Table 4. Table 4 indicates that an ‘input technology measure’ has highlighted significant differences between the sectors in terms of their actual appearance in the upper and lower quartiles of the input technology ranking compared with the expected appearance. The percentage of IT/software firms in the upper quartile is significantly higher than might normally be expected. A similar under-representation in the lower quartile of the technology ranking can also be observed. Electronics and electrical production are both over-represented in the upper quartile compared with the expected distribution. The analysis indicates that almost half the firms represented in the upper quartile of the technology ranking is associated with three sectors (and derived from less than a third of the sample population). Both electronics production and IT/software show the largest differentials in terms of their over-representation in the upper quartile and under-representation in the lower quartile. Mechanical, distribution and other manufacturing are all under-represented in the upper quartile and over-represented in the lower quartile thus emphasising and underlining the ‘technology gap’ existing between industrial sectors. Having

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Table 5: The expected and observed percentages of each sector in the upper and lower quartiles ranking of the input technology footprint. Electronic Mechanical Production (%) (%) Expected Upper quartile Lower quartile

17 24 14

Electrical (%)

44 37 48

6 8 4

IT/Software Distribution Other (%) (%) (%) 7 16 4

11 6 14

15 9 16

Table 6: Sector agility and age averages.

Electronics engineering production (n ¼ 25) Electrical engineering production (n ¼ 9) IT/Software (n ¼ 13) Mechanical engineering production (n ¼ 62) Logistics/Service (n ¼ 16) Other manufacturing (n ¼ 24)

Average Company Agility Score

Average Company Age

844 791 772 812 811 814

22 19 12 37 20 35

established three high-technology sectors using an input-based approach, the next stage is to consider if the derived high-Technology firms are more agile than other firms? An ‘agility’ footprint score was established for each of the firms in the same way that the ‘input technology footprint’ was calculated (Table 5). In developing the ‘agility footprint score’ we ranked each of the firms in terms of the 10 variables that contribute to the 3 core-enabling elements for agility outlined above. Table 6 shows the sample of firms (149 of which provided sufficient information in all footprints) split according to their sector designation showing the average agility score for each sector and each sector’s average company age. The analysis of Table 6 indicates that three identified high-technology sectors (electronics, electrical engineering and IT/software) results in a correlation of 0.88 (n ¼ 3) (significant at 90% confidence level) between average sector company age and average sector company agility. This suggests that as high-technology firms mature, they achieve greater agility, arguably to meet the demands of the market environment. The average sector agility score of 844 associated with our ‘oldest’ hightechnology sector (electronics engineering) is the highest of all the sector averages. This leads us to conclude that the derived high-technology firms are more agile than other firms.

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Conclusion Given the inherent difficulties in identifying high-technology-orientated firms, we proposed a number of research questions based on input-type drivers of technology performance. These measures are supported by the extant literature and enable us to devise a framework model that is relevant from a practitioner perspective as well as theoretically underpinned from an empirical perspective. Our findings indicate that the high-technology sectors — electronics production, IT/software development and electrical production — place higher levels of emphasis on R&D, creativity and innovation compared with other firms. Our analysis also reveals that they are more profitable than other firms. From a practitioner and investor perspective, the findings provide information to more readily identify high-technology firms and further suggest characteristics that reflect a firm’s agility that, in turn, support enhanced performance. For example, investors might be interested to learn that the results of this study depict high-technology firms as more likely to belong to the electronics production sector, with profitability higher than average, and who display a number of agile characteristics. One of the main limitations of this study was the lack of an established definition of high-technology firms. Another limitation is that while some firms perceive themselves as low technology oriented, they may have critical processes that are consistent with the essence of high technology. In addition, the SIC codes tend to classify the firms according to the industry in which it operates rather than on a more focused sub-sample set. Further research might examine the use of a hi-bred footprint containing a mix of input and output attributes to identify high-technology firms.

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Chapter 13

Implementing Open Innovation: Challenges in Linking Strategic and Operational Factors for Large Firms Working with HTSFs Tim Minshall, Letizia Mortara and Johann Jakob Napp

Introduction Innovation is an increasingly distributed process, involving networks of geographically dispersed players with a variety of possible, and dynamic, value chain configurations (Fraser, Minshall, & Probert, 2005). ‘Open innovation’ is one term that has emerged to describe ‘[y] the use of purposive inflows and outflows of knowledge to accelerate internal innovation, and expand the markets for external use of innovation, respectively’ (Chesbrough, Vanhaverbeke, & West, 2006). This is contrasted with the ‘closed’ model of innovation where firms typically generate their own ideas which they then develop, produce, market, distribute and support. Implementing an open innovation strategy presents many challenges for management. The core of this chapter is the presentation and discussion of case studies of 10 technology-intensive firms who are currently implementing open innovation strategies, and the linking of the results of these case studies to prior work on improving the management of partnerships between multinational corporations (MNCs) and high-technology small firms (HTSFs).

Research Context Openness in the process of technological innovation is not a new concept (see, e.g. Marshall, 1919; Auber, 1965; Wagner, 1991). If we view technological innovation as the result of activities relating to technological acquisition and exploitation, then a

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model such as that developed by Granstrand, Bohlin, Oskarsson, and Sjo¨berg (1992) gives us an overview of the specific approaches firms can implement to be ‘open’ within the innovation process (see Figure 1). Moving down the vertical axis in Figure 1 denotes increasing openness in both acquisition and exploiting activities. Breaking down the strategies for openness in the innovation process (as illustrated in Figure 1) shows individual concepts which have been applied in industry long before ‘open innovation’ as an integrated strategy became popularised. Examples of research on the individual aspects of acquisition and exploitation as shown in Figure 1 include work on contract research and technology purchasing through contracts and licensing (Teece, 1986), the formation of joint development partnerships (Wince-Smith, 1993), the creation of joint ventures and strategic alliances (Pennings & Harianto, 1992) and the possible acquisition of innovative firms (Ansoff, 1968). Research has also focused on commercialising technologies from universities and public research institutes (Rosenberg & Nelson, 1994), the involvement of customers and lead users (von Hippel, 1988, 2005; Luethje & Herstatt, 2004), innovation within networks such as regional clusters or science parks (Romijn & Albu, 2002) and alliances between large companies and start-up firms (Eisenhardt & Schoonhoven, 1996; De Meyer, 1999; Alvarez & Barney, 2001). Exploitation options such as forming joint ventures (Kogut, 1988), the outlicensing of technologies (Teece, 1986) and the formation of spin outs (Clarysse, Wright, Lockett, Van de Velda, & Vohora, 2005) have been the focus of research for a number of years. Building on these individual opportunities for openness, a new integrating concept of open innovation was introduced by Henry Chesbrough in 2003 (Chesbrough, 2003a). By synthesising the many existing strands of opportunities for openness within the innovation process, Chesbrough drew a new picture of the modern firm, concentrating on the underlying change of business models towards a more open approach. Chesbrough’s concept is best summed up by the comparison of the two funnel diagrams in Figure 2. From the case studies involving companies such as Xerox, IBM and Lucent, Chesbrough concluded that the traditional, closed model no longer reflected current business reality. Instead, he observed a trend which was that more and more firms had started to redevelop their business and innovation models. By transforming from a closed model of innovation to an open model, the case companies sought to find a more efficient balance between the use of internal and external resources. Within this open model the boundaries of the firm are considered to be permeable at every stage of the development process. This allows technology and ideas to be developed internally and exploited externally, or vice versa. This model can lead to a new understanding of a firm’s innovation process and business model, as it replaces the traditional thinking of a linear, closed R&D process, with a much more dynamic, iterative and interactive approach. Since the publication of the open innovation model by Chesbrough (2003b), this concept has attracted substantial academic and industrial interest (Dahlander & Gann, 2008) as many see the potential for improving innovation efficiency by implementing a strategy around open innovation.

Divestment

Technology scanning

Figure 1: Technology acquisition and exploitation strategies. Source: Granstrand et al. (1992) r Wiley, reproduced with permission.

Technology selling

Technology purchasing

Joint ventures

Creation of innovative firms

Acquisition of innovative firms

Technology base of the company

Internal exploitation

Internal R&D

Joint ventures

Technology exploitation strategy

Technology acquisition strategy

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Degree of openness

Figure 2: Open versus closed innovation. Source: Adapted from Chesbrough (2003a) and Docherty (2006).

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With increased flexibility, reduced development costs and risk reduction (Witzeman et al., 2006), higher return on R&D investments (Drake, Sakkab, & Jonash, 2006) and, more generally, broader access to a wider pool of ideas, knowledge and technologies (Brown & Hagel Iii, 2006) are seen to be achievable through more open, collaborative approaches to innovation. Aiming for the realisation of these benefits, some firms have recently developed different concepts and methods to implement the model of open innovation (Gassmann, 2006). Several success stories of restructured innovation processes in favour of a more open approach have been reported, mainly focused on large companies. Examples include Proctor & Gamble (Dodgson, Gann, & Salter, 2006; Huston & Sakkab, 2006a), DSM (Kirschbaum, 2005), Nokia (Dittrich, 2008) and Air Products (Tao & Magnotta, 2006). Current research on open innovation covers a broad spectrum of firm types and sizes (Chesbrough et al., 2006). From the academic point of view, a number of new research fields have emerged through the observation of the trend towards a new model of openness in the innovation process. Even though single methods of externalisation are not radically new, they can be seen from a new perspective, giving impetus an emerging focus on the radical changing of business models. On a more operational level, processes and tools for implementing an open innovation strategy have also been investigated. Open innovation-related processes such as technology intelligence (Kerr, Mortara, Phaal, & Probert, 2006), managing innovation within a supply chain (Chapman & Corso, 2005) and open source development (Swink, 2006) are not radically new but provide an additional component to support the implementation of various open innovation strategies. The importance of intellectual property management has also increased within the era of open innovation (Hogan, 2005). As the model of open innovation is comparatively new, many gaps exist, in particular, regarding the operational capabilities required to ensure implementation of open innovation strategies, operational capabilities and processes required to facilitate the implementation of open innovation strategies (Fredberg, Elmquist, & Ollila, 2008). Questions such as how to gain and measure value through open innovation projects, how to build and manage partnerships and how to gain the skills required for the implementation of an open approach to innovation have not been largely addressed. Our research on collaboration between ‘start-up’ firms and large companies within open innovation systems aims to contribute to an understanding of the operational level of open innovation.

Methodology This chapter presents the results of the first stage of an on-going project to help firms assess and develop the organisational capabilities required to successfully implement an ‘open innovation’ approach. Following a review of the literature, the methodology used for this initial stage was a case study approach to draw out the

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main themes from a complex context (Eisenhardt, 1989). The case study approach involved combined primary and secondary data gathering. Standard publicly available sources were used to provide context. To access more detailed information, primary data was gathered from the running of a one-day industrial workshop for senior managers from our selected survey firms. All the firms selected were technology-intensive, multinational firms who were moving from or who had moved from a closed to an open approach to innovation. The workshop was based on the presentation and discussion of three themes:  What are the current drivers of innovation within each firm?  What does open innovation mean for each firm?  What are the issues raised in attempting to implement an open innovation strategy? Each firm presented their perspective on these three issues, which were then captured and posted on charts at the workshop. This allowed for cross-referencing and discussion of common approaches and the identifying of contrasting ideas. This process, coupled with post-workshop comparison with other company case studies, helped identify the organisational capabilities that these firms believed to be key to the successful implementation of an open innovation strategy. The outputs of the workshop and additional analysis revealed themes to be taken forward for more detailed analysis. These themes are currently being researched, and the outputs of this second stage will form the basis for the development of management guidelines to assist firms in building an operational capability to successfully implement open innovation.

Case Study Summaries The case studies summarised below each provide some basic information on the company, the drivers of innovation for that company, the open innovation approaches used, and the challenges faced in attempting to implement open innovation.

Case 1 Case 1 was a U.S.-based consumer and industrial electronics firm with significant global presence in all its main business areas. It had traditionally taken a very closed approach to innovation, but the significant commercial impact of a disruptive technology on its core business area led to a rethink of its approach to innovation. The firm has significantly reduced the scale of its central U.S. labs and had established a small unit in Europe to act as a route to new technologies from regional start-ups and universities. It also aimed to provide an improved understanding of

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regional markets. The issues raised during this transition from closed to open innovation have included the following:  Overcoming the ‘not invented here’ (NIH) syndrome present among some engineers at the central U.S. labs when assessing ideas from the European labs.  Understanding and valuing the activities of those involved in ‘open’ activities (e.g. networking, attending conferences) which were not valued as much as ‘real’ scientific and technical work.  How to effectively utilise innovation intermediaries (e.g. consultants, networks).  A range of issues related to IPR management when dealing with external inventors and entrepreneurs.  The slow speed of decision making by the parent organisation when confronted with novel ideas from external sources.  Managing different expectations between top management, business unit management and R&D lab management.  How to get all business activities engaged in the open approach rather than only the R&D labs.

Case 2 Case 2 was a European motorsport engine manufacturer which was a sub-unit of a global automotive firm. Its key drivers were technology leadership, speed to market, regulatory requirements and increasingly competitive budgets. The firm’s move to open innovation was significantly influenced by budgetary constraints. The firm had leading-edge R&D labs but needed to be much more effective at sourcing new technologies from, in particular, its supply chain. It was also aware that much of its R&D capability was underutilised. The approach taken has been to build a physical infrastructure for open innovation by establishing a technology park in the grounds of its R&D labs, close to one of Europe’s main motorsport regions. This, it was hoped, would draw its suppliers and other motorsport firms into close proximity and facilitate the sharing of resources and ideas. The issues facing this firm’s approach to open innovation include the following:  A flexible approach to IPR: Because of the highly competitive nature of the industry, sharing IP was very problematic. The firm was seeking ways to build more links with firms in other industries.  How to move from being an ‘introverted’ business – staffed by engineers used to working in a very closed, secretive environment – to one which not only allowed but also encouraged openness.  How to create a new cluster in which firms could be attracted to ‘setup’ on the new technology park and collaborate.

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Case 3 Case 3 was a leading European supplier of industrial and transportation power generation systems. Its main innovation challenge was in maintaining its record of delivering highly R&D-intensive new products to all its target market segments in a cost-effective manner. In addition, the company’s revenues were increasingly drawn from services associated with a core product. To ensure efficiency and effectiveness of its R&D spend, the firm had implemented a number of open innovation initiatives. These included the establishment of laboratories embedded in universities, the formation of regional competence centres to draw together expertise around a particular theme, the management of a range of risk/reward sharing partnerships with suppliers and the formation of a corporate venturing unit. Problems faced through the implementation of these activities included the following:  As the business was highly IP dependent, moving to a more open model had raised numerous issues relating to IPR ownership, leakage and usage.  How to select which technologies around which to be open. The firm needed to be very selective regarding which core and non-core technologies it might choose to include in its move to open innovation.  The very high levels of R&D to date had resulted in a substantial IP portfolio, some of which was not of current, direct use to the firm. The firm had faced challenges in assessing how best to spin-out firms that would allow appropriate levels of reward to be returned to all stakeholders.

Case 4 Case 4 was a global defence systems provider. A major focus for innovation in this firm was an ability to introduce new technologies into existing systems. Completely new products, owing to their complexity and cost, tended only to be introduced once every 5 to 10 years. Another significant driver of change was a growing focus on support services as a major (and potentially main) revenue stream. Open innovation for this firm had in the past meant selecting strategic partners in specific areas of expertise. More recently, open innovation has been implemented through the establishment of a smaller number of significantly resourced centres that bring together the firm’s own researchers, university research groups, and selected other firms to focus on broad innovation themes such as systems engineering. Problems currently being faced by Case 4 included the following:  How to train scientists, engineers and managers in the necessary skills for acquiring ideas from outside the firm.  How to set up and manage flexible partnerships with a range of external organisations that can cope with the long-term, but changing, needs of customers of defence systems.

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 How to move from a culture based around internal IP development and ownership to one that focused more on IP access and usage.  How to build a skills base to manage the multiple strands of opportunities that may emerge from an open approach to innovation.  What metrics could be applied to managing open innovation and how do these metrics, especially value capture, differ between partners?

Case 5 Case 5 was an oil and gas extraction and processing firm. A key driver of change in their business was a need to identify new areas of opportunity outside their core businesses. The majority of R&D efforts were focused on improving performance in the core business areas. Open innovation for this firm meant the coordination of the process of guiding inventions through to proof of concept stage, whether or not they had come from internal or external sources. Open innovation, for this firm, also meant the managing of a range of linkages with universities around the world and the management of a corporate venturing programme linked to core and non-core business activities. Challenges faced by this firm included the following:  Designing and implementing the most appropriate organisational structure for open innovation.  How to assess the commercial viability of external ideas before internalising them.  How to access ideas via media such as public websites, without the process stalling over IP problems.  How to manage and integrate the activities of semi-autonomous units, such as the corporate venturing group.

Case 6 Case 6 was an oil and gas extraction and processing firm. Its main reason for innovation was the need to get into new business areas. It currently had a relatively small level of internal R&D activity, with a heavy reliance on a network of commercial and technical partners. Open innovation for this firm meant the management of an ‘ecosystem’ of partners. This ecosystem comprised, for example, universities, suppliers, start-ups and public R&D institutes. The key metric for the performance of this open innovation ecosystem was the improvement in innovation efficiency through the use of external resources. Issues facing this firm in the implementation of its strategy included the following:  Managing collaborations would require a specific skill set for researchers and managers. What were these skills, and how could they be developed?

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 How to manage multiple collaborations when they are at different levels of collaborative maturity and different degrees of alignment with current core business areas.  Within an open innovation environment, how to identify the most promising value creation opportunities at technology, business and strategy levels and to ensure appropriate linkages between these levels.

Case 7 Case 7 was a supplier of oilfield services. Its main task for innovation was to maintain its leading position in its chosen sectors. For this firm, their approach to open innovation was one of collaboration with universities, suppliers and customers based on new models of value creation that did not rely upon the Case 7 firm being the exclusive owner of the core IP. Issues they faced included the following:  Balancing consideration of IP ownership against IP usage, and when exclusivity of application is required.  Maintaining realistic expectations of the level and timescale of returns to be generated from IP exploitation when working in partnership with external organisations.  Understanding the complex range of motivations of a wide range of stakeholders when seeking to partner them through the value chain, both horizontally and vertically.

Case 8 Case 8 was a provider of mobile communications handsets and infrastructure. Key innovation drivers were cost reduction, the high speed of new product introduction (NPI) required from consumer markets and adapting to widespread competitive shifts in the industry. Open innovation for this firm related to the way in which it sourced new technologies from external organisations (particularly those within their current supply chain) and building appropriate businesses between these technologies, in partnership. This firm viewed the role to be played by its corporate venturing unit as particularly important, since they had started to source ideas from outside their traditional supplier base. Challenges they faced when implementing this approach included the following:  How to change the culture of the organisation to allow for more openness. There was a perception of risk aversion among their R&D engineers and, consequently, a lack of enthusiasm for sourcing from ‘unfamiliar’ organisations.

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 The heads of each business unit had very tight targets for sales and revenue. This caused a reluctance to experiment and a preference for business models and partnerships that had been proven to work in the past.  The need for realistic perceptions of returns to be generated from open innovation, in general, and the activities of corporate venturing units in particular.  When seeking new ideas from external sources, especially those at a very early stage, there were significant concerns relating to IP disclosure.

Case 9 Case 9 was a provider of mobile communications network products and services. Their main reasons for innovation were the ability to respond to fast-changing market demands, the need to respond to disruptive innovations and the need to deliver any new product or service rapidly across multiple technology platforms. Their approach to open innovation had included the use of external venture capitalists and business angels to assist with the screening of ideas sourced externally, the engagement of ‘lead users’ to operate new product and service concepts and engagement with universities on technical and commercial projects. Issues that the company had faced in implementing these three approaches included the following:  How to develop revenue models that allow the firm not to demand exclusivity of use of an externally sourced idea.  How to move beyond piloting open innovation processes to develop, and successfully embed within the organisation, new ways of working to enable open innovation.  How to develop an internal capability to leverage the potential benefits of open source software development.

Case 10 Case 10 was a leading provider of identity and security technologies. Their main drivers of innovation were maintenance of technology leadership, managing a response to the trend towards digital security, maintenance of reputation and an ability to maintain profitability in the face of high growth. Although their move to open innovation had only been recently initiated, they have attempted to capture new product and service ideas at the early stage (i.e. at the widest end of the product development funnel) from numerous partners. Challenges they faced included the following:  The security aspects of their business meant that there was an inherently closed mindset within the organisation.

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 How to assess which of the many technologies sourced from external organisations had the potential to be really successful. Linked to this is the need to devote appropriate resource to take the most likely candidates forward.  How to manage IP in an open environment and what balance of IP ownership versus IP usage is appropriate, and how does this change as the idea moves from concept to commercial realisation?

Discussion and Further Work Table 1 presents a summary of the main issues drawn from the 10 case studies. The case study firms revealed a diverse range of interpretations of open innovation, but common to most firms was working with or intending to work with HTSFs, either through partnering, corporate acquisition, technology purchasing, contract research or licensing. There were also a range of operational problems observed in the implementation of the open innovation strategies. From this range of problems, three themes common to a number of the firms could be identified: IP management, expectation management and skills development for open innovation.

IP Management The management of IP was a clear concern and though apparent at different levels was identified by all the case study firms. Concerns related to IP management at all stages of the development and exploitation of an idea. Key concerns raised included issues related to the sourcing of ideas via public websites, the effectiveness of nondisclosure agreements with external inventors, disclosure and leakage of IP within highly competitive or security-sensitive environments and the balancing of IP ownership versus IP usage. These practical concerns have also been apparent in the literature (Hogan, 2005). It is interesting to note that many of these challenges were anticipated 40 years ago by Auber (1965, p. 190), who warned of the many risks of drawing in ideas from outside and noted that ‘[y] the cost of implementing the policy can be quite substantial. [y] A comparison of [the] low probability of value to the company against the definite costs incurred and high probability of legal entanglement indicates that the receiving and considering of outside disclosures is indeed a poor risk’.

Expectation Management Most of the case study firms identified concern over the expectations being placed on the implementation of an open innovation approach. The often-cited high-profile examples of the perceived success of open innovation (Huston & Sakkab, 2006b) were felt not to be supported by clear commercial metrics that could be applied

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Table 1: Summary of issues from the case studies. Key Drivers Case1

What is ‘Open’

Current Issues

Technology change

External venturing

Change of business

Partners: Centres of excellence

Skills/Tools/IP management Meeting different expectations

Technology leadership Time to market

Supplier links

IP management

Cluster formation

Regional clusters

Time to market

University technology centres Risk/Revenue sharing programme

IP management

Flexibility in service needed Product updates

Cooperation with universities Partners of excellence

IP management

Technology driven

Broad innovation ecosystem Start-ups, universities, suppliers y

Process structure for OI IP management (-www)

Partnership-based business model Expanding to new businesses

Fast-moving markets

Skills

‘Fuzzy’ customers

Value creation

Case 7

Technology leadership

Collaboration with universities, suppliers, customers

IP management Meeting different expectations

Case 8

Fast-moving markets Cost reduction

New technology sourcing

Skills and culture/IP management Meeting different expectations

Case 2

Case 3

Cost reduction Case 4

Case 5

New business opportunities Case 6

Case 9

Case 10

Corporate ventures

Value creation (how/ where/win–win)

Skills/Value creation

Fast-moving markets Technology driven

VC initiative, lead-user method Cooperation with universities

Idea trade

Technology leadership Global pressure: Profitable growth

Funnel more open to partners

IP management

Tools (open source, www etc.)

Process structure for OI (How?)

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within the case study firms. This view links with the sentiments of other assessments of managers concerned with implementing open innovation (Schmitz & Brantley, 2005; Drake et al., 2006). The level of expectations regarding returns to be generated from corporate venturing activities and the way in which venturing activities were integrated with other open innovation activities were noted as over-optimistic by many of the case study firms.

Skills Development for Open Innovation Regarding openness at the level of R&D, the skills required of researchers and managers operating a closed model of innovation were regarded as being different from those needed in an open environment. For example, in a closed environment, the skills required of a researcher would include technical expertise and the ability to work effectively in a laboratory environment. In a more open environment, a researcher might be expected, in addition to technical and lab skills, to be able to access and source ideas, in a manner that does not weaken the employer’s IP position, from external organisations whose style, scale and scope of business may be very different from the researcher’s employer. The performance metrics applied to the researcher would also differ between closed and open environments. This presents challenges for the researchers and also their managers.

Skills for Managing Collaborations between HTSFs and MNCs Prior research has catalogued the challenges of managing partnerships between MNCs and HTSFs (De Meyer, 1999; Alvarez & Barney, 2001; Minshall, Mortara, Elia, & Probert, 2008). Table 2 summarises some of these challenges from each firm’s perspective. Research has also catalogued ways in which both HTSFs and MNCs have overcome some of the management challenges presented in Table 2. Appendix 1 presents some of the approaches used by firms for overcoming these challenges, grouped around the themes of ‘strategy’ and ‘business model’, the technology on which the collaboration is based, the characteristics of the organisations themselves and the structure and ongoing management of the partnership. However, the approaches given in Appendix 1 are a consolidation of good practices observed in a wide range of firms. Very few firms had a comprehensive view of how to make such partnerships work. Few employees had systems for capturing and disseminating this experience to others within the organisation so as to build a skills base for forming and managing such partnerships in the future. As such, the organisational capability to manage HTSF/MNC partnerships could not be regarded as a reliably deployable ‘tool’ within the range of open innovation approaches. Linking back to the issues identified in the case studies presented earlier in this chapter, a gap in current knowledge can now be identified. This gap relates to the

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Table 2: Management challenges of HTSF–MNC partnerships. HTSF Perspective

MNC Perspective

How to get in? For MNCs, the complexity and scale of operations may mean that even their own staff may not be able to help an HTSF contact the right people

Paranoia over IP and NDAs: HTSFs are often reluctant to reveal details of their technology without a non-disclosure agreement (NDA); what they may fail to see is that somewhere within the MNC, IP may already be owned in this area

Who to talk to? What the start-up really wants to know is: Who is the decision maker? Who influences them? Who will be working on implementing the partnership?

Brand abuse: HTSFs are often very keen to promote relationships with established players as it may be seen to confer credibility; they may use the partner’s brand in inappropriate ways in pursuit of this

Transfer of responsibility: The transfer of responsibility from R&D to legal and procurement can change and disrupt the flow of the negotiations

Technology, product or solution? The gap between technology demonstrator to fully supported product can often be quite significant, and HTSFs may not appreciate the time and cost involved in moving between the two

Slow decision cycles: For MNCs due to their complexity, size and multiple layers of management, it is often very hard for them to make decisions at ‘start-up speed’

Different functions: Even when there is enthusiasm from R&D within the MNC, the transfer to operations (and ‘collision’ with procurement systems) can be problematic

Power imbalance: The MNC may abuse its position by drawing-out negotiations and to attempt to prevent discussions with competitors

Resource constraint and financial stability: HTSFs need to be prepared to be subject to due-diligence checks to give potential partners confidence in their viability Culture: HTSFs may be run by individuals impatient for progress but unwilling to be governed by schedule and discipline dictated by the larger firm

Not understanding start-ups: Demands made of start-ups by large firms sometimes show a lack of awareness of how an HTSF operates Source: Minshall et al. (2006).

intersection of both the management approaches to HTSF partnerships with MNCs and the skills required to successfully implement open innovation. These two issues provide the basis for further research to answer the following question. How can MNCs develop the skills they need to work with HTSFs effectively within the

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framework provided by an open innovation strategy? The findings of this chapter are now underpinning a programme of research to help address this question. This ongoing work is also linked to the important, yet poorly understood, issue of measuring the performance of these partnerships from value creation and value capture perspectives.

Conclusions This chapter has summarised 10 cases studies of approaches used and issues faced by MNCs currently implementing open innovation. The case studies have revealed a wide range of challenges, but a degree of commonality around the themes of IP ownership, expectation management and skills development. Linking the issue of skills development to one particular, and popular, open innovation strategy of forming partnerships with smaller, younger firms, reveals a need for further research to help build and embed the skills required to be able to implement such partnerships effectively and reliably.

Acknowledgements We are grateful for the support of Unilever R&D, Vlaardingen (NL), in funding this research. We also thank all the firms who kindly agreed to collaborate on this research project. Thanks also to James Anderson and Tzelin Loo in providing research assistance for this project.

References Alvarez, S. A., & Barney, J. B. (2001). How entrepreneurial firms can benefit from alliances with large partners. Academy of Management Executive, 15(1), 139–148. Ansoff, H. I. (1968). The innovative firm. Long Range Planning, 1(2), 26–27. Auber, R. P. (1965). Outside ideas — Dynamite!. Research Management, VIII(3), 183–190. Brown, J., & Hagel, J. (2006). Creation nets: Getting the most from open innovation. McKinsey Quarterly (2), 40–51. Chapman, R. L., & Corso, M. (2005). From continuous improvement to collaborative innovation: The next challenge in supply chain management. Production Planning and Control, 16(4), 339–344. Chesbrough, H. (2003a). Open innovation: The new imperative for creating and profiting from technology. Boston, MA: Harvard Business School Press. Chesbrough, H., Vanhaverbeke, W., & West, J. (Eds). (2006). Open innovation: Researching a new paradigm. Oxford: Oxford University Press. Chesbrough, H. W. (2003b). Open innovation: The new imperative for creating and profiting from technology. Boston, MA: Harvard Business School Press.

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Clarysse, B., Wright, M., Lockett, A., Van de Velda, E., & Vohora, A. (2005). Spinning out new ventures: A typology of incubation strategies from European research institutions. Journal of Business Venturing, 20, 183–216. Dahlander, L., & Gann, D. (2008). How open is innovation? In: J. Bessant & T. Venables (Eds), Creating wealth from knowledge. Chelteham, UK: Edward Elgar. De Meyer, A. (1999). Using strategic partnerships to create a sustainable competitive position for high tech start-up firms. R&D Management, 29(4), 323–328. Dittrich, K. (2008). Nokia’s strategic change by means of alliance networks. A case of adopting the open innovation paradigm? In: P. Sivarajadhanavel & D. Vellingiri (Eds), Open innovation: The networked R&D. Chennai, India: Icfai University Press. Dodgson, M., Gann, D., & Salter, A. (2006). The role of technology in the shift towards open innovation: The case of Procter & Gamble. R&D Management, 36(3), 333–346. Docherty, M. (2006). Primer on ‘Open Innovation’: Principles and practice. Vision (Product Development and Management Association) (April), 13–17. Drake, M. P., Sakkab, N., & Jonash, R. (2006). Maximising return on innovation investment. Research Technology Management, 49(6), 32–41. Eisenhardt, K. M. (1989). Building theories from case study research. Academy of Management Review, 14(4), 532–550. Eisenhardt, K. M., & Schoonhoven, C. B. (1996). Resource-based view of strategic alliance formation: Strategic and social effects in entrepreneurial firms. Organization Science, 7(2), 136–150. Fraser, P., Minshall, T. H. W., & Probert, D. (2005). The distributed innovation paradigm: Evolution and dynamics. 6th International CINet Conference Continuous Innovation — (Ways of) Making Things Happen, Brighton, pp. 4–7. Fredberg, T., Elmquist, M., & Ollila, S. (2008). Managing open innovation — Present findings and future directions. Vinnova Report, Chalmers University of Technology, Gothenburg. Gassmann, O. (2006). Opening up the innovation process: Towards an agenda. R&D Management, 36(3), 223–228. Granstrand, O., Bohlin, E., Oskarsson, C., & Sjo¨berg, N. (1992). External technology acquisition in large multinational firms. R&D Management, 22(2), 111–133. Hogan, J. (2005). Open innovation or open house: How to protect your most valuable assets. Medical Device Technology, 16(3), 30–31. Huston, L., & Sakkab, N. (2006a). Connect and develop. Harvard Business Review, 84(3), 58–66. Huston, L., & Sakkab, N. (2006b). Connect and develop: Inside Proctor & Gamble’s new model for innovation. Harvard Business Review, 84(3). Kerr, C. I. V., Mortara, L., Phaal, R., & Probert, D. R. (2006). A conceptual model for technology intelligence. International Journal of Technology Intelligence and Planning, 2(1), 73–93. Kirschbaum, R. (2005). Open innovation in practice. Research Technology Management, 48(4), 24–28. Kogut, B. (1988). Joint ventures: Theoretical and empirical perspectives. Strategic Management Journal, 9, 319–332. Luethje, C., & Herstatt, C. (2004). The lead user method: Theoretical-empirical foundation and practical implementation. R&D Management, 34(5), 553–568. Marshall, A. (1919). Industry and trade. London: Macmillan. Minshall, T. H. W., Mortara, L., Elia, S., & Probert, D. (2008). Development of practitioner guidelines for partnerships between start-ups and large firms. Journal of Manufacturing Technology Management, 19(3), 391–406. Pennings, J. M., & Harianto, F. (1992). Technological networking and innovation implementation. Organization Science, 3(3), 356–382.

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Romijn, H., & Albu, N. (2002). Innovation, networking and proximity: Lessons from small high technology firms in the UK. Regional Studies, 36(1), 81–86. Rosenberg, N., & Nelson, R. R. (1994). American universities and technical advance in industries. Research Policy, 23(3), 323–348. Schmitz, W., & Brantley, M. (2005). ROI: Return in innovation. R&D, patent strategy and building a knowledge culture. Global Equity Research, Deutsche Bank, Accessed on 28 March 2005. Swink, M. (2006). Building collaborative innovation capability. Research Technology Management, 49(2), 37–47. Tao, J., & Magnotta, V. (2006). How air products and chemicals ‘‘identifies and accelerates’’. Research Technology Management, 49(5), 12–18. Teece, D. J. (1986). Profiting from technological innovation: Implications for integration, collaboration, licensing and public policy. Research Policy, 15, 285–305. von Hippel, E. (1988). The sources of innovation. Oxford: Oxford University Press. von Hippel, E. (2005). Democratizing innovation. Boston, MA: The MIT Press. Wagner, H. K. (1991). The open corporation. California Management Review, 33(4), 46–60. Wince-Smith, D. L. (1993). Driving competitiveness through partnerships. Economic Development Quarterly, 7(1), 12–17. Witzeman, S., Slowinski, G., Dirkx, R., Gollob, L., Tao, J., Ward, S., & Miraglia, S. (2006). Harnessing external technology for innovation. Research Technology Management, 49(3), 19–27.

 Technology readiness level: Make a realistic  Communicate need: Use shareable roadmap to assessment of the readiness level of the position start-up’s technology and show technology and draw on stakeholder’s experiences complementary resources needed and likely to identify tasks (e.g. compliance) and costs routes for development. If partnerships have been associated with manufacturability. formed with other start-ups, use these as examples.

2. The technology

Examples of Particular Approaches Used by Established Firms

 Business strategy: Draw information from the  Innovation strategy: Within broader strategy of business plan to map possible business models for company, develop a roadmap or portfolio map addressing different opportunity areas. Capture that can be shared with start-ups that positions non-confidential aspects of this as a roadmap for the technology capabilities and needs of the firm communication with potential partners. Identify (including criticality) and links these to factors (e.g. funding) that may change business opportunity areas.  Technology acquisition: Map all sources and model.  Partnering strategy: Map out internal mechanisms for internalising technologies (e.g. competences (tacit and explicit) and identify internal R&D, co-development, licensing, complementary assets needed to address different investment and acquisition). Ensure early opportunity areas. Use non-executives, investors, engagement with key stakeholders in technology etc. to help identify potential routes to access acquisition process (R&D, procurement, legal/IP, these assets. Be aware of three impacts of production, venturing, etc.). Consider de-risking partnership – helping intended business model, by having multiple internalising routes. opening new opportunity areas and restricting future opportunities.

Examples of Particular Approaches Used by Start-Ups

1. The strategy and business model

Management Issues

Appendix 1. Examples of Approaches Used to Manage HTSF–MNC Partnerships

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 Understanding large firms: If start-up  Explain: Spend as much time as is feasible to help management team do not have large company start-up understand needs, internal processes and experience, get non-executive directors, mentors culture of large firm. Use process maps to show and investors who have worked in large firm to start-up how engagement could work and how brief management team. decisions are made.  Understanding partners: Develop simple checklist  Shield: Use dedicated team or individual to cover issues such as ‘has this company ever champion to act as first point of contact and to worked with a start-up before?’ Talk to their shield start-up from unnecessary bureaucracy and suppliers to get a feel of partner’s ‘clockspeed’. to smooth communications in both directions.  Educate partners: Get large firm to engage other  Use of intermediaries: Links with consultants and than through formal meetings with the start-up to universities can provide a platform from which get a better sense of ‘start-up culture’. relationships with start-ups can be built.

 Who makes the deal ? Find out who are the  Setting the right tone: Agree overarching influencers, decisions makers, etc. within the large principles early on and use intermediate step of firm; get their names, map their roles and their term sheet to allow discussion around specific relationships.

4a. The deal – setup

 Technology ecosystem: Map system requirements  Technology readiness level: Assess readiness levels for the technology (i.e. What are the other for the start-up’s technology and how much of the components of the system that will deliver value technology is tacit versus explicit. Assess tasks for to the end user? Who owns these other raising readiness level, their associated costs and components? What are the relationships between where capability to do so rests. Assess start-up’s the different owners of these system commercial maturity. Balance with consideration components?) of criticality identified within innovation strategy.

Examples of Particular Approaches Used by Start-Ups

3. The organisations

Management Issues

Appendix 1. (Continued )

208 Tim Minshall et al.

 Communication: Keep in regular and open  Transitions: Those who set up the deal and those 4b. The deal – ongoing contact with partner, and do not only contact who are involved in its management may not be management when there is a problem. Assign members of the same people. Ensure that efforts are made to management team to ‘mark’ key contacts at large manage this transition.  Communication: Keep the start-up informed of firm. Keep board and investors informed of developments. developments through engagement in, for  Document: Ensure that all interactions are example, internal conferences. Devote time to documented. In case of any disagreements, this keeping up to date with partner. may prove critical information.

 What is the deal ? Have a clear sense of what is issues. Be as open as possible with the start-up really wanted from the partnership, what can be about concerns. realistically delivered, how this may change over  Cash flow: Be aware of start-up’s cash flow time and what the possible direct and indirect position – and see if a deal can be based around benefits are. Draw in experience from investors, short revenue generation. Working with start-up non-executives, etc. from the outset. on specific cash generating project will allow  Role of lawyers: Legal counsel should be sought at assessment of possible future development (or the outset of plan to partner. Though costs will be termination) of partnership. incurred, these are likely to be less than if lawyers  Consult widely and prepare ground: Drawing in are brought in later to fix problems. views from internal stakeholders (R&D, legal/IP,  It’s not about meetings: Decisions are unlikely to procurement, corporate venture capital, be made in meetings with start-up. Large production, commercial, etc.) in the early stages company champion should be given the of the partnership will smooth the deal setup. ammunition to support start-up’s case.  Set up partnership management process: Aside from what may be in contract, put in place regular review meetings, updates, etc. Draw upon experience of previous partnerships.

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Examples of Particular Approaches Used by Start-Ups

Examples of Particular Approaches Used by Established Firms

 Review: Staff who are key to the partnership may  Monitoring: Keep start-up informed of upcoming change roles. Strategies and business models are milestones and their criticality. Ensure that if not fixed. Regular reviews of the partnership, by underperformance is noted, the start-up knows management team, with board and with the early and is given assistance to deal with this. partner will help ensure the partnership continues  Review: Champion should ensure that the on the best footing, or is adapted/terminated. relationship with the start-up is fed into business and technology strategy review processes.

Source: Minshall et al. 2008.

Management Issues

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210 Tim Minshall et al.

Chapter 14

Forms of Market Orientation in French Young High-Technology Firms: A Typology Ste´phanie Petzold-Dumeynieux

Introduction The complicated environment surrounding high-technology firms, involving a high degree of market uncertainty, a high degree of technological uncertainty, a high degree of competitive volatility, high R&D expenditures and the rapid obsolescence of products, creates a great need for sophisticated marketing (Mohr & Shooshtari, 2003). Yet these firms continue to have underdeveloped competencies in marketing (Mohr & Sarin, 2009). As far as young high-technology firms are concerned, the marketing dimension is relatively poorly understood in so far as its characteristics are unusual, and rarely studied. Moreover, marketing is often informal because of the youth of the young firm that is under development and necessarily intuitive because of the innovative process that often protectively offers the firm’s supply of products to the market. The main contribution expected in this work is a better understanding of the application of the marketing concept to young high-technology firms. One previous work (Petzold-Dumeynieux, 2002) argued that to observe marketing in the context of young high-technology firms, market orientation is a useful concept, particularly in identifying the nature and the form in which the marketing concept is applied. Thus, the aim of this chapter is to propose a typology of market orientations for young high-technology firms. In the next section, attention is given to the literature on market orientation and the context of young high-technology firms, from which the research questions of the current empirical study have been derived. Then, the approach taken to operationalise this study is explained, followed by the presentation and the discussion of results.

New Technology Based Firms in the New Millennium, Volume VIII Edited by R. Oakey, A. Groen, G. Cook and P. van der Sijde r 2010 Emerald Group Publishing Limited. All rights reserved.

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Market Orientation Concept and Young High-Technology Firms: The Study of the Form The Market Orientation Concept The concept of market orientation was established in academic literature by two seminal articles that both appeared in 1990. First, Narver and Slater (1990) represent the cultural perspective view of market orientation. Second, the research of Kohli and Jaworski (1990) is viewed as representing behavioural perspective on market orientation (Lafferty & Hult, 2001). Narver and Slater (1990) define market orientation as ‘the organization culture that most effectively and efficiently creates the necessary behaviours for the creation of superior value for buyers and, thus, continuous superior performance for the business’ (p. 21). They state that market orientation consists of three behavioural components: customer orientation, competitor orientation and interfunctional coordination. Continuous innovation is implicit in each of these components (Narver & Slater, 1999), and two major decision criteria are long-term focus and profitability. As far as Kohli and Jaworski (1990) are concerned, they introduced market intelligence rather than customer focus as the central element of market orientation because in their view market intelligence is a much wider concept than customer focus: ‘It includes consideration of exogenous market factors that affect customer needs and preferences, and current as well as future needs of customers’ (p. 3). The definitions by Kohli and Jaworski (1990) or by Narver and Slater (1990) have been adopted in most academic research on market orientation concerning for instance innovation (Atuahene-Gima, 1996) and small firms (Pelham & Wilson, 1996) or have been used as a starting point (Deng & Dart, 1994). In general this research seeks to measure the links between market orientation and performance (Ellis, 2006), although this will not be the approach taken in this study. Our study is aimed at understanding behaviours relating to marketing in young high-technology firms, where the definition of market orientation used is ‘Market orientation is the organization-wide generation of market intelligence, dissemination of the intelligence across departments and organization-wide responsiveness to it’ (Kohli & Jaworski, 1990, p. 6). Responsiveness here involves the extent to which companies adjust their marketing policies in the light of market intelligence. This narrow interpretation of responsiveness is the adaptation of offerings to express customer needs and market structures. This reactive response is labelled ‘market driven’ by Jaworski, Kohli, and Sahay (2000) and ‘customer-led’ by Slater and Narver (1999, 1998). However, being market oriented means that companies also try to understand and respond to customers’ latent and future needs (Slater & Narver 1999, 1998). Jaworski et al. (2000) elaborate on this theme by suggesting that marketoriented companies can ‘drive markets’ by manipulating the structure of the market and the behaviour of market players. Narver, Slater, and MacLachlan (2004) consider this notion as a broader and more proactive strategic aspect of marketing, useful in the high-technology sector (Hills & Sarin, 2003). In this regard, product

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innovation can be the most appropriate response to market intelligence, which includes both customers and competitors in a current and latent needs manner. Indeed, in young high-technology firms, since the marketing dimension is almost non-existent and to be developed, we will take into account all dimensions used in previous works. However, it is clear that market orientation in high-technology and emerging firms must be adapted to suit specific firms.

Market Orientation in High-Technology and Emerging Firms Because in the context of high-technology firms, only few studies deal with market orientation, some important characteristics must be from other types of funds adapted to be applicable to young high-technology firms. Appiah-Adu and Ranchhod (1998) have investigated the link between market orientation and performance in a study of 62 biotechnological firms. The authors argue that their research constitutes a first step in investigating the market orientation in hightechnology firms, because it is concerned to these technology-based firms. The innovation network of the firm (Jones-Evans, 1997), the collaboration during product development with partners such as customers, distribution to licence users (Von Hippel, 1986; Lauglaug, 1993) and the use of the patent system as a tool of commercial management (Petzold-Dumeynieux, 2002) are dimensions that seem to usefully assist the nature of market orientation in high-technology firms. Indeed, market intelligence generation concerning both customers and competitors can come from all these specific management tools for these high-technology firms, and the reactivity of the firm to the market depends on all these dimensions (Day & Schoemaker, 2001). Moreover, emerging firms possess characteristics, such as newness and smallness that help to explain why start-up companies face several distinct challenges in their marketing activities. In addition, the uniqueness of marketing in emerging firms is the fact that the entrepreneurial team is confronted with all challenges simultaneously, whereas the marketing department in larger firms often faces fewer of these challenges. Table 1 summarises key implications for marketing in emerging firms in terms of their key characteristics (Gruber, 2003). In the same way that the characteristics of emergent firms have implications for their marketing dimension they also have implications for their potential market orientation. According to Verhees and Meulenberg (2004), the limited resources and capabilities of small firms have consequences for market orientation as defined by Kohli and Jaworski (1990). In small firms, resources for market intelligence generation are scarce, and there is often no room for a marketing specialist. In fact, market intelligence is based mostly on secondary data (from trade journals, sector research, conferences and professional magazines) or on personal contacts (with suppliers, customers or bank employees) (Smeltzer, Fann, & Nikolaisen, 1988). When small firms sell a differentiated product in a local or regional market, they can use market intelligence more effectively. Advances in information technology (IT)

Key implications for marketing

Small Size  Severe resource limitations  Critical skills might be lacking  An ability to act swiftly

Newness

 A low level of trust  Exchange relationships are lacking (particularly with customers)  Internal structural processes are lacking  A preoccupation with the process of building a viable organisation  The challenges of actively fuelling the growth of the firm  The planning and execution of marketing activities face severe time restrictions

Evolution and Growth

Table 1: Nature of the emerging firm and the implications for marketing.

 Marketing decisions often have to be made on the basis of very limited, uncertain information  It is necessary to remain flexible and keep strategic options open  The need to act swiftly

Uncertainty and Turbulence

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will be helpful in this respect. Intelligence on suppliers and potential collaborators is very useful for small firms to develop innovative processes, products and services. The dissemination of market intelligence is less relevant in small firms where the owner makes the major decisions. However, the dissemination of market intelligence to other people in the firm might increase employee motivation. In fact, Ruekert (1992) showed that successful market orientation is related positively to job satisfaction. Small firms, run by their owner, can often respond with alacrity and flexibly to market intelligence because decision-making is non-bureaucratic and because the decision-maker is able to oversee the whole production and marketing process (Carson, Cromie, McGowan, & Hill, 1995; Nooteboom, 1994). On the other hand, such responsiveness maybe constrained by limited financial and technical resources. Because market orientation is a useful concept in identifying the nature of the marketing process, the aim of this chapter is to propose a typology of forms of market orientation in young high-technology firms.

The Form of Market Orientation in Young High-Technology Firms The measurement of market orientation can be used to generate two results (Greenley, 1995): firstly, a profile of scores across the range of dimensions, which gives an individual measure of various forms of market orientation; secondly, the average score of all dimensions, which gives an overall measure of the degree of market orientation. These results give different insights into the overall nature of market orientation. However, even if some firms have the same, or a similar, degree of market orientation, their profiles of scores across the range of dimensions are likely to vary. The main research question is ‘what different forms of market orientation are to be found among young high-technology firms?’ Here, investigations can be extended to identify the relative importance of the dimension in discriminating between forms. Thus, a second research question is ‘what are the factors that discriminate between the different forms of market orientation?’ To respond to these questions, an adaptation of the concept of market orientation to apply it to young high-technology firms was necessary. We have thus adapted the concept of market orientation, by adapting young high-technology firms’ specificities to the original components of the concept, including a customer dimension, competitive dimension and the reactivity of the firm. To distinguish our modification from the original market orientation concept we prefer to use the terms ‘the customer talk’s dimension’, the ‘competitor talk’s dimension’ and ‘reactivity’ as terms more appropriate to our specific context (see appendix). The customer orientation dimension takes into account intelligence generation and intelligence dissemination concerning present and potential customers. The collection of information as, for example the institutional network of innovation, the patent system, collaboration with customers during industrial developments, in-house or

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delegated market research and informal is included (Deakins & Boussaouara, 1998). The behaviour of all the staff in relation to customers concerning both the collection and dissemination in a formal and an informal way is included in the customer orientation dimension; in so far as in young high-technology firms, the interfunctionality between departments of the firm is rare. The competitor orientation dimension takes into account the same modifications and concerns present and potential competitors. The reactivity of the firm deals with measures taken to take into account market information, to detect significant changes and to respond quickly to the market. A questionnaire was constructed to collect information on the behaviour of the high-technology small firm managers. Respondents were required to indicate the degree to which each dimension was present in their firms, using a six-point Likerttype scale.

Methodology An electronic e-mail survey was administered to 575 French young high-technology firms located in incubators. The questionnaire was tested with five managers of hightechnology firms located in incubators. The structure of the questionnaire was varied to avoid repetition bias since the format of the questions was repetitive (see appendix). Managers were sent one reminder. A total of 110 firms responded which yielded a usable response of 101 fully completed questionnaires. The profile of the respondents is given in Table 2. The geographical location and the sector activity of the firms correspond to French institutional classifications and are significant to this study in so far as the database for the mailing list was created using the official list of incubators of Metropolitan France where the activities of high-technology firms are identified. The sample appears relatively balanced concerning geographical location, except for the North East. From a sectoral viewpoint, firms of the sample were distributed in a balanced way when compared with the institutional classification except for the second class because firms in these activities (agriculture, space and aerospace) are often bigger and older. Since our work concerns young high-technology firms, ‘age’ gives us the stage of maturity of the firm, which can influence its behaviour concerning market orientation. Young high-technology firms located in incubators were normally less than 3 years old. In the literature, firms are considered in the first stages of their development until they are 8 years old, and this explains our age classes. It was noted that they were reasonably balanced, except that the ‘less than 1 year’ category was only 7.9%. We can explain this result by the newness of the firm, where in such instances, the manager is preoccupied with the start-up and rarely responds to survey requests. Concerning the employment, we can see that a majority of young high-technology firms of the sample were very small (where 78.3% had less than 10 employees). This

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Table 2: Characteristics of the sample. Percent of Sample Geographical location North East North West South East South West North and Ile de France (Paris)

6.9 25.7 25.7 18.9 22.8

Sector of activity Biotechnology and health Agriculture, space and aerospace Information and communication technology Energy, transport and environment Other

26.4 4.5 36.4 28.2 4.5

Age Less than 12 months 12–24 months 24–36 months 3–5 years More than 5 years

7.9 25.7 19.8 27.8 18.8

Employees Less than 5 5–10 10–20 More than 20

40.6 37.7 15.8 5.9

small size characteristic is relevant to market intelligence generation, market intelligence dissemination and reactivity to market information. As explained earlier, this is one of the reasons why the market orientation concept needed adaption. Results were analysed using Sphinx and SPSS. An exploratory factor analysis with Varimax rotation was used. A typology was built through a hierarchical cluster analysis (i.e. the Ward method) and a non-hierarchical cluster analysis (the K-means method). The crosschecking rate was .71%.

Results The factor analysis allows us to identify four factors. The results are given in Table 3, with the percent of information for each item of each factor and their reliability using

All the staff spend time discussing competitors in an informal way (e.g. at the coffee machine) All the staff are concerned about the collection of competitor information All the staff spend time discussing customers in an informal way (e.g. at the coffee machine) All the staff are concerned about the collection of customer information All the staff spend time discussing customers in a formal way (e.g. special meetings) Our patent system provides information on our competitors Our patent system provides information on our customers We always watch our environment to protect our patent royalties In a systematic way, we protect our international patents We order studies about competitors, (fundamental or applied) technological evolutions We order studies about sectors, technologies or markets to obtain information about our customers We are quick to respond to significant changes concerning our indirect competitors We are quick to respond to significant changes concerning our direct competitors We collect customers information by informal means (e.g. lunch) from our trade partners (e.g. customers, distributors, competitors, industry members) Collaborations on developments with our customers provide information about the future evolution of our markets We collect competitors information by informal means (e.g. lunch) from our trade partners (e.g. customers, distributors, competitors, industry members) We always take into account information coming from our customers Cronbach’s alpha

Table 3: Market orientation factor analysis.

.85

.797 .796 .783 .765 .746

1

.80

.847 .833 .718 .674

2

.73

.661 .654

.826 .764

3

Components

.644 .68

.668

.681

.784

4

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Forms of Market Orientation in French Young High-Technology Firms

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Cronbach’s coefficient alpha. The overall coefficient alpha was .80, suggesting a relative weakness for factors 3 and 4, which can be explained by the sample size. The first factor concerns the behaviour of the staff concerning the collection and the dissemination of information on customers and competitors. The factor is characterised by the fact that all the staff are supposed to feel concerned about the collection of information on both customers and competitors and the staff spends time discussing both customers and competitors. Only information about customers is discussed by all the staff in a formal way. This can be explained by the fact that competitors are often considered non-existent, thanks to the innovation or the patent system. This factor was named staff share information. The second factor deals with the patent system that allows the firm to gather information about customers and competitors and to protect innovation. Although the patent system is a genuine tool for marketing, that allows the firm to collect intelligence and to react to the market in order to manage innovation, the sample firms seem not to use the patent system systematically (see appendix). The name given to this factor was patent. The third factor took into account all types of studies used to obtain information concerning market evolution and the reaction of the firm towards indirect and direct competitors. As the patent system is generally used to neutralise competitors, consideration of patents would reflect a broader consideration of the market. This factor was named market consideration. The fourth factor refers to the existence of a close relationship with customers to collect intelligence and to react to the market and the fact that informal means are used to collect information about customers and competitors. The key characteristic of this factor was the importance of the proximity of the information. Indeed, the characteristics of young high-technology firms (i.e. newness of the firm and technological development) explain the need of the manager and his or her team to more easily take account of this factor, which has been termed information closeness. The quality of the representation of most variables that constitute our factors (Table 4) is often greater than .5, except for variables that are less relevant in defining the factor, partly due to the reliability problems mentioned before caused by the sample size. The hierarchical cluster analysis allowed the identification of three clusters. Also, three different groups of firms were identified, along with four factors that discriminate between them: ‘staff share information’, ‘patent’, ‘market consideration’ and ‘ information closeness’. They allow prompt discussion of three forms of market orientation in French young high-technology firms. Q1: What different forms of market orientation are to be found among French young high-technology firms? The different forms of market orientation among the clusters are given in Table 5, which shows, for each cluster, the profile of mean scores across the four factors that discriminate them: ‘staff share information’, ‘patent’, ‘market consideration’ and ‘information closeness’. The profile of each cluster is indicated below. Analysis of the characteristics of demographics did not produce any significant links, but some trends are highlighted in Table 6. The age of the firm does not appear

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Table 4: Reliability analysis. Item to Total Alpha if Item Correlation Deleted All the staff spend time discussing competitors in an informal way (e.g. at the coffee machine) All the staff are concerned about the collection of competitor information All the staff spend time discussing customers in an informal way (e.g. at the coffee machine) All the staff are concerned about the collection of customer information All the staff spend time discussing customers in a formal way (e.g. special meetings) Our patent system provides information on our competitors Our patent system provides information on our customers We always watch our environment to protect our patent royalties In a systematic way, we protect our international patents We order studies about competitors (fundamental or applied) technological evolutions We order studies about sectors, technologies or markets to obtain information about our customers We are quick to respond to significant changes concerning our indirect competitors We are quick to respond to significant changes concerning our direct competitors We collect customers information by informal means (e.g. lunch) from our trade partners (e.g. customers, distributors, competitors, industry members) Collaborations on developments with our customers provide information about the future evolution of our markets We collect competitors information by informal means (e.g. lunch) from our trade partners (e.g. customers, distributors, competitors, industry members) We always take into account information coming from our customers

.684

.819

.653

.828

.637

.831

.704

.815

.666

.824

.743

.677

.659

.720

.548

.775

.498

.801

.651

.580

.558

.640

.429

.713

.437

.708

.603

.507

.414

.643

.421

.646

.425

.635

Forms of Market Orientation in French Young High-Technology Firms

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Table 5: Profile of mean scores for each cluster.

Staff share information Patent Market consideration Information closeness

Cluster 1 (n ¼ 33)

Cluster 2 (n ¼ 41)

Cluster 3 (n ¼ 27)

F

p

.01026

 .32893

.48695

5.958

.0004

 .51960 .49276 .87565

 .20831 .05609  .84607

.95140 –.68743 .21454

26.533 12.948 62.099

.0000 .0000 .0000

Table 6: Demographics of the clusters. Cluster 1 (n ¼ 33) Sector of activity Geographical location Staff number

Transport and environment North 18.42

Cluster 2 (n ¼ 41) All South West and Ile de France o10

Cluster 3 (n ¼ 27) Biotechnology and health South East 17

as a variable able to discriminate among the clusters found. Nonetheless, it is in cluster 2 that we find the largest number of young firms. Cluster 1 is characterised by ‘market consideration’ (.49) and ‘information closeness’ (.87). The sources of the information collected are predominantly informal, and proximity renders such knowledge more accessible to young hightechnology firms. ‘Market consideration’ is an informal but nonetheless useful variable, and for this reason we propose to name this cluster informal market orientation. Cluster 2 is characterised by category of firms that is indifferent to the dimensions of market orientation proposed above to be important for young high-technology firms. This cluster is dominated by the younger firms of the sample. Compared to Greenley’s (1995) results, we consider this a cluster with what we term undeveloped market orientation. However, the youth of these firms suggests that the fact they have not developed a strong market orientation may be due to their age rather than to the unwilling of their managerial teams. This might be explained by the possibility that the need to commercialise is not necessarily strong for high-technology firms at the time of formation. Cluster 3 is characterised by the dimensions of ‘patent’ (.95) and ‘staff share information’ (.48). The behaviour of firms in this cluster is dominated by the technological dimension of the firm. The management of the firm is based on

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intellectual property protection through patents. Thus, logically, practices are the opposite of those we find with ‘market consideration’. Although the collection of information on customers and competitors is not considered superfluous, it is achieved, in part through the patent system of the firm. Moreover, we can note that this cluster is dominated by biotechnology and healthcare activities, where the level of research and development is generally high. Based on this analysis, Cluster 3 is termed technologically market oriented. Q2: What are the factors that discriminate between the different forms of market orientation? T distinguish between the different forms of market orientation, a discriminant analysis model was constructed, based on the above factors. The aim was to identify discriminating factors. The analysis produced two canonical discriminant functions. Their correlations with the discriminant factors are given in Table 7, along with their respective test statistics. As Table 7 shows, the two canonical discriminant functions account for 100% of the variance. Function 1 covers ‘market consideration’ and ‘information closeness’, as opposed to ‘patent’ and it appears to represent an aspect of market intelligence. The common theme of these three factors is the collection of information by all means possible encompassing, on the one hand, the market and, on the other hand, the technology. This function, comprising two factors, accounts for 53.4% of the variance (canonical correlation .794) and confirms the importance of market intelligence. Function 2 covers ‘information closeness’, ‘staff share information’ and ‘patent’ and appears to represent a technological bias. For this function, market intelligence is also characterised by proximity and its link with the patent system, but the importance of information dissemination emerges because all the staff feel concerned with the technological dimension of the relationship with customers and for the firm’s evolution in its competitive environment. In this case, Function 2

Table 7: Pooled (within group) correlations between discriminating variables and canonical discriminant functions. Function

Staff share information Patent Market consideration Information closeness Percent of variance Canonical correlation Wilks’ lambda w2 Significance

1

2

 .174  .808 .769 .635 53.4 .794 .149 183.802 .000

.610 .561  .338 .796 46.6 .773 .402 87.866 .000

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accounts for 46.6% of the variance (canonical correlation .773). Therefore, the technological dimension of the firm appears important for distinguishing between the different forms of market orientation. Our four factors are thus important in distinguishing between the different forms of market orientation.

Discussion The results of this study have extended previous empirical studies by investigating the nature of market orientation in the context of young high-technological firms. They show that different forms of an adapted market orientation dimension are to be found among these organisations. These different forms reflect different ways in which companies focus on market-related phenomena, highlighting four factors that characterise the specific orientation of young high-technology firms such as ‘patent’, ‘information closeness’, ‘staff share information’ and ‘market consideration’. However, this is only an exploratory study, and the above results have not been validated against external data or previous studies. Moreover, the general limitation of using Likert-type scales is relevant here. It may be that the respondents were not inclined to score items at the bottom of the scale, even if they consider that their firms rate poorly, thus preferring to score most variables higher up the scale, to demonstrate effective leadership. However, the mean score of all items and their standard deviation (see appendix) suggest that this type of bias is not really a problem in this study.

Discriminating Factors and Behavioural Differences The factors that discriminate between the forms of market orientation in young hightechnology firms highlight traditional dimensions of market orientation that have been termed ‘market consideration’ and ‘staff share information’ and integrate specific dimensions of young high-technology firms like ‘patent’ and ‘information closeness’. The dimension of ‘market consideration’ is clearly distinguished from that of ‘patent’. When the young high-technology firm is protected by the patent system, the patent becomes a real tool for marketing by allowing the firm to collect information on both customers and competitors (Petzold-Dumeynieux, 2002). Moreover, the patent protects the firm from competitors. In these conditions, the firm does not feel obliged to pursue its market to the same extent. When the firm does choose to take its market into account, the primary pursuit of customers and competitors are more important to understand their competitive environment. We cannot say whether the behaviour related to market consideration influences the implementation of specific types of strategy in a more or less aggressive way (Dobni & Luffman, 2000) or in a more or less efficient way (Homburg, Krohmer, & Workman, 2004).

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Our Cluster 1, characterised by ‘market consideration’, is sharply opposed to Cluster 3, being characterised by a ‘patent’ orientation. Cluster 1 was also characterised by ‘information closeness’. This factor highlights the newness of young high-technology firms, for whom it is more convenient to collect information in informal ways (Jones-Evans, 1997). Such proximity is linked to credibility in so far as customers are an important source of information in the process of innovation (Lauglaug, 1993). Cluster 3 is also characterised by ‘staff share information’. Here too the newness of young high-technology firms appears relevant. All the staff are concerned to generate market intelligence and its dissemination within the firm and this is a form of interfunctionality (Narver & Slater, 1990). This behaviour is more easily associated with ‘patent’ in so far as the workforce of young high-technology firms is comprised of engineers, technicians and researchers. In this case, the firm is market oriented, but with a technological bias. This technological tendency is often useful when the main activity of the firm is research and development. In this case too, ‘information closeness’ can be important because of the uncertainty of the innovation process. Indeed, the usefulness of ‘information closeness’ is linked to both entrepreneurship and innovation. Here, this factor is associated positively with only one cluster (i.e. Cluster 1). Thus, some young high-technology firms appear more likely to seek market intelligence in both formal and informal ways. Other firms seem to adapt their market orientation to the technological dimension of the firm, when they are more oriented towards the internal skills of the firm than external actors because they are protected by the patent system. Finally, Cluster 2 appears to not have a market orientation, which is perhaps due to their youth, and the fact that they are essentially oriented towards the innovation process through research and development. This explanation appears logical, but contradicts the fact that young high-technology firms are also heavily supported by institutional networks put in place to encourage firm creation and innovation. In this context, mangers are encouraged to develop a market orientation within their firm. Since the marketing practices of small firms are strongly linked to the motivations, beliefs attitudes and objectives of their managers (Siu & Kirby, 1998), it is feasible that the institutional support encourages young high-technology firms to develop a higher level of market orientation at an early phase of their development. Nevertheless, except for this group of firms that are not market oriented, our results show that, contrary to what might be expected, many young high technology firms are market oriented, even if this takes rather unusual forms, given their characteristics.

Future Research As the above approach has only given us a ‘snapshot’ of the phenomenon under analysis, we need to conduct case studies on firms from each cluster to develop a

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more in-depth understanding of the learning dynamics that are occurring over time in these organisations (Slater & Narver, 1995). As the age of the firm is not a general discriminator, except for Cluster 2, we suggest that many emerging high-technology firms begin life in the Cluster 2, and then go into 1 or 3, unlike others enter directly into 1 or 3. However, it is also worth considering whether young high-technology firms pass from 1 to 3 or from 3 to1 and, if so, when and for what reasons? We have highlighted the importance of the activity of the firm if it is oriented to a greater or lesser degree towards research and development, but the question of this type of learning organisation needs to be addressed in more detail. In addition, according to Chaston (1998), the marketing style that is adopted by a young high-technology firm depends on two criteria: namely closeness to the customer (which we have taken into account in the dimension of customer orientation) and the level of entrepreneurial activity. It appears to us that inclusion of the dimension of entrepreneurial orientation would permit a more refined analysis of the practices and, therefore, of the forms of market orientation young hightechnology firms might take.

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Appendix. Market Orientation in Young High-Technology Firms Scale

Customer Orientation Dimension 1. We order studies about sectors, technologies or markets to obtain information about our customers 2. We collect customer information by informal means (e.g. lunch) from our trade partners (e.g. customers, distributors, competitors, industry members) 3. We use institutional networks of innovation to collect information about our customers 4. We do in-house market research to collect customer information 5. Our patent system provides information on our customers 6. Collaborations on developments with our customers provide information about the future evolution of our markets 7. All the staff are concerned about the collection of customer information 8. All the staff spend time discussing customers in a formal way (e.g. special meetings) 9. All the staff spend time discussing customers in an informal way (e.g. at the coffee machine) Competitor orientation dimension 10. In a systematic way, we protect us with national patents 11. In a systematic way, we protect us with international patents 12. We order studies about competitors’ (fundamental or applied) technological evolutions 13. We collect competitor information by informal means (e.g. lunch) from our trade partners (e.g. customers, distributors, competitors, industry members) 14. We use institutional networks of innovation to collect information about our competitors 15. We do in-house market research to collect competitor information 16. Our patent system provides information on our competitors

Mean

Standard Deviation

3.44

1.78

5.13

1.10

2.76

1.53

3.92

1.78

3.18

2.05

5.40

.88

4.52

1.26

4.63

1.45

4.91

1.36

3.75

2.04

3.75

2.07

3.05

1.63

4.61

1.15

2.84

1.62

3.59

1.80

3.67

1.99

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229

Appendix (Continued ) 17. Collaborations on developments with our customers provide information about the future evolution of our competitive environment 18. All the staff are concerned about the collection of competitor information 19. All the staff spend time discussing competitors in a formal way (e.g. special meetings) 20. All the staff spend time discussing competitors in an informal way (e.g. at the coffee machine) Reactivity 21. We always take into account information coming from our customers 22. We always take into account information coming from our distributors 23. We always take into account information coming from our licence users 24. We are quick to detect significant changes concerning our customers 25. We are quick to detect significant changes concerning our competitors 26. We are quick to respond to significant changes concerning our customers 27. We are quick to respond to significant changes concerning our direct competitors 28. We are quick to respond to significant changes concerning our indirect competitors 29. We are always looking for satisfying our customers if their demands are reasonable 30. We always watch our environment to protect our patent royalties

5.04

1.07

4.38

1.24

3.75

1.68

4.21

1.47

5.32

.93

5.17

1.39

5.78

1.64

4.37

1.03

4.25

1.25

4.47

1.31

3.82

1.41

3.56

1.54

5.76

.79

4.08

1.81

Note: Instructions were given to respondents that customers should be understood as present and latent customers and competitors should be understood as present and latent competitors.