Innovation in Knowledge Intensive Business Services: The Digital Era 2019029029, 9780367341916, 9780429324390

Citation preview

Innovation in Knowledge Intensive Business Services

Knowledge Intensive Business Services (KIBS) are becoming more and more relevant both for their innovative content and as innovation boosters for manufacturing firms and, with this scenario in mind, this book first offers an in-depth analysis of what innovation in KIBS is and its performance outcomes, and then synthesizes what we know about KIBS firms’ innovation models, as well as their specific peculiarities and limitations. This book examines the recent trends in innovation, service design and development in KIBS, starting from a review of the extant literature, explaining the role and specific traits of innovation in KIBS. Then, it progresses our knowledge about KIBS and about how new technologies are offering unique opportunities to use and share their knowledge, within and across boundaries. The book also includes several cases that show how, at the micro level, firms can effectively design their services and boost their innovation performance by overcoming some of the traditional limits of innovation in services. While KIBS literature traditionally emphasizes that innovative and performing KIBS firms rely on tight client–provider interactions with service customization, recent research suggests that alternative modes of innovation are viable for performing KIBS firms: KIBS firms can develop mass customization strategies, ease interactions with clients via ICT interfaces and leverage on focused collaborations with expert clients. Particularly, the digitalization and ICT technologies are fostering platform and modular architectural designs of KIBS, as in the software and web design services. The book seeks a broader understanding of innovation in KIBS in the digital era and will be an essential guide for both academics and practitioners interested in KIBS innovation and design. Anna Cabigiosu is Associate Professor of Strategy and Innovation Management at Ca’ Foscari University of Venice (Italy), Department of Management. Anna received her Ph.D. in Economics and Management from the University of Padua, Italy. She was visiting Ph.D. student at the Ross School of Business (USA), and received a master’s degree in Business Management at the Ca’ Foscari University of Venice, Italy. Her research interests include innovation management, product and service modularity, and the study of the architecture of complex systems. Her research mainly focuses on the automotive, KIBS and fashion industries. Anna is the scientific director of the IOS (Innovation, Organization and Strategy) research centre and is the executive director of CAMI (Center for Automotive and Mobility Innovation) of the Ca’ Foscari University.

Routledge Studies in the Economics of Innovation

The Routledge Studies in the Economics of Innovation series is our home for comprehensive yet accessible texts on the current thinking in the field. These cutting-edge, upper-level scholarly studies and edited collections bring together robust theories from a wide range of individual disciplines and provide in-depth studies of existing and emerging approaches to innovation, and the implications of such for the global economy. Automation, Innovation and Economic Crisis Surviving the Fourth Industrial Revolution Jon-Arild Johannessen The Economic Philosophy of the Internet of Things James Juniper The Workplace of the Future The Fourth Industrial Revolution, the Precariat and the Death of Hierarchies Jon-Arild Johannessen Economics of an Innovation System Inside and Outside the Black Box Tsutomu Harada The Dynamics of Local Innovation Systems Structures, Networks and Processes Eva Panetti Innovation in Knowledge Intensive Business Services The Digital Era Anna Cabigiosu For more information about this series, please visit: www.routledge.com/ Routledge-Studies-in-the-Economics-of-Innovation/book-series/ECONINN

Innovation in Knowledge Intensive Business Services The Digital Era

Anna Cabigiosu

First published 2020 by Routledge 2 Park Square, Milton Park, Abingdon, Oxon OX14 4RN and by Routledge 52 Vanderbilt Avenue, New York, NY 10017 Routledge is an imprint of the Taylor & Francis Group, an informa business © 2020 Anna Cabigiosu The right of Anna Cabigiosu to be identified as author of this work has been asserted by her in accordance with sections 77 and 78 of the Copyright, Designs and Patents Act 1988. All rights reserved. No part of this book may be reprinted or reproduced or utilised in any form or by any electronic, mechanical, or other means, now known or hereafter invented, including photocopying and recording, or in any information storage or retrieval system, without permission in writing from the publishers. Trademark notice: Product or corporate names may be trademarks or registered trademarks, and are used only for identification and explanation without intent to infringe. British Library Cataloguing in Publication Data A catalogue record for this book is available from the British Library Library of Congress Cataloging-in-Publication Data Names: Cabigiosu, Anna, author. Title: Innovation in knowledge intensive business services : the digital era / Anna Cabigiosu. Description: Abingdon, Oxon ; New York, NY : Routledge, 2020. | Series: Routledge Studies in the Economics of Innovation Identifiers: LCCN 2019029029 Subjects: LCSH: Intellectual capital. | Service industries. | Knowledge economy. | Technological innovations--Economic aspects. | Information technology--Economic aspects Classification: LCC HD53 .C33 2020 | DDC 658.4/063--dc23 LC record available at https://lccn.loc.gov/2019029029 ISBN: 978-0-367-34191-6 (hbk) ISBN: 978-0-429-32439-0 (ebk) Typeset in Bembo by Taylor & Francis Books

To Giovanni Maria, my father Pale a prora

Contents

List of tables Introduction

x 1

PART I

Presenting KIBS firms

5

1 What are KIBS firms?

7

The service industry in the knowledge economy 7 KIBS firms 10 KIBS firms: A classification 12 KIBS firms: The main traits 14 2 The growing importance of KIBS in today’s economy

19

KIBS are bridges of innovation 19 New technologies for KIBS firms 24 Internationalization and globalization in KIBS 26 T-KIBS and p-KIBS in the Industry 4.0 paradigm 27 PART II

Innovation in KIBS 3 Multiple forms of innovation in services and in KIBS Innovation in services 35 Product and process innovations 37 Adding layers of innovation: From the concept to the interface 40 Do we really need specific categories of innovation for KIBS firms? 44

33 35

viii Contents 4 Measuring innovation in KIBS

50

The sources of innovation 50 Internal sources 50 External sources 51 The output of innovation activities: Timing and differentness 53 The timing of entry 54 Differentness 57 5 The specific traits of innovation in KIBS

62

Customization and client collaboration 62 The role and contribution of KIBS firms in the innovation process of their clients 67 Sharing knowledge with clients 70 Open innovation in KIBS 71 PART III

Innovation and performance in KIBS 6 Innovation and performance in KIBS: The empirical evidence

79 81

Innovation and growth in KIBS 81 Innovation, service types and performance in KIBS 84 Complementarities between innovation, service types and firms’ performance 85 Configurations of the best-performing service types and innovations 86 7 The productivity dilemma and digitalization in services

93

The growth of services, servitization and the productivity dilemma 93 Digitalization and the productivity dilemma 95 Measuring productivity in services 97 Productivity in KIBS 99 Service innovation and productivity: The empirical evidence 100 8 A critical view: How much do collaboration and customization support KIBS firms’ innovative performance? Client collaboration and KIBS firms’ innovativeness 103 Client collaboration, customization and KIBS firms’ innovative performance 105

103

Contents

ix

PART IV

Moving the innovation model in KIBS forward 9 Digitalization and internationalization in KIBS

113 115

Internationalization in KIBS and its drivers 115 Digitalization and internationalization: Opportunities and threats 118 10 Platforms and modularity in KIBS

123

Modularity in services: A new perspective 123 Modularity and platforms in services 125 Modularity in KIBS 127 Distinguishing modularity in products, in services and in KIBS 130 11 Modularity in software and web design

138

Modularity in software 138 Modularity in web design 140 Conclusions Index

147 153

Tables

6.1 Configurations and core conditions for achieving higher profitability (ROI) and higher growth (market share) 8.1 The relationship between “product innovations new to the industry” and “sales growth” for different combinations of the variables “clients’ collaboration” and “service customization”.

87

107

Introduction

Especially in the USA, but also in Europe, there are already algorithms that help professionals to carry out their activities to the point of partially substituting their work: software capable of seeking the most likely outcome of a lawsuit and programs able to carry out the due diligence for an accountant, to pre-set up a contract and to conduct independent research on the Web. In France and the USA, software exists that uses artificial intelligence and algorithms that promise to help lawyers in the process strategy, because they can extract from documents how certain judges decide certain types of cases, such as the position of the law, or even the opinion of a single judge on a certain subject, helping to choose the best strategy. Digital innovations are becoming part of knowledge intensive services. Traditionally, in services, new technologies served as tools to improve the service delivery process. However, advances in digital technologies have modified service innovation at its core, and today service innovation is more digital in nature. Services are translated into digital bits, stored across multiple geographical locations and available almost everywhere in real time via the Web. Service providers can also collaborate and communicate more easily with digital tools, exchanging immediate feedback. The openness of this scenario offers generative and unbounded opportunities, resulting in new service innovation opportunities that may not have been foreseen originally. This phenomenon is called digitalization and refers to “the encoding of analogue information into digital format and the subsequent reconfiguration of socio-technical context of production and consumption of the product and services” (Yoo, 2012). Today, digitalization is a key source of innovation in services and calls for specific contributions to understand service innovation in the digital age and the transformative role of digital technologies. Emerging digital technologies allow product and service innovation but are also challenging many firms that lack the required competences. In this context, web designers, software developers, consultants, marketers, R&D firms and engineering service providers are examples of knowledge intensive business services (KIBS), which are becoming more and more relevant both for their innovative content and use of digital technologies and as innovation boosters for manufacturing firms. KIBS have increasingly attracted the attention of scholars in the last 20 years as their role in

2

Introduction

the knowledge economy has increased. KIBS firms are continuously involved in the knowledge transfer with clients, research centres, universities and other organizations, and are high in terms of human capital compared with firms in other sectors. With this scenario in mind, this book first offers an in-depth analysis of what innovation in KIBS is and its performance outcomes, and synthesizes what we know about KIBS firms’ innovation mode, its peculiarities and its limits. Then the book expands our knowledge about KIBS and about how new technologies are offering unique opportunities to KIBS to use and share their knowledge, within and across their boundaries, redesign their services and increase their innovation performance by overcoming some of the traditional limits of innovation in services. This book seeks a broader understanding of innovation in KIBS in the digital era and aims at describing the recent trends in innovation, service design and development in KIBS. While the KIBS literature traditionally emphasizes that innovative and performing KIBS firms rely on tight client–provider interactions with service customization, recent research suggests that alternative modes of innovation are viable for performing KIBS firms: KIBS firms can develop mass customization strategies, ease interactions with clients via ICT interfaces and leverage focused collaborations with expert clients. Particularly, digitalization and ICT technologies are fostering platform and modular architectural designs of KIBS, as in the software and web design services. In the first chapter, the book presents the main definitions and classifications of KIBS firms and of the related industries. The aim is to present this specific category of services to a general audience. Then (in Chapter 2), the book underlines the role of KIBS in today’s economy and in the Industry 4.0 paradigm, emphasizing that they are “bridges” of innovation that both provide crucial services to manufacturing firms and can benefit from the new technologies to manage their offer and growth. This section also provides multiple examples of how digitalization is shaping the business model of KIBS. In Chapter 3, building on the extant literature, I describe the main categories of innovation in KIBS, distinguishing between product, process, concept, technological, organizational and interface innovations. This section also provides multiple examples of innovation in KIBS. Finally, the chapter synthesizes the existing debate within the innovation management literature about the need to use different categories of innovation to study innovation in KIBS, services and products. After having identified multiple categories of innovation in KIBS, Chapter 4 investigates how the KIBS literature measures innovation and specifically focuses on KIBS services’ differentness (or radicalness) and novelty, while Chapter 5 discusses the specific traits of innovation in KIBS: the customized nature of the service, the client–supplier interaction in service design and production, the relevance of open innovation strategies and of knowledge workers and the contribution of KIBS firms to the innovation process of their clients. Chapter 6 reviews the existing literature about innovation and performance in KIBS to understand how the identified categories of innovation, their novelty and their differentness affect multiple performance measures and which areas of research are underdeveloped, while Chapter 7 introduces the productivity

Introduction

3

dilemma. KIBS are often customized and intangible and cannot be stored. KIBS and service literature published over many years suggests that these properties negatively affect the impact of innovation on KIBS firms’ productivity and growth. This chapter discusses this assumption and the way in which digital technologies are modifying this scenario. Chapter 8 puts forward a critical view about if and to what extent collaboration and customization support KIBS firms’ innovative performance. There may be another “face of the coin” for both customization and clients’ engagement in innovation activities, and KIBS firms may combine different levels of customization and collaboration with clients. This chapter presents the theoretical arguments and the empirical evidence provided so far that question the emphasis on client collaboration and KIBS customization, delivers new hypotheses about how KIBS firms should design their service portfolio and client relationships and concludes by introducing the topic of mass customization in KIBS. After having presented and critically reviewed the innovation literature in KIBS, Chapter 9 explains how new ICT technologies help KIBS firms to increase their level of internationalization. New technologies allow many traditional barriers of service replicability and exportability in foreign markets to be overcome. Examples are provided. Finally, Chapters 10 and 11 explain in detail how mass customization strategies are eased by new design approaches and by digital technologies. Platform and modular designs are the pillars of a mass customization strategy. Chapter 10 explains what modularity and platforms are in KIBS and provides multiple examples. This section also briefly synthesizes what modularity is in products and services to help the readers understand the specific features of modularity in KIBS. Finally, Chapter 11 focuses on modularity in software and websites, which are undergoing a profound architectural change and today are converging overall toward a modular structure. Many of the ideas proposed in this book originate from my previous studies about KIBS firms that I have co-developed with Diego Campagnolo. Our joint work has been a fundamental source of inspiration for my research. I am also grateful to Francesco Zirpoli, Giovanni Costa, Andrea Furlan, Roberto Grandinetti, Eleonora Di Maria, Barbara De Bernardo, Stefano Li Pira and all the colleagues who have supported my work.

References Yoo, Y. 2012. Digital materiality and the emergence of an evolutionary science of the artificial. Materiality and Organizing: Social Interaction in a Technological World, pp. 134–154.

Part I

Presenting KIBS firms

1

What are KIBS firms?

This chapter presents KIBS firms, what they are, their relevance to the knowledge economy and their main features.

The service industry in the knowledge economy After World War II, the service sector arose in many developed countries, which moved from being manufacturing-based economies to being so-called knowledge-based economies. This shift is labelled “servitization”1 (Drejer, 2004). As a result, most of these economies today depend for the larger part of their GNP (gross national product) on services (Nijssen et al., 2006), which contribute over 70% of the employment in the OECD (Organisation for Economic Cooperation and Development) countries2 (Baltacioglu et al., 2007). Services include a heterogeneous set of activities from consumer services to business to business services. Traditionally, services were defined through a process of exclusion, which proceeds by identifying production industries and considering everything else as being part of the tertiary sector. This view has now changed thanks to the growing importance of this sector, and authors have provided multiple definitions and classifications of services (Metcalfe and Miles, 2000). Miles et al. (1995) classifies services on the basis of the functions performed and the markets served, and identifies the following groups: product services such as finance or business services; distributive services such as trade, transport and communication; personal services such as entertainment, hotels, catering and domestic services; and social services such as those related to medicine, health and government. Gadrey, Gallouj and Weinstein (1995) more generally define service providers as firms that organize a solution to a problem that does not principally involve supplying a good. Service firms put a bundle of capabilities and competences (human, technological and organizational) at the disposal of clients and use them to satisfy their needs. Generally, value creation in services is driven by the integration of intangible resources and capabilities, such as knowledge, competences, a cognitive-centric workforce and customer collaboration (Scerri and Randhawa, 2015). Sometimes tangible resources are also involved in service delivery, such as the use of cards in

8

Presenting KIBS firms

banking services, increasing the complexity of the distinction between products and services. Additionally, reseachers highlight the elements that distinguish services from products (Tether and Hipp, 2002). The first is the close interaction between production and consumption: services cannot be provided if the service user and the service provider do not contemporarily take part in the provision. Authors use the concept of inseparability to refer to the simultaneous provision and consumption of services. The client co-produces the service and is included in the processes of both providing and consuming the service. The contextual delivery and use of services generate multiple issues, such as the planning of the offer capacity and the management of queues. Perishability refers to the nature of services that cannot be kept or stored for later utilization. For example, the productivity of an emergency depends on patients’ needs, and patients with exactly the same disease may require different treatments depending on their age and general conditions. The second is the intangible nature of services’ output: services are defined by Pennant-Rea and Emmott (1983) as “the fruits of economic activity which you cannot drop on your foot”. The output of service firms is intangible and more difficult to appreciate and measure quantitatively. Because of their intangible nature, services tend to have a vaguer relationship between what is produced (i.e. the service product) and the process of production. Indeed, both service input and service output are difficult to estimate and evaluate. Third, human resources have a crucial role in service provision that is shaped by human resources’ knowledge endowment and capabilities, which are used directly when each transaction occurs, rather than the physical plant or equipment (Gallouj and Weinstein, 1997). For this reason, innovation in services often involves asking people to change what they do and how they do it, and this may meet several forms of resistance. Fourth, firms’ organization and supporting technologies are also central to service performance. The service cannot be separated from the process of provision, and the service provider and user are located at the same time in the same physical space. For this reason, their provision is often local and limited to a small scale. Conversely, today, more modern services, in particular those that rely on digital technologies, can relax some of these constraints: a growing number of services do not need to be provided in close proximity to the user but are provided via the Internet and websites instead of a human interface. This happens for many banking, rental and booking services. Other services, such as restaurants and cleaning, still display the features mentioned. Consequently, there is a strong relation between the technology employed by service firms and the way in which the firm is organized for the service provision and delivery, which in turn has implications for the nature of the service provided and its competitiveness. The fifth element is the weakness of intellectual property protection in services. Usually, patents and trademarks are not employed by service firms because they often fail to protect intangible products. For this reason,

What are KIBS firms?

9

competitors may quickly copy successful services, and companies may thus tend to focus their innovative efforts on back-office and process innovations, which are considered to be less imitable. The final element is the importance of client participation during service design and delivery, or co-production during service provision, which creates a bond between the service provider and the client during the provision of the service. Clients give the inputs to initiate the service provision, such as the information that clients give to banks about the risks that they are willing to support for their investments, and interact during the definition of the service features by specifying their needs better and giving real-time feedback about the service’s coherence with their desires. Many services are provided by humans via face-to-face interactions with clients, and these services are dependent on humans’ knowledge and capabilities. While service providers also rely on tools and technologies such as computers, socialization skills embodied in individuals (or teams) are still crucial for the success of service provision. Overall, such service specificities explain why services are heterogeneous in nature and heterogeneity describes the variability of the results when providing services. While the attributes listed represent the main peculiarities of services identified so far by the economic and managerial literature and influence deeply the way in which service firms innovate and conduct their business (Mustafa, 2019), a number of scholars argue in studies undertaken in the last decades that the leading edge of the economy has become driven by knowledge production and dissemination that nurture both products and services. Particularly, innovation today is often driven by the commercial application of new knowledge and has become one of the key drivers of growth in services. Accordingly, the ability to create and manipulate knowledge has become a strategic element, a source of competitive advantage and a critical factor for the production of value added in all sectors. The importance of knowledge in today’s economic environment is reflected by the term “knowledge economy”, coined to refer to a segment of the economic system in which value is produced through knowledge or in which the most important commodity to be produced and consumed is information rather than manufactured goods. Specifically, this is an economy in which the share of knowledge intensive employment is prevalent, the economic weight of the sectors linked to information has become decisive and the share of intangible assets has exceeded the share of tangible ones (Powell and Snellman, 2004). Unlike other productive factors, knowledge has no reproduction costs (or at least much lower ones than the cost of generation) and is a resource that can be multiplied. Its value in use can in fact be very high, regardless of the cost, if the same knowledge is reused thousands or millions of times. Each new replication and each new application increase the useful value of the knowledge possessed, without increasing (or at least to the same extent) the costs. Today, new ICT technologies allow firms more easily to store and share knowledge, which is becoming an economic renewable resource.

10

Presenting KIBS firms

In this context, in the last decades, we have observed the growing importance of those services that base their competitive advantage on the ability to generate new knowledge. These services are labelled KIS (knowledge intensive services) and describe service firms that rely on professional knowledge or expertise relating to a specific technical or functional domain to satisfy the needs of either private consumers or business clients. Examples include accounting, bookkeeping, construction, banking and environmental, marketing, R&D, real estate and telecommunication services (Windrum and Tomlinson, 1999). In Europe, KIS have been among the most dynamic for growth since the mid-1980s. The number of knowledge intensive services has more than tripled in European countries over the last 30 years, and today 30% of workers (generating the same percentage of value added) are employed in KIS. In 2006, around 70 million people in the EU27 worked in knowledge intensive services (Eurostat, 2008). The growing importance of knowledge intensive services has also affected manufacturing firms’ activities. To stay competitive, firms increasingly need to rely on ICT services to manage multiple processes as well as on a number of other knowledge intensive activities, such as R&D, design or legal services, which deserve attention, investments and specific competences. For this reason, they assisted in the growth of the service firms providing these services and operating in the business-to-business sector. Manufacturing firms are increasingly paying expert service providers to manage specific activities or functions, while they focus on their core competences and on the related processes, with growing importance of service industries in the production of value. These service companies, which are specialized in the development of knowledge intensive business services and develop tailored solutions for their business clients, are defined by the term KIBS (knowledge intensive business services). KIBS are organizations for which the primary activities depend on human capital, knowledge and skills, and their role consists of providing knowledge intensive inputs for the business processes of other firms (Muller and Doloreux, 2009). KIBS are one of the pillars on which the “knowledge economy” is based in that they offer knowledge intensive services to other firms and public institutions, thus supporting knowledge sharing and creation. In this sector, knowledge can be considered as the most relevant resource to increase new competencies and as a precondition for the generation of innovative services (Doloreux, Turkina and Van Assche, 2018). The next sections describe KIBS firms and their characteristics.

KIBS firms The relevance and diffusion of KIBS firms The main content of KIBS firms’ offerings is knowledge, their services provide knowledge intensive support for the business processes of other organizations with a highly educated workforce and their clients usually co-produce the service solution (Vargo and Lusch, 2004). KIBS firms are business-to-business

What are KIBS firms?

11

service firms that include professional, ICT, design and communication firms (Bettencourt et al., 2002). KIBS have increasingly attracted the attention of scholars in the last 20 years as their role in the so-called “knowledge economy” has increased (Pina and Tether, 2016). KIBS firms in Europe are generally micro enterprises with fewer than 10 employees (Muller and Zenker, 2001) and are estimated to represent on average 15% of the volume of business of market services in European economies as well as being the main activity of 3.2 million firms in the EU-27 in 2005 (Eurostat, 2008). Over the last three decades, the number of KIBS firms has drastically increased in Europe due to both the increased inter-industry linkages and the attempts of European economies to consolidate their knowledge-based economies. In this context, KIBS offer specialized expertise to other businesses and use their accumulated knowledge to engage in and foster innovation processes. KIBS have become crucial to the evolution of manufacturing businesses: by outsourcing their non-core activities to KIBS firms, manufacturing firms obtain superior efficiency and more focused business models. There are several regions in Europe where KIBS employees account for more than 11% of the population. The regions with the highest levels of employment in KIBS are the south of England and Ireland, some regions of France (the province of Paris and the south-east), Catalonia in Spain and several provinces of Germany, including Berlin. Overall, central Europe is dominated by areas with at least 7–8% of the population employed in KIBS, while, in Italy, KIBS firms are mainly located in the north and in the Lazio region (Schricke, Zenker and Stahlecker, 2012). Corrocher and Cusumano (2014) show that KIBS are mainly located in the European capitals, with the exception of Hamburg in Germany and Utrecht in the Netherlands. Metropolitan areas are home to many KIBS and manufacturing companies and are regions with high levels of education and infrastructures. These areas are able to attract and retain entrepreneurs and a skilled workforce. Urban agglomeration favours the growth of KIBS. The authors also rank the European regions according to the presence of KIBS (percentage of employees), manufacturing (percentage of employees) and gross domestic product growth from 1999 to 2006. In this way, they are able to identify areas with a p revalence of KIBS firms (KIBS-intensive areas), areas with a prevalence of manufacturing enterprises (core manufacturing areas), areas in which service firms are growing but not yet dominant (tertiarizing regions), developing regions (catching-up regions) and finally lagging regions. From this analysis, the authors confirm that KIBS are concentrated in smaller but very dynamic and relevant regions for the global economy, corresponding to the main European capitals, while central Europe is still characterized by the importance of manufacturing firms.

12

Presenting KIBS firms

Despite the relevance of KIBS, studies are still needed about their diffusion and growth in many geographic areas, especially Asia (Horváth and Rabetino, 2019).

KIBS firms: A classification Using an encompassing approach, KIBS firms can be seen as “consultancy firms” in a broad sense and more generally as firms that perform services with high intellectual value added, mainly for other firms (Muller, 2001). KIBS firms typically operate in the following sectors: software and computer services (ICT), strategy and management consultancy, auditing, accountancy, tax and legal advice, marketing services, opinion pooling, technical services, engineering, personnel training and headhunting (Miles, 2005; Miles et al., 1995). According to the European Commission (2012), KIBS include those activities related to computing, information and communication technologies (NACE Rev-2: 62), architectural and engineering technical services (NACE Rev-2: 71), research and development (NACE Rev-2: 72), legal, accounting, auditing, management consultancy, advertising and market research services (NACE Rev-2: 69, 70, 73 and 78) and other knowledge-oriented services (NACE Rev-2: 74). Brenner et al. (2018) build on the existing literature and list the following KIBS NACE (Rev. 2) codes: 62.01, 62.02, 64.1, 64.2, 64.3, 64.9, 66.11, 69.2, 70.1, 70.2, 73.1, 73.2, 72.1 and 72.2. In addition, third-party and fourth-party logistics service providers are KIBS firms. Third-party logistics (TPL) firms manage, control and provide external logistical services operated by corporate clients. TPLs are generally companies that offer sophisticated logistics solutions, including transport, warehousing, distribution, track and trace, quality control and product packaging. Fourth-party logistics (4PL) companies coordinate other companies offering logistics services, including TPL, often on an international scale (Cabigiosu et al., 2015). The KIBS literature often distinguishes between different categories of KIBS. The most popular distinction is between p-KIBS, which are professional service firms such as accountancy, legal and management consulting services, and tKIBS, which are technology-related services such as computer, R&D and engineering services (Miles et al., 1995). KIBS firms can vary from firms developing complex engineering or IT “solutions” that meet the needs of large client organizations (Miozzo and Grimshaw, 2011) to professional service firms such as R&D or design consultancy, which help their client organizations to implement new or improved technologies or operations (Hansen et al., 1999; Miozzo et al., 2012). T-KIBS and p-KIBS often differ in terms of their goals, their knowledge bases, the strategies that are available to them and the way in which the strategies are pursued (Miles et al., 1995; Pina and Tether, 2016). Furthermore, while t-KIBS are often firms that promote new technology implementation and diffusion, p-KIBS are mainly new technology users. Muller (2001) adds the category of creative KIBS, including industrial and product design, advertising and communications services, among others, to

What are KIBS firms?

13

emphasize their relevance as regards innovation, although they are still neglected by the literature. Finally, Martinez-Fernandez and Miles (2006) focus on computer- and software-related services, labelled c-KIBS. Furthermore, other classifications have been developed to increase our understanding of KIBS’ differences. Particularly, Pina and Tether (2016) provide a classification based on KIBS’ knowledge bases instead of their sector. The conviction behind their study is that KIBS firms are differentiated in their knowledge bases and that KIBS firms with different (primary) knowledge bases tend to have different characteristics and to behave differently. To this end, they apply the conceptual model of three “knowledge bases” to KIBS (Asheim et al., 2007). The first knowledge base is the “analytical knowledge” associated with specialized skills related to rational abstraction, objective reasoning and empirical testing. Analytical knowledge is often developed using standard and formalized scientific methods. Firms with analytical knowledge, such as ICT firms, often use formal or informal R&D activities as key inputs into the development of their innovative products or processes. The “synthetic knowledge base” is essentially pragmatic and primarily focused on specific problem-solving activities; synthetic knowledge is less formalized, more practical and mainly tacit knowledge. Innovation, often incremental, derives from the experience and interactions between partners and with clients. The third category is “symbolic knowledge,” which concerns expression, emotion and understanding and is transmitted through signs, symbols, images and sounds, and it is mainly relevant to creative and cultural industries, such as fashion, industrial design and advertising. This knowledge relates to the ability to stimulate and manage the emotions of consumers and requires the ability to interpret, create or manipulate symbols and languages but also to persuade others of their value. The findings show that, although KIBS firms could be associated with a single “knowledge base”, most are likely to combine knowledge bases to varying degrees along a continuum from (pure) analytical knowledge to (pure) symbolic knowledge. Synthetic knowledge appears to be the most widespread across all of the KIBS industries. The authors also relate these categories of knowledge bases to the KIBS firms’ characteristics and strategies. For example, the KIBS firms that are more likely to invest in both R&D and design are those with a primarily analytical knowledge base, which are also more likely to introduce all types of innovations, that is, product and process innovations. “This indicates that the classification of KIBS firms by their (primary) ‘knowledge bases’ has explanatory power, and moreover, that this categorization complements rather than replaces the established Standard Industrial Classification” (Pina and Tether, 2016, p. 411). Interestingly, investments in information technologies are particularly important for innovation among all the KIBS categories.

14 Presenting KIBS firms

KIBS firms: The main traits KIBS firms are those enterprises of which the primary value-added activities consist of the accumulation, creation or dissemination of knowledge for the purpose of developing a customized service (Bettencourt et al., 2002). Miles et al. (1995) suggest that KIBS could be described as service enterprises that are based on strong and intellectual value added and are strongly innovative. Overall, the distinguishing features of KIBS firms are the following. First, KIBS’ primary activities depend on human capital, knowledge and skills, and their role consists of providing knowledge intensive inputs for the business processes of other organizations (Doloreux, Turkina and Van Assche, 2018; Muller and Doloreux, 2009). Bilderbeek and den Hertog (1998) provide a similar description. According to them, KIBS are private (or semi-private) companies and organizations that rely heavily on professional knowledge, that is, knowledge or expertise related to a specific (technical) discipline or (technical) functional domain, and that supply intermediate products and services that are knowledge based. In this sector, knowledge can be considered as the most important resource to nurture valuable competencies and as a precondition for the generation of new services. Second, the knowledge intensive nature of KIBS presupposes that individuals with a high level of preparation and skills in the field in which they operate, so-called knowledge workers, are employed for the provision of the service and are oriented towards problem solving, that is, solving the specific problems of the clients, and capable of understanding the needs of the clients and consequently adapting the services offered to them. KIBS have personnel with deep professional knowledge and/or abilities related to the specific field or sector. They provide products and services based on knowledge (and often involve extensive use of technologies) as well as intermediary products and services that often promote information analysis and knowledge creation inside client firms. Third, the services provided by KIBS are very often based on ICT technologies, since the development of new technologies not only contributes to the development of KIBS but also involves the implementation of innovation in the client companies or within the network in which KIBS take part, which includes other KIBS companies, suppliers, institutions, universities, research centres and other parties. KIBS contribute, on the one hand, to the development of new technologies, but, at the same time, use them to increase their market share and continuously innovate their offer as well as using the means made available by information and communication technology (including digital technologies) to transfer knowledge within these networks. In this respect, KIBS can be considered as innovative companies. Fourth, KIBS firms’ main clients are “businesses” and not individual consumers. KIBS companies provide services and produce knowledge for other companies to satisfy their specific and business-related needs. This condition presupposes that the client companies are also involved in the development of new knowledge, since new knowledge is shared between

What are KIBS firms?

15

the client company and the service provider. Clients’ co-production of services is often a defining feature of KIBS, which have to meet the specific requirements of their customers for the provision of their services and thus operate under a condition of continuous cooperation and interaction with them. Clients possess the knowledge about their own business and specific sector functioning, which is necessary for KIBS firms to design their services effectively. Miozzo et al. (2016) emphasize that a defining feature of KIBS firms is that they are involved in the continuous creation and transfer of knowledge in collaboration with other organizations, especially client organizations (Doloreux and Shearmur, 2012; Gallouj and Weinstein, 1997). Innovations tend to be developed in the course of specific projects for clients and therefore often lead to the customization of the service. Scholars refer to the notion of “co-production” of knowledge with clients to denote the way in which routine work for specific clients relies on clients’ transfer of knowledge and how this is intertwined with learning and innovation on one or both sides of the relationship (Bettencourt et al., 2002). Several researchers emphasize the importance of innovation in collaboration with clients (Love, Roper and Bryson, 2011; Tether, 2005). Finally, the design of the services is performed in a personalized way, since it is expected that the services will have to function well within clients’ processes and with clients’ personnel, who will then use the service. The need to act as problem solvers and to develop solutions and services targeted to specific organizations leads to the development of customized services. This indispensable operational interaction with the client company also represents an opportunity for the development of a certain loyalty to the service provider and is a prerequisite for the latter to build up a long-lasting competitive advantage. To sum up, KIBS firms have the following distinctive features: they rely on extensive use of new knowledge and technology, often have personnel with high levels of personal preparation and act as problem solvers for their clients, with whom they have strong, repeated interactions over time and with whom they co-produce the services. Consequently, KIBS are often customized (Muller and Zenker, 2001). These features are relevant across the board, and overall p-KIBS and t-KIBS have a number of characteristics in common. Generally speaking, while the existence of different categories of KIBS is well established, the literature recognizes that these features of KIBS are quite diffused and relevant (Hu et al., 2013). Nevertheless, we need to be cautious in that p- and t-KIBS may display some differences, and further studies are necessary to appreciate them better. For example, the level of interaction with customers and suppliers is critical to innovative P-KIBS companies (Freel, 2006), while T-KIBS depend more on their own internal innovation resources (Cabigiosu and Campagnolo, 2019; Miles, Belousova and Chichkanov, 2017). Landry, Amara and Doloreux (2012) find that the propensity of KIBS firms to rely more on a commoditization strategy and less on a personalization strategy increases for KIBS firms operating in a technology-based industry rather than a traditional professional industry

16 Presenting KIBS firms (see also Chapter 11). Rodríguez, Doloreux and Shearmur (2017) find that the variety in knowledge sourcing influences the degree of novelty in KIBS innovation only in t-KIBS firms. Nevertheless, we still lack studies that systematically try to disentangle the differences between t-KIBS and p-KIBS as far their distinguishing features are concerned.

Notes 1 The growing importance of services in economic life (often referred to as the “servitization” of the economy) derives from the fact that firms in all sectors recognize that their competitive advantage is based more on the actual services delivered to their customers than on the particular goods being sold. 2 Today the OECD has 36 members in North and South America, Europe and AsiaPacific. They include many of the world’s most advanced countries as well as emerging countries. The full list of members is available on this website: www.oecd.org/a bout/membersandpartners/.

References Asheim, B., Coenen, L., Moodysson, J. and Vang, J. 2007. Constructing knowledgebased regional advantage: Implications for regional innovation policy. International Journal of Entrepreneurship and Innovation Management, 7(2–5), 140–155. Baltacioglu, T., Ada, E., Kaplan, M., Yurt And, O. and Cem Kaplan, Y. 2007. A new framework for service supply chains. Service Industries Journal, 27(2), 105–124. Bettencourt, L.A., Ostrom, A., Brown S.W. and Roundtree R. 2002. Client co-production in knowledge-intensive business services. California Management Review, 44(4), 100–128. Bilderbeek, R. and den Hertog, P. 1998. Technology-based knowledge-intensive business services in the Netherlands: Their significance as a driving force behind knowledge-driven innovation. Vierteljahrshefte zur Wirtschaftsforschung, 67(2), 126–138. Brenner, T., Capasso, M., Duschl, M., Frenken, K. and Treibich, T. 2018. Causal relations between knowledge-intensive business services and regional employment growth. Regional Studies, 52(2), 172–183. Cabigiosu, A. and Campagnolo, D. 2019. Innovation and growth in KIBS: The role of clients’ collaboration and service customization. Industry and Innovation, 26, 592–618. Cabigiosu, A., Campagnolo, D., Furlan, N. and Costa, G. 2015. Modularity in KIBS: The case of third-party logistics service providers. Industry and Innovation, 22(2), 126–146. Corrocher, N. and Cusumano, L. 2014. The ‘KIBS Engine’ of Regional Innovation Systems: Empirical Evidence from European Regions. Regional Studies, 48(7), 1212–1226. Doloreux, D. and Shearmur, R. 2012. Collaboration, information and the geography of innovation in knowledge intensive business services. Journal of Economic Geography, 12(1), 79–105. Doloreux, D., Turkina, E. and Van Assche, A. 2018. Innovation type and external knowledge search strategies in KIBS: Evidence from Canada. Service Business, 1–22. *Drejer, I. 2004. Identifying innovation in surveys of services: A Schumpeterian perspective. Research Policy, 33(3), 551–562. European Commission. 2012. Knowledge-Intensive (Business) Services in Europe. Publications Office of the European Union, Luxembourg.

What are KIBS firms?

17

Eurostat. 2008. Main Features of EU-27 Business Services. No. 101. http://epp.eurostat.ec. europa.eu/ cache/ITY_OFFPUB/KS-SF-8–101/EN/KS-SF-8–101-EN.PDF. Freel, M., 2006. Patterns of technological innovation in knowledge-intensive business services. Industry and Innovation, 13(3), 335–358. Gadrey, J., Gallouj, F. and Weinstein, O. 1995. New modes of innovation. International Journal of Service Industry Management, 6(3), 4–16. Gallouj, F. and Weinstein, O. 1997. Innovation in services. Research Policy, 26(4–5), 537–556. Hansen, M.T., Nohria, N. and Tierney, T. 1999. What’s your strategy for managing knowledge? Harvard Business Review, 77, 106–116. Horváth, K. and Rabetino, R. 2019. Knowledge-intensive territorial servitization: Regional driving forces and the role of the entrepreneurial ecosystem. Regional Studies, 53(3), 330–340. Hu, T. S., Lin, C. Y. and Chang, S. L. 2013. Knowledge intensive business services and client innovation. Service Industries Journal, 33(15–16), 1435–1455. Landry, R., Amara, N. and Doloreux, D. 2012. Knowledge exchange strategies between KIBS firms and their clients. Service Industries Journal, 32(2), 291–320. Love, J.H., Roper, S. and Bryson, J.R. 2011. Openness, knowledge, innovation and growth in UK business services. Research Policy, 40(10), 1438–1452. Martinez-Fernandez, M.C. and Miles, I. 2006. Inside the software firm: Co-production of knowledge and KISA in the innovation process. International Journal of Services Technology and Management, 7(2), 115–125. Metcalfe, J. and Miles, I. 2000. Introduction, overview and reprise. In: Metcalfe, J. and Miles, I. (Eds.) Innovation Systems in the Service Economy. Measurement and Case Study Analysis. Kluwer Academic Publishers, Boston, pp. 1–14. Miles, I. 2005. Knowledge-intensive Business Services: Prospects and Policies, Foresight. 7(6), 39–63. *Miles, I., Belousova, V. and Chichkanov, N. 2017. Innovation configurations in Knowledge-intensive Business Services. Foresight and STI Governance, 11(3), 94–102. Miles, I., Kastrinos, N., Flanagan, K., Bilderbeek, R. and den Hertog, P. 1995. KnowledgeIntensive Business Services. Users, Carriers and Sources of Innovation. PREST, Manchester. Miozzo, M. and Grimshaw, D. 2011. Capabilities of large services outsourcing firms: The “outsourcing plus staff transfer model” in EDS and IBM. Industrial and Corporate Change, 20(3), 909–940. Miozzo, M., Lehrer, M., DeFillippi, R., Grimshaw, D. and Ordanini, A. 2012. Economies of scope through multi-unit skill systems: The organisation of large design firms. British Journal of Management, 23(2), 145–164. Miozzo, M., Desyllasb, D., Lee, H. and Miles, I. 2016. Innovation collaboration and appropriability by knowledge-intensive business services firms. Research Policy, 45(7), 1337–1351. Muller, E. 2001. Innovation Interactions between Knowledge-Intensive Business Services – Analysis in Terms of Evolution, Knowledge and Territories. Physica, Heidelberg. Muller, E. and Doloreux, D., 2009. What we should know about knowledge intensive business services. Technology in Society, 31(1), 64–72. Muller, E. and Zenker, A. 2001. Business services as actors of knowledge transformation: The role of KIBS in regional and national innovation systems. Research Policy, 30, 1501–1516. Mustafa, E. 2019. Service Innovation. Routledge, Oxon. Nijssen, E., Hillebrand, B., Vermeulen, P.A.M. and Kemp, R. 2006. Exploring product and service innovation similarities and differences. International Journal of Research in Marketing, 23(3), 241–251.

18 Presenting KIBS firms Pennant-Rea, R. and Emmott, B. 1983. The Pocket Economist. 1st ed. Cambridge University Press, Cambridge. Pina, K. and Tether, B. 2016. Towards understanding variety in knowledge intensive business services by distinguishing their knowledge bases. Research Policy, 45(2), 401–413. Powell, W.W. and Snellman, K. 2004. The knowledge economy. Annual Review of Sociology, 30, 199–220. Rodríguez, M., Doloreux, D. and Shearmur, R. 2017. Variety in external knowledge sourcing and innovation novelty: Evidence from the KIBS sector in Spain. Technovation, 68(C), 35–43. Scerri, M. and Randhawa, K. 2015. Service innovation: A review of the literature. In: Argarwal, R., Selen, W., Roos, G. and Green, R. (Eds.) The Handbook of Service Innovation. Springer, pp. 27–51. Schricke, E., Zenker, A. and Stahlecker, T. 2012. Knowledge-Intensive (Business) Services in Europe. European Commission, Brussels. Tether, B.S. 2005. Do services innovate (differently)? Insights from the European Innobarometer survey. Industry and Innovation, 12(2), 153–184. Tether, B. and Hipp, C. 2002. Knowledge intensive, technical and other services: Patterns of competitiveness and innovation compared. Technology Analysis & Strategic Management, 14(2), 163–182. Vargo, S. and Lusch, R. 2004. Evolving to a new dominant logic for marketing . Journal of Marketing, 68, 1–17. Windrum, P. and Tomlinson, M. 1999. Knowledge-intensive services and international competitiveness: A four country comparison. Technology Analysis & Strategic Management, 11(3), 391–408.

2

The growing importance of KIBS in today’s economy

In recent years, the KIBS sector has shown a much higher growth rate than many other sectors. This sustained growth is attributed mainly to changes in the extent to which all sectors are demanding inputs from KIBS. KIBS act as a bridge of innovation, helping firms to acquire and use new technologies. However, new technologies are also employed by KIBS firms to improve their offer, productivity and internationalization, and can boost their relevance and growth.

KIBS are bridges of innovation Services were often seen in the past as laggards in innovation, despite their important contribution to manufacturing firms’ and regional systems’ competitiveness. During the last decades, shaped by the “knowledge economy”, globalization and new technologies, the perception of services, in particular KIBS, has changed. While services were initially considered as pure providers of data and information, more recently they have been acknowledged as sources of innovation and as being pivotal in many innovation networks. As economies develop, the demand for knowledge inputs increases and becomes more sophisticated and complex to satisfy. In this situation, the role of specialized service providers becomes crucial (Kuula, Haapasalo and Tolonen, 2018). The number of knowledge intensive services has more than tripled in European countries over the last 30 years (Eurostat, 2016). The growth of these services, such as ICT or marketing services, is largely explained by their importance in the competitive dynamics of manufacturing companies. Competition is no longer based solely on variables that are closely linked to production processes such as economies of scale or quality controls, but often lies in the ability to identify a complete set of complementary activities along the value chain. Companies are required to focus on their core competences and to collaborate effectively with external specialized suppliers with complementary resources. Manufacturing firms, especially small and medium enterprises, often outsource the management of many services, ranging from logistics to strategic analysis. Their competitive advantage is therefore linked to external collaborations on which depend the attributes of their products

20

Presenting KIBS firms

(consulting, R&D and design services), their communication (marketing services) and their placement on the market (logistics and distribution). Service providers are becoming more and more relevant in explaining firms’ success. Many support activities that allow a successful product to be sold on the market can be provided by KIBS. These synergies between KIBS and manufacturing firms have led to the development of geographical areas, often called regional innovation systems, with a high concentration of KIBS companies, the presence of which is positively correlated with the economic performance of the entire region. Examples are the metropolitan areas of Zurich, Stockholm, London and Berlin. Several theoretical and empirical analyses have shown that regional innovation systems provide favourable conditions for KIBS firms and vice versa (Corrocher and Cusumano, 2014; Muller & Zenker, 2001). KIBS firms are “knowledge agents” that generate and disseminate knowledge and contribute to the development of the region to which they belong. The role of KIBS is particularly important in advanced regions, where the competitiveness of the manufacturing industry is still due to the presence of a series of advanced complementary services, such as design or marketing studies. Schricke, Zenker and Stahlecker (2012), analysing the correlation between the gross domestic product per capita and the employment rate in KIBS firms in the different European regions, find that the correlation rate is about 70%, suggesting the importance of these services in explaining the economic performance of different European regions. KIBS firms are able to generate a spiral of growth in the tertiary and manufacturing sectors thanks to the innovativeness of their services and the support that they offer to their clients’ innovation processes (Miles, 2005; Muller and Doloreux, 2009; Muller and Zenker, 2001). The growing importance of these firms is thus one of the main traits of the “knowledge economy”: these services are dynamic and fast growing, and they represent a valuable source of new technologies that are able to affect the whole economy. Although KIBS firms still constitute a minor proportion of the service sector, their significance extends beyond their diffusion: they are a source of highquality, high-wage employment and wealth creation for the territories in which they operate, and they act as knowledge integrators, participating actively in ongoing knowledge networks with other firms, research institutes and universities (Bessant and Rush, 1995). Today, more and more scholars explicitly recognize their active role in the interactive learning process, involving multiple actors that help the development of innovation capabilities and innovation outcomes, calling them “bridges of innovation” and highlighting their potential in triggering and helping the process of knowledge creation and conversion in the firms with which they work (den Hertog, 2000). KIBS firms have tight interactions with dense networks of partners, and their role allows them to act as a bridge between firms involved in different innovation processes. This role is of particular relevance when KIBS interact with SMEs (small and medium-size enterprises). When SMEs try to innovate, they often face multiple problems, mainly related to the shortage of human and capital resources.

The importance of KIBS in today’s economy

21

They lack qualified managers and have difficulties in adopting new technologies. Internal R&D alone is not sufficient for most SMEs to be successful innovators, and their innovative capacity depends increasingly on their access to external information sources. Then, KIBS can help client firms by providing services that are fundamental to the success of their innovative efforts. KIBS can be considered as “bridges for innovation”, in particular for some roles that they play with respect to different actors in the market. KIBS firms are purchasers of business-related innovative services when they buy knowledge, equipment and investment goods from manufacturing industry or other KIBS firms; they provide innovative business-related services to companies in the manufacturing industry or in the service sector; and finally they can be partners of a network of firms involved in the development of new services (Bessant and Rush, 1995). Partnerships and networking are particularly relevant in KIBS, which are on average micro firms and do not have an R&D area (Muller and Zenker, 2001). Instead, they widely rely on the competences of their knowledge intensive workers and on external partners. KIBS firms innovate in collaboration with partners such as universities or research centres that have complementary competences and with which they share the risk of developing new services (Love and Mansury, 2007; Love, Roper and Bryson, 2011; Mansury and Love, 2008; Muller and Zenker, 2001). Furthermore, in the 4.0 economy, market information is crucial for the KIBS firms that are supporting the innovation processes of their clients (Cabigiosu et al., 2015). In this setting, KIBS firms rely on other KIBS, universities and research centres to improve their effectiveness. Finally, the choice of a broad set of sources will enable them to gain a good understanding of other competitors’ actions. In the 4.0 economy, KIBS can perform different functions for their clients, like the detection and analysis of new opportunities and problems, the development of an action plan or direct participation in new product development activities. Hence, KIBS firms’ bridging activity can take different forms: expert consultants, aiming to provide targeted solutions to specific and complex problems; experience sharing, consisting of transferring knowledge from one context to another; brokering, putting different users in contact across a range of different services and resources; diagnosis and problem clarification, based on helping users to identify and define their particular innovation needs; and benchmarking, with the aim of identifying and focusing on “good practices” in the same industry or in others (Bessant and Rush, 1995; Li Pira, Cabigiosu and Campagnolo, 2017). On account of this, KIBS can support clients’ innovative effort at different levels and play different roles in their innovation processes (see also Chapter 5). They can support client firms’ innovation process but without transferring any innovation to the clients. An example of this situation is a consultancy firm helping its client to introduce a new service by providing market analyses. Rawfish, which develops mobile applications, has recently developed a “design-shaping program”, which is a path designed specifically for companies in the engineering sector, for Digitec, a big company operating in the field of systems for the control, management and

22

Presenting KIBS firms

supervision of industrial plants. This program aims to introduce new guidelines for the creation of innovative and intuitive human–machine interfaces thanks to a quality design and an in-depth study of usability. Rawfish provided Digitec with the tools and know-how to create modular and immediate interfaces to control machines and robots, making them simple and effective to use. KIBS firms can also play a crucial role in transferring existing innovations between different firms, even though the innovation itself does not originate from the KIBS firm. Finally, KIBS firms can be the main source of innovation when they develop services that are new to the industry. For example, the track and trace system was introduced by third-party logistics service providers and today allows the positioning of trucks to be tracked in real time. Now this service is offered by almost all third-party logistic providers, such as UPS and Amazon. KIBS firms act as a bridge, or as an interface, between their clients and the environment, boosting their innovation capabilities. Many 4.0 technologies have increased the relevance of KIBS. IOT technologies and robots require software and Internet connections, and digital printing requires dedicated software and service firms that are able to design 3D objects. The same applies to big data analysis and interpretation. Moreover, all these technologies modify firms’ business opportunities and the competitive and legal environment and often require support from marketing consultants and professional firms and not only ICT competences. However, while the introduction of new 4.0 technologies into manufacturing firms is a business opportunity for many KIBS firms, such as R&D, engineering, consultant, data analysis, software development and marketing firms, they also present several challenges. First, KIBS firms are on average micro firms that are, at least partially, required to update their own competences before supporting clients’ innovation processes. These investments may generate a division between growing and performing KIBS firms and smaller and lagging behind traditional firms. This is especially true if the 4.0 economy favours the most innovative and bigger manufacturing firms that typically interact with bigger and better structured KIBS firms, thus generating a virtuous cycle only for the biggest and innovative KIBS firms. For example, in 2017, I collected articles published in the leading Italian newspapers containing economic sections, such as IlSole24 Ore or Corriere della Sera, presenting and discussing new Industry of Things (IOT) solutions. Taken together, these articles describe 47 cases of innovations in which firms producing connected artefacts mainly develop the software in house as well and follow a vertical integration strategy. Examples of firms that have developed both the product and the software in house are Texa for the Texa-Care device aimed at connecting a car to a smartphone and ensuring the remote control of the car, Edison for the production of a smart living console and e-goodlife, the new technological kit by Enel to transform a house into a smart environment. These examples suggest that big firms may move toward a servitization strategy in which they increase the value and share of their offering. Hence, instead of outsourcing services, manufacturing firms have another option: to modify their business model and strategy, and start producing services in house. This study of

The importance of KIBS in today’s economy

23

the Italian journals also provides examples of firms that have selected an outsourcing strategy and developed their products with KIBS firms: Samsonite, which collaborated with Vodafone for the development of connected luggage, Rebecca Minkoff, who worked with Zeekit on the development of a smart mirror, and Piaggio’s collaboration with Ericsson and Tim for the development of the connected Vespa scooter. Another example comes from the automotive industry, in which carmakers are called to introduce multiple innovations, such as connected and autonomous vehicles or alternative powertrains. A study of the Italian suppliers of the automotive industry shows that 56% of firms have introduced product innovations and that firms mainly innovate in house (71%). The data also show that, while suppliers at all levels of the value chain have been growing in the last three years (2015–2017), engineering and design services are the category of suppliers that grew the least (3.1%) in 2017 against the 6.9% of the whole sector and had a negative balance between the number of firms with a growing and decreasing revenue that endured from 2015. The authors suggest that E&D (engineering and development) services are facing a dichotomization and are split between KIBS firms that are growing and investing and KIBS firms of which the mean revenue decreased by about 10% from 2016 to 2017 (Cabigiosu and Zirpoli, 2018). In this setting, big KIBS firms, such as Italdesign and Pininfarina, are competitive if they are able to sell their services globally to distant clients who positively value their ability to create a modular architecture of services, each of which clearly addresses specific clients’ needs via codifiable knowledge that is easily transferable in international partnerships. Furthermore, the rapid increase in the demand for ICT services, for which relevant economies of scale in the R&D effort exist, may favour big and global service providers in multiple service industries, such as cloud or fog computing, dominated by Amazon, Google and Cisco, ERP business solutions, with SAP, or the emerging IOT industry, with Siemens and many big companies. While, in the past, the business model of KIBS could balance the emphasis on innovativeness with that of customization obtained via tight relationships and vis-àvis relationships with co-located clients, and local small KIBS could sell their services to small local clients, today the emphasis on new technologies enables small KIBS firms to evaluate the sustainability of their niche strategy. Today, the competition in many sectors is global, and KIBS can remain local if the competitive advantage of companies still originates at a local level from the network of companies that are responsible for the growth and competitiveness of their territory. A recent trend is the creation of partnerships and of aggregation of KIBS firms operating in the same industry to increase the range of services that clients can obtain from the same service provider and hence their competitiveness. For example, Avvecomm is a multidisciplinary Italian firm that was founded in 2006 by the aggregation of different professional realities with the aim of providing companies with assistance in every area that may concern them: from the relationship with banks to labour law issues, from finance to industrial property and from extraordinary mergers and acquisitions to the resolution of

24 Presenting KIBS firms states of crisis. Today, Avvecomm has about 70 employees and is structured in four different areas: legal, commercial and audit, management consulting and labour consulting. Each area is composed of professionals who cultivate skills and experience in different fields to be able to offer customers the most appropriate assistance at any time. In the marketing area, The Cluster is the result of an alliance of companies providing complementary services: marketing and communication plans, website development, mobile applications, and brand and event management. The Cluster offers different and specialized services through collaboration between four companies. “Sintesi Comunicazione” is a communication, marketing and strategic consumer agency. It is based in Padua, was founded in 1998 and has five employees. “MGP&Partners” is a public relations agency based in Milan, was founded in 2002 and has three employees. “NetBanana” is a multimedia agency specializing in the production, management and marketing of web applications, websites, multimedia products, apps and digital videos. It is based in the province of Padua, was born in 2002 and has five members. Finally, “GIR allestimenti” is composed of a staff of consultants, designers and architects specializing in the creation of exhibitions and events. It is based in the province of Padua, was founded in 1998 and has seven employees. The Cluster presents itself to customers as a single interlocutor. “Sintesi Comunicazione” is the leading firm that coordinates the activities of The Cluster. Representatives of all the partners are usually present at the moment of the first meeting with the customer. Subsequently, according to the specific needs of the customer, one of the partners may become the project leader (Cabigiosu, 2016). Altogether, these firms develop from being micro firms to constitute a small enterprise with a broader service offer.

New technologies for KIBS firms KIBS firms help their clients in developing new 4.0 products and employ new technologies to increase their competitiveness, productivity and internationalization. A major driver of growth in KIBS firms is represented by the rapid increase in technology-related business services, with ICT services being the most relevant example. Digital technologies are business opportunities for KIBS, as already broadly discussed, because a) they generate new clients’ needs and thus open new business opportunities for KIBS firms and b) they are incorporated into new KIBS firms’ products and services, improving their innovativeness and efficiency. First, new ICT technologies allow the storage of a huge amount of data and information that are available contemporarily to multiple actors at almost no cost. The most valuable resource of KIBS is the knowledge that they use to design and deliver their services and new technologies that allow the storing and sharing of a growing part of such knowledge, mainly the explicit part of the knowledge, via e-mails or documents, and of less structured information, via videos or images, and often direct interaction with employees and partners worldwide. KIBS are learning how to benefit from these technologies, which are also modifying their

The importance of KIBS in today’s economy

25

business model. For example, codified KIBS knowledge can also be accessed by clients and be sold as an additional service, as it may happen for legal offices that produce reports or videos discussing new norms or laws of interest to multiple clients. Codified knowledge can inform KIBS’ internal processes and increase their efficiency. Codified knowledge forms the basis of service modules that can be mixed and matched to address specific clients’ needs, as in ERP systems, made of combinable modules corresponding to different functional areas. Services’ codificability and replicability into modules increase the overall service scalability, which means that digital technologies are tools to codify, standardize, store and replicate firms’ knowledge at almost zero costs, thus also opening for services the chance to pursue mass customization strategies. The same trend is visible in software and website design (see Chapter 11). Second, digital technologies augment problem-solving effectiveness and efficiency and increase the level of problem-solving complexity that managers can handle. Digital technologies become part of the service delivery process and support knowledge workers in their work: business analytics and data science are two fields that nurture KIBS business, such as in the case of ICT, consulting and marketing services. Third, new technologies allow knowledge to be shared more easily within firms’ boundaries and enable the creation of repositories that help knowledge workers to share their expertise and best practices, as is the case for Myspace (Facebook). When knowledge can be explicated, codified and shared, it becomes easier to manage multiple and distant headquarters or teams working with different and international clients. Free technologies, such as Skype or other dedicated platforms, can suffice. All these technologies can increase KIBS firms’ offer, productivity and range of action. Digital technologies support professionals by providing tools to sustain humans’ creativity and connectivity. Furthermore, it becomes easier to attract knowledge workers if KIBS firms can give them working place flexibility. The rapid evolution and proliferation of ICT technologies represents not only a considerable opportunity for firms but also a problem for organizations that want to make effective use of these opportunities. To keep up with these developments and remain updated, it is necessary to acquire substantial (new) knowledge. De Luca Tamajo e Soci is a law firm located in Naples, Bergamo, Rome and Milan, with 17 partners and 90 collaborators and employees. The company is one of the leading Italian law firms specializing in labour law and trade union law and has recently created an R&D department in Naples, supported by a scientific committee of five partners. This firm is a perfect example of how new technologies shape the business and functioning of KIBS firms (not necessarily t-KIBS). The law firm’s R&D unit creates new tools and applications to leverage and use to the fullest extent the knowledge held by the study partners and employees to increase the quality of the services offered and the efficiency of its internal processes. In particular, the law firm has developed new knowledge management systems and training programs to ease the codificability,

26 Presenting KIBS firms transferability and accessibility of the knowledge. Once this knowledge management program had been developed internally in the back office, the firm understood that the new codified knowledge generated could also be offered to clients in the front office via an online reserved area in which clients can find dedicated documents and publications, books and web seminars. An example of a service developed by the firm is its own application, available in the Apple store, which focuses on the firm’s initiatives, issues of labour law, trade union law and pension law, and human resource management.

Internationalization and globalization in KIBS Internationalization is a growth strategy shared by both big and small-medium enterprises. Domestic markets often do not suffice to sustain firms’ business, while foreign markets may offer valuable business opportunities. When firms decide to export their products or make direct foreign investments, they face issues related to foreign countries’ own health, safety and environmental regulations, which may represent a major challenge for them. In this context, KIBS can often help by providing data, information, training and consulting services as well as intermediation services. In detail, KIBS firms perform different functions. First, they help firms ex ante in deciding which market to approach and with which strategy. KIBS firms, by providing market research, marketing and public relations services, help their clients in understanding and relating to different markets, cultures, consumers and stakeholders. These kinds of services have existed for a long time, but the globalization of many industries, such as the fashion and automotive industries, has increased their importance in the last decades. Second, KIBS firms assist their clients ex post when they enter a distant country, and they can provide support in loco. In this way, the internationalization and globalization of manufacturing firms also become a stimulus for KIBS firms themselves to internationalize their activities. An interesting example is VEASYT srl, a research spin-off of the Ca’ Foscari University of Venice, founded in 2012 and based at the Department of Linguistics and Comparative Cultural Studies. This firm built on the department’s know-how regarding the development of skills in the field of language and sensorial accessibility. Today, the company offers digital services to create full access to content and information in any language, and it is aimed at public and private institutions, companies and professionals who wish to offer accessible services to allow the full social inclusion of all citizens, overcoming all language and sensorial barriers. Hence, the firm combines scientific and linguistic expertise that is made available to clients via innovative digital solutions. One of the first services developed was VEASYT Live!, a professional video remote interpreting service available online through which anyone can have access to an online professional interpreter in any language in real time. The service was initially conceived for business meetings or for public institutions to communicate with their clients or stakeholders using the required language, including sign language. This case exemplifies how new technologies support KIBS firms’ and manufacturing firms’ internationalization process.

The importance of KIBS in today’s economy

27

Another example is Digital To Asia, a firm that aims to increase the purchases of Chinese customers in Italian shops and tourist facilities, with an appropriate mix of online and offline actions. Digital To Asia is a start-up that develops communication activities on Chinese digital channels and creates ad hoc events on the territory to promote shopping in Italy with the aim of making the stay of oriental tourists in Italy pleasanter and easier. The firm has in-depth knowledge of all culturally related aspects of shopping and offers training for the Italian sales force about Chinese traditions, prepares promotional materials and develops strategies for the digital channels. The firm also promotes the purchase of “Made in Italy” products even after the clients’ return to China. Digital To Asia has also entered into partnerships with Alipay, the digital payment company of the Alibaba Group, and Global Blue, another market leader in tax-free refunds for foreigners. These cases emphasize well how innovation and new technologies can play an important role in KIBS firms’ internationalization and how KIBS can support the internationalization of manufacturing firms (Rodríguez and Nieto, 2010, 2012). Interestingly, while scholars show the relevance of KIBS firms to the internationalization of their clients (Di Maria et al., 2012; Doloreux and Laperriere, 2014), little academic research focuses on the consequences for KIBS firms’ innovation strategies and activities (Doloreux and Laperriere, 2014; Marques et al., 2016, 2017). Future studies are expected to explore further the association between distinct strategies of internationalization, knowledge management, cooperation and innovation in KIBS firms. Generally, KIBS firms are seen as being sheltered from international competition. The differences across countries in regulations, in language and culture and in the national character of professional qualifications have all contributed to protecting KIBS firms’ area of business, and KIBS firms have a competitive advantage given by the proximity to their clients. In Chapter 9, I discuss further how new technologies can potentially modify this source of competitive advantage and the various internationalization strategies available to KIBS firms.

T-KIBS and p-KIBS in the Industry 4.0 paradigm The preceeding paragraphs discuss how t- and p-KIBS are experiencing a period of extreme growth in today’s competitive scenario both because they provide valuable services for manufacturing firms that are willing to approach new digital technologies and because KIBS firms themselves are using these technologies to innovate their offer. FabricaLab is a good example of how tKIBS firms are approaching the Industry 4.0 paradigm. FabricaLab is located near Florence (Italy) and was founded in 1998. FabricaLab is active in the market of software, solutions and ICT services and operates at the national and international levels, offering companies innovative and customized solutions to improve the management of their business processes. FabricaLab operates in the most advanced technological fields, such as the Internet of Things, cloud computing, big data and security, carrying out complex business intelligence projects.1

28

Presenting KIBS firms

The company’s mission is to provide manufacturing and service companies, mainly operating in the luxury fashion industry, with innovative projects and products, ensuring the best quality of implementation and the related maintenance services. FabricaLab closed 2018 with growing numbers, confirmed during the first months of 2019. The Italian company obtained a double-digit increase in revenues (+17%) in 2018, touching 5.8 million euros, with an EBITDA (Earnings Before Interest, Taxes, Depreciation and Amortization) of more than 18%, thanks to the increase in the customer portfolio and in particular in the core business, made up of companies in the luxury fashion sector. In 2018, FabricaLab also made significant investments in human resources, with the hiring of highly specialized professionals (mathematicians, data scientists and engineers), which enabled it to strengthen its technological skills. “The strengths that have been at the base of the excellent company performances,” underlines Giulio Meghini, CEO and Founder of FabricaLab, “have been the consolidation on the reference market of fashion luxury, the important investments in R&D, a shrewd financial management and, finally, the start of new partnerships and the strengthening of those already in place” (Pambianconews, 2019). FabricaLab has tight relationships with clients. The professionals consider themselves as strategic partners of their customers, with whom they co-make their business. Their mission is to create projects and solutions that are capable of enhancing the specific features of each company and assisting their clients in the development of their business through their ability to design, implement and support ad hoc solutions, integrated if necessary with third-party solutions, to meet the needs of each client. Hence, FabricaLab has a consulting approach that is based on the ability to analyse strategic processes and to offer customized solutions to clients thanks to the know-how of its team, the adaptability of its technology and services and its network of partners and suppliers, such as Oracle and Cisco. Overall, FabricaLab offers global support to its clients and provides services that are constantly adapted to the clients’ growth needs. PCube is among the main products offered by FabricaLab. PCube is software employed in R&D projects, which has been designed to provide solutions in the field of artificial intelligence, machine learning and business intelligence. PCube allows the collection of data from heterogeneous and distributed sources and consolidates them according to defined rules, reflecting the organizational structure and goals of the clients to transform data into information. PCube eases the budgeting and planning processes, the collection and certification of sales data, the analysis of margins and, more generally, all those processes that are often managed through the collection of countless Excel sheets, with little guarantee of data validity and poor control over the whole analysis process. PCube also helps each specific user to monitor and define specific variables and outputs in relation to his or her own organizational role. PCube interacts with the user by identifying useful data sources, such as data files, by suggesting specific analyses and by monitoring the whole process. FabricaLab is also developing an innovative project, named Sibilla, in partnership with other companies and the University of Pisa and founded by the EU,

The importance of KIBS in today’s economy

29

with the aim of designing and developing an innovative business intelligence system for Industry 4.0 companies. This new system has multiple functions, such as collaboration capabilities, automatic interaction, big data analytics and machine learning to extract knowledge by performing predictive analysis integrating big data acquired from the Web and Internet of Things architectures. The management and enhancement of big data represent one of the most important technological challenges that companies have to face in the context of Industry 4.0 to manage their processes more effectively and efficiently. The current business intelligence (BI) and corporate performance management (CPM) systems do not fully meet the need to adapt the BI environment by integrating it with solutions and technologies typical of Industry 4.0, such as data mining and machine learning, to extract knowledge from large amounts of data, whether they are held in business information systems, collected from the Web or acquired through IoT architectures. Sibilla aims to overcome the critical issues of the current CPM/BI systems by creating the prototype of a BI system that implements technologies of Industry 4.0 and is able to extract, from big data from heterogeneous, albeit exogenous, sources, useful information to perform predictive analysis and optimize the management of business processes. The project will develop software modules with web crawling, data pre-processing, text analysis and big data mining functions, capable of performing sentiment analysis and opinion mining on data collected from the Web. In addition, a solution will be implemented to exploit, using a predictive approach, the measurements of physical attributes of IoT architectures. Particular attention will also be paid to an innovative graphical interface and mobile apps that simplify the interaction with the system. Finally, important resources have been allocated to cloud architectures that strongly improve services’ scalability in terms of both storage and computational capacity. The firm emphasizes that scalability is now a strategic factor to be able to process the increasing amount of information coming from all internal and external sources, such as the Web and the IOT. While t-KIBS, such as FabricaLab, assist their clients by providing the new technologies and the related support and use the digital technologies to innovate their offer, other firms, typically p-KIBS, provide manufacturing firms with the competences to manage the change provided by Industry 4.0. Digitalization brings with it the obligation to rethink the very concept of business organization, and the same process underlines the centrality of human resources as a priority element within companies. Daxo2 is an example of p-KIBS providing support services for manufacturing firms that are willing to introduce new digital and 4.0 technologies. Daxo is a small Italian firm that helps its clients to change their culture and organization to embrace new technologies and provide those human resource services that bring firms into the new industrial revolution. For example, in 2019, it organized a set of seminars targeted at empowering women in Industry 4.0 and helping them to assess their competences, identify new business models offered by Industry 4.0, develop change management competences and develop those strategic competences to support the introduction of digital technologies.

30 Presenting KIBS firms In the coming years, companies will encounter technological changes with effects that are not entirely predictable, which in turn will trigger the introduction of new organizational models, requiring a serious reflection on the different professional roles, management, necessary skills and leadership. The success of a company’s digital transformations will depend first on the parallel enhancement of human resources. Employees will always make the difference, whatever the future contribution of computers, robots and artificial intelligence. The more companies become digital, the more they will understand the importance of rethinking their organization, so it can actually make them smarter, faster and able to adapt more quickly to internal and external changes as well as to the demands for greater dynamism on the part of the employees themselves. Unfortunately, however, these internal restructuring projects are not at all simple; on the contrary, many reorganizations fail in the short term and few companies are equipped internally to manage this change and understand how to carry out this process. This last aspect calls into question the issue of “careers and learning”. Once upon a time, workers learned what was needed to fulfil their role at the beginning of their career, and those skills were sufficient for decades, practically until retirement. Today, skills need to be renewed year after year, which means that a brilliant working career cannot be such without continuous updating. Hence, Industry 4.0 is only apparently a mere technological revolution in that it also affects heavily human resources and the way in which organizations function. In this context, both t-KIBS and p-KIBS provide valuable services. Particularly, while the FabricaLab case exemplifies well how t-KIBS support the introduction of new technologies, the considerations mentioned also show that p-KIBS provide valuable services in the following areas: firms’ cultural improvement and change, human resource management and change management, organizational design and information systems.

Notes 1 www.fabricalab.it/ 2 www.daxogroup.it

References Bessant, J. and Rush, H. 1995. Building bridges for innovation: The role of consultants in technology transfer. Research Policy, 24, 97–114. Cabigiosu, A. 2016. L’innovazione e la progettazione nei servizi knowledge-intensive. Giapichelli, Torino. Cabigiosu, A., Campagnolo, D., Furlan, N. and Costa, G. 2015. Modularity in KIBS: The case of third-party logistics service providers. Industry and Innovation, 22(2), 126–146. Cabigiosu, A. and Zirpoli, F. 2018. Digitalization in the Italian auto industry. Symphonya. Emerging Issues in Management, 2, 158–169. Corrocher, N. and Cusumano, L. 2014. The “KIBS engine” of regional innovation systems: Empirical evidence from European regions. Regional Studies, 48(7), 1212–1226.

The importance of KIBS in today’s economy

31

Den Hertog, P. 2000. Knowledge-intensive business services as co-producers of innovation. International Journal of Innovation Management, 4(4), 491–528. Di Maria, E., Grandinetti, R. and Di Bernardo, B. 2012. Exploring Knowledge Intensive Business Services. MacMillan, Palgrave. Doloreux, D. and Laperriere, A. 2014. Internationalisation and innovation in the knowledge-intensive business services. Service Business, 8, 635–657. Eurostat. 2016. Business Demography Statistics. http://ec.europa.eu/eurostat/statistics-exp lained/ index.php/Business_demography_statistics. Kuula, S., Haapasalo, H. and Tolonen, A. 2018. Cost-efficient co-creation of knowledge intensive business services. Service Business, 12(4), 779–808. Li Pira, S.L., Cabigiosu, A. and Campagnolo, D. 2017. How much do firms imitate each other? The role of external search strategies in KIBS firms. At the Toulon-Verona Conference on Excellence in Services, September 7 and 8, 2017. Love, J.H. and Mansury, M.A. 2007. External linkages, R&D and innovation performance in US business services. Industry and Innovation, 14(5), 477–496. Love, J.H., Roper, S. and Bryson, J.R. 2011. Openness, knowledge, innovation and growth in UK business services. Research Policy, 40(10), 1438–1452. Mansury, M.A. and Love, J.H. 2008. Innovation, productivity and growth in US business services: A firm-level analysis. Technovation, 28(1–2), 52–62. Marques, C.S., Leal, C., Marques, C.P. and Cardoso, A.R. 2016. Strategic knowledge management, innovation and performance: A qualitative study of the footwear industry. Journal of Knowledge Economy, 7(3), 659–675. Marques, C.S., Marques, C.P., Leal, C.T. and Cardoso, A.R. 2017. Knowledge, innovation, internationalisation and performance: Insights from the Portuguese footwear industry. International Journal of Entrepreneurship and Small Business, 32(3), 299–313. Miles, I. 2005. Knowledge-intensive business services: Prospects and policies. Foresight, 7(6), 39–63. Muller, E. and Doloreux, D. 2009. What we should know about knowledge intensive business services. Technology In Society, 31(1), 64–72. Muller, E. and Zenker, A. 2001. Business services as actors of knowledge transformation: The role of KIBS in regional and national innovation systems. Research Policy, 30, 1501–1516. Rodríguez, A. and Nieto, M.J. 2010. Cooperation and innovation in the internationalization of knowledge-intensive business services. In: Pla-Barber, J. and Alegre, J. (Eds.) Reshaping the Boundaries of the Firm in an Era of Global Interdependence. Progress in International Business Research (Vol. 5). Emerald Group Publishing, Bingley, UK, pp. 247–270. Rodríguez, A. and Nieto, M.J. 2012. The internationalization of knowledge-intensive business services: The effect of collaboration and the mediating role of innovation. Service Industry Journal, 32(7), 1057–1075. Schricke, E., Zenker, A. and Stahlecker, T. 2012. Knowledge-Intensive (Business) Services in Europe. European Commission, Brussels. Websites www.fabricalab.it/ (accessed March 8, 2019). “FabricaLab mette il turbo all’IT della moda e del lusso”, article published February 25, 2019, available online at www.pambianconews.com/2019/02/25/fabricalab-m ette-il-turbo-allit-della-moda-e-del-lusso-253801/ (accessed February 20, 2019).

Part II

Innovation in KIBS

3

Multiple forms of innovation in services and in KIBS

There are many difficulties in conceptualizing innovation in KIBS firms, and there is considerable heterogeneity among KIBS firms regarding the way in which they undertake innovation. To account for this heterogeneity of innovation forms and classifications, this chapter offers a synthesis of multiple existing forms of innovation in KIBS, provides several examples and finally summarizes the existing debate within the innovation management literature about the need to use different categories of innovation to study innovation in KIBS, services and products.

Innovation in services Service production means “to organize a solution to a problem (a treatment or an operation) that does not principally involve supplying a good. It is to place a bundle of capabilities and competences (human, technological, organizational) at the disposal of a client and to organize a solution, which may be given to a varying degrees of precision” (Gadrey, Gallouj and Weinstein, 1995). In services, the value creation is driven by the combination of intangible resources, such as knowledge and competences and customer collaboration (Scerri and Randhawa, 2015). Although the application of manufacturing-related concepts in several service innovation studies could suggest that these two sectors are substantially similar, the latter has some important differences that deserve an in-depth analysis, as they affect the way in which firms innovate. Tether and Hipp (2002) emphasize the elements that characterize services. Services require close interaction between the service user and the service provider, which take part in the provision at the same time. Services are contemporarily delivered and consumed, and services cannot be provided if the production and consumption are not simultaneous. This generates specific features of service production: the interaction with clients affects the service provision by modifying its content, length and productivity, thus negatively affecting the planning of production capacity. While manufacturers can produce forecasting of the demand and define an ideal and fixed production capacity using warehouses to meet the real demand, service providers traditionally do not have this opportunity.

36

Innovation in KIBS

Overall, intangibility, perishability, heterogeneity and inseparability are all elements of services that represent their main peculiarities and deeply influence the way in which both service firms innovate and researchers study this phenomenon. Witell et al. (2016), in their literature review, emphasize that much of the research on service innovation to date has failed to define the focal concept of innovation in services. Service innovation is generally defined as a “new service”, but this is an insufficient definition that risks suggesting that somehow all firms develop innovations. Frequently, researchers do not make clear whether they are using the concept of innovation to refer to the innovation process or to the outcome of this process, and this creates confusion when talking about successful service innovation (Toivonen and Tuominen, 2009). Other scholars define innovation based on the degree of newness and refer to innovations that are new to the world and innovations that are new to the market (Sundbo, 1997). Consequently, innovation research should still adopt a broad, shared and well-defined perspective on what innovation means in services. Sharing an overall view of service innovation would enable theory building and research to operationalize service innovation better in further empirical studies. Precisely defining and labelling constructs is fundamental for knowledge sharing and enables scholars to understand the theory and be able to criticize, control and reproduce their studies (MacKenzie, 2003). The most important analytical problem in relation to services is the intangible nature of their product: service output is not embodied in anything that is physically quantifiable. The main consequence is difficulties in measuring and quantifying innovativeness and innovation performance in services. Particularly, the link between innovation in services and economic variables such as productivity should be clarified. According to Djellal and Gallouj (2010), our economies contain invisible or hidden innovations that are not captured by the traditional definitions and indicators of innovation. This generates an innovation gap or bias in the measurement of innovation in services that, in turn, creates a performance gap, which is the underestimation of the outcomes of service firms’ innovation efforts in terms of productivity and growth. These methodological issues have historically led to the underestimation of innovation output and performance. Today, scholars recognize that services are actively engaged in innovation and can be extremely innovative. Services are active users and adopters of new technologies, especially ICT, which in turn has enabled productivity improvements in many services. Services can be the source of innovation, carry out R&D and be the producer of new technologies (Wong and He, 2005). Once the innovation and performance gaps emerged, scholars engaged in a vivid debate about innovation in services that led to the proliferation of different categories of innovation in services and to different approaches to the study of innovation in services. The next paragraphs provide a synthesis of this debate by presenting multiple categories of innovation in services and in KIBS (i.e. which types of innovations exist in services), such as product and process innovations, and by presenting the three perspectives that scholars use to study innovation in services:

Forms of innovation in services and KIBS

37

the demarcation, assimilation and integration perspectives. While this chapter analyses what innovation means in services, Chapter 4 focuses on innovation measurement, also disentangling the concepts of service newness and differentness (i.e. how innovative a service is).

Product and process innovations Product innovation is the introduction to the market of a product, or in this case a service, that is new in terms of technical characteristics and functions compared with the one previously offered by the company. Process innovation, on the other hand, refers to a change in a series of activities/processes connected with the provision of a service and ranging from production to distribution. Following the Oslo Manual 2018, product innovation includes significant improvements in technical specifications, components and materials, software, user friendliness or other functional characteristics of the service. Process innovation includes significant changes in techniques, equipment and/ or software (OECD and Eurostat, 2018). For example, the introduction of BIM (building information modelling) software for the design of buildings represents a product innovation for the ICT company that developed and launched it on the market and a process innovation for the architects who use it. Before the introduction of this software, architects created a project on their desk, then passed it on to the study office, and then it was possible to order the materials according to the needs of the building, which could be different from the original idea, hence the difference between the estimate and the real cost. Today, architects can use the three-dimensional software BIM that suggests ex ante which are the best materials to realize the project (components and related brands, price, characteristics, etc.). In real time, architects can understand the impact that each of their design choices can have on the cost and time of project development. The BIM is a process innovation in that it does not substantially modify the service provided by architects, the designing of buildings, but modifies the process through which a project is realized and improves the design’s adherence to the initial project and the time to market. The distinction between product and process innovation has long been recognized in the economic literature as crucial to identifying different business strategies. Product innovations are generally associated with technology-based strategies; they are more radical and proactive strategies that should be accompanied by important economic returns for the company. Process innovations prevail in the world of industry and signal a strategy whereby technology plays a defensive role: it does not serve to start new business lines but to defend existing ones by increasing the efficiency of production processes through their rationalization/restructuring. Process innovation makes the company more competitive on the price side. The literature available on the subject is largely focused on manufacturing.

38 Innovation in KIBS Initially, the literature suggested that it was not possible to distinguish the two types of innovation in services, because often the process of providing the service involves the customer, so there is no clear distinction between a production phase in the back office, in which to introduce process innovations, and a delivery phase in the front office. The concomitant delivery and fruition of the service and the impossibility of storage make it difficult to distinguish the two types of innovation (Evangelista and Savona, 1998; Miles, 1995). Consequently, the economic return of the two types of innovation can also be difficult to appreciate (Gallouj and Weinstein, 1997; Miles, 1995; Tidd, Bessant and Pavitt, 2005). Moreover, some authors suggest that, in many service industries, it is precisely the introduction of new processes that allows the development of product innovations and the development of new products that may require new processes (Barras, 1986). However, some authors acknowledge the relevance of this distinction in services too and the possibility of separating product and process innovations (Hipp and Grupp, 2005; Sirilli and Evangelista, 1998; Tether, Hipp and Miles, 2001). In a study on Germany, Hipp and Grupp (2005) show that the distinction between product and process innovation is relevant, because 55% of all surveyed service firms undertook product innovations, while 50% of them undertook process innovations. Castro, Montoro-Sanchez and Ortiz-deUrbina-Criado (2011) prove that most service innovation firms introduce both product and process innovations. Focusing specifically on KIBS, some authors show results comparable with the literature given here. Freel (2006) compares KIBS firms and manufacturing firms as well as p- and t-KIBS and concludes that KIBS firms innovate in either the product or the process. In services, some scholars argue that product innovations require greater organizational and learning efforts, because they require the introduction of both new services and new delivery procedures, while new processes focus only on procedures (Hipp and Grupp, 2005; Sirilli and Evangelista, 1998). Moreover, process innovations are often less destructive, because they are aimed at making the enterprise more efficient and thus build on the firm’s cumulated experience (Garcia and Calantone, 2002; Sirilli and Evangelista, 1998). In general, it has been observed that, other things being equal, product innovation requires greater efforts to acquire new knowledge and skills at the organizational and management levels, especially when the new service is based on new production and distribution processes (Hipp et al., 2000). Process innovations are less destructive in terms of existing skills and knowledge, because they consist of the implementation of changes in processes, not the specific functions of the service offered. Process innovations are aimed at gaining a competitive advantage, generally in terms of costs, through increased efficiency. In contrast, product innovations have a greater impact than process innovations on the growth of KIBS companies, as they are geared towards entering new segments or markets (differentiation or diversification strategy). In line with the arguments given, while the traditional product life cycle model suggests that product innovations come first and process innovations

Forms of innovation in services and KIBS

39

follow (Anderson and Tushman, 1990; Utterback and Abernathy, 1975), Barras (1986) argues that, in services, the cycle can be reversed because product innovations are riskier and more complex to introduce than process innovations, especially when they rely on new technologies. Abernathy and Utterback (1978) identify three phases that characterize the innovation process: the fluid phase, the transition phase and the specific phase. The fluid phase is characteristic of periods in which there is strong environmental uncertainty and product innovations are often radical and aim to open up new markets. During the transition phase, companies identify the highly performing technological solutions that best meet the customers’ needs, and a dominant design is often established. At this point, the competition increasingly shifts from product to process innovations, which allow the production costs to be reduced. The technology used by different companies is similar, and competition between companies is no longer based on product differentiation but on production costs. This condition is maintained until new radical product innovations arise. In the Abernathy and Utterback model (1978), product and process innovations evolve interdependently through distinct phases that correspond to differences in the structure of the sector and, consequently, in the source of competitive advantage. The Barras model (1986), developed for the case of services, is called “reversed cycle” because the relevance of product and process innovations is reversed in time. In the Barras model, innovation in services is guided by the adoption of new technologies, and service companies innovate mainly by adopting technical innovations. According to this model, the evolution of service innovation follows an inverted cycle, because first we observe the introduction of incremental process innovations and only later do service firms experiment with more radical product innovations. The Barras cycle is therefore reversed compared with that of Abernathy and Utterback (1978), because, in services, companies use new technologies first to be more efficient in delivering their services and to improve their service quality, and only later do they use the new technology also to develop a radical product innovation. The Barras cycle begins when companies, typically in the back office, adopt new technologies. At the time of the author’s first publications, Barras refers to the spread of personal computers, and interestingly this model could be of renewed importance today due to the relevance of digitalization processes in shaping service firms’ innovative offer. In the model, new technologies are initially adopted prudently, mainly in the back office, to increase the efficiency, responsiveness and quality of services. The dialogue between technology providers and service companies also triggers a cycle of incremental innovations that improves the existing technologies, such as the development of software dedicated to service companies with similar needs by sector or size. Incremental process innovations help service companies to be more competitive and attract new customers. In the second step, the knowledge and experience accumulated by service companies in using the new technologies in the back office allow firms to take a step further and start introducing the same technologies in the front office to

40 Innovation in KIBS improve the phase of service delivery in contact with the customer. These process innovations are more radical, because their aim is to improve not only the efficiency of the existing offer but also the quality of the experience offered to the customer. For example, these technologies are often used to manage queues. Innovation is not about the nature of the service provided but about how it is delivered. Process innovations increasingly augment the productivity of service companies and increase their service quality. For example, in law firms, PCs and software are used to store and manage client files (incremental process innovation in the back office), but they can also be used by secretaries to provide clients with real-time information on their status without the need to search and consult paper folders manually or to wait for the lawyer’s feedback. In recent years, specific software products have been developed to provide this service (process innovation in the front office). In the third phase of the cycle, service companies accumulate experience in using and managing the new technology and start investing in developing new services relying on these technologies by creating a dedicated R&D unit or collaborating with external partners. At this stage, the innovations introduced are product innovations. New technologies no longer improve the existing services but can be used to develop totally new services, such as a home banking service. The Barras model is therefore interesting due to its ability to enable a discussion on how innovation in services and in KIBS can follow an inverse cycle, with respect to the consolidated model of Abernathy and Utterback, when innovation is technology driven and new technologies are developed externally. In addition, the model is of interest as its application to real cases shows once again how it may be difficult to distinguish clearly between new products and new processes. Particularly, it becomes very difficult to distinguish between process innovations in the front office (satisfying the same needs in a different way) and product innovations (satisfying new needs). Moreover, in reality, the cycle often remains unfinished, because process innovations do not lead to product innovations. As Gallouj (1998) also points out, in the legal and notary professions, new technologies have often improved back-office and front-office management from a process point of view but have not had an impact on product innovation, which, by definition, must be subject to a stringent standard. According to Gallouj, the Barras model is applied to the services that are most sensitive to technological evolution and characterized by the need to offer a mass information service, such as banks, insurance companies, public administrations and large audit firms, but not to the generality of services.

Adding layers of innovation: From the concept to the interface The recent literature extensively discusses the competitive strategies and innovative pathways of service companies. In this context, the product/process dichotomy is explored further using more nuances. In fact, innovation in services can take different forms: it can concern the technologies used to provide a service (such as a piece of software or the Internet), the organization of human resources (who does

Forms of innovation in services and KIBS

41

what) and the actions necessary to provide the service (the processes in the strict sense and the procedures that characterize them). While Damanpour, Walker and Avellaneda (2009) provide a description of these categories with regard to services in general, den Hertog (2000) develops a model that identifies four areas of innovation in KIBS: the concept; technology; organization and human resources; and the relationship with competitors and the market. The concept of a service represents the notion of the service itself. The service concept is a brief description of how the service will meet the customers’ needs, its functions and characteristics, the customers for whom it is intended, its innovative elements and its position vis-à-vis the competition. A new concept is always so in relation to the sector and the time when it was introduced. Examples include call centres, which install, organize and hire staff for their customers, and IT consultancy firms, which provide customers with semi-standard and incremental plans to develop e-commerce services. Although not all service innovations derive from a newly generated concept, innovations of the concept are more widespread in service companies than in manufacturing companies. For the development of a new concept, first it is necessary to identify the needs of customers, activating information flows between the KIBS firm and its clients. Clients’ needs are used to set service specifications, and this is a crucial step that requires ad hoc tools, skills and metrics to translate customer needs adequately into service design specifications. In addition, new concepts require complex benchmarking against competitors or previous versions of the service provided. New concepts can lead to new business models. When we think of Uber, do we have in mind an innovative taxi company or a technology company? In the case of new service concepts, the technology often enables the development of a new business model, and it becomes difficult to distinguish the concept and the technological innovations. Another example of concept innovation is the development and management of digital boutiques. Retail and interior designers specializing in shop design, in collaboration with a team of software developers, are able to create a new shopping experience for customers, who are accompanied from their entrance to the purchase through digital media (such as tablets and interactive mirrors) that allow them to learn which clothes or accessories are best suited to their needs, see the recent trends, see how designers suggest completing an outfit, ask for advice through social networks, determine the availability of other clothes in other warehouses in real time and view them and interact with the clerks. DS Group1 is one of the companies operating in this sector that develops such an innovative boutique concept. The traditional tendency to see services as relatively low-tech when compared with the manufacturing sector is due to the fact that services often do not produce outputs that visibly incorporate advanced technologies. However, the relevant statistics show that, in many service industries, the ICT investments are greater than those in the manufacturing sector: the available statistics show that ICT expenditure in services is constantly increasing and that the total share of ICT expenditure by service companies exceeds the share of expenditure in the manufacturing system. The fact that KIBS companies are strongly oriented

42

Innovation in KIBS

towards investing in ICT technologies has important implications for their ability to innovate and for the way in which they produce, deliver and distribute their services. In services, we are moving from an idea of technology as supporting firms’ organization and service delivery to one of technology-driven innovations. An example of technology-driven innovation in KIBS is the trackand-trace systems that enable logistics service providers to offer a real-time tracking service for goods (Cabigiosu et al., 2015). New service concepts often require changes in the concepts and technologies adopted by KIBS companies. For this reason, product innovations, which bring new service concepts, are often coupled with process innovations, which concern how the new concept will be implemented by the KIBS company. However, while concept innovations are often coupled with other types of innovations, such as organizational or technological innovations, it is possible to introduce technological innovations, organizational innovations and, more generally, new processes without delivering a new service concept. Examples of new service concepts delivered through innovative technical/organizational solutions are ecommerce services, which can bring about substantial changes in the relationship between customers and suppliers and which may require strong reengineering processes. These can have substantial impacts not only on business transactions but also on internal business processes. On the contrary, an example of an organizational innovation that does not necessarily alter the product concept is the introduction of lean practices within a company, referring to both the internal organization of processes and for example the quality controls. The relevance of new technologies as a driver of innovation in KIBS, and in particular of ICT technologies, also allows an understanding of the importance of the synergistic relationships between p-KIBS and t-KIBS. Often the customers of t-KIBS are p-KIBS. Obviously, service innovation is feasible even without technological innovation, as technology is not always a decisive dimension in service companies. In spite of the increasing codification of knowledge, a trend that is correlated with the rise of ICT technologies, the tacit components of knowledge still play an important role in the processing of information and its transformation into added-value content for the KIBS company. Human resources are always central to the processes of knowledge creation, validation and accumulation (Corrocher, Cusumano and Morrison, 2009). Human capital is a strategic variable for KIBS companies showing increasing investment in human resources. These investments are crucial, because KIBS companies provide services with a high content of knowledge, which is tacit and explicit, and because technological innovation can be managed proactively if KIBS companies invest in human capital. According to Doloreux, Turkina and Van Assche (2018) and Tether (2005), service innovation is more likely to have an impact on internal organization than product innovation. Following the Oslo Manual, organizational innovation is a new organizational method in business practices, workplace organization or external relations (OECD and Eurostat, 2018), introducing new services means, as already discussed, modifying the delivery processes that involve the organization of

Forms of innovation in services and KIBS

43

work and often also human resources, as they require a widespread effort for change and learning. Innovation in KIBS requires the broadening of the knowledge base of all those workers involved in the innovation process but also the ability to manage the necessary process of codification of the new routines and standards associated with the new services. In other words, KIBS firms have to manage the well-known knowledge generation cycle described by Nonaka and Takeuchi (1995) in which the spiral cycle of learning is triggered not only by the internal sharing of tacit knowledge between employees but also by the interaction with expert suppliers that allows the acquisition and management of new technologies. Today, many big insurance brokers are introducing organizational innovations. These KIBS firms have business firms as their main clients and act for them as brokers searching for the market policies with the most favourable conditions. This search process is time consuming, and, if brokers are busy quoting for an insurance policy, they cannot search for new clients. Today, the most structured groups have modified their organization and introduced two additional profiles, specialized brokers and operations, that collaborate with brokers. Specialized brokers have in-depth competences in specific risks, such as insurance for ski lifts or art galleries, working both in the back office by supporting brokers when they meet clients with specific requirements that might eventually lead to writing and quoting customized policies and in the front office with their own clients. Brokers work in the front office and have many clients with multiple requirements. To increase their productivity, the operation is now in charge, each month, of asking for a quotation for all the policies of a given broker that expire by the end of the month. The operation requests the quotation from the same company with which the client previously signed the policy. If the price of the policy has not changed or has decreased, the broker can send the proposal for the policy renewal to the client; otherwise, if the price of the policy has increased, the broker starts directly managing the policy in search of better conditions. This new organization creates three different profiles that interact tightly: the specialist with the most specialized know-how, the broker, who mainly manages the commercial relationship with clients, and the operations, which renew existing insurance policies. Innovation in KIBS firms can also occur in the design of the interface between the service provider and the customer. A large body of research studies how novelty arises from and focuses on the interaction with clients, which is characteristic of service provision (Edvardsson et al., 2001; Hsieh and Tidd, 2012). This is of particular importance for KIBS firms, because they interact intensively with clients (den Hertog, 2000; Miles et al., 1995; Muller and Zenker, 2001). Services are increasingly marketed and produced in a client-specific fashion, even with regard to pricing and delivery policies. In the service sector in particular, customers are an integral part of the service delivery process. The way in which service providers interface with clients can also lead to innovation. The high degree of co-design and co-production of services can make it difficult to define exactly where innovation is collocated between buyer and supplier. An example

44

Innovation in KIBS

of this type of innovation is the introduction of electronic data interchange (EDI) technologies, which represent an effort to establish common formats for electronic documents that allow the automation, at least partially, of a large part of the interactions between clients and external service providers (den Hertog, 2000). These systems provide both innovative services and an innovative (electronic) interface with clients. Finally Amara, Landry and Doloreux (2009) and Doloreux, Turkina and Van Assche (2018) add the category of marketing innovation, which involves significant changes in product design or packaging, product placement and product promotion or pricing. Many authors simultaneously analyse multiple types of innovations. Amara, Landry and Doloreux (2009) discuss six types of innovation in KIBS: product, process, delivery, strategic, managerial and marketing innovations. Similarly, Corrocher, Cusumano and Morrison (2009) analyse innovation patterns across KIBS and uncover four profiles: product innovation, interactive innovation, conservative innovation and techno-organizational innovation. Different types of innovation (product, process, technological, organizational, etc.) are therefore mixed in the same service, and the use of different types of innovation can ensure significant synergies, sustaining firms’ growth (see Chapter 6).

Do we really need specific categories of innovation for KIBS firms? Despite the importance of services, they are subject to the same forces that manufacturing experiences. As a matter of fact, commoditization and shortening product life cycles create a commodity trap in services as much as in products. To mitigate this risk, service innovation is as essential as product innovation is in the manufacturing sector. Innovating in services is an escape route from the commodity trap and a solution for growth, giving firms a significant competitive advantage (Chesbrough, 2011). Nevertheless, services receive relatively little attention in the management literature, particularly at the micro level (Tether, Hipp and Miles, 2001). This is probably related to the intangible nature of services and the strong influence that the manufacturing-based approach to the study of innovation exerts on the study of innovation in services (Gallouj and Weinstein, 1997). Traditionally, scholars focus on how KIBS firms can contribute to innovation within their client firms and much less on disentangling KIBS’ own innovativeness (Amara et al., 2009; den Hertog, 2000). This gap is mainly because innovation output in service firms is difficult to measure and describe due to its intangibility (Leiponen, 2005). Furthermore, KIBS firms are known for formalizing their innovation efforts only occasionally (Miles, 2007). The observation that KIBS firms develop new services and that innovation capabilities are crucial for their competitive advantage has led to increasing interest in service innovation output (Gallouj and Savona, 2009). The recent literature on service innovation produces different definitions of innovation that seek a broader understanding of the meaning of the term innovation as applied to services and

Forms of innovation in services and KIBS

45

compared with products. Witell et al. (2016) synthesize this debate, starting from the tripartition identified by Coombs and Miles (2000). According to these authors, the studies on innovation in services alternatively adopt one of the following approaches: assimilation, demarcation or synthesis. The studies that use assimilation as a perspective focus on the impact and role of technology in promoting innovation. From this perspective, services are seen as technology and capital intensive and often adopt technological innovations developed externally by suppliers (Evangelista, 2000; Gallouj, 2002; Miozzo and Soete, 2001; Tether, 2005). In this sense, innovation in services is not very different from innovation in products, and the same definitions, theories and measures are usually applied. Studies in this tradition build on the same conceptual framework, definitions and instruments used to research technological and product innovation in manufacturing. However, many authors also acknowledge the importance of the development of taxonomies of specific technological trajectories for services (Miozzo and Soete, 2001). Djellal and Gallouj (2001), Drejer (2004), Tether and Howells (2007) and Hipp et al. (2000) somewhat criticize the assimilation approach, because it tends to ignore the facts that innovation in services has specific characteristics and that innovations encompass various forms. Consequently, those who want to emphasize the specificity of services adopt a demarcation perspective. In this vision, service innovation differs from product innovation and requires specific theories and definitions (Drejer, 2004; Droege, Hildebrand and Forcada, 2009; Gadrey, Gallouj and Weinstein, 1995). These researchers emphasize the peculiar aspects of service innovation, such as its intangible nature, the relevance of clients and the dialogue and integration with them, the relevance of organizational innovation and the non-technological aspects of innovation (Drejer, 2004; Hipp and Grupp, 2005). Accordingly, these scholars introduce ad hoc definitions and measures of innovation, such as organizational or interface innovation, and ad hoc control variables, such as the percentage of employees with a degree (see the next chapter). This approach rejects the centrality of technology in innovation (Drejer, 2004; Gallouj and Weinstein, 1997; Hauknes, 1996). The approach also requires the use of ad hoc surveys, specifically designed to understand innovation in services, but it is less suited to comparing the specificities of innovation in services with those in manufacturing: different constructs and surveys make it harder to obtain comparable data between manufacturing and service firms and grasp their similarities and differences to the fullest. Consequently, today, the literature on innovation in services recognizes the importance of monitoring technological and non-technological innovations and their interactions and complementarities (Tether and Howells, 2007). This view underpins the third approach to innovation in services, which Hauknes (1996) calls the integrated or synthesis approach and which highlights the growing complexity and multidimensional nature of innovation in services and manufacturing. The perspective of synthesis suggests that today it is difficult to distinguish products and services because many companies sell packages that include

46

Innovation in KIBS

products and services, such as digital antennas and pay TV, or services that are provided with material support, such as ATMs for the cash withdrawal service. Servitization is now also widely recognized as the process of creating value by adding services to products (Vandermerwe and Rada, 1988). Today, the value proposition of many firms often includes services as fundamental value-added activities and reduces the centrality of products, which may become just part of the offering, for example services such as those offered by General Electric (GE) around its product markets (e.g. financial services) or the distribution control system used by Coca-Cola to grab shelf space in its high-volume, low-margin supermarket segment (Baines et al., 2009). Innovation theories should therefore be broad enough to be applicable simultaneously to products and services. These authors define toolkits that are suitable for studies of innovation in multiple settings (Drejer, 2004; Flikkema, Jansen and Van Der Sluis, 2007; Sundbo, 1997; Toivonen and Tuominen, 2009). They usually imply the definitions of innovation included in the Oslo Manual (OECD and Eurostat, 2018). Witell et al. (2016) show that the majority of published research uses the demarcation approach. Their research questions the suggestion posed by prior research that synthesis as a perspective is replacing assimilation and demarcation. While the synthesis perspective is growing, the number of articles adopting assimilation or demarcation perspectives is neither decreasing nor disappearing. Furthermore, Wittel et al. (2016) find that several recent papers define service innovation according to the assimilation perspective, which suggests that the assimilation perspective might even be regaining its strength. Interestingly enough, Wittel et al. (2016) also show that simply defining service innovation as a “new service” is the most common interpretation, which implies that every firm, to some extent, is innovative without specifying how much, since “new” is a relative concept. However, the authors also identify differences between the three approaches. First, the assimilation perspective focuses on technology-based inventions, product, process or organizational, that are new to the world and have economic consequences for the firm. Examples are online banking or search engines. Second, the demarcation perspective focuses on inventions that are new to the firm and somehow suggests that all service firms develop some kind of service innovations. Finally, from the synthesis perspective, both products and processes that are new to the firm can be part of the value proposition offered to customers as a service innovation. From the assimilation perspective, innovation often means technical innovation; from the demarcation perspective, it often refers to minor process adaption for a firm; and, from the synthesis perspective, innovation means new skills in service development. Product and process innovations are examples of categories of innovation that can be traced back to the perspective of both synthesis and assimilation, while organizational and interface innovations are closer to the perspective of demarcation. Overall, these paragraphs suggest that the demarcation approach could be of value when researchers try to emphasize industry- and firm-specific innovation strategies, and several studies, especially qualitative ones, about KIBS firms rely

Forms of innovation in services and KIBS

47

on this approach. On the contrary, the synthesis approach may be more useful for capturing recent trends and in quantitative studies. In this respect, the alignment of definitions used in products, services and KIBS surveys may increase results’ comparability and respondents’ correct understanding of concepts, such as the difference between innovation that is new to the firm and innovation that is new to the industry.

Note 1 www.dsgroup.it/?lang=en

References Abernathy, W.J. and Utterback, J.M. 1978. Patterns of innovation in technology. Technology Review, 80, 40–47. Amara, N., Landry, R. and Doloreux, D. 2009. Patterns of innovation in knowledgeintensive business services. Service Industries Journal, 29(4), 407–430. Anderson, P. and Tushman, M. 1990. Technological discontinuities and dominant designs: A cyclical model of technological change. Administrative Science Quarterly, 35(4), 604–633. Baines, T.S., Lightfoot, H.W., Benedettini, O. and Kay, J.M. 2009. The servitization of manufacturing: A review of literature and reflection on future challenges. Journal of Manufacturing Technology Management, 20(5), 547–567. Barras, R. 1986. Towards a theory of innovation in services. Research Policy, 15, 161–173. Cabigiosu, A., Campagnolo, D., Furlan, N. and Costa, G. 2015. Modularity in KIBS: The case of third-party logistics service providers. Industry and Innovation, 22(2), 126–146. Castro, L.M., Montoro-Sanchez, A. and Ortiz-de-Urbina-Criado, M. 2011. Innovation in services industries: Current and future trends. Service Industries Journal, 31(1), 7–20. Chesbrough, H. 2011. Open Services Innovation: Rethinking Your Business to Grow and Compete in a New Era. Wiley, New York. Coombs, R. and Miles, I. 2000. Innovation, measurement and services: The new problematique. In: Metcalfe, J. and Miles, I. (Eds.) Innovation Systems in the Service Economy. Measurements and Case Study Analysis. Kluwer Academic Publishers, Dordrecht, pp. 83–102. Corrocher, N., Cusumano, L. and Morrison, A. 2009. Modes of innovation in knowledge-intensive business services: Evidence from Lombardy. Journal of Evolutionary Economics, 19, 173–196. Damanpour, F., Walker, R.M. and Avellaneda, C.N. 2009. Combinative effects of innovation types and organizational performance: A longitudinal study of service organizations. Journal of Management Studies, 46(4), 650–675. Den Hertog, P.D. 2000. Knowledge-intensive business services as co-producers of innovation. International Journal of Innovation Management, 4(4), 491–528. Djellal, F. and Gallouj, F. 2001. Patterns of innovation organization in service firms: Postal survey results and theoretical models. Science and Public Policy, 28, 57–67. Doloreux, D., Turkina, E. and Van Assche, A. 2018. Innovation type and external knowledge search strategies in KIBS: Evidence from Canada. Service Business, 1–22. Drejer, I. 2004. Identifying innovation in surveys of services: A Schumpeterian perspective. Research Policy, 33(3), 551–562. Droege, H., Hildebrand, D. and Forcada, M.A.H. 2009. Innovation in services: Present findings, and future pathways. Journal of Service Management, 20(2), 131–155.

48 Innovation in KIBS Edvardsson, B., Gustafsson, A., Kristensson, P., Magnusson, P. and Matthing, J. 2001. Involving Customers in New Service Development. Imperial College Press, London. Evangelista, R. 2000. Sectoral patterns of technological change in services. Economics of Innovation and New Technology, 9(3), 183–222. Evangelista, R. and Savona, M. 1998. Patterns of innovation in services. The results of the Italian innovation survey, paper presented to the VIII Annual RESER Conference, October 8–10, 1998, Berlin. Flikkema, M., Jansen, P. and Van Der Sluis, L. 2007. Identifying neo-Schumpeterian innovation in service firms: A conceptual essay with a novel classification. Economics of Innovation and New Technologies, 16(7), 541–558. Freel, M. 2006. Patterns of technological innovation in knowledge-intensive business services. Industry and Innovation, 13(3), 335–358. Gadrey, J., Gallouj, F. and Weinstein, O. 1995. New modes of innovation. International Journal of Service Industry Management, 6(3), 4–16. Gallouj, F. 1998. Innovating in reverse: Services and the reverse product cycle. European Journal of Innovation Management, 1(3), 123–138. Gallouj, F. 2002. Innovation in the Service Economy: The New Wealth of Nations. Edward Elgar Publishing, Cheltenham, UK. Gallouj, F. and Savona, M. 2009. Innovation in services: A review of the debate and a research agenda. Journal of Evolutionary Economics, 19(2), 149–172. Gallouj, F. and Weinstein, O. 1997. Innovation in services. Research Policy, 26, 537–556. Garcia, R. and Calantone, R. 2002. A critical look at technological innovation typology and innovativeness terminology: A literature review. Journal of Product Innovation Management, 19(2), 110–132. Hauknes, J. 1996. Innovation in the Service Economy. STEP report, Oslo, December 1996. Hipp, C. and Grupp, H. 2005. Innovation in the service sector: The demand for servicespecific innovation measurement concepts and typologies. Research Policy, 34(4), 517–535. Hipp, C., Tether, B.S. and Miles, I. 2000. The incidence and effects of innovation in services: Evidence from Germany. International Journal of Innovation Management, 4(4), 417–453. Hsieh, K. and Tidd, J. 2012. Open versus closed new service development: The influences of project novelty. Technovation, 32, 600–608. Leiponen, A. 2005. Organization of knowledge and innovation: The case of Finnish business services. Industry and Innovation, 12(2), 185–203. MacKenzie, S.B. 2003. The dangers of poor construct conceptualization. Journal of the Academy of Marketing Science, 31(3), 323–326. Miles, L. 1995. Service Innovation: Statistical and Conceptual Issues. PREST Working Paper, University of Manchester. Miles, I. 2007. Research and development (R&D) beyond manufacturing: The strange case of services R&D. R&D Management, 37(3), 249–268. -Miles, I., Kastrinos, N., Bilderbeek, R., den Hertog, P., Flanagan, K., Huntink, W. and Bouman, M. 1995. Knowledge-Intensive Business Services: Users, Carriers and Sources of Innovation. European Innovation Monitoring System (EIMS) Reports. Miozzo, M. and Soete, L. 2001. Internationalization of services: A technological perspective. Technological Forecasting and Social Change, 67(2–3), 159–185. Muller, E. and Zenker, A. 2001. Business services as actors of knowledge transformation: the role of KIBS in regional and national innovation systems. Research Policy, 30(9), 1501–1516. Nonaka, I. and Takeuchi, H. 1995. The Knowledge-Creating Company. How Japanese Companies Create the Dynamics of Innovation. Oxford University Press, New York/Oxford.

Forms of innovation in services and KIBS

49

OECD and Eurostat. 2018. Oslo Manual 2018: Guidelines for Collecting, Reporting and Using Data on Innovation, 4th Edition, The Measurement of Scientific, Technological and Innovation Activities. OECD Publishing, Paris/Eurostat, Luxembourg. Scerri, M. and Randhawa, K. 2015. Service innovation: A review of the literature. In: Argarwal Selen, R.W., Roos, G. and Green, R. (Eds.) The Handbook of Service Innovation. Springer, London, pp. 27–51. Sirilli, G. and Evangelista, R. 1998. Technological innovation in services and manufacturing: Results from Italian surveys. Research Policy, 27(9), 881–899. Sundbo, J. 1997. Management of innovation in services. Service Industries Journal, 17(3), 432–455. Tether, B.S. 2005. Do services innovate (differently)? Insights from the European Innobarometer survey. Industry and Innovation, 12(2), 153–184. Tether, B. and Hipp, C. 2002. Knowledge intensive, technical and other services: Patterns of competitiveness and innovation compared. Technology Analysis & Strategic Management, 14(2), 163–182. Tether, B.S., Hipp, C. and Miles, I. 2001. Standardization and particularization in services: Evidence from Germany. Research Policy, 30, 1115–1138. Tether, B. and Howells, J. 2007. Changing Understanding in Innovation in Services. DTI. Innovation in Services. Occasional Paper No. 9, June. Department of Trade and Industry, UK. Tidd, J., Bessant, J. and Pavitt, K. 2005. Managing Innovation: Integrating Technological, Market and Organizational Change. 3rd ed. John Wiley & Sons, Chichester, UK. Toivonen, M. and Tuominen, T. 2009. Emergence of innovations in services. Service Industries Journal, 29(7), 887–902. Utterback, J.M. and Abernathy, W.J. 1975. A dynamic model of process and product innovation. Omega, 3(6), 639–656. Vandermerwe, S. and Rada, J. 1988. Servitization of business: Adding value by adding services. European Management Journal, 6(4), 314–324. Witell, L., Snyder, H., Gustafsson, A., Fombelle, P. and Kristensson, P. 2016. Defining service innovation: A review and synthesis. Journal of Business Research, 69(8), 2863–2872. Wong, P.K. and He, Z.L. 2005. A comparative study of innovation behaviour in Singapore’s KIBS and manufacturing firms. Service Industries Journal, 25(1), 23–42.

4

Measuring innovation in KIBS

Studying innovation in KIBS requires both output and input measures. This chapter focuses on how studies about KIBS define and measure internal and external sources of innovation and how they measure innovative performance.

The sources of innovation While, for manufacturing firms, the input measures for innovation are overall standard control variables accepted across the board, in KIBS, with the exception of a few technology-oriented KIBS, new services are less the result of R&D than of the acquisition of new technologies and/or software (Doloreux, Turkina and Van Assche, 2018; Hipp and Grupp, 2005). Consequently, the measurement of internal sources of innovation requires the capture of the overall investments made in innovation activities and not only those in R&D activities. In addition, in KIBS, clients and other partners in prompting innovation are of particular relevance, because KIBS firms are very active as far as open innovation is concerned and rely on external partners for their innovations. The next two sections review the current knowledge about internal and external innovation sources in KIBS.

Internal sources The internal innovative capacity in KIBS is typically linked to the presence of knowledge workers and their qualifications, usually captured by the percentage of employees with a degree (Cabigiosu and Campagnolo, 2019; Rodríguez, Nieto and Santamaría, 2018). In more recent studies, authors measure internal sources dedicated to innovation by measuring the R&D internal investments, either with a dummy variable or as a percentage of the overall revenue. Howells (2000) and Young (1996) find some similarities between R&D conducted by manufacturing firms and R&D conducted by some service firms. Amara, Landry and Doloreux (2009) and Freel (2006) suggest that higher levels of R&D expenditure in KIBS contribute to increased innovation, although some differences are found between industries. For instance, Freel (2006) obtains different results for p-KIBS and t-KIBS, whereas Koch and Strotmann (2008) find a

Measuring innovation in KIBS

51

significant effect of R&D on radical, but not on incremental, innovation. Overall, t-KIBS seem to be more prone to carrying out R&D than p-KIBS. However, as Doloreux,et al. (2018) suggest, the predominance of R&D in t-KIBS may be apparent because scholars develop measures only to evaluate technological research, while we still lack tools to quantify other types of investments, such as marketing investments. Some authors also claim that internal investments span R&D internal investments, which are not so diffused in small KIBS firms. For example, Doloreux et al. (2018) measure KIBS innovation inputs by counting the number of ICT applications employed by KIBS firms and the scientific, technological, organizational, financial and commercial activities that lead, or are intended to lead, to the implementation of innovations. These activities are internal R&D, external R&D, the acquisition of equipment, and software training and design. Love and Mansury (2007) use dummy variables and distinguish between in-house R&D if the firm has in-house R&D, formal R&D if the firm has an R&D department and informal R&D if the firm has R&D but no formal department. To cope with this complexity, Rodríguez et al. (2018) measure both the R&D efforts with a binary variable coded 1 if the firm undertook internal R&D and 0 otherwise (they obtain a mean level of 0.79 with a standard deviation of 0.40) and the overall “innovation expenditure” by summarizing the number of investments in the following six areas: external R&D; acquisition of machinery, equipment and software; acquisition of existing knowledge from other firms or institutions; preparations for production and/or distribution; training; and market introduction of innovations. This variable ranges from 0 to 6, and they obtain a mean level of 0.93 with a standard deviation of 1.07. Rodríguez et al. (2018) find that KIBS firms’ innovation effort is partly captured by the investments in R&D and negatively correlated with the innovation outcome, while market sources (i.e. cooperation with suppliers, clients, competitors and commercial labs) have a positive effect. Overall, the authors emphasize the need for R&D in KIBS to be explored and understood better: their findings show that only the variable referring to the variety of innovation expenditures is positively associated with new-to-firm and new-to-market innovation in the whole sample, while internal R&D has a negative impact. These results also suggest the need to broaden the activities classified as R&D in KIBS and maybe to consider including as R&D some items that are currently classified as other innovation expenditures.

External sources In response to the constantly evolving market pressure, companies require complementary resources to innovate, create new sources of competitive advantage and thus increase their level of collaboration with external partners. The role of inter-organizational relationships is more and more relevant in the study of innovative performance (Katila and Ahuja, 2002; Powell, Koput and Smith-Doerr, 1996). Indeed, building a new product or service can be a very complex project in which many different actors become involved. In particular,

52

Innovation in KIBS

the “open innovation” literature argues that firms engage in external collaborations to gain access to skills and knowledge that are not available within the boundaries of the organization (Chesbrough, 2003; Laursen and Salter, 2006; Rosenkopf and Nerkar, 2001). KIBS often rely on external R&D and on expert partners to develop their innovations. In this respect, Rodríguez et al. (2018) identify two categories of partners in KIBS: market/value chain and research/institutional partners. Market/ value chain partners mainly include clients and suppliers. A substantial body of innovation literature suggests that firms should invest in client relationships to refine their products and services, sense market opportunities and threats, and ultimately gain valuable knowledge and information that foster their innovation processes (Chesbrough, 2003; Kotabe, Martin and Domoto, 2003; Sobrero and Roberts, 2002). Clients might have an active role in directing the firm’s attention toward specific opportunities, and their involvement in a firm’s innovation process is likely to lead to the development of superior innovations. In this context, the role of customers is widely recognized as an antecedent to innovation, but the exploitation of this source of external knowledge might be a very complex activity. Firms need multiple coordination and control mechanisms to build and sustain the relationship with clients and to avoid opportunistic behaviours (Von Hippel, 1988). Firms also need to balance their level of dependence on them by engaging in multiple partnerships (Stinchcombe, 1965; Thompson, 1967). Customers are not the only source of external knowledge that influences a firm’s ability to innovate. An “open innovation” model implies the use of a wide range of external actors and sources of innovation (Chesbrough, 2003; von Hippel, 1988). In the market/supply chain category, suppliers are also important partners, providing technology (often IT technology) and the required knowledge for technology adoption and support in new product development and in problem-solving activities (Leiponen, 2005; Tether, 2005; Tsai and Hsieh, 2009). At times, competitors can also be partners within specific, and often large, projects. However, cooperation with competitors can be risky (Freel, 2006) and requires a strong common interest or expected research results with a generic character (Miotti and Sachwald, 2003). Interestingly, Leiponen (2005) shows that information sourcing from both customers and competitors has a positive impact on innovation in KIBS. Research/institutional partners include universities and research organizations. These sources are vital for recognizing opportunities of all kinds, such as product and process innovations but also new markets, organizational structures and management processes (Ferreras-Méndez, Fernández-Mesa and Alegre, 2016; Monteiro, Mol and Birkinshaw, 2017). Although universities do not appear to be a relevant source for service innovation, this is contradicted by studies on KIBS (Amara et al.,2009; Muller and Zenker, 2001). Access to scientific and technical knowledge via research/institutional partners is an important complement to other sources of knowledge, first of all clients (den Hertog, van der Aa and de Jong, 2010; Mina, Bascavusoglu-Moreau and Hughes, 2014).

Measuring innovation in KIBS

53

Therrien, Doloreux and Chamberlin (2011) distinguish between technology push and market pull partners and sources of knowledge in that they can affect the success of the innovation. In fact, the innovation outcome might be different if the innovation was required by the market (clients, suppliers and competitors) or by science and technology advancement (knowledge generated by science institutions, such as universities and R&D labs). The authors do not find significant results. Usually external partnering is measured using a count variable if the purpose is that of capturing the breadth of the open innovation strategy (Laursen and Salter, 2006; Love, Roper and Bryson, 2011). For example, Doloreux,et al. (2018) measure “external partnering” by counting the number of types of external parties with which the KIBS firm cooperated during a three-year period. They include seven types of organizations: clients; suppliers; competitors; other KIBS; universities or higher education institutions; commercial laboratories or R&D institutes; and government or public research institutes. Rodríguez et al. (2018) also use a count approach and measure the number of a) market sources, that is, suppliers, clients, competitors and commercial labs, as the sum of the number of market sources with high/medium importance; b) research sources, specifically universities, public research institutes and technological centres, as the number of research sources with high/medium importance; and c) general sources, that is, conferences, trade fairs and exhibitions, scientific journals and technical publications, and professional and industry associations, as the number of general sources with high/medium importance. Therrien,et al. (2011) employ the following dummy variables: a) technology push collaborations equal one if the firm engaged in collaboration with commercial labs/R&D enterprises, universities/other higher education institutes, federal government research institutes, provincial government research institutes or private non-profit research institutes; b) technology push knowledge if the partners cited in a) played an important role as a source of information to innovate; c) market pull collaborations equal one if the firm engaged in collaboration with clients or suppliers of equipment, materials, components, software or competitors; and d) market pull knowledge if the partners cited in c) played an important role as a source of information to innovate (the respondent indicated high importance). Authors can also ask the percentage of ideas/suggestions for innovation derived from specific partners (Love and Mansury, 2007).

The output of innovation activities: Timing and differentness Service innovations are difficult to protect legally (Chang and Chen, 2016), and KIBS companies usually do not rely on patents, copyrights and trademarks because they do not typically consider formal protection mechanisms to be central to capturing value from innovation. Consequently, these indicators are not reliable measures of innovation performance in the service domain (Doloreux et al., 2018; Miozzo et al., 2016; Therrien,et al., 2011).

54 Innovation in KIBS The mainstream KIBS literature measures innovation as a dummy variable, taking the value one if the service firm introduced a new product during the last three years and zero otherwise (Doloreux et al., 2018; Turkina and Van Assche, 2018). Some authors also measure innovation by asking how many new products (or processes) have been introduced in the last three years (Cabigiosu and Campagnolo, 2019). Depending on the aim of the study, scholars can also distinguish the type of innovation, that is, product and process innovations or other types of innovations, such as organizational or marketing. In line with the innovation management literature and the Oslo Manual (OECD/Eurostat, 2018), most of the empirical studies on KIBS also distinguish between new innovations for the company and new innovations for the sector (Hipp and Grupp, 2005). Sometimes a tripartite approach is introduced, with innovations classified as new to the world, to the sector (or a specific region) and to the company (Therrien et al., 2011). The Oslo Manual also suggests that the novelty of innovation can be defined using either technical variables (the use of radical new technology) or the timing of the introduction of the new product in the market. However, most surveys use only the timing of the introduction by including a question on whether the innovation was new to the firm or new to the market.

The timing of entry Innovations that are new to the firm and new to the industry evaluate the market-based novelty of a service. Innovations that are new to the firm are innovations that the enterprise adopts from the external environment (Damanpour, 1992). In this case, KIBS firms innovate by imitating a preexisting offer on the market. As KIBS companies are business-to-business companies, it is often their customers who request new services and encourage them to update their offer. Alternatively, the KIBS firms, observing their competitors on the market, identify new services (processes) that are provided (implemented) by their competitors and decide to accept them to avoid differentiating themselves negatively from their competitors. New innovations for a company identify those innovations that are adopted by the company but that have previously modified the production processes and services offered by competitors on the market. This type of innovation therefore indicates a change in the skills and processes of the company, while other players in the sector have already introduced the innovation and developed the necessary competences and (eventually) the enabling technologies. These types of innovation concern aspects of products and processes that are already known to customers and suppliers and therefore do not require particular costs of change/adaption both downstream for the customers and upstream for the suppliers of the company. In this case, KIBS firms imitate the innovations introduced by competitors and update their range of products.

Measuring innovation in KIBS

55

As far as new innovations for the sector are concerned, however, they refer to changes that involve not only the company that adopts certain solutions but also the sector in which the company operates. If the new service is extended, it will have an impact on the quality, production and organizational standards of the sector. These innovations, unlike new innovations for the company, require greater managerial and organizational skills related to the area of change management. Moreover, at least in the first phase, only customers with less resistance to change and/or those who are particularly sensible to the proposed innovations will be the users of these services. In fact, customers could resist new services if they estimate the high learning costs of the service rather than the disposal of complementary assets. For the success of these innovations, it is therefore essential to know customers’ needs and to have accumulated experience in the co-production of knowledge and services with them. In this way, KIBS firms will reduce the risk of market acceptance that is often related to innovative services. KIBS firms introduce new innovations to the industry when they develop original services/processes compared with those of their competitors. These innovations are expected to have a greater impact on the growth of a company and its reputation (Love and Mansury, 2007) but at the same time may lead to greater difficulties in introduction (Afuah and Bahram, 1995). Innovations that are new to the industry can destroy the existing knowledge and procedures not only of KIBS firms but also of their external stakeholders. If innovations are new to the industry and radical or competence destroying, they may be destructive to the extent that they render existing customers, suppliers and complementors’ assets and knowledge bases obsolete. In these circumstances, external stakeholders may be reluctant to accept the new services. Moreover, new innovations for the sector can have a negative impact on the existing positive network externalities. On the contrary, new innovations for the enterprise are often less destructive, more easily accepted by the market and in line with its needs. In addition, it often happens that companies that imitate someone else’s innovations can improve them at a comparatively lower cost than the cost of the first mover. In this case, we can speak of creative imitations in which KIBS firms modify and improve the new service/process. Some companies systematically monitor the services, products and technologies of other companies operating in the sector and then decide whether to innovate to differentiate their offer from that of their competitors or imitate the offer of their competitors. Although the existing literature explains the determinants of imitation strategies in comparison with innovation strategies (Abrahamson and Rosenkopf, 1993; Bikhchandani, Hirshleifer and Welch, 1998; DiMaggio and Powell, 1983; Lieberman and Asaba, 2006), little attention is given to the analysis of imitative behaviours in KIBS and to the concept of new innovation for firms struggling to distinguish between pure and creative imitation. Companies may not only adopt or copy the innovations of their rivals (pure imitation), but they can also adopt a strategy called copy but improve, which can be a source of additional

56

Innovation in KIBS

competitive advantage (Schnaars, 2002). In the latter case, we can talk about creative imitation, because the company adds factors, or modifies some of them, to the offer of the competitors that it has imitated (Shenkar, 2010). In both cases, it is essential that the innovation (new to the company and the sector) captures the real needs of customers and is therefore open to collecting contamination and suggestions from them. As Chesbrough (2011) suggests, open innovation in KIBS leads to better results and performance for both service companies and their customers. The timing of entry to the market can be measured using a dummy variable, employing a count approach by asking about the number of innovations or by analysing the weight of each type of innovation. In the first case, scholars ask whether the KIBS firm introduced any innovation that was new to the market during the last three years (dummy=1) and whether the KIBS firm introduced any innovation that was new to the firm during the last three years (dummy=1) (Therrien et al., 2011). In the second case, authors ask how many innovations that were new to the firm were introduced in the last three years and how many innovations that were new to the industry were introduced in the last three years (Cabigiosu and Campagnolo, 2019). Finally, authors can ask about the proportion of current sales consisting of new services/products introduced to the market for the first time by the firm and the proportion of current sales consisting of new or improved services/products previously produced by this firm or other firms (Mansury and Love, 2008). An example of innovation that is new to the industry comes from “gamification”, which represents a new business opportunity for KIBS firms that develop new services (product innovation) for those firms that are willing to improve their relationship with employees or clients (Robson et al., 2016). Gamification is a term used to identify the adoption of elements typical of games in different situations. In 2003, Nick Pelling was among the first game designer to found a new start-up, Conundra Ltd., to develop new client interfaces for vending machines, employing elements of games and able to increase transactions’ rapidity and fun. Following Kapp (2012), gamification is the use of game-based mechanics, aesthetics and game thinking to engage people, motivate action, promote learning and solve problems. The goal of gamification is to increase the engagement, stimulating people’s involvement and participation. Kapp emphasizes in particular the importance of gamification to motivating people by stimulating problem-solving actions, people’s curiosity and at the same time the use of emotional rewards. Gamification can be adopted when a company decides to transform consumers into prosumers but also when companies want to innovate the way in which their brand is perceived by consumers, making it part of their daily lives or creating new associations with it. An example is Coca-Cola, which used gamification for its Hong Kong advertising campaign, in which the user, after installing the Coca-Cola application, can shake the mobile phone as if it is a bottle to win instant prizes. Nike’s application uses gamification to pursue health and wellness goals to

Measuring innovation in KIBS

57

encourage people constantly to engage in physical activity, thanks to points and rankings. The gamification strategy proved to be successful, as it was able to create a synergy between the brand’s image and the sporting activity. Gamification is used also in business-to-business situations to increase employees’ engagement. In this context, gamification is much more than just adding a competitive element to work; it is about using a fun format to align employees’ focus with business goals and recognize and reward employees’ performance. As far as B2B is concerned, Officina1 has developed Playoff, a versatile gamification platform that includes software, apps and a website, which can be used by Officina to implement customized gamification projects for its clients. For example, this platform is used for client companies to promote employees’ engagement or by insurance companies that incorporate the software into clients’ cars to control their driving style. This versatility is the strength of the platform.

Differentness These two levels of innovation (sector vs. enterprise) make it possible to distinguish between innovative and imitating enterprises, between first movers opening new markets and followers entering the new market once the necessary skills and knowledge observed in the innovative enterprise have been internalized. While innovations that are new to the firm and new to the industry distinguish innovations according to their timing of entry (the Oslo Manual refers to the newness of a service or a product (OECD and Eurostat, 2018)), it is difficult to grasp the degree of innovativeness with respect to existing services and competences (differentness). New innovations for the sector are services that appear for the first time on the market but could be based largely on existing knowledge, technologies and processes. This is why some studies, using Oslo Manual-based innovation surveys, try to measure the originality of innovations in addition to the timing of their introduction (Therrien et al., 2011). The originality, or differentness, of innovation is a proxy for whether the firm developed an absolutely new or significantly improved product. This idea recalls the distinction between incremental and radical innovations, which captures the extent to which an innovation is different from the existing services. Incremental innovations involve the strengthening of the existing skills within the sector, while radical innovations indicate changes that demolish the existing skills (Abernathy and Clark, 1985). Incremental innovations, therefore, are characterized by a lower level of complexity and consist of improvements and adaptations of specific features of the existing offer. Radical innovations, on the other hand, are revolutionary and relevant, and are usually the result of strong investments in technology and resources that allow the company to change its skills and competencies radically. In designing and developing such an innovation, the company will simultaneously have to monitor a complex set of variables that guarantee the desired level of economic performance.

58

Innovation in KIBS

In particular, the quality of the project (which must satisfy the needs of customers and has to be translated correctly into service specifications), the cost of project activities (equal to the sum of all the resources used or sometimes involved in the project itself) and the development time (from the generation of the concept to the development of the project and to the launch of the service itself). The achievement of all these objectives is linked to the company’s ability to develop its own skills by acquiring new knowledge and recomposing this knowledge, combining and integrating them to develop the project in accordance with performance objectives. Overall, this literature highlights the need for a better-synthesized taxonomy embodying the two aspects of novelty, namely market based (newness) and originality based (differentness), to assess the performance implications of innovation. Using only the timing of entry would give important but only partial information: the originality of innovation is another important aspect, as it would play a role in the market acceptance of the new product. However, due to data limitations and difficulties in collecting reliable data in large surveys, most studies use only the market-based aspect of novelty, while a few others estimate the originality, or differentness, of the innovation. Some studies, using Oslo Manual-based innovation surveys, try to incorporate the aspect of originality proxied by whether the firm developed a new or a significantly improved product (the originality would be greater with a new product than with a significantly improved one). One of the more interesting studies, within the services sector, is by Martínez-Ros and Orfila-Sintes (2009). This study identifies industry radical innovations as any activities that were introduced into the functional areas, departments or services for the first time. Incremental innovations are identified through the same process; however, the activities identified are seen to be improvements undertaken within the functional areas, departments or services. The authors find that firms that introduced incremental innovations were likely to have introduced radical innovations and vice versa. Therrien et al. (2011) measure originality using a 5-point Likert scale ranging from “1” referring to slightly new services, to “5” for totally new services. Then, the authors aggregate innovators’ responses into three categories: totally new (the respondents indicated that their product was totally new, or “5”, on the Likert scale), highly new (“4” on the Likert scale) and not particularly new (the summation of Likert scale scores of “1”, “2” and “3”). The authors show that first movers derive more commercial sales from innovation and that firms that introduce a product with highly novel components, even if this product is already on the market, will derive more commercial sales from innovation. “Therefore, late followers (establishment-first) would have higher sales from innovation by introducing products with high original content” (ibid., p. 664). However, if the products are not novel enough, the late entrants will not derive higher sales from innovation. This literature highlights the need for a bettersynthesized taxonomy embodying the two aspects of novelty, namely market based (newness) and originality based (differentness), to appreciate better the performance implications of innovators. Using only the timing of introduction of innovation would give important but nonetheless only partial information.

Measuring innovation in KIBS

59

However, due to the difficulties that respondents face in evaluating multiple attributes of innovations, most studies use only the market-based aspect of novelty, while a few others estimate the originality of the innovation, and to date there is a limited number of papers that deal with the radical–incremental dichotomy in the service sector. Finally, we still need studies that combine the two dimensions, novelty and differentness, to analyse the impact of innovation on KIBS firms’ performance.

Note 1 Officina is a small Italian consulting and ICT firm: www.officina.cc.

References Abernathy, W.J. and Clark, K.B. 1985. Innovation: Mapping the winds of creative destruction. Research Policy, 14(1), 3–22. Abrahamson, R. and Rosenkopf, L. 1993. Institutional and competitive bandwagons: Using mathematical modeling as a tool to explore innovation diffusion. Academy of Management Review, 18, 487–517. Afuah, A. and Bahram, N. 1995. The hypercube of innovation. Research Policy, 24, 51–76. Amara, N., Landry, R. and Doloreux, D. 2009. Patterns of innovation in knowledgeintensive business services. Service Industry Journal, 29(4), 407–430. Bikhchandani, S., Hirshleifer, D. and Welch, I. 1998. Learning from the behavior of others: Conformity, fads, and informational cascades. Journal of Economic Perspectives, 12(3), 151–170. Cabigiosu, A. and Campagnolo, D. 2019. Innovation and growth in KIBS: The role of clients’ collaboration and service customization. Industry and Innovation, 26, 592–618. Chang, Y.-C. and Chen, M.-N. 2016. Service regime and innovation clusters: An empirical study from service firms in Taiwan. Research Policy, 45(9), 1845–1857. Chesbrough, H. 2003. The logic of open innovation: Managing intellectual property. California Management Review, 33–58. Chesbrough, H. 2011. Bringing open innovation to services. MIT Sloan Management Review, 52(2), 85–90. Damanpour, F. 1992. Organizational size and innovation. Organization Studies, 13(3), 375–402. Den Hertog, P., Van der Aa, W. and De Jong, M. W. 2010. Capabilities for managing service innovation: towards a conceptual framework. Journal of service Management, 21(4), 490–514. DiMaggio, P. and Powell, W.W. 1983. The iron cage revisited: Collective rationality and institutional isomorphism in organizational fields. American Sociological Review, 48(2), 147–160. Doloreux, D., Turkina, E. and Van Assche, A. 2018. Innovation type and external knowledge search strategies in KIBS: Evidence from Canada. Service Business, 1–22. Ferreras-Méndez, J.L., Fernández-Mesa, A. and Alegre, J. 2016. The relationship between knowledge search strategies and absorptive capacity: A deeper look. Technovation, 54, 48–61. Freel, M. 2006. Patterns of technological innovation in knowledge-intensive business services. Industry and Innovation, 13(3), 335–358.

60 Innovation in KIBS Hipp, C. and Grupp, H. 2005. Innovation in the service sector: The demand for servicespecific innovation measurement concepts and typologies. Research Policy, 34(4), 517–535. Howells, J., 2000. Innovation & Services: New Conceptual Frameworks. Centre for Research on Innovation and Competition, the University of Manchester. Kapp, K.M. 2012. The Gamification of Learning and Instruction: Game-Based Methods and Strategies for Training and Education. Pfeiffer, San Francisco. Katila, R. and G. Ahuja. 2002. Something old, something new: A longitudinal study of search behavior and new product introduction. Academy of Management Journal, 45(8), 1183–1194. Koch, A. and Strotmann, H. 2008. Absorptive capacity and innovation in the knowledgeintensive business service sector. Economics of Innovation and New Technology, 17(6), 511–531. Kotabe, M., Martin, X. and Domoto, H. 2003. Gaining from vertical partnerships: Knowledge transfer, relationship duration, and supplier performance improvement in the US and Japanese automotive industries. Strategic Management Journal, 24(4), 293–316. Laursen, K. and Salter, A. 2006. Open for innovation: The role of openness in explaining innovation performance among UK manufacturing firms. Strategic Management Journal, 27(2), 131–150. Leiponen, A. 2005. Organization of knowledge and innovation: The case of Finnish business services. Industry and Innovation, 12(2), 185–203. Lieberman, M.B. and Asaba, S. 2006. Why do firms imitate each other? Academy of Management Review, 31(2), 366–385. Love, J.H. and Mansury, M.A. 2007. External linkages, R&D and innovation performance in US business services. Industry and Innovation, 14(5), 477–496. Love, J.H., Roper, S. and Bryson, J.R. 2011. Openness, knowledge, innovation and growth in UK business services. Research Policy, 40(10), 1438–1452. Mansury, M.A. and Love, J.H. 2008. Innovation, productivity and growth in US business services: A firm-level analysis. Technovation, 28(1–2), 52–62. Martĺnez-Ros, E. and Orfila-Sintes, F. 2009. Innovation activity in the hotel industry. Technovation, 29(9), 632–641. Mina, A., Bascavusoglu-Moreau, E. and Hughes, A. 2014. Open service innovation and the firm’s search for external knowledge. Research Policy, 43(5), 853–866. Miotti, L. and Sachwald, F. 2003. Co-operative R&D: Why and with whom? An integrated framework of analysis. Research Policy, 32, 1481–1499. Miozzo, M., Desyllasb, D., Lee, H. and Miles, I. 2016. Innovation collaboration and appropriability by knowledge-intensive business services firms. Research Policy, 45(7), 1337–1351. Monteiro, F., Mol, M. and Birkinshaw, J. 2017. Ready to be open? Explaining the firm level barriers to benefiting from openness to external knowledge. Long Range Planning, 50(2), 282–295. Muller, E. and Zenker, A. 2001. Business services as actors of knowledge transformation: The role of KIBS in regional and national innovation systems. Research Policy, 30, 1501–1516. OECD/Eurostat. (2018), Oslo Manual 2018: Guidelines for Collecting, Reporting, and Using Data on Innovation. OECD: Paris. Powell, W. W., Koput, K. W. and Smith-Doerr, L. 1996. Interorganizational collaboration and the locus of innovation: Networks of learning in biotechnology. Administrative Science Quarterly, 116–145. Robson, K., Plangger, K., Kietzmann, J.H., McCarthy, I. and Pitt, L. 2016. Game on: Engaging customers and employees through gamification. Business Horizons, 59(1), 29–36.

Measuring innovation in KIBS

61

Rodríguez, A., Nieto, M.J. and Santamaría, L. 2018. International collaboration and innovation in professional and technological knowledge-intensive services. Industry and Innovation, 25(4), 408–431. Rosenkopf, L. and Nerkar, A. 2001. Beyond local search: Boundary spanning, exploration, and impact in the optical disk industry. Strategic Management Journal, 22(4), 287–306. Schnaars, S.P. 2002. Managing Imitation Strategies. The Free Press, New York. Shenkar, O. 2010. Copycats: How Smart Companies Use Imitation To Gain a Strategic Edge. Harvard Business Press. Sobrero, M. and Roberts, E.B. 2002. Strategic management of supplier–manufacturer relations in new product development. Research Policy, 31(1), 159–182. Stinchcombe, A.L. 1965. Organizations and social structure. In March, J.G. (Ed.) Handbook of Organizations. Rand-McNally, Chicago, pp. 153–193. Tether, B.S. 2005. Do services innovate (differently)? Insights from the European Innobarometer survey. Industry and Innovation, 12(2), 153–184. Therrien, P., Doloreux, D. and Chamberlin, T. 2011. Innovation novelty and (commercial) performance in the service sector: A Canadian firm-level analysis. Technovation, 31(12), 655–665. Thompson, J.D. 1967Organizations in Action. McGraw-Hill, New York. Tsai, K.U. and Hsieh, M.U. 2009. How different types of partners influence innovative product sales: Does technological capacity matter? Journal of Business Research, 62(12), 1321–1328. Turkina, E. and Van Assche, A. 2018. Global connectedness and local innovation in industrial clusters. Journal of International Business Studies, 49, 706–728. Von Hippel, E. 1988. The Sources of Innovation. MIT Press. Young, A. 1996. Measuring R&D in the Services. STI working paper. OECD.

5

The specific traits of innovation in KIBS

KIBS firms are business-to-business service firms that often design their services to satisfy specific clients’ needs and for which clients become co-producers of innovative solutions. Along with clients, other partners often support KIBS firms’ innovation processes. This chapter describes the interplay between service customization and clients’ collaboration and the way in which KIBS firms spur innovation processes in clients’ firms as well as the relevance of the broader network of KIBS firms’ partners in supporting innovation in KIBS.

Customization and client collaboration The collaborative innovation literature widely debates the relevance of collaborating with customers to improve firms’ innovation performance. Working with clients helps KIBS firms to identify new business opportunities and new trends and design innovative service solutions quickly. Studies published over a long period emphasize that understanding clients’ needs improves firms’ performance and new product success (Sethi, Smith and Park, 2001). Li and Calantone (1998) and Ritala et al. (2015) find that knowledge sharing with clients has a positive impact on firms’ innovation performance. Lettl, Herstatt and Gemuenden (2006), Sethi et al. (2001) and Tether (2002) show that buyer–supplier collaboration is more frequent and knowledge of clients’ needs is more beneficial when firms pursue higher levels of innovativeness. Nieto and Santamaría’s (2007) results show that buyer–supplier collaboration is beneficial for both radical and incremental innovation. Love and Mansury (2007) focus on KIBS firms and find that clients’ participation in development activities positively affects product innovation but not organizational and technological innovation. KIBS firms need an in-depth understanding of their clients’ organization, business and strategy to adapt their services to their clients’ requirements. Therefore, KIBS are often the outcome of a joint effort by the service provider and the client (den Hertog, 2000) via intensive knowledge sharing between the two parties. The outcome of this process is mostly a customized service (Bettencourt et al., 2002; Landry, Amara and Doloreux, 2012).

The specific traits of innovation in KIBS 63 KIBS firms enter the organizational and operational processes of their clients deeply when providing their services; therefore, it is essential that they are able to interpret and adapt to specific clients’ requirements. Indeed, clients possess much of the knowledge and competence (e.g. their business/industry features, desired service attributes/goals, available technologies and routines) that a KIBS firm needs to design and deliver the service effectively (Bettencourt et al., 2002; Sundbo, 2002). Thus, client–supplier collaboration in service development and production emerges and usually takes place via intense knowledge sharing between the client and the KIBS firm. In KIBS, the service development process is strongly oriented toward collaboration with clients, as customers have much of the knowledge (which may be either tacit or codified) needed to deliver service solutions successfully. Customers help the service provider in setting services’ features and performance parameters according to their needs, they know how the service has to interact with their internal processes and resources, and finally they belong to different sectors and can provide valuable information to help the KIBS firm in providing ad hoc solutions. For KIBS firms, it is important to understand customers’ needs, their inner processes and procedures and their competitive environment, which together can affect the service attributes. These data, information and knowledge are the inputs that KIBS firms need to design and develop their services effectively and deliver customized service solutions able to target each client’s need and solve specific problems (Bettencourt et al., 2002; Strambach, 2001). Research points out that the innovation process in KIBS is often triggered by clients’ requirements (Hipp and Grupp, 2005; Larsen, 2001; Päällysaho, 2008; Tether and Metcalfe, 2004) and takes place through recursive loops of client–supplier interactions of knowledge and information sharing (den Hertog, van der Aa and de Jong, 2010). Several authors point out that this process leads to service customization, which is considered as the constitutive element of KIBS innovation, and even take a step further by arguing that service customization goes hand in hand with service innovation (Hipp, Tether and Miles, 2000). KIBS firms are problem solvers that are asked to develop customized solutions to answer clients’ needs. KIBS firms co-develop their services with clients because they must understand clients’ needs to define the content and characteristics of their services, which turn out to be customized and (often) innovative. The customization/collaboration loop nurtures innovation in KIBS firms, which rely on customization and clients’ collaboration to develop ad hoc new service solutions and, at the same time, reduce the development risks associated with market uncertainty (Campagnolo and Cabigiosu, 2015; den Hertog, 2000; Greer and Lei, 2012). The customization/collaboration loop is also linked with stronger relationships with clients and customer lock-in (Vandermerwe, 2000). The analysis of the studies listed suggests overall that client collaboration’s influences innovation performance and KIBS firms need to learn how to manage the co-production of service with customers to increase the likelihood of a

64

Innovation in KIBS

project’s success and to nurture their own learning potential and its effectiveness. Innovation capabilities are crucial for KIBS firms to satisfy clients’ need and for their competitive advantage. Furthermore, the ability to co-produce services with clients generate specific efficiencies by reducing KIBS firms’ time to market. Creating effective customer relationships for the co-production of services therefore becomes a crucial capability to establish a long-lasting competitive advantage, as underlined by various researchers (Bettencourt et al., 2002). The main traits that characterize effective client co-production concern the communication openness, the willingness to share problem-solving activities and a high level of tolerance, accommodation (i.e. the extent to which the client demonstrates willingness to accommodate the desires, approach and expert judgement of the service provider), advocacy (i.e. the extent to which the client acts as a vocal advocate for the project), personal dedication (i.e. the extent to which the client’s behaviours reflect a sense of personal obligation for the project success) and active involvement (i.e. the extent to which the client directly monitors the project progress) in the various design, production and delivery processes (Bettencourt et al., 2002). Open communication is the extent to which the client shares pertinent information for project success with the service provider. Open and frequent communications prevent buyer–supplier relationship failure and require ad hoc coordination mechanisms: customized service development is based on data and information gathering from clients about their needs, their production and distribution processes, and their technological and economic environments. During this phase, clients are expected to communicate openly with the service provider about their expectations, goals and priorities regarding the service. Openness is critical in the first steps of the project, when the nature of the problem has yet to be defined and the available solutions are different. In this situation, only the customer is in the position to define the key information. The client can contribute to the project by playing an active role in identifying any obstacle or problem and by providing real-time feedback. A client adopting a passive role during service design and delivery can compromise the relationship and its output. Customers and KIBS are also required to be flexible during the co-development, which may require compromises, openness to collaboration and unexpected solutions. Particularly, it is well known that problem solving can be a long process with unexpected outcomes that require flexibility and availability: clients are expected to respond to smaller problems with patience and promote the development of open relationships with the service provider. Clients that co-produce the service are involved in project governance to ensure that it achieves the planned goals and act as an internal reviewer and consultant. In this respect, clients become partners of KIBS companies, and their resources and competences are crucial to the success of the project. Although several customer employees can be involved in the project, it is the project leader’s commitment that is essential to achieve an effective partnership with KIBS.

The specific traits of innovation in KIBS 65 In this context, the beginning of a relationship is critical to ensure a future for the relationship itself. In fact, at this stage, the customer is more inclined to define contractual and behavioural standards and expectations. However, opinions will also soon be built about skills, motivation and needs, and these opinions, once formed, will hardly change. It is hence crucial, at this stage, to identify the relationship development opportunities, expectations, content of the relationship and importance of customer engagement. Overall, “co-production” mainly refers to interactions and interpersonal relationships between the KIBS firm and company employees. To be effective, they must be based on shared and recognized goals, trust and collaboration. Keeping training and information sessions at this stage of interaction with the client helps to clarify each other’s expectations and create a dialogue that is open to information transfer. At this stage, individuals can then socialize and start exchanging tacit knowledge and coding. These interactions also allow increased interpersonal sharing and mutual understanding, which are fundamental elements for creating a trustful relationship. Involving the customer in project planning is therefore important to facilitate cooperation, increase personal motivation and reach the project’s ultimate goal. In the case of companies that rely heavily on co-production, such as KIBS firms, acquired industry experience is not enough to ensure a competitive advantage: they are actually required to develop new projects to respond to specific customer issues. In such cases, KIBS firms cannot only have technical expertise in the field; they also need to develop soft skills, such as relational skills, to foster mutual trust and teamwork, and to engage the client actively in the process of problem solving. For this reason, KIBS firms need dedicated human resource management practices and performance measurement systems to reward behaviours that favour the creation of cooperative relationships as well as the implementation of indicators that allow the evaluation of the customer’s willingness to collaborate. As far as the latter is concerned, it is not always easy to evaluate the impact of customer relationships on projects’ performance. This is because continuous monitoring can lead to a decrease in the customer’s willingness to cooperate, as the KIBS firm could be perceived as too invasive. For this reason, the assessment should be based primarily on the self-assessment made by the customer as well as on the socialization and adaptation efforts in terms of shared norms and values. This co-production management model is relevant to a wide variety of KIBS businesses, especially for those offering relatively complex, unstructured and customized service solutions. Effective co-production in these cases can increase the likelihood of success and customer satisfaction and is a competitive opportunity for KIBS businesses. The relevance of co-production may vary depending on several factors, including the project’s innovativeness and the customer’s expertise. KIBS clients can be divided into two main categories: customers that rely on KIBS firms for their services but that have no specific expertise in this regard, and experienced customers with which KIBS exchange both information and knowledge. Expert clients have developed specific competences in service

66

Innovation in KIBS

provision either because they have an in-house production capacity for the service, as in the case of multinational firms that have central service departments but also rely on local KIBS firms for service delivery on a regional basis, or because, when they buy external services from KIBS firms, they systematically store the knowledge and competences generated by this interaction. Finally, expert clients had specific competences when they initially developed the service in-house and only recently outsourced the service. Expert clients are of particular relevance for KIBS firms in that they often share their expertise and knowledge with KIBS firms, which have the opportunity to learn and develop new procedures. Hence, these interactions generate new competences and knowledge that become part of the KIBS firms’ offering. Expert clients are the main source of innovation for KIBS for multiple reasons. First, expert clients often ask for more advanced service solutions that push KIBS firms to invest in innovation. Second, expert clients, during the interaction with KIBS firms, share their own knowledge and expertise. In this context, KIBS firms need effective coordination mechanisms to acquire both explicit and tacit knowledge from expert clients and should be able to motivate clients to participate in the design of the service (Cabigiosu et al., 2015). An example of an expert client is Unox, a large Italian manufacturing company specialized in the production of electric ovens. Over the years, the rapid growth of Unox increased the complexity that the firm had to manage for the supply of multiple components and the production of new product lines. For this reason, the company decided to invest in the lean principles and methods, which are helpful in introducing innovative solutions and, at the same time, simplifying the existing processes. To implement these principles, Unox relied on lean consultants and hired young graduates with specific skills who were able to adapt the lean method to the needs of Unox. After some years, Unox decided to externalize the lean management consulting to Auxiell, which was founded as a spin-off of Unox. Today, Auxiell is a young and dynamic Italian lean management consulting company that has quickly gained experience in the application of lean in various Italian companies. The collaboration between Unox and Auxiell continues, and Unox can be considered an expert client of Auxiell. For example, in 2007, Unox decided to extend lean techniques from the production area to the offices and assigned this task to Auxiell. In 2015, Auxiell redesigned the work flow of Unox’s new product. This project led to a fundamental revision of the information flow in many company areas, a new method of monitoring and formalizing the results of laboratory tests and the revision of the line layout. In addition, Auxiell relies on Unox to show its working methods and its results to potential customers and stakeholders. In this sense, Auxiell considers Unox as a kind of showroom to show managers and students how to apply lean practices and their potential results (Cabigiosu, 2016). Another example is Nestlé Purina, which can be considered as an expert client of Cablog. Cablog is a big TPL company operating in Italy and specializing in the warehousing and distribution of packaged and canned foods and beverages.

The specific traits of innovation in KIBS 67 Cablog’s most important customers are manufacturers such as Nestlé Purina (pet food) and Pepsi Cola (soft drinks). Although Cablog shares large amounts of information with its clients, knowledge sharing is limited to relationships involving the development of new services with competent clients. In this respect, Nestlé Purina had a central role in Cablog’s know-how, because it anticipated requirements that subsequently became standard for the industry. This happened in 2000, when it asked for an advanced traceability system that was new to Cablog. Nestlé Purina had engineers who had already started implementing the project with other TPLs in other countries, and they sent the software specifications and other procedures to implement the track-and-trace service to Cablog. Furthermore, they worked together to adapt and complete the software and implement the traceability system. Similarly, Cablog worked with Nestlé Purina to develop accurate pest prevention practices that are now part of the range of services that Cablog can offer to the rest of its customers (Cabigiosu et al., 2015).

The role and contribution of KIBS firms in the innovation process of their clients The previous paragraphs explain the relevance of buyer–supplier collaboration in KIBS and mainly emphasize the consequences of such a tight relationship at the service level, by focusing on service customization in KIBS, and at the KIBS firm level, by emphasizing that KIBS firms need to involve clients in the development process of the service to maximize their adherence to clients’ needs and performance. In this section, I focus on clients and on how their relationship with KIBS firms can support their innovation processes. Collaborative product innovation strategies enable firms to modify or develop new products continuously to meet changing customer needs and preferences. In this context, firms’ innovation mode is becoming more and more open to external partners and in turn associated with increasing levels of collaboration and outsourcing. Within this reach and complex realm, the literature identifies a set of actors who are termed as “intermediaries” and who perform a variety of tasks within the innovation process of client firms. The role of intermediaries and the process of intermediation are also explored in relation to the specific role of KIBS firms (Bettencourt et al., 2002; Miles et al., 1995, 2000; Wood, 2002). The relevance of KIBS firms in supporting innovation in manufacturing firms and, in turn, in wide geographical areas, such as in regional innovative systems, in which KIBS act as “bridges for innovation” to other manufacturing and service firms, has long been recognized (Muller and Zenker, 2001). KIBS firms often have close and continuous interactions with their clients and can perform crucial functions in supporting innovative change within their client companies (Howells, 2006; Nieto and Santamaría, 2010). Partnerships between manufacturers and KIBS firms for the development of new products generally offer multiple advantages, such as fewer investments, lower risks, greater flexibility, knowledge specialization and sharing. Partnerships with

68

Innovation in KIBS

KIBS firms may be valuable in managing growth when they permit partnering firms to focus on their unique resources and core competences while they gain access to those services that improve innovative products’ positioning, design, communication and delivery, such as market research, consultancy, R&D, marketing and logistics services. These alliances also reduce risks by spreading the research and development costs. For example, Bustinza et al. (2019) describe the case of truck manufacturers that access crucial enabling technologies through partnerships with telematics service providers. Firms’ choice of knowledge sourcing is a critical determinant of superior innovation performance. By collaborating with KIBS firms, manufacturing firms can experiment with service provision without fully internalizing the risks and costs of internal service implementation. KIBS firms have expertise to support effective and efficient innovation processes in clients’ firms and can thus act as “bridges for innovation” and play an important role in product–service innovation, economic performance and firm growth (Amara, Landry and Doloreux, 2009; Muller and Zenker, 2001). The analysis of the role of KIBS in innovation processes brings into focus the ways in which knowledge is produced and used by KIBS clients. The production of services is often the result of a joint effort of the service provider and client. In this process of co-production, the quality of the resulting service or product largely depends on KIBS firms’ ability to adapt and transfer their scientific and technological knowledge to the specific requirements and problems of their clients. KIBS firms operate a fusion between technical knowledge and more tacit knowledge, located within the daily practices of the firms and sectors that they serve. The result of client–supplier interaction is that feedback from clients can shape innovations in service firms just as much as service firms can influence their clients’ innovation. Gradually, the vision of KIBS in the literature has evolved from seeing KIBS as mere facilitators of innovation in manufacturing firms to viewing them as co-producers of innovation with manufacturing firms. In particular, KIBS firms can perform multiple functions as co-producers of innovation (den Hertog, 2000). KIBS can act as brokers by putting clients in contact with different sources of services and resources. KIBS help clients to navigate through the external landscape of possible partners and solutions. This is a crucial function in the Industry 4.0 paradigm. Often, manufacturing firms, especially small and medium firms, equally need the resources to make investments in digital technologies and the competences about how to select them, the incentives available and how to use them, and where to find all this information and partners that are able to support their adoption process. In this respect, KIBS firms provide complementary services, such as consulting and human resource services, and create bridges between service and manufacturing firms. KIBS firms also help users to articulate and define their needs (develop diagnosis and problem clarification), prioritize their problems, define a strategy and a coherent action plan and create a benchmark of alternative solutions. Finally KIBS firms help their clients in developing innovative solutions from their design to the

The specific traits of innovation in KIBS 69 final market delivery. In this respect, KIBS firms can play different roles in supporting innovation in client firms (Miles et al., 1995). Den Hertog (2000) suggests three roles for KIBS companies in supporting corporate clients’ innovation. First, KIBS firms can be facilitators when they support a client company in its internal innovation process. Innovation does not originate from the KIBS company, and it is not transferred from it to the client. Clients initiate and promote their own innovation processes and find in KIBS the external support and complementary skills that they need. One example is KIBS firms’ marketing and market research services, which provide their clients with the information input that they need to start the phase of generating and evaluating a new product concept. Second, KIBS can be vehicles of innovation: a KIBS company is a carrier of innovation if its role is to transfer existing innovations from one client to another, even if the innovation in question does not originate from the same KIBS company. In this case, KIBS firms learn from their customers and suppliers, innovate their processes and products and disseminate them in subsequent supply relationships. These innovations, assimilated by the market, are referred to in the literature as new to the firm: they are new to the KIBS firm and its customers but not absolutely new to the market. The significant contribution of KIBS firms is related primarily to their ability to codify into new services/processes what their customers and suppliers have taken, and secondly to their ability to disseminate these innovations to their customers. Finally, KIBS can be a source of innovation: a KIBS company is a source of innovation if it develops a new service or process that is original to the sector or new to the industry. Often it is the direct contact with customers and the ability to capture unmet needs (or to find a new way of satisfying them) that is the real driver of innovation in KIBS. In this case, KIBS firms and clients often co-produce the new service. The new services/processes are then (partially) replicated by KIBS firms in more supply relationships, favouring the diffusion of innovation. For example, in the 1990s, a new service offered by t-KIBS was the development of a website for the client company, while, after 2000, KIBS started to design applications dedicated to individual customers. When KIBS firms act as a carrier and source of innovation, they play an important role in the creation, transfer and diffusion of knowledge and high value-adding services for partner organizations, and they facilitate learning and the improvement of innovation outcomes. These in turn have remarkable consequences as far as the role of KIBS in the development of regions is concerned. This is especially true when considering the high level of geographical proximity between KIBS and manufacturing. These arguments clarify the importance of public policies supporting incentives for KIBS’ allocation and development: since manufacturing firms and especially R&D-intensive industries require advanced and knowledge intensive services, policy makers should try to boost territories and local economies by attracting knowledge workers and KIBS firms (Florida, 2007) and by supporting industrial clusters combining product and service sectors. While multiple studies

70

Innovation in KIBS

exist that describe successful partnerships between KIBS and manufacturing firms, we still need studies that employ a processual view of the antecedents of these relationships and of how these partnerships are formed and obstacles overcome.

Sharing knowledge with clients When KIBS firms support clients’ innovation processes, they need to rely on tight coordination mechanisms to understand the clients’ needs and how they manage their own business and processes to design services that can effectively support and be integrated into the clients’ offering. In this setting, innovation at the client level is the output of a cycle that also includes the interaction with KIBS firms and the integration of different bodies of knowledge. Knowledge involved in innovative activities can be tacit or codified and can be generated within the client firm or acquired externally. Explicit knowledge, which can be represented by data, scientific formulas or technical specifications, or can be incorporated into company tools and specific manual actions, is relatively easy to transfer and store. On the contrary, tacit knowledge, made up of ideas, experiences and facts, is personal, subjective and experiential and therefore difficult to transfer. Tacit knowledge cannot be codified and can only be understood and acquired through practice and experience. During innovation activities, both KIBS firms and their clients rely on a combination of explicit and tacit knowledge. It is this second type of knowledge that requires specific efforts to be shared and used successfully in supporting innovative activities. In their studies, Nonaka and Takeuchi (1995) identify four models of knowledge transformation. Socializing with clients facilitates mutual understanding and thus also the exchange of knowledge in the form of stories and examples of previous experiences. Socialization allows tacit knowledge to be made more explicit and knowledge more easily communicated and circulated. In this form, knowledge from different sources can be used and combined for the success of the innovation project. Finally, this knowledge transformation and creation process enriches firms’ knowledge bases, which absorb and internalize the new knowledge generated during the project. The model of Nonaka and Takeuchi is well suited to describing those forms of knowledge transformation that involve KIBS firms and customers and let us guess why these mixtures are a fundamental lever in the process of knowledge creation and dissemination nurtured by KIBS firms. Several case studies on the interaction between KIBS companies and their clients show that tacit knowledge flows are just as important as explicit and codified forms of knowledge exchange to promote the cross-fertilization of knowledge between service and manufacturing companies (Miles et al., 1995). Attention should also be paid to the dynamic nature of the knowledge transfer process. The constant activities of redefinition, linking, exchange, remodelling and enrichment of the various forms of knowledge are those that KIBS typically perform when they interact with their customers. KIBS companies can trigger and strengthen knowledge conversion processes in clients. When a client hires a KIBS company, new project teams are created and employees are forced to

The specific traits of innovation in KIBS 71 interact, to make tacit knowledge explicit and to think about new combinations of knowledge, and their mental models are thus questioned, generating, through internalization, new tacit knowledge that KIBS and clients can share through socialization/integration (den Hertog, 2000). Typical knowledge generation processes in KIBS companies include the integration of external knowledge, the acquisition of knowledge related to a specific problem and the processing of coded knowledge corresponding to a specific need of the client company. The contribution of customers to the process of designing and delivering services is integrated into the service itself and determines its success. In summary, by exploring the links between KIBS companies and their customers, three main stages are distinguished in the process of co-production and dissemination of knowledge by KIBS. The first is the acquisition of knowledge, tacit or not, by KIBS firms on the needs of the customer and any solutions that are already known to the customer regarding how to meet this need. In this phase, the interaction or socialization is crucial to acquire any tacit knowledge alongside the more easily transferable kind. The acquisition of new knowledge takes place in contact with client companies. This generation of knowledge based on interactions consists mainly of learning how to solve problems on behalf of customers. In this phase, proximity to the customer facilitates self-fulfilment. The second stage is the combination of the knowledge of the KIBS firm with that of the customer: in this stage, the KIBS firm learns from the customer, updates and modifies its knowledge base and develops solutions adapted to the customer’s needs on the basis of the information and knowledge acquired by the customer and on the basis of its specific skills. The second point is the combination of the knowledge acquired previously. The combination process takes place within the enterprise: knowledge from customer interactions is combined with existing knowledge. Finally, the actual provision of the service makes it possible to transfer the competencies incorporated into the KIBS to corporate customers. The greater their level of explanation and codification, the more easily these competencies and knowledge incorporated into the service will be used and assimilated by the customer. The application of this knowledge in the form of new or improved services constitutes a partial transfer of knowledge from the company to its customers. KIBS companies can therefore stimulate and support knowledge creation, dissemination and in turn innovation processes, making clients capable of optimally exploiting their own knowledge base and resources (Muller and Zenker, 2001; Strambach, 2001).

Open innovation in KIBS KIBS firms often find the primary source of innovation within their internal human resources. KIBS firms may also have an R&D area, especially if they are larger. However, innovation, as noted earlier, cannot be seen as an internal

72

Innovation in KIBS

matter for a KIBS company only, since the relations that the company manages with the external environment can also play a very important role. In particular, relationships with clients and suppliers are crucial in triggering effective and efficient innovation processes. Nowadays, firms rely on a rich network of partners, which often include clients, universities or consultants, to explore the external environment and improve their offer. External partners help firms in understanding the existing technologies, products and processes and assist in their search for opportunities to achieve more radical innovation and to exploit external knowledge sources with the aim of developing incremental innovations (Chesbrough, 2011; Gulati, Nohria and Zaheer, 2000; Kale and Singh, 2007). Firms’ competitive advantage and survival are more and more related to their ability to innovate by monitoring the external landscape and identifying those innovative technologies and product attributes that are able to increase clients’ satisfaction. Firms are required to understand new clients’ needs and develop innovative products coherently. Hence, to increase innovations’ adherence to clients’ needs, firms, especially in business-to-business environments, often increase clients’ involvement in NPD activities: clients’ embeddedness in firms’ innovation activities plays a crucial role in their willingness to innovate in their products, especially when firms introduce incremental innovations that increase products’ fit to clients’ needs (Bonner and Walker, 2004). At the same time, clients’ embeddedness has a dark side. Too high a level of embeddedness reduces firms’ knowledge heterogeneity and hence their problemsolving ability in product innovation. In addition, embeddedness may be dysfunctional when firms fear clients’ opportunistic behaviour. The dark side of clients’ embeddedness may hinder firms’ ability to adapt their offer effectively to the market needs. Only a few studies investigate how to cope with this dark side, examining the management of the relationships with clients (Noordhoff et al., 2011) and the nature of the knowledge that they hold (Bonner and Walker, 2004). In this context, if KIBS firms have a broader network of partners, these can increase their ability to draw knowledge and expertise from a wider range of external sources. Innovators rarely innovate alone. Firms are spurred by the interaction with lead users, suppliers and a range of institutions within the innovation system. There is evidence that suggests that firms’ openness to their external environment can improve their ability to identify new opportunities, even when the most relevant external source is that of clients (Laursen and Salter, 2006). The specific environment of the KIBS company thus becomes the place from which to draw the knowledge needed to fuel innovation. The ability to interface with the specific environment and to establish an osmosis and exchange relationship with its stakeholders can increase KIBS firms’ ability first to generate and then to appropriate innovation rents. Moreover, these relationships can be useful to stimulate creativity, reduce risks, accelerate or develop the quality of innovations and increase their diffusion (Love and Mansury, 2007). KIBS firms cooperate with competitors, suppliers or research centres in the form of strategic alliances and joint ventures (Hipp et al., 2000). Upstream,

The specific traits of innovation in KIBS 73 relations with suppliers may be either informal or structured but are generally aimed at the effective and efficient acquisition of new process technologies. An example is ICT companies, but more generally we find consulting companies, especially if the company is considering the idea of moving towards completely new areas. Expert advice can play a significant role for KIBS companies, the projects of which may require resources and expertise that do not exist within the company itself. The use of experts is an obvious solution to this problem, allowing the supply of knowledge intensive services to be increased in a short period of time. In general, therefore, the sharing of experience and knowledge within KIBS and between KIBS is essential to ensure effective and efficient innovation processes. Moreover, suppliers and consultants are often able to help KIBS to adopt incremental and modular innovation logics and to refine and differentiate the services offered to open new business opportunities. Finally, many KIBS firms communicate with their customers but know much less about the end customers of the product/service on which they are working. Consultants and external suppliers can help KIBS firms to understand the end market and its evolution better and therefore to predict when and how to update its offer. Part of the literature on service innovation emphasizes the role played by suppliers and sees innovation in KIBS firms as being determined by the introduction of new technologies acquired from outside (Therrien et al., 2011). Service companies therefore appear to be dependent on suppliers for innovative inputs, which are transformed, to varying degrees, into more or less innovative service offerings. KIBS providers offer them new technologies to improve their service delivery, such as new ICT technologies. Recent studies identify different innovative models that show that KIBS networks are not necessarily dominated by suppliers from a technology push perspective and in which different actors are more or less relevant (den Hertog, 2000). These networks can be characterized alternatively by the more prominent role of suppliers of multiple inputs (technologies but also competences and capital), customers (client-led innovation), competitors and other KIBS firms. Different models and innovative networks can also coexist in the same service company, which can collaborate from time to time with one or more of these actors and be more or less a protagonist of the (open) innovation process. The overall image that results is that of KIBS companies that are open to collaborations aimed at improving and expanding their activities. These companies do not seem to suffer from the “not invented here” syndrome, which instead affects many companies belonging to other sectors that are struggling to open up to an external network of collaborations to manage new product development activities. Nevertheless, understanding how openness affects innovation in KIBS still requires considerable work and theorizing efforts (Laursen and Salter, 2006). The first group of studies finds that KIBS that develop product innovations seem to be more likely to opt for high degrees of external partnering and vice versa. Amara and Landry (2005) find that firms that introduce innovations with a greater degree of novelty are more likely to use a wider range of information

74

Innovation in KIBS

sources to develop or improve their products. Hipp et al. (2015) and Mina, Bascavusoglu-Moreau and Hughes (2014) suggest that product innovation is driven by collaborative efforts to develop new services through the integration of resources and know-how exchanges. Leiponen (2005) and Leiponen and Helfat (2010) show that the breadth of knowledge sourcing is an important determinant of service innovation. Freel (2006) finds evidence of the importance of customers’ and suppliers’ cooperation to innovation in p-KIBS, while the employment of highly qualified staff is significantly associated with innovativeness in t-KIBS firms. However, the second group of studies suggests that we still need to understand how different partners and knowledge sources contribute to innovation in KIBS. Rodriguez, Doloreux and Shearmur (2016) examine the knowledge-sourcing strategies of Spanish KIBS and identify four strategies. KIBS firms can be: a) independent innovators when they mainly rely on internal R&D and have few external interactions; b) Barras-type innovators, which innovate as a consequence of introducing new technologies; c) balanced innovators or firms that rely on a variety of internal and external resources to innovate; or d) cooperative innovators when they engage in innovation partnerships to innovate. Interestingly, Rodriguez et al. (2016) find that the degree of openness of KIBS firms’ strategies is not associated with a higher or lower propensity to innovate. Rodriguez, Doloreux and Shearmur (2017) show that different sources affect new innovations to the firm and new innovations to the industry diversely. Trigo and Vence (2012) also investigate the scope and patterns of knowledge searching in Spanish service firms and find a significant relationship between cooperative behaviours and innovation. Furthermore, product innovation is linked to the techno-scientific flow of innovation, process innovation is linked to collaboration with clients and organizational innovation is associated with lonely innovators. Finally, recent studies find substantial differences between the knowledge bases and sources of KIBS sub-sectors (Mina et al., 2014; Pina and Tether, 2016). Rodriguez et al. (2017) find that, for t-KIBS, knowledge sourcing and cooperation for innovation is strongly connected to new-to-market innovation. For p-KIBS, only knowledge from general sources (i.e. conferences, trade fairs and exhibitions, scientific journals and technical publications, professional and industry associations) is associated with newto-market innovation and market sources (suppliers, clients, competitors and commercial labs) with new-to-firm innovation. The results also suggest that t-KIBS’ innovativeness is more strongly associated with market sources (suppliers, clients, competitors and commercial labs) and with the unspecified choice of cooperating for innovation and that p-KIBS’ innovativeness relates specifically to a variety of general information sources (i.e. external sources, such as conferences, trade fairs and exhibitions, scientific professional and industry associations). Theories explaining these results are still lacking, and, while the available empirical evidence is converging in emphasizing the relevance of clients to

The specific traits of innovation in KIBS 75 the development of new services, we still need studies to grasp the relative role of clients and other partners and their complementarities in explaining KIBS firms’ innovativeness and that of specific categories of KIBS, namely t-KIBS and p-KIBS.

References Amara, N. and Landry, R. 2005. Sources of information as determinants of novelty of innovation in manufacturing firms: Evidence from the 1999 statistics Canada innovation survey. Technovation, 25(3), 245–259. Amara, N., Landry, R. and Doloreux, D. 2009. Patterns of innovation in knowledgeintensive business services. Service Industries Journal, 29(4), 407–430. Bettencourt, L.A., Ostrom, A., Brown, S.W. and Roundtree, R. 2002. Client co-production in knowledge-intensive business services. California Management Review, 44(4), 100–128. Bonner, J.M. and Walker Jr, O.C. 2004. Selecting influential business‐to‐business customers in new product development: Relational embeddedness and knowledge heterogeneity considerations. Journal of Product Innovation Management, 21(3), 155–169. Bustinza, O.F., Gomes, E., Vendrell‐Herrero, F. and Baines, T. 2019. Product–service innovation and performance: The role of collaborative partnerships and R&D intensity. R&D Management, 49(1), 33–45. Cabigiosu, A. 2016. L’innovazione e la progettazione nei servizi knowledge-intensive. Giapichelli, Torino. Cabigiosu, A., Campagnolo, D., Furlan, N. and Costa, G. 2015. Modularity in KIBS: The case of third-party logistics service providers. Industry and Innovation, 22(2), 126–146. Campagnolo, D. and Cabigiosu, A. 2015. Innovation, service types, and performance in knowledge intensive business services. In: Agarwal, R., Selen, W., Ross, G. and Green, R. (Eds.) The Handbook of Service Innovation. Springer, London, pp. 109–121. Chesbrough, H.W. 2011. Bringing open innovation to services. MIT Sloan Management Review, 52(2), 85. Den Hertog, P.D. 2000. Knowledge-intensive business services as co-producers of innovation. International Journal of Innovation Management, 4, 491–528. Den Hertog, P., Van der Aa, W. and De Jong, M.W. 2010. Capabilities for managing service innovation: Towards a conceptual framework. Journal of Service Management, 21, 490–514. Florida, R. 2007. The Flight of the Creative Class: The New Global Competition for Talent. HarperCollins Publishers, New York. Freel, M. 2006. Patterns of technological innovation in knowledge‐intensive business services. Industry and Innovation, 13(3), 335–358. Greer, C. R., and Lei, D. 2012. Collaborative innovation with customers: A review of the literature and suggestions for future research. International Journal of Management Reviews, 14(1), 63–84. Gulati, R., Nohria, N. and Zaheer, A. 2000. Strategic networks. Strategic Management Journal, 21, 203–215. Hipp, C. and Grupp, H. 2005. Innovation in the service sector: The demand for servicespecific innovation measurement concepts and typologies. Research Policy, 34(4), 517–535. Hipp, C., Tether, B. and Miles, I. 2000. The incidence and effects of innovation in services: Evidence from Germany. International Journal of Innovation Management, 4(4), 417–453. Hipp, C., Gallego, J. and Rubalcaba, L. 2015. Shaping innovation in European knowledge-intensive business services. Service Business, 9(1), 41–55.

76 Innovation in KIBS Howells, J. (2006). Intermediation and the role of intermediaries in innovation. Research Policy, 35(5), 715–728. Kale, P. and Singh, H. 2007. Building firm capabilities through learning: The role of the alliance learning process in alliance capability and firm‐level alliance success. Strategic Management Journal, 28(10), 981–1000. Landry, R., Amara, N. and Doloreux, D. 2012. Knowledge exchange strategies between KIBS firms and their clients. Service Industries Journal, 3, 291–320. Larsen, J.N. 2001. Knowledge, human resources and social practice: The knowledgeintensive business service firm as a distributed knowledge system. Service Industries Journal, 21(1), 81–102. Laursen, K., and Salter, A. 2006. Open for innovation: The role of openness in explaining innovation performance among UK manufacturing firms. Strategic Management Journal, 27(2), 131–150. Leiponen, A., 2005. Organization of knowledge and innovation: The case of Finnish business services. Industry and Innovation, 12(2), 185–203. Leiponen, A. and Helfat, C.E. 2010. Innovation objectives, knowledge sources, and the benefits of breadth. Strategic Management Journal, 31(2), 224–236. Lettl, C., Herstatt, C. and Gemuenden, H.G. 2006. Users’ contributions to radical innovation: Evidence from four cases in the field of medical equipment technology. R&D Management, 36, 251–272. Li, T. and Calantone, R.J. 1998. The impact of market knowledge competence on new product advantage: Conceptualization and empirical examination. Journal of Marketing, 62, 13–29. Love, J.H. and Mansury, M.A. 2007. External linkages, R&D and innovation performance in US business services. Industry and Innovation, 14(5), 477–496. Miles, I., Andersen, B., Boden, M. and Howells, J. 2000. Service production and intellectual property. International Journal of Technology Management, 20(1/2), 95–115. Miles, I., Kastrinos, N., Bilderbeek, R., den Hertog, P., Flanagan, K., Huntink, W. and Bouman, M. 1995. Knowledge-intensive business services: Users, carriers and sources of innovation. European Innovation Monitoring System (EIMS) Reports. Mina, A., Bascavusoglu-Moreau, E. and Hughes, A. 2014. Open service innovation and the firm’s search for external knowledge. Research Policy, 43(5), 853–866. Muller, E. and Zenker, A. 2001. Business services as actors of knowledge transformation: The role of KIBS in regional and national innovation systems. Research Policy, 30, 1501–1516. Nieto, M.J. and Santamaría, L. 2007. The importance of diverse collaborative networks for the novelty of product innovation. Technovation, 27, 367–377. Nieto, M.J. and Santamaría, L. 2010. Technological collaboration: Bridging the innovation gap between small and large firms. Journal of Small Business Management, 48(1), 44–69. Nonaka, I. and Takeuchi, H. 1995. The Knowledge-Creating Company. How Japanese Companies Create the Dynamics of Innovation. Oxford University Press, New York/Oxford. Noordhoff, C.S., Kyriakopoulos, K., Moorman, C., Pauwels, P. and Dellaert, B.G. 2011. The bright side and dark side of embedded ties in business-to-business innovation. Journal of Marketing, 75(5), 34–52. Päällysaho, S. 2008. Customer interaction in service innovations – A review of literature. In: Kuusisto, A. and Päällysaho, S. (Eds.) Customer Role in Service Production and Innovation – Looking for Directions for Future Research. Faculty of Technology Management Research Report 195. Lappeenranta University of Technology.

The specific traits of innovation in KIBS 77 Pina, K. and Tether, B. 2016. Towards understanding variety in knowledge intensive business services by distinguishing their knowledge bases. Research Policy, 45(2), 401–413. Ritala, P., Olander, H., Michailova, S. and Husted, K. 2015. Knowledge sharing, knowledge leaking and relative innovation performance: An empirical study. Technovation, 35, 22–31. Rodriguez, M., Doloreux, D. and Shearmur, R. 2016. Innovation strategies, innovator types and openness: A study of KIBS firms in Spain. Service Business, 10(3), 629–649. Rodriguez, M., Doloreux, D. and Shearmur, R. 2017. Variety in external knowledge sourcing and innovation novelty: Evidence from the KIBS sector in Spain. Technovation, 68(C), 35–43. Sethi, R., Smith, D.C. and Park, C.W. 2001. Cross-functional product development teams, creativity, and the innovativeness of new consumer products. Journal of Marketing Research, 38, 73–85. Strambach, S. 2001. Innovation processes and the role of knowledge-intensive business services. In: Koschatzky, K., Zulicke, M. and Zenker, A. (Eds.) Innovation Networks: Concepts and Challenges in the European Perspectives. Springer-Verlag, Heidelberg, pp. 53–68. Sundbo, J. 2002. The service economy: Standardisation or customisation? Service Industries Journal, 22, 93–116. Tether, B.S. 2002. Who co-operates for innovation, and why: An empirical analysis. Research Policy, 31(6), 947–967. Tether, B.S. and Metcalfe, J.S. 2004. Services and systems of innovation. In: Malerba, F. (Ed.) Sectoral Systems of Innovation. Cambridge University Press, Cambridge, pp. 287–324. Therrien, P., Doloreux, D. and Chamberlin, T. 2011. Innovation novelty and (commercial) performance in the service sector: A Canadian firm-level analysis. Technovation, 31(12), 655–665. Trigo, A. and Vence, X. 2012. Scope and patterns of innovation cooperation in Spanish service enterprises. Research Policy, 41(3), 602–613. Vandermerwe, S. 2000. How increasing value to customers improves business results. Sloan Management Review, 42, 27–37. Wood, P. 2002. Knowledge-intensive services and urban innovativeness. Urban Studies, 39(5–6), 993–1002.

Part III

Innovation and performance in KIBS

6

Innovation and performance in KIBS The empirical evidence

This chapter reviews the existing literature about innovation and performance in KIBS to understand how the identified categories of innovation, their novelty and their differentness affect multiple performance measures and which areas of research are underdeveloped.

Innovation and growth in KIBS Following the early work of Schumpeter (1934), innovation is considered to be a key driver of firms’ competitiveness and growth. Innovations improve firms’ efficiency, product range and reputation, and overall innovators are more profitable than non-innovators (Cainelli, Evangelista and Savona, 2006; Mansury and Love, 2008). For “traditional” business services, authors show a positive relationship between innovation and performance. Cainelli et al. (2004, 2006) demonstrate that innovating firms perform better than non-innovating firms, both in productivity and in growth, and that better-performing firms are more likely to innovate. They affirm that the relationship that links innovation and performance is “cumulative and selfreinforcing” (Cainelli et al., 2006, p. 454). Along this line, some scholars show that service innovation positively affects firms’ total employment as well as their market share (Evangelista and Savona, 2003). At the firm level, studies show that firms that invest more in R&D activities display a significant correlation between innovation and growth and that external partnerships for innovation have a positive effect on service firm performance (Evangelista and Savona, 2003; Leiponen, 2006; Love and Mansury, 2007; Tether, 2005). Other studies depict a more nuanced scenario. Mansury and Love (2008) provide empirical evidence showing that service innovation has a positive effect on growth (sales and employment growth) but no effect on productivity (value added per employee). While innovation in both manufacturing and service industries is relevant in explaining competitive dynamics, still relatively little empirical work investigates and theorizes on the relationship between multiple categories of innovation, innovation novelty and the performance of KIBS firms.

82 Innovation and performance in KIBS As discussed in the previous chapters, the literature debates the distinctive features of innovation in services and in KIBS (Coombs and Miles, 2000; Droege, Hildebrand and Forcada, 2009; Gallouj and Savona, 2009; Gallouj and Weinstein, 1997), causing more scholars to introduce into their empirical works about KIBS the distinctions between product and process innovations and between innovations that are new to the firm and innovations that are new to the industry and provide original evidence about how different facets of innovation affect performance in KIBS (Doloreux, Turkina and Van Assche, 2018; Love and Mansury, 2007; Mansury and Love, 2008; Rodríguez, Nieto and Santamaría, 2018; Therrien, Doloreux and Chamberlin, 2011). In this chapter, I review the literature that analyses the direct impact of these dimensions of innovation on firms’ growth and take a step further by looking at their joint effect. A product innovation is defined as a new product or service offered to clients. Product innovations can be developed starting from new technologies pushed by the firm to the market or be primarily customer driven. In both cases, product innovation has mainly a market focus. A process innovation identifies a new mode of production or delivery of goods or services and concerns the firm’s production or service operations. Process innovations mainly have an internal focus and are introduced to increase a firm’s productivity and overall efficiency (Damanpour, Walker and Avellaneda, 2009; Utterback and Abernathy, 1975). The distinction between product and process innovation is now used in the service domain by a growing number of authors (Amara, Landry and Doloreux, 2009; Damanpour et al., 2009; Hipp and Grupp, 2005; Sirilli and Evangelista, 1998). Given the relevance of this distinction, in the current chapter, I seek to understand which one affects firms’ growth more strongly. In fact, the distinction between process and product innovations is often associated with different performance goals. Process innovation aims at increasing a firm’s efficiency, while product innovation is tailored to entering new markets (Garcia and Calantone, 2002). Consequently, process and product innovations have specificities that deserve to be considered more explicitly in studies about performance in KIBS. Research findings support a positive relationship between product innovations and growth (Cabigiosu and Campagnolo, 2019; Love and Mansury, 2007; Mansury and Love, 2008; Therrien et al., 2011). Moreover, the literature on KIBS highlights two common features that are likely to affect the relationship between innovation and growth, that is, client–supplier collaboration and service customization (Bettencourt et al., 2002). KIBS firms often develop tailored services using the knowledge that they obtain from collaborating with customers during service development and delivery (den Hertog, Van der Aa and De Jong, 2010; Hipp and Grupp, 2005; Larsen, 2001). Buyer–supplier collaboration allows KIBS firms to exchange a significant amount of data and information about clients’ requirements, thus identifying new business opportunities and innovative services to satisfy customers’ needs (Campagnolo and Cabigiosu, 2015). Along this line, several studies

Innovation and performance in KIBS

83

show that understanding the customer greatly affects new product success, because the market uncertainty is reduced (Nieto and Santamaría, 2007; Ritala et al., 2015). Moreover, such studies indicate that the introduction of radically new products is favoured in such environmental conditions. Tether (2002) and Lettl, Herstatt and Gemuenden (2006) confirm that collaboration is more frequent among firms pursuing radical innovations. KIBS firms are problem solvers that are asked to develop customized solutions to meet the clients’ needs (Bettencourt et al., 2002; Campagnolo and Cabigiosu, 2015; den Hertog, 2000; Muller and Zenker, 2001). The ability to offer precise customization at the level of the individual customer enhances a KIBS firm’s reputation as well as the clients’ perceived value and switching costs. Therefore, this feature is likely to lock customers into long-lasting client–KIBS relationships that facilitate further knowledge sharing and product innovation (Vandermerwe, 2000). Switching costs are an isolating mechanism that constrains latecomers from catching up with the pioneers (Golder and Tellis, 1993). Therefore, both client– supplier interaction and service customization are KIBS features that are likely to reinforce the positive relationship between product innovation and growth. Because of these features of KIBS, innovating KIBS firms do not face all the risks and uncertainty that typically hinder first-mover advantages (Massini, Lewin and Greve, 2005) and should be encouraged to anticipate the introduction of new products because they possess first-hand information about the customers’ needs. For example, Therrien et al. (2011) investigate the relationship between first-mover advantage and performance in Canadian KIBS industries, finding that services that are new to the industry guarantee the largest increase in sales. In addition, Mansury and Love (2008), studying US business-to-business services and KIBS, find that innovations that are new to the industry positively affect firms’ growth. Cabigiosu and Campagnolo (2019) study KIBS firms in Italy and find that product innovations that are new to the industry are positively correlated with firms’ growth. Different from product innovation, the relationship between process innovations in business services and their performance effects is less clear. Even though it has been established that this type of innovation is mostly aimed at enhancing internal efficiency, the evidence here is scant and studies show ambiguous results (Aboal and Garda, 2016; Damanpour et al., 2009). For example, Musolesi and Huiban (2010) find that process innovation is ineffective when it comes to a firm’s productivity. Again, Mairesse and Robin (2010) obtain comparable results. Cabigiosu and Campagnolo (2019) find that process innovations that are new to the industry have a negative effect on growth in t-KIBS. The current evidence about the effect of collaboration with clients mainly focuses on products. In the KIBS domain, collaboration with clients has unclear effects on KIBS firms’ ability to innovate inner procedures. The latter are often black boxes for clients that cannot be of help or are not even interested in their innovation process (Cabigiosu et al., 2015). Furthermore, as explained by Love and Mansury (2007), in KIBS, clients do not typically collaborate on process innovations, which stay the sole responsibility of KIBS firms. Therefore, it may become

84 Innovation and performance in KIBS more complex to market, let alone accept and communicate process innovations, especially when they do not provide any tangible benefit to the customer. Overall, the existing literature on KIBS suggests that the positive relationship between innovation and growth is stronger for product innovations that are new to the industry, while the relationship between innovation and productivity is more complex and is discussed further in Chapter 7 (Cabigiosu and Campagnolo, 2019).

Innovation, service types and performance in KIBS KIBS represent a particular category of service firms, and scholars discussing service innovation in KIBS clearly underline their customized nature until, to some extent, they superimpose service customization on service innovation (Bettencourt et al., 2002). This correlation between service customization and KIBS firms’ ability to develop new services leads to difficulties in theorizing the role of service standardization and modularity in KIBS as well as their impact on KIBS firms’ ability to develop successful new services. Recent contributions try to address this issue and demonstrate that KIBS firms also provide modular and standard services. These scholars also question the assumption that service innovation does not necessarily imply service customization: firms that design more customized services are not more innovative than firms that provide standard services. KIBS firms can also innovate when providing standard services (Cabigiosu et al., 2015; Hipp, Tether and Miles, 2000; Miozzo and Grimshaw, 2011; Pekkarinen and Ulkuniemi, 2008; Tether, Hipp and Miles, 2001; Voss and Hsuan, 2009). In this respect, the interplay between service innovation and service types (i.e. customized, standard, standard with minor customizations and modular) is a recent area of research that argues that KIBS firms’ performance may depend on the service portfolio deriving from the combination of service innovation and multiple service types. Gaining a deeper understanding of how service innovation (product and process innovations) and different types of services (customized, standard, standard with minor customizations and modular) complement each other and lead to different business models in KIBS is the aim of this section. Researchers now consider service customization to be a crucial feature and a source of competitive advantage of KIBS. KIBS services are customized because clients have a relevant role in their design (Bettencourt et al., 2002; Corrocher, Cusumano and Morrison, 2009). To develop their services, KIBS firms study in depth the operational process and organization of their clients and design their offer to meet each client’s request. KIBS need to be co-produced with the help of the clients, which possess the knowledge and competences about their specific business/industry that, in turn, are the inputs of KIBS firms’ design and problemsolving processes (Bettencourt et al., 2002; Skjølsvik et al., 2007; Sundbo, 2002). The argument that KIBS are often customized also supports the hypothesis that innovation in KIBS is the outcome of customization processes and that customization and innovation go hand in hand (Hipp et al., 2000). Customization

Innovation and performance in KIBS

85

processes allow KIBS firms to identify and develop new business opportunities, and innovations are tailored services. However, KIBS firms sometimes also replicate their services, and the relationship between service customization and service innovation is more nuanced. We cannot affirm that, when KIBS firms customize their offer, they are more likely to innovate than service providers that rely on multiple service types (Tether et al., 2001). Hence, the literature may stress the importance of service customization for innovation while missing the relevance of designing and having a portfolio of service types to increase the overall firm performance.

Complementarities between innovation, service types and firms’ performance The KIBS literature considers the following service types (Hipp et al., 2000; Sundbo, 1994; Tether et al., 2001). Customized services are designed to satisfy specific client needs, while standard services are undifferentiated between clients and the service is not adapted to them. Standard services with minor customizations include some changes to satisfy specific clients’ needs that usually do not alter the main attributes of the service. Modular services combine some elements of standardization and customization, and services are customized to some extent by mixing and matching standard elements or modules. Thus, modular services may be perceived as personalized while they derive from the combination of standard services (Pekkarinen and Ulkuniemi, 2008; Voss and Hsuan, 2009). The KIBS literature emphasizes that firms developing custom services exchange significant amounts of information and knowledge with clients about their needs and thus have the opportunity to identify new business opportunities (Cabigiosu et al., 2012). Firms’ ability to innovate successfully is tightly correlated with service customization, and the two may be complementary. However, contrary to the mainstream literature on KIBS, in recent studies, scholars show that KIBS services can also be standard, or partially standardized, and warn that innovating KIBS can develop a variety of services mixing different levels of customization/standardization and that KIBS firms focusing on customized services are not necessarily the best-performing firms (Cabigiosu and Campagnolo, 2019). KIBS firms have the ability and competences to codify the knowledge that they acquire through interacting with clients and exploit it in several supply relationships by introducing some levels of standardization and replication in their service offering. Replication processes support firms’ performance, increasing their level of productivity, while service customization is delivered via unique and unrepeatable activities that generate low experience effects. Moreover, when KIBS firms replicate their service offering, at least partially, they can increase their productivity, gain economies of scale and scope, serve a higher number of clients and increase their market share more rapidly. In addition, the combination of innovative services and standard/modular services may increase KIBS firms’ portfolio equilibrium. Innovative services are typically stars or question marks, with promising market share growth, while

86 Innovation and performance in KIBS standardized/modular services may play the role of cash cows and be used to satisfy the most common and widespread clients’ needs (Ghemawat, 2002). Standard/modular services generate cash flows that are used to foster service innovation in the long run. Furthermore, when KIBS firms are able to replicate their innovations in multiple supply relationships, they increase the market share of their innovations and positively affect their economic performance. Hence, a KIBS firm replicating its innovative services can exploit its original effort and investment more effectively, so standardization/modularization and innovation become complementary strategies (Muller and Zenker, 2001). Hence, a KIBS firm that innovates and produces some level of standard/modular services reinforces the positive effects of innovation on its profitability and sales. KIBS firms may become ambidextrous by balancing their innovation and replication and their exploration and exploitation efforts (March, 1991). The previous paragraphs suggest that the best-performing KIBS firms should couple innovation and customization with some levels of standardization: customization enhances innovations that can be reproduced via standard services in multiple supply relationships. This strategy maximizes the market share potential of new services, increases the firms’ efficiency and balances their portfolio of services. In this scenario, Campagnolo and Cabigiosu (2015) use the configurational approach to test these assumptions and show that different service innovations and service types generate different configurations and that these configurations are causally associated with the growth of KIBS firms’ market share and profitability (ROI).

Configurations of the best-performing service types and innovations A configuration is a mix of variables, each one displaying a given intensity, that generates an attended outcome. The configurational approach suggests that different sets of variables or attributes can lead to the same outcome depending on how they are arranged (Fiss, 2011). The configurational approach also emphasizes the concept of equifinality, which identifies the situation in which a firm can reach the same performance from different initial conditions, and we cannot postulate a priori that one unique optimal configuration exists (Katz and Kahn, 1978). For example, an athlete can achieve high performance both by combining high levels of training and dietary restrictions and by combining high levels of training and rest. Campagnolo and Cabigiosu (2015) suggest that product and process innovations and different service types generate different equifinal configurations as regards firms’ performance. These configurations can diversely combine the variables investigated, of which the causal relationships can be characterized by complementarity, substitution, additive or suppression effects. The data used concern the KIBS firms in the Veneto region (northeast Italy)1 and cover the period 2006–2008. They were collected by conducting a survey on a representative sample of KIBS firms, and ultimately answers were collected from 512 firms and 319 complete questionnaires. The sample was

Innovation and performance in KIBS

87

balanced in terms of the categories of the services provided and included ICT, design and communication and professional firms. Two outcomes were considered: the firm’s growth in ROI (return on investments), and the firm’s growth in market share, measured as two dummy variables with the values of dependent variables equal to 1 whenever the variables increased in the analysed period. The authors measured innovation distinguishing between product innovations and process innovations and used two dummy variables to map their presence or absence. Service types were classified as customized services, standard services with minor customizations, standard services and modular services. Finally, the authors included the firm size (total number of employees) and the quality of human resources (share of graduates in the total number of employees). Table 6.1 synthesizes the configurations obtained focusing on core conditions, while peripheral conditions, for which the evidence for a causal relationship with the outcome is weaker (Fiss, 2011), are excluded from the graphical representation. The results indicate one relevant configuration for ROI growth and three for the growth in market share. Solution 1 corresponds to the configuration generating the superior profitability of KIBS firms and is characterized by the following core conditions: the absence of product innovations, the presence of process innovations and the presence of a larger share of standard services. These core conditions are combined with a number of peripheral conditions: the presence of customized services, greater than average firm size and quality of human resources and the absence of modular services and of standard services with minor customizations. Table 6.1 Configurations and core conditions for achieving higher profitability (ROI) and higher growth (market share) ROI 1

Market share 3

4

⍉

○

○ ○

⍉

Graduates

○

⍉

Size

○

⍉

Product innovation Process innovation Customized Standard

2

⍉

○

○ ○

○

Standard custom Modular

⍉

○

○ = Presence of core condition ⍉ = Absence of core condition Source: Adapted from Campagnolo and Cabigiosu (2015).

88

Innovation and performance in KIBS

Solutions 2, 3 and 4 are those leading to an increase in a KIBS firm’s market share. Solution 2 can be combined with two different sets of peripheral conditions and the same core conditions. The core conditions are a portfolio of customized and modular services and the presence of process innovations. The two sets of peripheral conditions are: a) the presence of product innovations, the absence of standard services (both fully standard and standard with minor customizations), a larger size and the absence of graduates; and b) the presence of a larger size and share of graduates, the absence of product innovations and the absence of any type of standard services. Solution 3 merges the presence of process innovations, customized services, a bigger size and more graduates than average with the absence of product innovations as core conditions. This solution identifies as peripheral conditions the presence of standard services and the absence of standard service with minor customizations and modular services. Solution 4 is the unique configuration displaying product innovations as a core condition. Solution 4 also has as core conditions the absence of customized services, a larger size and a share of graduates. The peripheral conditions of Solution 4 are the presence of standard services with minor customizations and the presence of process innovations, while modular and standard services are absent. Comparing all the models, we observe recurring causal conditions independently from the outcome considered. Interestingly, the results indicate the existence of only one necessary condition, namely process innovations, that is shared across all the solutions (both ROI and market share). We also observe that customized services and standard services with minor customizations substitute for each other and that product innovations and a share of graduates that is larger than average substitute for each other. There are several insights and conclusions that can be drawn from these results. First, the emerging configurations lead to the main conclusion that a variety of paths support KIBS firms’ profitability and growth. Moreover, the configurations for profitability and for growth are different and lead to the idea that these are two potentially conflicting objectives. In particular, model 1 and model 3 share the presence and the absence of the same elements. For example, in model 1, process innovation is excluded as a core condition for ROI growth while it is included as a core condition in model 3 for market share growth. The results also indicate that multiple configurations support KIBS firms’ growth while only one configuration leads to higher profitability. The results furthermore show that product and process innovations behave differently. Process innovations are core conditions in three out of four models, while product innovations are core conditions in only one. Process innovation is a necessary, but not sufficient, condition for both growth and profitability. On the contrary, the role of product innovation is more controversial, and the results seem to suggest that product innovation is more disruptive than process innovation for profitability. No product innovation is a core condition for increasing profitability and, in one model, for firms’ growth (see models 1 and 3). In both models, product innovation is the only core condition of absence. Product innovation may render resources and processes obsolete both at the supplier and at the customer level, thus limiting their potential to contribute to firms’ performance (Mansury and Love, 2008).

Innovation and performance in KIBS

89

This study also supports the hypothesis that firms that are able to combine service customization and service standardization perform better. KIBS firms should balance their portfolio of service types, and these results suggest that the best-performing configurations focus on customized and modular services or on customized and standard services. Furthermore, in all these models, process innovation is combined with service customization, thus confirming that innovation and customization are complementary in KIBS. However, service innovation and customization are also combined with standard or modular services. This finding supports the hypothesis that the best-performing firms are those that mix service innovation and service customization with exploitation activities via service replication. In particular, the combination of fully standardized services and process innovations increases a firm’s efficiency, while process innovations coupled with customized and modular services augment a firm’s market share. Overall, this chapter leads to the following considerations. First, coherently with the established KIBS literature, it suggests that customization and innovation are complementary in that customization improves the comprehension of clients’ requirements, thus fostering innovation. Chapter 8 discusses this result further by considering the extent to which performing firms should rely on customization and client collaboration. Second, this chapter adds that innovation and standardization/modularization are complementary, since they increase the firm’s portfolio equilibrium and the market share of innovations that can be replicated in a number of supply relationships, with a positive effect on the firm’s performance. Third, the role of product and process innovations should be disentangled further in that we still need empirical evidence to detect their separate and joint effects on firms’ performance. Particularly, while the prior literature emphasizes the role of product innovations and particularly that of innovations that are new to the industry, this chapter highlights the importance of a more in-depth understanding of the joint effect of product and process innovations on different outcome measures and particularly on productivity (see also Chapter 7). The fact that the configurations for profitability and for growth are different presents the opportunity to investigate further these relationships, which deserve additional empirical tests. At least in the short run, the best-performing KIBS firms are those that focus either on product or on process innovations. Fourth, this analysis emphasizes that product and process innovations should also be considered for their levels of newness and differentness, which may amplify or hinder innovations’ effect via a number of mechanisms (see Chapter 4). Finally, different dynamics may exist for p- and t-KIBS.

Note 1 Veneto is among the most developed regions in Italy and in Europe in terms of the employment rate and GDP per capita. The load-bearing structure of the Veneto

90 Innovation and performance in KIBS economy is represented by small- and medium-sized enterprises. Veneto is still classified, along with the whole of the north of Italy, as a core manufacturing region (Corrocher and Cusmano, 2014), but more recently the Veneto region has also seen significant growth in the KIBS sector, particularly in terms of new firms being established: about two-thirds of Veneto KIBS firms were established after 1990. In 2009, about 63% of KIBS firms were p-KIBS, and 37% were t-KIBS. KIBS firms in Veneto are on average micro firms with seven employees (Cabigiosu, 2016).

References Aboal, D. and Garda, P. 2016. Technological and non-technological innovation and productivity in services vis-à-vis manufacturing sectors. Economics of Innovation and New Technology, 25(5), 435–454. Amara, N., Landry, R. and Doloreux, D. 2009. Patterns of innovation in knowledgeintensive business services. Service Industries Journal, 29(4), 407–430. Bettencourt, L.A., Ostrom, A., Brown, S.W. and Roundtree, R. 2002. Client co-production in knowledge-intensive business services. California Management Review, 44(4), 100–128. Cabigiosu, A. 2016. L’innovazione e la progettazione nei servizi knowledge-intensive. Giapichelli, Torino. Cabigiosu, A. and Campagnolo, D. 2019. Innovation and growth in KIBS: The role of clients’ collaboration and service customization. Industry and Innovation, 26, 592–618. Cabigiosu, A., Campagnolo, D., Furlan, A. and Costa, G. 2012. Knowledge dynamics in third-party logistics: Balancing exploitation and exploration through service architectures. In: Di Maria E., Grandinetti, R. and Di Bernardo, B. (Eds.) Exploring Knowledge-Intensive Business Services: Knowledge Management Strategies. Palgrave MacMillan, London, pp. 155–173. Cabigiosu, A., Campagnolo, D., Furlan, N. and Costa, G. 2015. Modularity in KIBS: The case of third-party logistics service providers. Industry and Innovation, 22(2), 126–146. Cainelli, G., Evangelista, R. and Savona, M. 2004. The impact of innovation on economic performance in services. Service Industries Journal, 24(1), 116–130. Cainelli, G., Evangelista, R. and Savona, M. 2006. Innovation and economic performance in services: A firm-level analysis. Cambridge Journal of Economics, 30(3), 435–458. Campagnolo, D. and Cabigiosu, A. 2015. Innovation, service types, and performance in knowledge intensive business services. In: Agarwal, R., Selen, W., Ross, G. and Green, R. (Eds.) The Handbook of Service Innovation. Springer, London, pp. 109–121. Coombs, R. and Miles, I. 2000. Innovation, measurement and services: The new problematique. In: Metcalfe, J. and Miles. I. (Eds.) Innovation Systems in the Service Economy. Measurements and Case Study Analysis. Kluwer Academic Publishers, Dordrecht, pp. 83–102. Corrocher, N., Cusumano, L. and Morrison, A. 2009. Modes of innovation in knowledge-intensive business services: Evidence from Lombardy. Journal of Evolutionary Economics, 19(2), 173–196. Corrocher, N., and Cusumano, L. 2014. The ‘KIBS Engine’ of regional innovation systems: Empirical evidence from European regions. Regional Studies, 48(7), 1212–1226. Damanpour, F., Walker, R.M. and Avellaneda, C.N. 2009. Combinative effects of innovation types and organizational performance: A longitudinal study of service organizations. Journal of Management Studies, 46(4), 650–675. Den Hertog, P.D. 2000. Knowledge-intensive business services as co-producers of innovation. International Journal of Innovation Management, 4, 491–528.

Innovation and performance in KIBS

91

Den Hertog, P., van der Aa, W. and de Jong, M.W. 2010. Capabilities for managing service innovation: Towards a conceptual framework. Journal of Service Management, 21(4), 490–514. Doloreux, D., Turkina, E. and Van Assche, A. 2018. Innovation type and external knowledge search strategies in KIBS: Evidence from Canada. Service Business, 1–22. Droege, H., Hildebrand, D. and Forcada, M.A.H. 2009. Innovation in services: Present findings, and future pathways. Journal of Service Management, 20(2), 131–155. Evangelista, R., and Savona, M. 2003. Innovation, employment and skills in services. Firm and sectoral evidence. Structural Change and Economic Dynamics, 14(4), 449–474. Fiss, P. 2011. Building better causal theories: A fuzzy set approach to typologies in organization research. Academy of Management Journal, 54(2), 393–420. Gallouj, F. and Savona, M. 2009. Innovation in services: A review of the debate and a research agenda. Journal of Evolutionary Economics, 19(2), 149–172. Gallouj, F. and Weinstein, O. 1997. Innovation in services. Research Policy, 26, 537–556. Garcia, R. and Calantone, R. 2002. A critical look at technological innovation typology and innovativeness terminology: A literature review. Journal of Product Innovation Management, 19(2), 110–132. Ghemawat, P.E. 2002. Competition and business strategy in historical perspective. Business History Review, 76(1), 37–74. Golder, P.N. and Tellis, G.J. 1993. Pioneer advantage: Marketing logic or marketing legend? Journal of Marketing Research, 30, 158–170. Hipp, C. and Grupp, H. 2005. Innovation in the service sector: The demand for servicespecific innovation measurement concepts and typologies. Research Policy, 34(4), 517–535. Hipp, C., Tether, B. and Miles, I. 2000. The incidence and effects of innovation in services: Evidence from Germany. International Journal of Innovation Management, 4(4), 417–453. Katz, D. and Kahn, R.L. 1978. The Social Psychology of Organizations. Wiley, New York Larsen, J.N. 2001. Knowledge, human resources and social practice: The knowledgeintensive business service firm as a distributed knowledge system. Service Industries Journal, 21(1), 81–102. Leiponen, A. 2006. Organization of knowledge exchange: An empirical study of knowledge- intensive business service relationships. Economics of Innovation and New Technology, 15(4/5), 443–464. Lettl, C., Herstatt, C. and Gemuenden, H.G. 2006. Users’ contributions to radical innovation: Evidence from four cases in the field of medical equipment technology. R&D Management, 36, 251–272. Love, J.H. and Mansury, M.A. 2007. External linkages, R&D and innovation performance in US business services. Industry and Innovation, 14(5), 477–496. Mairesse, J. and Robin, S. 2010. Innovation and Productivity: A Firm-Level Analysis for French Manufacturing and Services Using CIS3 and CIS4 Data (1998–2000 and 2002–2004). Paris: CREST-ENSAE. Mansury, M.A. and Love, J.H. 2008. Innovation, productivity and growth in US business services: A firm-level analysis. Technovation, 28(1–2), 52–62. March, L.G. 1991. Exploration and exploitation in organizational learning. Organization Science, 2(1), 71–87. Massini, S., Lewin, A.Y. and Greve, H.R. 2005. Innovators and imitators: Organizational reference groups and adoption of organizational routines. Research Policy, 34, 1550–1569. Miozzo, M. and Grimshaw, D. 2011. Capabilities of large services outsourcing firms: The “outsourcing plus staff transfer model” in EDS and IBM. Industrial and Corporate Change, 20(3), 909–940.

92 Innovation and performance in KIBS Muller, E. and Zenker, A. 2001. Business services as actors of knowledge transformation: The role of KIBS in regional and national innovation systems. Research Policy, 30, 1501–1516. Musolesi, A. and Huiban, J.P. 2010. Innovation and productivity in knowledge intensive business services. Journal of Productivity Analysis, 34(1), 63–81. Nieto M.J. and Santamaría, L. 2007. The importance of diverse collaborative networks for the novelty of product innovation. Technovation, 27, 367–377. Pekkarinen, S. and Ulkuniemi, P. 2008. Modularity in developing business services by platform approach. International Journal of Logistics Management, 19(1), 84–103. Ritala, P., Olander, H., Michailova, S. and Husted, K. 2015. Knowledge sharing, knowledge leaking and relative innovation performance: An empirical study. Technovation, 35, 22–31. Rodríguez, A., Nieto, M.J. and Santamaría, L. 2018. International collaboration and innovation in professional and technological knowledge-intensive services. Industry and Innovation, 25(4), 408–431. Schumpeter, J.A. 1934. The Theory of Economic Development. Harvard University Press, Cambridge, MA. Sirilli, G. and Evangelista, R. 1998. Technological innovation in services and manufacturing: Results from Italian surveys. Research Policy, 27(9), 881–899. Skjølsvik, T., Løwendahl, B.R., Kvålshaugen, R. and Fosstenløkken, S.W. 2007. Choosing to learn and learning to choose: Strategies for client co-production and knowledge development. California Management Review, 49, 110–128. Sundbo, J. 1994. Modulization of service production and a thesis of convergence between service and manufacturing organizations. Scandinavian Journal of Management, 10(3), 245–266. Sundbo, J. 2002. The service economy: Standardisation or customisation? Service Industries Journal, 22, 93–116. Tether, B.S. 2002. Who co-operates for innovation, and why: An empirical analysis. Research Policy, 31(6), 947–967. Tether, B.S. 2005. Do services innovate (differently)? Insights from the European Innobarometer survey. Industry and Innovation, 12(2), 153–184. Tether, B.S., Hipp, C. and Miles, I. 2001. Standardization and particularization in services: Evidence from Germany. Research Policy, 30(7), 1115–1138. Therrien, P., Doloreux, D. and Chamberlin, T. 2011. Innovation novelty and (commercial) performance in the service sector: A Canadian firm-level analysis. Technovation, 31(12), 655–665. Utterback, J.M. and Abernathy, W.J. 1975. A dynamic model of process and product innovation. Omega, 3(6), 639–656. Vandermerwe, S., 2000. How increasing value to customers improves business results. Sloan Management Review, 42, 27–37. Voss, C.A. and Hsuan, J. 2009. Service architecture and modularity. Decision Science, 40(3), 541–569.

7

The productivity dilemma and digitalization in services

KIBS are often customized and intangible and cannot be stored. The KIBS and service literature published over many years suggests that these properties negatively affect the impact of innovation on KIBS firms’ productivity and growth. This chapter discusses this assumption.

The growth of services, servitization and the productivity dilemma In the 1980s, the United States suffered from stagnation in productivity, which Baumol (1985) and other scholars attributed to the ever-greater weight of the service sector compared with the industrial sector. In those years, we observed a shift in employment and added value towards the service sector, paradoxically driven by the fact that new technologies in manufacturing allowed increasing productivity year after year. However, if the demand for material products thus obtained does not grow at the same rate – and does not grow because many of those products are already present in abundance in the homes and garages of American consumers – the continuous increase in industrial productivity translates into a corresponding reduction in manufacturing firms’ demand for employees and a decline in the prices of industrial products, which fall as a result of lower costs. What did consumers do with the money that they saved from purchasing fewer material products and the continuous decline in their prices? They discovered new needs, and most of them fed the demand for services: people go to the cinema, to the theatre, to the gym, to the restaurant and on tourist trips. Alternatively, they fall in love with luxury products (clothes, perfumes, bags, jewellery, etc.), which require a strong investment in the services needed to design, deliver and sell them, in particular in the creation of meanings, in brand communication and in the direct commercial network (single-brand) aimed at the final consumer, or they greatly value innovation that requires R&D, engineering and design services. It is not only the final consumers who feed the tertiarization of the economy. Even the public administration, with the increasing weight of welfare, drains resources from the private economy (through taxes) and returns them in the form

94

Innovation and performance in KIBS

of services such as health or social security services, which have a growing weight on employment and the overall GDP (gross domestic product). Furthermore, industrial companies themselves, to increase the productivity of the factory, are increasingly resorting to managerial, organizational, IT, creative (design, stylists, research and development), training management and human resource services, which are coupled with increasingly strong commitment at the level of marketing. These services are partly “internal” to the manufacturing company but partly resort to the “external” tertiary sector, becoming a visible vehicle for the tertiarization of the overall system (Bettiol, Di Maria and Grandinetti, 2012). In this phase, a large part of the employees and added value (with percentages ranging from 60% to 80%, including the public administration) come from the tertiary sector in mature economies (Rullani, 2014). Here arises the productivity dilemma and the “cost sickness”: tertiarization paralyses industrial growth with the continuous growth of services and their costs to the point of stifling the development tout court. The prevailing image fed by the Baumol disease is that of manufacturing that generates productivity and a service sector that “consumes” it: the value and resources generated by the ever-increasing productivity of manufacturing are then spent by and for services, each of which is useful for the manufacturing firms’ competitiveness but per se refractory to innovation and productivity gains. This is not the idea of classical economists that services are “unproductive” tout court, but we have little left. What prevented services from following manufacturing along the path of innovation and productivity gains? At the time, the answer seemed to be simple and convincing: the immaterial nature of the service. For a long time, services have been regarded as having inferior productivity. The application of productivity measures to service activities resulted in productivity levels far beyond those in manufacturing (Reckenfelderbäumer, 2008). This productivity gap has been correlated with the characteristic features of services: intangibility, heterogeneity, inseparability and perishability. Services are provided to customers and consumed at the same time, without any separation between the supply and the demand. Each service must be provided at the time and place where the demand arises: the specific demand of the client who requests a meal at a restaurant or a lesson from the trainer. The possibilities to aggregate the demand, to provide a joint, collective, offer, are limited: the chef can provide their local ten or 20 tables, but then they must serve to customers what each of them chooses from the menu. Only in exceptional cases (ports, airports, railway stations, schools, hospitals, etc.) is the supply able to concentrate the demand (in time and space) and apply operational programs established to deliver the service at an ex ante established rate. In this way, the offer of services can benefit from economies of scale, standardizing them with a para-industrial methodology, even though this way of producing the service is often at the expense of the flexibility and customization to which the traditional system of services has accustomed us. Manufacturing firms have a chance that services do not have: these firms can separate their production flows from the dispersed and fluctuating demand that

Productivity dilemma and digitalization

95

exists in the environment. Using a demand push approach, manufacturing firms forecast production volumes and produce items that can be stored in warehouses and transferred when and where clients want. The demand and the supply can be independent in terms of both time and space. In this context, the production processes are buffered from the uncertainty and variability of the external environment and can be designed to maximize the production’s efficiency and productivity. Services cannot do that. Furthermore, services’ heterogeneity is greater due to the client–supplier interaction during service provision: services are the by-product of interactions with clients and are (at least partially) consequently customized. This is the root of the cost sickness: service production cannot be separated from consumption and the service sector cannot design production systems that are highly efficient and benefit less from new technologies. Overall, productivity in services is limited by their intangible nature, and, if productivity does not increase significantly, service prices also do not diminish, thus limiting the richness and welfare of the states in which services dominate. However, this condition of services that are intangible and cannot be modernized ceases to exist when, starting from the 1990s, we observe the progressive development of digital networks that, to a certain extent, invert the roles: the immaterial (translated into bits) becomes transferable in real time and at no cost from one part of the world to the other.

Digitalization and the productivity dilemma Digital networks provide services with modern forms of production and consumption. Not all services, of course, can be translated into a flow of bits that can respond to a demand located one hundred or one thousand kilometres away. A cleaning service of streets, or of hotel rooms, needs to be carried out here and now, without great degrees of freedom for the service provider. Nevertheless, the separation between supply and demand can be practiced without great difficulty for all those services that satisfy the demand via coded knowledge, once this has been translated into software or a numerical database. The new communication technologies (ICT and the Internet) have eased the reproducibility and transferability of codified knowledge, which, in developed countries, has been elaborated in the form of scientific knowledge, technologies incorporated into machines and standard processing procedures that companies – especially large companies – have made abstract and explicit. It is the road that leads to the proliferation of call centres that moves the databases of large organizations into the cloud, thus making them accessible from many different locations. E-commerce gradually replaces less complex, more encodable transactions. Machines, factories and residences can increasingly be controlled and guided remotely, considering that now even surgical operations can be performed for a patient who is in Milan while the surgeon who operates it guides the necessary devices and robots from her clinic in New York (Di Maria, Grandinetti and Di Bernardo, 2012).

96 Innovation and performance in KIBS It is not only knowledge-based performance that is freed from the distance barrier. The space–time disjunction between those who offer and those who request a service is also possible (but not at zero cost) for those services in which generative knowledge must be employed that requires the intervention of the human mind to interpret, imagine, convince and make decisions in uncertain conditions. In this case, the relationship at a distance (in space and time) does not come at zero cost and in real time but requires the patience of interpersonal communication, which, however, can now also take place in effective forms through Skype, videoconferences, mobile connections and coworking outside the canonical places of the factory and the office. In a growing number of cases, the service offer can be organized in the most convenient forms, using ICT to connect with the demand. However, in this way, the barrier that excluded services from modernization processes, and from their economies of scale, is removed. In this setting, the historical demarcation between material (manufacturing) and immaterial (services) is broken. The first effect of this change is that an important tertiary (immaterial) part can now be “industrialized” using all the power of digital technologies. Millions of people, every day, use search engines such as Google or visit dedicated (virtual) places on social networks: the volumes of services offered and used are so high that many of them are free, since the advertising revenue is sufficient to finance the service. Furthermore, new technologies allow high service scalability and economies of scale. For example, applications may be expensive to develop but, once on the market, they have almost no replication costs and are very affordable to clients. Alongside this process of innovation in services, we are witnessing a change in the role of services in manufacturing firms. Today, these firms derive only part of the value from the sale of material products, while they are focusing more and more on the ability to create and sell meanings or emotionally engaging experiences associated with the material product. Industry, in other words, is dematerializing, and it is becoming similar in some ways, in terms of problems and modes of action, to the world of services. The latter, moving in a convergent way, are in turn exploring the advantages of business models that are close to the industrial tradition (economies of scale, modularity, standards, etc.). Today, at the frontier of innovation, we find manufacturing firms that are investing in the immaterial (servitization) and services that are becoming more and more industrialized, trying to increase their efficiency and economies of scale. Convergence extends beyond the old dichotomies and requires new distinctions. Alongside the mass production industry, which continues to be so and becomes a low-cost global commodities industry, there is a new industry that instead seeks quality and therefore begins to offer increasing levels of customization, variety, meaning, experience and guarantees that were once typical only of services. Similarly, in the opposite but convergent sense, part of services is transformed into new services, which are services delivered as in the industrial production paradigm: while they still guarantee a certain degree of flexibility, they are

Productivity dilemma and digitalization

97

mainly platform or modular services with practically zero reproduction and transfer costs (see Chapter 10). The result is that the traditional distinction between sectors (manufacturing, tertiary, etc.) is vanishing, and today it would be difficult to say whether a company like the Italian shoe producer Geox is a manufacturing company or an all-tertiary company. The same is true for a company like Google, which sells a standard service characterized by very large volumes, and sells it worldwide, even though the product is a “service”, not a good. In short, we need to redefine the variables that characterize firms’ activities, reaching beyond the traditional sectors, looking at their intelligence content, not at their content in terms of material/immaterial, and redefining the debate about productivity in services and in KIBS.

Measuring productivity in services Productivity captures the relationship between the production of goods and services and the factors of production used. Productivity is relevant both as a performance and as a planning measure. In planning activities, productivity should be used to identify firms’ goals and the resources needed to achieve them, respectively. By doing so, potential criticisms and bottlenecks should become evident. The overall aim of such planning activities is to outperform competitors by determining how a firm’s planned results can be achieved by deploying the smallest possible amount of resources. Alternatively, it is possible to specify how the greatest outcome can be achieved by employing the available resources. While the debate about the measurement of productivity in manufacturing firms is quite a consolidated topic with clear definitions and measures based on contrasting input and output, how to measure the productivity of services and KIBS is still a widely discussed topic, and it is currently being investigated by many scholars. In fact, well-established notions and measures that have long been applied to products cannot be transferred to services as they are due to their specificities. Clients are involved in the service design and delivery, and hence their contribution must be considered as an input for the service production process that is able to affect service firms’ productivity. Consequently, it becomes necessary to quantify clients’ cooperation. Additionally, service readiness and service innovation can affect productivity and need to be incorporated into measures of productivity. Biege et al. (2013), in their literature analysis, list multiple streams of literature dealing with this topic. The first is labelled industrial productivity (Levitt, 1972) and attempts to explore service productivity by transferring the concepts of industrial manufacturing productivity to the service area but neglects the fact that services need special attention when measuring their productivity. The second relies on Corsten (1994), whose concept of measuring service productivity is based on multiple stages of a service delivery process and accordingly divided into two main productivity ratios. The first is service readiness,

98 Innovation and performance in KIBS which compares the ratio of the initial output to the related inputs needed, that is, the ratio of the actually used service readiness to the total provided service readiness. The second index also includes customer-induced inputs (external factors). The productivity of the final service is therefore defined as the ratio of the output of the final service to the sum of service readiness, further internal factors and external factors. This approach is targeted to services in that it recognizes the relevance of clients’ contribution to service development. At least partially substitutive and combinatorial relations between internal and external inputs can lead to different input combinations with identical service outputs. Thirdly, Johnston and Jones (2004) take this perspective a step further and propose two measures of service productivity: operational productivity and customer productivity. The former is the ratio that measures service firms’ operational outputs, such as revenues or the number of customers served, against the inputs used to deliver the service, which include human resources, clients, equipment and other materials. The second is customer productivity, which is the ratio between customer outputs, such as experience, outcome and value, and customer inputs, which can be measured as the effort, costs and time correlated with their involvement in service design and delivery. The authors also emphasize that, while the buyer and the supplier typically share the benefits of high levels of productivity in industrial processes and in manufacturing firms, the scenario is more complex in services. In fact, in services, the supplier by definition benefits from higher productivity levels, while this is not necessarily true for the client. In services, a trade-off may exist between productivity and quality, and clients’ satisfaction may be negatively correlated with high productivity from a supplier point of view. For example, by speeding up an operation, the operational productivity is increased. However, the customer’s perception of the service process can deteriorate, since he or she might feel “pushed” through a delivery process. In addition, standardized or automated processes might lead to customer dissatisfaction, as they might feel that their multiple needs are not being addressed adequately. Building on these arguments, Grönroos and Ojasalo (2004) suggest that service quality and service productivity should both be monitored. Buyer–supplier inseparability during service delivery requires the evaluation, along with the supplier’s use of internal resources and the way in which the customer participates in service production as an input factor (i.e. the internal efficiency), of service quality as well; hence, quality and productivity are correlated but not necessarily with a positive sign. The way in which service quality is perceived by the clients should be included in a service productivity measure as the output that the authors label “external efficiency”, which includes the output quality and quantity. Finally, services being perishable, capacity efficiency is also included in this productivity model. Grönroos and Ojasalo hence propose to define service productivity as a function of three measures: internal efficiency, external efficiency and capacity efficiency. This brief literature review shows that general considerations of services and productivity measures exist and are useful for a better understanding of the peculiarities of services as far as productivity is concerned. However, the

Productivity dilemma and digitalization

99

analysis of the three approaches also shows that so far neither innovativeness nor knowledge intensity are explicitly included in service productivity measurement concepts, leaving space for future avenues of research (Biege et al., 2013).

Productivity in KIBS In KIBS, the service outcome is intangible and the personal component plays a major role, since they are personnel intensive on both the customer side and the provider side. The more the human factor is involved, the more heterogeneous is the outcome of a service production process and, at the same time, the less standardized. Coherently with Grönroos and Ojasalo (2004), to measure the productivity of KIBS, the knowledge and information of service workers and of their clients both need to be considered as service inputs (Gnatzy, 2010). Furthermore, production and consumption cannot be separated: the outcome of service production does not depend only on the service worker but also on his or her counterpart on the customer side. Measuring the productivity of KIBS raises even more challenges than measuring the productivity of services if we intend to incorporate innovativeness and knowledge intensity into a productivity measurement model and recognize both innovation and knowledge as crucial inputs of the service design and delivery. Knowledge intensity is one of the main input factors in KIBS and is tightly correlated with the productivity of employees, clients and other knowledge partners. In this scenario, it is hard to quantify the existing productivity inputs. Furthermore, innovation is a distinct trait of KIBS. Part of the KIBS offer is composed at least partially of standardized services, but the interaction with clients has high levels of customization and innovation as a by-product. As experience shows, innovative services often require ad hoc factor inputs, such as knowledge or partners, and the newness of each project reduces KIBS firms’ productivity. Hence, productivity measures that disregard the innovativeness of the service risk being hostile to innovation by reporting unsatisfactory performance results. It is important to note that investments in innovations may not have a direct, positive impact on the output but are necessary to maintain competitiveness. Following both the manufacturing and the service literature, firms introduce new products to increase, or protect, their market share while introducing process innovations to be more competitive from the cost side and become more efficient (Garcia and Calantone, 2002; Sirilli and Evangelista, 1998). Consequently, to measure productivity adequately, it is important to distinguish between product and process innovations. Process innovations mainly concern internal process redesign and are pursued to foster a KIBS firm’s productivity at least in the medium to long run. In fact, it is a question not just of adequately recording productivity but also of finding starting points to increase it, so considering the role of innovations is essential as well as understanding when KIBS firms’ employees become familiar enough with the new technologies to use them to increase firms’ productivity.

100 Innovation and performance in KIBS This distinction recalls the difference between radical, and more destructive, innovations and incremental innovations that can positively affect firms’ performance more rapidly. Incremental innovations require a shorter development time and lower investments, and hence the risk perceived with such a new offering is limited. Both incremental product and incremental process innovations can positively affect firms’ performance as well as their productivity in the short run. More radical innovations can generate longer-lasting benefits for innovative firms but are more complex to introduce and require more investments and often relevant additional resources, thus having questionable effects on firms’ productivity, at least in the short run. Furthermore, it is not a simple task to measure the output of innovative services due to their intangibility and the “close connection between products and processes” (Hipp and Grupp, 2005, p. 525). Overall, the arguments given can be translated into several requirements for productivity measures of KIBS. First, the output of KIBS firms should be measured as the output delivered to the client in terms of quantity, quality and innovativeness. Second, the inputs considered in productivity measures should at least include the service provider’s own inputs and the customer’s inputs. Especially the time and costs induced by interactions with clients in developing knowledge-intensive services can be incorporated into productivity measurement. Third, the type of innovation (i.e. product vs. process innovation) and the innovativeness of the output have to be considered to measure productivity adequately. Innovativeness can be measured by differentiating services on the basis of their newness and/or differentness. Finally, as knowledge is the central resource used in KIBS, it needs to be included in a productivity measurement concept both as an input and as an output due to the fact that the service provision both requires and generates new knowledge. In this respect, typically studies about firms’ performance include control variables such as the percentage of employees with a degree or the number of external knowledge sources (see Chapter 4).

Service innovation and productivity: The empirical evidence The increased importance of services makes improving productivity in services a necessary ingredient for enhancing the aggregate productivity in many regions. However, the evidence on the extent to which innovation in services can contribute to improving productivity remains inconclusive, while studies in the field are still scant and at an early stage of development (Drejer, 2004; Evangelista, 2000; Gallouj and Weinstein, 1997). Furthermore, the heterogeneity of services and their immaterial nature makes the use of traditional indicators of innovation and productivity problematic; this limits the capacity to track improvements or changes in products or services. These difficulties are accrued by the use of different approaches to analyse the topic empirically, that is, the assimilation, demarcation and synthesis approaches, which still co-exist. De Fuentes et al. (2015) apply the synthesis approach and show a positive and significant impact of innovation performance in services on firms’ productivity,

Productivity dilemma and digitalization 101 coherently with previous studies for Latin America (Crespi and Zuñiga, 2012) and Europe (Griffith et al., 2006). The results are supported for both technological and non-technological innovation. This result confirms those by Crespi and Zúñiga (2012) and points out the existence of complementarities between technological and non-technological innovation that contribute to firms’ productivity. Musolesi and Huiban (2010) use French micro data and focus on the effect of innovation on firm productivity. Interestingly, they find that innovation is significantly and positively correlated with productivity. Innovation affects the productivity of KIBS firms, and the authors underline that the magnitude of this effect is comparable with that in other studies on manufacturing that adopt similar definitions and measures. Nevertheless, they find that only product innovation significantly affects the firm productivity while process innovation seems to be ineffective. However, when considering the results obtained in other studies that use different categories of innovation and differentiate between product and process innovations, they find mixed results. Regarding services, Mairesse and Robin (2009) find that both process innovation and product innovation affect productivity in both manufacturing and services, while Campagnolo and Cabigiosu (2015), studying Italian KIBS firms, show that only process innovations affect productivity, and Cainelli, Evangelista and Savona (2006) find that only process innovations correlate with firms’ performance. Overall, it seems that the previous results suggest that innovation can positively affect firms’ productivity, but these results still exhibit high variability in terms of the sign and magnitude of the effect of different types of innovation, that is, process vs. product innovations. This could be linked to the choice of the estimation method, and further investigations are necessary.

References Baumol, W.J. 1985. Productivity policy and the service sector. In: Inman, R.P. (Ed.) Managing the Service Economy: Prospects and Problems. Cambridge University Press, London, chap. 11, pp. 301–337. Bettiol, M., Di Maria, E. and Grandinetti, R. 2012. Codification and creativity: Knowledge management strategies in KIBS. Journal of Knowledge Management, 16(4), 550–562. Biege, S., Lay, G., Zanker, C. and Schmall, T. 2013. Challenges of measuring service productivity in innovative, knowledge-intensive business services. Service Industries Journal, 33(3–4), 378–391. Cainelli, G., Evangelista, R. and Savona, M. 2006. Innovation and economic performance in services: A firm-level analysis. Cambridge Journal of Economics, 30(3), 435–458. Campagnolo, D. and Cabigiosu, A. 2015. Innovation, service types, and performance in knowledge intensive business services. In: Agarwal, R., Selen, W., Ross, G. and Green, R. (Eds.) The Handbook of Service Innovation. Springer, London, pp. 109–121. Corsten, H. 1994. Produktivitätsmanagement bilateraler personenbezogener Dienstleistungen. In: Corsten, H. and Hilke, W. (Eds.) Dienstleistungsproduktion. Betriebswirtschaftlicher Verlag, Th. Gabler, Wiesbaden, pp. 43–77. Crespi, G. and Zuñiga, P. 2012. Innovation and productivity: Evidence from six Latin American countries. World Development, 40(2), 273–290.

102 Innovation and performance in KIBS De Fuentes, C., Dutrenit, G., Santiago, F. and Gras, N. 2015. Determinants of innovation and productivity in the service sector in Mexico. Emerging Markets Finance and Trade, 51(3), 578–592. Drejer, I. 2004. Identifying innovation in surveys of services: A Schumpeterian perspective. Research Policy, 33(3), 551–562. Di Maria, E., Grandinetti, R. and Di Bernardo, B. (Eds.) 2012. Exploring KnowledgeIntensive Business Services. Knowledge Management Strategies. Palgrave, Cheltenham. Evangelista, R. 2000. Sectoral patterns of technological change in services. Economics of Innovation and New Technologies, 9, 183–221. Gallouj, F. and Weinstein, O. 1997. Innovation in services. Research Policy, 26(4–5), 537–556. Garcia, R. and Calantone, R. 2002. A critical look at technological innovation typology and innovativeness terminology: A literature review. Journal of Product Innovation Management, 19(2), 110–132. Gnatzy, T. 2010. Performance Measurement von Dienstleistungsinnovationen. In: Gleich, R. and Klein, A. (Eds.). Controlling von Dienstleistungen. Haufe Mediengruppe, Freiburg, pp. 63–78. Griffith, R., Huergo, E.Mairesse, J. and Peters, B. 2006. Innovation and productivity across four European countries. Oxford Review of Economic Policy, 22(4), 483–498. Grönroos, C. and Ojasalo, K. 2004. Service productivity: Toward a conceptualisation of the transformation of inputs into customer value in services. Journal of Business Research, 57(4), 414–423. Hipp, C. and Grupp, H. 2005. Innovation in the services sector: The demand for services specific innovation measurement concepts and typologies. Research Policy, 34, 517–535. Johnston, R. and Jones, P. 2004. Service productivity: Towards understanding the relationship between operational and customer productivity. International Journal of Productivity and Performance Management, 53(3), 201–213. Levitt, T. 1972. Production-line approach to service. Harvard Business Review, September–October, 41–52. Mairesse, J. and Robin, S. 2009. Innovation and productivity: A firm-level analysis for French manufacturing and services using CIS3 and CIS4 data (1998–2000 and 2002–2004). CREST-ENSAE, Paris. Musolesi, A. and Huiban, J.P. 2010. Innovation and productivity in knowledge intensive business services. Journal of Productivity Analysis, 34(1), 63–81. Reckenfelderbäumer, M. 2008. Der Einfluss von Immaterialität und Kundenmitwirkung auf das Produktivitätscontrolling bei Dienstleistungen- Dargestellt am Beispiel von Weiterbildungsleistungen. Controlling, 20(8/9), 415–412. Rullani, E. 2014. Manifattura in transizione. Sinergie, rivista di studi e ricerche, 93 (January– April), 141–152. Sirilli, G. and Evangelista, R. 1998. Technological innovation in services and manufacturing: Results from Italian surveys. Research Policy, 27(9), 881–899.

8

A critical view How much do collaboration and customization support KIBS firms’ innovative performance?

There may be another “face of the coin” for both the customization and the engagement of clients in innovation activities, and KIBS firms may combine different levels of customization and collaboration with clients. This chapter presents the theoretical arguments and empirical evidence provided so far that question the emphasis on client collaboration and KIBS customization, delivers new hypotheses about how KIBS firms should design their service portfolio and client relationships and concludes by introducing the topic of mass customization in KIBS.

Client collaboration and KIBS firms’ innovativeness The collaboration with clients and service customization are distinctive attributes of KIBS and affect their capacity to develop new services successfully. The relations between firms and their clients affect the firms’ capabilities of screening the external environment and transferring tacit knowledge. The role of customers is widely recognized as an antecedent to innovation (Rosenberg and Nathan, 1982), showing that users have a crucial role in invention, prototyping and field testing (von Hippel, 1976). Similarly, other studies analyse the role of user involvement. For example, Laursen and Salter (2006) provide data showing that “suppliers” and “clients or customers” are the two most important external sources of innovation among UK firms. In their survey, 66% of manufacturing firms indicated clients or customers as a source of knowledge or information for innovation, and 16% indicated that they are a very relevant source. In addition, marketing scholars are broadly supportive of the link between market orientation and various innovation measures (Han, Kim and Srivastava, 1998; Hurley and Hult, 1998; Lukas and Ferrell, 2000; Narver and Slater, 1990). Therefore, it is clear that the relationship with customers has a central role both in scanning the external environment and evaluating innovation opportunities and in acquiring valuable, complex and tacit knowledge through tight interactions with them.

104 Innovation and performance in KIBS The quality of interaction with clients varies with the strength of these ties. In arm’s length ties, which require little investment in time or mutual obligations, firms can maintain many relationships with clients. These types of partnerships are useful to collect generic information that is stored unevenly among multiple clients in the market: clients are a useful gateway to be aware of existing products or services offered by competitors and emerging business opportunities. On the contrary, tight relationships with clients permit the transfer of more idiosyncratic, tacit and complex knowledge but also require more time and resources. Typically, relationships with clients are managed via formal contractual arrangements and with limited investments in coordination and integration mechanisms. These transactions enable firms to enhance their current competencies and systems rather than restructuring them (Uzzi, 1996; Uzzi and Lancaster, 2003). On the contrary, in closer interactions, clients exchange knowledge with partners via tight coordination mechanisms that permit them to experiment jointly with new ideas. Therefore, we often observe that the learning process is functional to the type of relationship with clients. While arm’s length relationships enhance the access to information that is unevenly distributed in the market and the firms’ ability to monitor and scan the environment, more embedded relationships with clients reduce their capacity to be a source of heterogeneous information but also increase the transfer of complex and valuable knowledge and, in time, decrease the cost of learning and experimenting with new opportunities with these partners. For these reasons, a combined type of interaction with clients creates forms of learning that pool the advantage of heterogeneous selection and the capacity to learn from them. Coherently, the literature suggests that customers’ involvement in firms’ innovation processes might have a bright and a dark side. While firms’ openness to their external environment can improve their ability to identify new opportunities (Katila and Ahuja, 2002), previous search strategies can generate path dependency and might constitute an investment that influence the firms’ capacity to identify and use new information from outside (Andersson, Forsgren and Holm, 2001). Therefore, too embedded a relationship with clients might reduce firms’ knowledge heterogeneity and hence their problem-solving ability in product innovation. Furthermore, dependence on clients may be dysfunctional when firms fear clients’ opportunistic behaviour. The dark side of clients’ embeddedness may hinder firms’ ability to adapt their offer to the market needs effectively. Only a few studies investigate how to cope with this dark side, considering the management of the relationships with clients (Noordhoff et al., 2011) or at the nature of the knowledge that they hold (Bonner and Walker, 2004). Noordhodd et al. (2011) analyse the length and formalization of the relationships with clients and the relationship-specific investments with them, while Bonner and Walker (2004) focus on the heterogeneity of knowledge bases between client and supplier. The analysis of these contributions suggests that the effective management of clients’ collaboration should couple relationship management issues and knowledge management issues to cope with clients’

A critical view 105 dependence, main dysfunctionalities, opportunism and lack of knowledge heterogeneity as well as with their interaction and cumulative effects. Overall, as Laursen and Salter (2006) show, too great a depth of relationships with clients might have an inverse U-shaped correlation with firms’ innovativeness (see Figure 8.1). While client collaboration is beneficial to access information on the market and to transfer external complex and tacit knowledge, overemphasis on it may generate dependency on them as a source of external knowledge as well as opportunistic behaviours. Further studies are needed to test empirically the hypothesis described in Figure 8.1 in the specific context of KIBS.Figure 8.1 The dark and bright side of the buyer–supplier relationship in KIBS: KIBS firm’s innovativeness has an inverted U-shaped relationship with client collaboration.

Client collaboration, customization and KIBS firms’ innovative performance The KIBS literature emphasizes that collaboration with clients and service customization are quite diffused and relevant to both p-KIBS and t-KIBS. P-KIBS and t-KIBS are quite similar when considering the importance of customers as an external source of innovation (Freel, 2006). Particularly, the interaction with clients and the customization of services are crucial for innovative p-KIBS firms (Freel, 2006; Landry, Amara and Doloreux, 2012). Nevertheless, as already discussed, both the customization and the engagement of clients in innovation activities may have a bright and a dark side. Furthermore, KIBS firms may combine different levels of collaboration and customization with customers. First, KIBS firms face the challenge of balancing the need to adapt their service to specific clients’ needs and the need to serve several clients with the same offer (Sundbo, 2002). There is tension between the need to meet specific user requirements, which forces firms to seek a high degree of customization and adaptation in their service, and the need to reduce the costs of services, which leads firms to search for increasing standardization. This tradeoff can be solved by relying on a mix of configurations of the service, which can be standard or modular and not only fully customized (Pekkarinen and Ulkuniemi, 2008; Sundbo, 1994). KIBS firms can rely on a mix of service configurations that display different levels of service personalization. In this respect, KIBS firms should positively evaluate both standard and modular service configurations that introduce some degree of standardization. As also discussed in Chapter 6, levels of service customization that are too high compromise the possibility to replicate firms’ innovative efforts in multiple supply relationships and may absorb firms’ resources without providing a proportional benefit to their growth (Cabigiosu et al., 2015). Second, although several authors argue that service customization drives KIBS firms’ service innovation efforts and for this reason service customization is interlinked with service innovation (Hipp, Tether and Miles, 2000), other studies demonstrate that the correlation between service customization and

106 Innovation and performance in KIBS service innovation is not that strong, indicating that service providers that systematically customize their offer are not more innovative than service providers with a higher share of standard services (Tether et al., 2001). Furthermore, over a certain threshold, overemphasis on clients can compromise firms’ innovativeness (Li Pira, Cabigiosu and Campagnolo, 2017). Interestingly, Love and Mansury’s (2007) empirical results show that service customization and firms’ innovation are negatively related, while firms that have more standardized offerings tend to be more innovative. The authors also suggest that standardization helps innovating firms in spreading the cost of developing new services over more production levels, thus increasing their competitiveness. Third, the level of KIBS firms’ collaboration with customers provides a proxy for evaluating the extent to which KIBS firms draw from this source when they are willing to introduce new technologies, products and processes. In other words, firms’ collaboration with clients reflects the relevance of the use of customers to the development of innovations in KIBS. KIBS firms often transfer tacit and explicit knowledge from and to client organizations (Leiponen, 2006) and develop ad hoc specific solutions for their clients (Miles, 2008; Tether and Hipp, 2002). During this process, it is common for KIBS firms and customers to interact in tightly coupled relationships. Hence, KIBS firms that are willing to develop collaborative relationships with clients should also learn how to manage such relationships and make specific investments to build up an understanding of the norms and routines of each client, thus diverting KIBS firms’ resources from other valuable relationships with other partners, such as suppliers or research centres. KIBS firms should be aware of this trade-off between making high investments in their relationships with clients and maintaining high levels of openness and relationships of knowledge sharing with a variety of actors, not only with clients (Becheikh, Landry and Amara, 2006; Hipp, 1999; Hitt et al., 2001; Muller and Zenker, 2001). When KIBS firms are overdependent on clients for innovation, then the clients might close other windows of opportunity for new ideas and technological and market innovations (Katila and Ahuja, 2002; Laursen and Salter, 2006). Overall, overreliance on clients may generate negative consequences for the relationship between product innovation and growth. Both customization and clients’ importance as a source of relevant knowledge improve KIBS firms’ comprehension of clients’ needs. However, nurturing tight relationships with clients as drivers of innovation, coupled with service customization, requires relevant resources and pushes KIBS firms to develop strategies suited to specific clients, thus limiting their available attention for other types of partnership and services that can be valuable for multiple clients without customization. KIBS firms risk focusing too much on their actual customers, thus reducing the market share potential of their innovative efforts. Consequently, when an innovative KIBS firm relies too much on both client collaboration and customization, it may grow less, because it follows a niche strategy. KIBS firms that are able to moderate the levels of service customization and collaboration with

A critical view 107 clients are more likely to design new services that satisfy a higher number and variety of clients and, at the same time, have additional resources to build other partnerships and sustain additional innovation and growth. Cabigiosu and Campagnolo (2019) test these hypotheses empirically using data from 98 KIBS firms in the Veneto region (Italy). Using these data, the authors analyse how innovation, clients’ collaboration and customization all together affect KIBS firms’ performance. In this study, innovation is measured by counting the number of “product innovations new to the firm”, “product innovations new to the industry”, “process innovations new to the firm” and “process innovations new to the industry” in the period 2006–2008 (Mansury and Love, 2008; Therrien, Doloreux and Chamberlin, 2011). The dependent variable is “sales growth”, measured as the percentage of growth from 2007 to 2009. The results show that, in KIBS firms, “product innovations new to the industry” are the type of innovation that is more strongly associated with growth. Then the authors use two dummy variables that signal lower and higher than the median levels for the variables “clients’ collaboration” and “service customization” to study how the relationship between “product innovations new to the industry” and “sales growth” changes for different combinations of client collaboration and service customization. The authors multiply the variable “product innovations new to the industry” and each dummy variable, obtaining four possible combinations: product innovations new to the industry for service customization and client collaboration that are both higher than the median, product innovations new to the industry for service customization and client collaboration that are both lower than the median, product innovations new to the industry for high levels of customization and low levels of collaboration, and product innovations new to the industry for low levels of customization and high levels of collaboration. Table 8.1 synthesizes the results obtained and shows that “product innovations new to the industry” are positively correlated with “sales’ growth” only when “clients’ collaboration” and “service customization” are both lower than the median, suggesting that overemphasis on both client–supplier collaboration and customization turns out to be limiting to firms’ growth. Table 8.1 The relationship between “product innovations new to the industry” and “sales growth” for different combinations of the variables “clients’ collaboration” and “service customization”. Client’s collaboration

Service customization Higher than the median Higher than the median Lower than the median

Lower than the median Product innovation new to the industry has a negative effect on KIBS firm’s growth Product innovation new to the industry has a positive effect on KIBS firm’s growth

108 Innovation and performance in KIBS

KIBS firm’s innovativeness

Collaborations are likely to absorb the majority of KIBS firms’ resources and, when promoting customer-specific service solutions, they cannot be replicated in other supply relationships. The positive relationship between firms’ performance and highly innovative products is confirmed only for those KIBS firms that display comparatively lower levels of client collaboration and service customization. Interestingly, the authors also find a negative correlation between highly innovative products and growth in those KIBS firms that depend more on customer collaboration but have a smaller percentage of customized services. These results suggest that KIBS firms that maintain relevant collaboration with customers but, at the same time, do not customize their offer could lose such partners. The results do not show any effect in KIBS firms that sell more customized services, regardless of how tight the client–supplier relationships are. These results are overall confirmed for both p-KIBS and t-KIBS but are stronger for t-KIBS. This category of KIBS benefits more from internal R&D investments and suffers more than p-KIBS when relying on a strategy that merges high levels of collaboration with clients and customization. These results suggest that the general assumption about the positive relationship between service innovation and performance is more complex and multifaceted than expected. In KIBS firms, innovation strategies might have controversial results for growth depending on the type of innovations, the level of service customization and client–supplier collaboration. Although the literature emphasizes the concept that collaboration with clients and customization are the pillars of KIBS firms’ business model, this chapter contributes to a more in-depth comprehension of their joint effect. Following the mainstream KIBS literature, we would have foreseen that the KIBS firms with higher growth would be those that innovate, combining tight collaboration with clients and high service customization. Meanwhile, the results show that the firms that grow the most are those maintaining relationships with customers that are focused on a few areas and have in their portfolio some forms of service standardization (e.g. they combine customized, modular

Clients’ collaboration

Figure 8.1

A critical view 109 and standard services). Particularly, and coherently with previous results in the strategic management literature (Laursen and Salter, 2006), KIBS firms that expand the number of areas of collaboration with clients over the median lose the positive effect of innovations on growth, which in turn becomes negative. Collaboration with customers is a positive input for the innovation process of KIBS, but it also absorbs resources and diverts KIBS firms’ attention away from other valuable sources. Especially in a small KIBS firm, service customization absorbs human resources’ attention and limits the search for new market opportunities via the enlargement of the customer base or the replication of a standard solution. Furthermore, when a KIBS firm collaborates with its clients, it collects valuable information and eventually shares tacit knowledge, but these resources may be of value only within that relationship to develop client-specific solutions with limited chances to match such solutions to other business opportunities. Put differently, clients are relevant partners but should not be the main or unique source of knowledge. The more KIBS firms depend exclusively on clients’ specific instances, the more such a degree of dependence can eventually contrast the KIBS firms’ growth when they develop competences and services that partially lose their value outside those specific client relationships. Indeed, the best-performing KIBS firms are those that replicate their innovations developed with a specific client for other clients (Miozzo et al., 2016). Successfully leveraging past supply relationships to increase firms’ growth demands the ability to differentiate between client relationships that nurture firms with knowledge that has broad market potential and can foster firms’ growth and those relationships that generate only client-specific knowledge and problem-solving competences. These clients should not become exclusive points of reference. To grow, firms need to use a portfolio approach and balance the managerial attention and resources dedicated to specific partnerships with clients with the resources dedicated to other partners and to develop resources that are valuable within multiple buyer–supplier relationships (Campagnolo and Cabigiosu, 2015). The enthusiasm for customer– supplier collaborations should be tempered by envisioning their possible negative effects: the development of an excessive number of customized solutions limits firms’ market opportunities. Future studies could deepen our understanding about the interplay between innovation, buyer–supplier collaboration and customization by collecting empirical data in other regional innovation systems across different regions, investigate how multiple types of innovation interact in a portfolio approach and deepen the analysis in different categories of KIBS.

References Andersson, U., Forsgren, M. and Holm, U. 2001. Subsidiary embeddedness and competence development in MNCs: A multi-level analysis. Organization Studies, 22(6), 1013–1034.

110 Innovation and performance in KIBS Becheikh, N., Landry, R. and Amara, J. 2006. Lessons from innovation empirical studies in the manufacturing sector: A systematic review of the literature from 1993–2003. Technovation, 26(5/6), 644–664. Bonner, J.M. and Walker Jr, O.C. 2004. Selecting influential business‐to‐business customers in new product development: Relational embeddedness and knowledge heterogeneity considerations. Journal of Product Innovation Management, 21(3), 155–169. Cabigiosu, A. and Campagnolo, D. 2019. Innovation and growth in KIBS: The role of clients’ collaboration and service customization. Industry and Innovation, 26, 592–618. Cabigiosu, A., Campagnolo, D., Furlan, A. and Costa, G. 2015. Modularity in KIBS: The case of third-party logistics service providers. Industry and Innovation, 22(2), 126–146. Campagnolo, D. and Cabigiosu, A. 2015. Innovation, service types, and performance in knowledge intensive business services. In: Agarwal, R., Selen, W., Ross, G. and Green, R. (Eds.) The Handbook of Service Innovation. Springer, London, pp. 109–121. Freel, M. 2006. Patterns of technological innovation in knowledge-intensive business services. Industry and Innovation, 13(3), 335–358. Han, J.K., Kim, N. and Srivastava, R.K. 1998. Market orientation and organizational performance: Is innovation a missing link? Journal of Marketing, 62(4), 30–45. Hipp, C. 1999. The role of knowledge-intensive business services in the new mode of knowledge production. AI & Society, 13(1), 88–106. Hipp, C., Tether, B. and Miles, I. 2000. The incidence and effects of innovation in services: Evidence from Germany. International Journal of Innovation Management, 4(4), 417–453. Hitt, M.A., Bierman, L., Shimizu, K. and Kochhar, R. 2001. Direct and moderating effects of human capital on strategy and performance in professional service firms: A resource-based perspective. Academy of Management Journal, 44(1), 13–28. Hurley, R.F. and Hult, G.T.M. 1998. Innovation, market orientation, and organizational learning: An integration and empirical examination. Journal of Marketing, 62(3), 42–54. Katila, R. and Ahuja, G. 2002. Something old, something new: A longitudinal study of search behavior and new product introduction. Academy of Management Journal, 45(6), 1183–1194. Landry, R., Amara, N. and Doloreux, D. 2012. Knowledge exchange strategies between KIBS firms and their clients. Service Industries Journal, 32(2), 291–320. Laursen, K. and Salter, A. 2006. Open for innovation: The role of openness in explaining innovation performance among UK manufacturing firms. Strategic Management Journal, 27(2), 131–150. Leiponen, A. 2006. Organization of knowledge exchange: An empirical study of knowledge-intensive business service relationships. Economics of Innovation and New Technology, 15(4/5), 443–464. Love, J.H. and Mansury, M.A. 2007. External linkages, R&D and innovation performance in US business services. Industry and Innovation, 14(5), 477–496. Lukas, B.A. and Ferrell, O.C. 2000. The effect of market orientation on product innovation. Journal of the Academy of Marketing Science, 28(2), 239–247. Mansury, M.A. and Love, J.H. 2008. Innovation, productivity and growth in US business services: A firm-level analysis. Technovation, 28(1–2), 52–62. Miles, I. 2008. Patterns of innovation in service industries. IBM Systems Journal, 47(1), 115–128. Miozzo, M., Desyllasb, D., Lee, H. and Miles, I. 2016. Innovation collaboration and appropriability by knowledge-intensive business services firms. Research Policy, 45(7), 1337–1351. Muller, E. and Zenker, A. 2001. Business services as actors of knowledge transformation: The role of KIBS in regional and national innovation systems. Research Policy, 30(9), 1501–1516. Narver, J.C. and Slater, E.S. 1990. The effect of a market orientation on business profitability. Journal of Marketing, 54, 20–35.

A critical view 111 Noordhoff, C.S., Kyriakopoulos, K., Moorman, C., Pauwels, P. and Dellaert, B.G. 2011. The bright side and dark side of embedded ties in business-to-business innovation. Journal of Marketing, 75(5), 34–52. Pekkarinen, S. and Ulkuniemi, P. 2008. Modularity in developing business services by platform approach. International Journal of Logistics Management, 19(1), 84–103. Rosenberg, N. and Nathan, R. 1982. Inside the Black Box: Technology and Economics. Cambridge University Press, Cambridge, UK. Sundbo, J. 1994. Modulization of service production and a thesis of convergence between service and manufacturing organizations. Scandinavian Journal of Management, 10(3), 245–266. Sundbo, J. 2002. The service economy: Standardisation or customisation? Service Industries Journal, 22(4), 93–116. Tether, B.S. and Hipp, C. 2002. Knowledge intensive, technical and other services: Patterns of competitiveness and innovation compared. Technology Analysis & Strategic Management, 14(2), 163–182. Tether, B. S., Hipp, C. and Miles, I. 2001. Standardisation and particularisation in services: evidence from Germany. Research Policy, 30(7), 1115-1138. Therrien, P., Doloreux, D. and Chamberlin, T. 2011. Innovation novelty and (commercial) performance in the service sector: A Canadian firm-level analysis. Technovation, 31(12), 655–665. Von Hippel, E. 1976. The dominant role of users in the scientific instrument innovation process. Research Policy, 5(3), 212–239. Uzzi, B. 1996. The sources and consequences of embeddedness for the economic performance of organizations: The network effect. American Sociological Review, 61, 674–698. Uzzi, B. and Lancaster, R. 2003. Relational embeddedness and learning: The case of bank loan managers and their clients. Management Science, 49(4), 383–399.

Part IV

Moving the innovation model in KIBS forward

9

Digitalization and internationalization in KIBS

KIBS firms traditionally focus on a local market and base their competitive advantage on clients’ proximity. This chapter discusses the role of internationalization in KIBS, emphasizing how digital technologies are opening new opportunities for KIBS, especially t-KIBS, and identifying possible threats.

Internationalization in KIBS and its drivers KIBS tend to be concentrated geographically in metropolitan areas and in regional innovation systems (Doloreux, Freel and Shearmur, 2010). Spatial proximity plays a relevant role in explaining the growth and survival of KIBS firms. First, the presence of a large number of businesses within a limited space generates a high demand for business services and a supply dedicated to satisfying the specificities of the local demand. Each region has specific manufacturing traditions, present manufacturing districts or clusters that require business services targeted to support these industries. Second, KIBS are services characterized by a high level of customization achieved by collaborating with clients. Consequently, geographical proximity enables face-to-face interactions and socialization with clients that in turn prompt the sharing of more complex and tacit knowledge. Furthermore, several facets of KIBS, such as norms regulating their content in professional services or the cultural attributes dominating many marketing services, promote physical proximity, which is a proxy for competences’ fit with the external environment of service providers. Finally, KIBS are on average micro-firms with limited resources, for which proximity and closeness to clients are a natural strategy, while internalization and growth require different resource endowments. Despite this scenario, in recent years, we have observed growing importance of internationalization and trade in services in the global economy. Interestingly, the recent findings show that, while services are still less traded than products, knowledge intensive services are gaining importance and becoming more relevant for developing countries (Klimek, 2018). Trade in KIBS is growing as companies gravitate more and more to service offshoring, as it may increase their international competitiveness and the total value of their business (Wirzt, Tuzovic and Ehret, 2015; Wyszkowska-Kuna, 2017).

116 Moving the innovation model in KIBS forward The internationalization of KIBS firms is also increasing. Corrocher, Cusumano and Morrison (2012) describe two distinct business models well. Smaller KIBS competing on price and the speed of service delivery focus on highly localized markets. These firms offer mainly legal, accounting, architecture and engineering services. Given the highly intangible nature and the high degree of customization of the activity performed by these professional services, the proximity to customers and the institutional environment are extremely important. The second business model is that of t-KIBS, which are on average larger, compete on quality and reputation, and serve a relatively more distant market. Long-distance relationships are easier for technologyintensive firms, because codified knowledge prevails and they do not need very close contact with clients. Part of the KIBS literature also looks at the internationalization of KIBS firms’ partnerships. The diversity of knowledge deriving from international collaborations is highly useful, as firms can generate new ideas and innovations. More innovative firms can compete better and thus become more internationalized, because innovations allow firms to enter new markets and because internationalization facilitates access to inputs that are not available in domestic markets. Exports are positively associated with knowledge accumulation and innovation activities. Alliances also allow KIBS firms to ease and accelerate the internationalization process by providing them with access to partners’ resources and the capabilities that they need for both international operations and innovation, thus generating a virtuous cycle between cooperation and innovation as the antecedents of successful internationalization and growth (Braga, Marques and Serrasqueiro, 2017). Past research has demonstrated that innovation is directly linked to internationalization (Di Maria et al., 2012). Larsen’s (2001) analysis of a sample of Danish service firms shows a positive relation between high levels of internationalization and high levels of innovation activity. Czarnitzki and Spielkamp (2003), studying German business service firms, find that firms with a more structured and continuous approach to innovation have significantly better export performance than firms that do not innovate or undertake R&D. Studying service firms in Europe, Tether (2003) concludes that innovating firms, especially KIBS firms, also pursue the opening of new markets. Based on a quantitative analysis, Toivonen and Tuominen (2009) discover that innovative KIBS try to replicate their service offer in many supply relationships, even abroad. Rodriguez and Nieto (2010) find a positive relationship between cooperation, innovation and internationalization of KIBS. Braga et al. (2017), by analysing Portuguese KIBS, confirm the relevance of innovation to internationalization. Furthermore, KIBS that establish collaborative relationships gain easier access to international markets and improve their innovation capability. Thus, all these studies suggest the existence of relevant complementarities between KIBS firms’ cooperation with external partners, innovation capability and internationalization. In particular, innovation fosters internalization.

Digitalization and internationalization

117

Di Maria et al. (2012) explain well the mechanisms through which innovation, partnerships and internationalization interact. The authors show that the majority of the KIBS firms that they interviewed (68.6%) have clients that cross regional borders. Particularly, the authors, by studying KIBS firms in the Veneto region, show that two mutually reinforcing processes, namely innovation capability and networking, are positively related to KIBS firms’ market extension. The capability of KIBS firms to innovate pushes customer relationships outside the local context. At the same time, by extending the market, KIBS firms can benefit from further partnerships and different knowledge sources that reinforce their innovation capability. The positive relationship between network extension and market extension also suggests that KIBS firms with distant customers might be interested in selecting partners operating near to the customers’ location. However, other studies suggest that we still need to deepen our understanding of different regional dynamics and of the link between internationalization and innovation in KIBS. Wong and He (2005) study KIBS firms in Singapore and find that only 16.4% of KIBS firms’ turnover is from abroad and that they are less likely to have overseas partners for innovation collaboration than manufacturing firms. Interestingly, they show a U-shaped pattern of innovation collaboration with geographic distance for both KIBS and manufacturing firms. These KIBS also rate frequent personal contact and good knowledge of clients’ industry as important factors for the successful provision of innovation support for manufacturing clients, and, although “location close to the client” seems to be less important, most KIBS firms’ manufacturing clients are indeed located in Singapore. The authors find that the importance of spatial proximity between KIBS firms and their clients varies over different phases of innovation development and is central to market analysis and problem diagnosis. The results listed indicate that social capital, such as shared language/jargon, an overlapping knowledge structure and personal connections, is critical for KIBS firms’ successful innovation support for manufacturing clients. Following this logic, spatial proximity may be necessary to develop such social capital, but its importance may vary over different phases of innovation development. Rodríguez, Nieto and Santamaría (2018) look at the reverse relationship – that is, that of internationalization with innovation – and show that the impact of international collaboration on innovation performance is different for p-KIBS and t-KIBS. For p-KIBS, collaboration with “closer” partners produces the greatest impact on service innovations, suggesting the importance of direct interaction and similarity of knowledge in international collaborations. This result supports the “closeness” argument for professional service firms: greater spatial proximity to partners brings with it greater proximity in terms of rules, laws, culture, norms and habits, which all positively affect firms’ performance. For tKIBS, the situation is different, with international collaboration with diverse organizations having the greatest impact on innovation performance. These results reveal that collaborating with diverse partners from distant countries will

118 Moving the innovation model in KIBS forward produce the biggest impact on t-KIBS firms’ levels of knowledge and innovation performance. These results may be explained by the fact that the portion of codified knowledge in t-KIBS is usually larger and easier to share with partners from distant countries that possess more heterogeneous knowledge. This result is in line with Consoli and Elche-Hortelano’s (2010) description of t-KIBS as more standardized and less context-dependent services. Overall, KIBS, mainly t-KIBS, are facing a period of growth that is also pursued by opening their boundaries to international clients, partners and foreign investments. In this scenario, digital technologies play a major role.

Digitalization and internationalization: Opportunities and threats Traditionally, technologies have served as tools to improve production processes and increase products’ innovative content. Advances in digital technology have now opened tremendous opportunities for service production, innovation and delivery. This phenomenon is called digitalization and refers to “the encoding of analog information into digital format and the subsequent reconfiguration of socio-technical context of production and consumption of the product and services” (Yoo, 2012). Digitalization allows the codification of firms’ knowledge into bits for multiple purposes. First, this codified knowledge can be the input for modern machines, mainly PCs, and can be used to manage increasingly complex problem-solving activities. Software is an example of how codified knowledge can be used to increase computers’ functionalities or to govern robots. Second, knowledge, services and even artefacts are translated into bits and, once digitized, can be stored, replicated and shared across multiple geographical locations. In this respect, digital technologies ease the scalability and transferability of services. The Intranet is a place where firms can share their knowledge. Third, actors along the value chain can collaborate and communicate via digital tools and shared and free platforms, such as Skype, through which they can exchange feedback and socialize their knowledge. IBM and Siemens are examples of firms using Web-based platforms that allow for mass collaboration across business sectors and geographical borders. These platforms support focused online discussions that allow people to rapidly share, expand, elaborate on and select ideas on specific topics. For example, between 2009 and 2010, Siemens used the Intranet to support the debate and problem solving around two topics, related to antipiracy and how future information technologies might influence the way in which Siemens conducts its business between its employees around the world. New technologies also ease international collaborations, through which firms can share information with partners from different countries, producing benefits by increasing the variety of knowledge and thereby the likelihood of boosting innovation performance (Rodan and Galunic, 2004). Overall, digitalization is a socio-technical transformation that affects knowledge codification, usability, scalability, transferability and how people can share

Digitalization and internationalization

119

their knowledge. KIBS are services of which the characteristics are tightly related to the digital revolution. They are knowledge intensive services. Every time knowledge can be codified and shared, this increases KIBS’ portability and KIBS firms’ productivity. KIBS firms are also problem solvers that tightly collaborate and interact with clients to produce their services. In this respect, digital technologies provide additional means to interact with clients. While the close interaction with clients was a constraint for KIBS firms’ internationalization in the past, today digital technologies offer new opportunities: KIBS can more easily transfer their knowledge and interact with distant clients. ADP is an example of a firm that shows how digital technologies can support KIBS firms’ growth and internationalization. ADP was founded in 1949 in Roseland, USA, as Automatic Payrolls Inc., the first company to provide payroll services to companies. At the time, payrolls were processed manually, but when Automatic Payrolls Inc. became Automatic Data Processing (ADP) in 1956, the manual processing was replaced by more automated management of the entire process. In 1961, ADP entered the stock exchange and started a global expansion. Today, ADP operates in 140 countries with a staff of about 55,000 direct employees who manage 630,000 customers worldwide, delivering the following services: human resource administration, which includes services such as payroll, budget and labour costs, absence and shift and holiday plans; human resource management, which includes services such as performance management, talent management, selection and salary review; and a human resource portal, which mainly includes service analytics, reporting and mobile services. This set of services represents a modular offer that allows clients to purchase their preferred mix of services. Interestingly enough, ADP gives customers the possibility to buy these modules using different options. First, clients can buy a selection of these services from the Cloud (SaaS, Software as a Service), obtaining access to the platform and carrying out the entire process independently. Thanks to cloud technology, customers use the ADP solutions autonomously. ADP guarantees evolutionary maintenance of the product and regulatory updates through a high-level technical infrastructure. Second, at the managed service level, clients maintain the advantages and flexibility of the Cloud while delegating the processing, control and certification of the pay slips to ADP. In this way, customer companies obtain the maximum flexibility of use with the minimum responsibility. ADP is responsible for the correctness of employees’ pay slips. Finally, all human resources and personnel administration activities are outsourced: the input, processing, control and certification of the processes are the full responsibility of ADP. Through the analyses carried out by ADP, customers are able to monitor the performance of the main indicators and remain in contact with their employees through the HR portal. The success and rapid expansion of this business model is rooted in cloud technology. The Cloud allows firms to store, access and reuse knowledge and services, and it eases the continuous updates of software. Furthermore, the Cloud is a technology that is largely accessible not only by large multinationals but also by SMEs. Today, many ERP (enterprise resource planning) systems

120 Moving the innovation model in KIBS forward rely on the Cloud to serve small firms, which can finally afford these services. In the past, personnel services were managed either by installing expensive programs in the servers of each client company and supporting the personnel in learning how to use the system or by outsourcing the services. Now, instead, the Cloud allows the client and the supplier to share common technologies, knowledge and skills, which can be standardized and made easily available to customers. Digital technologies also suggest that internationalization in KIBS can be pursued diversely. Often advertising and consulting firms become multinational firms and make investments abroad by opening new offices. Foreign direct investments increase the closeness to foreign clients but are also more expensive and riskier. Professional firms mainly rely on networking by signing an agreement with foreign partners and by hiring third parties to manage special projects. In this respect, digital technologies provide the tools to manage relationships with distant partners and can be used in specific and temporary projects that do not require greenfield investments. Market research firms balance the two by either being multinational or having external partnerships, while ICT firms mainly develop standard global products (or platforms) and rely on international suppliers, as in the ADP case. In this case, digital technologies are the enabling technologies that support the service storage, delivery and reuse worldwide. Other studies emphasize that knowledge codification and the role of network technologies can also help KIBS to manage customer relationships at a distance, with potentially positive implications in terms of internationalization (Miozzo and Soete, 2001). Finally, KIBS firms also serve foreign clients in their home country when they support clients’ internationalization process (Rubalcaba and Toivonen, 2015), as in the VEASYT case described in Chapter 2. In their extended analysis of the internationalization of services, Miozzo and Miles (2002) stress the role of intangible assets of services in terms of competence and skill acquisition as well as management across boundaries. From this point of view, KIBS with higher capabilities in organizing internal (and external) resources and competences oriented toward innovation are also more international than other KIBS. The previous paragraphs emphasize that KIBS, mainly t-KIBS, are looking to international markets with more interest and that digital technologies are supporting their strategies. While this scenario opens many commercial opportunities, it also highlights a number of criticalities. Employees and users are required to be digitally literate in navigating the digital environment. KIBS firms are often smaller than their clients, but, while the majority of KIBS employees are graduates, this percentage is definitively lower for clients’ firms, thus generating a problem concerning the competences required to use the new technologies that are often involved in the delivery and provision of the service. Bigger problems may also arise when we look at the availability of the infrastructures in many developing countries, such as the fibre-optic Internet. Furthermore, while technologies put two managers in contact immediately, they do not help in managing other types of distance such as cultural distance and different norms between countries, which require specific investments and

Digitalization and internationalization

121

preparation to be managed carefully. Today, managers can transact with the support of interpreters rented online and ad hoc for a specific meetings, but technologies do not provide all the competences needed to co-develop services with distant clients. In this respect, it becomes clear that ICT services, which rely on more codified knowledge and standardized services, are those that can benefit the most from the synergies between internationalization and digitalization. Finally, we still lack studies that focus on how much and how KIBS internationalize. The majority of the available studies focus on clients’ distance, partners’ distance and KIBS’ trade, while we still need to understand how KIBS enter foreign markets, the percentage of sales from foreign countries and their growth rate.

References Braga, A., Marques, C.S. and Serrasqueiro, Z. 2018. Internationalisation strategy of knowledge-intensive business services. Journal of the Knowledge Economy, 9(2), 359–377. Consoli, D. and Elche-Hortelano, D. 2010. Variety in the knowledge base of knowledge intensive business services. Research Policy, 39(10), 1303–1310. Corrocher, N., Cusumano, L. and Morrison, A. 2012. Competitive strategies in knowledge-intensive business services: Evidence from Lombardy. In: Di Maria, E., Grandinetti, R. and Di Bernardo, B. (Eds.) Exploring Knowledge-Intensive Business Services. Palgrave Macmillan, London, pp. 231–251. Czarnitzki, D. and Spielkamp, A. 2003. Business services in Germany: Bridges for innovation. Service Industries Journal, 23(2), 1–30. Di Maria, E., Bettiol, M., De Marchi, V. and Grandinetti, R. 2012. Developing and managing distant markets: The case of KIBS. Economia Politica, 29(3), 361–380. Doloreux, D., Freel, M. and Shearmur, R. (Eds.). 2010. Knowledge-Intensive Business Services. Geography and Innovation. Ashgate, Farnham. Klimek, A. 2018. Advanced business services in the global economy and the Visegrád Group economies. International Business and Global Economy, 37, 399–408. Larsen, J.N. 2001. Knowledge, human resources and social practice: The knowledgeintensive business service firm as a distributed knowledge system. Service Industries Journal, 21(1), 81–102. Miozzo, M. and Miles, I. 2002. The relation between the internationalization of services and the process of innovation: A research agenda. In: Miozzo, M. and Miles, I. (Eds.) Internationalization, Technology and Services. Edward Elgar, Cheltenham. Miozzo, M. and Soete, L. 2001. Internationalization of services: A technological perspective. Technological Forecasting and Social Change, 67(2), 159–185. Rodan, S. and Galunic, C. 2004. More than network structure: How knowledge heterogeneity influences managerial performance and innovativeness. Strategic Management Journal, 25, 541–562. Rodríguez, A., and M. J. Nieto. 2010. Cooperation and Innovation in the Internationalisation of Knowledge-intensive Business Services. In Pla-Barber J. and AlegreJ. (Eds.), Reshaping the Boundaries of the Firm in an Era of Global Interdependence. Progress in International Business Research, 247–270. Emerald Group Publishing Limited, Bingley. Rodríguez, A., Nieto, M.J. and Santamaría, L. 2018. International collaboration and innovation in professional and technological knowledge-intensive services. Industry and Innovation, 25(4), 408–431.

122 Moving the innovation model in KIBS forward Rubalcaba, L. and Toivonen, M. 2015. Internationalisation of services: Modes and the particular case of KIBS. In: Bryson, J.R. and Daniel, P.W. (Eds.), Handbook of Service Business: Management, Marketing, Innovation and Internationalisation, Edward Elgar, Cheltenham, pp. 278–300. Tether, B.S. 2003. The sources and aims of innovation in services: Variety between and within sectors. Economics of Innovation and New Technology, 12(6), 481–505. Toivonen, M. and Tuominen, T. 2009. Emergence of innovations in services. Service Industries Journal, 29(7), 887–902. Wirzt, J., Tuzovic, S. and Ehret, M. 2015. Global business services: Increasing specialization and integration of the world economy as drivers of economic growth. Journal of Service Management, 26(4), 565–587. Wong, P.K. and He, Z.L. 2005. A comparative study of innovation behavior in Singapore’s KIBS and manufacturing firms. Service Industries Journal, 25(1), 23–42. Wyszkowska-Kuna, J. 2017. The role of intermediate demand and technology for international competitiveness of the KIBS sector: Evidence from European Union countries. Journal of International Trade & Economic Development, 26(7), 777–800. Yoo, Y. 2012. Digital materiality and the emergence of an evolutionary science of the artificial. In: Leonardi, P.M., Nardi, B.A. and Kallinikos, J. (Eds.) Materiality and Organizing: Social Interaction in a Technological World. Oxford University Press , Oxford, UK, pp. 134–154.

10 Platforms and modularity in KIBS

Platform and modular designs are the pillars of a mass customization strategy. This section explains modularity and platforms in KIBS and provides multiple examples.

Modularity in services: A new perspective In February 2017, Ottorino Passariello made a speech at the Department of Management of the Ca’ Foscari University (Venice) about the management of the Expo in Milan in 2015. The Expo is a large-scale, global event organized once a year by a different nation and serves to educate the public, share innovations, promote progress and foster cooperation. Within the Expo, each nation has its own space and exposition within which to present its most beloved products. At that time, Passariello was the chief of the Expo operations, and, during his speech at the University, he described the design, organization and management of the Expo, an event that lasted for six months in an area of over 100 hectares. “The secret to succeed in managing a complex event like the Expo is deconstruction,” explained Passariello, and “if I hadn’t used this method I would never have made it.” This approach has a number of operational advantages and allows the unexpected and emergencies to be dealt with in the most effective way. According to Passariello, deconstruction means conceiving the design and management of a complex project as a series of Lego bricks, and it works because it is replicable, flexible, based on main components and quickly adaptable to the current situation. Once the individual operating units, the bricks, have been conceived and designed, then they can be assembled, added or substituted as required. If the whole management process of Expo Milano 2015 had been organized in a structured way, according to strict and integrated procedures, the management of the emergencies would certainly have been ineffective, because the time needed to modify complex and interrelated procedures is not compatible with a sudden problem. In addition, there were many last-minute problems. Passariello explained that the Expo Milano 2015 area was divided into 84 districts or areas (i.e. the bricks), each of which was managed independently. Districts, which correspond to specific thematic areas and to common areas, shared similar procedures; for example, they provided

124 Moving the innovation model in KIBS forward areas to restore visitors and shared security norms, but these were not rigidly identical, since each district could have different characteristics. Districts were overall independent, and changes in the functioning of one district had minor implications for the others. As Passariello said: A Universal Exposition is very similar in its management to a huge shopping centre. Thanks to the deconstruction of the main activities we were able to modify, in the last months before the opening, many of the key processes of the event when the levels of security raised for the international situation of that moment. These changes would not have been possible without the “Lego bricks” approach. Designing and managing the Expo event was a great challenge. Often designing from scratch and customizing a service is a long and complex process. It is frequently necessary to develop projects and processes ad hoc for each customer and “assemble” them in a unique way. The process is similar to model making for the construction of boats and cars: there are boxes with lots of pieces, all different, that are stuck together with glue (a special type, to be applied in precise doses, with a tiny brush). The sequence of the operations to be carried out is unique, as provided for in the instructions, contained in densely written pages, which require careful study. If something is wrong, it must be undone and the process started from scratch. The pieces are designed in such a way that they fit perfectly only with some others and only in a certain position/part of the model. They cannot be used or reused in other parts of the model or to build other models. Model construction is an incremental, irreversible, go–no-go process that takes place in a specific place (e.g. a work table in a studio or garage), which remains dedicated for days (or weeks or months) to the construction of the model itself. Everything happens there. Whoever begins to build the model is likely to be the same person as whoever finishes building it. It is too complicated to try to fit into the process once it has started and too complicated to obtain help from others. Simon (1962) was among the first to capture how the design of product architecture affects its production as well by telling the story of Hora and Tempus. They both produce fine watches, but Tempus assembled one piece at time and, when a client called to order a watch, Tempus had to put it down to answer the phone and it immediately fell into pieces and had to be reassembled from its basic elements. On the contrary, Hora designed watches so that he could put together subassemblies of about ten elements each and have higher chances of completing each block before receiving a new telephone call or eventually lost only a small part of his work. Hora’s productivity was higher. According to most of the literature, KIBS companies are all a little like that. Their services are designed and assembled using the model construction or the Tempus approach. Services are all “integral” – that is, designed as a whole, “from scratch”, to satisfy a particular customer. The parts and components of the service are “unique” and selected and merged one by one to obtain a tailored product.

Platforms and modularity in KIBS 125 Service standardization is diametrically opposed. When a service is standard, the customers buy what the companies propose: “Take it or leave it.” Are there any attributes or characteristics “in excess” of the needs? Patience, you pay for those too, even if you do not use them. Are there, instead, others missing that are needed? Patience is also necessary in this case. The services are completely standard when they can be replicated as such and in different supply relationships. The concept of standardization refers to the rationalization of production processes, which are then imposed on and linked to predefined systems of measurement and evaluation of performance and objectives. The concept is that of Fordist mass production, oriented toward the maximum reduction of production costs and to the offer of a single product with predefined characteristics or, in any case, of a limited set of services defined ex ante. The rigidity of standardization can only be mitigated by a margin for adaptation and customization of the service requested by the customer. Today, mainly in ICT services, partial customization or adaptation of a standard service is quite widespread: software, websites, applications or programs are platforms, and less than 10%–20% of the service is adapted to the customers’ needs. The bi-partitioning of customization vs. standardization no longer represents the state of the supply of KIBS companies. In many companies, the situation is changing. Designing and implementing a service for the market resembles increasingly the game of Lego and less the model of Fordism. Hora is becoming the benchmark. The Lego bricks described by Passariello are also fundamental to complex project events, such as the Expo. The services are designed as “decomposed” systems, in which sets of functions and attributes are grouped independently into “almost autonomous” modules. These modules can be used to create different services through the logic of mix and match, as in the game of Lego. New modules, or “mats”, incorporating new technologies and superior performance compared with the past, can replace existing modules. Additional modules can be inserted to meet special requirements. There is therefore more variety and innovation, albeit resulting from the combination of existing modules. In a competitive environment that requires the pursuit of both flexibility and efficiency goals, the solution most often referred to in both the academic literature and the management practice is a strategy of complexity reduction through the use of modularization. This literature builds on Simon’s (1962) intuition that complex technological and social systems, like products and organizations, are more adaptive if modular. Modularization processes allow the reduction of the complexity of product design problems by breaking down complex problems in such a way that it is possible to manage their complexity more effectively and simply.

Modularity and platforms in services Today, many service providers offer a portfolio of services that may include customized, standardized and combinable or modular services (Sundbo, 2002). Customized services are designed and delivered according to the specific needs

126 Moving the innovation model in KIBS forward of the individual customer, therefore being fully adapted to these, while standardized services are replicated in such a way that all clients buy the same service, which is readily available at a competitive price. Modular services lie between customization and standardization. Customers who want customized services can “compose” their desired service as they like, taking advantage of the combination (mix and match) of different modules. Modular architectures have basic service components (modules) that implement specific functions and can be mixed and matched: by mixing and matching modules, it is possible to provide services that solve the trade-off between personalization (for the customer) and standardization (for the supplier) (Baldwin and Clark, 2000). Voss and Hsuan (2009) are among the first to try to deepen the concept of modularity in the specific field of services. The two authors suggest that a modular product architecture is characterized by a clear allocation of product functions to modules, the use of standard interfaces connecting modules and the possibility of associating specific performance indicators with each module. Voss and Hsuan define service architecture as the way in which service functions are separated into service components – that is, the modules – that implement the allocated functions in full. The adoption of a modular approach is characterized by the combined advantages of flexibility and efficiency in multiple phases of the service development and provision. First, a modular architecture allows the reduction of the design complexity by isolating within modules the elements of the service that are more tightly interdependent while minimizing the interdependence between modules. In this way, the company can more rapidly and easily introduce incremental or modular innovations (Henderson and Clark, 1990), which do not affect the modules’ interaction and hence imply the redesign of (a few) modules instead of the whole product. ERP systems manage multiple functions, and each function, such as human resources or finance, is a module that manages processes that are tightly related within them and less with other functions. Clients can buy or add on single modules without compromising the functionalities of their platform. Second, modular architectures ease the coordination between the organizational units involved in the design and delivery of service modules, both within and across firm boundaries. Multiple teams can design and develop each module in parallel, thus speeding the process with the contained need for coordination between teams if the interactions between modules are well defined ex ante. For the same reasons, modules can also be outsourced more easily. The management literature makes extensive use of the concept of modularity in products and in organizations to emphasize how, by reducing the complexity of the product architecture ex ante, the organization of the products’ design and production is simplified ex post (Cabigiosu, 2013; Cabigiosu and Camuffo, 2010, 2012; Sanchez and Mahoney, 1996). Third, clients can select the modules/functions that they want and pay only for the desired functionalities. Clients can also upgrade, add on or substitute modules later. Langlois and Robertson (1992) focus on this idea of modularity

Platforms and modularity in KIBS 127 in use and maintain that a modular service can be broken down into modules that customers can freely choose and combine according to their preferences. Patricio, Fisk and Cunha (2008) highlight that modularity improves the possibility of creating flexible solutions that offer customers opportunities for adaptation and customization according to their specific needs. The authors add that modular service architectures allows clients to participate in the design as well as in the customization of the service. Service modularity therefore seems to offer efficient opportunities for service customization and effective integration between the parties involved in service design. These are potentially very relevant features in knowledge intensive services (KIBS), in which value added is often related to service customization. Fourth, modular service architectures ease the life cycle management of the product by up-dating, adding or substituting specific modules and by easing the recycling of modules. Finally, the advantages of modularity listed explain why modules are widely used in mass customization strategies. In this respect, modules are often the building blocks of a family of products and are at the heart of product platforms. A platform consists of those common component(s) shared between multiple products. Hence, each product family is assumed to consist of common components – that is, the platform – and product-specific components, namely the modules that can be added to the platform (Fixson, 2005). In products, cars are built on platforms, while, in services, websites or mobile services are built on platforms (see the next chapter).

Modularity in KIBS In recent years, the number of contributions that further disentangle the concept of modularity in services and in KIBS has increased. Pekkarinen and Ulkuniemi (2008) focus on logistics management and develop a multidimensional definition of modularity that distinguishes between services, processes and organizations. Modularity in services refers to service combinability: clients can select and combine standard service modules to satisfy their own particular needs. Modular services are combined via standardized interfaces. In logistics services, firms can combine multiple services such as the order, inventor and supply chain management services. This concept of modularity recalls that of Voss and Hsuan (2009). Then the authors progress further with their reflection and introduce two other interrelated concepts. They define modularity in processes as standard processes that can be mixed and matched and together contribute to the service delivery. Examples of modularity in processes include the management of information flows and the physical movement of goods, both of which can be divided into several sub-processes, such as ordering and booking processes. Bask et al. (2010) also rely on the notion of modularity as a process. Finally, Pekkarinen and Ulkuniemi (2008) present the concept of modularity in organizations, which refers to the resources used by a firm to deliver the service and how the firm uses them. This concept recalls that of cross- and within-firm modularity, which describes who does what and the relationships between multiple partners or teams in charge of

128 Moving the innovation model in KIBS forward specific phases of the service delivery (Colfer and Baldwin, 2016). In this respect, organizational modularity refers to a firm’s use of multiple resources from either inside or outside the firm, with which the firm has loosely coupled relationships – that is, the firm exchanges low levels of knowledge and information sharing (Cabigiosu and Camuffo, 2012). Heikka, Frandsen and Hsuan (2018) suggest that KIBS firms’ core competence resides in their ability to satisfy clients’ needs by combining specific resources. In this context, modules are the internal (people, codified knowledge and ITC systems) and external resources (the organization’s network of suppliers). Internal resources can be either standardized or uniquely designed by the organization. Kuula, Haapasalo and Tolonen (2018) also suggest that, in KIBS, modularity aims more at cost efficiency and it is usually based on service platforms and/or scalable/repeating components. Cabigiosu et al. (2015) discuss the concept of modularity in KIBS, focusing on modules’ attributes and the ways in which modules can be combined. The service is obtained by combining service and sub-service modules selected by the customer. A module is a set of standard procedures used to deliver specific service functions. Coded procedures allow the replication and standardization of the service delivery process and the mixing and matching of service modules. In the modules, the delivery procedures are standard and coded and the interfaces between service modules are standard. Service customization is achieved by mixing standard procedures that process the specific clients’ data. For example, lawyers, notaries or accountants must follow standard procedures and methodologies in carrying out their work, but the data that they process are those of specific clients. In this way, the service will always appear to be dedicated to the client, even if the processes followed in providing it do not vary. While delivery procedures are standard and establish how a service is to be delivered, the information flows and data processed by procedures tend to be customer-specific. For example, logistics service providers use standard procedures to plan the distribution of products, but, depending on the processed data, which vary from customer to customer, such as the location and time of the delivery, the output of the service will be customized. The combinability of the service modules and the use of standard procedures that process data specific to the individual company allow KIBS firms to deliver a service that is perceived as customized by the customer. Cabigiosu et al. (2015) underline that it is difficult for some KIBS firms to standardize the procedures that they use to interact with clients and exchange with them the information necessary to manage the service offered and to deliver it. The integration mechanisms between the KIBS firm and the client company constitute a mix of procedures and resources that are both standard and customized. In KIBS, the customization of clients’ interfaces is often necessary, because KIBS firms have to integrate and coordinate their services with the internal processes of the client company. For this reason, software, telephone calls, meetings and all mechanisms of customer–supplier coordination/integration must be adapted to the way in which the customer company

Platforms and modularity in KIBS 129 manages its internal processes, how its encodes and stores its data and training and, more generally, how it organizes its work. Finally, Cabigiosu et al. (2015) recognize that, in KIBS, a number of services are still based on forms of service customization that rely on the use of clients’ dedicated procedures and resources. In these cases, the opportunities for standardization and coding of procedures are limited. Often, customization of service procedures is driven by clients’ request to use resources dedicated to their own needs. When KIBS use dedicated resources, either internal or external (Heikka et al., 2018), usually the service delivery procedures also become tailored to the individual customer. The authors use the case of logistics service providers. Sometimes these companies cannot consolidate the goods of all their customers in their warehouses but must use the customers’ warehouses, for example when the clients’ production facilities are too distant from the service provider’s warehouses. In this case, the warehouse management and distribution procedures become dedicated to the individual customer: service providers cannot replicate the procedures that they use to manage their own warehouses in clients’ warehouses because of the different spatial, human and technological resources and constraints. Overall, KIBS services can be described by the procedures and resources used to deliver the service. Procedures can be standard (when KIBS firms provide an existing service, replicating procedures that have already been developed and applied in other supply relationships) or new (when KIBS firms develop new services or otherwise adapt existing ones). The resources (such as infrastructure or software) can be shared between several customers or dedicated to a particular customer. Modular services are built by mixing standard procedures and relying on resources shared across different clients. In this setting, services are still perceived as highly customized, because: a) clients can select and mix and match the service components that they want (customers do not have to buy a standard package); b) services process customer information/data (for example, the distribution of products will take place in the places and on the days when the customer has to deliver his goods, but the procedure followed by the logistics operator is standard); and c) standard procedures can eventually be combined with customized services built using dedicated procedures and dedicated resources. The flexibility of modular architectures favours the introduction of innovations that may concern a single module to be added to the existing offer. Thanks to modularity, KIBS firms can introduce innovation more quickly and without having disruptive effects on the existing offer (Baldwin and Clark, 2000). SICS1 is an example of KIBS designing platform services with a modular architecture. SICS is a medium-sized Italian firm, founded in 1995, that develops services and applications for sports teams. SICS works with the most important national and international sports companies, mainly football teams of the major European leagues and the Italian football team, by developing and providing services to meet the increasing needs of technical staff and professional clubs, mainly for match analysis, planning and workout monitoring. Videomatch, for example, is software targeted at coaches who are willing to make a video analysis of their team’s performance. Videomatch is a modular

130 Moving the innovation model in KIBS forward platform linked to a website through which clients can have access to a video archive of games, tagged or not, and to additional statistics. The archive contains approximately 20,000 matches (all Serie A, Serie B, Lega Pro, Europa League and Champions League). Therefore, in addition to the Videomatch software, the client, by paying an additional annual fee, can have access to the archive and see all the games stored. Then, the customer has an additional option and can buy the videos catalogued (or tagged) by SICS internal analysts; cataloguing allows clients to define more easily the type of events that are recorded during the game. For example, coaches who are interested in having information on specific actions or tactics of the opposing team, such as corners, can extrapolate the information on which they intend to focus, without having to view the entire game, thus speeding up the process. Coaches or their staff usually film the match on their own and can independently analyse the video, but SICS also provides ad hoc support services for the analysis of the training or the match. In addition to this, the company provides a report, called Match Studio11, consisting of a dozen pages in which all the game statistics are reported. This report is based on the data collected by the company and sent to SICS’s web platform. Furthermore, every week, all Serie A and Serie B client companies can receive a “Summary” in Excel format at the league level, in which teams are ranked on the basis of multiple parameters, such as the number of shootings, goals, fails, won duels and so on. Therefore, Videomatch is the service platform to which other modular services, such as additional video access or statistical analyses, can be added. This platform is currently used by the Italian football team and by about 50%–60% of the Italian “Serie A” and “Serie B” teams.

Distinguishing modularity in products, in services and in KIBS Modularity in products In the past decades, modularity has attracted considerable interest from management and engineering scholars. This interest in modularity has produced numerous definitions (Fixson, 2005; Gershenson, Prasad and Zhang, 2004) and empirical studies conducted mainly in the field of manufacturing firms (Baldwin and Clark, 2000; Brusoni, Prencipe and Pavitt, 2001; Schilling and Steensma, 2001). Product architecture is the function–component allocation scheme and the description of how the components interact. Product architectures can be more or less complex and can comprise a (large) number of subsystems (components) with many interactions (Ulrich, 1995). In the management and engineering literature, the concept of modularity became popular as a means to face product architecture complexity. Modular architecture is therefore typically taken to mean that the interdependence between subsystems is sufficiently low to permit separability – that is, that either the subsystems themselves can be physically separated or that the management and development of subsystems can be performed independently. This reduces the complexity of development

Platforms and modularity in KIBS 131 processes (e.g., permitting modular or incremental innovations (Henderson and Clark, 1990)) and the complexity of managing the production processes (e.g., production units or external suppliers can specialize in more narrowly defined components) (Fine, 1998; Sanchez and Mahoney, 1996). A second key aspect of the engineering and management uses of the concept of modularity (but which is not always invoked in other research domains) is recombinability. Recombinability refers to a degree of flexibility in the combination and configuration of subsystems. The recombinability of modular products means that heterogeneous inputs can be mixed and matched to meet the heterogeneous demands of customers (Schilling, 2000). Substitutability (replacing one component with another), expandability (adding on additional components) and upgradeability (replacing a component with a version that is newer, bigger, etc.) are all types of recombinability. To clarify the modularity concept further, Cabigiosu and Camuffo (2017) use the example of a complex product: a personal computer. A personal computer is made up of several subsystems (display, chassis, hardware, etc.). These subsystems are physically separable and can be developed and produced independently one from another. They are then recombinable in the final product, often with a range of options in the type of components used and their ultimate configuration. A personal computer has to implement several functions. Individual subsystems such as a display or a mouse are not a computer; rather, they implement only a subset of specific functions. The specificity of the functions implemented by a subsystem is a key property that determines, in part, the degree to which that subsystem can be separated from the rest of the product and managed independently. If subsystems share some functions, it would be difficult to isolate them, for example during the design and production phases. Functional isolation, however, is not enough for the typical definition of product modularity. In the case of the personal computer, for example, the subsystems must also interact – that is, those components that have been separated and managed independently now have to be recombined. The recombinability of a product’s components depends on the component interfaces. Rather than designing each component to work specifically with other particular components in a tightly coupled system, a modular product design utilizes open-standard (or closed-standard) interfaces that permit a range of components to be recombined and to function and interact without undesired or uncontrolled effects. Standard interfaces fix the coupling rules among components (Sosa, Eppinger and Rowles, 2003) and thus allow firms to know a priori how components will interact. Summarizing, components’ separability and recombinability represent the key conceptual features of product modularity. They are properties that technically depend on the way in which functions are mapped onto components and on the number and type of interfaces between components. Ulrich (1995) defines a perfectly modular product as being made of components that perform entirely one or a few functions, with decoupled interfaces among components that are well known, defined, codified and of repeated use.

132 Moving the innovation model in KIBS forward Ulrich’s definition is one of the most popular, and important variants of it have been developed. The first variant pertains to the functions: while Ulrich emphasizes that modules ideally implement only one function each, other authors point out that components might be functionally isolated even if they implement more than one function so long as they do not share these functions with other components (Baiman, Fisher and Rajan, 2001). The second variant of Ulrich’s definition considers the type of interfaces. A product is modular if it can be broken down into subsystems (modules) that are functionally independent and connected by ex ante defined standard interfaces. The presence of both open and closed standard interfaces can yield modular products; however, they do so differently with regard to the type and extent of modularity under consideration. For example, if the details of a cross-component interface within a product are well understood and utilized by multiple firms, it enables inter-firm product modularity whereby end products can be assembled from components from multiple vendors in a variety of configurations. By contrast, a cross-component interface used only within a single firm might enable economies of substitution within the firm (Garud and Kumaraswamy, 1993) whereby a firm reuses components in multiple versions of its own products but the interface does not lend itself to utilizing components from other vendors. Thus, the authors distinguish between products with open interfaces, terming them “open modular” if the interface is open to a network of producers that adhere to a given set of rules that is widely diffused within a given industry and products with closed proprietary standards used by a single firm or a specific network of firms (Fine, Golany and Naseraldin, 2005). Only open-standard interfaces allow firms to separate and recombine product components freely and fully as modules. The same product can mix both open and closed standard interfaces. A modular architecture facilitates the design and production of complex products. In fact, modules can be designed and produced from different departments or divisions and in parallel: modules that do not share functions and standard interfaces at the industry level ensure that they will function properly when they are later combined (Ulrich, 1995). For example, USB memory sticks work on any PC with USB ports, and USB sticks and PCs can be produced by different companies that do not need to co-design their products because adherence to the ex ante USB standard guarantees their smooth operation. In addition, modular architectures facilitate the incremental innovation of individual modules and allow modules to be replaced or added without having to intervene in other subsystems. Modules are not standard, only their interfaces. The classic examples of product modularity are the PC and the bicycle. Computers are products obtained by assembling very different but often compatible components thanks to standard interfaces, such as microprocessors or memory keys. The modules of a bicycle are for example the wheels or the frame. In addition, the companies that produce these components are different and highly specialized. Intel produces microprocessors and Michelin tyres. Modular architecture therefore

Platforms and modularity in KIBS 133 allows players to specialize and have economies of scale and learning and at the same time allows each company to innovate its offer without necessarily having to coordinate with manufacturers of complementary components. Comparing modularity in products and in services Since (knowledge intensive) services are different from products in many aspects (Sundbo, 2002), increasing our understanding of service modularity and its applicability in the KIBS context would permit better inferences with respect to the consequences of modularity for KIBS firms’ internal organizational design, strategy and performance. In services, it is more complex to understand what is standard and replicable in a module and what is not. Product modularity focuses on the functional isolation of modules and on interface standardization. According to the modularity literature, modular service architecture consists of standard modules containing standard sub-modules that can be mixed and matched freely with one another; that is, they are combinable (Meyer and DeTore, 2001). Langlois and Robertson (1992) and Voss and Hsuan (2009) make the point that a modular system can be seen as a service that customers can separate into subgroups, that is, modules, which they can then arrange into various combinations that suit their personal preferences. Modularity offers flexible solutions that help customers co-create their unique value through multiple-service combinations and usage patterns and allow suppliers to exploit their knowledge base in a number of supply relationships, thus increasing their efficiency and competitiveness. Hence, modularity in services is initially conceived as full module standardization without an in-depth description of what is standard in services. Modularity in services suggests a higher degree of standardization than modularity in products, in which only interfaces are necessarily standard. In this respect, the KIBS literature increases our understanding of modules’ standardization. In KIBS, Cabigiosu et al. (2015) find that the use of standard procedures is the constitutive element of modular services. The procedure dictates the steps needed to deliver part of a service, and each of these can be mixed and matched, resulting in a customized service project. In addition, each service can comprise a number of sub-services that clients can mix and match to meet their specific needs. For example, TPL provides distribution, warehousing and transportation services and sub-services, such as insurance services, which can all be combined. Hence, combinability is a crucial property of modules, and Cabigiosu et al. (2015) explain that combinability is ensured by the use of standard procedures. Therefore, standard procedures are the constitutive elements of service modules. The ERP system is an example of modular service. ICT firms (e.g. SAP) typically develop sets of configurable ERP systems for different industries, firm sizes and countries. These sets of ERP systems are configurable in that they allow the monitoring and managing of a variety of business processes. Clients select the specific business processes to manage – that is, the ERP modules – and they can freely mix and match them. Moving to

134 Moving the innovation model in KIBS forward the professional services, a number of notary acts are standards, while consultants often offer customized services. Firms deliver modular services via standard procedures and develop new procedures only when they cooperate with competent clients, extend existing services to new industrial sectors or deliver existing services using clients’ dedicated resources (Cabigiosu et al., 2015). Hence, in KIBS, modularity requires only the standardization of the procedures used to deliver each service module and the standardization of the procedure used to combine service modules. When procedures are standard, firms’ transforming resources are typically standard and shared by several clients. When resources are dedicated to clients, procedures are also often customized. Interestingly, in KIBS, interfaces with clients are often customized. While standard procedures are the building blocks of modules, standardization quite rarely defines how service providers interact with clients. KIBS firms and their clients are integrated via multiple interfaces that are often customer-specific. KIBS services are tightly linked to clients’ operations, and this closeness requires specific coordination and control mechanisms: customized interfaces permit effective customer–supplier interactions. This finding signals a relevant difference between the concept of modularity in KIBS and in services: the service modularity literature emphasizes standard interfaces, while the KIBS literature is more cautious. KIBS are special types of services, because their relationship with customers has a central role in the effective design and delivery of the service and KIBS must be flexible and adapt to the needs of customers when interacting with them to share data and information. The concept of modularity in KIBS does not overlap with that found in the product modularity literature (Campagnolo and Camuffo, 2010) or with the concept of service modularity advanced by Voss and Hsuan (2009). While the product and service modularity literature ascribes modules’ combinability to standard interfaces, the combinability of modules in KIBS is ensured by the use of standard procedures between modules’ standard interfaces and customerspecific interfaces. The findings suggest that modularity in KIBS relates to the procedures and not to the modules’ boundaries and their interfaces with clients. In products, services and KIBS, combinability is achieved when modules can be combined without modifying their design or internal functioning, and firms develop modules as black boxes. While, in the product literature, the role of standardized interfaces is emphasized, in KIBS, the importance of standard procedures is emphasized; they increase the efficiency of the service that can be replicated without reducing the customization of the output obtained either by combining standard procedures incorporated into the modules or by processing customer-specific data and information. In KIBS, despite the replication of procedures, the need for customization for the customer remains relevant in the management and coordination of the relationship: each client processes data and information with its own routines, practices and software, and it is the service provider that has to adapt to its characteristics through dedicated interfaces.

Platforms and modularity in KIBS 135 For example, the procedure for distribution in TPLs is carried out by specialized planners once the order-receiving phase has been completed. Each day, clients send their distribution needs to TPLs, specifically which cargo is to be delivered, when and where. TPLs have a specific software that defines how to load trucks and their routes. The distribution solution is then controlled by planners according to a set of rules associated with the specific cargo (e.g., volumes, weights and number of items). Planning is a complete standard procedure that generates perfectly customized distribution solutions for each client. The order-receiving phase relies on Internet-based software compatible with all types of systems (SAP or others) to connect with the client’s ordering process and a proprietary trans-codification system to read the data. Trans-codification permits the adaptation of outbound information to each client’s software system as well as the transformation of inbound information into standard, readable formats. On the whole, this system has a technological interface that is specific to each customer, as it permits idiosyncratic exchanges of information. In addition, the interfaces in the products can be open standards at the industry level or closed standards when they are in use at the specific company, with remarkable repercussions in terms of competitive dynamics at the level of the industry. Open interfaces often favour vertical disintegration and the emergence of large suppliers specializing in specific components, and large-scale standardization and replication can also generate externalities, economies of scale and industry-wide learning networks. When, on the other hand, interfaces are closed standards, the repercussions are primarily internal to the enterprise and concern the development of platforms and related design and production efforts. The distinction between open and closed standard delivery procedures has not yet been disentangled in services. The procedures that concern how a service is designed and delivered often coincide with the best practices of the individual company, but we still know little about how open innovation in services affects platform design at the interface level. Furthermore, new digital technologies will improve firms’ ability to coordinate service design and delivery efforts and provide the means to interact via codified interfaces. New technologies allow the improvement of KIBS firms’ option to rely on standard procedures and transforming resources while delivering a customized service.

Note 1 www.sics.it/en/.

References Baiman, S., Fisher, P.E. and Rajan, M.V. 2001. Performance measurement and design in supply chains. Management Science, 47, 173–188. Baldwin, C.Y. and Clark, K.B. 2000. Design Rules, Volume 1, The Power of Modularity. MIT Press, Cambridge, MA.

136 Moving the innovation model in KIBS forward Bask, A., Lipponen, M., Rajahonka M. and Markku, T. 2010. The concept of modularity: Diffusion from manufacturing to service production. Journal of Manufacturing Technology Management, 21(3), 355–375. Brusoni, S., Prencipe, A. and Pavitt, K. 2001. Knowledge specialization, organizational coupling, and the boundaries of the firm: Why do firms know more than they make? Administrative Science Quarterly, 46, 597–621. Cabigiosu, A. 2013. Modularity in Design: Organizational and Performance Implications. Giappichelli, Torino. Cabigiosu, A., Campagnolo, D., Furlan, A. and Costa, G. 2015. Modularity in KIBS: The case of third-party logistics service providers. Industry and Innovation, 22(2), 126–146. Cabigiosu, A. and Camuffo, A., 2012. Beyond the “mirroring” hypothesis: Product modularity and interorganizational relations in the air conditioning industry. Organization Science, 23(3), 686–703. Cabigiosu, A. and Camuffo, A. 2017. Measuring modularity: Engineering and management effects of different approaches. IEEE Transactions on Engineering Management, 64 (1), 103–114. Campagnolo, D. and Camuffo, A. 2010. The concept of modularity in management studies: A literature review. International Journal of Management Reviews, 12(3), 259–283. Colfer, L.J. and Baldwin, C.Y. 2016. The mirroring hypothesis: Theory, evidence, and exceptions. Industrial and Corporate Change, 25(5), 709–738. Fine, C.H. 1998. Clock Speed—Winning Industry Control in the Age of Temporary Advantage. Sloan School. Manage., M.I.T., Cambridge, MA. Fine, C.H., Golany, B. and Naseraldin, H. 2005. Modeling tradeoffs in three-dimensional concurrent engineering: a goal programming approach. Journal of Operations Management, 23, 389–403. Fixson, S. 2005. Product architecture assessment: A tool to link product, process, and supply chain design decisions. Journal of Operations Management, 23, 345–362. Garud, R. and Kumaraswamy, A. 1993. Changing competitive dynamics in network industries: An exploration of Sun Microsystems’ open systems strategy. Strategic Management Journal, 14, 351–369. Gershenson, J.K., Prasad, J.K. and Zhang, Y. 2004. Product modularity: Definitions and benefits. Journal of Engineering Design, 14(3), 295–313. Heikka, E.L., Frandsen, T. and Hsuan, J. 2018. Matching value propositions with varied customer needs: The role of service modularity. Knowledge and Process Management, 25 (1), 64–73. Henderson, R. and Clark, K. 1990. Architectural innovation: The reconfiguration of existing product technologies and the failure of established firms. Administrative Science Quarterly, 35(1), 9–30. Kuula, S., Haapasalo, H. and Tolonen, A. 2018. Cost-efficient co-creation of knowledge intensive business services. Service Business, 12(4), 779–808. Langlois, R.N. and Robertson, P.L. 1992. Networks and innovation in a modular system: Lessons from the microcomputer and stereo component industries. Research Policy, 21(4), 297–313. Meyer, M.H. and DeTore, A. 2001. Perspective: Creating a platform-based approach for developing new services. Journal of Product Innovation Management, 18(3), 188–204. Patricio, L., Fisk, R.P. and Cunha, J.F. 2008. Designing multi–interface service experiences: The service experience blueprint. Journal of Service Research, 10(4), 318–334. Pekkarinen, S. and Ulkuniemi, P. 2008. Modularity in developing business services by platform approach. International Journal of Logistics Management, 19(1), 84–103.

Platforms and modularity in KIBS 137 Sanchez, R. and Mahoney, J. 1996. Modularity, flexibility, and knowledge management in product and organization design. Strategic Management Journal, 17(S2), 63–76. Schilling, M. A., 2000. Toward a general modular systems theory and its application to interfirm product modularity. Academy of Management Review, 25(2), 312-334. Schilling, M.A. and H. K. Steensma. 2001. The use of modular organizational forms: an industry-level analysis. Academy of Management Journal, 44(6), 1149–1168. Simon, H.A. 1962. The architecture of complexity. Proceedings of the American Philosophical Society, 106(6), 467–482. Sosa, M., Eppinger, S. and Rowles, C. 2003. Identifying modular and integrative systems and their impact on design team interactions. Journal of Mechanical Design, 125, 240–252. Sundbo, J., 2002. The service economy: Standardisation or customisation? Service Industries Journal, 22(4), 93–116. Ulrich, K. 1995. The role of product architecture in the manufacturing firm. Research Policy, 24, 419–440. Voss, C.A. and Hsuan, J. 2009. Service architecture and modularity. Decision Science, 40 (3), 541–569.

11 Modularity in software and web design

This chapter, by focusing on software and website architecture and design, explains how new technologies and modularity help KIBS firms to develop mass customization strategies. Particularly software and websites are undergoing a profound architectural change, and today they are overall converging toward a modular structure. This chapter explains what modularity is in this context, its impact and its use.

Modularity in software Modularity allows the designing of products by mixing and matching standard components, thus reducing the time to market and costs and increasing the product variety. This is an urgency that also concerns software design and development and software houses that are required to solve the trade-off between customization and costs. For this reason, software projects often start from a prior version, which is used as a platform on which new functionality is built. In many projects, the amount of “legacy code” exceeds the amount of new code, and mature products often significantly reuse code from their earliest versions (MacCormack, Rusnak and Baldwin, 2007). In this field, firms’ ability to design software reusing old codes depends on the software architecture. Software architecture is defined as the relationships between its components and the principles governing their interactions and design, and software modularity is the reuse of software modules, which are self-contained components of the software with well-defined interfaces with other components (Sun et al., 2017). Parnas (1972) is among the first to propose the concept of information hiding as a mechanism for dividing code into modular units and separating the details of internal module design from external module interfaces. Other authors build on this concept, proposing a variety of definitions and metrics, such as coupling and cohesion (Banker and Slaughter, 2000; Eick et al., 2001; Offutt, Harrold and Koltee, 1993). Today, developers must be aware of the consequences of the design decisions that they make to understand how designs evolve, how they can be made more manageable and the role that modularity plays in this process. Banker et al.

Modularity in software and web design 139 (1993) find that project costs increase with software complexity, Kemerer and Slaughter (1997) conclude that the enhancement and repair frequency increase with the module complexity, and Banker and Slaughter (2000) report that the total modification costs increase with the application complexity. Finally, Barry, Kemerer and Slaughter (2006) find that an increase in the use of standard components (a proxy for modularity) is associated with a decline in the frequency and magnitude of subsequent modifications. Some authors also suggest that open-source software is inherently more modular than proprietary software and that modularity is a required property for open development to succeed (MacCormack, Rusnack and Baldwin, 2006; O’Reilly, 1999). MacCormack et al. (2007) show the existence of a relationship between component modularity and design evolution and, in particular, indicate that modularity predicts component survival, component maintainability and component augmentation. More integral components are less adaptable via the processes of exclusion or substitution, they demand greater maintenance efforts and they are harder to augment. These results highlight the importance of design decisions made early in software design, because tightly coupled components are harder to modify and reduce the future flexibility of the software. In the digital era, many devices are also controlled by ad hoc software such as ovens, smart watches and cars. Embedded software is a type of computer software that is specialized for specified hardware and controls machines that are not typically PCs and comprise 99% of all computing units. Industries such as telecommunications, avionics, utilities, automotive and consumer electronics widely use embedded systems (Sun et al., 2017). Embedded software development is an important part of electronic product development process and faces the same trade-offs as product development: quality and variety vs. time and costs. Software development control is based on the development time, effort expenditure (cost), code production (productivity) and defect identification (quality). In this context, software architecture can affect software development performance (Buzurovic et al., 2010; Sommerville, 2007). Modularity is especially suitable for embedded software products, because it increases dependability, reduces process risk, ensures standard compliance and accelerates software development (Mikkola, 2006). Firms that develop embedded software have to adapt their features when hardware changes or product applications require modifications. When this happens, firms have two options: they can adapt the existing software to the new product or they can develop completely new software. The first option is more convenient only if the firm has designed the software architecture upfront to accommodate ad hoc modifications easily without altering the whole architecture. Sun et al. (2017) identify three characteristics of embedded software architecture that are important to adapt software easily to the improved or new product. The first is stability, which evaluates the number of modules, up to the total, affected by modifications when the product has to be improved. The greater the stability, the fewer the modules that require changes and the easier the software upgrade. Hence, designers are expected to cluster within a few

140 Moving the innovation model in KIBS forward modules those software functions that are more likely to change over time. The second property is scalability, which captures modules’ reusability by using the same modules to develop different software. Scalability reduces the lead time and development costs. Third, expandability is defined as the potential to expand functions by adding (or collapsing) modules, mainly microcontrollers or dedicated-function systems on chips. Scalability and expandability emphasize that modules’ standardization has a significant positive influence on software development performance and requires developers to consider these properties upfront when developing embedded software for a new product. Hence, modularity as applied to software requires developers to design any new modules based on the agreed architecture and interfaces. The studies by Menzies and Di Stefano (2003) and Morisio, Romano and Stamelos (2002) show that engineers’ culture and training positively influence software reuse, which may have a negative meaning if correlated with the idea of reuse of someone else’s effort, and that firms have to give guidance about software’s expected level of modularity, offer ad hoc training and managerial support and develop a culture of reuse in the organization.

Modularity in web design Recent trends in web design The invention of the World Wide Web (WWW) dates back to 1991, when the CERN (Conseil Européen pour la Recherche Nucléaire) in Geneva published the first website in history (Berners-Lee et al., 1992). In the WWB, resources are organized and made available according to a system of pages that can be accessed using special programs called web browsers, or simply browsers, through which users can navigate, viewing documents, images, movies and so on. In 1993, CERN decided to make the technology behind the WWW public so that it could be freely implemented by anyone. The basic principle of the Web is that when a document, a database or any other type of content is published, it automatically becomes accessible to anyone from any device and from any country. Although, before 1995, the Web was only used by the scientific community and between governmental and administrative associations, since that year, a growing number of private users have accessed the network through their computers. The real growth boom is evident between 2000 and 2010 thanks to the alignment of web browsers with imposed standards, the continuous improvement of the connection speed until the spread of broadband and the diffusion of laptops, tablets, smartphones, game consoles, smartwatches and so on (Lechman, 2013). Web design concerns the technical, structural and graphic design of websites and web applications. A website is a product that is designed and built by a web designer, sold to a customer and consumed by a web user. Initially, firms used websites to present their business, services and products. When the Web

Modularity in software and web design 141 started, it was just hypertext. The first websites were strongly static, similar to the pages of a book, the purpose of which is the mere consultation of information without any kind of human-contained interaction. Websites are today increasingly complex artefacts that are part of a comprehensive communication strategy as well as of the business of a company. Shaped by an experiential logic, in which interactivity with the site and multi-screen and multi-device fruition are increasingly important, today’s websites are dynamic and flexible. Today, a well-designed website can open a window on the world, allowing a company to improve its visibility and the availability of its offer, extend the potential market and encourage communication with old and new customers. Today, websites are not mere collections of pages. In the creation of a website, the design phase is increasingly important; in this phase, the foundations are laid for the development of a cohesive and scalable system that must achieve a set goal, such as involving the public and generating interest. A web designer, like an architect, designs a space that is not only aesthetically pleasing and usable but also dynamic, easily upgradable and scalable or extendable with additional features to meet future needs. In addition, a good web designer is able to leverage the experience to reuse solutions that have been tested successfully in the past to solve similar problems (Bichler and Nusser, 1996; Frost, 2016). The first step in the web design phase is the definition of the architecture of the site – that is, its structural organization, which includes the identification of the different component parts and the way in which they integrate and interact as a whole. The ANSI/IEEE Std 1471-200019 standard defines the architecture of a website as “the basic organization of a system, represented by its components, the relationships that exist between them and with the surrounding environment, and the principles that govern its design and evolution”.1 Once the architecture of the site has been defined, designers define and combine the different sections and components of the architecture. Recently, web designers have begun to embrace more modular, componentbased design practices. The main reason is twofold. On the one hand, the aim is to increase the efficiency and effectiveness in the creation of dynamic and flexible websites. On the other hand, the current landscape requires the creation of convincing and persuasive experiences for an ever-increasing number of screens, devices, places and people. In this context, a responsive system is based on modules, allowing the required flexibility and scalability, and web designers have thus begun to break down digital interfaces into smaller pieces, reusable modules, and begun to combine them differently to obtain more products, features and functionalities. It is in this context that the concepts of “atomic design” and modularity are introduced. As in the natural world, the most complex systems are composed of smaller parts. In chemistry, matter is composed of organisms, molecules and atoms. A similar decomposition can also be applied to web design. The design of the information architecture (IA) is important. Since the Web is mainly made up of content pages that represent articles or products, the information architecture aims to organize them into reliable and efficient

142 Moving the innovation model in KIBS forward hierarchies for archiving and retrieval (Hinton, 2009). The information architecture refers to the organization, classification, navigation and labelling of information so that it is readily available and easy to understand (Pasquini and Giomi, 2014). Designing the information architecture means, in fact, carefully evaluating the path to follow in the development of the site, taking into account three factors: the user, the content and the business context. The objective is to help users who move within a site to find the information that they seek. A well-structured, user-centered information architecture promotes both an adequate user experience and the achievement of the business objectives. When properly used in the process of building a site, it enables static websites to be transformed into complex adaptive systems (Rosenfeld, Morville and Arango, 2015). Modularity in web design Brad Frost discusses the concept of “atomic design” and explains the importance of designing a website, or an application, as a system of components rather than as a series of separate pages (Frost, 2016). Thousands of pages could be composed of the same few basic components, repeated and reused in different configurations. Thinking of a design system consisting of atomic components, which, like Lego, can be combined differently according to the required functionality, allows the reduction of the level of effort required in a project. Frost adopts a component-based approach typical of software development and explains how to design websites as systems made up of components that ensure greater flexibility, efficiency and speed of development. This approach also enables the release of a dynamic site, which is easily upgradable and, most importantly, scalable in components and functionality to meet future needs. The hierarchical breakdown of a problem into smaller and more easily manageable sub-problems is a particularly widespread and effective approach to deal with all those contexts characterized by increasing complexity. Such an approach allows for a significant reduction in the number and size of the sub-problems to be addressed simultaneously, focusing on more controllable structures – as they consist of fewer variables and interactions between them – and encouraging greater collaboration and cooperation within the team. In addition, by breaking down the problems into sub-problems, it is possible to identify and distinguish familiar problems that are already known and solved from those problems that require a greater level of detail and work. It would, however, be wrong and inefficient to consider the sub-problems as being independent, ignoring the possible links and interdependencies existing between different subsystems and components. The web community has long been committed to establishing shared principles and practices that enable effective and efficient website creation. Slowly, web designers have realized the rigidity and inefficiency of the design approach adopted earlier. It is no longer conceivable to look at the creation of websites in a static way, as simple collections of pages. The complexity has become such as to require the design of real systems of components, which are flexible, scalable and suitable

Modularity in software and web design 143 for survival in a constantly changing context. A well-thought-out, responsive design is device independent, which helps to manage hostile browsers, small screens, slow networks and many forms of input. The Web, today more than ever, has intrinsic variability that must be embraced in the creation of sites. In the age of the multi-screen, multi-device web, the concept of a page, with its rigid edges and dimensions, has become obsolete. The most rational and efficient option is, therefore, to design content networks in modular systems that are scalable, consistent and perfectly usable regardless of the screen size, device type and browser version. The advantages of a modular approach are well known; modules are scalable, replaceable, reusable, easy to test and faster to assemble (Frost, 2016). Designing a modular site implies the separation of the different sections of the layout of the site in independent components, and this requires a series of important decisions regarding the purpose of the site to be built, which modules and features to use, when to reuse a module and when to design a new one, how to make the modules quite distinct but consistent, how to combine them, how to avoid duplication with other modules and so on. Many of these decisions are made in the initial design phase of the site’s information architecture. The definition of the system architecture is, in fact, decisive for the adoption of a modular approach, since it allows the identification of the design rules that should guide the design and development of each individual module of the site (Endrei et al., 2004). In detail, modularity concerns the design and development of websites made of modular components that are obtained by working on websites’ modular content, modular code and a modular visual design. To obtain modular contents, the information is broken up into smaller blocks that perform a specific information function and that can be combined and made available in different ways. Although this is not a new idea, it is an urgency dictated by the current multi-screen and multi-platform landscape. Nowadays, content is consumed by a large number of devices of different sizes and graphic resolution – just think of the extreme variety of smartphones, tablets, televisions, smartwatches and notebooks with access to the network. Therefore, to ensure the fruition of content in line with an increasingly eclectic and diversified digital landscape, a change in perception has become necessary regarding the organization of the content and the tools used to manage it (Frost, 2016). A “page” of a site broken down into modules changes more easily, serving copywriters and users better. While the page is breaking up, even content management systems (CMSs) are constantly evolving towards platforms and tools that can elegantly create and effectively maintain modular content. CMSs are software tools that facilitate the management of a website and can be proprietary, customized by expert programmers or open source. WordPress is the best-known and most-used content management open-source system. Modular contents are supported by modular codes. HTML and CSS are two standard languages used to create web pages: the first defines the content of the site; the second specifies its appearance. In practice, what the human eye perceives of a site is rendered, during development, by a succession of strings of HTML/CSS code that specify its content, appearance and functionality. The

144 Moving the innovation model in KIBS forward blocks with which a page is structured are the HTML tags, while the CSS rules are used to intervene in the formatting of the text, the positioning of the graphic elements and the arrangement of the latter in different media and devices. Today, site reusability and scalability are facilitated and made possible by the adoption of a more modular approach to code architecture. Component-based development has provided a way to accelerate the potential of programming by making code cleaner, reusable and therefore easier to scale. Each component is nothing more than a portion of reusable code within the site system – as in other projects – and serves as a building block of the site interface (Frain, 2017). Finally, in a modular visual design, web pages can be graphically decomposed into multiple rectangles. Each rectangle is a component (or module or block) that is visually associated with a physical part of the web page. The reason for this specific geometric shape is twofold. First, the very nature of HTML code forces page designs to be defined by provisions of rectangular blocks. Secondly, it is evident that it is easier to assemble and combine rectangular blocks than round modules. We are faced with a proliferation of websites, each of which is very similar. Every year, within the web community, conventions are created that lead sites to align their graphic design. These conventions are very often dictated by the large, widely used websites – think of the authority and enormous traffic of Amazon, for example – that educate users to expect a certain disposition of the elements. The division of a page into independent components makes it easier to reuse them in different pages and sections of the site as well as ensuring the ability to modify the individual components as needed without affecting other components. For example, a component can combine a logo and a search form or contain the header of a site. If a company wants to change its logo and its position on the page, this can be easily achieved without affecting the other components. A modular visual design also helps designers to create coherent, adaptable and multi-device web experiences. Taking into account the continuous evolution of users’ expectations, it is much faster and more manageable to think about the construction of a site as a system of components that can be easily changed and reassembled. However, for the assembly of components on the site to be effective and efficient, it is necessary for the designer to know the role of each component used, its possibilities for reuse and how it fits into the design process (Curtis, 2010). When web components are modular, like Lego bricks, they become more versatile and easy to maintain.

Note 1 www.iso-architecture.org/ieee-1471/ansi-approves-ieee-1471.html

References Banker, R.D., Datar, S., Kemerer, C. and Zweig, D. 1993. Software complexity and maintenance costs. Communications of the ACM, 36(11), 81–94. Banker, R.D. and Slaughter, S.A. 2000. The moderating effects of structure on volatility and complexity in software enhancement. Information Systems Research, 11(3), 219–240.

Modularity in software and web design 145 Barry, E., Kemerer, C. and Slaughter, S. 2006. Environmental volatility, development decisions, and software volatility: A longitudinal analysis. Management Science, 52(3), 448–464. Berners-Lee, T., Cailliau, R., Groff, J.F. and Pollermann, B. 1992. World-wide web: The information universe. Internet Research, 2(1), 52–58. Bichler, M. and Nusser, S. 1996. Modular design of complex Web-applications with W3DT. In: Proceedings of WET ICE ’96. IEEE 5th Workshop on Enabling Technologies; Infrastructure for Collaborative Enterprises, pp. 328–333. Buzurovic, I., Podder, T.K., Fu, L. and Yu, Y. 2010. Modular software design for brachytherapy image-guided robotic systems. In: Proceedings of IEEE International Conference on BioInformatics and BioEngineering, Philadelphia, Pennsylvania, 31 May–3 June 2010, pp. 203–208. Curtis, N. 2010. Modular Web Design: Creating Reusable Components for User Experience Design and Documentation. New Riders, Berkeley, California, USA. Eick, S., Graves, T.L., Karr, A.F., Marron, J.S. and Mockus, A. 2001. Does code decay? Assessing the evidence from change management data. IEEE Transaction on Software Engineering, 27(1), 1–12. Endrei, M., Ang, J., Arsanjani, A., Chua, S., Comte, P., Krogdahl, P., … and Newling, T. 2004. Patterns: Service-Oriented Architecture and Web Services. IBM Corporation, International Technical Support Organization, pp. 17–44. Frain, B. 2017. Enduring CSS. Packt Publishing Ltd, Birmingham, UK. Frost, B. 2016. Atomic Design. Brad Frost, Pittsburgh, Pennsylvania, USA. Hinton, A. 2009. The machineries of context. Journal of Information Architecture, 1(1), 37–47. Kemerer, C. and Slaughter, S. 1997. Determinants of software maintenance profiles: An empirical investigation. Software Maintenance: Research and Practice, 9, 235–251. Lechman, E. 2013. New technologies adoption and diffusion patterns in developing countries. An empirical study for the period 2000–2011. Equilibrium. Quarterly Journal of Economics and Economic Policy, 8(4), 79–106. MacCormack, A., Rusnak, J. and Baldwin, C.Y. 2006. Exploring the structure of complex software designs: An empirical study of open source and proprietary code. Management Science, 52(7), 1015–1030. MacCormack, A., Rusnak, J. and Baldwin, C.Y. 2007. The Impact of Component Modularity on Design Evolution: Evidence from the Software Industry. Harvard Business School Technology & Operations Mgt. Unit Research Paper (8–38). Menzies, T. and Di Stefano, J.S. 2003. More success and failure factors in software reuse. IEEE Transactions on Software Engineering, 29(5), 474–477. Mikkola, J.H. 2006. Capturing the degree of modularity embedded in product architectures. Journal of Product Innovation Management, 23(2), 128–146. Morisio, M., Romano, D. and Stamelos, I. 2002. Quality, productivity, and learning in framework-based development: An exploratory case study. IEEE Trans Software Eng. 28(9), 876–888. Offutt, A.J., Harrold, M.J. and Koltee, P.A. 1993. A software metric system for module coupling. Journal of Systems Software, 20, 295–308. O’Reilly, T. 1999. Lessons from open source software development. Communications of the ACM, 42(4), 33–37. Parnas, D.L. 1972. On the criteria to be used in decomposing systems into modules. Communications of the ACM, 15(12), 1053–1058. Pasquini, J. and Giomi, S. 2014. Web Usability: Guida completa alla user experience e all’usabilità per comunicare e vendere online. Hoepli Editore.

146 Moving the innovation model in KIBS forward Rosenfeld, L., Morville, P. and Arango, J. 2015. Information Architecture: For the Web and Beyond. O’Reilly Media, Inc. Sommerville, I. 2007. Component-based software engineering. In: Software Engineering. 8th ed. Addison Wesley, New York, USA, pp. 439–461. Sun, H., Ha, W., Teh, P.L. and Huang, J. 2017. A case study on implementing modularity in software development. Journal of Computer Information Systems, 57(2), 130–138.

Conclusions

Digital technologies allow firms to manage increasing degrees of complexity. Computers and artifacts are becoming more and more intelligent, and their increased productivity and computational capabilities free firms’ resources. Robotics and information technology are the future, even for KIBS firms. One day, in many offices, there may be humanoid robots able to convey emotions. Today, androids not only recognize who is in front of them but also try to interpret data, information and emotions. From the interlocutor’s age, sex and posture, androids gain an idea of the state of mind and of the approach to be used. However, even though robots are rapidly evolving, their socializing capabilities are still (and will remain) far from ours. In this respect, Frey and Osborne (2017) suggest that two types of activities will never be performed by digital technologies: creative and social activities. Creative professions generate meanings and emotions and are culturally related, all aspects that machines cannot manage. Social activities concern people’s interactions, sharing and common problem solving. While digital technologies do not have these attributes – that is, creativity and socialization – they can still support them, for example via ICT platforms such as Facebook, or apps, such as Skype, which ease and foster interactions, socialization and in turn creativity. Creativity, complex problem solving and socialization are all attributes that define most KIBS, as widely debated in this book. Hence, most KIBS firms deliver services that benefit from new technologies, for the provision of which machines cannot substitute knowledge workers. Humans and technologies are complementary. Digital technologies improve human problem-solving ability, via deep learning or augmented intelligence, and provide tools to improve humans’ socialization and creativity. Digital technologies increase the value that KIBS firms produce via three selfreinforcing mechanisms. The first is scalability, which means that digital technologies are tools to codify, standardize, store and replicate firms’ knowledge at almost zero costs. Second, digital technologies augment problem-solving effectiveness and efficiency, and increase the level of problem-solving complexity that managers can handle. Third, digital technologies support professionals by providing tools to sustain humans’ creativity and connectivity.

148 Conclusions Thanks to the properties listed, digital technologies also ease internationalization strategies: codified knowledge can easily be transferred, and relationships can be managed more easily at a distance. However, while digital technologies free the work from being univocally physically located, the data still show that creative workers are mainly attracted by metropolitan areas or eventually by more peripheral areas, such as industrial districts, in which high-value productions are concentrated. Overall, in the digital era, people and knowledge are central to the value generation process, as well as their diffusion on the territory, in explaining performance gaps between regions. Interestingly enough, despite the relevance of KIBS, we still need studies about their diffusion and growth in many geographic areas, especially in fast-growing economic areas, such as China, or in developing countries. When KIBS firms act as a carrier and source of innovation, they play an important role in the creation, transfer and diffusion of knowledge and of high value-added services and facilitate learning and improvement at their clients’ level. KIBS companies can stimulate and support knowledge creation and dissemination and in turn innovation processes, enabling their clients to exploit their own knowledge base and resources optimally. This in turn has remarkable consequences as far as the role of KIBS in the development of regions is concerned. This is especially true when considering the high geographical proximity between KIBS and manufacturing firms. These arguments clarify the importance of public policies supporting incentives for KIBS’ allocation and development: since manufacturing firms and especially R&D-intense industries require advanced and knowledgeintensive services, policy makers should try to boost territories and local economies by attracting knowledge workers and by supporting industrial clusters combining the product and service sectors. All in all, digital technologies can support KIBS firms’ growth by spurring their innovativeness, solving (at least partially) the productivity dilemma in that they allow the replication and storing of the service offer and easing services’ transferability across geographical borders. Coherently, studies about KIBS find evidence that innovation is a relevant driver of growth, especially when innovations are new to the industry. While digital technologies open up special opportunities for growth for KIBS firms, they also need to be managed and require ad hoc technical competences as well as specific dynamic capabilities and soft skills in the area of change management. While technology per se is not a threat to KIBS firms, its process of adoption requires ad hoc strategies and resources. KIBS are on average micro firms that, at least partially, need to update their own competences to benefit from the digital revolution to the fullest. These investments may generate a division between growing and performing KIBS firms and smaller and lagging behind traditional firms. This is especially true if the 4.0 economy favours the most innovative and bigger manufacturing firms that typically interact with bigger and better-structured KIBS firms, thus

Conclusions

149

generating a virtuous cycle only for the biggest and innovative KIBS firms. In this setting, KIBS are competitive if they are able to sell their services to distant clients who positively value their ability to create a modular architecture of services, each of which clearly addresses specific clients’ needs via codifiable knowledge that is easily transferable. Furthermore, the rapid increase in the demand for ICT services, for which relevant economies of scale in the R&D effort exist, may favour big and global service providers in multiple service industries. Finally, while technologies can put two managers immediately in contact, they do not help in managing other types of distance, such as cultural distance and different norms between countries, which need to be managed carefully, and additional competences. While the business model of KIBS firms in the past could balance the emphasis on innovativeness with that on customization obtained via tight relationships and vis-à-vis relationships with co-located clients, and local small KIBS firms could sell their services to small local clients, today the emphasis on new technologies causes small KIBS firms to evaluate the sustainability of their niche strategy. Today, the competition in many sectors is global, and KIBS can remain local if the competitive advantage of companies still originates at a local level from the network of companies that are responsible for the growth and competitiveness of their territory. While this is still the case of some industries, such as those that constitute Made in Italy (fashion, food and furniture), which are strongly tied to the know-how of specific territories, this reasoning does not apply for example to the automotive industry, which is becoming an increasingly global industry in which KIBS are also required to act globally. For the reasons given here, this book emphasizes the relevance of modularity and standardization in KIBS and suggests that customization and standardization/modularization are complementary, because they allow the exploitation of the efforts associated with service customization in multiple supply relationships, and that standardization/modularization and innovation are complementary, since they increase firms’ portfolio equilibrium and the market share of innovations that can be replicated in a number of supply relationships. Collaboration with clients can be a valuable input for the innovation process of a KIBS firm, but, at the same time, it absorbs resources and diverts KIBS firms’ attention from other valuable sources. As a result, KIBS firms could perfectly address their customers’ requests, but such a degree of dependence can eventually contrast the KIBS firm’s growth when they develop competences and services that partially lose their value outside that specific client relationship. Indeed, the best-performing KIBS firms are those that replicate, at least partially, innovations developed jointly with a particular client with other clients as well. Successfully leveraging past supply relationships to increase firms’ growth requires the capacity to discriminate between those relationships with clients that nurture firms with knowledge that has a broad market potential and can foster firms’ growth and those relationships that generate only client-specific

150 Conclusions knowledge and problem-solving competences. These clients should not become exclusive points of reference. To grow, firms need to use a portfolio approach and wisely balance the resources and managerial attention dedicated to specific relationships with customers with the resources dedicated to other partners and to develop valuable resources within multiple buyer–supplier relationships. In particular, modularity, scalability and expandability emphasize that modules’ standardization has a significant positive influence on many ICT services, particularly in software and website development, and require developers to consider these properties upfront when developing a new product. In this respect, engineers need ad hoc training and managerial support to develop a culture of module reuse in product design. Overall, this book emphasizes that digital technologies offer new opportunities for growth in KIBS and identifies new research streams. First, we need further studies that explore KIBS firms’ business model in the digital era and that capture how services are designed and delivered and how relationships with clients and territories are changing. KIBS firms may display different growth strategies that diversely balance elements of customization, modularity, innovation, client collaboration and internationalization. Future studies could deepen our understanding about the interplay between innovation, buyer–supplier collaboration and customization by collecting empirical data in other regional innovation systems and investigate how different types of innovation interact in a portfolio approach by deepening the analysis in different categories of KIBS. Second, while the breadth of the knowledge search is often related to firms’ innovativeness, understanding how openness affects innovation in KIBS still requires considerable work and theorizing efforts. In particular, we need studies to grasp the relative role of clients, that of other partners and their complementarities in explaining KIBS firms’ innovativeness and their ability to adopt and use new technologies. Third, the increased importance of services makes improving productivity in services a necessary ingredient to enhance the aggregate productivity in many regions. However, the evidence on the extent to which innovation in services can contribute to improving productivity remains inconclusive. Furthermore, the heterogeneity of services and their immaterial nature make the use of traditional measures of innovation and productivity problematic, and this limits the capacity to track improvements or changes in services. These difficulties are accrued by the use of different approaches to analyse the topic empirically, namely the assimilation, demarcation and synthesis approaches, which still co-exist. Fourth, the previous paragraphs emphasize that KIBS, mainly t-KIBS, are approaching international markets with more interest and that digital technologies are supporting this strategy. While this scenario opens many commercial opportunities, it also emphasizes a number of criticalities. Employees and users are required to be digitally literate for navigating in the digital environment, and this generates a problem regarding the competences

Conclusions

151

involved in the delivery and provision of the service and the transfer of such competences to clients. Bigger problems may also arise when we look at the availability of the infrastructures in many developing countries, such as the fibre-optic Internet. Finally, we still lack studies that focus on how much and how KIBS firms internationalize. The majority of the available studies focus on clients’ distance, partners’ distance and KIBS trade, while we still need to understand how KIBS firms enter foreign markets and the percentage of sales from foreign countries and to disentangle systematically the differences between t-KIBS and p-KIBS.

References Frey, C.B. and Osborne, M.A. 2017. The future of employment: How susceptible are jobs to computerisation? Technological Forecasting and Social Change, 114, 254–280.

Index

Note: Page numbers in bold type refer to tables ; Page numbers in italic type refer to figures; Page numbers followed by ‘n’ refer to notes Abernathy, W.J., and Utterback, J.M. 39, 40 ADP (Automatic Data Processing) 119 advertising firms 120 algorithms 1 Alibaba Group 27 Alipay 27 Amara, N.: and Landry, R. 73; Landry, R. and Doloreux, D. 15, 44, 50 Amazon 144 architects, process innovation 37 artificial intelligence 1 Automatic Payrolls Inc. 119 automotive industry, Italian suppliers’ study 23 Auxiell 66 Avellaneda, C.N., Damanpour, F. and Walker, R.M. 41 Avvecomm 23–24 Banker, R.D.: et al. 138–139; and Slaughter, S.A. 139 Barras model 39–40, 74 Barras, R. 39–40 Barry, E., Kemerer, C. and Slaughter, S.A. 139 Bascavusoglu-Moreau, E., Hughes, A. and Mina, A. 74 Bask, A., et al. 127 Baumol, W.J. 93, 94 bicycles 132 Biege, S., et al. 97 Bilderbeek, R., and Den Hertog, P. 14 BIM (building information modelling) software 37 Bonner, J.M., and Walker Jr., O.C. 104

Braga, A., et al. 116 Brenner, T., et al. 12 bridges of innovation 19–24, 67 building design 37 business intelligence systems 29 business-to-business service firms 10–11, 14–15 Bustinza, O.F., et al. 68 buyer–supplier collaboration 82, 150 c-KIBS 12–13 Ca’ Foscari University of Venice 26, 123 Cabigiosu, A. 128–129, 133; and Campagnolo, D. 83, 86, 101, 107–108; and Camuffo, A. 131 Cablog 66–67 Cainelli, G. 81; Evangelista, R. and Savona, M. 101 Calantone, R.J., and Li, T. 62 call centres 95 Campagnolo, D. 3; and Cabigiosu, A. 83, 86, 101, 107–108 Camuffo, A., and Cabigiosu, A. 131 Castro, L.M., Montoro-Sanchez, A. and Ortiz-de-Urbina-Criado, M. 38 CERN (Conseil Européen pour la Recherche Nucléaire) 140 Chamberlin, T., Doloreux, D. and Therrien, P. 53 Chesbrough, H. 56 Chinese market, Italian firms 27 client: co-located 23; co-production of services 15; face-to-face interactions 9, 115; organizational and operational processes 63; own innovation processes 69

154 Index client collaboration, and customization 62–67 client participation, service design and delivery 9 clients’ needs: customized services 134–135; defining and articulating 68; innovation processes 63; satisfying 64; service specifications 41; understanding 62 client–KIBS firm relationships 83, 149–150 client–supplier collaboration 63 Cloud 119–120 cloud architectures 29, 95, 119 Cluster, The 24 co-production management model 65 Coca-Cola 46, 56 codified knowledge: digitalization 118, 147–148; ICT services 121; KIBS internal processes 25; law firms 26; reproduction costs/value 95 collaboration: buyer–supplier 82, 150; client 62–67 commodity trap 44 communication: interpersonal 96; openness 64 competences: clients’ focus on 10; digital technologies 120; firm’s lacking 1; ICT technologies 22; KIBS firms 22, 128, 147–148 competitive advantage: and customization 84; establishing 64; KIBS firms 72; and knowledge 10 Consoli, D., and Elche-Hortelano, D. 118 “consultancy firms” 12 consulting firms 120 Conundra Ltd. 56 Coombs, R., and Miles, I. 45 coordination mechanisms 64, 66, 70 Corrocher, N.: and Cusumano, L. 11; Cusumano, L. and Morrison, A. 44, 116 Corsten, H. 97–98 cost sickness 94, 95 CPM (corporate performance management) 29 Crespi, G., and Zúñiga, P. 101 Cunha, J.F., Fisk, R.P. and Patricio, L. 127 customer: engagement 65; productivity 98; understanding 83 customer relationships, platforms and modularity 134 customer–service provider interface design 43–44

customization: and client collaboration 62–67; and competitive advantage 84; mass customization strategies 2, 3, 25; and new services 84; and service innovation 105–106 customized services 85, 89; clients’ needs 134–135; clients’ procedures and resources 129 Cusumano, L.: and Corrocher, N. 11; Corrocher, N. and Morrison, A. 44, 116 Czarnitzki, D., and Spielkamp, A. 116 Damanpour, F., Walker, R.M. and Avellaneda, C.N. 41 Danish service firms 116 data: management 29; mining 29; storage 24 Daxo 29 De Fuentes, C., et al. 100–101 De Luca Tamajo e Soci 25–26 deconstruction, modular services 123–124 Den Hertog, P.D. 41; and Bilderbeek, R. 14 Di Maria, E., et al. 117 Di Stefano, J.S., and Menzies, T. 140 digital boutiques 41 digital literacy 120 digital media, shopping experience 41 digital technologies: big data 29; codified knowledge 147–148; embedded software 139–140; free platforms 118; infrastructure in developing countries 120, 151; interfaces 135; investment 68; KIBS firms use 24–26; and knowledge workers 25; new forms of production/consumption 95–96; process of provision 8 Digital To Asia 27 digitalization: codified knowledge 118; criticalities 120–121; and cultural distance 120–121; definition 1, 118; and internationalization 115–121; opportunities and threats 118–121; service industry 39–40; socio-technical transformation 118–119 Digitec 21–22 direct foreign investment 26, 120 Djellal, F., and Gallouj, F. 36, 45 Doloreux, D.: Amara, N. and Landry, R. 15, 44, 50; Chamberlin, T. and Therrien, P. 53; et al. 51, 53; Rodríguez, M. and Shearmur, R. 16,

Index 155 74; Turkina, E. and Van Assche, A. 42, 44 Drejer, I. 45 DS Group 41 E&D (engineering and development) services 23 e-commerce services 42, 95 e-goodlife 22 economic performance: growing importance of KIBS 19–30; KIBS share of business market 11; knowledge production and dissemination 9 economic return, innovation forms (multiple) 38 economics of scale 94, 96 economy, tertiarization 93–94 EDI (electronic data interchange) 44 Edison 22 Elche-Hortelano, D., and Consoli, D. 118 electronic document format 44 electronic product development 139 embedded relationships, dark side 72, 104, 106 embedded software 139–140 Emmott, B., and Pennant-Rea, R. 8 employees’ engagement, “gamification” 57 employment, in KIBS firms 20 Enel 22 Ericsson 23 ERP (enterprise resource planning) systems 119–120, 126, 133–134 European economies, KIBS share of business market 11 Evangelista, R., Cainelli, G. and Savona, M. 101 Expo Milan (2015) 123–124, 125 FabricaLab 27–29, 30 face-to-face interactions, clients 9, 115 fashion industry 28 Fisk, R.P., Cunha, J.F. and Patricio, L. 127 Fordist mass production 125 foreign direct investment 26, 120 Fourth-party logistics (4PL) 12 Frandsen, T., Heikka, E.L. and Hsuan, J. 128 Freel, M. 38, 50, 74 Frey, C.B., and Osborne, M.A. 147 Frost, B. 142 Gadrey, J.F., Gallouj, F. and Weinstein, O. 7 Gallouj, F. 40; and Djellal, F. 36, 45; Gadrey, J.F. and Weinstein, O. 7 “gamification” 56–57

GDP (gross domestic product), employment in KIBS firms 20 GE (General Electric) 46 Gemuenden, H.G., Herstatt, C. and Lettl, C. 62, 83 Geox 97 German business service firms 116 GIR allestimenti 24 Global Blue 27 GNP (gross national product), and service industry 7 Google 96, 97 Grönroos, C., and Ojasalo, K. 98, 99 Grupp, H., and Hipp, C. 38 Haapasalo, H., Kuula, S. and Tolonen, A. 128 Hauknes, J. 45 He, Z.L., and Wong, P.K. 117 Heikka, E.L., Frandsen, T. and Hsuan, J. 128 Helfat, C.E., Leiponen, A. 74 Herstatt, C., Gemuenden, H.G. and Lettl, C. 62, 83 Hipp, C.: et al. 74; and Grupp, H. 38; and Tether, B.S. 35 Hora 124, 125 Howells, J. 50; and Tether, B.S. 45 Hsuan, J., and Voss, C.A. 126, 127, 133, 134 Hughes, A., Bascavusoglu-Moreau, E. and Mina, A. 74 Huiban, J.P., and Musolesi, A. 83, 101 human resources: administration 119, 120; KIBS firms’ dependence 14, 71; knowledge endowment and capabilities 8, 43; management practices 65; strategic variable 42, see also knowledge workers human–machine interfaces 22 IBM 118 ICT services: business opportunities 24; codified knowledge 121; demand 149; ERP systems 133–134; manufacturing firms 10; partial customization 125 ICT technologies: competences 22; evolution and proliferation 25; interfaces 135; KIBS firms’ dependence 14, 147; measuring innovation in KIBS 51; service industry expenditure 41–42 industrial clusters 69 Industry (4.0): empowering women in 29; increased relevance of KIBS 22, 148–149; internal restructuring projects

156 Index 30; market information 21; t-KIBS and p-KIBS 27–30 industry experience, acquired by KIBS firms 65 innovation definitions, Oslo Manual (2018) 42–43, 46, 54 innovation forms (multiple) 35–47; assimilation perspective 46; buyer–supplier collaboration 150; categories of innovation 44–47; clients’ needs 41; demarcation approach 45, 46; economic return 38; innovation/ performance gaps 36; layers (concept to the interface) 40–44; process phases 39–40; product and process innovations 37–40; product and service packages 45–47; services 35–37; synthesis perspective 45–47; taxonomies of technological trajectories 45 innovation performance (KIBS) 81–90, 103–109; best-performing service types/innovations 86–89, 87; client collaboration 103–105; configurational approach 86; customization and client collaboration 62–67, 105–109; depth of relationships with clients 105, 108; innovation and growth 81–84; new innovation (sector) 82, 84; performance goals 82; profitability (ROI) configurations/core condition 87–88, 87; service innovation and performance 108–109; service type classification 87; service types 84–85; service types and firms’ performance 85–86; standard services 105; Veneto study 86–89, 89–90n1, 107–108, 107, 117 innovation processes: centrality of technology 45; customers’ role 103; managing collaboration 106–107; phases 39–40; roles 21; user involvement 103 innovation sources: external 51–53; internal 50–51 innovation traits (KIBS) 62–75; capturing unmet needs 69; clients’ embeddedness (dark side) 72, 104, 106; clients’ process and KIBS role/contribution 67–70; customization and client collaboration 62–67, 105–109; expert clients 65–66; external partnering 73–74; open innovation 51, 71–75; sharing knowledge with clients 70–71 innovative networks 73

innovative solutions, design to market delivery 68–69 insurance brokers 43 intellectual property protection 8–9, 53 intelligence: artificial 1; business systems 29 interactions, face-to-face 9, 115 interface design, service provider/ customer 43–44 internal innovative capacity 50 internationalization: and digitalization 115–121, 148; drivers in KIBS 115–118; and globalization 26–27; p-KIBS 117–118; regional dynamics 117; and social capital 117; t-KIBS 116, 118 interpersonal communication 96 Intranet 118 IOT (Industry of Things) 22–23 Italdesign 23 Italian firms: Chinese market 27; outsourcing 23 Italian suppliers of automotive industry study 23 Italy: Veneto study 86–89, 89–90n1, 107–108, 107, 117; Venice Ca’ Foscari University 26, 123 Johnston, R., and Jones, P. 98 Kapp, K.M. 56 Kemerer, C.: Barry, E. and Slaughter, S. A. 139; and Slaughter, S.A. 139 KIBS firms: big 23; bridges of innovation 19–24, 67; classification 12–13; competences 22, 128, 147–148, 150–151; definition 10; different categories 12, 15–16; further studies 150; geographic concentrations/ locations 11, 148; human resources 71; knowledge bases 13; main traits 14–16; micro enterprises 11, 21, 115, 148; portfolio equilibrium 85–86, 109, 149–150; relevance and diffusion 10–12 KIS (knowledge intensive services) 10, 19 knowledge: co-production 15, 71; and competitive advantage 10; creation, transfer, diffusion 69; end customers of product/service 73; explicit 70; generation processes 43, 71; reproduction costs/value 9; sourcing strategies 74–75; tacit 42, 70; transfer

Index 157 process 70; transformation models 70, see also codified knowledge “knowledge agents” 20 knowledge economy 2; main traits 20; and service industry 7–10 knowledge intensive services (KIS) 10, 19 knowledge workers: competences 43, 120, 150–151; and digital technologies 25; location of 148; problem solving tasks 14; qualifications 50 Koch, A., and Strotmann, H. 50–51 Kuula, S., Haapasalo, H. and Tolonen, A. 128 Landry, R.: and Amara, N. 73; Amara, N. and Doloreux, D. 15, 44, 50 Langlois, R.N., and Robertson, P.L. 126–127, 133 Larsen, J.N. 116 Laursen, K., and Salter, A. 103, 105 law firms 1, 25–26, 40 lean practices 42, 66 Lego 123, 124, 125, 142 Leiponen, A. 52, 74; Helfat, C.E. 74 Lettl, C., Herstatt, C. and Gemuenden, H.G. 62, 83 Li, T., and Calantone, R.J. 62 literature: client–provider interactions 2; collaborative innovation 62; innovation 62; service industry management 44; service innovation 73 logistics service providers 12; distribution procedure 135; Italian firms 66–67; modular services 133; modularity 127; track and trace systems 22, 42, 67; warehouse management 129 Love, J.H., and Mansury, M.A. 51, 62, 81, 83, 106 MacCormack, A., et al. 139 machine learning 29 Made in Italy 149 Mairesse, J., and Robin, S. 83, 101 management practices, co-production model 65 Mansury, M.A., and Love, J.H. 51, 62, 81, 83, 106 manufacturing firms: geographic proximity to KIBS 148; ICT services 10; outsourcing non-core activities 11, 19–20; production and demand 94–95; and servitization 96; synergies with KIBS 20, 67 market research services 69, 120

Martinez-Fernandez, M.C., and Miles, I. 13 Martínez-Ros, E., and Orfila-Sintes, F. 58 mass production, Fordist 125 Match Studio11 130 measuring innovation in KIBS 50–59; categories of partners 52; customers’ needs/resistance to change 55, 56; differentness 57–59; external partnering 53; external sources 51–53; “gamification” 56–57; ICT applications employed 51; imitation strategies 55–56; incremental/radical innovations 57, 58, 100; internal sources 50–51; new innovation (sector) 55, 57, 99; output of innovation activities 53–59; productivity dilemma 99–100; sources of innovation 50–53; t-KIBS 50–51; taxonomies of novelty (newness) 58, 59; timing of entry 54–57 media: digital 41; social 25 Meghini, G. 28 Menzies, T., and Di Stefano, J.S. 140 MGP&Partners 24 Miles, I. 12–13; and Coombs, R. 45; et al. 7, 14; and Martinez-Fernandez, M.C. 13; and Miozzo, M. 120 Mina, A., Bascavusoglu-Moreau, E. and Hughes, A. 74 Miozzo, M.: et al. 15; and Miles, I. 120 model making process (prototypes) 124 modular services 85, 123–127, 149; deconstruction 123–124; and modular products 133–135; service standardization 125, 126; and software 138–140; and web design 140–144 Montoro-Sanchez, A., Castro, L.M. and Ortiz-de-Urbina-Criado, M. 38 Morisio, M., Romano, D. and Stamelos, I. 140 Morrison, A., Corrocher, N. and Cusumano, L. 44, 116 Musolesi, A., and Huiban, J.P. 83, 101 needs see clients’ needs Nestlé Purina 66–67 NetBanana 24 networks: innovative 73; social 96 newspaper articles, Italian 22–23 Nieto, M.J.: and Rodríguez, A. 116; Rodríguez, A. and Santamaría, L. 117; and Santamaría, L. 62 Nike 56–57

158 Index Nonaka, I., and Takeuchi, H. 43, 70 Noordhoff, C.S., et al. 104 OECD countries, service industry 7, 16n2 Officina 57, 59n1 offshoring 115 Ojasalo, K., and Grönroos, C. 98, 99 open innovation 51, 71–75 openness, communication 64 operational productivity 98 Orfila-Sintes, F., and Martínez-Ros, E. 58 organizational innovation, Oslo Manual (2018) definition 42–43 organizational models, technological changes 30 Ortiz-de-Urbina-Criado, M., Castro, L. M. and Montoro-Sanchez, A. 38 Osborne, M.A., and Frey, C.B. 147 Oslo Manual (2018) 37; -based innovation surveys 57, 58; innovation definitions 42–43, 46, 54 outsourcing: Italian firms 23; non-core activities 11, 19–20 p-KIBS: customers’ and suppliers’ cooperation 74; definition 12; Industry 4.0 paradigm 29–30; internationalization 117–118; knowledge-sourcing strategies 74–75; traits 15–16 Parnas, D.L. 138 participation, client 9 partner networks 72, 73–74, 104, 120 Passariello, O. 123, 124 Patricio, L., Fisk, R.P. and Cunha, J.F. 127 patterns, innovation 44 PCube 28 Pekkarinen, S., and Ulkuniemi, P. 127–128 Pelling, N. 56 Pennant-Rea, R., and Emmott, B. 8 Pepsi Cola 67 performance: economic 9, 11, 19–30; goals 82 performance (KIBS) see innovation performance (KIBS) personal computers 131, 132 personnel services 119, 120 Piaggio 23 Pina, K., and Tether, B.S. 13 Pininfarina 23 platforms and modularity 123–135; customer relationships 134; customization for the customer 134–135; deconstruction 123–124; expandability 131; modular product architecture 126; modularity in

KIBS 127–130, 149; modularity in products 130–133; modularity products/ services (comparing) 133–135; modularity in services 123–127; recombinability 131; service standardization 125, 149; standard interfaces 132, 133, 135; substitutability 131; upgradeability 131 Playoff 57 portfolio equilibrium (KIBS firms) 85–86, 109, 149–150 Portuguese KIBS 116 problem solving process 64 process innovation: definition 82; and product innovation 37–40 processes see innovation processes product architecture 126, 130, 131 product innovation: collaborative strategies 67–68; definition 82; and process innovation 37–40; technology-based strategies 37 product life cycle: management 127; model 38–39 product modularity 130–133; and modular services 133–135; personal computers 131; standard interfaces 132, 133; Ulrich definition 131–132 product process management 131 production processes, rationalization 125 productivity, stagnation (USA) 93 productivity dilemma 2–3, 148; demand and supply 94–95; digitalization in services 93–101; measuring productivity in services 97–99; productivity in KIBS 99–100; service innovation and productivity 100–101; servitization 93–95; stagnation in USA 93 professional knowledge 14 professional service firms 12 R&D (research and development): expenditure in KIBS 50–51; FabricaLab 28; law firms 25–26; SMEs (small and medium-size enterprises) 21 Rawfish 21–22 Rebecca Minkoff 23 regional innovation systems 20, 115 relationships: client-KIBS firms (long lasting) 83, 149–150; communication openness 64; contractual arrangements 104; and cultural distance 120–121; embedded 72, 104, 106; face-to-face interactions 9, 115; inter-organizational 51; managing collaboration 106–107;

Index 159 platforms and modularity 134; standards and expectations 65; technology to manage geographical distance 120 restaurants 94 Ritala, P., et al. 62 Robertson, P.L., and Langlois, R.N. 126–127, 133 Robin, S., and Mairesse, J. 83, 101 Rodríguez, A.: et al. 51, 52, 53; and Nieto, M.J. 116; Nieto, M.J. and Santamaría, L. 117 Rodríguez, M.: Doloreux, D. and Shearmur, R. 16, 74; et al. 74 Romano, D., Morisio, M. and Stamelos, I. 140 Salter, A., and Laursen, K. 103, 105 Samsonite 23 Santamaría, L.: and Nieto, M.J. 62; Nieto, M.J. and Rodríguez, A. 117 Savona, M., Cainelli, G. and Evangelista, R. 101 Schricke, E., Zenker, A. and Stahlecker, T. 20 Schumpeter, J.A. 81 search engines 96 service: architectures 127; concept 41; outcomes 99 service delivery, tangible resources 7–8 service design and delivery, client participation 9 service development process, collaboration with clients 63 service firms: business-to-business 10–11, 14–15; Danish 116; German 116 service industry: digitalization 39–40; and GNP 7, 16n2; ICT expenditure 41–42; innovation and productivity gains 94; inseparability concept 8; and knowledge economy 7–10; management literature 44; measuring productivity 97–99; perishability 8; time and location limits 94; value creation 35 service innovation 35–37; definition 36; degree of newness 36; literature 73; new innovation (sector) 55, 57, 82, 84; “new service” 36, 42, 46, 54; and performance 108–109 service performance, firms’ organization and supporting technologies 8 service production, definition 35 service productivity, measuring 97–99

service provider: customer interface design 43–44; loyalty 15 service provision, competences 71 service sector, development 7 service specifications, clients’ needs 41 service types: best-performing 86–89, 87; definitions and classifications 7, 8, 87; demand for 93; and KIBS firms’ performance 84–86 services: customized 85, 89, 129, 134–135; elements of 36; modular 85, 123–127, 133–135, 138–144, 149; output 8; quality 98; service readiness 98; standard 85, 89, 99, 105, 125, 126, see also ICT services servitization 7, 16n1; and manufacturing firms 96; product and service packages 45–47; productivity dilemma 93–95 Sethi, R., et al. 62 Shearmur, R., Doloreux, D. and Rodríguez, M. 16, 74 shopping experience, digital media 41 Sibilla 28–29 SICS 129–130 Siemens 118 Simon, H.A. 124, 125 Singapore, KIBS firms and manufacturing clients 117 Sintesi Comunicazione 24 skills: company’s ability to develop 58; soft 65 Skype 96, 118 Slaughter, S.A.: and Banker, R.D. 139; Barry, E. and Kemerer, C. 139; and Kemerer, C. 139 SMEs (small and medium-size enterprises) 20–21 social capital, and internationalization 117 social media 25 social networks 96 soft skills 65 software: artificial intelligence 1; BIM 37; business process capabilities 1; codified knowledge 118; compatibility 135; customization and costs 138; embedded 139–140; modularity 138–140; open-source 139 software architecture 138 solutions 68–69 sources, innovation 50–53 Spanish KIBS, knowledge-sourcing strategies 74 Spielkamp, A., and Czarnitzki, D. 116 sports coaches 130

160 Index sports teams, services and applications 129–130 Stahlecker, T., Schricke, E. and Zenker, A. 20 Stamelos, I., Morisio, M. and Romano, D. 140 Standard Industrial Classification 13 standard services 85, 89, 99, 105, 125, 126 Strotmann, H., and Koch, A. 50–51 Sun, H., et al. 139 suppliers: productivity levels 98; relations with 73 switching costs 83 t-KIBS: definition 12; highly qualified staff (innovation) 74; Industry 4.0 paradigm 27–29; internationalization 116, 118, 150; knowledge-sourcing strategies 74–75; measuring innovation in 50–51; process innovations 83; traits 15–16 Takeuchi, H., and Nonaka, I. 43, 70 technological trajectory taxonomies 45 technologies see digital technologies; ICT technologies technology-related services 12, 24 telematics service providers 68 teleworking 25, 95–96 Tempus 124 Tether, B.S. 42, 62, 83, 116; and Hipp, C. 35; and Howells, J. 45; and Pina, K. 13 Texa 22 Therrien, P.: Doloreux, D. and Chamberlin, T. 53; et al. 58, 83 Tim 23 Toivonen, M., and Tuominen, T. 116 Tolonen, A., Kuula, S. and Haapasalo, H. 128 TPL (third-party logistics) 12, 66–67, 133; distribution procedure 135; track and trace systems 22, 42, 67 track and trace systems 22, 42, 67 traits see innovation traits (KIBS) Trigo, A., and Vence, X. 74 truck manufactures 68 Tuominen, T., and Toivonen, M. 116 Turkina, E., Doloreux, D. and Van Assche, A. 42, 44 Uber 41 Ulkuniemi, P., and Pekkarinen, S. 127–128

Ulrich, K. 131–132 Unox 66 USB memory sticks 132 Utterback, J.M., and Abernathy, W.J. 39, 40 value chain 19 value creation: creation/dissemination of knowledge 14; product and service packages 45–47; service industry 7, 35 value-added activities 46, 148 Van Assche, A., Doloreux, D. and Turkina, E. 42, 44 VEASYT 26, 120 Vence, X., and Trigo, A. 74 Veneto study 86–89, 89–90n1, 107–108, 107, 117 Venice, Ca’ Foscari University 26, 123 Vespa scooter 23 videoconferences 96 Videomatch 129–130 Vodafone 23 Voss, C.A., and Hsuan, J. 126, 127, 133, 134 Walker Jr, O.C., and Bonner, J.M. 104 Walker, R.M., Avellaneda, C.N. and Damanpour, F. 41 watch makers 124 web browsers 140 web design: “atomic” 141, 142; beginnings/growth 140–142; breaking down problems 142; device independent design 143; HTML/CSS code 143–144; information architecture (IA) 141–142, 143; logos 144; modular visual design 144; modularity 140–144; site architecture 141 Weinstein, O., Gadrey, J.F. and Gallouj, F. 7 Witell, L., et al. 36, 45, 46 women, empowering in Industry (4.0) 29 Wong, P.K., and He, Z.L. 117 workers see knowledge workers WWW (World Wide Web) 140 Young, A. 50 Zeekit 23 Zenker, A., Schricke, E. and Stahlecker, T. 20 Zuñiga, P., and Crespi, G. 101