Knowledge Management Philosophy: Communication As a Strategic Asset in Knowledge Management 9781787696624, 9781787696594, 9781787696617

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KNOWLEDGE MANAGEMENT AS A STRATEGIC ASSET

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KNOWLEDGE MANAGEMENT AS A STRATEGIC ASSET: AN INTEGRATED, HISTORICAL APPROACH

JON-ARILD JOHANNESSEN Nord University, Norway and Kristiania University College, Norway

United Kingdom – North America – Japan – India Malaysia – China

Emerald Publishing Limited Howard House, Wagon Lane, Bingley BD16 1WA, UK First edition 2019 Copyright © 2019 Emerald Publishing Limited Reprints and permissions service Contact: [email protected] No part of this book may be reproduced, stored in a retrieval system, transmitted in any form or by any means electronic, mechanical, photocopying, recording or otherwise without either the prior written permission of the publisher or a licence permitting restricted copying issued in the UK by The Copyright Licensing Agency and in the USA by The Copyright Clearance Center. Any opinions expressed in the chapters are those of the authors. Whilst Emerald makes every effort to ensure the quality and accuracy of its content, Emerald makes no representation implied or otherwise, as to the chapters’ suitability and application and disclaims any warranties, express or implied, to their use. British Library Cataloguing in Publication Data A catalogue record for this book is available from the British Library ISBN: 978-1-78769-662-4 (Print) ISBN: 978-1-78769-659-4 (Online) ISBN: 978-1-78769-661-7 (Epub)

CONTENTS Preface

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1. A Historical Introduction to Knowledge Management

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2. Knowledge Management and Innovation: Aspect of a Theory

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3. Knowledge Management and Internal Training

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4. Knowledge Management and Organizational Learning

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5. Epilogue

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Glossary

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Index

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PREFACE

When in this book we use the concept of a historical introduction to knowledge management, we here mean the period from around 1980 to 2018. This is because it is in this period knowledge management became a central business concept. Therefore we deliberately have used many references from the 1980s and 1990s in this book. Our knowledge philosophy is that without an understanding of the history of a knowledge field of inquiry, we cannot understand, describe, and analyze the now or predict the future. Even if it may be hard or impossible to predict the future, it may be possible to create it, but only if we know something about the history of what we are about to create. Creating the future of the company, social systems, etc., is the philosophy of thinking we use here, not the concept of adapting to what others have created. It is not the survival of the fittest, but the survival of those who are able to create their own future which is the foundation of the knowledge philosophy in this book. This may be understood as a way from red ocean strategy and Darwinism in social systems, over blue ocean strategy, to the strategy of creating our own future. This new strategy can only be successful if we know the history of what we are about to create.

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Preface

In this book, we use a systemic perspective to come to grip with what has happened in the past, what happens now, and how to create and predict the future. Many of the concepts used in this book are explained in the chapter on concepts (Glossary). Jon-Arild Johannessen

1 A HISTORICAL INTRODUCTION TO KNOWLEDGE MANAGEMENT

INTRODUCTION Accelerating technological development, a rapid change in consumer requirements, and a dramatic increase in product development, paralleled with a reduction of previous protective economic boundaries, have led to a globalized marketplace, characterized by turbulence, uncertainty, and complexity. Within these new realities, old prescriptions do not appear to provide the necessary cure. Hence, we have seen a shift in the strategic management literature from the industrial organization (IO) perspective toward the resource base perspective, the dynamic capability approach, and the activity-based perspective. Teece, Pisano, and Schuen (1997, p. 509) argue that the dynamic capability approach is: “. . .especially relevant in a Schumpeterian world of innovation-based competition, price/ performance rivalry, increasing returns, and the creative destruction of existing competencies.” Following this path, we have also seen that knowledge has emerged as the strategically

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most important resource for companies. Consequently, we have seen renewed interest for organizational learning and innovation. Much of the strategic attention has focused on the question of how to apply resources in order to generate, organize, and utilize knowledge to trigger innovation. Hence, a natural consequence of this development has been an increased emphasis toward innovation as crucial in the development of firm’s sustainable competitive advantages. However, although these new paths have provided us with a deeper understanding of factors and processes conducive to innovation and eventually to sustainable competitive advantages, little attention has been focused toward the social mechanisms which trigger innovations. We argue that it is social mechanisms among individuals and companies that initiate and sustain processes related to innovation in organisations. The problem presented in this chapter is: Which social mechanisms influence those processes affecting innovation in social systems. The purpose is to uncover processes and the corresponding social mechanisms promoting innovation in organisations. In the present chapter, it is the systemic angle of incidence which will be used. A system is defined by elements related to each other, and to other systems. By social system is here meant a system “composed of people and their artefacts” (Bunge, 1996, p. 21). Social systems are (in systemic thinking) kept together by dynamic social relations and social actions. Bunge (1997, p. 414) says: “. . .a mechanism is a process in a concrete system, such that it is capable of being about or preventing some change in the system as whole or in some of the subsystems.” The concept social mechanisms is controversial in social science, and there are also “remarkably few studies of social mechanisms” (Bunge, 1997, p. 411) in social science. Hence, those social mechanisms developed in this chapter must be regarded as tentative and will have to be tested empirically.

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The chapter is organized in the following way: First, we develop a conceptual model where organizational learning, the internal knowledge base, the external knowledge base, and innovation constitute the main components. Then we will be discussing each of the first three elements in relation to the effect they represent in unleashing the innovation potential in social systems. In conclusion, we present a conceptual model, which represents a synthesis of the social mechanisms which influence those processes affecting innovation in social systems.

INNOVATION AND KNOWLEDGE: A HISTORICAL JOURNEY During the last three decades (1988–2018)1 we have observed an explosive attention, both in the popular press and among academics, on innovation as a means to create and maintain sustainable competitive advantages. Innovative output is contingent on previous accumulation of knowledge, enabling innovation to assimilate and exploit new knowledge. Hence, it could be argued that there is a strong link between knowledge and innovation (Bleuer, Bouri, & Mandada, 2017). Consequently, we have also seen an explosive arguing for the importance of knowledge, and there are an increasing number of researchers arguing that knowledge constitutes the principal source of economic rent (Bratianu, 2015). The focus on knowledge and its importance may be seen as an extension of the efficiency-based approach. On the historical and theoretical level, we have seen the emergence of the 1 The fall of the Berlin Wall in 1989 and the Chinese entrance into the capitalist economy of the West in 1988.

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knowledge-based theory (Grant, 1996a, 1996b), the theory of organizational knowledge creation (Nonaka, Umemot, & Senoo, 1996), and the diamond theory (Porter, 1990, 1998, 2002). The underlying assumption of these approaches is that knowledge and innovation are the principal productive resources of the firm (Brynjolfsson & McAfee, 2014). We define knowledge here as systematizing and structuring information for a specific purpose. This definition is also consistent with Drucker (1994, p. 38), who argues that: “Knowledge is systematic, purposeful, organised information.” Knowledge can be divided into two different categories: explicit and tacit knowledge. Lei (1997, p. 213) stated that “explicit knowledge is that which can be written down, encoded, explained or understood by anyone with a basic understanding of the technology or phenomenon at hand—inside or outside of the firm.” Hence, explicit knowledge can relatively easily be formulated by means of digits and symbols and thus be digitalized. This knowledge can, in other words, easily be transmitted to others by means of, for example, information technology. Lei (1997) further argue that although explicit knowledge can be protected by patents and thus remain an intellectual property, such knowledge is “transparent” in the sense that anyone with a comparable knowledge or skill base can understand the relevant technology and decipher it. Moreover, explicit knowledge is not embedded or enshrouded in the firms’ organizational routines or practices. Tacit knowledge is defined by Howells (1966, p. 92) as: “non-codified, disembodied know-how that is acquired via the informal take-up of learned behavior and procedures.” Fleck (1996, p. 119) describes tacit knowledge as: “a subtle level of understanding often difficult to put into words, a trained recognition and perception, a good feeling for the

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technology. This form of knowledge is wholly embodied in individual, rooted in practice and experience, expressed through skilful execution, and transmitted by apprenticeship and training through watching and doing forms of learning.” In spite of the substantial interest in knowledge processes in organizations in the last three decades, the link between knowledge and innovation has not been extensively elaborated on. This is especially the case for tacit knowledge, which until fairly recently has been ignored and toned down in terms of its competitive importance, both by academics, managers, and policy-makers. However, this development has recently changed toward increased attention to this part of the company knowledge base and is now “recognised as playing a key role in firm growth and economic competitiveness” (Howells, 1996, p. 91). For the relationship between tacit knowledge and innovation, Sobol and Lei (1994, p. 170) make the following statement: “…the skills required to compete and develop new products…have become tacit, human embodied and organization-embedded.” This is also underlined by Marabito and Sach (2017) as a pathway to innovation leadership. Knowledge, both explicit and tacit, is, however, not developed in a vacuum with the individual person or company. It is mainly a process where the company is part of a larger social system. Antonelli (1996, p. 285) says: “In sum, the capability to innovate successfully appears to be strongly conditioned by learning opportunities and by the accumulation of specific knowledge that is both internal and external to the firm.” Hence, in studying knowledge in the individual companies it will be essential to consider external systems with which the company is interacting (the external knowledge base). Antoneli (1996, p. 283) expresses it in the following way: “…technology has a strongly systemic character so that each unit of technological knowledge can be created and

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traded only within a larger framework including the array of complementary and interrelated units of knowledge generated by firms.” Hence, the entire knowledge base of the individual company is developed in a social and cultural context, where the interaction between companies and between companies and external systems constitute major elements for both the development and transfer of knowledge, both tacit and explicit (Case, 2016). This is very clearly expressed with Sweeney (1996, p. 59): “in the past, organizational innovation tended to be the force driving technological and social change. The indications are that social forces will determine technological and organizational change in the next long wave.” Stejskal, Hajek, and Hudec (2018) too elaborate on this line of argument, by particularly arguing in favor of the link to the market as an important factor in knowledge spillovers. A natural place to search for a more profound understanding of the link between knowledge, particularly tacit knowledge, and innovation is to be found within the research theme “organizational learning.” As the marketplace increasingly has been characterized by profound social, economic, and technological changes, where we have an increasing demand for more knowledge both in companies and in the society as a whole, organizational learning has received growing attention. The reason is quite simply that knowledge is closely linked to learning and could be understood to the effect that knowledge is the result of learning encompassing cognitive development and behavioral change. Antonelli (1996, p. 284) underlines the link between organizational learning, knowledge, and the link between systems when he expresses: “…the generation of localised knowledge is viewed as the outcome of a collective undertaking strongly influenced by the availability of information and communication channels among learning agents.” The assumption of a link between “firm-specific skills and

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capabilities has made learning a focal point of concern” (Pisano, 1994, p. 85). Pisano’s statement suggests a clear link between tacit knowledge and organizational learning. This link has also been expressed by a number of other authors.2 The ability to develop, design, produce, and market involves the ability to learn (Anderson & Jefferson, 2018). This also links innovation and organizational learning. Organizational knowledge processes, innovation, and organizational learning are integrated in a process, and the one element cannot be studied independently from the two other elements. This is clearly underlined by Nonaka (1994) and Marabito and Sach (2017). Furthermore, Pisano (1994) emphasizes the necessity of, and increased attention to, the study of tacit knowledge and organizational learning. What particularly links tacit knowledge to organizational learning is perspectives linking the concepts “situated learning” (Lave & Wenger, 1991), “contextual learning” (Chaiklin & Lave, 1993; Østerlund, 1996), and “implicit learning” (Reber, 1993). The point of these three constructs is that they, through “learning by doing,” “learning by using,” “learning by experimenting,” and “learning by interaction,” constitute the processes that develop, transfer, and integrate tacit knowledge in the organization. Knowledge and tacit knowledge in particular, in a time with increasing hypercompetition will be focused on companies’ ability to learn and to innovate. Hence, we argue that knowledge becomes the most important resource, learning becomes the most important process, and the interaction between the various actors and the systems influencing or participating in the process becomes the most important

2 For example, Leonard-Barton (1995), Dosi (1988), Nelson (1987, 1988, 1990), Nelson and Winter (1982), Cohen and Levinthal (1990), Nonaka (1991, 1994), Nonaka and Takeuchi (1995), Dosi, Teece, and Winter (1992).

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Fig. 1.1. Innovation in Social Systems. Organizational learning

influence

influence

Is part of

Innovation In Social systems Is part of

Is part of

The Internal Knowledge base

influence

The External Knowledge base

prerequisite for innovation in social systems. It is the three entities – organizational learning, the internal knowledge base of the system, and the external knowledge base – which make up the conceptual model for this chapter (see Fig. 1.1). The model will be used to isolate those social mechanisms affecting innovation in social systems.

KNOWLEDGE MANAGEMENT: INNOVATION IN CLUSTERS Most of the widely used definitions of innovation focus on novelty and newness. We follow in the footstep of Zaltman, Duncan, and Holbeck (1973, p. 10) which defined innovation as: “any idea, practice, or material artifact perceived to be new by the relevant unit of adoption.” The literature on innovation research differentiates, both at the macro and micro levels, between two main models; the linear model with its theoretical foundation in neoclassical

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microeconomy and the interactive model (or cooperation model) based on evolutionary economics. The linear innovation model has constituted the foundation for innovation policy throughout the postwar period. The model is based on the idea that technological research and the diffusion of technology are the main elements in the development of innovations conducive to commercialization. This premise resulted in focus on technological research in research and university environments as the source of innovation and new technology. The task consisted of financing scientific research and to transfer the results from the laboratories to a business environment. Technological change was regarded as a sequential process, consisting of phases, where knowledge (usually derived from scientific research) was meant to generate innovation processes, followed by technological development, in turn leading to innovation (or commercial introductions of new products or processes) and finally resulting in diffusion. The main hypothesis pertaining to the linear model is then that major capitalization on R&D is closely related to the degree of innovation. Policy implications of this thinking have been a strong emphasis on R&D activities. This model focuses mainly on formal R&D and explicit knowledge. Subsequent research has, however, developed a more diversified view of what generates innovations, leading to a shift in focus toward interactive innovation models (North & Kumpta, 2017). Inherent in this development has been a growing awareness that the development of innovations imply both a social and a technical process and that innovation is a cooperative process involving a number of actors both internally and externally (for the company). We have further seen a growing focus on tacit knowledge, developed through experience and reflection in the interaction between the various actors. Both Howells (1996) and Reed and Shearer (2017)

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argues that tacit knowledge is important in the entire innovation process, and at all levels in the organization. The linear model for innovation has thus been toned down in recent years and gradually been supplanted by interactive innovation models, parallel with the increasing emergence of evolutionary economic theories (Jacobsen, 1992), new economic growth theories (Verspagen, 1992), and theory of practice (Reed & Shearer, 2017). The basic idea pertaining to the interactive innovation model is the link between various types of knowledge. Another important feature of this innovation model is the emphasis on cooperation as opposed to the emphasis on competition. The interactive innovation model also emphasizes the link between company-internal, company-external, and technological factors. A simplified outline of the distinction between the linear and the interactive innovation model could be explained in the following way. In the linear model, innovation is a function of investments in private and public R&D. In the interactive model, innovation is a function of investments in private and public R&D, in addition to knowledge spillovers from various intermediary links between R&D and practice (Reed & Shearer, 2017). This brings us to the activity-based approach and especially to cluster theory and its connection to innovation. Cluster as a competitive factor has a long-standing historical basis. It was, however, only with increased knowledge intensity both in input, process, and output, in addition to globalization of the economy, that both the depth and scope of cluster grow into a decisive factor for competitive strategies of companies. Porter (1998, p. 266) writes: “Cluster represents a new and complementary way of understanding an economy, organising economic development, and setting public policy.” The competitive situation for the individual

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enterprise is usually regarded from the perspective of what materializes on the inside of the system’s boundaries. This has also been the case with a nation’s competitive situation. For the individual enterprise a consequence of cluster thinking is that strategy thinking, the larger system of which one is part of, serves as the starting point. Porter (1998, p. 198) writes: “The health of the cluster is important to the health of the company.” The role of the authorities in this context will be to remove obstacles and promote cluster development, since cluster furthers export and attracts foreign capital. There are three factors that can explain the genesis and development of cluster (Porter, 1998, p. 25). 1. The degree of local competition 2. The conditions for the establishment of new enterprises 3. The degree of structural links in the geographical field When in turn a critical mass of enterprises is established in the region, the cluster will develop self-enforcing social mechanisms, perpetuating further development. The theoretical basis for the cluster theory is found with Alfred Marshall (1890).3 An increasing interest in cluster theory appears in the 1990s with, among others, Krugman (1995) and Porter (1990, 1998). Porter (1998, p. 266) says that cluster is a new way of understanding economic organizations in developed economies subject to global competition. Porter (1990) has in his theory for the competitive position of nations put cluster in a very prominent role. Porter (1998, pp. 197–198) defines cluster in the following way: “Clusters are geographic concentration of interconnected companies, specialized suppliers, service providers, firms in related industries, and associated institutions (e.g., universities, 3 https://en.wikipedia.org/wiki/Alfred_Marshall.

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standards agencies, and trade association) in particular fields that compete but also cooperate.” A further link between cluster theory and systemic thinking has been made by Porter (1998, p. 213), briefly explaining the essence of cluster: “a system of connected firms and institution whose value as a whole is greater than the sum of its parts.” This makes the construct emergence4 central for cluster theory as much as for systemic thinking. In the global economy there are three main factors having been pointed out by Porter (1998, p. 209) regarding businesses capable of competing: the degree of development in the cluster in which the businesses operate, productivity, and the innovative potential of the businesses. Productivity and innovative potential are, in fact, stimulated by their being established in a well-developed cluster. The presence of welleducated persons, effective public institutions, and the absence of bureaucratic hindrances give indications as to the degree of development on the part of a cluster. To think in terms of cluster will from a competitive point of view be important both for the individual business and the formation of the economic policy carried out by the authorities (Engel, 2017). A positive economic effect of clusters is, among other things, that they promote the establishment of new businesses stimulated by innovations made in the cluster. Another effect of cluster is the reduction of transaction costs, among other things, because the input factors are cheaper and the fact that time lags are reduced (Heeks & Foster, 2017). The more developed the cluster, the more represented the businesses. This is evident from Porter’s diamond (1990) and is underlined by Porter (2002). The competitive position of the individual company is to a greater extent determined by the degree of development on the part of the cluster and to a lesser 4 See Glossary on concepts.

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extent on the size of the individual business or trade in the cluster (Porter, 1998, p. 215). It will also be easier to attract specialized employees from other places in the region when developed cluster exist (Engel, 2017). In the same way, as the costs of input factors are reduced in clusters, similarly costs relative to information processes are reduced. For analytical reasons, we choose to denote the former as transaction costs and the latter as transformation costs. Transformation costs are reduced due to the fact that it becomes easier to understand the needs linked to placing orders, being a customer, user, etc., in addition to clusters being strongly internally linked. A well-developed cluster can also have well-developed complementary offers, not only for the individual final buyer but also for local requesters of services in the cluster. This is organized through a well-developed system of subsuppliers. Businesses in clusters quickly manage to grasp new trends and changes in the needs of customers. The reason for this is density, the strength of structural links in the cluster, the access to information, and the spillover effects of information and knowledge operating in cluster. If we compare clusters in more developed economies to clusters in less developed economies, the main difference to be noticed is that companies in clusters in developed economies are exposed to a much fiercer international competition than companies in less developed economies (Porter, 1998, p. 233). During the exposure to global competition, productivity and the degree of innovation are furthered. Low-cost strategies will only to a limited extent be appropriate in developed economies, since developed economies will never be able to compete with the cost structure of less developed economies. Developed economies compete on the basis of innovative clusters with a high degree of productivity. If the purpose is to develop material prosperity, the challenge will

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be to further productivity and innovative ability (Porter, 1998, p. 234). There appears to be a direct link between the degree of development in a cluster and the per capita income (Porter, 1998, p. 234). The two most central factors capable of distorting the position of clusters are change in technology and competition. They can be changed irrespectively of each other and in interaction with each other (Porter, 1998, p. 236). One interesting point in cluster thinking is that it may be fruitful to focus on the boundaries between two or more clusters. In this boundary area there might be potential for the development of unique products or service opportunities. These may then be developed into new specialized products. One effect of cluster development might be businesses reestablishing themselves in the region and national and international investments being attracted. This furthermore reenforces the degree of development in the cluster. Special competence is attracted, causing the cluster to be further reinforced. In this way structural links in the cluster are developed. Basically there are four factors of critical importance to the possible success of a cluster. These are the four factors in Porter’s diamond (1990): input factors, context factors, demand factors, and complementary factors. Authorities play a major part in the development of institutions, which, among other things, should ensure that the four main factors are instrumental in promoting clusters in a region. If productivity and the degree of innovation for some reason are hindered, this will lead to a reduction in the competitive ability of the cluster. The cluster will then initiate the process leading to its own disintegration (Porter, 2002). External conditions capable of threatening the development of a cluster are, among other things, technological, economic,

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and political changes. Technological and economic changes can lead to changes in demand and thus rapidly alter the competitive environment of the cluster. Political changes can lead to an altered business climate, influencing the competitive environment negatively. Political stability helps sustain expectations over a period of time, which will further the development of trust between the various actors in the economic field. While the paradigm of industrial policy was/is oriented toward scale and scope, then the cluster paradigm is oriented toward productivity and innovation (Porter, 1998, p. 249). The above discussion implies that unleashing the innovation potential in social systems require an increased emphasis on connectivity and social relations among a number of actors and on organizational learning.

ORGANIZATIONAL LEARNING: KNOWLEDGE AND INNOVATION Tusman and Nadler (1986, p. 75) explicitly express that innovative organisations have one thing in common, being “highly effective learning systems.” However, there exists considerable controversy regarding the term learning, and the literature on the topic tends to be disjointed and somewhat confusing. Much of the popular discussion on learning fails to distinguish carefully between individual learning and organizational learning, or collective learning. While it is true that knowledge is carried in the heads of individuals, it is equally true that it must be embedded in organizational routines to more fully maximize its utility. Fiol (1994) argue that organizational learning, like individual learning involves the development of new and diverse interpretation of events and situations. Unlike individual learning, collective learning also

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involves developing enough consensus around those diverse interpretations for organization action to result, i.e., the sharing of mental models. Powel (1998) further argues that knowledge is located not only in individuals and in the work routines of organisations but also in knowledge networks linking organisations, i.e., clusters. In a Schumpeterian world of innovation-based competition, learning needs to be dynamic. Teece et al. (1997, p. 515) refer to the term dynamic as: “the capacity to renew competence so as to achieve congruence with the changing business environment.” We define organizational learning here as the firm’s ability to structure and systematize knowledge in and between systems, both for the purpose of achieving congruence with the changing business environment and for creating the firm’s own future. Our definition of organizational learning is closely linked to our definition of knowledge and represents a dynamic perspective on learning. The definition is contrasted to authors who regard organizational learning as a pure management process. Mahoney (1995, p. 95) defines, for example, organizational learning as “the process whereby management teams change their shared mental models of their company, markets, and their competitors.” This is in our understanding not organizational learning, but management learning. Hence, in order for learning to become organizational, the shard mental models must encompass all members of the organization. This is strongly underlined by Senge (1991) and Senge, Kleiner, Roberts, Ross, and Smith (1994). A prerequisite for developing shared mental models is cooperation. “Co-operation is an outcome that despite potential relative costs to the individual is “good” in some appropriate sense for the members of a group, and whose achievement requires double action” (Dugatkin, 1997, p. 14).

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Our definition of organizational learning is also linked to Argyris and Schøn’s (1978) and Fiol and Lyles’s (1985) use of the concept, in addition to Ackoff’s (1974, 1976, 1981, 1984) concept “creating the corporate future,” and Weick’s (1979) concept “future perfect thinking,” as these authors also link organizational learning to visions mobilized toward a common goal. The definition is also linked to Kanter’s et al.’s (1992, p. 383) emphasis on the importance of “vision” in creating a company’s future: “vision is an attempt to articulate what a desired future for a company would be.” Vision understood in this way is to realize a common dream about the desired future, which is qualitatively different from extrapolating past trends into the future.5 Nonaka (1994) argues that a proactive view of knowledge creation characterizes learning as an innovative process in which the organization creates and defines problems and then actively develops new knowledge to solve them. Lumpkin and Dess (1996, p. 146) argue that “…a proactive firm is a leader rather than a follower, because it has the will and the foresight to seize new opportunities.” They make a distinction between competitive aggressiveness and proactiveness, where proactiveness has to do with meeting demand whereas competitive aggressiveness is about competing for demand. Hence, there is

5 The definition as developed here links organizational learning to scenario planning. There are two principal categories (not typologies) of scenario planning: (A) Trends are predicted on the basis of statistical and historical facts, and, on the basis of different prerequisites, indications of possible futures are given. (B) The starting point is what future is intended for the system (organization, society etc.), and then a reversal into the present is made, with regard to linking patterns, interactions succedents, effects, spinoffs, and possible side-effects of actions which eventually must be initiated in order to create the desired future. We then have two main categories of scenario planning, with a host of types within each of the categories.

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a link between vision and proactiveness in relation to innovation. Our definition also pays attention to the need of organizations to incorporate changes in the environment as a part of its learning strategy. This has previously been pointed out as a necessary condition for organizational learning by, for example, Argyris and Schøn (1978), Fiol and Lyles (1985), and Huber (1991). A consequence of our definition is that organizations must be designed to build in the ability to change, in their structures, processes, and activities, so that they can balance adaptation to change in the environment, while being instrumental in creating the future for themselves and others, i.e., develop innovations. Learning and change are closely related concepts. If we are to assume that learning has taken place in an organization, this must be expressed through various change processes in the organization. This is in line with Huber (1991, p. 89) who argues that: “An entity learns if, through its processing of information, the range of its potential behaviours is changed.” Although organizational learning presupposes change, as pointed out by Huber (1991), change and stability are not necessarily opposite poles. Change is here not regarded as the antonym of stability, but stability and change are regarded as complementary entities. Change is a necessary condition for an organization to maintain a steady course toward one (or several) goals. Bateson (1972, 1979) is partial to the use of the tightrope walker example, which metaphorically could be applied to organizations. For the tightrope walker to sustain his stability on the line going from one end to the other, he has to keep the position of his arms and legs in constant change. In this example Bateson points out that change is a necessary condition for stability. One of the tasks for leadership will, with this example as the basis, be to make sure that the various alliances and units in an organization continuously

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Fig. 1.2. Processes Leading to Innovation in Social Systems. Social mechanisms

Social processes

Vision

Proacveness

Cooperaon

Phenomenon

Innovaon In social systems

Shared mental models

build in learning and change as a natural part of their mental models. We have systematized the most important social mechanisms and processes of the model element: organizational learning in Fig. 1.2. We believe that the processes related to organizational learning, which promotes innovation in social systems, is proactiveness and shared mental models, i.e., the creation of the future for the social system. We further believe that the social mechanisms6 which trigger these processes are visions and cooperative behavior. Cooperative behavior as presented in Fig. 1.2 is meant as a social mechanism to behave cooperatively, not to achieve cooperation.

INTERNAL KNOWLEDGE The internal knowledge base of a company is closely related to its competence. Nordhaug (1994) defines competence as 6 See Glossary on concepts.

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knowledge and skills performed toward the completion of a task. This indicates that for knowledge to contribute to the value added, usually, it needs to be applied to a task by individuals possessing certain skills. Competence thus implies a link between knowledge, tasks, and skills. The question is “What tasks to perform, and what skills and knowledge are needed to perform the task?” In the same manner as other resources, for example capital and work, competence has certain specific properties. Competence is a resource, which is not easily divided into smaller units. This is primarily because it is linked to individuals. Competence is also bounded in terms of time. Furthermore, it is neither easily converted nor speedily and efficiently exchanged. One of the most critical aspects of competence-building efforts is in other words to what extent it is practicable to transfer competence to a real work situation. Competence can be general or specific. General competence could be exchanged in the job market in general, whereas specific competence can only be exploited by the individual companies. Evolving from the efficiency-based approach is the concept of core competence. Prahlad and Hamel (1990, p. 82) define core competence as “the collective learning in the organisation, especially how to co-ordinate diverse production skills and integrate multiple streams of technologies.” One of the cornerstones in the efficiency-based approach is found in the existence of isolating mechanisms as the fundamental determinants of firm performance. As argued by Rumelt (1987), such isolating mechanisms, hindering or delaying imitation, are required to encourage innovation. Isolating mechanisms are created through the development of resources, which are nonimitable, nonsubstitutable, and nontransferable. Explicit knowledge is increasingly accessible for a growing number of companies through, for example,

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information and communication technology. Hence, competitive advantages based on explicit knowledge will to an increasing extent only provide a short-term advantage. Therefore knowledge must be turned into competence not easily imitated by others. Spender (1993) and Howells (1996) argue that the resource base perspective, the dynamic capability approach and organizational learning have added new insight to strategy literature, but relatively little importance has been attached to the impact of tacit knowledge. We have, however, recently seen an increased attention toward tacit knowledge as being the most important isolating mechanism (e.g., Grant, 1996; Nonaka & Takeuchi, 1995). Polanyi (1966, p. 4) who developed the concept of tacit knowledge says: “We can know more than we can tell.” Hence, this knowledge is difficult to communicate to others as information and can at best be digitized with great difficulty. Polanyi’s theory about tacit knowledge (Polanyi, 1962, 1966) deals with how individuals develop and use their knowledge in a practical job situation. Tacit knowledge is embodied in action (practice) and is linked to concrete contexts. The distinction between knowledge and a skill can be expressed in the following way: “a skill combines elementary muscular acts” (Polanyi, 1966, p. 8). Knowledge, on the other hand, is not necessarily linked to muscular acts, but could be. Or according to Polanyi (1966, p. 19): “We are relying on our awareness of a combination of muscular acts for attending to the performance of a skill.” It is the awareness concept, which here links knowledge, and especially tacit knowledge, to the performance of a skill. Central in Prahalad and Hamel’s definition of core competence is knowledge integration. Grant (1996) argue that the most important task for companies is to integrate knowledge to generate value for customers/users. Several authors have pointed out the internal knowledge base of a

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company and the relations between the various knowledge areas of the company as the basis for innovation. A major uncertain factor pertaining to this knowledge integration is to what extent tacit knowledge is conducive to preventing competitors from imitating the core competencies of the company. The more tacit knowledge is allowed to dominate the core competencies, the more immune the company will be against imitation of them and the better the chances will be of profiting from innovation over a period of time, i.e., the core competence becomes distinctive. Building core competencies is particularly significant when tacit knowledge dominates the core competencies. Indeed, the more tacit knowledge is embedded in the core competence, the more immune the system is, and the more sustainable the advantages are. Connectivity is an expression of the number of connections in place among agents in a network. We argue that knowledge integration leads to and is dependent on a high level of internal connectivity. We further argue that internal connectivity is an expression for a shared value system, shared visions, shared mental models, and knowledge based on experience. Taken together it is the sharing of an organizational culture, which makes the organizational capabilities dependent on history, i.e., path dependency, which will make imitation difficult, if these capabilities are firm specific. The core competence will thus function as an isolating mechanism. It is this isolating mechanism which can cause rents on the basis of innovations to be sustained over a period of time. The core of this isolating mechanism is, according to our presentation of core competence, tacit knowledge, since this is difficult to communicate to others as information and because it is embedded in the culture of the organization. Tacit knowledge is also based on learning mechanisms, i.e., learning by doing, using, experimenting, and interacting, which cannot easily be transferred to other companies.

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However, the precondition for firm-specific tacit knowledge (and competence) to be strategic is its value for customers in a market. Teece et al. (1997, p. 516) defined core competence as “those competencies that define a firm’s fundamental business as core.” The core is decisive in what tasks the firm should conduct and the corresponding skills and knowledge needed to perform these tasks. In a business world characterized by a high degree of turbulence and complexity, tasks, skills, and knowledge will have to change accordingly. Hence, firms need to continuously upgrade their competencies. Lei, Hitt, and Bettis (1996, p. 550) noted: “Core competencies cannot remain static; only those firms that continue to invest and upgrade their competencies are able to create new strategic growth alternatives.” Hence, in building its competencies companies need to simultaneously focus on what the system is designed to do and on the tradability of its competencies. Lei et al. (1996) further argue that the concept of dynamic core competence is based on continuous learning and development of core competence. The tradability of the competencies presupposes information about the environment (market) in which the firm operates, but also the capacity to absorb information. Antonelli (1996) argue that receptivity is the capability of each member of the firm to absorb the information received. Hence a firm receptivity is related to its absorptive capacity, which is a firm’s ability to value, assimilate, and utilize new external knowledge. As a consequence, knowledge integration comprises the integration of both internal and external knowledge as a prerequisite for the initiation of innovation processes in the company. The dynamic perspective in Polanyi’s theory related to tacit knowledge also corresponds to the evolutionary perspective presented by Nelson (1987, 1988) and Nelson and Winter (1982) and “Austrian economics.” Helfat (1994, p. 1720)

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clearly says: “Tacit knowledge…underlie the evolutionary theory of business and firm development and strategy.” The company’s dynamic core competence is also dependent on organizational routines. These are designed to ensure interaction between individuals and partial systems in the organization, while at the same time coordinating activities in such a way that the organization produces what it is meant to produce without too much internal tension and turmoil. However, static routines may limit the kind of learning that a firm may undertake. Lei et al. (1996, p. 559) argue that: “Dynamic routines refer to the organisations cognitive maps and particular approaches to framing that provide the basis for understanding and creating new skills and technologies.” Hence, multiple perspectives and routines become paramount, avoiding a single dominant logic. What the system is designed to do, linked to competence and tradability, is contingent on dynamic routines to balance the processes in such a way that dynamic core competencies can be developed as something distinctive in relation to the company. It is the exploitation of already existing competencies and the development of new ones, which constitute the function of dynamic routines. There is in other words a crucial distinction between the resources (physical, human, and intangible) and competencies of the company; i.e., the resources are potential triggers of competencies but presuppose management and effective social mechanisms to trigger these competencies. To generate value for the customers and to ensure sustainable competitive advantages, the company must continuously upgrade its competencies and technology toward tradability, through an organizational learning process, where innovation is an important entity. A company is distinctively different from other companies in the way it develops and recombines its dynamic core competence, in addition to the relation between this and tradability.

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Fig. 1.3. Internal Knowledge. Social mechanisms

Knowledge integraon

Social processes

Phenomenon

Internal connecvity Innovaon In social systems

Dynamic rounes

Dynamic core competence

We have systematized the most important social mechanisms and processes with the model element: the internal knowledge base, in Fig. 1.3. We believe that the process related to the internal knowledge base, which promotes innovation in social systems, is internal connectivity in addition to dynamic core competencies. We further believe that the social mechanisms, which trigger these processes, are knowledge integration and dynamic routines.

EXTERNAL KNOWLEDGE We have argued that a social system needs internal connectivity and dynamic core competence, triggered by knowledge integration and dynamic routines to build its internal knowledge base, so as to maintain innovative power. However, most social systems will not be in the position to maintain a high standard of internal competence in all fields. Antonelli (1996, p. 284) states: “…innovation capability depends in fact also on the amount of information that each firm is able to receive from the environment in which it

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operates.” Iansiti (1998, p. 210) argues that: “…no single organisation could develop all its options internally any longer.” He further argues (1998, p. 211) that in developing innovations: “…what is traditionally thought of as R&D must provide relevant knowledge to an incredible complex and uncertain context. The source of this knowledge is more diverse than ever, and it is largely external to the firm.” To get access to this knowledge, companies need relations to its customers and other external actors. In literature we find this primarily discussed through the focus on a company’s proximity to its customers and through national and regional innovation systems (Cooke, 1996; Hansen & Serin, 1997). The link between customer proximity and innovation was focused on in the 1960s and 1970s through demand-oriented theories. Myers and Marquis’s (1969) study of more than 500 innovative companies confirmed the importance of customer relations for innovation activities in companies. This was further corroborated by Mowery and Rosenberg (1979) and strongly emphasized by Andersen (1994) as an important source of innovation. Andersen (1994, p. 57) explicitly expresses: “…firms with well-established information channels to sophisticated customers have a comparative advantage in the creation of innovations.” Despande et al. (1993) also found a strong relation between a high degree of innovation and customer proximity. Customers as triggers of innovation activity have also been pointed out by many authors.7 Lundvall (1988) also emphasizes the “user– producer” proximity and argues in favor of the contention that it is learning by interacting, which furthers innovation. Andersen (1994) argues that the interactive learning process, 7 Von Hippel (1986), Craig (1996), European Commission, 1995, and Knoedler (1993).

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occurring in the borderline area between the customer and the company represent a triggering effect on innovation activities. Learning by interacting presupposes information and communication systems where we can make inquiries and decisions together. Hence, we argue for the importance of communicative proximity, which not necessarily means physical proximity. Audretsch and Feldman (1996, p. 258) argue that: “…it is the communication between individuals which facilitates the transmission of knowledge across agents, firms, and even industries, and not just the high endowment of workers’ knowledge that is conducive to innovation activity.” A number of authors argue that there is a link between customer proximity, market and technology sensibility, and the ignition of innovation processes in the companies.8 It is believed that such proximity leads to a market orientation (Slater & Narver, 1995). Market orientation presupposes information and communication systems, ensuring continuous updating of needs and wishes on the part of the customers, in addition to changes in these, in order to generate value for the customers.9 But customer proximity must be balanced against “the tyranny of the market” (Hamel & Prahalad, 1991, p. 83). This means that there is a danger of only focusing on existing customers because it may entail an oblivious attitude toward up-and-coming markets and the new competitors who will appear in the latter category (Argyris, 1994). Christensen (1997) also points out the danger of only listening to existing customers. Hence, there is also a need to be distant to existing customers. The point is to create a balance between proximity and distance, which create room for learning leading to innovation. 8 Midley et al., 1992 and Deshpande, Farley, and Webster (1993). 9 Narver and Slater (1990) and Jaworski and Kohli (1993).

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Learning from competitors, suppliers and future users/ suppliers is also found to be a source of innovative ideas.10 The idea of national and regional innovation systems is theoretically embedded in criticism of the linear innovation model. The idea of national innovation systems dates back to List’s idea of national systems for the political economy (Freeman, 1995, p. 5). The first one to explicitly use the term national innovation systems was, however, Freeman (1987), who argued that company’s relations with other companies are crucial to the innovation activity of the company. Freeman11 defines national innovation systems as: “The network of institutions in public and private sectors whose activities and interactions initiate, import, modify, and diffuse new technologies.” Nelson (1987, 1988) also focused on the phenomenon on the basis of systemic thinking. Then the term was developed by Lundvall (1988), Andersen and Lundvall (1988), and Johnson and Lundvall (1991), who discovered an empirical foundation for national innovation systems in Danish agricultural Industry. Porter’s (1990) focus on industrial clusters where the interaction between industries (inside a country) factor conditions, demand conditions, related industries and the competitive arena also represent a dynamic system perspective. Analogue with national innovation systems are regional innovation systems, referring to the cognitive infrastructure and structural links existing in a region (Cooke, 1996). Regional innovation systems include the same elements as in national innovation systems, only that the geographical area is smaller. The suppositions behind the two concepts

10 Von Hippel (1986, 1988), Imai (1989), Lundvall (1988), Andersen (1992), ˚ and Hakansson (1989). 11 Freeman (1987) in OECD report 1992:1.

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are that companies establishing relations with various knowledge institutions and enterprises will be able to develop a higher degree of innovation activity, improve their competitive position, and furthermore exploit their growth potential better than other companies not doing it will be capable of. Even if the necessary elements are present for the existence of national and regional innovation systems, these are not sufficient preconditions for the innovation system to be operative. External connectivity ensuring interaction and coordination must also exist. This will generate a conceptual distinction between potential and operational innovation systems, both regional and national ones. The purpose of this conceptual distinction is to show the structural prerequisites that have to exist in order for national and regional innovation systems to promote innovative behavior at the company level. For national and regional innovation systems to be operational the following prerequisites must be fulfilled (see Cooke, 1996): 1. institutional range of variation, 2. a high degree of connectivity between companies and between companies and knowledge institutions (external connectivity), and 3. the existence of cooperative behavior within the system of connectivity. By applying the concept operational innovation systems, it is possible analytically to study the existence of degrees of, for example, regional innovation systems, from potential to operational, and how this influences innovation activities in the individual companies. The same argument as that used in discussing “the tyranny of the market” may also be applied for regional and national systems of innovation. The

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argument is that that a high degree of connectivity in such networks can entail limitations in innovation activities, as conventional solutions may be diffused in such networks. To meet this potential inertia, and to be more in tune with an economy that is becoming increasingly globalized, there may also be necessary to be linked to international knowledge institutions and networks. This may be handled by the companies themselves or, as suggested by Johannessen, Olaisen, and Olsen (1997), through regional innovation centers, which operate as knowledge brokers and information scanners in the global environment. We have systematized the most important social mechanisms and processes of the model element: the external knowledge base, in Fig. 1.4. We believe that the processes related to the external knowledge base, which promotes innovation in social systems, are market and technology sensibilities in addition to external connectivity. We further believe that the social mechanisms, which trigger these processes, are external information and communication systems, in addition to customer proximity.

Fig. 1.4. External Knowledge. Social mechanisms

External informaon and communicaon systems

Customer proximity

Social processes

Phenomenon

External connecvity Innovaon In social systems Sensibility towards market and technology change

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CONCLUSION We have argued that it is social mechanisms among individuals and companies especially in clusters which initiate and sustain processes related to organizational innovation, and the research question we set out to investigate was: Which social mechanisms influence those processes affecting innovation in social systems. At the outset of the chapter we proposed that we were using a systemic angle of incidence. One important question in systemic thinking is: What is the pattern which combines a given phenomenon or problem? The pattern is connected by relationships. Systemic thinking emphasizes relations between elements more than the substance of the individual element. In relation to the present work, one should debate how the various elements included in the external part of the knowledge base could be structurally linked to the development of the internal knowledge base. A major consequence of the idea of the importance of the external part of the knowledge base is that innovation activities depend more on a system of relations between the elements than on the effectiveness of the individual elements viewed in isolation. It is around this part–whole understanding our explanation should be focused, i.e., connections and patterns between the internal and the external knowledge base should be subject to holistic evaluations, both in terms of organization of such links and in the development and integration of knowledge within these structural links, i.e., different types of clusters. Connectivity in and among companies constitutes a robust indicator of the learning and innovation ability of companies. New organizational models (e.g., process organization and virtual organization) could potentially elicit a creative diversity in evidence in companies, by forging various knowledge domains into focused systems for development and integration of knowledge. The idea is that when several knowledge

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domains (practical, theoretical, internal, and external) are connected for one specific purpose, the inherent variety may release what is creatively new, igniting innovation in social systems. What has been mentioned above will in our view reinforce the notion of a tighter connectivity between the various elements in the external knowledge systems and the development of the companies’ knowledge base, in order to release the innovation potential in the companies. A synthesis of the model discussed in this chapter is shown in Fig. 1.5. With knowledge being the companies’ most important resource with regard to the development of innovations, strategic knowledge development will be essential. To guide and give direction for such strategic knowledge development, creating visions and cooperation triggering proactiveness and shared mental models become essential. We have argued that these elements are crucial in creating organizational learning. However, the raw material for learning in a turbulent and complex environment is found in the internal and external knowledge base. Hence, strategic knowledge development implies the need for ensuring that necessary information and knowledge become accessible to the system. For companies, this could be achieved by establishing or nurturing external information and communication systems and customer proximity, indicating the need for a solid link to the companyexternal part of the knowledge base and a sensibility toward market and technology changes. In order to profit from the explicit and tacit knowledge within these systems, tight personal links are essential. This could be maintained both through the institutional contacts of the company and through the personal contacts of each employee with their professional networks. In order for organizational learning to be developed in a company, these elements will however have to be subject to routine, putting

Organizaonal learning Proactiveness and shared mental models gjensidig påvirkning

Vision and cooperation

Knowledge Leading to innovation

The internal Knowledge base

Knowledge integration And dynamic routines Internal connectivity and dynamic core competence

External info., communication systems and customer proximity External connectivity and sensibility towards market and technology change

The external Knowledge base

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Fig. 1.5. Knowledge Leading to Innovation.

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the companies in a position to create learning systems that are robust in relation to important knowledge actors internally in the company. In order for companies to exploit the information and knowledge developed by the individuals of the company through their external contacts, knowledge must be integrated in the company and be applied through the solution of concrete company-related problems. This implies focus on knowledge integration and, in a turbulent and complex business environment, dynamic routines. In the same way as for external knowledge, tight internal connectivity among the employees are crucial, in order to integrate both the explicit and the tacit knowledge. This is knitted together by the company’s dynamic core competencies. At the outset of this chapter we argued that the concept of social mechanisms is controversial in social science. However, seen together, the social mechanisms we have isolated all become part of a system of mechanisms triggering processes leading to unleashing innovation in social systems. We believe that changing the social processes leading to innovation in social systems occur through social mechanisms. Hence, to achieve innovation in social systems, social mechanisms should become our main concern.

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Von Hippel, E. (1986). Lead-users: A source of new product concepts. Management Science, 32(7), 791–805. Von Hippel, E. (1988). The sources of innovation. Oxford: Oxford University Press. Weick, K. E. (1979). The social psychology of organizing. London: Addison-Wesley Publishing Company. Zaltman, G., Duncan, R., & Holbeck, J. (1973). Innovations and organizations. New York, NY: John Wiley & Sons.

2 KNOWLEDGE MANAGEMENT AND INNOVATION: ASPECT OF A THEORY

INTRODUCTION Norms specific to the company, development, integration, and the use of knowledge are supposed to correlate strongly with value generation in the individual companies and the economy in general. Innovation in this context is seen as the core of value generation and in the positioning by the company in an increasingly internationalized and globalized economy. The connection between innovation and economic growth is made visible in “the new theories of growth” and has also been discussed in the “Green Chapter on Innovation.” (Greenhalgh & Rogers, 2010). Abromovitz (1989) explicitly expresses the connection between knowledge development and economic growth: “…the advance of knowledge lies at the core of modern growth process.” Contemporary economic systems have become more knowledge intensive than in the past. That knowledge intensity and knowledge growth influence productivity improvements as well as quality improvements has

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been documented by Thompson (1996, p. 95) and Dabbert and Lewandowski (2017). The management of knowledge is also critical at both the strategic and operational levels of the companies. Continuous changes in the state of knowledge produce new disequilibrium situations and, therefore, new profit opportunities, and they do so at an increasing pace. Thus, as the competitive process eliminates an opportunity, changes in the stream of knowledge produce other opportunities. This is in line with Schumpeter’s vision of competition as a process of creative destruction, rather than as a static equilibrium condition. Consequently, there is an increasing emphasis on a knowledge-based economy. This unending stream of knowledge which keeps the market in perpetual motion calls for companies to execute continuous innovation and at the same time limit imitation. Knowledge about the possibility of innovation, as well as innovation being linked to competitive advantages and greater earning power, is a type of knowledge which is important in order to elicit innovation activity. If this type of knowledge is not accepted in the company context, innovative activities will most likely not be prioritized. Knowing that something is possible has proved to be extremely important to facilitate initiation of action. This is a type of knowledge which is critical for the development of action norms in the social system. Not knowing that innovation is possible, and not knowing conceivable consequences, one is likely to act in a system with a tendency to focus on “business as usual,” rather than innovative processes. Competitive advantage can be sustained only if capabilities creating the advantage are supported by resources that are not easily duplicated by competitors. Competitors are delayed from imitating innovators’ actions when, for example, knowledge available to them about these actions is ambiguous, and hence

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are “invisible.” Such resources are difficult to replicate because they are tacit (causally ambiguous). Tacit resources creating invisible assets are skill based and people intensive. This implies that as a resource, people are important, not just as participants in the labor force, but as accumulators and producers of invisible assets. The importance of tacit knowledge, competence specific to the company, and organizational learning for entry barriers and competitive leadership has been pointed out by Kaplan (2017), among others. As invisible assets are the unobserved factors creating knowledge in the organization, they do, in addition to limiting imitation, also help to position a firm to exploit new opportunities, hence enhancing continuous innovation. Invisible assets are key success factors because they are difficult to obtain. Invisible assets are often the only source of competitive edge that can be sustained over time. Also Nonaka and Takeuchi (1995) emphasize the role of tacit knowledge as well as the interaction between tacit and explicit knowledge. A firm’s capabilities are developed primarily on the basis of social norms and values already evident in social relations in the firm. This in turn impacts how the company develops and integrates knowledge, thus putting the company in a position to develop in an innovative direction. These elements will in turn affect the competitive position of the company. It is this context Fig. 2.1 aims to illustrate, and which this chapter is related to. The questions we will try to shed light on in this chapter are: What is the connection between norms specific to the company, the knowledge basis of the company, and innovation? We will see norms specific to the company in the light of social autopoiesis theory. It is this theory which will be used when evaluating the importance of knowledge development and innovation.

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Fig. 2.1. A General Model for Norms, Knowledge Creation and Innovation. Degrees of normative closeness and cognitive openness reinforces

determines

support

The competitive position support

support

Organizational innovation

enables

Creating new knowledge for innovation

The chapter is organized as follows: First companyspecific norms are debated in an autopoietic perspective. Then we will discuss company development and knowledge integration in organizations. We will then discuss the innovation concept. Finally we will integrate the entities of the model to underline how they can improve a company’s competitive position.

NORMATIVE CLOSENESS AND COGNITIVE OPENNESS The importance of a company’s norms and values pertaining to the development of the knowledge basis and for innovation activity has been described by Lantis (2016). Barton (1995) clearly expresses, “Values and norms: These determine what kinds of knowledge are sought and nurtured, what kinds of knowledge-building activities are tolerated and encouraged.”

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Turner (1993, p. 3) defines norms as: “a generally accepted way of thinking, feeling or behaving that is endorsed and expected because it is perceived as the right and proper thing to do. It is a rule, value or standard shared by the members of a social group that prescribes appropriate, expected or desirable attitudes and conduct in matters relevant to the group.” Parson (1967, p. 155) defines norms as: “Norms thus have, above all the function of integrating the needs of operating units with each other and reconciling them with the needs of the system as a whole…Norms spell out expectations for collectives and for persons acting in roles, and in doing so, may bring to light discrepancies among these expectations” (Parson, 1967, p. 155). Norms can also be understood as cognitive maps, interpretative schemes, cause maps, organizational ideologies, cognitive frameworks, frames of references, shared perspective, implicit thought structures, organizational schemes, dominant logic, perceptual filters, or belief structures. Autopoiesis means self-producing systems. The autopoiesis theory was developed by Maturana and Varela (1980), Maturana (1981), and Varela (1984). Luhman introduces the distinction between normatively closed and cognitively open systems at the social level (Luhman, 1975, 1982, 1990, 1992, 1995). An autopoietic social system with this distinction is simultaneously closed (normatively) and open (cognitively). The normative and the cognitive are also structurally linked, generating interaction between these two subsystems. A crucial point here is: “closure is a condition for openness” (Luhman, 1986, p. 183). It is, among other things, the link between the normatively closed and the cognitively open which is Luhman’s contribution to the autopoietic theory for social systems. The cognitive openness is a form of awareness or knowledge link to the environment of the system.

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For the individual system there exists a system-specific normative basis. At a superior recursivity level there is also a normative superstructure in evidence, influencing the normative basis for the subordinate recursivity level, i.e., the system in focus. The study of social systems as autopoietic systems, according to Luhman (1986, p. 186): “is a theory of selfreferential systems, to be applied to observing systems as well.” This links social autopoiesis theory to second-order cybernetics, as expressed by Von Foerster (1981), Geyer and Van der Zouwen (1978, 1992), among others. For the individual researcher it becomes just as much a question of self-observation as observation of the social system. It is selfreflection which Luhman and Foerster bring into the discussion. Luhman (1986, p. 187) says: “To combine these two distinctions (between autopoiesis and observation, and between external observation and self-observation, our inclusion) is one of the unsolved tasks in systems theory.” The core of the problem as we see it is that an observer observing a social system constitutes an autopoietic system in his own right, i.e., when we gather information about social systems we cannot avoid collecting information about ourselves. Luhman (1986, p. 188) points out that in order to solve this problem (paradox) a sort of exchange between external observation and self-observation is required. The system-specific normative basis, regardless of its being based on a model-weak foundation, generates an attention focus in the system. It influences and sets standards for signals, symbols, and the information to be selected, in addition to expectations on the part of the individual actors in the system. This in turn produces certain experiences in the system, which then reinforce or sustain the system-specific norms. Luhman emphasizes communication as the very foundation for social systems. Luhman’s conceptual pairings (normatively

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closed and cognitively open) make it possible for a social system to be simultaneously self-producing in terms of social norms and still maintain the capability of learning, through the cognitive openness of the system. Luhman (1990, p. 12) points out: “the concept of autopoietic closure has to be understood as the recursively closed organisation of an open system.” The point is the extent to which normative closure and cognitive openness exists in a specific system. It is, according to Luhman (1990, p. 13), communication which constitutes the evolutionary potential for the construction of systems able to “maintain closure under the condition of openness.” Even if the system is closed normatively, it does not follow that it is not subject to influences from the outside world. An autopoietic system is openly cognitive and can therefore both influence other systems and at the same time learn and adapt to the outside world. An autopoietic social system is, in other words, both open and closed at the same time. There is openness toward the outside world, starting as internal reflection, redefinition of situations, and generation of communication for the purpose of changing the system-specific normative basis. This normative closure is secured by means of a number of mechanisms preventing information and communication from the outside from penetrating the system. Examples of such mechanisms could be laws, rules, regulations, routines, and tribal language, i.e., the concepts, theories, and axioms of various professions. In turn these mechanisms can be constituted by standards, i.e., expectations and notions from economic, social, political, and cultural systems of the outside world. There is not any agreement as to whether social systems can be regarded as autopoietic systems. Luhman (1982, 1986, 1990, 1992, 1995) and Robb (1989) argue in favor of the contention that the theory can be adapted to social systems. Maturana (1981), Varela (1979), and Mingers (1989) have

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more doubt about the fruitfulness of this analogy. Our view is that autopoietic processes can be disclosed as parallel processes, not identical, in social systems and organizations. By this we mean that knowledge based on the autopoiesis theory at the cell level with Maturana and Varela can be adapted for the purpose of acquiring knowledge of social processes in organizations regarded as social systems. This we also interpret as Luhman’s point of view (1986, p. 173). Luhman’s application of the autopoiesis theory can be used to describe, explain, and possibly predicate change or lack of change in social systems. Luhman’s autopoiesis understanding is neither a conflict model nor a consensus model, but an evolution model. The normative elements have as their specific purpose to reproduce system behavior, while the cognitive elements are supposed to balance the normative development in the environment, putting the system in the position to reproduce its behavior continuously with regard to a mutual evolutionary development, i.e., the system itself is instrumental in creating its environment and simultaneously adapting to what other systems create in the environment. The system-specific normative basis constitutes the starting point for the development of identity on the part of the system, i.e., what separates it from the environment, and how the system understands itself. Through self-observation in the system, and reflection on itself and in relation to the environment, learning can take place. This reflects the cognitive opening of the system. The link between the cognitive opening and the environment is an opening for learning (Chia, 2017, pp. 107–118). The normative superstructure and the system-specific normative basis have a mutually conservative effect. The cognitive openness, on the other hand, adds requisite variety to the system.

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Selection processes (signals, symbols, information), the expectation mechanism, and the experience dimension reproduce the system-specific normative basis. It is basic experiences which to a great extent determine the selection mechanisms we utilize and the expectations determining our behavior. The selection processes and the expectations then reinforce and sustain the basic experiences and the systemspecific normative basis. Small differences pertaining to the starting point for basic experiences can, through dynamic and self-reinforcing processes, generate great differences both in terms of selection processes and expectations. It is the systemspecific normative basis which functions as a damper mechanism on these potentially self-reinforcing mechanisms and thus stabilizes the system. The reflection possibility and the variation potential are both firmly rooted in the cognitive openness. The internal variation potential is contingent on the actors reflecting on their own value basis or the system-specific normative basis. We here make a distinction between the value system and the system-specific normative basis. The value system is constituted by the needs and legitimate wishes on the part of the actors. “Values…I understand to be conceptions of the desirable, applies to various objects and standing at various levels of generality” (Parson, 1967, p. 147). The values being ingrained in needs and legitimate wishes are also explicitly expressed by Bunge (1989). The system-specific normative basis is the norm of the system in relation to the function the system is meant to fulfill. The norms have their functions in terms of sustaining the system of relations between positions in the field. The purpose of the cognitive openness is to increase the sensibility on the part of the system toward the world and thus establishing a link to selected parts of this world. Through communication with the environment, the awareness of the actors in the system is developed. When the

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actors in turn reflect on this awareness and introduce it communicatively to the system, irritation and/or tension toward the system-specific normative basis is easily generated, further reinforcing the communication in the system. The system identity is the distinction in evidence when differences between the systems and their environment are displayed. The normative superstructure and the system-specific normative basis generate a certain habitus (Bourdieu, 1992), i.e., patterns of thought and action dispositions on the part of the actors. The thought and action dispositions are contingent on how the actors have organized their knowledge. Their experiences are generated through the use of knowledge and reinforce the suppositions of the actors, due to expectations seen in the light of signals, symbols, and the information being selected in the system. The selection processes to a certain extent precipitate the events to be expected.12 When using the concepts the normative superstructure and the system-specific normative basis, there are no unambiguous definitions to be deduced from the concepts. In order to clarify these concepts, we shall borrow three concepts from Bourdieu: social field, symbolic capital, and habitus. By social field is meant a system of relations between positions occupied by special agents and institutions fighting for what they have in common (Broady, 1991, p. 17). The field concept is a system of relations between positions (Broady, 1991, p. 462). The position is indicated by means of position and location in the social room. The field concept can be seen as a breakdown of the role concept. While the role concept focuses on expectations directed toward certain roles, the field concept focuses on relations between positions. The 12 Thomas theorem

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field concept of Bourdieu becomes a tool suitable for the disclosure of the normative superstructure and the systemspecific normative basis. Every system becomes aware of its norms, according to Bourdieu, by relating them to the norms of other groups (Broady, 1991, p. 463). Symbolic capital is everything recognized as valuable by the social group (Broady, 1991, p. 462). Habitus is the system of dispositions permitting human beings to think, act, and orient themselves in the social world (Broady, 1991, p. 12). The habitus concept tries to interlink the subjective and the objective in the social room (Broady, 1991, p. 453). To disclose the normative superstructure and the systemspecific normative basis, the focus will have to be put on relations between actors in central positions. The question will then be: What system of relationships exists? Systems of relationships can, for example, revolve around: dominance relationships, access to resources, opinions regarding social problems, investments in knowledge, types of conversion strategies, networks available, relations to other fields, instances of symbolic access and material access, value hierarchy, access rules, and geographical location of the positions. It is in particular the relationship properties pertaining to Bourdieu’s concepts which make them conducive to systemic thinking. Systemic thinking emphasizes relations between elements more than the substance of the individual elements. This is also one of the basic prerequisites for the study of social systems. The relations and their system character is a central aspect of Bourdieu’s sociology, according to Broady (1991, p. 464). On the basis of this line of thinking, isolating single factors and establishing connections between them for example, would give the wrong idea. It is the entire system of relationships generating a phenomenon which should constitute the ambitions in terms of disclosure on the part of research or alternatively patterns of interactions over a period of time.

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On the basis of the previous discussion, we can enlist certain criteria for the study of the normative superstructure and the system-specific normative basis: 1. Patterns: Social relations between actors generate certain patterns of thought and action positions in the social field. 2. Distinction: The thought and action pattern differs from other social systems. 3. Unity: The thought and action pattern is shared by the actors in a specific social field. 4. Autopoiesis: The thought and action pattern reproduces itself through the norms. The normative superstructures and the system-specific normative basis can be depicted as shown in Fig. 2.2. The norms are institutionalized through the development of the system of relations between the actors, who in turn constitute the stability of the social system. The systems of relation are critical, as they develop a reciprocity between the actors and thus penetrate the entire system, or major parts of it. One major purpose of the normative superstructure as regarded in this context is to ascertain that the change in the individual system is not carried out more rapidly than what will allow for the complete structure to make the necessary adjustment. If this should happen, the entire field could collapse. One such change could be regarded as a morphogenetic change, i.e., as change affecting the entire system and possibly the fields and generating new relations between the elements allowing new structures and power constellations to occur. Changes not affecting the whole system, allowing new relations, structures, and power constellations to occur, are here called morphostatic changes. The normative superstructure is to ascertain that morphostatic changes take place, while preventing morphogenetic changes.

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Fig. 2.2. The Normative Superstructure and the SystemSpecific Normative Basis. maintain

creates

maintain

Distinction to other social systems

creates

Patterns of thought and action dispositions in social systems creates

The norms Reproducing themselves

Unity in the Social field

maintain

creates

maintain

Structural transformations happen • through the normative superstructure undergoing morphogenetic changes or • through the cognitive open system influencing the systemspecific basis in a manner conducive to the normative superstructure undergoing morphogenetic changes. The normative superstructure influences the system-specific normative basis, among other things, through its model ˚ power. Braten (1986, p. 193) defining sociocultural system as: “a meaning processing system interacting participants who maintain and transform the identity of themselves and their

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network through a more or less shared understanding of both themselves and of their network through a more or less shared understanding of both themselves and the world.” Under ˚ certain circumstances, according to Braten (1986, p. 193), the shared common notions are “closed to a degree that rules out any rival view…Such a system state may be called a model ˚ monopoly.” Braten’s concept model monopoly is here linked directly to the normative superstructure. The normative superstructure in one field differs from the other normative superstructures in other fields by virtue of its values, identity, and model monopoly. While we here use Bourdieu’s focus on the system of relations between positions to describe the normative super˚ structure, Braten in his model monopoly concept focuses on the concrete actors in the field, who by virtue of being modelstrong also induce other actors to reflect their interests and ˚ perspectives. There is no contradiction between Braten’s perspectives and ours; only a disclosure of different aspects of the normative superstructure. Morphostatic changes are necessary in order to maintain the stability and flexibility of the total system. This stability and flexibility is constituted through a constant disorganizing process. The normative superstructure has direct and subtle evaluation patterns for control of the individual systems. The subtle instrument is constituted by values and norms transferred and maintained in various ways, for example, through ceremonies, education, ideas, symbols, and the formation of opinion. The direct control system is more linked to rules and regulations. Both the direct and the subtle control mechanisms are differentiated and vague and thus relatively difficult to catch sight of for an observer of such systems. The system-specific norms are carriers of the normative superstructure in the same manner (analogy) as a context

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conveying messages, where the superstructure is analogue with the context. Every system-specific normative basis in a social field to a certain extent reflects the normative superstructure, i.e., the normative superstructure is recursively present in all systemspecific normative bases, like a holographic representation. Through the norms the system reproduces itself. The normative superstructure or the system-specific normative basis can rarely be disclosed through the study of individuals and their influence. It is the system of relations between positions which constitutes the superstructure and the interaction between the persons which occupies these positions. The relationship between the normative superstructure and the system-specific normative basis represents two different logical orders, where the normative superstructure takes precedence over the system-specific normative basis. From the discussion in this part of the chapter the following conclusion can be made: normative closedness and cognitive openness have impact on thought and action positions in a social system. Thought and action strategies indicate and influence the type of knowledge emphasized by the company. In the new part of the chapter we will discuss the development of a company’s knowledge basis and how it could be used by the company.

CREATING NEW KNOWLEDGE FOR INNOVATION The importance of interactive learning in companies has been discussed by many authors.13 Tusman and Nadler (1986, p. 75) explicitly point out that innovative organizations have 13 Teece (1986, 1988, 1989), Lundvall, 1992, 1995, Lundvall and Johnson (1994), Langer (2017) among others.

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one thing in common; they are: “highly effective learning systems.” To achieve this, according to the aforementioned authors, an organization aimed at “both stability and change” (Tusman & Nadler, 1986, p. 75) is required. Understood in this way the concepts normative closedness and cognitive openness become indicators of the performance and innovation level of the company. Nonaka and Takeuchi (1995) elaborate knowledge management too: “create new (task-related) knowledge, disseminate it throughout the organisation and embody it in products, services and systems.” Lundvall (1995) says: “Perhaps it is not at all fruitful to regard tacit versus codified knowledge as two different pools where there is a flow from one to the other. The relationships are much more complex and symbiotic.” There is a worldwide agreement that knowledge and innovation is the competitive strength needed for successful companies. Quinn (1992, p. 439) says: “Increasingly…developing and managing human intellect and skills—more than managing and deploying physical and capital assets—will be the dominant concerns for managers in successful companies.” Tacit knowledge creating invisible assets are skill based and people intensive. This implies that as a resource, people are important, not just as participants in the labor force, but as accumulators and producers of invisible assets. Invisible assets are also key success factors because they are difficult to obtain. Invisible assets are often the only source of competitive edge that can be sustained over time. Nonaka and Takeuchi (1995) emphasize tacit knowledge as a main source creating new knowledge and continuous innovation. McGrath, MacMillan, and Venkataraman (1995) also argue that the most potent of such assets are posited to be intangible or tacit. An example of a successful company,

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where the active use of tacit knowledge on the part of companies has generated performance and innovation in Scandinavia, is the Swedish company Ramnæs. Their knowledge basis is tacit and: “Largely acquired through on-the-job and organizational learning” (Eliason, 1996, p. 139). As a result of the more complex nature of work, the composition of the workforce will shift away from employees who have a traditional, practical training background and toward an ever increasing number of employees who have had a higher education and are theoretically well equipped. This type of employee must possess methodological strength, be capable of working in a problem definition and problemoriented manner, and possess skills for both analysis and synthesis. Nonaka and Takeuchi (1995, p. 237) say about this: “…the essence of knowledge creation is deeply rooted in the process of building and managing synthesis.” However also applied skills such as realism, initiative, ability to innovate and willingness to run risks will be in demand. Barton (1995, p. 75) refers to this type of knowledge as T-shaped skills. The persons possessing this type of knowledge have a combination of theoretical and practical knowledge and simultaneously have the ability to see how their branch of knowledge interacts with other branches of knowledge to function as a whole. These are persons with systemic knowledge, as a contrast to branch knowledge, who understand the language of all branches. These persons have usually expanded their competence across several functional branch areas and thus developed the skills of synergistic thinking. Participation and organizational learning actually demand that the middle managers or the project leaders (or both) take risks. These are also the lessons from Japan which Nonaka and Takeuchi (1995, p. 233) teach us: “…in our view, middle managers play a key role in the organizational knowledgecreation process.” They continue, however, “…in the West,

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where middle managers have been portrayed as ‘cancer’ and a ‘disappearing breed’. In contrast, in a knowledge-creating company they are positioned as the ‘knot’, ‘bridge’ and ‘knowledge engineers’.” Based on the above discussion we will propose a categorization of knowledge, which could be used for knowledge creation and knowledge integration aimed at innovation. The main distinction in the figure below is knowledge which is easily communicated to others and knowledge which is difficult to communicate to others. Metaknowledge is the knowledge base structuring explicit knowledge, i.e., know why. Metaknowledge is also a sort of knowing how we know, appearing when reflections are made on the basis of our normative basis: Metaknowledge is both a process and a product. As a process it is expressed by Maturana and Varela (1987, p. 24): “Reflection is a process of knowing how we know.” As a product it is knowledge on how we think. Metaknowledge has bearing on the perspectives of individuals, i.e., what is seen and how this is perceived. When a person in a company works within the framework of a particular perspective, for example a technological– economic paradigm, he is likely to set greater store by some methods than others. The perspective generates meaning in terms of how the work is perceived and interpreted, in addition to adding input as to what a person is looking for in a job context. Metaknowledge is thus a form of split interpretation competence among the persons sharing the perspective. In this way metaknowledge directly influences these persons as to what type of explicit knowledge is relevant and meaningful for the company. The more uniform this perspective is among the most important actors of the company, the more influential this perspective will be as to what knowledge type (explicit versus tacit, for example) is critical to the competitive position

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of the company. The persons in the company who have various degree of metaknowledge or different basis perspectives will be able to view the same phenomenon but interpret it differently, giving it various meanings relative to the opportunities and challenges of the company. Explicit knowledge is the part of our knowledge base which can be easily communicated to others as information, i.e., know what. Explicit knowledge can be objective and intersubjective. Bunge (1983, p. 80) defines objective knowledge in the following way: “Let p be a piece of explicit knowledge. Then p is objective if and only if (1) p is public (intersubjective) in some society, and (2) p is testable (checkable) either conceptually or empirically.” Tacit knowledge14 is a form of skill, ability, or “techne”, i.e., know how, which is difficult to communicate to other as information, but it may be expressible in metaphor. Drucker (1993, p. 24) says about tacit knowledge: “the only way to learn techne was through apprenticeship and experience.” Polanyi (1962, p. 54) says that this sort of knowledge also can be regarded as connoisseurship, and his example is the good wine-taster. Hidden knowledge, i.e., knowing how we know, is the premises, prerequisites, and motives influencing our thoughts and action positions. Hidden knowledge influences the way we think and act, as a sort of personal paradigm, or the technical–economic paradigm in the business world, a trajectory which leads our way of thinking and acting when expressing and interpreting, among other things, new ideas. Hidden knowledge organizes the development of mental models, the nature of the abstraction we make, the choice of “variables,” the facts we choose to focus on, our underlying metaphysical positions, our theoretical “tastes,” etc. Hidden 14 Framed by Polanyi (1962).

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knowledge can be divided in two parts: disposition to think and disposition to act. In this way hidden knowledge is linked to company-specific norms. Relationship knowledge, i.e., know who: “involves the social capability to establish relationships to specialised groups in order to draw upon their expertise” (Lundvall, 1995). In a time where turbulence and change are accelerating it is decisive for organizational survival to invest in relationship knowledge. As a basic rule all knowledge (in Fig. 2.3) is mutually complementary and not reciprocally preclusive. Metaknowledge and explicit knowledge are learned and shared in the formal education system and in the business world. We are so good at it in the West, that we have “forgotten” knowledge which we not so easily can communicate to others. But, this knowledge may be how the companies in the East create the dynamics of innovation. Tacit knowledge is learned by using and doing. It could be shared by “brainstorming camps,” using metaphors and analogies, in the education system and in the business world. This is done at Honda where they “set up brainstorming camps,

Fig. 2.3. Categorization of Knowledge. Process

Relatively easy to communicate as information Knowledge

Meta knowledge

Objective Eksplicit knowledge Tacit knowledge

Difficult to communicate as information

Product

Inter-subjective Personal experience (Connoisseurship) Apprenticeship Dispositions to think

Hidden knowledge

Dispositions to act

Formal Relationship knowledge

Informal

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informal meetings for detailed discussions to solve difficult problems in development project” (Nonaka & Takeuchi, 1995, p. 63). Keep in mind, however, that these meetings are focused upon tacit knowledge, not the brainstorming we usually are involved in, focusing upon explicit knowledge. Hidden knowledge is learned by socialization and could be shared in the business world, first of all by focusing upon its existence and second by using focus groups. It is the willingness to question underlying assumptions which in practical settings has to be focused. The use of focus groups gives access to uncodified knowledge, the language, mental models, the opinions, the meanings, the presuppositions, and the world view of the participants. Focus groups also give the opportunity to make synergy of the individual’s way of thinking as part of a collective. Relationship knowledge is learned by interaction and could be shared by systematic work in teams complementarily composed, both in the educational system and in the business world. An example for developing relationship knowledge is Japanese firms bringing their supplier partners along with them while visiting European customers. Both the firm and the supplier develop and strengthen relationships this way, in addition to the relationship with the customers. In these contexts, hidden knowledge also will be made explicit. Based on the previous discussion we propose a scheme for knowledge management (Fig. 2.4). In the West we are good at creating and using knowledge which is easy to communicate as information. In Japan, according to Nonaka and Takeuchi (1995), they emphasize tacit knowledge for the innovation process. If it is possible to make knowledge which is difficult to communicate to others (tacit, hidden, relationship knowledge) explicable, then we could speed up learning, transfer, and innovation processes in organizations.

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Fig. 2.4. Knowledge Management. Types of knowledge

Learning by

What is learned

How to share it

Media

Meta-knowledge

Reflection

Know why

Communication

Know how

Explicit knowledge

Listening/reading

Know what

Communication

Books, lectures, databases etc.

Tacit knowledge

Using/doing

Know how

«Brainstorming camps» structured as apprenticeship

Books, lectures, databases etc.

Hidden knowledge

Socialization

Knowing how we know

Focus groups

Practical experience, apprenticeshiprelationship

Relationship knowledge

Interacting

Know who

Partnership and teamwork

Social settings

In order to create knowledge for innovation we have to organize the process to make the knowledge which is difficult to communicate understood by the people involved. This could be looked upon as a systemic integration and networking model. To make this happen we have to make tacit knowledge, hidden knowledge, and relationship knowledge explicable in some way, in order to share it with other people. It is difficult to transmit knowledge whose importance eludes you. To understand what type of knowledge is essential in achieving, for example, innovative success, reflection on the company’s normative basis is critical. This model can be contrasted to the transfer of knowledge as bits of information or the algorithmic model. The question to be analyzed in the next part of the chapter is: How can we categorize innovation in companies. It is important to clarify this to see the connection between the company-specific norms, the knowledge basis of the company, and innovation.

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ORGANIZATIONAL INNOVATION Basically there are two types of innovations: product and process innovations. These are not mutually preclusive, but depend on each other in a major degree. Process innovations can furthermore be divided into organization and technology. Organization means new market organization and internal company organization. By technology in this instance we mean human artefacts. These can be classified as three entities: instrument, machine, and automaton. Innovations can also be seen as incremental, i.e., small stepby-step improvements, i.e., continuous innovations, or radical, i.e., something qualitatively new. Continuous and radical innovations can also be autonomous, i.e., what is new can be kept separate, or systemic, i.e., the new is dependent on changes taking place in the process/product linked to the new product or process. Fig. 2.5 offers a schematic depiction of these distinctions.

Fig. 2.5. Classification of Innovation. Autonomy Continous Process

Systemic Autonomy

Radical Innovation

Continous

Systemic Autonomy Systemic

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We have now examined norms from an autopoietic perspective, knowledge development, and types of innovation. In our conclusion we will integrate these three entities, in order to develop an initial effort to construct an integrated model. CONCLUSION The initial question of this chapter was: What is the connection between norms specific to the company, the knowledge basis of the company, and innovation? We presented a model for this context and have reviewed the individual elements of the model. We will now integrate the discussion so far, in order to answer the question more precisely. We will do this by presenting an integrated model, expressing policy implications at the company level (Fig. 2.6).

Policy implication of the model If continuous product innovations are wanted, then the company must stress the development of the part of the

Fig. 2.6. The Integrated Model. Continous Product Radical Innovation

Continous Process Radical

Tacit,HiddenRelationshipknowledge

Meta,Explicitknowledge Tacit,HiddenRelationshipknowledge Meta,Explicitknowledge

Cognitively Open systems

To a larger degree

Normatively closed systems Cognitively Open systems Normatively closed systems

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knowledge basis engrained in tacit-, hidden-, and relationbased knowledge, while ensuring that the system has a major degree of cognitive opening. If radical product innovations are wanted, then the company must stress the development of the knowledge basis based on meta-, and explicit knowledge, while maintaining a great degree of normative closedness. If continuous process innovations are wanted, then the company must stress the development of the knowledge base area emanating from tacit-, hidden-, and relation-based knowledge, while maintaining a relatively low degree of cognitive opening. If radical process innovations are wanted, then the company must stress the development of the knowledge base which is based on meta- and explicit knowledge, while maintaining a relatively little degree of normative closedness. It is fair to assume that various types of knowledge are utilized in relation to the various innovation types. While customer closeness has proved critical for continuous innovation, it is more dubious whether this also applies to the development of radical innovations, since the customers do not necessarily know the technical opportunities and the companies do not know who can be future buyers of radical innovations. Radical innovations and continuous innovations appear to require qualitatively different knowledge bases in the company and various normative bases, i.e., cognitively open and normatively closed. Radical innovations appear to require less or even no customer contact, but a firm belief in one’s own ability and values and norms, i.e., a great degree of normative closedness in the system. Continuous innovations, on the contrary, require very close customer contact and an active use of the part of the knowledge base not easily communicated to others,

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as this will, among other things, prevent swift imitations by the competitors. The normative basis is here a cognitively open system, which also protects itself against the competitors by emphasizing tacit, hidden, and relationship knowledge, reducing the chances of imitation and maintaining the competitive position over a longer period of time. REFERENCES Abramovitz, M. (1989). Thinking about growth. London: Cambridge University Press. Barton, D. L. (1995). Wellsprings of knowledge: Building and sustaining the sources of innovation. Boston, MA: Harvard Business School Press. Bourdieu, P. (1992). An invitation to reflective sociology. New York, NY: Polity Press. ˚ Braten, S. (1986). The third position: Beyond artificial and autopoietic reduction. In F. Geyer & J. Van der Zouwen (Eds.), Sociocybernetic paradoxes (pp. 193–205). Beverly Hills, CA: Sage Publications. Broady, D. (1991). Sociologi och Epistemologi: Om Pierre Bourdieus førfatterskap och den historiska epistemologin. Stockholm: HLS Førlag. Bunge, M. (1983). Exploring the world. Dordrecht: D. Reidel. Bunge, M. (1983a). Understanding the world. Dordrecht: D. Reidel. Bunge, M. (1989). Ethics: The good and the right. Dordrecht: D. Reidel. Chia, R. (2017). A process-philosophical understanding of organizational learning as “wayfinding”. The Learning Organization, 24(2), 107–118.

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Dabbert, S., & Lewandowski, I. (2017). Knowledge driven development in the bioeconomy. London: Springer. Drucker, P. F. (1993). Post-capitalist society. New York, NY: Butterworth Heineman. Eliason, G. (1996). Spillovers, integrated production and the theory of the firm. Journal of Evolutionary Economics, 6(2), 125–140. Geyer, R. F., & Van der Zouwen, J. (Eds.). (1978). Sociocybernetics: An actor-oriented social systems approach (Vols. 1 & 2). Leiden: Martinus Nijhoff Publishers. Geyer, R. F., & Van der Zouwen (1992). Sociocybernetics. In C. V. Negoita (Ed.), Cybernetics and applied systems (pp. 95–124). New York, NY: Marcel Dekker. Greenhalgh, C., & Rogers, M. (2010). Innovation, intellectual property and economic growth. Princeton, NJ: Princeton University Press. Kaplan, S. (2017). The invisible advantage: How to create a culture of innovation. Austin, TX: Greenleaf Book Group. Langer, A. M. (2017). Information technology and organizational learning. Boca Raton, FL: CRC Press. Lantis, J. (2016). Arms and influence: US technology innovations and the evolution of international security norms. Stanford, CA: Stanford Security Studies. Luhman, N. (1990). Essays on self reference. New York, NY: Columbia University Press. Luhman, N. (1995). Lykke og ulykke, kommunikasjon inden for familier: Om patologiens genese, In J. C. Jacobsen (Ed.), Autopoiesis. (Vol. 2). København: Politisk Revy. ¨ Luhmann, N. (1975). Sosiologische Aufklarung. (Vols. 1–5). Berlin: Westdeutscher Verlag.

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Luhman, N. (1982). The World Society as a Social System. International Journal of General Systems, 8, 131–138. Luhmann, N. (1986). The autopoiesis of social systems. In F. Geyer & J. van der Zouwen (Eds.), Sociocybernetic paradoxes (pp. 172–192). Beverly Hills, CA: Sage Publications. Luhmann, N. (1992). Ecological communication. Cambridge: Polity Press. ˚ (Ed.). (1992). Nationsl systems of innovations: Lundvall, B-A. Towards a theory of innovation and interactive learning. London: Pinter Publishers. ˚ (1995, November 10). Inaugural lecture. Lundvall, B-A. Department of Business Studies, Aalborg University. ˚ & Johnson, B. (1994). The learning economy. Lundvall, B-A. Journal of Industry Studies, 1(2), 23–41. Maturana, H. (1981). Autopoiesis. In M. Zeleny (Ed.), Autopoiesis: A theory of living organization (pp. 21–23). New York, NY: Elsevier. Maturana, H. R., & Varela, F. J. (1980). Autopoiesis and cognition: The realization of the living. Dordrecht: D. Reidel. Maturana, H. R., & Varela, F. J. (1987) The tree of knowledge. London: New Science Library. McGrath, R. G., MacMillan, I. C., & Venkataraman, S. (1995). Defining and developing competence: A strategic process paradigm. Strategic Management Journal, 16, 251–275. Mingers, J. (1989). An introduction to autopoiesis: Implications and applications. Systems Practice, 2, 159–180. Nonaka, I., & Takeuchi, H. (1995). The knowledge creating company: How Japanese companies create the dynamics of innovation. Oxford: Oxford University Press.

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Parson, T. (1967). Sociological theory and modern society. New York, NY: The Free Press. Polanyi, M. (1962). Knowledge and being. New York, NY: Routledge. Quinn, J. B. (1992). Intelligent enterprise. New York, NY: The Free Press. Robb, F. (1989). Cybernetics and supra human autopoetic systems. Systems Practice, 2, 47–74. Teece, D. J. (1986). Profiting from technological innovation: Implication for integration, collaboration, licensing and public policy. In I. D. J. Teece (Ed.), The competitive challenge: Strategies for industrial innovation and renewal. Cambridge, MA: Ballinger. Teece, D. J. (1988). The nature and the structure of firms. In I. G. Dosi, C. Freeman, R. Nelson, G. Silverberg & L. Soete (Eds.), Technical change and economic theory. London: Pinter Publishers. Teece, D. J. (1989). Inter-organizational requirements of the innovation process. Managerial and Decision Economics, (Special Issue), 35–42. Thompson, P. (1996). Technological opportunity and the growth of knowledge: A schumpeterian approach to measurement. Journal of Evolutionary Economics, 6(1), 77–97. Turner, J. C. (1993). Social influence. Milton Keynes: Open University Press. Tusman, M., & Nadler, D. (1986). Organizing for innovation. California Management Review, 28(3), 74–92. Varela, F. G. (1979). Principles of biological autonomy. New York, NY: Elsevier.

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Varela, F. G. (1984). Two principles of self-organization. In J. Ulrich & G. Probst (Eds.), Selforganization and the management of social systems (pp. 25–32). Frankfurt: Springer. Von Foerster, H. V. 1981. Observing systems. Seaside, CA: Intersystems Publications.

3 KNOWLEDGE MANAGEMENT AND INTERNAL TRAINING

INTRODUCTION In the global knowledge economy where the business environment is characterized by an increased turbulence and complexity, an organization’s capacity to create and sustain competitive advantages lies in what it knows, not what it owns. The management of knowledge is therefore increasingly considered an important source of sustainable competitive advantage. However, for knowledge to make this contribution, it need to be converted into competencies, and competence is only important as a strategic resource if it is “distinctive,” relative to its competitors. In strategically developing firms, competence, we believe, has a huge potential for improving firms sustainable competitive advantage, in capitalizing on training, because “Virtually all descriptions of high-performance management practices emphasize training” (Pfeffer, 1998, p. 112). The following is the topic to be investigated in this chapter: How could training be instrumental in developing competence into sustainable competitive advantages.

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The chapter is organized in the following manner: First, we will discuss the role of knowledge and competence in creating sustainable competitive advantages. Secondly, we discuss the need for a strategic approach to competence development, by asking the question, “What competencies do we need?” We present a methodology for isolating the competence that provides sustainable competitive advantages. Third, we discuss the role of training in meeting the strategic competence priorities of companies, by asking, “How should we train to develop the competence we need.” In the conclusion we will present a model for delivering training in the workplace.

COMPETENCE AND SUSTAINABLE COMPETITIVE ADVANTAGES In neoclassical microeconomic theory, it is argued that profitmaximizing firms in competitive environments need to exercise monopoly power in order to make supernormal profits, as they earn a return just sufficient to maintain capital investments (Jacobsen, 1992). The industrial organization theory (rooted in neoclassical microeconomic theory) is concentrating on market conditions which are in equilibrium, advocating a static notion of the nature of competition. The emphasis is on economies of scale and scope, the optimization of transaction costs across subsidiaries, and critical market characteristics to explain different firm level strategies. However, today most companies face a turbulent and complex business environment, and the industrial organization approach has been criticized for a lack of attention to such dynamic environments. Grant (1996, p. 375) argued that: “If market structure is in a state of flux, and if monopoly rents quickly succumb to new sources of competition, approaches

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to strategy based upon product markets and positioning within them are unlikely to yield profit advantages that are more than temporary”. The efficiency-based approach rooted in Penrose’s (1959) theory of the firm has an underlying theoretical approach whereby the firms are seen as a unique bundle of tangible and intangible resources and not through their activities in the product market. Within this approach, we have seen an increased emphasis on knowledge as the only truly sustainable competitive advantage for firms. Explicit knowledge, available for purchase on the “open market” is accessible for everyone and will then in itself not provide the company with the edge over other companies. Competitive advantages based on explicit knowledge will therefore to an increasing extent only provide a short-term advantage. Polanyi (1966, p. 4) who developed the concept of tacit knowledge says: “We can know more than we can tell.” Polanyi’s theory about tacit knowledge deals with how individuals develop and use their knowledge in a practical job situation. Tacit knowledge is embodied in action (practice) and is linked to concrete contexts. Tacit knowledge is intimately related to the task-related part of a company’s competence, i.e., skills and practical knowledge. This form of knowledge is wholly embodied in individual, rooted in practice and experience, expressed through skillfull execution, and transmitted by apprenticeship and training through watching and doing forms of learning. However, for knowledge to contribute to such advantage, it must be applied to a task by individuals possessing certain skills, i.e., there is a need for competence. Advocates of the efficiency-based approach argue that it is differences in the company’s competence which will lead to sustainable competitive advantages. This approach further argues that it is

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the type of competence which is difficult to imitate which generates the desired benefits.

STRATEGIC COMPETENCE DEVELOPMENT A central issue within the area of competence is the focus on core competence and core capabilities. Core competencies represent the set of differentiated technological skills, complementary assets, and organizational routines and capacities. The basic argument, according to Nelson (1998, p. 326), is that: “Firms have (at best) a limited number of things they can do well, which include operating and advancing the particular technologies they know well, their particular approaches to marketing and purchasing, their ways of identifying and responding to environmental changes, etc.” Leonard-Barton (1995, p. 113) defines a core capability as: “the knowledge set that distinguishes and provides a competitive advantage.” Her main emphasis was on employee knowledge and skills which are embedded in underlying technical systems, values, and norms. Nonaka and Takeuchi (1995) argued that the distinction between core competence and capabilities has not been clear. Teece, Pisano, and Schuen (1997, p. 516) defined core competence as “those competencies that define a firm’s fundamental business as core.” In spite of the proclaimed importance of core competencies and core capabilities, Leonard-Barton (1995) argues that core capabilities have a dysfunctional flip side, core rigidities. Leonard-Barton (1995, p. 55) stated that: “core rigidities are activated when companies fall prey to insularity or overshoot an optimal level of best practice”. Hence, as argued by Lei, Hitt, and Bettis (1996, p. 550): “Core competence cannot remain static; only those firms that continue to invest and upgrade their competence are able to create new strategic growth alternatives.” Therefore, in

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a dynamic business environment, we also need to nurture the potential for future core competencies. Next, we shall present a methodology for continually developing the core competence of a company. The methodology consists of three parts. First, we need to decide what the expected core competence of the company is, i.e., the core competence that is required to achieve the purpose of the company. Secondly, we need to map the actual core competence within the company. The differences between expectations and actual core competence constitute the core competence gap that needs to be diagnosed and resolved. Thirdly, we need to develop the firm’s core competence so as to close the gap. We argue that in deciding on a firm’s core competence, we need to ask three questions. First: What is the purpose of the company? The purpose of the company is related to its mission and its vision, i.e., what business are we in and were the company should head for the future. Second: What are the critical tasks to be performed in order to fulfill the purpose of the company? The reason for an organization to exist is to accomplish the tasks necessary to achieving its purpose, i.e., its core activities. Third: What competence is needed to accomplish these tasks, i.e., the company’s expected core competence? We further argue that core competencies also influence the definition and the fulfillment of the purpose of the company. The relation between purpose, core activities, and core competence is presented in Fig. 3.1. Core capabilities embody proprietary knowledge that is unique to the organization and is superior to the knowledge of its competitors. The degree to which a core competence is distinctive depends on how well endowed the firm is relative to its competitors and how difficult it is for

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Fig. 3.1. The Purpose of the Company, Its Core Activities, and Its Core Competence. Purpose influence

influence

Is part of

Sustainable competitive advantages Is part of

Is part of

Core competence

influence

Core activities

competitors to replicate its competence. We argue that the tacit knowledge of its organizational members is the most important proprietary and difficult to replicate knowledge that the organization holds, as it is invisible and difficult to imitate. In mapping the actual core competence of a company, and enabling the firm to prioritize its knowledge development, we argue that we need to answer four questions concerning the competence and knowledge of its organizational members. First we present these questions. Then we show schematically how these questions are linked to strategic competence development for each individual in the enterprise. The four questions forming the basis for mapping the knowledge and competence are the following ones: Question 1: Does the person possess a type of competence defined by the company as part of its core competence? Question 2: Can the type of knowledge possessed by the person be easily replaced?

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Question 3: Is this type of knowledge sufficiently in evidence in the company? Question 4: Is this type of knowledge difficult to communicate to others as information (i.e., tacit knowledge)? On the basis of these questions we have developed Fig. 3.2, which can be helpful to determine what priorities the company should give to competence development. The first logical line follows question 1: Has the person a type of knowledge which the company defines as its core competence’s? If the answer to this question is yes, the next question, question 2, will be as follows: Is it relatively easy to replace the knowledge which the person possesses? If the answer here too is yes, the next question, question 3, will be as follows: Does this type of knowledge exist to a sufficient extent in the company? If the answer to this question is also yes, then we will have defined this as a prioritized strategic

Fig. 3.2. Strategic Competence Development. Queson 1

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competence development task for the company, but at the lowest level of priority (here priority level 3). The reason for including this as a prioritized task is because the knowledge possessed by this person is basically a core competence for the company and must therefore be given attention. If the answer to question 3 in the logical line is no, then the next question, question 4, will be as follows: Is this type of knowledge difficult to communicate to others as information (difficult to articulate, tacit, etc.)? If the answer to this question is yes, then we will have defined this as the most important task for strategic competence development, i.e., here priority 1. This is because this type of knowledge is in fact the most invisible, which can help distinguish the company’s competence from that of the competitors. If the answer to question 4 in this logical line is no, then we will have defined this competence as priority 2 in the strategic competence development, since, even if this is a type of knowledge which can easily be communicated to others as information, it still belongs to the core competence of the company and must therefore be given high priority. If we follow the other logical line and get a yes to question 1, but no to question 2, question 3 will be as follows: Is this type of knowledge sufficiently in evidence in the company? If the answer to this question is yes, then we will have defined this as a strategic competence task at priority level 2. This has been done since, even if the knowledge is sufficiently in evidence, it is a part of the company’s core competence and should be given priority. If the answer, on the other hand, to question 3 in this logical line is no, then question 4 will be as follows: Is this type of knowledge difficult to communicate to others as information (difficult to articulate, tacit, etc.)? If the answer is yes, we will have defined this as a strategic competence task of utmost priority, for the same reason as above: This is a type of competence which is designed to

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distinguish the company from its competitors. If the answer is no, we will for the same reasons as above have defined this as a task of strategic competence development at a highly prioritized level, level 2, as it belongs to the company’s core competence. The next logical line starts with question 1. If the answer to this question is no, question 2 will then be as follows: Is it relatively easy to replace the knowledge a person possesses? If the answer to this question is yes, then we will have defined this as a competence task which should not be given priority by the company, since it does not belong to the company’s core competence. If the answer to the question 2 in the logical line is yes, then the next question, question 3, will be as follows: Is there a sufficient extent of this type of knowledge in the company? If the answer to this question is yes, we will, for the same reason as above, have defined this as a prioritized competence task for the company. If, on the other hand, the answer to the question is no, question 4 will be as follows: Is this type of knowledge difficult to communicate to others as information (difficult to articulate, tacit, etc.)? If the answer is yes, we will have defined this as a strategic competence task at priority level 2, since this type of knowledge is instrumental in making the company’s competence distinctively different from that of the competitors, even if it does not belong to the core competence of the company. Core competence cannot remain static, and our argument that tacit knowledge constitute the foundation from were competitive advantages should be built, as tacit knowledge is difficult to imitate. Hence, firms should nurture the tacit knowledge of their employees, even if it is not currently part of the firm’s core competence, as this tacit knowledge may well contribute in laying the foundation for future competitive advantages. Also, Teece et al. (1997) argue that the resourcebased view (which is part of the efficiency-based approach)

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suggest that firms should identify their firm’s unique resources and then decide in which markets those resources can earn the highest rents.

DYNAMIC CONTEXTUAL TRAINING After prioritizing the competence and knowledge of their employees, the next challenge for companies is to develop the knowledge and competence which represent the gap between expected and actual competence. Our focus is on training. Training is believed to be instrumental in increasing the knowledge and competence of individuals. Pfeffer (1998, p. 112) argue that: “Training is an essential component of high-performance work systems because these systems rely on front-line employees’ skills and initiative to resolve problems, to initiate changes in work methods, and to take responsibility for quality. All of these require a skilled and motivated work force that has the knowledge and capability to perform the requisite tasks.” An important explanation to the high level of innovation15 in Japanese companies may be that the Japanese management philosophy to a much greater extent prioritizes training of their employees than is the case in the western organizational culture. Japanese companies often recruit young people. They are, subsequent to their hiring, offered internal training in order to cope with tasks which they are asked to perform by the company. 15 Many people will, however, argue that it is imitation ability which is the strength of Japanese industry. This may possibly be the case in an historical industrial perspective. Today the Japanese innovation ability should not be understated, however.

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Several studies from British and American industry indicate that employers regard internal training as an insignificant factor for the company.16 Pfeffer (1998, p. 113) states that: “Japanese plants in North America provide 700 percent more training, and plants in newly industrialized countries such as Korea, Taiwan, Brazil provide more than 750 percent more training than do US plants.” Pfeffer (1998, p. 114) further argues that, on the basis of the insufficient emphasis on training in British and American companies: “And all of this is occurring in a world in which we are constantly told that knowledge and intellectual capital are critical for success.” Training has instead functioned as a balancing item during economic recession, whereas this may in fact be the most expedient time to capitalize on training in order to adjust to the requirements of a changing environment. To regard training as a cost will probably not make a positive contribution to a company’s sustainable competitive advantage. Companies which instead regard training as investments in human and social capital could achieve a higher degree of motivation among the employees. Focusing more on training can in turn generate more initiative and involvement on the part of the employees. It is fair to assume that employees who are involved and motivated will display a greater level of creativity and innovation than employees who do not feel appreciated as an important resource for the company. This should indicate that the attitude on the part of management toward training determines its usefulness in relation to firms’ sustainable competitive advantages. Hence, we argue that an emphasis on training is instrumental in achieving sustainable competitive advantages. This is also in line with Jacobs who 16 Senker (1989), Truss, Gratton, Hope-Haily, McGovern, and Stiles (1997), and MacDuffie & Kochan (1995).

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argues that the policy task is to persuade more enterprises to invest in their employees. However, emphasis is not enough. Training can take several forms. Two predominant modes of training are through classroom instruction and through experience. We have argued that knowledge is the main ingredients of competence. We argue that classroom instruction is instrumental in transferring explicit knowledge. However, although classroom instructions, especially the kind provided by from educational institutions, is a necessary condition for much competence development in companies, it is not a sufficient condition. This formal knowledge, available for purchase on the “open market” is accessible for everyone and will then in itself not provide the company with the edge over other companies. Hence, we argue that explicit knowledge, provided through classroom instruction, have a limited impact on sustainable competitive advantages, on its own, and we shall argue that it need to be merged with tacit knowledge to create the desired benefits. Lei (1977, p. 210) argue that: “Sustainable competitive advantage is more likely to result from building core competencies that possesses a high component of tacit knowledge that is embedded in the organization”. The training mode that is instrumental in building tacit knowledge is through experience. Caley and Hendry (1998) argued that, while evidence suggest that the majority of organizations recognize the value of delivering training in the workplace, it tends to be conventional, formal, and classroom-based. Nonaka and Takeuchi (1995) argue for the importance of making tacit knowledge explicit, and to focus on both the explicit and tacit part of the knowledge base, in creating knowledge for useful application. Lei (1997, p. 210) argue that: “Each firm’s core competence(s) are likely to be an idiosyncratic blend of both explicit and tacit forms of knowledge.” Hence, we argue that

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it is contributing in building core competencies; there is a need for training to integrate both tacit and explicit knowledge in creating a capacity for effective knowledge application. This is depicted in Fig. 3.3 below. However, a point to notice is that a too strong emphasis on tacit knowledge could easily cause the companies to lose their competitive advantages, since the competence pattern which benefits the company in one epoch could change during the next, and the tacit knowledge has also a markedly conservative side with regards to, for example, innovation. In Fig. 3.3 we argue that explicit knowledge, provided by conventional classroom instruction, has its bases in data which are converted into information. Knowledge is created by systematizing and structuring this information through explanations. Teaching is seen as a transfer of information from teacher to student. Tacit knowledge, on the other hand, has its base in practice and experience, which leads to

Fig. 3.3. Knowledge: The Capacity for Effective Knowledge Acquisition. Knowledge

Explicit knowledge Data Informaon explanaon

Tacit knowledge Experience Awarness Master/ apprenceship

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mastery provided an awareness related to the task at hand. Teaching takes place through apprenticeship. Using the concept “work-based learning,” Raelin (1997, p. 564) argue that: “Work-based learning is much more than the familiar experiential learning which consist of adding a layer of experience onto conceptual knowledge. In work-based learning, theory, for instance, may be acquired in concert with practice.” Our concept of training combines theory from formal education with practical tasks. Thus the training becomes more relevant and meaningful in the concrete work context. The effects of training for the employees will be evident in the form of specific task-oriented knowledge, skills, values, and attitudes. Combining tacit and explicit knowledge also involve sharing knowledge. Sharing of knowledge makes existing knowledge more productive and helps create new knowledge (Gant, 2014). The proposition thus becomes as follows: To share as much knowledge as possible with as many as possible and recombine and reconfigure knowledge faster than the competitors becomes the sustainable competitive positioning in the global knowledge economy. We have argued for the industrial organization approach’s lack of attention to dynamic environments characterized by turbulence and complexity business environment. Delivering training in the workplace tends to be concerned with perpetuating existing organizational practice. An organization that engages exclusively in exploitation (as opposed to exploration) will suffer from obsolescence. Hence, in turbulent and complex environments, one needs to take a more dynamic approach to training. Teece et al. (1997, p. 515) refers to the term dynamic as the following: “the capacity to renew competence so as to achieve congruence with the changing business environment.” They further argue that “Winners in

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the global marketplace have been firms that can demonstrate timely responsiveness and rapid and flexible product innovation, coupled with the management capability to effectively coordinate and redeploy internal and external competencies.” However, it is important to achieve the right balance between exploration and exploitation. Levinthal and Marc (1993, p. 105) argue that the basic problem confronting an organization is to engage in sufficient exploration to ensure its current viability and, at the same time, to devote enough energy to exploration to ensure its future viability. From this we introduce the concept “dynamic contextual training”. This concept emphasizes the ambidextrous nature of organizations in arguing that training, in addition to focus on existing organizational practice, also need to focus on the changing business environment. There are, however, limits to a firm’s ability to change. The contextual element focuses on the need for training to be rooted in practice and experience. Nonaka and Takeuchi (1995, p. 59) argue that: “Both information and knowledge are context-specific and relational in that they depend on the situation and are created dynamically in social interaction among people.” However, we have also pointed out the need to emphasize explicit knowledge, partly due to the conservative characteristics of tacit knowledge, and the need to include theory, but argued that this must take place in concert with practice. Tushman and O’Reiley (1997, p. 14) argue that “competencies that stimulate both innovation and efficiency are an important ingredient in differentiating between organizational success and failure over long periods—managers need to create ambidextrous organizations—that celebrate both stability and incremental change as well as experimentation and discontinuous change simultaneously.” When it comes to transferring tacit knowledge for exploration, we need to take into consideration that: “…tacit

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knowledge can be a key barrier to innovation. This is because tacit knowledge is usually part of a long-term learning process in a specific context, being embodied in the structure of thinking, the way of thinking, and therefore functions as a conservative element in relation to innovation” (Johannessen, Olaisen, & Olsen, 2001). This barrier may be partly met by combining the knowledge of masters from the companies various functional areas (instead of just focusing on apprenticeship within a narrow functional area). Also, tacit knowledge needs to be linked with the explicit knowledge in the system, and the system’s external knowledge base (customers, suppliers, etc.).

CONCLUSION Our objectives were to investigate how training could be instrumental in developing competence into sustainable competitive advantages. Although evidence suggests that the majority of organizations recognize the value of delivering training in the workplace, there is also evidence that the training tends to be conventional, formal, and classroom-based. To meet the challenges of developing and sustaining competitive advantages in an increasingly turbulent and complex business environment, we have argued for the need for dynamic contextual training. When the strategic focus is on exploitation and the type of knowledge that is being focused on is explicit, we find training that is perpetuating existing organizational practice; it is formal and classroom-based. With the same strategic focus and when the type of knowledge is focus, the transfer of knowledge is done in the form of apprenticeship, and training takes place through watching and doing forms of learning. With a shift in strategic focus from exploitation to exploration, and when the

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knowledge in question is explicit, training need to focus on connecting various knowledge sources, both internal and external. This is because exploration (or innovation) requires knowledge from a web of sources. For training to be instrumental in developing competence into sustainable competitive advantages, we therefore argue for the need to merge explicit and tacit knowledge and focus on both exploitation and exploration, leading to both an internal and external knowledge focus. Application of the model can spur both conceptual and practical developments. REFERENCES Caley, L., & Hendry, E. (September 1998). Corporate learning: Rhetoric and reality. Innovations in Education and Training International, 35(3), 241–247. Gant, A. (2014). Give and take. New York, NY: Weidenfeld & Nicolson. Grant, R. M. (1996). Prospering in dynamically-competitive environments: Organizational capability as knowledge integration. Organizational Science, 7(4), 375–387. Jacobsen, R. (1992). The Austrian School of strategy. Academy of Management Review, 17(4), 782–807. Johannessen, J-A., Olaisen, J., & Olsen, B. (2001). Mismanagement of tacit knowledge: The importance of tacit knowledge, the danger of information technology, and what to do about it. International Journal of Information Management, 21, 3–20. Lei, D. T. (1997). Competence-building, technological fusion and competitive advantage: The key roles of organizational learning and strategic alliances. International Journal of Technology Management, 14(2–4), 208–237.

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Lei, D., Hitt, M. A., & Bettis, R. (1996). Dynamic core competences through meta-learning and strategic context. Journal of Management, 22(4), 549–569. Leonard-Barton, D. L. (1995). Wellsprings of knowledge: Building and sustaining the sources of innovation. Boston, MA: Harvard Business School Press. Levinthal, D. A., & Marc, J. G. (Winter 1993). The myopia of learning. Strategic Management Journal, 14(Special Issue), 95–112. MacDuffie, J. P., & Kochan, T. A. (1995). Do U.S. firms invest less in Human Resources? Training in the world auto industry, Industrial Relations, 34, 15. Nelson, R. R. (1988). Institutions supporting technical change in the United States. In G. Dosi, C. Freeman, R. Nelson, G. Silverberg & L. Soete (Eds.), Technical change and economic theory (pp. 349–370). London: Pinter Publishers. Nonaka, I., & Takeuchi, H. (1995). The knowledge creating company. Oxford: Oxford University Press. Penrose, E. T. (1959). The theory of the growth of the firm. New York, NY: John Wiley & Sons. Pfeffer, J. (1998). Seven practices of successful organizations. California Management Review, 40(2), 96–124. Polanyi, M. (1966). The tacit dimension. Chicago: University of Chicago Press. Raelin, J. A. (November–December 1997). A model of workbased learning. Organization Science, 8(6), 563–578. Senker, P. (Autumn 1989). Managers, technology and market forces. Journal of General Management, 15(1), 4–18.

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Teece, D. J., Pisano, G., & Schuen, A. (1997). Dynamic capabilities and strategic management. Strategic Management Journal, 18(7), 509–533. Tushman, M. L., & O’Reilley III, C. A. (1997). Winning trough innovation: A practical guide to leading organizational change and renewal. Boston, MA: Harvard Business School Press. Truss, C., Gratton, L., Hope-Haily, L., McGovern, P., & Stiles, P. (1997). Soft and hard models of human resource management: A reappraisal. Journal of Management Studies, 34, 60.

4 KNOWLEDGE MANAGEMENT AND ORGANIZATIONAL LEARNING

INTRODUCTION The issues being focused on in this chapter are the following ones: What is the common connection between organizational learning and knowledge management? In the light of history, changes in management philosophy can be seen as three great shifts, displayed in Fig. 4.1. Functional organization is directly linked to “scientific management”, where technical rationality forms the basis, thus, among other things, disregarding tacit knowledge. If the resource base point of view17 and the knowledge base theory18 are right, it is this very tacit knowledge which will have considerable impact on the competitive position on the part of companies in the knowledge-based society.

17 Barney (1986a, 1986b, 1991, 1992). 18 Grant (1991, 1996).

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Fig. 4.1. Changes in Management Philosophy. 1895-1900 Owner

Manager

1920-1930 Manager

Functional organizing

1980-1990 Functional organizing

Knowledge organizing

There appears to be a shift from organization based on command and control to various types of relation-based selforganization, where tight competence networks constitute an important foundation and where new technology, new ideology, and a global perspective are important moorings. This new way of organizing work will further be based on knowledge learning and innovation, i.e., the knowledge-based organizations. Another reason for this shift, apart from the systemtheoretical school, is the quality movement, led by Demming and Juran.19 One of the objections of Demming is the very fact that the command and control economy, the functional organization, and scientific management have ruined the workers as creative individuals. Their motivation, creative ability and the urge to work for the benefit of total output, has been lost by courtesy of the old way of organizing work. This is essential in explaining some of the changes to be observed today. It is the front line, i.e., the ones in close contact with the customer, or the ones on the floor and who know where the shoe pinches who become the target of information system design, knowledge development, knowledge integration, decision-making processes, strategy development, etc. This will also have consequences for the way organizations structure the part– whole relation. 19 Garbor (1991) and Juran (1964, 1989).

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Fig. 4.2. The Link Between Systemic Thinking, Organizational Learning and Knowledge Management. Emphasis on internal motivation

Promotes

Influences the understanding of

Reinforces

Knowledge management and Organizational learning

Promotes

Idea generation in the system

Promotes

Affects

Relations in and among systems

Systemic thinking as the philosophical basis for the model

Three elements can be extracted as parts of the new models of thinking in organizations: • The importance of internal motivation • The emphasis on relations in and among systems • Focus on idea generation from everyone in the organization These entities also constitute important elements in systemic thinking (see Bunge, 1989) (Fig. 4.2).

EMPHASIS ON INTERNAL MOTIVATION A major point is that the transition from functional organization to knowledge organization and knowledge management, based on organizational learning processes, cannot

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materialize on the basis of mechanistic thinking with its emphasis on “command and control.” It is the employees themselves who have to be the driving force in this restructuring. Neither will we see a new pattern develop by investing in new technology, plugging it in, and hoping that new ways of coordination will emerge as a result. On the other hand, it is often through these strategies that organizations try to change. For most people learning will most likely be synonymous with information acquisition. But we do not learn by acquiring information. We neither learned how to swim nor to read or drive a bicycle by acquiring information on swimming, reading, or cycling. There is in other words no learning separated from action. But, action is not enough to learn; time has to be built in for reflection relative to the action as well as what is learned. A major part of learning is then carried out by means of the processes: planning, action, and reflection (Fig. 4.3). In all the elements of planning, action, and reflection, information is an important entity, leading to the conclusion that the social mechanisms behind the three entities are information, the consequence of learning, and knowledge development. This leads to the following definition of knowledge: Information which is structured and integrated for specific purposes. Knowledge is then an integral part of the processes planning, action, and reflection also as an input factor through various interrelated feedback loops. The procedure of designing the learning organization, according to this account, is to make sure that the organizational design coincides with the three processes which constitute learning. The core is that the employees must feel obligated toward this learning process, i.e., they must be internally motivated for learning. One thing which should be avoided is ensuring a decrease in motivation by, for example, creating uncertainty

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Fig. 4.3. Constituting Elements Behind Internal Motivation. Planning

constituting element for Influences Improves

Internal motivation constituting elements for

constituting elements for

Must generate room for

Reflections

Actions

Systemic thinking as the philosophical basis for the model

about the work situation of the individuals or for example by downsizing or outsourcing and other mechanisms conducive to short-term productivity gain, but with an in-built liability to generate a loss of motivation on the part of the employees being “left behind” in the organization. There are five questions which are crucial for the link between internal motivation and organizational learning, as presented above. These are as follows: 1. What will they (employees) learn? This is linked to personal and organizational goals. 2. What is the purpose of learning it (seen from the employees’ point of view)? This is linked to what the employees want to achieve by their actions.

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3. Why do they (employees) want to learn this? This is linked to past reasons, influencing the present situation. Question three is qualitatively different from question two. Question two is oriented toward a future situation, while question three is linked to a past situtation. 4. What are they (employees) prepared to sacrifice in order to learn something? This is linked to intensity and commitment to the learning process and indicates something about the strength of the internal motivation. 5. How will they (employees) learn? This is linked to methods which can be utilized in the learning process, for example “on the job training,” “learning by doing,” “learning by using,” “learning by experimenting,” “learning by interaction,” scenario processes, formal education in the college and university system, flexible learning, simulation models, etc.

RELATIONS IN AND AMONG SYSTEMS If the developmental features mentioned in the introduction turn out to be a reality in future organizations, the control of the activities will be more indirect. The informal network of the activity will emerge as the interesting area of knowledge pertaining to the influence of behavioral change in the system. To disclose this informal network in activities, where management is left to self-managed autonomous groups, will be crucial for any reversal operation or for generating effective learning processes. If knowledge of this kind does not exist,

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management may easily find themselves in a position where they exercise funfair steering, i.e., you turn the steering wheel like mad regardless of the fact that there are no connections between the steering wheel and the activities going on at the activity level. Many decisions can in such cases be made both quickly and effectively by the management, with the result being, however, that the effect of the decisions fails to materialize. Unless obligating feedback mechanisms are designed between the activities and the decisions, funfair steering will easily be the outcome. Examples from the public sector are numerous. A principal, who through his position as the leader of the operations makes decisions alone or in cooperation with the board, all too often experiences that the operations these decisions were meant to influence do not change regardless of what decisions are being made. The transition from funfair steering to learning organizations could be made by disclosing alliances and relations and then making decisions, integrating the persons linked to these activities in the decision-making process. The point of the reference funfair management is that decisions made by the management can go in one direction, while the operations one sets out to control and go in a completely different direction. If effective links and obligating feedback designs are not built in, funfair management will often be the outcome. The most obvious question is why things still work out satisfactorily if funfair management is such a widespread phenomenon. The answer is that persons carrying out the operations of the system to a major extent are responsible individuals and discharge their duties in a satisfactory manner in spite of this lacking link. Problems occur however during times of increasing turbulence and when major changes are to be carried out. It is in those kinds of situations that necessary changes in the system are impossible to carry out.

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The opposite of funfair management is the learning organization. In the learning organization there is consistency between the intention, the measures being used in the management context, and the goals being pursued by the system. There is further a strong link between decisions and operations. Persons carrying out operations are participants in the decision-making process in the manner previously discussed under internal motivation. Insight into existent relations is also important since what is reported in the system depends directly on what relations exist. If there is basic distrust in the system, one type of reporting will be the effect. If relations based on basic trust exist, an entirely different kind of reporting will take place. How relations are developed and maintained is among other things expressed in our way of using metaphors and symbols. The real meaning of metaphor is transfer, i.e., we transfer something from one area to the area we wish to say something about, for example, the performance of a machine. The operation is of course not a machine, but metaphorically we compare the organization with a machine. This type of comparison has bearing on how we act in the social system and thus the importance of the reaction between people. Metaphors can be described as the joining glue in the social system. Different use of metaphors has direct impact on both individual behavior and the system’s way of coping with adversity. We can also say that metaphors structure our way of thinking and acting. In this way our use of metaphors also becomes an expression of our way of running activities. If the military metaphor sets the tone for the operation, we will think of employees as soldiers and competitors as the enemy. In war, soldiers can in given situations be written off, if a victory was won through this loss. If the military metaphor is widespread in the operation, relations being developed will be based on

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this metaphor. The military metaphor is surprisingly common in organizational contexts: for example lines of command, staff, strategy and tactics, attacking competitors, carry out basic training, confer with headquarters, etc. The military metaphor used alone will limit the choice of solutions to problems, while clear hierarchical relations are being developed in the operation. The military metaphor also indicates that somebody must win and others must lose. The war metaphor develops the win–lose context in the operation, where the win–win context would have been more suitable. If the metaphor is play, i.e., organizations as play and fun, the action room immediately takes on a new meaning compared to a situation where the war metaphor is being used. In play the main objective is not necessarily winning. In play it is in fact participation, having fun, which is the main objective. Relations in an activity where this basic metaphor dominates will more easily develop win–win contexts, than would be the case if the military metaphor were used. The metaphors being used by us are not trivial but have direct behavioral impact on the relations in and between systems. It is therefore important for us to have a clear understanding of the basic metaphor being used, since it has a direct impact on how learning is achieved in the organization. The basic metaphor also has impact on the way in which we communicate with others. If the leader regards himself as a general and the actors as soldiers, he will relate to the actors in an entirely different way, compared to if sandlot play was the basic metaphor. In the sandlot everything is possible, and the sand castles we do not like are rebuilt without fuss. The use of metaphors also operates at a deeper level than relations and our way of communicating. They express our most basic values. Most of us are averse to disorder and insecurity. This could be one explanation why the military metaphor is so common

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in organizations. One way of loosening up the metaphor use is by developing creative groups in the operation, for the purpose of actively using more metaphors on quite concrete problems. These metaphor systems can then be filed in a database and related to the problems which were attempted and solved by means of the various metaphors. The various solutions and their results are further linked to this knowledge base. As this system has had a chance to develop in reality, the metaphors most suitable for solving given problems will crystallize. In this way the variety in metaphor use will be an integral part of the operation. This prevents metaphors from narrowing down the action room and will therefore serve to inspire relations in the operations. The sheer fun of it should not be underestimated as an asset in the organizational context. Emphasizing the build-up of good relations in an organizational context is not the same as toning down tasks and activities to be carried out by the system. On the contrary, a link between emphasis on tasks, activities, and the development of relations is a foundation in the development of the learning organization. All the three elements must be focused on if organizational learning is our target. One important factor in the knowledge-based organization is the distribution of power and authority (Uden, Lu, & Ting, 201720). It is impossible to handle complex systems with command and control, where authority and power are located in the top section of the organization (Smiraglia, 2016). Another important issue in knowledge-based organizations is how control, integration, and coordination are to be put into effect. One prerequisite is that everyone in the organization must gain knowledge of how their decisions impact others, 20 This is a conference report, and many of the contributors agree with the point made by us.

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since this develops learning of the part–whole relationship. Even if important lines of command disappear, even if the days are over when visions were created at the top and put into practice at the bottom, and even if the top no longer thinks and the actors act out their ideas, our way of thinking will be in the function-organized mode, since our thought models have been in this mode for several hundred years, causing a cognitive time lag. This is the core issue in the development of a learning organization: How can we change people’s mental models? How can we change people’s thought and action patterns? An important point is that everyone in the organization understands how the partial system of which they are a part influences the other partial systems, the system as a whole, and the environment (Fig. 4.4).

Fig. 4.4. Constituting Elements Behind the Relationships in and Between Systems. Our way of thinking (The use of metaphors etc.)

constituting element for Influences Reinforces

Relationships in and among systems constituting elements for

The receptivity of information and the connectivity to the environment

constituting elements for

Affects

The tension between the management level and the activity level

Systemic thinking as the philosophical basis for the model

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If there is a common obligation in the social system, or in partial systems within it, this will mean that plotting the course becomes a common concern for everyone in the organization, i.e., management has more responsibility than functional top-down control, and understanding consequences of one’s own actions will be easier as a result of this. However, if we try to change organizations, we won’t get anywhere if the structure does not support the intended changes. What, then, constitutes structure? 1. There are elements, for example, individuals, groups, departments etc. 2. There are relationships between the elements 3. Relationships as a whole constitute one unit Structure is then the superior composition of relationships. If we are to change a system (e.g., organizations), relationships must be changed. By changing relations, positions will also be changed. The simplest relationship, and most easily recognizable one for a lot of us, is the triangular relationship. If relationships are changed, the entire triangular relationship will change, i.e., the structure changes, and the relationships between the two remaining parties will also change. Relationships say something about potential behavior, i.e., there is a predicative effect inherent in relationships. One common way of changing relationships is to bring a new element into the relationship, for example the therapist, or in business, the consultant. While this element enters the system, the system is changed, as new relationships emerge, both internally in the system and between the system and the outside world. When there is tension in a relationship, very little annoyance is required to trigger large-scale behavior. One way of creating tension is to introduce contrast into the relationship, for example, paradoxical intervention.

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IDEA GENERATION IN THE SYSTEM A distinction which is important to make is the major difference between a research-based organization and a knowledgebased organization. Research-based organizations may well be organized according to functional principles and also are to a major extent. This is the R&D department in organizations. The knowledge-based organization is not organized according to functional principles, but process principles (Bolisani & Handzic, 2016). In a function-based organization vision will emanate from the top. The question is then how to communicate it to the employees; down the stairs to the employees, literally speaking. In the knowledge-based organization, information, vision and idea generation are supplied by the employees in the organization and particularly from the “floor” and the front line, i.e., those who are in contact with the customer/ user. The question here is how this can be integrated and coordinated in order to benefit the whole organization.

CONCLUSION In the knowledge-based organization the vision and ideas emanate from various parts of the system. One faces an integration and coordination problem in this kind of organizations and not a command and control problem. Another important aspect of vision and generation of ideas in knowledge-based organizations is ambiguity and the potential for continuous development. The vision in the function-based organization is fully developed from the top of the system, unambiguous and without doubt. In the knowledge-based organization, it is precisely the doubt and the ambiguous element which sow the seed of creativity and innovation. The

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point is that the vision should be developed by the employees of the system, making them aware of their ability to change the vision. In the function-organized organization, vision and idea generation are more to be regarded as a directive, an order, or something that could be carried out and communicated vertically in the system, i.e., some have contemplated the implementation of the ideas in practical action as being carried out by others. Communication courses for management are in such organizations focused on influence mechanisms. This does not generate committed participation from the employees of the company. When the vision is ambiguous, dynamic, and open to change, the employees can set up their own targets. Self-organization then appears as an important element and thereby the internal motivation to make the extra effort to gain competitive advantage. The point is, however, that the action sequence does not follow the classic hierarchy but arises from the interaction of the various parts, where there naturally will exist coordination and integration problems. The vision in knowledge-based organizations is developed in the entire organization. It is the real cooperation creating an obligating cooperative system which is instrumental in creating the future for itself and the organization (Fig. 4.5). A prominent feature in the knowledge-based economy is the insight into and experience on the part of the individual actor, to have his own goals, i.e., goals which they try to reach for themselves. They are not tools for others, machines to be turned on and off, or work for greater economic reward. They have another form of motivational structure than previous actors in social systems. At the same time, we see an increasing awareness among persons outside the organizations in question. They ask the following question: In what way do companies/organizations influence our way of living? The answers to many of the questions companies

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Fig. 4.5. Constituting Elements Behind Idea Generation in the System. A clear vision

constituting element for Influences Reinforces

Idea generation constituting elements for

Emphasis on co-operation

constituting elements for

Affects

The will to create the future

Systemic thinking as the philosophical basis for the model

were asked by persons outside the companies precipitated reactions against them, for example the environmental protection movement, women’s liberation movement, consumer movement, the inequality movement, etc. This was not necessarily based on economic forces but entirely different motivations and social mechanisms linked to the company in its environment. Companies then face three purposes which they must take under consideration: 1. The purpose of the organization 2. The purpose of the actors belonging to the organization 3. The purpose of the larger system in which they are involved It is therefore the system in the environment which becomes increasingly prominent in the knowledge-based economy.

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REFERENCES Barney, J. B. (1986a). Types of competition and the theory of strategy: Toward an integrative framework. Academy of Management, 11(4), 791–800. Barney, J. B. (1986b). Organizational culture: Can it be a source of sustained competitive advantage? Academy of Management Review, 11, 656–665. Barney, J. B. (1991). Firm resources and sustained competitive advantage. Journal of Management, 17, 99–120. Barney, J. (1992). Integrating organizational behavior and strategy formulation research: A resource based analysis. In P. Shrivastava, A. Huff & J. Dulton (Eds.), Advances in strategic management (Vol. 8, pp. 39–61). Greenwich, CT: JAI Press. Bolisani, E., & Handzic, M. (2016). Advances in knowledge management. London: Springer. Bunge, M. (1989). Ethics: The good and the right. Dordrecht: D. Reidel. Garbor, A. (1991). The man who discovered quality. New York, NY: Random House. Grant, R. M. (1991). The resource based theory of competitive advantage: Implication for strategy formulation. California Management Review, 33(3), 114–135. Grant, R. M. (1996). Prospering in dynamically-competitive environments: Organizational capability as knowledge integration. Organizational Science, 7(4), 375–387. Juran, J. M. (1964). Managerial breakthrough. New York, NY: McGraw-Hill.

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Juran, J. M. (1989). Juran on leadership for quality. New York, NY: The Free Press. Smiraglia, R. (2016). The elements of knowledge organization. London: Springer. Uden, L., Lu,W., & Ting, I. H. (Eds.). (2017). Knowledge management in organizations. London: Springer.

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5 EPILOGUE

Organizations of today will be divided into at least three categories. Firstly there are organizations which can metaphorically be regarded as machines. There are those which can be regarded as organisms, and there are the ones which function as social systems. It is organizations as social systems which characterize the knowledge-based economy, knowledge management, and the learning organization. The machine age had industrialization as its ally. The knowledge-based economy is based on robots, informats, artificial intelligence, symbol machines, computers, and automats. The knowledge-based economy is based on three pillars; observation, information, and communication by means of robots and informats. The physical revolution was linked to muscular strength, where the manufacturing of physical products was the essential element. The knowledge-based economy is linked to mental processes, symbol development, symbol integration, reflection, and learning, where knowledge development, knowledge transmission, and practical application of knowledge constitute the focus of attention.

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When systems become more complex, it may be difficult for us to see the consequences of our behavior. One major purpose of systemic thinking is to draw attention to the fact that the individual systems interact with each other. Due to rapid changes occurring in the environment (less and less time for reflection), it is neither desirable nor possible for management alone to manage to develop the necessary contacts with the environment. This means that the classic ways of organizing, with their hierarchies and command structures, will be totally changed in the knowledge society. There are other types of organizing which will be more beneficial for companies. New ways of organizing work will be a dominant feature of the knowledge-based society. Learning organizations start by changing established ways of thinking, not by changing the system of the organization or the environment. Organizational learning has our mental models and our relations to others as its starting point. The profound structure of a learning organization is how we think and how we interact with others. This influences how the organization functions. There are of course tools and methods which are used at the start, but the initial starting point is always our way of thinking. To bring about organizational learning, a group of people in the organization collectively trying to see the world in a new way is required. A very high degree of obligation on the part of these people is required to initiate processes instrumental in developing the learning organization. Until this commitment from a group of people exists, no process toward organizational learning will materialize. The purpose of developing models of a phenomenon and problem in the organization by means of positive feedback loops, negative feedback loops, and time lag is to generate awareness of the problem/phenomenon among the parties involved, i.e., the continuous process of part–whole relations in order to generate emergents.

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Fig. 5.1. The Distinction Between Functional Organizing and Knowledge-Based Organizing. Distinction

Functional organizing

Knowledge-based organizing

1. Long time lag

1. “ Information in time”

2. Independent partial systems

2. Positive and negative feedback structures (loops) designed into and between systems 3. Surveying incidents

3. The complete structure can only be detected in the event of crisis or collapse 4. System-focused

4. Person-focused

5. Re-actment

5. En-actment

A synthesis of what has been discussed in the epilogue can be done as in Fig. 5.1. The knowledge of systemic learning is to learn how to see the interdependence of the systems we are part of. If people are really committed to something, the commitment will spill over to others in the organization and the environment. And it is this commitment which constitutes the first step in developing learning organizations. One important issue is the following: How are we to design organizations; developing, integrating, and applying knowledge to practical purposes? What social mechanisms different from mechanisms existing in function-oriented organizations must exist in organizations of this kind? Four areas stand out: • Philosophy, which in this context means our thoughts and action patterns. • Attitudes, which here is meant our way of thinking, speaking, and acting.

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• Methods, skills, and behavior • Artifacts, which here mean instruments, machines, robots, and informats. The philosophical level is the basic foundation on which the entire pattern rests. On the other hand are practical tools instrumental in initiating a development toward the learning organization, knowledge creation, and innovation. The basic suppositions, what cannot be observed is a form of hidden knowledge, controlling our thought and action patterns should be emphasized because this form of knowledge is supposed to lead to creativity and innovation. Attitudes are more apparent than our thought and action patterns. This is a way of concretizing our philosophy of life. To change our basic way of thinking and acting is the most difficult and time-consuming project in the effort to develop learning organizations, but the initiation of this process is crucial if lasting changes are to be achieved. New tensions have occurred in social systems, and this means that new things must be understood in new ways. New ways of thinking and new methods are required to solve occurring problems. What will be required is creativity and innovation, in addition to the ability to see patterns in developmental features. New organizational forms, different from the function-based organization, are about to break through, where new artifacts linked to new ways of organizing, new ways of thinking, and new attitudes to knowledge develop in organizations.

GLOSSARY

Ambidextrous organizations. Ambidextrous organizations are organizations that have the ability to adapt to changes in external conditions while at the same time generating their own future by means of, among other things, performance improvement, growth, and innovation (Duncan, 1976; O’Reilly & Tushman, 2004, 2006, 2011; Thota & Munir, 2011). In 2004, O’Reilly and Tushman expressed that ambidextrous organizations would constitute one of the major challenges for management in the global knowledge economy. The findings of O’Reilly and Tushman (2004) were overwhelming. Regarding the launching of radical innovations, they found that none of the cross-functional or unsupported teams and only a quarter of the teams with functional designs were able to produce radical innovations. However, among the ambidextrous organizations, 90% were successful in producing radical innovations. Empirical research has shown that this type of organizational design is best for producing both incremental and radical innovations (Thora & Munir, 2011). Asplund’s motivation theory.21 In brief, this theory can be described in the following way: People are motivated by social 21 Asplund’s motivation theory, a term we use here, is based on Asplund’s research.

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responses (Asplund, 2010, pp. 221–229). The following statement may be said to be a central point made by Asplund’s theory: When people receive social responses, their level of activity increases. Asplund’s motivation theory is consistent with North’s action theory (ref. North’s action theory). Understood in this way, it seems reasonable to connect the two theories in the statement: People are motivated by the social responses rewarded by the institutional framework. Availability cascades. This refers to the idea that we are all controlled by the image of reality created by the media because this image is easy to retrieve from memory. Availability proposition. This may be expressed as follows: The more easily information enters into our consciousness, the greater the likelihood that we will have confidence in that information. In other words, we believe more in the type of information that is available in memory than the information that is not so readily available. Behavioral perspective. This perspective focuses on the behavior of employees as an explanation for the relationship between business strategy and the results obtained. Boudon–Coleman diagram. This research methodology was developed by Mario Bunge (Bunge, 1978, pp. 76–79) based on insights made by the sociologists Boudon and Coleman. The purpose of the diagram is to show the relationship between the various levels, such as the macro- and microlevels. For instance, it is shown how changes at the macrolevel, such as technological innovations in feudal society, can lead to increased income at the microlevel. However, it was shown that technological innovations could lead to weakening of the semifeudal structures because dependency on landowners was reduced. Consequently, the landowners opposed such changes especially in the case of technological innovations, which Boudon has

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shown in his research (Boudon, 1981, p. 100). Coleman (1990, pp. 7–12) started at the macrolevel, went to the individual level to find explanations, and finally ended up at the macrolevel again. An important purpose of Bunge’s Boudon–Coleman diagram is to identify social mechanisms that maintain or change the phenomenon or problem under investigation (as mentioned above, in Boudon’s analysis of semifeudal society). Bunge’s Boudon–Coleman diagram may be said to represent a “mixed strategy”; Bunge says the following: When studying systems of any kind (1) reduce them to their components (at some level) and the interaction among these, as well as among them and environmental items, but acknowledge and explain emergence (see the chapter on concepts) whenever it occurs, and (2) approach systems from all pertinent sides and on all relevant levels, integrating theories or even research fields whenever unidisciplinarity proves to be insufficient (Bunge, 1998, p. 78). The purpose of this research strategy is to arrive at a deeper and more complete explanation of a system’s behavior. Capabilities. Capabilities are for an organization what abilities are for an individual. An organizational capability may thus be defined as an organization’s ability to perform a task, activity, or process. Operational capabilities enable an organization to make money in the here and now (Winter, 2003, pp. 991–995). Dynamic capabilities, as opposed to operational capabilities, are linked to processes of change. Change and innovation are at the center of dynamic capabilities. Simplified, one may say that organizational capabilities are something an organization does well compared to its competitors (Ulrich & Brockbank, 2005). These capabilities are intangible and therefore difficult for competitors to imitate (Wernerfelt, 1984).

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Cohesive energy. In a social system cohesive energy is “the glue” that binds the system together. Cohesive energy is the social mechanisms that make the system durable. According to systemic thinking, it is the relationships and actions that bind social systems together. The rationale is that relationships and the systems of relationships may be said to control human behavior. Social systems are held together (in systemic thinking) by dynamic social relations (e.g., feelings, perceptions, norms) and social action (e.g., cooperation, solidarity, conflict, and communication). Cocreation. Cocreation involves working together to promote knowledge processes and innovation. If knowledge processes and innovation are essential for value creation in the knowledge society, cocreation is an important social mechanism for initiating, maintaining, and strengthening these processes. The balance between competition and cooperation, embodied in the concept of cocreation, leads to constructive criticism and the necessary scope of knowledge that exists in the network so as to promote creativity and the innovative. Instead of a zero-sum situation, a positive-sum situation will be developed where everyone wins. Collective blindness. Collective blindness may be said to be a form of collective arrogance, which results in irrational actions. Minor events slip under the radar, causing the system to not be fully aware of what is happening. Politicians’ explanations why voters in a referendum vote contrary to what most of the power elite and the media advocated are an example of collective blindness. Competence. Competence refers to knowledge, skills, and attitudes. Core competence. The concept was popular in the strategy literature of the 1990s. Core competence may be defined as: “a bundle of skills and technologies that enable a company to provide a particular benefit to customers” (Hamel &

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Prahalad, 1996, p. 219). More recently, core competence as a concept has been given less attention in the research on dynamic capabilities, and now there is more focus on the concept of fitness. The term evolutionary fitness is also used in the research literature in connection with technology, quality, cost development, market development, innovation, and competitive positioning (Helfat et al., 2007, p. 7). Discontinuous innovations. These are innovations that change the premises of technology, markets, our mindset, and so on. We know that sooner or later discontinuous innovations will emerge in the future (Hewing, 2013). Dynamic capabilities. Dynamic capabilities stem from the resource-based perspective and evolutionary thinking in strategy literature (Teece, 2013, pp. 3–65, pp. 82–113; Nelson & Winter, 1982). The dynamic perspective attempts to explain what promotes an organization’s competitive position over time through innovation and growth (Teece, 2013, p. x). The original thinking concerning dynamic capabilities may be related to Teece et al. (1997). These authors defined dynamic capabilities as an organization’s ability to create, develop, and modify its internal and external expertise in order to address changes in the external world. Dynamic capabilities are now seen as all the organizational processes, not only internal and external expertise, that contribute to an organization’s capacity to adapt to change while creating the organization’s future. Emergent. An emergent occurs if something new turns up on one level that has not previously existed on the level below. With emergent we mean: Let S be a system with composition A, i.e., the various components in addition to the way they are composed. If P is a property of S, P is emergent with regard to A, if and only if no components in A possess P; otherwise P is to be regarded as a resulting property with regards to A (Bunge, 1977, p. 97).

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Entrepreneurial spirit. The entrepreneurial spirit may be described as follows (Roddick, 2003, pp. 106–107): • The vision of something new and belief in this that is so strong that belief becomes reality. • A touch of positive madness. • The ability to stand out from the crowd. • Creative tension bubbling over. • Pathological optimism. • To act before you know! • Basic desire for change. • Creative energy focused on ideas, not on explicit factual knowledge. • Being able to tell the story you want to sell. Evidence. This may be results, such as research results, that can be relied on. However, it is also important to be aware of the fact that other evidence may be available without having to refer to figures and quantities, such as evidence that emerges from observations and good judgment without the assessment being quantified. Evidence-based research is research results that are based on approved and accepted scientific research methods. Explicit knowledge is the part of our knowledge base which can be easily communicated to others as information, i.e., know what. Explicit knowledge can be objective and intersubjective. Bunge (1983, p. 80) defines objective knowledge in the following way: “Let p be a piece of explicit knowledge. Then p is objective if and only if a) p is public (intersubjective) in some society, and b) p is testable (checkable) either conceptually or empirically.” Lei (1997, p. 213) stated that “explicit knowledge is that which can be written down, encoded, explained or understood by anyone with a basic understanding of the technology or phenomenon at hand – inside or outside of the firm.” Lei

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further argues that although explicit knowledge can be protected by patents and thus remain proprietary, such knowledge is “transparent” in the sense that anyone with a comparable knowledge or skill base can understand the relevant technology and decipher it. Feedback. Giving the other person feedback, for instance with regard to their behavior, attitudes, and the like, is the most important element in the area of interactive skills and emotional intelligence (Goleman, 1996, 2007). Analysis of feedback is a sure way to identify our strengths and then reinforce them (Wang et al., 2003). Failure to give people feedback on their behavior in some contexts may even be considered immoral. Feed-forward. Feed-forward is regarded here as an expectation mechanism. It seems reasonable to assume that our expectations influence our behavior in the present. It is therefore important that we make explicit to ourselves the expectations we have of a situation. By making expectations explicit, we have a greater opportunity to learn from our experiences and thus improve our performance. Front-line focus. This refers to those in the front line, i.e., in direct contact with customers, users, patients, students, etc. They have the greatest expertise, necessary information, and decision-making authority and are regarded as the most important resource in the organization because they are at the point where an organization’s value creation occurs. Global competence network. These competence networks may be divided into political, social, economic, technological, and cultural patterns. It is when these five patterns interact that one may perceive the overall pattern. In the global knowledge economy it seems reasonable to assume that those who control this pattern set the conditions for economic development. These global competence networks

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will most likely make an impact on HR departments in companies competing for this kind of expertise in national markets. Global competence networks are also emphasized as crucial for economic growth by OECD (2001), although they use the term innovative clusters. The purpose of innovative clusters and global competence networks is the development, dissemination, and use of new ideas that promote wealth creation. There is much to suggest that a greater degree of integration and cooperation between private and public sectors at the national and regional levels is an important prerequisite for initiating the innovative locomotive effect. The global competence networks are metaphorically the energy source that sustains the motion of this locomotive. It would be counterproductive to replace the locomotive once in motion. Conversely, the individual carriages of the locomotive (read: organizational level) can be changed depending on their competitive position. The individual passengers on the train create ideas and knowledge through the processes that may be called creative chaos. In this way we will arrive at a tripartite of the prerequisites for global competence networks. At the individual level, creative chaos occurs. At the organizational level, there will be creative destruction. At the social and global levels, creative collaboration takes place. These three processes create innovation and economic growth as an emergent, not as a future perfectum, i.e., a planned process with given results. A prerequisite for the reasoning above is that tension and competition at one level requires collaboration at another level. Competition and cooperation are both necessary if one is to develop innovation and economic growth, in the same manner that stability and change are necessary for flexibility. Too much of the one (stability) leads to rigidity, and too much

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of the other (change) leads to chaos. Understood in this way, emergents cannot be planned. Hamel’s law of innovation. The “law” states that only between one and two of one thousand ideas become innovations in a market (Hamel, 2002, 2012). Therefore, an infostructure must be created to ensure that ideas are continuously produced in a business. Hidden knowledge. Hidden knowledge is what we do not know we do not know. Kirzner (1982) says that hidden knowledge is possibly the most important knowledge domain of creativity, innovation, and entrepreneurship. Hidden knowledge, i.e., knowing how we know, is the premises, prerequisites, and motives influencing our thoughts and action positions. Hidden knowledge influences the way we think and act, as a sort of personal paradigm, or the technical– economic paradigm in the business world, a trajectory which leads our way of thinking and acting when expressing and interpreting, among other things, new ideas. Hidden knowledge organizes the development of mental models, the nature of the abstraction we make, the choice of “variables,” the facts we choose to focus on, our underlying metaphysical positions, our theoretical “tastes,” etc. Hidden knowledge can be divided in two parts: disposition to think and disposition to act. In this way hidden knowledge is linked to company-specific norms. Hidden knowledge is learned by socialization and could be shared in the business world, first of all by focusing upon its existence and second by using focus groups. It is the willingness to question underlying assumptions which in practical settings has to be focused. The use of focus groups gives access to uncodified knowledge, the language, mental models, the opinions, the meanings, the presuppositions, and the world view of the participants. Focus groups also give the opportunity to make synergy of the individual’s way of thinking as part of a collective.

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History’s “slow fields.” This refers to the fact that norms, values, and actions tend to be in operation long after the functions, activities, and processes that initially created them disappear, thus generating so-called slow fields of history. These norms, values, and actions exist though they have no apparent function, contributing to maintaining a type of behavior long after the type of behavior is functional or meaningful.22 For sociologists and historians it is important to determine whether norms and values have any function or whether they are part of history’s slow fields. By examining history’s slow fields, it may be possible to provide better explanations for phenomena. HR management. HR management is defined as HR practices at various levels (micro, meso, macro) for managing people in organizations. HR management has been defined in many different ways. For instance, Boxall and Purcell (2003, p. 1) define HR management as all those activities oriented toward managing relations between employees in an organization. This definition emphasizes the relational perspective. Later, they expanded their definition to include all the activities and processes that underpin an organization’s value creation (Boxall and Purcell, 2010, p. 29). On this basis, Armstrong defines the activities and processes that HR management should engage in: “HRM covers activities such as human capital management, knowledge management, organizational design and development, resource planning (recruitment, talent development), performance management, organizational learning, reward systems, relationships between employees, and employees’ wellness.” (Armstrong,

22 Asplund (1970, p. 55) refers to a similar phenomenon when he discusses Simmel. He points out that the norms that may have had a positive function during a historic phase become in a later phase dysfunctional.

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2014, p. 6). However, we believe Armstrong underestimates two essential areas of knowledge in his definition: the management of innovation processes and change processes in organizations. Innovation and change are strongly emphasized in the global HRM survey (White & Younger, 2013, pp. 35–39). Armstrong has included the ethical perspective in his handbook for HRM (Armstrong, 2014a, pp. 95–105). Management of innovation processes and change processes in organizations is also highlighted and underlined by Wright et al. (2011, p. 5) in their description of HRM. However, it must also be said that Armstrong discusses innovation (Armstrong, 2014, pp. 145–155), but not in his process definition of HR management. Innovation and change processes are also emphasized by Ulrich et al. (2013). Brockbank (2013, p. 24) especially mentions these two processes as being important in the research model Ulrich et al. (2013) have developed through their empirical research over 25 years. Implicit knowledge. This is knowledge that is spread throughout an organization but not integrated. Informat. Robots connected globally with all new research and information related to their field of inquiry. By informat is also meant: symbol-transmitting devices and symbolconnecting devices, which focus on connectedness. Information input overload. This occurs when an individual, a team, an organization, or a community receive more information than they can manage to process. In a situation characterized by information input overload the following may occur (Miller, 1978, p. 123): 1. 2. 3. 4.

Designated tasks and responsibilities are left undone Errors are made Queues of information occur Information is filtered out that should have been included

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5. Abstract formulations are made when they should have been specific 6. Communication channels are overloaded, creating stress and tension in the system 7. Complex situations are shunned 8. Information is lumped together for processing Each of the above eight points may result in a decrease in efficiency when the system is exposed to information input overload. Infostructure. The infostructure concerns the processes that enable the development, transfer, analysis, storage, coordination, and management of data, information, and knowledge. The infostructure consists of 11 generic processes, as shown in Fig. 8 in this book. The 11 processes in the infostructure may be considered as nodes in a social network at different levels, for example team, organization, society, and region, all in the global space. Together, the 11 processes comprise the totality of the infostructure. It may be said that the infostructure has the same importance in the knowledge society as the infrastructure had in the industrial society. Innovation. Innovation is here understood as any idea, practice, or material element, which is perceived as new for the person using it (Zaltman et al., 1973). Ideas are seen as the smallest unit in the innovation process (Hamel, 2002, 2012). However, this refers to the ideas that are in process of development and not fully developed ideas. Before an idea can be characterized as innovative, it must prove to be beneficial to somebody, i.e., the market must accept the idea and apply it. Consequently, the creative process of innovation is here understood as the benefit it has for a market (Amabile, 1990, Johannessen et al., 2001, p. 25). Thus, it is not sufficient that an idea is new for it to be

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considered an innovation. An idea may have a great degree of novelty, but if it is of no benefit to anybody in the market, then it has no innovative value. Kaizen. This is a Japanese method, which means that an organization develops systems for organized improvement (Maurer, 2012). Knowledge. The definition of knowledge used here is the systematization and structuring of information for one or more goals or purposes. Knowledge enterprise. This is an enterprise that has knowledge as its most significant output. It is perhaps helpful to think of the process input – process – output to separate industrial enterprises from knowledge enterprises. Much knowledge and skills are needed to produce high-tech products such as computers, and there are also many knowledge workers involved in this process. However, the majority of products produced today are high-tech industrial products, and although such products require very skilled knowledge in the production process, they are nevertheless output industrial products. On the other hand, law firms, consulting firms, and universities are examples of knowledge enterprises. Knowledge worker. A knowledge worker has been described by the OECD as a person whose primary task is to generate and apply knowledge, rather than to provide services or produce physical products (OECD, 2000a,b,c,d,e, 2001). This may be understood as a formal definition of a knowledge worker. This definition does not restrict knowledge workers to creative fields, as is the case with, for example, Mosco and McKercher (2007, pp. vii–xxiv). The OECD definition also allows for the fact that a knowledge worker may perform routine tasks. The definition also does not limit the type of work performed by knowledge workers to tasks relating to

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creative problem-solving strategies, unlike the definition provided by Reinhardt et al. (2011). Knowledge management. Management of knowledge resources in an organization. These resources may be explicit knowledge, implicit knowledge, tacit knowledge, and hidden knowledge. Locomotive effect. This refers to something that generates and then reinforces an activity or development. Metaknowledge. It is the knowledge base structuring explicit knowledge, i.e., know why. Metaknowledge is also a sort of knowing how we know, appearing when reflections are made on the basis of our normative basis: Metaknowledge is both a process and a product. As a process it is expressed by Maturana and Varela (1987, p. 24): “Reflection is a process of knowing how we know.” As a product it is knowledge on how we think. Metaknowledge has bearing on the perspectives of individuals, i.e., what is seen and how this is perceived. When a person in a company works within the framework of a particular perspective, for example a technological– economic paradigm, he is likely to set greater store by some methods than others. The perspective generates meaning in terms of how the work is perceived and interpreted, in addition to adding input as to what a person is looking for in a job context. Metaknowledge is thus a form of split interpretation competence among the persons sharing the perspective. In this way metaknowledge directly influences these persons as to what type of explicit knowledge is relevant and meaningful for the company. The more uniform this perspective is among the most important actors of the company, the more influential this perspective will be as to what knowledge type (e.g., explicit versus tacit) is critical to the competitive position of the company. The persons in the company who have various degrees of metaknowledge or different basis perspectives will

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be able to view the same phenomenon, but interpret it differently, giving it various meanings relative to the opportunities and challenges of the company. Metaknowledge and explicit knowledge are learned and shared in the formal education system an in the business world. Modularization. An extreme fragmentation of the production process in the global knowledge economy. Production is fragmented and distributed according to the following logic: costs – quality – competence – design – innovation. Modular flexibility. The modulization of value creation. Modular flexibility may best be understood as the globalization of production processes and extreme specialization of work processes with a focus on core processes. Necessary and sufficient conditions. It may often be appropriate to divide conditions or premises into necessary conditions and sufficient conditions. Necessary conditions must be present to trigger an action, but these may not be sufficient. The sufficient conditions must also be present to trigger the action. North’s action theory.23 This action theory may be expressed in the following statement: People act on the basis of a system of rewards as expressed in the norms, values, rules, and attitudes in the culture (the institutional framework) (North, 1990, 1993). North’s action theory is also consistent with Asplund’s motivation theory (ref. Asplund’s motivation theory). Organizational learning. The firms ability to structure and systematize knowledge in and between systems, both for the purpose of achieving congruence with the changing business environment and for creating the firms own future. Our definition of organizational learning is closely linked to our 23 North’s action theory is a term we use here based on North’s research.

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definition of knowledge and represents a dynamic perspective on learning. Paradoxical intervention. The concept is from Waslawich (1984). It means to intervene contrary to what is expected and then act on the upcoming reactions. Primary task. An organization’s primary task is what the system is designed to do. Proposition. This is an overarching hypothesis. It says something about the relationship between several variables. A proposition relates to a hypothesis in the same way the main research problem relates to research questions. Punctuation. By punctuation (Bateson, 1972, pp. 292–293) a distinction is drawn between cause and effect; this is done with a clear motive in mind. A causality is thus created which does not actually exist in the real world, and one is then free to discuss the effects of this cause which has been created through a process of punctuation. A sequence of a process is selected, and then bracketed. In this way, we delimit what is punctuated from the rest of the process. Figuratively, we may imagine this as a circle that is divided into small pieces; one piece of the circle is then selected and folded out into a straight line. This results in the creation of an artificial beginning and end. This beginning and end of course cannot exist in a circle, but only through the process of punctuation. Relationship knowledge, i.e., know who, is defined as that which: “involves the social capability to establish relationships to specialized groups in order to draw upon their expertise” (Lundvall, 1995). In a time where turbulence and change are accelerating it is decisive for organizational survival to invest in relationship knowledge. Relationship knowledge is learned by interaction and could be shared by systematic work in teams complementarily composed both in the educational system and in the business

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world. An example for developing relationship knowledge is Japanese firms bringing their supplier partners along with them while visiting European customers. Both the firm and the supplier develop and strengthen relationships this way, in addition to the relationship with the customers. In these contexts hidden knowledge also will be made explicit. Social laws. Social laws constitute a pattern of a unique type. They are systemic and connected to a system of knowledge and cannot change without the facts they represent also being changed (Bunge, 1983, 1983a). The main differences between a statement of a law and other statements are as follows: 1. Law statements are general. 2. Law statements are systemic, i.e., they are related to the established system of knowledge. 3. Law statements have been verified through many studies. A pattern may be understood as variables that are stable over a specific period of time. A social law is created when an observer gains insight into the pattern. By gaining such insight, we can also predict parts of behavior or at least develop a rough estimate within a short period of time. Social laws are further related to specific social systems, both in time and space. However, this does not represent any objection to social laws because this is also true of natural laws (although these have a longer time span and are of a more general nature). Social mechanism. Robert Merton (1967) brought the notion of social mechanisms into sociology, although we can find rudiments of this in both Weber – with the Protestant ethic as an explanation for the emergence of capitalism in Europe – and in Durkheim, who uses society as an explanation for a rising suicide rate. For Merton, social mechanisms are the building blocks of middle range theories. He

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defines social mechanisms as social processes having designated consequences for designated parts of the social structure (Merton, 1968, p. 43). In the 1980s and 1990s, Jon Elster developed a new notion of the role of social mechanisms in sociology (Elster, 1983, 1989). Hedstrom and Swedberg write that the advancement of social theory calls for an analytical approach that systematically seeks to explicate the social mechanisms that generate and explain observed associations between events (Hedstrøm & Swedberg, 1998, p. 1). It is one thing to point out connections between phenomena. It is something quite different to point out satisfactory explanations for these relationships, which is what social mechanisms accomplish. A social mechanism tells us what will happen, how it will happen, and why it will happen (Bunge, 1967). Social mechanisms are primarily analytical constructs which cannot necessarily be observed; in other words, they are epistemological, not ontological. However, social mechanisms are observable in their consequences. An intention can be a social mechanism of action. We cannot observe an intention, but we can interpret it in light of the consequences manifested through an action. Preferences can also function as a social mechanism for economic behavior. We cannot observe a person’s preferences, but we can interpret them in the light of the behavioral consequences that manifest themselves. Social mechanisms are, understood in this way, analytical constructs, indicating connections between events (Hernes, 1998). Bunge says: “… a social mechanism is a process in a concrete system, such that it is capable of being about or preventing some change in the system as a whole or in some of its subsystems” (Bunge, 1997, p. 414). By “social mechanism” here we mean those activities that promote/inhibit social processes in relation to a specific problem/phenomenon.

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Material resources and technology are social mechanisms of the economic subsystem; power is a social mechanism of the political subsystem; fundamental norms and values are a social mechanism of the cultural subsystem; and human relationships are a social mechanism of the social subsystem. These system-specific social mechanisms interact with each other to achieve certain goals, maintain these systems, or avoid certain undesirable conditions in the system or the outside world. The difficulty of discovering social mechanisms and distinguishing them from processes may be partly explained by the fact that social mechanisms are also processes (Bunge, 1997, p. 414). For the application of social mechanisms, see the Boudon–Coleman diagram. Social system. From a systemic perspective, social systems can be conceptual or concrete. Theories and analytical models are examples of conceptual systems. Further, social systems are composed of people and their artifacts (Bunge, 1996, p. 21). Social systems are held together (in systemic reasoning) by dynamic social relations (such as emotions, interpretations, norms, etc.) and social actions (such as, cooperation, solidarity, conflict and communication, etc.). None of the social actions have precedence in the systemic interpretation of social systems, such as conflict in the case of Marx, and solidarity in the case of Durkheim. Staccato behavior (erratic behavior). If organizations introduce too many change processes in succession too quickly, a phenomenon may occur called “staccato behavior.” If an organization does not deal with this appropriately, it seems reasonable to assume that workers will become tired, burnt-out and demotivated. Perhaps most damaging to business, employees will lose focus on their primary task – what the business is designed to do. In addition, businesses will

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often experience that this leads to an increasing degree of opportunistic behavior (Ulrich, 2013a, p. 260). Strategic HR management. Strategic HR management is defined in this book as: The choices an HR department makes with regard to human resources for the purposes of achieving the organization’s goals. This is analogous to the view of Storey et al. (2009, p. 3) and consistent with the definition we employ of HR management. This means that strategic HR management must be focused on the micro-, meso-, and macrolevels. There are many definitions of strategic HR management. For instance, use of human resources in order to achieve lasting competitive advantages for the business (Mathis and Jackson, 2008, p. 36); management of the employees, expressed through management philosophy, policy, and praxis (Torrington et al., 2005, p. 28); development of a consistent practices in order to support the strategic goals of the business (Mello, 2006, p. 152); and a complex system with the following characteristics: vertical integration, horizontal integration, efficiency, and partnership (Schuler and Jackson, 2005). Systemic thinking. Systemic thinking makes a distinction between the epistemological sphere (Bunge, 1985), the ontological sphere (Bunge, 1983), the axiological sphere (Bunge, 1989, p. 1996), and the ethical sphere (Bunge, 1989). Systemic thinking makes a clear distinction between intention and behavior. Intention is something that should be understood, while behavior is something that should be explained. To understand an intention we must study the historical factors, situations, and contexts, as well as the expectation mechanisms. Behavior must be explained with respect to the context, relationships, and situation it unfolds in. What implication does the distinction between intention and behavior have for the study of social systems?

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Interpretation of meaning is an important part of the intention aspect in the distinction. Explanation and prediction become an essential part of the behavioral aspect of the distinction. In systemic thinking it is the link between the interpretation of meaning and explanation, and prediction, which provides historical and social sciences with practical strength. By making a distinction between intention and behavior, the historical and the social sciences are interpretive, explanatory, and predictive projects. According to systemic thinking, many of the contradictions in the historical and social sciences spring from the fact that a distinction is not made between intention and behavior. The problem of the historical and social sciences is that the actors who are studied have both intentions, and they also exercise types of behavior; however, this isn’t problematic as long as we make a distinction between intention and behavior. By simultaneously introducing the distinction between intention and behavior, systemic thinking has made it possible to identify, for instance, partial explanations from each of two main epistemological positions, namely, the naturalists and antinaturalists (Johannessen & Olaisen, 2005, 2006), and synthesize these explanations into new knowledge. Systemic thinking emphasizes circular causal processes, also called interactive causal processes, in addition to linear causal processes (Johannessen, 1996, 1997). Systemic thinking argues that to understand objective social facts, one must examine the subjective aspects of these. In systemic thinking, objective social facts exist, but they are often more difficult to grasp than facts in the natural world because social facts are often influenced by expectations, emotions, prejudices, ideology, and economic and social interests. “Aspect seeing” is thus a way of approaching these social facts.

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Emergents are central to systemic thinking. A pattern behind the problem or phenomenon is always sought in systemic investigations. Patterns may be revealed by studying the underlying processes that constitute a phenomenon or problem, and the search for pattern is what scientific research is all about (Bunge, 1996, p. 42). According to systemic thinking it is a misconception to say that the facts are social constructions. The misunderstanding involves confusing our concepts concerning facts and our hypotheses about the facts together with the facts. Our concepts and hypotheses are mental constructs. The facts, however, are not mental constructs. Social need, for instance, is not a social fact; it is a mental construct of, for instance, starvation. Starvation is a social fact. Social need is a mental or social construction. Not being able to read is a social fact. Illiteracy is, however, a social construction. A symbol should symbolize something, just as a concept should delineate something. A hypothesis should explain something or express something about relationships. A conceptual model should say something about the relationships between concepts. A theory should say something about relationships between propositions. Physical or social facts are untouched by all these mental constructions. That one can through constructs change social facts, or that social facts are changed as a social consequence of using constructs, is neither original nor new. The aim of theoretical research, according to the systemic position, is the construction of systems, i.e., theories (Bunge, 1974, p. v). The order in systemic research is thus: theory – analysis – synthesis. In the methodological sphere, the systemic position has its main focus on relationships, both in terms of concrete things, ideas, and knowledge. Consequently, systemic thinking encourages interdisciplinary and multidisciplinary approaches to problems or phenomena.

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The systemic position thus attempts to bridge the gap between methodological individualism and methodological collectivism, which is considered the classic controversy in historical and social sciences. The perceptions that an observer has about social systems will influence his/her actions, regardless of whether the perceptions are true or fallacious. Systemic investigations start, therefore, writes Bunge, from individuals embedded in a society that preexists them and watch how their actions affect society and alter it (Bunge, 1996, p. 241). The study of social systems from a systemic perspective for these reasons always includes the triad: actors – observers – social systems. The observer tries to uncover a system’s composition, environment, and structure. Then the actors’ subjective perception of composition, environment, and structure is examined. In other words, both the subjective and objective aspects are studied. When we wish to study changes in social systems, from a systemic point of view, we have to examine the social mechanisms (drivers) that influence changes; both internal and external social mechanisms must be identified. This study takes place within the four subsystems: the economic, political, cultural, and relational. According to systemic thinking, social changes occur along seven axes: 1. As an expectation of new relationships, values, power constellations, technologies, and distribution of material resources. 2. As a result of our beliefs (mental models) about relationships, values, power constellations, technical, and material resources. 3. As a result of psychological elements, such as: irritation, crisis, discomfort, unsatisfactory life, unworthy life, loss of well-being, etc. 4. As a result of communication in and between systems.

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5. As a result of an understanding of connections (contextual understanding). 6. As a result of learning and new self-knowledge. 7. As a result of new ideas and ways of thinking. Historiography, from a systemic perspective, has one clear goal: to investigate what happened, where it happened, when it happened, how it happened, why it happened, and with what results. Systemic assumptions related to historiography and social sciences may be expressed in the following (Bunge, 1998, p. 263): a. b. c. d.

The past has existed. Parts of the past can be known. Every uncovering of the past will be incomplete. New data, techniques, and systemizations and structuring will reveal new aspects of the past. e. Historical knowledge is developed through new data, discoveries, hypotheses, and approaches.

In systemic thinking if changes are to take place, then the material will sometimes be given precedence; at other times, ideology, ideas, and thinking are given precedence. In other contexts, there is a systemic link between the material and ideas that is needed to bring about changes. In such contexts, it is difficult and irrelevant to say what is the primary driver, i.e., the material or ideas; this would be on par with discussing what came first, the chicken or the egg. The processes that drive social change, according to a systemic perspective, are the interaction between the economic, political, relational, and cultural subsystems. In some situations, one of these four perspectives will prevail, whereas in others it will be one or more of the four subsystems that are the drivers of social change. In many cases, it is precisely the interaction between the four subsystems that leads to social changes.

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In this context the systemic perspective may be described by saying that material conditions/energy, such as economic relationships, may provide the ground from which ideologies develop, but that these ideologies in return influence the development of the material. Whether material conditions/ energy or ideology comes first is often determined by a historiographical punctuation process (Bateson, 1972, p. 163). The systemic perspective balances historical materialism and historical idealism. It assumes that overall social changes are the result of economic, political, social, and cultural factors, in addition to the interaction between material conditions/energy and ideas. Furthermore, a systemic perspective views any society as being interwoven into its surroundings (Bunge, 1998, p. 275). The systemic position attempts to view the relevant event in a larger context, in order to find the patterns which combine (Bateson, 1972, pp. 273–274), because change depends upon feedback loop (Bateson, 1972, p. 274). Bunge says about this position: By placing the particular in a sequence, adopting a broad perspective the systemist overcomes the idiographic/ nomothetic duality…as well as the concomitant narrative/ structural opposition (Bunge, 1998, p. 275). This means, metaphorically, that the systemic researcher uses a microscope, telescope, and a helicopter to investigate patterns over time. Systemic research strategy is a zig-zagging between the micro-, meso-, and macrolevels (Bunge, 1998, p. 277). Through a systemic research strategy the researcher has ample opportunities to use a Boudon–Coleman diagram. Systemic thinking examines four types of changes.24

24 The four types of changes are related to Bateson’s (1972, pp. 279–309) work on different types of learning, especially those discussed in his chapter Logical types of learning and communication.

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Type I change concerns individuals who change history, such as Genghis Khan, Hitler, Stalin, Mao Zedong, etc. Type II change concerns groups of people acting together who change history. Examples of type II change include the invasion of the Roman Empire by peoples from the north; and the Ottoman expansion into the Balkans between the late 1400s and when the Ottoman Empire was pushed back partly due to nationalist liberation movements in the early 1900s. Type III change includes changes in history that are caused by natural disasters, such as the volcanic eruption that destroyed Pompeii. Climate change may also be said to an example of a type III change. Type IV change involves a total change in the way of thinking, such as the emergence of new religions, like Islam, or a new political ideology, such as Marxism. The systemic researcher attempts to explore the relationship between the four types of changes. A single event is in itself not necessarily of special interest to the systemic researcher; rather, the focus is on the system of events of which the single event is a part. All the social sciences are used in the systemic position to seek insight and understanding and to explain a phenomenon or problem. Tacit knowledge. Knowledge that is difficult to communicate to others as information. It is also very difficult, if at all possible, to digitize. Tacit knowledge25 is a form of skill, ability, or “techne,” i.e., know how, which is difficult to communicate to others as information, but it may be expressible in metaphor. Drucker (1993, p. 24) says about tacit knowledge: “the only way to learn techne was through apprenticeship and experience.” Polanyi (1962, p. 54) says that this sort of knowledge also can 25 Framed by Polanyi (1962).

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be regarded as connoisseurship, and his example is the good wine taster. Tacit knowledge is learned by using and doing. It could be shared by “brainstorming camps,” using metaphors and analogies, in the education system and in the business world. This is done at Honda where they “set up brainstorming camps, informal meetings for detailed discussions to solve difficult problems in development project” (Nonaka & Takeuchi, 1995, p. 63). Keep in mind, however, that these meetings are focused upon tacit knowledge, not the brainstorming we usually are involved in, focusing upon explicit knowledge. The knowledge-based perspective. The knowledge-based perspective is defined here as creating, expanding, and modifying internal and external competencies to promote what the organization is designed to do (Grant, 2003, p. 203). The resource-based perspective. This perspective can be defined as the structuring and systematization of the organization’s internal resources so it is difficult for competitors to copy them. Theory. Here understood as a system of propositions (Bunge, 1974, p. v).

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INDEX Absorptive, 23 Analysis, 23, 61, 128 Assumption, 4, 6, 65, 125, 140 Austrian economics, 23 Autopoiesis, 47, 49, 50, 52, 56 Boudon-Coleman diagram, 118–119, 135, 141 Bunge, 118, 119, 134, 139, 141 Business cluster development, 14 establishment, 12 factors, 12 hidden knowledge, 65 metaknowledge and explicit knowledge, 64 Capabilities competitive advantage, 46 core competence, 78 dynamic capabilities, 1, 21, 119, 121 innovation capability, 25

organizational capabilities, 22, 119 Circular causal processes, 137 Cognitive infrastructure, 28 maps, 24, 49 opening, 52, 69 time lag, 105 Communication, 27, 51, 54, 108, 128, 139 Company competitive position, 47, 48, 95, 130 core competencies, 22 innovation processes, 23 internal knowledge, 19 norms and values, 48 product innovations, 68, 69 purpose, 79, 80 vision, 17 Competence core competence, 22 description, 19 general competence, 20 strategic competence development, 78–84

145

146

sustainable competitive advantages, 76–78 Competitive advantage, 2, 46–47, 76–78, 108 Complexity, 1, 23, 75, 88 Concept autopoietic closure, 51 Bourdieu’s concepts, 55 dynamic contextual training, 89 efficiency-based approach, 20 future perfect thinking, 17 situated learning, 7 social mechanisms, 34 Connection, 10, 22, 45, 95, 134 Consciousness, 118 Continuous innovation, 46, 60, 67, 69 Core competence company’s core competence, 83 definition, 21 dynamic core competence, 24, 25 Culture/cultural, 6, 22, 51, 123, 135, 139 Density, 13 Distinction, 10, 50, 56, 107, 115, 136 Educational, 65, 86, 133 Embedded, 4, 15, 22, 78, 86, 139 Emergent, 114, 122, 124, 125, 138

Index

Equilibrium, 46, 76 Evolutionary, 10, 24, 51, 52, 121 Expansionistic, 142 Explanation, 31, 84, 103, 126, 133, 137 Explicit expectations, 123 feed-forward, 123 hidden knowledge, 65, 133 tacit, 5, 62, 86 Explicit knowledge competitive advantages, 21 conventional classroom instruction, 87 objective and intersubjective, 63, 122 open market, 77 Exploration, 88, 89, 91 External information, 30, 32 External knowledge, 3, 25–30, 90, 91 Feedback loops, 98, 114, 141 Feed-forward, 123 Frameworks, 6, 49, 62, 118, 130 Function investments, 10 isolating mechanism, 22 organization, 107 principles, 107

Index

Hidden knowledge, 63–64, 116, 125, 130 Idiosyncratic, 86 Industrialization, 113 Industrial organization (IO) theory, 1, 76, 88 Information acquiring information, 98 availability, 6 communication systems, 27, 32 explicit knowledge, 63 input overload, 127–128 selection processes, 53 Information acquisition, 98 Innovation classification, 67 clusters, 8–15 continuous innovations, 69 creating new knowledge, 59–66 development, 9, 32 discontinuous innovations, 121 economic growth, 45 Hamel’s law, 125 knowledge, 3–8, 15–19 organizational innovation, 67–68 radical innovations, 67, 69, 117 Instrumental, 14, 52, 75, 85, 108, 114 Knowledge definition, 129 enterprise, 129–130

147

external knowledge, 25–30 hidden knowledge, 63, 116, 125, 130 implicit knowledge, 127 innovation, 3–8, 15–19 internal knowledge, 19–25 internal training, 75–91 management, 8–15, 45–70 metaknowledge, 62, 130–131 organizational learning, 15–19, 95–110, 131–132 perspective, 143 relationship knowledge, 64, 65, 132–133 systemic learning, 115 tacit knowledge, 4, 23, 60, 63, 142–143 Knowledge creation, 4, 17, 48, 61, 62, 116 Learning collective learning, 15, 20 conceptual model, 3 “contextual learning” concepts, 7 dynamic perspective, 16, 132 environment, 18, 23 “highly effective learning systems”, 15, 60 “implicit learning” concepts, 7

148

individual learning, 15 innovation, 15–19 interactive learning process, 26, 59 knowledge-based economy, 108 model element, 19 organization, 15–19, 61–62, 95–110, 131–132 “situated learning” concepts, 7 systemic learning, 115 tacit knowledge, 90 work-based learning, 88 Linear thinking, 9, 10, 28 Management funfair management, 101, 102 HR management, 126–127 knowledge. See Knowledge philosophy, 84, 95, 96 scientific management, 95, 96 strategic HR management, 136 Management science, 95, 96 Mechanistic thinking, 98 Metaphor, 102–104, 113, 141, 142 Methodology, 76, 79, 118 Model conceptual model, 3, 8, 138

Index

cooperation model, 9 integrated model, 68 interactive model, 9, 10 linear model, 9 mental model, 16, 19, 32, 63, 105, 125 model monopoly, 58 networking model, 66 new organizational models, 31 research model, 127 Motivation Asplund’s motivation theory, 117–118, 131 decision-making process, 96, 102, 123 employees, 85 internal motivation, 97–100 motivational structure, 108 organizational learning, 96 self-organization, 108 National innovation systems, 28 Neoclassical, 8, 76 Normative elements, 52 metaknowledge, 62 normative closedness, 59, 60, 69 open system, 49, 51, 70 selection processes, 53 superstructure, 50, 52, 54, 55, 56, 57

Index

system-specific normative basis, 50, 52, 53, 54, 56, 57 Observation, 50, 113, 121 OECD, 124, 129 Organizational learning, 131–132 course tools and methods, 114 definition, 16, 17 innovation, 15–19 internal knowledge, 19–25 knowledge management, 95–110 knowledge, 15–19 model element processes, 19 participation, 61 social mechanisms, 19 Organization ambidextrous organizations, 89, 117 capabilities, 119 dynamic capability approach, 1, 21 function-oriented organizations, 115 industrial organization theory, 76 innovation, 15–19, 59–66 knowledge, 15–19 knowledge creation, 4, 17, 28, 61

149

knowledge management, 95–110 knowledge processes, 7, 120 organizational innovation, 6, 67–68 organizational routines, 4, 15, 24, 78 social systems, 2, 8, 120, 135 tacit knowledge. See Tacit knowledge value creation, 120, 123, 126 Patterns action patterns, 105, 115, 116 cultural patterns, 123 five patterns, 123 normative superstructure, 54, 56 scientific research, 138 systemic position attempts, 141 system-specific normative basis, 54 Perception, 4, 120, 139 Performance, 1, 21, 60, 61, 117, 123 Phenomenon Bunge’s Boudon–Coleman diagram, 119 developing models, 114 explicit knowledge, 4, 63 systemic thinking, 28, 31

150

Problem company-related problems, 34 coordination problem, 107 integration, 108 military metaphor, 103 paradox, 50 phenomenon, 114 problem-solving strategies, 129 research problem, 132 social problems, 55 social sciences, 137 systemic thinking, 137 Processes action, 98, 99 causal process, 137 competitive process, 46 decision-making process, 96, 101, 102 global levels, 124 ideas, 128 information processes, 13 innovation process, 67, 127 knowledge processes, 120 long-term learning process, 90 mental process, 113 model element, 19, 25, 30 organizational learning. See Organizational learning

Index

organizational levels, 124 planning, 98, 99 production process, 131 reflection, 53, 62, 130 selection process, 53 sequential process, 9 social levels, 49 social process, 134 social systems, 19 work process, 131 Reality, 100, 104, 122 Receptivity, 23 Reductionistic, 1, 12, 14, 119 Relationships cohesive energy, 120 knowledge, 64, 65, 132–133 pattern, 31 systems of, 58 Resources, 24, 46–47, 77, 130, 135 Routines, 4, 15–16, 24, 25, 34, 78 Scientific management, 95, 96 Social mechanisms, 134–135 Bunge’s Boudon–Coleman diagram, 119 cocreation, 120 cohesive energy, 120 companies, 109 concept, 2

Index

elements, 97 function-oriented organizations, 115 material resources, 135 organizational learning, 19 preferences, 134 social science, 34 social systems, 8 synthesis, 3 Social science, 2, 34, 137, 139, 142 Social systems, 133–135 cohesive energy, 120 communication, 50–51 external knowledge, 25–30 innovation, 3–8 motivational structure, 108 problems, 2 process, 19 self-observation, 50 social laws, 133 systemic thinking, 55 Strategics competence development, 78–84 competitive strategies, 10 mixed strategy, 119 problem-solving strategies, 129 strategic HR management, 136 strategic resource, 75 systemic research strategy, 141

151

Structures belief structures, 49 cost structure, 13 infostructure, 128 metaphors, 102 motivational structure, 108 norms, 49 organizations structure, 96 profound structure, 114 semifeudal structures, 118 tacit knowledge, 91 Structuring, 4, 62, 87, 129, 130 Superstructures, 54, 55, 56, 55–59 Sustainable, 3, 76–78, 85, 86 Sustainable competitive advantage, 2, 76–78, 85–86 Synthesis, 3, 32, 61, 115, 138 System autopoietic social system, 49 behavior, 119 cohesive energy, 120 communication systems, 27, 32 composition, 139 definition, 2 education system, 64, 131, 143 events, 142 external knowledge, 8

152

highly effective learning systems, 15 idea generation, 107 relationship, 100–106 social mechanisms, 19, 34 social systems, 2, 8, 51–52, 135 system identity, 54 system-specific normative basis, 50, 51, 53–57 Systemic assumptions, 140 integration, 66 investigations, 138, 139 knowledge, 61 perspective, 135, 139, 140, 141 position, 138, 139, 141, 142 reasoning, 135 research, 138, 141, 142 social systems, 2 Systemic thinking, 2, 28, 55, 97, 114, 136–143 Systems of innovation, 29 Tacit. 47. See also Tacit knowledge Tacit knowledge, definition, 4, 142–143 organizational learning, 7 explicit, 5, 47, 62, 86, 91

Index

companies, 61 invisible assets, 47 Technology competencies, 27 diffusion, 9 material resources, 135 organizational innovation, 67–68 phenomenon, 4, 123 self-organization, 96 Theory Asplund’s motivation theory, 117–118 autopoiesis theory, 49, 50, 52 cluster theory, 10, 11, 12 definition, 138, 143 diamond theory, 4 industrial organization theory, 76 knowledge-based theory, 4 neoclassical microeconomic theory, 76 North’s action theory, 131 organizational knowledge, 4 Polanyi’s theory, 23, 77 Training, 5, 75–91, 61 Trigger, 2, 19, 24–27, 106, 131 Trust, 15, 102 Turbulence, 1, 23, 64, 75, 101, 132

Index

Understanding cluster, 11 contextual understanding, 130

153

metaphor, 103 tacit knowledge, 5 technology, 4, 123

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