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Journal of Intellectual Capital

An Intellectual Capital based differentiation theory of innovation practice.

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Manuscript ID: Manuscript Type: Keywords:

JIC-02-2013-0024.R2 Research Paper Intellectual capital, Innovation, grand theory, differentiation theory, practice

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An Intellectual Capital based differentiation theory of innovation practice. Purpose: This paper responds to calls to research recognising impediments to innovation practice. The paper argues that decision-making preferences by risk averse managers are a key impediment to the organisational support required for the commercialisation of new ideas, by exploring the relationship between forms of intellectual capital and innovation. As a result, categories are derived that contrast with the current grand theory that IC drives innovative practices. Design/Methodology/Approach: The research critically examines cross-sectional empirical data gathered through semi-structured interviews with 27 Australian executive managers from leading Australian companies and the public sector. These interviews elicited narratives about successful and unsuccessful innovations where interviewees had significant involvement in the outcome. 54 narratives of innovation from executive managers – 27 successes and 27 failures, were analysed using the repertory grid technique to unearth patterns about the process of innovation, especially in relation to the stability of the business environment and the need for innovation.

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Findings: This research finds that successful innovation in a context identified as demonstrating risk averse decision-making behaviours requires different management approaches, depending on whether the innovation is radical, evolutionary or incremental. The study discovers twelve different factors contributing to innovation processes and identifies those that are more likely to contribute to the success of innovative endeavours. From this the current grand theory that IC drives innovative practices is challenged by developing an IC based differentiation theory of innovation practice.

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Originality/Value: The paper is novel because it addresses the interaction and complexities of the different factors that enable successful innovation and possibly contribute to innovation failures, and the types of innovation relevant to each context. This approach is in contrast to the contemporary innovation literature, which tends to focus on successful radical innovation. As a result, the paper offers a more holistic view of the diverse and interrelated factors that impact innovation success and/or failure.

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Limitations: As always, the observations and conclusions reached are limited to the 27 interviews and the Australian context. Further, findings are based on the authors’ objective analysis. As with any qualitative study the authors also caution about generalising the findings, and as with any theory it should be used to develop insights into actions, rather than prescribing them.

Implications: For educators it highlights the need to teach students to critique innovation rather than accepting that all innovation is beneficial. For researchers it shows they must avoid success bias by investigating both successful and failed innovations, developing 1


differentiation theories of innovation practice. The findings highlight how senior managers responsible for enabling and resourcing innovation need to develop skills for identifying the innovation type enabled, matching it to an appropriate strategic approach. Finally, for policy makers it shows how different forms of successful innovation require different approaches, and each can be encouraged, developed and enabled differently. Keywords:

Intellectual Capital, innovation, grand theory, differentiation theory, practice.

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An Intellectual Capital based differentiation theory of innovation practice.

Introduction The purpose of this paper is to develop an understanding of behavioural influences on current innovation practice and their association with Intellectual Capital (IC). Thus the aim of the study is to address the question, “What categories of IC contribute to successful and or unsuccessful innovations to managers’ perceptions of the process of innovation and how do these factors contribute”? Based on field studies in which these behavioural influences are present, the research explores the relationship between intellectual capital and innovation and develop categories that contrast with the current grand theory (Dumay, 2012) that IC drives innovative practices (e.g. Humphreys et al., 2010) to develop an IC based differentiation theory (see Llewelyn, 2003) of innovation practice.

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Developing a differentiation theory of innovation practice is novel because most contemporary studies focus on either radical or incremental innovations, while this study seeks to understand the enabling conditions for innovation from the perspective of all three types of innovation, being radical, evolutionary and incremental. To do so the research critically examines cross-sectional empirical data gathered through semi-structured interviews (Qu and Dumay, 2011) with 27 Australian executives from leading Australian companies and the public sector. These interviews elicit narratives about successful and unsuccessful innovations where interviewees had significant involvement in the outcome. The narratives of innovation are analysed using the repertory grid technique (Fransella and Bannister, 2004) to unearth patterns about the process of innovation, especially in relation to the stability of the business environment and the need for innovation

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The paper contributes to the IC and innovation management literature by examining the link between IC and innovation, and the conditions associated with innovation success and failure and not just successful innovations (see Sveiby et al., 2009), by providing insights into the factors promoting innovation and those hampering innovation. Developing these insights opens the potential for identifying how educators, researchers, practitioners and policy makers can critique the success bias associated with innovation (Sveiby et al., 2012), identify the type of innovation being developed, link innovation to strategy and enable conditions to promote a greater likelihood that future innovations will be successful.

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Literature review: Linking IC and innovation Innovation is a multifaceted expression used at strategic and operational levels of business, encompassing business processes, products and services, competitor intelligence, business policy, policy formulation, and understanding customers. As innovation is power and value laden, it also encompasses a variety of research perspectives informed by theories in economics, sociology and psychology. In particular, this review identifies the grand theory linking innovation with Intellectual Capital (IC), which implies the relationship is overwhelmingly positive. Since the first stages of developing IC as a management 3


technology, innovation has been identified “as the principal determinant of competitiveness” (Petty and Guthrie, 2000, p. 157). However, research has also shown that the outcomes derived from innovative processes are difficult to predict (Tidd, 2001). Furthermore, the measurement of inputs and outputs is challenging and dependent on the business environment in which the company operates (Tidd, 2001). This is at least partly due to the difficulty in establishing a relationship between measures of innovation and firm performance (Tidd, 2001, p. 169) “because innovation management best practice is contingent on a range of factors”. An initial review of the practice literature on innovation identifies a gap between managers’ perceptions of innovation and awareness of the criteria required for successful innovation (Cooper and Kleinschmidt, 1993, p. 74).

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A review of early practitioner implementations of IC practice identified innovation as being central to justifying investment in measuring, managing and reporting IC. For example, innovation capital is featured in the original Skandia navigator and is defined as the “Renewal strength in a company, expressed as protected commercial rights, intellectual property, and other intangible assets and values” (Skandia, 1995, p. 22). The link between IC and innovation gained more prominence after Skandia entitled their subsequent report Power of Innovation and declared “Innovation is now understood as the driving force behind increases in wealth” (Skandia, 1996, p. 3).

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The link between IC and innovation also spread to policy makers interested in promoting innovation in national economies as a source of growth and economic prosperity. As outlined in the Meritum Project (2002, p. 59): ... the disclosure of a greater amount of reliable information on the firm’s intangible investments may help overcome the problems currently affecting the validity of the results of innovation studies. For it will facilitate the design and implementation of public policies aimed at increasing economic growth and social welfare by promoting innovation.

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Over time, the policy making chorus progressed to lauding the power of IC to promote innovation through the refinement of internal company processes. This is exemplified in the Danish IC guidelines, developed with the support of the Danish Ministry of Science, Technology and Innovation (Mouritsen et al., 2003, p. 11): Processes relate to the knowledge content embedded in the company’s stable procedures and routines. These can be the company’s innovation processes and quality procedures, management and control processes and mechanisms for handling information. Since this time there have also been several other IC initiatives linking the development of IC to innovation. A prime example is the European Commission (EC) sponsored RICARDIS1 report, whereby the authors advocate that (EC, 2006, p. 10): 1

An acronym for “Reporting Intellectual Capital to Augment Research, Development and Innovation in SMEs”.

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Intellectual Capital is a key element in an organisation’s future earning potential. Theoretical and empirical studies show that it is the unique combination of the different elements of Intellectual Capital and tangible investments that determines an enterprise’s competitive advantage. R&D and innovation can be regarded as one element of Intellectual Capital. However, research intensive enterprises invest not only in R&D and innovation, but also in other forms of Intellectual Capital. Empirical studies provide evidence for the tight link and contingency between investments in R&D, Innovation, Human Resources and Relational Capital. A more contemporary example can be found in another EC sponsored project, InCAS (Intellectual Capital Statement: Made in Europe). In line with the RICARDIS rhetoric, the authors advocate the link between IC, innovation and competitive advantage (Humphreys et al., 2010, p. 4): As a result of constant changes caused by globalisation, emerging technologies and shorter product life-cycles, knowledge and innovation have already become the main competitive advantages of many companies.

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Intellectual Capital (IC) forms the basis for high quality products and services as well as for organisational innovations. So far, conventional management instruments and balance sheets do not cover the systematic management of IC.

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As can be seen by the evolution of these IC statement guidelines, policy makers still seek to convince themselves and others of the need to develop IC by promoting the grand theory that IC is necessary for innovation (Llewelyn, 2003; Dumay, 2012). However, it seems that policy makers have yet to achieve this end, despite continuing exhortations for organisations to develop IC in order to promote innovation that will lead to competitive advantage. Unfortunately, this seems to be based on industrial-age strategic thinking (e.g. Porter, 1980), “creating economic value through competitive positioning …, rather than knowledge-age strategic thinking which advocates knowledge sharing and collaboration as keys to value creation” (Dumay, 2013, p. 8).

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A similar progression of calls linking IC to innovation can be found in the IC literature. For example, a search of all articles published in the Journal of Intellectual Capital (JIC) up until the end of 2012 shows 26 articles that use the keyword innovation to attract readers. Here researchers focus on linking IC, knowledge management and innovation from an ostensive perspective (Mouritsen, 2006), along with continued efforts to justify these links empirically (de Castro and Sáez, 2008; Delgado-Verde et al., 2011). Researchers continue to seek evidence to prove the grand theory that IC is linked to innovation. The problem with any grand theory is that it is difficult, if not impossible, to prove empirically because they represent “meta-narratives ... formulated at a high-level of generality and reflect ideas that have been arrived at by thinking through the issues and relationships in an abstract way – rather than being derived from empirical research” (Llewelyn, 2003, p. 676). As such a research gap is based on, Llewelyn’s (2003, p. 672) argument that more “differentiation theories” of practice are needed, therefore researchers 5


need to establish the “meaning and significance” about innovation “through setting up contrasts and categories”. For example, the gap can be evidenced in the many studies that attempt to demonstrate the grand theory, as most presume that developing IC and innovation is beneficial. This is almost never questioned. For example, Delgado-Verde et al. (2011, p. 5) claim that “Organizational knowledge assets are key organizational factors responsible for firm innovation, as well as effective management” and declare afterwards that “The main contribution of the empirical findings of this research is precisely providing evidence that supports that organizational capital is one of the main sources for firm innovation” (Delgado-Verde et al., 2011, p. 14). However, there is a need to critique and contrast the manner in which the Delgado-Verde et al. (2011) and similar studies are conducted. In the case of Delgado-Verde et al. (2011, p. 10) their data emanates from “a set of firms where the intangible resources represent an important determinant of business competitiveness” being medium and high technology manufacturing firms. This, in our view, is a skewed sample. For example, when asking respondents whether “In the last three years, the number of product innovations developed by my company is higher than my competitors” it is not surprising the overwhelming response is “yes”.

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Three reasons are proffered as to why the “yes” answer must be queried. First, it can be argued that few respondents working in these high-technology firms would deny they are innovative or are not beating their competition. Surely, when sampling so many firms in the same industries each firm cannot be more innovative than all their competitors. If a true assessment were made each firm would be placed somewhere on a continuum from having achieved the most to least number of innovations.

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Second, it is questionable whether the employees interviewed would have privileged and reliable access to this type of information. How would they know the “number of product innovations” competitors have developed? It is thus suggested that only individual competitor firms would know this confidential information. Similarly, is there a highly accurate product innovation scorecard developed by each and every one of these firms, based on the confidential information of competitors, which is regularly updated and disseminated to all employees? It is highly doubtful, given the paucity of internal or external IC reporting being conducted by companies in general (Dumay, 2009a, p. 491).

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Third, the “yes” question assumes that all product innovation is good and that all innovations are successful. Therefore, it is naive to think that innovation does not also have its undesirable impacts and failures. For example, Apple, often lauded as a highly successful and innovative firm has its share of failures, such as Newton PDAs, PiPPiN game consoles and Macintosh TVs. These failures have cost Apple millions of dollars in R&D resources (Gardiner, 2008). Witness also the recent replacement of Google maps with Apple’s own maps, a product innovation gone wrong, causing CEO Tim Cook, to issue a public apology.2 2

See http://www.apple.com/au/letter-from-tim-cook-on-maps/

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Thus, for every successful product innovation there are likely to be several failed innovations. This view is also supported by Sveiby (2012) in his critique of the radical financial product innovation3 of securitisation, which was seen by many as one cause of the recent global financial crisis. Sveiby (2012, p. 114) contends “that practically all innovations also have less beneficial consequences, which often are systemic in nature, and this reduces the net value for users and at least some members of society”. This critique of the innovation paradigm by Sveiby (2012, p. 115) outlines another gap in innovation research based aligned with a theory of managerial incompetence associated with failed innovations as detailed in Figure 1. [Insert Figure 1 here]

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The basis of Sveiby’s theory is that when a radical innovation takes place, it changes the professional context where managers (actors) make informed decisions and predictions about the future. When a radical innovation occurs, actors can become incompetent and unable to reliably predict the future. The rationale is that in unfamiliar contexts, actors become temporarily incompetent leading to prediction errors. This, in turn, can lead to innovation failure as an unintended consequence.

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Academics also seem to fall for what is seen as a success bias trap. As Sveiby et al. (2009, p. 2) outline, less than 1 in 1000 articles written about innovation discuss the undesirable consequences of innovation, even though “innovation is one of the most commonly mentioned concepts in social science”. Furthermore the authors’ own review of the literature also found evidence to suggest that the majority of articles tend to focus on radical innovation rather than incremental innovation that has been driving economic growth in many countries (see ADIBlumentritt, 2005; Koch and Strotmann, 2008; 2011, p. 1).

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As a consequence of the gaps outlined above, the primary research question is “What categories of IC contribute to managers’ perceptions of successful or unsuccessful innovation processes and how does this contribute to the grand theory linking IC as an enabler of innovation?” To do so exploratory research is presented, examining both failed and successful innovations to allow development of categories to help understand innovation in practice. The findings are then contrasted with the grand theory advocating IC as an enabler of innovation.

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Research context and method Our research involved gathering structured innovation narratives (Bartel and Garud, 2009) via semi-structured interviews with 27 Australian Executive Managers and Chief Executive Officers (EMCs) across a range of industry sectors selected from the top 300 Australian 3

In the literature the terms radical and revolutionary innovation can be used interchangeably or at times to denote different forms of innovation. For simplicity we adopt the term radical innovation to denote the most extreme innovative processes, products and services.

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Stock Exchange (ASX) listed corporations and major Government Departments. The interviews were designed to link EMC perceptions of innovation with their business circumstances. Focus was on understanding this context and how they approached innovation processes. The interviews collected two forms of data. •

Demographic background; including industry, range of experience, risk appetite and views on resource allocation for innovation.

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Narratives about innovation in practice from the EMCs’ professional experience – one of a successful innovation, one of an unsuccessful one. The selection of which narratives to tell was left to the EMC, however, they must have been personally involved in the innovation and the narrative should involve multiple people. Where EMCs were uncertain about which narrative to disclose they were encouraged to choose experiences that had led them to question their thinking in relation to innovation.

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To ensure against selecting a biased sample of knowledge intensive industries as is common with many innovation studies, the researchers interviewed EMCs from a wide variety of industries including the public sector as summarised in Figure 2. [Insert Figure 2 here]

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Interviews normally took approximately 1 hour to complete, though in some cases went considerably longer. In all the researchers collected 54 innovation narratives from EMCs – 27 of success and 27 of failure. During the interviews the researchers also utilised a technique called the repertory grid. Repertory grid (Fransella and Bannister, 2004) is a psychometric interviewing technique requiring the interviewee to distinguish the difference between two ‘elements’ in narrative form, in this case people identified in EMCs’ innovation narratives. The points of difference identified represent dimensions against which the interviewee construes the topic of the interview – in this case innovation. Developed as a technique to support empirical investigation of Personal Construct Psychology (Kelly, 1955), it is a demonstrably effective interviewing method for the elicitation of meanings.

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Repertory grids are applicable to a wide range of contexts where understanding individuals' patterns of construal is necessary. This was advantageous to the research, as the researchers sought to establish categorisations of innovation practice, rather than rely on a preset list of categories derived from the positively biased innovation literature. The method is particularly adept at uncovering the hidden meanings and points of view that interviewees may not disclose in a semi-structured interview (Qu and Dumay, 2011, pp. 251-2). It is fundamentally different to survey based approaches used to explore innovation, in that the vast majority of the data comes from the EMCs without specific questioning thus eliminating interviewer biases from impacting interviewee’s responses. For this reason the researchers specifically excluded any mention of IC to ensure interviewees did not give us answers they thought the researchers were looking for.

The analytical model 8

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A key issue is the term innovation and what does it mean? This paper adopts the definition according to the Oslo Manual issued by the OECD and Eurostat (2005, p. 46) being “Innovation is the implementation of a new or significantly improved product (good or service), process, new marketing method or a new organisational method in business practices, workplace organisation or external relations”. Seen in this light, innovation is a general concept that, in an organisational sense, encompasses all levels of product or service improvement (van de Ven, 1986; Damanpour, 1996). In the management literature a distinction is usually made between two categories of innovation namely, radical and incremental (Green et al., 1995, p. 203). In broad terms, radical innovation represents a significant departure from the previous business model of the organisation, may have a disruptive impact on the industry involved, and for the customer represents a fundamentally different opportunity or experience. Here organisations are dealing with high levels of uncertainty and risk (Mcdermott and Handfield, 2000).

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Radical innovation relates to the classical notion of Schumpeterian innovation (Schumpeter, 1934), in that managers recognise that what is developed represents a discontinuity or disruption of what was before (Dosi, 1982, p. 147). Radical innovation is associated with breakthrough ideas (Gundling, 2000; O'Connor and Rice, 2001) and with the development of new business or product lines based on new ideas or technologies or substantial cost reductions that transform the economics of a business (Leifer et al., 2000). If management is looking for growth levels significantly larger than industry growth then discontinuous or radical innovation needs to be seriously considered by decision makers (Bessant et al., 2004). Mcdermott and Handfield (2000) agree by arguing that in order to achieve long term growth, firms need either novel replacements, new to the market products, or product breakthroughs. Radical innovation is high-risk and high-return, and does not respond well to the management practices applied to incremental innovation activities.

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Incremental innovation, on the other hand, represents an improvement to current business models not involving significant change. It often involves fixing problems with current operations rather than creating new operations. There is a high level of certainty about the internal and external business environments. Incremental innovation is a gradual change and improvement, product and processes are modified starting from what there was before (McGuigan and Henderson, 2005, p. 199). Firms that focus only on incremental innovation are avoiding risk, but potentially missing opportunities. However, minor day-to-day incremental improvements can bring competitive advantage, guaranteeing a continuous movement of the cost/performance frontier (Tidd, 2001).

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The development of this literature can arguably be described in terms of three phases. First, for almost 30 years before 1995, innovation is characterised as either radical or incremental. Authors have tended to address one or the other form of innovation, the main assumption being that management chooses which form of innovation to pursue and the strategy to adopt it (Green et al., 1995, p. 203). Second, in the 1990s there is an increase in awareness that the 9


challenge for managers is creating organisations capable of simultaneously pursuing incremental and discontinuous innovation (Tushman and O'Reilly, 1996) with the focus being largely about strategy. Finally, in the past decade, authors have focused on technological and market contingencies where the main object is defining the context. This paper’s contribution is at this phase; while most authors focus only on one of the factors that might enhance innovation; this research considers a broader view of the diverse and interrelated factors that impact both innovation success and failure. In response, a third intermediate innovation category, evolutionary innovation, is added in order to address the aims of this paper. Evolutionary innovation is typically an expansion of, or significant change to, current products and services, vertical integration, an expansion of core competencies or exploring a significantly new market (see Pascale, 1984; Kay and Goldspink, 2013). Projects or innovations of this type usually require a top-down impetus for their initiation and sponsorship. Senior management may be dealing with moderately high levels of uncertainty in either the external environment or within the organisation but usually not both. In contrast to radical innovations, evolutionary innovation does not “re-write the rules of the competitive game, creating a new value proposition” and is more than “continuous movement in the cost/performance frontier” (Tidd et al., 2005).

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To help understand the relationship between IC and these innovation categories, consistent with prior management research, innovation is categorised as a knowledge management practice (see Madhavan and Grover, 1998). In this sense, human, structural and relational capital are theorised to reinforce and transform the knowledge existing in an organisation as mediating forces. Table 1 summarises these key relationships.

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The relationship is based on an identified gap between managers’ perceptions of innovation and awareness of criteria required for implementing successful innovation processes (Cooper and Kleinschmidt, 1993, p. 74). The difficulty in establishing a relationship between measures of innovation and organisational performance is an example of this gap as innovation is often perceived as unpredictable and the measurement of its inputs and outputs is challenging (Tidd, 2001, p. 169). Hence, successful innovation often depends on understanding the business environment in which the company operates. However, the management literature provides support for the notion that there is no one best way to manage innovation and that managing innovation should take a contingency approach based on a range of factors (Tidd, 2001, p. 173).

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From this literature, two main contingencies influence innovation practice: uncertainty and complexity. Uncertainty and complexity need to be differentiated; as they appear to have different management requirements (Hobday et al., 2000; Hobday et al., 2005). Uncertainty is a function of the rate of change of technologies and product-markets, whereas complexity is a function of technological and organisational interdependencies. Tidd (2001, p. 176) 10

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represents the two dimensions in the matrix presented in Figure 3, where he highlights the relationships between environmental contingencies, organisation configurations and performance.

[Insert Figure 3 here]

The quadrants each bring different problematic and features, however, from an examination of the strategic management literature on innovation, what seems to be missing is an understanding of the factors that can activate innovation. An understanding of the distinction between different forms of innovation and their alignment to different levels of organisational uncertainty provides a basis from which innovation performance can be measured, success rates increased, and high performance achieved.

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Because the interviewees are from a wide variety of industries and backgrounds, using industry definitions of innovation to classify the different narratives is not appropriate. To address this issue, the analysis looked for the common contextual factors that played a role in their narratives and influenced their motivations. Thus, based on the discussion above two key dimensions are identified being, the EMC’s level of certainty about both the organisational situation and the environment in which it was operating; and the level of proactivity. Did the EMC respond to a critical issue, or was there no reason to start the innovation?

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Plotting the 54 innovation narratives against these two key dimensions (see Figure 4 below) allows them to be grouped and compared and allows categorising them into three broad forms of innovation based primarily upon the EMC’s level of certainty about their context. Certainty is a critical factor in understanding the way EMCs think about innovation. For them, innovation is about taking a risk, and the central element of that risk is the certainty that the idea will work. Decrease the level of certainty and the risk of failure increases (Sveiby, 2012). It also tends to increase the degree of cooperation.


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As a result of this initial grouping of innovation narratives, the researchers were able to identify distinct characteristics of successful versus unsuccessful innovation when dealing with high uncertainty contexts (Kay and Goldspink, 2013). This is discussed next along with some of the contrasts of contemporary innovation literature and the grand theory linking IC as an enabler of innovation.

IC as an enabler of innovation? The EMC perspective To begin the discussion, it should be noted that some of the EMCs interviewed would disagree with the categorisation of their narratives in Figure 4. Indeed, a number of EMCs 11


described their achievements as radical, yet when considered against the degree of certainty and pro-activity described in their narratives, they could only be classified as incremental. This is consistent with some early management literature where “... an innovation can be revolutionary for one firm but incremental for another” (Linton, 2009, p. 736). Based on the innovation descriptors adopted for the purposes of this study, they were not interpreted by the researchers as representing revolutions for their organisations or industries. Given the results of the grid analysis outlined next, many EMCs are unlikely to survive in the role even if the disruption is resolved. The grid analysis required mapping of individual world views across the innovation decisionmaking chain, enabling an understanding of how these world views collectively contribute to the formulation of innovation frameworks and decision making within the organisation. The narrative analysis, combined with repertory grid data, facilitated observation of interaction between situations, individuals, and their meanings, to gain an understanding of what drives the EMC and the organisation’s approach to innovation and the subsequent categories of behaviour exhibited by the different groups within the sample. By understanding the interaction of micro and macro level behaviours in an organisational context, it is possible to understand better the drivers for decisions to invest in innovation projects, rather than taking a singular macro, meso, or micro focus (see Kay and Goldspink, 2013).

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By analysing the results of the repertory grid and in keeping with answering the research question, Table 2 presents 12 categories or typologies of innovation, which will be later classified according to their link to IC. The analysis involved taking all the different data types collected and looking for recurring patterns of association between them. The categorisation process differentiates between events and situations in ways that were meaningful to interviewees for decision making. This analysis follows the three stage construct elicitation method typical of repertory grid technique namely, triading, laddering and pyramiding (see Fransella and Bannister, 2004) to derive the 12 categories of innovation practice. Each category is defined by an interrelated set of self-organised decision strategies, or rules as an alternative unit of analysis to the divisions of human experience into cognitive, feeling and behaving attributes pervasive in the social sciences. The patterns combine data points including described behaviours, opinions, observations and personal constructs.

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[Insert Table 2 here] For example, the Improving Current Practice category is derived from the bipolar dimension of existing processes can be improved and existing processes cannot be improved. Each of these are then examined in terms of how they are construed by interviewees to determine the range of convenience or context which, for this practice, included elements such as process efficiency (measured in terms of relevant dimensions such as elapsed cycle time, cost and process wait times) and effectiveness (recognised in terms of quality attributes such as appearance and customer acceptance). The third or pyramiding stage focused on how these elements and characteristics were defined. For this practice, it involved identifying the 12

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detailed descriptors of efficiency and effectiveness, including benchmarks and comparators used by interviewees to identify the need to improve current practice. Across all three innovation categories, the percentage influence of the described categories the EMCs considered important for successful innovation can be identified as captured in Figure 5. These categories are the basis for the contrasts of innovation in practice. [Insert Figure 5 here] In aggregate, the roles of EMC personality, organisational culture and process orientation were highlighted and, in turn, focus was largely on improving current practice. A focus on product use and unseen customer need is also seen as important aims for innovation in this world. In contrast, ideas and capabilities were seen as being of less interest, contrasting the resource based view of the firm (RBV) theory which advocates that “strategic choices should flow mainly from the analysis of [...] unique skills and capabilities” (Barney, 1986, p. 1231) .

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For unsuccessful innovation in aggregate, the role of the process, executive personality, partners and chance/probability (given uncertainties associated with the innovation) were perceived as key drivers for attempting the innovation. To understand the implications of these findings, the analysis explored substantive differences in the factors important to different innovation categories. The 12 patterns were analysed further to identify how they influenced the three categories of innovation in different ways as follows.

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Radical Innovation

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Analysis of the narratives meeting the radical innovation classification, three factors emerge, starting with a focus on selecting the ‘right’ partner. Based on the profile highlighted in Figure 7 partner cooperation is more important to radical innovation than EMC personality that, in fact, may even get in the way of this category of innovation. A quote from one EMC responsible for a failed innovation with industry changing implications illustrates the point in relation to attempts to gain buy‐in for his innovation:

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I built the models; I've actually built the [examples] downstairs. I found some suppliers here and overseas that would be able to [produce] a kind of a physical model of the environment. And in fact held a cocktail party down here in early 2007, I think it was, invited all the [stakeholders] in one evening and explained to them what that vision was. As I said [to them] ‘you don’t get this at the moment but I want to describe what we're doing here...’ And managing directors of [stakeholder organisations] here in Australia [were] gobsmacked by the idea. But then what they do… here is dictated by the British, and no‐one in the world was thinking or talking about doing this sort of approach, and they're still not. [Insert Figure 7 here]

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Here the situation was characterised by the EMC’s vision of the future, that none of his key external stakeholders would accept. The story appeared to present the ‘right’ idea or direction for the industry, however, the approach compared to the examples of success would appear to be appropriate for evolutionary, not radical innovation. The EMC himself recognised this: If you Google my name and go and have a look you'll see thousands of articles about my frustration with the lack of innovation in the XYZ industry globally, let alone here in Australia. And my biggest frustration is the fact I haven't been able to successfully sell to anybody else, or certainly the people that count... A noteworthy contrast here is the relative absence of EMC personality and organisational culture as factors in successful radical innovation. These characteristics are highlighted in the right half of Figure 7. Contrast this with a different approach taken in one of the successful radical innovation narratives:

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Yes, well we simultaneously worked with the standards bodies, and understood where standards were heading and what the general views were. So there'd been a huge amount of work going on in the standards arena, which I actually went to, I went to all of the standards meetings. In fact, I became secretary of the ABCD Committee for a term. And what that meant was that we understood first of all when you start doing those standards work, there's a market requirement specification done there with all the industry partners getting involved. And that’s a fairly generic thing.

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The second factor relevant to radical innovation emphasised a portfolio (probability) approach to selecting initiatives that meet use or unseen customer needs. As shown in Figure 7, the focus on use and/or unseen needs is as prevalent for successful as for unsuccessful innovations, highlighting what Dierickx and Cool (1989) refer to as the “jackpot model” of innovation. This model outlines that “Firms sink R&D flows in projects with highly uncertain outcomes, and only few firms actually ‘hit the jackpot’ by bringing out highly successful products”. Furthermore, innovation based on process or current use is less important. One interpretation of this finding is that identifying an unseen need is necessary, but not a precursor, for successful radical innovation as expressed by one EMC:

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...the biggest thing I learnt was this business of how to work with customers and distil a set of conflicting and disparate requirements that customers give you. I understand that customers don’t know what they want, mostly. When the process of uncovering the unseen needs is developed as a portfolio of ideas with the help of partners who contribute capabilities, capacity or social capital, uncertainty is gradually and systematically reduced over time. The need to balance rational considerations of likely success before committing to an individual innovation was recognised by EMCs as being detrimental to enabling innovation: If you start to be rational about these things then there would be a very small fraction of people who would be justified in moving forward, not just simply dreaming and 14

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walking past the thought. This innovation, in my opinion, is risky. Now, without courageous people, progress won’t happen. Hence, the vision of the inventor and entrepreneur is the third important factor to successful radical innovation. Given a portfolio approach to radical innovation, successful EMCs pointed to the need to identify failure but, at the same time, the need to be prepared to abandon individual innovation initiatives and focus on the emerging successes. What these results highlight is that the role of individual personalities in radical innovation is more subtle than the leadership literature would suggest, but that does not mean it is unnecessary. Further, there appears to be little role for organisational culture. In summary, radical innovation is seen by EMCs as most appropriate where there is a significant departure from the previous business model of the organisation, particularly where there is a disruptive impact on the industry involved. A key factor in the successful radical innovation narratives was identifying and effectively managing business partners. EMC narratives identified the importance of partners in particular in terms of capability acquisition, selected intellectual property, brand association and capacity. This finding is consistent with the entrepreneurship and outsourcing literature where high growth, knowledge-based firms are significant adopters of outsourcing and other forms of business networks (Granlund and Taipaleenmäki, 2005).

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Evolutionary Innovation

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Based on our earlier explanations of evolutionary innovation, projects of this category usually require a top-down impetus for their initiation and sponsorship. An EMC may be dealing with moderately high levels of uncertainty in either the external environment or within the organisation but usually not both. Analysis of our data is consistent with this proposition regarding evolutionary innovation. These characteristics are highlighted in Figure 8 below.

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In the data analysed here, successful evolutionary innovation does appear to be largely driven by EMC personality. Further, the analysis of successful narratives found that culture did not play a significant role in developing evolutionary innovation. To be successful, initiatives need to be legitimately led by the EMC: … first of all, you have to have champions and, unashamedly, I’m a champion for applying that type of philosophical construct to the organisation This does not mean that employees will automatically follow the EMC’s vision but, with this category of innovation, EMCs can wield significant influence and control over the implementation of change than appears possible when dealing with a radical change. There is a power relationship that exists here, as one CEO suggested: We'd get together, we'd talk about the issues, we'd work out why we are getting beaten in this business, where the market is going, how it's changing, what our perception of 15


[XYZ] is in the marketplace. And then we'd sit there and we'd brainstorm solutions. But at the end of the day someone has got to drive, you get five or six different things up on the board and you go that's the one we're going to do. Many EMCs acknowledged that the ‘Personality‐Driven’ style was not limited to them, and often innovation of this category required multiple champions in order to be successful. Many used the word ‘belief’ to describe the critical differentiator between success and failure. Fundamentally they needed to believe in the idea for the ‘Personality-Driven’ approach to be effectively enacted. If the EMC did not believe in it, then it was unlikely the rest of the organisation would. As expressed by another EMC: We've got a beautiful system because we've stolen it from everyone else and designed it, but the system doesn't do the deal, you know the gates and everything ... It doesn't make innovation flow through to the belief stage where you get momentum.

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Additionally, as Figure 8 shows, a key difference is that the focus of evolutionary innovation is more likely to be process and use oriented and therefore, largely internal to the organisation. The differentiating feature of a good process was the EMC’s ability to use the process to improve decision making relevant to the innovative idea.

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So another lesson learnt there is you've got to have your checks and balances in along the way, especially if you are trying to do something that's innovative and a bit out of the box and a bit expensive. Yes, you’ve got to continue to check it and you’ve got to continue to monitor it...

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Thus, a tension exists for EMCs when it comes to process because they acknowledge its importance, but do not like its constraints. In the realm of evolutionary innovation, process does not make a difference but the ability to drive change through it does. Hence, inspiring the organisation to get behind the innovation is more likely to lead to success.

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The internally focused nature of evolutionary innovation allows for greater EMC control and the exercise of organisational power relationships. Further, the presence of structure-based patterns of innovation is consistent with an internal focus. If this focus is combined with formal or hierarchical management controls there is a greater risk of failure:

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.. hierarchy kills innovation. So, my thought was to make communication flat, and I think to do collaboration you really need a shared interest and a way to communicate. But, to do it well you need good contribution and feedback. Hence, a distinctive element of the Evolutionary category is the role of the structure‐based pattern. Structure, in the form of organisational hierarchy or organisational silos, was seen as something that had to be overcome before innovation could begin. The creation of an organisational environment for innovation therefore, was not simply cultural as may be expected, but clearly highlighted the need for structures that enabled ideas and innovations to develop: An example would be in restructuring parts of the businesses where staff seek the hierarchical structures of 'where's my box?' and 'who do I report to?' 'There used to be six of those and now there is only four. How am I going to do the work? 16

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In summary, evolutionary innovation is typically an expansion or significant change to the current business model employed by the firm. The organisation may be dealing with moderately high levels of uncertainty in either the external environment or within the organisation but usually not both. In this context, projects or innovations usually require a top-down impetus for their initiation and sponsorship. Hence, a charismatic EMC is best suited to this category of innovation.

Incremental innovation Finally, incremental innovation appears to be more successful if focused on alignment with accepted organisational culture rather than EMC personality or external factors. As shown in the comparison between successful and unsuccessful innovation initiatives represented by Figure 9, there is material risk of failure if culture is subsumed by EMC enthusiasm.

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Many of the incremental innovation narratives were characterised as having a relatively high level of certainty but these were most often a reaction to a problem that needed to be addressed. Unlike other innovation categories, the scope of the problem was often understood early and a viable solution was clearly identified early by the EMC. An EMC describing a successful incremental innovation:

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So what we realised was for us to be good collectively, we had to change the individual view of success from a context of ‘me’ to ‘we’. Once we did that and we created an understanding that it’s the bigger picture; it’s the overall goal of the network; and it’s supporting each other than matters the process of designing and innovating on [the project] started to drop down into the organisation to almost any level. So anyone anywhere could come up with a great idea...

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Further, overt imposition of incremental improvements by the EMC was viewed by many of those interviewed as counter-productive. Figure 9 represents this perception that an EMC ‘personality-driven’ approach is more strongly associated with innovation failure than success. It appears that insufficient knowledge of the details required for successful incremental innovation is a substantive contributor to this result.

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For incremental innovation to succeed, the focus on alignment with organisational culture and limited EMC personality-driven involvement is more likely to succeed with processoriented change. The preference is for problem-based innovation that is incorporated into ‘normal’ business practice and routines. A key element for success is routine engagement: .. we had to be focused on closing the feedback loop, not necessarily on an individual basis .. What we had ended up doing was showing a pie chart. A year later, we went back and said ‘here’s an analysis of the issues and you can see what the result was’. In summary, incremental innovation encompasses improvements to the current business model that do not involve changing it significantly. Often this involves fixing problems with 17


current operations as opposed to creating new operations. There will be a high level of certainty about both the internal and external business environments as they relate to the idea. As a consequence, process-driven change and engagement of the existing organisational culture is more likely to be successful. Support from the EMC is useful but a personalitydriven approach is detrimental to incremental innovation. This type of innovation appears to support bottom-up approaches from those who have their “hands on” these processes. Having outlined the results in terms of the three categories of innovation, the next section describes the links and some of the contrasts between the grand theory linking IC as an enabler of innovation as found within the EMC’s narratives.

Linking IC with the Innovation Grand Theory Overall, the findings of this study are consistent with the grand theory that IC is an antecedent for successful innovation. The research finds that elements of human, structural and customer capital are required for successful innovation. However, the findings expand upon the grand theory and outline that if there is not a balance of different IC types that this could contribute to innovation failures. This finding is novel within the literature linking IC to innovation as the a priori focus of the literature generally links IC to successful innovation rather than trying to understand how specific aspects of IC contribute to and/or hinder different types of innovation. Thus, in contrast to the grand theory, the findings offer a more detailed examination of the categories of innovation success and failure, indicating that understanding of the mix of IC components leads to more nuanced conceptualisation of the IC-innovation relationship. These relationships, expressed in terms of the prevalent links between IC, innovation category and innovation practice, are summarised in Table 3.

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[Insert Table 3 here]

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Thus Table 3, while consistent with the grand theory that IC is an enabler for innovation, is different from Figure 5, which confirms that a mix of human, structural and customer capital is implicated in successful innovation where the type of innovation is not differentiated. However, on closer examination of successful and unsuccessful innovation, it is found that different categories of innovation are driven by different combinations of IC types. Thus, in terms of how these findings contrast the grand theory linking IC as an enabler of innovation the findings support some of its contentions, however the grand theory begins to evolve into what Llewelyn (2003, pp. 670-2) calls differentiation theories of practice. According to Llewelyn (2003, p. 670) “Peoples’ understanding and experience of the world is differentiated by a multitude of what come to be highly significant pairings, contrasts, dualities or dualisms”, which differentiates between innovation types and shows the impact of different IC categories.

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First, radical innovation requires a focus on customer capital supported by structural and human capital. Compared to other innovation categories, radical innovation is significantly more complex from an IC perspective. Whilst the focus is on human capital, there is also a 18

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need to manage the interaction between all three forms of IC. For example, even where a partner-based relational capital focus was emphasised, human capital in the form of individual know-how in partner firms, team-work capacity across organisations, and structural capital, in the form of organisational culture, needs to be managed across the interorganisational relationship. As one EMC unsuccessfully pursuing a radical innovation stated: I thought I sort of understood this innovation thing at that stage, I thought we’d done all the right work to convince the company that what we were doing was the right thing... we’d worked together, we’d gone through all the arguments and debates about what the product should do, we’d made a lot of effort to have it integrated with all their existing staff and so on and there was real disappointment when it didn’t go anywhere. Second, evolutionary innovation is perceived by the EMCs to be largely driven by human capital in the form of EMC personality and internal communication within the innovating firm. In the words of one EMC:

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.. the system doesn’t do the deal. You know the gates and everything. It doesn’t do it. It doesn’t make innovation flow though to the belief stage where you get momentum and cultural belief in an organisation.

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Additionally, structural capital supports human capital elements. In the words of one EMC, the technology adoption enables evolutionary innovation:

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So we probably did three or four months worth of just internal, in the group doing some prototyping, proving out some context and then getting to the point of a demo. And then I was able to show my management at the time, OK, here’s the demo of what is possible. And then you start to get buy-in form outside the group.

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Finally, with a focus on problem-solving, product improvement and performing existing processes better, incremental innovation is dependent on structural capital. In terms of success, reduction in uncertainty is often influenced by human capital in the form of organisational culture. For this innovation category, staff and management tend to drive change innovation rather than top management, as expressed by one EMC:

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.. it didn’t involve somebody who’s job was to do new things. It involved somebody that was just doing an ordinary job thinking about ‘I’ve got a problem with this particular technique in the process and how I can fix it’. It didn’t involve somebody who was a card carrying rocket scientist whose job was to think new things. In summary, the analysis shows how the different types of IC influence different forms of innovation. Thus, the findings break free from the grand theory linking IC as an enabler of innovation, by developing a differentiation theory of practice by showing how an IC perspective can be used to develop successful innovation and possibly prevent failures by understanding the type of innovation being attempted and the mix of IC components that are required, or otherwise. By expanding the grand theory it is argued that it is possible for practitioners to develop successful innovations instead of blindly applying IC as suggested by 19


the original grand theory without considering the finer nuances of innovation type and whether the innovation was a success or failure.

Conclusions The main contribution of this paper is to expand on the grand theory linking IC to enabling innovation by developing a differentiation theory of innovation practice. While the study does not discredit the grand theory it builds on it by highlighting that depending on the type of innovation being developed, that different IC types may be put into practice. The study finds that some of the IC types that have generally all been lauded as necessary for successful innovation were not always required, and may even be detrimental to innovative processes. This is counter to many innovation studies based on trying to prove the grand theory linking all IC as an enabler innovation which do not pay particular attention to the type of innovation being developed and how particular aspects of IC are deployed. This discrepancy is, in part, attributable to the need to explore innovation categories and recognise that innovations might also fail.

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Thus, the study is innovative because most contemporary studies focus on either radical or incremental innovations, with the former being the most prevalent, while this study seeks to understand the enabling conditions for innovation from the perspective of all three types of innovation. It also contributes to the innovation management literature as it examines the conditions required for successful innovation and failure. This provides insights into the factors promoting innovation and those hampering innovation. The continued development of these insights has the potential to identify how organisations can understand the type of innovation being developed, how to link the innovation to strategy and enable conditions within the organisation to promote a greater likelihood that innovation will be successful.

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Implications for education One of the key roles of educators is to teach critical thinking, which is a generator of intellectual ability (Dumay, 2009b; Duarte, 2012). Currently there appears to be a danger that by adopting the uncritical nature of contemporary IC literature which, as highlighted by Sveiby et al. (2009), has a success bias, our universities and business schools will continue to educate future managers into believing that all innovation is beneficial. The study highlights the need to critique innovation rather than accepting this commonly held view. It is the duty of management educators and researchers to ensure this happens, otherwise the future leaders of commerce and government will graduate from our universities and business schools inadequately equipped to deal with innovation in practice.

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Implications for research For researchers, this study also highlights the need for future research to be focused on understanding the antecedent conditions for successful and failed innovations. The literature review proposes that there is often a success bias in the way innovation research is conducted from both a methodological as well as practical perspective. Methodologically, researchers 20

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often ask loaded questions or introduce respondents to terminology that entices respondents to give responses biased towards the grand theory under scrutiny. Thus, because a researcher already ascribes to a grand theory, such as the one outlined in this paper, they can only discover results that support it because of the general nature of the theory. Unfortunately this is inevitable because the development of grand theories are “technical social science language games that academics, in particular, are trained in” (Llewelyn, 2003, p. 676). From a practical perspective the success bias towards innovation exists because researchers often only analyse successful companies, notwithstanding the availability of data, the willingness of successful companies to allow access to promote their good fortune and the fact that unsuccessful companies have disappeared. Whittington et al. (2003, p. 400) outline, how one spectacularly failed innovative company, Enron, was originally seen as “a strategy pioneer, vaunting its asset-light business model, the value of its intellectual capital, its adroit exploitation of deregulated markets, its innovativeness in Web-based commodity trading, and its atomization of the value chain”. Dumay (2012, p. 12) also contributes to understanding the success bias stating that “Analysing winners enlightens us to wining strategies while analysing losers enlightens us to losing strategies. Unfortunately, they have often been the same strategies, just executed differently”. Thus, researchers need to break free from analysing grand theories of success and develop insights by developing differentiation theories of innovation practice.

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Implications for practice This paper is a must read for managers and practitioners because it is one of the few that delves deeper into the espoused benefits of innovation and a differentiation theory of innovation practice. By understanding that applying IC concepts to innovation practice is distinctly different to the espoused grand theory, managers and practitioners must take one step backward to first recognise what they are trying to achieve and how IC concepts may be applied in enabling the desired outcomes, and second to be aware of and plan for the detrimental, unintended consequences of innovation should they arise. This means that managers and practitioners need to develop critical and reflective skills allowing them to recognise, redirect or abandon an innovation gone awry, before further damage is done.

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Implication for policy makers Enabling the conditions for successful innovation in organisations and thus a national economy as a whole is a key role for policy makers. This study highlights there are different forms of innovation and each is enabled differently, thus different approaches are necessary towards ensuring all forms of innovation are supported, not just the radical forms of innovation often lauded in academic journals, popular management press and the news media. As our research shows, there are varying degrees of innovation and each has their successes and failures. While it is not espoused that the differentiation theory linking IC to enabling different forms of innovation is the answer to ensuring all innovation will be successful, it highlights to policy makers that recognising different forms of innovation requires different approaches; a one size fits all approach to innovation policy only advocating and encouraging radical innovation may not be the answer. Economic prosperity 21


is built on all forms of innovation and each can be encouraged, developed and enabled differently. Limitations The main limitation of this paper is that it was produced in the Australian context and is based on the authors’ analysis and interpretation of a limited amount of data from 27 respondents. However, as indicated earlier, this was exploratory research with a limited scope. As such, future studies could be advanced to include many more respondents from different industries and nations, but this volume of research would require substantially more resources and time than was available. The research also attempts to avoid bias by selecting a range of different organisations rather than just those recognised as being highly innovative and by openly questioning the EMCs about innovation success and failure. Thus, it is argued that this paper is one of the few innovation studies to critically report on how IC can be applied to enabling innovation rather than accept the assumptions of the empirically unproven grand theory linking IC to enabling innovation. As with any qualitative study the authors also caution about generalising the findings, and as with any theory it should be used to develop insights into actions rather than prescribing them.

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Petty, R. and Guthrie, J. (2000), “Intellectual capital literature review: Measurement, reporting and management”, Journal of Intellectual Capital, Vol 1 No 2, pp. 155-76. Porter, M. (1980), Competitive Strategy: Techniques for Analyzing Industry and Competitors., Free Press, New York. Qu, S. Q. and Dumay, J. (2011), “The qualitative research interview”, Qualitative Research in Accounting & Management, Vol 8 No 3, pp. 238-64. Schumpeter, J. A. (1934), The Theory of Economic Development, Harvard University Press, Cambridge, MA. Skandia (1995), Intellectual Capital: Value-Creating Processes: Supplement to Skandia's 1995 Annual Report, Skandia Insurance Company Ltd., Sveavägen 44, SE-103 50 Stockholm.

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Skandia (1996), Power of Innovation: Intellectual Capital Supplement to Skandia's 1996 Interim Report, Skandia Insurance Company Ltd., Sveavägen 44, SE-103 50 Stockholm. Sveiby, K.-E. (2012), “Innovation and the global financial crisis: Systemic consequences of incompetence”, in K.-E. Sveiby, P. Gripenberg and B. Segercrantz (Eds), Challenging the Innovation Paradigm, Routledge, New York, pp. 113-42. Sveiby, K.-E., Gripenberg, P. and Segercrantz, B., Eds. (2012), Challenging the Innovation Paradigm. Routledge Studies in Technology, Work and Organizations. New York & London, Routledge. Sveiby, K.-E., Pernilla Gripenberg, Beata Segercrantz, Andreas Eriksson and Aminoff, A. (2009), “Unintended and undesirable consequences of innovation”, paper presented at the XX ISPIM conference The Future of Innovation, Vienna, 21-24 June, 2009.

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Table 1: Innovation, competitive advantage and linkages to Intellectual Capital

Innovation category Radical

Competitive advantage Significant impact on the industry

Linkages to IC Mainly customer capital supported by structural and human capital Mainly human capital supported by structural capital Mainly structural capital supported by human capital

Evolutionary

Significant change to the business model Incremental Improvement to the current business model Source: Based on interpretation of Tidd (2001).

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Table 2: Derived patterns of innovation from repertory grid analysis

Innovation Practice Improving Current Practice

Personality Driven

Description This refers to the application of ideas to improving a current or existing practice. The key motivator is increasing efficiency, though, in some cases, it was simply doing things a bit better than before. This pattern characterises the force of personality of the leader to drive through the change and keep the innovation going in spite of the various hurdles it may face. It extends to the ability to influence others in the organisation both politically and behaviourally to get behind the change. This pattern utilises the assumption “innovation is everyone’s responsibility”. The source of innovation is the organisation’s culture, and the extent to which the EMC can nurture it. This typology refers to the process or method adopted by the organisation for its innovation. This includes stage-gated commercialisation pipelines, ideation methods, due diligence, partnering agreements etc. The engagement with and use of partners to assist in the development, commercialisation and adoption of the new idea, as opposed to attempting to do it all within the organisation.

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Culture Sourced

Process Based

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Probability Based

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Partner Enabled

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Approaches innovation as bets, within a portfolio, expecting that few innovations will succeed and most will fail. There is a high acceptance of failure and an associated need to spread risk as well as killing an idea that was not working out as expected. Advocates the application of high domain skills to overcoming a current technical barrier. The absence of an expected application for the innovation is often not a concern with the commercialisation process occurring later on after the discovery. Pursuing ideas by inspiring the use of existing products or practices. Refers to the ideas inspired by the vision of an inventor or entrepreneur. In most cases, the customer is unable to conceptualise the need until the product is commercialised. A belief that through the recruitment of a selection of ‘smart’ people, innovation will occur. Under this approach it is assumed that by putting ‘smart people’ (i.e. highly developed

Discovery Driven

Use Inspired Unseen Need Inspired

Capability Based

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Ideas Based

Structure Based

domain skills, intelligent) together and freeing them of dayto-day distraction the organisation will become innovative. Here the innovation is based upon a powerful idea or vision. The power or love of the idea then becomes the driving force behind investment and the political will to push the idea. Here the EMC begins their approach to innovation by attempting to work around the organisational structure, which could involve breaking down silos, or setting up a unique structure to deal with the idea.

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Table 3: Linkages between IC, innovation category and practice.

IC Type Human capital

Link to innovation category A key factor for successful incremental innovation. Also a mitigating factor in radical and evolutionary innovation.

Structural capital

A key factor for successful evolutionary innovation. Also a mitigating factor in radical innovation.

Relational capital

A key factor for successful radical innovation.

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Link to innovation practice Improving Current Practice Personality Driven Culture Sourced Discovery Driven Capability Based Ideas Based Process Based Probability Based Partner Enabled Structure Based Use Inspired Unseen Need Inspired

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Figure 1: Unintended consequences of radical innovation

Source: Sveiby (2012, p. 115)

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Figure 2: Summary of industry sectors addressed in this study.

Telecommunica tions 2

Transport 1

Utilities 1

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Public sector 2 Media 1

FMGC 1

Health 1

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Information technology 7


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Figure 3: Effect of uncertainty and complexity in the management of innovation

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Source: Tidd (2001, p. 176)

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Figure 4: Classification of innovation narratives

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Legend: Successful innovation narratives - Light gray: Failed innovation narratives – Dark gray


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Figure 5: Patterns of innovation practice for all initiatives considered successful.

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Figure 6: Patterns of innovation practice for all initiatives considered unsuccessful.

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Figure 7: Patterns of radical innovation practice for all initiatives

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Legend: Successful innovations are highlighted in white, failed innovations in gray

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Figure 8: Patterns of evolutionary innovation practice for all initiatives

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Figure 9: Patterns of incremental innovation practice for all initiatives

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