فشار تکنولوژی و دیدگاه های کشش تقاضا در مطالعات نوآوری : یافته ها و دستورالعمل های تحقیقات آینده

This study updates the debate on the sources of innovation. Using techniques like factor analysis, multidimensional scaling, and pathfinder analysis, we examine the most influential articles that have dealt with the topic. Our analysis provides three main findings. The first more precisely highlights the role of demand as a source of innovation. The second illustrates how competences enable firms to match technology with demand and capitalize on technology and demand as sources of innovation. The third unveils a distinction between external and internal sources of innovations. The sources of innovation can be purely external or internally generated competences that enable the firm to integrate external knowledge within its boundaries. Our work contributes to the classic debate by providing a more granular understanding of how technology and demand interact. In discussing our findings, we link our framework to strategy, innovation and entrepreneurship studies that expressly call for a better understanding of technology and demand factors in value creation and capture.

For years, scholars investigating the economics of technical change conducted their pioneering research by juxtaposing the forces that were to shape two alternative perspectives (e.g., Schmookler, 1966, Meyers and Marquis, 1969, von Hippel, 1976, Mowery and Rosenberg, 1979 and Rosenberg, 1982). On the one hand, those who referred to the so-called technology-push perspective pinpointed the key role that science and technology play in developing technological innovations and adapting to the changing characteristics of the industry structure. On the other hand, scholars embracing a demand-pull approach identified a broader set of market features, including characteristics of the end market (particularly, the users) and the economy as a whole, that affects the performance of innovation. The juxtaposition of these two approaches to innovation fostered a fruitful debate that reached its apex in the Seventies. Those years have witnessed a confirmation of the role of science and technology in generating innovation and a growing skepticism regarding a pure demand-pull perspective. In particular, the latter raised a number of theoretical and empirical concerns. For instance, given the interrelated nature of the curves of demand and supply, Mowery and Rosenberg (1979) claimed that is technically complicated to distinguish a demand-pull situation from a technology-push one. Relatedly, Dosi (1982, p. 150) remarked that research in the demand-pull tradition failed “to produce sufficient evidence that ‘needs expressed through market signaling’ are the prime movers of innovative activity”. Along with this chorus of critiques, but approaching the issue from a disciplinary angle, Stigler and Becker (1977) claimed that de gustibus non est disputandum: namely, when the discussion goes so far as to examine differences in tastes among people, economists should leave the floor to those who study and explain tastes – namely, psychologists, anthropologists and phrenologists. The debate therefore reached a sort of deadlock in the Eighties. At that time it seemed clear that while most technical innovations were driven by science and technology, the role of demand and more broadly of market and social forces was complementary in that respect. For instance, when it is a matter of selecting a specific technological trajectory, “the role of economic, institutional and social factors must be considered in greater detail. A first crucial role (…) is the selection operated at each level, from research to production-related technological efforts, among the possible “paths”, on the ground of some rather obvious and broad criteria such as feasibility, marketability and profitability” (Dosi, 1982, p. 155). Similarly, Kline and Rosenberg (1986) advocated a shift from linear models of technology and demand to a more interactive model between these two potential sources of innovation. Overall, science and technology seemed to be “the” source for the vast majority of technological innovations and demand was the best companion to drive innovation in the right economic and institutional directions. Despite the growing consensus about this mutual dependence with an emphasis on technology as the ultimate source of innovation, the way the selection process and, more broadly, the interaction might have occurred was primarily described conceptually and was discussed mostly at a macro level. Instead, due to the increasing importance of technology within organizations ( Arora and Gambardella, 1994, Chesbrough, 2003 and von Hippel, 2005) and the impressive growth of fields focusing on the economics and management of technology ( Fagerberg et al., 2012 and Martin et al., 2012), in this paper we aim to review the influential articles published on the sources of innovation in recent years. The question that motivated our research is to see whether these more recent studies have enriched our understanding of technology and demand as sources of innovation and have explained more specifically how the two can be leveraged in order to commercialize successful innovations. Our review follows mainstream methodologies of bibliometric analysis (e.g., Acedo et al., 2006, Nerur et al., 2008 and Di Stefano et al., 2010). In addition to better clarifying the role of demand as a source of innovation, our findings show that a clearer balance between the two approaches has apparently now been reached from both an empirical and a more micro standpoint. Indeed, in addition to confirming the dual nature of innovation sources (technology push and demand pull), our findings highlight that scholars have paid particular attention to studying and demonstrating how firm competences enable firms to match the two sources and thus deliver the right innovations to the market. In this respect, researchers seem to have focused their attention on different approaches to knowledge integration: those who start with a clear focus on the external environment and try to absorb knowledge within firm boundaries and those who start from internal sources and focus on integrating external knowledge. While in the former case, external sources remain the ultimate source of innovation, in the latter case internally generated competences seem to be the sources of innovation. The rest of the paper is organized as follows. We explain in detail our methodological approach (Section 2); we then present our findings with respect to the three analyses we ran (Sections 3, 4 and 5); finally, we conclude with a discussion section in which we call for: studies on the microfoundations of innovation, research linking innovation and entrepreneurship, and the pluralism of methodologies for the understanding the topic under investigation.

In this paper we have provided a detailed review of academic articles dealing with the sources of innovation. After debating the juxtaposition between technology and demand as sources of innovations, classic works on the sources of innovation converged on the mutual importance of the two sources. While science and technology provide the trajectories of innovation, demand is a crucial component in order to direct the trajectory towards the right economic venues (e.g., Dosi, 1982 and Kline and Rosenberg, 1986). Despite an agreement was reached, many questions were left open in the debate. For instance: does demand generate innovation in addition to selecting it? How can firms capitalize both technology and demand in the process of innovation development and commercialization? Are firms passive or active actors in the process of leveraging on technological or demand sources? What are the mechanisms that enable firms to leverage the different sources of innovation? In the attempt to see how scholars have addresses these and related questions, we have carried out a thoroughout review of papers published in business and management journals. In so doing, we believe we have contributed to the field of innovation studies by providing a systematization of journal articles on the topic of the sources of innovation. Like all review based on bibliometrics, this paper presents a number of limitations. First of all, it excludes books, book chapters, and working papers from the set of papers. Second, it selects papers based on keywords. Third, it limits the number of reviewed papers to the most cited. Finally, it works on co-citation as a pattern of analysis. While these limitations enable researchers to work on a robust database, we are perfectly aware of alternative approaches to some of them. For instance, the recent work by Fagerberg et al. (2012) uses cluster analysis to study the broader topic of innovation as it has been published in handbooks. The work by Martin (2012) is based on a review of highly cited papers and traces the innovation of the field of science policy and innovation over the last 50 years. Both studies can be seen as complementary to our approach in both the method used and the more “macro” focus presented. While we are aware of the limitations of our review, we believe that our investigation has brought to light three important findings. First of all, our contribution has more precisely highlighted the role of demand as a source of innovation. Scholars in the past have criticized the actual role of demand and narrowed it to the role of a selection force of technology (e.g., Mowery and Rosenberg, 1979 and Dosi, 1982). While the lever of demand is particularly important in the case of selection (e.g., Factor 2; Factor 4b), our analysis has also unveiled how an interrelates set of more recent studies have provided a better understanding of the role of demand as a source of innovation (Factor 3). Second, in addition to confirming the importance of technology as a source of innovation and clarifying the role of demand, our contribution has identified resources, competences, and knowledge as a crucial dimension in providing a synthesis of the two. Indeed, many technological innovations have their origin in science and technology but still need a market and the related complementary assets (Teece, 1986) to be successfully commercialized (e.g., Christensen and Bower, 1996 and Gatignon and Xuereb, 1997; and, more broadly, Factors 1, 2, and 4a). Similarly, innovations that stem from a pure demand pull perspective (von Hippel, 1976 and von Hippel, 1994; and, more broadly, Factors 3 and 4b) still require technological competences to be developed effectively. In all these cases, competences are at the basis of this fundamental synthesis, as demonstrated by most of the articles linked to these factors. Third, resources, competences, and knowledge can themselves be a source of innovation. This means that in some cases the competences serve the need of simply importing external sources within the firm (e.g., the case of sticky information of von Hippel, 1994 and more broadly of Factor 3). Most often, competences are internally generated and help the firm absorb the signals of technology and/or demand according to the firm characteristics (e.g., Teece et al., 1997; and, more broadly, Factor 1). This result brings in the issue of the firm's absorptive capacity (Cohen and Levinthal, 1989 and Cohen and Levinthal, 1990) as a crucial ability of the innovator to absorb such signals. While the previous findings represent the more objective conclusions that can be drawn from our analysis, we also see other important implications of our study. In particular, and in a more interpretative fashion, we believe that our analysis can be seen as uncovering three potential venues for future research on the topic, related respectively to: methodology, microfoundations, and entrepreneurship. First of all, some methodological issues emerged after examining the contributions collected in our analysis. We believe it is important to rely more on methods that today appear to be under-utilized in order to enrich the field with heterogeneous perspectives. Let us consider some examples that emerged in our analysis and how they contributed to research in this area. Studies based on primary data and in-depth case study, both at the supplier and user level, such as those by von Hippel, 1994 and von Hippel, 1998, have provided important insights on users’ characteristics and their impact on innovation. Longitudinal analyses, such as the one performed by Christensen and Rosenbloom (1995) and Christensen and Bower (1996) on the disk drive industry, have helped to better understand the impediments driven by mainstream customers in launching technological innovation. Analytical models, such as the one by Adner and Levinthal (2001), have highlighted the impact on technological innovation of factors such as customer preferences and their heterogeneity. Studies based on experimental design characterized primarily the discipline of marketing, but they can provide important base of exploration even when adopting other views of innovation. Overall, a wealth of methods means a wealth of findings, perspectives, and details, and has to be fostered if the field of innovation is to develop and, in particular, the sources of innovation better understood. Second, in addition to stimulating the importance of a pluralism of methodologies, we believe that our analysis should encourage future research to combine micro and macro levels of information, and to go into the microfoundations of the relationship under study. Indeed, the study of microfoundations of capabilities can enhance our understanding of strategy making but also of competence-leverage (Teece, 2007) and as such can improve our understanding of the sources of innovation. As pointed out by Rothaermel and Hess (2007), academic research has tended to focus on only one level of analysis at a time (individual, firm or network), assuming that the other levels are homogeneous and that the chosen level is independent from the others. Taken together, these two assumptions can potentially harm the reliability of empirical findings by suggesting that research be carried out at multiple levels in order to capture most of the heterogeneity. With reference to the issue of microfoundations, in examining the research on the relationship under study, most of the attention seems to have been devoted to the firm or network level of analysis, except for the longstanding tradition of research on lead users (von Hippel, 2005) and recent contributions on managerial cognitive frames (Tripsas and Gavetti, 2000). The study of microfoundations seems to be an emerging and interesting path to follow in this domain: substantial attention needs to be devoted to explanatory mechanisms at the individual level. Consider the exemplary case of the long-debated research on disruptive technologies. The question stemming from this debate is whether incumbent firms will inevitably fail to seize radical innovation opportunities. Research in this area started by examining industries in which incumbent firms were unable to capture radical innovations, because of managerial focus on target markets in the allocation of innovation resources. However, the fortune of firms is not the fortune of the industry, and disruptive innovations have been shown to create new markets and net growth, even though incumbents still do not always seize the opportunities associated with these innovations. The attention has therefore moved to a more fine-grained analysis at the firm and individual level. At the firm level, research has examined incumbent inertia from two viewpoints (Gilbert, 2005), i.e., in terms of resource rigidity (Christensen and Bower, 1996 and Henderson, 1993) and routine rigidity (Leonard-Barton, 1992 and Nelson and Winter, 1982). Recently, also institutional explanations for incumbent inertia have also been advanced, according to which pressures from financial markets during periods of radical change may impede incumbents from responding to change (Benner, 2007). At a more detailed level, research has even examined organizational inertia in terms of distinctive competences and official corporate strategy (Burgelman, 1994), as well as managerial cognitive frames (Gilbert, 2006). Since firms have an opportunity cost in capturing innovation opportunities, current literature has tried to identify ways through which incumbent firms can overcome inertia. At the industry level, the role of complementary assets has been widely examined starting from the seminal contribution by Teece (1986). Indeed, complementary assets can dramatically affect the division of returns to innovation in industries where they are important (Tripsas, 1997, Gans and Stern, 2003, Rothaermel, 2001 and McGahan and Silverman, 2006). Additionally, at the industry level, incumbents have been shown to adapt to change by devising start-ups to operate in new fields (Allen, 1998), or being subject to the phenomenon of spinoffs (Klepper, 2007). At lower levels, literature has studied economic, organizational and strategic factors allowing incumbents to successfully respond to radical technological change (see, for a review, e.g., Hill and Rothaermel, 2003), as well as the impact of managerial cognitive frames (Tripsas and Gavetti, 2000). To sum up, it is by looking at multiple levels of analysis, with an integrative and contingent perspective, that one can better understand why firms may be unable to see emerging trends in the industry, and how they can improve their ability to do so. In this respect microfoundations seem the level that it is more penalized thus far. Third, our results highlight one final important aspect relates to the field of entrepreneurship. Although sometimes developed as separate fields, entrepreneurship and innovation are closely interrelated – see also the papers by Aldrich (2012) and Bhupatiraju et al. (2012). It is no accident that reviews of each of the two fields highlight the importance of the other: innovation turns out to be one of the core domains of entrepreneurship (Hitt and Ireland, 2000) and entrepreneurship is one of the core themes within the innovation domain (Shane and Ulrich, 2004). More specifically, on the one hand, the process of creating new products, processes, markets and ways of organizing is primarily based on entrepreneurship (Schumpeter, 1934). On the other, the very definition of entrepreneurship incorporates the idea of exploiting environmental opportunities through innovation for the purpose of wealth creation (Hitt et al., 2001). In the words of Drucker (2007, p. 25), “the entrepreneur always searches for change, responds to it and exploits it as an opportunity”. And he can do so primarily through the process of innovation. In fact, entrepreneurial actions entail creating new resources or combining existing resources in new ways (Hitt et al., 2001 and Ireland et al., 2001). Entrepreneurship research has started to focus its attention on a new, active relationship between the firm and its external environment, calling for the need to focus on opportunities created by supply-driven as well as demand-driven changes (Eckhardt and Shane, 2003). Linking more formally these first results to innovation studies would benefit both themes. In conclusion, we hope that scholars will benefit from our effort to better untangle emerging topics in this field of inquiry, which seems to be increasingly important in business practice and research. In this respect, we believe our contribution will help the literature dealing with the sources of innovation move from a bifurcation between market-pull and technology-push to a more comprehensive and balanced consideration of the different foundations of innovation, in which demand and technology are understood to be the levers and sources of innovation.