1 DYNAMIC CAPABILITIES DECONSTRUCTED: A ...

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DYNAMIC CAPABILITIES DECONSTRUCTED: A BIBLIOGRAPHIC INVESTIGATION INTO THE ORIGINS, DEVELOPMENT, AND FUTURE DIRECTIONS OF THE RESEARCH DOMAIN

Giada Di Stefano Bocconi University Via Roentgen 1, 20136 Milan, Italy Email: [email protected] Phone: ++39 (02) 5836-5797 Fax: ++39 (02) 5836-2530 Margaret Peteraf Tuck School of Business at Dartmouth 100 Tuck Hall, Hanover, NH 03755, USA Email: [email protected] Phone: ++1 (603) 646-1944 Fax: ++1 (603) 646-1698 Gianmario Verona Bocconi University Via Roentgen 1, 20136 Milan, Italy Email: [email protected] Phone: ++39 (02) 5836-6522 Fax: ++39 (02) 5836-2530 January 2009

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DYNAMIC CAPABILITIES DECONSTRUCTED*: A BIBLIOGRAPHIC INVESTIGATION INTO THE ORIGINS, DEVELOPMENT, AND FUTURE DIRECTIONS OF THE RESEARCH DOMAIN

ABSTRACT This paper uses co-citation and content analyses to explore the structure of the Dynamic Capabilities research domain, to better understand its origins, current state of development, and future directions.

Co-citation analysis reveals the field’s ‘invisible colleges’ and research

directions, whereas content analysis is used to explore key themes and applications, the construct’s definition and its theoretical roots. We find evidence of commonalities as well as polarizing differences among understandings across this research domain, suggesting opportunities and challenges for future research.

* We use the word ‘deconstruct’ in its simplest etymological sense, and not in terms of its usage in literary criticism.

3 INTRODUCTION Since the publication of Teece, Pisano and Shuen’s (1997) seminal work on ‘Dynamic Capabilities’, the topic has become one of the most active research areas in the field of Strategic Management. In recent years, there has been a sharp rise in working papers, workshops, and conference sessions throughout the world on this topic. Special Issues focused on ‘Dynamic Capabilities’, such as this, are beginning to appear in scholarly journals (e.g. Easterby-Smith et al., British Journal of Management, 2009). Since 2006, articles concerning dynamic capabilities have been published in Business and Management journals at a rate of more than 100 per year.1 From the intensity of this research effort and evident interest in the topic, one might surmise that there exists a common understanding of dynamic capabilities. This is far from the case.

The construct remains open to a variety of conceptualizations and interpretations

concerning even its most basic aspects, including how dynamic capabilities are defined. This lack of accord may seem surprising in light of the definitive nature and strong influence of Teece et al.’s (1997) article (with over 1500 by December 2008). While the variation in understandings has contributed to the richness and vibrancy of the research on dynamic capabilities, it has also created confusion over the meaning and utility of the construct. This has led some to doubt even the existence of dynamic capabilities as more than a fanciful concept (Winter, 2003). At some point, these issues must be resolved for research in this area to advance further. A lack of clarity concerning basic understandings can limit fruitful conversation, impede progress on the theoretical front, and prevent empirical work from cumulating. These issues may resolve themselves in time as this research domain evolves. Publication success rates will vary across competing lenses and points of view. Authors whose

4 work is selected more often for inclusion in higher impact journals will be more widely read. Articles that are selected by more authors for citation will have a greater influence over how unresolved questions are settled. The pattern of selection may reveal the outline of the debates in sharper form and the underlying bases for the different positions. Over time, it may indicate the emergence of a consensus and which of the competing lenses and viewpoints is gaining sway. Alternatively, it may suggest that the domain is beginning to split into distinct branches, as researchers develop different aspects of the domain and as lines of thought become more distinctive. For those striving to make sense of the confusion, it would be useful to apprehend this pattern as it surfaces, since it provides form to an otherwise elusive research frontier. It serves as an indicator of the direction in which the frontier is moving and as a signal of the types of research garnering the most attention. Early notice of how the research domain is taking shape can help a researcher cut through the confusion and allocate their efforts towards those that will add the most value and prove most fruitful. Seeing the underlying issues in sharper relief can help them choose a position, refine the arguments, or find opportunities to reconcile differing positions. Discerning this selection pattern as it emerges, however, poses a challenge. Patterns can be hard to detect and even harder to decipher when a research domain is in its early stages of development, when the domain is complex, and when it is rapidly changing. For research on dynamic capabilities, its relative immaturity as a field of inquiry, the complexity of the research questions, the breadth of the research community, and the frenetic pace at which the research is accumulating all exacerbate the challenge.

5 In this paper, we take on this challenge by employing a combination of bibliometric and content analytic techniques to explore the way in which the scholarly literature on dynamic capabilities has been evolving and taking shape. Bibliometric methods, such as co-citation analysis, bring a level of objectivity and quantifiability to the task that reduces the level of bias inherent in alternative approaches, such as surveys of experts or more traditional literature reviews (Nerur, Rasheed and Natarajan, 2008). Content analysis adds a more fine-grained form of analysis that complements and enriches the insights available from more mechanical bibliometric approaches. All together, they help expose the underlying pattern of intellectual activity that gives shape, structure, and direction to the research domain as it develops and evolves. In the following section, we present an overview of the methods that we employ in our analysis. The next two sections are dedicated to a more detailed presentation of our bibliometric methods and findings, followed by a parallel presentation of the methods and findings of our content analyses. We conclude by commenting on both the limitations of and the insights gained from our investigations, and by identifying the implications of our study for future research.

BRIEF OVERVIEW OF THE METHODS Bibliometrics refers to “the collection, the handling, and the analysis of quantitative bibliographic data, derived from scientific publications” (Veerbek et al., 2002, p. 181). One of the most common bibliometric techniques is co-citation analysis, a method used to examine relationships among articles or authors contributing to the development of a research field. In recent years, this method has been applied increasingly across a variety of research fields for the purpose of uncovering and articulating their underlying structure. Examples range from a broad

6 examination of the Management field (e.g. Ramos-Rodríguez and Ruíz-Navarro, 2004), to the identification of the main trends within particular theoretical perspectives (e.g. Acedo, Barroso, and Galan, 2006), to the identification of communities of interest within specific topical areas (e.g. Gartner, Davidsson and Zahra, 2006). As these applications suggest, the technique can be employed to discern patterns within a field of endeavor as they emerge, and before they are widely recognized and readily observable otherwise. In this paper, we focus on those contributions to the dynamic capabilities literature recognized as being the most influential, and use co-citation analysis to trace the linkages among them, search for broad research fronts or subfields, and determine the relationships, if any, among the subfields. With multivariate techniques, we expose the “invisible colleges” within the research domain, and map the intellectual structure graphically.

Depicting the structure

graphically allows us to visualize more clearly the directions in which the field has been moving, as well as the distances between different pockets of intellectual activity. To complement these endeavors, we employ content analysis (Holsti, 1969). Content analysis involves the “systematic, objective, quantitative” examination of texts and provides another approach to uncovering the underlying structure of a field as it is taking shape (Neuendorf, 2002, p. 1). It is defined as “a research technique for making replicable and valid inferences from texts (or other meaningful matter) to the contexts of their use” (Krippendorff, 2004, p. 18). With keyword analysis, we uncover major research themes and applications of the concept. With lexicographic analysis, we find structural commonalities among the varying definitions of the concept and yet divisions within those common structures. We conclude with an analysis of the theoretical roots of the dynamic capabilities construct, to consider the bases for different conceptions of the construct, and to find the way forward.

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CO-CITATION ANALYSIS: METHODS AND FINDINGS Identifying the core A critical first step in uncovering the underlying structure of a field is the identification of its intellectual core (McCain, 1990). While this can be based on either contributing authors or published works, we use published articles on dynamic capabilities as our unit of analysis, since the same author may have published in different fields (Acedo et al., 2006). We use citation analysis to identify the intellectual core of research on dynamic capabilities on the assumption that citation counts are a valid measure of prominence and influence.

This is a standard

assumption for bibliometric analyses (Ramos-Rodríguez and Ruíz-Navarro, 2004). We based our analysis on the Social Science Citation Index (SSCI) of Thomson-ISI Web of Science over a time span from 1990 to 2007.

This database provides bibliographic

information for over 1,700 leading scholarly social sciences journals in more than 50 disciplines. Since ISI may take some months to complete data entry at the end of each calendar year, the analysis was performed after the month of April 2008, consistent with previous literature (e.g., Podsakoff et al., 2005). We began by retrieving all papers that were published in the Business and Management categories of the ISI Web of Science database, with titles, abstracts, or keywords containing the expressions “dynamic capability” or “dynamic capabilities”.2

This yielded a set of 371

contributions, all published between 1995 and 2007, 281 of which had at least one citation.3 These were published in a variety of journal categories, indicating that the dynamic capabilities perspective is beginning to diffuse from the Strategic Management area into fields such as Information Systems (22 articles, 8.9% of citations), Marketing (22 articles, 2.1% of citations)

8 and Operations (12 articles, 0.8% of citations).4 Within the Management area, the journals that ranked highest in terms of number of papers published on the topic are: Strategic Management Journal (46 papers with a cumulative citation score of 2,742), Journal of Management Studies (21 papers with 169 cites), Academy of Management Review (15 papers with 397 cites), Industrial and Corporate Change (13 papers with 100 cites), and Organization Science (12 papers with 313 cites). To identify the intellectual core of dynamic capability research, we restricted our analysis to the 225 papers published in the field of Management, where the concept originated. To this end, we ordered this panel of papers according to the number of times that they have been cited by any type of publication in the ISI database. Previous studies have used subjective criteria to determine a threshold of citation counts for inclusion in the core, such as the 100 most highly cited papers or papers with at least 50 citations (e.g., Ramos-Rodríguez and Ruíz-Navarro, 2004; Acedo et al., 2006). We chose to establish a more objective threshold by including only articles that received a number of citations greater than the average number of citations within our panel (20 citations). This lower threshold (relative to past practices) also counteracts a tendency for citation counts to underweight the impact of newer publications (Brown and Gardner, 1985). Applying this threshold led to the identification of a core set of the 40 most influential contributions, published in 14 different journals. These account for 68.4% of the total number of citations garnered by the entire set of the 371 journal articles published on dynamic capabilities through 2007. The complete list of this “Intellectual Core of Dynamic Capabilities Research” is shown in Table 1.5 -Insert Table 1 about hereAnalyzing the structure

9 Co-citation analysis of documents is used to reveal a field’s underlying structure, in terms of varying degrees of relatedness among the articles defining its intellectual core. It is a method for ascertaining the subject similarity between articles, based on the assumption that if two articles are cited together often, they are related by the broad questions they address, even if they are not in agreement (White and Griffith, 1981). The more often they are cited together, the stronger the relationship and the more likely they belong to the same research front, sometimes referred to as an “invisible college” (Crane, 1972). The method begins with the retrieval of co-citation frequencies for the set of core articles, and the compilation of these into a raw co-citation matrix. This is a square matrix, with rows and columns representing the articles in the set and cells representing the number of times each pair of documents has been cited together.6 The raw co-citation matrix is then converted into a matrix of Pearson’s correlation coefficients. Correlation coefficients represent a measure of similarity between two works. They are preferable to co-citation frequencies, since they make it possible to standardize the data and reduce the number of zeros, thus providing a better basis for subsequent statistical analyses (Rowlands, 1999). The last steps of co-citation analysis involve applying various multivariate techniques to analyze the data, and interpreting the findings. In this study, we used three techniques often used in co-citation analyses to assess the structure of a field of research: factor analysis, cluster analysis, and multidimensional scaling (McCain, 1990). Factor analysis is a data reduction method that we use here to classify the core articles into related sets, called factors, by detecting structure on the basis of varying degrees of relatedness among the articles.

The factors comprise relatively homogenous groupings of

articles that may represent a subfield, research front, or community of interest. Since the results

10 from cluster analysis were quite consistent with those we obtained from factor analysis, we report only the latter here. We used principal components analysis as the extraction method7, varimax rotation of the extracted factors to interpret the results8, and Kaiser’s criterion along with a scree test to determine the number of extracted factors. As shown in Table 2, the analysis resulted in 4 factors, explaining 94.1% of the variance. The factor loadings represent the correlation between a given article and the factor, or the degree to which the article belongs to that set. Consistent with prior studies (McCain, 1990), we include only factor loadings higher than 0.4, with loadings of 0.7 or greater indicating very high correlation. Loadings of the same article on more than one factor indicate that it is related secondarily to additional factors. - Insert Table 2 about here The Findings from Factor Analysis To characterize the factors, we examined the set of contributions loading on each factor for common themes and similarities in subject matter or approach, since this is a key driver of co-citation frequencies.

To lessen the problem of subjectivity, the three authors worked

independently to characterize each of the factors and then worked together, iteratively, to find the most satisfactory characterizations.

In this manner, we labeled the four factors as: (1)

Foundations and Applications; (2) Interrelationships with Other Theoretical Perspectives; (3) Issues of Governance Structure; and (4) Transformation Processes and Entrepreneurship. Factor 1 (Foundations and Applications) comprises what appears to be the structural center of the dynamic capabilities domain. It contains the greatest number of papers in our panel (29 out of 40), and includes those papers most identified with the concept of dynamic capabilities, including Teece et al. (1997), Eisenhardt and Martin (2000), Zollo and Winter

11 (2002), as well as Helfat (1997), Makadok (2001) and Winter (2003). It is weighted heavily towards the papers with the greatest number of citations, containing 17 of the 20 most cited papers and encompassing 90.6% of the citation total for the panel. This is indicative of the fact that these are truly foundational papers within the body of dynamic capabilities research.9 Papers loading on this factor are concerned largely with defining the construct, articulating the processes by which it evolves and is deployed, and exploring its application as well as its effects. The factor is revelatory of the key issues and concerns within the body of research on dynamic capabilities, including how they function and how they evolve (e.g. Helfat, 2000; Benner and Tushman, 2003; Helfat and Peteraf, 2003). It is suggestive of a pivotal role for managers, both in terms of their own such capabilities and in terms of enabling the creation, exercise, and maintenance of other types of dynamic capabilities (e.g. Carpenter, Sanders and Gregersen, 2001; Makadok, 2001; King and Tucci, 2002; Adner and Helfat, 2003). Factor 2 (Interrelationships with Other Theoretical Perspectives) seems best characterized in terms of the connections between dynamic capabilities and a key set of other theoretical perspectives in Management research. Among the papers loading on this factor, the relationship of dynamic capabilities to the Resource-Based View and its Penrosean roots is most strongly represented (e.g. Mahoney, 1995; Mahoney, 2001; Rugman and Verbeke, 2002). Other linking perspectives include Transaction Cost Economics (Mahoney, 2001), Learning Theory (Mahoney, 1995), Social Theory (Jarzabkowski, 2004), and Social Psychology (Dutton et al., 1997). This factor is also suggestive of the centrality of certain issues in dynamic capabilities research that are of particular concern to top managers. These include growth (Rugman and Verbeke, 2002), adaptation (Jarzabkowski, 2004), and change processes (Dutton et al., 1997). Like factor 1, this factor highlights some key themes within dynamic capabilities research,

12 including entrepreneurship, the role of management, innovation, and organizational learning (e.g. Mahoney, 1995; Hitt et al., 2001b). Among papers loading on factor 2, Agarwal et al. (2004) displays a negative load, indicating that it has a reverse co-citation profile with respect to the other papers in the group. This means that it is unlikely to be cited along with other papers in this group, and as such is not really a part of this group. Indeed, results from hierarchical cluster analysis show this paper, together with the contribution by Dutton et al. (1997), clustered together with the papers loading on factor 4 (Transformation Processes and Entrepreneurship), since they focus respectively on spin-outs (Agarwal et al., 2004) and on issue-selling performed by middle managers and processes of strategic change (Dutton et al., 1997). Factors 3 and 4 constitute only a minor part of the research on dynamic capabilities, each consisting of only two articles. Factor 3 (Issues of Governance Structure) forms a distinctive set, concerned with the determination of how economic activity is organized and with the location of firm boundaries. It echoes a theme found in factor 2, namely that dynamic capabilities links to both resource-based theory (Wernerfelt, 1984) and transaction cost economics (Williamson, 1975). Factor 4 (Transformation Processes and Entrepreneurship) includes the contribution by Ireland, Hitt and Sirmon (2003) dealing with strategic entrepreneurship, and the contribution by Uhlenbruck, Meyer and Hitt (2003) on organizational transformation - themes that are central to strategic management and to the notion of dynamic capabilities itself.

These papers also

highlight another theme of importance to the dynamic capabilities domain – that of seeking out and taking advantage of new opportunities.

This is related to themes of exploration and

13 capability exploitation found in some of the foundational papers (e.g. Luo, 2002; Benner and Tushman, 2003). One of the advantages of factor analysis with respect to other multivariate techniques is that it allows the analyzed objects to load on more than one factor, thus providing an indication of the breadth of the considered contributions. Indeed, the papers having significant but minor loadings on other factors can be seen as bridging different perspectives or subfields within the main research domain (McCain, 1990). In this respect, it is evident that factors 1 and 2 are deeply intertwined: 9 out of the 29 papers loading on factor 1 display a significant secondary loading (greater than 0.4) on factor 2, while 5 out of the 7 papers loading on factor 2 display a significant secondary loading on factor 1.

This characteristic becomes even clearer in

considering the results of the multidimensional scaling analysis, discussed in the next section. The Findings from Multidimensional Scaling Multidimensional scaling (MDS) provides a graphical representation of the similarity, or conceptual proximity, between the objects of our analysis - the panel of 40 papers analyzed (Kruskal and Wish, 1978).

Using Pearson’s correlation coefficients, MDS generates a bi-

dimensional map, shown in Figure 1, in which the position of each paper on the map depends on its relationship to the other papers in the panel, as perceived by the community of authors citing them.10 The closer papers appear on the map, the more likely they are to have similar intellectual content. - Insert Figure 1 about here MDS shows co-citation links among all of the contributions in the panel. Accordingly, papers positioned close to the (0, 0) point have been cited together with a higher number of the 40 contributions than papers positioned near the border of the map. The heterogeneous citation

14 profiles of papers near the center imply that they are linked to many different content areas, or schools of thought. Further, the greater the proximity between papers within a group, the higher the internal consistency of the set of documents, i.e. the tendency to cite these documents together. In this respect, it is worth noticing that most of the papers in Figure 1 tend to be positioned close to the center, as well as close to one another. This indicates the presence of strong ties among the majority of the papers, suggesting that dynamic capabilities research is still in its infancy and has not developed sufficiently for distinct topical streams to have been constituted. The lines on the map enclosing groups of papers show where the 4 factors identified earlier are positioned on the map. The position of factor 1 on the map is consistent with our interpretation of this factor as foundational, since it close to the center of the map. The majority of the papers in factor 1 are clustered very tightly together, indicating a similarity of co-citation profiles within the group. This suggests close links in terms of their underlying themes and central concerns. Moreover, there is an equally tight clustering between the majority of the papers loading on factor 2 and those of factor 1. The existence of close ties between these two factors was suggested by the prevalence of bidirectional secondary factor loadings found within these groups.

The visual representation of this offered by MDS shows the tightness and

significance of these connections. Their interpretation, however, requires a deeper and more fine-grained examination of these contributions. We return to this issue in the section on content analysis. The axes of the graph also require content-based interpretation. We used the position of the four factors on the map to help with this, but also examined the topical concerns of the papers at the poles of the axes. Our consensus-based interpretation is as follows.

15 The x-axis juxtaposes an internal perspective, focusing on matters inside the organization, with an external perspective, concerned more with markets and matters outside of the firm. This is illustrated on the left side of the map (External), by the position of Agarwal et al. (2004), which is on spin-outs, and of the factor 4 papers, both of which concern finding and seizing new opportunities. At the edge of the right side (Internal), we have papers on internal issues such as organizational learning (Zollo and Winter, 2002), absorptive capacity (Zahra and George, 2002), and rent creation mechanisms (Makadok, 2001). Fittingly, we find the majority of papers within the core of dynamic capabilities to be focused on internal matters. This is not unexpected, given the nature of dynamic capabilities and the need to understand the processes involved in creating, deploying, and maintaining them. The y-axis represents a continuum going from individual cognition and skills, with a stronger focus on the role played by managers and entrepreneurs (e.g., Dutton et al., 1997; Ireland et al., 2003), to organizational routines, with more attention to the organization, its competences, and routinized activities (e.g., Becker, 2004; Zollo and Singh, 2004), as we move from the top to the bottom of the graph. A more far-reaching interpretation of this graph is that it may suggest a possible development path for dynamic capabilities, as it expands beyond the limiting boundaries of its current clusters. Teece’s (2007) recent paper on the microfoundations of dynamic capabilities and his forthcoming special issue on a similar theme (Lovallo et al., Strategic Management Journal, forthcoming) suggest some movement in the direction of the individual manager. The attention given to the topics of growth, markets, and alliances in Helfat et al.’s (2007) recent book on dynamic capabilities suggests a potential for more research on the external.

16 CONTENT ANALYSIS: METHODS AND FINDINGS With bibliometric methods, we have been able to uncover some of the underlying patterns providing form and direction to the research on dynamic capabilities. We have uncovered four invisible colleges, while noting that the field remains focused on the most fundamental of concerns, regarding the nature and application of the construct. We have examined the network of relationships within the core of the field and found strong connections, as well as contentoriented dimensions providing structure to the field and indicating the direction that the research has begun to take. Content analysis allows us to deepen our understanding of these patterns. We use this method of analysis in three ways. We begin with a keyword analysis of central themes. Next, we examine a component of dynamic capabilities research that is critical to the field’s advancement: the definition of the concept. Lastly, we analyze the references cited by our core panel to explore their theoretical underpinnings. Keyword Analysis and Main Themes Keyword analysis allows us a more systematic way to check the validity of the themes that we have already uncovered.11 The results of this are found in Table 3, which displays all of the keywords used to describe the core papers (with the exception of the overall topic of dynamic capabilities). Note that only 25 papers out of 40 used keywords, since not all journals require them, for a total of 125 keywords used. The keywords are grouped in Table 3 into thematic areas and are listed along with the number of papers that provided each keyword. The classification resulted from a process of codification performed independently by the authors. We used Cohen’s Kappa (Cohen, 1960) to test for agreement among coders, since the data is nominal in form (e.g. diversification,

17 innovation, capability lifecycles), with no natural ordering. The computed value of k = 0.964 indicates high agreement. The table confirms the existence of themes identified earlier in the factor analysis, although there is little emphasis here on governance and transaction issues.12 The topical areas receiving the most emphasis were resources and capabilities, evolution and change, and innovation and technology. Other key themes include knowledge and learning, management and decision making, corporate strategy, multinational and global strategy, and firm performance. Of all of these themes, only firm performance was not identified earlier as a key issue. This analysis, then, adds value not only in its confirmatory role, but also by drawing attention to an important topical concern that was missed by the more mechanical review methods. - Insert Table 3 about here The Definition of the Construct The themes uncovered suggest central topical concerns and key areas of application within the body of research on dynamic capabilities. The concentration of high profile research efforts on certain themes may also suggest the way in which the field is being developed. They are one indicator of the underlying structure of an intellectual field. Themes exposed through citation analysis and content analysis of keywords, titles, and abstracts cannot, however, capture the essence of more complex debates and thorny issues occupying core researchers. One such issue, and arguably the most critical for the robust development of the field, is how to define dynamic capabilities. Due to the complexity of the construct, this has perhaps sparked the most debate and produced the most confusion. While Teece et al. (1997) first defined the term, their definition has been expanded and refined by subsequent authors.13 In the process, it has also been modified, producing conflicting understandings regarding critical issues,

18 including the nature of dynamic capabilities and their effect on organizational outcomes. Given the level of uncertainty about basic meanings and their organizational implications, it is not surprising that the field has been unable to break out of the concentrated topical realm represented by factor 1. Here, we bring a content analytical approach to this issue, in order to uncover the underlying structure of the debate, identify the main points of contention, and clarify understandings, in the hope of helping to move the debate forward. We employ a data analysis and interpretation procedure inspired by the ‘ladder of analytical abstraction’ described by Miles and Huberman (1994) for the interpretation of data in qualitative research. According to this approach, the researcher extracts text to work on, tries out coding categories to find a set that fits, identifies themes and trends in the data, and finally constructs an explanatory framework. As Miles and Huberman (1994, p. 91) explain, “the progression is a sort of ‘ladder of abstraction’ (Carney, 1990). You begin with a text, trying out coding categories on it, then moving to identify themes and trends, and then to testing hunches and findings, aiming first to delineate the ‘deep structure’ and then to integrate the data into an explanatory framework. In this sense we can speak of ‘data transformation’, as information is condensed, clustered, sorted, and linked over time (Gherardi and Turner, 1987).” Accordingly, first we extracted the definitions of dynamic capabilities from the papers of our panel. Out of 40 papers, 13 provide an original definition of dynamic capabilities. Of these, it is interesting to note that 4 are empirical papers, suggesting that some feel that more clarity is required in the definition for empirical work to proceed with confidence. Of the remaining papers, 9 quote explicitly a definition provided by others, while the rest do not provide an explicit definition, although in using the construct, they cite others who have defined it.14

19 Once we extracted the definitions, we coded them using thematic coding. That is to say, we broke down the text into manageable and meaningful content categories, grouping together data referring to similar themes under the same “umbrella” terms, allowing us to make comparisons among the different cases (Miles and Huberman, 1994). This process led us to the development of a summary model, shown in Figure 2, which shows 5 main issues over which there is debate and, in bifurcated form, alternative approaches to these issues. In constructing this model there was high agreement among coders, as indicated by a Cohen’s k value of 0.957. - Insert Figure 2 about here The summary model lays out the basic structure of the definitions of dynamic capabilities in terms of 5 structural components. It also exposes the nature of the debate over content within each structural component. It is interesting to note the polarization within each of the 5 content domains around two main approaches.15 We consider the meaning and importance of these divisions within the content domains of the definition next. The Nature The debate over the basic nature of dynamic capabilities concerns whether it is defined in terms of latent action, such as an ability, capacity, or enabling device, or in terms of constituent elements, as in a process, routine, or pattern. The first conception is distinguished from the second, in part, over the degree of observability. Action that is latent cannot be observed until called into use, while constituent elements have a more concrete and observable form (Helfat et al., 2007). This has implications for the empirical identification of dynamic capabilities and suggests some of the challenges involved.

But as Helfat et al. (2007, p. 37) observe,

“Approaching research on dynamic capabilities from a process perspective (may) provide the needed link to action.”

20 The Agent, The Action, The Object of the Action The divisions in content within the three structural components in the center of Figure 2, i.e. Agent, Action, Object, suggest differences in emphasis more than arenas of debate. With respect to the issue of agency, our content analysis of definitions mirrors what was concluded from the map produced by MDS, showing that the research splits with respect to an emphasis on the organization versus an emphasis on the managerial role. These are not incompatible issues, however, and there is no debate over the fact that both the organization and the individual manager serve as important loci of action. The numbers provided in the figure show, however, that the agency of organizations is receiving greater attention at present. Similarly, whether dynamic capabilities act upon (existing or new) (capabilities or opportunities) is not matter of debate but rather an indication of researcher orientation. The Aim A more critically divided issue concerns the aim of dynamic capabilities and the likelihood of realizing that aim.

That it remains a divided issue, despite its criticality, is

suggestive of the complexities and subtleties involved. It is also indicative of differences that may be harder to reconcile, deriving from the mental models, disciplinary-based viewpoints, and theoretical orientations of the researchers driving the debate. We explore this issue in the next section of the paper. While the general themes of addressing new market needs, seizing opportunities, adapting to changing conditions, and competing over time are found throughout our sample, this is not true of the issue of organizational performance.

As our examination of keywords

uncovered, performance is a common theme and yet it is not a universal theme. Our results here simply confirm what the keywords search revealed – that there is variation with respect to the

21 kind of performance indicators associated with dynamic capabilities.

These range from

improving effectiveness (e.g. Zollo and Winter, 2002), to achieving a competitive advantage (e.g. Zahra and George, 2002), to capturing rents (e.g. Luo, 2002).16 The real debate, however, lies beneath the surface of the results captured in Figure 2. The central issues are twofold.

The first question is whether dynamic capabilities can lead to

competitive advantage or whether they can only produce competitive parity. This debate was sparked by Eisenhardt and Martin (2000, p. 1108), who characterized dynamic capabilities as best practices, noting that while dynamic capabilities may be “idiosyncratic in their details”, they also exhibit “commonalities” that make them equally effective across firms. As examples of best practice, then, they cannot be a source of competitive advantage. This view contrasts sharply with the position of Teece et al. (1997, p. 516) who linked dynamic capabilities directly to the notion of competitive advantage, asserting that dynamic capabilities “reflect an organization’s ability to achieve new and innovative forms of competitive advantage”. The second question is over the strength of the relationship between dynamic capabilities and competitive advantage. At one end of the spectrum of views, there are those who hold that dynamic capabilities necessarily provide firms with a competitive advantage. This, however, is not a matter for debate, but only a matter of confusion, in that it produces the same tautology of which the resource-based view has been accused (e.g. Bromiley and Fleming, 2002). Whether a specific dynamic capability is capable of creating value, providing a competitive advantage, or generating rents depends on a set of conditions that Helfat et al. (2007) describe concisely. Advancing the level of understanding within the field concerning these issues depends on a more uniform use and better understanding of various performance metrics (Peteraf and Barney, 2003).

22 Cited Reference Analysis and Theoretical Roots The differences we observe with regard to the nature and effects of dynamic capabilities may well be due to the different disciplinary lenses and theoretical perspectives being brought to bear on these questions. This, in turn, may be an expression of the heterogeneity within the Management field and of the fact that dynamic capabilities have attracted a wider array of participants than most research topics. Differences in training and theoretical orientation lead legitimately to differences in viewpoint and understandings. More awareness and appreciation of what is driving the differences in point of view may eliminate some confusion, encourage more fruitful debate, and allow the field to advance in a more straightforward fashion. To this end, we conducted a content analysis of the references cited by our panel of 40 papers, in order to trace the core papers back to their theoretical roots. Beginning with a total of 2,300 references, we narrowed these down to the top-cited references: those that were cited by at least 5 papers in our core panel.17 This criterion led to a set of 61 articles and books highly cited by the core papers of the dynamic capabilities literature. Eliminating papers focused directly on dynamic capabilities reduced the set further to 56 publications.18 These are displayed in Table 4, along with the number of times each was cited by our core panel. - Insert Table 4 about here What is immediately apparent from a perusal of this list is that it contains a set of publications that are widely considered the founding papers of a set of theoretical perspectives familiar to researchers in Management. There are six such perspectives represented, namely: Evolutionary Economics (Nelson and Winter, 1982), the Resource-Based View (Wernerfelt, 1984), the Knowledge-Based View (Kogut and Zander, 1992), Transaction Cost Economics

23 (Williamson, 1975), Behavioral Theory (Cyert and March, 1963), and the Positioning View (Porter, 1980).19 To assess the relative influence of these different theories/views among the core panel, we classified the remaining references in Table 4 in terms of the extent to which they were associated with these six founding references.

To accomplish this, the three authors

independently coded the content of the titles, keywords, and abstracts of each remaining reference, as well as the reference lists of these papers, and classified the publications accordingly. The three resulting classification lists were then compared iteratively until an agreement was reached for each remaining reference.20 The results are displayed in Table 5. Note that several remaining references did not fit our classification schema, and hence are not displayed in this table.21 - Insert Table 5 about here One indicator of the relative influence of these different theoretical perspectives in dynamic capabilities research is simply the number of times the founding publications were cited by our panel of 40 core papers. From this, the strong influence of Evolutionary Economics becomes clear, matched only by that of the Resource-based View (23 citations each). This is an interesting result; although the influence of evolutionary economics was suggested more indirectly by the MDS map, the extent of its influence on the development of dynamic capabilities had not been so apparent. Less strongly represented but still influential, consistent with our prior results, is the Knowledge-based View; its founding paper was cited directly by over a third of the core papers (14/40). A fourth of the papers cite the founding book for Transaction Cost Economics, while just 15% cite the books representing the Behavioral View and the Positioning View.

24 A second indicator is the number of citations to related references – those associated with or based on the founding work. This indicator provides weaker evidence regarding the influence of the founding work, since it is a more indirect measure.22 Moreover, there is a great deal of variation among the references included concerning the closeness of their connections to the founding work. Some, like Grant (1996) or Barney (1991), are perfect surrogates for the founding work.

Others required more judgment to be classified, since they have deep

connections to multiple perspectives (e.g. Conner and Prahalad, 1996; Helfat and Raubitschek, 2000; Winter and Szulanski, 2000).

Others have only a weak association with a given

perspective and were classified only on the basis of their reference lists. What these citation numbers may reveal more clearly, however, is something about the orientation of the researchers citing the references, i.e. the authors of the core papers on dynamic capabilities. In our experience, researchers tend to cite those articles with which they are most familiar. Reference lists, then, are suggestive of a researcher’s training, expertise, disciplinary affiliation and focal interests.23 While authors may often cite founding references to well-known theoretical perspectives, citing a variety of the references associated with a given perspective requires deeper knowledge of the work in that area and is thus a better indicator of training, disciplinary orientation, and expertise. Similarly, citing a greater number of such references indicates more strongly the focus of the author’s paper and their focal interests. In this respect, the distribution of the citations to references related to the founding works is quite revealing. While the emphasis given to the Resource-Based View is hardly surprising, it is thought-provoking that the second most active area for citations is the Behavioral View of the firm (Cyert and March, 1963).

This is particularly interesting, given the fact that some

proponents of this view (i.e. Bromiley, 2004) consider it to be in stark opposition to the

25 Resource-Based View, which they criticize for its economics orientation and equilibrium-based logic (e.g. Bromiley & Fleming, 2002). In attending to such issues as organizational learning, ‘problemistic’ search, and memory, the Behavioral View has a greater affinity to the KnowledgeBased View, which is also strongly represented. In reflecting upon the implications of these results regarding the roots of dynamic capabilities, several things come to mind. First, the breadth of the theoretical roots suggests the richness and complexity of the research domain. It also suggests a set of theoretical resources that scholars can continue to draw upon in their efforts to develop the theory in a more concrete and robust manner. Second, the dominance of the direct influence of Evolutionary Economics, on the one hand, and the Resource-Based View, on the other hand, provides an indicator of revealed preferences by scholars regarding the most promising theories for developing the dynamic capabilities construct further. That these are complementary theories, as suggested by their role in developing a Dynamic Resource-Based View (e.g. Helfat and Peteraf, 2003), is also a promising sign that the research may develop along logically consistent and more unified lines. The most interesting result, however, indicates a more fundamental division within the dynamic capabilities research community, found by probing more deeply. The strong affinity for Behavioral Theory is revealing, particularly in light of the concerns raised by some proponents of the Behavioral View (i.e. Bromiley, 2004) over perceived incompatibilities with the ResourceBased View. The strong connection to the Knowledge-Based View invokes similar concerns, given the opinion by some that the more dynamic applications of the Resource-Based View are in opposition to the part concerned with sustainable competitive advantage (e.g. Schulze, 1994).

26 This may help explain the bifurcated content domains within the definition of dynamic capabilities and why it is taking so long to unify these domains. The Resource-Based View of competitive advantage is rooted in competitive strategy, with its focus on competitive dynamics and their implications for firm performance. The Behavioral View of the firm is concerned with broader organizational objectives, such as growth; with its assumption of satisficing behavior, it is less concerned with competitive outcomes.

It is no wonder that firm performance is

acknowledged as a key theme in only 20% of the core literature on dynamic capabilities, as we have found.

This helps explain, as well, some of the divide over the nature of dynamic

capabilities, since competitive strategy has little to say about processes, routines, or patterns, which are key themes of the Behavioral View. The resolution of these fundamental differences is, of course, another matter. Given positions on fundamentals that are not only divided but discordant, it may be difficult to find a route to reconciliation. The sharp debate between Arend & Bromiley (2009) and Helfat & Peteraf (2009) over the value of continuing research on dynamic capabilities is suggestive of the extent of this problem. Still, recent contributions (e.g. Kay, 2008: 1223) have shown that, “while it is important to separate out these issues for analytical purposes”, the resource-based view and the behavioral view of the firm offer complementary rather than competing perspectives, since they are concerned with different aspects of the same overall problem. Hence by exposing the underlying source of such tensions, our findings may help researchers to understand the source of their differences, communicate more clearly with those holding different views, resolve misunderstandings and terminological ambiguities, realize the potential for complementary understandings, and find a more effective way forward.

27 CONCLUSIONS In this paper, we have taken on the challenge of detecting and deciphering the pattern of evolution of the rapidly emerging domain of dynamic capabilities. In this respect, we have tried to shed light on some of the difficult yet crucial questions posed by ten years of research on the topic. To this aim, we employed a combination of techniques that helped us make sense of how the literature in this area is developing and taking shape. Our study is subject to the limitations of bibliometric analysis, which is typically conservative in nature, since citations of published articles are a lagging indicator of a contribution’s influence (Brown and Gardner, 1985).24 In addition, our method ignores the influence of book chapters and books (e.g. Fujimoto, 2000; Helfat et al., 2007). It suffers as well from the limitations of content analysis, with its primary problem of coding subjectivity (Duriau, Reger and Pfarrer, 2007). To address the first issue, we included papers with citation numbers that exceeded the average for articles on dynamic capabilities. Since this literature is relatively young, this allowed the influence of newer publications to surface, while still providing sufficient time for evidence to accumulate. With respect to the latter issue, the problem was mitigated by the limited need for judgment in parts of this analysis (e.g. keyword counts). Where the problem was likely to be greater, we used standard methods to address this. By unveiling the patterns underlying dynamic capabilities research, we contribute to the future development of the construct in a number of ways. As a research domain still in its early stages of development, it remains tightly focused on foundational issues, as we have shown. Our research suggests some ways to expand beyond these issues. By mapping the network of topical connections and identifying content-oriented dimensions, we find potential avenues of expansion

28 and enrichment.

By uncovering central themes within the research, we find key areas of

application. These provide some clues not only about where the concept is likely to have the greatest utility, but also about the kinds of settings where dynamic capabilities are most likely to be found. This type of knowledge is critical for empirical work, since investigating the existence and deployment of dynamic capabilities depends upon looking in the right places. Our findings regarding the multiplicity of definitions of dynamic capabilities suggest there may be something preventing the research from expanding beyond the tightly-wound cluster that characterizes it to date. By deconstructing the definitions, we are able to locate the sources of disagreement within different content domains and differentiate between those that signify only differences in emphasis from those signifying real difference of opinion. Better knowledge of the structural components of these varying definitions and better understanding the precise nature and locus of disagreement may help the field move more rapidly toward consensus on this critical issue. It may help resolve some of lexical ambiguity (Kay, 2008) that has characterized this research domain. Our exploration of the theoretical roots of the dynamic capabilities literature reveals a heterogeneous theoretical basis for the construct. This suggests a rich set of theories to draw upon in building a clearer, stronger, and more robust theoretical foundation for dynamic capabilities research, but it also suggests the complexity of the task. On the one hand, we find evidence of a strong revealed preference for grounding dynamic capabilities in two complementary perspectives - Evolutionary Economics and the Resource-Based View. On the other hand, we find evidence of tensions at a deeper level between theoretical influences that may be less compatible - the Resource-Based View, in opposition to the Behavioral View and the Knowledge-Based View. These tensions may explain not only why dynamic capabilities

29 research continues to struggle over fundamentals, but also why there exists such radically different views over the connection between dynamic capabilities and competitive advantage. By exposing the underlying intellectual structure of the field and its theoretical roots, our findings may promote a greater understanding of differences, the resolution of conflict, the development of a clearer and more uniform conception of dynamic capabilities, and a research agenda capable of exploiting the complementarities available from a combination of perspectives.

30 FOOTNOTES 1

According to preliminary analysis we performed on the ISI Web of Knowledge database.

2

For journals without keywords, Thomson ISI uses KeyWords Plus®, which are index terms

created by Thomson Reuters from significant, frequently occurring words in the titles of an article's cited references. 3

While chapters such as Teece and Pisano (1994) and working papers on dynamic capabilities

existed before 1995, no journals included in the ISI database published articles on this topic prior to this date. 4

Indeed, we found an additional 53 articles on dynamic capabilities that were not classified

under the Business or Management categories in the Thompson ISI Web of Science database. 5

Note that this list omits influential books, monographs, and book chapters, since these types of

publications are not readily extracted from the ISI Web of Science database. 6

We treat the cells of the main diagonal (i.e., the number of times a paper has been cited together

with itself) as missing values (White and McCain, 1998). 7

Principal Component Analysis is based on seeking a linear combination of variables such that

the maximum variance is extracted from the variables. It is by far the most common form of factor analysis and it is generally preferred for purposes of data reduction (translating variable space into optimal factor space). Other methods (such as unweighted least squares, generalized least squares, maximum likelihood, principal axis factoring, alpha factoring and image factoring) are less used, except for principal axis factoring which is better suited for causal modeling. 8

In the choice for rotation methods, orthogonal solutions such as varimax (as used in Acedo et

al., 2006) should be preferred when one expects factors to be theoretically independent, whereas oblique rotations such as oblimin (as used in Nerur et al., 2008) should be preferred in the

31

opposite case. We chose the varimax method because we did not want to make an assumption of theoretical dependence. Second, this choice had no impact on the results, which were consistent in terms of factor loading regardless of which types of analysis we employed. However, the component correlation matrix displayed with oblimin rotation showed poor correlation among the four factors, providing further support for our choice of the varimax method. 9

They received 62% of the citations for all the 371 articles dealing with dynamic capabilities

that were published prior to 2008 in any of the business and management journals included in the Thomson ISI Web of Science database. 10

The Kruskal's Stress test result of 0.10708 indicates good fit (McCain, 1990).

This is

confirmed by an R-squared (RSQ) value of 0.98623, where RSQ is the proportion of variance of the scaled data in the matrix that is accounted for by their corresponding distances. 11

We also performed an analysis of title words. The results were consistent, with the ranking led

by capability- and resource-related words, along with words related to dynamism and learning. Words concerning transactions, entrepreneurship, managers, innovation, and corporate strategy followed in importance. We used the abstracts of papers as a further check on our identification of themes. 12

13

Title word analysis, however, revealed a stronger concern with these issues. While definitions of dynamic capabilities were published prior to theirs (e.g. Teece and

Pisano, 1994), Teece et al. (1997) preceded these in working paper form, which was available in 1989. 14

The definitions quoted explicitly were those of Teece and Pisano (1994, p. 541), Teece et al.

(1997, p. 516), and Eisenhardt and Martin (2000, p. 1107).

32

15

To a degree, there is also some division of opinion within the subcategories listed here, such as

whether dynamic capabilities are better categorized as routines or processes. In the coders’ judgment, however, these distinctions are less fundamental than those highlighted by the model. 16

Note that achieving a competitive advantage and capturing rents are not one and the same. See

Coff (1999) and Peteraf and Barney (2003) on this point. 17

This cut-off implies that at least 1 out of every 8 papers in the panel cited a given reference.

This choice was driven by an interest in including only the very top cited references. The results at this cut-off level are consistent with those using a cut-off minimum of 4 citations. 18

Four of these were part of our core panel. The 5th (Teece and Pisano, 1994) is closely related

to Teece et al., 1997. 19

While Schumpeter (1934; 1942) and Chandler (1962) are classics works known for new and

influential ideas, they are not linked to readily identifiable theoretical perspectives. And while Penrose (1959) is often referred to as the foundation of the RBV, this work did not actually launch this perspective, or give it its name. 20

The value for Cohen’s k = 0.607, indicating substantial agreement.

21

Besides the two classics mentioned, these include Teece, 1986; Milgrom and Roberts, 1990;

Clark and Fujimoto, 1991 and McGrath and MacMillan, 2000. 22

An absence of related references, however, provides stronger evidence of a negative kind. It

suggests that references to the founding work should be discounted. Without additional support from related references, it is unlikely that a particular perspective provides significant theoretical support.

Here, the absence of any references related to Porter (1980) suggests that this

perspective does not underlie dynamic capabilities research in any meaningful way.

33

23

An alternative hypothesis is that researchers tend to cite articles that have been cited by others

whose work and reputation they know and trust. We view this as also indicative of training, disciplinary orientation, and interest domain, although one step removed. Whether our suppositions are correct cannot be resolved here, but could be addressed more directly in future research, possibly through a more micro-level qualitative analysis. (We are grateful to a referee for suggesting these points.) 24

Previous literature has thoroughly discussed other possible limitations related to the use of

citations, such as perfunctory mentions, citations that are incorrectly employed, and citations aimed at pleasing potential reviewers (see, for instance, Baumgartner and Pieters, 2003). Still, if compared to alternative techniques (such as key informants’ judgments), citations are less prone to systematic biases in providing an objective assessment of the influence of publications or authors (Baumgartner and Pieters, 2003).

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42 TABLES AND FIGURES Table 1 The Intellectual Core of Dynamic Capabilities Research* References Teece, Pisano and Shuen. Strategic Management Journal, 1997. 18 (7) Eisenhardt and Martin. Strategic Management Journal, 2000. 21 (11) Zahra and George. Academy of Management Review, 2002. 27 (2) Zollo and Winter. Organization Science, 2002. 13 (3) Amit and Zott. Strategic Management Journal, 2001. 22 (7) Makadok. Strategic Management Journal, 2001. 22 (5) Helfat. Strategic Management Journal, 1997. 18 (5) Winter. Strategic Management Journal, 2003. 33 (2) Mahoney. Journal of Business Research, 1995. 24 (10) Benner and Tushman. Academy of Management Review, 2003. 28 (2) Helfat and Peteraf. Strategic Management Journal, 2003. 24 (10) Wright, Dunford and Snell. Journal of Management, 2001. 27 (6) Danneels. Strategic Management Journal, 2002. 23 (12) Rindova and Kotha. Academy of Management Journal, 2001. 44 (6) Knight and Cavusgil. Journal of International Business Studies, 2004. 35 (2) Dutton, Ashford, O’Neill, Hayes and Wierba. Strategic Management Journal, 1997. 18 (5) Teece. Long Range Planning, 2000. 33 (1) Galunic and Eisenhardt. Academy of Management Journal, 2001. 44 (6) Carpenter, Sanders and Gregersen. Academy of Management Journal, 2001. 44 (3) Hitt, Ireland, Camp and Sexton. Strategic Management Journal, 2001b. 22 (7) Helfat. Strategic Management Journal, 2000. 21 (11) Madhok. Strategic Management Journal, 2002. 23 (6) King and Tucci. Management Science, 2002. 48 (2) Aragon-Correa and Sharma. Academy of Management Review, 2003. 28 (1) Uhlenbruck, Meyer and Hitt. Journal of Management Studies, 2003. 40 (2) Zott. Strategic Management Journal, 2003. 24 (2) Jarzabkowski. Organization Studies, 2004. 25 (4) Vohora, Wright and Lockett. Research Policy, 2004. 33 (1) Rosenbloom. Strategic Management Journal, 2000. 21 (11) Miller. Strategic Management Journal, 2003. 24 (10) Becker. Industrial and Corporate Change, 2004. 13 (4) Jacobides and Winter. Strategic Management Journal, 2005. 26 (5) Agarwal, Echambadi, Franco and Sarkar. Academy of Management Journal, 2004. 47(4) Rugman and Verbeke. Strategic Management Journal, 2002. 23 (8) Ireland, Hitt and Sirmon. Journal of Management, 2003. 29 (6) Zollo and Singh. Strategic Management Journal, 2004. 25 (13) Adner and Helfat. Strategic Management Journal, 2003. 24 (10) Deeds, DeCarolis and Coombs. Journal of Business Venturing, 2000. 15 (3) Luo. Organization Science, 2002. 13 (1) Mahoney. Journal of Management, 2001. 27 (6)

*Includes only articles published in Management journals prior to 2008, available in the Thomson-ISI Web of Science database.

Times cited 1193 470 218 206 119 103 93 82 81 81 76 75 59 50 49 48 48 47 47 44 38 38 38 38 34 31 31 31 29 29 27 27 26 25 24 24 23 22 22 21

43 Table 2 Factor Analysis*

Benner and Tushman, 2003 Zahra and George, 2002 Galunic and Eisenhardt, 2001 Danneels, 2002 Rindova and Kotha, 2001 Vohora, Wright and Lockett, 2004 Rosenbloom, 2000 Winter, 2003 Zott, 2003 Zollo and Winter, 2002 Teece, Pisano and Shuen, 1997 King and Tucci, 2002 Adner and Helfat, 2003 Helfat, 1997 Helfat and Peteraf, 2003 Luo, 2002 Knight and Cavusgil, 2004 Helfat, 2000 Eisenhardt and Martin, 2000 Amit and Zott, 2001 Aragon-Correa and Sharma, 2003 Deeds, DeCarolis and Coombs, 2000 Makadok, 2001 Becker, 2004 Carpenter, Sanders and Gregersen, 2001 Miller, 2003 Teece, 2000 Zollo and Singh, 2004 Wright, Dunford and Snell, 2001 Dutton, Ashford, O’Neill, Hayes and Wierba, 1997 Rugman and Verbeke, 2002 Mahoney, 2001 Agarwal, Echambadi, Franco and Sarkar, 2004 Jarzabkowski, 2004 Hitt, Ireland, Camp and Sexton, 2001b Mahoney, 1995 Jacobides and Winter, 2005 Madhok, 2002 Uhlenbruck, Meyer and Hitt, 2003 Ireland, Hitt and Sirmon, 2003

Factor 1 0.953 0.949 0.949 0.943 0.931 0.929 0.921 0.919 0.907 0.894 0.893 0.892 0.887 0.866 0.862 0.856 0.843 0.831 0.828 0.827 0.816 0.812 0.795 0.792 0.770 0.746 0.732 0.719 0.693

Factor 2

Factor 4

0.485 0.491 0.523 0.471 0.474 0.539 0.542 0.477 0.542

0.608 0.476 0.492

0.580 0.874 0.855 0.785 -0.776 0.657 0.634 0.604

0.487

0.465

0.434 0.443

Factor 3

0.543 0.489 0.894 0.704 -0.416

* Extraction method: Principal Component Analysis with Varimax Rotation. Variance explained: 94.1%. Only factor loadings higher than 0.4 are reported.

0.942 0.692

44 Table 3 Some Statistics about Keywords* Keywords

TA Keywords

Management & DecisionResources 14 Making resource-based theory/view 7 cognition resources Penrose resources and capabilities

5 1 1

Dynamic Capabilities 11 dynamic capabilities 8 dynamic capability dynamic-capability view

2 1

governance leadership management practices Middle managers problem solving top management

Evolution & Change

TA Keywords 7 1 1 1 1 1 1 1

13

capabilities

8 5

(organizational) evolution (organizational) change path dependency

4 3 2

capability lifecycles competences firm competences

1 1 1

dynamic markets high-velocity markets organizational inertia

1 1 1

organizational routines

1

Innovation & Technology innovation disk drives niche innovation product innovation R&D technological change technology transfer

11 5 1 1 1 1 1 1

Capabilities

Knowledge & Learning organizational learning knowledge knowledge articulation knowledge assets knowledge codification learning learning by doing

8 2 1 1 1 1 1 1

Entrepreneurship entrepreneurs strategic entrepreneurship

2 1 1

TA

Corporate Strategy M&A

8 2

transaction costs corporate effects diversification firm boundaries post-acquisition integration

2 1 1 1 1

Multinational & Global Strategy born global firms early adopters of internationalization foreign market global strategy market entry multinationals

6 1 1 1 1 1 1

Networks & Interfirm cooperation

2

Firm Performance competitive advantage rents economic profit firm performance value creation wealth creation

8 2 2 1 1 1 1

Other

20

* Cohen’s kappa for inter coder agreement: 0.964. Note: TA refers to the number of papers in the collection adopting the keyword. Other includes: cost-benefit; experience; firm asymmetries; human capital; image risk; institutional; issue selling; organization design; organization theory; recursiveness; simulation; social capital; social theory; strategy (3 keywords); structure of production; task frequency; task heterogeneity; universities.

45 Table 4 Top cited references* # 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28

Reference Nelson and Winter, 1982 Wernerfelt, 1984 Barney, 1991 Penrose, 1959 Dierickx and Cool, 1989 Cohen and Levinthal, 1990 Kogut and Zander, 1992 Amit and Schoemaker, 1993 Grant, 1996 Henderson and Cockburn, 1994 Szulanski, 1996 Leonard-Barton, 1992 Levitt and March, 1988 Lippman and Rumelt, 1982 Peteraf, 1993 Prahalad and Hamel, 1990 Williamson, 1975 Barney, 1986 Schumpeter, 1934 Brown and Eisenhardt, 1997 Henderson and Clark, 1990 Mahoney and Pandian, 1992 March, 1991 Rumelt, 1984 Tripsas and Gavetti, 2000 Liebeskind, 1996 Priem and Butler, 2001 Zander and Kogut, 1995

TC 23 23 21 20 18 16 14 13 11 11 11 10 10 10 10 10 10 9 9 8 8 8 8 8 8 7 7 7

# 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56

Reference Conner and Prahalad, 1996 Cyert and March, 1963 Helfat and Raubitschek, 2000 Huber, 1991 Hitt, Bierman, Shimizu and Kochhar, 2001a Leonard-Barton, 1995 Porter, 1980 Prahalad and Bettis, 1986 Rumelt, 1991 Teece, 1982 Teece, 1986 Williamson, 1985 Winter, 1987 Chandler, 1962 Clark and Fujimoto, 1991 Coase, 1937 Cohen and Bacdayan, 1994 Collis, 1991 Eisenhardt, 1989 Karim and Mitchell, 2000 Lane and Lubatkin, 1998 Levinthal and March, 1993 March and Simon, 1958 McGrath and MacMillan, 2000 Milgrom and Roberts, 1990 Nonaka and Takeuchi, 1995 Schumpeter, 1942 Winter and Szulanski, 2000

*Consisting of the references cited by at least 5 of the papers in the collection. Note: TC refers to the number of papers in the collection citing the paper.

TC 6 6 6 6 6 6 6 6 6 6 6 6 6 6 5 5 5 5 5 5 5 5 5 5 5 5 5 5

46 Table 5 Theoretical Roots of the Dynamic Capabilities Work*

Core work Citations received Related references

Citations received

Evolutionary Economics

Resource-Based View

Knowledge-Based View

Transaction Cost Economics

Behavioral Theory

Positioning View

Nelson and Winter, ‘82

Wernerfelt, ‘84

Kogut and Zander, ‘92

Williamson, 75

Cyert and March, ‘63

Porter, ‘80

23

23

14

10

6

6

Helfat and Raubitschek, ‘00 Winter, ‘87 Karim and Mitchell, ‘00 Winter and Szulanski, ‘00

Barney, ‘91 Penrose, ‘59 Dierickx and Cool, ‘89 Amit and Schoemaker, ‘93 Henderson and Cockburn, ‘94 Lippman and Rumelt, ‘82 Peteraf, ‘93 Prahalad and Hamel, ‘90 Barney, ‘86 Mahoney and Pandian, ‘92 Rumelt, ‘84 Priem and Butler, ‘01 Hitt et al., ‘01a Rumelt, ‘91 Collis, ‘91

Teece, ‘82 Williamson, ‘85 Coase, ‘37

Cohen and Levinthal, ‘90 Levitt and March, ‘88 Brown and Eisenhardt, ‘97 March, ‘91 Tripsas and Gavetti, ‘00 Huber, ‘91 Prahalad and Bettis, ‘86 Cohen and Bacdayan, ‘94 Eisenhardt, ‘89 Lane and Lubatkin, ‘98 Levinthal and March, ‘93 March and Simon, ‘58

22

162

17

87

Grant, ‘96 Szulanski, ‘96 Leonard-Barton, ‘92 Henderson and Clark, ‘90 Liebeskind, ‘96 Zander and Kogut, ‘95 Conner and Prahalad, ‘96 Leonard-Barton, ‘95 Nonaka and Takeuchi, ‘95

71

* Cohen’s kappa for inter coder agreement: 0.607 Note: Related references are ranked according to the number of citations received by papers in the collection.

0

47 Figure 1 Multidimensional Scaling INDIVIDUAL COGNITION and SKILLS

F4

EXTERNAL

INTERNAL

F1 F2

F3

ORGANIZATIONAL ROUTINES

C1 C2 C3 C4 C5 C6 C7 C8 C10 C11 C12 C13 C14 C15

Factor 1 Teece, Pisano and Shuen, 1997 Eisenhardt and Martin, 2000 Zahra and George, 2002 Zollo and Winter, 2002 Amit and Zott, 2001 Makadok, 2001 Helfat, 1997 Winter, 2003 Benner and Tushman, 2003 Helfat and Peteraf, 2003 Wright, Dunford and Snell, 2001 Danneels, 2002 Rindova and Kotha, 2001 Knight and Cavusgil, 2004

C17 C18 C19 C21 C23 C24 C26 C28 C29 C30 C31 C36 C37 C38 C39

Teece, 2000 Galunic and Eisenhardt, 2001 Carpenter, Sanders and Gregersen, 2001 Helfat, 2000 King and Tucci, 2002 Aragon-Correa and Sharma, 2003 Zott, 2003 Vohora, Wright and Lockett, 2004 Rosenbloom, 2000 Miller, 2003 Becker, 2004 Zollo and Singh, 2004 Adner and Helfat, 2003 Deeds, DeCarolis and Coombs, 2000 Luo, 2002

C9 C16 C20 C27 C33 C34 C40 C22 C32 C25 C35

Factor 2 Mahoney, 1995 Dutton, Ashford, O’Neill, Hayes and Wierba, 1997 Hitt, Ireland, Camp and Sexton, 2001b Jarzabkowski, 2004 Agarwal, Echambadi, Franco and Sarkar, 2004 Rugman and Verbeke, 2002 Mahoney, 2001 Factor 3 Madhok, 2002 Jacobides and Winter, 2005 Factor 4 Uhlenbruck, Meyer and Hitt, 2003 Ireland, Hitt and Sirmon, 2003

Note: The circles on the map were added by the authors to show where the 4 factors identified in Table 2 are positioned on the map.

48 Figure 2 Defining Dynamic Capabilities: the Emerging Evidence*

THE AGENT THE NATURE - ability/capacity/ enabling device (8) OR - process/routine/ pattern (6)

- managers (4) OR - organizations/firms (10)

THE AIM

THE ACTION - act upon existing (9) OR - develop new (10)

THE OBJECT OF THE ACTION

- address new needs/opportunities (2) - adapt to/achieve congruence with changing conditions (7) - compete over time (1) AND ?? - achieve competitive advantage /create value/improve effectiveness (5) - earn/capture rents (2)

- competences/capabilities/ - internal resources (11) - external OR - markets/ - new opportunities (3) - existing

* Cohen’s kappa for inter coder agreement: 0.957 Note: the numbers in parenthesis refer to the number of papers in the collection using each of the approaches within the definitional options. Some papers use more than one single approach, and hence the numbers do not necessarily sum up to 14 (i.e., the number of definitions coded).