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The Dynamic Capability View in StrategicManagement: A Bibliometric Review
Rick Vogel and Wolfgang H. Güttel1
Chair of Public Management & Public Policy, Zeppelin University, D-88045 Friedrichshafen, Germany, and 1Institute of Human Resource and Change Management, Johannes Kepler-University, A-4040 Linz, Austria
Corresponding author email: [email protected]
The dynamic capability view (DCV) is one of the most vibrant approaches to strategicmanagement. In this study, the extant literature published between 1994 and 2011 is
analysed, using bibliometric methods in order to explore the scope of this approach anddetect current research priorities. For this purpose, the method of bibliographic cou-pling is introduced in management research, which shifts the focus of analysis from
past traditions to current trends. Several clusters of thematically related research areextracted from bibliographic networks, which represent interconnected yet distinct
subfields of inquiry within the DCV. The core cluster of the current DCV, whichvisualizes this research field’s nascent but fragile identity, focuses on learning andchange capabilities and relates them to firm performance, thus merging aspects of
organization theory and strategic management. In addition, several peripheral clustersof research are identified, which reflect a parallel process of differentiation in theoverall field. Both trends, i.e. of integration and differentiation, attest to the emanci-
pation of the DCV as a distinct approach to strategic management. However, the DCVstill lacks consensual concepts that allow comparisons of empirical studies and advance
the theoretical understanding of dynamic capabilities. In the light of the above, someimplications of this analysis for further research are discussed.
Introduction
The dynamic capability view (DCV) has become one
of the most vibrant topics in the domain of strategic
management, and has even been referred to as ‘the
new touchstone firm-based performance-focused
theory’ (Arend and Bromiley 2009, p. 75). Since the
DCV first appeared in scientific literature (Teece
et al . 1990), several hundred research publications
have elaborated on this approach (Di Stefano et al .
2010). Another indication that the DCV is maturing
into an established perspective is the recent publica-tion of the first introductory textbooks (Helfat et al .
2007; Teece 2009). The most seminal papers on
dynamic capabilities (Eisenhardt and Martin 2000;
Helfat 1997; Teece et al . 1997; Zollo and Winter
2002) are among the highest cited in the broader
array of strategic management publications (Furrer
et al . 2008). In these articles, dynamic capability has
been introduced, for instance, as ‘the firm’s ability to
integrate, build and reconfigure internal and external
competences to address rapidly changing environ-
ments’ (Teece et al . 1997, p. 516) or as ‘the firm’s
processes that use resources – specifically the proc-
esses to integrate, reconfigure, gain and release
resources – to match or even to create market
change’ (Eisenhardt and Martin 2000, p. 1107). Con-
sidering that the responsiveness of a firm’s resource
stock to increasingly turbulent environments is asso-
ciated with competitive advantage, dynamic capa-
bilities are of inherent strategic relevance to a firm.However, Eisenhardt and Martin (2000) and Zollo
and Winter (2002) emphasize that firms also need
dynamic capabilities in markets characterized by
lower rates of change, in order to keep pace with
competitive dynamics.
The fast-growing number of publications on
dynamic capabilities and the considerable theoretical
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DOI: 10.1111/ijmr.12000
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and methodological variety within this body of
literature make it difficult, if not impossible, to keep
track of how this research field evolves. Recent quali-
tative reviews and assessments of the extant literature
offer some useful orientation in this regard (Ambro-
sini and Bowman 2009; Arend and Bromiley 2009;
Barreto 2010; Easterby-Smith et al . 2009; Helfat and Peteraf 2009; Helfat and Winter 2011; Schreyögg
and Kliesch-Eberl 2007; Wang and Ahmed 2007;
Zahra et al . 2006). These works trace the intellectual
origins of the DCV approach, provide syntheses of
definitions, discuss the constituents, enablers and
inhibitors of dynamic capabilities, summarize key
empirical findings and also identify shortcomings in
conceptual clarity and empirical applicability.
However, in terms of method, qualitative reviews
tend to reflect the idiosyncrasies of the reviewers,
who are deeply involved in the topic. Single-expert
reviews are indispensable for assessing the state of afield and launching discussions on its future devel-
opment; however, they tend to suffer from general
problems of subjectivity and hence are inherently
biased. An additional problem is that relevant publi-
cations proliferate at rates that increasingly exceed
the information-processing capacity of individual
researchers. This is reflected in the considerable dif-
ferences between the various views on how the DCV
is to be understood, how it might be applied and
how it might influence the development of strategic
management. For example, Arend and Bromiley
(2009) draw the conclusion that, because of its vagueor inconsistent theoretical foundations, the DCV
approach is at a disadvantage compared with other
approaches to strategic organization. They also criti-
cize the fact that the DCV approach underutilizes
organization theory in general and concepts of
organizational change, such as ‘absorptive capacity’,
‘organizational learning’ and ‘change management’,
in particular. In contrast, Helfat and Peteraf (2009)
respond by arguing that terminological and concep-
tual variety simply reflects the complexity of the
phenomenon, which requires multiple theoretical
views. In their view, the continuing exploration of
fundamental issues and the lack of empirical valida-
tion are features of any field of inquiry in the state of
adolescence.
In view of such fundamental disagreements with
regard to the scope, and even usefulness, of the DCV,
a structured quantitative approach to the extant litera-
ture can help (i) to explore the scope of the DCV in the
broader field of strategic management, (ii) to detect
current research schools and perspectives within the
DCV and (iii) to push the envelope by identifying
hitherto unaddressed issues and unconnected sub-
fields. Accomplishing these goals will substantiate
and complement qualitative literature reviews and
critiques of the DCV and help cross-validate their
findings and assessments. To provide an alternative to
qualitative reviews, we employ bibliometric methods,which involve the aggregation of large amounts of
bibliographic data (for a review, see Verbeek et al .
2002) and are therefore deemed to be objective. In the
course of our analysis, we introduce in manage-
ment research the method of bibliographic coupling
(Kessler 1963), which complements the widespread
co-citation technique (e.g. Di Stefano et al . 2010) by
shifting attention from traditions to trends in the sci-
entific literature. This method enhances bibliometric
applications of social network analysis, which have so
far been used predominately for visualization pur-
poses. Furthermore, we examine the thematic expan-sion of the DCV by analysing the diffusion process
over time, instead of merely taking a snapshot.
The results delineate the DCV in the current
literature. The bibliographic networks that we iden-
tify reveal several distinct yet interrelated subfields
of research that evolve dynamically over time. While
the resource-based view (RBV) of strategic manage-
ment and organizational learning were constitutive of
the DCV in the earlier stages of its evolution, more
recent literature indicates that the field is shifting
towards a more integrated agenda of research. We
have labelled the core cluster of the current DCV,which captures this research field’s nascent, fragile
identity, as ‘strategic learning and change’. This
stream focuses on learning capabilities and relates
them to firm performance, thus merging aspects of
organization theory and strategic management. We
show that, in the course of the DCV’s evolution, the
RBV has made a ‘learning turn’, while organiza-
tional learning has undergone a ‘strategic turn’. In
addition, we identify several peripheral clusters of
research that reflect a parallel process of differentia-
tion in the overall field. Both trends, i.e. of integra-
tion and differentiation, attest to the emancipation of
the DCV as a distinct approach to strategic manage-
ment. Nevertheless, despite an increasing number of
papers that focus on the microfoundations of the
approach – for example, routines, practices or cog-
nition – the DCV still lacks consensual concepts that
allow comparisons of empirical studies and advance
the theoretical understanding of dynamic capabili-
ties. In the light of the above, we discuss some pos-
sible directions for further research.
2 R. Vogel and W.H. Güttel
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The paper is organized as follows: in the next
section, the data and methods are introduced. We
commence with a brief review of bibliometric appli-
cations in management research and compare the
complementary techniques of co-citation analysis
and bibliographic coupling. Subsequently, we outline
the multivariate methods by means of which we process the results of bibliographic coupling. A brief
documentation of the selected data completes the
second section. In the third section, we analyse and
compare the extracted bibliographic networks and
divide them into several clusters. In the fourth
section, we discuss the findings in order to delineate
the various research schools and perspectives within
the DCV and to identify the possible paths of the
field’s further development. We conclude with
remarks on the directions in which future research on
the DCV could develop.
Data and methods
The method followed in this review is rooted in
bibliometrics, i.e. the statistical analysis of scholarly
communication through publications (De Solla Price
1965; Garfield 1955; Pritchard 1969). The most
common bibliometric methods are variants of cita-
tion analysis. Citation retrieval can be used descrip-
tively (as opposed to evaluatively; Van Leeuwen
2004), to reveal the intellectual traditions within a
field and to trace its development in the course of time. Advanced bibliometric methods were intro-
duced in strategic management research by Ramos-
Rodríguez and Ruíz-Navarro (2004), who explored
the intellectual structure of the field by analysing
citations from issues that were published in that
field’s leading journal in the first two decades after
its launch. In their study, they identified the emer-
gence of the RBV, whose pivotal role in recent
strategic management research was confirmed by a
complementary study by Nerur et al . (2008). While
those studies looked at the delineation of the RBV
within the broader field of strategic management,
Acedo et al . (2006) turned it into a bibliometric
subject in its own right, tracing the main research
trajectories of the RBV. One of those trajectories
records the development of the DCV as an emergent
school of thought. A recent study by Di Stefano et al .
(2010) further narrowed the focus of analysis on
scholarly orientations within the DCV. The authors
identified the main theoretical traditions in which the
approach is anchored and showed how different con-
ceptions of the construct have evolved from these.
Complementing the study by Di Stefano et al .
(2010), the present paper focuses on the evolution of
these theoretical traditions in current research.
Co-citation analysis vs. bibliographic coupling
Two citation-based methods of mapping scientific
literature in intellectual fields have dominated biblio-
metrics over the past five decades: co-citation ana-
lysis and bibliographic coupling. Co-citations and
bibliographic couplings are intertextual relationships
between scientific publications that are established
by the referencing behaviour of authors. Both
methods share the basic assumption that these rela-
tionships reflect some textual similarity between the
co-cited or coupled documents. However, while these
techniques appear to be alike at first glance, a closer
look reveals considerable differences. A co-citation
is defined as the frequency with which two docu-
ments1 are cited together in the literature (Small
1973). Documents are thus co-cited if they are
included in the same reference list. In contrast,
bibliographic coupling is said to occur when two
documents have at least one reference in common
(Kessler 1963). Documents are thus coupled if their
bibliographies overlap. It follows from these defini-
tions that co-citation analysis and bibliographic cou-
pling differ with regard to the level of analysis: while
a co-citation is a similarity relationship between two
cited publications, bibliographic coupling is ameasure of association between two citing publica-
tions (see Figure 1).
This difference has important implications with
regard to the analytical scope of co-citation analysis
and bibliographic coupling. First, co-citation ana-
lysis is a dynamic approach, while bibliographic cou-
pling is static. A co-citation is established by authors
of papers other than those it links; in other words, it
is a relationship extrinsic to the documents involved.
In contrast, a bibliographic coupling is established
through references made by the authors of the
documents involved and is thus intrinsic to thosedocuments.The coupling strength of published docu-
ments is determined by the amount of overlap
between their bibliographies. Therefore, the results
of bibliographic coupling are independent of the
point in time at which the analysis is conducted,
while co-citation frequencies can increase over time.
1In this paper, we only discuss document co-citation ana-lysis. The technique could also be applied to other biblio-graphic items such as authors or journals.
DCV in Strategic Management 3
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Second, precisely because of that feature (i.e. that
citations accumulate over time), co-citation analysis
lends itself to tracing the intellectual roots of an
academic field through the identification of its
foundational works. The older a document, the
longer the period in which it can have accumulated
citations. Compared with the ‘classics’ of an aca-
demic field, more recent publications have had lesstime to leave their marks, regardless of their potential
to become classic works in the future. In view of that,
most researchers who employ co-citation analysis
acknowledge that the method is biased towards ‘the
past’ of an academic field (Gregoire et al . 2006;
Ramos-Rodríguez and Ruíz-Navarro 2004). In con-
trast, bibliographic coupling is suitable for detecting
current trends and future priorities as they are
reflected at the forefront of research. Documents that
include citations are de facto more recent than the
documents they cite (with the exception of docu-
ments cited as ‘forthcoming’). Shifting the focus of analysis from cited to citing texts, i.e. from texts that
are included as references to the texts that include
references, shifts the emphasis from older to younger
publications and thus from traditions to trends in a
specific field. This feature makes bibliographic cou-
pling a particularly important method in subject
areas characterized by vibrant publication activity,
such as the DCV.
Third, as the previous points suggest, while
co-citation is a reliable indicator of the impact of
publications, bibliographic coupling measures publi-
cation activity. According to the general assumptions
of bibliometrics, citation counts reflect the resonance
of a paper in the scholarly community (Verbeek et al .
2002). Co-citation analysis focuses on the most
influential contributions to a given field. This is
because, in standard applications of this method, data
are reduced on the basis of a specific threshold of
citation counts (McCain 1990). In contrast, biblio-
graphic coupling considers documents independ-
ently of the number of citations, thus reflecting the
production rather than consumption of scientific
publications. While the latter, less restrictive proce-
dure means that mainstreams are not overempha-
sized, it may over-represent works that turn out to be
insignificant in the course of a field’s intellectual
development.
In sum, co-citation analysis is advantageous for
mapping the intellectual heritage of a particular field on the basis of high-impact publications, but tends to
neglect the publication dynamics at the forefront of
research. Bibliographic coupling, in contrast, cap-
tures more recent contributions, including the classics
of tomorrow, so to speak, however, this method has a
blind spot with regard to the history of an intellectual
field. Because our intention is to focus on present
activities, rather than recount past achievements, we
have chosento apply bibliographiccoupling andat the
same time introduce this method in the field of man-
agement research. Scholars who try to orientate them-
selves in this field in order to set their own researchagenda are more likely to benefit from looking not
only at mainstreams but also at ‘newstreams’. In that
respect, this study complements the co-citation ana-
lysis of the DCV that was recently conducted by Di
Stefano et al . (2010). Empirical evidence confirms
thatthese two methods produce considerably different
results and thus supplement, rather than substitute
each other (Jarneving 2005).
Network and factor analysis
Drawing on the literature published between 1994
and 2011, we compiled a pool of data, which
we analysed using bibliographic coupling. As has
been outlined above, bibliographic coupling refers
to the number of references shared by at least
two documents. The method assumes that, the greater
the number of references to the same documents, the
greater the similarity between the citing texts. The
intermediate result of bibliographic coupling is an
aggregated matrix that displays for all document pairs
Citing document
Cited document
A B
aa b
A
Co-citation
Bibliographic
coupling
Figure 1. Co-citation and bibliographic coupling
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the co-occurrences of references in their bibliogra-
phies. This similarity matrix must be further proc-
essed with standard multivariate methods that allow
the graphic or metric detection of homogeneous sub-
fields within a heterogeneous research landscape.
We processed the raw matrix using two comple-
mentary methods. First, we applied network analysis,a method that increasingly attracts attention among
researchers who employ bibliometric methods (Cor-
nelius et al . 2006; Ma et al . 2008; McMillan 2008;
Neely 2005; Pilkington and Chai 2008; Pilkington
and Fitzgerald 2006; Pilkington and Meredith 2009;
Schildt et al . 2006).2 We created network diagrams
on the basis of the spring embedder algorithm pro-
vided by the UCINET software package by Borgatti
et al . (2002). Similarly to multidimensional scaling
approaches, this graph layout algorithm optimizes
distances between every pair of nodes. The distances
between any two nodes are approximated by the pathlength, i.e. the number of edges between them. The
shorter the mean path length between a given node
and other nodes, the higher its centrality in the
network. Although network analysis in bibliometric
studies is mostly applied for visualization purposes,
a few studies also compute network metrics (McMil-
lan 2008; Pilkington and Chai 2008; Pilkington and
Fitzgerald 2006).
In the present study, in addition to the visual infor-
mation presented in the network diagrams, we calcu-
lated metric measures for the density and cohesion of
subgroups within the network. We chose to reportthese measures because they help to assess how the
identified perspectives are delineated within the
DCV. Here, ‘density’ refers to the distinctiveness of a
subgroup within the entire network; it is thus an
attribute of a partial network. Density is calculated as
the ratio of realized links to all possible links within
a subgroup. A maximum density is obtained when all
nodes in a subgroup are linked to all other nodes in
that group. As a bibliometric indicator, density
reflects the extent to which various streams within a
subfield of research pursue their agendas on common
grounds. A related network measure is ‘cohesion’,
which is an attribute of a partial network, too. Cohe-
sion measures relate the density of a subgroup to its
interconnectedness with other groups. A subgroup is
highly cohesive if its members are densely intercon-
nected, but only weakly linked to non-members. In bibliometric applications, cohesion indicates the
extent to which a subfield of research pursues an
agenda that is independent of other discourses.
In order to enhance the robustness of the results,
we complemented the network analysis with factor
analysis, which is a routine clustering procedure in
bibliometrics (McCain 1990). For this purpose, we
converted the raw data matrix to correlation matrices
based on Pearson’s coefficient. Using measures of
relative document similarity instead of mere fre-
quency counts has the advantage that it takes the
coupling ‘profiles’ of these documents into account,rather than the absolute co-occurrence of references
(McCain 1990). Here, we considered the main diago-
nal of the correlation matrix as missing values. An
alternative procedure suggested for co-citation ana-
lysis by White and Griffith (1981) (dividing the sum
of the three highest scores by two) led to similar
results, so we left it out for the sake of simplicity. The
factor extraction by means of principal component
analysis and scree tests was followed by Varimax
rotation with Kaiser normalization. Documents with
mixed loadings, i.e. with significant loadings (0.4)
on more than one factor, were assigned to the factor on which they loaded highest.
Data
In the data sampling process, we started the analysis
with a broad data set that was gradually reduced at
later stages. We initially selected all documents that
included the search term ‘dynamic capabilit*’ in the
title, abstract and/or keywords from the Social
Science Citation Index® (SSCI), the authoritative
bibliographic database covering academic journals in
the social sciences. Since its first appearance in the
academic literature (Teece et al . 1990), the term
‘dynamic capability’ has become a technical term in
strategic management research. We thus expected it
to be indicative of documents that were of potential
relevance to our study. Of course, some authors use
the phrase ‘dynamic capability’ without the intention
to refer and contribute to the respective discourse in
strategic management. However, since in bibliomet-
ric terms items with low or no relevance to the topic
2In contrast to our study, many papers apply multidimen-sional scaling (MDS) for science mapping (e.g. Acedo et al .2006; Di Stefano et al . 2010; Nerur et al . 2008; Ramos-Rodríguez and Ruíz-Navarro 2004). We prefer network ana-lysis because MDS can transform metric similarities intospatial distances only for a limited number of documentswithin the tolerance range of stress values, while network analysis can display an unlimited number of documents asnetwork nodes. Thus, network analysis allows us to draw amore comprehensive picture of the DCV, which has rapidlygained in scope in the recent literature.
DCV in Strategic Management 5
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keep being unrelated to the literature in this field,
such items were successively eliminated through the
application of thresholds at later stages of the ana-
lysis. Using the results that our search term yielded,
we compiled an initial data set, which contained
1152 items (i.e. articles, reviews and proceedings
papers) published in academic journals until and
including 2011. These texts contained 91,137 refer-
ences to 37,541 documents.
The proliferation of publications on dynamic
capabilities shows an exponential growth since the
appearance of the first journal article on that topic in1994 (see Figure 2). In fact, the number of relevant
papers has approximately doubled within the last
three years (i.e. from 2009 to 2011). To account fully
for this trend, we adopted a comparative approach to
the analysis of the data, which we divided into two
roughly equal parts. We initially ran an analysis only
on the first half, which consisted of 560 items pub-
lished between 1994 and 2008. We then added the
remaining 592 documents and repeated the proce-
dure for the whole time series from 1994 to 2011. By
comparing the results, we were able to track how the
most recent publications have shaped the biblio-
graphic network and to identify in which directions
research on the DCV is developing.
Results
Bibliographic network, 1994–2008
The first network of bibliographic couplings within
the DCV, which covers the period 1994–2008, is
presented in Figure 3. The nodes symbolize citing
documents (i.e. documents that include citations),
while the edges represent bibliographic couplings, i.e.
the number of references that any two nodes share.To
achieve clarity, we specified a minimum number
of couplings between a document and a minimum
number of other documents, and only considered
publications at or above these thresholds. By varying
the thresholds within a broad range of values, we
adjusted the resolution of the method in order to
reduce complexity without being too reductive. While
the size of the network varied when we applied differ-ent thresholds, its structure did not change signifi-
cantly. Eventually, we decided to consider only those
items that had at least 16 couplings with at least two
other documents (tie strength 16, node degree 2).
This procedure reduced the stock of documents from
the 560 initially selected items to the 120 most inter-
related documents. Table 1 shows the summary
results, which include size, explained variance,
density and cohesion of the extracted clusters. We
assigned the documents to four factors, which explain
a total variance of 93.0% (see Table 1). Because we
deleted documents with no significant loadings and
reapplied the thresholds afterwards, the final number
of nodes in the network amounted to 105.
In the network of bibliographic couplings, several
regions that display densely interconnected nodes are
prominent. By contrast, it is harder to discern a
distinct network core. The polycentric structure is
confirmed by the results of the factor analysis, as the
emerging clusters are largely congruent with the
extracted factors (which are represented by different
1 1 2 4 4 1 7 11 22
44 4967
102 112
133
161
208223
0
50
100
150
200
250
300
350
1 9 9 4
1 9 9 5
1 9 9 6
1 9 9 7
1 9 9 8
1 9 9 9
2 0 0 0
2 0 0 1
2 0 0 2
2 0 0 3
2 0 0 4
2 0 0 5
2 0 0 6
2 0 0 7
2 0 0 8
2 0 0 9
2 0 1 0
2 0 1 1
N u m b e r o f d o c u m e n t s
Year
Figure 2. Growth of publications on the DCV
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F i g u r e 3 .
B i b l i o g r a p h i c n e t w o r k , 1
9 9 4 –
2 0 0 8
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node symbols and shades). The network is dominated
by two large clusters to which two smaller subgroups
are peripherally attached. In the following, we
outline the content of the publications that each sub-
field contains, the stream of literature they represent
and how they contribute to the DCV in strategicmanagement. Of course, each cluster has a richer
tradition and is far more complex than its brief
description suggests.
Learning and innovation. In our view, ‘learning
and innovation’ is an appropriate umbrella label for
the relatively heterogeneous body of literature that
loads on the first factor. Documents in this cluster
build on diverse theoretical foundations, e.g. on evo-
lutionary economics (Nelson and Winter 1982),
behavioural theory (Cyert and March 1963) and the
knowledge-based view (Kogut and Zander 1992). Aconsiderable number of those documents address the
emerging tension between the building of new and
the use of existing capabilities or, in broader terms,
between stability and change. These works shed light
on the alignment of exploration and exploitation
(Benner and Tushman 2003; Lubatkin et al . 2006;
O’Reilly and Tushman 2008; Raisch and Birkinshaw
2008), on the responses of incumbent companies to
discontinuous change (Benner 2007; Gilbert 2006;
Keil 2004; Keil et al . 2008; Lavie 2006b; Martin and
Eisenhardt 2004) and on radical innovation capabili-
ties within established firms (O’Connor 2008;
O’Connor and DeMartino 2006; O’Connor et al .
2008). Another group of documents in this cluster is
concerned with how a firm’s capabilities can be
advanced by building on the stock of existing know-
ledge in new domains (Cattani 2005, 2006, 2008;
Nerkar and Roberts 2004), as well as through emer-
ging R&D capabilities (Nerkar and Roberts 2004;
Tzabbar et al . 2008) and evolving resources more
generally (Ahuja and Katila 2004). Other publica-
tions deal with the subject of firm acquisitions, which
are a typical setting for reconfiguration capabilities
(Barkema and Schijven 2008; Puranam and Srikanth
2007; Zollo and Singh 2004). A smaller group of
publications on the microfoundations of dynamic
capabilities, particularly on the cognitive skills of individuals (Gavetti 2005; Kaplan 2008; Teece
2007), completes this cluster. Although this is, to
some extent, a cross-cutting issue through all clus-
ters, accordant works figure most prominently in the
‘learning and innovation’ cluster.
Resource-based view. We chose to describe the
second cluster as ‘RBV’, because resource-based
theory stands out as the predominant theoretical per-
spective in most of the publications it includes
(Barney 1991; Conner 1991; Penrose 1959; Peteraf
1993; Wernerfelt 1984). What unifies one group of works within this cluster is a substantial number of
‘affirmative’ references to the original version of the
RBV; dynamic capabilities are referred to only en
passant. For example, many of these publications
review the state-of-the-art of RBV research (Arm-
strong and Shimizu 2007; Newbert 2007; Newbert
2008; Wade and Hulland 2004), call for its extension
and operationalization (Colbert 2004; De Toni and
Tonchia 2003; Escrig-Tena and Bou-Llusar 2005;
Newbert et al . 2008) or apply standard versions
of the perspective, particularly to IT capabilities
(Hulland et al . 2007; Jarvenpaa and Leidner 1998;
Melville et al . 2004; Soto-Acosta and Meroño-
Cerdan 2008). However, the references to the RBV
made by other works in this cluster have compara-
tively ‘negative’ connotations. These publications
support the ‘dynamization’ of resource-based theory
(Helfat 2000; Helfat and Peteraf 2003) and draw on
it mainly to stress the differences rather than the
common ground between the DCV and the RBV. For
example, the RBV is criticized for neglecting the
Table 1. Full network, 1994–2008: factor analysis and network metrics
No. Symbol Label No. of
docs
Factor analysis Network analysis
Eigenvalue Variance
explained (%)
Cohesiona Density b
1 Learning and Innovation 41 49.682 41.402 1.489 0.179
2 RBV 49 43.552 36.294 1.713 0.2433 Vertical scope 8 11.241 9.368 2.420 0.576
4 Alliances 7 7.117 5.931 2.055 0.333
aCohesion index of Bock and Husain (1950). bTotal number of ties divided by the total number of possible ties in binarized network.
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negative effects of assets and capabilities on firm
rents (Arend 2004), for paying limited attention to
the process of resource creation (Bowman and
Collier 2006) or for disregarding resources in the
interfirm domain (Lavie 2006a; Mathews 2003;
Zander and Zander 2005). To overcome the static
approach of the RBV, the earlier works on dynamiccapabilities (Eisenhardt and Martin 2000; Teece
et al . 1997) open this perspective to other streams of
literature, in particular to evolutionary economics
(Nelson and Winter 1982) and behavioural theory
(Cyert and March 1963). Interestingly, both theories
also play an important role as the theoretical founda-
tion of papers in the ‘learning and innovation’ cluster.
The imprint of evolutionary and behavioural theories
is most apparent in articles on strategic entrepreneur-
ship (Ireland et al . 2003), the role of knowledge in
strategy formulation (McGee and Thomas 2007),
learning (Isobe et al . 2008; King 2007; Uhlenbruck et al . 2003), human motivation (Gottschalg and
Zollo 2007) and managerial decision-making (Adner
and Helfat 2003). Finally, this cluster includes long-
standing research in marketing that has co-evolved
with the DCV (Jarratt 2008; Kyriakopoulos and
Moorman 2004; Morgan et al . 2003).
Vertical scope. We labelled the third cluster in the
network ‘vertical scope’, because works in this
cluster focus on vertical integration and strategic
outsourcing (Holcomb and Hitt 2007; Jacobides
2008; Jacobides and Hitt 2005; Jacobides and Winter 2005). These issues also raise more general questions
about organizational boundaries (Santos and Eisen-
hardt 2005) and the choice of governance modes
(Parmigiani 2007). References to transaction cost
economics (TCE) are the binding component of the
vertical scope cluster. While the RBV and TCE have
long been regarded as opposite theories of the firm,
they converge, to some extent, under the capability-
based view (Madhok 2002). In this line of reasoning,
dynamic capabilities are significant as sources of
capability differentials between firms, since learning
curves are assumed to bring about changes in a
firm’s skills and abilities (Jacobides 2008). However,
this cluster is more isolated from those subgroups
that refer to learning theory more explicitly.
Alliances. We named our fourth and final factor
‘alliances’, since this cluster includes mostly publi-
cations on alliance capabilities (Heimeriks and
Duysters 2007; Rothaermel and Deeds 2006) and
alliance learning (Kale and Singh 2007). The
stronger a firm’s alliance orientation, the more prom-
ising its external sourcing in networked environ-
ments (Kandemir et al . 2006). Once a firm has
entered an alliance, experiences from prior or
ongoing partnerships improve the chances of the
alliance’s success (Heimeriks and Duysters 2007;
Rothaermel and Deeds 2006). These performanceeffects increase when firms leverage their alliance
experiences and translate them into alliance or
network capabilities (Heimeriks and Duysters 2007;
Kale and Singh 2007; Rothaermel and Deeds 2006;
Walter et al . 2006). Alliance capabilities are built
through various learning mechanisms such as the
internalization, integration and institutionalization of
alliance know-how (Heimeriks and Duysters 2007;
Kale and Singh 2007), whereby the effectiveness of
these mechanisms depends, among other factors, on
the type of the alliance (Rothaermel and Deeds
2006). The separate cluster on alliances suggests thatmechanisms of external learning and forming capa-
bilities in alliances differ remarkably from those in
other settings.
Bibliographic network, 1994–2011
In the second step of analysis, we integrated docu-
ments that were published from 2009 up to and
including 2011 and repeated the bibliometric ana-
lysis on the full database in order to trace the path
along which the DCV had developed during that
period. Expanding the data sample more thandoubled the amount of processed data. For that
reason, we applied a higher threshold than in the first
step of the analysis and only considered publications
that displayed at least 19 couplings with at least two
other documents (tie strength 19, degree 2).
After excluding items that did not show significant
loadings in the factor analysis, we ended up with a
network that contained 132 interrelated documents
(see Figure 4). The factor analysis revealed six com-
ponents that, together, explain 80.3% of the total
variance in the bibliographic network (see Table 2).
Integrating the most recently published documents
into the analysis yielded a network composed of one
large cluster and five much smaller clusters. The first
component explains approximately three times as
much variance as the next largest factor. Strikingly,
the explanatory power of the smaller components
does not co-vary strongly with cluster size and
network cohesion. For instance, the third largest
component is a small yet dense cluster, while the
fourth factor clusters a larger number of publications
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F i g u r e 4 .
B i b l i o g r a p h i c n e t w o r k ,
1 9 9
4 –
2 0 1 1
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that are widely dispersed over the network. This sug-
gests that the subfields of the DCV differ consider-
ably with regard to the coherence of their research
agendas. We now briefly outline the identified clus-ters with regard to their structure and content.
Strategic learning and change. We labelled the
dominant cluster in the entire bibliographic network
‘strategic learning and change’. Approximately half
the works it contains had been previously assigned to
the RBV cluster, so the ‘strategic learning and
change’ cluster exhibits a similarly strong focus on
the strategic management of firm resources in pursuit
of competitive advantage and rent appropriation.
However, in this cluster the emphasis has shifted to
learning capabilities with relation to firm perform-ance. As a result, the cluster’s profile, which is
shaped by more recent publications, differs consid-
erably from earlier stages of the field’s development.
For example, the more recent publications draw more
attention to knowledge assets that are leveraged
into human capital and organizational capabilities
through learning mechanisms on multiple levels
(Clougherty and Moliterno 2010; Moustaghfir 2009;
Ployhart and Moliterno 2011). This reveals that the
creation, recombination and integration of know-
ledge is crucial to the firm’s overall innovation
capacity (Garcia-Muina et al . 2010; Regner and
Zander 2011). The increasingly dynamic view of
capabilities also raises the question of how they
co-evolve with other organizational phenomena such
as governance structures (Lee et al . 2011) or the bar-
gaining power of stakeholders (Coff 2010). Overall,
the research that this cluster represents contributes to
the dynamization of the RBV, which many authors
have called for, and directs it towards issues of stra-
tegic learning and change. As the cluster also
includes reviews of the dynamic capability approach
(Ambrosini and Bowman 2009; Barreto 2010) as
well as works that attempt to conceptualize, opera-
tionalize and measure dynamic capabilities (Kim and Mahoney 2010; Pavlou and El Sawy 2011), it lies at
the core of the DCV.
Technological innovation and adaptation. Roughly
two-thirds of the publications assigned to the second
factor were part of the previous ‘learning and inno-
vation’ cluster. Focusing especially on large incum-
bent firms in specific industries, these works keep
radical innovation capabilities, technological adapta-
tion and strategic responses to change high on the
research agenda. For that reason, we gave it the new
label of ‘technological innovation and adaptation’.For example, this stream of research investigates the
way in which capabilities affect how firms decide
when and how to adopt emerging technologies
(Anand et al . 2010). Technological adaptation may
be inhibited by organizational routines, such as
process management practices, that disadvantage
incumbents in the face of radical discontinuities
(Benner 2009). In particular, pre-existing capabilities
have an impact on the choice of sourcing modes that,
in turn, affect the acquisition of new capabilities
(Capron and Mitchell 2009). Organizational
responses to technological change may also be influ-
enced by managerial cognition (Eggers and Kaplan
2009) or securities analysts (Benner 2010). All in all,
research in this subfield is highly cumulative with
regard to the antecedents of technological innovation
and adaptation.
Vertical scope. The third subgroup encompasses
most of the works that composed the ‘vertical scope’
cluster in the previous analysis. There are only three
Table 2. Full network, 1994–2011: factor analysis and network metrics
No. Symbol Label No. of docs Factor analysis Network analysis
Eigenvalue Variance
explained (%)
Cohesiona Density b
1 Strategic learning and change 55 50.636 36.961 0.342 0.127
2 Technological innovation and adaptation 24 16.191 11.819 1.741 0.1383 Vertical scope 9 13.266 9.683 2.127 0.222
4 Microfoundations and acquisitions 15 10.514 7.675 1.790 0.191
5 Ambidexterity 15 10.011 7.308 2.386 0.238
6 Alliances 10 9.374 6.842 0.633 0.289
aCohesion index of Bock and Husain (1950). bTotal number of ties divided by the total number of possible ties in binarized network.
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new publications in this subfield, which have low
loadings on the respective factor and are thus not
characteristic of this stream of research. Given that
economic analyses of vertical integration and strate-
gic outsourcing remain the dominant theme, we
decided to retain the label ‘vertical scope’.
Microfoundations and acquisitions. One half of the
next cluster consists of publications previously
included in the ‘learning and innovation’ cluster, the
other half is composed of new publications. This
composite body of literature addresses two distinct
but interrelated topics: the microfoundations of the
DCV and the knowledge-based view of corporate
acquisitions. The works that are concerned with the
first topic trace dynamic capabilities back to routines,
processes and collective activities that are rooted in
the intentional behaviour of individuals (Felin and
Foss 2009). To illuminate this subject and to bridgethe ‘micro–macro’ divide in management research,
the authors of those studies attempt to identify the
components of capabilities and to investigate how
they interrelate across the individual and the collec-
tive levels (Lewin et al . 2011; Salvato and Rerup
2011; Schilke and Goerzen 2010). The remaining
works in this cluster take a knowledge-based view of
corporate acquisitions (Zollo 2009; Zollo and Reuer
2010). These works shed light on integration capa-
bilities and learning mechanisms that foster post-
acquisition knowledge spillovers. These streams
merge into a single cluster, which we decided to call‘microfoundations and acquisitions’. It is possible
that these two streams are seen to merge because
research on corporate acquisitions analyses manage-
rial processes in acquisition decisions and integration
activities. These efforts to look at the components of
capabilities at the individual level also contribute to
the microfoundations of the DCV.
Ambidexterity. Most works included in the fifth
cluster are concerned with the discussion that char-
acterized the subfield of ‘learning and innovation’,
except that here almost all relevant publications have
been published between January 2009 and December
2011; that is, they are very recent. This body of
literature obviously represents a particularly vibrant
subfield of DCV. Most works in this cluster address
the balance of flexibility and efficiency (Eisenhardt
et al . 2010), stability and change (Farjoun 2010),
incremental and radical innovation (Tushman et al .
2010) or exploration and exploitation (Lavie et al .
2010; Raisch et al . 2009); for that reason, we gave
this cluster the label ‘ambidexterity’. Ambidextrous
organizations are able both to explore new know-
ledge domains and to exploit current ones. Related
research predominantly deals with the antecedents
and consequences of ambidextrous learning. For
example, factors that promote ambidexterity include
integration mechanisms at the senior team level(Jansen et al . 2009), intellectual capital architectures
(Kang and Snell 2009), total quality management
(Luzon and Pasola 2011), organizational design
(Tushman et al . 2010), executive leadership (Martin
2010) and managerial cognition (Eisenhardt et al .
2010). The publications that are typical of the
‘ambidexterity’ cluster show many similarities and
interconnections with those in the ‘technological
innovation and adaptation’ cluster.
Alliances. Finally, the smallest component encom-
passes a variety of publications. Few of the publica-tions of the original ‘alliances’ cluster appear in this
one, which consists mainly of recent publications,
integrated in the second round of the analysis, and of
publications that were initially included in the ‘learn-
ing and innovation’ field. Alliances, however, are still
the main theme of the recomposed cluster, for which
reason we have decided to retain the label. Much of
the research reflected in this cluster focuses on learn-
ing from alliance partners, and thus essentially
addresses the question of what enables firms to
source knowledge beyond their own boundaries and
what the outcomes of such processes are. The per-formance effects of external sourcing, for example,
depend on what kind of experience a firm has gained
from previous alliances (Hoang and Rothaermel
2010) and on how this is combined with internal
sourcing strategies (Rothaermel and Alexandre
2009). Because of this focus on learning across
organizational boundaries, the concept of absorptive
capacity figures prominently in this cluster (Rothaer-
mel and Alexandre 2009; Volberda et al . 2010).
Other publications in this cluster address how firms
can retain knowledge that they have sourced outside
their boundaries and how they can use interorganiza-
tional relations to extend their knowledge base (Lich-
tenthaler 2008).
Discussion
The results of this study reveal the breadth of the
diversified territory of the dynamic capabilities
approach in strategic management. The networks that
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we extracted from the extant literature on the basis of
shared references give a visual impression of the
densely interconnected documents that are encom-
passed in this field of inquiry. Running closer factor and network analyses on the data, we detected the
topics to which priority is given within this field of
research. The DCV has integrated theoretical aspects
of evolutionary economics, behavioural theory and
the knowledge-based view into core issues of stra-
tegic management. In conceptual terms, several
dynamic capabilities, such as sensing and opportu-
nity recognition, or capabilities related to learning,
reconfiguration and replication, have created distinct
bodies of literature. It should be noted that, under-
neath the clusters that emerged from our results,
there may be considerable variety even within thesubgroups, considering that a particular body of lit-
erature might be relevant to a number of different
topics. Our overall results support the view that
dynamic capabilities are far from being a well-
defined construct based on a coherent theoretical tra-
dition and validated with strong empirical evidence
(Arend and Bromiley 2009). On the contrary, the
field appears to be developing along a path of theo-
retical and conceptual diversification, but also with
the emergence of an identity-building foundation.
The bibliometric review of the diffusion of DCV
literature from a dynamic perspective reveals the dif-
ferent strands of emerging DCV research (Figure 5).
The main avenue of DCV research corresponds
to the core cluster ‘strategic learning and change’,
which originated in a learning turn within earlier
research on dynamic capabilities in the context of the
RBV perspective. We further identified three clusters
that reflect efforts within DCV research to uncover
the processes of firm evolution through the develop-
ment of new technologies, through balancing
exploratory and exploitative learning processes or
through the acquisition of other companies. These
were the ‘technological innovation and adaptation’,
‘ambidexterity’ and ‘microfoundations and acquisi-
tions’ clusters, which represent the further differen-
tiation of the DCV and its linkages to related
subfields, in particular to innovation and ambidexter-ity research streams. Lesser current research paths
in the DCV are represented by the minor clusters
‘vertical scope’ and ‘alliances’. All clusters include
works concerned with the reactive adaptations to
environmental demands, observed in firms that aim
to remain competitive, as well as the proactive and
entrepreneurial approach many firms adopt (such as
developing new products or markets) in order to
create competitive advantage.
To observe the thematic expansion of the DCV, we
adopted a dynamic perspective, comparing two
views of the DCV network: one covering the period 1994–2008 (Figure 3) and a second one, covering
the full period 1994–2011 (Figure 4). In that respect,
our analysis goes beyond traditional bibliometric
reviews. Furthermore, through this innovative meth-
odological approach, we were able to identify the
trajectories of research fields within the DCV to
indicate potential avenues for further research
(Figure 5).
More specifically, this bibliometric analysis con-
tributes to DCV research in three ways: first, the data
show that research within the DCV field leads both to
differentiation and to identity formation. Compared with earlier DCV research (that is, until 2008; see
Figure 3), recent research (that is, until 2011; see
Figure 4) shows a shift from a cluster reflecting
classical RBV research (dynamic capabilities are in
those works mentioned only with minor notions to
emphasize generally the need of a dynamic evolve-
ment of the firm’s resource base) to a cluster where
learning processes are driven mainly by dynamic
capabilities. This cluster, which we labelled ‘strategic
learning and change’, turned out to be the dominant
one within the DCV. The strategic governance of
learning processes with relation to reconfiguring the
firm’s resource base emerged as the DCV’s core
topic. In contrast to the backward-looking co-citation
analysis of Di Stefano et al . (2010), our forward-
looking data indicate that the works comprising the
cluster ‘strategic learning and change’ form the
identity-building base of the DCV. In that cluster,
classical RBV arguments merge with learning topics
in the context of reconfiguration processes, while
the emphasis is seen to shift from minor notes on
Alliances Alliances
Learning &
Innovation
RBV
Vertical Scope
Strategic Learning
& Change
Technological
Innovation &
Adaptation
Vertical Scope
Microfoundations& Acquisitions
Ambidexterity
1994-2008 1994-2011
Learning Turn
Strategic Turn
Differentiation
Continuity
Differentiation
Differentiation
Recomposition
Figure 5. Development patterns of DCV research
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developing a firm’s resource base in the context of
the RBV to papers that perceive the DCV as a dis-
tinct approach or even as the main lens for analysing
organizational development. The works comprising
this cluster feature prominent reviews (Ambrosini
and Bowman 2009; Barreto 2010; Wang and Ahmed
2007), as well as fundamental papers in DCVresearch (Eisenhardt and Martin 2000; Teece 2007;
Teece et al . 1997), which indicates that the ‘strategic
learning and change’ cluster represents the core of
the DCV.
Topics such as capabilities and knowledge also
explore the foundation of sustainable competitive
advantage. The bibliometric analysis identified a
learning turn in strategy literature. More precisely, it
showed that, especially among publications that
came out in or after 2009, behavioural aspects
increasingly under pin strategic topics in the DCV. We
also noted a strategic turn in the literature on learningin the DCV field that corresponds directly to the
learning turn; the link between learning and firm
performance features prominently in those works.
These streams of research tend to merge. Our data
confirm the analysis of Di Stefano et al . (2010), who
found that behavioural theory (Cyert and March
1963) and evolutionary economics (Nelson and
Winter 1982) form the theoretical foundation of both
streams and thus facilitate their integration. As the
first network indicates (Figure 3), the DCV is no
longer a by-product of the RBV. Instead, in the
second network (Figure 4), the identity of the DCV builds mainly on the idea that organizations need to
govern processes of learning and change, which the
relevant research explores, in order to adapt their
capabilities to novel situations and thus keep pace
with environmental development.
Two additional clusters emerged from the initial
‘learning and innovation’ cluster, which fit our obser-
vation that, from a strategic perspective, learning
becomes central to the DCV: ‘ambidexterity’ and
‘technological innovation and adaptation’. Both clus-
ters are more homogeneous than the original one,
and the focus of the publications they contain is
narrower in comparison. Research on ambidexterity,
i.e. a firm’s capability to combine exploratory and
exploitative learning, sheds light onto the firm’s
internal learning processes and how firms can
achieve a balance between different learning modes
in order to remain competitive. In the works included
in the ‘technological innovation and adaptation’
cluster, we see the other side of the same coin: they
investigate the firm’s adaptive responses (such as
innovation) to market pressure that arises from new
technologies or changing customer expectations.
Second, the bibliometric analysis identifies
research into the microfoundations of dynamic capa-
bilities. Compared with the first network (Figure 3),
in the second network this stream of research is not
only more prominent but also present in differentfields (Figure 4). The publications contained in the
‘microfoundations and acquisitions’ cluster build on
research on routines, practices and managerial cog-
nition to identify those mechanisms and patterns that
lead to organizational adaptation. Given the signifi-
cance of the DCV concept, precisely this line of
research can provide the DCV with a conceptual base
that, on the one hand, enables the comparison of
empirical studies and, on the other, helps to deter-
mine concrete manoeuvre options for management
practitioners. Nevertheless, more research in this
field is essential, as the different works within thecluster are only loosely related to each other.
Third, the bibliometric analysis complements
qualitative reviews of the DCV. Reviews continu-
ously pursue the concrete meaning of the DCV
concept and present taxonomies of the components
of dynamic capabilities (Ambrosini and Bowman
2009; Easterby-Smith et al . 2009; Helfat and Peteraf
2009; Helfat and Winter 2011; Wang and Ahmed
2007; Zahra et al . 2006). In contrast to the
co-citation analysis of Di Stefano et al . (2010),
which traces the origins of the DCV, we elucidate
current trends and future perspectives in DCVresearch by employing the method of bibliographic
coupling. According to our data, the diffusion of
DCV research leads to the further differentiation of
the field’s research agenda, but also to the emergence
of an identity-building core of the DCV, which
matches the findings of qualitative reviews.
The identity-building core cluster of the DCV
‘strategic learning and change’ covers the topic of
how firms modify their resource base in response to
dynamically evolving environmental demands. Such
responses are characterized by the processes of
learning, reconfiguration and adaptation, which
describe the dynamics of capability evolution both in
our bibliometric analysis and in qualitative reviews
(Ambrosini and Bowman 2009; Barreto 2010;
Easterby-Smith et al . 2009; Helfat and Winter 2011;
Schreyögg and Kliesch-Eberl 2007; Teece 2007;
Wang and Ahmed 2007; Zahra et al . 2006).
According to our bibliometric analysis, other
strands of DCV research are in the process of differ-
entiation, and their empirical and conceptual scope is
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also only partially addressed in qualitative reviews.
In the ‘technological innovation and adaptation’
cluster, sensing opportunities, absorbing knowledge,
innovation or entrepreneurial behaviour (Barreto
2010; Teece 2007; Wang and Ahmed 2007; Zahra
et al . 2006) shape a common overlap. In the ‘ambi-
dexterity’cluster dual-purpose capabilities for explo-ration and exploitation or the role of integrative
capabilities (Helfat and Winter 2011; Teece 2007)
build on the same conceptual foundation. Finally, the
‘microfoundations and acquisitions’ cluster incorpo-
rates managerial behaviour or the explicit microfoun-
dations of dynamic capabilities, which are also
mentioned in qualitative reviews (Ambrosini and
Bowman 2009; Barreto 2010; Easterby-Smith et al .
2009; Teece 2007).
By contrast, qualitative reviews highlight topics
that empirical and theoretical research does not
investigate sufficiently. Such topics are the interplay between dynamic and operational capabilities, the
different constitution of dynamic capabilities (rou-
tines vs. simple rules) and the impact of market
dynamism on the characteristics of dynamic capa-
bilities. Nevertheless, more conceptual work is
necessary to release the full potential of the DCV
in order to deepen the understanding within the
subfields of DCV research and to establish how
the diverse strands of DCV research interrelate
respectively.
Limitations
One drawback of bibliometric methods in general is
that their quantitative approach does not capture in
what context and with what intention authors refer
to other works. Thus, bibliometrics cannot account
comprehensively for the complex nature of citing
behaviour. As empirical research shows, references
may be motivated by self-legitimization strategies
and micro-politics, although these motives turn out
to be less important than reviewing earlier works,
recognizing priority and substantiating assumptions
(for an overview, see Bornmann and Daniel 2008).
Another shortcoming of bibliographic coupling is the
overweighting of publications with comparatively
long reference lists. The more documents a bibliog-
raphy contains, the more likely are intersections with
the reference lists of other publications. Works with
extensive bibliographies tend, therefore, to have a
higher network centrality than those with shorter bib-
liographies. Nevertheless, the length of a reference
list may depend on author preferences as well as on
journal standards. A further limitation is that the
resolution of the applied method depends on the
thresholds defined in the course of data reduction and
factor extraction. In the case of this study, although
we broadly varied the thresholds without observing
significant changes in the network structures, the
final solutions depended partly on technical deci-sions that we, as the researchers, had to make. In
addition to the general limitations of bibliometrics,
which also apply to this study, we should note that the
results overstate the distinctiveness of the extracted
clusters because, in assigning documents to factors,
only the main loadings were considered, while
cross-loadings, which signify interrelations between
different streams of research, were not taken into
account.
Directions for future research
On the basis of this analysis of the existing literature
on the dynamic capability view, we divided the
relevant research into six streams: ‘strategic learning
and change’, ‘technological innovation and adapta-
tion’, ‘ambidexterity’, ‘microfoundations and acqui-
sitions’, ‘vertical scope’ and ‘alliances’. The findings
suggest that the existing research is not exhaustive.
On the contrary, they indicate that more research is
necessary in each of those subfields to explore in
depth certain important aspects; for instance, in the
‘strategic learning and change’ cluster, further research can distinguish between top-management
decisions with regard to change and subsequent
reconfiguration activities; in the ‘technological inno-
vation and adaptation’ cluster, it can help differenti-
ate between operational innovation capabilities and
innovation capabilities that facilitate the fracturing of
technological trajectories; finally, in the ‘ambidexter-
ity’ cluster, it can reveal concrete mechanisms that
help to achieve a balance between exploration and
exploitation and thus to foster a dynamic adaptation
to novel situations.
‘To avoid the problems of tautology [. . .], for
dynamic capabilities to be a useful construct, it must
be feasible to identify discrete processes inside the
firm that can be unambiguously causally linked to
resource creation’ (Ambrosini and Bowman 2009, p.
44). Although there are signs of progress in this field
as current papers, e.g. by Helfat and Winter (2011)
and Barreto (2010), provide some new conceptual
insights on the microfoundations of dynamic capa-
bilities and on their impact in reconfiguring the
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firm’s resource base, our results do not indicate that
in this central field of dynamic capabilities research a
conceptual basis is currently being developed that
would be strong enough to meet the expectations of
both scientific research and practice.
In this analysis, the ‘microfoundations and acqui-
sition’ cluster has a low level of coherence, whichindicates that the cluster is still at an early stage of
development. In this regard, therefore, the call by
Arend and Bromiley (2009, p. 86) for a stronger
foundation of DCV concepts in organization theory
is justified. A stronger foundation, they argue, would
stabilize this perspective and ensure that empirical
studies are assessed and compared in a structured
manner. Streamlining research in this field would
lead to a better understanding of the microfounda-
tions of dynamic capabilities. It would also help elu-
cidate the field’s central theoretical concept, and thus
consolidate the field’s identity, by drawing on (a) theinteraction between top-management cognition, (b)
strategic decision-making and (c) routines and prac-
tices for reconfiguring the firm’s resource base.
Moreover, referential definitions and operationaliza-
tions of the construct could provide a common
ground for quantitative studies – downstream
research. Nevertheless, upstream research is more
important in the current state of the DCV’s develop-
ment; in particular, qualitative research and case
studies that elucidate the micro-mechanisms of rou-
tines, practices or decision-making patterns and thus
advance the theoretical understanding of dynamiccapabilities. So far, the theoretical basis of the DCV
has been advanced mainly through conceptual papers
(e.g. Eisenhardt and Martin 2000; Teece et al . 1997;
Zollo and Winter 2002), not through empirical
research. This may explain why only a few abstract
recommendations for management practice can be
traced in the available literature.
More research on the micro-level of analysis is
also necessary to reveal in what concrete ways
dynamic capabilities help to reconfigure the firm’s
resource base. Arend and Bromiley (2009) claim that
the topic of change management has yet to be inte-
grated into research on dynamic capabilities. The
existing literature shows that managing change is
difficult (Brown and Eisenhardt 1997; Edmondson
et al . 2001) and fraught with resistance to change at
the individual, group and organizational level (Ford
et al . 2008; Piderit 2000). Although dynamic capa-
bilities are perceived as the firm’s capacity to recon-
figure its resource base, advanced research on the
management of change has not yet been integrated
into the existing literature. Future studies could shed
more light on the topic of change by building a con-
ceptual bridge between the DCV and research in the
field of change management (e.g. Schreyögg and
Sydow 2010; Vergne and Durand 2011). They should
also leverage any insights from the field of change
management in order to investigate in detail thecomplex interaction between dynamic capabilities
and operative routines in the process of reconfigura-
tion. The topic of resistance to change also needs to
be addressed in DCV research, both on the level of
concepts and on that of practice.
Because the DCV perspective has its origins in
organization theory (Di Stefano et al . 2010), most
publications focus on strategic and organizational
aspects of firm development. From a managerial
standpoint, two important topics are missing from
the research agenda of the DCV literature: leadership
and human resource management. Both topics areclosely related to organizational reconfiguration.
They are also key topics in the discussion of how the
firm can put its capabilities into action and govern
learning and change processes strategically.
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