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Absorptive Capacity and Firm Performance: The Moderating
Impact of Modes of Diversification.1
Pavlos C. Symeou
School of Management and Economics Cyprus University of Technology Email: pavlos.symeou@cut.ac.cy
Tobias Kretschmer
Institute for Strategy, Technology and Organization Munich School of Management
Ludwig-Maximilians-Universität München Email: t.kretschmer@lmu.de
Abstract
The entrenched use of absorptive capacity as a silver bullet to solve an increasing
number of organizational problems has detached the concept from its original
assumptions. Consequently, we are deprived of knowledge regarding the impact of
absorptive capacity’s underlying abilities to acquire, assimilate and exploit external
knowledge on firm performance and whether it can be modified by boundary
conditions. In this paper, we delve into the acquisition, assimilation, and exploitation
abilities of the firm and put forward the different moderating impact that modes of
diversification can have on their effect on performance. We test our hypotheses on a
sample of 150 large firms traded in the United States operating in the information,
communication and technology (ICT) industries for the period 1975-2010.
1 Acknowledgements to follow on final version of the paper
2
Introduction
Cohen & Levinthal (1990)’s seminal study on the concept of absorptive capacity
sparked a conversation about the firm’s ability to exploit external knowledge, which it
characterized as a critical component of innovative capabilities. Absorptive capacity’s
importance lies in that it reflects the firm’s abilities to recognize the value of new
external information; assimilate it; and apply it to new commercial ends (Lane &
Lubatkin, 1998). Active engagement in R&D activities builds the ability of the firm to
identify and value external knowledge as it enables it to grow organizational
knowledge about specific areas of technology and how these areas relate to its
products and markets. The ensuing development of processes, procedures and policies
that facilitate knowledge sharing across organizational units enable the firm to build
its ability to assimilate external knowledge. Contingent on the effectiveness of the
firm’s knowledge acquisition and assimilation, the firm can build skills of employing
this knowledge to create new knowledge, products, and markets and to anticipate
future technological trends (Zahra & George, 2002).
Several studies find that absorptive capacity exhibits important effects on
various dimensions of firm performance (e.g. Rothaermel & Alexandre, 2009). For
instance, Narasimhan, Rajiv, and Dutta (2006) find a positive link between absorptive
capacity and firm performance that becomes stronger in more dynamic environments.
In the context of international joint ventures, Lane, Salk and Lyles (2001) find that as
partners acquire and assimilate new external knowledge, performance increases.
Moreover, Fernhaber and Patel (2012) conclude that absorptive capacity can have a
positive moderating impact on the relationship between product portfolio complexity
and a young firm’s performance. They suggest that absorptive capacity allows young
firms to better integrate essential external knowledge into their management teams
3
that culminates in the alleviation of potential strain on product development
processes.
Though absorptive capacity receives escalating attention by the literature, it
increasingly becomes reified since “researchers have ceased to specify the
assumptions that underlie the concept and treat it like a general-purpose solution to
an increasing number of problems” (Lane, Koka, & Pathak, 2006: 835). The
repercussions of reification can be substantial, particularly when firms misconceive
the development of distinct underlying dimensions for the development of absorptive
capacity per se (Jansen, Van Den Bosch, & Volberda, 2005). This is manifest in cases
where firms that develop their acquisition and assimilation abilities in order to benefit
from knowledge stock renewal, are left with the costs of acquisition and unexploited
knowledge. Similarly, firms that concentrate on knowledge exploitation may be able
to capture short-term profits, but lay a competence trap (Leonard-Barton, 1992;
Prahalad & Hamel, 1990) that can restrain their responses to environmental changes.
Moreover, firms which possess a strong ingenuity to understand complex technical
problems may not be as effective in translating such knowledge into product
innovation strategies (Baker, Miner, & Eesley, 2003). Therefore, new knowledge
about the effects of absorptive capacity on firm performance requires first, strategy
research to refocus on the underlying abilities of absorptive capacity and second, to
identify contextual conditions that influence the abilities’ underpinning mechanisms.
Herein lies the contribution of the current study that delves into the underlying
abilities of absorptive capacity, identifies major supporting mechanisms and
recognizes a set of boundary conditions that moderate the abilities’ impact on firm
performance.
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A major mechanism underpinning all components of absorptive capacity is
knowledge diversity that exhibits the degree of relatedness in existing knowledge and
between existing and newly acquired external knowledge. Related and therefore less
diverse knowledge, contrary to unrelated knowledge, allows the firm to sense
valuable external resources (Vasudeva & Anand, 2011), to understand them, as well
as to transfer them from other organizations (Lane et al., 2006). It enables the sharing
and transferring of externally acquired knowledge across business units and
organizational departments and therefore contributes to the development of the
assimilation ability. Moreover, it determines the promptness and ease of knowledge
retrieval (Zahra & George, 2002), the extent of the need for establishing common
interfaces between diverse knowledge vectors (Garud & Nayyar, 1994), and
knowledge transferability (Kogut & Zander, 1992), which are important prerequisites
for effective knowledge exploitation. An equally important mechanism pertains to the
organization’s communication structure. Communication structure reflects the
coordination capabilities that a firm possesses, which enable teams belonging to
different divisions to collaborate combining their varied skills, backgrounds and
knowledge to learn, assimilate and share newly acquired knowledge (Barkema &
Vermeulen, 1998; Helfat & Raubitschek, 2000).
We argue that knowledge diversity and communication structure are strongly
influenced by the diversification mode of the firm. Firms diversify in order to induce
growth, reduce the total risk of earnings variability, accelerate adaptation to
environmental change, and overall, realize positive synergies between internal
businesses (Tanriverdi & Venkatraman, 2005). From the very early studies on the
matter, diversification’s impact on performance was found to be contingent on the
mode of diversification (Rumelt, 1974). The two main modes, related and unrelated
5
diversification, differed on their underlying capacity to enable super-additive value
synergies to be captured through resource combinations (Tanriverdi & Venkatraman,
2005). Whilst the predominance of related diversification has largely rendered it the
prevailing mode (Wan, Hoskisson, Short, & Yiu, 2010) empirical studies suggest that
organizations diversify more broadly than envisaged by the relatedness logic
(Argyres, 1996; Mayer & Whittington, 2003). In effect, either mode of diversification
can modify the organization’s knowledge diversity and communication structure,
which underpin the constituent abilities of absorptive capacity. Therefore,
diversification is expected to play an important moderating role in the relationship
between absorptive capacity and firm performance.
We examined this moderating effect on a sample of 150 large firms traded in
the United States operating in the information, communication and technology (ICT)
industries for the period 1975-2010. Our base results support existing theoretical
expectations for the positive impact of the three organizational abilities underlying
absorptive capacity on performance. More importantly, our main results suggest this
impact is moderated by the firm’s diversification mode in distinct fashion.
Theory and Hypotheses
The firm’s abilities to acquire, assimilate, and exploit new external knowledge are
interrelated and jointly can produce a dynamic capability that impacts firm
performance and competitive advantage (Narasimhan et al., 2006; Teece, 2007). Their
underpinning mechanisms depend on knowledge diversity and the organization’s
communication structure that are influenced by the scope of the knowledge that the
firm desires to absorb, which varies with the mode of the diversification strategy of
the firm. Thus, understanding how diversification modes can modify the effectiveness
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of absorptive capacity and its impact on performance is paramount. Following, we
unravel the underpinning mechanisms of the three underlying abilities of absorptive
capacity and suggest how their impact on firm performance is influenced by related
and unrelated diversification.
Acquisition of external knowledge
The firm’s ability to utilize externally held knowledge is bound up with its ability to
recognize, value, and understand potentially valuable new knowledge outside the firm
through exploratory learning (Lane et al., 2006). Superior profitability is increasingly
interlinked with technology and knowledge resources and capability-based advantages
rather than with positioning advantages (Grant, 1996). That is particularly important
in contemporary competitive conditions for many product and resource markets that
often take the form of dynamic competition or hypercompetition (D’Aveni, 1994).
Consequently, the speed and effectiveness with which positions of competitive
advantage in product and resource markets are established or undermined, are critical
and are contingent on the ability of the firm to identify, value and acquire external
resources needed to initiate competitive actions (Grant, 1996).
The acquisition ability of the firm depends on the degree of diversity in
existing knowledge and diversity between existing and newly acquired external
knowledge. The firm’s prior knowledge, basic skills, and technological developments
shape a firm’s learning about its environment (Vasudeva & Anand, 2011) that is
important to sensing valuable external intangible assets (Teece, 2007). Prior scientific
or technological knowledge must be relevant to the new knowledge to facilitate
understanding and valuing the latter (Cohen & Levinthal, 1990; Phene, Tallman, &
Almeida, 2012). For example, knowledge relatedness mitigates the degree of
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difficulty in acquiring external knowledge, parts of which may exhibit tacitness in
complex processes and routines (Simonin, 1999; Van Wijk, Jansen, & Lyles, 2008).
Van Wijk, Jansen, and Lyles (2008) lend support to the relatedness argument as they
find that related knowledge and prior experience facilitate knowledge transfer
between different organizations. In the context of international joint ventures, Lane et
al. (2001) found that the relatedness of partners’ businesses and the similarity of the
problems in which they were involved were most important for the recognition of new
knowledge. Moreover, relatedness reduces knowledge complexity arising from the
interdependency of technologies, routines, individuals, and resources. Knowledge
complexity poses stress on the ability of the organization to evaluate and absorb
knowledge and understand all possible interlinkages between the different content
areas (Lane et al., 2006).
On the other hand, the breadth of categories into which prior knowledge is
organized, the differentiation of those categories, and the linkages across them must
increase over time so that they can permit firms to identify and acquire new and fairly
diverse knowledge (Volberda, Foss, & Lyles, 2010). Diversity in existing knowledge
will enable the firm to effectively identify and acquire diverse knowledge (Cohen &
Levinthal, 1990). In turn, diversity in newly acquired knowledge will enable further
expansion of the breadth, differentiation and linkages between categories of existing
knowledge. Schildt, Keil, and Maula (2012) lend empirical support to this logic in a
study of the effectiveness of collaboration between alliance members. They posit that
at the beginning of an alliance, experience with diverse knowledge prepares
companies to understand knowledge from external partners as do similarities between
the technological domains within which the companies in an alliance work. In
addition, knowledge and technological diversity can prepare companies for
8
collaboration by increasing their long-term ability to identify and acquire valuable
resources from collaborators more thoroughly. These conclusions are congruent with
Cohen & Levinthal (1990) and Zahra and George (2002) who stress that
organizations without diverse foundations of technological knowledge cannot acquire
one readily and may overlook emergent developments in areas they do not invest.
The relationship of interdependence between external knowledge and the
hitherto and future ability of the firm to value and acquire external knowledge is
conditioned by the mode and scale of firm diversification. The relationship cannot be
sustained if the level of overlap between existing and new knowledge is marginal
(Lane & Lubatkin, 1998). That is because diversification into related technological
and knowledge domains impels the organization to expand its current acquisition
ability and induces its predictive power about emerging consumer needs. Therefore,
organizations which diversify in related areas are expected to reinforce the firm’s
acquisition ability and its positive impact on firm performance.
On the other hand, firms diversifying in unrelated areas may impair
performance as they exert mounting pressures to the effectiveness of their current
ability to recognize, value and absorb unrelated external knowledge. As diversity in
unrelated areas increases, managers experience increased coordination and
communication costs (Fernhaber & Patel, 2012) that mitigate their ability to make
optimum decisions about knowledge acquisition. Empirical evidence shows that firms
that search for external knowledge beyond a small number of sources augment their
innovative performance, but as the number of external sources of new knowledge
increases this relationship exhibits decreasing returns (Laursen & Salter, 2006). We
can therefore expect that the two modes of diversification moderate the effect of the
acquisition ability of the firm on its performance as follows:
9
H1a: Related diversification has a positive moderating effect on the relationship
between the firm’s ability to acquire new external knowledge and performance.
H1b: Unrelated diversification has a negative moderating effect on the relationship
between the firm’s ability to acquire new external knowledge and performance.
Assimilation of external knowledge
The development of processes, policies, and procedures that facilitate sharing and
transferring externally acquired knowledge within the organization manifest the
organization’s assimilation ability (Cohen & Levinthal, 1990; Lane et al., 2006). The
assimilation of external knowledge can have important implications for both
organizational performance and innovativeness (Gupta & Govindarajan, 2000; Lyles
& Salk, 2006; Van Wijk et al., 2008). On the one hand, research has shown that
effective knowledge learning and transfer contribute to the development of difficult to
imitate organizational capabilities, which subsequently enhance performance
(Szulanski, 1996). Lane et al. (2001) cast support with a study of partner knowledge
sharing in international joint ventures where they find that the more the partners
acquired and assimilated new external knowledge the higher was the joint venture’s
performance. On the other hand, existing research has shown that organizational
knowledge learning and transfer relates to innovativeness. According to Cohen and
Levinthal (1990), knowledge transfer and accumulation facilitate the efficient
utilization of knowledge and enable organizations to better understand and assess the
nature and commercial value of knowledge and technological advances. In addition,
knowledge assimilation stimulates the blending of existing and newly acquired
knowledge and reinforces the organization’s capacity for making fresh associations
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and linkages (Jansen et al., 2005). In turn, knowledge assimilation promotes the
generation of novel ideas and the development of new products (Tsai, 2001).
Because learning is a cumulative process shaped by pre-existing knowledge,
organizations can achieve better learning performance when the new knowledge
domain objective is related to what is already known (Zahra & George, 2002). Hence,
to assimilate new and externally acquired knowledge, some degree of overlap is
required with an organization’s previous knowledge (Cohen & Levinthal, 1990; Zahra
& George, 2002). However, Lane and Lubatkin (1998) and Schildt et al. (2012) find
that knowledge and technological similarity between firms in joint ventures increases
the ability of firms to rapidly transfer knowledge from one partner to another at best
moderately, while it keeps the technological domain of the partnership quite narrow
reducing opportunities to learn. This can render a firm that invariably concentrates on
related knowledge acquisition unable to successfully explore, learn, share, and
integrate innovative knowledge (Phene et al., 2012).
The above arguments suggest that the ability of assimilation of acquired
knowledge as a cognitive process is bound up with the knowledge and technological
diversity of the firm (Schildt et al., 2012). Diversity in prior related knowledge can
play a critical role as it can increase the possibility that newly acquired and inherently
uncertain knowledge will overlap with the existing domains of firm knowledge. That
is in accord with Cohen and Levinthal (1990), who draw particular attention in
contexts where there exists high uncertainty about the knowledge fields from which
potentially useful information may emerge. They suggest that firms that diversify in
related product markets and resources will expand their assimilation’s effectiveness.
However, the impact of the firm’s unrelated diversification on the power of its
assimilation ability is more complicated. Business units that typically operate as part
11
of a unified firm, are more likely to learn, share, and transfer knowledge that is
reasonably related to what they already know (Van Wijk et al., 2008). Hence, the
existing structure of communication of knowledge across and within business units
underpins the organization’s ability to assimilate external knowledge (Volberda et al.,
2010). Diversifying in highly unrelated areas can cause complications in the structure
of communication since unrelated diversification affects the business units’ velocity
to assimilate the newly acquired knowledge and the effectiveness of ensuing intra-
organizational transfer of knowledge that are important for organizational
performance. This is consistent with Lei and Hitt (1995) who suggest that high levels
of merger and acquisition activity in unrelated knowledge domains are expected to
produce a diminished resource base for organizational learning and technology
development. Unlike situations in which information flow is definite and is clear
where in the firm or subunit a piece of information can be applied, the effectiveness of
knowledge transfer is challenged (Cohen & Levinthal, 1990). Under such
circumstances, the ideal knowledge structure for the subunit and the organization as a
whole should reflect a good balance between overlapping and non-overlapping,
though related knowledge (Leiblein, 2011). This balance notwithstanding, is upset
with diversification in unrelated product and resource markets.
Moreover, diversification strategy is interlinked with organizational structure
(Chandler, 1962; Hall & Saias, 1980; Hill & Hoskisson, 1987; Rumelt, 1974) that
greatly influences the organization’s communication structure (Lane et al., 2006;
Protogerou, Caloghirou, & Lioukas, 2011; Van Den Bosch, Volberda, & De Boer,
1999). Chandler (1962) and Rumelt (1974) emphasized that no two firms possess the
same organizational structure that comprises systems of control, planning,
information flow, methods of reward and techniques of coordination. Their shared
12
thesis was that diversification strategy places great strains on organizational structure
that commands the refocus of R&D and performance criteria, the restructuring of
reward systems, and re-evaluation of decisions about resource development and
allocation2
Hall & Saias, 1980
. Several cases of M&As which intended to exploit promising
combinations of resources or attack new markets and technologies failed because of
the clash of cultures and the incapacity of the corporate structure to integrate them
( ). Therefore, organizational structure has a strong impact on the
effectiveness of communication structure as it determines the strength of coordination
capabilities related to knowledge sharing according to which teams belonging to
different firm divisions and departments work together combining their varied skills,
backgrounds and knowledge to learn, assimilate and share newly acquired knowledge
(Barkema & Vermeulen, 1998; Helfat & Raubitschek, 2000).
The impact of organizational structure on communication structure should
vary among the two forms of corporate diversification. Several investigators (e.g. Hill
& Hoskisson, 1987; Michel & Hambrick, 1992) argue that unrelated diversifiers
rarely promote synergies or interrelationships among divisions, but instead emphasize
financial controls that facilitate capital allocation based on relative yields. Hill and
Hoskisson (1987) posit that excessive integrative effort in an unrelated firm would
compromise autonomy and accountability, thereby making the realization of financial
economies difficult and low performance likely. Therefore, corporate managers
generally would refrain from direct intervention in divisional strategy and would not
seek synergistic relations between unrelated divisions (Michel & Hambrick, 1992).
On the other hand, related diversifiers emphasize strategic control systems designed to
encourage resource- and information-sharing among divisions that often include
2 Ensuing studies stress a reciprocal relationship between strategy and structure (e.g. Hall & Saias, 1980; Hill & Hoskisson, 1987).
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monitoring operational and product-market information to enable coordination among
divisions and identify possible synergies. We therefore expect the two forms of
diversification to moderate the positive relationship between the firm’s ability to
assimilate new external knowledge and performance as follows:
H2a: Related diversification has a positive moderating effect on the relationship
between the firm’s ability to assimilate new external knowledge and performance.
H2b: Unrelated diversification has a negative moderating effect on the relationship
between the firm’s ability to assimilate new external knowledge and performance.
Exploitation of external knowledge
Absorptive capacity extends to the organization’s ability to exploit external
knowledge for the creation of new commercial ends and new knowledge and to
predict future technological developments and opportunities ahead of its competitors
(Lane et al., 2006; Volberda et al., 2010). As an organizational capability,
exploitation can increase economic performance by refining, extending, and
leveraging existing competencies or creating new ones by incorporating acquired and
assimilated knowledge into its operations. Whereas exploitation may occur
serendipitously, it is the presence of systematic and organized routines that can allow
the organization to continuously exploit knowledge over prolonged periods for the
creation of new innovative goods, knowledge and markets (Zahra & George, 2002).
The ability of the firm to exploit the specialized knowledge stored within
individual organizational members, such as employees and business units, is primarily
determined by knowledge diversity (Grant, 1996). Particularly for the exploitation
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ability, knowledge diversity is manifest in the speed and difficulty of knowledge
retrieval (Zahra & George, 2002), the demand for common interfaces between
available knowledge vectors (Garud & Nayyar, 1994), and the transferability of
knowledge (Kogut & Zander, 1992). Diversification strategy, by influencing these
dimensions, alters the organization’s knowledge diversity and therefore, its
exploitation ability.
The swift retrieval of assimilated knowledge and technologies from the firm’s
depositories underlies the timely recognition and exploitation of emergent market
opportunities (Zahra & George, 2002). Opportunities that fall within diverse still
related regions of the current knowledge of the firm should place it in a more
responsive position than opportunities arising from unrelated territories. The
overarching logic is that retrieval speed depends on the intensity of using existing and
new knowledge for problem solving, e.g. for new product development (Cohen &
Levinthal, 1990), the recentness of knowledge use, and the proximity of new
knowledge to the organization (Garud & Nayyar, 1994). Therefore, new knowledge
acquired by organizations which diversify into related areas is more readily integrable
into existing knowledge. In addition, related diversity in a newly acquired knowledge,
product or capability can allow the organization to gain competitive advantages
through difficult to imitate combinative schemes of complementary resources.
Moreover, firms have difficulty retrieving old unused knowledge or skills and
only part of a firm’s memory is likely to be evoked at a particular time (Garud &
Nayyar, 1994). Hence, firms must be able to combine newly acquired and assimilated
knowledge with existing knowledge promptly following acquisition, since shortened
product life-cycles and increasing rivalry exert mounting pressures on market
opportunities. Early combination weakens the prerequisite for adaptation of retrieved
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knowledge to new knowledge and changed consumer needs, social and economic
circumstances. This suggests smaller lapses between product inception and
commercialization, greater responsiveness to market opportunities and superior
performance for firms that diversify in related knowledge with a given level of
exploitation ability.
The combination of different resources and knowledge from different units
within the firm requires establishing common interfaces among knowledge vectors.
That implies that the organizational design must facilitate information processing
among diverse groups within the firm, such as through lateral information processing
mechanisms. To deal with knowledge ambiguity, facilitate choice of constituent
knowledge, and accelerate retrieval, firms employ rich media to exchange views and
opinions among managers about the combinative future of technologies. They may
use a mixture of formal planning mechanisms, personal meetings and job rotation
systems to draw out, contemplate and share their understanding about the prospects of
technologies before choosing the combination of available knowledge vectors (Garud
& Nayyar, 1994). Since unrelated diversifiers are inclined to adopt variations of M-
form designs with autonomous business units (Chandler, 1962; Rumelt, 1974), they
inherently elevate the degree of difficulty to develop such mechanisms. This suggests
that unrelated diversifications are negatively associated with the effectiveness of rich
media and coordination and constrain the exploitation ability of the firm.
A similar logic underlies the transferability of “know-how knowledge” (Kogut
& Zander, 1992) across business units. Know-how knowledge refers to hitherto
practice inside firms and business units on matters such as the transformation of
knowledge inputs into outputs, the commercialization and management of new
product portfolios. Its transferability underpins the regeneration and synthesis of
16
assimilated knowledge and attainment of new knowledge combinations. Know-how
knowledge is contingent on individuals’ skills and tacit knowledge that can be
extremely difficult to pass on, especially if human intelligence is dedicated on solving
differentiated problems specific to the business unit of origin (Kogut & Zander,
1992). The teaching of know-how requires frequent interaction within small groups,
often through the development of a unique language or code that is less attainable
with the establishment of increasing numbers of autonomous business units in the
unrelated firm. Therefore, diversification in unrelated areas impairs the transferability
of know-how within the multi-business firm reducing the potential to effectively
exploit emerging market opportunities. Moreover, a consequence of engaging in the
development of a vast array of unrelated products is an increased state of complexity
and information processing difficulty associated with product portfolio management
(Fernhaber & Patel, 2012; Vasudeva & Anand, 2011). The more diverse the product
portfolio the higher the coordination and communication costs that managers incur
that may overwhelm the positive implications emanating from innovativeness and
access to diverse markets. Therefore we can expect that:
H3a: Related diversification has a positive moderating effect on the relationship
between the firm’s ability to exploit new external knowledge and performance.
H3b: Unrelated diversification has a negative moderating effect on the relationship
between the firm’s ability to exploit new external knowledge and performance.
17
Methods
Performance Measure
Performance was measured using a firm’s return on assets (ROA) (Miller, 2004;
Robins & Wiersema, 1995). ROA has been shown to be related to a variety of other
indicators of firm financial performance and has been widely employed in the
strategy-performance literature (Hoskisson & Hitt, 1990). Despite the existing debate
over the use of accounting versus market performance measures, Robins & Wiersema
(1995) report a number of advantages for the former, including their close connection
to the decision variables controlled by managers and their enabling direct comparison
with a substantial body of research on diversification and performance in strategic
management.
Acquisition Ability
Several studies have operationalized the unified construct of absorptive capacity as
R&D intensity (R&D expenditure to sales) (e.g. Meeus, Oerlemans, & Hage, 2001;
Rothaermel & Alexandre, 2009). However, R&D spending, as a non-core skill
(Teece, 2007), cannot reflect or give evidence of the quality of the firm’s ability to
integrate and combine assets including knowledge, which pertain to core skills (Grant,
1996; Kogut & Zander, 1992). Moreover, knowledge depositories and diversity can
differ greatly among firms despite similarities in their R&D spending (Schildt et al.,
2012). Therefore, Cohen & Levinthal (1990)’s original use of R&D intensity as a
proxy for technological diversity, which is a central determinant of absorptive
capacity, is unsound because the two are conceptually distinct (Schildt et al., 2012).
The empirical limitations of employing R&D intensity as an all-encompassing
measure of absorptive capacity is evident in the low explanatory power of R&D
18
spending on firm performance (Lane et al., 2006). This calls into question the
usefulness of this unrefined, absolute measure of absorptive capacity (Lane &
Lubatkin, 1998).
Instead, in this study, we consider R&D intensity as an appropriate measure of
the acquisition ability of the firm. According to Cohen and Levinthal (1990), a firm’s
ability to acquire knowledge from its external environment is a byproduct of its own
R&D. R&D efforts provide an in-house technical capability that can keep firms
abreast of the latest technological developments and facilitate the identification,
valuation, and acquisition of new technology developed elsewhere (Lane et al., 2006).
Moreover, R&D activity can be thought of as a form of search for new knowledge and
products that allows the firm to sense what is going on in its business ecosystem
(Teece, 2007).
Assimilation Ability
The assimilation ability refers to the organization’s ability to understand technological
advances and make fresh associations and linkages between existing and newly
acquired knowledge. We therefore expect the assimilation ability of the firm to be
reflected in the diversity of knowledge resources it utilizes to produce new knowledge
and commercial ends. We operationalize the assimilation ability as the diversity in
citations the firm capitalizes on to produce its own patents. To measure diversity in
technological resources, we calculated a concentric measure of diversification
originally used by Caves, Porter, and Spence (1980) using firm patents and patent
citations that we translated both to four-digit SIC codes using the concordance index
developed by Silverman (1999). The index is given by:
19
i ij ji j
Assimilation Ability p d p=∑ ∑ (1)
where ip is the proportion of patent applications in 4-digit SIC i; jp is the proportion
of patent citations in 4-digit SIC j; and ijd equals 1,2,3,4 if i and j are in the same
4,3,2,1-digit SIC, respectively. The index ranges from 0 to 2 and is increasing in
diversity. The index compares each patent with its citations measuring the “distance”
between patents and citations concentrically (Argyres, 1996).
Exploitation ability
The exploitation ability refers to the organization’s ability to exploit external
knowledge for the creation of new knowledge and product outputs. We expect this
ability to be reflected in the diversity in the firm’s technological outputs. To
operationalize exploitation ability we calculated a concentric measure of
diversification using patents that we translated to four-digit SIC codes using the
concordance index developed by Silverman (1999). The index is given by:
t i ij ji j
Exploitation Ability p d p=∑ ∑ (2)
where ip is the proportion of patent applications in 4-digit SIC i in year t; jp is the
proportion of patent applications in 4-digit SIC j; and ijd equals 1,2,3,4 if i and j are in
the same 4,3,2,1-digit SIC, respectively. The index ranges from 0 to 2 and is
increasing in diversity. Patents assigned to more than one SICs were treated as
different applications in order to better capture firm-level technological diversity. The
20
index compares each patent with every other patent in the firm’s portfolio measuring
the “distance” between patents concentrically (Argyres, 1996).
Modes of diversification
Existing operationalizations of modes of diversification center on certain functional
resources such as product relatedness (Rumelt, 1974), technological relatedness
(Robins & Wiersema, 1995; Silverman, 1999), managerial relatedness (Prahalad &
Bettis, 1986), human resources relatedness (Farjoun, 1998), or a combination
(Tanriverdi & Venkatraman, 2005). Researchers resort to indirect measures that
capture the industry participation profiles of firms and the resource similarities of
industries (Tanriverdi & Venkatraman, 2005). In this study, we use such an indirect
measure for corporate diversification by adopting a widely used entropy measure of
diversification developed by Jacquemin & Berry (1979), which allows for the
calculation of a firm’s total, related, and unrelated diversification. Total
diversification (DT) is computed as follows:
1lnN
ii j i
DT PP=
=
∑ (3)
where N is the number of industry segments a firm operates in at the 4-digit SIC level
and Pi is the share of the ith segment in the total sales of the firm. If we let the N
number of industry segments at the 4-digit SIC level aggregate into M industry groups
at the 2-digit SIC level, related diversification (DR) can be computed as follows:
1lnji j
i j i
DR PPε
=
∑ (4)
21
where jiP is defined as the share of segment i of group j in the total sales of the group.
Unrelated diversification (DU) derives from the difference between equations (3) and
(4). According to Palepu (1985) the entropy measure considers three important
elements of diversification: the number of segments in which a firm operates, their
degree of relatedness, and their relative importance for the firm’s total sales.
Controls
Firm size
Firm size has been considered as an indicator of market power and scale economies.
Empirical evidence exists linking size to profitability (Bettis, 1981; Robins &
Wiersema, 1995). Market power may allow control over pricing and economies of
scale can allow cost reductions. Combined they can enable large firms to achieve high
levels of profitability. We control for the firm’s size with the log of the number of
firm employees and expect it to have a positive relationship with performance.
Industry concentration
From the early works in industrial organization (Bain, 1956) industry concentration
has been considered as a strong indicator of barriers to entry. In highly concentrated
industries, market power enjoyed by firms may allow them to sustain high levels of
profitability. This measure reflects a firm’s relative sales in different industries by
multiplying the proportion of firm sales in a focal industry with the concentration
ratio of the industry and aggregating as follows:
4t i iIndustry Concentration CR P=∑ (5)
22
where CR4i is the four-firm concentration ratio for the 2-digit SIC industry i and Pi is
the proportion of a firm’s sales in the 2-digit SIC industry i. Prior empirical evidence
in strategy (Markides, 1995) suggests a positive relationship between industry
concentration and firm profitability.
Industry profitability
We account for the profitability in a firm’s industries to control for any industry effect
not captured by industry concentration. According to Robins & Wiersema (1995) the
interrelationships between the firm’s businesses may have an impact on performance.
A weighted measure of industry profitability can be estimated by computing the
average profitability of each 4-digit SIC industry in which a focal firm operates,
multiply it by the proportion of firm sales in the industry and aggregate for the firm as
follows:
i iIndustry Profitability ROA P=∑ (6)
where ROAi is the average return on assets for industry i and Pi is the proportion of a
firm’s sales in SIC i. Industry profitability is expected to have a positive relationship
with firm profitability.
Debt burden
Managerial discretion in the allocation of organizational resources across the
organization’s operations can be reduced in the face of high debt level. In effect, the
firm’s debt burden compels management to invest wisely and be more efficient
(George, 2005). We measure debt burden as the firm’s debt to shareholder equity ratio
(Markides, 1995).
23
Capital investments
We control for the firm’s capital investments, an indicator of the firm’s tangible
nature of assets used in firm growth, which may result in higher total factor
productivity and higher performance not attributable to absorptive capacity or
diversification (Miller, 2006; Palich, Cardinal, & Miller, 2000). Capital investments is
measured as the firm’s capital expenditures as a percent of sales. We expect it to have
a positive relationship with firm performance.
Technological output
Prior research demonstrates a positive relationship between technological output and
measures of firm performance (Miller, 2006). We control for the effect of
technological output by incorporating in the analysis the firm’s number of patents to
its sales.
Labor Productivity
Changes in labor productivity attributed to renegotiated labor contracts, new
investments in technology, and improvements in the monitoring from firm managers
during the study period can have an important effect on firm performance (Markides,
1995). We control for labor productivity using the ratio of the number of employees
to firm sales, with higher productivity expected to have a positive relationship with
performance.
Foreign sales
The literature on international diversification suggests a positive relationship between
foreign operations and profitability (Capar & Kotabe, 2003; Kotabe, Srinivasan, &
24
Aulakh, 2002; Lu & Beamish, 2004; Wan & Hoskisson, 2003). We include in the
analysis the firm’s foreign to domestic sales ratio to account for the part of variation
in firm performance attributed to variations in the extent of the firm’s international
diversification.
Advertising Intensity
Organizations that spend more resources to interact with customers are more likely to
understand complex consumer needs, achieve product differentiation relative to
competition, attain superior brand equity and in effect financial performance (Day,
1994; Dutta, Narasimhan, & Rajiv, 1999; Narasimhan et al., 2006; Song, Droge,
Hanvanich, & Calantone, 2005). We control for the effect of the firm’s marketing
capability on performance by including in the analysis the firm’s ratio of advertising
expenses to sales.
Complexity of Organizational Structure
Organizational structure determines the coordination of knowledge sharing between
business units, divisions, and operational departments and consequently impacts
organizational performance (Chandler, 1962; Hill, Hitt, & Hoskisson, 1992; Rumelt,
1974). We account for this relationship by including in the analysis a variable that
looks into the degree of organizational structure and knowledge relatedness between a
firm and its subsidiaries. The variable is calculated as follows:
t j jtj
Complextity of Organizational Structure d p=∑ (7)
25
where jtp is the proportion of subsidiaries in the 4-digit SIC j in year t; and jd takes
the value 1,2,or 3 if j and the firm’s SIC are in the same 3,2,1-digit SIC, respectively.
The index ranges from 0 to 3 and is increasing in complexity as it considers a firm
whose subsidiaries are unrelated to its core industry as one requiring more complex
organizational structure. The variable measures the “distance” between the firm’s core
industry classification and its subsidiaries’ classifications. Greater distance suggests
additional strains on the firm’s organizational structure to adjust existing systems of
control, planning, information flow, methods of reward and techniques of
coordination.
Time Effects
Because our study examines performance effects over a large number of years, we
incorporated in the analysis year dummies to control for possible unobserved time-
specific effects and the effects of serial correlation. We followed Phene et al. (2012)
and created dummies based on blocks of five years: 2005-2010 (the base), 2000-2005,
1995-2000, 1990-1995, 1985-1990, 1980-1985, and 1975-1980.
Industry Effects
According to Hoskisson and Hitt (1990) and Palich et al. (2000), one important
limitation of previous studies of the relationship between strategy and performance is
that they do not control for industry effects. In the present study, accounting for
industry effects may allow unique variance explained by the dimensions of absorptive
capacity and its interactions with diversification to be unmasked. To control for
performance variations between firms due to industry structure effects we include in
the analysis 2-digit SIC industry dummies.
26
Sample selection
The sample consists of 150 large firms traded in the United States operating in the
information, communication and technology (ICT) industries. Following the
recommendation of previous empirical studies we examine the relationship between
strategy-performance in a fine-grained study within a focused set of industries as
opposed to across multiple and diverse industries (Palich et al., 2000). Therefore,
along with the explicit control for industry effects and the incorporation of industry
and concentration effects that can have a strong influence on firm performance, our
sample implicitly renders our research findings robust to industry structure. Sample
firms were randomly selected based on a minimum of $1billion sales for 2010.
The ICT industries are characterized by a dynamic environment with rapid
technological change and intense restructuring activity. They exhibit extensive
consolidation through industry alliances and mergers, the combination of technology
and network platforms, and the integration between services and markets (Bum Soo,
Choi, Barnett, Danowski, & Sung-Hee, 2003; Greenstein, 2000; Wirtz, 2001). The
integration of technologies creates conditions of market failure (Gambardella &
Torrisi, 1998) in which organizations have increasing incentives to expand
diversification on the expectation they will benefit from an “internal capital market”
that could be more efficient for trading and sharing resources, knowledge and
technology (Chatterjee & Wernerfelt, 1991; Hill et al., 1992).
Data were collected from multiple sources. Thomson Reuters’ Derwent
database, one of the world’s most comprehensive databases of patent documents, was
used for the collection of patent data. Since large multi-business firms frequently
assign patents to subsidiaries, we used the Bureau Van Dijk’s Orbis database to
identify every subsidiary – domestic and foreign – of each firm in the sample. We
27
were thus able to search the Derwent database for patents assigned to any of these
parent or subsidiary names, and aggregate all patents at the parent level. We collected
a total of 1,914,597 patents assigned to the sample firms and their subsidiaries
between 1966 and 2010. Each patent and its cited patents are identified by
International Patent Class (IPC). We translated all patents and cited patents to the
distribution of their application across industries using the concordance index
developed by Silverman (1999), which assigns each patent to four-digit SIC codes.
Compustat was the source for the financial3
1992
, industry, and segment data. Davis
and Duhaime ( ) note that the use of Compustat for the study of diversification
offers some advantages. The assignment of business activities to Compustat segments
is conducted by respondents in firms and the data are thus expected to involve some
information about managers’ views of relationships among businesses. This additional
information can be valuable in research that employs the entropy index of
diversification (Robins & Wiersema, 1995). Data from Compustat span from 1975 to
2010. Sample firms fall in seven 2-digit industries: 35 - Industrial And Commercial
Machinery And Computer Equipment; 36 - Electronic And Other Electrical
Equipment And Components, Except Computer Equipment; 37 - Transportation
Equipment; 38 - Measuring, Analyzing, And Controlling Instruments; Photographic,
Medical And Optical Goods; Watches And Clocks; 48 - Communications; 50 -
Wholesale Trade-durable Goods; and 73 - Business Services.
The complete dataset used in the analysis comprises an unbalanced dataset of
2,344 firm-year observations with 141 firms as 9 firms were dropped from the sample
due to missing data. Table 1 presents summary statistics for and pairwise correlations
between our dependent, independent, and control variables. Interestingly, the
3 Financial data were deflated and converted to constant US$ of 2005 using the CPI.
28
correlation coefficient between the assimilation and exploitation abilities of the firm is
positive and high suggesting that firms with higher assimilation ability tend to also
have higher exploitation ability. Based on the underlying variables, the positive
correlation implies that the sample firms expand the breadth of knowledge they use in
the production of new technological output over time and also increase the range of
applications of each patent produced. Moreover, their low correlations between the
assimilation and exploitation abilities with the acquisition ability suggest that the
operationalization of an absolute measure of absorptive capacity as R&D intensity by
existing studies is unsound.
- Insert Table 1 about here -
Results
Table 2 presents the results from our analysis. The models were estimated with
generalized least-squares regression that accounts for the problem of
heteroskedasticity we diagnosed in our data. Otherwise, the estimation of our models
with ordinary least-squares would result in inefficient estimates (Cameron & Trivedi,
2009). Previous studies of strategy’s effects on performance recommend the use of
lagged effects in empirical analyses. In particular, changes in industry structure,
industry concentration, and also firm diversification strategy are not fully realized
until a number of years has elapsed (Markides, 1995). We account for lagged effects
by lagging all control variables, apart from industry and time dummies, for one year.
The first model on Table 2 presents the output when ROA is regressed on only the
control variables.
29
In the next two models, we introduce the effects of the three dimensions of
absorptive capacity and the two modes of diversification. With regard to the size of
lags for the main independent variables, we follow a more systematic approach, which
represents a balance between the rationale used for the controls, the contribution of
the lagged effects to the explanatory power of the model, and the ensuing loss of
observations. In particular, we allow for longer lags for the effects of absorptive
capacity on firm performance than for the effects of diversification on performance.
This is because we expect that changes in firm resources require time before they can
influence hitherto abilities to acquire, assimilate, and exploit external knowledge.
Moreover, following existing studies of the effect of firm diversification on
performance (Markides, 1995) and studies of the transformative capacity of the firm
(Garud & Nayyar, 1994), we tested alternate models that involved the 4- to 5-year
lagged effects of diversification and the 2- to 3-year lagged effects of absorptive
capacity. For the evaluation of alternative model specifications we capitalized on the
Akaike and Bayesian Information Criteria. The model specification that resulted in
the loss of the fewest data points and yielded the lowest AIC and BIC values involved
two-year and four-year lags for the effects of absorptive capacity and diversification,
respectively.
The last model on Table 2 incorporates the interaction effects between the
acquisition, assimilation, and exploitation abilities of the firm and related and
unrelated diversification. The incorporation of variables that suffered from several
missing values along with the use of long lags, culminated in the drop of 17 firms and
323 firm-year observations from our sample. To ensure that our results would not
suffer from a possible selection bias attributed to the smaller sample size, we tested
whether the firms dropped from the model and those preserved for the remaining of
30
the analysis differed in size or industry membership. Our t-tests rejected the
hypotheses of differences across the two groups of firms.
- Insert Table 2 about here -
With regard to the control variables, sample firms that improve their
productivity, expand international sales, and invest more in advertising exhibit higher
performance on average. On the other hand, firms with more complex organizational
structures experience lower performance. Contrary to our expectations, the firm’s
size, technological output, capital investments, and debt burden have negative and
statistically significant effects on firm performance. Moreover, industry profitability
does not have a statistically significant effect.
Our results confirm existing theoretical expectations about the positive effect
of absorptive capacity on firm performance and the opposite effects for the two forms
of diversification on performance. Specifically, the Base and Diversification models
on Table 2 suggest that the firm’s acquisition, assimilation, and exploitation abilities
induce performance. Moreover, related diversification has a positive effect whereas
unrelated diversification has a negative effect. The Interactions model, based on
which we test this study’s hypotheses, suggests that the main effects remain stable at
large, apart from the effect of unrelated diversification which changes sign and
becomes positive and statistically significant.
The majority of the interaction effects are statistically significant lending
support to four of our hypotheses whilst they reject the remaining two. In particular,
the interaction effect between the acquisition ability of the firm and related
diversification is positive and statistically significant, supporting H1a and suggesting
31
that related diversification reinforces the acquisition ability’s underlying mechanisms
that contribute to firm performance. This relationship is illustrated in Figure 1 where
Graph (a) exhibits how the marginal effect of the firm’s acquisition ability on
performance is modified with higher values of related diversification. Graph (a)
shows a linear moderating effect for related diversification on the impact of the
acquisition ability on performance that is positive and gradually increasing. Contrary
to our expectations, H2a that assumed a positive moderating effect for related
diversification on the impact of the assimilation ability of the firm is rejected. Not
only is the interaction effect negative, but it is also statistically significant, suggesting
that the expansion of related diversification undermines the mechanisms that underpin
the firm’s ability to assimilate and share existing and newly acquired knowledge. This
relationship is illustrated in Graph (b) that allows us to make additional important
observations. For instance, low levels of related diversification moderate the impact
of the assimilation ability on performance positively. This result partially supports
H2a, however, as related diversification increases and passes the sample firms’
average related diversification, the moderating effect becomes negative. This suggests
a non-linear moderating effect for related diversification on the assimilation ability,
since the effect becomes increasingly negative as the firm increasingly exceeds the
sample’s mean related diversification. As regards H3a, the coefficient of the
interaction variable between related diversification and the exploitation ability is
positive and statistically significant. This supports our hypothesis that related
diversification has a positive moderating effect on the relationship between the
exploitation ability of the firm and performance. The moderating effect is illustrated
in Graph (c) where related diversification shows a positive but decreasing effect on
the relationship between the exploitation ability of the firm and performance.
32
The results also support H1b and H3b and reject H2b, which pertain to the
moderating effects of unrelated diversification on the three dimensions of absorptive
capacity. The coefficients for the interaction variables between unrelated
diversification and the acquisition and exploitation abilities of the firm are expectedly
negative and statistically significant. These findings are illustrated in Graphs (d) and
(e). Interestingly, contrary to the moderating effect of unrelated diversification on the
relationship between the exploitation ability and performance, the moderating effect
on the relationship between the acquisition ability and performance is non-linear.
Accordingly, firms which preserve unrelated diversification lower than the sample’s
mean, reinforce the impact of their acquisition ability on performance. It is not after
they exceed the sample’s mean unrelated diversification that firms exhibit a
decreasing effect for the acquisition ability on performance.
- Insert Figure 1 about here -
Discussion
In this paper, we argue that due to the reification of absorptive capacity (Lane et al.,
2006) existing empirical research has shed limited light on its underlying abilities that
drive its impact on firm performance. As this calls for an expansive view that
accounts for contextual conditions that may influence absorptive capacity, we delved
into its constituent dimensions, which Cohen and Levinthal (1990) put forward as the
firm’s acquisition, assimilation, and exploitation abilities, and identified important
boundary conditions that can moderate their impact on firm performance. We
postulated that the main mechanisms underpinning the dimensions of absorptive
capacity relate to knowledge diversity and the organization’s communication
33
structure. The former is reflected in the speed and difficulty of knowledge retrieval,
the demand for common interfaces between available knowledge vectors, and the
transferability of knowledge, whereas the latter determines the effectiveness of
internal knowledge transfer and sharing. We then examined how related and unrelated
diversification can influence these mechanisms and consequently, moderate the
impact that absorptive capacity has on firm performance. Our results support existing
theoretical expectations that suggest the positive impact of the three dimensions of
absorptive capacity on performance and the opposite effect of the two modes of
diversification. More importantly, our results illustrate that the effects of the
constituent abilities of absorptive capacity are conditioned by the firm’s mode of
diversification strategy in different fashions.
Our study allows us to make several important contributions to the literature.
First, by disassembling the construct of absorptive capacity, we empirically find that
each dimension has a distinct positive effect on firm performance. This finding
suggests that the misconception of absorptive capacity as a unified construct detached
from its underlying abilities may render this capability of strategic value largely
unexploited. The overarching logic is that firms that invest in developing any of the
constituent abilities may attain performance improvements but fall into the fallacy of
building absorptive capacity. In effect, firms may focus on the valuation and
assimilation of external knowledge and thereby renew their knowledge stock and gain
access to unique resources, but remain with the costs of acquisition if they do not
convert resources into innovative outputs. Moreover, the invariant focus on the
resource exploitation and production of new commercial ends may limit the firm’s
resilience and responsiveness to environmental and technological shifts.
34
Second, by looking into the underlying abilities of absorptive capacity and
identifying their supporting mechanisms, we recognized important boundary
conditions whose effect appears to be critical. Absorptive capacity depends on
diversity among internal and external knowledge and the communication structure of
the firm, which jointly determine the development of its underlying abilities. This
dependence renders absorptive capacity vulnerable to the firm’s actions that can alter
the qualities of underpinning mechanisms and ultimately moderate its effect on
performance. Specifically, we posited and examined the modifying effect that modes
of diversification strategy can have on the relationship between absorptive capacity
and firm performance by influencing the underpinning mechanisms of its constituent
abilities. Our expectations suggested that related and unrelated diversification
strategies can alter the nature of knowledge diversity and exert differential pressures
on the firm’s communication structure. Correspondingly, our empirical findings
report that these effects have important and different moderating influence on firm
performance.
Third, the moderating impact of diversification strategy unearths a deeper
insight. Namely, absorptive capacity and the diversification mode are strategic tools
that cannot be designed and implemented in isolation, for their interdependence
requires the formulation and implementation of an orchestrated strategy. On the one
hand, absorptive capacity reflects the scale of the ability of the firm to acquire,
assimilate, and exploit externally acquired knowledge. On the other hand, our findings
suggest that related diversification reinforces the positive impact of the acquisition
and exploitation abilities of the firm on its performance. Moreover, unrelated
diversification moderates these effects negatively, though sufficiently low levels of
unrelated diversification reinforce the acquisition ability of the firm. The functions of
35
absorptive capacity along with our empirical findings jointly suggest that
organizations cannot diversify unreservedly, because hitherto amounts of absorptive
capacity are decisive for the effective implementation of diversification strategy and
vice versa. Therefore, according to this reciprocal relationship the existing absorptive
capacity of the firm determines the feasible type and magnitude of newly acquired
knowledge and resources it can absorb. Moreover, unless the organization pushes the
existing frontiers of absorptive capacity through a carefully designed diversification
mode the firm risks to fail to recognize emerging opportunities to create competitive
advantages (Zahra & George, 2002).
Fourth, our study additionally sheds some light on the ongoing debate in
strategy research over the effects of related and unrelated diversification on firm
performance. The prevailing resource-based view (RBV) of diversification postulates
that resource relatedness can allow the production of super-additive value and sub-
additive costs that improve firm performance (Farjoun, 1998; Markides &
Williamson, 1994; Robins & Wiersema, 1995). This reasoning is consistent with our
absorptive capacity perspective, which emphasizes the role of related knowledge in
building the acquisition, assimilation, and exploitation abilities as well as in
mitigating the pressure exerted on the organization’s communication structure.
Despite that our empirical findings suggest that the assimilation ability of the firm is
impaired when related diversification exceeds the sample’s average, overall, the
interplay between absorptive capacity and related diversification is reinforcing and
yields positive returns. On the other hand, the logic of synergies and path-dependence
of the RBV is too narrowly defined to account for the firm’s efforts to alleviate the
risk attached to resource allocation in conditions of market failure, which lead to
unrelated diversifications (Ng, 2007; Villalonga, 2004). Our empirical examination
36
that looks into a sample of firms from markets that exhibit imperfections
(Gambardella & Torrisi, 1998) shows that unrelated diversification does contribute to
performance. The base effect of unrelated diversification was negative and
statistically significant, but it reversed when its interaction effects were incorporated
in the model. Moreover, despite that unrelated diversification weakened the
exploitation ability of the firm, as we hypothesized, it only impaired the acquisition
ability after it exceeded the sample’s average. Instead, it reinforced the acquisition
ability at lower levels. Therefore, our study is in congruence with the RBV’s support
of related diversification in that firms can exercise greater discretion in diversifying in
related than in unrelated knowledge areas.
37
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Table 1: Summary statistics and correlation matrix
Variable Mean SD Min Max 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 1. ROA 0.05 0.10 -0.85 0.48 1
2. DR 0.56 0.54 0.00 2.34 0.12 1 3. DU 0.52 0.70 0.00 3.91 -0.18 0.12 1
4. Acquisition 0.06 0.06 0.00 0.44 0.09 -0.11 -0.12 1 5. Assimilation 0.97 0.61 0.00 1.68 -0.02 0.04 -0.10 0.17 1
6. Exploitation 0.87 0.55 0.00 1.71 -0.01 0.10 0.02 0.02 0.78 1 7. Advertising intensity 0.02 0.02 0.00 0.12 0.01 0.15 0.06 -0.01 -0.06 -0.01 1
8. Complexity of organizational
2.08 0.70 0.00 3.00 -0.04 -0.18 -0.04 0.04 0.24 0.33 -0.11 1 9. Technological output 0.04 0.08 0.00 0.57 -0.11 -0.13 0.27 0.08 0.11 0.15 -0.22 0.23 1
10. Firm size 3.41 1.45 -1.93 6.06 -0.12 0.24 0.45 -0.25 0.09 0.21 -0.01 0.01 0.25 1 11. Industry Concentration 0.14 0.17 0.00 0.81 -0.04 -0.10 0.37 0.03 0.02 0.07 -0.13 0.19 0.37 0.49 1
12. Industry Profitability 0.36 3.45 0.00 70.23 -0.03 -0.02 0.10 0.00 -0.06 -0.05 -0.05 0.02 0.13 0.10 0.13 1 13. Capital investments 0.09 0.08 0.01 0.88 -0.03 0.04 -0.12 -0.36 -0.18 -0.12 0.02 -0.13 -0.08 -0.03 -0.23 -0.04 1
14. Debt burden 0.50 7.47 6.53 108.33 0.00 0.03 0.01 0.00 0.04 0.06 -0.08 0.02 0.03 0.07 0.03 0.01 0.01 1 15. Labor productivity 379.46 297.79 6.02 2281.21 0.11 0.03 -0.16 0.02 0.04 -0.02 0.03 0.04 -0.11 -0.16 -0.09 -0.03 -0.02 -0.01 1
16. Foreign to Domestic Sales Ratio 0.41 0.28 0.00 0.93 0.20 0.11 -0.03 0.36 0.07 0.07 0.10 0.00 -0.04 0.07 0.08 -0.02 -0.26 -0.01 0.12 1 17. Time effects 7.65 1.40 1.00 7.00 0.03 0.31 0.02 0.04 0.00 -0.02 0.02 -0.18 -0.28 0.14 -0.22 -0.02 -0.09 0.01 0.33 0.34 1
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Table 2: Regression Outputs: The moderating impact of modes of diversification on
the effects of acquisition, assimilation, and exploitation abilities on firm performance
Dependent variable: ROA Controls Base Diversification Interactions
Coef./SE Coef./SE Coef./SE Coef./SE Acquisition
0.099* 0.098* 0.091†
(0.04) (0.05) (0.05)
Assimilation
0.006* 0.006* 0.006†
(0.00) (0.00) (0.00)
Exploitation
0.006* 0.007* 0.010**
(0.00) (0.00) (0.00)
DR
0.007* 0.009**
(0.00) (0.00)
DU
-0.004* 0.009*
(0.00) (0.00)
DR x Acquisition
0.129†
(0.07)
DR x Assimilation
-0.016**
(0.01)
DR x Exploitation
0.014*
(0.01)
DU x Acquisition
-0.208***
(0.06)
DU x Assimilation
0.010
(0.01)
DU x Exploitation
-0.012*
(0.01)
Firm size -0.000 -0.006*** -0.006** -0.008**
(0.00) (0.00) (0.00) (0.00)
Technological output -0.061** -0.057** -0.059** -0.094***
(0.02) (0.02) (0.02) (0.02)
Capital investments -0.024* -0.064* -0.054† -0.018
(0.01) (0.03) (0.03) (0.04)
Debt burden -0.000 -0.001** -0.001** -0.001**
(0.00) (0.00) (0.00) (0.00)
Industry concentration -0.051*** -0.044*** -0.046*** -0.056***
(0.01) (0.01) (0.01) (0.01)
Industry profitability -0.000 -0.000 -0.000 -0.000
(0.00) (0.00) (0.00) (0.00)
Labor productivity 0.000** 0.000* 0.000* 0.000*
(0.00) (0.00) (0.00) (0.00)
Complexity of organizational structure -0.009† -0.026*** -0.026*** -0.021***
(0.00) (0.01) (0.01) (0.01)
Advertising intensity 0.440** 1.039*** 1.050*** 0.499*
(0.14) (0.21) (0.21) (0.23)
Foreign to domestic sales ratio 0.006 0.013* 0.014* 0.020*
(0.01) (0.01) (0.01) (0.01)
Industry effects: SIC 35 0.019*** -0.001 0.004 0.014 (0.01) (0.01) (0.01) (0.01) 36 0.007 -0.012† -0.009 0.011
(0.00) (0.01) (0.01) (0.01)
37 0.022† 0.020 0.027†
43
(0.01) (0.01) (0.01)
38 -0.002 -0.006 0.002 0.016
(0.01) (0.01) (0.01) (0.02)
50 -0.030** -0.044** -0.040** (0.01) (0.02) (0.01) 73 0.012** 0.017* 0.019* 0.020†
(0.00) (0.01) (0.01) (0.01)
Time effects: 1975-1980 0.021** 0.029*** 0.030***
(0.01) (0.01) (0.01)
1980-1985 0.006 0.013* 0.015* 0.021**
(0.01) (0.01) (0.01) (0.01)
1985-1990 0.003 0.006 0.008 0.014†
(0.00) (0.01) (0.01) (0.01)
1990-1995 -0.005 -0.003 -0.002 0.002
(0.00) (0.01) (0.01) (0.01)
1995-2000 -0.004 -0.006 -0.004 -0.002
(0.00) (0.00) (0.00) (0.01)
2000-2005 -0.006* -0.007* -0.005† -0.002
(0.00) (0.00) (0.00) (0.00)
Constant 0.047*** 0.069*** 0.061*** 0.052***
(0.01) (0.01) (0.01) (0.01)
Observations 2344 2021 2021 2021 Firms 141 124 124 124 Chi_sq 137.68 195.57 213.56 224.70 Notes:
1. Financial figures were converted to constant USDs of 2000. 2. Models are estimated using feasible generalized least squares that yields robust estimates to autocorrelation within panels, cross-sectional
correlation and heteroskedasticity across panels. 3. All control variables except “Period” and “Industry” dummies are lagged for one year 4. The base Time effect dummy refers to the period 2005-2010 5. The base “Industry Effect” is the 2-digit SIC 48 (Communications) 6. Absorptive capacity variables are lagged for two years 7. Diversification variables are lagged for four years
† p<0.07, * p<0.05, ** p<0.01, *** p<0.001
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Figure 1: Graphical presentation of the interaction effects
.0
5.1
.15
.2
Mar
gina
l Eff
ect
0 .1 .2 .3 .4
Acquisition Ability
DR = Mean - 0.5SD DR = Mean DR
DR = Mean + 1SD DR = Mean + 2SD
DR = Mean + 3SD
Graph (a)The Marginal Effect of the Acquisition Ability:
The Moderating Effect of Related Diversification
.06
.07
.08
.09
.1
Mar
gina
l Eff
ect
0 .3 .6 .9 1.2
Assimilation Ability
DR = Mean - 0.5SD DR = Mean DR
DR = Mean + 1SD DR = Mean + 2SD
DR = Mean + 3SD
Graph (b)The Marginal Effect of the Assimilation Ability:The Moderating Effect of Related Diversification
.04
.05
.06
.07
.08
.09
Mar
gina
l Eff
ect
0 .4 .8 1.2 1.6
Exploitation Ability
DR = Mean - 0.5SD DR = Mean DR
DR = Mean + 1SD DR = Mean + 2SD
DR = Mean + 3SD
Graph (c)The Marginal Effect of the Exploitation Ability:
The Moderating Effect of Related Diversification
-.2-.1
0.1
Mar
gina
l Eff
ect
0 .1 .2 .3 .4 .5
Acquisition Ability
DU = Mean - 0.5SD DU = Mean DU
DU = Mean + 1SD DU = Mean + 2SD
DU = Mean + 3SD DU = Mean + 4SD
Graph (d)The Marginal Effect of the Acquisition Ability:
The Moderating Effect of Unrelated Diversification
-.02
0.0
2.0
4.0
6
Mar
gina
l Eff
ect
0 .4 .8 1.2 1.6
Exploitation Ability
DU = Mean - 0.5SD DU = Mean DU
DU = Mean + 1SD DU = Mean + 2SD
DU = Mean + 3SD DU = Mean + 4SD
Graph (e)The Marginal Effect of the Exploitation Ability:
The Moderating Effect of Unrelated Diversification