Journal of Management Studies 44:8 December 2007 doi: 10.1111/j.1467-6486.2007.00719.x

A Modern Resource Based Approach to Unrelated Diversification

Desmond W. Ng
Texas A&M University abstract For over three decades, the questions of how and why an organization diversifies into related and unrelated businesses have drawn the attention of strategy scholars. However, explanations of unrelated diversification have been less than clear. A conceptual model of unrelated diversification is thus proposed. In drawing on Penrose’s (1959) resource based approach, unrelated diversification is explained by an organization’s ‘three pillars’, which consist of its strength of dynamic capabilities, absorptive capacity, and weak ties. The role of the three pillars is to discover new resource applications or uses in conditions of market failure that are characterized by ‘incomplete’ markets. A novel feature of this model is that an organization can diversify more broadly than predicted by Penrose (1959) and other modern resource-based approaches (Teece et al., 1997). Furthermore, unrelated diversification can be beneficial. This study also offers suggestions to measure the three pillars; its contributions and implications are discussed as well.

INTRODUCTION The questions of how and why an organization diversifies into related and unrelated businesses have been a central focus of strategy research (Palich et al., 2000; Rumelt, 1974; Teece, 1982). These diversifications have been defined by the degree to which an organization’s products and services draw from a common pool of resources (Chatterjee and Wernerfelt, 1991; Montgomery and Wernerfelt, 1988; Teece, 1982). In particular, a rich volume of research has found related diversification to be the dominant mode of organizational expansion and superior in performance to unrelated diversification (Montgomery and Wernerfelt, 1988; Palich et al., 2000; Rumelt, 1974). These findings have largely been attributed to Penrose’s (1959) resource-based approach (Kor and Mahoney, 2000, 2004; Lockett and Thompson, 2004; Montgomery and Wernerfelt, 1988; Teece, 1982). According to Penrose (1959), an organization is a bundle of resources that yield multiple untapped uses. An organization can render multiple related and unrelated
Address for reprints: Desmond W. Ng, Department of Agricultural Economics, Texas A&M University, Blocker Building 349B, 525 Ireland Street, College Station, Texas, 77843-2123, USA (dng@ag.tamu.edu).
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products even from the same set of resources. This is because resources can be applied in different ways that yield different productive services or uses. As a result, the discovery of a resource’s varied or heterogeneous uses (i.e. products and services) is a primary inducement for growth (Kor and Mahoney, 2000, 2004; Montgomery and Hariharan, 1991; Penrose, 1959; Rugman and Verbeke, 2004; Sirmon et al., 2007). Growth, however, is not random, but is directed to the growth of related resources and uses (Farjoun, 1994; Penrose, 1959). As noted by Penrose (1959), The general direction of innovation in the firm is not haphazard but is closely related to the nature of existing resources and to the type and range of productive services they can render. (p. 84) Related diversification is favoured because resources are used in discrete or complementary combinations, to which the growth of related resources yields synergies that increase the use of an organization’s core resources (Kor and Mahoney, 2000; Penrose, 1959; Teece et al., 1994). Moreover, as growth builds upon an organization’s prior experiences, path dependencies are leveraged to exploit the further use of related resources (Kor and Mahoney, 2000; Penrose, 1959; Teece et al., 1994). Yet, empirical evidence finds organizations diversify more broadly than predicted by Penrose (1959) and other modern resource-based approaches (Teece et al., 1997). The empirical studies of Argyres (1996), Mayer and Whittington (2003), McGrath and Nerkar (2004), Montgomery and Hariharan (1991), Montgomery and Wilson (1986), and Williams et al. (1988) have found evidence of unrelated diversification. For instance, in hi-technology industries, Argyres (1996) and McGrath and Nerkar (2004) have found significant diversifications in the pharmaceutical industry. Furthermore, other hi-technology studies have found that organizations leverage their resources and experiences into increasingly unrelated product markets (Eisenhardt and Martin, 2000; Helfat and Raubitschek, 2001; Miller, 2003; Rindova and Kotha, 2001). Moreover, earlier (Chatterjee and Wernerfelt, 1991; Hoskisson, 1987; Michel and Shaked, 1984) and even more recent empirical evidence (Campa and Kedia, 2002; Khanna and Palepu, 2000; Villalonga, 2004) has found that unrelated diversifications perform at a premium. Therefore, despite Penrose’s seminal contributions to diversification research (Kor and Mahoney, 2000, 2004; Rugman and Verbeke, 2004), Eisenhardt and Martin (2000) contend Penrose’s logic of synergies and path dependence is too narrowly defined to account for such unrelated diversified behaviours. For instance, Miller’s (2003) case study of over two dozen organizations finds an organization’s discovery of its latent or ‘asymmetric resources’ can transform its initial resources into increasingly unrelated resources and capabilities (see also Helfat and Raubitschek, 2001; Montgomery and Hariharan, 1991; Rindova and Kotha, 2001). Moreover, Montgomery (1994), Montgomery and Hariharan (1991) and Teece (1982) argue Penrose’s diversification argument is incomplete because it does not fully account for market failures. In conditions of market failure, an organization has an incentive to diversify into unrelated businesses because conglomerates benefit from an ‘internal capital market’ that is efficient in trading tacit know-how, allocating and discovering valued resources over inefficient markets (Chatterjee and Wernerfelt, 1991; Teece, 1982; Williamson, 1975).
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Although an internal capital market argument is the leading explanation of unrelated diversification (Hill et al., 1992; Teece, 1982; Williamson, 1975), a theory of unrelated diversification remains unclear (Chatterjee and Wernerfelt, 1991; Hill and Hoskisson, 1987; Hill et al., 1992; Hoskisson and Hitt, 1990) for two reasons. First, the efficiencies of ‘internal capital market’ are predicated on an internal competition of autonomous business units (Hill and Hoskisson, 1987; Hill et al., 1992; Williamson, 1975). Yet, since the discovery of new resource uses arises from novel resource combinations (Denrell et al., 2003; Eisenhardt and Martin, 2000; Kor and Mahoney, 2000), this internal competition precludes business units from collaborating and synthesizing new resource combinations (see also Argyres, 1996; Hill and Hoskisson, 1987; Hill et al., 1992). Internal capital market explanations, therefore, do not adequately explain an organization’s discovery and thus diversification of its resources’ varied uses. Second and subsequently, this internal competition implicitly assumes resources are homogeneous (e.g. Hill and Hoskisson, 1987), yet various researchers have recognized heterogeneous resources lead to market failures (Denrell et al., 2003; Montgomery and Hariharan, 1991; Teece, 1982). With heterogeneous resources, markets cannot determine the value of a resource(s) in all its possible uses, but can only value a resource(s) in accordance to its existing uses (Denrell et al., 2003). Markets are, therefore, subject to a form of market failure characterized by ‘incomplete markets’ because they fail to fully impute the value of the potential uses from all possible resource combinations (Denrell et al., 2003; Sirmon et al., 2007). This form of market failure has not been considered in either internal capital market explanations or in Penrose’s (1959) resource base logic. As various researchers have recognized an organization’s heterogeneous resources are key to explaining the behaviour and performance of large diversified firms (Montgomery, 1994; Montgomery and Hariharan, 1991; Teece, 1982), a conceptual model that integrates Penrose’s (1959) resource-based approach with an incomplete market approach (Denrell et al., 2003) is proposed. However, since Penrose’s (1959) resource based logic is limited in its explanation of unrelated diversification, this conceptual model also draws on the concepts of dynamic capabilities (Eisenhardt and Martin, 2000), absorptive capacity (Cohen and Levinthal, 1990) and weak ties (Granovetter, 1983). In particular, dynamic capabilities emphasize that changes to an organization’s resources can promote an organization’s diversification into increasingly unrelated product markets (Eisenhardt and Martin, 2000; Helfat and Raubitschek, 2001; Miller, 2003).[1] Furthermore, as unrelated diversifications broaden an organization’s knowledge base (Eisenhardt and Martin, 2000; Hales, 1999; Miller, 2003), a diverse knowledge base can increase an organization’s ‘absorptive capacity’ to assimilate a broader range of market opportunities (Cohen and Levinthal, 1990; Lane et al., 2006; Nicholls-Nixon and Woo, 2003). As new information is assimilated, it promotes new learning (Cohen and Levinthal, 1990) which can increase an organization’s absorptive capacity to further diversify into unrelated product markets (Bowman and Hurry, 1993; Lane et al., 2006). Unrelated diversifications can also be further reinforced by ‘weak ties’ (Granovetter, 1983). Weak ties refer to bridging relationships that connect an organization to novel resource and experiences (Granovetter, 1983; McEvily and Zaheer, 1999; McFadyen and Cannella, 2004). Weak ties can, thus, enhance an organization’s dynamic capabilities to not only seek new resource combinations, but as a consequence increase an organization’s absorptive
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capacity to further diversify into increasingly unrelated product markets. By drawing on these three concepts, Penrose path dependent logic is expanded to explain unrelated diversifications. Specifically, these three concepts are termed an organization’s ‘three pillars’. These three pillars reflect an organization’s efficiencies in discovering its resources’ heterogeneous uses in incomplete markets. In outlining the arguments of the three pillars model (see also Figure 1), an organization’s increasingly unrelated diversification resides in solving Penrose’s ‘jigsaw problem’ in ‘incomplete’ markets. An organization’s three pillars reflect internal efficiencies to solve a jigsaw puzzle that maximizes the heterogeneous resource uses of an organization’s discrete and lumpy resources. An organization’s discovery of these new resource uses is driven by arbitrage opportunities of incomplete markets. These opportunities are discovered through an organization’s strength of dynamic capabilities. These capabilities positively impact an organization’s ‘balance of process’ (Penrose, 1959) to seek new resource combinations that reveal new resource uses in incomplete markets. Exploiting such arbitrage opportunities seeds the specialized growth of new resources and uses whose latent uses provide ‘expansion options’, which promote future first mover advantages (FMA) in increasingly distant product markets. Entrance into these new and distant markets increases an organization’s knowledge of its resources’ various uses. This increases an organization’s absorptive capacity to assimilate resources from its weak ties partners. These weak ties subsequently reinforce an organization’s strength of dynamic capabilities to further discover new resources and uses in increasingly unrelated markets. The three pillars model offers three contributions. First, the three pillars introduce ‘discovery’ efficiencies that have not been examined in internal capital market explanations (e.g. Hill and Hoskisson, 1987; Hill et al., 1992; Williamson, 1975). Second, by incorporating incomplete markets to Penrose’s resource-based logic, the three pillar model shows that an organization’s path dependencies can broaden rather than restrict (Penrose, 1959; Teece et al., 1994, 1997) diversifications. Third, as there is still considerable debate on the performance of related and unrelated diversifications (Campa and Kedia, 2002; Hoskisson and Hitt, 1990; Khanna and Palepu, 2000), the three pillars model predicts that in conditions of market incompleteness and when resources are heterogeneous, discrete and indivisible, unrelated diversifications can be beneficial. To develop the three pillars model, Penrose’s (1959) resource based approach is extended by concepts of dynamic capabilities (Eisenhardt and Martin, 2000; Teece et al., 1997), absorptive capacity (Cohen and Levinthal, 1990) and weak ties (Granovetter, 1983). Next, the unrelated diversification performance of the three pillars model is discussed. Measures for the three pillars follow. Lastly, this study’s contributions and implications are discussed. CONCEPTUAL FOUNDATIONS As an organization’s growth and survival rests on the discovery of new products and services (Eisenhardt and Martin, 2000), diversification is defined by the degree to which an organization expands its pool of resources to discover their varied uses in incomplete markets. This definition draws from an emerging body of research that emphasizes an
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organization’s growth stems from the discovery of the varied and unrealized uses of its resource bundles (Helfat and Raubitschek, 2001; Matsusaka, 2001; Montgomery and Hariharan, 1991). Readers are, however, reminded that diversifications also depend on an organization’s production technologies and scale economies because they dictate the efficient production of such discoveries. Penrose Theory of the Firm (1959) According to Penrose (1959), an organization’s growth stems from not only having better resources (i.e. valuable, rare, and imitable) as prescribed by the resource-based view (Barney, 2002), but from knowing how to seek new and better uses from its untapped resources (Kor and Mahoney, 2004: Montgomery and Hariharan, 1991; Rugman and Verbeke, 2004). This means resources can yield related and unrelated applications (Montgomery and Hariharan, 1991; Montgomery and Wernerfelt, 1988; Teece, 1982). As Teece (1982) notes, . . . the final products produced by a firm at any given time merely represent one of several ways in which the organization could be using its internal resources (Penrose, 1959) . . . a firm’s capabilities lie upstream from the end product – it lies in a generalizable capability which might well find a variety of final product applications. (p. 45) Such heterogeneity in resource uses stems from the indivisible and discrete nature of resource bundles (Montgomery and Hariharan, 1991; Penrose, 1959; Teece, 1982). Indivisible or lumpy resources create excess capacity, which provides incentives to seek their varied uses (Montgomery and Hariharan, 1991; Penrose, 1959; Teece, 1982). In addition, as resources are combined in discrete or complementary configurations, the greater utilization of one set of lumpy resources stimulates the specialized growth of other related resources and uses (Montgomery and Wernerfelt, 1988; Penrose, 1959). This process of specialized growth is described by Penrose’s (1959) ‘balance of process’, which refers to a ‘virtuous circle’ of increasing specializations. Namely, for an organization to maximize its resource’s varied uses, the specialized growth of other related resources is required. Yet as resources are indivisible, the specialized growth of these related resources requires the further specialization of other discrete and indivisible resources that reveal further uses. This creates a ‘virtuous circle’ of increasing specializations, as described by Penrose (1959), . . . and once new products are added, new types of specialized resources may be required at other stages of production or distribution, and a new series of advantages from further specialization in still different directions may become obtainable. (p. 73) For instance, in Sony’s evolution of technological capabilities (Helfat and Raubitschek, 2001), Sony initially leveraged its core resources in transistor radios and miniaturization of electronic products to develop the first portable black and white TV. This became the technological foundation for developing Sony’s successful Trinitron colour TV. In building on Sony’s expertise in colour TV technologies and its prior technical expertise in
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producing magnetic audio tapes, Sony developed the U-Matic video machine. This later became the technology platform for the Betamax videocassette recorder (VCR). The growth of one technology, therefore, evolved the growth of other specialized technologies whose creation of products (i.e. resource uses) led to the specialization of other technologies that provided a platform for future product sequences (Danneels, 2002; Helfat and Raubitschek, 2001). Penrose’s Jigsaw Problem This ‘balance of process’ is, however, complicated by Penrose’s ‘jigsaw problem’. This jigsaw problem arises because resources can only be combined in discrete ways. This means not all resources can ‘fit’ perfectly without causing incompatibilities with other resources. This happens because as an organization’s balance of process drives the growth of an increasing number of lumpy and discrete resources, this introduces resources that are increasingly incompatible to its existing resources. An organization is, therefore, confronted by an evolving ‘jigsaw problem’ in which by seeking fitting resources, they present another jigsaw problem to be solved (Penrose, 1959). The concept of dynamic capabilities is introduced to solve this jigsaw problem. Dynamic Capabilities As an outgrowth of Penrose (1959), an organization’s ‘dynamic capabilities’ refer to its capability to develop and seek new resources and configurations that match the changing conditions of the market (Eisenhardt and Martin, 2000; Teece et al., 1997). Dynamic capabilities are defined as: the firm’s processes that use resources – specifically to integrate, reconfigure, gain and release resources – to match and even create market change. (Eisenhardt and Martin, 2000, p. 1107) Dynamic capabilities involve path dependencies that leverage the growth of an organization’s related resources (Teece et al., 1997), yet also can develop new and even unrelated resources and uses (Eisenhardt and Martin, 2000; Helfat and Peteraf, 2003; Miller, 2003). An organization’s strength of dynamic capabilities (weak and strong form) is introduced to capture this range of diversifications while also solve Penrose’s jigsaw problem. Weak form dynamic capability. Weak form dynamic capability draws on an organization’s prior knowledge of resource uses to reveal new uses from its ‘existing’ resource bundle. Weak form dynamic capability is an outgrowth of an organization’s balance of process. Through this balance of process, an organization accumulates experiences of various ways in which its existing resources can be used – termed resource use experiences. Increases in an organization’s resource use experiences facilitate the discovery of other closely related resources and uses (Denrell et al., 2003; Mishina et al., 2004; Penrose, 1959). This is consistent with Montgomery and Wernerfelt’s (1988) empirical study,
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which finds that organizations will first exploit excess resources that are closest to an organization’s core resources and experiences. Similarly, other studies find organizations leverage their prior experiences to reduce the cost of developing related resources (Danneels, 2002; King and Tucci, 2002). For instance, King and Tucci (2002) argue prior change experiences – ‘transformational experiences’ – increase an organization’s dynamic capabilities to promote further change. Specifically, since prior experiences facilitate the discovery of closely related resources, weak form dynamic capability solves Penrose’s jigsaw problem by revealing varied uses from those untapped resources that are closely related to its core resources and experiences. This follows a logic of path dependence in which an organization’s diversification is constrained by its related domains of expertise (King and Tucci, 2002; Penrose, 1959; Teece et al., 1997).

Strong form dynamic capability. Unlike weak form dynamic capability, an organization’s strong form dynamic capability introduces new resources to change its existing resource bundle. In addition, strong form dynamic capability does not rely on an organization’s prior knowledge of resource uses. Instead, it discovers new resources and uses through innovative experimentation and improvisational processes (e.g. Eisenhardt and Martin, 2000). Cross-functional teams, real time responses to market feedback, and prototyping of multiple products are mechanisms that promote such strong form dynamic capability (e.g. Eisenhardt and Martin, 2000). Since strong form dynamic capability is not constrained by an organization’s prior knowledge of resource uses, it amplifies an organization’s balance of process into increasingly unrelated resources and uses. This is because the discovery of new resources introduces new resource combinations and synergistic relationships that reveal further resource uses (Denrell et al., 2003; Montgomery and Hariharan, 1991). This creates a new arrangement of discrete and lumpy resources whereby maximizing their heterogeneous uses leads to the specialized growth of other resources (Montgomery and Hariharan, 1991). Due to the discrete nature of resources, specialized growth of these resources reinforces an organization’s strong form dynamic capability to introduce other resources and uses. This induces the specialization and diversification of other resources and uses not held by the organization. An organization’s strong form dynamic capability, therefore, solves a series of jigsaw problems whose solutions reinforce increasingly unrelated diversifications. This is consistent with dynamic capabilities research that finds organizational growth exhibits a ‘branching’ of diverse resources and products (Eisenhardt and Martin, 2000; Helfat and Peteraf, 2003; Helfat and Raubitschek, 2001; Miller, 2003; Montgomery and Hariharan, 1991; Rindova and Kotha, 2001). For instance, Yahoo undertook a series of profound transformations (Rindova and Kotha, 2001). Termed as ‘continuous morphing’, Yahoo evolved from an initial provider of internet search to a destination site for content (i.e. news) and then to a provider of a multiplicity of interactive online services (i.e. email, personalized websites, communications, and commerce). Such transformations required new technological and logistic capabilities that fundamentally departed from its initial search technology (Rindova and Kotha, 2001).
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Strength of Dynamic Capabilities: A Response to Incomplete Markets? In addition to solving Penrose’s jigsaw problem, an organization’s strength of dynamic capabilities is a response to inefficient markets. That is, why does an organization require such dynamic capabilities when their resource combinations and varied uses can be simply revealed through the market valuation process? In efficient markets, the price of any given resource(s) is determined by the value in all of its possible uses (Denrell et al., 2003). Therefore, under complete or efficient markets, the value of all possible combinations of an organization’s resources would be revealed by the market valuation process. However, markets are inefficient or ‘incomplete’ because they cannot determine the value of resource(s) in all their possible uses, but can only value resource(s) in accordance to their existing uses (Denrell et al., 2003; Sirmon et al., 2007). This incompleteness provides ‘arbitrage opportunities’ for an organization to discover new ways of combining resources (Denrell et al., 2003). As noted by Denrell et al. (2003): . . . incomplete markets means that opportunity can inhere in novel combinations of existing resources . . . It is this fact that makes the image of an ‘arbitrage opportunity’ valuable in the strategy context . . . because its feasibility was simply hidden by market incompleteness. (p. 981) However, discovering arbitrage opportunities is complicated by a problem of combinatory search (Denrell et al., 2003). In the presence of complementary or discrete resources, the ability to reveal new resource uses requires a search over an infinite space of resource combinations, many of which will fail to yield valuable uses. An organization’s strength of dynamic capabilities is advantageous in searching this space of resource combinations because an organization can discover new or extended uses from its resource bundle if it already possesses or has prior knowledge of its component parts (Denrell et al., 2003). As Denrell et al. (2003) note, Specifically, when many of the necessary components were available to the firm, it is possible that the value of the eventual combination could be foreseen. The process is analogous to an individual facing a jigsaw puzzle with only a few lacking pieces. (p. 987; author’s emphasis) To reveal such an ‘eventual combination’ of resources, weak form dynamic capability draws on the biased and simple dimensions of ‘problemistic search’ (Cyert and March, 1963). Since weak form dynamic capability discovers new resources uses that are in close proximity to its prior experiences, search is necessarily ‘biased’. This reduces an organization’s search space and thus alleviates the cognitive demands of combinatorial search. Furthermore, since weak form dynamic capability does not alter existing resources, search is ‘simplified’ to the discovery of new uses from its existing resource bundle. Through the biased and simple dimensions of ‘problemistic search’, weak form dynamic capability offers a slightly different, but nevertheless consistent, argument to the ‘Penrose effect’ (1959). This is because as weak form dynamic capability alleviates the cognitive demands of combinatorial search, it frees up managerial services to pursue
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the related diversification of its untapped resources. However, for any given resource configuration, there are exhaustible limits to the discovery of new resource uses. Therefore, once nearby diversification opportunities have been exhausted, an organization will pursue the broader diversifications (e.g. Montgomery and Wernerfelt, 1988) of strong form dynamic capability. As strong form dynamic capability discovers ‘new’ resources and uses, existing resource combinations are changed that reveal new uses not discovered by weak form dynamic capabilities. This is because a resource’s varied uses are also dependent on its particular combination with other held resources (Denrell et al., 2003; Miller, 2003; Penrose, 1959). Therefore, as strong form dynamic capability introduces new resources it alters existing resource combinations, which reveals further resource uses. As new resource uses are revealed, they evolve the growth of other specialized resources whose newfound uses lead to the increasing specialization and diversification of other resources not held by the organization (Helfat and Raubitschek, 2001; Montgomery and Hariharan, 1991). This strong form dynamic capability, therefore, increasingly extends an organization’s discovery of new resource combinations and uses that were previously hidden by incomplete markets. Both weak and strong form dynamic capabilities are, therefore, not only solutions to Penrose’s jigsaw problem, but they also reflect an organization’s advantage in revealing increasingly heterogeneous resource uses in incomplete markets. Absorptive Capacity As an organization’s strength of dynamic capabilities promotes increasingly unrelated diversifications in incomplete markets, it also increases an organization’s ‘absorptive capacity’. Foreshadowed by Penrose (1959) (Kor and Mahoney, 2000), an organization’s ‘absorptive capacity’ refers to its ability ‘to recognize the value of new information, assimilate it, and apply it to commercial ends’ (Cohen and Levinthal, 1990, p. 128). To assimilate new information, some degree of overlap is required between an organization’s prior knowledge and the new and external information (Cohen and Levinthal, 1990; Nicholls-Nixon and Woo, 2003; Zahra and George, 2002). To promote this assimilation, Cohen and Levinthal (1990) argue ‘a diverse background [knowledge] provides a more robust basis for learning because it increases the prospect that incoming information will relate to what is known’ (p. 131). However, Cohen and Levinthal (1990) provide limited discussion on the origins of this diverse knowledge. In this study, an organization’s diverse knowledge originates from its strength of dynamic capabilities. As an organization’s strength of dynamic capabilities induces increasingly unrelated diversifications, it accumulates knowledge of the various ways in which its resources can be used. This increases an organization’s absorptive capacity to assimilate external information on new resource uses (see also Kor and Mahoney, 2000). Subsequently, increases in an organization’s absorptive capacity also reinforce its strength of dynamic capabilities. As an organization’s absorptive capacity assimilates information on a greater diversity of resource uses, this strengthens its dynamic capabilities to further discover and diversify into new resources and uses in incomplete markets. With this increasing diversification, an organization accumulates new resource
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use experiences which further reinforce its absorptive capacity to assimilate new information. This subsequently shapes an organization’s strength of dynamic capabilities to further diversify in incomplete markets. Discovery of New Resource and Uses Through Weak Ties An organization’s increasingly unrelated diversification is also shaped by its ‘alertness’. Alertness rests on a subjective tenet in which undiscovered market opportunities are revealed by leveraging externally subjective experiences (Kirzner, 1997). Subjectivity refers to the notion that each individual has unique perceptions and experiences of how resources can be used (Shane, 2000). For instance, in Shane’s (2000) study of MIT’s three-dimensional printing technology, entrepreneurs in industries ranging from architectural design to pharmaceuticals perceived new and different applications for the same printing technology. Given subjectivity, an organization’s alertness involves recombining these subjective resource use experiences to gain further knowledge of its own resources’ varied uses. This increases an organization’s ability to diversify in incomplete markets. This alertness is captured by an organization’s ‘weak ties’. ‘Weak ties’ refer to ‘bridging’ relationships that expose an organization to distant members that possess new or non-redundant ideas and resources (Granovetter, 1983; McEvily and Zaheer, 1999; McFadyen and Cannella, 2004). As ‘weak ties’ bridge an organization to new ideas, it exposes an organization to subjective resource use experiences. This exposure to subjective experiences increases an organization’s knowledge of its own resources’ varied uses which increases an organization’s innovation. This argument is consistent with empirical studies that find weak ties increase an organization’s knowledge creation and product innovation (McEvily and Zaheer, 1999; McFadyen and Cannella, 2004).[2] Furthermore, since weak ties provide access to new and distant resources (McEvily and Zaheer, 1999; McFadyen and Cannella, 2004), an organization’s weak ties gains access to unrelated resources. This promotes novel resource combinations that reveal further resource uses. Therefore, since weak ties promote such creative and innovative behaviours, an organization’s weak ties increase its diversification in incomplete markets. An organization’s weak ties also reinforce the diversifying influences of its strength of dynamic capabilities and absorptive capacity. In particular, as weak ties expose an organization to subjective experiences, weak ties increase an organization’s weak form dynamic capabilities to reveal a greater variety of uses from its untapped resources. Furthermore, since weak ties promote the recombination of subjective experiences and provide access to unrelated resources, weak ties change the discrete, indivisible, and heterogeneous nature of an organization’s resource bundle. Such changes in resource bundle induce an organization’s strong form dynamic capabilities to seek the specialized growth of those unrelated resources and uses revealed by its weak ties. Specialized growth of these unrelated resources and uses subsequently increases an organization’s diversity of resource use experiences, which increases an organization’s ability to further relate and assimilate new resource use experiences. This greater absorptive capacity subsequently reinforces an organization’s alertness to form further weak ties, which advances an organization’s diversification in incomplete markets. Therefore, through these mutually reinforcing influences, an organization’s weak ties, strength of dynamic
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capabilities, and absorptive – termed as the three pillars – drive an increasing discovery of unrelated resources and uses in incomplete markets. This self-reinforcing behaviour is consistent with product sequencing studies that find an organization’s diversification in one period provides the seeds for further diversified growth (Helfat and Peteraf, 2003; Helfat and Raubitschek, 2001; Miller, 2003; Montgomery and Hariharan, 1991; Rindova and Kotha, 2001). The three pillars are proposed by the following: Proposition 1: In incomplete markets, the degree of diversification is positively related to an organization’s three pillars – weak ties, strength of dynamic capabilities, and absorptive capacity. Performance of Increasingly Unrelated Diversification Although much empirical evidence favours the superior advantages of related diversification (Montgomery and Wernerfelt, 1988; Palich et al., 2000; Rumelt, 1974), a limitation of these findings is they do not control for industry effects (Palich et al., 2000). When studies do control for industry effects, results are less conclusive. For instance, in conditions of market failure, unrelated diversifications have been found to perform at a premium (Campa and Kedia, 2002; Chatterjee and Wernerfelt, 1991; Hoskisson, 1987; Khanna and Palepu, 2000; Michel and Shaked, 1984; Villalonga, 2004). As related diversification studies do not typically control or consider for such market conditions (Palich et al., 2000; Teece, 1982), their performance findings[3] may under-represent the unrelated diversification advantages of an organization’s internal capital markets. To capture these advantages, two unrelated diversification advantages are proposed: arbitrage opportunities; and expansion options and first mover advantage. Arbitrage opportunities. First, unrelated diversification benefits from the ‘arbitrage opportunities’ of incomplete markets. Arbitrage opportunities are returns to an organization’s three pillars in revealing new resource uses that cannot be discovered by incomplete markets. Arbitrage opportunities are in essence returns to an organization’s internal efficiencies – three pillars – in maximizing the heterogeneous resource uses of its discrete and lumpy resources. The three pillars, therefore, appeal to the efficiencies of internal capital markets (Williamson, 1975). According to Williamson (1975), an organization diversifies into unrelated businesses (conglomerates) because its internal capital market is efficient in trading tacit know-how, allocating and discovering valued resources over inefficient markets (Hoskisson, 1987; Teece, 1982; Williamson, 1975). In the context of the three pillars, their self-reinforcing influences accumulate unique experiences and understandings of an organization’s resources’ varied uses. With this superior information, an organization diversifies because it is better able to value and allocate its resources than incomplete markets. However, there is one important distinction. Williamson (1975) argues that internal capital market efficiencies are realized through a multi-divisional structure. In an M-form structure, there are multiple business units that act as ‘quasi-firms’ (Williamson, 1975). Each quasi-firm is responsible for its own operational decisions and profits (Hales, 1999; Hill et al., 1992; Williamson, 1975). Through an internal competition of these
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decentralized and independent business units, corporate head office can then focus its efforts on the allocation of financial capital to high performing business units (Hales, 1999; Hill et al., 1992; Williamson, 1975). However, since a resource’s varied uses are also dependent on its combination with other held resources (Denrell et al., 2003), this internal competition reduces incentives for business units to share or combine their resources (Hill et al., 1992; Hill and Hoskisson, 1987). This internal competition, therefore, precludes the internal discovery of new resource combinations and uses. Thus, an important distinction from Williamson’s (1975) internal capital market argument is: that the three pillars are not analogous to the efficiencies of an external competitive market system. Rather, an organization’s internal efficiencies – three pillars – are rooted in solving a jigsaw puzzle that maximizes its resources’ varied uses in incomplete markets. However, according to the resource-based view (Barney, 2002), once new resources uses are discovered, they become vulnerable to competitive imitation (Barney, 2002). This means arbitrage returns to an organization’s three pillars are subject to competitive imitation. Yet, since resources are combined in discrete combinations and have heterogeneous uses, there are multiple combinations and interpretations of their valued uses (Denrell et al., 2003). Furthermore, as an organization’s knowledge of resource uses is path dependent, interpretation of their uses can only be understood through an organization’s unique history of resource use experiences (e.g. Shane, 2000). These factors contribute to causal ambiguity to which mitigates competitive imitation. This implies arbitrage opportunities do not stem from an organization’s ability to quickly develop new resource combinations – as prescribed by dynamic capabilities research (Eisenhardt and Martin, 2000; Teece et al., 1997). Instead, and consistent with Penrose (1959), frequent resource changes are a means to accumulate an organization’s know-how in making better uses of its resources. These experiences uncover latent opportunities for further growth. Expansion options and first mover advantage (FMA). To elaborate, an organization’s exploitation of arbitrage opportunities seeds the development of ‘expansion options’. According to a real options framework, expansion options enable an organization to compete for future first mover advantages (FMA) in multiple product markets (Vassolo et al., 2004). This is because investments carry within them ‘expansion options’ or latent growth opportunities. These opportunities broaden an organization’s ‘ability to expand its strategy beyond its current boundaries’, which provides for ‘. . . the development of other products in the future’ (Barney, 2002, pp. 316–17). These options are a result of sunk costs or semi-irreversible resource commitments that give an organization the right, but not the obligation, to realize the latent values of its earlier investments (McGrath and Nerkar, 2004; Sirmon et al., 2007; Vassolo et al., 2004). In particular, Vassolo et al. (2004) show that expansion options lower the cost of entry into other product-markets and thus increase the odds of achieving FMA. However, as a real option logic has received only limited investigation in diversification research (Bowman and Hurry, 1993; McGrath and Nerkar, 2004), little is understood on the ‘organizational mechanisms’ that drive the discovery of expansion options (Bowman and Hurry, 1993). This study argues that the three pillars can promote the discovery of these options. Specifically, an organization’s strength of dynamic capabilities
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responds to the arbitrage opportunities of incomplete markets by diversifying into increasingly unrelated resources and uses. Diversification into these resources contains latent opportunities for further expansive growth, and thus acts as a purchase price for ‘expansion options’ to enter other products and markets. As these expansion options increase an organization’s odds of achieving future FMA (Vassolo et al., 2004), entry into new markets increases an organization’s resource use experiences. This increases an organization’s absorptive capacity and alertness to form weak ties. As weak ties introduce new resource use experiences and unrelated resources, they reveal further expansion options to enter more distant product markets. Therefore, through the self-reinforcing influences of the three pillars, the discovery of expansion options in one period provides opportunities to reveal further expansion options in the next. This subscribes to the view that prior sunk investments have a ‘super-additive effect’, in which the sequential exercise of expansion options lowers the costs of entry into increasingly distant markets (Vassolo et al., 2004). Since these super-additive effects are dependent on an organization’s unique resource use experiences, these expansion options and subsequent FMA are not imitable at a low cost. Therefore, relative to arbitrage opportunities, they yield a more sustainable source of competitive advantage. However, expansion options and their subsequent FMA may be tempered by obsolescence considerations because their underling sunk investments are subject to obsolescence (Lieberman and Montgomery, 1998). A real options logic, however, contends that multiple sunk investments create multiple product market positions that can be taken advantage of, if their market conditions later turn out to be promising (Bowman and Hurry, 1993; McGrath and Nerkar, 2004; Vassolo et al., 2004). This reduces an organization’s portfolio risk (e.g. Hoskisson, 1987; McGrath and Nerkar, 2004; Michel and Shaked, 1984). Nevertheless, expansion into multiple product-markets can be complicated by agency problems. At the expense of shareholder value, managers can undertake unrelated diversifications to benefit their personal interests (i.e. power, salary compensation) (e.g. Jensen, 1986; Shleifer and Vishny, 1989). Such conflicts of interests or agency costs are most pronounced when an organization has excess free cash and faces limited or declining markets ( Jensen, 1986). With excess free cash, managers have greater discretion to over-diversify because it increases managers’ compensation, power and control of resources ( Jensen, 1986). Furthermore, under limited or declining markets, managers face few investment opportunities, and thus diversified expansions are not likely to be value creating ( Jensen, 1986). Jensen (1986) thus concludes that managers with excess free cash ‘. . . are more likely to undertake low-benefit or even value-destroying mergers. Diversification programs generally fit this category’ (p. 328). Empirical studies have subsequently found that diversified organizations are traded at ‘discounted’ stock values (Berger and Ofek, 1995; Comment and Jarrell, 1995; Jensen, 1986). However, under incomplete markets, the three pillars model argues for an opposite conclusion to Jensen’s (1986) free cash flow argument. As market conditions dictate an organization’s optimal size, an optimal level of diversification therefore depends on the conditions of the market ( Jensen, 1986; Khanna and Palepu, 2000; Williamson, 1975). Specifically, as Jensen’s (1986) free cash flow argument rests on limited or declining market conditions, an optimal level of diversification is, therefore, to divest unrelated
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businesses. Yet, under incomplete markets, organizations are presented with opportunities to expand into new resources and uses. As a result, due to the growth prospects – arbitrage and FMA – of incomplete markets, the three pillars model favours diversified expansions rather than divestitures (see also Matsusaka, 2001). Furthermore, incomplete markets can also resolve Jensen’s (1986) agency cost of free cash flow. Namely, due to the arbitrage and FMA opportunities of incomplete markets, there are internal prospects (ex-ante) to invest in positive net present value projects (see also Matsusaka, 2001). With greater investment opportunities, free cash flows decline ( Jensen, 1986), which reduces managerial discretion to invest in personal projects. Moreover, a broader implication of the three pillars model is that aligning shareholder interests to an organization’s internal discovery process can ‘unintentionally’ reduce unrelated diversification performance. Under incomplete markets, external shareholders are less knowledgeable of an organization’s resources’ varied uses (Teece, 1982). As a result, by aligning shareholders’ interests to an organization’s discovery process, it would suppress the three pillars from discovering expansion options and thus reduce an organization’s FMA in multiple product markets. As unrelated diversification advantages are dependent on incomplete markets, the following is proposed: Proposition 2: In incomplete markets, increasingly diversified growth is positively related to arbitrage opportunities and expansion options that exploit FMA across multiple product markets. Limits to Unrelated Diversification Although the three pillars ‘accelerate’ the discovery of increasingly unrelated resources and uses, there are, however, increasing diversification costs. As an organization increasingly diversifies, the number of possible resource interdependencies grows at a geometric rate (Hill and Hoskisson, 1987). These interdependencies increase the likelihood of combining incompatible resources (Hales, 1999; Wright and Thompson, 1987) which can generate sub-optimal performance outcomes (Khanna and Palepu, 2000; Teng and Cummings, 2002; Whittington et al., 1999). For instance, Teng and Cummings (2002) and Whittington et al. (1999) argue that with increasing resource interdependencies, piecemeal or incremental changes to one resource can generate negative payoffs to other resources. Furthermore, there are also limits in an organization’s ability to efficiently govern diverse resources (Hales, 1999; Markides, 1995; Wright and Thompson, 1987). With increasing diversification, information is progressively communicated across multiple bureaucratic layers and across disparate business units (Markides, 1995). This greater administrative complexity distorts the quality of internal information which can result in a loss of control of operating activities (Hales, 1999; Markides, 1995). This is consistent with Hales (1999), Hill and Hoskisson (1987), Hill and Pickering (1986), and Wright and Thompson (1987), who contend that organizations face governance limits in effectively coordinating, monitoring and managing increasingly diverse resources and products. Moreover, despite the diversification advantages of internal capital markets (Williamson, 1975), the competitive efficiencies of internal capital markets have been criticized.
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Various researchers argue that the allocation of internal funds does not occur on the basis of internal competition, but rather on the basis of bargaining power (Argyres, 1996; Rajan et al., 2000; Scharfstein and Stein, 2000). Namely, as an organization diversifies, its weak divisions engage in wasteful rent seeking or lobbying behaviours (Argyres, 1996; Scharfstein and Stein, 2000). Such bargaining behaviours arise because ‘the opportunity cost to such managers of taking time away from their productive work to engage in rent seeking is lower’ (Scharfstein and Stein, 2000, p. 2539). As weaker divisions are better able to negotiate funds from senior management, weak divisions become subsidized by stronger divisions (e.g. Hill and Pickering, 1986; Rajan et al., 2000). Therefore, unlike the competitive efficiencies of internal capital markets (Williamson, 1975), internal funds are not allocated to strong performing divisions. Furthermore, this subsidization of weak divisions also leads to a less than efficient use of internal capital (Rajan et al., 2000; Scharfstein and Stein, 2000). In that, an organization’s opportunity cost of capital increases because opportunities to invest financial capital to higher yield alternatives are increasingly diverted to low valued business. These internal inefficiencies can, therefore, outweigh the discovery advantages of the three pillars. Summary of the Three Pillars Model Figure 1 outlines the key arguments of the three pillars model. The three pillars reflect an organization’s internal efficiencies to discover new resources and uses that cannot be revealed by incomplete markets. Unrelated diversifications are induced by the arbitrage opportunities of incomplete markets. Exploiting such arbitrage opportunities seeds the specialized growth of new resources and uses. As these new resources contain latent uses, they provide ‘expansion options’ to compete for future FMA in increasingly distant product markets. Entrance into these new and distant markets subsequently reinforces an organization’s three pillars to further diversify in incomplete markets. There are, however, some caveats to this model. First, a linear argument is made in which each pillar is built upon the diversification effects of others. That is, the three pillars rests on an implicit assumption that each pillar has functional and temporal interdependencies to other pillars. Yet, in practice these interdependences need not be fully realized because an organization may not possess all three pillars. As a result, some interdependencies and pillars will be emphasized over others which can yield a different linear sequence of diversification. Second, unrelated diversification is beneficial, only when resources are heterogeneous, discrete and indivisible. For instance, if resources are not heterogeneous, markets are ‘complete’ and thus the discovery advantages of the three pillars would be eliminated. Furthermore, in conjunction with heterogeneous resources, the absence of discrete and indivisible resources removes an organization’s jigsaw problem, which leaves no internal incentive for an organization to diversify. Future Directions As incomplete markets are key to an organization’s unrelated diversification, a useful exercise would be to identify industries that are most suitable to examining the three pillars logic. Since knowledge intensive industries exhibit market inefficiencies in trading
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Increasing Diversification and Development of Expansion Options

Arbitrage Opportunities of Incomplete Markets

Exploit FMA in Distant Product Markets

Strength of Dynamic Capabilities

Alertness to Weak Ties

Absorptive Capacity (Diversity of Resource Use Experiences)

(Three Pillars of Growth)
Figure 1. Balance Process of Increasingly Unrelated Diversification

and valuing knowledge (Teece, 1982), these industries are more likely to experience incomplete market conditions. For instance, in the biotechnology industry the development of basic biotechnology research requires protracted periods of development (7–11 years), during which their varied commercial applications (i.e. heterogeneous resource uses) are highly uncertain (McGrath and Nerkar, 2004). As the varied commercial applications of basic biotechnology research are not well known to the market, the biotechnology industry is, therefore, vulnerable to incomplete market conditions. There is also some supporting evidence to suggest a high level of diversification in this industry. For instance, relative to manufacturing based segments (i.e. paper, rubber, metal and food manufacturing), Argyres (1996) found significant technological diversification in the chemical and pharmaceutical industries (see also McGrath and Nerkar, 2004). Furthermore, in Carow et al.’s (2004) study of merger waves in the 1990s, they found 10 of the 14 identified mergers were expansionary and occurred in knowledge intensive industries, while the remaining mergers were of a contractionary nature and occurred in less knowledge intensive industries (i.e. manufacturing based segments). Measures of Diversification and the Three Pillars Furthermore, as the measurements of diversification, and in particular, dynamic capabilities, absorptive capacity and weak ties remain key challenges in empirical research
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(Hall and St John, 1994; Hoopes et al., 2003; McEvily and Zaheer, 1999; Zahra and George, 2002), this study offers some suggestions for their measurement. An organization’s unrelated diversification can be measured by its product diversification (Chatterjee and Wernerfelt, 1991; Khanna and Palepu, 2000; Montgomery and Hariharan, 1991). This is measured by the ‘distance’ of an organization’s product sales from its core business. This distance draws on the SIC (Standard Industrial Classification) system, whereby the sales of products that are not in same SIC classification as an organization’s core business are given a larger distance or weight (i.e. greater diversification) (Chatterjee and Wernerfelt, 1991; Khanna and Palepu, 2000; Montgomery and Hariharan, 1991). Although this measure is commonly used in unrelated diversification research, readers should be aware of its limitations. SIC measures tend to focus on an organization’s inputs and production[4] and do not capture an organization’s resource relatedness (Hall and St John, 1994). Farjoun (1994) offers one approach to measuring resource relatedness; however, relatedness is measured at the industry group level. Other researchers have used Rumelt’s (1974) diversification categorical measure because it directly captures an organization’s resource relatedness, which can include other forms of relatedness such as marketing and distribution relatedness (Hall and St John, 1994). With respect to the strength of dynamic capabilities, it can be measured by an organization’s patent rate. An organization’s patents are a common measure of its technical expertise and reflect signals to commercialize basic inventions (Sorenson and Stuart, 2000). Since an organization’s weak form dynamic capability leverages prior experiences to reveal new uses (i.e. commercialize products), the rate at which an organization cites its prior patents – self citations – can be used (e.g. Sorenson and Stuart, 2000). Similarly, as strong form dynamic capabilities do not leverage prior organizational experiences, it can be measured by the rate at which it cites non-self-citing patents (e.g. Sorenson and Stuart, 2000). An organization’s absorptive capacity can be measured by its cumulative number of distinct areas of research/technological specializations (Nicholls-Nixon and Woo, 2003). This is because increases in an organization’s diversity of experiences promote the commercialization of new products (Cohen and Levinthal, 1990; NichollsNixon and Woo, 2003; Zahra and George, 2002). In this way, an organization’s diversity of technological specializations (Nicholls-Nixon and Woo, 2003) is an input to its unrelated diversification. Lastly, an organization’s weak ties can be measured by the frequency of its alliance relationships (e.g. McEvily and Zaheer, 1999). However, to account for the bridging function of weak ties, alliance frequency can be measured by the frequency of alliances with organizations of a different primary SIC classification. Based on these measures, Proposition 1 can be restated as Hypothesis 1. Hypothesis 1: In incomplete markets (e.g. biotechnology), an organization’s unrelated diversification (product diversification) is positively related to each of the three pillars: (a) self (weak form dynamic capabilities) and non-self cited (strong form dynamic capabilities) patent rates, (b) diversity of specialized expertise (absorptive capacity), (c) alliance frequencies (weak ties).
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Diversification performance. Arbitrage opportunities can be measured by an organization’s ‘move timing’, which is measured as the elapsed time between the launch date of a new product and the date competitors introduce an imitative product (Lee et al., 2000). Move timing can measure arbitrage opportunities because it reflects an organization’s ability to foresee and capitalize on the value of its new resource uses (i.e. new products) before the arrival of its competitive rivals. Lee et al. (2000) also found that move timing is positively related to organization performance. In addition, expansion options can be measured by the number of expansionary investments made outside an organization’s primary SIC classification. Such expansionary investments consist of the number of acquisitions made into non-primary SIC segments (e.g. Vassolo et al., 2004). Lastly, FMA can be measured by an organization’s Tobin’s q (Bharadwaj et al., 1999). Since diversification rests on seeking better uses from an organization’s untapped resources, Tobin’s q can measure the latent value of an organization’s resources. Furthermore, relative to accounting based measures, Tobin’s q is used as a preferred measure of diversification performance (e.g. Khanna and Palepu, 2000; Montgomery and Wernerfelt, 1988; Villalonga, 2004) because accounting based measures (i.e. ROA, ROE and ROS) have been criticized for not considering market based risks, can be biased by accounting conventions and are not forward looking (Bharadwaj et al., 1999; Khanna and Palepu, 2000; Montgomery and Wernerfelt, 1988). Given these measures, Proposition 2 can be restated as Hypothesis 2. Hypothesis 2: In incomplete markets, unrelated diversification (i.e. product diversification) is positively[5] related to each of the following performance measures: (a) move timing (arbitrage), (b) number of expansionary investments (expansion options), (c) Tobin’s q (FMA). DISCUSSION AND CONCLUSIONS How and why an organization diversifies into unrelated businesses is not well understood in strategy research. In augmenting Penrose’s (1959) resource-based approach with an incomplete market approach (Denrell et al., 2003), a three pillars model is proposed. This conceptual model offers three contributions to unrelated diversification research. First, although the three pillars subscribes to the efficiencies of internal capital markets (Williamson, 1975), an organization’s unrelated diversification is motivated by a different form of internal efficiency. Unlike Williamson (1975), the efficiencies of the three pillars are not based on an internal competition of homogeneous business units, but rather are founded on a resource based logic. Specifically, in conditions when markets are incomplete and when resources are heterogeneous, discrete and indivisible, an organization diversifies into unrelated businesses because of its internal efficiencies – three pillars – in seeing and putting together pieces of a jigsaw puzzle that cannot be seen or solved by incomplete markets. This internal efficiency has not been discussed in prior unrelated diversification research (see Campa and Kedia, 2002; Chatterjee and Wernerfelt, 1991; Hill and Hoskisson, 1987; Hoskisson, 1987; Khanna and Palepu, 2000; Teece, 1982; Villalonga, 2004; Williamson, 1975). Furthermore, this internal efficiency also provides
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a different motivation for explaining an organization’s exchange relationships with external markets. For instance, according to Williamson’s (1975) Transaction Cost Economic (TCE) logic, the internalization of diversified activities is a means to circumvent the contractual problems of hold up. However, the three pillars model contends that the internalization of resources is a response to an organization’s internal ability to see better uses for its resources than external markets. Consequently, problems of opportunism or hold up need not be exclusive motivations for the internalization of market activities. Second, a market failure treatment of Penrose’s (1959) resource based logic has been largely absent in diversification research (see Montgomery and Hariharan, 1991; Teece, 1982). This is because resource based and market failure explanations have developed as largely separate research streams (see Hoskisson and Hitt, 1990; Palich et al., 2000). By introducing the notion of incomplete markets, the three pillars model (i.e. Proposition 1) broadens the path-dependent logic ascribed by Penrose and other modern resourcebased approaches (e.g. Teece et al., 1997), and as a consequence provides an explanation of unrelated diversifications that has not been examined by these approaches. The three pillars model also provides broader contributions to strategy research. As there is an absence of models that explain an organization’s resource heterogeneity (Helfat and Peteraf, 2003; Hoopes et al., 2003; Miller, 2003), the three pillars model provides one alternative to explaining this heterogeneity. Third, by taking account of incomplete market conditions, this study also introduces unrelated diversification advantages – arbitrage opportunities, expansion options and FMA – that have not been examined in resource-based (Penrose, 1959; Teece et al., 1997) and unrelated diversification-performance research (Hill and Hoskisson, 1987; Hill et al., 1992; Williamson, 1975). In particular, as there is still considerable debate on the performance of related vs. unrelated diversification (Hoskisson and Hitt, 1990; Khanna and Palepu, 2000), the three pillars emphasizes that the sequential discovery of expansion options can positively impact an organization’s diversification performance. Such a real options approach to explaining unrelated diversification performance has been absent in prior studies (see Campa and Kedia, 2002; Chatterjee and Wernerfelt, 1991; Williamson, 1975). This is because these studies do not typically consider the latent value of resources (Bowman and Hurry, 1993; McGrath and Nerkar, 2004). Furthermore, unlike Jensen’s (1986) free cash flow argument, the three pillars model predicts that diversification in incomplete markets can yield a premium and can reduce the agency cost of free cash flow. The three pillars model, therefore, offers potential extensions to Jensen’s free cash flow logic. The three pillars model is, however, limited in its discussion of organizational decline. Peteraf and Bergen’s (2003) lifecycle framework can be used to address this limitation. According to their lifecycle framework, an organization can ‘retire’ its resources and capabilities if demand for its products is reduced. This would lead to a ‘retrenchment’ or a gradual refocusing of an organization’s resources and capabilities (Peteraf and Bergen, 2003). In the context of the three pillars, this involves the divestiture of non-related resources, which would favour weak rather than strong form dynamic capabilities that emphasize the discovery of untapped uses from its core resources. This reduces an organization’s diversity of resource use experiences and absorptive capacity. Strong (as
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opposed to weak) ties are formed with similar organizational members (Granovetter, 1983). As strong ties leverage redundant knowledge experiences (Granovetter, 1983), they promote incremental innovations that build on an organization’s core resources. Through Peteraf and Bergen’s (2003) life cycle argument, the three pillars model can, therefore, be extended to explain an organization’s decline. This calls for future research. NOTES
[1] Furthermore, Kor and Mahoney (2004) and Rugman and Verbeke (2004) agree that Penrose has directly or indirectly impacted the development of dynamic capabilities research. [2] This is consistent with a key argument in strategic alliance research which finds that social ties promote value creation (Anand and Khanna, 2000). [3] Note that a majority of related diversification studies measure performance with financial accounting measures of performance (ROA, ROS, ROE, etc) to which does not account for the market risks that are implicit in market failures. [4] This was pointed out by an anonymous reviewer. [5] However, as pointed by an anonymous reviewer, due to the rising costs of diversification, unrelated diversifications beyond a certain point can potentially exhibit a diminishing effect.

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