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Ian P. L. Kwan

Introduction

This review identifies relevant theories and methods from the strategy literature on organizational learning and from the finance literature on valuation concerning strategic alliances. It proceeds as follows. The first section reviews answers to preliminary questions about strategic alliances, serving as an introduction to the topic for readers. The next section reviews earlier strategy literature on the market-based view, resource-based view, knowledge-based view, and transaction cost approaches, analyzing strategic alliances in the light of each. It also reviews relevant financial methods of valuation, including the discounted cash flow method, real options method, and event study method, again applying them to the case of alliances. The final section provides a summary of studies on value creation by strategic alliances.

Preliminary questions and answers on strategic alliances

Many researchers on strategic alliances frequently introduce the setting of their academic papers by describing a significant aspect of strategic alliance activity to attract their readers’ attention. This is often a definition of what a strategic alliance is or some important or well-known aspect of alliances, such as how often they occur, who engages in them, why they engage in them, when they occur, when they break up, and so on. These preliminary issues provide context for the readers and lead to the papers’ main issues. I would like to do the same in this chapter by providing a summary of answers to common preliminary questions on strategic alliances that are often found in the introductory sections of this literature.

What is a strategic alliance?

A strategic alliance is a cooperative agreement made between two or more independent firms to achieve a mutual set of objectives (Kogut, 1988; Gulati, 1998; Ireland, Hitt, and Vaidyanath, 2002). Through an alliance, firms necessarily commit to share a subset of their tangible and intangible resources (Barney, 1991; Grant, 1991). Tangible resources include physical assets such as plant and equipment, or services such as a proprietary distribution network or computer system, while intangible resources include access to intellectual capital tied up in licensed patents and production processes.

An alliance is a hybrid organizational form through which two or more firms can combine their business resources. The alliance organizational form lies in the continuum between a market exchange contract and a merger of firms (Kogut, 1988; Lerner and Rajan, 2006; Villalonga and McGahan, 2005). A firm can access the resources of another through market exchange contracts quickly and without the buyer and seller knowing each other. Market exchange contracts are characterized by their standard terms, standard product or service quality, industry accepted delivery times, common pricing methods, and so on. A firm can also access the resources of another by merging with that firm. Mergers are characterized by their complexity, extended personal negotiations, and information asymmetries (Zollo and Reuer, 2010).

In this chapter, I use strategic alliance or simply alliance as a collective term to mean licensing agreements, franchise agreements, contractual (non-equity) joint ventures, and equity joint ventures (Inkpen, 1998a; Parkhe, 1991).

Where? How many? How significant?

Alliances are found in almost all industries, in both domestic and international business environments. However, they are most prevalent in high-technology, fast-changing, highly competitive, research-intensive industries, including computers, telecommunications, pharmaceuticals, chemicals, electronics, biotechnology, and services (Kale, Dyer, and Singh, 2002; Rothaermel and Deeds, 2004). Alliances are less common in stable, mature industries (Koza and Lewin, 1998).

The empirical findings of Eisenhardt and Schoonhoven (1996) provide a good answer to the question of where to find alliances from both a strategic and a social point of view.

More alliances are formed in industries that have more competitors. In competitive markets with many players, greater market power can be achieved through forming an alliance. Alliances with well-known firms also provide legitimacy to less well-known firms, especially in a crowded market.
There is a greater rate of alliance formation in industries that require greater innovation. As innovative products are costly to create, firms tend to choose alliances to gain access to and share their own innovative know-how to reduce costs.
Alliances form more often when there are a large number of top management team members. Top management members provide the necessary connections to potential alliance partners.
The more previous employees the top management team has had, the greater will be the rate of alliance formation.
The more senior were the previous positions of top management members, the more frequent will be the rate of alliance formation.
Although the empirical support is not strong, the frequency of alliance formation tends to be highest in emergent-stage markets, lower in growth-stage markets, and lowest in mature-stage markets.

International joint ventures are the usual mode of entry for domestic firms to enter into global markets (Berg, Duncan, and Friedman, 1982; Harrigan, 1985), especially those of emerging economies (Peng, 2003; Fang, 2011) because their structural attributes help firms to reduce risk (Reuer and Leiblein, 2000).

The number of alliances has grown significantly over the past 30 years. There was a huge wave of 57,000 alliances for US firms between 1996 and 2001 (Dyer, Kale, and Singh, 2004). World-wide, 20,000 alliances were formed between 1998 and 2000 (Anand and Khanna, 2000). According to the Securities Data Corporation (SDC) Joint Ventures and Alliances database, in 2005 over 52,000 completed or pending alliances were reported. According to a 2009 study by KPMG International, the number of joint venture strategic alliances continued to grow in spite of the global financial crisis.^¹

The volume of assets and revenue linked with alliances in mainstream business is also very significant. Before the year 2000, many of world’s largest firms had over 20 percent of their assets and over 30 percent of their R&D budget tied up with alliances (Ernst, 2004; Kale and Singh, 2009). In the 2007–2008 financial year, more than 80 percent of Fortune 1000 CEOs believed that alliances would account for 26 percent of their companies’ revenues (Kale, Singh, and Bell, 2009; Kale and Singh, 2009). In sum, as a way of doing business, alliances seem here to stay for some time into the future.

Why do firms form alliances?

Some commonly cited motives why firms form alliances include:

strengthening their competitive position through combined market power (Kogut, 1991);
increasing scale efficiencies through reduced transaction costs (Hennart, 1988; Ahuja, 2000);
gaining access to new and critical resources and capabilities (Hitt et al., 2000; Rothaermel and Boeker, 2008);
accessing new technologies and innovative know-how of partners (Hamel, 1991; Vanhaverbeke, Duysters, and Noorderhaven, 2002);
responding to strategic resource interdependence between partners (Gulati, 1998);
lowering the risk of entering new markets for the first time (Inkpen and Beamish, 1997; García-Canal, Duarte, Criado, and Llaneza, 2002);
trust and repeated ties (Gulati, 1995); and
complementarity of resource bases (Lin, Yang, and Arya, 2009).

Other reasons why firms may form alliances include:

following the momentum created from successfully forming previous alliances (Dyer, Kale, and Singh, 2004);
taking advantage of the resources available through the rich industry network (Mitsuhashi and Greve, 2009; Ahuja, Polidoro, and Mitchell, 2009);
perceptions of fairness of between firms negotiating an alliance (Ariño and Ring, 2010); and
the relative status of firms within the industry or alliance network (Lin, Yang, and Arya, 2009).

Rothaermel and Boeker (2008) provide a good summary of different motives for alliance formation in the introductory section of their paper with the requisite citations to the literature.

Do alliances create value? How is it shared?

On average, the formation of alliances creates value for the partners’ stock holders, albeit in the short term (McConnell and Nantell, 1985; Chan, Kensinger, Keown, and Martin, 1997; Anand and Khanna, 2000). There is a positive correlation between the short-term performance measured by stock market reaction to alliance announcements and the long-term performance measured by alliance managers’ assessments of success (Kale, Dyer, and Singh, 2002).

Alliance value creation depends on the experience firms gain from forming alliances and the type of alliance contract that is drafted (Anand and Khanna, 2000). For example, experience in joint ventures creates more value than more experience in licensing agreements. Furthermore, Anand and Khanna (2000) found that more experience in joint ventures that involved research and production showed stronger learning effects than those of marketing joint ventures. However, there are conflicting results about the effect of partner-specific experience on alliance value creation. While Hoang and Rothaermel (2005) find partner-specific experience or repeated alliances with the same partner to have a negative impact on value creation, Zollo, Reuer, and Singh (2002) and Gulati, Lavie, and Singh (2009) argue that it has a significantly positive effect.

Asymmetries in the sharing of value created from alliances depend on the position in the value chain and the resource dependency between partners (Dyer, Singh, and Kale, 2008). Partners of horizontal joint ventures tend to share the synergy gains equally, while suppliers of vertical joint ventures tend to gain significantly more than buyers (Johnson and Houston, 2000). Kumar (2010) found that partners with a strong resource dependency on the other joint venture partner experienced lower gains than the less dependent partner. This finding agrees with other research (Adegbesan and Higgins, 2011; Inkpen and Beamish, 1997), which shows that asymmetries in sharing of value created also depend on the bargaining positions in terms of the partners’ mutual resource dependency. Other factors that drive asymmetric gains include differences in the firms’ abilities to learn and benefit from that learning (Hamel, 1991) and differences in information access among parent firms (Reuer and Koza, 2000).

Do alliances fail? How often? Why are they unstable?

Although alliances on average create value, more than half of them fail (Kale and Singh, 2009). In fact, various studies have estimated the failure rate to be anywhere between 30 and 70 percent, where “failure” is defined as either not meeting the goals set by the parent firm or not delivering the operational or strategic benefits they were designed to achieve (Bamford, Gomes-Casseres, and Robinson, 2004). Alliances are particularly prone to failure in the first few years after formation (Kogut, 1989; Bleeke and Ernst, 1993).

International alliances are more unstable because of the significant coordination costs, cultural and language differences, difficulties reconciling conflicting goals between independently owned partners, and always the threat of creating a competitor (Porter, 1990; Inkpen and Beamish, 1997; Peng and Shenkar, 2002; Fang, 2011). They are also notorious for their 50 percent failure rates (Bleeke and Ernst, 1993; Kogut, 1988).

Alliances, both domestic and international, often fail because of poor partner selection, which later results in a mismatch of resources and insignificant synergy gains (Hitt et al., 2000). Failure can also be due to poor management of the alliance, which fails to build social capital that maximizes the trust between the partners and to develop adequate learning systems within the alliance (Ireland, Hitt, and Vaidyanath, 2002). Competitive rivalry between partners may also cause alliance failure (Kogut, 1989; Dussauge, Garrette, and Mitchell, 2000). While reducing competitive rivalry may have been an initial reason behind allying firms’ decision to cooperate, the same competitive forces may later drive them to take advantage of each other.

In general, failures to form alliances or challenges in managing alliances can be understood in terms of the internal tensions between the partners. Specifically, the three key dimensions are: cooperation versus competition; rigidity versus flexibility; and short-term versus long-term orientation (Das and Teng, 2000a). These internal tensions are feedback mechanisms that force the partners to engage in the renegotiation of the alliance contract or to modify their behavior to restore balance to the relationship (Ariño and de la Torre, 1998). Coupled with the tensions caused by the simultaneous changes in the external business environment, the alliance relationship co-evolves in tandem, adding to the instability (Doz, 1996; Das and Teng, 2002).

Which one? Alliance or acquisition?

Combining resources through alliances and acquisitions are similar but not identical processes (Yin and Shanley, 2008). Acquisitions are competitive processes and involve the displacement of the target firm’s management. Alliances, on the other hand, are cooperative and require ongoing dealings with the partner’s management (Dyer, Kale, and Singh, 2004). Choosing between engaging in one or the other requires firms to analyze at least three factors: the desired resources and synergies; the market place in which they are competing; and their ability to collaborate with the partner firm (Dyer, Kale, and Singh, 2004: 110). However, firms may have a pre-specified preference to engage in one form of governance over the other because of certain characteristics of the firm itself, rather than the characteristics of the deal or the partner/target (Villalonga and McGahan, 2005).

Firms that are more likely to engage in an acquisition have similar resource bases to the target and more prior acquisition experience, while firms that are more likely to engage in an alliance tend to have complementary resource bases with the target and more prior alliance experience (Wang and Zajac, 2007). Furthermore, the decision a firm makes to ally or acquire is taken in view of its overall position in the network of firms with which it has relationships, rather than as if it were independent of these influences (Yang, Lin, and Lin, 2010).

Firms may also engage in an alliance with the intention of investing in an option to acquire the partner later (Kogut, 1991; Chi, 2000). Gaining partner-specific alliance experience with a target before acquiring it is one way in which firms reduce information asymmetries before engaging in an acquisition (Agarwal, Anand, and Croson, 2006; Zaheer, Hernandez, and Banerjee, 2010; Porrini, 2004). However, the most recent literature that looks at the relationship between alliances and acquisitions (Ragozzino and Moschieri, 2014) finds that less than 1.3 percent of 25,000 global acquisitions occurring between 1995 and 2012 involved a prior alliance between acquirer and target before the acquisition, suggesting that the practice of acquiring an alliance partner is not as widespread as the theory would suggest.

A review of the strategy and financial valuation literatures

Theories from the strategy literature

The following sub-sections provide brief summaries of various theoretical views of the firm that are found in the strategy literature. The idea is to highlight relevant parts of these theories that provide insights into strategic alliances from the organizational learning and financial valuation perspectives. The four sub-sections cover: the market-based view; resource-based view; knowledge-based view; and transaction cost approach.

Market-based view

The market-based view (MBV) is an outside perspective of the firm and concerns how companies position themselves in the market or industry in order to compete profitably (Makhija, 2003). Originating from early industrial organization theory (see Bain, 1950, 1956; Mason, 1964), MBV describes how firms effect long-term profitability by erecting entry barriers to increase monopoly power over customers and bargaining power over suppliers (Grant, 1991). These barriers, which may prevent new industry entrants, are formed by developing: greater economies of scale; finer product market differentiation; higher capital resource requirements; lower cost advantages; more complex proprietary knowledge; more exclusive access to distribution channels; and lobbying for government policy that discriminates against competitors that do not meet certain standards (Bain, 1956; Porter, 1979a). MBV is based on two assumptions: that entry barriers provide common and equal protection to all incumbent firms, conferring some degree of monopoly or oligopoly power; and that firm resources are homogeneous and hence relatively transferrable between incumbent firms (i.e. mobile resources). This version of MBV, however, cannot explain why over the long term in the same industry different firms or groups of firms can coexist, with each pursuing different strategies while at same time earning different profit margins.

Explaining this mutual but differential coexistence requires extending MBV to include concepts such as strategic groups and mobility barriers (see Porter, 1979b; Caves and Porter, 1978). It is worth summarizing these concepts in more detail because of the similarities and relevance in respect to strategic alliances and valuation. As Porter (1979b) and Caves and Porter (1977) explain, an industry consists of multiple strategic groups – collections of firms that are defined by their member firms’ adherence to a particular strategy. Each strategic group erects its own set of entry barriers to prevent the mobility of new rival groups entering the industry (inter-industry mobility) and to deter the mobility of other strategic groups within the industry entering their territory (inter-group mobility). Strategic groups with high mobility entry barriers are relatively more insulated from competitive rivalry within the industry, have superior bargaining power over other strategic groups both within and outside the industry, and experience less threat from rivals. Thus, the distribution of profitability rates enjoyed by individual firms will depend on two structural influences:

the structural nature of the firm’s industry relative to other industries – the greater the bargaining power the firm’s industry has over its buyer or supplier industries, the more profitable will be the industry as a whole; and
the structural nature of the firm’s strategic group relative to other strategic groups – the higher the mobility barriers of the strategic group, the greater will be that group’s share of the industry profits.

Mobility barriers include investments in advertising, R&D, or building an in-house service capability (Porter, 1979b: 217), which, while costly in the short run, protect long-run profits.

The presence of multiple strategic groups in an industry, Porter (1979b: 217–218) goes on to explain, affects the nature of inter-firm rivalry and hence the average level and dispersion of profits enjoyed by industry participants under the basic rule that the greater rivalry, the lower the profits. Three factors affect the competitive rivalry between strategic groups:

number and size distribution – the more groups and the more they are equal in size, the greater will be the rivalry;
strategic distance – the more similar they are in strategy, the more will be the rivalry (this can be described in terms of advertising, cost structure, R&D, etc.); and
market interdependence – the more they share the same customers from the same market segment, the greater the rivalry.

Porter (1979a, 1985) summarizes the principal concepts of MBV in his celebrated five-forces model, which includes:

threats of new entrants;
threats from substitutes;
bargaining power of suppliers;
bargaining power of customers; and
industry rivalry.

The model can be applied at either the firm or the industry level (i.e. inter-firm and inter-group rivalry). Under MBV, the role of management is therefore to assess the industry environment and to position the firm in attractive market segments according to three generic competitive strategies:

low-cost strategy in which it can take high market share;
differentiation strategy in which it tries to dominate in a certain number of segments; or
niche strategy in which it aims for high margins in selected segments.

(Porter, 1985)

While MBV is an external view of the firm from the industry or market level, Porter recognizes the importance of the structure and organization within firms. His widely celebrated value chain (Porter, 1985) divides the firm into primary or line activities and secondary or support activities. The ability for the firm to manage the linkages between these activities effectively is a source of competitive advantage that positively affects the profit margins the firm is able to achieve from customers above its competitors.

Application to alliances

MBV would therefore argue that strategic alliances of same-industry firms are motivated to cooperate (i.e. collude) in order to achieve at least one of three main objectives (Grant, 1991; Makhija, 2003):

to increase market power or strengthen market position against other competing firms or alliances;
to raise higher entry barriers to prevent new rival firms or alliances from entering the market segment; or
to increase bargaining power against common suppliers and customers of the alliance partners.

MBV would further argue that the formation of strategic alliances dynamically changes the structure of market power of the industry as competing alliances (i.e. strategic groups) change their mobility barriers with respect to each other. If the formation of alliances consolidates the industry into a smaller number of alliances, industry rivalry should decrease, positively affecting profit margins. If the number of alliances increases, the opposite effect would be observed. Furthermore, Porter (1979b: 217) would argue that the strength of monopoly or oligopoly power enjoyed by alliance firms is a function of the unity of strategy amongst the allying firms. However, divergent strategies amongst allying firms reduces this power, with a concomitant decrease in margins, because of increased difficulty in tacit coordination between partnering firms and decreased information flow through common customers.

But not all alliances which may seem to be motivated by collusion are contrary to public welfare, even amongst firms in a concentrated industry. As Kogut (1988: 322) points out,

Where there are strong network externalities, such as in technological compatibility of communication services, joint R&D of standards can result in lower prices and improved quality in the final market. Research joint ventures which avoid costly duplication among firms but still preserve downstream competition can similarly be shown to be welfare-improving.

Other studies do show that alliances are motivated by market-positioning motives, however. Vickers (1985) shows that firms may sometimes use joint ventures to patent small technological innovations pre-emptively as deterrents against new market entrants. Using a simple model of Cournot competition, Mathews (2006) shows how an incumbent deters an entrepreneurial firm from market entry by selling equity in its firm.

Resource-based view

In contrast to MBV, the resource-based view (RBV) is an inside perspective of the firm and concerns how a firm combines its strategically important resources using the capabilities it has developed to compete profitably against other firms (see Barney, 1991; Grant, 1991; Peteraf, 1993; Prahalad and Hamel, 1990). The origins of RBV stem from the work of Penrose (1959), who observed that strategic resource heterogeneity between firms was a source of earning sustainable Ricardian rents – that is, firms with superior resources have lower average costs than other firms (Peteraf, 1993) and the asymmetry of resource positions leads to the sustainability of above-average rents (Amit and Schoemaker, 1993). Following Penrose’s work, RBV arose from a certain “dissatisfaction with the static, equilibrium framework industrial organization economics that [had] dominated much of contemporary thinking about business strategy” (Grant, 1991: 114). It began to emerge in the 1980s as an alternative explanation for the competitive strategies of firms (Wernerfelt, 1984; Barney, 1986). Rather than focusing on the competitive position of a firm in the market, “managers should instead [focus] their analysis on their unique skills and resources” (Dierickx and Cool, 1989: 1504).

Unlike MBV, which views strategic firm resources as homogeneous and mobile between firms of the same strategic group (i.e. easily transferrable), RBV conceptualizes each firm as a bundle of heterogeneous strategic resources that are generally not easily transferrable between firms (Barney, 1991) and therefore are not usually traded in strategic factor markets (Barney, 1986). Firms can develop a sustained competitive advantage and achieve superior profitability if they have access to strategic resources that possess four important attributes:

valuable;
rare;
non-imitable; and
non-substitutable.

(Barney, 1991)

However, competitive advantage is not achieved merely by combining strategic resources, but requires a careful system of coordination and control across an entire firm, which in turn fits the firm’s corporate strategy (Collis and Montgomery, 1998).

Scholars have put forward various classifications of a firm’s strategic resources. Grant (1991) provides six major categories of resources: financial; physical, human; technological; reputational; and organizational. Barney (1991) groups resources into just three categories: physical capital; human capital; and organizational capital.

As strategic resources are generally not traded in strategic factor markets, to access new ones, firms need to either develop them internally or combine theirs with those of other firms (Wernerfelt, 1984; Dierickx and Cool, 1989). The internal accumulation of a strategic resource, however, requires choosing appropriate time paths of flow variables to build the resource stocks (Dierickx and Cool, 1989) – that is, a firm builds a strategic resource through a deliberate and consistent policy of acting, which requires time and constant effort. Dierickx and Cool (1989: 1507–1509) distinguish between stocks and flows of assets or strategic resources. The term “stock” refers to the level of asset accumulation, while flow refers to the rate of accumulation. These authors also identify several characteristics of the process of accumulating stocks of strategic resources:

time decompression economies – certain resources need a minimum amount of time to build and shortening the process leads to diseconomies or lower-quality stock;
asset mass efficiencies – a minimum stock of existing resources is required to build new ones efficiently (“success is needed to breed success”);
asset interconnectedness – the growth in stock of one asset may depend on the level of stock of other assets (growth interdependencies);
asset erosion – the strategic value of resource stocks decreases over time and certain “maintenance costs” need to be paid to keep them from decaying excessively;
causal ambiguity – the direction of resource accumulation is not linear, and depends on current levels of stock and on factors that are beyond the firm’s control or simply random; and
asset substitution – stocks of strategic resources can be substituted by other resources.

These characteristics do not apply to all resources, but to those of a strategic nature.

Application to alliances

If a firm cannot overcome the stock and flow process limitations to build its own strategic resources, it will need to resort to strategic alliances and acquisitions in order to remain competitive. While these forms of business combinations may help the firm to catch up with or even overtake its competitors by “leap-frogging” certain requirements of the resource-building process – for example, jumping over the time diseconomies to build a minimum asset base – it may still be limited by the other requirements, such as managing the interdependencies between its existing asset base and the assets to be combined. Firms that have developed a capability to combine resources accessed through a strategic alliance or acquired through an acquisition are therefore at a distinct advantage (Kogut and Zander, 1992; Bresman, Birkinshaw, and Nobel, 1999; Hamel, 1991). The ability to learn as an organization is itself a strategic firm resource (Grant, 1991; Kogut and Zander, 1993).

Knowledge-based view: organizational learning and capabilities

The study of organizational learning and how firms develop organizational capabilities has emerged from the knowledge-based view (KBV) of firms, an important extension of RBV. Under KBV, the firm is conceived as an organizational structure through which knowledge is created (Nonaka, 1991, 1994).

Knowledge is a special type of firm resource that has been categorized into two types: tacit knowledge and explicit knowledge (Nonaka, 1994; Grant, 1996a). The categories can be further analyzed according to three important characteristics (Grant, 1996a):

Transferability. Explicit knowledge is transferred as soon as it is revealed because it can be codified in a common format or language that others can read and interpret, such as: statistics, lists, tables, descriptions, and so on. Tacit knowledge, in contrast, is “sticky” because it stays with the knowledge owner and is transferred to the learner only if it is constantly practiced with use and experience. It is not easily codified or expressed in a standard language.
Aggregability. While explicit knowledge, because of its common format, can be easily stored and transferred in limitless quantities, tacit knowledge resides with the knowledge owner and is not easily duplicated or imitated.
Appropriability. This refers to the resource owner’s ability to receive a return equal to the value created by the resource (Teece, 1987). While explicit knowledge becomes a public good (i.e. has low marginal cost) and loses its appropriability as soon as it is revealed, tacit knowledge increases in appropriability because its non-transferability and non-aggregability make it a rare and valuable good. In sum, tacit knowledge is a strategic resource, while explicit knowledge is not and quickly loses value.

Tacit knowledge is more easily transferred if the learner already has a base of similar knowledge – that is, absorptive capacity (Cohen and Levinthal, 1990). Absorptive capacity is firm’s ability to value, assimilate, and utilize new external knowledge, and it is critical to its innovative capability and sustainable competitive advantage (Zahra and George, 2002). The development of absorptive capacity is history- or path-dependent and the failure of a firm to continue to invest in its development, especially in fast-pace and research-intensive industries, may foreclose future opportunities for absorptive capacity development (Cohen and Levinthal, 1990; Dierickx and Cool, 1989). While absorptive capacity is a firm-level resource, it can also be conceptualized as an inter-firm-level resource called relative absorptive capacity (Lane and Lubatkin, 1998). Relative absorptive capacity is based on the dyadic relationship between two firms, for example in a strategic alliance, and depends on the similarity between the firms’ knowledge bases, organizational structures and policies, and business strategies.

Application to alliances

Firms are able to access each other’s tacit knowledge resources through strategic alliances (Inkpen, 1998b; Stuart, 2000; Gomes-Casseres, Hagedoorn, and Jaffe, 2006). Value creation through strategic alliances is enhanced because the tacit knowledge resources of each allying firm are imperfectly mobile (not easily transferred), imperfectly imitable, and imperfectly substitutable (Das and Teng, 2000b; Grant and Baden-Fuller, 2004). Furthermore, as firms share their tacit knowledge resources, they tend to become more specialized in their area of knowledge expertise (Mowery, Oxley, and Silverman, 1996). Specialization in knowledge creation allows allying firms to prosper in competitive environments by allowing each one, on the one hand, to focus efforts on creation of its specialized knowledge while, on the other, to access its alliance partners’ specialized knowledge and integrate it with their own (Grant and Baden-Fuller, 1995, 2004).^²

Firms also learn how to learn as they gain experience in strategic alliances (Anand and Khanna, 2000). They internalize this ability by setting up intra- and inter-organizational routines to increase the efficiency and effectiveness with which the knowledge is accessed and transferred, positively affecting the performance of the alliance (Inkpen, 2000; Zollo, Reuer, and Singh, 2002). Firms also learn from their repeated alliances with the same partner (Gulati, 1995), as well as from their alliance failures (Ariño and de la Torre, 1998). Repeated alliances with the same partner, however, in general lead to deterioration in the value created (Goerzen, 2007). Experience from prior alliances reduces the time needed to complete the negotiation of subsequent alliances (Ariño, Reuer, Mayer, and Jané, 2014)

Organizational routines are patterns of behavior that are followed repeatedly, but change if conditions change (Nelson and Winter, 1982; Dyer and Singh, 1998). In markets that are moderately stable, organizational routines are internal firm processes that are complex, detailed, and analytic, and they produce predictable outcomes (Eisenhardt and Martin, 2000: 1106; Cyert and March, 1963; Nelson and Winter, 1982). Because of their tacit nature, organizational routines can become a source of competitive advantage (Grant, 1996b; Dyer and Singh, 1998). For example, Dyer and Hatch (2006) found a significant performance difference between auto manufacturers that used the same supplier network. Whereas Toyota established greater knowledge-sharing routines with the common supplier network, resulting in faster learning and lower defect rates, US auto manufacturers shared much less knowledge with this same supplier network, resulting in slower learning and a higher rate of defects, ceteris paribus.

However, in high-velocity markets, where industry structure is blurred and emergent, firms learn how to adapt their organizational routines agilely into flexible modes of operating, converting them into dynamic capabilities (Teece, Pisano, and Shuen, 1997; Eisenhardt and Martin, 2000; Helfat et al., 2007). Under these market conditions, dynamic capabilities are simple, experimental, and unstable processes that produce unpredictable outcomes. Dynamic capabilities are a subset of organizational routines that include product innovation, strategic decision-making, and alliancing, and they are a further source of sustainable competitive advantage (Eisenhardt and Martin, 2000: 1111). Operating routines are another subset of organizational routines that are geared to the normal or stable operation of the firm. While operating routines are directed at the firm’s operations, dynamic capabilities are directed at the modification of operating routines (Zollo and Winter, 2002: 340).

As firms learn to learn from their alliance experience, they develop alliance capability (Kale and Singh, 2007; Kale, Dyer, and Singh, 2002; Simonin, 1997). Alliance capability consists of how a firm is able to coordinate, communicate with, and integrate or bond an individual alliance into its network of alliances (Schreiner, Kale, and Corsten, 2009). One of the key success factors for firms to build alliance capability is setting up a dedicated alliance function. The alliance function plays the role of articulating, codifying, sharing, and internalizing the organizational routines of alliance management that make up the firm’s alliance capability (Kale and Singh, 2007; Heimeriks and Duysters, 2007).

Transaction cost approach

The transaction cost approach has its origins in a classic paper on “The nature of the firm” by Coase (1937), who observed that goods and services produced by firms are the product of early stage processing and assembly of activities (Williamson, 1981: 550). The basic idea of the approach is that firms purchase production inputs based on minimizing the sum of the production and transaction costs. Transaction costs include “the costs of negotiation, drawing up contracts, managing the necessary logistics, and monitoring the accounts receivables” (Child and Faulkner, 1998: 20). Furthermore, firms will choose an organizational form that enables them to access or purchase their production inputs at the lowest transaction cost (Williamson, 1979). These forms include market exchange contracts (at one extreme), mergers or acquisitions of suppliers (at the other extreme), or a middle-ground hybrid form, such as alliances, including licensing contracts to joint ventures.

Three critical dimensions of the transaction to acquire inputs determine a firm’s preferred organizational form: frequency of transactions; uncertainty of acquiring inputs; and asset specificity involved in input production and supply (Williamson, 1975, 1979, 1985). The second and third are the two most critical dimensions (Williamson, 1991; Hennart, 1988; Dyer and Singh, 1998; Amit and Schoemaker, 1993). Market uncertainty incurs transaction costs involved with performance monitoring, while asset specificity incurs transaction costs relating to acquiring inputs at stable prices (Kogut, 1988; Hennart, 1988).

Application to alliances

Kogut (1988: 321) explains how uncertainty makes equity joint ventures (alliances) the preferred organizational form: two or more firms that are vertically contiguous in the supply chain will choose an alliance over other organizational forms when uncertainties exist over downstream demand or upstream supply. The supplier’s transaction cost involves monitoring the quality of the buyer’s market information about downstream conditions; the buyer’s cost is monitoring the quality and timely delivery of the supplier’s inputs; and both will incur price negotiation costs. The uncertainties over the general market conditions amplify the monitoring costs for both firms. Under these uncertain conditions, a market exchange contract would not be the preferred organizational form. A merger of firms, on the other hand, would also be excluded because uncertainty over market conditions demands flexibility in the organizational relationship. An alliance provides this flexibility in conditions of uncertainty and at the same time introduces a mutual hostage situation through the joint commitment of financial and real assets that aligns the firms’ incentives and reduces the associated transaction costs of monitoring and negotiating the transaction of inputs and market information.

Hennart (1988: 371) explains in a different way why an equity joint venture (alliance) would be preferred when resources with high asset specificity are involved. Such resources require large investments over an extended period of time and include tacit knowledge assets that are not readily marketable or physical assets with high operating leverage.^³ Again, take two firms in vertically contiguous positions in the supply chain. The downstream firm needs inputs from the upstream firm, but a market exchange contract for the inputs it needs does not exist; developing its own source of inputs is prohibitively expensive in terms of development costs and time; and acquiring the upstream firm for the sake of accessing its inputs introduces other transaction costs that complicate its problems, such as managing a new business and displacing the old management. For the upstream firm, acquiring the downstream firm to ensure a buyer again incurs management transaction costs; and the downstream firm’s required input volume may not match its current output. An alliance such as an equity joint venture between the two firms will avoid many of these transaction costs, however. The upstream alliance partner can produce the inputs at low or negligible marginal cost, while the downstream partner can obtain the inputs at a lower total cost, compared to producing the inputs itself. The incentives of the alliances align their cost structures.

In sum, the transaction cost approach provides insights into the economic incentives that drive firms to choose certain organizational forms over others by focusing on the level of the transaction between firms. The approach is not an alternative to MBV, RBV, or KBV. In fact all these theoretical views should be seen as complementary explanations (Kogut, 1988: 322).

Theories from the financial valuation literature

“A valuation is just an opinion” (Fernández, 2009: 8). Value should not be confused with price, which is the quantity of money agreed between a buyer and seller to exchange goods or services (Fernández, 2002). Value, on the other hand, is a subjective judgment that depends on how important the good in question is to the buyer or seller. A good may be more valuable to one buyer than another. Thus, the valuation made by a single investor on a firm’s traded stock is contingent on his or her expectations of the future and on the risk assessment of the firm (Fernández and Bilan, 2007). The traded price for that stock, however, is the consensus of valuations made by market participants who publicly manifest their opinion by buying or selling that stock.

The assessment and measurement of synergies are of fundamental importance to valuation for any form of business resource combination, such as an alliance or M&A. In finance, there are two main sets of synergies, especially in the case of mergers: operating synergies and financial synergies (Damodaran, 2005, 2012). Operating synergies include:

greater economies of scale because of larger size with the same fixed costs;
increased pricing power because of reduced competition and the ability to earn higher margins;
complementary functional strength brought by combining the best practices of firms; and
increased sales in new or existing markets because of extended sales network and complementary brand recognition.

Financial synergies from the merger of two firms include:

increased debt capacity and hence lower cost of debt capital because combining uncorrelated operating cash flows reduces their overall volatility;
increased tax benefits, especially if one of the firms has accumulated tax losses that can be used to reduce the combined firm’s tax burden;
diversification, which reduces the overall cash flow volatility of the portfolio of firms, although this synergy is usually valid only for privately held firms; and
cheaper access to project capital, especially when a capital constrained firm with good projects is acquired by another with excess cash, thus avoiding the need to go to the capital markets.

Both types of synergies, if they are realized, show up in the valuation as increased cash flows or lower discount rates (Damodaran, 2005).

While the valuation of synergies generated by M&As depends to a great extent on the assumptions upon which they are based, valuing alliances has the additional difficulty of defining the limits to firm boundaries. As alliance partners commit to share both tangible and intangible resources without legally merging as one entity, the boundary between them is blurred, making it difficult to accrue value created to one party or the other. A firm’s bargaining power against its alliance partner will determine to a great extent the portion of the total value pie created (Adegbesan and Higgins, 2011; Adegbesan, 2009).

This section provides a summary of theories and methods that could be used to value the wealth creation of strategic alliances. However, the purpose of the summary is not to provide an exhaustive account of all the theories or methods in the financial literature, but rather to highlight certain issues that could be related to valuing strategic alliances within the context of this paper. For proper treatment of the methods mentioned, please refer to the references provided.

Discounted cash flow method

The discounted cash flow (DCF) method of valuation is the financial “gold standard” for both firm and project valuation. The basic economic intuition is that the present value of a stream of cash flows (PV₀) is the sum of the discounted value of those cash flows (CF) each discounted by a rate (k), as shown in Equation (1). The term “cash flow” refers to the “future net cash in-flow” – that is, the difference between cash received and cash paid out within each time period in the future. The discount rate is usually simplified so that k₁ = k₂ = … = k and depends on the risk of receiving the cash flows: if the risk is low, then the cash flows are discounted at a lower rate; if the risk is high, then the discount rate is higher. The net present value (NPV) is the remaining economic value after making the investment (I₀) today in order to receive the cash flows, as shown in Equation (2).

\begin{array}{l} P V_{0} = \frac{C F_{1}}{1 + k_{1}} + \frac{C F_{2}}{{(1 + k_{2})}^{2}} + \frac{C F_{3}}{(1 + k_{3})} + \dots \\ = \frac{C F_{1}}{1 + k} + \frac{C F_{2}}{{(1 + k)}^{2}} + \frac{C F_{3}}{{(1 + k)}^{3}} + \dots \end{array}

(1)

N P V_{0} = P V_{0} - I_{0}

(2)

DCF is easy to apply once the cash flows and discount rate have been determined. However, the differences in the assumptions used to calculate these values can be problematic. Determining the value of cash flows requires assessing and measuring the operational and financial synergies outlined above, tasks that depend to a great degree on the assumptions made. Calculating the discount rate also requires tacit know-how on forecasting market interest rates, industry risks, and the systematic risk of the firm. Understandably, these are all non-trivial tasks.

There are many “flavors” of DCF, depending on whether one is valuing a firm or project, a firm that is stable, growing, or in decline, a high-technology or standard-technology firm, whether the firm has debt or is all equity funded, and so on. Fernández (2002: 38) proposes three basic methods of DCF:^⁴

FCF method: Free cash flows (FCF) discounted by the weighted average cost of capital (WACC) of the firm. Free cash flows are defined as the after-tax surplus cash generated by a firm’s operations (or project) regardless of any financing costs, and is a measure of that firm’s ability to make money regardless of the origins of its capital.
CFe method: Equity cash flows discounted by the required return to equity holders, k_e.
CFd method: Debt cash flows discounted by the required return to debt holders, k_d.

Fernández (2005a) gives a more comprehensive account of the three methods of DCF.

The FCF method (see Brealey, Myers, and Allen, 2008) enables the calculation of the total value of the firm or project (V_FCF). Theoretically (i.e. in the absence of market inefficiencies and financial distress costs), the total value of the firm^⁵ (or project) equals the market value of the equity (E) and the market value of debt (D) issued by the firm, as in Equation (3).

V_{F C F} = E + D = P V (F C F, W A C C)

(3)

where PV(FCF, k) is the DCF operator given by Equation (1) and

{NPV}_{F C F} = V_{F C F} - I_{0}

(3a)

where

W A C C = [E k_{e} + (1 - T) D k_{d}] / [E + D]

(3b)

and T is the firm’s marginal tax rate.

The FCF method, however, assumes that the capital structure of the firm (debt to equity ratio) remains constant, which may not always be the case unless the firm continuously rebalances its financing structure.^⁶

A useful extension of the DCF method is the adjusted present value (APV) method, which does not assume a constant capital structure. The intuition to APV is that the value of the firm or project (V_APV) is equal to the sum of the value generated by the unlevered firm or project (V_u)^⁷ and the value generated by the tax benefits due to debt,^⁸ as in Equation (4). APV is a particularly useful method for project valuation as project value should not depend on the source of financing for the project, but rather only on the cash flows it generates and the risk of the project with respect to the firm’s risk.

V_{APV} {= V}_{u} {+ Value of tax benefits due to debt = V}_{FCF}

(4)

where V_u = PV(FCF, k_u) = Unlevered value of firm or project and

{NPV}_{APV} {= V}_{APV} {-I}_{0}

(4a)

and where

k_{u} {= r}_{A} {= [Ek}_{e} {+ Dk}_{d}] / [E+D]

(4b)

where r_A is the expected return to assets,^⁹ k_u is the unlevered expected return to equity, k_e is the levered expected return to equity and

k_{e} {= R}_{f} + β {(R}_{m} {– R}_{f}) \to Capital Asset Pricing Model

(4c)

where R_f is the risk free rate, R_m is the market risk premium, and β is the systematic risk of the firm’s stock.

Application to alliances

Strategic alliances can be considered joint projects between allying firms who share a subset of their resources. Equations (3) and (4) can be combined to give equations (5a) and (5b), one for each firm in the alliance (say, Firm A and Firm B):

E_{A} {+ D}_{A} {= V}_{uA} {+ V}_{TDA}

(5a)

E_{B} {+ D}_{B} {= V}_{uB} {+ V}_{TDB}

(5b)

where V_TD is the value of the tax benefits due to debt of Firm A or Firm B.

If the risk of the alliance project is no different from the risk of the respective parent firms’ risk and no new debt is issued, then there should be no change in the market value of debt and all the benefits of the project should go to the equity holders. However, if the project risk is different from the respective partner firms’ risks, there may be a change in the market value of debt.

Research has shown that firms tend to choose alliances as the organizational form through which to undertake projects that are more risky than their normal business risk (Contractor and Lorange, 1988; Robinson, 2008). Given this, questions arise as to what the appropriate discount rate should be to value the expected cash flows from the alliance and the commensurate effect on capital structure of each allying firm.

Real options methods

One disadvantage of the discounted cash flow method is that it assumes that once the decision has been made to accept or reject a project it will not be changed later. In practice, managers do change their decisions as new information arrives that gives them a better indication of the future performance of the project. If the news is good, they may decide to go ahead or even expand the project’s scope; if it is bad, they may scale it back or even abandon it altogether. The option to choose based on future market conditions is therefore valuable. DCF methods, however, do not account for this strategic managerial flexibility. The real options methods do.

Myers (1977) first used the term real option to refer to the present value of the future assets in which a firm has the discretion to invest depending on the market conditions in later periods. He observed that

[M]ost firms are valued as going concerns, and this value reflects and expectation of continued future investment by the firm. However, the investment is discretionary. The amount invested depends on the net present values of opportunities as they arrive in the future. In unfavorable future states of nature, the firm will invest nothing.

(Myers, 1977: 148)

Some types of investment decisions are more suitable for using the real options methods (Amram and Kulatilaka, 1999: 25–27), such as:

irreversible investments – large investments in fixed assets can be built in flexible stages or delayed until more favorable times;
flexibility investments – designing manufacturing processes so that they can switch between several different products or uses;
insurance investments – when exposed to risk, paying an insurance premium provides protection in the event of a loss;
modular investments – stages of product design that can be upgraded or changed independently of other modules allows flexibility to meet future requirements;
platform investments – a technology platform, such as Apple’s iOs operating system, allows many different yet-to-be-designed products to be sold through the same platform; and
learning investments – exploration of oil or minerals allows for future investments in oil production based on initial finding.

There are three main types of real options embedded in the investments made by firms (Damodaran, 2008: 235):

option to expand an investment;
option to delay an investment; and
option to abandon an investment.

Real options methods incorporate the flexibility of strategic managerial decision-making into the valuation process using the theories of financial options (Black and Scholes, 1973).

In financial options, the buyer of a call option pays a premium for the right but not the obligation to buy the underlying asset at a preset exercise price before the option expiry date. If the price of the underlying asset is below the exercise price at the time of expiry, the call option owner will obviously not exercise the option. Thus, the option owner has downside protection from loss as well as upside opportunity for gain. In an analogous manner, the buyer of a put option buys the right but not the obligation to sell the underlying asset at a preset exercise price if the price of the underlying asset falls below the exercise price before the option expires. Regardless of the type of option, an option always has positive value as long as it has not expired. The underlying asset can be any asset, including stocks, bonds, real estate, commodities, and so on.

Table 14.1 presents the analogy between a financial American-style call option and a real option to expand a project (see Hull, 2000; Damodaran, 2008).

Table 14.1 A comparison of a financial call and real option to expand

Financial call cption	Symbol	Real option to expand

Value of underlying asset, e.g. a stock price	S	Estimated present value of project cash flows
Exercise price of call option	K	Cost of investment in expansion if option is exercised
Volatility of underlying asset e.g. standard deviation of stock price returns	σ	Standard deviation in project value, usually obtained by simulations
Time remaining to option expiry	T	Time remaining to decide before expiry of option to expand
Dividends of underlying asset	δ	Other income from the project
Risk-free rate	r	Risk-free rate taken from government Treasury bills

Application to alliances

Alliances can be understood as joint investments by the partnering firms in real options (Kogut, 1991; Chi, 2000; Folta and Miller, 2002). Although they are started as a joint project, changes in the market conditions may make it favorable for one partner to buy out the other’s share and expand the project under its own management. Alliance contracts may be designed with this buyout option included (see Reuer and Ariño, 2007). In a similar vein, in order to increase the number and value of their growth options, Reuer and Tong (2010) show that cash-rich firms will often use investments in alliances with new publicly listed technology firms as a way of discovering new technologies and market opportunities to which they would otherwise not have access. However, despite the theory of the option approach, in practice very few acquisitions involve a prior alliance between acquirer and target (Ragozzino and Moschieri, 2014).

Alliance capability or capabilities in general can also be understood as a real option. Firms that have invested in strengthening their alliance learning routines by simplifying and making them more flexible, especially in times of high market volatility, will be more able to respond and take advantage of market upswings (Kogut and Kulatilaka, 2001).

Valuation of projects using real options methodsis not without difficulties, however. Once touted as a way of unifying strategic thinking with financial option methods (Kester, 1984; Bowman and Hurry, 1993), difficulties in customizing the reality to the financial models has limited its wider use (Bowman and Moskowitz, 2001). Nevertheless, as a way of thinking about projects, real options methods continue to provide a way forward for research (see Krychowski and Quélin, 2010).

Event study method

The discounted cash flow and real options methods require information inputs that come from within the firm to evaluate expected performance of the firm or a project. However, event study methods of evaluating firm performance rely solely on publicly available sources, namely corporate security prices. The purpose of an event study is to examine the market reaction, reflected in corporate security prices, to news of firm-specific events, such as earnings announcements or mergers (Brown and Warner, 1980, 1985). The methods assume that the market is efficient and that investors react quickly in consonance with the publicly available information about the event.

According to Kothari and Warner (2005), in the period 1974–2000 the five major finance journals published 565 studies that used the event study method, and this number has continued to grow. The vast majority of these studies examine corporate stock prices. They further note that many other studies look specifically at the statistical properties of event studies. Much fewer studies, however, examine corporate bond prices, mainly due to the lack of transparency in corporate bond markets until recently (Bessembinder and Maxwell, 2008).

Table 14.2 Basic methods of calculating abnormal returns for stocks and bonds

	Stocks	Bonds

Mean adjusted	AR_it = SR_it – E(SR_it)	AR_it = (SR_it – TR_it) – E(SR_it – TR_it)
Market adjusted	AR_it = SR_it – E(R_mt)	AR_it = SR_it – MPR_it
Factor model adjusted	AR_it = SR_it – FMR_it	AR_it = SR_it – FFFMR_it

Notes: I = security; t = event time; AR_it = abnormal return of security of i at time t; SR = security return; E(.) = mean or expected return in estimation period; R_mt = return on market portfolio at time t; TR = return of treasury security of matching maturity; MPR = matching portfolio return for a portfolio of bonds with similar in credit rating and time to maturity; FMR = factor model return, where the factor model can be one of the CAPM models; FFFMR = Fama French factor model return, where Fama and French (1993) factor model is used as the benchmark.

The basic approach is similar in all event studies methods, which is to calculate the abnormal returns,^¹⁰ where “abnormal” is defined as the security return compared with some benchmark return. Three methods – summarized briefly in Table 14.2 – are used to calculate benchmark return. (For stocks, see Brown and Warner, 1980; for bonds, see Bessembinder, Kahle, Maxwell, and Xu, 2009.)

The main disadvantage of the event study method is that it is valid only for short-term security performance. Improvements have been made to the event study method for long-term horizons, but serious limitations still exist (see Kothari and Warner, 2005). A more thorough review of the event study method used in the financial and accounting literature can be found in Corrado (2011).

A review of studies of strategic alliance value creation

There are many studies in both the financial and strategy literatures that examine the value creation effects of strategic alliance formation. The vast majority use the event study methodology to measure the short-term market reaction of announcements of alliances. In fact, in my review of the empirical literature, the use of any other method was the exception rather than the rule.

Tables 14.3a and 14.3b provide summaries of a partial list of this empirical literature. As mentioned earlier, Kothari and Warner (2005) noted that more than 500 papers in the top five financial journals have employed the event study method. Some conclusions can be drawn from analyzing Tables 14.3a and 14.3b:

The most prevalent method for studying value creation from strategic alliance formation has been the event study method.
Strategic alliances in general create value for their stock holders in the short term.
There are studies that show strong negative effects on value creation, although they are in the minority. These studies are of international joint ventures (Reuer, Park, and Zollo, 2002; Chung, Koford, and Lee, 1993)
No event studies examine the effect of strategic alliance formation on corporate bonds.

Table 14.3a Selected key studies on the value creation of strategic alliances

Researchers	Sample period	Sample	Event window	* = AR (day 0)/** = CAR (over event window)

McConnell and Nantell (1985)	1972–1979	136 domestic US joint ventures (in various industries: real estate development, nuclear power, coal mining, petrochemical, satellite communication, others)	2 days (–1/0)	0.73% all joint ventures 1.10% smaller partner *0.63% larger partner Dollar value gains smaller/larger partner were $4.5m/$6.6m
Chan, Kensinger, Keown, and Martin (1997)	1983–1992	345 alliances: 114 all public partners 231 only one public partner (involving 460 firms, with 394 in hi-tech industries and 66 in low-tech industries)	26 days (–20/+5)	0.64% all alliances 2.22% smaller partner *0.19% larger partner Dollar value gains: smaller/larger partner were $8.9m/$8.1m
Das, Sen, and Sengupta (1998)	1987–1991	119 US–Japanese alliances: 49 technology alliances 70 marketing alliances	7 days (–3/+3)	0.20% all alliances 1.6% technology alliances **–0.8% marketing alliances
Anand and Khanna (2000)	1990–1993	1,576 alliances: 870 joint ventures 1,106 licensing agreements	12 days (–10/+1)	0.67%/1.82% JVs 1.42%/**3.06% Licensing Dollar value gains: JV/licensing deals were $44.1m/$20.4m
Kale, Dyer, and Singh (2002) Kale, Dyer, and Singh (2001)	1993–1997	1,572 alliances reported by 78 companies with more than $500 million in 1997 in whose industries alliances are generally considered an important part of firm strategy (e.g. computers, telecoms, pharmaceuticals, chemicals, electronics, and services)	14 days (–10/+3)	0.84% all alliances 1.35% with alliance function *0.18% without alliance function Dollar value gains: all/with alliance function/without alliance function were $58.3m/$75.1m/$20.2m
Reuer, Park, and Zollo (2002)	1995–1997	1,318 international joint ventures	3 days (–1/+1)	**–1.83% all joint ventures

Table 14.3b Other studies on the value creation of strategic alliances

• Koh and Venkatraman (1991) – study joint venture announcements and find they are in general value creating

• Chung, Koford, and Lee (1993) – study international joint ventures and find a strong negative effect on value creation

• Mohanram and Nanda (1996) – find value creation at the parent-level but not at the firm-level

• Johnson and Houston (2000) – study the motives of joint ventures and find asymmetries in partners’ value creation

• Gupta and Misra (2000) – study the effect of experience in international joint ventures and find it value creating for partners

• Brooke and Oliver (2005) – study the source of gains for strategic alliances

• Mantecon and Chatfield (2007) – compare value creation in short-term market reaction with assets sales of terminating joint ventures

• Kumar (2007; 2010) – find asymmetrical gains for the shareholders of parents of joint venture partners

• Bösecke and Pfaffenberger (2009) – study value creation in small European utilities and find significantly positive returns

• Keasler and Denning (2009) – large sample study confirms that strategic alliances on average create value

• Gulati, Lavie, and Singh (2009) – study the effect of partner-specific experience on repeated alliances and find it significant

• Sánchez-Lorda and García-Canal (2012) – study how equity investors value prior experience in alliances and acquisitions

• Amici et al. (2013) – study US and European banking sector alliances and find they create value for non-bank partners

Conclusion

In this chapter, I reviewed relevant theories and methods in the strategy and financial literature and applied them to develop an understanding of strategic alliances from organizational learning and valuation perspectives. I began by answering preliminary questions about strategic alliances to serve as an introduction for readers who may be unfamiliar with the strategic alliance literature. I then reviewed the strategy literature theories of the firm from a market-based view, resource-based view, knowledge-based view, and transaction cost approach, and applied them to further readers’ understanding of strategic alliances. From the financial valuation literature, I reviewed the discounted cash flow, real options, and event study methods and explored how these could be applied to understanding strategic alliances. Finally, I summarized the results of many prior studies on the value creation of strategic alliances.

Notes

1 This may be due to the sample of executives surveyed. In my own research, conducted using SDC Platinum data, there was a significant drop in the number of alliances from 2008 onwards.

2 While transfer of tacit knowledge through an alliance is more efficient than market exchange contracts, transfer of tacit knowledge within a (multinational) firm itself is still more efficient than across an alliance (Almeida, Song, and Grant, 2002).

3 Operating leverage can be thought of as the ratio of fixed costs to variable costs. Firms with high operating leverage make large upfront investments and need large sales volumes to break even. Each dollar of sales contains a high percentage of profit because the variable or marginal costs of production are relatively small or almost negligible. For example, an airline operator would have high operating leverage compared with a supermarket chain.

4 There are, of course, many more. See, for example, Copeland, Koller, and Murrin (2000) and Brealey, Myers, and Allen (2008).

5 Another name for the value of the firm is enterprise value.

6 This assumption is required to ensure no change in k_u or k_d such that WACC also remains constant.

7 V_u means the value of the firm or project as if it were entirely funded by equity, i.e. no debt or unlevered.

8 The equation states “value” of tax benefits due to debt, not “present value” as it does in Brealey, Myers, and Allen (2008: 546). This point is argued in Fernández (2004, 2005b) and Fieten et al. (2005).

9 This is also called the opportunity cost of capital and is the “simplest” formula to find k_u, the unlevered expected return to equity (Brealey, Myers, and Allen, 2008: 543). Note that, in this formula, k_e and k_d are observable values, where k_e is the levered return to equity, the return to equity when the firm also has debt financing.

10 The term abnormal return is used synonymously with excess returns or excess residuals.

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Table of Contents for 14 Strategic alliances in the organizational and financial literatures: a review

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14Strategic Alliances in the Organizational and Financial Literatures

Introduction

Preliminary questions and answers on strategic alliances

What is a strategic alliance?

Where? How many? How significant?

Why do firms form alliances?

Do alliances create value? How is it shared?

Do alliances fail? How often? Why are they unstable?

Which one? Alliance or acquisition?

A review of the strategy and financial valuation literatures

Theories from the strategy literature

Market-based view

Application to alliances

Resource-based view

Application to alliances

Knowledge-based view: organizational learning and capabilities

Application to alliances

Transaction cost approach

Application to alliances

Theories from the financial valuation literature

Discounted cash flow method

Application to alliances

Real options methods

Application to alliances

Event study method

A review of studies of strategic alliance value creation

Conclusion

Notes

References

Table of Contents for
14 Strategic alliances in the organizational and financial literatures: a review

14
Strategic Alliances in the Organizational and Financial Literatures