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Keywords:

  • exploration alliances;
  • exploitation alliances;
  • small firms;
  • large firms;
  • alliance strategy

Abstract

  1. Top of page
  2. Abstract
  3. INTRODUCTION
  4. THEORY AND HYPOTHESES
  5. METHOD
  6. RESULTS
  7. DISCUSSION AND CONCLUSION
  8. ACKNOWLEDGEMENTS
  9. REFERENCES

How do small firms manage their alliance strategies with large firms? This study compares the relative impacts of exploration and exploitation alliances with large firms on small firms' valuation. Integrating the literatures on the exploration/exploitation paradigm and alliance governance, we argue that exploitation alliances with large firms will on average generate higher values for small firms than exploration alliances with large firms due to a heightened risk of appropriation in exploration alliances. However, if small firms can manage their alliances with large firms via proper alliance governance, they will increase their valuations from exploration alliances with large firms. Analyses of the U.S. biopharmaceutical industry from 1984 to 2006 largely support our hypotheses. Copyright © 2013 John Wiley & Sons, Ltd.


INTRODUCTION

  1. Top of page
  2. Abstract
  3. INTRODUCTION
  4. THEORY AND HYPOTHESES
  5. METHOD
  6. RESULTS
  7. DISCUSSION AND CONCLUSION
  8. ACKNOWLEDGEMENTS
  9. REFERENCES

How can small firms benefit from strategic alliances with large established firms? Prior research on strategic alliances has primarily taken the perspective of large firms while paying scant attention to alliances in entrepreneurial settings (Katila, Rosenberger, and Eisenhardt, 2008; Rothaermel, 2001). There is now a growing research interest in small firms engaging in strategic alliances with large partners. On the one hand, empirical evidence indicates that alliances with large firms are vital to the survival and growth of small firms, as these alliances can offer small firms not only the legitimacy and reputation necessary for external stakeholders to interact with them, but also complementary resources for commercializing their technologies (Stuart, Hoang, and Hybel, 1999). On the other hand, while alliances between small and large firms can create value, in some circumstances small firms may suffer from alliances with large firms because the latter tend to outlearn or exploit the small firms and take away the lion's share of the value created in alliances (Alvarez and Barney, 2001). Small firms therefore often face the challenge of configuring their alliance portfolio with large firms: which alliance strategies will benefit small firms, and under what circumstances?

We address these questions by examining the relative performance implications of exploration versus exploitation alliances with large firms for small firms and further investigate the contingencies of their relative impacts. Entering exploration alliances with large firms reflects a small firm's desire to discover new opportunities with the aim of building new competencies and better adapting to the environment (Koza and Lewin, 1998). In contrast, exploitation alliances with large firms leverage a small firm's existing capabilities and combine competencies across organizational boundaries (Rothaermel and Deeds, 2004). Although both exploitation and exploration alliances may create value, they compete for limited resources within each partner firm. This is particularly the case for small firms that often lack sufficient resources to afford both alliance strategies (Lin, Yang, and Demirkan, 2007).

Following the exploration/exploitation paradigm (March, 1991), we argue that although exploration alliances enable small firms to generate larger performance variations by experiencing substantial successes as well as failures (He and Wong, 2004; McGrath, 2001), these variance-increasing activities pose significant challenges to small firms. Apart from the highly uncertain outcome of exploratory activities, small firms are often at a high risk of appropriation by large firms. The potential appropriation concerns originate from the difficulties of governing exploratory alliances as manifested in contract design, monitoring, and enforcement (Teece, 1992). It is accordingly difficult for small firms to manage asymmetric alliances with large firms, which often have much stronger bargaining power. In contrast, exploitation alliances allow small firms to engage in well-defined collaborations with large firms and generate more predictable performance. We therefore propose that, in general, exploitation alliances with large firms will bring greater benefits to small firms than exploration alliances with large firms.

We further extend this line of logic by investigating the critical contingencies from an alliance governance perspective (Poppo and Zenger, 2002). While in general small firms are better off forming mean-seeking exploitation alliances than variance-seeking exploration alliances with large firms (McGrath, 2001), we contend that small firms can utilize proper alliance governance in terms of formal or relational structure to mitigate the risks of exploration alliances. As a result, they may obtain greater value from exploration alliances with large firms.

We tested our hypotheses using alliances formed by small U.S. biotechnology firms with large pharmaceutical or chemical firms from 1984 to 2006. We chose this industry because it presents an ideal context for investigating the tension between exploration and exploitation, as well as that between small and large firms in alliances (Rothaermel and Deeds, 2004).

THEORY AND HYPOTHESES

  1. Top of page
  2. Abstract
  3. INTRODUCTION
  4. THEORY AND HYPOTHESES
  5. METHOD
  6. RESULTS
  7. DISCUSSION AND CONCLUSION
  8. ACKNOWLEDGEMENTS
  9. REFERENCES

Strategic alliances are cooperative agreements between firms involving exchange, sharing, or codevelopment of products, technologies, or services (Gulati, 1998: 293). A firm's strategic alliances can be classified as exploration or exploitation alliances according to its motivation either to explore new opportunities or to exploit existing opportunities (Koza and Lewin, 1998). Exploration alliances are formed to seek and generate new knowledge and technologies, while exploitation alliances are formed to leverage complementary assets between alliance partners (Rothaermel and Deeds, 2004). Both exploration and exploitation alliances with large firms may improve the performance of small firms.

First, exploration alliances with large firms provide opportunities for a small firm to access tacit and often diverse knowledge from large firms. The knowledge required for scientific discovery is both complex and multifaceted, demanding both a broad and deep knowledge base that greatly exceeds the capacity of a single firm. Small and large firms often possess complementary innovation-enhancing resources since small firms excel at product innovations while large firms are good at process innovations (Abernathy and Utterback, 1988; King, Covin, and Hegarty, 2003). A small firm may therefore benefit from the high returns of exploration alliances with large firms by acquiring and learning advanced technological know-how from the latter. For example, Shan, Walker, and Kogut (1994) found that cooperative relationships with large established firms lead to greater innovation output for small biopharmaceutical firms. Second, exploitation alliances with large firms provide a small firm with efficient access to complementary resources in large firms such as manufacturing, marketing, financial, and other resources for commercializing its technologies (Rothaermel, 2001). Third, alliances with large firms may provide a small firm with external legitimacy that buffers it from the liabilities of newness or smallness. A small firm generally lacks the external legitimacy associated with stable exchange relationships with key environmental constituencies and does not have track records in providing products or services. Alliances with large firms for either exploration or exploitation may be particularly desirable for a small firm seeking to gain legitimacy and reduce uncertainty regarding its quality (Stuart et al., 1999).

However, small firms often face high risks in allying with large firms. Since these asymmetric alliances are more critical to small firms than to large firms (Doz, 1988), this dependence will increase small firms' vulnerability in contract design, interorganizational learning, and outcome sharing due to their weak bargaining power. For example, Alvarez and Barney's (2001) study of 128 alliances between small and large firms found that the majority of small firms are unfairly treated and that their performance and even long-term survival are at risk.

Relative influences of exploration vs. exploitation alliances

We argue that both exploration and exploitation alliances with large firms are beneficial for small firms. However, due to bounded rationality and resource constraints, small firms face tremendous pressure to balance between exploration and exploitation in their alliance formation decisions. We posit that, in general, small firms will derive greater benefits from exploitation alliances with large firms because these alliances ensure well-defined returns for small firms by combining the complementary resources between small and large firms. Although the performance potential of exploration alliances with large firms may exceed that of exploitation alliances, small firms often face heightened risks of appropriation in exploration alliances.

First, small firms have higher risks of being out-learned by large firms in exploration alliances than in exploitation alliances. Large firms often form exploration alliances with small firms with the purpose of accessing the latter's cutting-edge technological knowledge. This is particularly the case in the biopharmaceutical industry where the technology paradigm for drug development is shifting from chemistry-based to biotech-based technologies, which are often the competencies of many small biotech firms (Pisano, 1990). Since the success of exploration alliances depends on each firm's willingness to integrate and share respective knowledge bases (Ireland, Hitt, and Webb, 2005), this integration process will open up the door for large firms to access the tacit knowledge of small firms. The knowledge resources of small firms are also more easily appropriated than the resources of large firms because small firms often have a limited product development scope (Deeds and Hill, 1998), and many resources from large firms tend to be physical in nature (Katila et al., 2008). In contrast, the concerns of proprietary knowledge spillover to large firms tend to be less in exploitation alliances since less integration of partners' tacit knowledge is involved in exploitation than in exploration alliances (Ireland et al., 2005).

Second, the value created by exploration alliances between small and large firms is subject to appropriation by large firms. Since small firms often challenge large firms' existing products or business, they simultaneously compete and collaborate in alliances. Value appropriation is a critical issue for alliances composed of competing firms (Dussauge, Garrette, and Mitchell, 2000), particularly when the involved firms have asymmetric bargaining powers. Large firms are likely to wield their influence by capturing larger shares of the value (Alvarez and Barney, 2001). This is especially the case in exploration alliances because future contingencies are difficult to anticipate and firms are constantly subject to value allocation renegotiation (Rothaermel and Deeds, 2004). For instance, exploration alliances often entail high uncertainty and cause friction between partners over alliance outcomes such as intellectual property rights. Large firms are more likely to gain control over newly-developed technologies in alliances since they typically possess greater bargaining power than small firms.

In contrast, small firms may be able to generate greater values from exploitation alliances with large firms. Exploitation alliances are formed to capitalize on complementary assets between partner firms. Going it alone is usually not a viable option for a small firm attempting to commercialize its technologies because the process is costly, time-consuming, and risky. Instead, small firms may benefit greatly from the value created by allying with large firms via economies of specialization (Teece, 1992). In addition, the likelihood of proprietary knowledge outflow toward large firms tends to be minimal in exploitation alliances since this type of alliance involves less integration of partners' tacit knowledge (Ireland et al., 2005). Exploitation alliances also entail lower uncertainty; it is easier for partner firms to delineate obligations and benefits because the technology for commercialization is often both well-developed and protected (Rothaermel and Deeds, 2004). The value appropriation risks for small firms are much lower in exploitation alliances than in exploration alliances with large firms.

We argue that although exploration alliances with large firms may create high returns, small firms also face high risks of appropriation. Conversely, exploitation alliances with large firms allow small firms to generate more predicable returns from the synergistic combination of their complementary resources (Hoang and Rothaermel, 2010; McGrath, 2001). Small firms are therefore generally better off forming exploitation rather than exploration alliances with large firms.

Hypothesis 1: A small firm's exploitation alliances with large firms have a greater positive effect on its market valuation than its exploration alliances with large firms.

Moderating roles of alliance governance

Although small firms may benefit more from mean-seeking exploitation alliances than variance-seeking exploration alliances with large firms in general, we contend that small firms can mitigate the high risks of appropriation in exploration alliances with large firms by resorting to governance mechanisms such as formal and relational governance (Gulati and Nickerson, 2008; Hoetker and Mellewigt, 2009). Formal governance refers to the legal delineation of rights and obligations between alliance partners within an exchange agreement, while relational governance entails the informal enforcement of obligations, promises, and expectations following the values and agreed-on processes in social relationships (Poppo and Zenger, 2002). We argue that increased protection from either formal or relational governance is likely to reduce the appropriation risks, making it more beneficial for small firms to engage in exploration alliances with large firms.

Formal governance

Equity structure imposes a formal governance mechanism in that the rights and obligations of participating partners can be specified via ownership control in alliances. Equity alliances refer to structures that involve equity ownership such as equity transfers or the creation of a new entity, while nonequity alliances refer to contractual agreements that do not involve any equity ownership changes. Equity alliances are considered to present a higher level of hierarchical control than nonequity alliances because equity ownership helps align partners' interests and deter opportunistic behaviors (Gulati and Singh, 1998).

We argue that an equity alliance will generally be a better governance mode for small firms' exploration alliances with large firms. First, an equity governance structure will foster close knowledge integration so that all firms could work closely in order to generate new knowledge. Unlike a contractual agreement that asks for detailed specification of activities to be undertaken at specific times, an equity governance structure gives participating firms significant leeway in following where the knowledge and discovery process leads. This structure accordingly provides greater flexibility for exploration activities than contractual agreements do (Ireland et al., 2005). Second, an equity structure will help protect small firms' benefits via hierarchical control in exploration alliances. As noted earlier, exploration alliances often carry high levels of uncertainty associated with the difficulty of specifying and enforcing contractual agreements (Rothaermel and Deeds, 2004). This uncertainly increases the risk that alliance outcomes such as intellectual properties will be appropriated by larger partners due to the relatively weak bargaining power of the smaller firm. The equity investment made by large firms in alliances can serve as a hostage for small firms to leverage when protecting their interests (Klein, 1980). The hierarchical governance structure also improves control by aligning partner firms' incentives and better restricting their appropriation potential. Equity arrangements are therefore more desirable than nonequity arrangements for a small firm in its exploration alliances with large firms.

In a similar vein, we argue that a nonequity governance structure is desirable for small firms when forming exploitation alliances with large firms. Exploitation alliances generally involve lower levels of coordination and uncertainty than exploration alliances (Ireland et al., 2005; Rothaermel, 2001). This lower level of coordination is better matched with a loose governance structure such as nonequity alliances. First, firms are able to clearly define each other's responsibilities in exploitation alliances via a nonequity governance structure. For instance, a small firm can form a marketing alliance with a large firm where the division of labor can be clearly spelled out in contractual terms. Second, the risk of a small firm's loss of its core technological knowledge to its large partners is lower due to the packaged knowledge utilized in exploitation alliances (Mowery, Oxley, and Silverman, 1996), and the need for greater hierarchical governance is therefore reduced. Third, the profit sharing from exploitation alliances with large firms is relatively certain and can be well specified when firms enter into alliance relationships, reducing the risks of appropriation by large firms. We therefore contend that a nonequity governance structure is more desirable than an equity structure for small firms forming exploitation alliances with large firms.

Hypothesis 2a: A small firm's equity-based exploration alliances with large firms have a greater positive effect on its market valuation than its nonequity-based exploration alliances with large firms.

Hypothesis 2b: A small firm's nonequity-based exploitation alliances with large firms have a greater positive effect on its market valuation than its equity-based exploitation alliances with large firms.

Relational governance

An informal governance mechanism created through trust and shared value may serve as an alternative interorganizational governance structure in alliance relationships (Poppo and Zenger, 2002). Firms are embedded within interfirm relationships where norms and common values are developed in order to fill in the voids left by formal contracts. Westphal and Zajac (2001) argued that firms not only seek legal compliance in interfirm relationships, but also abide by institutional norms and values. We contend that relational governance can serve as alternative means of mitigating the appropriation risks (Poppo and Zenger, 2002), making it more desirable for small firms pursuing exploration alliances with large firms.

First, strong relational governance is particularly effective for reducing the risks of the learning race in exploration alliances. Trust relationships developed via closed networks and repeated interactions direct partnering firms' interests for the long-term health of interfirm relationships and deter short-time opportunistic behaviors in existing alliances (Deeds and Hill, 1998). This is important in knowledge-intensive activities such as exploration alliances where the uncertainty regarding future outcomes is high (Hoetker and Mellewigt, 2009). The knowledge integration process is likely to be smooth when both parties have trust toward each other. Small firms will therefore have fewer concerns of being out-learned by large firms in exploration alliances because trust serves as a self-monitoring mechanism, and firms tend to obey the rules of collaboration (Deeds and Hill, 1998). The effect of relational governance on knowledge protection will be much less in exploitation alliances where the demand for knowledge integration is reduced.

Second, strong relational governance will also protect small firms against potential appropriation by large firms, particularly in exploration alliances with greater ambiguities over property rights and profit sharing. Firms are likely to use goodwill rather than bargaining power to resolve conflicts over newly-generated intellectual properties in exploration alliances. Carson, Madhok, and Wu (2006) also argued that relational governance may increase the alliance's overall value creation by increasing efficiency, enhancing flexibility, and lowering set-up costs vis-à-vis formal governance.

We thus argue that the beneficial effect of relational governance will be more prominent for exploration than exploitation alliances with large firms. This is not only because trust and social norms are critical for uncertain projects involving an intensive exchange of tacit knowledge and a higher level of collaboration, but also because rights and obligations can be easily delineated in more certain exploitation alliances. Small firms may better realize the potential of exploration alliances with large firms under the protection of relational governance.

Hypothesis 3: A small firm's exploration alliances with large firms have a greater positive effect on its market valuation than its exploitation alliances with large firms when strong relational governance exists between them.

METHOD

  1. Top of page
  2. Abstract
  3. INTRODUCTION
  4. THEORY AND HYPOTHESES
  5. METHOD
  6. RESULTS
  7. DISCUSSION AND CONCLUSION
  8. ACKNOWLEDGEMENTS
  9. REFERENCES

The research context for this study is the U.S. biopharmaceutical industry. This industry has witnessed numerous alliances between small biotechnology firms and large partners such as pharmaceutical or chemical companies over the past two decades (Shan et al., 1994; Stuart et al., 1999). While the competence-destroying technologies from the biotechnology sector pose significant challenges for large pharmaceutical and chemical firms, small biotechnology firms often ally with large firms in order to access complementary resources in manufacturing, distributing, and marketing. The biopharmaceutical industry therefore provides an ideal setting for our study. We retrieved data from two premier sources of business information in this industry: BioScan and Recombinant Capital (RECAP). We identified all small biotechnology firms founded between 1984 and 1992 that generated revenues lower than $100 million as well as their alliance histories with large partners (e.g., Pfizer) with annual revenues greater than $1 billion during the observation period. Large biotech firms such as Amgen and Genentech were therefore excluded from our sample. We collected patent information for our sample firms from the United States Patent and Trademark Office (USPTO) and compiled an unbalanced panel data of 753 firm-year observations for small biotech firms from 1984 to 2006.

Dependent variable

Firm valuation is the market value of the company's equity. We operationalized this as the product of its shares outstanding and the stock price per share. This is a more accurate measurement of firm performance for small firms than other commonly used financial measurements (e.g., P/E ratio) because biotech start-ups are typically not profitable. In practice this is of great interest to entrepreneurs because their economic returns hinge on how the markets value their firms. We collected sample firms' valuation data primarily from the Center for Research in Security Prices (CRSP) and RECAP. We derived the market value as the average of 12 end-of-month daily values for corresponding years (Lavie, 2007).

Independent variables

Each alliance was classified as either exploitation or exploration according to the detailed alliance information acquired from either BioScan or RECAP. Following Rothaermel and Deeds (2004), we coded alliances that focused on upstream activities of the value chain such as drug discovery and development as exploration alliances. Downstream activities of the value chain such as manufacturing and marketing alliances were coded as exploitation alliances (Rothaermel, 2001). In addition, since firms may have different intentions, our coding used the perspective of the focal firm (i.e., small firms in our study) (Lavie and Rosenkopf, 2006). Because the termination information for alliances is not available for many alliances, we constructed an alliance portfolio to include all alliances announced between year t and t − 4 for a firm at year t using a five-year moving window (Yang, Lin, and Peng, 2011). We then counted the number of exploitation or exploration alliances with large partners within the alliance portfolio as our measure.

We measured the number of equity- or nonequity-based exploration alliances as well as the number of equity- or nonequity-based exploitation alliances. We used the absolute number of these four types of alliances in the analyses in order to assess which alliance type was likely to generate greater valuation for small firms. A ratio variable was not used, because we believe that a high degree of both exploration and exploitation alliances can coexist within a firm's alliance portfolio. The relationship between exploration and exploitation was therefore treated as orthogonal rather than continual in this study (Gupta, Smith, and Shalley, 2006). In order to correct for the potential bias in size effect, we controlled for firm size and alliance experience in our analyses.

It has been widely acknowledged in the literature that firms are likely to develop relational governance within a dense network (Coleman, 1988). A dense network will foster the cultivation of trust, common norms, and values that are likely to be shared by network members. We therefore used the ego network density as the proxy for relational governance. Specifically, we constructed yearly alliance matrices within the biopharmaceutical industry from 1984 to 2006 using a five-year moving window. Altogether we identified 65,864 pairs of alliances from various data sources. Alliances with more than two firms were entered into the matrices as separate dyadic combinations of all firms within the alliance. Ego network density was calculated as the percentage of existing alliance ties within an ego's alliance portfolio divided by all possible ties (Phelps, 2010).

Control variables

We controlled a series of variables that are influential in affecting a firm's market valuation. We measured biotech population density as the counted number of total biotech firms in each year, a proxy of industry competition. From investors' perspective the existence of a large number of competing firms provides the option to leverage across different firms with similar technologies. Firm age was measured as the number of years from the date of incorporation; firm size was measured as the natural log of the number of employees; and alliance experience was measured as the count of all prior alliances formed by the focal firm including alliances with both large and other partners. Technological dynamism was controlled for in order to capture the exogenous velocity surrounding a firm's technological endeavors via a multistep approach as follows. We began with the population of all biopharmaceutical patents. For each three-digit patent class we regressed the number of patents over the past five years based on calendar year. We then divided the standard error of the regression coefficient by the average number of patents filed within the specific class during the past five years. This measurement is similarly constructed as environmental dynamism and has been adopted in previous research (Keats and Hitt, 1988).

A small firm's technological capability may have a considerable impact on its market valuation. We measured this variable as the number of its academic journal publications (Rothaermel and Hess, 2007). This information was retrieved from the Science Citation Index database. We also experimented with an alternative measurement of technological capability by using the total number of citation-weighted patents the focal firm filed and owned between years t − 4 and t. This alternative measurement generates consistent findings with our reported one using the publication-based measurement.

Small firms' financing capability also greatly influences their market valuations. We measured this variable as the U.S. dollar amount of accumulative equity investment in millions. The rationale is that a small biotech firm's ability to attract equity investments reflects its strong financing capability and accordingly influences its bargaining power over large firms. We obtained this information from RECAP database, which has collected financial history for a large number of biotech firms from their inception (Zheng, Liu, and George, 2010).

Analysis

We tested our hypotheses using the time-series cross-sectional feasible generalized least squares (FGLS) regression model for the unbalanced panel data we complied. This model is appropriate because it addresses potential heteroskedasticity and autocorrelation, which often exist in ordinary least squares regression (Wooldridge, 2002). A potential selection bias may exist in our analysis because small firms' valuation may be affected by unobserved factors that also influence small firms' intentions of forming alliances with large firms, causing the endogeneity problem. We therefore performed a conventional Heckman two-stage approach addressing this problem. In the first stage we regressed the tendency of forming alliances with large firms on the alliance density within the interfirm network, small firms' financial resources, technological resources, firm size, and firm age. We assume that small firms with fewer resources are more pressured to form alliances with large firms in order to access external resources (Eisenhardt and Schoonhoven, 1996). We generated the inverse Mills ratio (IMR) from the first-stage estimation and controlled it in the second stage.

RESULTS

  1. Top of page
  2. Abstract
  3. INTRODUCTION
  4. THEORY AND HYPOTHESES
  5. METHOD
  6. RESULTS
  7. DISCUSSION AND CONCLUSION
  8. ACKNOWLEDGEMENTS
  9. REFERENCES

Table 1 presents a summary of the descriptive statistics. Following Aiken and West (1991), we mean-centered the predictor variables before generating interaction terms. A variance inflation factors (VIF) test found that the average VIF value was 2.13, far below the critical value of 10.

Table 1. Correlations
 MeanS.D.123456789101112131415
  1. Note: N = 753. *Refers to alliances with large partners. Correlations above | 0.07| are significant at the 0.05 level.

1. Firm valuation301.69365.48               
2. Biotech population density937.79216.250.32              
3. Firm age12.034.790.250.77             
4. Firm size5.251.560.570.490.44            
5. Alliance experience12.7514.200.450.440.320.52           
6. Technological dynamism0.080.060.07−0.08−0.15−0.02−0.06          
7. Inverse Mills ratio0.960.66−0.170.260.50−0.21−0.07−0.35         
8. Technological capability2.750.82−0.050.060.070.020.08−0.04−0.05        
9. Financing capability341.67466.540.380.080.030.200.090.18−0.22−0.20       
10. Exploration alliances*0.761.400.09−0.25−0.35−0.050.130.20−0.300.010.06      
11. Exploitation alliances*0.441.020.27−0.09−0.130.100.240.12−0.20−0.080.110.22     
12. Relational governance22.9922.30−0.040.010.020.01−0.090.09−0.08−0.09−0.020.05−0.04    

13. Number of equity-based

exploration alliances

0.260.690.13−0.18−0.26−0.010.070.16−0.280.020.170.710.110.05   

14. Number of nonequity-

based exploration alliances

0.501.030.03−0.22−0.30−0.060.130.16−0.21−0.01−0.030.880.230.040.30  

15. Number of equity-based

exploitation alliances

0.050.22−0.04−0.16−0.12−0.09−0.030.02−0.060.000.010.070.27−0.040.010.09 
16.

Number of nonequity-based

exploitation alliances

0.400.990.29−0.06−0.110.130.250.12−0.19−0.080.120.210.98−0.030.110.210.06

Table 2 displays the FGLS estimations. Model 1 presents the baseline model with control variables only. Larger firms are perceived more positively by the market, and firms with more alliance experience and financing capability receive higher market valuations. In Model 2 we entered the predictor variables such as exploration and exploitation alliances. We found that exploitation alliances are positively related to firm valuation at a significant level (b  =  58.77, p  <  0.001), while exploration alliances are positively related to firm valuation at a marginally significant level (b = 15.47, p < 0.10). A t-test suggests that there is a significant difference between the coefficients (p < 0.01), supporting Hypothesis 1 that a small firm's exploitation alliances with large firms have a greater positive effect on its market valuation than its exploration alliances with large firms.

Table 2. FGLS estimates of small firms' alliance strategy with large firms
VariablesModel 1Model 2Model 3Model 4
  1. Note: Nonstandardized coefficients are reported with z-values in parentheses. Two-tailed test.

  2. p < 0.10; *p < 0.05; **p < 0.01; ***p < 0.001

    .

Biotech population density0.050.110.100.12
 (0.61)(1.44)(1.32)(1.53)
Firm age−2.160.420.510.20
 (−0.53)(0.10)(0.13)(0.05)
Firm size96.13***95.01***94.34***95.33***
 (10.33)(10.47)(10.44)(10.51)
Alliance experience5.35***3.44***3.47***3.38***
 (6.20)(3.81)(3.85)(3.73)
Technological dynamism279.60139.98141.63142.71
 (1.43)(0.72)(0.74)(0.74)
Inverse Mills ratio7.8510.6413.3310.87
 (0.34)(0.48)(0.60)(0.49)
Technological capability−8.21−4.67−5.58−4.30
 (−0.64)(−0.37)(−0.45)(−0.34)
Financing capability0.21***0.20***0.19***0.20***
 (9.15)(8.91)(8.46)(8.92)
Relational governance −0.48−0.52−0.37
  (−1.07)(−1.15)(−0.69)
Exploration alliances 15.47 12.77
  (1.95) (1.05)
Exploitation alliances 58.77*** 75.06***
  (5.70) (4.14)
Number of equity-based exploration alliances  43.80** 
   (2.80) 
Number of nonequity-based exploration alliances  0.42 
   (0.04) 
Number of equity-based exploitation alliances  −13.78 
   (−0.31) 
Number of nonequity-based exploitation alliances  65.21*** 
   (6.12) 
Exploration alliances × relational governance   0.12
    (0.29)
Exploitation alliances × relational governance   −0.83
    (−1.09)
N753753753753
Log likelihood−5,297−5,278−5,274−5,277

In Model 3 we entered the variables of four different combinations between formal governance and exploration or exploitation alliances with large firms to test Hypotheses 2a and b. To avoid the multicollinearity arising from high correlations among exploration alliances, exploitation alliances, and the four different combinations, we excluded the variables of exploration alliances and exploitation alliances in Model 3. The findings show that the coefficient for the number of equity-based exploration alliances is positive and significant (b = 43.80, p < 0.01), while the coefficient for number of nonequity-based exploration alliances is not significant (b = 0.42, p > 0.10). A t-test shows that there is a significant difference between the two coefficients (p < 0.05). Therefore, Hypothesis 2a is supported, indicating that a small firm benefits more from its equity-based exploration alliances than its nonequity-based exploration alliances with large firms. Model 3 also shows that the coefficient for number of nonequity-based exploitation alliances is positive and significant (b = 65.21, p < 0.001), while that for number of equity-based exploitation alliances is not significant (b = −13.78, p > 0.10). A t-test shows that there is a marginally significant difference between the two coefficients (p < 0.10). This suggests that nonequity alliance governance is more desirable than equity governance for exploitation alliances with large firms, supporting Hypothesis 2b.

In Model 4 we entered the interaction between exploration alliances and relational governance, as well as that between exploitation alliances and relational governance. The results show that the former is positively related to firm valuation but at a nonsignificant level (b = 0.12, p > 0.10), while the latter is negative and nonsignificant (b = −0.83, p > 0.10). A t-test shows that there is no significant difference between the two coefficients (p > 0.10), suggesting that relational governance does not make much difference between small firms' exploration alliances and exploitation alliances with large firms. Therefore, Hypothesis 3 is not supported.

DISCUSSION AND CONCLUSION

  1. Top of page
  2. Abstract
  3. INTRODUCTION
  4. THEORY AND HYPOTHESES
  5. METHOD
  6. RESULTS
  7. DISCUSSION AND CONCLUSION
  8. ACKNOWLEDGEMENTS
  9. REFERENCES

Both researchers and practitioners have been intrigued by the question of how small firms should develop their alliance strategies with large firms. Which alliance strategy will better enhance small firms' market valuations and under what circumstances? This study addresses these questions by comparing the relative influences of exploration and exploitation alliances with large firms on the market valuations of small firms.

Our findings suggest that alliance strategies with large firms in terms of exploration or exploitation exert differential impacts on small firms' valuations. Due to the high risks of appropriation in exploration alliances with large firms and the general incapability of small firms to govern these complex and uncertain activities, small firms reap less returns from exploration than exploitation alliances with large firms. This is analogous to the general advice given to novice investors to invest in low-variance stocks rather than in high-volatility ones. Our findings further suggest that, if small firms are equipped with proper alliance governance, they are able to capture greater benefits from their alliances with large firms. We found that small firms are better off governing exploration alliances with an equity-based structure, while governing exploitation alliances with a nonequity-based structure. Our analyses suggest that small firms reap the highest benefits from their nonequity-based exploitation alliances with large firms, followed by equity-based exploration alliances. We did not find support for relational governance. It suggests that formal structure is more effective than relational structure in governing small firms' exploration alliances with large firms. Part of the reason can be explained by the fact that small firms are often at a disadvantage to vie for large firms' trust, which is especially the case in the biopharmaceutical industry.

This study contributes to both the entrepreneurship and strategic alliances literatures. While most prior research on strategic alliances has primarily focused on large firms, we examined alliances from the perspective of small firms. In particular, we suggest that in general small firms can derive greater benefits from exploitation alliances than from exploration alliances with large firms. However, if small firms manage their alliances with large firms via proper alliance governance, they will enhance their value from exploration alliances with large firms. Our findings extend prior studies that adopted the perspective of large firms in allying with small biotech firms (Rothaermel, 2001) by highlighting the contingencies that help small firms configure their alliances with large firms.

The study offers important insights for managers of small firms to understand better how to benefit from alliances with large partners. Managers should proactively design their strategic alliances with large firms and consider the ramifications of each new partnership choice. For example, managers should recognize that while both exploration and exploitation alliances with large firms may be beneficial, small firms will generally benefit more from exploitation than from exploration alliances. Exploration alliances with large firms are riskier for small firms due to potential value appropriation by their large partners. However, small firms protected by formal governance such as an equity-based structure are likely to have greater returns from the variance-seeking activities in exploration alliances.

Limitations and directions for future studies

The findings of this study should be considered in light of its limitations, which also provide directions for future studies. First, our data come from a single industry. This sampling creates a well-defined context for examining our theoretical hypotheses but limits the generalizability of the findings to other contexts. Although we believe that the general pattern may hold for small firms' alliances with large firms in other contexts, further empirical validation is required in other industries such as computers and telecommunications industries. Second, given that firm performance is commonly considered as a multidimensional construct, it will be interesting to explore whether a small firm's high valuation will lead to its long-term economic returns (Kale, Dyer, and Singh, 2002). In addition, our study focused on the public market valuations rather than private equity valuations as the latter may be conducted differently in terms of actors, process, and frequency. Future research may probe into the unique context of private equity valuations to gain additional insights. Third, future research may consider conducting field studies to measure directly the relational governance between small firms and large firms in alliances. Our research implies that a small firm's embeddedness in an alliance network may not win trust for them from large firms. Probably it is easier for a small firm to develop trust with a few rather than many large alliance partners. Future research may explore the development of trust mechanisms between asymmetric firms in alliances. Finally, while we compared the relative impact of small firms' exploration and exploitation alliances with large firms, we did not address the question of alliance portfolio balance in terms of exploration and exploitation alliances (Lin et al., 2007). Future research may investigate whether small firms should focus on dynamic balance via sequential ordering of exploitation and exploration (Rothaermel and Deeds, 2004).

In conclusion, small firms often face a challenge of configuring their alliance portfolio with large firms: they should address not only the tension between the need for resources and the risk of appropriation, but also the balance between exploration and exploitation alliances with large firms. This study investigates the relative impacts of exploration and exploitation alliances with large firms on small firms' valuations by drawing on the exploration/exploitation framework as well as the alliance governance literature. We find that in general small firms benefit more by forming exploitation alliances with large firms than by forming exploration alliances with large firms. However, if small firms are protected by proper alliance governance such as an equity-based structure they are likely to increase their returns from their exploration alliances with large firms. This study conveys an important message that small firms should adjust their alliance strategies with large firms by considering appropriate alliance governance.

ACKNOWLEDGEMENTS

  1. Top of page
  2. Abstract
  3. INTRODUCTION
  4. THEORY AND HYPOTHESES
  5. METHOD
  6. RESULTS
  7. DISCUSSION AND CONCLUSION
  8. ACKNOWLEDGEMENTS
  9. REFERENCES

We thank Editor Edward Zajac and the anonymous reviewers for their invaluable comments and guidance throughout the review process. This research was supported by the Research Grants Council of the Hong Kong Special Administrative Region, China (CityU 151810).

REFERENCES

  1. Top of page
  2. Abstract
  3. INTRODUCTION
  4. THEORY AND HYPOTHESES
  5. METHOD
  6. RESULTS
  7. DISCUSSION AND CONCLUSION
  8. ACKNOWLEDGEMENTS
  9. REFERENCES
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