The Effect of Acquisitions on New Alliance Formation

University of Groningen Faculty of Economics and Business

MASTER THESIS

MSc Business Administration: Strategic Innovation Management

The Effect of Acquisitions on New Alliance

Formation

Derek Jesse Telman

Supervisor: A.A. Oleksiak Co-assessor: dr. I. Estrada Vaquero

Word count: 9046

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ABSTRACT

Previous literature on acquisitions and strategic alliances is far-reaching. Both concepts have been studied separately and as alternatives. However, the current literature on acquisitions and strategic alliances as two related concepts is still limited. In this paper we research this relation by examining if pursuing acquisitions impacts the new alliance formation, thus the engagement into new strategic alliances. Furthermore, the importance of complementarity in inter-firm resource exchange has been emphasized by several scholars. Therefore, we examined if complementarity has a moderating role in this research. Through press releases, annual reports, Lexis-Nexis, Orbis and Google a panel set was created for 36 firms from the biotechnological industry. The results show that an increase in the number of acquisitions subsequently increases the number of new strategic alliances a firm will engage into. Moreover, companies that acquire firms with a high percentage of complementary resources are more beneficial in case of an increasing number of acquisitions. Whereas for companies that acquire firms with a low percentage of complementary resources, an increasing number of acquisitions has a negative impact on the engagement into new strategic alliances. The results demonstrate that acquirers are still tempted or forced into alliances, because these complement or are even essential to the acquired resources. Whereas complementarity strengthens this relation and enables firms to attract future alliance partners.

Key words: acquisitions, strategic alliances, complementarity, substitutable, resource

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TABLE OF CONTENT

INTRODUCTION ... 4

LITERATURE REVIEW ... 5

Acquisitions and Strategic Alliances ... 6

Type of Acquisition: Substitutable and Complementary Resources ... 8

METHODOLOGY ... 10

Data Collection ... 10

Sample ... 11

Measures ... 12

Analysis ... 14

RESULTS ... 15

Descriptive Statistics ... 15

Regression Results ... 16

DISCUSSION ... 19

Theoretical Implications ... 19

Managerial Implications ... 22

Limitations and Future Research ... 22

CONCLUSION ... 23

REFERENCES ... 24

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INTRODUCTION

In the last two decades, firms increasingly started forming strategic alliances to gain greater efficiency and create value (Krishnan, Geyskens, and Steenkamp, 2015). The increasing engagement of firms in strategic alliances makes it one of the most important tools of a firm’s strategic plan (Wassmer, 2010). Not all strategic alliances share the same goals and objectives, hence in this study we use the definition of Gulati and Singh (1998:781). Where they define strategic alliances as “voluntarily initiated cooperative agreements between firms that involve exchange, sharing, or co-development”.

Strategic alliances can help firms to increase their capabilities because of the new knowledge and resources an alliance can provide them (Kavusan, Noorderhaven and Duysters, 2016).Moreover Kavusan et al. (2016) state that next to engaging in alliances, acquiring knowledge is an important organizational activity to access external resources. In this case, a firm is more interested in acquiring a partner’s knowledge instead of creating a joint commercial outcome. Moreover, in order to gain access to external knowledge, a firm can use the acquisition of a firm’s full stock (Grimpe and Hussinger, 2013). However, the fundamental difference between an alliance and acquisition is that “alliances only allow for partial control, while acquisitions afford complete ownership control of assets” (Peng, Lin, and Yang, 2011:1070). In comparison to acquiring knowledge, the acquisition of a firm is a more excessive activity to gain new knowledge and resources (Grimpe and Hussinger, 2013). Moreover, firms are often looking for complementary knowledge and resources (Lavie, 2007). The search for complementarity is in line with the relational view by Dyer and Singh (1998), where complementary resources are approached as one of the potential sources of a firm’s inter-organizational competitive advantage.

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we will investigate the relationship between pursuing acquisitions and the engagement into new alliances. Due to the important role complementarity has for firm’s inter-organizational competitive advantage (Dyer and Singh, 1998), we will investigate if the acquisition type (substitutable or complementarity) plays a moderating role in our study. In this study we point at the relationship between the acquisitions a firm pursues and the new strategic alliances it gets engaged in. In order to test our hypotheses, a panel database with firm level data from 36 biotechnology firms for the years 1996-2010 was used. Lexis-Nexis, Orbis, Google, press releases and annual reports have been used to obtain all the relevant data. The findings show that pursuing acquisitions has a positive linear impact on the engagement into new strategic alliances. Moreover, the positive linear relation increases when the acquisition contains complementary resources. The study contributes to the existing literature on strategic alliances, acquisitions and the resource-based view. The results show that scholars and managers should not consider strategic alliances and acquisitions as two separate concepts and furthermore, should avoid to only focus on the choice between either of these forms. This contribution is of great importance, since it helps firms to see the influence of an acquisition on future engagement into strategic alliances. Furthermore, it gives firms a new insight on the importance of complementary resources. By showing that pursuing acquisitions can enhance the ability to recombine and share knowledge within future strategic alliances, firms will be able to increase their competitive advantage through complementarity. This paper is structured as follows. First, we review the existing literature on acquisitions, strategic alliances and resource types. Secondly, the hypotheses and conceptual framework will be compiled based on the existing literature. Next, the data collection process, the sample, the measures and the statistical analysis we used to test our hypotheses are discussed. Subsequently, an extensive description of the descriptive statistics and statistical tests is given. Finally, we discuss the theoretical and managerial contributions, followed by limitations, future research and a conclusion.

LITERATURE REVIEW

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definitions of substitutable and complementary resource exchange will be addressed. This will enable us to develop the second hypothesis.

Acquisitions and Strategic Alliances

An acquisition is when one firm obtains majority ownership over another firm (Shanley and Yin, 2008). This implies that not only a technology is acquired, but at the level of firm acquisitions the acquiring firm buys most, if not all, ownership stakes of the targets firm to obtain full control. Acquisitions were often used to acquire a contested patent portfolio that threatens their own research and development activities. In this way a firm can protect itself by blocking the competition (Grimpe and Hussinger, 2013). However, one of the current observed corporate trends is the acquisition of firms to gain access to new resources (Grimpe and Hussinger, 2013). Resources can be defined as “stocks of knowledge, financial assets, physical assets, human capital, and other tangible and intangible factors that a business owns or controls” (Capron, Mitchell and Swaminathan, 2001:818). Because of the full control over a target firm’s assets, the acquirer will have the ability to enter the acquired firm’s resources. Extant literature on the inter-firm exchange of knowledge has been inclined to treat acquisitions as an alternative to strategic alliances (Wiklund and Shepherd, 2009; Vanhaverbeke, Duysters and Noorderhaven, 2002). Strategic alliances are defined as a “purposive relationships between firms that share compatible goals and strive for mutual benefits” (Albers, Wohlgezogen and Zajac, 2016:583). The increasingly use of alliances is a result of the competitive pressures that increased due to the faster and more efficient commercialization of knowledge by firms. Due to this shift, firms are more often looking for alternatives to in-house R&D and resources (Sampson, 2007). Strategic alliances on R&D level can provide firms access to “complementary capabilities, reap economies of scale in R&D, and shorten development time while spreading the risk and cost of such new development” (Sampson, 2007:364). Which stimulates firms to engage in alliance and keeps the number of ongoing engagement growing.

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2016). However, the same author states that it is crucial to balance different types of resources in the alliance portfolio, to alter the best performances. Therefore, partners’ resources are highly rated by firms in order to engage into alliances. Sampson (2007) confirmed that the resource pool of the partner firm is highly appreciated to determine the success of an alliance. This reflects firms’ search criteria; firms are often looking for unique resources and preferably avoid partnerships with firms that have less resources (Katila et al., 2008). A firm with a lot of resources is in the eyes of most firms more likely to be of any use or value, since more resources reduces the chance on overlap and therefore there is a greater potential for knowledge recombination (Sears and Hoetker, 2013). However, a firm first needs to redeploy external resources to their own needs. During the post-acquisition it is important that all the resources are being redeployed so they can be fully utilized by the acquirer (Capron et al., 2001). After the redeployment period, a firm can use the acquired resources in their own advantage to potentially attract firms into inter-firm engagements.

Furthermore, external resources are used to enhance the internal resources or capabilities and to increase the initial resource pool. As mentioned earlier, the increase in resources makes firm more attractive to potential partners (Katila et al., 2008). However, firms are not always primarily interested in the resources the acquired firms shelter or the learning opportunities that lie ahead (Grimpe and Hussinger, 2013). The increasing engagement into inter-firm resource exchange does also creates other needs. A growing resource portfolio brings opportunities, but also risks and difficulties (Mishina, Pollock and Porac, 2004). Several firms chose for an alliance to outsource production processes (Hoffmann, 2007), which is in several cases the result of resource acquisition. Because a number of firms acquire and access so many resources, that they cannot generate their resources internally anymore (Quinn, 1999). Next to this, the overflow of external resources makes that some firms lack the assets to protect their own resources. Therefore, firms use alliances to share the risks and costs that the operations and their resources face (Li, Qian and Qian, 2013). Firms that pursue acquisitions could face protection problems, because the internal processes and routines are not used to quantity and composition of all the resources.

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increases the chance that these firms engage in more alliances. Partly because an increase in resources subsequently enhances the bargain position and attractiveness of firms (Lavie, 2007), because this enhances the chance that potential partners need and become dependent on the resources this firm holds. The acquired resources do also force firms to engage into alliances to share risks, costs (Li et al., 2013; Quinn, 1999), and outsource processes (Hoffmann, 2007). Therefore we expect that the number of acquisitions a firm pursues produces a positive effect on the number of new strategic alliances in the future. This leads to the first hypothesis:

H1: The relationship between pursuing acquisitions and engaging into new strategic alliances is positive.

Type of Acquisition: Substitutable and Complementary Resources

Resources are described as heterogeneous, imperfect and mobile by the resource based-view (Peng, 2010). Firms are seen as entities that are not able to internally produce and create all the needed resources to grow and compete. Therefore firms often search for external resources (Peng, 2010). We see an increasingly use of alliances and consequently growing alliance portfolios, business are more focused on the performances of the alliances they are engaged in (Krishnan et al., 2015). These firms are looking to create a competitive advantage. There are several ways how external resources can enhance a firm’s competitive advantage, firms increasingly use external resources to modify their internal resources and routines (Capron et al., 2001). Thus external resources that have been obtained or accessed through an acquisition or alliance can increase the resource pool and possibly enhance the use of existing resources and their related processes and routines. Acquisitions of firms will enable the acquirer to access, appropriate, utilize or use the resources a target firm possesses. The new resources will be fully controlled and owned, which is not the case when resources are accessed through an alliance or collaboration (Shanley and Yin, 2008).

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allies the chance to create a surplus over the existing value and forms an important basis for the creation of value (Albers et al., 2016). These arguments are in line with the relational view by Dyer and Singh (1998), according to them complementary resources are one of the potential sources of a firm’s inter-organizational competitive advantage. This is also the reason that complementary resources are more often utilized and eventually redeployed to the preferences of the acquirer (Capron et al., 2001).

Both the acquisition of complementary and substitutable resources increase the number of resources a firm possesses, which makes a firm more attractive to potential partners (Katila et al., 2008). However, substitutable resources cannot be used to avoid losing synergies and the utilization and development of capabilities, with these similarity of outputs the synergies that come from combining different resources are limited (Miller, 2003). These substitutable resources give a smaller chance of creating and exploring new technologies and capabilities, and also new strategic alliances. This is mainly due to the fact substitutable resources have a large overlap with the internal resources. Subsequently, this reduces the possibility to create truly novel recombinations from the acquired resources (Sears and Hoetker, 2013). Therefore, substitutable resources are less valued (Lavie, 2007), which makes substitutable resources ultimately less attractive than complementary resources. So, firms that supplemented their existing resources with external complementary resources are more attractive.

Lastly, firms that want to leverage external resources are more often looking for complementarities to their own resources. This leads to firms that have the capabilities to complement others’ resources, obtaining a better bargain position in case of an alliance (Katila et al., 2008). So firms with complementary resources are not only more attractive than firms with only substitutable resources, they also establish a better bargaining position which enables them to coordinate and chose the right allies. This will enable a firm to be more often engaged into new strategic alliances and consequently leads to the second hypothesis:

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H2: substitutable – negative; complementary -positive

H1: +

METHODOLOGY

In this section we will describe the methodological choices that we made. We will describe our data collection process and our sample. Next, all the variables that are included in the different models will be discussed. Finally, a description and explanation of our choice for the conducted analyses. We conducted a longitudinal study, because we want test the effect and variety over different years. The included firms are all engaged in the biotechnology industry. Which benefits our study, because firms in the biotechnology industry are known for their inter-firm engagement (Lerner and Merges, 2003).

Data Collection

For this study we created a database with mainly the data of press releases and annual reports from several biotechnology firms. All still missing firm-level data was collected with Lexis-Nexis, Orbis and Google before added to the existing database. This database exists of mainly firm-level data and provides both information about the strategic alliances and acquisitions

Pursuing acquisitions Engagement into new _{strategic alliances}

Type of

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that were publicly announced during the last decades. All the included firms are active in the biotechnological industry. The initial pool of the database exists of the top 50 biotechnology firms1_{, for this study the date of these firms will be observed for the period of 1996-2010.} All the acquisitions that are included have been found with the help of the press releases, annual reports or through Google. For all acquired firms the SIC and NCAIS codes are looked up with LexisNexis, Orbis or Google, which helped us to determine the acquisition type and subsequently provides us of the necessary information to create the moderating factor. The number of strategic alliances that will be used as dependent variable were also found by the help of Lexis-Nexis, Orbis, press releases, annual reports and Google. Strategic alliances that were just mentioned once without a starting nor a termination date were ignored. Moreover, we used the first mentioned that as starting date for the strategic alliances that did not include a clear starting date. Provided that the alliances was mentioned more than once. For alliances that did not have a termination date, we expected the alliances to end on the end of the year of the last mention date. The control variable firm age was conducted through annual reports and Orbis, where we could find the exact number of employees the firm carried. Google helped us to find the founding date of every firm, so we could determine the firm age for every firm. The net profit margin was conducted through Orbis and the financial data in annual reports. The last control variable, number of patents, was conducted through the patents section on Orbis.

Sample

For the sample we use 36 firms, because some firms were excluded by STATA to keep the panel data balanced. The first sample exists of 251 observations, result of the short existence or acquisitions of focal firms. The focal firms together started 1506 new strategic alliances between 1996 and 2010. The number of acquisitions is 80, however we use a lead independent variable by 1 year (t-1). Which makes that only the years 1997 until 2010 are used in the third sample, which brings the number of acquisitions and alliances respectively down to 77 and 1430. In the final sample the moderator and interaction effect are included. This brings the observations down to 36 as the model only includes the necessary variables and the years and firms that include one or more pursued acquisitions.

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Measures

Dependent variable

Engagement into new strategic alliances. The number of new strategic alliances a firms

entered will be included per year by every firm. This dependent variable will be a count variable, because the smallest possible number is zero. However, the conducted test is designed for continuous variables. Therefore we will logarithmical transform the dependent variable, so we can conduct the necessary statistical test.

Independent variable

Firm acquisitions. For the independent variable, firm acquisitions, is stated by the number of

acquisitions per year for every firm. There has to be a clear distinction between firms that do pursue acquisitions and firms that do not. In the data, the number will indicate the number of acquisitions the firm pursued in the concerned year. If a firm did not pursue any acquisitions in the concerned year, the box will stay empty. We have chosen to compare the firm acquisitions, the independent variable, with the dependent variable from one year ahead. This because we expect the firms to redeploy the acquired resources before they actually attract potential partners with it (Capron et al., 2001). To realize the desired effect, we have use a lead of one year for the independent variable (t-1).

Moderator

Type of acquisition. For the only moderator in this study, the acquired firms by the focal firm

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the firm acquired in the concerned year2_{. The moderator is also lead by one year (t-1), because} the acquisition type should be simultaneous with the independent variable.

Control variables

The dependent variable is the engagement into new strategic alliances, therefore the control variables should have a significant influence on this variable. The first control variable is firm

size. Larger firms make higher investments in R&D, because they possess the resources to

finance R&D expenditures (Revilla and Fernández, 2012). This helps larger firms to create a more diverse pool of resources, which enhances the ability to develop more complementary resources and activities internally. We expect large firms to have a larger and more complementary resource pool, which subsequently leads to a higher attractiveness towards potential partners. Therefore we expect a significant relation between the number of new strategic alliances and firm size. For our sample the firm size is reflected by the total number of employees a firm possesses. We have logarithmically transformed the variable to deal with the skewed data from the variable (Fagiolo, 2006).

The second control variable is firm age, more established firms usually have greater resource availability. This allows them to develop more in-house, which makes them less dependent on external resources. However, commonly they possess more resources than new ventures (Antolin-Lopez et al., 2015). And new ventures have often less resources and thus less to offer, which makes potential collaborations less interested in partnering with these firms (Baum, Calabrese and Silverman, 2000). The alliance experiences and market power that more established firms often possess enables these firms to attract potential partners and establish a dominant bargain position (Shan, Walker and Kogut, 1994). So a positive influence from firm age is expected on the engagement into new strategic alliances. This control variable will be measured by stating all focal firms’ founding years.

The third control variable is financial performance. We use the net profit margin formula for this variable ‘net profit/revenue’, because it gives a good display of the way a firm weights their costs and sales. We have chosen not to multiply it by 100, to decrease the large differences between the values. Some firms did experienced years without any revenues, which creates very low net profit margin values. However, net profit margin gives us a better opportunity to benchmark between multiple firms then for example with just net profit or

2 _{For example, a company acquires two firms in the same year. One with substitutable resources (0), the other}

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revenue. Financial performances are highly valued by potential partners. Firms with less financial performance are seen as a more risky partner, because this affects the financial assets. These assets are seen as an important tool to generate potential returns on their future investments in any collaboration (Hitt et al., 2000). Which is why we use this variable as a control variable and expect a significant relationship with the dependent variable.

The last control variable is the number of patents. We expect the number of patents to have a positive impact on the engagement into new alliances. Patents are more often used to improve the firm’s co-operative position (Blind, Cremers and Mueller, 2009). The number of patents does reflect the attractiveness of a firm, because these firms are expected to have a strong technology base and a productive R&D department. The value that is generated through the technology and R&D attracts other firms, because these firms want to exploit that value (Blind et al., 2009). The numbers of patents is also skewed, because some firms do submit significantly more patents than others. Therefore we have logarithmically transformed the variable (Agrawal and Henderson, 2002).

Analysis

A longitudinal study approach was used to test the impact of pursuing acquisitions on the engagement into new strategic alliances. The number of new strategic alliances, our dependent variable, is a count variable. This means that the variable does not hold any negative values. Therefore, a negative binomial regression or Poisson regression is generally the right statistical approach (Hausman et al., 1984). However, the standard deviation of the dependent variable exceeds the mean3_{, which is called over dispersion (Ver Hoef and Boveng,} 2007). And in case of over dispersion, the negative binomial regression is preferred over the Poisson regression.

However, the nbreg model does not account for variance between and within groups (Allison and Waterman, 2002). And due to the small sample size when we include the moderator, the xtnbreg model is not able to converge. The only model left to use is a linear regression (xtreg). Unfortunately this regression is not created for panel data, but for continuous dependent variables. However, by transforming the dependent variable into a logarithm we can test our database (with caution).

3 _{The mean of the dependent variable, number of strategic alliances, is 2.601 and the standard deviation is}

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So to test the hypotheses, a linear regression analysis has been conducted. The Hausman test was conducted to see if a fixed- or random-effects linear regression analysis was more adequate to use (Greene, 2012). The test did reject the null-hypothesis (X2=17.44, P = .015), so the fixed-effects regression is better suited than the fixed-effects regression according to the test. In addition, the random-effects regression does not allows for unrestricted heterogeneity between firms and over time (Allison and Waterman, 2002). So in response to the conducted Hausman test and to prevent the results being biased by unrestricted heterogeneity, we have chosen to conduct a fixed-effects linear regression.

RESULTS

In this section we will discuss the results of the statistical analyses. Firstly the descriptive statistics and secondly the regression analyses.

Descriptive Statistics

The summary statistics and correlations are displayed in table 1. The first models included 251 observations distributed over a number of 36 firms. When we include the moderator effect the number of firms drops to 19 and 36 observations, because the moderator only accounts for the firms that did pursue acquisitions. The sample consists out of 1430 new strategic alliances and 77 acquisitions. A firm engages on average into 2.6 new strategic alliances per year. Where it only pursues an acquisition once every 7 years (mean = 0.14). Interestingly the number of new strategic alliances varies strong amongst years. Figure 1 shows the number of new strategic alliances and acquisitions per year. As shown, the years 2000, 2001 and 2002

Figure 2: Number of new strategic alliances and acquisitions per year

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were the most active years in numbers of new strategic alliances. These years account for 31.28% of the total number of new strategic alliances in the period from 1996 until 2010. Both 2005 as 2009 included the highest number of acquisitions per year, both 8.

The results in table 1 do not show too high correlations4_{. However, the correlation} between firm size and the number of patents is the highest with a value of 0.65. Fortunately this value is between two control variables and the Variance Inflection Vactors (VIF) do show good values5_{. The mean VIF of all variables is 1.71. Firm size (log) has the highest VIF value} (2.72) and Acquisitions per year (t-1) does have the lowest VIF value (1.02).

Table 1: Summary Statistics and Correlations

Variable Mean

Std.

Dev. Min Max 1 2 3 4 5 6 7

1 Strategic alliances (log) 0.93 0.73 0.00 2.89 1.00

2 Acquisitions (t-1) 0.14 0.40 0.00 3.00 -0.05 1.00

3 Acquisition type (t-1) 0.78 0.40 0.00 1.00 -0.18 0.02 1.00

4 Firm size (log) 5.91 1.29 2.56 9.91 0.43 0.02 -0.21 1.00

5 Firm age 20.34 20.44 0.00 107.00 -0.11 -0.03 0.08 0.43 1.00

6 Net profit margin -3.30 21.34 -398.66 0.81 -0.19 0.08 -0.17 0.32 0.21 1.00

7 Number of patents (log) 1.88 1.25 0.00 5.38 0.38 0.10 -0.37 0.65 -0.04 0.33 1.00

Regression Results

Table 2 provides the results of the fixed-effects linear regression that is used to test both hypotheses. All models contain the four control variables; firm size (log), firm age, net profit margin and the number of patents (log). The first model only includes the control variables, partly to test if the data corresponds with the extant literature. The second model tests the first hypothesis. The third model is used to test for a direct relation between the moderator and the number of new strategic alliances. The fourth model includes both the acquisitions and the acquisition type. And the last model tests the second hypothesis by including all the variables.

4 _{We speak of high correlations, multicollinearity, when the correlation between two values exceeds the value}

of 0.70.

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Table 2: Fixed-effect linear regression results (Number of new strategic alliances as dependent variable) a,b,c

a _{Significance levels: *p < 0.1, **p < 0.05, ***p < 0.01.} b _{Unstandardized coefficients are reported}

c _{Standard errors in parentheses}

Model 1 tests the relation between the control variables and the dependent variable. We see that firm size (log) is positively and significantly related (B = 0.195, p = .031), whereas firm age is negatively and significantly related (B = -0.031, p = .028). Firm size does show the expected sign. However, firm age was expected to have a positive relation with the number of new strategic alliances. Net profit margin shows a negatively and nonsignificant relation (β = -0.003, p = .429), where a positive relation was expected. The last control variable, number of patents, was not significant, but did show the expected signs (B = 0.043, p = .545). However,

Variable Model 1 Model 2 Model 3 Model 4 Model 5

Acquisitions (t-1) 0.180* 0.165 -0.859*

(0.099) (0.184) (0.435)

Acquisition type (t-1) -0.199 -0.293 -1.630**

(0.211) (0.237) (0.567)

Acquisitions (t-1) x Acquisition type (t-1) 1.214**

(0.484)

18 -8 -6 -4 -2 0 2 4 6 8 Low Number of acquisitions High Number of acquisitions De p en d en t var iab le Low Complementarity High Complementarity

the F-test from model 1 is greater than the critical value of the F distribution (F = 1.96, p > .05). Therefore the model is not statistically significant and the results from model 1 can only be interpreted with caution (Markowski and Markowski, 1990).

In model 2 we test the first hypothesis, expecting a positive impact of the independent variable (pursuing acquisitions (t-1)) on the dependent variable (number of new strategic alliances). The model shows the expected signs, acquisitions is positively and significantly6 related to the number of new strategic alliances (B = 0.180, p = .069). Therefore, the first hypothesis is supported.

In model 3, 4 and 5 we have included the moderator. This results in a substantial drop of observations and firms. Model 3 tests for a direct relationship between acquisition type (t-1) and the number of new strategic alliances (dependent variable). There is no significant relation between the two variables (B = -0.199, p = .363). In model 5 we included all the variables to test our second hypothesis. R² shows the variance in the data that is explained by the model (R² within = 0.791, R² overall = 0.034). We see a changed relation between acquisitions and alliances (B = -0.859, p = .077).

6 _{Significant on the 10% level.}

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The interaction between acquisitions and acquisition type is positively and significantly related to the dependent variable (B = 1.214, p =.031). To demonstrate the moderator effect, we created a graph. Figure 3 demonstrates that with regards to companies that acquire firms with a high percentage of complementary resources, increasing number of acquisitions has a positive impact on the engagement into new strategic alliances. In case of companies that acquire firms with a low percentage of complementary resources, increasing number of acquisitions has a negative impact on the engagement into new strategic alliances. Thus, we can conclude that hypothesis 2 is supported.

In the final sample we see that not all control variables show the expected signs. Where in model 1 firm age and net profit margin showed a negative relation, show the results from model 5 a negative relation for firm age and firm size (log). So the results do not correspond with the extant literature. The firm size (log) is negatively and significantly related (B = -0.340, p = .044). Firm age is negatively and significant on the 1% level (B = -0.120, p = .001). Whereas the net profit margin is positively but not significantly related (B = 0.003, p = .963). And finally, the number of patents is positively and significantly related to the dependent variable (B = 0.877, p = .000).

DISCUSSION

In this section, we firstly give the theoretical implications that occur and result following our research. Secondly we discuss the managerial implications, how our research can be of any use beyond the theoretical framework. Thirdly we discuss the limitations and future research. Lastly we will conclude on our research.

Theoretical Implications

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type.

This study contributes to the resource-based view by addressing the relation between acquisitions and the new alliance formation. In other words, the external resources that were acquired through a full-stock acquisition and the future external resources that can be accessed through new strategic alliances. Extant research already emphasized on the importance of accessing external resources to the firm’s competitive advantage (Peng, 2010; Vanhaverbeke et al., 2002). The results from the statistical analyses do show the expected signs and support the extant research. The direct linear relation between the number of strategic alliances and the engagement into new strategic alliances is confirmed by the fixed-effects linear regression. The acquisition behaviour by firms does influence their future7 engagement in new strategic alliances. This can be explained by the following, already existing line of components and literature. Firstly, obtaining the majority ownership of a firm allows a company to access these external sources (Wiklund and Shepherd, 2009). Secondly, we can link this to capability of firms to recombine resources, a larger number of resources does enhance the recombination potential of firms (Sears and Hoetker, 2013). Lastly, the recombination potential does attract potential partners (Griffith, Lee and Straathof, 2017), because recombination enlarges the chance that firms create novel ideas. And the attractiveness of a firm increases the engagement into new strategic alliances. These results suggest that scholars should not look at acquisitions and alliances as two alternatives. Future research should embrace that one does not exclude the other.

Moreover, the acquisition type has a moderating role regarding the relation between pursuing acquisitions and the new alliance formation. The statistical analyses support the expected signs; for companies that acquire firms with a high percentage of complementary resources, an increase of number of acquisition has a positive impact on the engagement into new strategic alliances. On the contrary, for companies that acquire firms with a low percentage of complementary resources, an increase of number of acquisition has a negative impact on the engagement into new strategic alliances. So there is no incentive to chase for substitutable resources with regard to new alliance formation. Whereas firms that look for complementary resources benefit from an increase in acquisitions. This is consistent with the resource based-view, which states that complementary resources are crucial to develop a

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sustainable competitive advantage (Mahoney and Pandian, 1992). In other words, by obtaining complementary assets a firm will become more attractive to other firms. The attractiveness of a firm depends highly on the complementarity the partner brings with (Shah and Swaminathan, 2008). This is due to the fact that the value of resources increases when they are complementary (Wiklund and Shepherd, 2009), and thereby the attractiveness. The value increases because of an increase in the possibility of novel ideas, which is influenced by the percentage of complementarity (Sears and Hoetker, 2013).

So far in this study we have considered resource sharing as the main motive to engage into strategic alliances. However, we should not exclude other possible explanation. An acquisition allows a firm to access new resources (Wiklund and Shepherd, 2009). The tested relationship could also be a result of something other than resource sharing, as firms can also chose to engage into alliances to share their costs and risks (Li et al., 2013). Particularly firms in high-tech industries use alliances to share their risks and costs. They tend to use alliances to outsource production processes to their partners. This allows them to reduce costs and to focus on research & development and subsequently increase their chance on breakthrough innovations (Hoffmann, 2007). So scholars should be careful by adopting the relation between acquisitions and alliances. The positive relationship is partly their because of share of risks and costs concerning the deployment of the resources that have been acquired by means of an acquisition.

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Managerial Implications

Our results provide different implications that can be used for managerial ends. This study can help managers guide through the different resource and knowledge sharing possibilities. Regarding to our results, managers should not rule out any options. When desired alliance partners or resources are inaccessible, a manager could chose to acquire a firm to access and use external resources in their advantage. This will not expel other options. On the contrary, pursuing acquisitions can help firms to become more attractive or dependent towards potential partners. However, not considering the acquisition type might hinder the desired outcomes. The choice between substitutable and complementary resources is an important factor for future new alliance formation. By acquiring firms that possess complementary resources relative to the acquirer, the acquirer can establish a competitive advantage and subsequently increase their engagement into new strategic alliances.

Limitations and Future Research

We acknowledge that our study is not without limitations. First, the study is conducted by using solely firms from the biotechnology industry. This industry is known for the high density of strategic alliances and other forms of inter-firm collaborations (Lerner and Merges, 2003). This is due to the high development costs that are usually included, therefore we have to be careful with the generalizability of our resources to less technological and complex industries. Second, as the dependent variable that is used in this study highly depends on the starting dates that have been conducted from press releases, annual reports and Google. However, some press releases did not possess the exact starting date. In this case we have used the first mentioned date, provided that the alliances was mentioned more than once. So we have to take in consideration that not every starting date is accurate, which could have affected the final results.

Third, the conducted control variables do have a considerably number of missing values. The annual reports, Lexis-Nexis, Orbis and Google did not hold all the desired figures. These missing values form a limitation, because they unbalance the data (Little and Rubin, 1989).

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rough approach, and therefore has to be adopted with caution. Furthermore, the SIC and NAICS codes do not reclassify firms over time (Hoberg and Phillips, 2016). Therefore we have to be even more cautious, because we conducted a longitudinal study.

Last, the most notable limitation according the empirical part. Due to the small sample size, we were restrained from using the panel negative binomial regression (xtnbreg). This problem was caused by the moderating factor, because the number of acquisitions in the sample was limited. Therefore we transferred the dependent variable to a logarithmic, which forces us to interpret the results with more caution.

For future research we suggest a bigger sample size. This enables researchers to use the most suitable model. This bigger sample size can be realized by including more firms in the sample size and increasing the time frame. It would be interesting to shift this study to different industries. Because the industry has a substantial influence on firms’ alliance formation (Stuart, 2000). A different moderating factor would be interesting to see in future research. Particularly alliance portfolio size (Wassmer, 2010) or post-acquisition strategies (Capron et al., 2001). Where we compared the new alliance formation with the pursued acquisitions from the year before, an interesting study could be the influence two or three years after the acquisition. Future research could also focus on an equation between these years, to find out how long it takes a firm to fully optimize the advantages of an acquired firm.

CONCLUSION

The aim of this study was to find a significant relation between pursuing acquisitions and the engagement into new strategic alliances. In addition, we tried to prove a moderating effect from acquisition type according this relation.

This study contributes to the resource-based view, where extant literature treats acquisitions and alliances as two alternatives to acquire external resources. The access to external and new resources is central to this view, where the relation between the resource acquisitions methods are less emphasized. We showed that the one can enhance the other by finding a positive linear relation pursuing acquisitions enhances new alliance formation. The results show that firms should be open for both acquisitions and alliances.

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do not need to exclude acquisitions or alliances. And the strive for complementarity to increase their performance and establish a competitive advantage does not end after an acquisition, because these acquired resources can potentially become a useful tool to enhance future new alliances formation.

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APPENDIX

Table A1: Descriptive statistics dependent variable; number of new strategic alliances

Variable Obs Mean

Std.

Dev. Min Max

Alliances 579 2.601 2.781 0 18

Table A2: Variance Inflection Factors (VIF) test

Variable VIF 1/VIF

Firm size (log) 2.73 0.37

Number of patents (log) 2.53 0.40

Firm Age 1.62 0.62

Net profit margin 1.20 0.84

Acquisition type (t-1) 1.18 0.85 Acquisitions per year (t-1) 1.02 0.98