THE RELATIONSHIP BETWEEN COLLABORATION-FOR- INNOVATION EXPERIENCE AND THE INNOVATION PERFORMANCE OF THE ACQUIRING FIRM

THE RELATIONSHIP BETWEEN COLLABORATION-FOR- INNOVATION

EXPERIENCE AND THE INNOVATION PERFORMANCE OF THE

ACQUIRING FIRM

AN EMPIRCAL STUDY IN THE PHARMACEUTICAL INDUSTRY

P.A.L. HULSHOF

University of Groningen

Master Thesis

Ma Business Administration: Strategic Innovation Management

First supervisor: I. Estrada Vaquero,

i.estrada.vaquero@rug.nl

Second supervisor: F. Noseleit,

f.noseleit@rug.nl

June 24

, 2013

Abstract

This study investigates whether pre-acquisition experience in collaboration-for-innovation of the acquiring firm has a positive effect on the post-acquisition innovation performance of the acquiring firm. Three types of collaboration-for-innovation experiences are examined: acquisition experience, alliance experience and a combination of these two. An empirical analysis was made based on a data sample of 101 pharmaceutical firms that acquired another firm or sub-unit in the year 2006. The results show solely non-significant outcomes and therefore none of the hypotheses is supported. However, firm size is found to have a moderating effect on the relationship between pre-acquisition alliance experience and the innovation performance of the acquiring firm.

Introduction

The growing uncertainty and competitiveness of the business environment has increased the overall importance of innovation for future growth (Han et al. 2012; Franko, 1989) and thereby, the need to gain new knowledge. Firms are constrained to make a trade-off between developing this knowledge internally and externally (Raisch et al., 2009). Internal development of knowledge takes a long time and can be very expensive due to the need of large investments in money, time and effort, while it is entering a new market with possible barriers and high profitable established firms (Sing & Montgomery, 1987). The chances of capturing a first-mover advantage will then often be lost to the quicker competitors (Deeds & Hill, 1996). The highly competitive environments, rising R&D costs and a declining technology- and product life cycle time have already led to increasing developments of collaboration-for-innovation strategies (de Man & Duysters, 2005). Making use of external sources of information, by purchasing an on-going firm or sub-unit, is faster and could be cheaper, and therefore more profitable. This way of operating can be of great importance to a firm’s survival and further knowledge development.

Acquisitions make external knowledge development possible and are often used as an important innovation strategy (Vermeulen & Barkema, 2001). However, before any increase in a firm’s innovation performance is possible through acquisitioning, the acquisition process itself should be successful. A long history of completed acquisitions show high failure rates (Hunt, 1990; Forbes, 2010), nevertheless it did not stop firms from trying. In general, previous research about how to increase the innovation performance through acquisitions does not offer conclusive findings (Prabhu et al. 2005; Hitt et al., 1996; de Man & Duysters, 2005). This arouses to search into this topic for further clarification.

collaboration-for-innovation strategy. Looking at alliances as pre-acquisition experience, it was stated that when acceding certain criteria, it could enhance the performance of subsequent acquisitions of a firm (Chang & Tsai; 2013).

This article will investigate whether pre-acquisition collaboration-for-innovation experience (from now on experience refers to pre-acquisition experience) can positively influence the performance of the acquiring firm. Where previous research, like Chang & Thai (2013), measured the stock performance as an indicator of the post-acquisition performance, this article will focus on measuring the innovation performance. Furthermore, experience will be studied for former alliances and former acquisitions, but also as a combination of these two. Alliance experience of the acquiring firm is seen as having done one or more alliances in which capabilities, skills and the ability of information sharing can be developed. Acquisitions experience also concerns having done one or multiple acquisitions to develop these skills and capabilities, but also dealing with the integration and coordination processes. The combined experience of acquisitions and alliance experience is a sum up of these two.

Evidence on the relationship between acquisitions and the post-acquisition innovation performance (from now on innovation performance refers to the post-acquisition innovation performance) is up till now still ambiguous, mostly stated as neutral or negative (de Man & Duyster, 2005; Zollo & Singh, 2004). When acquisition intensity was indicated as a negative influencer for a firm’s innovation performance, it was stated that this was due to the acquiring process being a substitute for innovation since it would neglect research and development programs (Vermeulen & Barkema; Hitt et al., 1990). This article explores if this still would be the case when a firm has experience in collaborations-for-innovation. The fact that previous research (de Man & Duyster, 2005; Zollo & Singh, 2004; Vermeulen & Barkema; Hitt et al., 1991) about the innovation performances of acquiring firms was rather diffused, hence sometimes negative, can and may not be neglected. Therefore, it is emphasized here that this study will also take the relative innovation performance into account. With this, I aim at the possibility of the innovation performance not to improve, but show results that are, relatively seen, more positive than an acquiring firm without any experience in collaborations-for-innovation. So, a measurement of the innovation performance can indicate a result that is less worse than in the case of not having any experience in collaborations-for-innovation at all.

empirical analyses. However, combining different variables per analysis showed divergent outcomes which indicates that there are some relationships. The control variable firm size though, showed multiple significant outputs which insinuated the possibility of the firm size operating as a moderating variable. A new regression analysis showed positive significant results for the firm size as moderating variable of the relationship between alliance and combined experience and the innovation performance.

In the following, first the theories about acquisitions, alliances and innovation performances will be discussed. Based on previous researches and literature, assumptions about the relationships between these concepts will lead to hypotheses to be tested. Secondly, it will be discussed how this empirical study is done, which variables are participating and which relationships between these variables will be tested. Subsequently, the results of the empirical analysis will be displayed. After the statistical analysis, I conclude and discuss the results in retrospect to my expectations and additional literature. Finally, I elaborate on what limitations may have influenced these outcomes and what possibilities there are for future research in this study field.

Theory and hypotheses

Even though earlier research about the innovation performance of the post-acquisition position of a firm remains rather unclear, acquisitions are often used as an important innovation strategy (Vermeulen & Barkema, 2001; Ahuja & Katila, 2001). If positive results are derived, it is mostly due to reflecting the performances on the long term effects of the acquisition instead of the more short term effects (Hagedoorn & Duysters, 2002). Taking this perspective into account, multiple explanations can be related to the choice of acquisitions as a strategy to enhance the innovation performance.

Even though an increase in innovation performance is possible through acquisitioning, the acquisition process itself should be successful. This is a tough battle against the minor chance it has and due to the huge management challenges involved in the process, acquisitions are known to have failure rates around 60% (Hunt, 1990; Forbes, 2010; de Man & Duysters, 2005). One of the most important requisites and at the same time struggling points for a successful acquisition is a good management of the coordination-autonomy dilemma (Puranam et al., 2006). When a large firm acquires a smaller firm, it should be omniscient to find a good balance between a structured coordination of the capabilities and technologies of the acquired firm and preserving its autonomy at the same time (Puranam et al., 2006). If this autonomy is not well preserved, the acquired firm loses its exploration capacity. This firm will then not be able to provide the acquiring firm new knowledge which should improve post-acquisition performances. These types of capabilities are important for future innovations and growth of the firm. Alongside with this, management should be able to target the right firm; this means a firm with related knowledge on a moderate base (Cloodt, et al., 2006). It concerns an inverted u-shaped relation here, where too similar knowledge will lead to a waste of money since the transferred knowledge will not enrich the already existing knowledge. On the other hand, if information differs too much, it becomes too difficult to handle due to the causal ambiguity it presents (Cloodt et al., 2006; Barkema & Schijven, 2008). The management of an acquiring firm needs to take a lot into account when planning to do an acquisition. Resolutions could be found in earlier experiences and give decisions of managers more strength and certainty. Aiming at decreasing acquisition failure, earlier research (de Man & Duysters, 2005) suggests that firms with collaboration-for-innovation experience are better at breaking inertia and changing their organizational structure, to eventually improve the effectiveness and efficiency of the integration process.

In the following part, the concept of collaboration-for-innovation will be explicated in more detail. After this, the concept will be divided in the relationship between acquisition experience, alliance experience, a combination of these experiences and the innovation performance. This will lead to the hypotheses to be investigated in this research.

Collaboration-for-innovation experience

& Reuer, 2010). According to Zollo & Reuer (2010), these experience spillovers can be defined as “the impact of the experience accumulated in the execution of activity j on the performance of i”, so in this case the impact of experience in collaboration-for-innovation on the post-acquisition innovation performance of the acquiring firm. It has already been found that there should be some similarity between the skills which are necessary to undertake these activities in order to make use of this experience (Haleblian & Finkelstein, 1999; Sirmon, Hitt, & Ireland, 2007; Barkema & Schijven, 2008). If this condition is complied, experience can create much higher innovation performances for the acquiring firm (Meschi & Metais, 2006). However, it can not be neglected that comparable research has had negative outcomes. Acquisition intensity was sometimes indicated as a negative influencer for a firm’s innovation performance, due to the fact that acquiring processes would form a substitute for innovation and would neglect research and development programs (Vermeulen & Barkema, 2001; Hitt et al., 1991). Since there was no evidence of the presence of any collaboration-for-innovation experience for the firms that had failing performances, this research is looking to find different results for the relation between acquiring firms with experience and their innovation performance.

2010). In addition to that, it is essential that management’s decision making skills are qualified, and since acquisitions and alliances are often coordinated by the same people, these skills can improve through accumulated knowledge from previous experiences.

In the next section, the relationships between collaboration-for-innovation experiences and the innovation performance of the acquiring firms will be discussed. From this, the hypotheses for this study will be built on previous literature.

Acquisition experience

Acquisition experience can rely on historical data and create a better vision on the risks of a potential future acquisition (Kim et al., 2011). Companies are able to avoid the winner’s curse since it has a greater insight in what price to pay for that particular acquisition, which target firm to select and achieve greater success in the integration process of the acquisition (Giliberto & Varaiya, 1989; Hitt et al., 2001; Higgins & Rodriguez, 2006). In addition to that, prior acquisition experience can also support the identification and integration of a firm’s resources, which will benefit the post-acquisition performance (King et al., 2004; Hitt et al., 1998). These new identified and selected external resources can be transferred, copied to or combined with existing resources, which can create innovative resource combinations (Christensen, 1997; Wiklund & Sheperd, 2009), and thus will enhance the innovation performance of the acquiring firm.

Moreover, acquisition experience in general imposes that firms are better at breaking inertia and organizational changing, improving the effectiveness and efficiency of the integration process (de Man & Duysters), which will make innovations more likely to arise in every new acquisition deal. Therefore, the following hypothesis is set:

H1: Acquisition experience has a positive effect on the innovation performance of the acquiring firm

Alliance experience

First, it will be shortly discussed how alliances can create experience to benefit a subsequent alliance in order to get a better view on the process of the alliance itself and future decision making. After that, alliances will be deliberated in the view of its purpose as a pre-acquisition experience to improve innovation performances.

Companies can learn from previous alliances and create experiences that could be beneficial for future decisions. This is the case for both alliance experience based on similar skills and for prior alliances that differ from subsequent alliances (Barkema & Schijven, 2008). Research (Sampson, 2005) has shown that when alliances are formed frequently, and the time duration between them is considerably short, the experience can benefit the future performances of alliances. Even though alliances are indeed less risky than acquisitions, it must be acknowledged that they can and do often fail. These failures mostly occur due to differences in the corporate culture, processes and knowledge base, which makes knowledge transfer difficult (Lane & Lubatkin, 1998). Furthermore, alliances are frequently formed between competitors, whereby fear of helping the other party to develop new technologies easily arises (de Man & Duysters, 2005). When a firm does succeed, it is able to learn from this and enrich its experience. Subsequently it is the case that this experience can improve the innovation performance (de Man & Duysters, 2005; Sampson, 2005).

firm are bigger, this relationship is expected to still be positive with a random acquirer as well. Since more experience is accumulated in prior alliances, manager’s skills to distinguish the right decisions improve which will appropriate this knowledge better (Zollo & Reuer, 2010). This leads to positive spillover effects, and are assumed to make more room for a focus on innovation processes (Zollo & Reuer, 2010). Consequently, the following hypothesis can be stated as follow:

H2: Alliance experience has a positive effect on the innovation performance of the acquiring firm

Combined acquisition and alliance experience

In the following part, the third hypothesis will be build based on previous developed theories. It must be acknowledged that there is only limited explicit research on the effects of acquisitions combined with alliances in the perspective of post-acquisition innovation performances. However, previous research (Wiklund & Sheperd, 2009) has used acquisitions and alliances interchangeably as pre-acquisition experience, based on their similar activities. They (Wiklund & Sheperd, 2009) argue that firms that engage in multiple knowledge acquiring activities, are more likely to develop capabilities which will improve knowledge integration and thereby increase their ability to create synergies. Based on the limited research on this and other previously spoken topics of acquisitions and alliances separately as pre-acquisition experience, a few more assumptions are made here.

When a firm is successful in acquiring, and thereby able to properly handle the coordination-autonomy dilemma, the developed skills can reduce the thwarting of the coordination of the acquisition by pre-acquisition alliances. Related to the spillover effects as discussed by Zollo and Reuer (2010), alliances and acquisitions both could strengthen a firm’s capabilities, and increase the ability of the acquiring firm to handle different corporate cultures, adjust to certain management styles and share knowledge, which are all required to create success in an acquisition. The acquisition of different types of knowledge bases is found to be relevant contributions to a firm’s post acquisition innovation performance (Cloodt et al., 2006). Moreover, Wiklund & Sheperd (2009) suggest that these combinations of external knowledge gaining activities form a construct linked to both entrepreneurship as well as innovation. Therefore, companies that have both acquisition and alliance experiences can complement and enhance the effect of each other, to increase successes in the innovation performance of acquiring firms. The last hypothesis is stated as:

I seek to fulfil multiple objectives in this study. The model (figure 1) predicts the outcomes of the hypotheses that the condition of having experience in collaborations-for-innovation will positively affect the innovation performance. Interactions between the control variables and the innovation performance of the acquiring firm are also included for comparative purposes and might influence the outcomes.

Figure 1. Model and hypotheses

Methodology

In order to execute my research, multiple data sets had to be combined to investigate the relationship between alliances and acquisitions, and acquisitions and the acquiring firm’s innovation performance. I started on the data for the acquisitions, since this would indicate the companies of which the innovation performance needed to be measured after certain collaboration-for-innovation experiences. The source for the acquisition data was the Securities Data Corporation (SDC) Merger and Acquisition database. From this database, I obtained my first acquisition sample, which consisted of all firms in the pharmaceutical industry, concerning companies with the Standard Industry Code (SIC) 2833 to 2836 (Higgins & Rodriguez, 2004). The selected firms announced only one acquisition in the year 2006 and solely covered acquisitions in which 51 percent or more of the shares were acquired in the transaction. The acquisitions being announced in the year 2006 should increase the likelihood of any innovations being created of which the patents are formally present in 2012. This will impose the guarantee for the most recent information on the innovation performance of the acquiring firm and thereby increase the validity. Since data is based on the announcement information of the acquiring firms, it was also checked whether these acquisitions actually pulled through and were completed, in order to increase the reliability of the sample. Furthermore, a selection criterion was made of the region in which the acquiring firms were operating and covered the Western world (U.S., Canada and Western Europe). These regions are most active in the pharmaceutical industry and enclose the largest firms in that business (Cooke, 2004). In order to make sure that the selected companies are retrievable in the other data sources that need to be used, an additional selection criterion was that the acquisition should be marked as public. These criteria led to a sample of 107 Western firms across 34 nations with primary SIC codes of 2833, 2834, 2835 or 2836.

The sample that I took from the SDC of Mergers and Acquisitions met the requirement of having a public status to assure the fact that there would be access to information on other collaborative operations of these acquiring firms. Namely, a part of this study makes it necessary that some of the acquiring firms were previously involved in an alliance. Therefore, the SDC database on Alliances was checked based on the acquiring firm’s CUSIP code for the 107 firms that were present in the selected sample of the Merger and Acquisition data set. This resulted in complementing the data of acquiring firms of which 39 were involved in an alliance between the years 2003 to 2005.

added the variable ‘number of patents’ that the acquiring firm possessed in 2012. Since some companies of the 107 focal firms where missing and in order to increase the reliability, I checked the company name for all the firms in the whole Orbis database and was able to make the dataset more complete.

All used data was publicly available and solely contained factual information which should decrease the variation of the scores due to random errors and thereby increases the reliability of this research (Brahma, 2009). Furthermore, the sample was reduces by six firms after the data collection was completed. These six firms were lacking some critical information for the study which would negatively affect the validity due to a wrong estimation of the construct it is purported to assess (Brahma, 2009). Table 1 shows an overview of the amounts of firms being involved in the corresponding strategic collaboration-for-innovation. The final data sample contained 101 acquiring firms in the pharmaceutical industry.

Table 1. Number of firms per collaboration-for-innovation strategy

Model specification and measures

This empirical study is performed using version 20 of the comprehensive and flexible statistical analysis and data manger Statistical Product and Service Solutions (SPSS). The hypotheses that were set in the theoretical background are tested in this program by means of a linear regression analysis in which the innovation performance of the acquiring firm is explained by different collaboration strategies and a set of additional control variables. The dependent variable innovation performance will be expressed as a linear function of the variables acquisition experience, alliance experience and the combined experience. The following equation shows the relation between the different variables in this research:

Innovation performance = a + b1 * Innovation Performance + b2 * Acquisition experience + b3 * Alliance experience + b4 * Combined experience + b5 * Firm size + b6 * Geographic distance + b7 * Acquisition size + ε

Type of pre-acquisition experience Number of firms

Acquisition experience 39

Only acquisition experience 17

Alliance experience 39

Only alliance experience 16

Table 2 gives an overview of all the variables that are included in this empirical research and shorty describes how they are measured and which database were used to build these measures. In all following tables, experience ‘1’ refers to the number of previous acquisitions and/or alliances the acquiring has done, regardless of the fact of being involved in one or more collaborations.. Experience ‘2’ refers to the dummy variant of that variable, so whether an acquiring firm has, or does not have any experience in a particular collaboration-for-innovation strategy. In the following part, the measures of the variables are explicated in more detail.

Table 2. Overview variable measurement and database

Dependent variables

Innovation performance: The firm’s post acquisition innovation performance is, consistent with Cloodt et al.

(2006), measured by the amount of patents. This number is based on the patents that the acquiring firm possessed in the year 2012, six years after the focal acquisition. These can include patents that were announced some years ago and are still valid, but could also be recently announced in 2012. Patents form a reliable indicator of the innovation performance since they, among others, have a strong correlation with new products and seem to specify the innovative results of R&D better than for R&D spendings (Comanor and Scherer, 1969; Sampson, 2005).

Variable Measurement Database

Dependent variables

Innovation performance Exact number of patents in 2012 Orbis – a world of company information

Independent variables (Pre-acquisition)

Acquisition experience 1 Exact number of acquisitions in 2003-2005

SDC Mergers & Acquisitions

Acquisition experience 2 Division of none or >=1 acquisition in 2003-2005

SDC Mergers & Acquisitions

Acquisition experience square Square of exact number of acquisitions in 2003-2005

SDC Mergers & Acquisitions

Alliance experience 1 Exact number of alliances in 2003-2005

SDC Alliances

Alliance experience 2 Division of none or >=1 alliances in 2003-2005

SDC Alliances

Alliance experience square Square of exact number of alliances in 2003-2005

SDC Alliances

Control variables

Size acquisition Price paid for acquired target firm in 2006

SDC Mergers & Acquisition

Geographic diversity Division the acquisition concerning a domestic(0) or international(1) collaboration

SDC Mergers & Acquisition

Firm size Total assets of the acquiring firm in 2006

Independent variables

Acquisition experience: I measure the acquisition experience, consistent with Zollo & Reuer (2010), by the

number of acquisitions the focal firms have done in the recent past. Since a firm’s acquisition experience is the sum of recent undertaken acquisitions (Hayward, 2002), the experience is based on the acquisitions for the years of 2003 until 2005, one year for the focal year. The value of knowledge depreciates faster when operating in a high turbulence industry, like the pharmaceutical industry. This is due to high levels of inter-period uncertainty (Glazer & Weiss, 1993). For this reason, the acquisition experience was tested for a rather short period and just before the focal acquisition year.

Alliance experience: This variable is measured by the amount of previous completed alliances the acquiring firm

has done prior to the focal acquisition (Zollo & Reuer, 2010). This number is once again checked for the years 2003 until 2005. Since the name of a firm sometimes changes over years or due to mergers or acquisitions, the search for the firms was mainly based on the CUSIP codes in order to find the right firm.

Combined (acquisition and alliance) experiences: The outcome of this variable indicated a zero if there was no

or only one collaboration-for-innovation strategy used in the recent pre-acquisition years. Value for this variable was only created when the acquiring firm performed at least one acquisition and at least one alliance. The fact that the data for this variable was derived from the sum of the exact amount of alliances and acquisitions, made ‘1’ an impossible outcome.

For all the independent variables a dummy variant was formed, where ‘0’ stands for no collaboration and ‘1’ stands for at least one appearance of a collaboration. These additional variants of measurement of the independent variables were developed in order to check the robustness of the results and see whether I would obtain the same results while using these different types. Furthermore, a square of each independent variable was formed to do additional analyses in relationship to the innovation performance and check the possibility of having an inverted U-shape relationship with the innovation performance.

Control variables

Size acquisition: The size of the acquisition influences the impact of the later acquisition performance since

research (Hayward, 2002; Kim et al., 2011) has shown that larger acquisitions are more capable of affecting the returns of the acquiring firm. The data for this variable was measured based on the price that was paid for the target firm.

Geographic diversity: Problems in the knowledge transfer process arise when geographical and cultural distance

portfolio. At the same time, this competitive resource portfolio is hard to develop, which could lead to positive outcomes. With a dummy variable, a distinction is made between a domestic (0) and an international (1) collaboration strategy.

Firm size: This data was obtained on the base of the total assets of the acquiring firm (Kuperman et al., 2004) in

the year 2006, when the acquisition took place. The amount of assets can be of influence on how much can be invested in alliances and acquisitions (Wiklund & Scheperd, 2009). Larger firms therefore, can undertake a greater volume of knowledge transfer (Bresman et al., 1999) and have higher chances on succeeding in an acquisition, making the chances on higher innovation performances larger. It also makes an important control variable since previous studies (Cohen & Levin, 1989) showed that patent activity, which I refer to innovation performance in this article, increases with size.

Results

Table 3 shows the descriptive statistics and the bivariate correlations for the variables used in this study. The Pearson correlation is used to determine associations between the research variables, since focus is on the correlation coefficient as a computational index used to measure the bivariate association (Rodgers & Nicewander, 1988). As table 3 shows, different research variables are correlated with each other, but from the independent variables, only the alliance experience variable is significantly correlated with the innovation performance (p < 0.05). The various appearances of the independent variables (acquisition, alliance and combined experience) show mostly high significant correlations. Since the combined experience variable includes a combination of acquisition and alliance experience, an overlap in results seems inevitable. For this reason, it was in order here to test if there were any multicollinearity issues and I therefore, measured the variance inflation factors (VIF) of the independent variables. Only the alliance and combined experience squares experienced a multicollinearity issue with the acquisition square experience, since the VIF was above 10. All other tests showed VIF’s around 1, which is well below the threshold that would indicate any problems of collinearity (Frenz & Ietto-Gillies, 2009). Since there are almost no multicollinearity issues, all variables were inserted together in the regression analysis.

Even though there was no official problem regarding the multicollinearity issue, I want to emphasize the fact here that there is some definite overlap between the variables (see table 1) which is too high for the variable of the combined experience with respect to the acquisition and alliance experience variables. For this reason of common sense, I will not look at the outcomes of model 5, 10 and 15 from table 3 which include all three independent variables. The remainder models are analyzed and used to examine this study’s hypotheses and to verify whether the inclusion of additional variables increases the variance explained, which can be indicated from an increase in the r-squared (Heimeriks & Duysters, 2007).

Models 1 to 4 show the results of the relationship between the experiences based on the number of collaboration strategies they performed in the past and the innovation performance. To find similar results, the dummy variant of the experiences was developed of which the outcomes are shown in models 6 to 9. More concrete, model 1, 4, 6 and 9 tested hypothesis 1, which expected a positive relationship between acquisition experience and the innovation performance of the acquiring firm. Model 2, 4, 7 and 9 tested hypothesis 2, which expected that alliance experiences have a positive effect on the innovation performance of the acquiring firm. Model 5 and 8 tested hypothesis 3, which indicated that having both acquisition and alliance experience would complement each other and result in a positive effect for the innovation performance of the acquiring firm. All results were non-significant (p>0.10) for the independent variables which consequently leads to the conclusion that based on this regression analysis, none of the hypotheses could be supported. Acquisitions, alliances and a combination of these two as pre-acquisition experience do not appear to have a general positive or negative impact on the acquiring firm’s innovation performance. Remarkable though is that all tested relationships regarding the acquisition experience show negative outcomes. Even though the results are all non-significant, it is rather striking that a positive prospect turns into negative outcomes. This result will be discussed later on.

Table 4. Regression results

Except for the geographic distance in model 6, only the control variable “firm size” showed multiple significant results. This made it interesting to investigate whether firm size might have a moderating effect on the relationship between the diverse pre-acquisition collaborations-for-innovation. After categorizing the firm size in five categories (see table 5) and multiplied it with the number of experiences per collaboration-for-innovation, a moderating factor was created. This new moderating variable was tested by using a regression analyses of which the results are displayed in table 5.

From this regression analysis it can be obtained that firm size has a definite positive moderating effect on the relationship between alliance experience and the innovation performance of the acquiring firm with a coefficient of .383 based on a p<0.05 significance level in model 3. The positive effect is shown in both model 2 and model 3 but the latter model has a better significance level (.033 versus .021) and is therefore to attend. Furthermore, model 4 shows a positive significant result of .298 at a 90% confidence level for the moderating effect of firm size between the relationship of combined experience and the innovation performance of the acquiring firm. This positive effect was most likely reached due to a rather high positive force of the firm size on the relationship between the alliance experience and the innovation performance of the acquiring firm. Regarding the control variables, they show solely positive, but non-significant results here and therefore give no new insights.

Table 5. Firm size categories Table 6. Regression analysis moderating variables

The dependent variable is the innovation performance, measured by the amount of patents. Robust standard errors are in parentheses. *p<0.10; **p<0.05.

Firm size categories ($) 1 (XS) = 0 – 50.000 2 (S) = 50.000 – 150.000 3 (M) = 150.000 – 500.000 4 (L) = 500.000 – 2.000.000 5 (XL) = 2.000.000 - < Variables (1) (2) (3) (4) Intercept 36.441 (7.465) 33.316 (7.149) 35.420 (6.794) 34.540 (6.780) Moderating variables (pre-acquisition)

Firm size (acquisition experience 1) -.001 (1.563)

-.148 (1.627)

Firm size (alliance experience 1) .322**

(.686)

.383** (.747)

Firm size (combined experience 1) .298*

Discussion and conclusion

This section summarizes the main findings of this study, provides a conclusion in retrospect to existing literature and finally suggests some managerial implications. Despite the large number of studies that have been done about both acquisitions and alliances in relation to firm performances, there has been a lack in the search field of influencers of the innovation performance of an acquiring firm. Moreover, a key contribution of this study lies in drawing attention for a possible mechanism to increase the post-acquisition innovation performance of an acquiring firm, namely through pre-acquisition collaboration-for-innovation experience. This study was tested among 101 acquiring firms who are operating in the pharmaceutical industry. The collaboration-for-innovation experiences were measured on the base of solely alliances, solely acquisitions and a combination of these two. Since this combination has never been investigated before, this variable was especially interesting to measure.

Earlier research about the innovation performance of the post-acquisition position of a firm remains rather unclear (Vermeulen & Barkema, 2001; Ahuja & Katila, 2001; Haleblian & Finkelstein, 1999; Hayward, 2002; Lei, Hitt & Bettis, 1996), but with this research I tried to clarify this topic some more. De Man & Duysters (2005) looked at several former researches regarding, besides alliances, acquisitions and their effect on innovation performances. Measuring the output of the effects of acquisitions on the innovation performance, they mainly found negative results. Despite these results, pharmaceutical firms have continued to engage in acquisition activities, aiming at gaining a superior performance and learning how to deal with future uncertainties and increasingly intensifying competitive environments (Demirbag, 2007). My study tried to prove that having experience in any form of collaboration-for-innovation would help these acquisition activities to improve the innovation performance. Measuring the effects of experiences on the innovation performance of the acquiring firm however, resulted in rather unsatisfying findings.

of firm performances, let alone the post-acquisition innovation performance. This attempt to test a novel relationship has nevertheless yielded no significant results, even though it was theoretically argued that firms do benefit from a variety of different types of experiences (Brown & Eisenhardt, 1997).

Regarding the second hypothesis, which expected a positive effect of alliance experience on the innovation performance, my analysis produced some mixed results. On the one hand, this hypothesis was not supported since no positive significant relation was found according to the first regression analysis. On the other hand, I found that the acquiring firm’s firm size had a positive moderating effect on this relationship, insinuating that the positive effect of alliance experience on the innovation performance increases when the acquiring firm has a higher amount of total assets in the year of acquiring. This moderating effect of firm size can be related to the higher amount of investments that can be made to benefit greater volumes of knowledge transfer (Wiklund & Sheperd, 2009; Bresman et al., 1999). However, this moderating effect was not found for pre-acquisition acquisition experience. Explanation for this can be reflected on the inevitable struggles of the coordination-autonomy dilemma, a problem that does not occur while forming an alliance (Puranam et al., 2006). Complications that arise due to the coordination-autonomy dilemma can overrule the benefits from that particular acquisition.

In addition to that, previous research (Haleblian & Finkelstein, 1999; Zollo & Reuer, 2010; Hayward, 2002) emphasized that the degree of similarity of prior collaboration-for-innovation strategies influenced the acquisition performance. Due to the generalizability of the acquisition knowledge (Haleblian & Finkelstein, 1999), firms are in a condition to make wiser decisions regarding collaborations-for-innovation. This similarity is not tested in this study and it therefore could be the case that a sample selection was tested which encountered solely dissimilar acquisitions from prior strategic collaborations.

Furthermore, it is to say that this was a rather general research which also could have enhanced the insignificant results. For instance, criteria like the right partner selection, which is theoretically argued to make a big difference in subsequent performances (Arend, 2004), are not taken into account. However, the insignificant outcomes of the hypotheses do not necessarily state that there is no relationship between the different variables. It could be the case that the research was limited in such a way that the significant outcomes couldn’t be produced. In the next chapter, the limitations of this research and implications for future research will be explicated.

To conclude, there are no direct significant relationships found between pre-acquisition acquisition, alliance and combined experience, and the post-acquisition innovation performance of the acquiring firm. The relationship between alliance experience and the innovation performance however, is significant positively moderated by the firm size of the acquiring firm. In that perspective, alliance experience is somewhat outperforming acquisitions in its influence on the innovation performance.

Research limitations and future research

Like any other empirical study, my research has several limitations, of which some can lead to further researches. Remarkably I did not find any significant effects for my originally stated hypotheses. The fact that no evidence was found, does not necessarily mean that the relationship does not exist. The final data selection of my research may have restricted the output that would have shown other (significant) results when having a more extensive data sample.

The first main restriction was that only firms that at least acquired another firm or sub-unit in the year 2006 were selected. Even though this selection was necessary to obtain more concrete data on the experience and innovation performance for this rather small study, it deleted a lot of acquiring firms from the first sample selection. Checking the innovation performance for a firm that acquired a few years back was necessary to be certain of having information on the later performances of the firm. Unfortunately, this rather old data of the acquiring firm increased the risk of the acquiring firm being acquired itself. For this reason among others, the Orbis dataset could not always show complete and most up-to-date patent data for these firms. From the Orbis data set, I got information on the amount of patents as well as on the firm size, but it lacked in information for some companies. It is therefore recommended to use multiple sources in order to obtain a completer data sample.

The fact that the sample only contained acquiring firms that are operating in the Western world is no real limitation, since these countries give a good example of fast moving high-tech countries. However, it would be very interesting to include, or do a separate research on other parts of the world as well, for instance Asia. The Asian innovation developments are growing very fast and some countries are nowadays titled as worlds of high tech power (Porter et al., 2004). Of course, the criterion of the acquiring firm operating in the pharmaceutical industry in this study is by itself a limitation. Even though this industry selection is critical in ensuring internal validity, it also raises the issue of generalizability. Therefore, not only an expansion of the geographic areas that are participating is suggested, but also testing another industry. It needs to be taken into account, when doing a similar type of study in another industry, that the measurements fit the industry. Patents were the correct type of measurement to indicate the innovation performance, since this research focuses on the pharmaceutical industry (Cockburn et al. 1999). High-tech industries are known for their many patent requests, but lower tech industries find a better indication of the innovation performance with for instance the R&D expenditures.

give less concrete information than if you also have the abstract number. Making use of a larger sample would supplement the amount of data and make, when it does not concern exclusive categories, the use of dummy variables obsolete.

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