The impact of parallel integration on technological
capability building and on acquisition program
performance
V.T.K. Koski
S2965380
MSc BA Strategic Innovation Management
Supervisor
Dr. P.J.O. Kuusela
Co-assessor
Prof. dr. J. Surroca
June 22, 2020
Word count: 11831
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Abstract
This research contributes to the increasing amount of literature related to acquisition programs and studies how parallel company integration influences technological capability building via acquisition programs in high-tech acquisitions. The effect of parallel integration on acquisition program performance was studied using a dataset consisting of 237 acquisition deals done by large public companies located mostly in the United States and operating only in high-tech industries, such as in software and telecommunication industries between the years of 2000 and 2018. Against both of the hypotheses it was found that parallel integration has a positive influence on acquisition program performance and on technological capability building, while the acquirer’s larger size seems to have a negative moderating effect on the relationship between parallel integration and acquisition program performance. These findings could be explained by the fact that the high-tech acquirers have completed a significant amount of acquisitions beforehand, which has given them a possibility to improve their acquisition capabilities over time, which then allows them to better manage multiple parallel integrations simultaneously within an acquisition program. Previous literature has also found that large companies in strong governance countries, like in the United States seem to have lower acquisition performances, which could be explained by the possibility of hostile takeovers or in costs related to agency conflicts and managerial entrenchment, which is why larger acquirer size did not show positive moderating effect as hypothesized.
Keywords: Acquisition program, technological capabilities, absorptive capacity, dominant logic, parallel
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Introduction
Companies are known for a long time to acquire other companies for various reasons and the trend has not been declining over time, instead it seems that companies are now more than ever acquiring each other, as the value of worldwide merger and acquisition activity set a new record in 2006 with USD 3.79 trillion worth of transactions (Berman, 2007). Acquisitions have a unique potential to transform the acquirers and to contribute to their corporate growth and renewal, but also to renew their market positions at a pace not possible through internal development or to realize the benefits from combining assets and sharing capabilities not obtainable through partnerships or alliances (Haspeslagh & Jemison, 1991). The word ‘acquirer’ is used in this research to describe a company, which is acquiring other companies. Acquiring other companies can be related to reaching a strategic objectives and this phenomenon has spurred a new stream of research related to acquisition programs (Laamanen & Keil, 2008). Keil,
Laamanen and Mäkisalo (2012) define acquisition program as “a sequence of acquisitions initiated by the acquiring firm, with the intention of achieving a specific business goal or market position” (p.153), which shows the difference to the context of single acquisitions. For the remaining part of this study the words ‘firm’ and ‘company’ are used interchangeably.
Some acquisition programs can be highly clustered in time, such as when Oracle completed 20 acquisitions between 2005 and 2007 (Chatterjee, 2008), while some are less clustered, such as when Cisco and General Electric engaged in extensive acquisition programs in the 1990s (Laamanen & Keil, 2008). As defined that acquisition program is about multiple acquisitions to reach a certain objective, this business logic explains how the acquisitions will create shareholder value and it also reduces the chances of acquisition program failure (Chatterjee, 2008).
The reasons why Oracle, Cisco and General Electric acquired those firms can vary, but one of the reasons can be for their technological capabilities, as technological capabilities are valuable assets which are difficult for competitors to imitate (Coombs & Bierly, 2006). The impact of technological capability on firm performance has been widely studied (DeCarolis & Deeds, 1999) and there have been studies related to acquiring technological capabilities from other firms in the context of single acquisitions (Ranft & Lord, 2002; Ahuja & Katila, 2001), but not in the context of acquisition programs, which is the gap in the literature this research tries to fill.
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Cool, 1989). Meaning firms do not only look internally for new knowledge creation, instead they are also now relying on external sources as well. In-house development takes longer than acquiring new external knowledge and it also requires more personnel to be hired, such as research and development employees, which is why acquiring technological know-how and developing technological capabilities are
increasingly important motives for acquisitions (Granstrand & Sjölander, 1990).
This research contributes to the emerging stream of research in the acquisition program literature by focusing on how parallel integrations of acquired companies and organizational size of the acquirer influences the technological capability building process and the performance of an acquisition program. This research was done in the field of high-tech industries, such as in the software industry which is the connection point to building technological capabilities via acquisition programs. There is a gap in the literature for a research like this, as it has been studied how single acquisitions influence building
technological capabilities, but there is no prior research done in the context of acquisition programs. This research provides some managerial implications as well, as the outcomes of this study provides managers and other decision-makers insights about how to design their acquisition programs in a way which will provide the best possible outcomes, but also how to maximize the financial performance of the acquisition programs.
The outline for this research is as follows, the following chapter explains the theoretical background for this study where the main concepts are explained. Afterwards the hypotheses for this study are explained and motivated, which leads to the chapter about methods, where the data, data collection and analytical model are elaborated on. This is then followed by the results chapter, where the outcomes of the analytical model are provided. Then the discussion chapter includes paragraphs about implications to theory and practice, limitations of this study followed by ideas for future research. Lastly, there is a concluding chapter which provides the main findings of this research.
Theoretical background
Acquisition programs
As mentioned in the introduction, an acquisition program is defined as “a sequence of acquisitions
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how the acquisitions will create shareholder value and allows the firm to think through the processes needed to successfully carry out the acquisition program (Chatterjee, 2008).
When a firm acquires multiple companies over time, the company generates strategic momentum, which can last for several years (Amburgey & Miner, 1992). Haleblian and Finkelstein (1999) found that those firms that make multiple acquisitions within the same industry benefit from generalizing past acquisition knowledge and concluded that it is possible to apply this previous knowledge inappropriately, but these negative outcomes can be avoided if firms apply this prevous experience to a similar acquisition. Laamanen & Keil (2008) also found that the serial acquirers, which they define as acquirers which have completed at least 4 acquisitions in a 10 year period, accumulate their acquisition experiences over time and gradually grow their acquisition capacity, leading them to outperform acquirers that perform less acquisition or none at all. Other studies have found similar results that prior acquisition experience can positively influence acquisition performance (Fowler & Schmidt, 1989; Barkema, Bell & Pennings, 1996). However, it should be noted that acquisitions are complex and the learnings from one acquisition can not simply be transferred to another acquisition (Hayward, 2002).
Even when Cisco, Oracle and General Electric have had acquisition programs (Chatterjee, 2008;
Laamanen & Keil, 2008) it should be understood that not all serial acquirers have acquisition programs in place. For example, Microsoft has made multiple acquisitions almost every year since the 1990s and many of these acquisitions can be linked to the acquisition of a technology, but none of these Microsoft’s acquisitions could be matched to a proper acquisition program logic (Chatterjee, 2008).
Keil, Laamanen and Mäkisalo (2012) identify four different capabilities which are needed for firms to be successful in their acquisitions. These four capabilities are; (1) the capability to pace the acquisition program, (2) the capability to optimize the program scope, (3) the capability to acquire optimally sized and strategically, organizationally and culturally fit targets, (4) the capability to manage multiple
simultaneous integration processes, which is looked next in more detail. In this research, the word ‘target’ is used to describe a company, which is being acquired by another firm, the acquirer.
Acquisition rate and its variability are related to the first capability to pace an acquisition program and these are important characteristics of acquisition behaviour, as they reflect the temporal distribution of acquisitions in the context of acquisition programs (Laamanen & Keil, 2008). When the pace of
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case of Oracle in 2005 (Chatterjee, 2008), while some are less like Cisco and General Electric in the 1990s (Laamanen & Keil, 2008).
In regard to the second capability, acquisition scope reflects the degree of business relatedness between the acquiring firm and the target firms (Keil et al. 2012). Pehrsson (2006) found that managers see company relatedness based on five different aspects: product technology, general management skills, end customers, brand recognition and types of supply channels. The logic behind this is that the more similar industries are, the more they may share operating procedures, cultures, and dominant logic, while firms from unrelated industries are likely to have more differences along these dimensions (Prahalad and Bettis, 1986), thus broadening the scope of an acquisition program.
In regard to the third capability, the optimal size of a target is a firm-specific measure and it depends on the characteristics of the acquirer and on the logic of the acquisition program (Keil et. al, 2012).
Therefore, serial acquirers such as larger firms which have acquisition programs in place should avoid acquisitions which are too small for them, since in this case these acquisitions only take up resources without providing sufficient shareholder value for the company (Fuller, Netter & Stegemoller, 2002). The fourth capability is relevant to this research, as it deals with the ability to handle integration processes of the acquired companies. When it comes to acquisition programs, the firm’s ability to manage
integrations can be considered critical, as there is a larger number of acquisitions and because the value creation happens only after when the target companies’ capabilities are transferred to the acquirer (Haspeslagh & Jemison, 1991). As acquisition programs contain multiple acquisition deals, there may be multiple integration processes taking place simultaneously within the acquiring firm or even within a specific acquisition program. This can put pressure on the corporate-level acquisition team and if they fail to support the different business units in their processes, it may result in rapid escalation of complexity, which can then have negative consequences to the organization and to the performance of the acquisition program (Keil et al, 2012).
Even the acquirers with improved acquisition capabilities can make a poor purchase, but if these failed acquisitions are relatively minor the program can manage the mistake, but often the failed acquisitions are caused by trying to acquire a too large company in relation to the acquirer (Chatterjee, 2008). This shows the importance of the third acquisition capability to acquire optimally sized and strategically,
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To conclude, acquisition programs include multiple acquisition deals to reach a specified goal or objective and there are four capabilities firms need to become successful with their programs; the
capability to pace the acquisition program, the capability to optimize the program scope, the capability to acquire optimally sized and strategically, organizationally and culturally fit targets, the capability to manage multiple simultaneous integration processes (Keil et al, 2012).
Technological capabilities
Technological capability can be defined as the company’s ability to perform a relevant technical function or volume activity within the company, such as developing new products or processes (Teece, Pisano & Shuen, 1997). These technological capabilities are valuable assets, which are difficult for competitors to imitate (Coombs & Bierly, 2006), which is why obtaining technological know-how and developing technological capabilities are increasingly important motives for acquisitions (Granstrand & Sjölander, 1990). Therefore, knowledge transfer, which can be defined as the acquisition and utilization of new knowledge-based resources can be a key acquisition objective, which is achieved when the acquirer integrates technologies and capabilities from the target firm and commercializes them (Ranft & Lord, 2002).
Technological capabilities can be divided into three different key elements; strategic, internal and external capabilities as can be seen on the right in the table 1. Arnold and Thuriaux (1997) in their research indicate that the strategic level provides the intelligence or control mechanism, which allows the firm to manage its capabilities and exploit them via the market, while the internal capabilities relate to the
management team’s abilities and the third capability is concerned with managing the relationships between the firm and the outside resources it needs.
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The table 1 above shows that firms can develop technological capabilities internally, such as developing their employees or using external organisations such as universities to access their information resources or understanding via their strategic capabilities a need in their technological knowledge, which then can lead to the acquisition of a company to obtain those needed technological capabilities.
In high-tech industries such as in the software industry and in other knowledge-intensive industries highly skilled human capital may be one of the most sought-after strategic resources (Ranft & Lord, 2000). This specialized knowledge resides in individuals which are transferable between firms and because the rents generated by specialized knowledge are more likely to be appropriated by the individuals themselves rather than by the firm, human capital is increasingly important motive for acquisitions (Grant, 1996). In fact, in the industries the acquirers in the sample of this research operate are characterized by rapid innovation and technological complexity, this environment may not allow these firms to internally develop all the technologies and capabilities they need to stay competitive (Ranft & Lord, 2002). This further supports the claim that acquisitions are becoming more and more important for technological capability building next to internal development and other methods.
Acquiring technological capabilities does not come without challenges, for example the managers of the acquiring company need to consider the potential overlap in the knowledge bases of the acquirer and the target company’s knowledge bases, as Sears and Hoetker (2013) studied in their research. They concluded that acquiring a target company with much overlap with the acquirer’s knowledge base is unlikely to create value for the acquirer and such an acquisition may reduce the value of the acquirer’s pre-existing knowledge as well.
The knowledge-based literature also highlights how fragile and how difficult to manage knowledge-based resources may be, but it also shows how the characteristics that bring the greatest value are as likely to result in as many problems as benefits (Ranft & Lord, 2002). It should be noted that the critical source of competitive advantage is the knowledge integration rather than the knowledge itself, as this specialized knowledge will not in its own provide a base for sustainable advantage (Grant, 1996). This conclusion further supports the claim that the successful integration of the acquired companies is critical to realize the benefits of acquisitions by transferring the acquired capabilities to the acquiring organization, as it was concluded by Haspeslagh and Jemison (1991) in their study.
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to imitate (Coombs & Bierly, 2006). Because of this, they have become increasingly important motives for companies to acquire other, especially smaller startup companies with innovative technologies and highly skilled employees (Ranft & Lord, 2000), but the benefits of an acquisition are realized only after successful integration of knowledge (Grant, 1996).
Absorptive capacity
Absorptive capacity can be defined as the company’s ability to acquire, assimilate and to apply this newly acquired knowledge to commercial ends (Cohen & Levinthal, 1990) and it is the limit to the rate at which a firm can absorb scientific or technical information (Datta, 2011). This concept is of importance as studies within the strategic management literature have highlighted the important role of absorptive capacity in achieving higher firm performance (Wales, Parida & Patel, 2012). Zahra and George (2002) identify absorptive capacity having four different dimensions; acquisition, assimilation, transformation and exploitation and they also extend absorptive capacity to having two sub-sets, potential and realized absorptive capacity, which are explained next in more detail.
Potential absorptive capacity includes the acquisition and assimilation dimensions, where acquisition refers to the firm’s capability to identify and acquire externally generated knowledge that is critical to its operations (Zahra & George, 2002). For firm to recognize and value new external knowledge, first the acquiring firm must possess some amount of prior basic knowledge related to the external knowledge (Cohen & Levinthal, 1990). Assimilations stands for the company’s ability to understand the
information’s content and process it (Oehmichen, Schuster & Wolff, 2008) and this assimilation process is influenced by the firm’s tacit, firm-specific knowledge regarding its established systems for processing knowledge (Nelson & Winter, 1982).
Realized absorptive capacity includes the transformation and exploitation dimensions (Zahra & George, 2002) and it converts knowledge into products, services and technologies (Jansen, Van den Bosch & Volberda, 2005). The transformation dimension refers to the firm’s ability to develop and refine the routines that facilitate combining existing knowledge with the newly acquired knowledge, while exploitation is an organizational ability that allows firms to refine, extend and leverage existing
competencies or to create new ones by incorporating this acquired and transformed new knowledge into its operations (Zahra & George, 2002).
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they have and how the acquirer could commercialize this knowledge to their own benefit. The realized capacity deals with the acquirer’s routines to facilitate the combining of the existing and newly acquired knowledge, but also how to leverage existing competences or to create new ones by incorporating the acquired technological knowledge to the acquiring firm’s operations, which can also be described as a knowledge integration. Therefore, realized absorptive capacity is more relevant as this research studies how the parallel integration of companies influences the technological capability building process and the acquisition program’s performance and not how well a firm is able to identify the right target companies to acquire.
Dominant logic is a concept related to absorptive capacity and acquisitions, which can be defined as the firm’s preference for projects of a given type, size, or risk level and favors strategies dependent upon certain key success factors, stages of product life cycle or product market positions (Grant, 1988). While dominant logics differ between companies, the more similar the logics are between companies, the faster the acquiring firm can commercially apply the new knowledge (Lane & Lubatkin, 1998). Therefore, this dominant logic could have several implications to the integration processes of acquired knowledge. As Lane and Lubatkin (1998) concluded, that the more the dominant logics between acquiring firm and the target firm are similar, the faster the knowledge can be integrated and applied commercially, which then could allow the acquiring firm to pace the acquisitions in their acquisition program in a faster manner, which can potentially have either a positive or a negative impact on the performance of the acquisition program.
In short, absorptive capacity is the firm’s ability to acquire, assimilate and to apply new knowledge to commercial ends (Cohen & Levinthal, 1990). Realized absorptive capacity is more relevant for this research than potential capacity, as realized capacity includes the transformation and exploitation capabilities, which deal with the company’s ability to combine acquired and existing knowledge and to apply it to commercial ends (Zahra & George, 2002).
Hypotheses
Acquisition scholars have suggested that acquisitions involve two main components, namely the strategic and financial analysis which is initially done before the deal (Hitt, Harrison & Ireland, 2001) and the firm integration after the deal is completed, which is also called post-acquisition integration (Haspeslagh & Jemison, 1991). In the initial analysis of potential acquisition targets a major consideration is the
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factors can facilitate similar industry practices resulting more likely in a positive company integration (Finkelstein & Haleblian, 2002). However, the integration of companies can be considered more critial in acquisition programs as the value-creation of an acquisition happens only after an successful integration (Haspeslagh & Jemison, 1991) and the ability to manage these integrations is important due to higher number of acquisitions compared to single acquisition deals (Keil et al, 2012).
When firms engage in multiple acquisitions as in the context of acquisition programs, the overall
performance impact may not only be influenced by the characteristics of individual acquisitions but may also depend on the pattern of acquisitions (Laamanen & Keil, 2008). The managers of the acquiring company have to decide on this pattern in the design phase of the acquisition program, which is also one of the capabilities to manage acquisition programs, called the capability to pace the acquisition program (Keil et. al, 2012) as explained in the theory section.
Depending on how the acquirer paces their acquisitions, there might be overlap in the integrations of the target companies at the company-level, or even at the acquisition-program-level. The entire personnel of both companies should be involved in the integration process to ensure that the acquiring company can realize the benefits of the acquisition and to commercially apply the newly acquired knowledge (Haspeslagh & Jemison, 1991). In acquisition programs this ability to handle multiple integration processes can be considered being critical due to the larger number of acquisitions, which puts heavy-strain on the corporate level acquisition team and if this team fails to support the integration processes, it can lead to escalation of complexity of the target company integrations (Keil et al, 2012). The ability to handle integrations is also critical as any acquisition can look good on paper, but the value creation happens only after the acquisition when capabilities are transferred to the acquiring company and when people from both organizations collaborate to realize the potential benefits of the acquisition (Haspeslagh & Jemison, 1991).
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As all firms have limited resources (Løwendahl, 2009) and parallel integration of acquired companies can require more resources than single integrations, it can be considered putting heavier strain on the
corporate-level acquisition team, which then can lead to different problems for the company integration (Keil et al, 2012) lowering the performance of the acquisition program. As in high-tech industries highly skilled human capital is increasingly important motive for acquisitions (Ranft & Lord, 2000) and it resides in individuals (Grant, 1996), the successful integration of acquired companies can be considered being critical in the context of high-tech acquisition programs to realize the benefits of the acquisitions. With this logic it is hypothesized that parallel integration of target companies leads to lower acquisition program performance, as it takes more resources from the acquirer’s side to manage these integrations. Furthermore, the higher the number of parallel integrations taking place, the more resources are needed and while the acquirer’s resources are limited, this higher number of parallel integrations leads to even lower acquisition performance. Therefore, the first hypotheses of this research is:
Hypotheses 1: Parallel integration of acquired companies will negatively influence the technological capability building process, leading to lower performance of acquisition programs.
When acquirers are large multinationals, they have more organizational resources available such as higher number of employees and more monetary resources compared to smaller companies. These smaller firms have less managerial services, meaning they are often lacking in managerial power and thus cannot expand as fast as larger firms can (Penrose & Pitelis, 2009). As larger companies have more resources available, they have the possibility to assign specific employees to work on acquisitions and these dedicated teams can act as systemic repositories of knowledge of previous acquisition experiences, while smaller companies face the trade-off of whether to focus on their managers’ time on growing the existing business or to work on acquisitions (Laamanen & Keil, 2008). Therefore, larger companies have
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Hypotheses 2: Organizational size positively moderates the negative effect of parallel integration on technological capability building process and on the performance of acquisition programs.
Methods
Data and sample
The data for this research contains a dataset of acquisitions done by large multinational companies, which are mostly located in the United States and operate in high-tech industries such as software,
telecommunications and computer hardware. The acquisitions were gathered using the SDC Platinum database and the dataset contains acquisition deals between the years of 2000 - 2018 done by these high-tech acquirers. The acquirers, which are public firms, have been members of S&P 1500 anytime since 1992 and every single acquisition deal contains several different variables of information such as the individual deal number, date of announcement, date of completion, ultimate acquirer parent, acquirer name, target name and target location.
The data was extended by identifying if an individual acquisition deal was part of an acquisition program set by the acquiring company. For every single acquisition Nexis Uni was searched for a relevant press-releases to find relevant information about the rationales of the acquisition from the acquirer’s and target’s perspectives. After researching all the acquisition deals done by a certain acquirer, it was identified whether a single acquisition was part of a program or not. This was done by looking at all the deal rationales and identifying similarities in multiple deals, such as when multiple deals were related to the improvement of the acquirer's certain product. In this case these acquisition deals would then be matched as being part of the same acquisition program. This process was repeated for every single acquisition in the dataset in order to identify all the acquisition programs of the acquirers and to remove certain acquisitions which were not part of a program, as individual acquisitions which are not part of a program are not relevant for this research.
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verification and prototyping category. After researching a second deal from this same acquirer with the same method as explained above, it was found that this acquirer had acquired a supplier of emulation platforms for systems on chips verification and the rationale for this acquisition was to expand the acquirer’s investments in verification to bring new solutions to their customers. Therefore, this second deal was also categorized in belonging to the same verification and prototyping category as the previous deal, making them belong to the same acquisition program of this one acquirer.
The dataset was also extended by calculating the cumulative abnormal returns for every single acquisition done by the acquirers and the database used to gather this information was CapitallQ (WRDS). Moreover, the dataset was also extended by adding the acquirers’ annual sales for every acquirer within the dataset in order to measure the organizational size for hypotheses 2. This information was gathered using the Compustat database and it was merged to the original dataset such as the information related to cumulative abnormal returns was.
After removing all the acquisitions which were not part of acquisition programs and all other acquisitions where enough information was not available for the measurements, the ultimate sample used for this research contains in total of 237 acquisition deals done by public multinational companies operating in high-tech industries.
This can be considered as a good setting to study the impact of parallel integration on technological capability building via acquisition programs, as the acquirers have been members of the S&P 1500, meaning they are all public companies with enough information available to categorize acquisition deals to acquisition programs and the information available such as sales from annual reports can be considered being accurate. Moreover, as the acquirer’s operate in high-tech industries and the deals have been researched with this accurate information to identify the individual acquisition programs, this setting gives a good starting point to research both of the hypotheses.
Operationalizations
Dependent variable. The dependent variable for this research follows the trend in the acquisition
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returns is in total of 250 days, starting from 295 days before each event to 45 days after and to determine the influence of an event on a firm, the abnormal returns are averaged over an event window. The event window for this research also follows the work of McNamara, Halebillian and Dykes (2008) where the event windows is medium term (more than 10 days in total) and more specifically the cumulative abnormal returns for the event window were calculated 5 trading days before to 15 trading days after the announcement of the acquisition.
Independent variables. The independent variables for this research consist of parallel integration
and organizational size variables. Parallel integration is considered taking place when two or more acquisitions are being integrated in the same time to the acquiring company. Hayward (2002) found that on average there are benefits from acquisition intervals of 6 to 12 months in different industries, in which high-tech industry as telecommunications was included, so this timeline can be assumed to be suitable for this research as well, but it was also concluded that optimal intervals are shorter when target companies are smaller. Hayward (2002) also concluded in the study that the time elapsed between two different acquisitions has an inverted u-shape and the point of inflection of the inverted U-shaped curve was at around 220 days before the announcement of the acquisition. Therefore, to simplify the measurement of the parallel integration the timeframe of 7 months is considered to be the integration period for each acquisition in this research, as it also supports the finding that smaller acquired target companies require shorter acquisition intervals and because the larger acquirers in this dataset have acquired smaller companies than themselves. The interval of 7 months is calculated in the following way; for simplicity each month is considered having 31 days and as 220 days is divided by 31 it gives the result of 7.096, which is then rounded to 7.00 months.
The second independent variable for this research is the organizational size and the measurement of it follows the work of Amburgey and Miner (1992), where they measured this variable by using the logarithm of acquirer’s annual sales from the previous year before an specific event and logarithm was used as sales figures can be highly skewed between companies. For this research the event is considered taking place when a specific acquisition is announced by the acquirer, therefore the organizational size for that occasion is calculated from the annual sales of the previous year before the acquisition announcement date.
Control variables. For this research there are also some control variables included for the
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which is then reflected in the size of the specific acquisition deal in monetary terms. The target company size is measured as the logarithm of the value of the transaction in monetary terms following the work of Sears and Hoetker (2014), where they also controlled for the monetary size of the acquisition.
The second control variable is related to the acquirer and it measures the acquirers’ experience in
acquiring other companies, which is then a proxy for the firm’s acquisition capability (Laamanen & Keil, 2008). This variable is measured in the number of acquisitions completed beforehand at a company level which follows the works of (Fowler & Schmidt, 1989; Haleblian & Finkelstein, 1999).
Third control variable relates to the location of both companies and it is a dummy variable that measures whether an individual acquisition deal was an international deal taking place over different countries, which has values between 0 and 1, where 1 represents that the deal is international.
The fourth and last control variable is related to the deal itself, which is if the value of the deal in
monetary terms has been made public. This variable is also a dummy variable with values between 0 and 1, where 1 represents that the price of the deal has been made public.
Analytical model
To test the hypotheses first descriptive statistics was conducted to get an overview of the sample and the measures. Then the multicollinearity of independent variables was checked to see if there is a correlation between them and if it is possible to continue the research with the selected variables. Then the relation between the dependent variable and independent variables was tested using OLS regression model. To confirm the findings of the main analysis, a robust regression was also conducted by modifying the parallel integration variable and removing the outliers in the sample by using Cook’s distance. Then the possibility of U-shaped relationship between the cumulative abnormal returns and parallel integration was also tested.
Results
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in this regression model are not correlated and allows the continuation of this research (Alauddin & Nghiemb, 2010).
Variables Obs Mean Std. Dev. Min Max VIF 1/VIF
Dependent: car 1,552 .0011219 .0475387 -.5180319 .2273078 Independent: sumoverlap 689 1.129173 1.440437 0 7 1.10 0.905412 orgsize_log 1,834 8.111454 2.262858 -.9623347 12.97971 2.33 0.429259 Control: Targetsize_log 237 4.927481 1.692099 .8329091 9.957094 1.15 0.872217 CROSS_n 689 1.2627 .4404203 1 2 1.04 0.959002 dealsequence 689 82.25399 69.81846 1 281 2.37 0.421408 price_disclosure 689 .3383164 .4733423 0 1 1.01 0.991609
Table 2: Descriptive statistics and multicollinearity
In the main analysis, which is the regression model 1 below in table 3, the parallel integration variable counts the number of parallel integrations taking place per acquisition program for each acquisition deal. For hypotheses 1 it was hypothesized that parallel integrations require more resources from the acquirer, leading to lower ability to integrate the target companies, which then decreases the performance of the acquisition program as a whole.
The results show that this model is statistically significant as the F-test gives a value of 0.0061, which is smaller than 0.1, meaning this model has some explanatory power. The value of R-squared is 0.0708, meaning that the independent variables account for 7,08% variation in the dependent variable, which in this case is the cumulative abnormal returns. Looking more closely at the results, the parallel integration variable is significant in relation to the cumulative abnormal returns and surprisingly it has a positive direction, meaning that parallel integration would increase the cumulative abnormal returns which is against the hypotheses. Therefore, there is no support for the hypotheses 1.
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the relationship, reducing the negative effects of parallel integration on cumulative abnormal returns. Therefore, there is no support for hypotheses 2 either in this main analysis.
VARIABLES Model 1 Model 2 Independent variables: parallel_integration 0.0757** (0.0340) sumoverlap 0.0389*** (0.0117) orgsize_log 0.00322 0.00337 (0.00313) (0.00326) c.sumoverlap#c.orgsize_log -0.00393*** (0.00118) c.parallel_integration#c.orgsize_log -0.00816** (0.00389) Control variables: targetsize_log -0.00612** -0.00407** (0.00275) (0.00173) CROSS_n -0.00837 -0.00581 (0.00680) (0.00722) dealsequence 0.000145** 6.24e-05 (5.49e-05) (8.60e-05) price_disclosure 0.0167** 0.0207 (0.00815) (0.0219) Constant -0.0168 -0.0250 (0.0297) (0.0369) Observations 237 237 R-squared 0.071 0.055 *** p<0.01, ** p<0.05, * p<0.1
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Looking at the control variables, only the target size, acquirer’s acquisition experience and the price disclosure variables have significant impact on the cumulative abnormal returns. More specifically, target company size negatively influences the cumulative abnormal returns while the deal sequence and price disclosure variables positively influence the cumulative abnormal returns. The results for the international deal variable are insignificant in relation to the cumulative abnormal returns.
Looking at the predictive margins of the parallel integration variable on the right in the figure 1, the prediction shows that it has a positive influence on the cumulative abnormal returns. This closer look at this relationship is an interesting finding, as it was hypothesized that parallel integration would have a negative influence on the returns. However, it seems like parallel integrations has a positive influence on the acquisition program
performance, but when the number of parallel integrations reach 6 and 7, the acquisition
program performance starts to decline. Figure 1: Predictive margins for parallel integration
Robustness checks
For robustness checks the parallel integration variable was changed to a dummy variable, that measures whether the parallel integration of target companies takes place or not with values of 0 and 1, where 1 represents parallel integration taking place. This differs from the previous regression model, where the parallel integration variable was a count variable, which measured the number of parallel integrations taking place simultaneously. Therefore, now the variable is slightly different and is used for the robustness check to confirm the findings of the previous regression analysis.
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order to make new regression without them. The results of this robustness regression can be seen above in table 3 as the regression model 2.
The F-test shows significance for this model as the value of 0.0704 is smaller than 0.1. Therefore, this model has some explanatory power. The results of this model are similar to the previous regression, as the variable parallel integration has a positive direction and it is significant with a p-value of 0.027, which is smaller than 0.1. For hypotheses 1, it was proposed that parallel integration negatively influences the acquisition program performance. Based on this robustness regression there is no support for hypotheses 1, which is the same result as in the main regression analysis.
For hypotheses 2, that organizational size moderates the relationship between parallel integration and acquisition program performance, the results show again a negative direction as in the previous
regression. The results are also significant for this variable with a p-value of 0.037, which is smaller than 0.1. Therefore, there is no support for hypotheses 2 either in this robustness check, as the results show a significant and negative influence.
Looking at the controlling variables, only the results for target size are significant and show negative influence on cumulative abnormal returns. The results for acquisition experience and for price disclosure are not significant anymore, as they were in the main analysis.
Looking at the predictive margins for the parallel integration variable can be seen on the right in the figure 3. It shows that when there is a parallel integration taking place, it has a larger positive influence on the acquisition program performance, compared to a situation when there is no parallel integration taking place. The results of this are against the hypotheses that parallel integration would
negatively influence the cumulative Figure 3: Predictive margins for parallel integration
abnormal returns, which is an interesting
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One possible explanation for the relationship between parallel integration and acquisition program performance is that they have either a U or an inverted U-shaped relationship. In the case of technology acquisitions as studied in this research, when a firm acquires another high-tech firm there can be an overlap in their technological knowledge bases. Any given increase over a low level of target
technological overlap can improve the acquirer’s absorptive capacity in a way it increases the acquirer’s ability to create value from the target’s capabilities by more than the increase in knowledge redundancy decreases it, which is reversed when starting from a high technological base resulting in a U-shaped relationship (Sears & Hoetker, 2014).
Therefore, as an additional robustness check the possibility of a U-shaped relationship between acquisition program performance and parallel integration was also tested, which follows the method of other studies in the acquisition program literature such as in the study of Ahuja and Katila (2001). For this test the count variable of parallel integration was used which calculates the number of parallel
integrations taking place within acquisition programs per acquisition deal, which has values between 0 and 7 instead of the dummy variable, which was used for the robust regression model. The results of this test are explained in the following paragraph.
The results of the test show that the interval has a lower bound at 0 and upper bound at 7 with a slope at lower bound of .0392445 and upper bound of .0334765. It is concluded that the vertex of the parabola is not on the interval, because the results show that there is an extremum outside interval leading to a trivial failure to reject the hypotheses 0, which measures whether relationship is monotone or U-shaped.
Therefore, according to this test there is no U-shaped relationship between the cumulative abnormal returns and parallel integration.
Discussion
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optimal number of firms to acquire, how to time individual acquisitions and what type of firms to acquire (Laamanen & Keil, 2008), which could help to explain the findings of this research.
First, it was hypothesized that parallel integration of target companies would have a negative influence on the technological capability building via acquisition programs and because of the limited resources of acquirers, this would then eventually lead to lower acquisition program performance. However, the main regression analysis and the robust analysis show otherwise and the hypotheses 1 is not supported. In fact, the results for parallel integration are significant with a positive sign, meaning that when two or more target companies within an acquisition program are integrated simultaneously, it would be beneficial for the acquisition program performance. This is a surprising finding, as using the argument of acquirer’s limited resources it could be logical to find that when integrating two or more firms the acquirer has to spend more efforts in the coordination of the integrations and leaving less resources left for other acquisition program tasks, which then would lower the acquisition program performance.
There are some potential explanations for this finding that parallel integration has a positive influence on the acquisition program performance. As the acquirers in this dataset are all multinational companies, which have been using acquisitions to grow for even decades and have acquired even tens of companies, they have potentially developed acquisition program capabilities over time and improved their realized absorptive capacity, so they know what types of firms to acquire, how to pace the acquisitions and how to integrate companies for the best acquisition program performance. It is also possible that they might undertake similar successful acquisitions, which relates to the concept of dominat logic, and with this knowledge from previous acquisitions they are able to manage multiple integrations simultaneously. Another explanation for this finding is the choice of the dependent variable, cumulative abnormal returns, as it measures the market reaction to the acquisition. It could be possible that investors do not
acknowledge if an acquisition program exists or if the integrations overlap, as they might use other aspects or measurables in their decision-making on how to value a certain firm, which is one of the limitations of this research and it is discussed in the limitations chapter.
However, when the number of parallel integrations reach 6 or 7, it starts to negatively influence the program performance. The acquirers who integrated 6 or 7 companies simultaneously are very few, as parallel integration has a mean of about 1,13 integrations per acquisition program. It could be possible, that as the acquirers are all large multinationals they have enough resources to manage multiple
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over time to manage the integration of multiple target companies simultaneously. When they try to integrate 6 or more companies simultaneously they are over the limits of their integration capabilities resulting in the negative influence on the acquisition program performance. It is likely that the number of parallel integrations when acquisition program’s performance starts to decline differs per company, but the main idea holds that after a certain amount of parallel integrations the acquisition program
performance starts to decline and it is up to each company to find their integration limits.
The possibility of an U-shaped relationship was also considered between the parallel integration and cumulative abnormal returns. However, the results of this analysis show that there is no inverted U-shaped or U-shape relationship.
For the second hypotheses it was proposed that larger organizational size of the acquirer moderates the negative relationship between parallel integration and the acquisition program performance, which follows the logic that the larger the acquirer, the better they are able to manage the resource requirements of parallel integrations. The main analysis shows significant and negative results for this hypotheses and so does the robust regression analysis. Therefore, the hypotheses 2 is not supported either.
Previous studies can provide some explanations for this finding; for example, Humphery-Jenner and Powell (2014) found that larger acquiring firms tend to earn lower acquisition returns than do smaller acquiring firms, especially in strong governance countries. They hypothesized that this is due to agency conflicts related to managerial entrenchment, as the benefits of large size in weak governance countries may partially off-set agency-related costs. There is also other prior literature which has found similar results, that larger acquirers tend to earn lower acquisition returns in strong governance countries (Moeller, Schlingemann & Stulz, 2004). These findings are relevant, as the acquirers in this dataset are mostly from the United States, which is one of the mostly highly rated countries on a range of governance metrics, including the International Country Risk Guide (ICRG) and the World Rank (WR) (Humphery-Jenner & Powell, 2014).
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might not be the most beneficial for the company in the long-term, which could potentially cause damage to the company, leading to value destruction and to lower acquisition program performance. How likely hostile takeovers are going to take place in the context of acquisition programs is not exactly clear, as there is a gap in the literature for this kind of research. However, as hostile takeovers started to become more popular and acceptable since the 1980s in the United States and now all over the world (Gaughan, 2013), it is possible to assume that hostile takeovers do also take place in the context of acquisition programs.
Looking at the controlling variables, in the main analysis the size of the target company, acquirer’s acquisition experience and price disclosure have significant impact on the cumulative abnormal returns. The size of the target company has a significant negative influence, which could be explained that when a firm acquires a more established and larger company, this company may not have such innovative
technology as startups tend to have, which then leads to lower performance.
In the main analysis the acquisition experience has a significant positive influence on the acquirer’s cumulative abnormal returns, which may be the results of improved acquisition capabilities or improved realized absorptive capacity, as the company has been able to acquire other companies over time. Therefore, they have been able to improve these capabilities, leading to better acquisitions and their integrations.
The price disclosure variable has also a positive and significant impact on the cumulative abnormal returns, which potentially could be explained that when investors see the value of the acquisition deal, they can decide using their own knowledge and information available whether the deal was too high-priced, lower-priced or somewhere between, which then could potentially show investors the company’s ability to value different deals which reflects the acquirer’s acquisition capabilities. If the price is disclosed and investors see it as a suitable price in their opinion, they might consider it as a good acquisition, which is then reflected in the market’s reaction to positively influencing the stock returns of the acquirer.
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instead of larger more established companies, as focusing on smaller companies positively influences the acquisition program performance.
Implications to theory
This research has several implications to theory, first of all there was a gap in the literature for this type of study, which shows that this research is significant and adds to the increasing amount of acquisition program literature. After analyzing 237 acquisition deals done by large public acquirers in high-tech industries, this research found that parallel integration does positively impact the acquisition program performance, even though it could make sense that parallel integration negatively influences acquisition program performance due to acquirer’s limited resources. This could be explained by the concept of dominant logic, acquisition capabilities and experiences or with the acquirer’s improved realized absorptive capacity, as the acquirers in this sample have completed multiple acquisition beforehand. This research also found that acquirer’s size does not positively moderate the relationship between parallel integration and acquisition program performance, instead it negatively moderates this
relationship. This was also a surprising finding, as logically it could make sense that when the acquirer has more resources available, it is better able to handle the increased resource demands needed for parallel integration of companies.
There is also a third implication from this research to theory, it was found that the size of the target company significantly impacts the acquisition program performance and it was significant in both the main and robust analysis, meaning it is more beneficial for the acquisition program’s performance to acquire smaller companies such as startups.
Implications to practice
This research has also several implications to practice. For example when the employees who are tasked with acquisitions are designing an acquisition program, they can use this research as a source of
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It also seems like larger multinational acquirers in high-tech industries can manage multiple parallel integrations within an acquisition program, but then after a certain point the amount of parallel integrations starts to negatively influence the acquisition program’s performance.
In this study the results show that when there are 6 or more parallel integrations, it starts to negatively impact the acquisition program performance, but it is possible that in reality this number differs per acquirer. Based on these results, it seems like even larger high-tech acquirers do not have enough resources to facilitate any number of parallel integrations within an acquisition program. Managers who are designing acquisition programs should keep in mind that after acquirer’s integration capabilities are exceeded, because there are too many parallel integrations taking place for the acquirer, it starts to negatively influence the acquisition program’s performance.
Regarding the hypotheses 2, when the acquirers are large companies this seems to negatively moderate the relationship between parallel integration and acquisition program performance. This could be explained by the possibility of managers in larger companies acting in their own interest and deciding to acquire companies which may not bring the most benefits for the company over a long period of time, but benefit the managers in the short-term, so this is something the owners of these companies should keep in mind.
This research also showed that it is beneficial to acquire smaller sized companies, such as startups, as this seems to have a positive impact on the acquisition program performance. These are the findings of this research that managers can use for their benefit when designing an acquisition program for the best performance in the context of high-tech acquisitions.
Limitations
This research has some limitations, starting with the assumption that all acquired target companies are integrated as in reality sometimes these acquired companies are not integrated at all to the acquirer or are only partially integrated. The timeframe for integration also has some limitations as 7 months was used for all acquisition, even though the time to integrate a target company can take much longer and can vary between acquisitions.
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not consider for example the cultural differences based on locations within the acquirers or the target companies, even though they can influence the integration process and therefore the performance of the acquisition program.
Moreover, this research also did not consider the aim of the acquisition program, whether it was related to improving a specific product category of the acquirer or if the program was related to an expansion. It is possible that the goal of the acquisition program influences the program’s performance and it could also explain the differences in performances between acquisition programs of an acquirer.
There are also some limitations to the measurements, as acquisition program performance was measured using the market’s reaction to the specific acquisition deal, which then does not clearly reflect how the acquirer was able to integrate the technological knowledge acquired and if it led to improved performance over time, such as in the following years.
Future research
To fully answer the research questions whether parallel integration leads to lower acquisition program performance, more comprehensive research needs to be conducted. As the limitations of this study are related to the sample size, a larger sample size covering more acquisition deals covering more countries and continents would be appropriate to confirm the findings of this research. Future research could also include a different timeframe for the integration instead of the 7 months, which was used in this research to see if longer or shorter integration periods would create a difference in the results.
Future research could also control for several different variables, such as what was the goal of the acquisition program, if it was related to market expansion or to product development and to see whether this would create a difference with the results of this research. It could be also an option to use deals in the dataset only from acquirers which are not located in strong governance countries like in the United States or United Kingdom. This way it would be interesting to see whether the results differ between acquirers from strong and weak governance countries.
For the dependent variable it could be an option to consider some other measurement for the cumulative abnormal returns, as the way it was measured in this research reflects the market reaction to the
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the returns of a certain time period afterwards, as this could reflect how well the acquirer has been able to integrate the companies, develop technological capabilities and whether it has increased the acquirer’s performance over time.
With these improvements for future studies, the effect of parallel integration on technological capability building via acquisition programs could be more comprehensively identified and the type relationship proven accurately.
Conclusion
This research studied the effect of parallel company integration on technological capability building via acquisition programs and how the acquirer’s organizational size moderates this relationship. The dataset for this research included acquisition deals done by large acquirers located mostly in the United States and operating in the high-tech industries such as software and telecommunications during the years of 2000 to 2018. Eventually, the sample used consisted of in total of 237 acquisition deals done by these large acquirers, which then the analyses were based on.
It was hypothesized that parallel integration would lower the performance of an acquisition program, but the main analysis and robust analysis showed different results. In fact, the results show that parallel integration has a positive influence on the acquisition program performance. This finding could be explained with the fact that the acquirers in this dataset are large multinationals which have been completing acquisitions for even decades to grow and to reach certain objectives. Therefore, they have potentially been able to develop their acquisition capabilities, to improve their realized absorptive capacity over a long period of time and have learned to acquire the right companies to reach their desired objectives or are acquiring similar companies as beforehand via dominant logic, which then helps them to manage these multiple integrations.
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It was also hypothesized that the acquirer's organizational size would positively moderate the relationship between parallel integration and acquisition program performance. However, the analyses show different results that this relationship is negative. Previous research helps to explain this finding, such as Moeller, Schlingemann & Stulz (2004), as they have found that larger acquiring firms tend to earn lower
acquisition returns than do smaller acquiring firms. Humphery-Jenner and Powell (2014) found similar results that this happens especially in strong governance countries, such as in the United States where most of the acquirers in this dataset are located. They hypothesized that this is due to agency conflicts related to managerial entrenchment, as the benefits of large size in weak governance countries may partially off-set agency-related costs such as monitoring the managers of the company.
Humphrey-Jenner and Powell (2014) also found that large acquirers in strong governance countries may participate in hostile takeovers, which has the potential to lower the returns of the acquisitions. This previous literature could help in explaining the findings of this research, as these agency costs and hostile takeovers are more likely to take place for larger acquirers than for smaller ones, which then could explain why acquirer’s size has a negative moderating effect on parallel integration and acquisition program performance.
To conclude, parallel integration seems to have a positive impact on acquisition program performance and on technological capability building, while the acquirer’s size seems to negatively moderate this
relationship. Based on the results of this study, the acquirers have the capabilities to manage multiple parallel integrations, but there seems to be a limit to the number of parallel integrations after which the acquisition program’s performance starts to decline. These findings could be explained by the fact that the acquirers in the sample are serial acquirers and have completed multiple acquisitions beforehand, which has given them an opportunity to improve their acquisition capabilities or realized absorptive capacitities or via dominant logic they are using previous acquisition experiences to their benefit.
Acquirer’s size does not positively moderate the relationship between parallel integration and acquisition program performance, as it could be that large companies are more likely to participate in hostile
takeovers or there are agency conflicts and costs related to managerial entrenchment, lowering the acquisition program’s performance.
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