THE INFLUENCE OF ACQUISITION EXPERIENCE ON ACQUISITION
PROGRAM PERFORMANCE
David Bos S2812150
MSc BA Strategic Innovation Management January 20, 2020 Supervisor Dr. P.J.O. Kuusela Co-assessor Prof. dr. J.D.R. Oehmichen Abstract
How firms learn from prior acquisition experience is still ambiguous. The organizational learning perspective is used to examine how accumulated prior experience of internal acquisitions, acquisition programs and experience of other firms may provide opportunities to improve acquisition program performance. Based on an analysis of six large acquiring ICT firms in the United States from 1997 to 2015, press releases were used to categorize 441 acquisitions to 32 acquisition programs. This study is the first to categorize a considerable amount of acquisitions to acquisition programs and analyze such specific acquisition programs. Using cumulative abnormal returns, results show that a firm’s acquisition program performance is positively influenced by internal acquisition experience. In other words, acquisition programs become more effective if they have more experience from acquisitions that are not part of an acquisition program. These findings contribute to an improved understanding of acquisition programs, prior acquisition experience, acquisition program capability and acquisition program performance.
Key words: Acquisition program, acquisition experience, acquisition program capability, acquisition program performance, organizational learning
INTRODUCTION
Google acquired Looker in 2019 for 2.6 billion to focus on growing its cloud offerings. Google launched its cloud services in 2008 and yet they are still spending billions to acquire new targets to grow its market share (Chan, 2019). To achieve such strategic goals, firms are engaging in multiple acquisitions to exploit synergies to achieve corporate strategies (Laamanen & Keil, 2008). Prior literature suggests that firms have the opportunity to learn from their acquisition experience to enhance the performance of future acquisitions (Barkema & Schijven, 2008; Hayward, 2002). To illustrate, findings support that prior acquisition experience increases acquisition performance which implies that serial acquirers have the potential to learn from acquisitions (Aktas et al., 2009; Henningsson, 2015; Luo, 2005). However, prior acquisition experience can also be negatively related to acquisition performance (e.g., Aktas et al., 2009; Fuller, Netter, & Stegemoller, 2002; Kusewitt, 1985; Tuch & O’Sullivan, 2007; Kengelbach et al., 2012). Most of these studies have proven that cumulative abnormal returns (CARs) decrease after multiple acquisitions, implying negative learning effects. The field is inconsistent as there is currently no clear understanding when and how firms learn from their acquisition experience (e.g. Aktas, de Bodt, & Roll, 2009; Barkema & Schijven, 2008; Haleblian & Finkelstein, 1999; Hayward, 2002). However, if serial acquisitions are part of acquisition programs, firms most likely will increase their acquisition performance (Chatterjee, 2009). The success of acquisition programs centers around the concept of clearly defined boundaries to acquire targets for acquisition programs (Chatterjee, 2009). Therefore, this study proposes that acquisition programs may be a solution to this learning problem.
Acquisitions programs are serial acquisitions intending to reach a specific business goal or market position. The distinction between the two concepts lies in the achievement of overarching business goals. Defining strategic goals for acquisition programs might be difficult for Managers and CEO’s as they have to translate objectives into specific strategic- and investment criteria for future acquisitions (Marks & Mirvis, 2001). Moreover, effectively managing acquisition programs requires managers and CEO’s to learn from each completed deal since they are crucially involved in executing acquisition programs (Aktas et al., 2009). Poorly executed acquisition programs can cause internal problems such as loss of control due to managerial complexities, and cultural clashes and tensions (Ravenscraft & Scherer, 1989; Vermeulen & Barkema, 2001). By way of contrast, correctly executed acquisition programs can revitalize firms by enabling synergies, growth of earnings and long-term survival (Shleifer & Vishny, 2003; Vermeulen & Barkema, 2001).
However, executing acquisition programs may be challenging. Serial acquirers are exposed to acquisition challenges such as identifying targets, price negotiation and target integration (Keil et al., 2012). However, acquisition programs are even further exposed to acquisition challenges. The ability to carry out acquisition programs is a higher-level capability than carrying out serial acquisitions as it requires coordination across all acquisitions within an acquisition program (Keil et al., 2012). Acquisition program capabilities can repeatedly be leveraged to improve the productivity of acquired companies (Chatterjee, 2009). Therefore, knowing how to build acquisition program capability is crucial to manage acquisition programs and increases acquisition performance. Building acquisition program capabilities requires firms to learn from their prior acquisition experience. This study emphasizes the importance of prior acquisition experience such as experience from acquisitions outside acquisition programs, experience from acquisitions within acquisition programs and experience from acquisitions of other firms. This research adds to the organizational learning perspective by examining how learning from experience influences acquisition program performance. The findings of this thesis contribute to an improved understanding of acquisition programs, acquisition experience, acquisition program capability and acquisition program performance.
THEORETICAL BACKGROUND Acquisitions, serial acquisitions and acquisition programs
are “sequences of acquisitions initiated by an acquiring firm, with the intention of achieving a specific business goal or market position” (Keil et al., 2012, p. 153) and “driven by a core business logic often with significant interdependencies” (Chatterjee, 2009, p. 138).
Sequences of acquisitions and interdependencies suggest that multiple acquisitions are being carried out in patterns that interact with each other. Sequences of acquisitions depend on characteristics such as acquisition rate, variability of the acquisition rate and acquisition timing (Iyer & Miller, 2008; Kusewitt, 1985; Laamanen & Keil, 2008). Studies show that these characteristics influence learning capabilities affecting acquirer performance (Finkelstein & Haleblian, 2002; Fowler & Schmidt, 1989; Hayward, 2002; Hitt, Harrison, Ireland, & Best, 1998). Firms need sufficient time to learn from acquisition experience to build acquisition capabilities (Zollo & Winter, 2002). This interaction will be emphasized in the organizational learning section.
Acquisition programs aim at achieving specific goals or market positions (Laamanen & Keil, 2008) that follows a core business logic (Chatterjee, 2009). Rather than setting goals for single acquisitions, serial acquirers are defining overarching goals to pursue their strategic goals for their acquisition programs. Acquisition goals may be “to achieve greater market power, to overcome barriers to entry, to enter new markets quickly and to acquire new knowledge and resources” (Vermeulen & Barkema, 2001, p.457). Moreover, clarified business logic defines how an acquisition program creates shareholder value. Therefore, acquirers will think through the processes required to successfully carry out acquisition programs and reduce the chance of failure (Chatterjee, 2009). As a result, acquisitions within acquisition programs may be more similar due to shared strategic goals. The importance of acquisition similarity in acquisition programs will be emphasized in the paragraph of balancing exploitation and exploration activities.
A firms’ top management has a major role in carrying out acquisition programs as they set strategic goals and clarify a core business logic. Moreover, managers have to keep track of underlying logic for acquisition programs because “an acquisition program ends when the underlying business logic is no longer viable” (Chatterjee, 2009, p. 138). Managers constantly scan for potential acquisition targets (Iyer & Miller, 2008) that adhere to defined acquisition program goals and business logic. Additionally, “the ability to identify and exploit market inefficiencies; the conscious striving for a win-win deal; and not deviating from established processes” (Chatterjee, 2009, p. 141), are crucial capabilities that have to match business logic in order to execute a successful acquisition program. Experienced managers are able to develop such capabilities to manage acquisition programs (Fowler & Schmidt, 1989; Hitt et al., 1998; Keil et al., 2012). Acquisition program capabilty will be emphasized in the acquisition capability section.
The next paragraphs elaborates on relevant prior theory regarding the organizational learning perspective. The importance of these aspects in the context of acquisition programs will be emphasized in the hypotheses section.
Learning by doing. Barkema and Schijven (2008) define organizational learning as the transfer of an organizations’ experience from one event to a subsequent one. Additionally, organizational learning is viewed as routine-based, history-dependent, and target-oriented (Levitt & March, 1988). Organizations can learn from historical experiences, built these into new routines and apply them to future behavior (Levitt & March, 1988). Prior literature emphasized the relationship between acquisition experience and improvement in acquisition performance (e.g. Fowler & Schmidt, 1989; Haleblian & Finkelstein, 1999; Hayward, 2002). “Firms might be able to learn how to manage acquisition processes by simply doing more of the same” (Zollo & Singh, 2004, p. 1237). As a result, experience can be used to improve routines that might directly impact the performance of subsequent acquisitions (Zollo & Winter, 2002). Executing multiple acquisitions provide firms the opportunity to accumulate prior experience from which they can learn to improve acquisition performance (Hayward, 2002; Kusewitt, 1985). Based on the idea of “learning by doing”, firms can apply lessons from prior experiences to future contexts (Arrow, 1971).
Transferring experience. Although, prior research shows that acquisition experience can negatively relate to acquisition performance (Haleblian & Finkelstein, 1999; Kusewitt, 1985). Firms can fail to draw correct inferences from prior experience when applying them to future acquisitions (Kolev & Haleblian, 2018). Acquisitions are complex and lessons from one acquisition cannot simply be transferred to another (Hayward, 2002). Inexperienced acquirers can inappropriately apply experience from first acquisitions to following dissimilar acquisitions resulting in negative transfer effects (Finkelstein & Haleblian, 2002; Haleblian & Finkelstein, 1999). Moreover, “experiences may be detrimental when transferred to a setting where previous lessons do not apply” (Barkema & Schijven, 2008, p. 596).
On the other hand, prior acquisition experience can positively relate to acquisition performance (Barkema, Bell, & Pennings, 1996; Fowler & Schmidt, 1989; McCarthy, 2011). Firms with previous acquisition experience will do better than those without such experience (Lubatkin, 1983). Prior acquisition experience enables firms to become more adept at avoiding problems that can negatively influence acquisition performance (Barkema, Bell, & Pennings, 1996; Fowler & Schmidt, 1989). Some firms have sufficient experience to appropriately learn and apply those lessons to future acquisitions (Haleblian & Finkelstein, 1999). Therefore, the improvement of acquisition capability by learning from experience is critical (Finkelstein & Haleblian, 2002; Haleblian & Finkelstein, 1999).
struggle to balance organizational attention between exploring new routines and exploiting existing routines (Levinthal & March, 1993; March, 1991). Novel acquisitions tend to be more of exploratory nature, while more similar acquisitions tend to be more exploitative (March, 1991). Acquiring highly similar businesses promotes specialized learning about that business (Hayward, 2002) but may fail to explore new opportunities (Levinthal & March, 1993; Barkema & Schijven, 2008). However, acquiring series of highly dissimilar businesses help firms to explore new bases of knowledge, but prevents specialized learning about other domains (Hayward, 2002). Similarity is important but at higher levels similarity might be detrimental for learning (Finkelstein & Haleblian, 2002). Therefore, “firms that make acquisitions that differ somewhat from prior acquisitions seem better able to balance the demands of exploiting and exploring growth opportunities” (Hayward, 2002, p.34).
Vicarious learning. “Learning by doing” ignores the opportunity of firms to learn from the experience of other firms. External learning can also be recognized as “learning from others” (Levitt & March, 1988; Barkema & Schijven, 2008). Specifically, firms benefit from vicarious learning by observing the strategic behavior of other firms (Kolev & Haleblian, 2018). Vicarious learning provides opportunities for exploratory learning because they are dissimilar to the focal firm (Barkema & Schijven, 2008). Firms can learn from others without having the need of significant experience themselves. This requires attention to organizational networks (Levitt & March, 1988). Firms can imitate the acquisition behavior of others to increase the success of their acquisitions to enhance performance (Barkema & Schijven, 2008). Thus, firms can potentially learn by observing others in the industry and imitate acquisitions that seem successful (Levinthal & March, 1993).
Acquisition capability
Firms differ in their ability to carry out acquisition programs mainly due to acquisition experience and capability development (Keil et al., 2012). The ability to carry out acquisition programs is a higher-level capability than carrying out individual acquisitions or serial acquisitions. Capabilities to engage in individual acquisitions are independent transactions with little connection to other parts of the firm compared to acquisition programs (Keil et al., 2012). However, “coordination across acquisitions within an acquisition program is critical for the success of the overall program” (Keil et al., 2012, p.152). Acquisition program capability can be developed through carrying out acquisitions (Ahuja & Katila, 2001), used to manage acquisitions and acquisition programs (Laamanen & Keil, 2008) repeatedly leveraged to improve the productivity of acquired companies (Chatterjee, 2009). Crucial capabilities to manage acquisition programs “include the ability to decide on the optimal number of firms to acquire, the timing of individual acquisitions and the types of firms to acquire and the optimal scope of an acquisition program” (Laamanen & Keil, as cited in Keil et al., 2012, p.155). Thus, acquisition program capability development is important to identify suitable targets, negotiate deals and manage acquisitions (Keil et al., 2012). Ultimately, acquisition capability is the ability of a firm to execute acquisitions. Or as Laamanen and Keil (2008) define it: “an acquisition capability can be defined to comprise the knowledge, skills, systems, structures, and processes that a firm can draw upon when performing acquisitions (p. 664)”. As a result, acquisition program-level capabilities tend to reside in the top management of a firm (Keil et al., 2012). To conclude, the ability of firms to effectively carry out acquisition programs depends on the acquisition program capability that the firm has managed to build before the acquisition deal by learning from experience.
HYPOTHESES
Learning from experience accumulation is accepted as the foundation for acquisition capability development (Aktas, De Bodt, & Roll, 2013; Zollo & Winter, 2002). Moreover, firms require acquisition program capability to increase the effectiveness of acquisition programs (Keil et al., 2012). This study hypothesizes that firms build acquisition program capability by learning from three kinds of experience. Following on mentioned organizational learning theory aspects, acquisition programs may become more effective if they learn from experience from acquisitions that are not part of acquisition programs, acquisitions within acquisition programs and acquisitions executed outside the focal firm. The mechanisms will be covered in the next paragraphs with corresponding hypotheses.
Internal acquisition experience
of acquisition program capability allows firms to draw correct inferences from prior experience when transferring them to acquisition programs (Kolev & Haleblian, 2018) and avoid transferring experience to a setting where previous lessons do not apply (Barkema & Schijven, 2008). As a result, the improvement of acquisition program capabilities may be more important than neglecting the experience from acquisitions outside acquisition programs. Therefore, firms executing acquisition programs may be able to develop superior acquisition program capabilities because they learn from the experience of acquisitions outside their acquisition programs. Thus:
H1: Acquisition programs become more effective the higher the firm's internal acquisition experience Acquisition program experience
Acquisition program experience is critical to balance the demands of exploiting and exploring growth opportunities. To illustrate, acquisitions within an acquisition program share commonalities due to its business logic (Chatterjee, 2009; Keil et al., 2012). Additionally, research finds that incorrect experience generalization is smaller if acquisition targets are similar (Finkelstein & Haleblian, 2002). Therefore, acquisition programs should be able reduce incorrect experience generalization. As a result, acquisition programs have similar experiences mitigating transfer problems. Some acquisition programs aim to exploit existing opportunities whereas others explore for new ones. Following, learnt lessons from similar experiences in acquisition programs can be transferred between other acquisition programs to balance exploration and exploitation efforts. In other words, built up experience in one acquisition program as a result of its strategic goal may be used in another acquisition program and vice versa. Therefore, acquisition programs would function as a platform for learning.
Consistent with the organizational learning argument, firms can likewise improve their acquisition program capability by learning from the experience of acquisitions within their acquisition programs. For instance, targets in an acquisition program share similarities in target identification. Therefore, firms learn from such acquisition program experience to develop acquisition program capability. In other words, firms develop acquisition program capabilities to be superior at identifying which targets are effectively benefitting the strategic goal of acquisition programs (Keil et al., 2012). As a result, firms may be able to improve acquisition program capabilities by learning from acquisition program experience. Thus,
H2: Acquisition programs become more effective the higher the acquisition program’s acquisition experience.
External acquisition experience
Haleblian, 2018; March, 1991) without the costs and risks of experimenting with such acquisitions (Miner & Haunschild, 1995). Firms executing acquisition programs are typically large organizations and their achieved sizes suggest they are doing the right thing. Especially those are likely to be imitated because of their status, observability, and visibility of actions (Haunschild & Miner, 1997). Vicarious learning provides firms executing acquisition programs the opportunity to imitate others to increase the performance of their acquisition programs. As a result, firms can observe and imitate acquisitions for their acquisition programs and learn from that experience to increase acquisition program capability. Thus,
H3: Acquisition programs become more effective the higher the firm's external acquisition experience
DATA AND METHODS Sample and Data Collection
The sample consists of acquisitions executed by six large ICT companies in the United. Additionally, these companies met the following criteria and were: serial acquirers, executing acquisition programs, operating in SIC 737; announced between 1997 and 2015; doing at least 20 acquisitions within this timeframe; and were completed acquisitions. Acquisitions are identified as technological acquisitions if it operates in SIC 737. The sample consists of 441 acquisitions fitting the criteria. Data was collected from Thomson Reuters SDC Platinum. The dataset contained information such as parent acquirer, announcement date, target acquired, and stock prices varying from 4 weeks after announcement date and 4 weeks prior to the announcement date. Additionally, a dataset is used containing daily stock prices for the acquiring firms. Further, the monthly prices of SP400 Computer Storage & Peripherals Index are used to calculate the market index for calculating CARs.
to 32 acquisition programs. A list of all acquisition programs and its rationales are provided in Appendix A. To illustrate, here is an example of Oracle’s data management acquisition program:
The database management program of Oracle is about complementing the unique range of integrated tools it offers for all databases for multiple platforms. The program is also about growing capabilities to broaden data warehousing and data quality solutions. Acquisitions within this program helps Oracle ensure the availability and recoverability of database and other business applications across their storage infrastructure for their clients. Moreover, the program acquires organizations that are experienced in cloud computing technology to provide data storage services to thousands of users by improving cloud networking software.
Dependent Variable
Cumulative abnormal returns. Acquisition programs become more effective if performance improves. Therefore, the dependent variable is defined as the effectiveness of acquisition programs. The performance effects of acquisitions in acquisition programs were measured using event study methodology in line with Mcwilliams and Siegel (1997). The stock market reaction to the announcement of each individual acquisition in the acquisition program is captured by using CARs. There is sufficient evidence that this measure predicts the performance of an acquisition in an acquisition program (Haleblian & Finkelstein, 1999; Hayward, 2002). The stock market returns in the sample is assessed against the monthly prices of SP400 Computer Storage&Peripherals to calculate the value-weighted market index. This may be expressed mathematically as follows:
𝐶𝐴𝑅𝑡 (𝑇1, 𝑇2) = ∑{𝑅𝑖𝑡− (𝛼𝑖+ 𝛽𝑖𝑅𝑚𝑡)} 𝑇2
𝑡=𝑇1
To define, 𝑅𝑖𝑡 = the return on stock 𝑖 for day 𝑡, 𝑅𝑚𝑡= the return on the value-weighted market index
for day 𝑡; 𝛼𝑖 = a constant, 𝛽𝑖 = 𝛽 of stock 𝑖 and 𝑇1 and 𝑇2 are the lower and upper limits of the window.
The estimates of α and β are calculates during a 250-day window that falls between 280 and 30 days before the announcement of an acquisition that is part of an acquisition program. In line with Hayward (2002), 30 days, prior to the announcement of an acquisition in an acquisition program, is used to remove the effect of take-over news. Additionally, consistent with Graffin, Haleblian and Kiley (2016), a three-day event window centered on the acquisition announcement date (three-day -1 to three-day +1) is reported. Independent variables
However, experience cannot be accumulated infinitely because management may forget about experience gained from acquisitions in the past or experience may become obsolete due to environmental changes (Argote, Beckman, & Epple, 1990; Hayward, 2002; Laamanen & Keil, 2008). Therefore, in line with Ingram and Baum (1997) and Ji Yub Kim et al. (2011), accumulated experience is discounted by the age of experience because a linear depreciation of prior experiences seems most likely in the context of acquisition programs. This is expressed mathematically as follows:
Experience Independent Variablesit = ∑Accumulated experience Age of experience
t-1
t
Internal acquisition experience. Acquisitions not part of acquisition programs may still provide meaningful experience to execute acquisition programs. Consistent with prior studies (Fowler & Schmidt, 1989; Hayward, 2002; Kusewitt, 1985), prior internal acquisition experience is measured as accumulated internal acquisition experience discounted by the age of experience. The accumulated internal experience is the total number of previous acquisitions outside acquisition programs prior to the acquisition announcement date of an acquisition that belongs to an acquisition program of a firm.
Acquisition program experience. Acquisition program experience may be a proxy for a firms’ acquisition program capability. Acquisition program experience is measured as the accumulated acquisition program experience discounted by the age of experience. The accumulated acquisition program experience is the total number of previous acquisitions in an acquisition program done by a firm prior to the acquisition announcement date of an acquisition that belongs to an acquisition program of the same firm. The operationalization of this measure includes experience from any acquisition program as experience in an acquisition program may be used in another.
External acquisition experience. Large firms are highly likely imitation candidates to each other because of their salience, status, and visibility of their actions (Haunschild & Miner, 1997). The achieved sizes of six large US ICT firms in the dataset imply that they have effective acquisition strategies. Therefore, these firms are likely to observe and imitate the acquisition behavior of each other as they operate in the same industry. In line with Baum, Li, & Usher (2000), the acquirer may only observe and imitate other firms when their strategy is sufficiently similar and they deliver considerable value. Therefore, similarity in acquisitions among firms in the same industry imply observed and imitated acquisitions to acquire external experience.
0
1
1
3
3
experience. Therefore, external acquisition experience is measured as the accumulated external acquisition experience discounted by the age of experience. The accumulated external experience is the total number of previous acquisitions done by other firms in the same SIC code prior to the announcement date of an acquisition that belongs to an acquisition program. Note that the count of previous acquisitions done by other firms goes to zero every time the focal firm acquires.
To clarify this new measure, an additional illustration and explanation are provided below. The arrow corresponds to a four-digit SIC code. The shape corresponds to different firms executing acquisitions. Firm A at the first circle cannot observe and imitate others since it has no preceding acquisitions, implying an external experience of 0. Firm B at the first triangle can potentially observe and imitate the first acquisition of firm A, implying an external experience of 1. Firm A at the second circle can potentially observe and imitate the preceding acquisition of Firm B, but not from the preceding circle since it is an acquisition of Firm A, implying an external experience of 1. Firm C at the first square can potentially observe and imitate all preceding firms, implying an external experience of 3. Firm B at the second triangle can learn from the preceding acquisition of Firm A and B but not from the preceding triangle since it is an acquisition of firm B, implying an external experience of 3. The accumulated experiences are respectively 1, 4 and 3 for firm A, B and C.
Moreover, to provide evidence for SIC code primary targets and their implications for potential imitation in acquisition programs, a list of the SIC-code categories and examples of potential imitated acquisitions within acquisition programs is provided in Appendix B. To illustrate, here is an example of TSIC7372: TSIC 7372: The majority of our acquisition targets share SIC-code 7372. In 4 out of 5 firms, a total of 41 out of 61 acquisitions from 2011 to 2015 were part of an acquisition program that adds to the business logic of improving data management particularly in cloud services. 9 out of 61 were not part of any acquisition program.
Control variables
Year of acquisition announcement. This categorical variable controls for the year where an acquisition part of an acquisition program is being announced. Each number is a dummy variable for
Figure 1: SIC Code imitation
the years 1997-2015. Year dummies are included in the estimation equations but not shown in the resulting tables to keep it comprehensive.
Firm. The dataset contains 6 firms. Some firms may be better at executing their acquisition programs than others. To control for firms, firm dummies are included to identify the acquirer. Firm dummies are included in the estimation equations but not shown in the resulting tables to keep it comprehensive.
Acquirer firm performance. Acquiring firm performance may be related to acquisition program performance as research shows that firms with better financial performance make better acquisitions (Morck, Shleifer, & Vishny, 1990). Additionally, higher acquiring firm performance may encourage managers to pursue an aggressive strategy (Haleblian, Kim, & Rajagopalan, 2006). Therefore, in line with Graffin et al. (2016), the model controls for firm performance as opposed to a firms’ acquisition performance prior to an acquisition announcement part of an acquisition program. Firm performance is measured as the acquirers’ return on assets. Acquirers’ return on assets is measured by dividing net income by average total assets.
Acquirer firm size. Firm size may influence strategic choices in acquisition behavior in such a way that larger firms may be more influenced by inertia and thus more likely to repeat prior acquisition behavior (Haleblian et al., 2006). The model controls for acquirer firm size which is measured as the logarithm of an acquirer’s total assets in line with Boone and Mulherin (2005).
Analysis
This event study measures the reaction of investors to the announcement of an acquisition in an acquisition program. Therefore, the ordinary least squares (OLS) regression is the primary empirical approach to test the hypothesis. The OLS regression can be used to explain CARs with the operationalized experience measures. The models are performed using the software program Stata.
RESULTS
Table 1: Descriptive Statistics
Variables Obs Mean Std.Dev. Min Max
CARs (-1, +1) 310 .002 .025 -.087 .12
Return on Assets 322 -9.754 271.548 -2790.75 427.16
Natural log of Assets 322 4.465 .427 3.7 5.246
Internal experience 324 .02 .004 0 .025 Program experience 324 .044 .009 0 .074 External experience 324 .008 .013 0 .133 Table 2: Correlations Variables (1) (2) (3) (4) (5) (6) (1) CARs 1.000 (2) Return on Assets -0.005 1.000 (3) Log of Assets 0.005 0.071 1.000 (4) Internal experience 0.085 0.005 0.149* 1.000 (5) Program experience -0.067 0.043 0.321* 0.431* 1.000 (6) External experience 0.084 -0.007 -0.120* -0.167* -0.060 1.000 * shows significance at the .05 level
Table 3: Effects of experience on acquisition program CARs
Model 1 Model 2 Model 3 Model 4 Model 5
Return on Assets 0.000 0.000 0.000 0.000 0.000 (0.000) (0.000) (0.000) (0.000) (0.000) Log of Assets 0.037*** 0.036*** 0.038*** 0.036*** 0.036*** (0.011) (0.011) (0.011) (0.011) (0.011) Internal experience 1.737** 1.937** (0.816) (0.843) Program experience -0.327 -0.288 (0.227) (0.227) External experience 0.145 0.227* (0.123) (0.125) _cons -0.145*** -0.160*** -0.134*** -0.144*** -0.151*** (0.043) (0.044) (0.044) (0.043) (0.045) Obs. 308 308 308 308 308 R-squared 0.103 0.117 0.110 0.107 0.132
Standard errors are in parenthesis *** p<0.01, ** p<0.05, * p<0.1
acquisition experience measure. The remaining acquisitions are part of an acquisition program and measured in acquisition program experience. The remaining correlations of the independent variables are in the low-to-moderate range. To detect the presence of multicollinearity, the variance inflation factors (VIF) are calculated for all models of Table 3. The results show that show in all models VIFs smaller than 10. The average VIF for Model 5 in Table 3 is 5.86. VIFs smaller than 10 should not raise significant multicollinearity concerns, thus there was not any evidence of multicollinearity in the sample. Table 3 reports the models that test the hypotheses. Model 1 in Table 3 reports the control model. Model 2,3 and 4 respectively adds the measure of internal experience, acquisition program experience and external experience separately. All independent variables are included in Model 5. The results of the regression indicated that Model 5 explains 13,2% of the variance. Considering the independent variables, internal acquisition experience (p < .05) and external acquisition experience (p < .1) contributed significantly to the model whereas acquisition program experience did not.
Effect of internal acquisition experience
Hypothesis 1 predicted that acquisition programs may become more effective if they have more internal acquisition experience. The coefficient for internal acquisition experience in Model 5 is positive and significant (p < .05), supporting Hypothesis 1. For instance, in the sample, an acquisition part of an acquisition program has at the mean level 0.02 internal acquisition experience which increases the CAR by 0.02×1.937=0.0387 which is approximately 3,9%. Considering the average amount of internal acquisitions not part of an acquisition program divided by the age of experience, this represents an increase of 3,9% in the market reaction when an acquisition part of an acquisition program is announced. The effect size implications for a manager should be taken cautiously. Model 5 explains 13,2% of the variance whereas the remaining is not accounted for. Moreover, only the effect size of internal acquisition experience is considered here. Nevertheless, internal acquisition experience does seem to have a positive effect on market returns to acquisitions part of acquisition programs.
Effect of acquisition program experience
Hypothesis 2 predicted that acquisition programs may become more effective if they have more acquisition program experience. The coefficient of acquisition program experience in Model 5 is negative and not statistically significant, failing to support Hypothesis 2.
Effect of external acquisition experience
Additional analysis and robustness checks
Literature is still inconclusive on how the value of experience depreciates over time (e.g. Barkema & Schijven, 2008a; Ingram & Baum, 1997; Ji Yub Kim, Haleblian, & Finkelstein, 2011; June Young Kim, Kim, & Miner, 2009). Therefore, by doing robustness checks, additional models were ran using different discount methods to depreciate the value of experience over time. This may be expressed mathematically as follows:
Experienceit = ∑Accumulated experience Discount
t-1
t
In line with the methods of Ingram and Baum (1997), three additional discount methods were used. First, the discount is equal to 1, which assumes that prior experiences do not depreciate over time. Second, the discount is set equal to the age of experience squared, which assumes that experience depreciates rapidly at first and more quickly with time. Third, the discount is set equal to the square root of the age of experience, which assumes that the depreciation of experience is initially slow and slows further with time. For clarification, Figure 2 is drafted from the sample showing graphically how the average acquisition program experience depreciates from 1998-2015 using discount factors.
Figure 2: Acquisition program (discounted) experience
Additionally, consistent with Barkema & Schijven (2008), natural log transformations were used to capture the declining marginal returns associated with experience to see if it would provide different results. The results of the models using the different discount methods and natural log transformations
0 10 20 30 40 50 60 70 80 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 A cc um ul at ed (di sc ount ed) expe ri enc e Year
are presented together in Table 4. For discount methods 1-3, all results were positive and insignificant excluding acquisition program experience which was negative and insignificant using discount 2. Using natural log transformations along with discount method 1-3, discount 1 was positive and insignificant. For discount 2, only negative relations were found and acquisition program experience was statistically significant (p < .001). Discount 3 had negative insignificant results for acquisition program experience and positive insignificant results for internal and external acquisition experience. Lastly, taking the natural log of our original model shows a negative and significant relation for acquisition program experience. As a result, there were no statistically significant results when using other different discount measures. There were only statistically significant differences when using natural log transformations along with other discount methods.
Even though these measures are not part of my main model, it is still important to keep them in mind when interpreting the results. Conclusions change when the assumptions change for different discount measures and natural log transformations. In other words, for acquisition program experience there is a negative significant relationship when assuming experience depreciates rapidly at first and more quickly with time when using natural log transformation to capture the declining marginal returns associated with experience. Additionally, for acquisitions program experience there is a significant negative relationship (p < .05) when assuming a linear depreciation of prior experience using natural log transformations to capture the declining marginal returns associated with experience. With these assumptions, acquisition program experience has a negative effect on cumulative abnormal returns failing to support and contradicts Hypothesis 2.
Table 4: Discount methods and natural log transformations
Discount 1 Discount 2 Discount 3 Natural log
Discount 1 Natural log Discount 2 Natural log Discount 3 Natural log original Model Original model Internal experience Positive and insignificant Positive and insignificant Positive and insignificant Positive and insignificant Negative and insignificant Positive and insignificant Positive and insignificant Positive and significant (p < .05) Program experience Positive and insignificant Negative and insignificant Positive and insignificant Positive and insignificant Negative and significant (p < .001) Negative and insignificant Negative and significant (p < .05) Negative and insignificant External experience Positive and insignificant Positive and insignificant Positive and insignificant Positive and insignificant Negative and insignificant Positive and insignificant Positive and insignificant Positive and insignificant DISCUSSION
This study is the first to categorize a considerable amount of acquisitions to acquisition programs and analyze such specific acquisition programs. It examines the effects of acquisition experiences on acquisition program performance. Depending on antecedent conditions (e.g. internal acquisition experience, acquisition program experience, and external acquisition experience), the effects on acquisition program performance may vary. Hence, the organizational learning theory helps to explain and predict the effects of prior acquisition experiences on acquisition program performance.
Internal acquisition experience
Prior research extensively analyzed how previous acquisition experience increases performance. Consequently, there are certain prerequisites for effective acquisition program capability development due to learning from experience accumulation. For instance, Thomas and Keil (2008) find that acquisition experience, the acquisition rate and variability of the rate are related to acquisition performance and acquisition program capability development. This study adds a deeper understanding of the role of acquisition experience from acquisitions that are not part of acquisition programs and how it relates to performance and acquisition program capability development.
Acquisition program experience
Contrary, acquisition program experience did not lead to a significant increase in. Therefore, acquisition program did not become more effective when acquisition program experience was higher. By way of contrast, results show that acquisition program experience might even be harmful for the performance of acquisition programs. In the original model, a negative and insignificant relationship was found. However, under the assumption of declining marginal returns associated with experience, the market returns significantly decreased for acquisition program experience. The same applies when acquisition program experience depreciates rapidly at first and more quickly with time, using natural log transformation to capture the declining marginal returns associated with experience.
Acquisition programs may be unable to improve their acquisition program capabilities by learning from prior acquisition program experience. One reason might be the inappropriate generalization from prior acquisition program experience to subsequent dissimilar acquisition programs (Haleblian and Finkelstein, 1999). Some experiences are only valid within an acquisition program and not necessarily across acquisition programs. Each acquisition program has its own business logic. Therefore, acquisition programs are inherent dissimilar from each other and may unable to generalize experience into useful lessons to improve acquisition program capabilities, resulting in worse acquisition program performance. However, this seems odd as prior research argues that false experience generalization is smaller if acquisition targets are similar (Finkelstein & Haleblian, 2002).
External acquisition experience
One reason may be that firms are unable to learn from acquisitions part of acquisition programs done by others because experience does not transfer easily between firms. Firms miss out on underlying experiences and learnt lessons when acquisitions are imitated. The ‘why’ and ‘how’ a target has been acquired by the focal firm for an acquisition program is ignored. Alternatively, imitating “rivals without understanding the motives and underlying capabilities behind rivals’ behaviors” (Kolev & Haleblian, 2018, p.2) may influence acquisition program performance.
Firms may require sufficient experience themselves before they tap into the acquisition strategy of competitors. Consequently, firms executing acquisition programs may be more effective at imitating the acquisition strategy of others when sharing similarity in business logic among their acquisition programs. Altogether, firms may be able to improve their acquisition program capability by “learning from others” if they share the same underlying business logic and understand the ‘why’ and ‘how’ to effectively learn from experience when imitating competitors. However, that would require future research.
Managerial implications
The results have practical implications for managers as they are involved in defining strategic goals for acquisition programs and have to translate objectives into specific strategic and investment criteria for future acquisitions (Marks & Mirvis, 2001). Results show that internal acquisition experience matters for the performance of acquisition programs. Hence, my results may encourage managers to be aware of their internal acquisitions that are not part of any acquisition program. Management needs to take into consideration how acquisitions perform, to what goals it contributes to, whether it fits an acquisition program and what useful lessons can or cannot be translated to an acquisition program level. If targets do not fit a business logic then avoid integrating them into acquisition programs. My final implications are based on the findings that external acquisition experience has no convincing support for increasing acquisition program performance. Management should be aware of their investment decisions when imitating a target that is similar to other firms’ strategic acquisition choices.
Limitations
that make multiple acquisitions within the same industry benefit by generalizing all past acquisition experience. However, it is possible that prior experiences in acquisition programs among firms may be applied inappropriately or less extensively resulting in poor outcomes.
The measurement of the dependent variable, acquisition program performance by using CARs, remains an ongoing challenge in acquisition research (e.g. Barkema & Schrijven, 2008; Hayward, 2002; Haleblian & Finkelstein, 1999; Lamaanen & Keil, 2008). Some say it causes potential validity problems (Fama & French, 1996) and captures an effect that is completely distinct from other performance measures (Zollo & Meier, 2007). Moreover, this study assumed that acquisition programs can learn from prior experiences, use those lessons to improve acquisition program capability and ultimately acquisition program performance. However, causality between these concepts may be untrue. This study only analyzes the relationship between experience and acquisition program performance. The interaction effects of learning from experience and acquisition program capabilities are left out of scope. Next, to measure the independent variables, the value of experiences is depreciated by using the age of experience in the main model. There were different results using other discount methods as robustness checks. The applied depreciation method may be wrong and is therefore a limitation. Additionally, this study reported a three-day event window for calculation CARs. No other event windows as robust were added due to time limitations.
Moreover, measuring external experience was an empirical challenge due to dataset limitations and may be inaccurate. Additionally, the measurement of external learning or experience is narrowly researched in the academic acquisition literature. Therefore, the best available method was to use targets’ four digit SIC-codes. Even though this measure may have been the best alternative to measure external experience by using potential imitated acquisitions, it still has limitations. The first assumption is that imitation only took place within the same four digit SIC-code. Secondly, external experience may not have been measured accurately because a potential imitated acquisition does not directly lead to external experience. Additionally, external experience may also be obtained through merely observation. Thirdly, causality between imitated acquisitions and external acquisition experience may be ambiguous. The assumption that imitated acquisitions fully provide external experience may be untrue since firms miss out on underlying motives.
Future research
whether all acquisition program capabilities are useful in all acquisition programs. There is a possibility that a set of acquisition program capability may be used in specific acquisition programs. Another limitation lies in the measurement of experience. Different discount methods are used to depreciate the value of experience over time. Future research could build on this study by investigating different discount methods and its antecedents. The depreciation curve of experience may be different for different types of experience. For instance, internal acquisition experience may depreciate faster than acquisition program experience. Additionally, future research is required to study how and whether firms capture experience by observing and imitating acquisition behavior of other firms. An accurate way to measure external experience remains a challenge.
Conclusion
This study adds to the acquisition program perspective by researching how acquisition experience influences acquisition program capabilities. A new way of categorizing acquisitions to acquisition programs is introduced by using press releases. Based on quantitative analysis of prior acquisition experience and acquisition program performance, it can be concluded that that acquisition programs become more effective if firms have higher internal acquisitions experience. In other words, acquisitions not part of an acquisition program provide useful experience to translate into lessons in order to improve acquisition program capabilities. The integration of the organizational learning theory is further facilitated by translating prior acquisition experiences into improved acquisition program capabilities. Moreover, acquisition program experience and external acquisition experience did not influence acquisition program performance. To better understand the implications of these results future research could consider alternative and improved measures for acquisition experience and acquisition program performance. Further research should encourage others to continue to explore the acquisition program perspective to find factors that enhance the performance of firms and their long-term survival.
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APPENDICES
A. Acquisition program rationales Automatic Data Processing
Automotive: The ADP automotive program is about providing automobile manufacturers and dealers with industry leading solutions. They invest in technology to ensure dealers and manufacturers have a flexible and secure path to the solutions they need now and in the future. The solutions aim at meeting retailers’ demands to better manage their customers, grow revenue and create competitive advantage with expanded product offerings. These acquisitions represent a continued focus to deliver solutions that will help dealers improve sales and profitability, while decreasing costs.
Human resources: The ADP HR program is about acquiring organizations that improve humans resource capabilities. These acquisitions underscores ADP’s commitment to help their clients drive business success by helping them better manage talent, make quality hires and control costs associated with the recruitment process. The overall program aims at acquiring HR resource solutions that includes be nefits eligibility and enrollment, payrolling, absence management and benefits advocacy. The key logic of this program is to acquire organizations that enhance their human resources management software and services to keep a leading position in the HR industry.
Financial services: The ADP financial services program is about improving the arsenal of transaction processing platforms. Their financial services include expanding needs of its brokerage and banking clients to further enhance their high-quality customer support infrastructure. Additionally, the program aims to expand their brokerage services by investing in online trading and provides security and reliability solutions. Moreover, this program focusses on its core strengths in transaction and payment processing for merchants and financial institutions. The key idea of this program is that ADP invests in organizations that enables them to be the world’s best transaction processing company.
Medical: The ADP medical program is about improving health care solutions. These solutions include effectively informing their clients about healthcare decisions. ADP has a long-standing history of serving medical progression practices of all sizes. The key idea of this program is to invests in organizations that support ADP in providing health insurance plan options for different kind of businesses.
Computer Associates International programs
Enterprise management: The enterprise management program of CA aims at acquiring organizations that enable their clients to enhance enterprise management by improving their IT infrastructures, including systems and database management, e-commerce, application infrastructure management, data warehousing, knowledge management and decision support. The key logic of this program is to build a stronger enterprise that can provide a broader range of solutions to clients, greater opportunities for employees, and accelerated near and long-term shareholder return.
Data management: The database management program of CA is about complementing the unique range of integrated tools CA offers for all the industry’s leading databases for multiple platforms. The program is about growing capabilities to broaden data warehousing solutions. Acquisitions within this program help CA ensure the availability and recoverability of database and other business applications across client storage infrastructure.
Access management: The access management program of CA is about boosting its market share in identity and access management software. Acquisitions within the program will help to transform identity and access management to comprehensive information security solutions. The key logic of this program is to invest in access solutions for controlling and protecting user accounts from external attacks or insides mistakes and malicious misuse.
Cloud services: The cloud program of CA invests in organizations that excel in cloud management. The program aggressively expands its portfolio of solutions to manage cloud computing as part of an integrated information technology management program. The goal of this program is to use the cloud computing technology to provide data storage services to thousands of users and strengthen CA's ability to build and manage internal cloud environments.
Computer Sciences Corporation
Federal: The federal program of CSC is about expanding businesses to federal fields. They invest in organizations that enable CSC to complement their work done for governmental clients such as the Department of Homeland Security and other Defence agencies. Acquired organizations within this program own IT services and system integration solutions that deliver value to federal organizations.
Data management: The data management program of CSC aims at acquiring organizations that have expertise in the data management field. The data management program includes solutions in the field of big data management, security services and cloud computing that CSC provides to their customers.
transportation services. The key logic of this program is to expand to different industries and create opportunities to deliver core business to these industries.
IT services: The IT services program of CSC is about enhancing their IT services. This program invests in IT organizations that further strengthen CSC’s capabilities. The key logic of this program is to deliver a world-class IT program that will provide a high quality, cost effective and scalable platform to organizations’ business development programs, improve efficiency and enhance their business agility. Geographic: The geographic program of CSC consists of acquisitions that enables CSC geographical expansion. Acquisitions within this program facilitate market expansion in different countries in Asia, Europe and America. The key logic of this program is to strengthen global commercial businesses throughout the world.
Electronic Data Systems
Airline: The airline program of EDS is about investing in the airline industry. EDS acquires organizations that enable them to run operations for multiple airlines to achieve economies of scale. Ultimately EDS strives to strengthen their leadership position in the airline industry.
Market expansion: The market expansion program of EDS show acquisitions that enable EDS to expand in new industries and geographical locations. It achieves synergies by building offshore capabilities. The key logic of this program is that EDS acquired organizations in different geographical areas to improve global opportunities to expand their market opportunities.
IT services: The IT services program of EDS aims to invest in organizations that enable EDS to automate and accelerate the services quality in the IT sector. The key logic of this program is EDS acquiring organizations that improve IT management and process implementation to serve clients in their expansive global infrastructure.
Microsoft
Advertising: The advertising program of Microsoft is about finding and creating new and effective ways to advertise products and services to improve sales. The program extends marketing efforts to help clients get more global exposure. Additionally, this program shows throughout the years new methods of advertising (e.g. mobile and internet advertising). Moreover, acquisitions within this program enhances its advertising platform to create alternative revenues across offline and online environments.
online) on different platforms (e.g. PC and Xbox). Additionally, this program invests in the development of the Xbox.
Security: The security solutions program of Microsoft is about enhancing security solutions for its networks. These solutions include developing state of the art Virtual Private Network (VPN) technology and anti-virus technology to protect data assets from threats. Furthermore, the program acquires organizations that own leading security products and services for cloud and virtualization to secure clients’ web-based businesses. Additionally, the program invests in access solutions for controlling and protecting user accounts from external attacks or insider mistakes and malicious misuse. Microsoft Office: The Microsoft Office program invests in organizations that can enhance Microsoft Office’s product offerings. Microsoft Office has different applications such as Powerpoint, Word and Outlook. Acquired organizations in this program enhance the functionality of Microsoft Office.
Windows: The Windows program enables Microsoft to develop Windows operating systems to improve its functionality. Acquisitions in this program enable customers to benefit more from Windows-based systems. The key logic of this program is the addition of expertise to Microsoft helping them to provide edge technologies to continue to raise the quality and functionality for Windows on both the client and server.
Data/Cloud service: The data/cloud service program of Microsoft invests in organizations that excel in data management and cloud management. The program aggressively expands its portfolio of solutions to manage cloud computing as part of an integrated information technology management program. The goal of this program is to use the cloud computing technology to provide data storage services to thousands of users and strengthen its ability to build and manage internal cloud environments. Moreover, the program aims to ensure the availability and recoverability of database and other business applications across their storage infrastructure for their clients.
Mobile: The mobile program of Microsoft is about the mobile projects. Acquisitions in this program aim at improving the mobile platform. It connects people to their social circles and other rich content and is an integrated end-to-end solution that enables people to interact with their friends, social communities and content through the Internet and Internet services. The key logic behind this program is enabling the improvement of mobile functionalities to improve customer experience.
Oracle
