The development of capabilities in new firms - Wiley Online Library

Strategic Management Journal Strat. Mgmt. J., 31: 1–18 (2010) Published online EarlyView in Wiley InterScience (www.interscience.wiley.com) DOI: 10.1002/smj.797 Received 14 October 2005; Final revision received 3 July 2009

RESEARCH NOTES AND COMMENTARIES THE DEVELOPMENT OF CAPABILITIES IN NEW FIRMS ASLI M. ARIKAN1 * and ANITA M. MCGAHAN2 1 2

Georgia State University, Atlanta Georgia, U.S.A. Rotman School of Management, University of Toronto, Toronto, Ontario, Canada

This research explores evidence of corporate capabilities for conducting acquisition and alliance deals in young firms. We hypothesize that investors conjecture about the future based on information about a firm’s capabilities. Each successive deal carries intrinsic value, creates experience, generates feedback, and yields information about the firm’s underlying capabilities. We evaluate whether stock prices impute expectations that firms will capably pursue particular programs of acquisitions and alliances. The analysis covers how investor responses change across successive deals on the theory that firms with a concentrated program of deals may develop capabilities more intensively than those with programs that involve both acquisitions and alliances. The dataset covers the population of firms that went through an initial public offering (IPO) in the United States between 1988 and 1999. It contains information on all of their post-IPO acquisitions and alliances, and on how their stock prices changed in response to the announcement of each deal. The results suggest that within the first year after IPO, investors expect firms to execute particular streams of alliances and acquisitions that reflect their unique histories of demonstrated capabilities. We also find evidence that investors cannot fully anticipate deal programs. The findings support a capabilities-based view of the firm and also show that accurate inference using event-study methods may require digging deep into the early histories of firms. Copyright  2009 John Wiley & Sons, Ltd.

INTRODUCTION This study investigates how stock prices adjust to the development of underlying corporate capabiliKeywords: corporate capability; mergers and acquisitions; alliances; abnormal performance; experience; IPO; stock market reaction

∗ Correspondence to: Asli M. Arikan, Georgia State University, 35 Broad Street, Atlanta, GA 30303, U.S.A. E-mail: [email protected]

Copyright  2009 John Wiley & Sons, Ltd.

ties for conducting acquisition and alliance deals. The setting is the population of newly public firms in the United States during the 1990s and early 2000s restricted to include only those firms that had no prior experience with acquisitions or alliances at the time of initial public offering (IPO). The principal research question is: Do changes in investor responses to the announcements of successive deals by a firm support the idea that the firm’s capabilities for conducting

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A. M. Arikan and A. M. McGahan

acquisitions and alliances become apparent in early deals? The motivation is to assess how firms become enabled and constrained by capabilities. How early in the life of a firm is path dependency established? On average, do capabilities create strong incentives for firms to pursue a circumscribed strategy of future deals, or do they tend to develop in a way that gives firms significant latitude to tailor the choice of an acquisition or alliance to the idiosyncratic conditions of each deal? The results have implications for a wide range of management problems. For example, if path dependency is established early, then corporate restructuring among mature firms may require a major investment in environmental scanning and resource shedding. On the other hand, if deal capabilities emerge incrementally, then dynamism may depend on a purposeful process of learning through successive events to accumulate specialized, strategically valuable resources. Our results also have methodological implications for event studies that rely on investor responses to information about deals. An empirical finding of early path dependency would suggest that event studies should account for previously imputed investor expectations. We concentrate on acquisitions and alliances for reasons that follow precedent in the literature (Doz 1996; Dyer, Kale, and Singh 2001, 2004; Ethiraj et al., 2005; Finkelstein and Haleblian 2002; Hayward 2002; Kale, Dyer, and Singh 2002; Villalonga and McGahan, 2005): (a) acquisitions and alliances are significant drivers of firm value creation, (b) the required capabilities are uniquely relevant to alliances and acquisitions, and (c) the capabilities are at least partly observable through the deals themselves. Prior research suggests that deal capabilities accumulate incrementally through experience (Anand and Khanna, 2000), and that the robustness and effectiveness of capabilities cannot be verified except when the capabilities are enacted in deals, and that even then they are only partially observable (Villalonga and McGahan, 2005). Experience with deals is important to the creation of capabilities because some activities associated with doing deals cannot be simulated, that is, identifying targets and partners, negotiating terms, and planning collaboratively. Investors focus intensively on the information disseminated with early deals about underlying capabilities because of the implications for future deals (Schipper and Thompson, 1983; Villalonga Copyright  2009 John Wiley & Sons, Ltd.

and McGahan, 2005; Laamanen and Keil, 2008). For example, if a firm executes its second acquisition with capabilities that demonstrate a sophisticated integration of knowledge from its first acquisition, then investors can anticipate astutely executed future acquisitions as well. With the second acquisition, the firm is revealing a capability for future acquisitions, which might be further developed subsequently to create additional value. Thus, we expect evidence in early deals of accumulating capabilities, but we also expect evidence that investors respond as if the capabilities for future deals will continue to develop over time. Our empirical strategy involves modeling investor responses to the first, second, third, etc., acquisitions and the first, second, etc., alliances of firms. The hypotheses reflect theorized relationships on the simultaneous, interacting emergence of corporate capabilities and investor responses. The dataset covers all firms that went through an IPO between 1988 and 1999 and excludes those IPO’d firms that did acquisitions or alliances prior to their IPOs. The results indicate that, on average, investors adjust expectations within a year of IPO to anticipate subsequent deals by type. We interpret this empirical result to suggest that emerging capabilities quickly become identified, and that the implications for deal strategy quickly become apparent. However, we also find evidence that unanticipated capabilities emerge after an initial burst of information into the investor community about original capabilities. This second result suggests that capabilities continue to develop dynamically after they are established initially. Theory and hypotheses Following Schreyögg and Kliesch-Eberl (2007), we conceptualize capabilities as embedded in activities and routines for addressing complex, practical, and repeated problems such as the execution of alliance or acquisition deals. Some of the capabilities required to execute acquisitions and alliances are similar (e.g., for partner search, negotiation, and outcome evaluation), while others are specialized either to alliances or acquisitions (Zollo and Reuer, 2001; Wang and Zajac, 2007). Prior research has documented that alliance capabilities develop around detailed partner selection criteria (Shah and Swaminathan, 2008), learning processes across deals (Doz, 1996; Kale and Singh, Strat. Mgmt. J., 31: 1–18 (2010) DOI: 10.1002/smj

Research Notes and Commentaries 2007), the portfolio of ongoing partnerships (Hoffmann, 2007; Goerzen, 2007), cooperating to create value (Luo, 2008), contending with value appropriation between partners (Lavie, 2007) and evaluating outcomes continuously in situations where mutual interdependence makes the attribution of value to each partner difficult (Bourdeau, Cronin, and Voorhees, 2007; Lunnan and Haugland, 2008). A contrasting range of capabilities are particularly relevant to acquisitions: target identification (Capron and Shen, 2007), formal due diligence (Laamanen, 2007; Zollo and Reuer, 2001), structured negotiation and integration activities (Ashkenas, DeMonaco, and Francis, 1998) and retention of the target’s valuable human capital (i.e., top management) in the post-integration period (Walsh, 1988). Thus, while capabilities to conduct acquisitions and alliances may sometimes be relevant to both types of deals, prior research demonstrates that many capabilities are specifically relevant to either acquisitions or alliances. In general, capabilities emerge over time from the activities that occur during relevant events. In the current analysis, these events are the acquisition and alliance deals themselves. As Schreyögg and Kliesch-Eberl explain: ‘Capability development comes close to a chain of reactions triggered by an initial event, thereby establishing a capability trajectory. Capability development takes time and the specific way in which time has been taken (i.e., the intensity, frequency, and the duration of social interactions) is relevant for the gestalt of a capability’ (Schreyögg and Kliesch-Eberl, 2007: 916). In this analysis, the initial event is the seminal acquisition and/or alliance deal for a newly formed firm, and the trajectory is the stream of acquisition and/or alliance deals. Two related processes are occurring simultaneously as a capability is gradually revealed to managers, investors, and other constituents: (a) the capability forms through the successive deals, and (b) information about it disseminates. These processes are intertwined and mutually constrained in several fundamental ways. First, the information cannot disseminate until the capability is formed. Second, investor responses cannot incorporate expectations about the future trajectory of deals until both the capability is formed and information is evident about its implications for a future deal program. Finally, investor expectations about future deals may compel the firm to pursue additional deals of a particular type (Dyer et al., 2004). Copyright  2009 John Wiley & Sons, Ltd.

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These related processes are difficult to discern, and yet two of their characteristics are observable. The first is the frequency of the deals, which can be measured as the compression in time between related events. For a number of theoretical reasons, the amount of time between deals diminishes as specialized capabilities develop: (i) the firm may be better at ‘resource picking,’ that is, at identifying potential acquisition targets or alliance partners (Makadok, 2001), which may lead to: (i) a greater frequency of high-quality deals that pass subsequent tests of viability; and (ii) the capability to achieve a greater return through superior execution makes a marginal deal that would otherwise be rejected appear attractive (Haleblian and Finkelstein, 1999), which leads in turn to a greater number of deals over a fixed period of time. The execution of additional deals of the same type—made attractive by established capabilities—may further cement the firm into the capability trajectory (Dyer et al., 2004). Thus, evidence of a short time between deals may reflect the presence of an established capability and the unfolding of path dependency in a reinforcing program of deals that exploit and reinforce the capability (Schipper and Thompson, 1983; Haleblian, Kim, and Rajagopalan, 2006; Laamanen and Keil, 2008). The second is the investor response to each deal. Initially, when the firm has no or little deal experience, the abnormal return associated with each event reflects investor responses to the value created both by the contemporaneous event and by the information disseminated about possible future deals (Villalonga and McGahan, 2005). In this situation, a prerequisite for an investor response is the development within the firm of a capability and the dissemination of information about it. A strong investor response is predicated on the existence of a capability, and also acts as a source of feedback to the firm (Arthur, 1990; Greve, 1998). Thus, the information disseminated is an exchange. Investors respond to the information about capabilities released by the firm and managers receive information in the form of imputed expectations that the firm has the potential for future deals on a capability trajectory (Levinthal and Myatt, 1994). As a result, our first hypothesis is about imputed expectations and path dependency: Hypothesis 1: Acquisition/alliances are (are not) preceded by strong prior responses to deals of the same type. Strat. Mgmt. J., 31: 1–18 (2010) DOI: 10.1002/smj

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Hypothesis 1 focuses on the exchange of information between the firm and investors and specifically on the process by which capabilities develop as a prerequisite to strong investor response. The idea is that firms pursue deals that are implied by the accumulation of their established capabilities, which may have generated strong prior responses (Levinthal and Myatt, 1994). The central causal relationship embedded in the hypothesis is that the path dependency that emerges from the establishment of capabilities generates both investor responses to early deals and an incentive for the firm to pursue additional deals on the emerging path (Nelson and Winter, 1982; Greve 1998; Kale et al., 2002). The hypothesis would be rejected if any of the implied mechanisms fail: capabilities do not develop, information about them does not disseminate, investors do not respond, or path dependency within the firm does not emerge. As deals accumulate serially, information about capabilities disseminates among investors, who calibrate expectations not only about the contemporaneous deal but also about the implications of the path dependency. The signal disseminated about capabilities is stronger if the firm concentrates deals in either the acquisition or alliance form. The notion is that investors react less strongly to deal announcements by firms with relatively greater experience with either acquisitions or alliances as compared to other deal-making firms. The reasoning: after a firm accumulates a track record of acquisitions or alliances, investors have imputed expectations that the firm will pursue further deals of the same type. As a result, they react less strongly to successive deals for the firm than to those announced by firms that have less of a track record. Because the announcement of a deal communicates credible, economically significant, qualitative information (Narayanan et al., 2000) about the development of the underlying capability as well as information about the focal transaction, each subsequent deal decreases the information asymmetry between insiders and outsiders about the path of subsequent deals (Myers and Majluf, 1984). Thus, once deals have accumulated, capabilities have been established, path dependency is evident, and information has disseminated into the investment community, then investor responses to each deal announcement are only adjustments to previously imputed expectations based on the ‘new information’ embedded in the contemporaneous deal (McWilliams and Siegel, 1997) rather Copyright  2009 John Wiley & Sons, Ltd.

than on the form of the deal as an acquisition or alliance. As a result, our second hypothesis is about concentrated deal experience: Hypothesis 2: Incremental change in investor reactions to subsequent same-type deals decreases with (is not related to) increases in same-type deal experience. In other words, because of previously imputed expectations about future deals, stock market responses to acquisitions or alliances are lower for firms with greater acquisition or alliance experience. Hypothesis 2 is focused on the process of information dissemination (Narayanan et al., 2000) about capabilities and the firm’s commitment to deals of a particular type. The hypothesis would be rejected if firms with a higher proportion of prior deals as acquisitions/alliances do not exhibit lower financial market responses to subsequent acquisitions/alliances because deal programs may change over time or because prior experience is not relevant. This alternative would be supported if either (i) any step in the process fails—deal experience does not generate capabilities, information is not disseminated, investors do not respond—or (ii) expectations about implications are not imputed. As deals accumulate, the underlying capabilities for conducting them develop along a trajectory that may become, with each deal, augmented and deepened (Nelson and Winter, 1982; Levinthal and Myatt, 1994; Eisenhardt and Martin, 2000; Helfat and Peteraf, 2003). Recent research by Mayer and Argyres demonstrates that firms learn to mitigate recently experienced hazards in successive transactions and that ‘this learning was quite gradual and incremental, and occurred over a relatively long period’ (Mayer and Argyres, 2004: 395). Firms that concentrate on doing particular types of deals within the ‘alliance’ or ‘acquisition’ category may become specialists of unprecedented capability at executing deals of a particular type. As information about capabilities disseminates through deal announcements, the cumulative abnormal return to deals may not converge to zero, especially in firms with mature capabilities; in other words, investors may—especially late in a deal program—deduce more additional valuable information about the implications of specialized capabilities through each deal announcement. Taken together, these processes lead to the following predictions: (a) the Strat. Mgmt. J., 31: 1–18 (2010) DOI: 10.1002/smj

Research Notes and Commentaries cumulative number of past alliances or acquisitions decreases the magnitude of investor reactions (as expressed in Hypothesis 2), and (b) as the process of capability deepening and specialization develops, new information about them may disseminate. Thus, our third hypothesis addresses whether continuing, unobservable capability development: Hypothesis 3: The incremental change in cumulative abnormal returns to successive acquisitions/alliances alliances does not (does) converge to zero. Hypothesis 3 focuses on the imputation of investor expectations about future deals into stock prices. The emphasis is on the idea that capabilities may be revealed to investors for firms that are quite specialized in the deal type and then enacted in forecasts about future deals. If the underlying capabilities in the firm continue to develop in a process of experience-based learning (Helfat and Peteraf, 2003), then some valuable, qualitative information may be disseminated even when a firm has a track record of intensively pursuing a particular type of deal. Essentially, this hypothesis tests the strength of the path dependency that arises from capabilities. The stipulated hypothesis is that, while path dependency may arise, the firm’s trajectory of deals cannot be fully anticipated and imputed into the stock price, and, thus, systematic differences may arise in the cumulative abnormal returns realized by firms over time. This hypothesis would be rejected if the average incremental change in the cumulative abnormal return to later acquisitions or alliances is lessened as a firm accumulates deals of a particular type, because each new acquisition or alliance contains little new and valuable information about the underlying capabilities of the firm. This would arise if, as a result of both or either of these processes, the abnormal returns that arise at deal announcement eventually become distributed around zero to reflect the idiosyncrasies of the focal transaction. Data and methods The dataset includes information on all completed deals conducted by the population of firms that went through an IPO between 1988 and 1999, but that conducted no acquisitions or alliances prior to their IPOs. The data on the incidence of deals Copyright  2009 John Wiley & Sons, Ltd.

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were drawn from the Securities Data Corporation (SDC) report on Global New Issues. We relied on the COMPUSTAT/CRSP merged database maintained by Wharton Research Data Services for the information necessary to calculate the cumulative abnormal returns to each deal announcement (i.e., stock prices, market returns, etc.). The sample is restricted to the years 1988 through 1999 for two reasons. First, comprehensive data on alliances is not available for years prior to 1988. Comprehensiveness is important for identifying all of a firm’s relevant experience. Second, for years subsequent to 1999, we cannot conclusively identify whether a deal was completed and have only incomplete information about deal characteristics. The first three columns of Table 1, Panel A, describe the screens on the dataset, which was constructed from the population of 3,595 privately held companies that went through IPOs for the first time in their histories between 1988 and 1999. The dataset excludes 949 firms that did no acquisitions or alliances after their IPOs and 629 firms that could not be verified in the Compustat/CRSP merged database maintained by the Wharton Research Data Service. An additional 567 firms were eliminated because they had an acquisition or alliance prior to their IPO. This last exclusion assures that the analysis captures all of the deal experience of these young firms. With these exclusions, the dataset includes 1,450 firms, which we refer to as ‘qualified IPOs’ and that are represented in the fourth column of Table 1a.1 Alliance data for qualified IPOs was gathered from the SDC Joint Ventures & Strategic Alliances report. Over 90 percent of the alliances involve only two participants, with five as the largest number of partners involved in any alliance. The qualified IPOs engaged in 1,507 alliances, which constitute 3.15 percent of the total number of alliances for all public firms over the period. Acquisition data was gathered from the SDC Mergers & Acquisitions report. Qualified IPOs 1 These exclusions raise a question about selection bias, that is, perhaps the firms that did deals prior to IPO or that did no deals subsequent to IPO differed systematically from those that are included in the final dataset. Following the suggestion of a referee, we endeavored to find evidence of these systematic differences to conduct a Heckman analysis in two stages but could not isolate an instrument uncorrelated with the subsequent decision to ally or acquire by included firms. Therefore, we cannot conclusively determine whether the characteristics of included firms differed systematically from excluded firms. Our empirical results should be interpreted to apply narrowly only to IPO’d firms with no deals before IPO and with deals after IPO.

Strat. Mgmt. J., 31: 1–18 (2010) DOI: 10.1002/smj


1988 1989 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 Total

IPO year

1988 1989 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 Total

IPO year

0 0 0 0 0 0 2 1 0 5 11 0 19

Agriculture, forestry, & fishing

192 140 130 220 345 453 347 300 485 366 234 383 3595

33 13 24 34 101 32 63 30 54 64 28 18 494

58 59 50 84 146 177 177 130 208 166 86 109 1450

44 83 64 128 172 192 182 116 253 137 49 87 1507

Total # of alliances 0.76 1.41 1.28 1.52 1.18 1.08 1.03 0.89 1.22 0.83 0.57 0.80 1.04

Average # of alliances

0 0 0 2 25 20 9 0 43 32 1 0 132

Construction

81 42 65 72 67 268 376 97 162 161 48 17 1456

Finance, insurance, & real estate 57 163 99 140 316 316 292 148 302 132 37 14 2016

Manufacturing

6 0 23 46 34 61 31 20 33 50 6 9 319

Retail trade

0 4 13 0 12 14 37 9 22 12 0 0 123

Mining

76 50 55 156 260 221 238 225 301 379 175 98 2234

Services

15 10 10 27 55 25 35 95 36 66 15 6 395

Wholesale trade

224 199 225 349 698 765 901 511 700 769 272 75 5688

0 0 0 0 0 0 0 2 0 5 0 0 7

268 282 289 477 870 957 1083 627 953 906 321 162 7195

Total

3.86 3.37 4.50 4.15 4.78 4.32 5.09 3.93 3.37 4.63 3.16 0.69 3.92

Average # of M&As

Unknown

Total # of acquisitions

Qualified IPOs (no pre-IPO deals)

Panel B. Number of deals by qualified IPOs per one-digit SIC industry category

60 62 54 121 190 243 215 185 300 230 137 220 2017

N

Panel A. IPOed firms over 1988–1999 Total IPOed firms that did M&As and alliances and merged to COMPUSTAT/CRSP

Transportation & public utilities

Total # of IPOs from SDC

Table 1. Sample description

6 A. M. Arikan and A. M. McGahan


Research Notes and Commentaries engaged in 5,688 acquisitions between 1988 and 1999, which constitute 8.41 percent of all acquisitions involving public companies over the period. Thus, the qualified IPOs engaged in more than twice as many acquisitions as alliances. We verified the accuracy of the announcement dates of corporate deals following the suggestion of Anand and Khanna (2000) through searches of the Lexis-Nexus database and other business news sources such as the Wall Street Journal online. The accuracy of our estimates of each cumulative average return to a deal was validated through a supplementary analysis on the preannouncement period (spanning the period 100 days prior to five days prior to the reported announcement date) to assure that estimates of cumulative abnormal returns were not inaccurate because of leaked information about deals prior to each event period. The last five columns of Panel A of Table 1 show the total number of alliances and acquisitions among the firms for inclusion in the dataset. Three regularities are worth emphasizing. First, the qualified IPO firms engage in significantly more acquisitions than alliances. Second, the period between 1992 and 1997 accounted for 69 percent of IPO activity, suggesting that this was a ‘hot’ period for IPOs (consistent with Helwege and Liang, 2004: 555; Ibbotson and Jaffe, 1975). As a result, we control for ‘hot’ markets in our analysis. Third, the general level of alliance and acquisition activity varies by IPO year. Thus, year effects are expected to be important. Panel B of Table 1 describes the 7,195 corporate deals conducted by the qualified IPOs. During this period, the highest percentage of deal activity occurred in the service sector (31.05%), closely followed by the manufacturing sector (28.02%). Thus, industry controls are expected to be significant. The dataset includes firms that exited from the population and accounts for differences in their activity. This accounting is important because new firms are prone to delisting due to merger and liquidation. Of qualified firms, 10.41 percent were delisted before their fourth year. Over the entire period, 310 of the 1,450 firms (or 21%) were delisted. The highest mortality rate (52%) occurred among firms that IPO’d in 1990. The dependent, independent, and control variables in the analyses are described in Table 2. The unit of analysis in models for testing all hypotheses is the deal. The dependent variables Copyright  2009 John Wiley & Sons, Ltd.

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for testing Hypothesis 1 are indicators representing whether a deal was either an acquisition (ACQ) or an alliance (ALLIANCE). These models are tested using a logit specification and incorporate generalized estimating equations in models that demonstrate evidence of correlation in errors.2 The dependent variable for testing Hypotheses 2 and 3 is the difference between the stock market reaction to the focal deal from the average for prior deals of the same type conducted by the firm. We operationalized the change in market reaction for successive acquisition (alliance) deals, CHGCAR ACQ (CHGCAR ALL), as the difference between (a) the absolute value of the cumulativeabnormal return (CAR) for the focal acquisition (alliance) and (b) the average absolute value of the cumulative abnormal returns (CARs) for the firm’s prior acquisition (alliance) deals. Thus, the variables CHGCAR ACQ and CHGCAR ALL represent the change in the stock-market response between the focal deal and the firm’s prior deals. Hypothesis 1 on imputed expectations is a test of whether acquisitions or alliances tend to be preceded by strong prior CARs to deals of the same type. The theory here suggests that the incidence of an acquisition is more likely if prior returns to acquisitions are large in absolute value, which occurs as investors incorporate into firm value their expectations that the firm would subsequently pursue same-type deals. To test this hypothesis, we distinguish the effects of investor responses to the most recent deal from the firm’s trajectory of experience with the deal type by including the variables ACQEXP or ALLEXP as controls (Haleblian et al., 2006; Laamanen and Keil, 2008; Zollo and Singh, 2004). We also control for the possibility of nonlinear, diminishing, or enhanced effects of prior experience by including ACQEXPSQ or ALLEXPSQ (Haleblian and Finkelstein, 1999). Hypothesis 2 on concentrated deal experience incorporates several countervailing influences. This 2 The dataset has a panel structure in which multiple deals are represented for each firm. Moreover, we argue that firms pursue deal programs over time, which suggests that the independence assumptions of ordinary logit may be violated. Thus, we examined initial results for significant panel-level variance component and within-group serial correlation to evaluate whether the estimations of a pooled-sample logit model were unreliable. In instances of panel-level variance, we employed a randomeffects model. If these models showed additional evidence of within-firm serial correlation, then we employed generalized estimating equations (GEE). This relatively new technique models the theorized within-firm (within-group) autocorrelation in a panel dataset as a precursor to hypothesis testing.


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Table 2. Description of variables Category

Description

Dependent variables Deal type Deal is an acquisition (Yes=1) Deal is an alliance (Yes=1) Change in [Cumulative abnormal return to the market deal]-[Absolute value of average reaction CARs for prior same-type deals] Independent variables Prior investor Absolute value of average CARs for reaction prior acquisition deals Absolute value of average CARs for prior alliance deals Deal Portion of all prior deals as acquisitions experience Portion of all prior deals as alliances (nb ALLEXP=1-ACQEXP) Nonlinear Squared portion of all prior deals as effects of acquisitions Deal Squared portion of all prior deals as experience alliances Controls Year Deal announcement year

Sector

Firm size Real options Managerial self-interest Immediate prior deal Deal experience Nonlinear effects of Deal experience

IPO occurred in a “Cold” year (Yes=1) Deal announced in 1995–1999 merger boom (Yes=1) Manufacturing Finance, Insurance, & Real Estate Retail Trade Services Log of market value of assets in prior year Sector market/book value of equity for deal year FCF in prior year Prior deal is an acquisition (Yes=1)

Code

Type

Relevant Hypotheses

ACQ ALL CHGCAR ALL

indicator indicator continuous

1 1 2, 3

CHGCAR ACQ

continuous

2, 3

CAREXPACQ

continuous

1

CAREXPALL

continuous

1

ACQEXP

continuous > 0

2

ALLEXP

continuous > 0

2

ACQEXPSQ

continuous > 0

3

ALLEXPSQ

continuous > 0

3

DEALYRt

dummy, t= {1988,. . ., 1999} indicator indicator

All

MANUF FIN RETAIL SERV FIRMSIZE

indicator indicator indicator indicator continuous

All All All All All

MB

continuous

All

FIRMFCF

continuous

All

indicator

All

HOTIPO BOOM

PACQ

All All

Prior deal is an alliance (Yes=1) Portion of all prior deals as acquisitions

PALL ACQEXP

indicator continuous > 0

All 1

Portion of all prior deals as alliances (nb ALLEXP=1-ACQEXP) Squared portion of all prior deals as acquisitions Squared portion of all prior deals as alliances

ALLEXP

continuous > 0

1

ACQEXPSQ

continuous > 0

1

ALLEXPSQ

continuous > 0

1

hypothesis tests whether the change in CARs to a deal as compared to the firm’s prior sametype deals are affected by the firm’s experience in conducting acquisitions and alliances. We seek Copyright  2009 John Wiley & Sons, Ltd.

to find evidence in line with the idea that investors react less strongly to deals of a particular type among experienced firms, because their expectations about the contemporaneous deal had been Strat. Mgmt. J., 31: 1–18 (2010) DOI: 10.1002/smj

Research Notes and Commentaries previously incorporated into the firm’s financial market value. To test the hypothesis, we regress the CARs onto ACQEXP and ALLEXP. A finding of a negative and significant coefficient on ACQEXP and ALLEXP favors the stipulated explanation that investors tend to anticipate deals that are part of a program. The alternative to Hypothesis 2 reflects the idea that deal programs may change over time for a number of reasons. Firms may pursue new kinds of capabilities and change their deal strategies (Helfat and Peteraf, 2003). ‘Digestion’ problems due to an increase in the size, scope, recency, and complexity of deals may prevent firms from exercising their capabilities effectively, and may lead them to pursue other types of deals (Hoffman, 2007; Homburg and Bucerius, 2006. Or firms may eventually exhaust the pool of available partners for exercising particular capabilities. A finding of no significant relationship—or even of a positive and significant relationship—between CARs and ACQEXP and/or ALLEXP would suggest that these countervailing influences are at least as prevalent as the influence of capability development. Hypothesis 3 on continuing, unobservable capability development stipulates that the CARs to either acquisitions or alliances do not ultimately converge toward zero based on the information implied by the historical concentration of firms on particular types of deals. The theory here is that, eventually, investors cannot fully observe capabilities, infer the implications for path dependency, and build into the stock price an accurate expectation about the series of deals pursued by firms. As a result, any CAR associated with a marginal deal in the long run reflects new information disseminated about underlying capability development. The null is that signals become less and less noisy, ultimately converging toward zero, and reflect only adjustments for the idiosyncratic characteristics of the partner or the transaction. To test Hypothesis 3, we consider whether the dependence of CARs on ACQEXP and ALLEXP is affected by nonlinearities, which we represent by taking each of these independent variables in squares (i.e., ACQEXPSQ and ALLEXPSQ, respectively) after controlling for ACQEXP and ALLEXP. For example, consider a firm that has done half of its deals as acquisitions as compared to a firm that has done all of its deals as acquisitions. This hypothesis evaluates whether the CARS to a subsequent acquisition for these firms differs systematically—on the Copyright  2009 John Wiley & Sons, Ltd.

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theory that the firm with a history of proportionately more acquisitions may not disseminate more information into the investor community about the likelihood for an additional acquisition than the firm with proportionately fewer historical acquisitions. A finding of a significant relationship in the test of Hypothesis 3 would favor the hypothesis that investors do not infer from the firm’s concentrated experience that it will pursue additional same-type deals; this alternative would be consistent with the idea that investors and the managers within them change strategies or build different capabilities after accumulating experience. We used cross-sectional time series nonlinear regression models for testing Hypothesis 1 and cross-sectional time series linear models for testing Hypotheses 2 and 3. All models are specified on assumptions of random effects using generalized least squares (GLS) estimators. The dataset has an unbalanced panel structure that comprises multiple deals for each firm. Theoretically we expect (i) within-group autocorrelation across each deal and (ii) lack of independence across observations due to having multiple deals for firms to be present in our specifications. Therefore we account for the lack of independence of observations for each firm by clustering the error terms and calculating the robust standard errors. Also we test for the existence of within-group autocorrelation as well as within-group cotemporaneous correlation using the Wooldridge test for autocorrelation in panel data (Wooldridge, 2002) and for all specifications we failed to reject the null that there is no evidence of within-group autocorrelation across deals. Thus, the models are robust. CARs were calculated with a market model based on the CRSP Value-Weighted Index and an estimation period of [−60,. . ., −20] days around the announcement day of t=0, with abnormal returns calculated using a 10-day event window.3 3 The analysis was verified through three robustness checks on the method for calculating CARS: 1) instead of CRSP valueweighted index, we used CRSP equally weighted index, which ignores the heterogeneity in the market capitalizations of firms included in the index; 2) the CARS were estimated using a window of [−100,. . ., 20] to increase the accuracy of the market model but at the cost of a decrease in the relevance of the event window to the event; 3) the CARS were estimated on models that incorporated varying numbers of days in the event window around the announcement date, that is, of [−10.,+10], [−5,. . ., +5], and [−1.,+1]. Although differences in the results arose, the results associated with the hypotheses presented in this study did not vary statistically.


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All of the analyses incorporate a series of control variables as summarized and described in Table 2. First, year and sector indicators represent the idiosyncratic effects of year of the deal and the sector of the firm on the firm’s proclivity for either acquisitions or alliances and on the CARs to deals. These are represented in the variable names DEALYEAR88 through DEALYEAR99 [and MANUF (for ‘manufacturing’), FIN (for ‘financial services’), RETAIL (for ‘wholesale and retail trade’), and SERV (for ‘business, health and other services’)]. Sectors are assessed through inspection of the firm’s primary standard industrial classification code at the onedigit level. Second, we include an indicator using Helwege and Liang’s (2004) classification on whether the firm itself went through its IPO in a ‘hot’ year (represented as HOTIPO). We also test whether the deal itself occurred during the 1995–1999 dotcom boom by including an indicator called BOOM for deals during this period. To resolve colinearity between BOOM and the year control variables, we omit one of the independent year dummies. Third, we include a measure of the firm’s size as a control variable (called FIRMSIZE), which we take as the log of the firm’s assets in the prior year. Imagine that a firm grows over time—either de novo or through acquisition. As the firm ages, it may become larger relative to the size of its targets and partners, and therefore the impact of successive deals on the firm’s CAR may diminish independently of the firm’s capabilities for conducting deals. Therefore, FIRMSIZE is included in regressions on CARs. This variable is also included in the logit analysis to account for the possibility that larger firms have greater ‘capacity’ to conduct multiple programs of acquisitions and alliances. Ideally, we would also incorporate information on the size of the target or partner in the analysis. Unfortunately, data on the characteristics of the targets and partners are only sparsely available through SDC, and as a result, the number of observations that are included in the regression models drops significantly when TARGETSIZE is included. In a sensitivity analysis, we estimated three sets of models to isolate the implications of the missing data for our principal conclusions:4 1) the full model, including an estimated coefficient 4 The full results of these sensitivity analyses are available from the authors.


on TARGETSIZE, in the subsample for which data are available, 2) an abbreviated model that omits the TARGETSIZE variable on the same subsample, and 3) an abbreviated model that omits TARGETSIZE on the whole sample. The results on the first set of these models indicate a significant negative and economically small coefficient on TARGETSIZE, suggesting that CARs may have declined through successive deals partly because the protagonist firms pursued deals that were successively smaller relative to the firms’ own sizes. In the second set of models in which TARGETSIZE was omitted in the subsample, the estimated value of the coefficients changed less than five percent from the fully specified model, indicating that TARGETSIZE did not materially influence the estimates of the other coefficients in the models. We therefore report in our main results on the third set of models in which all the data is deployed and the TARGETSIZE variable is omitted. If additional information were available, we would include control for other facets of the target/partner’s characteristics such as the target’s industry, age, and the degree of relatedness between the firm and the target. Controlling for these facets of specific deals would allow us to identify idiosyncrasies that had not been previously anticipated by investors. Unfortunately, only very limited information is available on deal and target characteristics (such as TARGETSIZE, as noted earlier). The reason relates to the fact that our research focuses on the deals of newly IPO’d firms. While the acquisitions and alliances pursued by these firms are announced publicly, they often involve private and very small targets for which no information is recorded. Thus, we cannot model or control for idiosyncratic elements of the deals. Yet despite this deficiency, we proceed by noting that, unless idiosyncratic elements of deals are systematically favorable or unfavorable, the absence of these controls creates a bias against hypotheses derived from theories that enduring capabilities and deal programs are involved in investor responses to deals. Fourth, we include a measure of the firm’s overall growth options on the theory that alliances may provide firms with real options for further growth that are not available through acquisitions (Villalonga 2002). Folta and O’Brien (2004) similarly maintain that acquisitions may provide firms with capabilities that may pay off in the future. Pursuing Strat. Mgmt. J., 31: 1–18 (2010) DOI: 10.1002/smj

Research Notes and Commentaries deals to acquire real options may occur either independently or simultaneously with the development of capabilities for conducting deals of a particular type. To control for the independent effects of real options on the firm’s decision to pursue deals of a particular type, we include the measure of the firm’s overall growth options employed by Folta and O’Brien (2004): the market-to-book value of assets, which we call MB. Fifth, we control for the possibility that managers pursue programs of successive acquisitions or even programs of alliances in their own selfinterest or self-dealing rather than because the firm has developed capabilities for conducting the particular type of deal. Dyer et al. (2004) suggest that this problem may be particularly prevalent in acquisitions and alliances. Pursuing acquisitions or alliances in self-interest could influence both the incidence and returns to specific deals. To control for this possibility, we include a measure of the firm’s free cash flow (called FIRMFCF). Sixth, we control for the possibility that the immediate prior deal type has an especially strong influence on the current deal. The inclusion of this variable, called PACQ and PALL, reflects Hayward’s (2002) recency hypothesis, which suggests that firms are especially likely to replicate deals that are most immediate in their experience. In theory, recency effects may arise from cognitive biases (Tripsas and Gavetti, 2000) and stability in the short-run environment. In this context, managers may choose to pursue an acquisition or alliance immediately after a successful deal of one particular type because of beliefs, ideas, and thoughts that bridge between deals.

RESULTS Table 3 presents results on tests of Hypotheses 1 through 3. Each column is a distinctive model that is estimated separately from the others. The panel at the bottom reports goodness-of-fit statistics, information on the number of observations in each model, and modeling assumptions. The number of observations, reported at the bottom of each column, is less than the 7,150 total deals reported in Table 1 due to specialization by type of deal or because of dropped observations due to missing information for control variables. The independent variables of interest are presented in the initial Copyright  2009 John Wiley & Sons, Ltd.

11

rows and are followed by estimates on the control variables. The first set of four columns represents the results of tests on Hypothesis 1 for alliances and acquisitions, respectively. This hypothesis stipulates that the type of deal depends on prior CARs. The theory is that firms that had provoked a large response to previous deals from investors had disseminated more information into the investor community about their capabilities, path dependency, and deal strategy, and that this process would be associated with more deals of the same type. Hypothesis 1 on imputed expectations is confirmed for alliances and acquisitions as the coefficients on CAREXPALL and CAREXPACQ in the second and fourth columns are significant. The results are consistent with prior research showing that the average CAR associated with alliances is positive and with acquisitions is negative (Chan et al., 1997; Das, Sen, and Sengupta, 1998; Krishnaswami and Subramaniam, 1999). In the second column, the sign on CAREXPALL is positive, which signifies that alliances are preceded by strong positive responses to prior alliances, but in the fourth column, the sign on CAREXPACQ is negative, which signifies that acquisitions are preceded by strong negative responses to prior acquisitions. Specifically, an increase by one percent in the absolute value of CARs for prior alliance deals is associated with an increase in the odds of a subsequent alliance by 11 times. Conversely, a one percent increase in the absolute value of CARs for prior acquisition deals is tied to a decrease in the odds of a subsequent acquisition by nine times. These results are consistent with theories suggesting that strong and positive feedback serves as an encouragement to pursue alliances, whereas strong but negative feedback serves as a discouragement to pursue acquisitions. Additional research is needed to evaluate whether the positive prior CAR for alliances occurs as investors observe underlying capabilities with each deal and thus anticipate subsequent value-creating alliances, and whether the negative CAR for acquisitions reflects the same process—with investors observing underlying acquisition capabilities and then anticipating additional value-destroying mergers. The tests on Hypothesis 2 on concentrated deal experience, represented in the fifth and sixth columns in Table 3, are also confirmed. Hypothesis 2 stipulates that incremental changes in CARs Strat. Mgmt. J., 31: 1–18 (2010) DOI: 10.1002/smj


FIN

MANUF

1999

1998

1996 1997

1995

1994

DEALYR1988–DEALYR1992 1993

ACQEXPSQ

ACQEXP

CAREXPACQ

ALLEXPSQ

ALLEXP

CAREXPALL

Hypothesis Model Dependent variable

Table 3. Results

(a) 0.199 0.293 −0.046 0.282 0.285 0.218 (a) 0.301 0.193 0.123 0.190 0.495∗∗ 0.194 0.719∗∗∗ 0.178 0.098 0.233

2.896∗∗∗ 0.293 −1.032∗ 0.561

1 LOGIT ALL

(a) −0.036 0.382 0.04 0.362 0.349 0.28 (a) 0.490∗∗ 0.241 0.129 0.237 0.433∗ 0.238 0.538∗∗ 0.229 0.017 0.355

2.411∗∗∗ −0.821 2.181∗∗∗ 0.576 −0.284 0.861

1 LOGIT ALL

2.510∗∗∗ 1.209 1.249∗∗ 0.554 (a) −0.234 0.293 0.035 0.281 −0.271 0.217 (a) −0.274 0.193 −0.106 0.189 −0.489∗∗ 1.193 −0.721∗∗∗ 0.176 −0.094 0.232

1 LOGIT ACQ

−2.235∗∗∗ 0.689 2.092∗∗∗ 0.341 1.712∗ 0.894 (a) −0.294 0.345 −0.101 0.332 −0.045 0.254 (a) −0.176 0.213 −0.098 0.209 −0.364∗ 0.215 −0.593∗∗∗ 0.191 −0.06 0.243

1 LOGIT ACQ

(a) 0.012 0.037 −0.004 0.03 0.012 0.026 (a) −0.011 0.025 −0.023 0.026 −0.049∗∗ 0.025 −0.005 0.021 −0.01 0.022

−0.084∗∗∗ 0.03

2(b) OLS CHGCAR ALL

(a) −0.026 0.024 −0.043∗∗ 0.021 −0.002 0.011 (a) −0.011 0.009 −0.004 0.01 −0.033∗∗∗ 0.013 −0.011 0.013 0.024∗ 0.012

−0.039∗∗ 0.017

2 OLS CHGCAR ACQ

(a) 0.012 0.036 −0.001 0.029 0.002 0.026 (a) −0.01 0.025 −0.02 0.025 −0.044∗ 0.024 −0.009 0.021 −0.027 0.022

−0.173∗∗∗ 0.039 0.233∗∗∗ 0.071

3(b) OLS CHGCAR ALL

−0.040∗∗ 0.018 0.199∗∗∗ 0.048 (a) −0.023 0.019 −0.039∗∗ 0.018 −0.003 0.01 (a) −0.01 0.009 −0.003 0.009 −0.029∗∗∗ 0.011 −0.008 0.015 0.022 0.015

3 OLS CHGCAR ACQ

12 A. M. Arikan and A. M. McGahan



na −0.555∗ na 462.47∗∗∗ −1576.60 3978 Ramdom effects(c)

−2.281∗∗∗ 0.361

(a) 0.003 0.190 0.053 0.292 −0.235 0.274 −0.009 0.037 0.247∗∗∗ 0.043 0.000 0.000 −0.021 0.157

na −1.027∗∗ na 174.45∗∗∗ −897.01 1601 Ramdom effects(c)

−2.271∗∗∗ 0.457

(a) −0.089 0.245 0.106 0.348 −0.294 0.347 0.027 0.045 0.226∗∗∗ 0.053 0.000 0.000 −0.011 0.161

na −0.600∗∗ na 472.06∗∗∗ −1574.791 3978 Ramdom effects(c)

−0.001 0.155 1.834∗∗∗ 1.387

(a) −0.003 0.189 −0.027 0.29 0.209 0.273 0.007 0.037 −0.250∗∗∗ 0.043 0.000 0.000

na −0.615∗ na 263.47∗∗∗ −1311.187 3534 Ramdom effects(c)

0.001 0.164 2.386∗∗∗ 0.470

(a) 0.096 0.202 −0.288 0.307 −0.067 0.319 −0.006 0.041 −0.265∗∗∗ 0.048 0.000 0.000

0.07 na 0.31 52.996∗∗∗ na 881 Ramdom effects(c)

−0.083∗∗ 0.039

(a) −0.042∗ 0.023 −0.070∗ 0.037 0.01 0.031 0.008∗ 0.004 −0.001 0.005 0.000 0.000 −0.012 0.021

0.03 na 85.2∗∗∗ 57.52∗∗∗ na 3041 Ramdom effects(c)

−0.011 0.010 −0.011 0.026

(a) −0.033∗∗∗ 0.013 −0.064∗∗ 0.026 −0.030 0.020 −0.001 0.003 0.002 0.003 0.000 0.000

0.08 na 0.1 71.52∗∗∗ na 881 Ramdom effects(c)

−0.132∗∗∗ 0.041

(a) −0.047∗∗ 0.023 −0.055 0.035 0.017 0.031 0.009∗∗ 0.004 0.002 0.005 0.000 0.000 −0.014 0.021

0.04 na 83.46∗∗∗ 68.54∗∗∗ na 3041 Ramdom effects(c)

−0.014 0.010 −0.060∗∗ 0.029

(a) −0.032∗∗ 0.016 −0.059∗∗ 0.028 −0.023 0.018 0.000 0.003 0.003 0.004 0.000 0.000

Significance levels are reported as ∗ p