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STAKEHOLDERS’ INVOLVEMENT IN MERGERS AND ACQUISITIONS:
THREE EMPIRICAL STUDIES
A dissertation presented
by
JaSeung Koo
to
the Graduate School of Commerce
in partial fulfillment of the requirements
for the degree of
Doctor of Philosophy
in the subject of Commerce
Waseda University
Tokyo, Japan
April 2017
○C 2017 JaSeung Koo
All rights reserved.
ii
Dissertation Advisor: Professor Tomoaki Sakano JaSeung Koo
STAKEHOLDERS’ INVOLVEMENT IN MERGERS AND ACQUISITIONS:
THREE EMPIRICAL STUDIES
ABSTRACT
This dissertation consists of three separate but inter-related studies with a common
theme, namely, stakeholders’ involvement in mergers and acquisitions (M&As). Different
methodologies and viewpoints within stakeholder theory and the resource dependence
perspective are used for the analysis.
The first study examines the impact of an acquisition announcement on a market
reaction to an acquirer’s alliance partner in a bilateral alliance. From a transaction-cost
perspective, I argue that the market valuation of an alliance partner around an acquisition
announcement is negative, because the stock market recognizes that an acquisition causes an
unanticipated increase in the uncertainty of the acquirer’s behavior, decreasing the expected
value from the alliance. Additionally, the negative impact of an acquisition announcement
depends on the alliance and acquisition characteristics, which affect the degree of unanticipated
increase in the acquirer’s behavioral uncertainty and the alliance’s tolerance of this unanticipated
increase. Using an event study of 347 alliances associated with 150 acquisitions of Japanese
public non-financial firms, I found general support for my hypotheses.
Extensive management literature exists on stakeholder influence on corporate business
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operations, yet information is scarce on whether and how stakeholders influence M&A progress
after the public announcement. The second study focuses on three types of primary
stakeholders—employees, shareholders, and lenders—and examines their influence on the
likelihood of completing an announced M&A. This study explores stakeholder reactions, which
reflect their anticipation of benefits and losses from the proposed M&A with an empirical
analysis of longitudinal data for listed Japanese non-financial firms’ M&As between 1995 and
2012, yielding a sample of 3,039 M&A cases for the analysis of deal completion probability. Two
out of four hypotheses were supported by the empirical results, showing that the target firm’s
employees are concerned about their job stability and react negatively to the acquisition process
when the acquiring firm’s employees outnumber them, assuring their job stability, and the
lenders become supportive if the acquirer has a higher dependency on financial institutions to
achieve new business opportunities. These findings offer new insight into stakeholder
relationships in M&As. This study demonstrates the influence of external determinants on the
success of an M&A, which provides an outward perspective in addition to the focus on internal
factors in existing research. In addition, this study proposes dynamic settings when approaching
stakeholder interaction with firms.
The third study investigates cases where both the acquirer and the target firm in an M&A
use a common lender. Specifically, the study examines the impact of the common lender and the
lender’s relationships on the acquirer’s cumulative abnormal returns. The hypotheses are as
follows: 1) the existence of a common lender is negatively associated with the acquirer’s
abnormal returns; 2) the strength of the ties between the common lender and the acquiring and
target firms is positively associated with the acquirer’s abnormal returns. Using regression
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analyses on M&A transactions in Japan between 1995 and 2012, the cumulative abnormal
returns of 448 sampled firms were examined; the hypotheses were generally supported.
Taken together, these three studies are based on previous theoretical and empirical
foundations and attempts to advance strategy research by applying various dynamic perspectives
to reflect the rapidly changing business environment.
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ACKNOWLEGMENTS
To complete this dissertation, some individuals provided me with tremendous support.
First, I am indebted to my dissertation chair, advisor, mentor, and friend Tomoaki Sakano and co-
advisor Junichi Yamanoi for their exceptional guidance, inspiration, and patience. I also
appreciate committee members Tatsuhiko Inoue and Jesper Edman for their insightful comments
to improve this dissertation. In addition, I am grateful to my friend EungKyo Suh for his
guidance and moral support from the beginning of my doctoral course, and to my colleagues
Tsukasa Yamaguchi and Susumu Ohira for their positive energy.
The completion of this dissertation would not have been possible without the strong
support and patience of my wife, Jiin Um, and my mother, YoungSook Lee. I would like to take
this opportunity to thank them from the bottom of my heart for always being there and for taking
care of our lovely daughter, Bona Koo, and son, BonJoon Koo. In addition, I express my
gratitude to my father, who passed away in 2007, and would like to give him every honor for
completion of this dissertation.
Finally, I thank God for giving me the strength, ability, and courage to undertake and
complete this work. I thank Him for giving me the courage to quit work and decide to come to
Japan and start university work, and eventually to complete it. I am also grateful for the
opportunity to give back to society using what I have learned. I thank Him for never giving up on
me and for His constant and unconditional love, reflected by the way He has shaped my life.
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TABLE OF CONTENTS
LIST OF TABLES…………………………………...………………………………………….. ix
CHAPTER 1. GENERAL INTRODUCTION………...……………………………………….… 1
1.1 Study One: Acquisition Announcements and Stock Market Valuations of Acquiring Firms’
Alliance Partners……………………………………………………………………………....... 2
1.2 Study Two: Stakeholders’ Influence on the Deal Completion Probability in M&As…....…. 4
1.3 Study Three: How Does a Common Lender to Both Sides of the M&A Deal Influence the
Acquirer’s Market Valuation?....................................................................................................... 6
1.4 Overall Contribution………………………………………………………………..………. 7
CHAPTER 2. STUDY ONE: ACQUISITION ANNOUCEMENTS AND STOCK MARKET
VALUATION OF ACQUIRING FIRMS’ ALLIANCE PARTNERS………………………......... 9
2.1 Introduction………………………………………………………………………..………... 9
2.2 Theory and Hypotheses……………………………………………………………...…….. 12
2.2.1 Transaction hazards and expected returns from alliances…………………..………… 12
2.2.2 Acquisition impact on alliance partners………………………………...…...………... 14
2.2.3 Alliance characteristic 1: Past alliance experience between an acquirer and an alliance
partner…………………………………………………..……………………………...…… 16
2.2.4 Alliance characteristic 2: Horizontal vs. non-horizontal alliance…..……………...…. 18
2.2.5 Alliance characteristic 3: Technological alliance………………...………...…………. 19
2.2.6 Acquisition characteristic 1: Acquisition deal value………………..………………… 20
2.2.7 Acquisition characteristic 2: Related vs. unrelated acquisition…..………...………… 21
2.2.8 Acquisition characteristic 3: Industry relatedness between a target and an alliance
partner………………………………………………………………………………………. 23
2.3 Research Methods………………………………………………………..……………...… 24
2.3.1 Sample and data collection……………………………………………………..…….. 24
2.3.2 Event study methodology………………………………...………………...…….…... 26
2.3.3 Variables and measures…………………………………………………...…………... 27
2.3.4 Model specification……………………………………...…………………………..... 31
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2.4 Results……………………………………………………..………………………………. 32
2.4.1 Robustness checks………………………………………...………………………….. 38
2.5 Discussion and Conclusions………………………..……………………...……………… 40
2.5.1 Theoretical and practical implications…………………………......…………………. 41
2.5.2 Limitations and future directions………………………...…………………...………. 44
CHAPTER 3. STUDY TWO: STAKEHOLDERS’ INFLUENCE ON THE DEAL
COMPLETION PROBABILITY IN M&As……………..……………………….……….…… 46
3.1 Introduction…………………………………..……………………………………………. 46
3.1.1 Research streams on M&A…………………………………...……...……………….. 47
3.1.2 Stakeholders and M&As………………………………………...…...……………….. 48
3.2 Literature Review………………………………………………...…...…………………… 50
3.2.1 M&A announcement to deal completion / withdrawal…...……...………...…………. 50
3.2.2 Theory and hypotheses……………………………………...…………….…………... 52
3.3 Research Methods…………………………………………….…………………………… 58
3.3.1 Sample and data………………………………………...……...……………………... 58
3.3.2 Variables and measures………………………………...…...………………………… 58
3.4 Results……………………………………………………………..………………………. 60
3.5 Discussion and Conclusion………………………………...…………………..………….. 64
3.5.1 Theoretical and practical implications……………...…………………...……………. 64
3.5.2 Limitations and directions for future research…..………………………...………….. 66
CHAPTER 4. STUDY THREE: HOW DOES A COMMON LENDER TO BOTH SIDES OF
THE M&A DEAL INFLUENCE THE ACQUIRER’S MARKET VALUATION?..................... 68
4.1 Introduction………………………………………………………………………………... 68
4.2 Theory and Hypotheses……………………………………………………………………. 72
4.2.1 Common lender and lender benefits………………………………………………..… 72
4.2.2 Strong ties between the common lender and borrowers and borrower benefits ……... 77
4.3 Research Methods……………………………………………………………………...….. 79
4.3.1 Data and samples…………………………………………………………………....... 79
4.3.2 Cumulative abnormal returns……………………………………………………..…... 80
4.3.3 Variables and measures………………………………………………………...……... 81
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4.3.4 Research model……………………………………………………………....……….. 83
4.4 Results……………………………………………………………………………………... 84
4.5 Discussion and Conclusions……………………………………………………...……... 89
4.5.1 Theoretical and practical implications……………………………………………...… 91
4.5.2 Limitations and directions for future research…………………………………..……. 92
CHAPTER 5. GENERAL CONCLUSION…………………………………………………...... 94
5.1 Major Findings…………………………………………………………………………... 94
5.2 Theoretical and practical implications………………………………………………...…... 97
5.3 Limitations and directions for future research……………………………………..…….. 102
REFERENCES………………………………………………………………………...…….... 106
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LIST OF TABLES
Table 1: Descriptive statistics and correlation matrix…………………………..………………. 33
Table 2: Cumulative abnormal return of an alliance partner…………………..……………….. 34
Table 3: Result of regression analysis of cumulative abnormal return of an alliance partner….. 36
Table 4: Descriptive statistics and correlation matrix………………………………………..…. 61
Table 5: Result of regression analysis of deal completion probability………………...……….. 63
Table 6: Descriptive statistics……………………………………………………...………..….. 85
Table 7: Correlation matrix……………………………………………………...…………….... 86
Table 8: Result of regression analysis of acquirer’s cumulative abnormal return……...………. 88
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CHAPTER 1. GENERAL INTRODUCTION
Mergers and acquisitions (M&As) are a popular strategic option; successful execution of
an M&A and achievement of the targeted financial and strategic objectives have become one of
the most important issues for a firm’s long-term sustainability. Therefore, how to undertake
successful M&As from start to finish has garnered significant academic and business interest
(King, Dalton, Daily, and Covin, 2004). Much academic literature on M&As has focused on
methodologies with scientific accuracy for financial analyses or measuring acquisition
performance via strategic analyses and has paid attention mostly to the participants of M&As
(e.g., Capron, 1999; Cartwright and Cooper, 1993; Chatterjee, 1986; Datta, Pinches, and
Narayanan, 1992; Ravenscraft and Scherer, 1987).
On the other hand, management researchers have demonstrated stakeholders’ strong
influence on corporate business operations and firm performance, and have asserted the
importance of appropriate stakeholder management for an organization’s sustainable growth (e.g.,
Carroll, 1991; Freeman, 1984; Mason, Kirkbride, and Bryde, 2007). Stakeholders have a variety
of channels to exert influence, which enables them to participate in a firm’s strategic decision-
making process (Preston and Sapienza, 1990). Therefore, stakeholders’ responses to a firm’s
critical strategic decisions, such as an M&A, are one of the most important issues to manage for
a successful M&A. Although researchers have recognized stakeholders’ significant influence on
a firm’s business operations from various perspectives, only a few studies have considered
stakeholders in the M&A process.
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According to stakeholder research, firms are surrounded by a variety of stakeholders
who act strategically based on their relationship with the focal organization and react sensitively
to situational changes that may affect their future benefits or losses (e.g., Frooman, 1999;
Jawahar and McLaughlin, 2001; Rowley and Moldonevau, 2003). Therefore, when stakeholders
confront any event that accompanies massive changes in the business environment, I expect them
to have a corresponding reaction to defend their existing power and benefits in their relationship
with the focal organization. Furthermore, I expect the reactions of stakeholders with close
relationships to firms to be clearly visible from the outside. Thus, this dissertation attempts to
deepen the understanding of why and how various stakeholders respond to the focal firm’s public
announcement of an M&A in empirical settings by presenting three separate but inter-related
studies. Each study is discussed separately in the following three sub-sections.
1.1 STUDY ONE: ACQUISITION ANNOUCEMENTS AND STOCK MARKET
VALUATION OF ACQUIRING FIRMS’ ALLIANCE PARTNERS
The first study aims to examine the impact of post-formation events that occur to alliance
partners, which are not necessarily anticipated at the formation of alliances, on the expected
returns from their alliances. In this study, I focus on alliance partners’ acquisitions as significant
post-formation events, which potentially influence the activities in and commitment to the
alliances.
An M&A requires firms to engage in the restructuring and integration of their business
portfolios and to commit enormous financial and human capital to acquisition-related activities
(for a review, see Haleblian, Devers, McNamara, Carpenter, and Davison, 2009). Accordingly, an
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acquiring firm’s alliance partners will suffer from unanticipated renegotiation or unintended
dissolution of their alliances. Given the benefits of an alliance, its performance depends on the
costs of contracting, adjusting, monitoring, and enforcing activities associated with the alliance.
The main proposition is that a firm’s acquisition increases the governance costs of its alliance
with an alliance partner, thereby reducing the expected value that the alliance partner can create
through the alliance. An acquisition requires the acquirer to engage in restructuring its business
portfolio. Such opportunistic attempts inevitably raise the governance costs of the existing
alliances. Thus, the alliance partners of an acquirer can create less value from their alliances after
the acquisition announcement.
The negative impact of the acquisition announcement of an acquirer on its alliance
partner’s market evaluations varies depending on the alliance and acquisition characteristics
pertaining to asset specificity and transaction uncertainty. The number of past alliances between
an acquirer and its alliance partner, technological alliances, industry relatedness of alliances, and
acquisition transaction value influence the degree of increase in the governance costs of an
alliance, because these factors determine the asset specificity and transaction uncertainty of the
alliance. In addition, the aforementioned relationships can be moderated by the industry
relatedness of acquisitions. In the case of unrelated acquisitions, an acquirer has to engage in
larger-scale change in its business portfolio.
Through event study and regression analysis, I find general support for the hypotheses.
The findings of this study offer new insight into inter-firm cooperation, such as the fact that
inter-firm cooperation is influenced by post-formation events that have not necessarily been
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anticipated at the alliance formation stage. By illuminating this point, my study opens a new
research direction in the field of inter-firm cooperation.
1.2 STUDY TWO: STAKEHOLDERS’ INFLUENCE ON THE DEAL COMPLETION
PROBABILITY IN M&As
Study two focuses on three types of primary stakeholders—employees, shareholders, and
lenders—and examines their influence on the likelihood of completing an announced M&A. I
explore stakeholders’ reactions, which reflect their anticipation of benefits and losses from the
focal firm’s balancing operations for the power and resources after closing the proposed M&A,
with an empirical analysis of longitudinal data for listed Japanese non-financial firms’ M&As.
In study two, I examine the opportunistic behavior of primary stakeholders (i.e.,
employees, shareholders, and lenders) to create a positive or negative impact on the success of
the M&A effort. Employees anticipating benefits from the proposed transaction become strong
supporters of the deal, making it easier for the acquirer to persuade them to cooperate and
lowering the cost of closing the deal successfully. Thus, I expect that the target firm employees
anticipate they would be better off after the transition, considering the higher compensation level
for the acquiring firm’s employees compared to that of the target firm’s employees. This would
encourage cooperation from the target firm’s employees, resulting in a positive association with
the deal completion probability. Unlike the compensation level, the larger work force of the
acquirer firm could be recognized as a potential risk factor of the restructuring from the target
firm employees’ perspective. Therefore, the move would face resistance from the target firm’s
employees, resulting in a negative association with the likelihood of a deal completion. In the
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event of an M&A, shareholders eventually gain investment returns through dividends unless
they sell their shares, and they automatically pay attention to the post-acquisition stage (Dorata,
2012). Since dividend propensity varies by company, owning shares in a firm that tends to offer
high dividends is important for all investors. Thus, from the shareholders’ perspective, the
merged firm’s dividend propensity is a considerably crucial point when deciding their response
to the proposed transition. If the acquiring firm were to show a higher dividend propensity than
the target firm, shareholders would be likely to cooperate with the deal, increasing the deal
completion probability. Previous literature has demonstrated the lenders’ benefits from the
borrower’s higher dependency on financial institutions (i.e., strong lender–borrower relationship),
generating new business opportunities for lenders (e.g., Bharath, Dahiya, Saunders, and
Srinivasan, 2007; Drucker and Puri, 2005; Petersen and Rajan, 1994). Based on such findings,
the target lenders are expected to respond positively to the proposed M&A once they recognize
that the acquiring firm has higher dependency on financial institutions and potential business
opportunities, thereby increasing the deal completion probability.
Through statistical analysis, I find support for two out of four hypotheses using a sample
of 3,039 cases for the analysis of deal completion probability. The findings of this study offer
new insight into stakeholder relationships in M&As and open a new research direction in the
field of stakeholder theory and M&A research.
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1.3 STUDY THREE: HOW DOES A COMMON LENDER TO BOTH SIDES OF THE
M&A DEAL INFLUENCE THE ACQUIRER’S MARKET VALUATION?
The third study asks the following questions. As a primary stakeholder, how does the lender react
to a firm’s M&A? How would the deal be influenced when the same lender advises both sides of
the deal? How would this common lender’s strong lender–borrower relationships influence deal
progress and post-acquisition performance? In an empirical setting, this study examines cases in
which both sides of the M&A deal have the same lender. The influence of the common lender, as
a stakeholder who directly and significantly influences a firm’s business activities, on deal
progress and M&A performance is investigated, along with the lender’s relationship with the
firms.
Prior research on lending relationships describes various benefits to lenders and
borrowers of a strong relationship, such as additional loans, fee-based advisory services, and a
stable financial resource supply (Burch, Nanda, and Warther, 2005; Drucker and Puri, 2005;
Yasuda, 2005). Based on such research, this study predicts that the existence of a common lender
on both sides of the deal and the nature of lending relationships bring benefits and costs to the
lender and borrower, such that the lender and borrower react and influence the deal progress and
post-acquisition performance. I expect the common lender on both sides of the deal to reinforce
the lending relationship with the borrower and, in turn, the lender’s benefit, leading to the
lender’s cooperation in the deal. However, with the same lender on both sides of the deal, the
borrower firm and its shareholders would consider the potential risks from over-centralized
benefits to one lender, which may cause negative returns for the borrower, and therefore a
negative association with post-acquisition performance. As for the common lender’s
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relationships, the borrower’s higher dependency on the lender in terms of loan amounts could be
more beneficial to the borrower than to the lender (Dass and Massa, 2011), since a higher level
of borrower dependency could imply a higher risk for the lender in managing existing loans and
business opportunities with other current “big” clients. Thus, lenders may cede profits in this
relationship, probably creating a negative response to the deal from the lenders. However, a
strong relationship between a borrower and lender is positively associated with the lender’s
future returns.
Statistically analyzing 448 cases of post-acquisition performance, I obtain empirical
support for two hypotheses. The findings of this study extend the research horizon on lender–
borrower relationships to the context of M&As and offer in-depth understanding of such
stakeholders’ underlying motives in influencing firms’ strategic actions.
1.4 OVERALL CONTRIBUTION
Taken together, studies one, two, and three of this dissertation offer several significant
contributions to the M&A and stakeholder literature. First, this dissertation successfully
demonstrates the influence of external determinants on the success of an M&A, which enables an
outward perspective in addition to the existing internal focus of existing research. This
dissertation focuses on and provides empirical support for the role of stakeholders surrounding
focal firms and M&As, which so far have not been regarded as influential factors in management
research.
In addition, this dissertation successfully proposes dynamic settings when approaching
stakeholders’ interactions with firms. Management literature has addressed stakeholder issues in
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a static business environment, and this study induces a dynamic perspective to capture the
extemporary but fundamental motivation of stakeholders’ responses. Moreover, this dissertation
considers stakeholders’ motivations in their reactions from a dyadic viewpoint by addressing
both the acquiring and target firms’ stakeholders and comparisons to measure the influence on
dependent variables.
Overall, the three studies in this dissertation provide empirical evidence for stakeholders’
influence on M&As with different stakeholders’ perspectives, using different methodologies to
test resource dependence perspectives for stakeholders, which constitutes the primary
overarching theme of this dissertation. The remainder of this dissertation presents each of the
three studies in detail.
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CHAPTER 2. STUDY ONE: ACQUISITION ANNOUCEMENTS AND STOCK
MARKET VALUATIONS OF ACQUIRING FIRM’S ALLIANCE PARTNERS
2.1 INTRODUCTION
Strategic alliances, or “voluntary arrangements between firms involving exchange, sharing, or
codevelopment of products, technologies, or services” (Gulati, 1998: 293), are recognized as a
governance mode designed to build temporary interfirm cooperative exchanges in transaction
cost economics (TCE) (Williamson, 1985). Because alliance partners may behave
opportunistically to maximize expected returns from their alliances, previous studies have
reported that transaction attributes heighten the alliance’s transaction hazard, leading to lower
performance and higher likelihood of termination (Gulati, 1995; Kogut, 1988; Parkhe, 1993).
The expected hazard of an alliance is calculated at the alliance formation stage, because the
alliance’s transaction attributes can be predicted based on the alliance’s and alliance partners’
characteristics. However, exogenous changes affecting transaction hazards may not be known at
the alliance implementation stage and such changes can potentially cause unanticipated
uncertainties within the alliance. In fact, few studies have revealed how post-formation changes
in an alliance partner affect the transaction hazard of its alliance.
In this study, I focus on an alliance partner’s acquisition as a significant post-formation
change that could potentially influence its activities with and commitment to alliances,
generating its behavioral uncertainty. Acquisitions require acquirers to commit enormous
financial and human resources to acquisition-related activities, such as integrating targets’
10
businesses and realizing synergies between their businesses (see, for review, Haleblian, Devers,
McNamara, Carpenter, and Davison, 2009; Haspeslangh and Jemison, 1991; King, Dalton, Daily,
and Covin, 2004). Therefore, when engaging in an acquisition, an acquirer needs to reformulate
its current strategy and business portfolio, which could potentially endanger the fulfillment and
continuance of its current alliances.
I investigate this phenomenon from a transaction cost perspective. The theoretical
perspective postulates the hazards of governing exchanges and their performance implications
(Williamson, 1975, 1985, 1991). The transaction hazard of an alliance is partially determined by
its uncertainty derived from the degree of an alliance partner’s opportunistic behaviors. Based on
this logic, it can be inferred that an increase in behavioral uncertainty associated with an alliance
naturally raises its transaction hazard, thereby lowering the value created through the alliance
(Williamson, 1979, 1991).
My main thesis is that, by making an acquisition, a firm increases the transaction hazard
of its alliance with an alliance partner, thereby reducing the expected value created through that
alliance. Conducting an acquisition requires the acquirer to modify any current alliance, because
it cannot spare sufficient resources for the alliance or because its reformulated strategy no longer
fits the alliance. Therefore, an acquirer may intend to renegotiate its contracts with its alliance
partner and, in extreme cases, to negate them. Such opportunistic attempts, which were not
expected at the alliance formation stage, inevitably cause an unanticipated increase in the
uncertainty within the alliance. Since the unanticipated behavioral uncertainty shifts the hazard
of the alliance upward, the acquirer’s alliance partner gains less value from the alliance after the
acquisition. Based on this prediction, the stock market will provide a negative market valuation
11
of the alliance partner in reaction to the announcement of the acquisition.
In addition, I expect that the negative impact of an acquirer’s acquisition announcement
on its alliance partner’s market valuation will vary depending on the alliance and acquisition
characteristics. This is because these characteristics are expected to affect the degree of
unanticipated increase in an acquirer’s behavioral uncertainty caused by its acquisition and the
alliance’s tolerance of the unanticipated increase. If an acquirer behaves more opportunistically
within the alliance after making an acquisition, the acquirer’s behavioral uncertainty within the
alliance will be more significant. Consequently, its transaction hazard will be still greater,
resulting in a more negative market valuation of its alliance partner. In contrast, if an alliance can
absorb the acquirer’s behavioral uncertainty caused by an acquisition, the increase in its
transaction hazard will be limited, leading to a less negative market valuation.
The sample for this study consists of 347 cases of alliances among Japanese public non-
financial firms associated with 150 acquisition deals from 1995 to 2012. This sample is suitable
for this study because the period includes a considerable number of acquisition deals and alliance
cases that are sufficient for statistical analysis. During the period studied, Japanese firms
experienced poor performance after the collapse of an asset price bubble in the early 1990s and
aggressively engaged in acquisitions and strategic alliances in order to restructure their
businesses.
Through statistical analysis, I found support for six out of seven hypotheses. The
findings of this study offer new insight into interfirm cooperation—that interfirm cooperation is
subject to the influence of post-formation changes unanticipated at the alliance formation stage.
As a change in an alliance, an alliance partner’s acquisition serves as a shift parameter of its
12
transaction hazard (Williamson, 1991). By illuminating this point, my study opens up a new
research direction in the field of interfirm cooperation and TCE.
2.2 THEORY AND HYPOTHESES
2.2.1 Transaction hazards and expected returns from alliances
The performance of a transaction depends on the costs governing its activities, called transaction
costs (see for reviews, Crook, Combs, Ketchen, and Aguinis, 2013; Geyskens, Steenkamp, and
Kumar, 2006; Gibbons, 2010; Shelanski and Klein 1995). Transaction costs include the ex-ante
costs of drafting, negotiating, and safeguarding an agreement between two or more actors and the
ex-post costs of contracting, generated by maladaptation, haggling, administration, and bonding
(Williamson, 1991). The type and degree of activities required for a transaction are determined
by the transaction hazard, which is derived from the transaction attributes: asset specificity (i.e.,
how unique the investment supporting a transaction is), transaction uncertainty (i.e., how
unpredictable the contingencies and performance of a transaction are), and transaction frequency
(i.e., how often a transaction occurs) (Crook et al., 2013; Williamson, 1985). If a firm matches a
transaction to an appropriate governance mode, it can achieve cost efficiency, thereby creating
more value (Nickerson and Silverman, 2003; Sampson, 2004; Williamson, 1991). According to
the transaction cost perspective, strategic alliances, one of the hybrid forms, are an appropriate
governance mode when a transaction’s asset specificity, uncertainty, and frequency are
intermediate (Williamson, 1991). This is because hybrids can deal with unforeseen disturbances
more elastically and adaptively than can markets and hierarchies (Williamson, 1985).
If a firm’s alliance is expected to add value to the firm, it can receive a higher market
valuation. In an efficient capital market, in which stock prices reflect all publicly available
13
information, market valuation of a firm that publicly announces the formation of an alliance will
be favorable if investors recognize the possibility of value creation from the alliance (Das, Sen,
and Sengupta, 1998). From this viewpoint, several studies have shown the positive impact of
alliance announcements on market valuations of alliance partners using the event study method,
which examines market reactions to events or news (Kothari and Warner, 2007). Positive
expected returns arising from alliances appear as positive stock return anomalies, which are
called positive abnormal returns. Previous event studies of strategic alliances have empirically
corroborated the impact of alliance formation and the validity of the event study method to
capture it (e.g., Anand and Khanna, 2000; Chan, Kensinger, Keown, and Martin, 1997; Das et al.,
1998; Kale, Dyer, and Singh, 2002).
Nonetheless, these previous studies of alliances adopt a static viewpoint by focusing on
an expected transaction hazard at the point of alliance formation. It is still unclear how
unanticipated changes pertaining to a contracting party of an alliance influence the transaction
hazard of the alliance and the expected return attributed to the other party. When unanticipated
changes provoke disturbances in an alliance that exceed its “tolerance zone,” within which
misalignments in an alliance can be absorbed (David and Han, 2004), the alliance governance
mode may not be able to achieve transaction cost efficiency. Consequently, the parties modify or
terminate their ongoing alliance and have to bear additional transaction costs. Accordingly, the
parties cannot create expected value through their alliance.
Recent studies in TCE have started to investigate the impact of unanticipated external
shocks on transactions, focusing in particular on changes in the institutional environment
surrounding transactions. Williamson (1991) proposes the shift parameter framework, in which
14
the institutional environment is viewed as a set of parameters determining transaction hazards,
changes in which produce shifts in the comparative costs of governance. In pioneering work in
this field, Fabrizio (2012), for instance, empirically demonstrated that, in response to regulatory
changes, firms with strong institutional safeguards chose market procurement over internal
production in the U.S. electric utility industry. Likewise, Brahm and Tarziján (2014) showed that
a change in subcontracting law that increased the transaction hazard of subcontracting raised the
likelihood of vertical integration in the Chilean construction industry. However, none of the
previous studies in TCE has clarified how changes pertaining to the contracting parties of an
alliance shift its transaction hazard.
In fact, in reaction to unanticipated changes pertaining to an alliance, one contracting
party may alter its behavior in pursuit of self-interest, which is not predictable for the other party.
This unanticipated behavioral change, which causes behavioral uncertainty, or the
unpredictability of a contracting party’s behavior and its performance consequences, is a
composite of transaction uncertainty (Williamson, 1985). Behavioral uncertainty arises from the
opportunistic inclinations of contracting parties (John and Weitz, 1988; Niesten and Jolink, 2012).
For example, Reuer and Arino (2002) empirically demonstrated that an alliance partner
renegotiated the contracts of an alliance in response to strategic change. Such renegotiating and
drafting of a new agreement involves additional transaction costs defrayed by the other alliance
partner (Reuer and Arino, 2002; Reuer, Zollo, and Singh, 2002), thereby shifting the alliance
governance mode toward inefficiency (Williamson, 1991).
2.2.2 Acquisition impact on alliance partners
If an increase in behavioral uncertainty caused by unanticipated changes is not absorbed within
15
the tolerance zone of the alliance, it is unlikely that the alliance can create the expected value
because its transaction hazard increases. The question that naturally arises is what types of
changes in alliance partners trigger behavioral uncertainty. I argue that acquisitions are highly
likely to cause an unanticipated increase in uncertainty within alliances for three important
reasons. First, acquisitions require acquirers to deal with complex organizational challenges such
as the integration of operations and restructuring of business portfolios (Haleblian et al., 2009;
Haspeslangh and Jemison, 1991). After making an acquisition, an acquirer will need to
reformulate its strategy and business portfolio, which may significantly change the assumed
conditions for and strategic importance of its alliances. Accordingly, the acquirer is likely to
renegotiate the alliance with the alliance partner opportunistically in order to adapt it to its new
strategy and business portfolio.
Second, because acquisitions are a large-scale firm-level practice, an acquirer generally
needs to mobilize its financial resources and managerial capabilities fully for the processes
(Haspeslangh and Jemison, 1991; Larsson and Finkelstein, 1999). Since such firm resources are
never infinite, the acquirer may be unable to spare sufficient resources for its ongoing alliances
simultaneously. Accordingly, the acquirer may opportunistically change its commitment to its
alliances. Finally, since acquisitions are planned and implemented in secret, they are generally
unanticipated by outsiders, like the acquirer’s alliance partner. Therefore, the alliance partner
cannot prepare for the disturbances triggered by the acquisition in advance.
Since an acquirer’s acquisition causes unanticipated behavioral uncertainty within its
alliance, its alliance partner receives a negative market valuation around the acquisition
announcement. Because the acquisition changes the acquirer’s strategy and results in resource
16
constraints, the acquirer will be inclined to modify or terminate existing alliances, which was not
anticipated at the alliance formation stage. This acquirer’s behavioral uncertainty in an alliance
inevitably increases the alliance’s transaction hazard. The higher transaction hazard of an alliance
indicates a higher likelihood of resultant failure. In order to deal with the increased transaction
hazard, an alliance partner will need to renegotiate the alliance and monitor the acquirer’s
fulfillment, thereby increasing transaction costs in an unanticipated way. Accordingly, an
increase in the transaction hazard associated with the alliance reduces the alliance’s expected
value. Because of the reduction in the expected value, the stock market will immediately react to
the acquirer’s acquisition announcement by giving a negative market valuation to its alliance
partner. Therefore, I propose the first hypothesis as follows:
Hypothesis 1: An acquirer’s acquisition announcement results in a negative abnormal
return for its alliance partner.
2.2.3 Alliance characteristic 1: Experience of past alliance between acquirer and alliance
partner
Although an acquirer’s acquisition announcement is expected to produce a negative market
valuation of its alliance partner, the degree of the negative market valuation will vary depending
on the characteristics of the alliance and the acquisition. This is because alliance and acquisition
characteristics affect the degree of unanticipated increase in the uncertainty of the acquirer’s
behavior and the breadth of the alliance’s tolerance zone for the unanticipated increase. As
explained above, the market will negatively value the alliance partner if the unanticipated
increase in the acquirer’s behavioral uncertainty significantly raises the transaction hazard
associated with the alliance. Therefore, even if an acquirer announces an acquisition, its alliance
17
partner may receive a less negative market valuation if the acquisition is expected to trigger
smaller unanticipated changes in the acquirer’s behavior. Likewise, if the alliance between an
acquirer and an alliance partner is more tolerant to the unanticipated increase in behavioral
uncertainty, the negative market valuation of the alliance partner will be less.
As a first influential alliance characteristic, I propose past alliance experience between
an acquirer and an alliance partner. Long-term alliance experience generates interfirm trust
between an acquirer and its alliance partner (Gulati and Nickerson, 2008; Ring and Van de Ven,
1992, 1994; Uzzi, 1997; Zaheer, McEvily, and Perrone, 1998). Interfirm trust is defined as a
firm’s willingness to be vulnerable to its alliance partner based on positive expectations about the
partner’s actions and intentions (Rousseau, Sitkin, Burt, and Camerer, 1998). Interfirm trust
reduces the perception of opportunistic behavior (Das and Teng, 1998; Parkhe, 1993; Saxton,
1997). As a result, interfirm trust is likely to limit the drafting and enforcing costs associated
with an exchange (Gulati, 1995; Gulati and Nickerson, 2008; Mayer and Argyres, 2004).
Based on the argument above, I expect that past alliance experience between an acquirer
and an alliance partner will reduce the negative impact of an acquisition announcement on the
alliance partner’s market valuation. This is because the interfirm trust between an acquirer and an
alliance partner developed through their past alliance experience makes their alliance more
tolerant to the unanticipated increase in the acquirer’s behavioral uncertainty following its
acquisition. Interfirm trust will soften post-acquisition uncertainty associated with the alliance
because the alliance partner can accommodate small adjustments in the alliance without fear of
the acquirer’s opportunistic behavior, leading to only a limited increase in transaction costs. In
this case, it is highly likely that the alliance will continue without a reduction in value creation
18
after the acquisition announcement. Accordingly, I propose the following hypothesis:
Hypothesis 2: The greater the past alliance experience between an acquirer and an
alliance partner, the less negative the abnormal return for the alliance partner attributable to the
acquirer’s acquisition announcement.
2.2.4 Alliance characteristic 2: Horizontal vs. non-horizontal alliance
Horizontal alliances are alliances between firms operating within the same industry (Rothaermel
and Deeds, 2006). Through horizontal alliances, alliance partners can gain access to
supplementary resources in order to increase their market power through horizontal production
integration, input supply restrictions, and market foreclosure (Berg and Friedman, 1977; Tong
and Reuer, 2010). On the other hand, non-horizontal alliances provide alliance partners with
access to complementary resources and new markets. Therefore, firms can learn know-how and
capabilities for business activities in new product markets from their non-horizontal alliance
partners (Kale, Singh, and Perlmutter, 2000; Inkpen, 2000).
If the alliance between an acquirer and an alliance partner is non-horizontal, the negative
market valuation of the alliance partner around the acquisition announcement will be greater.
This is because non-horizontal alliances are less tolerant than horizontal alliances of
unanticipated increases in behavioral uncertainty caused by acquisitions. Since non-horizontal
alliance partners expose their proprietary assets to each other as learning targets (Kale et al.,
2000), an alliance partner in a non-horizontal alliance is inherently cautious about the acquirer’s
opportunistic attempts to access intellectual property within the alliance (Khanna, Gulati, and
Nohria, 1998; Oxley, 1997). Therefore, when the acquirer engages in an acquisition and intends
to realign an alliance, its alliance partner in the non-horizontal alliance will deal more sensitively
19
with the post-acquisition renegotiation of the alliance to protect their proprietary assets,
inevitably increasing the transaction costs defrayed by the alliance partner. Consequently, the
non-horizontal alliance will create less value after the acquisition announcement, leading to a
more negative market valuation of the alliance partner. Thus, my third hypothesis is as follows:
Hypothesis 3: When the existing alliance between an acquirer and an alliance partner is
non-horizontal, the abnormal return for the alliance partner attributable to the acquirer’s
acquisition announcement is more negative.
2.2.5 Alliance characteristic 3: Technological alliance
Whether an alliance includes technological elements is another alliance characteristic that affects
the negative impact of an acquirer’s acquisition announcement on the market valuation of its
alliance partner. Unlike marketing alliances or royalty contracts, technological alliances
inevitably include investments in property, plant, and equipment specific to the alliance, such as
specialized production facilities or cross-organizational R&D teams (Das et al., 1998; Hagedoorn,
1993; Sampson, 2004). Such specialized investments are regarded as a type of non-recoverable
investment closely associated with asset specificity (Williamson, 1985).
If the existing alliance between an acquirer and an alliance partner is a technological
alliance, the alliance partner’s market valuation around the acquisition announcement becomes
more negative. This is because, after the acquisition, the alliance partner will bear larger
transaction costs from its technological alliance because of its higher asset specificity. In TCE,
the uncertainty associated with a transaction is more problematic when it is coupled with high
asset specificity because a contracting party investing in transaction-specific assets may be
exposed to “hold-up” (Klein, Crawford, and Alchian, 1978; Williamson, 1975, 1985). Along with
20
the same logic, because the alliance partner cannot easily redeploy or realize its alliance-specific
investments (Oxley, 1997), it may not be able to accommodate the post-acquisition realignment
of the alliance. Therefore, the acquirer will opportunistically renegotiate the alliance to fit its
reformulated strategy or appropriate the specialized investments, thereby increasing the
transaction hazard through its behavioral uncertainty. This increase in the transaction hazard
raises the transaction costs defrayed by the alliance partner, thereby decreasing the value created
through the alliance; as a result, the alliance partner will receive a more negative market
valuation around the acquisition announcement. Therefore, I propose the following hypothesis:
Hypothesis 4: When the existing alliance between an acquirer and an alliance partner is
technological, the abnormal return for the alliance partner attributable to the acquirer’s
acquisition announcement is more negative.
2.2.6 Acquisition characteristic 1: Acquisition deal value
As explained, acquisition characteristics determine the degree of unanticipated increase in an
acquirer’s behavioral uncertainty caused by an acquisition. The first acquisition characteristic is
the deal value of the acquisition. This characteristic represents the acquirer’s resource
commitment to an acquisition; if the deal value of an acquisition is higher, the acquirer draws on
more financial resources for the deal (Alexandridis, Fuller, Terhaar, and Travlos 2013).
I predict that the deal value of the acquisition conducted by an acquirer will increase the
negative market valuation of its alliance partner around the acquisition announcement. By
definition, an acquisition with a higher deal value requires the acquirer to mobilize more
financial resources for the deal, inevitably imposing more severe resource constraints. Such
severe resource constraints increase the degree of unanticipated increase in the acquirer’s
21
behavioral uncertainty within the alliance, because alliances are not cost-free activities; a certain
amount of resource commitment is critical to implement alliances successfully (Kale et al., 2000).
Therefore, if an acquirer utilizes a larger amount of resources exclusively for its acquisition, it
may become less able to fulfill the commitment to the alliance simultaneously as planned.
Accordingly, the acquirer may shirk the assumed obligations of the alliance or renegotiate its
contracts to avoid them. The acquirer’s opportunistic attempts inevitably increase the transaction
hazard of the alliance. Consequently, the alliance partner needs to deal with this increase in the
transaction hazard by taking countermeasures to address the acquirer’s renegotiation and closely
monitor its behavior, incurring additional transaction costs. As a result, the alliance partner can
create less value through the alliance and will receive a more negative market valuation after the
announcement of an acquisition with a higher deal value. Therefore, I propose the following
hypothesis:
Hypothesis 5: The higher the deal value of an acquirer’s acquisition, the more negative
the abnormal return for its alliance partner attributable to the acquirer’s acquisition
announcement.
2.2.7 Acquisition characteristic 2: Related vs. unrelated acquisition
The relatedness of an acquisition is an acquisition characteristic influencing the acquisition’s
impact on the market valuation of an alliance partner. The relatedness of an acquisition is based
on the resource or product similarity between an acquirer and a target (King et al., 2004). A
considerable body of research has reported that related acquisitions increase post-acquisition
performance more than do unrelated acquisitions (Bergh, 1997; Palich, Cardinal, and Miller,
2000; Rumelt, 1974, 1982) for several reasons. First, the managers of an acquirer can effectively
22
employ the acquirer’s dominant logic to an acquired business in the same industry (Prahalad and
Bettis, 1986). Second, managers will be relatively familiar with an acquired business in the same
industry (Hitt, Harrison, and Ireland, 2001). Third, the acquirer’s resources and capabilities can
be smoothly redeployed in an acquired business in the same industry (King et al., 2004). Thus,
related acquisitions decrease post-acquisition integration difficulty. In contrast, in an unrelated
acquisition, an acquirer needs to engage in large-scale changes in its business portfolio to
integrate the acquired business, because firms in different industries generally follow dissimilar
dominant logics and possess diverse resources and capabilities.
If an acquirer engages in an unrelated acquisition, its alliance partner will face more
negative market valuation around the acquisition announcement. This is because an unrelated
acquisition will cause the acquirer’s behavioral uncertainty within the alliance to be more
significant. Unlike related acquisitions, an unrelated acquisition requires the acquirer to deal with
the integration of the target business’s industry. Since the integration of unrelated businesses
requires drastic transformation of the acquirer’s business portfolio, it is highly likely that the
acquirer will reformulate its strategy. That strategic reformulation may change the strategic
importance of its ongoing alliances as well. Consequently, it is more likely that the acquirer will
adjust its commitment to its alliances and not proceed as planned. Because of an increase in its
transaction hazard, the alliance partner cannot create the expected value from its alliance.
Additionally, because of integration difficulty following unrelated acquisitions, an
acquirer cannot mobilize firm resources for its alliances as planned. Since the acquirer has to
concentrate firm resources on the difficult integration processes, it may not be able to commit
itself to an ongoing alliance, increasing its transaction hazard. In order to ensure the acquirer puts
23
the necessary effort into the alliance to deal with the increased transaction hazard, its alliance
partner needs to engage in closer monitoring of the acquirer’s behavior, thereby incurring
additional transaction costs for the alliance. Accordingly, since the alliance can create less value,
the stock market will provide a more negative market valuation of the alliance partner. Based on
this argument, I propose the following hypothesis:
Hypothesis 6: When an acquirer engages in an unrelated acquisition, the abnormal
return for the alliance partner attributable to the acquirer’s acquisition announcement is more
negative.
2.2.8 Acquisition characteristic 3: Industry relatedness between a target and an alliance
partner
Finally, industry relatedness between an acquirer’s target and an alliance partner may
unexpectedly stimulate behavioral uncertainty in the alliance between the acquirer and the
alliance partner. If the target and the alliance partner operate in the same industry, their resource
profiles and product markets are broadly similar. Therefore, after acquiring the target, the
acquirer can obtain access to firm resources and product markets similar to those provided
through the alliance with the alliance partner. The acquisition thus changes the alliance to a
conduit of redundant firm resources and product markets. Accordingly, the strategic importance
of the alliance may decrease, because such an alliance will create less value than those providing
access to different firm resources and product markets, which achieve resource and market
complementarity (Harrison, Hitt, Hoskisson, and Ireland, 2001; Mitsuhashi and Greve, 2009).
Thus, the acquirer will no longer need to maintain the alliance to access redundant resources and
product markets and may intend to modify or terminate it, thereby endangering the fulfillment of
24
the alliance. These opportunistic attempts on the part of the acquirer increase the transaction
hazard of the alliance. The alliance partner may have to bear additional transaction costs to
handle this increase in the transaction hazard by confirming the acquirer’s commitment and
behavior. As a result, the alliance partner will receive a more negative market valuation because
the expected value created through the alliance decreases.
Hypothesis 7: When an acquirer’s target and an alliance partner operate in the same
industry, the abnormal return for the alliance partner attributable to the acquirer’s acquisition
announcement is more negative.
2.3 RESEARCH METHODS
2.3.1 Sample and data collection
The sample of this study comprises 347 bilateral alliances associated with 150 domestic
acquisition deals conducted by Japanese public non-financial firms announced from January 1,
1995 to December 31, 2012. This sample and period are suitable for the study because Japanese
firms frequently engaged in acquisitions and strategic alliances during this period in order to
improve their disappointing performance attributable mostly to the collapse of the Japanese asset
price bubble in the 1990s. Therefore, I could collect sufficient numbers of acquisition deals and
alliance cases for statistical analysis.
I focused only on public firms because of the availability of firm-level data and the
difficulty of collecting reliable information on private firms. Further, I sampled non-financial
firms because regulations specific to financial institutions may distort empirical findings. I
included acquisition deals in the sample only when the acquirer of an acquisition controlled more
than 50 percent of the target after the acquisition announcement date (Moeller, Schlingemann,
25
and Stulz, 2005). Following recent studies of mergers and acquisitions through the event study
method (e.g., Fuller, Netter, and Stegemoller, 2002; Graham, Lemmon, and Wolf, 2002; Moeller
et al., 2005), I investigated only complete acquisition deals.
In terms of alliance cases, I restricted the sample to bilateral alliances. As Das and Teng
(2002) argue, the nature of multilateral alliances is different from that of bilateral alliances,
because they have more complicated design and governance mechanisms. In addition, some of
my independent variables cannot be appropriately defined for multilateral alliances.
I identified completed bilateral alliances of public non-financial firms engaging in
acquisitions that met the above criteria. A major issue in identifying alliances is that the
continuation of an alliance is unclear. Although, in general, the formation of an alliance is widely
announced in public, its termination is rarely announced. Therefore, as a conservative criterion in
previous alliance studies (e.g., Lavie, 2007), I used a three-year time window to identify the
alliances associated with the sampled acquisition deals. More specifically, if an alliance
associated with an acquisition deal was formed within 1,095 days before the announcement date
of the acquisition, I included the alliance in the sample.a I also excluded alliance cases in which
one alliance partner acquired the other.
I collected data on acquisition deals and alliance cases from the Securities Data
Corporation’s (SDC) databases. SDC’s databases achieve broad coverage of acquisition deals
and alliance cases (Schilling, 2009). Because of their coverage and reliability, these databases
have been frequently used in studies of acquisitions and alliances. I obtained the data on firm
characteristics from Needs Financial Quest.
a As more conservative criteria, I used 1,000-, 900-, and 800-day time windows and obtained virtually identical
estimation results from these different samples.
26
2.3.2 Event Study Methodology
Following previous studies examining the impact of corporate announcements (McWilliams and
Siegel, 1997), I used the event study method for this study. The event study method is used to
measure the effect of an unanticipated event on stock prices. The effects are captured by the sum
of abnormal returns within an event window, or cumulative abnormal returns (CARs). Abnormal
returns are stock return anomalies, that is, the difference between the actual return and the
expected return on a stock. I estimated the following ordinary least squares (OLS) model:
𝑅𝑖𝑡 = 𝛼𝑖 + 𝛽𝑖 × 𝑅𝑚𝑡 + 𝜀𝑖𝑡,
where i indexes firms; t indexes days; Rit is the rate of return on the stock price of firm i on day t;
Rmt is the rate of return on TOPIX, the stock price index capturing all Japanese domestic
companies listed in the first section of the Tokyo Stock Exchange, on day t; 𝛼 is the intercept
term; 𝛽 is the systematic risk of stock i; and 𝜀𝑖𝑡 is the error term with E(𝜀𝑖𝑡) = 0. The estimation
period for this model is 150 days, that is, from 200 to 51 trading days prior to acquisition
announcements (Chatterjee, 1991).
Then, I estimated the return on the stock of firm i on day t as follows:
�̂�𝑖𝑡 = 𝛼𝑖 + 𝛽𝑖 × 𝑅𝑚𝑡,
where 𝛼 and 𝛽 are the OLS parameter estimates.
Based on the estimated return on the stock of firm i on day t, I computed the abnormal
return of firm i using the following equation:
𝐴𝑅𝑖𝑡 = 𝑅𝑖𝑡 − �̂�𝑖𝑡.
Accordingly, I calculated CAR for each time interval by summing up the abnormal
returns within six event windows, namely, -1 to 0, -1 to 1, -2 to 2, -3 to 3, -5 to 5, and -10 to 10
27
trading days, where day 0 indicates the announcement of an acquisition. These event windows
have been used in recent studies using the event study method in the management field (e.g.,
Arikan and Capron, 2010; Das et al., 1998; Fan and Goyal, 2006; Flammer, 2013; McWilliams
and Segel, 1997; Oxley, Sampson, and Silverman, 2009; Shahrur, 2005). Stock market reactions
to acquisition announcements can be sufficiently reflected within these event windows because,
during the sampled period, the Japanese stock market and its related institutions were well
developed and its market participants could readily access information about acquisitions
immediately after their announcements.
2.3.3 Variables and Measures
Dependent variable
The dependent variable of regression models is the CAR of an alliance partner within the event
window [-1, 1]. I chose this short event window because shorter event windows may limit the
possibility of capturing noise unrelated to the acquisition announcements of interest
(McWilliams and Siegel, 1997). Confounding effects are frequently involved in longer event
windows (Ryngaert and Netter, 1990). Since acquisition announcements can be quickly and
widely spread across investors in the stock market, the short event window sufficiently reflects
stock market reactions to the impact of acquisition announcements on alliance partners.
Independent variables
The first independent variable is the Past alliance experience between an acquirer and an
alliance partner. Following previous studies, I measured the variable using the number of the
previous alliances between an acquirer and an alliance partner, because frequent interactions
through repeated alliances between partners produce trust (Granovetter, 1973, 1983; Gulati,
28
1995; Gulati, Wohlgezogen, and Zhelyazkov, 2012; Kale et al., 2000; Leiblein and Miller, 2003;
Parkhe, 1993; Saxton, 1997). Following Reuer et al. (2002), I counted the number of previous
alliances between an acquirer and an alliance partner from January 1, 1985, to the date of the
acquisition announcement, excluding their current alliance.
Non-horizontal alliance was measured by a dummy variable that takes 1 if an acquirer
and an alliance partner operate in different industries, and 0 otherwise. Following previous
studies of industry diversification and joint ventures (e.g., Jacquemin and Berry, 1979; Kogut,
1988; Palepu, 1985), I used the two-digit SIC code to identify industry relatedness.
In order to identify a Technological alliance, I created a dummy variable that takes 1 if
an alliance includes technology-related activities (Das et al., 1998), such as manufacturing,
supply, technological licensing, and technology transfer agreements, and 0 otherwise. I collected
information about the content of alliance agreements from SDC’s database.
The Deal value of an acquisition was measured by the value of the acquisition in
millions of dollars. Since all of the acquirers and targets in the sampled acquisitions were public
firms, the acquirers were required to report the deal values officially. Therefore, the data on the
deal values are reliable.
Unrelated acquisition is a dummy variable taking 1 if an acquirer and its target operate
in unrelated industries, and 0 otherwise. As I did to identify non-horizontal alliances, I adopted
the two-digit SIC code (e.g., Jacquemin and Berry, 1979; Palepu, 1985). If the industries of the
acquirer and the target are not categorized as the same two-digit industry, the acquisition is
counted as an unrelated acquisition. Likewise, the dummy variable of the Related industry
between a target and an alliance partner takes 1 if the target and the alliance partner operate in
29
the same industry, and 0 otherwise.
Control variables
In order to exclude the possibility of alternative explanations, I entered several control variables
in the estimation. First, An acquirer’s acquisition experience was controlled, because an acquirer
engaging in more acquisitions may suffer from greater resource constraints, which will decrease
its commitment to its current alliances. In addition, acquisition experience facilitates integration
processes and reduces post-acquisition integration problems (Haleblian and Finkelstein, 1999;
Haspeslangh and Jemison, 1991; Hitt, Harrison, Ireland, and Best, 1998). I measured the variable
by the number of acquisition deals by an acquirer over the last three years. I counted only recent
acquisitions (the last three years) because learning effects from experience tend to diminish over
time (Haunschild and Sullivan, 2002).
Second, I considered the Equity alliance dummy variable in the estimation. It has been
reported that equity alliances, or alliances involving the sharing or exchange of equity, differ
from non-equity alliances in terms of monitoring and enforcing mechanisms (Gulati, 1995;
Hennart, 1988, 1991). These differences in governance mechanisms could potentially influence
an alliance’s tolerance of unanticipated uncertainty. I created a dummy variable taking 1 if the
alliance between an acquirer and an alliance partner is equity-based, and 0 otherwise.
I adjusted for the acquirer’s CAR around its acquisition announcement as the third
control variable because the variable indicates the market expectations for the performance of the
acquisition (Agrawal, Jaffe, and Mandelker, 1992; Chatterjee, 1991). If the acquisition is
expected to succeed, its alliance partner may receive positive spillovers. Corresponding to the
CAR of an alliance partner, the variable was calculated through the same event study method
30
with the estimation window [-200, -51] and the event window [-1, +1].
The fourth set of controls is an Acquirer’s ownership share of a target. If an acquirer and
a target have an equity-based partnership before the acquisition, the acquisition processes will
proceed smoothly (Zaheer, Hernandez, and Banerjee, 2010), potentially reducing negative
spillovers to associated alliances. Likewise, the target ownership share acquired by an acquirer
reflects the degree of post-acquisition integration, which could potentially influence the
acquisition’s impact on alliances, as well. Therefore, I controlled for the Acquirer’s ownership
share of the target before and after its acquisition.
Fifth, the Firm size of alliance partners, Acquirers, and Targets were controlled. In terms
of alliances, the size imbalance between alliance partners will result in resource dependency
asymmetry, which generates unequal abnormal returns (Das et al., 1998; Pfeffer and Salancik,
1978). Additionally, because of integration difficulty, a large-scale acquisition by a large acquirer
generates more significant losses (Moeller et al., 2005). In the same vein, acquisition
performance depends on the size difference between an acquirer and its target (Fuller et al.,
2002). These acquisition consequences derived from firm size could potentially influence the
acquirer’s ongoing alliances. I used the natural logarithm of the number of employees before the
acquisition announcement as the measure of firm size.
Sixth, I adjusted for the Operating performance of alliance partners, Acquirers, and
Targets. Alliance partners with lower performance may be unable to continue their alliances
because of resource constraints. In terms of acquisitions, when a high-performing acquirer
merges with a low-performing target, it will need to engage in intensive target restructuring.
Such intensive post-acquisition integration may reduce the acquirer’s attention and commitment
31
to its existing alliances. Accordingly, I included alliance partners’, acquirers’, and targets’ after-
tax returns on assets (ROA) before the acquisition announcement as controls.
Seventh, the Number of days from the alliance formation to the acquisition
announcement was also adjusted in the estimation. A longer period of interactions between an
acquirer and an alliance partner within the focal alliance generates alliance-specific relational
capital (Uzzi, 1997). Since the distribution of the variable was highly skewed, I log-transformed
it in order to approximate it to the normal distribution.
Eighth, in order to control for industry-related effects on an alliance partner’s CAR, I
entered the dummy variables of Alliance partners’ and Acquirers’ industries in the estimation.
Because of the relatively small sample size of this study, the industry dummies were based on the
primary two-digit SIC code. Finally, year-specific effects may explain the variance in the CARs
of alliance partners. I included fiscal Year dummy variables in the estimation models.
2.3.4 Model specification
I used OLS for analysis as follows:
𝐶𝐴𝑅𝑖𝑟𝑠𝑡 = 𝛼𝑟 + 𝛼𝑠 + 𝛼𝑡 + 𝑋𝑖𝑟𝑠𝑡′ 𝛽 + 𝜀𝑖𝑟𝑠𝑡,
where i represents alliance partners, r represents alliance partners’ industries, s represents
acquirers’ industries, and t represents years. The fixed effects of alliance partners’ industries,
acquirers’ industries, and years are represented by 𝛼𝑟, 𝛼𝑠, and 𝛼𝑡, respectively. CAR is the
individual CAR in the three-day event window of -1 to +1 trading days. However, I also used
CARs computed in different event windows to check the robustness of my empirical findings. 𝛽
is a vector of the regression coefficients, 𝑋 is a vector of explanatory variables, and 𝜀 is the
error term. Since 80 acquisition deals in the sample involved multiple alliances, the alliances
32
associated with one acquisition deal may be interdependent, violating the OLS assumption of
independency among observations. Therefore, I clustered standard errors at the acquisition level.
Because all of the hypotheses are directed, I used a one-tailed test for the significance levels of
explanatory variables.
2.4 RESULTS
Table 1 summarizes the descriptive statistics and correlation matrix of all the variables,
excluding industry- and year-dummy variables. Table 2 lists the CARs of alliance partners within
six event windows: -1 to 0, -1 to 1, -2 to 2, -3 to 3, -5 to 5, and -10 to 10 trading days. Day 0 is
the event date of an acquisition announcement. As in Hypothesis 1, I expect that when an
acquirer announces an acquisition, its alliance partners will receive a negative market valuation
in the stock market. CARs within the event windows are all negative, and four of them are
statistically significant. In particular, CARs within -1 to 0 and -1 to +1 trading days, which
reflect the immediate responses of the stock market to acquisition announcements, are
significantly negative: -0.45 percent (p < 0.01) and -0.28 percent (p < 0.10), respectively.
According to this result, a firm’s stock price decreases by about 0.3 or 0.4 percent when its
alliance partner announces an acquisition. Thus, this result strongly corroborates Hypothesis 1.
33
Table 1. Descriptive statistics and correlation matrix
1. -0.28 3.40
2. 2.50 2.69 0.07
3. 0.71 0.46 -0.19 * -0.30 *
4. 0.46 0.50 -0.05 0.26 * -0.08
5. 266.78 562.32 0.01 0.24 * -0.10 -0.04
6. 0.55 0.50 -0.01 -0.10 0.19 * -0.04 -0.30 *
7. 0.24 0.43 -0.05 0.25 * -0.55 * 0.06 0.14 * -0.33 *
8. 1.03 1.62 -0.04 0.04 -0.02 0.06 0.05 0.03 0.02
9. 0.44 0.50 0.04 -0.08 0.12 * 0.12 * -0.09 0.26 * -0.23 * -0.09
10. 0.01 0.05 0.10 0.05 -0.18 * 0.05 0.12 * -0.12 * 0.15 * 0.08 -0.05
11. 0.50 0.22 0.05 0.07 -0.05 0.04 0.01 -0.07 0.01 0.01 -0.14 * 0.19 *
12. 0.88 0.17 -0.01 0.06 -0.06 0.01 0.12 * 0.03 0.04 -0.08 -0.07 0.11 * 0.45 *
13. 6.09 0.81 -0.04 0.09 -0.02 0.11 * 0.05 -0.04 0.01 0.06 -0.05 0.07 0.07 0.08
14. -0.02 0.17 0.15 * -0.06 -0.08 0.05 0.04 -0.15 * 0.02 0.07 0.16 * 0.06 -0.02 0.06 -0.06
15. 0.02 x 10-1 0.04 -0.03 -0.26 0.09 -0.21 * -0.01 -0.11 * -0.10 0.04 0.17 * -0.20 * -0.05 -0.24 * -0.16 * -0.02
16. -0.01 0.13 0.05 -0.03 0.06 0.05 0.04 -0.02 -0.02 -0.13 * 0.11 * 0.05 0.06 0.00 -0.01 -0.02 0.08
17. 8.75 1.56 0.08 0.50 * -0.18 * 0.24 * 0.18 * -0.26 * 0.18 * 0.04 -0.10 0.17 * 0.10 0.10 0.13 * 0.27 * -0.23 * -0.02
18. 9.54 1.31 0.11 * 0.34 * -0.09 0.19 * 0.23 * -0.32 * 0.09 0.12 * -0.18 * 0.06 0.02 -0.01 0.08 0.05 -0.34 * 0.04 0.36 *
19. 6.88 1.27 0.06 0.32 * -0.13 * 0.22 * 0.47 * -0.36 * 0.17 * 0.09 -0.27 * 0.11 * 0.05 0.01 0.09 0.04 -0.22 * 0.07 0.42 * 0.63 *
* for p < 0.05.
8 9 10 11 12 13Variable Mean s.d. 1 2 3 4 5 6 7 1814 15
Unrelated acquisition (Yes=1; No=0)
Technological alliance (Yes=1; No=0)
Number of past alliances between an
acquirer and a partner
Cumulative abnormal return of a partner at
its acquisition announcement (%)
16 17
Acquisition deal value
(1million dollar)
Non-horizontal alliance (Yes=1; No=0)
Acquirer's acquisition experience
Cumulative abnormal return of an acquirer
around its acquisition announcement
Acquirer's ownership share before
acquisition announcement
Equity alliance (Yes=1; No=0)
Industry relatedness between a target and
an alliance partner(Yes=1; No=0)
Target's firm size
Acquirer's ownership share after acquisition
announcement
Partner's ROA
Acquirer's ROA
Target's ROA
Partner's firm size
Acquirer's firm size
ln(dates from alliance to acquisition)
34
Table 2. Cumulative abnormal return of an alliance partnerb
b CAR represents “cumulative abnormal return”, which is expressed in a percentage. Event time is shown in days.
All t-tests are two-tailed.
Event Time CARNumber of
Observation
(-1, 0) -0.45 -3.24 ** 347
(-1, +1) -0.28 -1.52 † 347
(-2, +2) -0.16 -0.65 347
(-3, +3) -0.4 -1.23 346
(-5, +5) -0.56 -1.42 † 346
(-10, +10) -1.34 -2.43 ** 343
† for p<0.10, * for p<0.05, and ** for p<0.01.
t
35
Table 3 presents the results of OLS, estimating the effects of alliance and acquisition
characteristics on alliance partners’ CARs expressed as a percentage. In Model 1, only control
variables were included. The coefficients for the acquirer’s acquisition experience (b = -0.19, se
= 0.10, p < 0.01), the acquirer’s CAR (b = 0.11, se = 0.06, p < 0.01), the partner’s ROA (b = 4.73,
se = 1.77, p < 0.01), the acquirer’s ROA (b = 7.52, se = 5.07, p < 0.10), and the log-transformed
employee size of the target (b = 0.35, se = 0.22, p < 0.10) are statistically significant.
36
Table 3. Result of regression analysis of cumulative abnormal return of an alliance partner
(-1. +1)c
c Robust standard errors are in parentheses. n=347.
0.18
(0.10)
* 0.17
(0.09)
*
-1.82
(0.62)** -1.51
(0.55)**
-0.76
(0.40)
* -0.67
(0.40)
*
-0.40
(0.23)
* -0.34
(0.21)
*
0.08
(0.51)
0.60
(0.51)
-1.09
(0.54)* -0.54
(0.52)
-0.19
(0.10)** -0.22
(0.10)* -0.21
(0.10)* -0.20
(0.10)* -0.19
(0.10)* -0.18
(0.10)* -0.20
(0.10)* -0.20
(0.10)*
-0.13
(0.45)
0.11
(0.49)
-0.23
(0.44)
0.13
(0.48)
0.06
(0.48)
-0.12
(0.45)
-0.14
(0.45)
-0.22
(0.43)
0.11
(0.06)** 0.11
(0.06)* 0.11
(0.57)* 0.10
(0.06)* 0.11
(0.06)* 0.13
(0.06)* 0.12
(0.06)* 0.12
(0.06)*
0.03
(0.94)
0.02
(0.92)
0.21
(0.92)
-0.06
(0.88)
0.01
(0.93)
0.15
(0.93)
0.35
(1.05)
-0.09
(0.91)
-0.27
(1.26)
-0.27
(1.37)
-0.49
(1.27)
-0.44
(1.25)
-0.26
(1.25)
-0.04
(1.31)
-0.74
(1.37)
-0.16
(1.24)
0.02
(0.22)
0.16
(0.23)
0.07
(0.23)
0.14
(0.22)
0.03
(0.22)
0.02
(0.22)
0.03
(0.22)
-0.01
(0.23)
4.73
(1.77)** 4.30
(1.81)** 5.15
(1.78)** 4.08
(1.80)** 4.49
(1.75)** 4.77
(1.78)** 4.71
(1.78)** 4.80
(1.79)**
7.52
(5.07)† 8.48
(5.27)† 7.36
(5.03)† 7.85
(4.92)† 6.34
(5.14)
8.96
(5.35)* 8.54
(5.28)† 7.66
(4.96)†
-0.87
(1.55)
-1.25
(1.68)
-1.11
(1.51)
-1.06
(1.53)
-0.91
(1.61)
-0.74
(1.58)
-0.75
(1.62)
-0.88
(1.60)
-0.13
(0.24)
-0.17
(0.23)
-0.28
(0.24)
-0.04
(0.24)
-0.01
(0.24)
-0.13
(0.24)
-0.10
(0.24)
-0.14
(0.24)
0.01
(0.30)
0.13
(0.29)
0.07
(0.29)
0.16
(0.29)
0.09
(0.28)
0.08
(0.30)
0.14
(0.30)
0.10
(0.29)
0.35
(0.22)† 0.56
(0.23)** 0.37
(0.21)* 0.34
(0.21)† 0.38
(0.22)* 0.46
(0.25)* 0.36
(0.23)† 0.35
(0.23)†
Included Included Yes Yes Yes Yes Yes Yes
Included Included Yes Yes Yes Yes Yes Yes
Included Included Yes Yes Yes Yes Yes Yes
-17.14
(3.66)** -19.59
(4.08)** -16.28
(3.66)** -19.76
(4.04)** -17.19
(3.64)** -18.23
(3.79)** -17.89
(3.68)** -16.54
(3.64)**
0.42 0.46 0.43 0.44 0.42 0.42 0.42 0.42
Model 7
Year dummy
Acquirer's firm size
† for p<0.10, * for p<0.05, and ** for p<0.01. One-tailed test.
Intercept
R2
Acquirer's industry dummy
Model 4 Model 5 Model 6
H4: Technological alliance
H5: Acquisition deal value/1,000
(1 million dollar)
H6: Unrelated acquisition
Acquirer's acquisition experience
Equity alliance
Partner's firm size
Model 3
Partner's industry dummy
H7: Industry relatedness between a target and
an alliance partner
Model 8
Target's firm size
H3: Non-horizontal alliance
Variables
Partner's ROA
Acquirer's ROA
Model 1 Model 2
Acquirer's ownership share after acquisition
announcement
Cumulative abnormal return of an acquirer
around its acquisition announcement
Acquirer's ownership share before acquisition
announcement
Target's ROA
H2: Number of previous alliances between
an acquirer and a partner
ln(days from alliance to acquisition)
37
In Model 2 in Table 3, in addition to the set of the control variables, all the independent variables
were included simultaneously, whereas, in Models 3 to 8, they were tested separately. I check the
results of Model 2 for all hypothesis testing. Hypothesis 2 predicts that the number of previous
alliances between an acquirer and an alliance partner will decrease the negative CAR of the
alliance partner around the acquisition announcement by the acquirer. The regression coefficient
for the variable is positive and statistically significant at the 5 percent level (b = 0.18, se = 0.10,
p < 0.05), corresponding to the prediction. According to this estimation result, if an acquirer and
an alliance partner have experienced a previous alliance, the CAR of the alliance partner
increases by 0.18 percent. Therefore, Hypothesis 2 is supported.
Hypothesis 3 indicates that an acquirer’s acquisition announcement results in a more
negative abnormal return to an alliance partner when the alliance is non-horizontal. The
regression coefficient for a non-horizontal alliance is significantly negative at the 1 percent level
(b = -1.82, se = 0.62, p < 0.01). On average, the CAR of an alliance partner connected through a
non-horizontal alliance with an acquirer decreases by 1.82 percent, supporting Hypothesis 3.
The negative impact of a technological alliance between an acquirer and an alliance
partner on the abnormal return to the alliance partner around the acquirer’s acquisition
announcement is postulated in Hypothesis 4. The coefficient for the dummy variable of
technological alliance is negative and statistically significant at the 5 percent level (b = -0.76, se
= 0.40, p < 0.05). If the alliance between the acquirer and the alliance partner is technological,
the CAR of the alliance partner decreases by 0.76 percent around the acquisition announcement
of the acquirer. This result is consistent with Hypothesis 4.
38
Focusing on the deal value of an acquisition, Hypothesis 5 states that the abnormal
return to an alliance partner around the acquisition announcement is more negative when the deal
value is greater. The regression coefficient for the variable is negative and statistically significant
at the 5 percent level (b = -0.40, se = 0.23, p < 0.05), lending support to Hypothesis 5. According
to this result, the CAR of an alliance partner lowers by 0.40 percent when the deal value of the
acquisition increases by 1 billion dollars.
Hypothesis 6 predicts that when an acquirer engages in an unrelated acquisition, the
abnormal return to its alliance partner around the acquisition announcement will be more
negative. Contrary to my prediction, the regression coefficient for the dummy variable for
unrelated acquisition is positive and statistically non-significant (b = 0.08, se = 0.51, n.s.).
Accordingly, Hypothesis 6 is not supported.
Finally, I predicted, as Hypothesis 7, that when an acquirer’s acquisition target and
alliance partner operate in the same industry, the alliance partner receives a more negative market
valuation around the acquisition announcement. Consistent with this prediction, the regression
coefficient for the dummy variable indicating that the target and the alliance partner belong to the
same industry is negative and statistically significant at the 5 percent level (b = -1.09, se = 0.54,
p < 0.05), supporting Hypothesis 7. This result suggests that the CAR of the alliance partner
lowers by 1.09 percent when the target and the alliance partner operate in the same industry.
2.4.1 Robustness Checks
I conducted robustness checks to confirm that my empirical results were not derived from
specific measures. First, for the regression estimation, I used CARs within a different event
window of -3 to 3 trading days. The significance levels of the regression coefficients of the
39
independent variables varied. Although regression coefficients for Non-horizontal alliance,
Technological alliance, and Industry relatedness between a target and an alliance partner are
still negative and significant, the number of previous alliances and the deal value of an
acquisition deal are non-significant. These non-significant variables may be subject to
confounding factors.
Second, I used different estimation windows to compute the abnormal returns of alliance
partners. The estimation windows were 150 days (170 to 21 trading days prior to acquisition
announcements), 100 days (130 to 31 trading days), and 250 days (300 to 46 trading days), all of
which were used in recent studies adopting the event study method (Fan and Goyal, 2006; Gaur,
Malhotra, and Zhu, 2013; Oxley et al., 2009). Using abnormal returns estimated with the three
estimation windows, I calculated CARs within the event window of -1 to 1 trading days. I
estimated the same estimation models with these CARs, and their results are virtually identical to
those of the original model in terms of the signs and significance levels of the independent
variables.
Third, I used the rate of return on a different market portfolio of stocks to compute
abnormal returns. I used the Nikkei 225 instead of TOPIX. The Nikkei 225 is a stock market
index for the Tokyo Stock Exchange. It is the weighted average of the stock prices of 225
representative stocks in the stock market. The signs and significance levels of the regression
coefficients for the independent variables are virtually unchanged.
Fourth, I used a different measure for the past alliance experience between an acquirer
and an alliance partner. Since the alliance experience between firms also reflects the duration of
the alliance, I adopted the number of years from the first alliance to the current alliance for
40
analysis (Hoetker, 2005). Although the significance level of the variable is slightly lower, its
direction did not change.
Finally, as shown in Models 3 to 8 in Table 3, the signs and significance levels of the
regression coefficients for the independent variables, except industry relatedness between a target
and an alliance partner, are identical to those in Model 2, in which the independent variables
were included simultaneously. Therefore, it can be concluded that the results are not produced
after including certain independent variables in the estimation. According to the results of these
robustness checks, I conclude that my statistical findings are reliable.
2.5 DISCUSSION AND CONCLUSIONS
This study began with the research question of why and how an acquirer’s acquisition
announcement influences the stock market valuation of its partner in a bilateral alliance. Using a
sample of 347 alliances associated with 150 acquisition deals by Japanese public non-financial
firms, I examined the research question using the event study method. The empirical findings of
the study are summarized as follows. First, on average, an acquirer’s acquisition announcement
leads to a negative abnormal return for its alliance partner. This finding corroborates my
prediction that an acquisition conducted by a firm is expected to reduce the value the alliance
partner derives from the alliance. Because the acquisition triggers an unanticipated increase in
the acquirer’s behavioral uncertainty, the transaction hazard associated with the alliance activities
will increase, such that alliance becomes an inappropriate governance mode for economizing
transaction costs. Since the alliance partner cannot create the expected value though the alliance,
it receives a negative market valuation around the acquisition announcement.
Second, the negative impact of the acquisition announcement on the abnormal return
41
varies depending on the alliance and acquisition characteristics. These characteristics determine
the degree of unanticipated increase in an acquirer’s behavioral uncertainty caused by the
acquisition and the alliance’s tolerance of the unanticipated increase. In terms of alliance
characteristics, past alliance experience decreases the negative impact of acquisition
announcements, whereas non-horizontal and technological alliance types increase the negative
impact of acquisition announcements. As for acquisition characteristics, acquisition deal value
and industry relatedness between a target and an alliance partner enhance the negative impact on
the market valuation of the alliance partner.
Contrary to my prediction, I did not find empirical support for the negative impact of an
unrelated acquisition on the CAR of an alliance partner. A possible reason for this unexpected
result is that the two-digit SIC code may be too broad to capture the actual impact of acquisition
relatedness. However, I also tested the dummy variable of an unrelated acquisition based on the
three-digit SIC code, and the empirical finding did not change. Accordingly, measurement may
not be the cause of this unexpected finding. The other possible explanation is that the impact of
an unrelated acquisition on the CAR of an alliance partner may be mixed. The potential positive
effect of an unrelated acquisition is that an acquirer engaging in unrelated diversification may
increase its commitment to its current alliances, because it will put more value on options with
higher strategic flexibility. Because of the simultaneous presence of the positive and negative
effects of unrelated acquisition, I might not find significant effects.
2.5.1 Theoretical and practical implications
This study provides several theoretical and practical implications. As a first theoretical
implication, I successfully proposed the dynamic view of strategic alliances and its performance
42
implications by using the shift-parameter framework (Williamson, 1991). Previous studies of
alliances have focused on the pre-formation conditions of alliances and their performance
implications. In contrast, this study shifted its research focus to the impact of the post-formation
conditions. From this viewpoint, I theoretically and empirically revealed the increase in the
behavioral uncertainty caused by unanticipated changes, and how it shifts the transaction hazard
of alliances, thereby influencing their expected performance. The findings of this study
illuminate a novel antecedent of expected alliance performance: alliance partners’ acquisitions.
Although this study showed only acquisitions as significant changes, it surely enriches the
alliance literature.
Second, I theoretically and empirically indicated that alliance partners’ acquisitions,
which are changes in contracting parties’ preconditions for their transactions, work as a
transaction shift parameter. The main research focus of TCE has been on transaction attributes
and institutional environments as determinants of transaction costs (Chiles and McMackin, 1996;
Williamson, 1991). Pioneering work in TCE sheds light on the roles of contracting parties’
characteristics in the governance mode choice, such as transaction-related capabilities (e.g.,
Hoetker, 2005; Leiblein and Miller, 2003; Mayer and Salomon, 2006). I further extended this
line of research from a dynamic viewpoint: Changes in contracting parties themselves shift
transaction hazards and influence performance consequences. If contracting parties’
preconditions for a transaction change in an unanticipated way, this raises transaction uncertainty.
This rise in transaction uncertainty increases transaction hazards and causes the alliance to incur
additional transaction costs.
Third, my study successfully revealed the negative spillovers of acquisitions to alliance
43
partners. The study is complementary to the work of Gaur et al. (2013), which empirically
demonstrated the positive impact of an acquirer’s acquisition announcement on the market
valuations of its rivals. In other words, Gaur et al. (2013) examined the impact of a foe’s
acquisition and found the acquisition produces positive spillovers to its competing firms by
signaling the presence of growth opportunities in their industry. In contrast, my study examines
the impact of a friend’s acquisition and finds that cooperative relationships can be spoiled by the
negative spillovers of alliance partners’ acquisitions because of unanticipated increase in
behavioral uncertainty. As shown, acquisition spillovers have diverse aspects. By examining
acquisition spillovers in a different context, the study contributes to the literature on acquisitions’
spillover effects.
Practitioners can gain useful insights from the findings of this study. First, a firm
engaging in an alliance has to pay attention to its alliance partner’s actions outside the alliance.
The stock market may react sensitively to acquisition actions by discounting the expected return
from the alliance. If a firm senses that an alliance partner is planning an acquisition, it should
prepare for the negative spillovers arising from the acquisition. Second, a firm needs to design an
alliance such that it can accommodate the disturbances generated by unanticipated events. In my
analysis, non-horizontal alliances and technological alliances may have narrower tolerance zones
for unanticipated uncertainty. Firms would be advised to form alliances that are either non-
horizontal or technological, but not both, to make their alliances somewhat tolerant. Likewise,
choosing reliable partners with previous alliance experience will make alliances more tolerant to
unexpected disturbances provoked by external shocks.
44
2.5.2 Limitations and future directions
Although this study obtained consistent evidence of the negative impact of acquisition
announcements on the market valuations of acquirers’ alliance partners, it inevitably includes
several limitations that illuminate potential avenues for future research. First, this study did not
reveal the long-term performance consequences of strategic alliances after acquisitions. The
event study method is an ideal method of capturing the immediate effects of acquisition
announcements on the expected returns from alliances, but the method is heavily based on the
market efficiency assumption. My results are subject to the caveat that I assume that the stock
market recognizes an acquirer’s alliance partners and is able to compute the expected value from
their alliances. If the stock market is not efficient, the abnormal returns of an alliance partner
following an acquisition announcement would not accurately reflect the effects of the acquisition
(Oler, Harrison, and Allen, 2008). In order to estimate acquisitions’ impact on alliances more
accurately, future research can confirm my findings by focusing on the long-term consequences
of alliances, such as alliance performance and termination.
The Japanese context may be a second limitation of this study, because it may lower the
generalizability of my findings. The Japanese societal culture is characterized by collectivism
and long-termism (Hofstede, 2001). Accordingly, since firms in Japan may have stronger
intentions to maintain interfirm cooperation than would those in countries with individualism and
short-termism cultures, the negative impact of an acquisition on the market valuation of an
alliance partner may appear smaller in the Japanese context. To check the generalizability of my
findings, the same hypothesized relationships should be tested in different national contexts.
In conclusion, the expected value of strategic alliances can be negatively influenced by
45
post-formation changes that have been unanticipated, because such changes may increase the
transaction hazard associated with an alliance. Through this mechanism, an acquirer’s acquisition
announcement triggers a negative market valuation of its alliance partners. I hope that my study
will contribute to a more complete picture of strategic alliances.
46
CHAPTER 3. STUDY TWO: STAKEHOLDERS’ INFLUENCE ON THE DEAL
COMPLETION PROBABILITY IN M&As
3.1 INTRODUCTION
Mergers and Acquisitions (M&As) are a popular strategic option, though the investments during
the early stage can become a huge risk if the process is not appropriately executed and managed.
Successful execution of an M&A and achieving targeted financial and strategic objectives is
therefore one of the most important key issues for a firm’s long-term sustainability. Thus, how to
lead a successful M&A effort from beginning to end garners significant academic and business
interest.
Many studies address M&As as a popular research topic, discussing areas such as how
to choose the right industry or target company, how to manage the execution process, and how to
manage post-merger integration to achieve the acquisition’s objective. Existing research also
includes scientifically accurate methodologies for financial analyses or to estimate the
acquisition performance with quantitative analyses of the organizational and cultural aspects of
the acquisition. However, few studies investigate the stakeholders around the deal, though
researchers have looked at stakeholder influence on corporate business operations from a variety
of perspectives. Internal and external stakeholders have various channels to communicate and
expand their opportunities to participate in the corporate decision making process (Preston and
Sapienza, 1990). Thus, stakeholders’ responses to a critical strategic decision, such as an M&A,
would be one of the most important issues to manage for a successful M&A. This study
47
empirically examines stakeholders’ influence on the deal completion probability in M&As.
Compared to the previous internally focused studies of M&As, this study investigates elements
one step outside. By addressing M&A events, which bring massive changes in the business
environment and lead to stakeholders’ varying responses, this study argues for a dynamic
perspective in stakeholder research, particularly the dyadic perspective, when considering
acquirer and target stakeholders’ relative benefits or losses.
3.1.1 Research streams on M&As
Management researchers have considered M&As from various academic perspectives, such as
the economics of M&As (Ravenscraft and Scherer, 1987), research in finance (Datta, Pinches
and Narayanan, 1992), strategic implications of M&As (Capron, 1999; Chatterjee, 1986), and
organization theory (Datta, 1991; Larsson and Lubatkin, 2001). To find the determinants of
successful M&As, studies focused on the nature of deals from the financial and strategic
viewpoints. Selecting the right target is one popular topic, as are analyses of pricing, synergy
estimation, industry fit, and so on, to gain a more precise understanding of the characteristics of
the right target. Researchers have examined failing or underperforming M&As by reassessing the
initial appraisals (Cartwright and Cooper, 1993). Others examine organizational culture and
human resources. Cartwright and Cooper (1996) demonstrated the important role of people and
culture when investigating acquisition performance rather than focusing on accurate estimations
of corporate value. A number of case studies, including the failed merger between AOL and Time
Warner, also indicated the importance of cultural fit between acquirer and target firms (Ray,
2012). Many studies also focus on finding critical success factors for acquisition performance
using different methods (King, Dalton, Daily and Covin, 2004).
48
However, research into successful M&As focused on internal elements of the transaction
such as acquirer and target firm characteristics, transaction terms, industry relatedness, payment
methods, and so on, although external factors significantly influence M&A deals. Though it is
important to make appropriate decisions based on valid assessments of the deal environment, the
area requires more dynamic approaches to discover more practical determinants of a successful
acquisition. There are many interested parties, or stakeholders, in a proposed M&A’s progression,
including internal members and those outside of the organization such as suppliers, customers,
governments, and so on, who have some interest in sustaining normal business operations. The
current business environment requires that firms cope with various stakeholders’ needs.
Academic research should also carefully investigate external parties’ influence on the success of
an M&A. This study thus examines a variety of stakeholders’ influences on M&A transactions by
reviewing previous studies on stakeholders and M&As and proposing a comprehensive empirical
research model to verify the theoretical findings. Addressing stakeholders’ influence on M&A
should be significantly meaningful in the context of shifting academic attention from internal
elements to external factors when investigating the determinants of successful M&A deals.
3.1.2 Stakeholders and M&As
Management researchers demonstrated stakeholders’ strong influence on corporate business
operations and firm performance, and asserted the importance of appropriate stakeholder
management for an organization’s sustainable growth (Carroll, 1991; Freeman, 1984; Mason,
Kirkbride and Bryde, 2007). Stakeholders’ power, position, and overall relationship with an
organization is usually based on a contract or other agreement with the focal firm, which affect a
focal firm’s key decision-making process and selection of strategic options. M&As may provoke
49
diverse responses from individual stakeholders since it brings considerable change to the
relationship between stakeholders and the focal firm. According to the relational structure with
the focal firm, stakeholders possess different interests, sensitivity, and influence on the
organization. Firms must therefore address stakeholders with a precise understanding of the
stakeholder environment, particularly when an organization considers strategic initiatives that
affect stakeholders’ interests. Companies must manage stakeholders both in the final decision
and to ensure the success of a strategic initiative.
Previous research on stakeholders focused on identifying stakeholders, and thus helped
firms clearly understand the stakeholder environment. These studies categorized stakeholders by
their legal and economic rights with respect to an organization, grouped by stakeholders’ position
and power in the economic and social network (Pajunen, 2006; Preston and Sapienza, 1990).
Prior studies on stakeholder theory also addressed stakeholders’ reactions to an organization’s
strategic moves. Jawahar and McLaughlin (2001) examined firms’ stakeholder management
strategy. Other researchers focused on stakeholders’ influence on an organization’s strategic
decision-making process (Frooman, 1999). Pajunen (2006) and Savage, Nix, Whitehead, and
Blair (1991) approached the characteristics of the relational network between stakeholders and a
focal organization and its influence on the focal firm’s decision-making process. In addition,
some studies addressed the motivations behind stakeholder’s reactions, asserting that
stakeholders’ moves depend not only on economic interest but also on the expectation of gains
and losses in their current power and position (Rowley and Moldonevau, 2003).
According to the stakeholder literature, firms are surrounded by various stakeholders,
who act strategically based on their relationship with the focal organization and react sensitively
50
to situational changes that could affect their future benefits or losses. Therefore, when
stakeholders confront any event accompanying massive changes in the business environment, we
can expect they will have a corresponding reaction to defend their current power and benefits in
their relationship with the focal organization. Furthermore, we can expect stakeholders with a
closer relationship to a firm to have reactions clearly visible from the outside. Despite the
extensive stakeholder-related literature, the studies focused on only a few aspects of the
phenomenon and approached related issues piece by piece. Thus, the present study aims to
reflect previous findings, examine stakeholders’ influence on M&As empirically, and provide
additional insights into stakeholders and M&A issues.
3.2 LITERATURE REVIEW
3.2.1 M&A Announcement to Deal Completion / Withdrawal
M&As generally have three phases: the pre-announcement stage, post-announcement to deal
closing or withdrawal, and post-acquisition integration. Before making a public announcement of
the acquisition, the acquirer conducts pre-due diligence with publicly available information about
the target, preliminary valuation, and pricing based on estimates of potential synergies, preparing
and delivering a letter of intent, a preliminary negotiation, and secondary due-diligence by
mutual agreement on how the deal should progress. Public announcements of an acquisition are
made by agreement between the potential acquirer and target firms on the proposed conditions of
the transaction. In most cases, the process behind the deal and related information remain
confidential and only members of the top management teams and other key staff make decisions
before the announcement (Koo, 2012). After the public announcement, the acquirer performs
51
more detailed due diligence to realize the expected synergies and find any unexpected or
problematic issues to finalize the acquisition process. Of course, the deal may be withdrawn if
the due diligence uncovers any surprises or serious difficulties in achieving the targeted
synergies. The third stage involves integrating the two entities after finalizing the transaction,
which could be a partial or complete integration or be limited to sharing key functions to reach
the goals of the transaction. Since stakeholders affect business operations, their influence begins
to appear during the second stage of the process. Though much information remains private
during the public announcement, various stakeholders can get to know the deal and prepare for
the proposed transaction.
This study therefore focuses on the second stage, during which the transaction is either
completed or withdrawn. After the public announcement, stakeholders surrounding the proposed
deal start responding by reckoning their gains and losses in the post-acquisition stage.
Stakeholders who foresee maintaining or enhancing their current power and position after the
acquisition strongly support the deal and positively influence the deal progress. On the other
hand, those predicting losses in power and position because of the transaction may resist the
proposed deal (Wong and O’Sullivan, 2001). Before making the public announcement, the
acquirer performs a valuation of the target firm based on the due diligence and estimations of
synergies. However, firms require support and cooperation from various stakeholders to ensure a
successful deal and to achieve the targeted synergies. Considering the importance of managing
stakeholders’ reactions appropriately, the period between the announcement and closing would
be of utmost interest. Therefore, to demonstrate the significance of stakeholders’ influence on
M&As most effectively, this study chooses the period “after announcement to closing” for the
52
research setting.
3.2.2 Theory and Hypotheses
Freeman (1984) described stakeholders as business entities affecting, and affected by, a firm’s
achievements and performance. Prior studies group stakeholders into primary and secondary
stakeholders (Clarkson, 1995; Waddock, 2006). Primary stakeholders are internal and external
interest parties possessing a direct relationship with the focal company, such as including
investors, employees, and suppliers, while secondary stakeholders have less direct interactions
with the organization, such as the community, particular interest groups, and governments
(Waddock and Graves, 2006). Primary stakeholders may have a stronger influence on the focal
firm than secondary stakeholders through their closer relationship to the firm. Thus, this study
concentrates on primary stakeholders’ influence on M&As in the empirical analysis, including
shareholders, employees, and lenders.
Employees. During the process of major strategic decision making, such as to pursue an M&A,
employees are not frequently invited to the process, or not adequately integrated into the project
plan. While a selection of top managers hold decision-making authority for efficiency, these
managers should consider employees because they need substantial cooperation from employees
to realize the expected synergies. In particular, firms need to communicate major changes in
corporate strategy to field workers and sales staff in order to share the strategic vision with them
and urge them to contribute to the newly established strategic target. If firms do not recognize the
importance of building relationships with employees, they could miss an M&A opportunity due
to strong resistance by employees or lose key employees after the deal because of an overall
53
failure of deal (Moran, 2014).
Stakeholders, including employees, will respond according to calculations of gains and
losses from the M&A, often to defend against any potential losses. Thus, for example, target firm
employees focus on compensation levels at the acquirer to determine whether they can expect a
rise or fall in their own incomes after the acquisition (Moran, 2014). Employees anticipating
benefits from the proposed transaction will become strong supporters of the deal, making it
easier for the acquirer to persuade them to cooperate and lowering the cost to close the deal
successfully. Avkiran (1999) showed acquirers to be more generous, reasonable, and innovative
than target firms in terms of welfare plans for employees and compensation policies. Acquirers
provide higher compensation overall, but especially in the case of overseas targets (Conyon,
Girma, Thompson and Wright, 2002). Parvinen and Tikannen (2007) showed that incentive
asymmetry in M&As results in opportunistic behavior from organization members, creating a
largely negative impact on the success of the M&A effort. Overall, previous research showed that
employees are sensitive to gains and losses after a firm’s strategic transition, such as during an
M&A, and normally expect to be better off. Thus, firms should approach employees’
anticipations carefully, particularly during M&As to avoid employees’ resistance against deal
progress that could lead to an unsuccessful effort.
In particular, the target firm’s employees and stakeholders may have a stronger reaction
than those of the acquiring firm since the stakeholders on the target’s side of the transaction will
undergo more change during the post-merger integration stage (Steynberg and Veldsman, 2011).
Target firm employees need to go through a negotiation stage for new working conditions, often
including compensation. Thus, target firm employees should have more anxiety around
54
upcoming changes in the transition period, or as early as the start of rumors of M&A. Since this
is so important, this study focuses on target firm employees’ responses and proposes that target
firm employees will expect to be better off after the transition if the acquiring firm’s employee
compensation in the year prior to the acquisition announcement is higher than the target firm’s,
which will encourage target firm employees’ cooperation. Thus,
Hypothesis 1. When acquirer employees’ average compensation is higher than target
employees’, the likelihood of completing an announced deal becomes higher.
In contrast to the acquirer’s compensation level, larger workforce size of the acquiring
firm could be recognized as a potential risk factor from the target firm employees’ perspective.
With a larger workforce, the acquiring firm may not need redundant roles and responsibilities
after the deal, which would lead to layoffs of target firm employees. Considering the target firm
employees’ anxiety on maintaining job security, larger employee size in the target firm would
result in resistance from its employees to the proposed M&A deal. Thus, the following
hypothesis is proposed:
Hypothesis 2. When the acquirer’s workforce is larger than target firm’s, the likelihood
of completing an announced deal becomes lower.
Shareholders. Other than the major shareholders, few are invited to participate in the corporate
decision-making process. Strategically important confidential information and critical decision-
making processes cannot be shared with every shareholder; therefore, most shareholders can
react to the firm’s strategic decision (i.e., M&A) only after the public announcement. A
considerable body of academic literature deals with shareholder issues during M&As, mostly
55
focusing on shareholder benefits (Ferreira, Massa, and Matos, 2009). The target firm’s
shareholders generally benefit via bid premiums immediately after the acquisition (Bradley,
Desai, and Kim, 1988; Jarrell and Poulsen, 1989). Previous studies pointed out that acquirer firm
shareholders expect to benefit by realizing post-acquisition performance (Jarrell and Poulsen,
1989; Laughran and Ritter, 1997). Usually, shareholders eventually gain investment returns
through dividends unless they sell their shares. Thus, shareholders who would maintain their
shares after the deal would carefully consider the post-deal stage (Dorata, 2012). Investors focus
on corporate business performance, particularly the financial aspect of the outcome, and try to
motivate better operational performance. Shareholders are also concerned about the share of the
realized profits. Since dividend propensity varies by company, owning shares in a firm that tends
to offer high dividends is important for all investors. Thus, from the shareholders’ perspective,
the merged firm’s dividend propensity is a considerably crucial point to consider, in addition to
operational performance.
Prior studies indicated that for M&As, the target firm’s shareholders benefit because the
acquirer pays the transaction cost. However, target shareholders seeking long-term benefits by
maintaining their shares after the acquisition may try to participate actively in the deal closing
process. As Laughran and Ritter (1997) describe, since the acquirer’s shareholders can further
benefit from various synergies during the post-acquisition stage, the target firm’s shareholders
are likely to be more active during the process than the acquirer’s shareholders. Thus, if the
acquiring firm shows a higher dividend propensity than the target firm, the target firm’s
shareholders would welcome the proposed M&A and cooperate in the deal. Therefore, the
following hypothesis is proposed:
56
Hypothesis 3. When the acquirer’s dividend propensity is higher than target firm’s, the
likelihood of completing an announced deal becomes higher.
Lenders. As suppliers of financial resources, banks and various financial institutions have a
strong influence on corporate business operations. Financial institutions such as banks have
expanded their business portfolios to possess multiple business operations and become financial
conglomerates. Financial conglomerates can utilize banks’ client relationships to pursue
additional business opportunities within the conglomerate. Drucker and Puri (2005) describe
financial conglomerates’ tendency to maximize synergies between businesses within the portfolio.
Banks have recently begun expanding their business from granting loans to providing financial
services. So far, few studies have examined how borrowers benefit in the lender-borrower
relationship considering bank’s limited business operations and its relatively fractional benefit
(Bharath, Dahiya, Saunders, and Srinivasan, 2007). Thus, recent research on lender-borrower
relationships examines various synergies of lending operations within financial conglomerates
(Bharath et al., 2007). Banks’ information about borrowers frequently includes important internal
information, making it difficult for borrowers to change main lenders easily, so lenders try to use
this relational asset (Petersen and Rajan, 1994).
Bank’s efforts to manage the client relationship and marketing activities to expand their
client base closely relates to maintaining relational assets. Strategic change, such as an M&A, in
a focal firm, as one of the suppliers, should allow lenders to connect with new opportunities.
Drucker and Puri (2005) also considered financial conglomerates’ expanded roles and
concentrated on M&As as events offering new business opportunities. Having more profits from
57
a current client through expanded service portfolios should be a great motivation for lenders to
support an M&A deal if they can maintain their position during and after the deal. However, not
every M&A of current clients can ensure new business opportunities, so lenders should examine
the benefits and losses to have a good understanding of the forthcoming situation and take
advantage of potential opportunities. To determine how to respond to a proposed M&A, lenders
should appropriately address the state of the relationship with the borrower and the possibility of
exploring new business opportunities after the deal.
To maximize the synergies within a financial conglomerate, lenders can participate
significantly in the clients’ M&A process from the early stage. Engaging early in the deal process
would enhance existing relational assets and urge clients to share more strategic plans with
lenders, resulting in further business chances. In particular, target lenders can be more active in
the deal process than the acquirer’s lenders due to anxieties around the potential loss of their
position after the proposed acquisition. If the target lenders foresee serious disadvantages after
the deal is completed, they would oppose and resist the deal progress as much as possible.
However, once they recognize the acquiring firm’s higher dependency on financial institutions
and potential business opportunities, they will cooperate during the M&A. Thus, the following
hypothesis is proposed:
Hypothesis 4. When the acquirer’s loan amount is higher than target firm’s, the
likelihood of completing an announced deal becomes higher.
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3.3 RESEARCH METHODS
3.3.1 Sample and Data
The analysis in this study uses data for M&As in Japan from 1995 to 2012. During this period,
Japanese economy went through a continuous depression after the collapse of asset-price bubbles
in the late 1980s, forcing firms to transform their business portfolios and follow an innovative
growth strategy to survive. There were 4,186 acquisitions during that period, allowing a
sufficient sample to perform empirical analyses.
This study focuses on M&As of publicly listed companies’ M&As to ensure the validity
and reliability of the information, excluding the financial industry, yielding a sample of 3,039
cases for the analysis of deal completion probability. Information about these M&As was
acquired from the Securities Data Corporation’s (SDC) worldwide merger, acquisitions, and
alliance database. SDC’s database provides detailed descriptions of public and private M&A
announcements internationally, including acquirer and target firm information. SDC’s database is
frequently used by academic researchers because it possesses an outstanding operating system
and knowledge to collect and provide information from more than 200 foreign language news
sources, SEC filings, and multi-national partners, including various proprietary sources from
investment banks and financial advisors. As for further information about shareholders and other
variables, I obtained the data from Needs Financial Quest.
3.3.2 Variables and Measures
Dependent Variables. I adopted dependent variable of deal completion probability, the
likelihood of completing an announced M&A was measured with a dichotomous variable coded
59
1 if an announced M&A was completed, and 0 otherwise.
Independent Variables. Employees’ compensation dummy took the value of 1 if acquirer firm
employees’ average compensation was greater than target firm employees’ average compensation
reported a year before the announcement, and 0 otherwise. Employees’ size dummy was coded 1
if the acquire firm’s figure was greater than the target’s figure for the year before the
announcement, and 0 for otherwise. Dividend propensity dummy took 1 if the acquirer firm’s
dividend propensity was greater than the target firm’s propensity, and 0 otherwise. Dividend
propensity information was also based on the financial statements for the year prior to the
announcement and was calculated by subtracting the target’s dividend propensity from the
acquirer’s dividend propensity. Loan amount dummy was coded 1 if the acquirer firm’s figures
were greater than the target firm’s figures. Loan amount difference was calculated by subtracting
the target firm figures from those of the acquirer based on the same financial statements.
Control Variables. To avoid any alternative explanations, this study considers several control
variables. Industry relatedness is a control variable because a related acquisition could enhance
frictions between negotiating firms that were previously industry rivals during the due diligence
stage and it could affect the likelihood of completing an announced M&A (Bergh, 1997).
Friction may also arise from excessive knowledge in the industry and among competitors, which
is associated with less information asymmetry in the acquisition (Hill and Hoskisson, 1987). I
applied dummy variables to measure industry relatedness, taking 1 if the primary four digits of
the Standard Industry Classification (SIC) code of the acquirer and target firms are the same, and
0 otherwise. M&A studies frequently use SIC codes when considering industry relatedness
(Markides and Ittner, 1994; Palepu, 1985). In addition, I controlled for the Existence of
60
competing bidders, since competing bidders remind firms that they may lose the benefits of a
proposed deal, as well as incur significant damage from the failed M&A (Puranam, Powell, and
Singh, 2006; Schweiger, 2002). I adopted a binary measure coded 1 if there is another bidder for
the target firm, and 0 otherwise, based on the SDC database.
As financial measures, I controlled for the Value of the deal, Operational performance of
the acquiring and target firms, and the Method of payment. The value of the announced deal was
obtained from the SDC database and measured as the log of the transaction value. Operating
performance was measured using the after-tax return on equity (ROE) of the previous year.
Several studies highlight the method of transaction payment and target firms’ preference for cash
(Fuller, Netter, and Stegemoller, 2002), captured in the present study with a dummy variable
coded as 1 if the acquirer used cash to pay for more than 50% of the transaction cost and 0
otherwise.
Research Model. To analyze stakeholders’ impact on the deal completion probability, I applied
logistic regression (Long, 1997), which regresses the dichotomous withdrawal and completion
variable on Xj, a vector of explanatory variables, with β as a vector of parameter estimates:
Logit: Pr (Completionj = 1｜Xj) = exp(Xjβ) / (1 + exp(Xjβ))
3.4 RESULTS
Table 4 summarizes the descriptive statistics and correlation matrix of all variables, excluding
year-dummy variables.
61
Table 4. Descriptive statistics and correlation matrix
Mean Std. Dev. 1. 2. 3. 4. 5. 6. 7. 8. 9. 10.
1. Deal completion (Yes=1; No=0) 0.97 0.17
2.Aspiration from employees' compensation difference
(1 if Acquirer - Target>0, 0 for otherwise)0.25 0.43 0.02
3.Aspiration from employees' size difference
(1 if Acquirer - Target>0, 0 for otherwise)0.64 0.48 0.00 0.34 *
4.Aspiration from dividend propensity difference
(1 if Acquirer - Target>0, 0 for otherwise)0.00 0.07 -0.02 0.01 0.01
5.Aspiration from loan amount difference
(1 if Acquirer - Target>0, 0 for otherwise)0.44 0.50 0.05 * 0.49 * 0.55 * 0.05 *
6. Acquisition deal value (Natural log of million USD) 2.56 2.03 -0.03 0.13 * -0.06 * -0.01 0.24 *
7.Industry relatedness between target and acquirer
(Yes=1; No=0)0.58 0.49 -0.03 -0.45 * -0.49 * -0.05 * -0.74 * -0.20 *
8. Acquirer's ROE 0.05 0.71 0.01 -0.01 -0.04 * 0.00 0.03 0.03 0.00
9. Target's ROE -0.18 3.77 0.01 0.01 -0.05 * 0.00 -0.01 0.01 0.06 * 0.04 *
10.Method of payment
(more than 50% of cash=1; otherwise=0)0.83 0.38 0.00 -0.23 * -0.21 * 0.00 -0.36 * -0.30 * 0.27 * 0.05 * -0.02
11. Existence of competing bidder (Yes=1; No=0) 0.00 0.04 -0.08 * 0.01 0.03 0.00 0.02 0.04 * -0.05 * 0.01 0.00 0.02
* for p<0.05
62
Table 5 presents the findings from the OLS estimate of the effects of stakeholders on the
likelihood of completing an announced M&A. Model 1 includes only the control variables. The
coefficients for the industry relatedness (b = -0.54, se = 0.24, p < 0.05) and the existence of
competing bidders (b = -2.65, se = 0.94, p < 0.01) are statistically significant. Control variables
and all independent variables were included in Model 2 to check the results for all hypotheses,
but they were tested separately in Model 3 to 6. The regression coefficients for the variable
Employees’ size dummy is negative and statistically significant at the 5 percent level (b = -0.57,
se = 0.27, p < 0.05), consistent with Hypothesis 2. As Hypothesis 2 predicts that a larger number
of employees in the acquirer firm than in target firm induces anxiety among the target firm
employees about the deal, a statistically significantly negative influence on deal completion
probability supports Hypothesis 2. Hypothesis 4 indicates that higher loan amounts for the
acquirer attract the target lenders and thus raise the deal completion probability. The regression
coefficient for Loan amount dummy is positive and statistically significant at the 1 percent level
(b = 0.98, se = 0.35, p < 0.01), thus supporting Hypothesis 4.
Hypothesis 1 predicts that higher average compensation for the acquirer firm employees
is positively associated with deal completion probability. The regression coefficient for the
dummy variable for Employees’ compensation dummy is positive but statistically non-significant
(b = 0.17, se = 0.31, n.s.), and thus not supported. Contrary to the prediction of Hypothesis 3, the
coefficient for Dividend propensity dummy is negative and statistically non-significant (b = -1.68,
se = 1.19, n.s.). Accordingly, a positive association of the acquirer’s higher dividend propensity
63
with the likelihood of deal completion is not supported.
Table 5. Result of regression analysis of deal completion probabilityd
d Robust standard errors are in parentheses. n = 3039.
Model1 Model2 Model3 Model4 Model5 Model6
H1 Employees' compensation dummy0.17
(0.31)
0.24
(0.29)
H2 Employees' size dummy-0.57
(0.27)
* -0.30
(0.26)
H3 Dividend propensity dummy-1.68
(1.19)
-1.42
(1.17)
H4 Loan amount dummy0.98
(0.35)
** 0.81
(0.36)
*
Acquisition deal value-0.06
(0.05)
-0.11
(0.06)
† -0.07
(0.05)
-0.08
(0.06)
-0.07
(0.06)
-0.07
(0.05)
Industry relatedness between target and acquirer-0.54
(0.24)
* -0.14
(0.35)
-0.46
(0.26)
† -0.67
(0.27)
* -0.55
(0.24)
* -0.04
(0.36)
Acquirer's ROE0.12
(0.08)
0.09
(0.07)
0.12
(0.08)
† 0.12
(0.08)
0.12
(0.08)
† 0.10
(0.07)
Target's ROE0.01
(0.01)
0.01
(0.01)
0.01
(0.01)
0.01
(0.01)
0.01
(0.01)
0.01
(0.01)
Method of payment
(more than 50% of cash=1; otherwise=0)
0.14
(0.30)
0.27
(0.32)
0.18
(0.30)
-0.07
(0.30)
0.13
(0.30)
0.33
(0.32)
Existence of competing bidder-2.65
(0.94)
** -2.44
(0.91)
** -2.63
(0.99)
** -2.59
(0.93)
** -2.67
(0.94)
** -2.58
(0.89)
**
Year dummy Yes Yes Yes Yes Yes Yes
Intercept4.01
(0.53)
** 3.77
(0.71)
** 3.88
(0.55)
** 4.38
(0.63)
** 4.03
(0.53)
** 3.28
(0.64)
**
R2 0.03 0.04 0.03 0.03 0.03 0.04
† for p<0.10, * for p<0.05, and ** for p<0.01. One-tailed test.
VariablesDeal Completion
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3.5 DISCUSSION AND CONCLUSION
This study begins by asking whether and how stakeholders influence the likelihood of
completing an announced M&A and analyzes data for M&As conducted by Japanese publicly
listed non-financial companies from 1995 to 2012 to address primary stakeholders’ influence on
the deal completion probability. First, stakeholders influence the likelihood of completing
announced deals. As existing stakeholder studies indicated, stakeholders influence focal firm’s
strategic decisions to defend their current benefits, which is in line with the findings in the
present study, which extends the basis of this theory to include the M&A context. Second,
stakeholders estimate their potential gains or losses when determining their response to a
proposed M&A. Stakeholders prefer to maintain their current power and benefits in their
relationship with a focal firm, even during a large-scale change, such as an M&A, and resist any
potential risk of loss to their current benefits or position. However, once they recognize the
potential benefits of the proposed changes, they become cooperative. The analytical results show
that the target firm’s employees react negatively to the acquisition process when the acquiring
firm’s employees outnumber them, thus assuring their job stability, and the lenders become
supportive if the acquirer has a higher dependency on financial institutions to achieve new
business opportunities.
3.5.1 Theoretical and practical implications
This study has several theoretical and practical implications. In terms of theory, this study
successfully demonstrated the influence of external determinants on the success of an M&A,
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which enables an outward perspective in addition to the existing internal focus of existing
research. This study concentrated on and provided empirical support for the role of stakeholders
surrounding focal firms and M&As, previously not regarded as influential factors in management
research.
In addition, this study successfully proposed dynamic settings when approaching
stakeholders’ interactions with firms. The management literature addressed stakeholder issues in
a static business environment, and this study induced a dynamic perspective to capture the
extemporary but fundamental motivation of stakeholders’ responses. Moreover, this study
considered stakeholders’ motivations in their reactions from a dyadic viewpoint by addressing
both the acquiring and target firms’ stakeholders’ and comparisons to measure the influence on
dependent variables.
For practitioners, the results of this study provide meaningful strategic screening criteria
when performing due diligence on a target firm. During the due diligence stage, the acquirer
focuses on corporate valuation, risk assessment, and synergy estimation (Steynberg and
Veldsman, 2011), with the scope now expanding to include integration and operational due
diligence. However, this focus on the financial aspects and economic benefits of the acquisition
and risk calculations rarely consider stakeholders, though they have a considerable influence
after the announcement stage and into the post-acquisition period. Thus, as this study
demonstrated that firms need to consider stakeholders as potential obstacles to deal completion
and devise effective plans to utilize them as valuable resources for a successful M&A.
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3.5.2 Limitations and Directions for Future Research
Though this study provides meaningful results, it has a few limitations that could be addressed
by further research. First, the research model in this study does not account sufficiently for all
independent variables since there is limited knowledge outside of that provided by finance
scholars assessing market pressures after the announcement stage such as competing bids,
financial status, and so on (Weston, Siu, and Johnson, 2001), which demonstrated a strong
influence in my analyses as well. Future studies could complement this research model by
narrowing the research focus to specific stakeholder issues, including more subspecialized
situations or sub-categorized stakeholder characteristics.
Second, the sample of this study is restricted to listed Japanese non-financial firms. The
deal completion probability of my sample was extremely high (0.96), possibly due to the well-
mannered Japanese business culture (Cartwright and Cooper, 1993), especially the tendency to
observe a commitment. Furthermore, employees’ attitude toward job security, as well as the
relationship with lenders and shareholders, should be considered in conjunction with the
Japanese cultural context. This may decrease the overall generalizability of the findings. An
analysis using data from another cultural context would add to this study’s accountability and
generalizability. Additionally, considering the increasing number of cross-border transactions
(Muehlfeld, Sahib, and Witteloostuijn, 2012), a study of stakeholders and M&As in a cross-
border setting would be interesting. Cross-border transactions have more complexity, including
stakeholder relationships, cultural differences, and so on. Several earlier studies noted the issue
of culture in cross-border transactions and deal completion probability (Muehlfeld et al., 2012),
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but could not exhaustively account for the effect of these factors on a successful acquisition.
Thus, future research on cross-border transactions addressing stakeholder issues with deal
completion would be meaningful and contributive to stakeholder, M&A, and international
business research.
Finally, as an extension of this study, it would be interesting to examine the events
following a deal’s closure. This study postulated completion as a successful transaction in the
short-term. However, completion does not guarantee a successful integration process or
increased firm performance. There remain some risks after closing, especially due to the
remaining concerns from the surrounding stakeholders. This study explored stakeholders’
immediate and extemporal responses to an announcement based on their anticipation of
upcoming changes. However, during the integration stage, stakeholders will face a reality that
diverges from their expectations. Thus, the predictors of higher deal completion probability may
not be good predictors of post-acquisition performance. Extending my research horizon to the
post-deal stage would help clarify the dynamics of influential factors affecting the success of an
M&A.
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CHAPTER 4. STUDY THREE: HOW DOES A COMMON LENDER TO BOTH SIDES
OF THE M&A DEAL INFLUENCE THE ACQUIRER’S MARKET VALUATION?
4.1 INTRODUCTION
The corporate business environment is often difficult to cope with and challenges managers to
better understand their surrounding stakeholders (Freeman, 1984; Frooman, 1999). As the
influence of stakeholders on corporate business activities grows stronger, stakeholders are
participating more and more in firms’ strategic decisions directly and indirectly (Frooman, 1999).
Academic research has paid significant attention to the stakeholder phenomenon (i.e., Freeman,
1984; Frooman, 1999; Clarkson, 1995; Waddock, 2006; Dorata, 2012), examining stakeholders’
involvement in the corporate decision-making process, among other aspects. Recent research
streams on the stakeholder perspective include the issue of corporate sustainability, which
reflects the trend to broaden the definition of stakeholders to cover more and more business
relationships (Waddock, 2006; Waddock, and Graves, 2006). Although many studies have paid
attention to the categories or definitions of stakeholders and their levels of participation in
business activities, few studies cover the impact of stakeholders on firm strategic actions such as
mergers and acquisitions (M&A). M&A are a frequently used corporate growth strategy (King et
al., 2004). Due to maturing markets and a globalized economy, M&A have become much more
popular as strategic growth options (Dorata, 2012). However, because of the financial nature of
M&As, firms are strongly advised to overcome any potential risks from such large-scale
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investments, particularly in the early stage of M&A implementation, by appropriately managing
deal progress and post-merger integration (PMI). In reality, there are many M&A failures, which
result in significant damage (Haspeslangh and Jemison, 1991; Schweiger, 2002). To enable M&A
success, an in-depth understanding of the stakeholders involved is necessary as stakeholders
have significant influence on corporate strategic decisions such as M&A (Preston and Sapienza,
1990). A better understanding of the stakeholders involved includes an awareness of the
characteristics of their reactions to M&A and the motives behind their responses. As posited in
prior studies (i.e., Frooman, 1999; Preston and Sapienza, 1990), stakeholders influence firms’
strategic decisions. Thus, they can also significantly influence the decisions and progress of
M&A. At the same time, depending on their expectations of receiving either a benefit of a loss
from the proposed M&A, stakeholders may try to influence the deal positively or negatively. In
the case of a proposed M&A, it is extremely important for the corporate business manager to
predict and manage stakeholder reactions appropriately and be able to gain cooperative support
to proceed with the deal and achieve successful outcomes.
According to prior studies on stakeholders, there are several categories (i.e. Waddock,
2006; Waddock and Graves, 2006). There are primary stakeholders such as employees,
customers, suppliers, and shareholders, who provide basic management resources and directly
influence daily corporate business operations, and secondary stakeholders such as special interest
groups and the government, who have an indirect but critical impact on corporate business
activities (Waddock and Graves, 2006). Among the most important groups of stakeholders
influencing a firm’s daily business operations are the firm’s financial lenders responsible for
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supplying financial resources.
The means of obtaining financial resources have evolved and have become more
complex and difficult to understand. However, the need for financial resources for strategic
growth remains continuously important for survival in mature markets as well as fast-changing
business environments (Lummer and McConnell, 1989). Thus, there has long been academic
attention paid to lenders and borrowers and this relationship. In the past, financial economists
addressed the lender-borrower relationship by mainly focusing on the borrower’s benefit (i.e.,
Dass and Massa, 2011; Lummer and McConnell, 1989; Petersen and Rajan, 1994), emphasizing
information asymmetry and a lending relationship that enabled borrowers to obtain the necessary
financial resources to successfully execute a planned business strategy. Subsequently, researchers
turned their attention to the lender’s benefit (Bharath et al., 2007). Some recent strategic changes
in the scope of banking services have brought about various opportunities for lenders who have
maintained strong lending relationships. Such relationships enable lenders to provide a variety of
financial services such as underwriting and M&A advice (Drucker and Puri, 2005). Following
the changes in the lenders’ business models and new business opportunities from lending
relationships, academic research studied the lending relationship and its positive association with
the lender’s benefit (e.g., Bharath et al., 2007; Drucker and Puri, 2005).
To further expand on the existing research on this topic, this study asks the following
questions in terms of four hypotheses. As a primary stakeholder, how does the lender react to a
firm’s M&A? How would the deal be influenced when the same lender advises both sides of the
deal? How would this common lender’s strong lender-borrower relationships influence deal
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progress and post-acquisition performance? In an empirical setting, this study examines cases
where both sides of the M&A deal have the same lender. As a stakeholder who directly and
significantly influences a firm’s business activities, the common lender’s influence on deal
progress and M&A performance is investigated, along with its relationship with the firms.
Prior research on lending relationships describe the various benefits to lenders and
borrowers of a strong relationship such as additional loans, fee-based advisory services, and a
stable financial resource supply (Burch, Nanda, and Warther, 2005; Drucker and Puri, 2005;
Yasuda, 2005). Based on such research, this study predicts that the existence of a common lender
on both sides of the deal and its lending relationships bring benefits and costs to the lender and
borrower such that the lender and borrower react and influence the deal progress and post-
acquisition performance. I expect the existence of the common lender on both sides of the deal to
reinforce the lending relationship with the borrower in the deal, which reinforces the lender’s
benefit and results in the cooperation of the lender in advancing the deal. However, the existence
of the same lender on both sides makes the borrower firm and its shareholders consider the
potential risks from over-centralized benefits to one lender, which may cause negative returns for
the borrower that result in a negative association with post-acquisition performance. As for the
common lender’s relationships, the borrower’s higher dependency on the lender in terms of loan
amounts could be more beneficial to the borrower than the lender (Dass and Massa, 2011) since a
higher level of borrower dependency could imply a higher risk for the lender in managing
existing loans and business opportunities with other current “big” clients. Thus, lenders may cede
profits in this relationship that may create a negative response to the deal progress by lenders.
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However, a borrower who enjoys a strong relationship with a lender would be expected to have a
positive association with their future returns.
The analysis in this study examines publicly listed companies and their M&A in Japan
between 1995 and 2012. This research looked at 448 cases of post-acquisition performance
examples. During this 18-year period, to survive a persistent economic recession, financial
institutions in Japan developed various new businesses under the umbrella of financial
conglomerates, while corporations (the borrower side) put extensive efforts into strategic
transformation (Ogawa, Sterken, and Tokutsu, 2007). Thus, this situation allows for a suitable
environment in which to examine the lender-borrower relationship and the lenders’ active
responses based on expected future benefit or loss from borrowers’ strategic transformation.
The findings of this study extend the research horizon on lender-borrower relationships
to the context of M&A and offer an in-depth understanding of such stakeholders’ underlying
motives in influencing firm’s strategic actions.
4.2 THEORY AND HYPOTHSES
4.2.1 Common lender and lender benefits
The lender-borrower relationship has been discussed extensively in the finance field, especially
in finance intermediation and finance economics (i.e., Bharath et al., 2007; Boot, 2000; Dass and
Massa, 2009; Drucker and Puri, 2005; Lummer and McConnell, 1989; Petersen and Rajan, 1994).
Many academic studies in the past regarding lender-borrower relationships have focused on
borrower benefits, but there are many recent studies that pay attention to lender benefits (i.e.,
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Dass and Massa, 2011; Lummer and McConnell, 1989; Petersen and Rajan, 1994). Lenders are
able to obtain a variety of corporate information, including insider information that may not be
known to external parties, during the due diligence process for loan approve (Diamond, 1984;
Lummer and McConnell, 1989). Moreover, after the approval of the loan, the lender may have
sustainable access to insider information through the monitoring process as well (Diamond, 1991;
Rajan and Winton, 1995). Lenders obtain insider information by continuous interactions with
borrowers though their lending relationships (Lummer and McConnell, 1989). The renewal of a
loan agreement provides a longer-term lending relationship and reinforces the depth of the
relationship through the accumulated volume and quality of the insider information, enabling the
lender to sustain a competitive edge through information asymmetry, resulting in an even longer
and stronger relationship with the borrower (Dass and Massa, 2011).
Such insider information can be considered an advantage for lenders, helping them save
on the costs of the services they provide. These costs include screenings and evaluations for loan
approvals, which require processing time (Petersen and Rajan, 1994). However, by securing
accumulated insider information, including quantitative and qualitative operational information,
financial performance, and records of prior assessments, lenders can significantly save on the
costs of processing borrower evaluations (Drucker and Puri, 2005). The cost savings capability
of the lender for a specific borrower can be regarded as a fundamental competitive advantage
and thus recognized as a potential benefit to the lender.
Another lender benefit from its strong lender-borrower relationship relates to the scope
of the lender’s business activities (Drucker and Puri, 2005; Yasuda, 2005). As already stated, the
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traditional business model of commercial banks has evolved and now includes a variety of
financial services such as underwriting and M&A advice, which in the past were traditionally
regarded as security industry companies’ service offerings (Drucker and Puri, 2005). These
changes in the traditional scope of work and the expansion of the banks’ service portfolios
enabled these lenders to make better use of their lender-borrower relationships. Drucker and Puri
(2005) found lenders with existing lending relationships had a higher probability of getting
additional investment banking business such as seasoned equity offerings (SEO). Yasuda (2005)
also found a positive association between the existing lending relationship and a positive
probability of additional debt underwriting business. Such findings imply that the lending
relationship not only enables lenders to sustain longer-term relationships but also to enjoy new
business opportunities.
Strong lender-borrower relationships allow lender benefits as described above. At the
same time, many corporations are pursuing strategic transformation to cope with fast-changing
business environments such as globalization and industry maturation (Dorata, 2012). The firm’s
strategic decisions and implementation of strategic initiatives accompanies a need for large-scale
financial investments and can be recognized as an opportunity for lenders. However, not every
lender can take advantage of such opportunities. Only lenders who obtain and maintain strong
lending relationships will be able to enjoy the benefits of these new opportunities (Dass and
Massa, 2011). The firm’s strategic transformation and related strategic initiatives, such as M&A,
can bring basically three potential benefits to lenders (Bharath et al., 2007; Drucker and Puri,
2005). First, M&A enable lenders to receive additional loan business. Executing M&A
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agreements requires a large amount of financial resources in the early stages of implementation;
this means that the acquirer needs to plan for various financing strategies such as additional loans,
issuing bonds, or other financial instruments. Thus, additional loan business would be the first
benefit that a current lender could expect. Second, beyond the additional loans, the acquirer will
be considering many other ways to obtain sufficient financial resources to implement its strategic
initiatives and will thus look for advice on various financing strategies. Considering that M&As
are infrequent within a firm, even with a regular team in charge of the execution of M&As and
related financing, an advisory service from an external professional firm would be necessary to
develop a comprehensive financing strategy and the management of related initiatives efficiently
and successfully. The recent expansion of these lenders’ work scope to cover investment banking
now enables lenders to meet this need on advising overall financing strategy and supporting
implementation of large-scale strategic activities such as M&A. Third, M&As accompany
various environmental changes, including the position and power of various stakeholders, which
allow some stakeholders opportunities to grow their business (Haspeslangh and Jemison, 1991;
Dorata, 2012). In particular, lenders who have relationships with acquirers and target firms who
are significantly dependent on them may continue to have power after the closing of the deals,
with their positions sustained during the PMI period. Thus, overall, lenders who maintain strong
lending relationships can benefit through M&As. Moreover, in the case of a common lender on
both sides of the deal with a strong lending relationship with both M&A participants, service
offerings of the lender can be more competitive and their business more efficiently operated by
utilizing integrated sales channels and the accumulated information of both participants. The
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scope and depth of services that lenders can provide can be broader and deeper after the
acquisition.
Lenders with strong lending relationships can enjoy benefits from firms’ large-scale
strategic actions such as M&As. If the lender on both sides of the deal is the same, the lender can
expect greater benefits through these lending relationships. However, the existence of one
common lender on both sides of the deal can cause concerns in the capital market and among the
borrowers (acquirers) over the possibility of excessive benefits to the one lender. In other words,
the lender could be perceived as a sole beneficiary of the deal. In a previous study, Boot (2000)
pointed to this as a “hold-up” problem, which describes the lender’s status in having an
information monopoly from the overflow of the borrower’s proprietary information and a loss in
bargaining power for the borrower. In that case, borrowers cannot control the depth and volume
of insider information that the lender already possesses and it enables the lender to maximize its
profits from the relationship through its dominant power position (Rajan, 1992). For example,
lenders can request unreasonable interest rates and rearrange loan agreements for their own
profits (Rajan, 1992; Sharpe, 1990). Thus, the lender’s dominant power in the relationship with
the borrower may have a negative influence on the borrower’s operational performance in the
long run. In particular, the capital market may notice such risks from a shareholder perspective
and may respond negatively to the existence of a common lender on both sides of the deal. Thus,
this research predicts the existence of a common lender in M&A brings a negative association
with the acquirer’s cumulative average returns (CAR).
Hypothesis 1. The existence of a common lender on both sides of the M&A is negatively
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associated with the acquirer’s abnormal returns.
4.2.2 Strong ties between the common lender and borrower and borrower benefits
In this study, M&As have been regarded as events reinforcing the existing lender-borrower
relationship and predicts that a common lender will influence the deal progress and stock market
valuation of the acquiring firm. In this section, I address the influence of the common lender’s
relationship on the deal’s progress and acquisition performance in terms of CAR. The lending
relationship and depth of the relationship can be interpreted mainly from the borrowers’
perspective in terms of their dependency on the lender.
What are the borrower’s benefits from a strong lender-borrower relationship? Many
economic researchers have examined the impact of the lending relationship in terms of the
capability to obtain sufficient financial resources (i.e., Dass and Massa, 2011; Lummer and
McConnell, 1989; Petersen and Rajan, 1994). The findings indicate that borrowers can have
stable access to financial resources through strong lending relationships based on accumulated
insider information and enhanced information asymmetry (Lummer and McConnell, 1989). In
addition to outstanding operational performance, having a strong lender-borrower relationship
also enables corporations to obtain sufficient financial resources to consider more aggressive
strategic options for further growth (Petersen and Rajan, 1994). Moreover, recent lender service
offerings in the investment banking arena offer further benefits to borrowers as well (Drucker
and Puri, 2005; Fraser et al., 2011). In the past, corporate financing was rarely utilized by small,
medium, non-listed companies. However, today, many financial institutions, including
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commercial banks and financial conglomerates, provide services and advice on corporate
financing, and more companies are seeking such financial resources through a variety of
corporate financing methods (Yasuda, 2005). Through the lending relationship, borrowers can
take advantage of the lender’s agency role within the capital market. These lenders cooperate
with other players in the capital market as they conduct various business activities (Lummer and
McConnell, 1989). Once the lending relationship is established, a lender can monitor the
borrower’s business performance and try to get its creditworthiness recognized in the overall
capital market by utilizing the lender’s own network in the capital market (Diamond, 1984,
1991). Moreover, by getting the lending approval of a credible financial institution, a positive
impression can be created of the borrower’s creditworthiness throughout the capital market (Dass
and Massa, 2011). In short, a strong lender-borrower relationship offers a variety of opportunities
to borrowers, and M&As reinforce the existing lending relationship. For the successful execution
of the M&A, borrower benefits arising from the strong lender-borrower relationship, such as a
comprehensive financial advisory service with sufficient financial resources and an active agent
role in the capital market, would be necessary. Through M&A events, the borrowing firm will be
able to receive strong support from the lender to achieve successful acquisition performance.
Thus, this study predicts that stronger ties between the common lender and the borrower have a
positive influence on the stock market valuation of the borrower.
Hypothesis 2. The stronger the ties between the common lender and the acquiring and
target firms, the higher the acquirer’s abnormal returns.
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4.3 RESEARCH METHODS
4.3.1 Data and samples
The samples used in this research are publicly listed companies with M&As in Japan between
1995 and 2012. There were 448 cases in the CAR model. During the given period of observation,
many Japanese financial institutions had actively developed new business models to survive
through the continuous economic recession (Ogawa et al., 2007). This situation enables this
study to effectively address the lender-borrower relationship, reflecting the lenders’ strong
intentions to develop new business.
This study focused on publicly listed firms to avoid difficulties in collecting sufficient
data and to ensure reliability. Moreover, considering the financial industries’ discriminative
characteristics, this study excluded samples from the financial industry. As for the M&A, I
consider the equity transfer of more than 50% of the firm share to the acquirer as a sample M&A
(Moeller, Schlingemann, and Stulz, 2005). M&A data were obtained from the Securities Data
Corporation’s (SDC) worldwide merger, acquisitions, and alliance database. The SDC database
gives detailed descriptions on M&A carried out both publicly and privately. Many academic
studies use M&A data from SDC’s database since it has a renowned system and the ability to
collect information from various related news sources (Schilling, 2009). The database
incorporates information from SEC filings, investment banks, and various M&A advisors.
Corporate financial information and data on lenders were collected from the Needs Financial
Quest database.
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4.3.2 Cumulative abnormal returns
This study adopted the event study method based on previous research (i.e., McWilliams and
Siegel, 1997). The event study is a method for measuring the impact of an unpredicted event on
stock prices in the form of the sum of abnormal returns or CAR during an event window.
Abnormal returns are the difference between the stock market’s expected value and the real value
of the stock. The ordinary least squares (OLS) estimation used here is as follows:
𝑅𝑖𝑡 = 𝛼𝑖 + 𝛽𝑖 × 𝑅𝑚𝑡 + 𝜀𝑖𝑡,
where i represents the firms; t indexes days; Rit is the rate of return on the stock price of firm i on
day t; Rmt is the rate of return on TOPIX, the stock price index capturing all Japanese domestic
companies listed in the first section of the Tokyo Stock Exchange, on day t; 𝛼 is the intercept
term; 𝛽 is the systematic risk of stock i; and 𝜀𝑖𝑡 is the error term with E(𝜀𝑖𝑡) = 0. The estimation
period for this model is 150 days, that is, from 200 to 51 trading days prior to acquisition
announcement (Chatterjee, 1991).
In addition, the study measured the return on the stock of firm i on day t as follows:
�̂�𝑖𝑡 = 𝛼𝑖 + 𝛽𝑖 × 𝑅𝑚𝑡,
where 𝛼 and 𝛽 are the OLS parameters.
Based on the estimated return on the stock of firm i on day t, I calculated the abnormal
return of firm i as follows:
𝐴𝑅𝑖𝑡 = 𝑅𝑖𝑡 − �̂�𝑖𝑡 .
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Then, I calculated CAR by summing the abnormal returns during -3 to 3 trading days, where day
0 represents the acquisition announcement. The seven-day (-3 to 3) event window has been used
in other academic research (e.g., Arikan and Capron, 2010; Flammer, 2013). The capital market’s
response to the announcement of an acquisition can be appropriately captured within this period
of time considering the Japanese capital market’s well-developed access to market information.
4.3.3 Variables and measures
Dependent variable. The dependent variables for the regression analysis is the CAR of the
acquirer within the event window [-3, 3]. I selected this event window since a shorter window
may reflect unnecessary noise that does not relate to the acquisition announcement (McWilliams
and Siegel, 1997). Considering the fast-spreading nature of the acquisition announcement news
across the overall capital market, this event window will still be able to reflect the reactions of
the stock market to the lender-borrower relationship.
Independent variables. The first independent variable is The existence of the common lender. It
was measured by a dummy variable that takes 1 if there is a common lender on both sides, and 0
otherwise. The relationship between the common lender and both potential borrowers was
estimated by the total amount of loans from the common lender to the acquiring and target firms.
This can be interpreted as the indicator showing the M&A participants’ dependency on the
common lender and represents the levels of their lender-borrower relationships.
Control variables. To avoid alternative explanations, this study applied several control variables
in the research model. Deal size was controlled for since the size of the transaction may
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accompany more complex issues in managing successful integration (Laamanen, 2007). Deal
size was measured by the value of the transaction in millions of US. dollars. An Industry
relatedness dummy variable was included in the estimation, taking 1 if the acquirer and target
firms operated in the same industry, and 0 otherwise. This factor could influence the CAR as a
result of added resistance from the target firm since, during the due diligence process of the
acquisition, conflicts may be exacerbated between the negotiating firms who had been rivals in
the industry (Bergh, 1997). Moreover, better knowledge of the business and the industry
competitors may positively influence the post-acquisition performance (Hill and Hoskisson,
1987). To identify the industry relatedness, this study used primary four-digit Standard Industry
Classification (SIC) codes (Palepu, 1985). The Operating performance of acquirer and target
firms were adjusted due to the nature of the CAR, reflecting the prior economic and financial
condition of the firms in the form of their returns on equity (ROE) before the acquisition
announcement. The Method of payment was controlled for as a dummy variable as a cash
payment may accelerate the stabilization of business operations in the post-acquisition period,
resulting in a positive acquisition performance (Fuller, Netter, and Stegemoller, 2002). The
dummy variable took the value of 1 if more than 50% of the payment was cash, and 0 otherwise.
The existence of a Competing bidder was controlled for as a dummy variable in the estimation
since the acquisition price follows the principles of the market economy and free competition,
while its fluctuation reminds bidders of the possible significant disadvantages of a failed
acquisition (Puranam, Powell, and Singh, 2006; Schweiger, 2002). The Cross-border transaction
was also controlled for as this transaction accompanies complex problems for the acquirer to
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manage and, thus, may have a negative influence on post-acquisition performance (Koo, 2012;
Schweiger, 2002). The Cross-border deal dummy variable took the value of 1 if the deal
included either an in-bound or out-bound M&A transaction, and 0 otherwise. The acquirer’s
Acquisition experience was also controlled for in the estimation because such experience could
enhance the integration capability of the acquirer and the possibility of successful acquisition
performance (Haleblian and Finkelstein, 1999; Haspeslangh and Jemison, 1991; Hitt et al., 1998)
and recent acquisition experience may also overcome any resource insufficiency to cope with
challenges in the integration stage. This was measured by the frequency of acquirers’ acquisitions
in the last three years. In addition, the model included the acquirer and target firms’
Manufacturing dummy and Fiscal year dummy variables.
4.3.4 Research model
To discover the influence of the common lender on M&A progress and acquisition performance,
this study adopted the dependent variable of the cumulative abnormal returns for regression
analysis. Accordingly, the OLS model used for analysis was as follows:
𝐶𝐴𝑅𝑖𝑡 = 𝛼𝑡 + 𝑋𝑖𝑡′ 𝛽 + 𝜀𝑖𝑡,
where 𝑋 is a vector of explanatory variables, with 𝛽 as a vector of the regression coefficients
and 𝜀 as the error term; i represents the acquirer and t the number of years while 𝛼𝑡 represents
the fixed effects of the number of years. CAR has a seven-day event window of -3 to +3 trading
days. A one-tailed test was applied for the significance levels of the explanatory variables.
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4.4 RESULTS
Tables 6 and 7 summarize the descriptive statistics and the correlation matrix, respectively, of all
variables except the manufacturing dummy and year dummy variables.
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Table 6. Descriptive statistics
Variable Description Obs Mean Std. Dev. Min Max
car_m3_~4_TX Cumulative abnormal return 448 0.00 0.10 -0.88 0.90
OV_Lender_~m Common lender_dummy 448 0.35 0.48 0.00 1.00
Total_Debt~l Total borrowing from common lender 448 38,403.32 120,193.30 0.00 1,025,178.00
ln_deal_size Deal size (natural log of Mil. USD) 448 4.32 1.62 -0.04 9.15
SIC_dummyIndustry relatedness b/w acquirer and target
(Yes=1; No=0)448 0.28 0.45 0.00 1.00
ROE_A Acquirer's ROE 448 0.02 0.53 -6.96 1.65
ROE_T Target's ROE 448 -0.22 2.06 -24.14 20.27
method_pay2Method of payment
(+50% of cash=1; otherwise=0)448 0.47 0.50 0.00 1.00
competing_~d Existence of competing bidder (Yes=1; No=0) 448 0.00 0.07 0.00 1.00
cross_bd2 Cross border transaction dummy (Yes=1; No=0) 448 0.01 0.09 0.00 1.00
A_acq_exp_3 Acquirer's acquisition experience 448 0.44 1.03 0.00 6.00
A_Manuf_du~y A_Manuf_du~y 448 0.56 0.50 0.00 1.00
T_Manuf_du~y T_Manuf_du~y 448 0.17 0.38 0.00 1.00
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Table 7. Correlation matrix
Description 1 2 3 4 5 6 7 8 9 10
1. car_m3_~4_TX Cumulative abnormal return
2. OV_Lender_~m Overlapping lender_dummy -0.11*
3. Total_Debt~l Total borrowing from common lender 0.00 0.45*
4. ln_deal_size Deal size (natural log of Mil. USD) -0.01 0.03 0.12*
5. SIC_dummyIndustry relatedness b/w acquirer and target
(Yes=1; No=0)0.03 0.02 -0.02 0.25
*
6. ROE_A Acquirer's ROE -0.23*
-0.04 -0.02 -0.03 -0.04
7. ROE_T Target's ROE 0.01 0.02 0.01 0.13*
0.03 0.02
8. method_pay2Method of payment
(+50% of cash=1; otherwise=0)-0.01 -0.04 -0.02 -0.27
*-0.26
*0.10
*-0.06
9. competing_~d Existence of competing bidder (Yes=1; No=0) 0.00 0.00 -0.02 0.12*
0.00 0.00 0.01 0.07
10. cross_bd2 Cross border transaction dummy (Yes=1; No=0) 0.04 -0.06 -0.03 0.00 0.01 -0.03 -0.09*
-0.01 -0.01
11. A_acq_exp_3 Acquirer's acquisition experience -0.06 -0.01 0.00 0.01 -0.04 0.01 -0.04 0.21*
0.04 -0.04
* for p<0.05
Variable
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Table 8 describes the results of the OLS models, which estimated the common lender’s impact
on the acquisition performance. Models 1 include only the control variables of both estimation
models. The coefficients for the acquirer’s ROE (b = -0.05, se = 0.01, p < 0.00) and acquisition
experience (b = -0.01, se = 0.00, p < 0.03) are statistically significant.
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Table 8. Result of regression analysis of cumulative abnormal return of acquirer (-3, +3)e
e Robust standard errors are in parentheses.
Model1 Model2 Model3 Model4
-0.03 * -0.02 *
(0.01) (0.04)
0.00 * 0.00
(0.01) (0.45)
0.00 0.00 0.00 0.00
(0.17) (0.16) (0.22) (0.15)
0.01 0.01 0.01 0.01
(0.44) (0.33) (0.37) (0.43)
-0.05 ** -0.05 ** -0.05 ** -0.05 **
(0.00) (0.00) (0.00) (0.00)
0.00 0.00 0.00 0.00
(0.16) (0.24) (0.22) (0.16)
0.01 0.01 0.01 0.01
(0.31) (0.37) (0.32) (0.32)
0.00 0.01 0.01 0.00
(0.90) (0.45) (0.64) (0.87)
0.04 0.03 0.03 0.04
(0.61) (0.72) (0.71) (0.61)
-0.01 * -0.01 * -0.01 * -0.01 *
(0.03) (0.04) (0.04) (0.03)
-0.01 -0.01 -0.01 -0.01
(0.44) (0.23) (0.30) (0.42)
0.00 0.00 0.01 0.00
(0.69) (0.74) (0.63) (0.73)
Year dummy Yes Yes Yes Yes
0.09 ** 0.09 ** -0.05 † 0.09 **
(0.00) (0.00) (0.07) (0.00)
R2 0.13 0.14 0.14 0.13
† for p<0.10, * for p<0.05, and ** for p<0.01. One-tailed test.
Intercept
Method of payment dummy
Competing bidder dummy
Cross border deal dummy
Acquisition experience
Acquirer's industry dummy
(Manufacturing=1; No=0)
Deal size
Industry relatedness dummy
Acquirer's ROE
Target's ROE
Target's industry dummy
(Manufacturing=1; No=0)
VariablesCumulative Abnormal Return
Common lender dummy
Total borrowing from common lender
H1
H2
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Models 2 in Table 3 include both independent variables in their respective estimations with the
set of control variables, whereas in Models 3 and 4 these were tested separately. Models 2
present the results of both hypotheses tested in this study. Hypothesis 1 predicts that a common
lender results in negative abnormal returns for the acquirer. The regression coefficient for the
variable is significantly negative at the 5 percent level (b = -0.03, se = 0.01, p < 0.01). The CAR
of the acquirer decreases by 0.03 percent when there is a common lender on both sides of the
deal, supporting Hypothesis 1. The positive influence of strong ties between the common lender
and borrower on the CAR of the acquirer is predicted in Hypothesis 2. The coefficient of the
variable is positive and statistically significant at the 5 percent level (b = 6.17E-08, se = 0.01, p <
0.01), supporting Hypothesis 2. According to the results, the CAR of the acquirer increases by
6.17E-08 percent when the total debt of the acquirer and target firms from the common lender
increase by one thousand dollars.
To ensure the empirical results’ robustness, I conducted regression estimations using
CARs with different event windows: -1 to 1 and -2 to 2 trading days. The results are identical to
the original in terms of the signs and significance levels of the independent variables.
4.5 DISCUSSION AND CONCLUSIONS
This study investigates whether a common lender on both sides of the M&A influences
acquisition performance. This research question was empirically examined based on 18 years of
M&As in Japan. The findings from the empirical tests can be summarized as follows. First, the
90
existence of a common lender on both sides of the M&A has a negative association with CAR.
This result corroborates the prediction, reflecting the capital market’s concerns over the
possibility of excessive and biased benefits to the common lender. The existence of common
lenders on both sides of the deal includes the possibility for lenders to wield larger power in the
lender-borrower relationship. For example, through the common lending position, the lender can
have “more than enough” insider information on both M&A participants, and this information
monopoly may enable the lender to amend a loan agreement to their advantage when renewing
the agreement or request for immoderate interest rates. In addition, the lender’s monitoring
authority may result in lender-oriented financial management decisions such as reducing
dividends or investments, which could result in a negative response from the capital market to
the existence of the common lender in the M&A deal.
Second, higher dependency of the borrowers on a common lender has a positive
influence on the acquirer’s CAR. In this case, the implication is that the capital market
recognizes the acquirer’s benefits in this strong relationship with the common lender. Specifically,
the fact that the lender’s awareness of the potential risk of losing all the business post M&A
potentially encourages the lender to forgo profits to maintain the relationship. Moreover, the
acquirer may also gain the benefit of expanded service offerings from the lender in terms of
corporate finance, which may enable the acquirer to obtain additional financial resources. Further,
the acquirer could benefit from the lender’s role as agent in the capital market to encourage other
financial institutions and investors to positively view the acquirer’s operating performance and
creditworthiness.
91
4.5.1 Theoretical and practical implications
This study provides several theoretical and practical contributions. First, as a theoretical
contribution, the findings expand the existing lender-borrower research horizon to include M&A
events. In particular, by observing the influence of the common lender on both sides of the M&A,
the study empirically examined and supported the role of the common lender as a reinforcing
factor in the lending relationship. In addition, although existing lender-borrower relationship
theories focus on the “static” status of the relationship (e.g., Bharath et al., 2007; Dass and
Massa, 2011; Drucker and Puri, 2005), this study sheds light on the “dynamics” of the changing
relationship through the acquirer’s strategic transformation. Thus, this study provides insights on
how the existing lending relationship is utilized based on a firm’s strategic actions.
Second, this research provides insights regarding stakeholder management theory. The
findings describe the dynamics of stakeholders’ reactions to M&A based on the lender-borrower
relationship. In particular, the study was able to account for the common lenders’ influence on
M&A. The role of the common lender on both sides of the deal has been found to reinforce the
lender-borrower relationship and various lender benefits while there is a negative stock market
reaction to the acquirer due to the concerns about potential excessive lender benefits. In addition,
the influence of the extent of the lending relationship and borrower dependence on the common
lender was found to have a positive influence on the acquirer’s post-acquisition performance.
Thus, the analysis found that all stakeholders in the M&A responded to their own future benefits
or loss by considering the power of the common lender or borrower after the acquisition. Thus,
these can be interpreted as an M&A principle for stakeholder management.
92
Last, the findings of this research offer practical management implications for the
lender-borrower relationship. Beyond simply understanding the “static” characteristics of the
relationship and potential benefits, the outcome here suggests a way to manage the relationship
and related stakeholders. For example, when a common lender is identified in the beginning of
the deal process, by understanding the nature of the lender-borrower relationship based on this
study, proactive steps can be taken, such as requesting necessary advisory services from the
common lender before asking other financial institutions, and thereby gaining stronger support
from the lender for the deal. At the same time, based on the findings, the acquirer should control
in advance its dependency on the common lender to avoid unnecessary concerns in the capital
market.
4.5.2 Limitations and directions for future research
The analysis of this study is based on listed firms’ M&A in Japan. Japanese firms have a strong
dependency on long-term bank loans and a long history of maintaining the main banking system
for economic development following the post-war period (Ogawa et al., 2007). Therefore, based
on such national, regional, and cultural characteristics, the findings here could be misleading in
terms of the overall lender-borrower relationships. In future research, these potential problems
could be generalized by introducing more samples from various countries.
In this study, additional business opportunities for lenders, such as investment banking
services, were regarded as among the most attractive future benefits that could arise from a
strong lender-borrower relationship. However, in reality, many M&A participants hire
93
independent M&A advisors such as investment banks and boutique firms, or accounting, tax, and
legal advisors (Kale, Kini, and Ryan, 2003). If the borrowers on both sides of the deals have
already hired those advisors independent of the lender, the expectation of benefits from the
lender decreases. Future study could consider the independent advisor issue when addressing the
lender-borrower relationship in M&As, and this could be theoretically and practically interesting
and meaningful.
94
CHAPTER 5. GENERAL CONCLUSION
This dissertation consists of three separate but inter-related studies with the common
theme of stakeholders’ influence on M&As, using different methodologies and viewpoints within
stakeholder theory and the resource dependence perspective.
5.1 MAJOR FINDINGS
Study One. The first study posed the following research question: why and how does an
acquirer’s acquisition announcement influence the stock market valuation of its partner in a
bilateral alliance? Using a sample of 347 alliances associated with 150 acquisition deals by
Japanese public non-financial firms, I examined the research question using the event study
method. The empirical findings of the study are summarized as follows. First, on average, an
acquirer’s acquisition announcement leads to a negative abnormal return for its alliance partner.
This finding corroborates my prediction that an acquisition conducted by a firm is expected to
reduce the value the alliance partner derives from the alliance. Second, the negative impact of the
acquisition announcement on the abnormal return varies depending on the alliance and
acquisition characteristics. These characteristics determine the degree of unanticipated increase
in an acquirer’s behavioral uncertainty caused by the acquisition and the alliance’s tolerance of
the unanticipated increase. In terms of alliance characteristics, past alliance experience decreases
the negative impact of acquisition announcements, whereas non-horizontal and technological
alliance types increase the negative impact of acquisition announcements. As for acquisition
characteristics, acquisition deal value and industry relatedness between a target and an alliance
95
partner enhance the negative impact on the market valuation of the alliance partner. These
findings suggest that the expected value of strategic alliances can be negatively influenced by
unanticipated post-formation changes, because such changes might increase the transaction
hazard associated with an alliance. Through this mechanism, an acquirer’s acquisition
announcement triggers a negative market valuation of its alliance partners.
Study Two. The second study posed the following question: do stakeholders influence the
likelihood of completing an announced M&A and if so, how? This study analyzed data for
M&As conducted by Japanese publicly listed non-financial companies from 1995 to 2012 in
order to investigate primary stakeholders’ influence on the deal completion probability. The
findings from the empirical test are as follows. First, stakeholders influence the likelihood of
completing announced deals. As existing stakeholder studies have indicated, stakeholders
influence the focal firm’s strategic decisions to defend their current benefits; this is in line with
the findings in the present study, which extends the basis of this theory to include the M&A
context. Second, stakeholders estimate their potential gains or losses when determining their
responses to proposed M&As. Stakeholders prefer to maintain their current power and benefits in
their relationship with a focal firm, even during a large-scale change, such as an M&A, and resist
any potential risk of loss to their current benefits or position. However, once they recognize the
potential benefits of the proposed changes, they become cooperative. The analytical results show
that the target firm’s employees react negatively to the acquisition process when the acquiring
firm’s employees outnumber them, assuring their job stability, and the lenders become supportive
96
if the acquirer has a higher dependency on financial institutions to achieve new business
opportunities.
Study Three. The third study investigated the following question: does a common lender on
both sides of the M&A influence the acquisition performance and if so, how? This research
question was empirically examined based on 18 years of M&A data in Japan. The findings from
the empirical tests are summarized as follows. First, the existence of a common lender on both
sides of the M&A has a negative association with CAR. This result corroborates the prediction
reflecting the capital market’s concerns over the possibility of excessive and biased benefits to
the common lender. The existence of common lenders on both sides of the deal includes the
possibility for lenders to wield larger power in the lender-borrower relationship. For example,
through the common lending position, the lender can have “more than enough” insider
information on both M&A participants, and this information monopoly may enable the lender to
amend a loan agreement to their advantage when renewing the agreement or request for
immoderate interest rates. In addition, the lender’s monitoring authority may result in lender-
oriented financial management decisions such as reducing dividends or investments, which could
result in a negative response from the capital market to the existence of the common lender in the
M&A deal.
Second, higher dependency of the borrowers on a common lender has a positive
influence on the acquirer’s CAR. In this case, the implication is that the capital market
recognizes the acquirer’s benefits in this strong relationship with the common lender. Specifically,
the fact that the lender’s awareness of the potential risk of losing all business post M&A
97
potentially encourages the lender to forgo profits to maintain the relationship. Moreover, the
acquirer may also gain the benefit of expanded service offerings from the lender in terms of
corporate finance, which may enable the acquirer to obtain additional financial resources. Further,
the acquirer could benefit from the lender’s role as agent in the capital market to encourage other
financial institutions and investors to positively view the acquirer’s operating performance and
creditworthiness.
These findings describe the dynamics of stakeholders’ reactions to M&As based on the
lender–borrower relationship. In particular, the study accounted for common lenders’ influence
on M&As. Thus, the analysis found that each stakeholder in the M&A responded to its own
future benefit or loss by considering the power of the common lender or borrower after the
acquisition. Thus, these can be interpreted as M&A principles for stakeholder management.
5.2 THEORETICAL AND PRACTICAL IMPLICATIONS
Study One. The first study provides several theoretical and practical implications. As the first
theoretical implication, I successfully proposed the dynamic view of strategic alliances and its
performance implications by using the shift-parameter framework (Williamson, 1991). Previous
studies of alliances have focused on the pre-formation conditions of alliances and their
performance implications. In contrast, this study shifted its research focus to the impact of the
post-formation conditions. From this viewpoint, I theoretically and empirically revealed the
increase in the behavioral uncertainty caused by unanticipated changes, and how it shifts the
transaction hazard of alliances, thereby influencing their expected performance. The findings of
98
this study illuminate a novel antecedent of expected alliance performance: alliance partners’
acquisitions. Although this study showed only acquisitions as significant changes, it surely
enriches the alliance literature.
Second, I theoretically and empirically indicated that alliance partners’ acquisitions,
which are changes in contracting parties’ preconditions for their transactions, work as a
transaction shift parameter. The main research focus of TCE has been on transaction attributes
and institutional environments as determinants of transaction costs (Chiles and McMackin, 1996;
Williamson, 1991). Pioneering work in TCE sheds light on the roles of contracting parties’
characteristics in the governance mode choice, such as transaction-related capabilities (e.g.,
Hoetker, 2005; Leiblein and Miller, 2003; Mayer and Salomon, 2006). I further extended this
line of research from a dynamic viewpoint: Changes in contracting parties themselves shift
transaction hazards and influence performance consequences. If contracting parties’
preconditions for a transaction change in an unanticipated way, this raises transaction uncertainty.
This rise in transaction uncertainty increases transaction hazards and causes the alliance to incur
additional transaction costs.
Third, my study successfully revealed the negative spillovers of acquisitions to alliance
partners. The study is complementary to the work of Gaur et al. (2013), which empirically
demonstrated the positive impact of an acquirer’s acquisition announcement on the market
valuations of its rivals. In other words, Gaur et al. (2013) examined the impact of a foe’s
acquisition and found the acquisition produces positive spillovers to its competing firms by
signaling the presence of growth opportunities in their industry. In contrast, my study examines
99
the impact of a friend’s acquisition and finds that cooperative relationships can be spoiled by the
negative spillovers of alliance partners’ acquisitions because of unanticipated increase in
behavioral uncertainty. As shown, acquisition spillovers have diverse aspects. By examining
acquisition spillovers in a different context, the study contributes to the literature on acquisitions’
spillover effects.
Practitioners can gain useful insights from the findings of this study. First, a firm
engaging in an alliance has to pay attention to its alliance partner’s actions outside the alliance.
The stock market may react sensitively to acquisition actions by discounting the expected return
from the alliance. If a firm senses that an alliance partner is planning an acquisition, it should
prepare for the negative spillovers arising from the acquisition. Second, a firm needs to design an
alliance such that it can accommodate the disturbances generated by unanticipated events. In my
analysis, non-horizontal alliances and technological alliances may have narrower tolerance zones
for unanticipated uncertainty. Firms would be advised to form alliances that are either non-
horizontal or technological, but not both, to make their alliances somewhat tolerant. Likewise,
choosing reliable partners with previous alliance experience will make alliances more tolerant to
unexpected disturbances provoked by external shocks.
Study Two. The second study has several theoretical and practical implications. In terms of
theory, this study successfully demonstrated the influence of external determinants on the success
of an M&A, which enables an outward perspective in addition to the existing internal focus of
existing research. This study concentrated on and provided empirical support for the role of
stakeholders surrounding focal firms and M&As, previously not regarded as influential factors in
100
management research.
In addition, this study successfully proposed dynamic settings when approaching
stakeholders’ interactions with firms. The management literature addressed stakeholder issues in
a static business environment, and this study induced a dynamic perspective to capture the
extemporary but fundamental motivation of stakeholders’ responses. Moreover, this study
considered stakeholders’ motivations in their reactions from a dyadic viewpoint by addressing
both the acquiring and target firms’ stakeholders and comparisons to measure the influence on
dependent variables.
For practitioners, the results of this study provide meaningful strategic screening criteria
when performing due diligence on a target firm. During the due diligence stage, the acquirer
focuses on corporate valuation, risk assessment, and synergy estimation (Steynberg and
Veldsman, 2011), with the scope now expanding to include integration and operational due
diligence. However, this focus on the financial aspects and economic benefits of the acquisition
and risk calculations rarely consider stakeholders, though they have a considerable influence
after the announcement stage and into the post-acquisition period. Thus, this study demonstrated
that firms need to consider stakeholders as potential obstacles to deal completion and devise
effective plans to utilize them as valuable resources for a successful M&A.
Study Three. The third study provides several theoretical and practical contributions. First, as a
theoretical contribution, the findings expand the existing lender-borrower research horizon to
include M&A events. In particular, by observing the influence of the common lender on both
101
sides of the M&A, the study empirically examined and supported the role of the common lender
as a reinforcing factor in the lending relationship. In addition, although existing lender-borrower
relationship theories focus on the “static” status of the relationship (e.g., Bharath et al., 2007;
Dass and Massa, 2011; Drucker and Puri, 2005), this study sheds light on the “dynamics” of the
changing relationship through the acquirer’s strategic transformation. Thus, this study provides
insights on how the existing lending relationship is utilized based on a firm’s strategic actions.
Second, this research provides insights regarding stakeholder management theory. The
findings describe the dynamics of stakeholders’ reactions to M&As based on the lender-borrower
relationship. In particular, the study was able to account for the common lenders’ influence on an
M&A. The role of the common lender on both sides of the deal has been found to reinforce the
lender-borrower relationship and various lender benefits while there is a negative stock market
reaction to the acquirer due to the concerns around potential excessive lender benefits. In
addition, the influence of the extent of the lending relationship and borrower dependence on the
common lender was found to have a positive influence on the acquirer’s post-acquisition
performance. Thus, the analysis found that all stakeholders in the M&A responded to their own
future benefits or loss by considering the power of the common lender or borrower after the
acquisition. Thus, these can be interpreted as M&A principles for stakeholder management.
Last, the findings of this research offer practical management implications for the
lender-borrower relationship. Beyond simply understanding the “static” characteristics of the
relationship and potential benefits, the outcome here suggests a way to manage the relationship
and related stakeholders. For example, when a common lender is identified in the beginning of
102
the deal process, by understanding the nature of the lender-borrower relationship based on this
study, proactive steps can be taken, such as requesting necessary advisory services from the
common lender before asking other financial institutions, and thereby gaining stronger support
from the lender for the deal. At the same time, based on the findings, the acquirer should control
in advance its dependency on the common lender to avoid unnecessary concerns in the capital
market.
5.3 LIMITATIONS AND DIRECTIONS FOR FUTURE RESEARCH
Study One. Although the first study obtained consistent evidence of the negative impact of
acquisition announcements on the market valuations of acquirers’ alliance partners, it inevitably
includes several limitations that illuminate potential avenues for future research. First, this study
did not reveal the long-term performance consequences of strategic alliances after acquisitions.
Event study is an ideal method for capturing the immediate effects of acquisition announcements
on the expected returns from alliances, but the method is heavily based on the market efficiency
assumption. My results are subject to a caveat: I assume that the stock market recognizes an
acquirer’s alliance partners and is able to compute the expected value from their alliances. If the
stock market is not efficient, the abnormal returns of an alliance partner following an acquisition
announcement would not accurately reflect the effects of the acquisition (Oler, Harrison, and
Allen, 2008). In order to estimate acquisitions’ impact on alliances more accurately, future
research can confirm my findings by focusing on the long-term consequences of alliances, such
as alliance performance and termination.
103
The Japanese context may be a second limitation of this study, because it may lower the
generalizability of my findings. The Japanese societal culture is characterized as collectivism and
long-termism (Hofstede, 2001). Accordingly, since firms in Japan may have stronger intentions
to maintain interfirm cooperation than would those in countries with individualism and short-
termism cultures, the negative impact of an acquisition on the market valuation of an alliance
partner may appear smaller in the Japanese context. To check the generalizability of my findings,
the same hypothesized relationships should be tested in different national contexts.
Study Two. Though the second study provides meaningful results, it has a few limitations that
could be addressed by further research. First, the research model in this study does not
sufficiently account for all independent variables, since knowledge in the field is limited to
finance scholars assessing post-announcement market pressures, such as competing bids and
financial status (Weston, Siu, and Johnson, 2001), which demonstrated a strong influence in my
analyses as well. Future studies could complement this research model by narrowing the research
focus to specific stakeholder issues, including more subspecialized situations or sub-categorized
stakeholder characteristics.
Second, the sample of this study is restricted to listed Japanese non-financial firms. The
deal completion probability of my sample was extremely high (0.96), possibly due to the well-
mannered Japanese business culture (Cartwright and Cooper, 1993), especially the tendency to
observe a commitment. Furtherore, employees’ attitude toward job security, as well as the
relationship with lenders and shareholders, should be considered in conjunction with the
Japanese cultural context. This may decrease the overall generalizability of the findings. An
104
analysis using data from another cultural context would add to this study’s accountability and
generalizability. Additionally, considering the increasing number of cross-border transactions
(Muehlfeld, Sahib, and Witteloostuijn, 2012), a study of stakeholders and M&As in a cross-
border setting would be interesting. Cross-border transactions are more complex, involving
stakeholder relationships, cultural differences, and so on. Several earlier studies have noted the
issue of culture in cross-border transactions and deal completion probability (Muehlfeld et al.,
2012), but have not been able to exhaustively account for the effect of these factors on a
successful acquisition. Thus, future research on cross-border transactions addressing stakeholder
issues with deal completion would be meaningful and contribute to stakeholder, M&A, and
international business research.
Finally, as an extension of this study, it would be interesting to examine the events
following a deal’s closure. This study postulated completion as a successful transaction in the
short term. However, completion does not guarantee a successful integration process or increased
firm performance. There remain some risks after closure, especially due to the remaining
concerns from the surrounding stakeholders. This study explored stakeholders’ immediate and
extemporal responses to an announcement based on their anticipation of upcoming changes.
However, during the integration stage, stakeholders will face a reality that diverges from their
expectations. Thus, the predictors of higher deal completion probability may not be good
predictors of post-acquisition performance. Extending my research horizon to the post-deal stage
would help clarify the dynamics of influential factors affecting the success of an M&A.
105
Study Three. The analysis of the third study is based on listed firms’ M&As in Japan. Japanese
firms have a strong dependency on long-term bank loans, with a long history of maintaining the
main banking system for economic development following the post-war period (Ogawa et al.,
2007). Therefore, based on such national, regional, and cultural characteristics, the findings here
could be misleading in terms of the overall lender-borrower relationships. In future research,
these potential problems could be generalized by introducing more samples from various
countries.
In this study, additional business opportunities for lenders, such as investment banking
services, were regarded as among the most attractive future benefits that could arise from a
strong lender-borrower relationship. However, in reality, many M&A participants hire
independent M&A advisors such as investment banks and boutique firms, or accounting, tax, and
legal advisors (Kale, Kini, and Ryan, 2003). If the borrowers on both sides of the deals have
already hired those advisors independent of the lender, the expectation of benefits from the
lender decreases. Future study could consider the independent advisor issue when addressing the
lender-borrower relationship in M&As, and this could be theoretically and practically interesting
and meaningful.
In summary, these three studies have built on prior theoretical and empirical foundations
to prove and develop M&A and stakeholder research through various standpoints and
methodological lenses. Overall, the analytical results have important theoretical and practical
implications, and support the argument that stakeholders have significant influence on the
process and results of a focal firm’s M&A.
106
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