BUSINESS MANAGEMENT A+ WORK, ON TIME, NO PLAGARIZING

Vol.:(0123456789)

Group Decision and Negotiation (2023) 32:1083–1115 https://doi.org/10.1007/s10726-023-09835-z

1 3

M&A Negotiations: Role of Negotiation Process, Ownership and Advisors on Deal Completion

Deepak Kumar1  · Keya Sengupta2 · Mousumi Bhattacharya2

Accepted: 16 May 2023 / Published online: 13 June 2023 © The Author(s), under exclusive licence to Springer Nature B.V. 2023

Abstract Mergers and acquisition deals are uncertain, with completion likelihood chang- ing throughout the negotiation process. During negotiations, the firms process new information to modify their choices. This study aims to examine the dynamic nature of the M&A negotiation process. The study uses a sample of 983 worldwide unso- licited deals from 1999 to 2019 and classifies M&A deal outcomes using logistic regression, decision tree, and random forest classifiers. Ownership considerations and advisors are essential elements of the negotiation. Ownership sought has the potential to impact the deal’s complexity and exercisable control. Prior ownership may either help gain information or recover due diligence costs. The advisors may assist the firms in the available information’s financial and legal due diligence. Prior research lacks the negotiation period’s dynamism and gives mixed results for the impact of ownership and the role of advisors. We uniquely identify a non-linear inverted U-shaped relationship between the negotiation period and completion like- lihood. The results prove that prior ownership, over the negotiation period, serves the dual objective of assisting deal completion and acting as a substitute for the ter- mination fee. The acquirer and target advisors help with the completion of the deal. The varying effects for ownership and advisors over the negotiation process help explain the conflicting results in previous studies. The evolving negotiating circum- stances play an important role in affecting the outcome. Our work shows the impor- tance of temporal characteristics and the dynamic nature of decision-making during the M&A negotiation process and encourages further studies exploring processual theories.

Keywords Toehold · Duration · Financial advisors · Legal advisors · Completion · Termination · Hostile · Mergers · Acquisitions · Takeover

Extended author information available on the last page of the article

1084 D. Kumar et al.

1 3

1 Introduction

In the present globalized world, firms face intense competition. Mergers and acquisitions (M&As) help the strategy to compete, grow, enter new geography and remain sustainable (Hossain 2021). M&A transactions form a significant part of foreign direct investment flows in developed economies (UNCTAD 2021), and their proportion has increased in the emerging world over the last two decades (Brooks and Jongwanich 2011). The heightened M&A activity worldwide drew attention to the overlooked aspects of M&A abandonments (Kumar and Sengupta 2020). The abandonment rates vary with industry and context, reaching values higher than 1 in 3 announced deals getting dropped due to various complexities (Doan et al. 2018; Gao et al. 2022).

M&A deals are subject to multiple complexities during the negotiations, aris- ing from global, national, industrial, firm, and deal-level complexity. Communi- cation during negotiations, the support structure and planning play an essential role in the deal (Calcagno et  al. 2021). Most M&A negotiations typically last three to four months (Branch and Yang 2003; Dong et al. 2019; Li et al. 2019). During the negotiation process, the firms argue about the valuation, terms of the agreement, and future directions (Welch et al. 2020). The potential sources of dis- agreement during negotiations include divergences in purpose, future direction, and performance expectations (Jemison and Sitkin 1986). During post-announce- ment negotiation, the firms renegotiate the initial proposal in light of newly dis- covered information (Hotchkiss et al. 2005). The new information includes con- fidential secrets, future plans and expectations after the deal (Calcagno et  al. 2021). The information revealed may change the outlook and lead to roadblocks in negotiation. The passage of time after the announcement carries information about a deal’s negotiation and outcome (Giglio and Shue 2014). The negotiation process closely affects the deal terms.

Ownership considerations essentially influence the negotiation process. Pre- vious research has found that both prior and post-deal ownership are important when considering deal outcomes (Kumar and Sengupta 2020). The shareholders enjoy power and influence through ownership (Schaik 2008). In M&A literature, small prior ownership of the acquirer in the target firm is referred to as having a "toehold." There is mixed literature on the impact of a toehold on pre-deal nego- tiation (Bessler et al. 2015; Ten Brug and Sahib 2018). The advisors are a vital part of the pre-deal negotiation process. Advisors are usually intermediary firms that provide support services, analyze the profitability of deals, and assist the companies during negotiation (Hunter & Jagtiani 2003; Loyeung 2019). Based on their functions, the advisors are of two types, financial and legal. These advisors indulge in the M&A negotiation process affecting the outcome.

Previous studies analyze the negotiation period of completed deals (Dikova et  al. 2010). Deal complexity increases deal duration. Luypaert and De Maese- neire (2015) report increased complexity associated with longer deal duration. Hukkanen and Keloharju (2019) find that deals with precise initial offers com- plete faster. Muehlfeld et al. (2012) moot whether a higher probability of closing

1085

1 3

M&A Negotiations: Role of Negotiation Process, Ownership…

a deal requires sacrifices in terms of longer duration. Post-merger integration studies have shifted their focus to more processual theories over time, but the pre- deal decision-making studies lag behind (Welch et al. 2020). To the best of our knowledge, no study explores the role of the negotiation period affecting the deal outcome. The pressures and commitment vary with time, affecting the final deci- sion (Younkin 2016). Our work extends the knowledge in the field by focusing on the negotiation process and its dynamic nature. We argue that the firms process new information with the advisors’ help, and the response is contingent on the deal terms. The study analyzes the aspects under the direct control and up in par- ley between the negotiating parties and predicts the deal’s completion likelihood.

We address the following research questions (RQs) in this study. M&A negotia- tion is an ongoing process till the outcome, with each passing day carrying infor- mation, possibly impacting the outcome. We addressed this through RQ1: Does the negotiation period affect the likelihood of deal completion? RQ2: How does owner- ship (ownership sought and prior ownership) affect the likelihood of deal completion over the negotiation period? Extant literature also highlighted the role of advisors during negotiations. So, we formulated the following RQ, RQ3: Does hiring advi- sor firms affect the likelihood of deal completion over the negotiation period? We reduce the complexities due to private negotiation by limiting the context to unsolic- ited deals where pre-announcement contact between acquirer and target is minimal.

The rest of the paper is as follows. Section 2 provides a literature review of the M&A process perspective and unsolicited deals. Section  3 gives the hypothesis development. Section 4 presents the data and methodology. Section 5 outlines the empirical results, Sect. 6 offers discussions and implications, and Sect. 7 reflects on the inferences from the analysis.

2 Literature Review

2.1 M&A Process Perspective

The M&A process has three critical events, initiation, announcement, and outcome (Boone and Mulherin 2007; Ermolaeva 2019). The initiation to the announcement phase is confidential, and the negotiation details during this phase do not get public (Aktas and Boone 2022). The date of initiation is also seldom known. The public takeover phase starts after the announcement, and the data for this period is more readily available. The major negotiations between the firms start after the deal announcement, and some talks happen during the private takeover process. The pro- cess perspective states that the acquisition process impacts activities and outcomes (Jemison and Sitkin 1986). The processual theory has been extensively applied to the integration phase research (Welch et al. 2020). The process perspective argues that the M&A process fosters M&A performance by affecting the speed of integra- tion (Bauer and Matzler 2014). The M&A negotiation process has uncertainty, and firms ascertain the synergies during the process (Calcagno et  al. 2021). The pro- cess is dynamic, and recent reviews such as Kumar and Sengupta (2020) and Welch et al. (2020) recommend the extension of the process perspective to analyze the deal

1086 D. Kumar et al.

1 3

outcome. The M&A process includes the private takeover phase, and negotiations in this period may impact the outcome. Thus, overlooking the phase before public announcement may lead to erroneous results when focusing on the deal’s temporal attributes. The study evades the problem caused due to the unavailability of private takeover process data by focusing on unsolicited deals.

2.2 Unsolicited Mergers and Acquisitions

The unsolicited deals are a subsection of all M&A deals, in which the target firm remains unaware of the offer till announcement. Hostile M&As are a subset of unso- licited deals where the target firm initially opposes the acquirer firm’s offer. The unsolicited deals exhibit the unique feature of not having a private takeover process. The unsolicited/hostile bids do not have private negotiations, and pre-offer commu- nication is absent among the parties (Boone and Mulherin 2007; Zhou et al. 2016). The unsolicited/ hostile bids do not have the prior consent of the target firm. The acquirer announces the deal, and then the negotiations between the parties begin. Hostile deals are related to high complexity, lower probability of success, higher premiums, and longer duration (Luypaert and Maeseneire 2015; Officer 2003). Most recent studies on M&As show that unsolicited bids are more likely to get abandoned (Bessler et al. 2015; Krishnan et al. 2012; Schwert 2000). The acquirer and target firm managers publicize their views openly to influence the shareholders, leading to extensive information about unsolicited/hostile negotiations in the public domain. (Schwert 2000).

3 Hypotheses Development

3.1 Duration of Negotiation Period

The negotiation period is the number of days from signing a definitive merger agree- ment to the deal outcome (completion or abandonment). At the time of initiation, there is a lot of information asymmetry. Once the deal gets announced, both firms share more information (Calcagno et al. 2021). Heightened tensions characterize the negotiation period due to ambiguous information (Jemison and Sitkin 1986). Earn- ings forecasts by the acquirer firm reduce the negotiation period (Amel-Zadeh and Meeks 2019). Socially responsible firms have faster M&A negotiations (Deng et al. 2013). State owned enterprises (SOEs) undertaking M&As have a larger negotiation period (Li et  al. 2017). Overall, more complex deals take more time to complete. Earlier studies focused on the duration of negotiation of completed M&As because of the unavailability of the date of abandonment of abandoned deals (Dikova et al. 2010). However, Aguilera and Denker (2012) use deal duration to account for tem- poral characteristics in their analysis. Merging firms benefit from a better-negotiated deal with a longer duration (Song et al. 2013a). The various studies acknowledge the

1087

1 3

M&A Negotiations: Role of Negotiation Process, Ownership…

importance of the negotiation period in the M&A process but do not explore its role in the final outcome (completion or abandonment) of the M&A negotiation process.

The deal duration proxies complexities in the negotiation and longer duration depict that parties undertake multiple complex tasks (Luypaert and De Maeseneire 2015; Reddy and Fabian 2020). Target management also requires time to build con- sensus or deploy defensive measures. Thus, after the announcement, the acquirer and target management use their resources to achieve their objectives. An initial passage of time may indicate acquirers and targets discussing the prospects of the deal and increased commitment. The initial information asymmetry and ambiguity should decrease and reduce with time. The probability of completion should increase with the increasing negotiation period. However, a deal negotiation extended to large lengths portrays a deadlock during negotiation. Further, deal‐specific synergy dis- sipates when market conditions change (Calcagno et  al. 2021). Thus, we propose that the increase in the likelihood of deal completion should have a decreasing rate of growth, leading to the following hypothesis,

H1: There is an inverted-U-shaped relationship between the negotiation period and the completion probability of an unsolicited M&A transaction.

3.2 Ownership

3.2.1 Percentage of Ownership Sought

M&A involves the acquirer buying a portion of the stocks of the target firm. A higher percentage of target shares involved in a deal raises the degree of implica- tions for both the acquirer and target shareholders (Dikova et al. 2010). Higher own- ership of the acquirer in the target firm increases the extent of exercisable control. A larger stake in a company also reduces opportunistic managerial behavior (Zhu et al. 2014). A deal involving larger ownership witnesses more attention and resource deployment from both firms. A change in the management board is evident after an M&A involving a significant transfer of ownership. Thus, a higher requirement of shares/ownership/stakes generates more resistance from the target management (Li et al. 2019). The acquirer firm tries to accelerate the M&A process for deals involv- ing larger stakes to avoid defensive moves by the target (Dikova et al. 2010). The desire to obtain a larger number of target shares suggests the deal’s strategic impor- tance for the acquirer and ensures high-level managerial involvement (Muehlfeld et al. 2007). A deal involving large stakes can trigger CEOs’ egoistic characteristics, affecting the negotiation process (Aktas et al. 2016). A deal with substantial owner- ship change may alter the industry structure, creating monopolies. The competition commissions are responsible for ensuring healthy competition in the country and scrutinizing deals involving large stake transfers more carefully (Lim and Lee 2016, 2017). A deal involving larger stakes becomes complex. Several studies find that a larger percentage of target shares sought negatively affects the completion of M&A deals (Fuad and Gaur 2019; Lim and Lee 2016, 2017). However, certain other stud- ies find no significant relationship between stakes sought and completion likelihood

1088 D. Kumar et al.

1 3

(Abdou and Gupta 2011; Dikova et al. 2010; Kim and Song 2017; Li et al. 2017; Popli et  al. 2016). The negotiation period of an M&A deal experiences informa- tion asymmetry and distrust between the parties (Jemison and Sitkin 1986). Due to the hostile environment, an unsolicited deal has much higher levels of distrust. It becomes much more challenging to convey and convince the deal’s benefits to a larger percentage of shareholders in such a setting. The hostile target board some- times releases negative statements about the deal, making the acquisition of shares much more difficult. The number of shares sought affects the entire M&A negotia- tion process and should harm the deal’s completion likelihood.

H2.1 There is a negative relationship between the target share percentage sought and the completion probability of an unsolicited M&A transaction.

3.2.2 Ownership Prior to Deal (Toehold)

The toehold can serve as a means of reversing the due diligence costs if the deal gets poached by a competitor at a higher valuation (Bessler et al. 2015). Toeholds and termination fee provisions are found to exist alternatively in M&A deals (Bates and Lemmon 2003; Jeon and Ligon 2011; Officer 2003). Toeholds help to manage the closing risk associated with the uncertain negotiation process (Boone and Mulherin 2007). The toehold restricts the target firm’s opportunistic behavior and bargaining power and provides a way out for the acquirer if negotiations are not going the usual way (Hotchkiss et al. 2005). A stake in the target firm may also provide private infor- mation otherwise unavailable in the public domain. Loyeung (2019) finds higher information asymmetry between the firms without an existing stake of the acquirer in the target firm. The absence of previous ownership of the acquirer in the target company suggests a weak bargaining power of the acquirer and presents the need for acquiring a larger number of shares (Loyeung 2019). Toeholds also reduce compet- ing bids and increase deal completion likelihood in contests (Bessler et  al. 2015). Despite the advantages, toeholds are rare and deal with acquirer’s existing owner- ship in the target firm ranges between 5 and 15% (Bessler et al. 2015). Toeholds can intimidate target management and large shareholders, eliciting resistance (Krishnan et al. 2012; Muehlfeld et al. 2012; Ten Brug and Sahib 2018). The termination fee provisions for M&A deals are drafted during the private negotiation period between the initiation and public announcement. Unsolicited deals do not have a private take- over negotiation period, and thus the termination fee provisions are absent (Bates and Lemmon 2003). Further, having a toehold benefits the acquirer by acquiring fewer shares at a premium and completing a deal at an overall lower price (Bessler and Schneck 2015). The toehold can be sold at a higher premium if the rival bid- der wins (Betton et al. 2009). The absence of a toehold increases competing bids’ probability, especially for hostile bids (Krishnan and Masulis 2013), increasing complexity in negotiations and decreasing completion likelihood. Toeholds are rare in friendly bids but common in hostile bids having a frequency of about 50% (Bet- ton et al. 2009). There are two possible reasons for having a toehold, to help during negotiations or create a contingency for a potential abandoned deal.

1089

1 3

M&A Negotiations: Role of Negotiation Process, Ownership…

Pre-bid ownership of the acquirer in the target company influences the takeover outcome (Henry 2004). The effect of a toehold on completion likelihood is mixed with studies finding positive (Bessler et al. 2015) and non-significant results (Ngo and Susnjara 2016; Officer 2003). Holl and Kyriaziz (1996) find that a larger toehold helps complete both friendly and hostile bids. A toehold may also derail the M&A process and increase the probability of abandonment (Ten Brug and Sahib, 2018) for energy firms. The stakes acquired as toehold is usually larger for unsolicited bids (Officer 2003). Negotiating an unsolicited bid is complex, and toehold may reduce information asymmetry and make it easier to convince other shareholders. The study hypothesizes that an acquirer’s prior ownership/toehold increases the probability of deal completion.

H2.2 There is a positive relationship between prior ownership and the completion probability of an unsolicited M&A transaction.

3.3 Acquirer and Target Advisors

Communication is a critical element of the negotiation process (Ahammad et  al. 2016). Malik and Yazar (2016) find that cultural gap can adversely impact negotia- tion outcome. Intermediaries are vital to bridge the gap between two corporations engaged in negotiations of M&A. The acquirers occasionally indulge in M&As, whereas the advisors have experience guiding in multiple deals and thus have skills and expertise in deal-making. Investment banks usually perform the function of financial advisors (Aktas and Boone 2022). Sometimes, firms hire specialist bou- tique financial advisor firms (Loyeung 2019). The advisory firms get repeat business by successfully meeting client goals (Krishnan and Masulis 2013). The advisors pre- pare the formal deal structure, conduct due diligence, and value the target (Reddy et al. 2016; Song et al. 2013b). Financial advisors reduce the probability of a bad deal, evaluate synergies, and speed up the transaction process (Chuang 2017). Advi- sors help the bidders make media statements (Restrepo and Subramanian 2017). The statements made in the media can signal the intent and willingness of the acquirer. In the case of hostile bids, media communication is essential to convince the share- holders. The choice of advisors depends on the transaction, contracting, and infor- mation asymmetry costs (Loyeung 2019). A higher probability of deal completion is associated with more popular financial advisors (Hunter and Jagtiani 2003; Raghav- endra, 2000). However, Reddy et al. (2016) find that advisors do not influence the deal’s completion likelihood. There are mixed results for financial advisors and a small number of studies analyzing the role of legal advisors in M&A deals. The passive execution hypothesis asserts a minimal role of advisors, whereas the skilled advice hypothesis states a significant influence on the M&A process (Aktas and Boone 2022).

Advisors are specialist firms assisting the target and acquirer during the deal. The advisors assist the clients in valuation, assessment of counterbidders, defense tactics, and being updated on the latest laws and policies. Legal distances impact investment decisions (Malik et al. 2022). Legal advisors are considered essential

1090 D. Kumar et al.

1 3

for analyzing investment (Reddy et al. 2016) and competition laws. Law firms are involved in intermediation, negotiation, certification, and drafting contracts and agreements (Krishnan and Laux 2008). An acquirer legal advisor can negotiate lockups with the target, increasing the probability of success (Bates and Lem- mon 2003). Managers sometimes suggest that lawyers impede the deal (Krishnan and Laux 2008). Several studies include the number of advisors in their analy- sis of calculation completion likelihood (Becher et al. 2015; Hunter and Jagtiani 2003). Hunter and Jagtiani (2003) and Ngo and Susnjara (2016) find a positive relationship between completion likelihood with an increasing number of advi- sors employed by the acquirer and target. Krishnan and Masulis (2013) find that top law firms hired by acquirers increase the completion likelihood, whereas the reverse is valid for the target. The importance of an advisory team increases with increased complexity, as in hostile bids. The literature shows no contradiction in the objectives of the financial and legal advisors hired by the firms. The aims of the advisors (financial and legal) should match those of the hiring firm. The acquirer and target usually strive to complete the deal (Hunter and Jagtiani 2003). However, in the case of unsolicited deals, target management is not friendly with the acquirers and may have the objective of avoiding the deal. Thus, the target advisors (financial and legal) hired by the unfriendly management may be more aligned to get the deal abandoned.

H3.1 There is a positive relationship between the hiring of acquirer advisors (Finan- cial and Legal) and the completion probability of an unsolicited M&A transaction.

H3.2 There is a negative relationship between the hiring of target advisors (Finan- cial and Legal) and the completion probability of an unsolicited M&A transaction.

The deal attributes are interrelated and depend on each other. However, litera- ture on the pre-completion phase has tried to create simplistic models to avoid the interaction of various factors during the negotiations (Welch et al. 2020). Our research objectives based on RQ2 and RQ3 are analyzed throughout the nego- tiation period. Thus, interaction terms of the negotiation period with the advisor, ownership percentage sought, and prior ownership variables are included in the model to analyze the impact of the variables over changing time.

The model controls for several other important variables for the negotiation process. A high premium increases target announcement returns and the likeli- hood of completion (Wong and O’Sullivan 2001). The premium affects the nego- tiation during the M&A process. Larger deals are complex and more prone to abandonment (Branch et  al. 2008; Caiazza and Pozzolo 2014). The deals with higher total value are larger and more complex and necessarily affect the nego- tiation process. In some cases, the acquirer firm tries to fully acquire the target firm and own 100% of its shares. The 100% ownership cases experience varied outlooks of target shareholders compared to when other shareholders exist along with the acquirer. The company takeover events have been separated through the inclusion of a dummy. The study controls for the deal being a company takeover

1091

1 3

M&A Negotiations: Role of Negotiation Process, Ownership…

where the final ownership rises to 100%. Macroeconomic factors such as inter- est, inflation, GDP and exchange rate impact country-level M&A abandonment rates (Kumar et al. 2023). This effect may vary with time. Country and year dum- mies are used to take care of such effects. The geographic distance between the acquirer and the target headquarters may affect the information flow (Chakrabarti and Mitchell 2016). Deals within the same industry are structurally similar (Mue- hlfeld et al. 2012), and the same industry M&A increases economies of scale and scope (Doan et  al. 2018). The knowledge and information affecting the M&A process are better utilized in the case of a related industry M&A.

4 Data and Methodology

4.1 Sample and Data

The late 1990s and early 2000s saw increased participation of emerging economies in M&A activity (Brooks and Jongwanich 2011). The period witnessed liberaliza- tion in many countries kick-starting the M&A activity. While analyzing the data since 1990, it is found that there were very few unsolicited M&As in the earlier half of the decade. The unsolicited M&A activity increased closer to the year 2000. The sample period thus considered is from 1999 to 2019. The end of the year 2019 pro- vides sufficient time for a deal to get to an outcome avoiding censoring issues.

The data1 for the firm and deal-level characteristics are collected from the Bloomberg Terminal database, which records all global mergers and acquisitions. The Bloomberg database on M&A is similar to that of the SDC Platinum database used in most M&A studies. The sample selection criteria include the following: (1) Dates: Custom (January 1, 1999, December 31, 2019) Apply to—Announced Date (The announce date is the date on which the deal is publicly announced); (2) Nature of Bid: Any of these—Hostile, Unsolicited; and (3) Deal status: Completed, Termi- nated, Withdrawn.

The search gave a total of 1451 deals following the three criteria mentioned above. Deals with a negotiation period of fewer than 24 h and deals with missing values of other variables under consideration are dropped. This study is based on a sample of 983 deals. “Appendix” shows sample names of acquirer/target—com- panies, industries, countries, advisors and announcement and outcome dates. The study uses standardized-logged values of numeric variables. The dummy and integer variables are in their original forms. There is no obligation for the target board to accept or reject the takeover bid until it releases its target statement (Gajic and Scarf 2020). The deals completed on the announcement date are excluded from the analy- sis. Deals cannot be announced and completed on the same day unless negotiated

1 Other data sources: The distances between the acquirer and the target country are obtained from the CEPII database (http:// www. cepii. fr/ cepii/ en/ bdd_ modele/ bdd. asp). The sector classification has been done using the Global Industry Classification Standard (GICS) index(https:// www. msci. com/ gics).

1092 D. Kumar et al.

1 3

before being announced, and therefore such cases do not represent an accurate nego- tiation period. (Ertugrul and Krishnan, 2014).

The analysis performed on unsolicited deals will help reveal the intricacies of the M&A process and its impact on deal abandonments and provide avenues of comparison with friendly deals. Figure 1 shows the number and volume of unso- licited mergers over the period 1999–2019. The number of deals starts increasing in the early 2000s, reaching a peak in the first quarter of 2006. The deals decline during the financial crisis and the numbers after that show lower fluctuations. However, the volume shows higher spikes in 2014 and 2017, indicating that indi- vidual deals are getting bigger in subsequent years.

4.2 Analytical Model

Table  1 lists all the variables with their description. The study has a binary response variable status-completed/abandoned. Logit and probit are general- ized linear models used to estimate a functional relationship between the binary response variable and predictors. Both logit and probit produce similar results, with the difference lying in the data-generating process’s assumption. The choice between the logit and probit models is subjective, and following most M&A com- pletion studies, a logit model is used to find the probability of completion of hos- tile M&As.

Figure 2 shows the model with variables and hypotheses under consideration. The dependent variable is Status, which takes the value of one if the deal gets completed and zero if not completed. Termination fee, common advisors, and cash are excluded as variables from the model as they are either very rare or very common in hostile bids. Most of the firms in the sample participated in only one deal over the period under consideration. We follow, Lim and Lee (2016) in mak- ing the analysis using pooled models. The study controls for the year effects by including year dummies and specific country effects by including acquirer and

(1)Prob (Status = 1) = f (

∑

�i ∗ Explanatoryi + ∑

�j ∗ Controlj

)

0

5E10

1E11

1.5E11

2E11

2.5E11

3E11

0

5

10

15

20

25

30

35

40

45

19 99

Q 1

19 99

Q 2

19 99

Q 3

19 99

Q 4

20 00

Q 1

20 00

Q 2

20 00

Q 3

20 00

Q 4

20 01

Q 1

20 01

Q 2

20 01

Q 3

20 01

Q 4

20 02

Q 1

20 02

Q 2

20 02

Q 3

20 02

Q 4

20 03

Q 1

20 03

Q 2

20 03

Q 3

20 03

Q 4

20 04

Q 1

20 04

Q 2

20 04

Q 3

20 04

Q 4

20 05

Q 1

20 05

Q 2

20 05

Q 3

20 05

Q 4

20 06

Q 1

20 06

Q 2

20 06

Q 3

20 06

Q 4

20 07

Q 1

20 07

Q 2

20 07

Q 3

20 07

Q 4

20 08

Q 1

20 08

Q 2

20 08

Q 3

20 08

Q 4

20 09

Q 1

20 09

Q 2

20 09

Q 3

20 09

Q 4

20 10

Q 1

20 10

Q 2

20 10

Q 3

20 10

Q 4

20 11

Q 1

20 11

Q 2

20 11

Q 3

20 11

Q 4

20 12

Q 1

20 12

Q 2

20 12

Q 3

20 12

Q 4

20 13

Q 1

20 13

Q 2

20 13

Q 3

20 13

Q 4

20 14

Q 1

20 14

Q 2

20 14

Q 3

20 14

Q 4

20 15

Q 1

20 15

Q 2

20 15

Q 3

20 15

Q 4

20 16

Q 1

20 16

Q 2

20 16

Q 3

20 16

Q 4

20 17

Q 1

20 17

Q 2

20 17

Q 3

20 17

Q 4

20 18

Q 1

20 18

Q 2

20 18

Q 3

20 18

Q 4

20 19

Q 1

20 19

Q 2

20 19

Q 3

20 19

Q 4

Volume Announced Terminated

De al

C ou

nt

Vo lu

m e(

M ill

io n

U S$

)

Time

Fig. 1 Number and volume of unsolicited mergers for the period 1999–2019

1093

1 3

M&A Negotiations: Role of Negotiation Process, Ownership…

Ta bl

e 1

V ar

ia bl

e de

fin iti

on

Va ria

bl e

N am

e D

es cr

ip tio

n So

ur ce

D ep

en de

nt St

at us

A d

ic ho

to m

ou s v

ar ia

bl e

eq ua

l t o

1 fo

r C om

pl et

ed d

ea ls

an

d 0

ot he

rw is

e Zh

ou e

t a l.

(2 01

6) , F

ua d

an d

G au

r ( 20

19 ),

Er m

ol ae

va

(2 01

9) In

de pe

nd -

en t/

ex pl

an a-

to ry

O w

ne rs

hi p

pe rc

en ta

ge so

ug ht

Th e

am ou

nt o

f t he

ta rg

et b

ei ng

so ug

ht in

th e

cu rr

en t d

ea l.

(B lo

om be

rg c

om pi

le s d

et ai

ls o

n al

l g lo

ba l a

cq ui

si tio

ns in

w

hi ch

a t l

ea st

5% o

r m or

e of

a ta

rg et

is b

ei ng

p ur

ch as

ed )

Li e

t a l.

(2 01

7) , P

op li

et  a

l. (2

01 6)

Pr io

r o w

ne rs

hi p

It is

a d

um m

y va

ria bl

e th

at in

di ca

te s a

su bs

eq ue

nt p

ur -

ch as

e of

a st

ak e

in a

c om

pa ny

e qu

al to

1 fo

r e xi

ste nc

e of

pr

io r o

w ne

rs hi

p an

d 0

ot he

rw is

e

B es

sl er

e t a

l. (2

01 5)

, T en

B ru

g an

d Sa

hi b

(2 01

8)

A cq

ui re

r’s fi

na nc

ia l a

dv is

or s

N o.

fi na

nc ia

l a dv

is or

fi rm

s h ire

d by

A cq

ui re

r C

hu an

g (2

01 7)

, K ris

hn an

a nd

M as

ul is

(2 01

3) A

cq ui

re r l

eg al

a dv

is or

s N

o. le

ga l a

dv is

or fi

rm s h

ire d

by A

cq ui

re r

K ris

hn an

a nd

L au

x (2

00 8)

, R ed

dy e

t a l.

(2 01

6) Ta

rg et

fi na

nc ia

l a dv

is or

s N

o. fi

na nc

ia l a

dv is

or fi

rm s h

ire d

by T

ar ge

t C

hu an

g (2

01 7)

, K ris

hn an

a nd

M as

ul is

(2 01

3) Ta

rg et

le ga

l a dv

is or

s N

o. le

ga l a

dv is

or fi

rm s h

ire d

by T

ar ge

t K

ris hn

an a

nd L

au x

(2 00

8) , R

ed dy

e t a

l. (2

01 6)

N eg

ot ia

tio n

pe rio

d (N

eg _p

er io

d) D

ur at

io n

of n

eg ot

ia tio

n is

th e

nu m

be r o

f d ay

s t he

n eg

ot ia

- tio

n en

su ed

a nd

is e

qu al

to th

e nu

m be

r o f d

ay s b

et w

ee n

th e

de al

a nn

ou nc

em en

t d at

e an

d th

e de

al e

ffe ct

iv e

da te

(w

he n

a de

al su

cc ee

ds ) o

r t he

w ith

dr aw

al d

at e

(w he

n a

de al

fa ils

)

Lu yp

ae rt

an d

D e

M ae

se ne

ire (2

01 5)

, R ed

dy a

nd F

ab ia

n (2

02 0)

, C al

ca gn

o et

 a l.

(2 02

1)

1094 D. Kumar et al.

1 3

Ta bl

e 1

(c on

tin ue

d)

Va ria

bl e

N am

e D

es cr

ip tio

n So

ur ce

C on

tro ls

A nn

ou nc

ed p

re m

iu m

Th e

pr em

iu m

in di

ca te

d w

he n

th e

de al

w as

o ffi

ci al

ly

an no

un ce

d W

on g

an d

O ’S

ul liv

an (2

00 1)

A nn

ou nc

ed to

ta l v

al ue

Th e

to ta

l d ol

la r v

al ue

o f t

he e

nt ire

o ffe

r, w

hi ch

in cl

ud es

al

l d is

cl os

ed p

ay m

en t t

yp es

(c as

h, st

oc k,

n et

-d eb

t, or

a

co m

bi na

tio n

th er

eo f)

B ra

nc h

et  a

l. (2

00 8)

, C ai

az za

a nd

P oz

zo lo

(2 01

4)

C om

pa ny

ta ke

ov er

A d

um m

y va

ria bl

e in

di ca

tin g

th at

th e

ta rg

et is

b ei

ng fu

lly

ac qu

ire d,

e ith

er 1

00 %

fu ll

pu rc

ha se

o f t

he c

om pa

ny o

r th

e re

m ai

nd er

o f t

he c

om pa

ny , b

rin gs

a cq

ui re

r o w

ne rs

hi p

to 1

00 %

o f t

he ta

rg et

Li e

t a l.

(2 01

7) , P

op li

et  a

l. (2

01 6)

Ta rg

et to

ta l a

ss et

s It

in di

ca te

s a ny

th in

g ow

ne d

by a

b us

in es

s t ha

t h as

c om

- m

er ci

al o

r e xc

ha ng

e va

lu e.

A ss

et s m

ay c

on si

st of

sp ec

ifi c

pr op

er ty

o r c

la im

s a ga

in st

ot he

rs . T

hi s i

s t he

su m

o f a

ll cu

rr en

t a ss

et s,

no n-

cu rr

en t a

ss et

s, an

d ot

he r a

ss et

s

B ra

nc h

et  a

l. (2

00 8)

, C ai

az za

a nd

P oz

zo lo

(2 01

4)

D ist

an ce

Th e

gr ea

t c irc

le d

ist an

ce b

et w

ee n

th e

ac qu

ire r a

nd ta

rg et

co

un try

C ha

kr ab

ar ti

an d

M itc

he ll

(2 01

6)

C om

m on

G IC

S It

is a

d um

m y

va ria

bl e

w ith

a v

al ue

e qu

al to

1 w

he n

ac qu

ire r a

nd ta

rg et

b el

on g

to th

e sa

m e

se ct

or , o

th er

w is

e 0

M ue

hl fe

ld e

t a l.

(2 01

2) , D

oa n

et  a

l. (2

01 8)

1095

1 3

M&A Negotiations: Role of Negotiation Process, Ownership…

target country dummies for countries. The interpretation of the interaction effect in a non-linear model is different compared to linear models. It is not equal to the marginal effect, can have different values, even with a reversed sign (Karaca- Mandic et al. 2012). Further, a squared term of the negotiation period makes the model more complicated. Thus, the relationship between the interaction term is not hypothesized beforehand, and behavior is analyzed post-regression.

5 Results

5.1 Logistics Regression Results

Table 2 provides the summary statistics and correlation of the variables used in the analysis. The non-integer numeric variables have been standardized. The correla- tion coefficients for the variables are lower than 0.7, indicating the lack of effects of multicollinearity.

Table 3 provides the logit regression results, with each subsequent model being an addition to the previous model. We first include the controls (Model 1), followed by the inclusion of ownership (Model 2) and advisor variables (Model 3) succes- sively in the regression model. The negotiation period variable (Model 4) containing the squared term is then added, followed by the interaction terms (Model 5 and 6). The models are compared using the Bayesian information criterion (BIC), and the main effects are interpreted from model 4, the best model, without including the interaction terms (Aiken et al. 1991; Whisman and McClelland 2005). The interac- tion effects in models 5 and 6 are analyzed through average marginal effects graphs. The Receiver Operating Characteristics (ROC) curve measures the performance of classification. The value of ROC represents the area under the ROC curve, with a value close to 1 (100%) representing a good measure of separability between the

Fig. 2 Ownership, advisors, negotiation duration and M&A completion

1096 D. Kumar et al.

1 3

Ta bl

e 2

S um

m ar

y st

at ist

ic s a

nd c

or re

la tio

n

Va ria

bl e

M ea

n St

d. D

ev (2

) (3

) (4

) (5

) (6

) (7

) (8

) (9

) (1

0) (1

1) (1

2) (1

3) (1

4)

(1 )

St at

us 0.

40 2

0. 49

1 (2

) N

eg ot

ia tio

n Pe

rio d

4. 41

1 0.

97 4

1. 00

0

(3 )

A cq

ui re

r Fi

na nc

ia l

A dv

is or

0. 96

9 1.

12 3

0. 14

8* **

1. 00

0

(4 )

Ta rg

et

Fi na

nc ia

l A

dv is

or

0. 93

6 1.

02 3

0. 15

5* **

0. 43

6* **

1. 00

0

(5 )

A cq

ui re

r Le

ga l

A dv

is or

0. 85

8 1.

07 6

0. 24

8* **

0. 45

3* **

0. 39

9* **

1. 00

0

(6 )

Ta rg

et

Le ga

l A

dv is

or

0. 78

2 0.

94 6

0. 22

3* **

0. 31

6* **

0. 43

8* **

0. 49

2* **

1. 00

0

(7 )

Pr io

r O w

n- er

sh ip

0. 35

7 0.

47 9

0. 06

7* *

−  0

.0 91

** *

−  0

.0 41

−  0

.0 24

−  0

.0 35

1. 00

0

(8 )

O w

ne rs

hi p

Pe rc

en t-

ag e

So ug

ht

4. 22

7 0.

79 4

0. 03

1 0.

14 1*

** 0.

13 7*

** 0.

09 1*

** 0.

10 6*

** −

 0 .3

67 **

* 1.

00 0

(9 )

A nn

ou nc

ed

Pr em

iu m

4. 85

9 0.

29 1

0. 10

7* **

−  0

.0 09

−  0

.0 04

0. 00

9 0.

02 5

−  0

.0 87

** *

0. 13

1* **

1. 00

0

(1 0)

A nn

ou nc

ed

To ta

l Va

lu e

5. 52

9 2.

41 2

0. 11

2* **

0. 52

1* **

0. 56

2* **

0. 41

4* **

0. 42

6* **

−  0

.1 36

** *

0. 43

3* **

0. 03

1 1.

00 0

(1 1)

Ta rg

et

To ta

l A

ss et

s

6. 09

5 2.

61 7

0. 08

4* **

0. 40

1* **

0. 40

7* **

0. 28

8* **

0. 27

9* **

0. 02

2 0.

03 8

−  0

.1 04

** *

0. 69

4* **

1. 00

0

1097

1 3

M&A Negotiations: Role of Negotiation Process, Ownership…

* p <

0. 1;

* *p

< 0.

05 ; *

** p <

0. 01

Ta bl

e 2

(c on

tin ue

d)

Va ria

bl e

M ea

n St

d. D

ev (2

) (3

) (4

) (5

) (6

) (7

) (8

) (9

) (1

0) (1

1) (1

2) (1

3) (1

4)

(1 2)

C om

pa ny

Ta

ke ov

er 0.

85 0

0. 35

7 0.

06 8*

* 0.

06 5*

* 0.

06 6*

* 0.

07 4*

* 0.

10 0*

** −

 0 .1

46 **

* 0.

49 6*

** 0.

04 6

0. 22

0* **

−  0

.0 65

** 1.

00 0

(1 3)

D ist

an ce

7. 03

8 1.

30 7

0. 05

5* −

 0 .0

54 *

0. 00

8 0.

13 4*

** 0.

10 8*

** 0.

02 7

0. 00

4 0.

10 9*

** 0.

00 8

−  0

.0 39

0. 03

7 1.

00 0

(1 4)

C om

m on

G

IC S

0. 55

7 0.

49 7

0. 00

6 0.

21 3*

** 0.

16 9*

** 0.

13 3*

** 0.

13 5*

** −

 0 .1

87 **

* 0.

10 4*

** 0.

08 7*

** 0.

15 6*

** 0.

06 4*

* 0.

12 0*

** 0.

03 9

1. 00

0

1098 D. Kumar et al.

1 3

Table 3 Results of logistic regression analysis predicting M&A completion

Model1 Model 2 Model3 Model4 Model5 Model6

Independents Neg_period ^2 − 0.705*** − 0.968*** − 1.065***

(0.16) (0.17) (0.19) Neg_period 1.862*** 2.331*** 2.408***

(0.21) (0.27) (0.32) Acquirer financial advisor 0.31*** 0.311*** 0.284*** 0.333**

(0.1) (0.11) (0.11) (0.13) Target financial advisor 0.175 0.115 0.09 0.439***

(0.12) (0.12) (0.13) (0.17) Acquirer legal advisor 0.565*** 0.543*** 0.591*** 0.322**

(0.12) (0.13) (0.13) (0.14) Target legal advisor 0.446*** 0.34*** 0.342*** 0.349**

(0.1) (0.11) (0.11) (0.16) Prior ownership 0.242 0.431** 0.185 0.542** 0.484**

(0.19) (0.2) (0.22) (0.24) (0.24) Ownership percent sought − 1.088*** − 1.027*** − 1.377*** − 1.303*** − 1.334***

(0.17) (0.18) (0.21) (0.2) (0.21) Interactions Acquirer legal advisor ×

Neg_period 0.09

(0.16) Target legal advisor ×

Neg_period 0.493**

(0.22) Target financial advisor ×

Neg_period − 0.585***

(0.19) Acquirer financial advisor ×

Neg_Period − 0.001

(0.14) Prior ownership × Neg_period − 0.707** − 0.691**

(0.3) (0.31) Ownership percent sought ×

Neg_period 0.566*** 0.583***

(0.16) (0.16) Controls Announced Premium 0.169** 0.252*** 0.252*** 0.105 0.084 0.081

(0.08) (0.09) (0.09) (0.1) (0.1) (0.1) Announced total val − 0.453*** 0.105 − 0.626*** − 0.476** − 0.455** − 0.492**

(0.14) (0.16) (0.19) (0.22) (0.22) (0.23) Company takeover − 1.288*** − 0.379 − 0.296 − 0.781** − 0.698** − 0.718**

(0.24) (0.29) (0.31) (0.35) (0.35) (0.36) Target total assets 0.169 − 0.191 − 0.289* − 0.615*** − 0.676*** − 0.679***

(0.13) (0.14) (0.16) (0.19) (0.19) (0.2) Distance 0.088 0.027 − 0.047 − 0.027 0.014 0.013

(0.09) (0.1) (0.11) (0.13) (0.13) (0.13)

1099

1 3

M&A Negotiations: Role of Negotiation Process, Ownership…

classes. Model 4 has 89.5% of the area under the curve, representing a good clas- sification of the model.

The average marginal effects graph in Fig. 3 also shows the inverted-U-shaped relationship of negotiation period with completion likelihood supporting H1. Fig- ure  3 shows that the peak reaches between − 0.5 and 0.5 standard deviations, fol- lowed by a sharp fall in completion likelihood.

Results in model 4 show that an ownership percentage sought increase leads to a decrease in the likelihood of deal completion (β = − 1.377***) accepting H2.1. The predictive margin in Fig. 4 shows that as the ownership sought increases, the prob- ability curves shift downwards, confirming the negative nature of the relationship

*p < 0.1; **p < 0.05; ***p < 0.01; numbers in parentheses are standard errors

Table 3 (continued)

Model1 Model 2 Model3 Model4 Model5 Model6

Common GICS 0.171 0.204 0.048 0.158 0.175 0.121 (0.09) (0.17) (0.18) (0.2) (0.2) (0.21)

Constant 1.979 1.452 0.305 1.087 1.115 1.112 (0.63) (0.65) (0.72) (0.8) (0.82) (0.85)

No of observations 983 983 983 983 983 983 Log likelihood − 552.98 − 515.57 − 464.39 − 392.95 − 383.55 − 377 AIC 1241.96 1171.13 1076.77 937.91 923.15 918 BIC 1574.52 1513.48 1438.68 1309.59 1304.62 1319.03 AUROC 0.757 0.7934 0.8444 0.895 0.9004 0.903 pseudo R2 0.165 0.2215 0.2988 0.4067 0.4209 0.4308 Country dummy Y Y Y Y Y Y Year dummy Y Y Y Y Y Y

Fig. 3 Average marginal effects negotiation period

1100 D. Kumar et al.

1 3

between completion likelihood and ownership sought. The average marginal effect initially remains negative, with negative values increasing to a certain negotiation period and becoming non-significant at higher negotiation period values with 95% confidence interval touching the zero mark.

The ownership prior to the deal variable becomes insignificant after the addition of the negotiation variable in model 4, rejecting hypothesis H2.2. The average mar- ginal effect shows that the 95% confidence interval of impact on completion likeli- hood remains close to zero for the entire negotiation period. The predictive margins graph in Fig. 4 shows that the effect of toehold reverses after 0.5 standard deviations of the negotiation period. The average marginal effect on completion likelihood becomes negative after 0.5 standard deviations of the negotiation period. The toe- hold’s predictive margin curves are close, and the 95% confidence interval overlaps; however, a small difference in effect is noticeable.

The β value for acquirer’s financial advisor variable varies between 0.28 and 0.33. The hiring of financial advisors by the acquirer increases the completion likelihood supporting H3.1. The β value of the acquirer’s legal advisor varies between 0.322 and 0.591. The values are significant throughout accepting H3.1. Target’s financial advisor variable is positive but not significant in model 4 but positive and significant

Fig. 4 Predictive margin and average marginal effects of ownership percentage sought and prior owner- ship (Toehold)

1101

1 3

M&A Negotiations: Role of Negotiation Process, Ownership…

in model 5. Model 6 includes an interaction term of negotiation period and target financial advisor and is thus not used to interpret the main effects of the target finan- cial advisor on deal completion (Aiken et al. 1991; Whisman and McClelland 2005). Also, model 6 does not have a higher explanatory power than model 5. Thus, a non- significant impact of target financial advisors on deal completion is inferred, not supporting H3.2 for target financial advisors. The target’s legal advisor has a con- sistently positive effect on completion likelihood in all models. Figure 5 shows that this effect is positive and significant in model 5, not supporting H3.2 for target legal advisors. Instead, it is found that a larger number of target legal advisors positively impact the completion likelihood.

The control variable announced premium is insignificant in the final model. The firms mostly renegotiate the premium, and the final premium may differ substan- tially. The announced total value, company takeover, and total target assets are all negative, decreasing completion likelihood. The announced value and assets are measures of the target’s size, and negative values show that bigger targets are chal- lenging to acquire. The company takeover variable’s negative value shows that acquiring 100% of the target ownership is challenging. The distance variable dis- tinguishes closer deals from far away locations in other countries. The insignificant GICS variable shows that related and unrelated M&As’ completion likelihood is similar.

5.2 Robustness Tests

There are chances of simultaneity between the negotiation period and completion likelihood. The likelihood of deal completion might affect the negotiation period. Under the existence of simultaneity, logistic regression results would be biased. An

Fig. 5 Average marginal effects of acquirer and target advisors

1102 D. Kumar et al.

1 3

Table 4 Instrument variable test and Probit with endogenous Regressors

*p < 0.1; **p < 0.05; ***p < 0.01; numbers in parentheses are stand- ard errors

M1 M2

Neg_period 0.914*** (0.34)

Economic freedom − 0.017*** (0.00)

Acquirer financial advisor 0.035 0.165 ** (0.03) (0.06)

Target financial advisor 0.056 0.051 (0.04) (0.07)

Acquirer legal advisor 0.147*** 0.131 (0.04) (0.10)

Target legal advisor 0.149*** 0.155 (0.04) (0.1)

Announced premium 0.110*** 0.028 (0.03) (0.07)

Announced total value −0.061 −0.6*** (0.05) (0.14)

Prior ownership 0.198** 0.401** (0.07) (0.17)

Target total assets −0.021 −0.016 (0.05) (0.07)

Company takeover 0.288*** −1.011*** (0.09) (0.14)

Ownership percent sought 0.148*** 0.133 (0.03) (0.10)

Distance 0.034 −0.041 (0.03) (0.05)

Common GICS −0.058 0.136 (0.06) (0.10)

Constant 0.651* 0.196 (0.36) (0.32)

Number of observations 971 971 F(13, 957) 11.33 Prob > F 0 R-squared 0.1334 Adj R-squared 0.1216 Root MSE 0.93 Wald test of exogeneity,chi2(1) 0.54 Prob > chi2 0.4636

1103

1 3

M&A Negotiations: Role of Negotiation Process, Ownership…

instrumental variable approach is used to address the endogeneity issue. The deal and firm-level factors are expected to affect both the negotiation period and status. Political obstacles increase the acquisition duration (Li et al. 2017). They can create hindrances by slowing down the process. The economic freedom index2 developed by the Heritage Foundation is used for the target country as the instrument variable. Several other studies use the index in their work (Dong et al. 2019; Ermolaeva 2019; Zhou et al. 2016). The index has economic freedom data from the year 1995–2019. The index acts as a proxy for the enabling environment created by the target coun- try’s government.

The test for a weak instrument is important because weak instruments induce bias in two-stage least squares estimates. The null of weak instruments is rejected based on a 5% exact critical value for a single endogenous regressor and a 10% maximum bias of instrument variable relative to ordinary least squares (OLS) (Staiger and Stock 1997). Next, probit regression is performed with endogenous regressor to find non-rejection of the null hypothesis of exogeneity. Table 4 shows the results of IV regression and probit model with endogenous regressors. Two- step probit estimation with endogenous regressors (Newey 1987) is also per- formed, and finds similar results of non-rejection of exogeneity. Thus, the logit estimates are correct.

Next, Table 5 shows the division of the data into a training set and validation set (in the ratio of 70:30). Logistic regression is performed on the training set, and the outcome is predicted on the validation set data. The logistic regression results on the training dataset have the same sign, and all the hypotheses are similarly accepted/ rejected as in the complete set (Table 6).

Machine learning classifiers sometimes better classify complex business-related models (Wu et al. 2021). The logistic regression results are also compared with the results of machine learning classifiers (decision tree and random forest). We find that logistic regression identifies completed deals better (Table  7). Seventy-seven deals, compared to 65 and 72, are correctly classified by logistics regression, com- pared to the random forest and decision tree, respectively. The logistics regression also classifies the abandoned deals better (154 vs 146) than the decision tree classi- fication. Overall, both logistics regression and random forest classify 231 deals cor- rectly (154 + 77 for logit and 165 + 65 for random forests). However, the completed deals belong to the minor class, and logistic regression classifies it better. Thus, the use of logistic regression for the analysis is reasonable.

Table 5 Data division into training set and validation set

0 1

Trainset 410 279 Valid set 180 116

2 https:// www. herit age. org/ index/.

1104 D. Kumar et al.

1 3

Table 6 Logistics regression on trainset

Trainset

Neg_period ^2 −1.373*** (0.27)

Neg_period 2.447*** (0.44)

Acquirer financial advisor 0.422*** (0.16)

Target financial advisor 0.498** (0.23)

Acquirer legal advisor 0.322* (0.18)

Target legal advisor 0.409** (0.2)

Prior ownership 0.489 (0.32)

Ownership percent sought −1.561*** (0.27)

Acquirer legal advisor x Neg_Period 0.331 (0.24)

Target legal advisor x Neg_Period 0.444* (0.26)

Target financial advisor x Neg_Period −0.47* (0.28)

Acquirer financial advisor x Neg_Period −0.102 (0.17)

Prior ownership x Neg Period −0.679* (0.4)

Ownership percent sought x Neg_Period 0.655** (0.27)

Announced premium 0.041 (0.12)

Announced total value −0.227 (0.29)

Company takeover −0.642 (0.44)

Target total assets −0.921*** (0.26)

Distance −0.024 (0.18)

Common GICS 0.064 (0.26)

(Intercept) 0.705 (1.02)

No of observations 681

1105

1 3

M&A Negotiations: Role of Negotiation Process, Ownership…

6 Discussions and Implications

6.1 Discussions

We analyzed the role of negotiation period, ownership on M&A outcome over the negotiation process. The research questions RQ1, RQ2 and RQ3 led to the hypotheses H1, H2.1-H2.2 and H3.1-H3.2, respectively. Table 8 provides a summary of the vari- ous hypotheses tested in the model. The results of the hypothesis testing give interest- ing insights into the research questions. The analysis provides several reflections. Our work provides evidence for the applicability of the process perspective to M&A deal outcomes. We confirm the importance of temporal characteristics in affecting deal completion. The negotiation period variable is positive and significant, indicating an increase in completion likelihood with increasing the negotiation period. The results confirm Muehlfeld et al. (2012) ’s proposition that a higher likelihood of deal closure requires sacrifice for a longer duration. The squared negotiation period variable is nega- tive and significant, showing that the rate of increase in probability decreases. Longer negotiations can only increase the likelihood of completion for a while. A diminishing impact of duration exists, with the effect ultimately turning negative for higher values. Faster negotiations are less costly for both partners (Reddy and Fabian 2020). The deal

* p < 0.1; **p < 0.05; ***p < 0.01; Numbers in parentheses are stand- ard errors

Table 6 (continued) Trainset

Log likelihood −247.86 AIC 655.7 BIC 1017.6 AUROC 0.914 pseudo R2 0.4622 Country Dummy Y Year Dummy Y

Table 7 Prediction results Prediction FALSE TRUE Total

Logit 0 154 26 180 1 39 77 116

Prediction FALSE TRUE Total

Random forest 0 166 14 180 1 51 65 116

Prediction FALSE TRUE Total

Decision tree 0 146 34 180 1 44 72 116

1106 D. Kumar et al.

1 3

is highly susceptible to abandonment during the initial periods of negotiation. As time progresses, the teams negotiate, agree, and prepare plans for the future. However, a pro- longed deal signals deadlock and disagreement during negotiations. The inverted-U- shaped relationship of the negotiation period is corroborated by Aguilera and Denker (2012) and Giglio and Shue (2014). Aguilera and Denker (2012) analyzes the top 100 deal over 11 years and ignores the private takeover negotiations of friendly deals in the analysis. The similarity of results suggests that negotiations before announcements are non-consequential or the private takeover phase’s length is proportional to the public negotiations, creating a similar impact on deal completion likelihood.

The dynamic nature of decision-making is also evident, with varying impacts of ownership and advisors over the negotiation period. Ownership is central to M&A negotiations and higher ownership requirements negatively affect the probability of completion (Fig. 4, left-up). However, as the deal progresses, the negative effect dissi- pates and becomes insignificant from zero. This explains previous studies’ mixed nega- tive and insignificant results (Fuad and Gaur 2019; Kim and Song 2017). The results hint at a dynamic impact of ownership sought and a deal negotiated long enough. The issues related to ownership sought by the acquirer become less relevant over time. A less complex deal (lower ownership percent sought) is more likely to be completed at the beginning of the negotiations. The probabilities converge as the deal becomes prolonged (Fig. 4, left-down). Like ownership sought, prior ownership (toehold) is also a critical deal attribute impacting M&A outcome. Studies have mostly found a positive or insig- nificant impact of a toehold on the deal outcome (Bessler et al. 2015; Ngo and Susnjara 2016). The predictive margin graph (Fig. 4, right-up) shows the toehold acting to help in negotiations in the initial part of the negotiation process and increasing the likelihood of success. As the M&A progresses, the positive effect diminishes and becomes insignifi- cant. Our results conform to both the perspectives of reducing information asymmetry (Loyeung 2019) and recovering due diligence costs (Bessler et  al. 2015), both in the same M&A deal but at different times. We confirm that ownership and advisor struc- ture impart power to complete deals (Malik and Yazar 2016) during the initial period and the power dissipates as the negotiation becomes prolonged. The results demon- strate dynamic decision-making as with lapse of time role of toehold changes (Fig. 4, right-down), and acquirers anticipate an abandonment and contemplate using toehold to recover the due-diligence costs. Hiring financial and legal advisors by both acquirer and the target is positively related to completion. The results for advisors are similar to those found for friendly deals (Hunter and Jagtiani 2003). It shows both parties’ commitment

Table 8 Results of hypothesis tests

* Positive for target legal advisor and insignificant for target financial advisor

Hypothesis Result

H1: Neg_Period, Neg_period^2 Inverted-U Supported H2.1: Ownership percentage sought Negative Supported H2.2: Prior ownership (Toehold) Positive Not-supported H3.1: Acquirer advisor (financial and legal) Positive Supported H3.2: Target advisor (financial and legal) Negative Not supported*

1107

1 3

M&A Negotiations: Role of Negotiation Process, Ownership…

to reaching an agreement, tidying over the target board’s initial hostility, and aiming to negotiate a better deal for its shareholders. The positive and significant results are in con- formation with the skilled advice hypothesis (Aktas and Boone 2022) and also hint that target managers’ hostility is a strategy to ensure a better bargain (Schwert 2000), and the sole aim of the target firm is not to get the deal abandoned. The acquirer (financial and legal) and target (legal) advisors provide support during the entire process of negotia- tions positively, and their effectiveness remains positive and significant throughout the negotiation, dipping slightly for highly prolonged deals (Fig. 5).

6.2 Theoretical Implications

The M&A abandonment theories are developmental and have several prepositions with challenging arguments (Kumar and Sengupta 2020). Through the three RQs and related hypotheses, the study extends the understanding of the M&A negotiation process. The decision to abandon any M&A deal is more complex than indulging in a deal. This study extends the concept of process perspective to the pre-completion negotiation stage. We find that prior ownership behaves distinctly during early and late periods of the negotiation process and exhibits the existence of both information asymmetry and due diligence cost perspectives. Thus, explaining the variation in the sign among different studies. Further, the work encourages future work to con- sider the M&A events and decisions, creating multiple options for the future, such as prior ownership reducing information asymmetry and helping to recover due dili- gence costs both at different times for the same deal. The study also conforms to the skilled advice hypothesis of advisors in M&A negotiations and shows that financial and legal advisor firms of both acquirer and target work to negotiate a mutually ben- eficial deal. The study highlights the important role of legal advisors and encour- ages future research incorporating and extending research on legal advisors in M&A negotiations. Overall, the dynamic nature of the M&A process becomes evident from our work, and we recommend that future work may necessarily incorporate and extend the processual approach in M&A completion studies.

6.3 Managerial Implications

A potential deal requires planning and resources to reach desired outcomes. New information is revealed to the managers during the negotiation period and thus requires a constant reassessment of the merged entity’s future and walk-away price. M&A abandonment causes the loss of valuable time and resources. The managers of both firms must be accommodative of the other party and connect the different stages of the acquisition process. A swift negotiation engagement is important for the parties’ confidence-building. If they are unable to build confidence and consen- sus in the initial negotiation period, the likelihood of completion drops drastically. The managers should understand the importance of negotiating teams and select appropriate internal teams and external financial and legal advisors. A swiftly com- pleted/abandoned deal will benefit both the acquirer and the target.

1108 D. Kumar et al.

1 3

7 Conclusion

The study examines the attributes of the M&A process affecting the outcome. The negotiations affect the completion likelihood through the process (negotiation dura- tion) and transaction-specific factors such as ownership and advisors. The analysis is done through logistics regression and reveals the importance of speed of nego- tiation. The negotiations have a peculiar non-linear relationship with the comple- tion of a deal. The firms need to invest time after the announcement to reduce the information asymmetry and build trust with the other party. Initially, the likelihood of completion increases with the time invested in the negotiation. However, the rela- tionship is inverted U-shaped, and a situation arises when a new day of negotiation decreases the completion likelihood. The advisors assist in the negotiation process and increase the likelihood of completion.

The objective of advisors is to facilitate the deal. The results indicate that target management does not blindly try to get the deal terminated but works con- structively to bargain a better value for the shareholders and agree to the hos- tility being a strategic decision. The transactions involving a bigger change of ownership make the deal complex and reduce the probability of deal completion. The impact of different ownership percentages sought becomes insignificant for higher negotiation duration and suggests a deadlock and stubborn shareholders’ presence in the target firm unmoved by the negotiations.

The prior ownership variable has an insignificant impact on the deal’s com- pletion likelihood, suggesting the use of toeholds as a substitute for termination fees. However, the evidence of firms utilizing the toeholds to reduce information asymmetry in the initial negotiation periods and as a substitute when the deal gets deadlocked is also witnessed in the predictive margins graph of the prior ownership variable in Fig. 4.

Negotiation teams should quickly engage in reducing distrust and information asymmetry. Selecting advisors and deal terms impact the likelihood of deal com- pletion and must be selected accordingly. The study showcases that the M&A process itself affects the outcome. If negotiators cannot build confidence and consensus in the initial negotiation period, the likelihood of completion starts falling. The classification of the deals is compared with various classification techniques. The study provides a good level of accuracy using easily available data. It will help assess the likelihood of ongoing and unannounced deals if the duration of the private takeover phase gets known.

Our study limits itself to the completion/abandonment of deals. We do not differentiate between desirable/good and undesirable/bad M&A deals. We focus on the public takeover process. The private takeover process is confidential and difficult to measure. We do not distinguish between the abilities of advisor firms. The study of the private takeover process’s duration through interviews may help predict the likelihood of deal completion at the time of public announce- ment. Authors can further work to establish the relationship between the private and public takeover process and deal outcome. Future studies may also work on the distinct impact of advisors’ expertise over the negotiation period.

1109

1 3

M&A Negotiations: Role of Negotiation Process, Ownership…

A pp

en di

x: S

am pl

e of

 A cq

ui re

r/ Ta

rg et

: C om

pa ni

es , I

nd us

tr ie

s, C

ou nt

ri es

, A dv

is or

s an

d  A

nn ou

nc em

en t

an d 

O ut

co m

e D

at es

A cq

ui re

r na

m e

Ta rg

et

na m

e A

nn ou

nc e

D at

e C

om -

pl et

io n/

Te rm

i- na

tio n

D at

e

D ea

l St

at us

A cq

ui re

r In

du str

y Se

ct or

Ta rg

et

In du

str y

Se ct

or

A cq

ui re

r C

ou nt

ry /

Re gi

on

Fu ll

N am

e

Ta rg

et

C ou

nt ry

/ Re

gi on

Fu

ll N

am e

A cq

ui re

r L eg

al

A dv

is er

Ta rg

et

Le ga

l A

dv is

er

A cq

ui re

r Fi

na nc

ia l

A dv

is er

Ta rg

et

Fi na

nc ia

l A

dv is

er

G B

ST

H ol

d- in

gs L

td

FN Z G ro

up

Lt d

29 –0

7- 20

19 08

–1 1-

20 19

C om

- pl

et ed

Fi na

nc ia

l Te

ch no

l- og

y N

ew Z

ea -

la nd

A us

tra lia

D av

is P

ol k

A lle

ns /

N or

to n

Ro se

U B

S D

eu ts

ch e

B an

k/ M

ar lin

&

A ss

oc A

hl se

ll A

B C

V C

A

dv is

- er

s L td

11 –1

2- 20

18 07

–0 3-

20 19

C om

- pl

et ed

Fi na

nc ia

l C

on su

m er

, C

yc lic

al B

rit ai

n Sw

ed en

C liff

or d

C ha

nc e/

Fr es

hfi el

ds /R

os ch

ie r

M an

- nh

ei m

er

Sw ar

t

C ar

ne gi

e/ G

ol dm

an

Sa ch

s

N or

de a

C ap

io A

B R

am sa

y G

en er

- al

e de

Sa

nt e

SA

13 –0

7- 20

18 29

–1 1-

20 18

C om

- pl

et ed

C on

- su

m er

, N

on -

cy cl

ic al

C on

su m

er ,

N on

- cy

cl ic

al

Fr an

ce Sw

ed en

B re

di n

Pr at

/C ra

- va

th S

w ai

ne /

G er

na nd

t& da

ni el

s

M an

- nh

ei m

er

Sw ar

t

C re

di t

A gr

ic ol

e/ Ro

th s-

ch ild

&

C o

PJ T Pa

rtn er

s In

c

U ni

pe r S

E Fo

rtu m

O

yj 26

–0 9-

20 17

26 –0

6- 20

18 C

om -

pl et

ed U

til iti

es U

til iti

es Fi

nl an

d G

er m

an y

H en

ge le

r M ue

lle r

Li nk

la te

rs /

Su lli

va n

C ro

m w

el

B ar

cl ay

s/ Pe

re lla

W

ei nb

er g

G ol

dm an

Sa

ch s/

M or

ga n

St an

le y/

Ro th

s- ch

ild &

C

o

1110 D. Kumar et al.

1 3

A cq

ui re

r na

m e

Ta rg

et

na m

e A

nn ou

nc e

D at

e C

om -

pl et

io n/

Te rm

i- na

tio n

D at

e

D ea

l St

at us

A cq

ui re

r In

du str

y Se

ct or

Ta rg

et

In du

str y

Se ct

or

A cq

ui re

r C

ou nt

ry /

Re gi

on

Fu ll

N am

e

Ta rg

et

C ou

nt ry

/ Re

gi on

Fu

ll N

am e

A cq

ui re

r L eg

al

A dv

is er

Ta rg

et

Le ga

l A

dv is

er

A cq

ui re

r Fi

na nc

ia l

A dv

is er

Ta rg

et

Fi na

nc ia

l A

dv is

er

IS TA

Ph

ar m

a- ce

ut ic

al s

LL C

B au

sc h

H ea

lth

C os

In c

16 –1

2- 20

11 30

–0 1-

20 12

Te rm

i- na

te d

C on

- su

m er

, N

on -

cy cl

ic al

C on

su m

er ,

N on

- cy

cl ic

al

U ni

te d

St at

es U

ni te

d St

at es

Sk ad

de n

A rp

s St

ra dl

in g

Yo cc

a M

or ga

n St

an le

y G

re en

hi ll

& C

o

So ut

he rn

U

ni on

C

o

W ill

ia m

s C

os

In c/

Th e

23 –0

6- 20

11 19

–0 7-

20 11

Te rm

i- na

te d

En er

gy U

til iti

es U

ni te

d St

at es

U ni

te d

St at

es C

ra va

th S

w ai

ne /G

ib -

so n

D un

n C

ru t

Lo ck

e Lo

rd /

M or

ris

N ic

ho ls

/ Ro

be rts

H

ol la

nd /

Su lli

va n

C ro

m w

el

B ar

cl ay

s C

ap ita

l/ C

iti

Ev er

co re

Pa

rtn er

/ G

ol d-

m an

Sa

ch s

A lta

ba In

c M

ic ro

so ft

C or

p 01

–0 2-

20 08

03 –0

5- 20

08 Te

rm i-

na te

d Te

ch no

l- og

y C

om m

un i-

ca tio

ns U

ni te

d St

at es

U ni

te d

St at

es C

ad w

al ad

er W

ic k/

M al

le so

ns S

te ph

/ Su

lli va

n C

ro m

w el

C liff

or d

C ha

nc e/

La th

am

&

W at

ki ns

/ M

in te

r El

lis on

/ M

un ge

r To

lle s

O l/S

ka d-

de n

A rp

s

B la

ck sto

ne

G ro

up /

M or

ga n

St an

le y

B ar

cl ay

s C

ap ita

l/ G

ol d-

m an

Sa

ch s/

M oe

lis

& C

o

1111

1 3

M&A Negotiations: Role of Negotiation Process, Ownership…

A cq

ui re

r na

m e

Ta rg

et

na m

e A

nn ou

nc e

D at

e C

om -

pl et

io n/

Te rm

i- na

tio n

D at

e

D ea

l St

at us

A cq

ui re

r In

du str

y Se

ct or

Ta rg

et

In du

str y

Se ct

or

A cq

ui re

r C

ou nt

ry /

Re gi

on

Fu ll

N am

e

Ta rg

et

C ou

nt ry

/ Re

gi on

Fu

ll N

am e

A cq

ui re

r L eg

al

A dv

is er

Ta rg

et

Le ga

l A

dv is

er

A cq

ui re

r Fi

na nc

ia l

A dv

is er

Ta rg

et

Fi na

nc ia

l A

dv is

er

R io

T in

to

A lc

an

In c

A lc

oa

C or

p 07

–0 5-

20 07

12 –0

7- 20

07 Te

rm i-

na te

d B

as ic

M

at er

i- al

s

B as

ic

M at

er i-

al s

U ni

te d

St at

es C

an ad

a B

la ke

D aw

so n/

C le

ar y

G ot

tli eb

/S ka

dd en

A

rp s/

St ik

em an

El

lio tt

La th

am &

W

at ki

ns /

O gi

lv y

Re na

ul t/

Su lli

va n

C ro

m w

el

B M

O C

ap i-

ta l M

kt s/

C iti

/ G

ol dm

an

Sa ch

s/ Le

hm an

B

ro th

er s

JP M

or -

ga n/

M or

ga n

St an

le y/

R B

C

C ap

ita l

M kt

s/ U

B S

Vo da

fo ne

G

m bH

Vo da

fo ne

G

ro up

PL

C

14 –1

1- 19

99 12

–0 4-

20 00

C om

- pl

et ed

C om

- m

un ic

a- tio

ns

C om

m un

i- ca

tio ns

B rit

ai n

G er

m an

y Li

nk la

te rs

Fr es

h- fie

ld s/

Sh ea

r- m

an

St er

ln g

G ol

dm an

Sa

ch s/

U B

S Se

cu ri-

tie s

D eu

ts ch

e B

an k/

JP

M or

ga n/

M er

ril l

Ly nc

h/ M

or g

St an

D

w M

ur ra

y &

Ro

be rts

H

ol d-

in gs

L td

A TO

N

G m

bH 04

–0 9-

20 18

30 –0

9- 20

19 Te

rm i-

na te

d Fi

na nc

ia l

In du

str ia

l G

er m

an y

So ut

h A

fr ic

a B

ow m

an &

C o/

H en

ge le

r M ue

lle r

W eb

be r

W en

tz el

M ac

qu ar

ie

G ro

up D

eu ts

ch e

B an

k

1112 D. Kumar et al.

1 3

Acknowledgements Authors would like to thank the editor and the three anonymous reviewers for their useful comments and suggestions to improve the quality of the article.

References

Abdou K, Gupta P (2011) The role of executive blockholder in a completed merger. Bank. Financ. Rev. 3(1):55–68

Aguilera RV, & Denker JC (2012) Determinants of acquisition completion: a relational perspective Ahammad MF, Tarba SY, Liu Y, Glaister KW, Cooper CL (2016) Exploring the factors influencing the

negotiation process in cross-border M&A. Int Bus Rev 25(2):445–457. https:// doi. org/ 10. 1016/j. ibusr ev. 2015. 06. 001

Aiken L, West S, & Reno R (1991) Multiple regression: testing and interpreting interactions Aktas N, Boone AL (2022) The private deal process in mergers and acquisitions. SSRN Electron J.

https:// doi. org/ 10. 2139/ SSRN. 41264 31 Aktas N, De Bodt E, Bollaert H, Roll R (2016) CEO Narcissism and the takeover process: from private

initiation to deal completion. J Financ Quant Anal 51(1):113–137. https:// doi. org/ 10. 1017/ S0022 10901 60000 65

Amel-Zadeh A, Meeks G (2019) Bidder earnings forecasts in mergers and acquisitions. J Corp Finan 58:373–392. https:// doi. org/ 10. 1016/j. jcorp fin. 2019. 06. 002

Bates TW, Lemmon ML (2003) Breaking up is hard to do? an analysis of termination fee provisions and merger outcomes. J Financ Econ 69(3):469–504. https:// doi. org/ 10. 1016/ S0304- 405X(03) 00120-X

Bauer F, Matzler K (2014) Antecedents of M&A success: the role of strategic complementarity, cultural fit, and degree and speed of integration. Strateg Manag J 35(2):269–291. https:// doi. org/ 10. 1002/ smj. 2091

Becher DA, Cohn JB, Juergens JL (2015) Do stock analysts influence merger completion? an examination of postmerger announcement recommendations. Manag Sci 61(10):2430–2448. https:// doi. org/ 10. 1287/ mnsc. 2014. 2065

Bessler W, Schneck C (2015) Excess premium offers and bidder success in European takeovers. Eur Econ Rev 5(1):23–62. https:// doi. org/ 10. 1007/ s40822- 015- 0017-6

Bessler W, Schneck C, Zimmermann J (2015) Bidder contests in international mergers and acquisitions: the impact of toeholds, preemptive bidding, and termination fees. Int Rev Financ Anal 42:4–23. https:// doi. org/ 10. 1016/j. irfa. 2015. 04. 004

Betton S, Eckbo BE, Thorburn KS (2009) Merger negotiations and the toehold puzzle. J Financ Econ 91(2):158–178. https:// doi. org/ 10. 1016/j. jfine co. 2008. 02. 004

Boone AL, Mulherin JH (2007) Do termination provisions truncate the takeover bidding process? Rev Financ Stud 20(2):461–489. https:// doi. org/ 10. 1093/ rfs/ hhl009

Branch B, Yang T (2003) Predicting successful takeovers and risk arbitrage. Quart J Bus Econ 42(1):3– 18. https:// doi. org/ 10. 1142/ 97898 13148 529_ 0015

Branch B, Wang J, Yang T (2008) A note on takeover success prediction. Int Rev Financ Anal 17(5):1186–1193. https:// doi. org/ 10. 1016/j. irfa. 2007. 07. 003

ten Brug H, Rao Sahib P (2018) Abandoned deals: the merger and acquisition process in the electricity and gas industry. Energy Policy 123:230–239. https:// doi. org/ 10. 1016/j. enpol. 2018. 08. 042

Caiazza S, Pozzolo AF (2014) The determinants of abandoned M&As in the banking sector. SSRN Elec- tron J. https:// doi. org/ 10. 2139/ ssrn. 25083 40

Calcagno R, de Bodt E, Demidova I (2021) Takeover duration and negotiation process. Eur Financ Manag 27(4):589–619. https:// doi. org/ 10. 1111/ eufm. 12331

Chakrabarti A, Mitchell W (2016) The role of geographic distance in completing related acquisitions: evidence from U.S. chemical manufacturers. Strateg Manag J 37(4):673–694. https:// doi. org/ 10. 1002/ smj. 2366

Chuang KS (2017) The role of investment banks on the impact of firm performance in mergers and acqui- sitions: evidence from the Asia-Pacific market. Rev Quant Financ Acc 48(3):677–699. https:// doi. org/ 10. 1007/ s11156- 016- 0564-2

Deng X, Kang JK, Low BS (2013) Corporate social responsibility and stakeholder value maximization: evidence from mergers. J Financ Econ 110(1):87–109

1113

1 3

M&A Negotiations: Role of Negotiation Process, Ownership…

Dikova D, Sahib PR, Van Witteloostuijn A (2010) Cross-border acquisition abandonment and comple- tion: The effect of institutional differences and organizational learning in the international business service industry, 1981–2001. J Int Bus Stud 41(2):223–245. https:// doi. org/ 10. 1057/ jibs. 2009. 10

Doan TT, Rao Sahib P, van Witteloostuijn A (2018) Lessons from the flipside: How do acquirers learn from divestitures to complete acquisitions? Long Range Plan 51(2):252–266. https:// doi. org/ 10. 1016/j. lrp. 2018. 01. 002

Dong L, Li X, McDonald F, Xie J (2019) Distance and the completion of Chinese cross-border mergers and acquisitions. Balt J Manag 14(3):500–519. https:// doi. org/ 10. 1108/ BJM- 06- 2018- 0223

Ermolaeva L (2019) M&A deals completion and abandonment by Russian MNE. Int J Emerg Mark 14(3):475–494. https:// doi. org/ 10. 1108/ IJOEM- 05- 2016- 0140

Fuad M, Gaur AS (2019) Merger waves, entry-timing, and cross-border acquisition completion: a fric- tional lens perspective. J World Bus 54(2):107–118. https:// doi. org/ 10. 1016/j. jwb. 2018. 12. 001

Gajic M, & Scarf M (2020) Takeovers in Australia—guide: responding to a hostile takeover bid—the first 24 hours. In Minter Ellison

Gao Q, Zhang Z, Li Z, Li Y, Shao X (2022) Strategic green marketing and cross-border merger and acquisition completion: the role of corporate social responsibility and green patent development. J Clean Prod. https:// doi. org/ 10. 1016/j. jclep ro. 2022. 130961

Giglio S, Shue K (2014) No news is news: do markets underreact to nothing? Rev Financ Stud 27(12):3389–3440. https:// doi. org/ 10. 1093/ rfs/ hhu052

Henry D (2004) Corporate governance and ownership structure of target companies and the outcome of takeovers. Pac Basin Financ J 12(4):419–444. https:// doi. org/ 10. 1016/j. pacfin. 2003. 09. 004

Holl P, Kyriaziz D (1996) The determinants of outcome in UK Take–over bids. Int J Econ Bus 3(2):165–184. https:// doi. org/ 10. 1080/ 75852 8451

Hossain MS (2021) Merger & acquisitions (M&As) as an important strategic vehicle in business: thematic areas, research avenues & possible suggestions. J Econ Bus 116:106004. https:// doi. org/ 10. 1016/J. JECON BUS. 2021. 106004

Hotchkiss ES, Qian J, Song W (2005) Holdups, renegotiation, and deal protection in mergers. SSRN Electron J. https:// doi. org/ 10. 2139/ ssrn. 705365

Hukkanen P, Keloharju M (2019) Initial offer precision and M & A outcomes. Financ Manag 48(1):291–310. https:// doi. org/ 10. 1111/ fima. 12229

Hunter WC, Jagtiani J (2003) An analysis of advisor choice, fees, and effort in mergers and acquisi- tions. Rev Financ Econ 12(1):65–81. https:// doi. org/ 10. 1016/ S1058- 3300(03) 00007-7

Jemison DB, Sitkin SB (1986) Corporate acquisitions: a process perspective. Acad Manag Rev 11(1):145–163. https:// doi. org/ 10. 5465/ amr. 1986. 42826 48

Jeon JQ, Ligon JA (2011) How much is reasonable? the size of termination fees in mergers and acqui- sitions. J Corp Finan 17(4):959–981. https:// doi. org/ 10. 1016/j. jcorp fin. 2011. 04. 013

Jongwanich J, Brooks DH, Kohpaiboon A (2011) Cross-border mergers and acquisitions and financial development: evidence from emerging Asia. Asian Econ J 3:265–284

Karaca-Mandic P, Norton EC, Dowd B (2012) Interaction terms in nonlinear models. Health Serv Res 47(1):255–274. https:// doi. org/ 10. 1111/j. 1475- 6773. 2011. 01314.x

Kim H, Song J (2017) Filling institutional voids in emerging economies: the impact of capital market development and business groups on M&A deal abandonment. J Int Bus Stud 48(3):308–323. https:// doi. org/ 10. 1057/ s41267- 016- 0025-0

Krishnan CNV, Masulis RW (2013) Law firm expertise and merger and acquisition outcomes. J Law Econ 56(1):189–226. https:// doi. org/ 10. 1086/ 667361

Krishnan CNV, Masulis RW, Thomas RS, Thompson RB (2012) Shareholder litigation in mergers and acquisitions. J Corp Finan 18(5):1248–1268. https:// doi. org/ 10. 1016/j. jcorp fin. 2012. 08. 004

Krishnan CNV, Laux PA (2008) Legal advisors: popularity versus economic performance in acquisi- tions. Corp Ownersh Control 6(2):475–499. https:// doi. org/ 10. 22495/ cocv6 i2c4p6

Kumar D, Sengupta K (2020) Abandonment of mergers and acquisitions: a review and research agenda. Int J Emerg Mark 16(7):1373–1403. https:// doi. org/ 10. 1108/ IJOEM- 12- 2019- 1056

Kumar D, Sengupta K, Bhattacharya M (2023) Macroeconomic influences on M&A deal outcomes: an analysis of domestic and cross-border M&As in developed and emerging economies. J Bus Res 161:113831. https:// doi. org/ 10. 1016/J. JBUSR ES. 2023. 113831

Li J, Xia J, Lin Z (2017) Cross-border acquisitions by state-owned firms: how do legitimacy concerns affect the completion and duration of their acquisitions? Strateg Manag J 38(9):1915–1934. https:// doi. org/ 10. 1002/ smj. 2609

1114 D. Kumar et al.

1 3

Li J, Li P, Wang B (2019) The liability of opaqueness: State ownership and the likelihood of deal completion in international acquisitions by Chinese firms. Strateg Manag J 40(2):303–327. https:// doi. org/ 10. 1002/ smj. 2985

Lim MH, Lee JH (2016) The effects of industry relatedness and takeover motives on cross-border acquisition completion. J Bus Res 69(11):4787–4792. https:// doi. org/ 10. 1016/j. jbusr es. 2016. 04. 031

Lim MH, Lee JH (2017) National economic disparity and cross-border acquisition resolution. Int Bus Rev 26(2):354–364. https:// doi. org/ 10. 1016/j. ibusr ev. 2016. 09. 004

Loyeung A (2019) The role of boutique financial advisors in mergers and acquisitions. Aust J Manag 44(2):212–247. https:// doi. org/ 10. 1177/ 03128 96218 792970

Luypaert M, De Maeseneire W (2015) Antecedents of time to completion in mergers and acquisitions. Appl Econ Lett 22(4):299–304. https:// doi. org/ 10. 1080/ 13504 851. 2014. 939370

Malik TH, Yazar OH (2016) The negotiator’s power as enabler and cultural distance as inhibitor in the international alliance formation. Int Bus Rev 25(5):1043–1052. https:// doi. org/ 10. 1016/j. ibusr ev. 2016. 01. 005

Malik TH, Huo C, Nielsen K (2022) Legal distance moderation in the inter-partner technology distance on cross-country equity investments: a multilevel analysis of the information & communication technology sector. J Gen Manag. https:// doi. org/ 10. 1177/ 03063 07022 11230 52

Muehlfeld K, Sahib PR, Van Witteloostuijn A (2007) Completion or abandonment of mergers and acqui- sitions: Evidence from the newspaper industry, 1981–2000. J Media Econ 20(2):107–137. https:// doi. org/ 10. 1080/ 08997 76070 11937 46

Muehlfeld K, Rao Sahib P, Van Witteloostuijn A (2012) A contextual theory of organizational learning from failures and successes: a study of acquisition completion in the global newspaper industry, 1981–2008. Strateg Manag J 33(8):938–964. https:// doi. org/ 10. 1002/ smj. 1954

Newey WK (1987) Efficient estimation of limited dependent variable models with endogenous explana- tory variables. J Econ 36(3):231–250. https:// doi. org/ 10. 1016/ 0304- 4076(87) 90001-7

Ngo T, Susnjara J (2016) Hostility and deal completion likelihood in international acquisitions: the mod- erating effect of information leakage. Glob Financ J 31:42–56. https:// doi. org/ 10. 1016/j. gfj. 2016. 04. 002

Officer MS (2003) Termination fees in mergers and acquisitions. J Financ Econ 69(3):431–467. https:// doi. org/ 10. 1016/ S0304- 405X(03) 00119-3

Popli M, Akbar M, Kumar V, Gaur A (2016) Reconceptualizing cultural distance: The role of cultural experience reserve in cross-border acquisitions. J World Bus 51(3):404–412. https:// doi. org/ 10. 1016/j. jwb. 2015. 11. 003

Raghavendra Rau P (2000) Investment bank market share, contingent fee payments, and the performance of acquiring firms. J Financ Econ 56(2):293–324. https:// doi. org/ 10. 1016/ S0304- 405X(00) 00042-8

Reddy RK, Fabian F (2020) Information asymmetry and host country institutions in cross-border acquisi- tions. Manag Int Rev 60(6):909–938. https:// doi. org/ 10. 1007/ s11575- 020- 00431-w

Reddy KS, Xie E, Huang Y (2016) The causes and consequences of delayed/abandoned cross-border merger & acquisition transactions: a cross-case analysis in the dynamic industries. J Organ Chang Manag 29(6):917–962. https:// doi. org/ 10. 1108/ JOCM- 10- 2015- 0183

Restrepo F, Subramanian G (2017) The new look of deal protection. Stanford Law Rev. 69(4):1013–1074 Schaik D van (2008) An Analysis of Merger Waves and Hostile Takeovers M & A in Japan An analysis

of merger waves and hostile takeovers. ERIM electronic series portal: http:// hdl. handle. net/ 1765/1 Schwert GW (2000) Hostility in takeovers: in the eyes of the beholder? J Financ 55(6):2599–2640.

https:// doi. org/ 10. 1111/ 0022- 1082. 00301 Song W, Diana J, Zhou L (2013a) The value of boutique financial advisors in mergers and acquisitions. J

Corp Finan 20:94–114. https:// doi. org/ 10. 1016/j. jcorp fin. 2012. 12. 003 Song W, Wei J, Zhou L (2013b) The value of boutique financial advisors in mergers and acquisitions. J

Corp Finan 20(1):94–114. https:// doi. org/ 10. 1016/j. jcorp fin. 2012. 12. 003 Staiger D, Stock JH (1997) Instrumental variables regression with weak instruments. Econometrica

65(3):557. https:// doi. org/ 10. 2307/ 21717 53 UNCTAD (2021) World investment report 2021: investing in sustainable recovery Welch X, Pavićević S, Keil T, Laamanen T (2020) The Pre-deal phase of mergers and acquisitions: a

review and research agenda. J Manag 46(6):843–878. https:// doi. org/ 10. 1177/ 01492 06319 886908 Whisman MA, McClelland GH (2005) Designing, testing, and interpreting interactions and moderator

effects in family research. J Fam Psychol 19(1):111–120. https:// doi. org/ 10. 1037/ 0893- 3200. 19.1. 111

1115

1 3

M&A Negotiations: Role of Negotiation Process, Ownership…

Authors and Affiliations

Deepak Kumar1  · Keya Sengupta2 · Mousumi Bhattacharya2

* Deepak Kumar [email protected]; [email protected]

Keya Sengupta [email protected]

Mousumi Bhattacharya [email protected]

1 Indian Institute of Management Ranchi, Prabandhan Nagar, Nayasarai Rd, Ranchi, Jharkhand 834004, India

2 Indian Institute of Management Shillong, Umsawli Shillong, East Khasi Hills District, Shillong, Meghalaya 793018, India

Wong P, O’Sullivan N (2001) The determinants and consequences of abandoned takeovers. J Econ Surv 15(2):145–186. https:// doi. org/ 10. 1111/ 1467- 6419. 00135

Wu HC, Chen JH, Wang PW (2021) Cash holdings prediction using decision tree algorithms and com- parison with logistic regression model. Cybern Syst 52(8):689–704. https:// doi. org/ 10. 1080/ 01969 722. 2021. 19769 88

Younkin P (2016) Complicating abandonment: how a multi-stage theory of abandonment clarifies the evolution of an adopted practice. Organ Stud 37(7):1017–1053. https:// doi. org/ 10. 1177/ 01708 40615 613376

Zhou C, Xie J, Wang Q (2016) Failure to complete cross-border M&As: to vs. from emerging markets. J Int Bus Stud 47(9):1077–1105. https:// doi. org/ 10. 1057/ s41267- 016- 0027-y

Zhu PC, Jog V, Otchere I (2014) Idiosyncratic volatility and mergers and acquisitions in emerging mar- kets. Emerg Mark Rev 19:18–48. https:// doi. org/ 10. 1016/j. ememar. 2014. 04. 001

Publisher’s Note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.

Reproduced with permission of copyright owner. Further reproduction prohibited without permission.