Cross-Border M&A Motives and Home Country Institutions: Role of Regulatory Quality and Dynamics in the Asia-Pacific Region

Abstract

The purpose of this paper is to analyze the relationship between home country institutions and cross-border merger and acquisition (M&A) motives of MNEs from the Asia-Pacific region, with a focus on the role of regulatory quality and dynamics. We empirically examine how M&A motives are affected by elements related to risk of the institutional environment of the acquiring firm’s home country regulatory quality over time. The study is grounded in the general theory of springboard MNEs, and the institutional views of cross-border operations, namely the institutional escapism and institutional fostering perspectives. Using data on over 700 cross-border M&As of European firms by Asia-Pacific MNEs in 2007–2017, we analyze the rationales for these deals and their relationship to the institutional characteristics of the buyers’ home countries including regulatory quality and voice and accountability. We found that the quality of home country regulatory environment is significantly related to domestic firms’ motivation for international M&As. However, the significance and sign of the effects differ for different types of motives and over time. Our findings contribute to the literature on general versus emerging MNE-specific internationalization theories (particularly the theory of springboard MNEs) by expounding on the types and dynamics of cross-border M&A motives.

1. Introduction

Outward foreign direct investment (FDI) from the Asia-Pacific region is an important trend and area of research (Paul and Benito 2018), and over a third of global outward FDI are cross-border mergers and acquisitions (M&As) (UNCTAD 2020). While the importance of cross-border M&As in firm internationalization is evident (Luo and Tung 2018), theory and research explaining the motives related to why they are undertaken has recently seen new calls for a better understanding of how these motives might differ between acquirers from advanced and emerging economies (Xie et al. 2017; Sutherland et al. 2020), especially in the Asia-Pacific region (Faff et al. 2019) where there are both rising emerging economies (Scalera et al. 2020) and developed countries active in M&As (Ahmed 2019; Luo et al. 2019). Institutions were highlighted as one of the factors underlying the potentially unique motives for M&As by firms from emerging economies (Lebedev et al. 2015; Dikova et al. 2016). Several studies have proposed that emerging market firms are unique in some ways to developed firms in their motives for acquiring abroad (Mathews 2006; Luo and Tung 2007; Gaffney et al. 2016).

However, the differences between advanced and emerging market MNEs (EMNEs) may not exist in the level previously stated, and observable differences could potentially diminish over time (Narula 2012). This study responds to the recent calls for a dynamic perspective on EMNE FDI and M&As and their motives (Elia and Santangelo 2017; Kumar et al. 2020) and a need for a general multinational enterprise (MNE) theory that would include both unique features (e.g., home country institutional volatility) and similarities (e.g., a desire to achieve economies of scale and expand geographic footprint) between advanced and emerging MNEs (Luo and Tung 2018).

Differences may exist in M&A determinants and investment motives because of the characteristics of the acquiring firm’s home country (Erel et al. 2012; Xie et al. 2017) and host country location advantages (Dikova et al. 2019). However, understanding the firm-specific strategic motives that underlie them is also important (Hassan et al. 2018). M&A motives can be studied by scrutinizing company and analyst statements on the rationales for M&As rather than relying on data about host country locations of acquisitions (Rabier 2017). M&A motives are not only driven by host country location advantages but also firm-specific strategic considerations such as product and international diversification (Kumar 2009) and operational synergy, including revenue growth through new product innovation and access to target’s product offerings (Puranam and Srikanth 2007; Hoberg and Phillips 2010). Additionally, an important M&A motive related to product diversification is strategic asset-seeking (Dunning and Lundan 2008; Deng 2009; Meyer 2015).

However, purely considering a firm’s motivation to conduct M&As based on the host country location advantages and firm-specific considerations is problematic, given the recent literature that also emphasizes the importance of home country institutions and firm-specific strategic intents relative to firms’ engagement in outward FDI (Cuervo-Cazurra et al. 2018; Dikova et al. 2016; Luo and Tung 2018). Thus, we draw insights from the institution-based international business research and analyze firms’ M&A motivation through explaining its relationship with home country institutions. We analyze the motives of acquirer firms from Asia Pacific countries most active in M&As in over 700 cross-border deals in European countries in 2007–2017, a period of an outward cross-border M&A wave (Xie et al. 2017; Xu 2017) from the Asia-Pacific region (Verbeke et al. 2019). In an analysis of the motives of both emerging and advanced MNEs (AMNEs), we aim to test whether any significant differences between the motives exist. We develop hypotheses explaining how (different) motives are affected by elements related to risk of the institutional environment of the acquiring firm’s home country institutions (regulatory quality in particular) over time (Elia and Santangelo 2017).

Our study finds that home country regulatory quality is a significant factor that connects to MNEs’ motivation to conduct M&As. The ability of home country governments to formulate and implement sound policies and regulations to facilitate private sector development (Kaufmann et al. 2009) has a positive relationship with domestic firms’ motives for engagement in M&As with ‘springboard’ motives, namely, ‘add products/expand offerings’ and negative effect on the likelihood of acquirers to have ‘traditional’ motives, namely, ‘increase (economies of) scale’. Extending the literature that often aggregated the institutional indicators and focused on institutional distance (Dikova 2009; Shirodkar and Konara 2017), we find that both home country regulatory quality and voice and accountability have significant (but varied) effect on M&A motives. This adds to the evidence on the role of other institutional factors such as corruption and political stability (Dikova et al. 2016) in stimulating cross-border M&As. Building on the springboard theory (Luo and Tung 2018), we develop explicit hypotheses linking regulatory quality to the two main types of M&A motives (‘traditional’ and ‘springboard’) over time and link them to motives most frequently mentioned by firms in our sample (‘increase scale, geographic footprint, and product offering’).

We also contribute to our understanding of the dynamics of the cross-border M&A motives and develop a typology of factors influencing the motives. We find that the propensity to use the three main M&A motives is significantly related to the deal year. The ‘traditional’ motive to ‘increase scale’ is positively related to time while the ‘springboard’ motive to ‘add products/expand offerings’ is negatively related to time. There are also notable interactions between the effect of regulatory quality on the M&A motives and time. In the following sections, we first review literature on cross-border M&A motives and institutions. We then build hypotheses and a theoretical framework explaining the link between home country regulatory quality and M&A motives over time, present our data, method, and analysis. Finally, we present our discussion and conclusions.

2. Literature Review

The preeminent theory in analysing MNE’s motives for internationalization over previous decades is Dunning’s (1993) OLI paradigm, which is based on a firm’s exploitation of ownership, location, and internalization advantages. When discussing motives, Dunning (1993) proposes three main motives for foreign investments: market-seeking, resource-seeking, and efficiency-seeking. Meyer (2015) suggests Dunning’s work remains important when analysing business strategies, adding that including strategic asset-seeking motive is increasingly necessary, especially with the increasing importance placed on technology. However, Cuervo-Cazurra and Narula (2015, p. 11) assert that Dunning’s conceptualization of motives can be broadened and encourage researchers to use other types of FDI motives embedded in appropriate frameworks and theories.

International business scholars tend to follow the OLI paradigm when analysing the traditional M&A motives (Dikova et al. 2019). However, the true reason for selecting the M&A route may be missed if more thorough analysis is not made: broader M&A literature is possibly as relevant as the IB literature. One of the first papers that identified common motives for M&As was that of Haspeslagh and Jemison (1991). In this study, contributing motives included inefficient management, synergy, diversification, agency problems, tax considerations, and market expansion. Purchasing assets below replacement costs is also touted as a reason for firms to acquire (Machiraju 2007). Acquirer motives have been described as either value-increasing or value-decreasing. Nguyen et al. (2012) describe value-increasing motives as those wherein benefits are found from the merger of two firms, and these are driven by market power, economies of scale, financial synergy, taxes, and the exploitation of asymmetric information between the two firms. M&As with value-decreasing motives consist of three main types: agency, hubris, and market timing (Nguyen et al. 2012). Shimizu et al. (2004) explain that many cross-border M&As arise from an attempt to use a new opportunity or conversely avoid a potential threat.

Equally, motivations are perceived as fundamentally different between the emerging and developed country firms engaging in foreign investment (Hope et al. 2011; Gaffney et al. 2016). Luo and Tung (2007) propose that emerging market firms aiming to remain globally competitive are driven to seek rather than exploit assets when acquiring overseas firms. Many EMNEs have historically lacked managerial skills, patent-protected technology, and natural resources (Athreye and Kapur 2009; Deng 2009; Rui and Yip 2008). Since such strategic resources have been missing, EMNEs have used cross-border M&As as the best option for improving their competitive advantage in these areas (Gubbi et al. 2010). These strategic resources are essential for EMNEs, especially as they move into a global marketplace wherein competition is greater (Luo and Tung 2007). Deng and Yang (2015) suggest that a higher level of resource and market availability in the host country increases the likelihood and intensity of acquisitions to occur by an EMNE.

Buckley et al. (2007) argue that for many emerging countries with lower labour cost, the efficiency seeking motive of an outward investment would be unlikely. Lebedev et al. (2015) note that some emerging economy firms may consider engaging in cross-border M&As to minimize environmental uncertainty and avoid resource dependency. Firms from emerging markets (such as China and India) can also be very different from each other and sometimes more unique than when compared to those from developed backgrounds (Nicholson and Salaber 2013). Kolstad and Wiig (2012) propose that China is anomalous for several reasons. Mainly, the majority of outward investing firms in China are state-owned enterprises; therefore, a greater sense of political strategy is involved with their actions. The argument for caution is made by Lebedev et al. (2015), who assert that antecedents identified for EMNEs undertaking a cross-border M&A are not necessarily invalid for firms from developed markets and identify only three truly distinct motives for EMNEs: their home country institutions, latecomer advantages, and national pride (Hope et al. 2011).

Lebedev et al. (2015) also identify that an institutional environment in an emerging market providing greater protection of minority shareholders’ rights is likely to facilitate M&As. When matched with the analysis in this study, the institutional environment would also arguably have greater impact on firms from developing countries. The importance of a strong institutional environment in the motivation for cross-border M&As was potentially underestimated in extant research, as a commonality between developed nations is often a more established and matured institutional environment. Once emerging market firms were studied in greater detail, effort was made to explain the differences; one possibility included institutional factors (Buckley et al. 2007; Deng 2009; Mathews 2006).

Narula (2012) also contends that large EMNEs can have similar advantages to those from developed origins, such as lower costs of capital and state guarantees and that dynamic effects such as the company maturity must be considered in comparing between AMNEs and EMNEs. When these firms begin going global, the question of the motivation behind such movements may not be as different as previously thought. This is consistent with the study by Luo and Tung (2018), who repurposed their concept of springboard FDI (Luo and Tung 2007) into a general theory of springboard MNEs. In addition, they acknowledged that while emerging MNEs are the premier subset of springboard MNEs, ‘the perspective can be applied to MNEs in general to the extent that these firms aggressively seek strategic assets from the outset of outward FDI (OFDI) to augment their home capabilities and use their strengthened capabilities and improved home base to better compete globally’ (Luo and Tung 2018, pp. 129–30). They also suggested for future researchers to focus on the dynamism and evolutionary trends associated with springboard strategies (and the associated M&A motives).

EMNEs’ evolutionary paths have been studied relative to building competitive advantage from emerging markets to developed countries (Kotabe and Kothari 2016). However, we can ground our understanding of the dynamics of EMNE’s M&A motives theoretically in the general theory of springboard MNEs (Luo and Tung 2018). This theory aims to explain EMNEs’ internationalization and show how they differ and resemble AMNEs. It acknowledges that ‘the [springboard] view does not adequately address the evolution of springboard MNEs’ (Luo and Tung 2018, p. 134) and submits that ‘a springboard MNEs’ internationalization process would be an upward spiral trajectory, being radical and accelerated in their early-stage OFDI, but their overall internationalization over a long horizon is still evolutionary’ (Luo and Tung 2018, p. 148). Luo and Tung (2018) urge researchers to build a more nuanced understanding of springboard MNEs’ susceptibility to regulatory requirements at home (and abroad) and changes of these firms over time (Kumar et al. 2020). They also encourage researchers to consider the diversity of home countries, including differences between Asia-Pacific economies with large home markets (e.g., China and India) and newly industrialized economies (e.g., South Korea, Taiwan, and Singapore), making the Asia-Pacific region a suitable ground for testing and extending the theory.

3. Theory and Hypotheses Development

Many researchers have highlighted the differences between emerging and advanced MNEs in FDI and cross-border M&As (Luo and Tung 2007; Guillén and García-Canal 2009; Deng and Yang 2015). The motives for undertaking M&As have been discussed often in the literature, with distinctions regularly made between firms from different national environments, usually along emerging and developed lines (Buckley et al. 2007; Luo and Tung 2007; Deng 2009). Moreover, the level of differences reported between emerging and developed firms when investing abroad have been examined (Narula 2012; Ramamurti 2012; Hernandez and Guillén 2018), resulting in an active debate in the literature on whether EMNE-specific internationalization theories are needed or can be repurposed into a general theory, such as the general springboard MNEs theory (Luo and Tung 2018). The springboard theory may benefit from the development and empirical testing of specific hypotheses related to differences between the characteristics of AMNEs and EMNEs such as the characteristics of their home countries (e.g., resource munificence and institutions) and their impact on M&A motives. A general theory of springboard MNEs does not imply that the home country’s income per capita in itself affects M&A motives; thus, deeper home country institutional factors may have to be considered (Kumar et al. 2020; Luo and Tung 2018).

If the motives of firms engaging in cross-border M&As differ relative to home country, then the question arises as to which characteristics of the country’s level of development (other than income per capita) are significant. A common basis for determining the level of development within a country is its institutional environment. This can be further decomposed into various governance indicators, including voice and accountability, political stability, government effectiveness, regulatory quality, rule of law, and control of corruption (Kaufmann et al. 2009). Home country institutions have been recognized as important influences behind cross-border M&A location choices (Buckley et al. 2016) and M&A performance (Zhu et al. 2019). Kim and Song (2017) built on the concept of institutional voids (Khanna and Palepu 1997, 2010) to explain M&A deal abandonment. Additionally, home country institutions can also relate to M&A motives as they are determining factors behind outward FDI, especially from emerging economies (Wang et al. 2012; Sun et al. 2015). Consequently, the governance quality in the home country—namely, voice and accountability, political stability, government effectiveness, regulatory quality, rule of law, and control of corruption—can be expected to have significant effect on the motives for cross-border M&As, with potentially different impact of each of these types of institutional characteristics on particular types of M&A motive (Dikova et al. 2016).

3.1. Regulatory Quality and the Nature of Cross-Border M&A Motives

Regulatory quality being related to cross-border M&A motives is particularly reasonable (Witt and Lewin 2007; Sun et al. 2015; Luo et al. 2010; Cuervo-Cazurra et al. 2018). Furthermore, the relationship between the likelihood to acquire with a particular motive and quality of home country regulations can be explored. One could expect that regulatory quality in the home country can be related differently to specific M&A motives including traditional ones such as increasing (economies of) scale and ‘springboard’ M&A motives such as expanding product offerings. Additionally, motives such as ‘expanding geographic footprint’ can possibly be classified as in-between ‘traditional’ and ‘springboard’ motives as they are acknowledged both by the springboard theory (Luo and Tung 2018) and literature on traditional M&As (Rabier 2017).

‘Regulatory quality’ is defined by Kaufmann et al. (2009) as ‘the ability of the government to formulate and implement sound policies and regulations that permit and promote private sector development’. Governments being inadequate at this could drive their firms to increase scale beyond home shores, acquire firms in countries they are not present in, and obtain firms with products and offerings not currently in the acquirer’s portfolio. High-quality regulations conducive to outward FDI could also have effects on the particular motives, depending on the home government’s priorities on the types of ‘desirable’ M&A abroad.

The ‘expand offerings’ motive could be linked to the relatively weak regulatory environment for protecting intellectual property or stimulating domestic innovation (Elango and Pattnaik 2011; Cuervo-Cazurra et al. 2018). Regulatory quality includes (among other factors): (1) the risk that normal business operations become more costly due to the regulatory environment and, (2) effect of taxation on incentives to invest (Kaufmann et al. 2009; Witt and Lewin 2007). Such an environment can be argued unfavorable to domestic innovation and new product development to such as degree that it can drive companies not to innovate at their home country but instead acquire foreign firms with new products, offerings, and innovative capabilities. In contrast, some aspects of regulatory quality (such as positive effects of taxation on foreign investment incentives) can also lead to higher propensity to invest abroad (Sun et al. 2015), especially by acquiring companies with new products and offerings, which could be considered strategic assets (Meyer 2015; Ramamurti 2012). Such favorable regulations and policies exist to support M&As aimed at capability-enhancing acquisitions of foreign companies with new products and offerings rather than cross-border M&As aimed at expanding scale (or geographic footprint).

These arguments expand research emphasizing the role of intellectual property protection and regulatory institutions in cross-border M&A research but go beyond the link to the size of equity shares in acquired firms (Chun 2009; Gaffney et al. 2016) or the role of better institutional support for protecting innovative technologies abroad (Gaur and Lu 2007). We refocus attention on the currently unexplored relationship between home country regulatory quality and motive to acquire firms that add new products/offerings to the acquirer’s portfolio (Puranam and Srikanth 2007), often through intra-industry M&A (Park and Roh 2019). Taken together, we hypothesize:

Hypothesis 1a (H1a).

The regulatory quality of the acquirers’ home country will have a negative effect on the likelihood of acquirers from that country to have ‘traditional’ M&A motives, namely, ‘increase (economies of) scale’.

Hypothesis 1b (H1b).

The regulatory quality of the acquirers’ home country will have a positive effect on the likelihood of acquirers from that country to have ‘springboard’ M&A motives, namely, ‘add products/expand offerings’.

3.2. The Dynamics of Cross-Border M&A Motives

Moreover, considering the dynamics of cross-border M&A motives is important. Luo and Tung (2018) urged researchers to consider dynamism associated with (springboard) strategies, as motives for FDI and M&As abroad evolve over time (Narula 2012). However, Luo and Tung (2018) did not thoroughly focus on the dynamics of specific M&A motives. Elia and Santangelo (2017) developed hypotheses emphasizing the importance of the evolution of strategic asset-seeking M&A motive, suggesting that the older the acquisition in advanced countries by an EMNE and the weaker the home country national innovation system of the EMNEs, the greater the extent to which the EMNE will engage in strategic asset-seeking acquisitions in advanced countries (Elia and Santangelo 2017, p. 857).

We extend the arguments of Elia and Santangelo (2017) by considering different dynamics in different M&A motives (not focusing only on strategic asset-seeking but on traditional vs. springboard types of motives) and considering both firm-level and country-level analysis (dynamics of motives for a population of acquirers from a particular country), as every country’s institutional context, such as the regulatory quality, is unique (Scott 2014). We argue that over time, as acquirers from weaker regulatory environments mature in their internationalization (and their home countries develop), their motives will increasingly resemble those of AMNEs (‘increase scale’ and possibly ‘expand geographic footprint’) and be decreasingly targeted at ‘springboard’ motives such as strategic asset-seeking and diversification into new products and offerings. This argument is grounded in the study by Luo and Tung (2018) as we aim to understand how springboard MNEs may evolve and become similar to AMNEs considering their M&A motives. Luo and Tung (2018) emphasized the issue of dynamics relative to how EMNEs may evolve into AMNEs by being springboard MNEs as an aspect of their theory that needs further development. Taken together, we hypothesize:

Hypothesis 2a (H2a).

Companies from the same country will increasingly have ‘traditional M&A motives’ such as an ‘increase scale’.

Hypothesis 2b (H2b).

Companies from the same country will decreasingly have ‘springboard M&A motives’ such as ‘expand offerings’.

3.3. The Dynamics of Home Country Institutional Effects on M&A Motives

Hypotheses 1a, 1b, 2a and 2b provide opportunities to explain cross-border M&A motives, their nature and dynamics of home country institutional effects with a more robust theoretical lens. The general theory of springboard MNEs can therefore be extended by incorporating additional important factors such as the evolution of home country institutions and their relationship with cross-border M&A motives over time (Elia and Santangelo 2017). Due to the poor regulatory quality and ‘institutional voids’ often seen in emerging economies (Meyer and Peng 2016; Doh et al. 2017), domestic firms seek aggressive investment via outward FDI (e.g., M&A) to quickly adapt to global competition (Kumar et al. 2020). This leads to their adoption of the springboard FDIs such as to internationalize with an ‘expanding product offerings’ motive. Over a medium term (which is about 5–10 years, wherein firms may change significantly but institutions will not evolve much), as these firms mature and become established in the global market, they can develop better capabilities that allow them to navigate around institutional complexity. This will lead to these firms changing their M&A motives from springboarding (e.g., adding products or expanding offerings) to more traditional and long-term ones such as aiming for economies of scale (and expanding geographic footprint). Therefore, poor (but possibly somewhat improved) home country regulatory quality is now fostering domestic firms’ M&A engagements (Sun et al. 2015), which will facilitate these firms’ sustainable long-term growth.

These insights from the general theory of springboard MNEs (Luo and Tung 2018) can be integrated into additional hypotheses and a theoretical framework related to M&A motives and their dynamics. Figure A1 provides a typology of the factors behind and dynamics of cross-border M&A motives. This depicts and extends how our hypotheses fit with the main dimensions of our theoretical development: (1) the nature of M&A motives, related to the ‘traditional’ M&A motives vs. ‘springboard’ motives and (2) the nature and dynamics of home country institutional effects on M&A motives, particularly the effects of home country regulatory quality on the motives and transition from springboard to traditional motives over time. The effect of home country regulatory quality on ‘traditional M&A motives’, typically associated with AMNEs (‘increase scale’ and possibly ‘cross-border/expand geographic footprint’ motives) is negative (H1a), while it is positive with regard to the ‘springboard M&A motive’ (‘add products/expand offerings’ motive from H1b), mostly associated with EMNEs.

The effect of time on the propensity to use traditional M&A motives is positive (H2a), while the springboard M&A motive is negatively related to time (H2b) as the maturing of EMNEs (and their home country development) makes acquirers from emerging markets less unique and they behave over time in ways more consistent with AMNEs. Moreover, there is interaction between the effects of home country regulations and time on traditional versus springboard motives, with traditional M&A motives initially being positively related but later negatively related to home country regulatory quality. Conversely, springboard M&A motives are first negatively related and later positively related to home country regulatory quality (see Figure A1). Combined, our theoretical framework indicates that:

Hypothesis 3a (H3a).

The more recent the year of the M&A and the better the home country regulatory quality, the greater the likelihood of traditional M&A motives such as ‘increase scale’.

Hypothesis 3b (H3b).

The less recent the year of the M&A and the poorer the home country regulatory quality, the greater the likelihood that the MNE will engage in M&A with springboard M&A motives such as ‘expand offerings’.

4. Sample, Variables, and Estimation Strategy

4.1. The Sample

The sample of cross-border M&As is collected from the financial deals tracker portion of the Marketline Advantage database. The database has been used in other business and finance research (e.g., Oderanti et al. 2021; Wang et al. 2016). The time period selected was from 2007 to 2017. This was a period when the share of cross-border M&A deals that involved Asia-Pacific acquirers increased from 12% in 2000–2006 to over 30% of total world cross-border M&As in 2007–2017, and then fell to 22% in 2018–2020 (UNCTAD 2021), as depicted in Figure A2. European targets accounted for about 42% of total cross-border purchases in the world in 2007–2017 (UNCTAD 2021). Only completed deals were included (minority, majority, and 100% acquisitions and mergers) for Asia-Pacific firms as acquirers and European firms as targets. M&As were included from countries where only Asian and/or Pacific-country firms act as the acquirer, with examples excluded when firms from other locations cooperated in this role. The sample was collected of 713 M&As taking place by firms from 11 different locations in the Asia Pacific most active in cross-border M&A (with available data): Japan (178), India (139), Australia (124), China (78), Hong Kong (64), Singapore (50), New Zealand (23), Republic of Korea (20), Taiwan (13), Malaysia (12), Thailand (6), Philippines (4), and Indonesia (2). Please see

Table A1. Sample information (N = 713).

Variable	Range	N (% of Total Sample Size)	Variable	Range	N (% of Total Sample Size)
M&A motive *	Increase scale	557 (78.12)	M&A type	100% Acquisition/Merger	208 (29.17)
	Cross-border/ expand geographic footprint	615 (86.26)		Majority Acquisition	418 (58.63)
	Add products/expand offerings	107 (15.01)		Minority Acquisition	87 (12.20)
Home country	Japan	178 (24.96)	Year	2007	12 (1.68)
	Australia	124 (17.39)		2008	77 (10.81)
	Singapore	50 (7.01)		2009	37 (5.19)
	New Zealand	23 (3.22)		2010	71 (9.96)
	India	139 (19.51)		2011	92 (12.9)
	China	78 (10.94)		2012	81 (11.36)
	Hong Kong	64 (8.98)		2013	60 (8.42)
	Republic of Korea	20 (2.81)		2014	83 (11.64)
	Taiwan	13 (1.82)		2015	91 (12.76)
	Malaysia	12 (1.68)		2016	95 (13.32)
	Thailand	6 (0.84)		2017	14 (1.96)
	Philippines	4 (0.56)
	Indonesia	2 (0.28)

Note: * many M&As have more than one motive, which is consistent with Rabier (2017).

for sample information. Acquisitions are of target firms based in Europe, with over 20 countries (coming vastly from the European Union) as venues for this investment. The United Kingdom is included in the host country sample, and was the most common host country for Asia-Pacific M&As in 2007–2017.

The rationales are the main focus of the paper and are coded in the Marketline Advantage database as follows: increase scale, expand offerings/add products, integration (forward, backward and complementary), access to resources, cross-border, finance growth, debt repayment, restructuring capital/business, diversification, cost benefits/advantages, and access to new customer segments.

Table A2. Definitions of main motives (dependent variable) and supporting literature.

Motive and Definition Based on the Literature	Examples of Rationales from Marketline Advantage	Concepts in the Supporting Literature
‘Increase scale’ This motive indicates that the rationale for the M&A was to expand or increase scale, resulting in either significant economies of scale or market growth.	‘The acquisition will strengthen GenesisCare’s position as a provider of cancer treatments in Spain.’ ‘The transaction will allow Creative Technology to further strengthen its audio visual and associated services offering and its position.’	Market-seeking (Dunning 1993) Economies of scale (Singh and Montgomery 1987) Expansion (Jagersma 2005) Cost reductions through economies of scale/scope (Rabier 2017)
‘Cross-border/expand geographic footprint’ This motive indicates that the rationale for the M&A was access to target’s geographic footprint, expanding geographic presence in new markets and spreading the activities geographically.	‘The transaction will enable MSL Solutions to expand into international markets.’ ‘The transaction will allow Delta Lloyd to expand its business in Belgian life insurance and pensions market.’ ‘The acquisition will allow Freelancer to expand its position in the Latin American, Spanish and Portuguese markets.’	Market-seeking (Dunning 1993) Market entry (Jagersma 2005) Geographic risk spreading (Jagersma 2005) Revenue growth through access to target’s geographic footprint (Rabier 2017) Access to target’s geographic footprint (Houston et al. 2001)
‘Add products/expand offerings’ This motive indicates that a transaction results in adding a new product or offering to the acquirer. Through the M&A, the acquirer can add new product line to its existing portfolio of products.	‘It will also allow Snom and VTech to strengthen their product portfolios and technological position in VoIP industry.’ ‘The acquisition will allow Trakka to expand its capabilities and product offering.’ ‘The acquisition will enable Mitsui Chemicals to accelerate the development of products and to introduce new products into the market.’ ‘The acquisition will allow AllyGrow to strengthen its position in the product development domain.’ ‘The transaction will enable XIN Gaming to expand its service offerings.’	Product diversification (Chang 2007; Kumar 2009) Revenue growth through access to target’s product offering (Rabier 2017) Target’s product offering (Hoberg and Phillips 2010; Puranam and Srikanth 2007) Innovation and new product creation (Ahuja and Katila 2001; Makri et al. 2010)

Note: Each M&A can be tagged with a number of motives. The three above were the most typical, and often at least two of them were tagged for each of the deals. The motives were pre-coded by Marketline Advantage analysts. Each of the other motives (e.g., restructuring and diversification) accounted for less than 3% of the coded dataset.

outlines the full definitions of the main motives (increase scale, cross-border/expand geographic footprint, and expand offerings/add products), examples of ‘rationale statements’ used to code them (by Marketline Advantage), and academic literature linked to them. The other motives were only marginally represented in the data, with each of the other motives quoted in less than 3% of deals. Described as rationale on the database, motives are perceived synonymous in this situation. The sample of M&As comprise both single rationale examples and those with multiple rationales (Rabier 2017). Data collected contained information on the industry of each M&A and these widely differed, including everything from aerospace to agriculture.

4.2. Variables

The dependent variable tested focuses on the three most commonly quoted motives (rationales) and the likelihood whether the deal had that rationale (increase scale, cross- border/expand geographic footprint, or add products/expand offerings). Country-specific effects are also tested when determining whether differences exist between countries. Initially, we explored trends in the data based on the GDP per capita (as a measure of wealth and a rough indicator of living standards in each participating country), sourced from the International Monetary Fund and reported in US dollars. The footnote in Figure A3 provides definitions and shows trends in the propensity of M&A deals to have the three main motives by emerging vs. developed countries. The differences between the two groups of countries are not significant, and both emerging-economy and developed-economy firms appear to have a trend, increasingly using ‘increase scale’ and ‘cross-border/expand geographic footprint’ motives and decreasingly ‘expand offerings’ motive.

Consistent with our hypotheses development, we transcend income per capita as a measure of development and consider additional indicators such as institutional effects. Specifically, we consider the World Bank Governance Indicators (Kaufmann et al. 2009) including voice and accountability, political stability, government effectiveness, regulatory quality, rule of law, and control of corruption from the year prior to the completion of the M&A deal (to reduce the potential issue of endogeneity). These six indicators are highly correlated with income per capita, and our main explanatory variable from Hypotheses 2a and 2b (regulatory quality) has low correlation only with voice and accountability (among the six institutional indicators). Therefore, we use only regulatory quality and voice and accountability in our main analysis to avoid multicollinearity concerns. The World Bank data measure the governance indicators two ways: (1) as a percentile ‘rank’ from 0 to 100; and as (2) ‘estimate’ ranging from −2.5 to 2.5 to account for both ranking among all countries and relative changes and the absolute changes in the value of a specific indicator, such as regulatory quality. We use each of these (highly correlated) measures separately in our analysis but only report the results using ‘rank’ in

Table A5. Logistic regressions for the three main motives.

Dependent Variable—Motives	Model 1	Model 2	Model 3	Model 4	Model 5	Model 6
Independent Variables—Below	Increase Scale	Cross Border	Expand Offerings	Increase Scale	Cross Border	Expand Offerings
Regulatory Quality—Rank	−0.116 ***	0.046	0.185 ***	8.138 **	5.935 **	−7.502 **
	(0.043)	(0.051)	(0.065)	(3.739)	(2.996)	(3.331)
Voice Accountability—Rank	0.036 ***	−0.028 **	−0.050 *	0.038 **	−0.031 **	−0.049 *
	(0.013)	(0.014)	(0.028)	(0.016)	(0.013)	(0.028)
Deal Year	0.457 ***	0.217 ***	−0.099 **	0.785 ***	0.479 ***	−0.430 ***
	(0.114)	(0.032)	(0.048)	(0.153)	(0.138)	(0.160)
Regulatory Quality—Rank * Deal Year				−0.004 **	−0.003 **	0.004 **
				(0.002)	(0.001)	(0.002)
R&D/GDP	0.543 *	1.343 *	−0.057	0.360	0.924	0.289
	(0.306)	(0.747)	(0.550)	(0.312)	(0.828)	(0.533)
GDP	−1.536 ***	1.168 **	−0.196	−1.661 ***	0.745	0.445
	(0.414)	(0.455)	(0.594)	(0.518)	(0.620)	(0.765)
GDP change	0.023	0.275	0.871 ***	0.159	0.402 *	0.718 ***
	(0.385)	(0.187)	(0.294)	(0.390)	(0.209)	(0.237)
OFDI Agency	−0.065 ***	−0.022	−0.025	−0.072 ***	−0.024	−0.032
	(0.019)	(0.018)	(0.031)	(0.020)	(0.019)	(0.036)
Shared Language	−0.512	−0.424	−0.688 *	−0.544	−0.428	−0.658 *
	(0.445)	(0.530)	(0.406)	(0.433)	(0.532)	(0.369)
English	1.200	6.029 ***	−3.355	0.330	3.083	0.158
	(1.358)	(1.959)	(2.295)	(1.479)	(3.336)	(2.958)
French Law	8.488 ***			8.605 ***
	(1.344)			(1.558)
Acquirer Public	0.336	−0.140	−0.015	0.332	−0.148	0.000
	(0.257)	(0.321)	(0.332)	(0.250)	(0.321)	(0.328)
Target Public	−0.281	−1.351 ***	0.742	−0.297	−1.392 ***	0.787
	(0.226)	(0.369)	(0.538)	(0.191)	(0.396)	(0.508)
100% Acquisition	−0.310	0.068	0.484 **	−0.330	0.066	0.490 **
	(0.311)	(0.328)	(0.218)	(0.313)	(0.323)	(0.208)
Minority Acquisition	−0.943 ***	−0.036	−0.830 **	−0.994 ***	−0.037	−0.810 **
	(0.246)	(0.524)	(0.358)	(0.271)	(0.525)	(0.349)
Industry Relatedness	0.166	−0.078	−0.056	0.208	−0.071	−0.074
	(0.362)	(0.198)	(0.272)	(0.380)	(0.200)	(0.283)
Constant	−867.322 ***	−474.314 ***	190.810 *	−1524.418 ***	−990.695 ***	839.479 ***
	(222.451)	(65.605)	(105.203)	(299.750)	(270.470)	(310.341)
Country dummies	Yes	Yes	Yes	Yes	Yes	Yes
Clustered standard errors	Yes	Yes	Yes	Yes	Yes	Yes
Observations	596	591	591	596	591	591
Log likelihood	−196.2	−273.6	−231.8	−194.9	−273	−230.8
Pseudo R2	0.158	0.118	0.0807	0.164	0.120	0.0846
AIC	418.4	567.3	483.6	413.8	565.9	481.7
BIC	475.5	611.1	527.4	466.5	609.7	525.5
Hosmer-Lemeshow Chi2 (Goodness-of-fit test [4 quartiles])	1.923	0.396	0.653	1.152	1.721	0.311
Prob > chi2	0.382	0.821	0.721	0.562	0.423	0.856

Note: *, **, and *** denote statistical significance at the 10%, 5% and 1% level, respectively. Standard errors are clustered at the country level.

(while we conduct sensitivity analysis for the ‘estimate’ variables and discuss these results in the Results section).

We also consider a number of potentially relevant control variables (refer to

Table A3. Independent and control variables (descriptions, measures, and sources).

Variable	Description and Source	Supporting Literature
Regulatory quality—Rank Regulatory quality—Estimate	The ability of the government to formulate and implement sound policies and regulations that permit and promote private sector development. Relative percentile rank (0–100) or absolute ‘estimate’ (−2.5 to 2.5). Year prior to the M&A deal (World Bank).	(Witt and Lewin 2007; Sun et al. 2015; Luo et al. 2010; Cuervo-Cazurra et al. 2018)
Voice and accountability—Rank Voice and accountability—Estimate	The extent to which a country’s citizens are able to participate in selecting their government, as well as freedom of expression, freedom of association, and a free media. Relative percentile rank (0–100) or absolute ‘estimate’ (−2.5 to 2.5). Year prior to the M&A deal (World Bank).	(Hur et al. 2011)
Deal year	The year when the M&A deal was completed.	(Elia and Santangelo 2017)
R&D/GDP	Gross domestic expenditures on R&D, expressed as a percent of GDP. Year prior to the M&A deal (World Development Indicators).	(Deng 2009; Meyer 2015)
GDP	Gross domestic product of the home country (at purchaser’s prices in current USD). Year prior to the M&A deal. (World Development Indicators).	(Rabbiosi et al. 2012; Hope et al. 2011)
GDP change	Change in GDP (definition above) in the home country ten years prior to the M&A deal (World Bank Development Indicators).	(Elia and Santangelo 2017)
OFDI agency	Number of years between the M&A deal and the year of the establishment of an outward FDI promotion agency in the home country of the acquirer (UNCTAD 2015 and authors’ research).	(Luo et al. 2010; Rasiah et al. 2010)
Shared language	Dummy variable = 1 when the home and the host country have at least one of their official languages in common.	(Arora and Fosfuri 2000; Kedia and Reddy 2016)
English	Dummy variable = 1 if English is one of the official languages in the acquirer country.	(Globerman and Shapiro 2003)
French law	Countries whose corporate law or commercial law originate in French law.	(La Porta et al. 1998; Nicholson and Salaber 2013; Globerman and Shapiro 2003)
Acquirer type—public	Specifies whether the acquirer is a public firm trading on a stock exchange or a private firm. Takes value of 1 if the acquirer is a public firm.	(Nicholson and Salaber 2013)
Target type—public	Specifies whether the acquirer is a public firm trading on a stock exchange or a private firm. Takes value of 1 if the target is a public firm.	(Nicholson and Salaber 2013)
100% acquisition	Takes a value of 1 if the deal resulted in a 100% acquisition.	(Chun 2009; Gaffney et al. 2016)
Minority acquisition	Takes a value of 1 if the deal resulted in acquiring a minority stake in the target.	(Ouimet 2013)
Industry relatedness	Takes a value of 1 if both the acquirer and target operate in at least one industry that is the same for each party at a broad (first two digits of SIC code) level of classification.	(Nicholson and Salaber 2013; Park and Roh 2019)

for the definitions and sources of the independent variables). A potential variable that could explain the cross-border M&A motives is R&D per capita of a home country, a proxy for the home country technological assets/R&D strength (strength of home strategic assets, e.g., Deng 2009; Meyer 2015). We measure this variable using the gross domestic expenditures on R&D, expressed as a percent of GDP data from the World Development Indicators since the year prior to the deal. The R&D data include both capital and current expenditures in the following four main sectors: business enterprise, government, higher education, and private non-profit. R&D covers basic research, applied research, and experimental development.

Another potential explanation for M&A motives is related to home country size (Rabbiosi et al. 2012), which could also be potentially related to the effects of country pride (Hope et al. 2011). We therefore include the GDP variable for the acquirer (home country), measured in constant USD (World Bank). We also consider the effects of change in GDP ten year prior to the deal. This indicates potential effects of rapid economic development in emerging markets on the M&A motives (e.g., Elia and Santangelo 2017). We also consider the effects of policies for promoting outward FDI. We construct a variable measuring the number of years since the establishment of an outward FDI promotion agency in the home country, based on UNCTAD (2015) and secondary research of OFDI agency websites in the Asia-Pacific home countries in our sample. Additionaly, we considered several country-level dummy variables as controls, based on the extant literature, including legal origin (La Porta et al. 1998; Nicholson and Salaber 2013), language origin, and shared language (Globerman and Shapiro 2003; Arora and Fosfuri 2000; Kedia and Reddy 2016). We also included firm- and deal-specific control variables including dummy variables for acquirer and target that are publicly listed firms (Nicholson and Salaber 2013); M&A type based on the final acquirer stake after the deal (Xie et al. 2017; Chun 2009; Gaffney et al. 2016; Wu and Deng 2020); and industry relatedness (Nicholson and Salaber 2013; Park and Roh 2019). We have also considered several other control variables such as corporate tax rates (Haspeslagh and Jemison 1991; Nguyen et al. 2012) but excluded them from the analysis because they were highly correlated with other control/independent variables and had high variance inflation factor values that would indicate multicollinearity.

Table A4. Correlation table and summary statistics.

Variables	(1)	(2)	(3)	(4)	(5)	(6)	(7)	(8)
(1) Regulatory quality—Rank	1
(2) Voice Accountability—Rank	0.59 ***	1
(3) Regulatory Quality—Estimate	0.99 ***	0.58 ***	1
(4) Voice Accountability—Estimate	0.56 ***	0.99 ***	0.55 ***	1
(5) R&D/GDP	0.43 ***	0.30 ***	0.35 ***	0.28 ***	1
(6) GDP	−0.41 ***	−0.18 ***	−0.47 ***	−0.19 ***	0.50 ***	1
(7) GDP change	−0.59 ***	−0.68 ***	−0.55 ***	−0.70 ***	−0.41 ***	0.19 ***	1
(8) OFDI Agency	−0.10 ***	−0.10 ***	−0.03	−0.06 *	−0.56 ***	−0.53 ***	0.08 **	1
(9) Shared Language	0.14 ***	0.19 ***	0.18 ***	0.18 ***	−0.29 ***	−0.34 ***	0.04	0.22 ***
(10) English	0.12 ***	0.27 ***	0.21 ***	0.27 ***	−0.65 ***	−0.66 ***	0.10 ***	0.50 ***
(11) French Law	−0.10 ***	−0.05	−0.11 ***	−0.04	−0.17 ***	−0.10 ***	0.03	0.10 ***
(12) Acquirer Public	0.07 **	0.17 ***	0.04	0.17 ***	0.24 ***	0.13 ***	−0.22 ***	−0.11 ***
(13) Target Public	−0.01	−0.01	−0.02	−0.01	0.11 ***	0.12 ***	−0.05	−0.10 ***
(14) 100% Acquisition	0.08 **	0.03	0.06 *	0.04	0.09 **	0.05	−0.11 ***	−0.05
(15) Minority Acquisition	−0.06	−0.08 **	−0.07 *	−0.07 *	0.05	0.05	−0.03	−0.06
(16) Industry Relatedness	−0.07 *	0	−0.07 *	0	−0.06	−0.01	0.05	0
Mean	75.22	65.4	0.92	0.52	1.99	28.07	2.49	26.26
SD	24.01	26.66	0.93	0.9	1.02	1.23	1.27	11.83
Min	34.62	4.69	−0.47	−1.72	0.12	25.44	0.92	4
Max	100	98.12	2.26	1.62	4.29	30.05	5.8	53
Variables	(9)	(10)	(11)	(12)	(13)	(14)	(15)	(16)
(1) Regulatory quality—Rank
(2) Voice Accountability—Rank
(3) Regulatory Quality—Estimate
(4) Voice Accountability—Estimate
(5) R&D/GDP
(6) GDP
(7) GDP change
(8) OFDI Agency
(9) Shared Language	1
(10) English	0.50 ***	1
(11) French Law	−0.05	−0.10 ***	1
(12) Acquirer Public	−0.09 **	−0.16 ***	−0.03	1
(13) Target Public	−0.07 *	−0.12 ***	−0.01	0.04	1
(14) 100% Acquisition	−0.01	−0.09 **	−0.06	0.19 ***	0.02	1
(15) Minority Acquisition	−0.06	−0.11 ***	0.01	−0.02	0.13 ***	−0.24 ***	1
(16) Industry Relatedness	0.01	0.03	0.04	−0.02	0.01	0.02	−0.09 **	1
Mean	0.24	0.56	0.01	0.49	0.02	0.29	0.12	0.76
SD	0.43	0.5	0.09	0.5	0.12	0.45	0.33	0.42
Min	0	0	0	0	0	0	0	0
Max	1	1	1	1	1	1	1	1

Note: *, **, and *** denote statistical significance at the 10%, 5% and 1% level, respectively.

provides summary statistics and a correlation table for all our independent and control variables. No pairs of variables exhibit a high correlation (other than estimate and rank versions of the main institutional variables and to a small degree the GDP change variable). We checked for potential collinearity problems by completing the variance inflation factor (VIF). None of the VIF values for our independent variables are above the threshold of 10 (none is over 6), thus collinearity seems not to be a problem (O’Brien 2007).

4.3. Estimation Strategy

To analyze the relationships between cross-border M&A motives and institutions over time, based on our hypotheses and theoretical framework, we perform a logistic regression analysis. We test Hypotheses 1a, 1b, 2a, 2b, 3a and 3b by performing regressions for each of the three main M&A motives and independent/control variables, including separate regressions for ‘rank’ (Table A5) and ‘estimate’ (not reported) measures of our key independent institutional variables—regulatory quality and voice and accountability. We include relevant country fixed effects and specifications with standard errors clustered by home country to account for within-country correlation, following Elia and Santangelo (2017). The dependent variable in all models is the likelihood of an M&A to have a specific motive (the three most commonly cited motives are ‘increase scale’, ‘cross-border/expand geographic footprint’, and ‘add products/expand offerings’). We also include ‘deal year’ in the models to test H2a and H2b. Finally, we include separate models with the interaction term between ‘deal year’ and ‘regulatory quality’ to account for the changes in the impact of regulatory quality on the motives over time (Models 4–6 in Table A5), consistent with our reasoning in Figure A1 and H3a and H3b.

Our dependent variable was given a value of 1 if the M&A had a particular motive, and a value of 0 if it did not. Accordingly, we performed binary logistic regression analysis to test our hypotheses. In order to select the most appropriate model, we initially followed Cui and Jiang (2012) and estimated baseline models including only the control variables. The models yielded Akaike’s information criteria of 465.9, 579.3 and 498.3, higher than respective AICs for models 1, 2, and 3 that included both our explanatory variables and all the controls that satisfied the independence conditions (AICs of 418.4, 567.3 and 483.6, respectively). This indicated an improvement in model fit over the baseline. Including interaction terms between regulatory quality and time (Models 4–6) further improved the AIC to 413.8, 565.9 and 481.7, respectively, resulting in even better model fit in these specifications (please see Table A5).

5. Results

Our analysis tests the hypotheses related to the differences of motives for cross-border M&As between countries from different institutional environments over time, with a focus on the impact of regulatory quality. Table A5 presents the results of logistic regressions for the three main motives in our sample using the percentile ‘rank’ measure of institutions. Models 1–3 are testing Hypotheses 1a and 1b (linked to the role of regulatory quality) and 2a and 2b (linked to the role of time), focussing on the impact of regulatory quality on specific motives (e.g., increase scale, cross-border/expand geographic footprint, and add products or expand offerings). The results are strong and significant, and Hypotheses 1a (for the increase scale motive) and 1b (for the expand offerings motive) are supported at 1% level. The insignificant coefficient on regulatory quality for the cross-border motive indicates that this motive might not be suitable for H1a (and the ‘traditional’ motives) or H1b (springboard motives).

The positive coefficient on regulatory quality (for the expand offering motive) suggests that, as regulatory quality increases, the likelihood of a particular ‘springboard’ motive being involved in the M&A also increases (Model 3). A higher quality regulatory environment has been linked to boosting the propensity for firms to invest directly across borders, including through M&As (Lebedev et al. 2015). The results presented in Table A5 (Model 3) appears to be consistent with the institutional fostering literature (Sun et al. 2015). One the other hand, the institutional escapism (Witt and Lewin 2007) perspective appears to be relevant for ‘traditional’ motive of ‘increase scale’, where the coefficient on the regulatory quality—rank is negative. These results indicate that both the effects of institutional fostering and escapism are at play for the M&A motives and home country regulatory quality. Results using the ‘estimate’ measure of institutions (not reported) are broadly consistent with those presented in Table A5, relative to a strong positive effect of regulatory quality on the ‘expand offerings’ (H1b supported at 1% significance level), although the result for the ‘increase scale’ motive is not statistically significant.

Interestingly, some evidence also exists for the association between voice and accountability in the home country and the three M&A motives. Although we did not initially expect this relationship and did not develop specific hypotheses for the impact of voice and accountability on M&A motives, the coefficients on this variable are statistically significant at 1% level Model 1, at 5% in Model 2 and at 10% in Model 3 (Table A5), with an opposite sign to the effects of regulatory quality. The negative effect on the ‘expand offerings’ and ‘cross-border/expand geographic footprint’ motives are also confirmed in models using ‘estimate’ measure of voice and accountability (at 5% and 1% significance levels, respectively). This suggests that institutional fostering and institutional escapism effects can work differently for various types of institutions. These findings extend the analysis of Hur et al. (2011) who found that voice and accountability had the strongest effect on M&A inflows among the other institutional indicators, with regulatory quality and government effectiveness also showing significant results (although their paper did not study the effects on various M&A motives, and did not acknowledge that the effects may be positive or negative depending on the motive type).

We have also tested Hypotheses 2a and 2b about the impact of deal year on the motives. Both of these hypotheses were supported at 1% significance level in all our models (in model 3 at 5% level). As predicted, all models presented in Table A5 show robust results for all three motives in terms of the effect of the deal year (and so do all the six models in the specifications with the ‘estimate’ measure of institutions). Consistent with H2a and H2b, for the three main motives and for both the developed and emerging acquirers, the tendency is that firms are more inclined to invest with ‘expand scale’ and ‘expand geographic footprint’ motives over time, while for both groups of acquirers, they are less inclined to invest with ‘add products/expand offerings’ motive over time. This result is consistent with the suggestions of Narula (2012) to consider the maturity and the evolution of the (motivations of) EMNEs over time when comparing them to AMNEs. However, our results extend the hypotheses and findings of Elia and Santangelo (2017) by pointing to different evolutions of various motives. While they focused on the strategic asset-seeking motive, our typology distinguished between the springboard and traditional M&A motives and different impacts of home country regulatory quality (not just of national innovation systems) on motives over time.

To confirm the effects of home country regulatory quality over time (Hypotheses 3a, 3b and Figure A1), we have also included an interaction term between home country regulatory quality and deal year (see Models 4–6). Regulatory quality remains fairly stable over the 10-year time horizon that we analyze (e.g., it rises from 1.98 to 2.16 between 2007 and 2017 in Hong Kong on a −2.5–2.5 scale, with the highest value of 2.19 in 2015 and lowest value of 1.78 in 2011). However, as we explained in our H3a, H3b and Figure A1 theoretical development, the impact of regulatory quality over time may change from institutional escapism to institutional fostering logic and vice versa, even with relatively stable institutions. Our results confirm these arguments. Including an interaction term for regulatory quality times deal year to the logit regression Models 1–3 does not change the sign or significance (it remains at p < 0.01) for deal year for any of our three main motives (refer to Models 4–6 which include the interaction effects between deal year and regulatory quality). The same result holds in the robustness checks conducted by using ‘estimates’ (scale of −2.5–2.5) of our institutional measures.

However, the coefficient of the interaction term between home country regulatory quality and deal year is positive and statistically significant (p < 0.05) for the expand offerings motive (with the sign on regulatory quality changing from positive significant in Model 3 to negative significant in Model 6). In other words, the inverse effect of higher regulatory quality on the propensity to invest with the expand offerings motive is not as inverse for more recent years. This can also be interpreted as regulatory quality initially affecting the expand offerings motive significantly and negatively (the initial institutional escapism effect of poor institutions leading to springboarding), and over time (in more recent years) positively (the institutional fostering effect captured in our H3b and Figure A1). This indicates that home country regulatory quality and the extent to which MNEs undertake M&As with springboard motives (e.g., expand offerings) have possibly evolved, consistent with the findings of Elia and Santangelo (2017), Cuervo-Cazurra (2012) and Meyer (2015) about the convergence in the patterns of internationalization of emerging and advanced country firms. The results for ‘expand offerings’ in Model 6 are consistent with the robustness check we performed using ‘estimate’ measures of institutions (at 10% significance).

Moreover, the significant negative result for regulatory quality’s impact on the increase scale motive (Model 1) changes to significant positive effect in Model 4, which includes the interaction effect between regulatory quality and deal year in the increase scale motive (p < 0.05). The significant negative interaction effect in Model 4 indicates that the positive effect of regulatory quality on the increase scale motive will decrease over time and that the positive effect of time on the increase scale motive will decrease as regulatory quality improves. This can also be interpreted initially as regulatory quality (in early years), affecting significantly and positively the increase scale motive and not very much or negatively over time. The results for the ‘increase scale’ motive in a model using ‘estimate’ measure of institutions are consistent with those in Model 4 (p < 0.01). The results for the ‘cross-border’ motive with the interaction terms (deal year, time, and regulatory quality) included (Model 5) change from insignificant in Model 2 to a positive main effect and negative interaction effect (similar to the ‘increase scale’ motive.) The mixed evidence for this motive (and the insignificant results in a model with the ‘estimate’ measure), confirm the suggestion that this motive cannot be considered as firmly ‘traditional’ or ‘springboard’, but perhaps is more associated with the ‘traditional’ motives (as was also evident in Model 2 results).

We have also conducted a robustness check with alternative models that yielded the highest precision of relevant coefficient estimates at the expense of omitting GDP, OFDI Agency and French Law control variables from Models 2, 3, 5, and 6. These additional models showed results consistent with our main models, but resulted in a higher significance for H1b (p < 0.01), H2b (p < 0.01) and H3b (p < 0.01). The Hosmer-Lemeshow goodness-of-fit test (Lemeshow and Hosmer 1982) for the main models presented in Table A5 shows satisfactory results. The test assesses the model calibration, which is the agreement between the observed and predicted risk, and insignificant p-values indicate satisfactory model calibration for Models 1–6. Finally, our control variables showed a positive effect of R&D/GDP (p < 0.1) on the increase scale and cross border motives, positive effect of GDP change on the expand offerings motive (p < 0.01), positive impact of English language on the cross-border motive (p < 0.01), positive effect of French Law on the increase scale motive (p < 0.01), and positive effect of the 100% Acquisition variable on the expand offering motive (p < 0.05). Meanwhile, the GDP of the home country had a negative and statistically significant effect on the increase scale motive (p < 0.01) but positive effect on the cross-border motive (p < 0.05), Shared Language had a negative effect on the expand offerings motive (p < 0.1), Target Public had a statistically strong negative effect on the cross-border motive (p < 0.01), Minority Acquisition had negative effect on the increase scale (p < 0.01) and the expand offerings motives (p < 0.05), and OFDI Agency had a negative and statistically significant effect on the increase scale motive (p < 0.01).

6. Discussion

First, our results show that regulatory quality and voice and accountability are important institutional factors to explain the motives for cross-border M&As. Hypotheses 1a and 1b have explained the links between motives and home country regulatory quality. This indicator measures the ability of the government of a country to formulate and implement sound policies and regulations that reduce risk and facilitate private sector development (Kaufmann et al. 2009). It considers exclusively the regulations on the private sector development. This indicator should be distinguished from the rule of law, which provides a further overall idea of the legal framework of a country in general, including issues such as property rights, contract enforcement, and the criminal system (Kaufmann et al. 2009). While definitions of the rule of law differ, we interpret it in line with Kaufmann et al. (2009) as ‘the extent to which agents have confidence in and abide by the rules of society, and in particular the quality of contract enforcement, property rights, the police, and the courts, as well as the likelihood of crime and violence’. Private sector development-related policies will affect the motives of a firm acquiring abroad regardless other ‘non-business’ statutes.

In general, our empirical results suggest that in addition to the features of the home country political system, including political (in)stability and corruption, it is important to consider regulatory quality and voice and accountability as factors underpinning M&A motives, adding to extant research (Dikova et al. 2016). By analyzing different types of cross-border M&A motives, we progress beyond the motives rooted in Dunning’s OLI paradigm to motives driven by the springboard theory (Luo and Tung 2018) and broader research on acquisition motives (Rabier 2017). We also find that M&A motives are not driven only by institutional distance in terms of corruption, political and cultural factors (Dikova et al. 2016) and location advantages of host countries (Dikova et al. 2019), but also by home country institutions, especially regulatory quality. We also extend the arguments of Hur et al. (2011) about the impact of voice and accountability on cross-border M&As by distinguishing between a different impact of this institutional factor on outward (not just inward) M&As with different motivations.

Second, our results suggest two important contributions to the theory of springboard MNEs (Luo and Tung 2018). In particular, our hypotheses were developed to extend the ‘strategic asset-seeking’ part of the springboard theory. In other words, the motivation for MNEs is to obtain critical capabilities from mature MNEs in advanced economies. We extended this concept with a more detailed account of springboard M&A motives and linked them to the literature on M&A motive to expand products and offerings. H1b and H3b results show that the regulatory quality of MNE’s home countries significantly influences domestic firms to obtain strategic assets via M&As (focused on adding products and offerings) and springboarding. Initially, low-quality home regulations encourage firms to seek for overseas strategic assets through M&As, that is, to expand their products and offerings. However, over time, MNEs appear to be less motivated in finding strategic assets despite still being driven by the same low-quality home institutional impact. This is consistent with the springboard theory which predicts that the springboard firms will gradually find a balance between continuing seeking strategic assets overseas and using the overseas assets to grow their home market dominance.

More specifically, this change in motivation may be caused by MNE’s own capability development over time (Luo and Tung 2018). In other words, our study has advanced the springboard theory by showing that in early stages of a company’s outward FDI, poor regulatory quality makes a firm want to ‘escape’ (Witt and Lewin 2007); however, later the firm realized that a ‘poor regulatory quality’ can improve in some respects and/or be exploited better by finding aspects of the regulations that promote M&As. Hence, the logic evolves in an ‘institutional fostering’ (Sun et al. 2015) that allows the company to continue internationalizing with more ‘traditional’ motives. This dynamic of motives also indicates that ‘institutional fostering’ and ‘institutional escapism’ logics do not co-exist in the context of home institutions and M&A motives (Witt and Lewin 2007). In addition, we must highlight that the logics of the joint impact of regulatory quality and time have different applications to ‘traditional’ and ‘springboard motives’, as indicated in Figure A1 and supported by our results with interaction effects of home country regulatory quality and deal year. However, the effects of ‘institutional fostering’ will diminish over time as the motives evolve from ‘springboard motives’ to ‘traditional motives’, consistent with our H2a/H3a and H2b/H3b.

Further, our reasoning from H2a, H2b, H3a, H3b and Figure A1 also enrich the springboard theory by showing that the springboard motives can evolve over time—from springboarding into more traditional ones. In other words, during the course of international operations, weak home regulatory quality gradually encourages firms to adopt more traditional M&A motives, namely increasing scale, as opposed to the springboard motives that drive initially MNEs to engage in M&As (e.g., expand products and offerings). This result contributes to our understandings on the dynamics of springboard MNEs, as our study links the springboard motives to MNE’s home country institutions and shows their significant dynamic relationships. Thus, our study adds an additional layer to the springboard theory, showing that home regulatory quality and time are two (interlinked) factors that can drive the springboard motives (e.g., add products/expand offerings) to evolve into traditional internationalization motives (e.g., increase scale). This is an important extension to the springboard theory as it shows a possible evolution of the springboard firms into more traditional MNEs. According to Elia and Santangelo (2017), the dynamics of various types of FDI and M&A motives over time must be considered. We explain in Figure A1 the impact of regulatory quality on different types of motives over time. This study also contributes to the springboard theory given that it does not adequately address the evolution of springboard MNEs in terms of when they will exit from the springboard path as they grow (Luo and Tung 2018).

7. Conclusions

In summary, this study focuses on the motives behind cross-border M&As. Our results show that regulatory quality in the private sector is an important governance indicator with a significant positive effect on the ‘expand offerings’ motive and significant negative effect on the ‘increase scale’ motive for cross-border M&As. We also found robust evidence for the effects of deal year on M&A motives. The evidence is positive for ‘expand scale’ and ‘expand geographic footprint’ motives, but it is negative for ‘add products/expand offerings’ motive. Finally, our results suggest that the impact of regulatory quality on cross-border M&A motives changes over time, but that the impact differs for ‘traditional’ and ‘springboard’ motives.

This study has important policy implications, as it acknowledges that policies, regulations, and their enforcement change over time and how such changes could affect the internationalization (M&As in particular) motives and strategies of the domestic firms. Kumar (2007) and Buckley et al. (2007) both considered the changes in policy of India and China, respectively, at a similar time in the early 1990s. With the changes in attitudes toward a closer economic world, many emerging markets were introducing policies conducive to FDI and M&As, but a lack of experience of policymaking could affect the quality of their regulations. When assessing China, Buckley et al. (2007) and Luo et al. (2010) confirmed that economic transition with policy liberalization can lead to a greater amount of outward FDI. As countries have greater experience over time with creating regulatory environments conducive to outward cross-border M&As, the quality of regulations will potentially increase. Thus, our results on the significance of regulatory quality indicate that home country governments could concentrate on improving the quality and effectiveness of their outward FDI regulations to promote acquisitions abroad (Buckley et al. 2018).

Policy makers should also consider the nature and dynamics of motivations of MNEs from their countries, and realize that different types of institutions and institutional voids (Khanna and Palepu 2010) impact motives differently. FDI regulatory risk is receiving an increased attention from policy makers when it comes to host countries (World Bank 2020). However, it is also important to consider various forms and impacts of regulatory risk and volatility in home countries (Yin et al. 2021). Moreover, as indicated in our findings, firms’ M&A motives may change over time—springboard firms may be less interested in investing in strategic assets as they develop and evolve into more traditional MNEs. This could potentially be utilized by the policymakers to fine-tune their outward FDI policies by purposively promoting domestic firms to engage in the M&A projects that can also bring back strategic assets for national interests. This policymaking strategy has proven to be a crucial contributor for rapid economic development as seen in the experience of successful emerging economies such as China and Korea (Deng 2013; Luo et al. 2010). The latter has also been classified as an advanced economy in 2021 by the UNCTAD and its MNEs were dubbed to be neither emerging nor developed but ‘emerged’ (Lee et al. 2021).

In terms of managerial implications, our study suggests that managers considering M&As abroad need to take into account both the stage of the “upward spiral” their companies are in (in terms of internationalization stage) and the quality, nature and dynamics of the regulatory environment in their home countries. In particular, they can build their capabilities in navigating the volatility of their home country institutional environments and progress from “springboard” M&A motives (e.g., adding products, expanding offerings) to more traditional M&A motives (e.g., increase scale and expand geographic footprint) as they catapult their companies onto the global stage with stronger capabilities. Managers also need to recognize that the nature and role of home country regulations (such as China’s “Going Out” Policy) in strategy change over time with both firm growth and country development and political dynamics.

This study has the following limitations, which present opportunities for future research. The first limitation is that it focuses on home country factors when assessing motives for cross-border M&As. Deng and Yang (2015) found that government effectiveness in the host country has an impact on a firm’s responsiveness toward M&As. Moschieri and Campa (2014) highlighted regulations in Europe as an important factor for M&As, and this continues to be relevant with recent increased stringency of screening procedures for cross-border acquisitions (especially by Chinese acquirers) in the European Union and other advanced economies (Riela and Zámborský 2020). Hence, a future analysis could consider both home and host country effects on M&A motives (Baik et al. 2015) and various measures of distance including cultural distance (Jensen et al. 2022) and institutional distance and its directionality (Shirodkar and Konara 2017). Second, sub-national differences in institutions and their impact on M&A motives may also be explored (Li et al. 2020; Nayyar and Prashantham 2021). Third, the three motives that we used in our analysis could be also seen as overlapping, and further research is needed to distinguish specific M&A motives (Rabier 2017) and disentangle the microfoundations of M&A behaviors (Meyer-Doyle et al. 2019). Another limitation of our study is its relatively short time frame, which does not allow us to fully study institutional change, especially in the “new normal” not yet captured by our data (Ahlstrom et al. 2020). The last limitation is a limited use of firm-specific independent variables. Thus, firm-specific variables related to motives, management and performance of EMNE M&As are also an avenue for future research (Khanna and Palepu 2000; Yu et al. 2019).