Host country distance and unrealized cross-border merger and acquisition deals: perspectives from China and Russia Open Access

Globalization has led to a notable surge in scholarly investigations concerning emerging market multinational enterprises (EMNEs) originating from countries such as China, India, Brazil and Russia (Buckley et al., 2007; Deng, 2009; Kotabe and Kothari, 2016; Bhasin and Paul, 2016; Buckley et al., 2016; Paul and Benito, 2018; Gammeltoft and Panibratov, 2024). Cross-border mergers and acquisitions (CBMAs) by EMNEs from China and Russia represent a critical yet underexplored lens through which to examine how institutional asymmetries shape global strategic decisions. Although international business (IB) scholars have extensively studied institutional distance and EMNE internationalization (Kostova et al., 2020; Luo and Tung, 2007), the influence of distance – the ways in which institutional gaps between the home and host countries differentially impact deal completion for rumored deals – remains opaque, particularly for state-influenced EMNEs navigating politicized scrutiny (Panibratov and Klishevich, 2023).

Prior work assumes institutional distance uniformly impedes deals (Dikova, et al., 2019) and focuses primarily on post-announcement outcomes (Zhang et al., 2011). However, the pre-announcement stage, where rumors signal intent but deals often collapse, reveals how EMNEs anticipate and respond to host-country institutional barriers. This is especially salient for Chinese and Russian EMNEs, whose state ties and home-country institutional weaknesses (e.g. corruption and low economic freedom) trigger unique liabilities abroad (Child and Rodrigues, 2005; Cuervo-Cazurra, 2006). However, prior literature has not examined in detail how rumors of CBMAs can influence unrealized deals.

In this study, we focus on CBMAs from EMNEs. Previous research has found that only a small percentage of evaluated target firms are acquired (Muehlfeld et al., 2012; Wong and O’Sullivan, 2001), suggesting that many acquisition attempts are unrealized. As we understand it, only a few studies (Gubbi et al., 2010; Zhang et al., 2011; Dikova et al., 2016) have investigated the impact of home-to-host country distance on the realization of EMNE CBMA deals, and none specifically compared how institutional distance between Chinese and Russian EMNEs and their host countries affects the realization of rumored CBMA deals. We argue that analyzing rumored-but-unrealized CBMAs exposes strategic misalignment: EMNEs target institutionally distant host countries for asset-seeking or risk diversification, but face backlash when host-country norms (e.g. transparency and rule of law) clash with home-country practices. By comparing China and Russia, we disentangle how variations in state capitalism (e.g. China’s strategic asset-seeking vs Russia’s oligarchic diversification) influence institutional friction.

We argue that the internationalization and CBMA patterns of Chinese and Russian EMNEs will be different from those of Western MNEs. A distinctive feature of Chinese CBMAs is that the Chinese Government can be a potential shareholder of acquired firms, and host country constituents may be concerned about the consequences of this. Taking an institutional distance view (Kostova, et al., 2020), we theoretically justify comparing Chinese and Russian firms engaging in CBMAs because both countries have authoritarian regimes. These countries also share some similarities and differences in their political and economic systems, cultures and institutional environments. Chinese firms will pursue CBMAs to acquire strategic assets, including technology, brands and market access, while Russian firms will diversify their assets, reduce political risks and increase their bargaining power (Child and Rodrigues, 2005). Chinese and Russian firms may face different institutional and cultural challenges in their CBMA activities, such as government intervention, political risk, corruption levels and cultural distance, which may lead to different “deal realization” outcomes (Child and Rodrigues, 2005).

The financial literature generally explores how markets react to rumors (Yang and Chen, 2021), and a growing body of literature investigates how mergers and acquisitions can be influenced by rumors (Alperovych, Cumming, and Groh, 2016; Liu, 2021). Nevertheless, the IB literature neglects the impact of rumors on deal realization, as most CBMAs research focuses on the stage between a deal’s announcement and completion (Dikova et al., 2010).

Given the above, we make several significant contributions to address the abovementioned gaps. First, we examine the influence of institutional distance, comprising the regulatory and normative dimensions. We also investigate the degree of cultural distance between home and host countries and how they impact the realization of CBMAs that emanate from China and Russia after they have been rumored, then investigate how institutional distance can affect whether a rumored deal is realized or not. To do this, we study rumored CBMA attempts by Chinese and Russian EMNEs from 2003 to 2019, defining “unrealized deals” as publicly rumored but never officially announced or completed. We define a deal as realized only if the initial market rumor about the deal is later confirmed to be true, and there is an official public announcement of the deal’s closure. Rumors, hence, serve as a proxy for intent, while non-completion reflects institutional barriers. In the next section, we explore the literature around CBMAs.

CBMAs conducted by Chinese and Russian EMNEs have increased since the early 2000s; however, the volume of CBMAs has declined in recent years because of geopolitical tensions, which has led to increased regulatory scrutiny and risk aversion. There are multiple reasons why EMNEs may pursue CBMAs. Earlier studies (Taylor, 2002) found that Chinese firms pursue natural resources abroad. Similarly, Buckley et al. (2016) found that FDI from China often targets politically risky countries, indicating that Chinese investors exhibit a distinct approach to risk compared to their Western counterparts. Chinese MNEs will invest abroad to acquire strategic assets and overcome competitive disadvantages in their home country (Rui and Yip, 2008; Deng, 2009). Moghaddam et al. (2014) used Dunning’s (1988) typology to investigate a sample of Russian firms. They found that EMNEs will acquire resources, markets, technology and strategic assets. Dikova et al. (2016) found that Russian firms tend to invest in countries with better institutional quality, higher business freedom and a greater respect for property rights. The likelihood of deal completion increases when host countries have stronger business freedom and property rights protections than Russia (the home country). Other studies, such as Dikova et al. (2019), have examined motives for Russian CBMAs, with some reasons being that they can gain more market power and control and ensure less dependence on the home market. A larger market size and access to resources in the host country may also be influential (Roh et al., 2024). Furthermore, Russian firms might be influenced by a greater number of “strategic assets” available in the host country or may even be motivated by greater efficiency-seeking, such as cheaper labor costs.

The level of institutional distance between the home and host countries can impact whether CBMAs are realized. Dikova et al. (2019) found that the greater the distance between the home and host country, the less likely the CBMA would occur, indicating a negative association between institutional distance and the number of completed Russian CBMAs. Anti-trust and M&A legislation, as well as a lack of understanding of the rules and regulations, and the culture in a host country, could also be reasons for failed CBMA deals after they have been rumored. For Chinese and Russian EMNEs, operating within the institutional environment of a developed country may increase internationalization costs. The greater the institutional distance, the greater the complexity of the CBMA and, hence, the higher the cost and a greater chance of an unrealized deal (Sun et al., 2021).

To understand whether institutional distance influences whether CBMA deals are realized after a rumor has been made, it is essential to understand how a CBMA might occur. As presented in Figure 1, during the pre-announcement stage, before a deal is announced, parties to a deal will begin to initiate the transaction process. At this stage, the proposal for the CBMA is discussed, negotiations occur, and an auction takes place. The acquiring company also conducts due diligence. At any point during this pre-announcement stage, rumors can arise.

Rumors are ungrounded public information that is difficult to verify (Kosfeld, 2005; Yang and Chen, 2021). Not all rumors on financial markets are informative (Chou et al., 2015), and some are intentionally made to mislead or manipulate the market. Rumors can be disseminated by anyone who has access to that information, including insiders such as directors or senior managers, as well as outsiders such as professional investors or financial journalists (Liu, 2021). Notwithstanding the nature of rumors, whether they are fake from the beginning or reveal the company’s real intentions, research demonstrates that if an M&A is rumored, then it is more likely to result in a failed deal (Alperovych et al., 2016). Herein lies why a deal may be rumored to negatively affect the realization of a deal.

Considering the influence of institutional distance, a rumored or publicized deal may face local backlash from community groups or the government, which suggests that understanding the influence of institutional distance is important (Dikova et al., 2010). Shareholder backlash against a proposed deal from the target company could also pose a problem, causing investors to sell their shares because of perceptions of Chinese or Russian acquirers, potentially triggering a special meeting by the Board of Directors (Liu, 2021). Here, the Board of Directors discuss the effect of the proposed deal and subsequently abandons it at a later stage. CBMA deals are typically characterized by significant complexity and uncertainty, as they often involve navigating major procedural and regulatory hurdles. CBMAs must comply with domestic and international regulations, such as anti-trust laws and procedures for CBMA evaluations (Dikova et al., 2010). Governments try to prevent market dominance by regulating CBMA deals through anti-trust legislation (Finkelstein, 1997). Deals may be subject to regulatory scrutiny induced by bureaucratic self-interest, political extraction and private benefits such as protecting local firms, which could negatively affect the realization of those deals.

Prior literature reveals that institutional distance can negatively affect business performance when a firm internationalizes to an institutionally distant host country (Kostova et al., 2020). Dikova et al. (2010) examined the likelihood that CBMAs will be completed after an announcement and found that differences in formal and informal institutions have an impact. Attah-Boakye et al. (2020) found that withdrawals tend to increase when the economic freedom/quality of the legal environment in the acquired firm’s country is lower than that of the acquiring country. This may occur when financial markets are underdeveloped, there is a lack of legal regulations or property rights, and government intervention is elevated. Reasons why CBMA deals could be unrealized may stem from differences in corruption, cultural differences, institutional heterogeneities, political clashes between countries and low levels of property rights in the acquired firm’s country (Du et al., 2021). Other reasons include erratic behavior by government agencies, ruling-party interventions and regulatory hurdles, such as stringent merger conditions, nationalistic sentiments, political, legal and economic instability, as well as weak institutional frameworks (Zhang et al., 2011). Significant differences in national culture between the home and host countries may also influence the success of deal completion (Rottig, 2015). CBMA partners need cultural sensitivities to resolve incompatibilities (Dikova et al., 2010). The above research highlights a strong case for why CBMA deals could be abandoned after a rumor has been made because of institutional distance. However, we still lack an understanding of whether institutional distance affects the realization of CBMA deals during the pre-announcement stage, when such deals have been rumored. Furthermore, no prior research exists on the realization of rumored deals from countries that score lower on institutional quality than the host location.

Prior studies on the CBMA behavior of firms from various countries have found that CBMA deal completion is more successful in institutionally distant countries, especially when host countries have stronger and more transparent institutional structures (Dikova et al., 2016). This finding conflicts with the distance hypothesis that CBMA deal completion will be unsuccessful in institutionally different countries. Developed markets offer access to advanced technologies, knowledge and many other advantages that home markets may lack (Elango and Pattnaik, 2011), such as larger markets, access to technology and companies with ownership advantages.

Given the variation in previous studies and the fact that most studies have not considered the influence of distance on unrealized deals after they have been rumored, we now proceed to our hypothesis development.

In this study, we use institutional theory to help frame our hypotheses. The three dimensions of institutional theory are regulatory, normative and cognitive (Scott, 2002). Regulatory institutions comprise the rules and laws governing each country. Regulations may be more restrictive in some nations and less so in others, and they may also be more exhaustive, clearly presented and better enforced in some nations (Chao and Kumar, 2010). The normative dimension refers to informal ways of doing things, such as using relationship-based networks or engaging in corrupt practices to achieve goals (Chidlow et al., 2021), whereas the cognitive dimension refers to the conceptual beliefs, mental models and shared meanings among individuals (Powell and DiMaggio, 1991).

We chose China and Russia because they share some similar characteristics, such as being governed by authoritarian regimes. Both countries score moderately on business/investment freedom (Heritage Foundation, 2021), meaning their CBMA deals face institutional distance in either direction. However, their asset-seeking motives (e.g. technology and brands) make acquisitions in more regulated host countries more common and prone to failure because of higher adaptation costs. Informal practices in China and Russia (e.g. guanxi and blat) further complicate deals in more formal economies. As the institutional profiles of the home countries share some similarities yet have some differences, we test whether the impact of host country institutions on CBMAs realization will also be similar or different.

Prior research has acknowledged that institutions vary in quality across countries (Shleifer, 2000), including aspects such as business and investment freedom. According to Luo, Xue and Han (2010), EMNEs face disadvantages in the global business environment compared to firms in developed markets because they are viewed as latecomers. The institutional environment in China and Russia is less developed than that of advanced economies, implying that the Chinese and Russian MNEs face an institutionally distant environment. Thus, transaction costs are increased because of information asymmetry. Furthermore, stakeholders may have a negative view of CBMAs coming from countries where business and investment freedoms are lower than those of the host country, and stakeholders might attempt to derail a deal after it has been rumored. Hence, we hypothesize that CBMAs are more likely to be unrealized when host countries have significantly higher economic and investment freedom than the acquiring firm’s home country (China or Russia). This is because firms from restrictive environments face higher adaptation costs and stakeholder resistance in host markets with stronger regulatory institutions. Conversely, deals targeting host countries with lower economic freedom than the home market are less common, as such markets typically lack the strategic assets (e.g. technology and brands) that motivate Chinese and Russian acquisitions. Furthermore, well-developed institutions might support the market and facilitate a greater number of new entries into the market (Peng, 2003), thereby increasing the level of competition (Miller and Eden, 2006), which may make “realizing” a deal unviable. Accordingly, we derive the following hypotheses:

IB research often examines the occurrence of Western firms entering corrupt countries, which can be regarded as a tax for a foreign firm (Mauro, 1995; Sun et al., 2021). We classify corrupt conditions as a normative element of society (Selznick, 1948), and corruption encompasses bribes to government officials and transaction costs resulting from poor contract enforcement (Fisman, 2001). However, what happens when EMNEs from corrupt countries, such as Russia or China, attempt CBMAs in countries that are not corrupt? We argue that EMNEs target less corrupt host countries for strategic assets but face backlash because of home-country institutional legacies. At the same time, these markets will have lower levels of corruption. We propose that after a rumor of a CBMA from a more corrupt country, there will be shareholder and stakeholder backlash, leading to the rumored deal being unrealized. We justify the testing of separate hypotheses based on the differing corruption scores of China and Russia as reported by Transparency International (2024). Specifically, China has a score of 43, ranking 76th out of 180 countries, whereas Russia scores 22, ranking 154th (Transparency International, 2024). These figures indicate that Russia experiences significantly higher levels of corruption compared to China, whose corruption is comparatively more moderate in nature. We test whether there will be higher levels of unrealized CBMAs, after rumors in countries that have lower corruption levels than China or Russia, reflected in the following hypotheses:

Taking a cultural-cognitive perspective, prior research suggests that the cultural distance between the home and host countries can impact the success or failure of CBMA deals (Dikova et al., 2019). Cultural distance can influence:

• learning and synergy stimulus;

• potential competency and knowledge transfer; and

• the transaction costs resulting from intercultural contact and geographic diversification (Stahl and Voigt, 2008).

MNEs can generate value by capitalizing on assets from distant cultures, leveraging their ability to overcome and capitalize on this cultural distance. Morosini et al. (1998) argue that when there is greater cultural distance between two countries, the management styles, practices and corporate values will differ, which can cause cultural shock and conflicts that impede the realization of CBMA deals. Hagendorf and Voss (2010) argue that a lower cultural distance between merging parties has a positive influence on the value of the shared intangible assets and, by contrast, a higher level of cultural distance results in higher transaction costs, which can further hinder the transfer of competencies and, thus, reduce the value of CBMA deals. Reus and Lamont (2009) also emphasize that cultural distance integration costs can increase post-merger integration challenges, particularly in decision-making processes and leadership alignment, further complicating the realization of synergy. Rottig’s (2015) meta-analysis of cultural consequences for CBMAs finds that cultural differences do indeed have a significant and negative impact on the success of CBMAs.

Furthermore, Ahern et al. (2015), in their analysis of 20,893 cross-border mergers from 52 different countries from 1991 to 2008, found that culture had a significant and economically meaningful effect on the volume of CBMAs. They found that the greater the cultural distance between the acquiring and acquired countries, the lower the volume of mergers that occur (Ahern et al., 2015). Considering the above, firms generate value by capitalizing on assets from distant cultures, leveraging their ability to overcome and leverage this cultural distance. More recently, Weber et al. (2021) highlighted that cultural distance affects deal volume and post-merger performance, with firms from culturally distant countries experiencing lower long-term shareholder returns because of misaligned organizational practices. We argue that cultural differences make it hard for acquiring and target firms to gain common ground, which is necessary for successfully realizing a CBMA deal. Based on this argument, we derive the following hypotheses:

To test the hypotheses, we examined a sample of 357 deals from Chinese firms and 527 CBMA deals from Russian firms that were targeted toward a range of host countries ( AppendixTable A1), covering the period from January 2003 to December 2019. This period was selected because there were no CBMA deals in these countries prior to 2003. We assume that the period of 17 years is appropriate for identifying common trends and differences. Thus, we limit the study to 2019. We focus our analysis on rumored deals, which we define as “a news story in the media that identifies a specific company being for sale or an investor’s possible interest in acquiring a particular target firm” (Alperovych et al., 2016, p.3). Rumors can be initiated by insiders, such as senior managers or CEOs of the firm, or by outsiders, such as investment experts, financial journalists or professional speculators (Liu, 2021). Rumored CBMAs have been predominantly analyzed in the financial literature, where scholars aim to uncover the effect of rumors on stock returns. In contrast, the IB literature has largely neglected these events, particularly regarding the host country and the home country’s environment. CBMA rumors have not been thoroughly examined by scholars from the perspective of formal and informal institutions and their impact on the deal’s realization.

To conduct our research on CBMA deal realization, we use the Zephyr Bureau Van Dick (2015) database, a reliable source of data commonly used in IB research (Chittoor et al., 2015; Grimpe and Hussinger, 2014), which provides information about rumored deals. “Rumored deals” in the database means that there has been an unconfirmed report or an announced CBMA deal, and the identity of one of the parties is known. The report may appear in the press, a company press release or elsewhere, and the rumored date refers to the first mention of the deal, as far as Zephyr researchers can ascertain. In the database, there are also “rumored-withdrawn deals,” meaning that the parties involved in the rumor decide to discontinue negotiations or state that a deal will not go ahead. The final category is the “rumor-expired deal,” meaning that more than two years have passed, and the deal was not announced. If the rumored deal was announced, then it gets another status – announced, completed or completed-assumed.

In our research, we analyzed all rumored deals that were unrealized. We set a lower limit for acquisition at 10% of the stake, and we have not set a lower limit for the deal’s value, as we were interested in deals that had no financial impact on the market. The deal should also be new, so we eliminated all deals that stated an increase in share or capital increase. When the Chinese firm is the acquirer, we observe 357 rumored deals in 21 host countries in our sample. On average, 53% of all rumored deals were not realized, which is significantly more than in the case of Russia (33%). By the absolute number of rumored CBMA deals, most deals of Chinese firms were withdrawn in the USA (81), Australia (55), Germany (51), Russia (45) and the UK (43). However, the share of unrealized deals in foreign countries looks different. Indonesia had the largest share of unrealized deals with 77% of rumored deals not realized, followed by Russia (71%), France (66%), Korea (65%) and Italy (64%). In the USA, Chinese firms did not realize 50% of all rumored deals; in Australia, 40%; whereas in Argentina, the lowest share was observed at 27% (Table 1). The largest unrealized CBMA deal of Chinese firms was the planned acquisition (100%) of the French-based Alcatel-Lucent SA through ZTE Corporation, with a deal value of US$11.5bn. The second largest deal was the planned acquisition of 56.97% of the Korean-based Woori Bank through Charlye Group LP, with a deal value of US$7.5bn. The third largest unrealized deal was the acquisition (majority stake % unknown) of an Unnamed Brazilian Iron Ore Company through Hebei Iron and Steel Group Co., Ltd., with a deal value of US$6bn (Table 2).

When the acquirer firm comes from Russia, we observed 527 unrealized deals in 32 host countries. On average, 33% of all rumored deals were not realized. By the absolute number of rumored withdrawn/expired CBMA deals, Ukraine forges ahead of other countries with 90 deals, followed by Belarus (54), Kazakhstan (33) and Germany (31). However, by the percentage of unrealized CBMA deals, Hungary leads with 60%, followed by India (58%), Australia (56%), Bulgaria (47%) and Poland (43%) (Table 1). The largest unrealized CBMA deal for Russian firms was the planned acquisition (100%) of the Finnish-based Neste Oil OYJ by oil MNC Lukoil OAO, with a deal value of US$9.3bn. The second biggest unrealized deal was the planned acquisition of 51% of Turkish-based Turpas-Turkiye Petrol Rafineri, with a deal value of US$8bn. The third largest unrealized deal was the planned acquisition (100%) of the Ukrainian-based Kyivstar DZH ES EM ZAT through Vympel-Kommunikats II OAO, with a deal value of US$5.5bn (Table 2).

In the following sections, we describe the selected dependent variable, a set of key explanatory variables and a set of chosen control variables. The variables are selected based on the theoretical analysis of the existing literature and the hypotheses developed. Table 3 provides a summary and overview of all variables, their proxies and data sources.

According to the theoretical framework, the variable of interest is the counted numbers of unrealized (rumor-withdrawn, rumor-expired) CBMA deals of Chinese and Russian EMNEs in country X in year Y.

In line with the developed hypotheses, we selected a set of explanatory variables that reflect regulative, normative and cognitive institutional dimensions. At the country level, we test the Economic Freedom Index, performed by The Heritage Foundation each year. This indicator represents the regulatory dimension of host country institutions. We use the Corruption Perceptions Index, created by Transparency International (2024), as a measure of normative institutional dimension. The distances between the host and home countries were calculated as the differences between the Economic Freedom Indicators and CPI in both countries for each year of the research period. The formal institution and corruption distance variables are directional, meaning that the value will be positive in the cases of CBMA in markets with more developed institutions. Thus, we have negative values of the CPI (corruption) and EF (economic freedom) variables in a few cases in Russia’s sample (e.g. Ukraine, Uzbekistan and Azerbaijan) and a few cases in China’s sample (e.g. Kazakhstan, Russia and Indonesia).

We choose cultural distance as a measure of cognitive institutional dimension. The indicator for cultural distance was calculated using Kogut and Singh’s (1988) formula, which is widely used in internationalization studies (Habib and Zurawicki, 2002). Cultural distance is measured using Kogut and Singh’s (1988) index, capturing disparities in power distance, individualism, masculinity and uncertainty avoidance. Unrealized deals are often driven by integration challenges, including misaligned management practices. The formula allows a calculation of an index that bunches together the four dimensions of culture (Hofstede, 1980): power distance (PDI); individualism (IDV); masculinity (MAS); and uncertainty avoidance (UAI). The data was cropped from Geert Hofstede and Gert Jan Hofstede’s online website (Hofstede, 2020).

For the control variables, we use the GDP growth rates of the host and the home country.Kobrin (1976) and Nigh (1986) showed that the classic reason for FDI is the search for new markets and that FDI positively depends on the economic potential of a host country, which can be measured by GDP growth.

In addition to GDP growth, we also control market attractiveness with GDP per capita. According to Grosse and Trevino (1996) and Wells and Wint (2000), GDP per capita significantly explains FDI. A high GDP per capita indicates a high consumption potential in the host country. The GDP and GDP per capita data were collected from World Bank National Accounts data and OECD National Accounts data files (World Bank, 2015). Another control variable – geographical distance – was also used, a widely accepted control variable for the CBMA deals testing (Ragozzino, 2009; Ghemawat, 2001).

Our empirical analysis is based on two data sets representing the number of unrealized CBMA deals of MNEs from China and Russia. The most suitable model for measuring the number of occurrences or counts of an event is the negative binomial regression. We use panel negative binomial regression that draws attention to the quality of host country institutions and institutional distance between the host and the home country; its impact on unrealized CBMA deals that we use to test our hypothesis is as follows:

The response variable μ represents the number of events in the host country i in year t. rs β₀, β₁, β_2,[…] β_p represent the population regression coefficients for the explanatory variables X_1,i,t, X_2,i,t,[…] X_p. Integrating our variables (Table 3) into the basic model, the baseline specification of our model looks as follows:

where CBMA_i,t represents the counted number of unrealized rumored CBMA deals of Chinese or Russian firms in host country i in year t. The regressors CP_i,t indicates control of corruption in host country i in year t, EF_i,t indicates economic freedom in host country i in year t, CD_i indicates the cultural distance in host country i, GDPgrowth_i,t indicates GDP growth of host country i in year t and GDPgrowth_hc_i,t indicates GDP growth of home country i in year t.

Tables 4 and 5 show the descriptive statistics and standard summary of correlations between the Russian and Chinese country-level variables. The correlation between corruption distance and economic freedom distance is quite high, so we cannot test both variables in One model. Therefore, we tested several models, including One that combined corruption distance and economic freedom of the home country, and another that combined the host country’s economic freedom distance and corruption. Multicollinearity is not an issue in both models; VIF is less than 3.

Table 6 presents the results of the negative binomial regression model of counted CBMA deals of Russian and Chinese EMNEs. Overall, we can see that the results (p = 0.000) at the 10% significance level are statistically significant, and the models are supported.

The negative binomial regression model results provide insights into the factors influencing unrealized CBMAs involving Chinese and Russian firms.

For H1a and H1b, which suggest that CBMAs are more likely to be unrealized when host countries have higher business and investment freedom compared to the acquiring country, the findings do not support this claim. The variable of economic freedom in the home country is negative and highly significant (−0.325***) for China and (−0.258***) for Russia. This indicates that these deals are less likely to be unrealized when Chinese and Russian firms attempt CBMAs in countries with greater business and investment freedom. For both China and Russia, greater economic freedom in the host country improves the likelihood of completing CBMA deals, and larger positive EF distance values reduce the probability of unrealized deals. This does not align with the hypothesis that firms from more restrictive economic environments face greater challenges when expanding into freer markets.

The findings reject hypotheses H2a and H2b, which propose that CBMAs are more likely to be unrealized when host countries have lower corruption levels than the acquiring country. The CPI_distance variable, which measures the difference in corruption levels between the acquiring and target countries, is negative and significant (−0.373*) for China and also negative and significant for Russia (−0.328***). As CPI distance is defined as CPIhost - CPIhome, positive values indicate that the host country is less corrupt than China or Russia. In both samples, CPI distance has a negative and significant coefficient (China: −0.373; Russia: −0.328). This means that as host-country corruption decreases and the transparency gap widens in favor of the host country, the expected number of unrealized CBMA deals declines. Specifically, a one-unit increase in CPI distance reduces unrealized deals by approximately 31% for Chinese firms and 28% for Russian firms. Thus, Chinese and Russian EMNEs are more likely to complete acquisitions in cleaner, less corrupt institutional environments, where due diligence, compliance expectations and governance requirements are more predictable and less distortionary. Please see Figure 2 for a plot graph of this relationship. These graphs illustrate relationships between unrealized deals and CPI distance, and we can see that the most unrealized deals are present in countries which are more corrupt than Russia or China (negative CPI distance), whereas the least unrealized deals are present in countries that are least corrupted despite the larger institutional distance.

For H3a and H3b, which propose that greater cultural distance between the acquiring and target countries increases the likelihood of unrealized CBMAs, the results strongly support this claim. The cultural distance variable is positive and significant for Chinese (0.008***) and Russian (0.005**) firms. This suggests that as cultural differences between the two countries increase, CBMA deals become more difficult to complete, likely because of integration, management and operational alignment challenges.

Overall, the findings provide strong empirical support for the cultural distance hypothesis. Higher economic freedom and lower levels of corruption in host countries are associated with fewer unrealized CBMA deals by Chinese and Russian firms, indicating that transparent and market-oriented environments facilitate successful deal completion. At the same time, greater cultural distance increases the likelihood of unrealized transactions, underscoring the cultural and institutional barriers that shape the international expansion strategies of EMNEs from China and Russia. Figure 3 visually summarizes the hypothesized and empirically tested relationships between institutional distance dimensions (economic freedom, corruption and cultural distance) and the likelihood of unrealized CBMA deals for Chinese and Russian firms. Cultural disparities can act as barrier to CBMA completion for Chinese and Russian firms, with similar patterns observed for both countries despite slight differences in significance levels. However, our findings indicate that for corruption-perception distance and economic freedom distance, the key factor is the host country’s governance quality and transparency, not the distance per se.

We have compared probability values to test the effect of the coefficient for each model (p-value). We found that the probability value of the cultural distance variable in China’s model is higher than in Russia’s model. In contrast, the probability value of corruption distance is higher in Russia’s case. This can be explained by a lower index of corruption perception in Russia than in China; thus, we see the stronger effect of this distance. The same can be applied to formal institutional distance, which shows a high significance in Russia’s case and insignificance in China’s case. This means that the EF distance in China’s and Russia’s models does not vary significantly (16,1 and 14,6, respectively); however, this highlights the importance of this factor for Russian EMNEs. One possible explanation could be that Chinese firms have better learning capabilities or a more extensive international experience compared to Russian ones. However, this assumption requires further elaboration and testing.

We conducted a robustness test verify the reliability and validity of our analysis. First, we included an alternative dependent variable – the percentage of unrealized CBMA deals – and tested the model using a Tobit regression analysis. The results are presented in Table 7.

The table presents the results of a robustness check using a Tobit regression model, which is commonly applied when the dependent variable is censored or has limited values. The analysis examines two models: Model 1 (China) and Model 1 (Russia), assessing the influence of several independent variables on the dependent variable. Key explanatory variables include cultural distance, economic freedom distance (EF_distance), corruption perceptions index distance (CPI distance), corruption index at home (CPI home), economic freedom at home (EF_home), GDP growth in the host country (GDPgrowth_host) and geographical distance (LnGEO_distance).

The results reveal several statistically significant relationships. In Model 1 (China), EF_distance has a significant negative effect (−1.12**), indicating that greater economic freedom distance is associated with a reduction in the dependent variable. Similarly, CPI distance shows a significant negative impact in Model 1 (Russia) (−5.62**), indicating that a greater disparity in corruption perceptions between home and host countries negatively influences the outcome. In addition, EF_home also has a significant impact (−4.66**), indicating that economic freedom has a negative influence on the outcome. The constant term (Cons) is significantly positive in Model 1 (Russia) (210.3**), indicating a strong baseline effect in that model.

The models demonstrate strong statistical significance, as indicated by the low Prob > Chi values (0.01 or 0.00). The sample sizes vary across models, with 253 observations for China and 391 for Russia. Overall, the robustness check confirms that corruption-related factors (CPI distance) and economic freedom (EF_distance, EF_home and GDPgrowth_host) play a crucial role in determining unrealized CBMA deals (the dependent variable). The differences in significance across models for China and Russia suggest potential country-specific effects, indicating that institutional and economic contexts influence the outcomes differently. We assume that formal institutional distance regarding the CBMA realization requires further investigation, and alternative measures of institutional distance should be tested.

Beyond just validating distance effects, we also show which distances matter most for which EMNEs. Chinese firms’ sensitivity to cultural differences reflects integration challenges in technology acquisitions; Russian firms’ sensitivity to corruption distance reflects host skepticism toward oligarchic capital. We contribute to the literature by demonstrating that institutional distance affects how EMNEs behave in foreign markets regarding CBMAs and the realization of CBMA deals. Despite prior literature indicating investors’ behavior regarding rumored deals (Chou et al., 2015; Kosfeld, 2005), we argue that environmental factors such as regulative, normative and cognitive institutions also play a role in the initial stages of M&A announcements. The study of Russia and China demonstrates that although both countries have similar and different institutional structure characteristics, they follow similar patterns regarding the realization of CBMAs. The study found that many rumored CBMA deals abroad remain unrealized. In China, this indicator was extremely high, 53%, compared to 33% in Russia. Institutional distance between the home and host country determines the number and percentage of unrealized deals, with similar patterns observed in both countries.

More specifically, more developed and transparent regulatory institutions in the host country are associated with a lower likelihood that announced CBMA deals will remain unrealized after rumors become public. Clear rules, predictable regulatory procedures and higher levels of economic freedom in the host environment facilitate due diligence, reduce information asymmetry and lessen the risks faced by Russian and Chinese acquirers. In such settings, potential backlash from local shareholders or stakeholders is also less likely to derail the transaction, as deals unfold within a more structured and transparent governance framework. Consequently, adhering to the “rules of the game” in advanced institutional environments does not hinder these acquisitions. Instead, it supports the successful completion of CBMA deals by Chinese and Russian firms. Regarding the CPI, the results are the same; the less corrupt the host country is, the smaller the number of unrealized deals, implying that deals in the least corrupt countries are more successful for Chinese and Russian firms. According to our argument, corruption is an additional tax on economic activity that can significantly harm initial plans and intentions. Our results show that even being familiar with a corrupt environment, Russian and Chinese EMNEs are more consistent with their strategic plans in countries that are less corrupt than them. This contradicts some scholars’ arguments that EMNEs originating in highly corrupt environments may not be as sensitive to high levels of corruption abroad; instead, they may be attracted to the environment and even take advantage of corrupt activities (Cuervo-Cazurra, 2006; Suchman, 1995).

We found that the greater cultural distance between the home and host countries impacted the realization of CBMA deals. For example, there were more unrealized deals in countries with a higher cultural distance between the home and host countries. This was apparent for both Russia and China. This finding supports prior meta-analytical research by Rottig (2015), which suggests that cultural distance can impact the success of CBMAs. To explain our findings, we suggest that the higher the cultural distance between the home and host countries, the more it may affect the negotiations of the CBMA deal once they are announced. For example, after a deal has been rumored, a higher cultural distance may impact the ability to communicate, relate and create synergies between the acquiring and acquired firms in the initial stages of the CBMA. As a result, cultural distance may become a significant barrier to completing a CBMA deal (Panibratov, 2017), leading to a higher number of unrealized deals.

The research had several limitations, including examining only two home countries, China and Russia. Future studies could examine CBMA deals emanating from other emerging markets to determine whether the findings remain true for other countries. On another note, we focused on unrealized deals by examining whether rumored deals were ultimately realized or not. The method of our study meant that we test our hypotheses on a macro-level – aggregating the data on rumored/announced deals at the country level, which does not allow us to control for firm-level indicators such as cumulative abnormal returns, which can point to the nature (true or false) of CBMA rumors (Chou et al., 2015). Thus, we cannot easily identify rumors intended to manipulate the market. In the future, studies conducted at the firm level of analysis can provide us with additional insights about a firm’s behavior during pre-announced CBMA deals. This research was conducted before the 2022 war in Ukraine and the subsequent economic sanctions. Future researchers are encouraged to examine CBMAs after 2022 to observe the impacts of this event on CBMA behavior emanating from Russia following the imposition of sanctions and embargoes. However, we focus on rumors, future work could integrate firm-level political ties (e.g. Chinese SOEs vs Russian oligarchs) to refine directional distance thresholds. We acknowledge that this new context can affect the CBMA behavior of Russian EMNEs. Hence, future researchers are encouraged to examine the influence of this critical event on CBMA behavior.

In this paper, we present several theoretical insights derived from our findings. First, institutional distance matters when Chinese and Russian firms seek to make decisions around CBMA decisions in foreign markets, suggesting that the competing institutional framework in different countries impacts CBMA decisions. Second, it was interesting to note that Russian and Chinese acquiring firms preferred to focus their targets on institutionally different countries, from the perspective of economic freedom and corruption. One possible explanation for this result is that corruption may not be the primary influencing factor. Rather, it could be the appealing characteristics of CBMA targets located in developed countries, where the rule of law is upheld and informal institutions, such as corruption, play a minimal role. Therefore, the influence of institutional distance does matter in this case. However, the influence of institutional distance and the failure of CBMAs may stem from the reluctance of host country organizations to be acquired by organizations with lower institutional quality (Wei and Wu, 2015). Similarly, rumored CBMAs may also be at risk of community backlash, especially from countries that score high on institution quality, and we shift the discourse from whether distance matters to how its directionality creates asymmetric barriers. For example, lower host-country corruption facilitates deal completion for both Russian and Chinese firms, but the effect is stronger for Russian acquirers, illustrating how home-country institutional legacies shape firms’ responses to host-country governance standards. Contrary to the expectations in the literature, the findings demonstrate that Russian and Chinese EMNEs are not attracted to corrupt or institutionally weak environments. Instead, their CBMA completion rates are highest in well-governed, transparent and market-oriented economies.

A few managerial implications arise from the study. First, one relates to the higher level of unrealized deals in countries that score high on economic freedom. One reason for failure may be the “distance hypothesis,” when these EMNEs try to effectuate deals in countries that are significantly different to their home country. To minimize the effect of unrealized deals, we suggest that Russian and Chinese EMNEs target countries similar to themselves in terms of economic freedom. At the same time managers in Russian and Chinese firms should prioritize acquisitions in cleaner, less corrupt host countries, as greater transparency and stronger governance environments significantly increase the likelihood that cross-border deals will be successfully completed (Fjellstrom et al., 2023).

Furthermore, rumored deals that are not realized may provide EMNEs with several future benefits for internationalization. A rumored deal may be a form of advertising and promotion that an EMNE is seeking to acquire a target; thus, dealers and companies looking for acquisitions could approach them with future opportunities. Similarly, attempting an acquisition in a foreign country can help build knowledge, learning and capabilities for future CBMAs or internationalization.

We contribute to the literature by identifying the institutional factors that influence the realization of CBMAs from the perspectives of China and Russia. China has garnered significant attention from scholars, whereas the foreign expansion of Russian EMNEs has attracted less attention. Also, host country factors have rarely been studied. Based on institutional distance concepts, we developed a set of testable hypotheses related to three institutional distance dimensions (regulatory, normative and cognitive). We tested them using a negative binomial regression model that highlights the quality of host country institutions and cultural distance, focusing on corruption and its impact on unrealized CBMA deals of EMNEs for deals that have been rumored. Based on the results, we conclude that the distance between home and host country institutions, in terms of economic freedom and corruption, has a substantial impact on the realization rate of CBMA deals for these Chinese and Russian EMNEs. Thus, better quality regulatory institutions (i.e. economic freedom and less corruption) do lead to the realization of CBMA deals in the host country for Chinese and Russian EMNEs. Another interesting finding is that cultural distance impacts a firm’s behavior, which leads to not realizing CBMA deals. EMNEs may underestimate the challenges of the host country’s environment, so they need more time to learn about the foreign environment.

There was no funding associated with this research.

This article contains no studies with human participants or animals performed by the authors.