The Effect of State Ownership on a Cross-Border Acquisition Wave

Abstract

More enterprises from developing countries are conducting cross-border acquisitions (CBA) in the global market. Inter-industry acquisitions take the form of waves, and the position in an acquisition wave has been confirmed to be related to acquisition performance in developed countries. This paper examines the relationship between state ownership and position in a CBA wave using a sample of Chinese firms’ CBA events from 2008 to 2019. This article also attempts to examine the moderating effect of the number of board members with overseas work experiences and educational backgrounds.

1. Introduction

Acquisitions generally occur in a pattern of waves—short periods of intense merger activity in an industry [1]. Prior studies have shown that the position of the merger and acquisitions (M&A) wave affects the acquiring firms’ performance [1] and profits. Over the past decades, most of the growth in international production has been achieved through cross-border acquisitions(CBA) [2]. However, scholars also have examined waves in domestic M&A in industries [3]. With the development of the international economy and trade, increasing numbers of enterprises are making CBA address its competitive disadvantages [4]. Consequently, more research into CBA is needed [5].

Most prior research has examined M&A waves in developed countries [1]. Most of the empirical studies of M&A waves at the industry level in transnational M&A (hereinafter referred to as CBA) have been conducted in the context of developed countries, where the overall institutional framework remains unchanged [6]. While global economic activity has slowed, emerging economies have actively expanded their M&A activities [7]. Compared to M&A in developed countries in Europe and America [8], there has been little research conducted in emerging markets [6].

As Zhu et al. [9] concluded scholars have continued to examine how the characteristics of a company influence its acquisition decisions, including acquisition experience [10], firm strategy [11], firm capital structure [11] and firm network attributes [12]. Previous papers focused on the analysis of the characteristics of the wave of enterprise M&A, not involving considerations of the company’s property rights. Our research question examines how enterprise ownership types influence the position of entering a CBA wave.

“Marketization” has been one of the most important social changes in China since 1992 [13]. China’s economic reform process has resulted in major changes occurring in the structure and management of work organizations. The core of this process is the marketization of state-owned enterprises(SOEs) [14], according to the three market-type standards proposed by Szelenyi et al. [15], during the transition from a planned economy to a market economy, the proportion of state intervention investment in total investment will be decreased.

After the 15th National Congress of the Chinese Communist Party adopted a policy of state-owned economic layout adjustment, SOEs began leaving strategic industries and general competitive fields and began turning to strategic emerging industries and the competitive landscape [16]. SOEs have become more competitive and have begun to exhibit more diverse strategies [17]. Additionally, China’s “going out” strategy encourages domestic enterprises to participate in the international capital market and invest abroad directly. This has helped Chinese enterprises achieve success in the process of internationalization [18].

Stearns et al. [19] determined that changes in the economic and political environment could create conditions conducive to a merger wave. Political capital exists in companies, especially in China state, where ownership affects corporate activities [20]. We consider that there is a difference in global business activities, such as CBAs, between state-owned and private enterprises. Is this difference the result of national policy changes?

According to SDC data (Figure 1), China’s CBAs have grown rapidly since 2008, forming a trend of CBA waves that affect China’s economy and relate to the internationalization of Chinese companies. Considering this institutional background, we examine the formation of CBA waves among Chinese enterprises.

In the process of societal reform and opening, China has gradually formed a basic economic system with the publicly owned economy as the main component developing together with a hybrid economy developing. Different types of Chinese enterprises (privately owned or state-owned organizations, collective hybrids, and joint ventures) are developing together with different ownership types [21]. Chinese enterprises can be divided into SOEs and private enterprises (including foreign enterprises). In the process of Chinese companies’ internationalization, the crucial role of SOEs in CBA is not questioned [22]. In China’s context, it is worthwhile to discuss how ownership types affect the position of Chinese enterprises entering a CBA wave.

Moreover, Ferrier [23] discussed the impact of the top management team’s characteristics on the enterprise’s competitive actions and Chen et al. [24] described the role of top corporate managers’ cognitive factors in firms’ M&A strategy and performance [25]. Examining the moderating impact of the number of board directors who have an overseas background on this process is one goal of this article.

2. Theoretical Background and Hypotheses

2.1. Enter the CBA Wave Position

The position of entering the M&A wave is related to the acquisition performance [1] or M&A-associated profits [26]. Prior studies have focused on the consequences of M&A waves but not their antecedents. To identify which firms can be early or late movers in M&A waves, researchers examined firm-level antecedents, such as firm size [6], structure [11], and resources [11] that affect the position.

Table 1. Literature review of the position of entering M&A waves.

Literature	Drivers of M&A Wave Entry Position
Harford [27]	Capital mobility allows industry M&A waves to propagate, while most of the activities in the cumulative wave of mergers are driven by the aggregation of industry-level merger waves.
Haleblian et al. [11]	The competitive dynamic Awareness-Motivation-Capability (AMC) model suggests that strategic orientation, structure, and resource base influence the entry position of companies into M&A waves.
Popli et al. [6]	Prior experience (with alliances), firm size, and international embeddedness of business groups influence the position of the firms’ CBA.
Ahern et al. [12]	Demonstrate how acquisition waves transfer across industries, starting from customers, traveling to close suppliers, and further expanding to distant industries. Show that the network of economic transactions helps to explain the formation and propagation of merger waves.

summarizes prior research into drivers of M&A wave entry positions.

2.2. Competitive Dynamics Theory

Since China’s Reform and Opening Up in 1978 and the implementation of the “One Belt, One Road” policy in 2013, the Chinese economy has become increasingly diversified through “go global” and “bring in” strategies. This has left Chinese firms facing a more volatile internal and external competitive environment than before. Thus, in response to uncertainty in dynamic markets, firms are likely to expand their resource pool and stabilize their market position through M&A [1].

Examining the antecedents of firms’ CBA activities is an important step toward understanding Chinese firms’ position within a CBA wave. However, most of the existing studies have focused on the impact of the timing of participation in the CBA wave on acquisition performance, while there was a lack of attention to the drivers that influence the timing of entry into the CBA wave. We approach the question by applying of the Awareness- Motivation- Capability (AMC) model of competitive dynamics. Based on Chen et al.’s [28] review and summary of competitive dynamics theory, we focus on strategic behaviors, such as the CBA activities of companies competing in a dynamic environment as follows.

Competitive dynamics theory explains competition among enterprises, which refers to the alternating situation of competitive attack and response [29]. Through analysis of the interactive process, the competitive dynamics theory focuses on the causes and consequences of behavior and reaction [30] and can anticipate competitors’ actions and adjust responses based on competitors’ actions and other business environment changes. Therefore, many researchers have demonstrated the applicability of the competitive dynamics perspectives to analyze the competitive behaviors of firms [11,28,31,32,33].

Building on the competitive dynamic perspectives, the importance of being an M&A early mover is that it is the initiator of the attack and is the beneficiary of the action’s outcome. Therefore, the competitive dynamics theory focuses on how the characteristics of firms can be early movers. Three vital organizational characteristics of AMC influence strategic actions. The model integrates the micro-behavioral and macro-organizational aspects of the strategy and links competitive dynamics to areas not previously explored in the literature [29]. Haleblian et al. [11] used the AMC model to study the factors at the company level that influence the large-scale strategic behaviors of leaders in a wave of industry M&A. Cui et al. [34] studied external and internal firm characteristics that drive firms’ intent to seek strategic assets by applying the AMC model. Following these earlier studies, we utilize the AMC model within the Chinese institutional environment to explore the position of different ownership types of Chinese companies within M&A waves. It is noteworthy that “State-owned enterprises (SOEs)” refers to the state ownership or control of a firm’s capital, and the government’s will and interests determine the behavior of SOEs.

2.3. Awareness-Motivation-Capability (AMC) Model

The three drivers encompassed by competitive dynamics: awareness, motivation, and capability can further explain the strategic behavior of firms. Moreover, firms with high AMC are better able to jump into the M&A wave and receive the strongest positive performance than firms with low AMC [11].

2.3.1. Awareness

A firm’s awareness reflects its ability to recognize and respond to the competitive environment, and firms with superior awareness can quickly identify growth opportunities and act first to seize the lead. Specifically, Brief et al. [35] proposed that cognition impacted corporate strategic decision-making. Ownership structure determines that private enterprises focus on maximizing profits, thus increasing the level of awareness of external exploration. Faced with a competitive environment, they are with a stronger sense of counterattack. Cui et al. [34] argued that private ownership is positively associated with seeking intent in CBAs. When more foreign competitors enter a domestic market, private firms are more likely to enter the international market earlier, increase their capacity utilization and improve returns of scale effects, thus enhancing a firm’s capabilities [36].

With policy protection, state policies support and protect SOEs, which leads them to be possibly unaware of environmental threats. The strategic decisions of enterprises are dominated by political and economic motivations, while the institutional environment constrains the environmental munificence of enterprises in emerging economies, such as China [4,37].

SOEs benefit from government contacts to gain access to financial capital and development resources, so the urgency to seek strategic assets overseas is not obvious [38]. Additionally, the government has issued numerous rules and regulations on outward foreign direct investment (FDI) by Chinese firms [4]. Each constraint reduces the likelihood that an organization can find and adopt an adaptive solution to specific competitive threats [39].

2.3.2. Motivation

Motivation encourages firms to quickly implement appropriate actions to increase the speed of acquiring vested interests. Private companies have greater motivation to adopt strategic actions through CBA. Compared with SOEs, private firms are not protected by policies and financial support, and they are more vulnerable to market volatility and foreign competition. It is, therefore, important for private companies to acquire strategic resources for survival [40]. Private enterprises in pursuit of international expansion can compensate for their competitive weaknesses arising from operating only in the increasingly competitive domestic market by seeking foreign investment via CBA with mature enterprises [41]. This is consistent with the imitation theory [42] and bandwagon effects [1,43]. Relatively free from political influence and constraints, they are willing to take risks in pursuit of strategic intent to improve their flexibility, profitability, market position, and long-term other strategic interests [38].

To prevent the outflow of state assets, SOEs tend to be more cautious than private companies in making overseas investments. Lin et al. [44] posits that enterprises in transition economies like China have undertaken multiple government objectives (such as economic development strategies, employment, social endowment, and social stability). This has led to a policy burden for SOEs. In the process of enterprise development, SOEs are less vulnerable to threats from external competition and are more likely to wait for national policy guidance rather than try to fill a competence gap [34]. As a result, they do not take excessive risks, such as CBA, in pursuit of interests.

2.3.3. Capability

Capability refers to a firm’s ability to take action with its resources. Private enterprises are probably more efficient in raising factor productivity, efficiently using their resources, and increasing their technological innovations [36] than SOEs. Private enterprises have greater operational autonomy than SOEs and are catching up quickly by hiring competent human resources managers and learning from foreign companies. As private companies pursue market economic interests, their interests will be affected by the decisions they make, which will be more in line with actual capabilities. Additionally, with the internationalization of the market, the deregulation of private enterprises has provided a new source for their merger activities [19].

Many prior studies have suggested that SOEs are inefficient in strategic decision-making because the performance of companies without political capital is better in the corporate governance [40,44,45]. The state as a shareholder often lacks effective supervisory incentives and capabilities, leading to widespread potential agency problems [46,47], as well as corruption and bribery [40]. State equity represents the corresponding rights and obligations of the state, which can often result in adverse reactions from host countries, such as ideological conflicts, national security threats, and M&A that exceed one’s capabilities and cause problems, such as unfair competitive advantages and other issues [48,49]. To comply with policies and obtain legitimacy, CBAs made by SOEs are likely to exceed the investment and management capability of the enterprise itself. The liability of the opaqueness of SOEs increases the difficulty of them doing M&A [50].

Hypothesis 1.

SOEs enter a cross-border M&A wave later than private enterprises.

2.3.4. Boards of Directors’ Overseas Backgrounds

Resource dependence theory (RDT) recognizes the influence of external factors on organizational behavior. Despite environmental constraints, managers can reduce environmental uncertainty and dependence through their experience [51]. Scholars have recently begun to examine the role of senior leadership in the M&A behaviors [9]. We used the definition by Hillman et al. [52] in this article that boards of directors serve two critical functions for organizations: monitoring management on behalf of shareholders and providing resources.

Ocasio [53] posited that decision-maker actions depend on what issues and answers focus their attention. Strategic decisions depend on how decision-makers use internal and external resources, with internal resources including human capital and external resources including external connections between organizations and organizational behavior [54].

Specifically, internal resources can influence the timing of entering the CBA wave. Internal resources, such as board members with overseas experience/education, use their experience to decide whether to enter the CBA wave and develop appropriate strategic plans to complete the CBA quickly and accurately [9].

Moreover, the connection between a company’s board of directors plays an essential role in the company’s investment decisions. The connection may be a subset of broader social and school ties among executives [55]. Schonlau et al. [56] found that companies whose boards were more closely aligned with other companies were more likely to make acquisitions. This implies that board members with overseas backgrounds may bring these types of networks (social and school ties) with them to overseas companies that may promote CBA.

First, in terms of awareness, board connections improve the flow of information and communication between companies, increasing each company’s knowledge and understanding of the operations and cultures of other companies [55]. Specifically, executives with overseas experience can minimize the cultural differences between the acquiring and the target firms when conducting CBA due to their understanding of the foreign cultural context and improve the company’s performance after CBA [57,58]. When faced with a dynamic environment, board members with overseas backgrounds are more conscious and potentially capable of formulating strategies with an international perspective. They are more likely to be willing to learn from foreign advanced technologies and practices. Thus, they are more likely to perceive and adapt to dynamic environments.

Second, from a motivation perspective, if executives have the opportunity and individual incentives to make changes, they may have a greater willingness to innovate and to successfully use their network and organizational resources to promote mergers [19]. The experience of studying or working internationally allows them to understand the needs of overseas markets, and the decision-making power of corporate strategy motivates them to use their capabilities to increase enterprise profit.

Finally, capability plays an important role in the board’s CBA decisions. Boards can take existing knowledge and skills and apply them to their tasks [59]. Diverse strategic experience among board members through their network ties should enhance their ability to contribute in turbulent environments [60]. Overseas study and work experience could provide professional advantages, increased management abilities, practical experience, global vision, and learning capabilities related to CBA. These facilitate establishing close ties with overseas companies to conduct CBA.

Furthermore, board members with overseas backgrounds may be better aware of the dynamic competitive environment, enhancing the firm’s motivation and capability to conduct CBA.

Hypothesis 2.

Board members’ overseas background positively moderates the relationship between SOEs and the timing of entering a CBA wave.

3. Research Methods

3.1. Data and Sample

We assessed CBA waves in China from 2008 through 2019, utilizing data from the China Stock Market and Accounting Research Database (CSMAR). The CSMAR contains firm-level information on Chinese companies’ CBAs and is more comprehensive than other databases. China began to implement the reform of its socialist market economy in 1994. However, from the existing data, it is clear that there were insufficient data from before 2008, and the waves formed lack clarity, as shown in Figure 1. Additionally, the data about company board numbers can be assessed since 2008 in CSMAR. Therefore, we decided to use this period to test our hypotheses.

The selection criteria of the sample were as follows: (1) the M&A announcement period was from January 2008 to December 2019; (2) this sample only included completed M&A transactions; (3) Chinese acquirers and non-Chinese target companies (because of the special economic system in Hong Kong, target companies included Hong Kong companies); (4) target companies included non-financial services because their asset structure is different from that of other industries and the stock market may react differently [11,61]; (5) the acquirer owned 51% or more of the target’s shares after the transaction was completed.

The above criteria produced a sample of 1507 completed acquisitions. Additionally, the methods of McNamara et al. [1] was followed to identify M&A waves. First, we limited wave periods to 6 years. Second, we validated a pattern of a more than 100% increase in the peak year over the first year and a more than 50% decrease from the peak year to the last year. Meanwhile, from the beginning year to the peak year should be within 3 years. In terms of the Securities Regulatory Commission (SFC) industry classification, eight industries showed industrial waves (

Table 2. Description of Wave Industries.

Industry Description (CSMAR)	Wave and Range	Total N	First Year N	Peak Year N	Last Year N
Electricity, heat, gas and water production and supply	2012–2017	16	1	5	2
Real estate	2014–2019	47	2	17	1
Construction industry	2013–2016	15	1	8	2
Transportation, warehousing and postal services	2015–2018	25	3	13	2
Wholesale and retail trade	2014–2019	55	6	13	4
Information Transmission, Software and IT Services	2014–2018	77	3	28	4
Manufacturing	2014–2019	664	62	150	80
Leasing and business services	2013–2015	14	3	7	4

).

This study focused on the manufacturing and information industries because they have the most significant waves. The wave from 2014 to 2019 is the most obvious, with as many as 741 firms. Therefore, we focused on analyzing CBA waves in the manufacturing and IT industry. See

Table 3. CBA Waves in IT and Manufacturing.

	2014		2015		2016		2017		2018		2019
Property	SOE	Private	SOE	Private	SOE	Private	SOE	Private	SOE	Private	SOE	Private	Total
IT Services	0	3	0	28	2	17	5	18	0	4	0	0	77
Manufacturing	13	49	29	97	31	119	27	101	7	111	12	68	664
Total	65		154		169		151		122		80		741

.

Since the share conversion between the owned subsidiary and the parent company in the transaction does not equal market transactions, we deleted all transactions with a transaction amount of 0. This left a total of 748 transactions. After deleting the transactions with missing data (e.g., target firms’ information only since 2013 and board oversea background information since 2008) and the cases of wholly-owned subsidiaries (a wholly-owned subsidiary is a company whose common shares are 100% owned by the parent company), we were left with two industries and a total of 666 transactions.

3.2. Description of Related Variables and Model Design

Variables

Dependent variable. The dependent variable is wave timing, which compares the position difference between private firms and SOEs in waves of CBA, and we calculated wave timing as “0” or “1”. When firms pursued CBAs from the beginning to the peak year, wave timing was coded as “0”. Wave timing was “1” if firms pursued CBA after the peak year of the wave.

Independent variable. First, we coded based on the property type of the company. Foreign, Sino-foreign joint ventures and small public numbers were all classified as private, with SOE = “1” and others = “0” according to CSMAR data. Then, to study the position of Chinese enterprises of different ownership in the wave of M&A, we analyzed the overseas M&A of state-owned and private enterprises divided in the CSMAR database. While CSMAR’s categorization can be regarded as a conservative definition without a specific standard for the division of state and private enterprises, we obtained a highly correlated coefficient by calculating the correlation between the proportion of the top ten shareholders of Chinese shares in the total share capital and in SOEs. We agree with the definition that a company is an SOE if the total state ownership is greater than the ownership shares of any other individual entity [50].

Moderator. To define the overseas backgrounds of board members, we used two types of overseas backgrounds: (a) the percentage of board directors with overseas experience/the acquiring firm board scale and (b) the percentage of board directors with overseas educational backgrounds/the acquiring firm board scale. The CSMAR data in this field began in 2008.

Control Variables. To control for alternative interpretations of the state’s ownership relative to CBA waves, we controlled for the age of the acquiring firm, the size of the acquiring firm, the prior performance of the acquiring firm, the year, the industry and the prior CBA experience. Additionally, the difference between the firm age was calculated by year and was natural logarithm transformed. This is because acquiring firm size could influence firms’ behavior, and regular firm size is the natural logarithm of the total assets of the acquirer 1 year before the CBA announcement [62]. Next, prior firm performance was measured using the ln-transformed with the firm’s return on assets (ROA) 1 year before the acquisition [22] in RMB. Furthermore, we set a year from 2014–2019 as a dummy variable, with only 2016 not omitted in the logit model. Additionally, we measured the company’s past experience by how many CBAs it has engaged in since 2018. Lastly, industry dummy variables were also set to control for structural differences between the industries included in the study.

3.3. Analysis

In this paper, the independent variable and controls were cross-section dimensions since the dependent variable (wave timing) was the time dimension. Thus, mixed data on different samples in multiple time dimensions are called pool data (mixed) cross-sectional data. The data were analyzed using the Stata MP logit model.

A multivariate Logit regression analysis was utilized, which employed the company property of Chinese firms that conduct CBAs as the explained variable. To obtain a robust standard error, we examined clustering adjustment by clustering the companies, assuming that the interference of different companies was independent of each other, while the interference of the same company in different years is related.

4. Results

Examining our control variables in

Table 4. Descriptive Statistics and Correlations.

Variables	N	Mean	Min	Max	(1)	(2)	(3)	(4)	(5)	(6)	(7)	(8)
(1) wave timing	666	0.49	0	1	1.000
(2) acquire firm age	666	2.71	1.39	3.87	0.124 ***	1.000
(3) acquire firm size	666	22.24	19.60	26.05	0.106 ***	0.267 ***	1.000
(4) acquire ROA	666	5.82	−77.47	49.64	0.038	−0.093 **	−0.060	1.000
(5) Industry	666	0.92	0	1	−0.003	0.044	0.135 ***	−0.025	1.000
(6) prior experience	666	1.88	1	10	0.087 **	0.121 ***	0.288 ***	−0.020	−0.123 ***
(7) SOE	666	0.17	0	1	−0.047	0.225 ***	0.401 ***	−0.140 ***	0.102 ***	1.000
(8) overseas experience	666	0.14	0	1	0.095 **	0.022	0.183 ***	−0.017	−0.075 *	−0.023	1.000
(9) overseas educational	666	0.15	0	1	−0.015	0.032	0.167 ***	0.043	−0.01	−0.046	0.516 ***	1.000

*** p < 0.01, ** p < 0.05, * p < 0.1.

, we found some evidence that larger and older firms move later in the wave. The correlations between SOE and wave timing were not significant linear relations.

We now examine the results of our hypotheses.

Table 5. Logit Cluster (Company).

	M1	M2	M3	M4	M5
Acquire firm age	0.682 ***	0.785 ***	0.778 ***	0.771 ***	0.784 ***
	(0.260)	(0.268)	(0.265)	(0.262)	(0.267)
Acquire firm size	0.160	0.263 **	0.244 **	0.290 ***	0.264 **
	(0.099)	(0.106)	(0.108)	(0.105)	(0.106)
Acquire ROA	0.021 *	0.019	0.016	0.017	0.018
	(0.013)	(0.012)	(0.012)	(0.012)	(0.012)
Prior experience	0.128	0.090	0.069	0.081	0.094
	(0.090)	(0.090)	(0.092)	(0.096)	(0.092)
Overseas experience	1.493 ** (0.698)	1.419 ** (0.694)	0.601 (0.594)		1.216 (0.753)
overseas educational	−1.357 * (0.735)	−1.451 ** (0.739)		−0.581 (0.622)	−1.229 (0.793)
SOE		−0.722 **	−0.758 *	−0.660 *	−0.704 *
		(0.332)	(0.397)	(0.380)	(0.400)
Overseasexp ∗ property			0.637 (1.265)		1.499 (1.939)
Overseased ∗ property				−0.750 (1.691)	−1.601 (2.106)
Industry	Included	Included	Included	Included	Included
Year	Included	Included	Included	Included	Included
Constant	−5.489 **	−7.834 ***	−7.411 ***	−8.211 ***	−7.846 ***
	(2.132)	(2.350)	(2.376)	(2.321)	(2.355)

* p < 0.1, ** p < 0.05, *** p < 0.01.

shows the coefficients, their standard errors, and associated p-values. According to logit regression models, M1 included the effects of all control variables on the CBA (wave participation timing); M2 examined the main effect of the independent variable on the CBA wave participation timing; M3 and M4 included the interaction effect to examine the moderating effect of the number of board members with overseas experience/education on the relationship between state ownership and wave participation timing; and all variables were added in M5.

As shown in Table 5, we believe that position and company property are negatively related. Therefore, the empirical results show that the SOE is in an earlier position in a CBA wave. Similarly, SOEs tend to move earlier in the wave. Moreover, in Model 2, this relationship is significant at the 0.05 (−0.722 **) level. Thus, Hypothesis 1 is rejected.

Some control variables in the tested model are also significant. This includes the coefficient of acquiring firm age at the 0.01 significance level, which was positive (0.785 ***). The coefficient of acquiring firm size at the 0.05 significance level was positive (0.263 **). The coefficient of acquiring the year 2016 at the 0.01 significance level was negative (−3.645 ***). The overseas work experience (1.419 **) and overseas educational background (−1.451 **) were also significant in model 2.

5. Discussion

This paper explores the Chinese corporate property factors related to the company’s position in the CBA wave. In contrast to previous strategic management work that has examined the consequences of a company’s actions in a wave [60], we focused on property, one of the unique drivers in China that influences the position of a firm entry into a merger wave. Based on the competitive dynamic framework, we identified that boards with members with overseas backgrounds would enable their companies to enter these waves earlier. This study aims to advance institutional theory with a competitive dynamic perspective and apply it to emerging economics CBA research. It provides some direction to the research questions “How about the CBA wave in China?” and “What factors cause the different positions of different ownership enterprises entering the CBA wave?” Existing research presents a gap in this field since the focus has been on firm-level factors and post-acquisition outcomes. While overseas acquisitions by companies from emerging economies are receiving increasing attention in the business press, our understanding of how and when this pattern of international expansion begins to affect acquirers is limited [63]. Thus, by analyzing Chinese SOEs and private firms through the AMC model, we contribute to the understanding of the position of different company properties of Chinese firms within a CBA wave.

Despite this, the results of the empirical study utilizing a competitive dynamic perspective did not validate the hypothesis of the drivers of the entry of Chinese firms with different ownership into the CBA wave. However, we believe there are several reasons for this outcome.

First, firms that are part of external institutions respond to institutional pressures in different manners [34]. Although the results are inconsistent with the assumptions, we believe that the policy impact is significant. The start time of our wave testing was 2013, which coincided with the implementation of the “Belt and Road” initiative by the Chinese government. When faced with environmental competition, SOEs rely on the resources and support provided by the country, which also makes them more compliant with national policies. Thus, they pursue strategies to meet the political goals of the politicians who control them [64] and have stronger awareness, motivation, and capability to comply with national policies.

Moreover, Stearns et al. [19] identified the changes in economic and political environments that can create conditions conducive to a merger wave. In 2016, the FDI of Chinese enterprises reached 112.9 trillion yuan, a year-on-year increase of 44.1%, a growth rate three times that of 2015. M&A is the primary form of Chinese companies’ overseas investment (Ministry of Commerce). According to the central argument of RDT is that environment-dependent enterprises can and do develop multiple strategies to combat external constraints and obtain key resources [65]. Deng et al. [66] explored resource dependence logic to explain why firms engage in CBAs. In this age of global interdependence, the outward investment activities of emerging market firms are increasingly dependent on technology, natural resources, and markets of other countries [4,38]. To cope with environmental uncertainty, domestic enterprises have increased demand for overseas resources, markets, brands, and technologies, and the willingness of enterprises to allocate resources in the international market is extreme [41,48,54]. The overall external economic environment is sluggish, and the relatively low asset prices have also promoted the motivation for enterprises to conduct CBAs. Chinese firms’ internationalization and transnational operations are gradually improving [17], and Chinese SOEs have integrated business expansion plans with national priorities and played a leading role in the current process of internationalization. Their critical business efforts include resource extraction, trading, services, and manufacturing [67]. The SOEs’ awareness, motivation, and capacity for CBA have also increased.

The board of directors’ overseas backgrounds was found to have no noticeable moderating effect on the CBA wave of Chinese enterprises. Yet, there is a critique of our approach. Any attempt to explore a company’s strategic options requires an understanding of its institutional framework [4]. In the 1990s, China’s typical listed stock company had a mixed ownership structure consisting of three main shareholder groups: the state, institutional (legal person) investors, and individual investors. Each of them accounted for about one-third of the shares [68]. However, it has been suggested that there may be no truly independent directors in China [69]. In many SOEs, senior management or local government officials control human resource management, paying more attention to their political futures. For state-owned asset management agencies and listed companies controlled by central SOEs, their managers often maintain closer ties with government officials, so they are more likely to focus on their political careers, which is reflected in their actions and may be manifested in higher government obedience to directives and self-restraint of opportunistic behavior.

Limitations and Future Directions

The data of this study comes from CSMAR, although they contain more comprehensive firm-level information on the CBA of Chinese firms compared to other databases (e.g., SDC platinum). However, due to the limitations of the original database, there was not enough data to support hypothesis testing because of the narrower wave and scope of CBA involved in industries other than manufacturing and IT. Therefore, this significantly shrunk our sample size. Moreover, the characteristics of the target company can also influence the acquirer’s awareness of entering the CBA wave [11]. However, variables, such as age and size of the target companies, were not controlled for due to database limitations. Additionally, our reliance on archival data results in less information about the internal workings of the boards.

This study used company property as the only independent variable, and only the micro-level elements of the time to enter the wave were considered. This leads us to ignore macro-level (time-varying) environmental factors involved in dynamic competition theory. Examples of these environmental factors include the impact of external environmental policies, the specific role of state ownership in M&A, and how it responds to the dynamic changes in the external environment, which is reflected in the AMC model. These factors were not discussed in this article.

These findings indicate at least four future lines of research. First, because of the limitation of the database, we only tested the data after 2008, and the wave was formed after 2013. While waves are formed for a variety of reasons, waves will occur in contexts such as management trends, technology trajectories, new product launches, and compensation practices [34]. Dunning [70] emphasized the importance of macroeconomic variables, which may improve our understanding of macroeconomic variables. Different data analysis methods and research on other variables are also worth exploring because there are many variables, including how the external environment changes over time and how to better respond and control policies.

Second, in this study, we only focused on the general trend of Chinese manufacturing and IT industries to participate in the CBA wave using the industry level and did not break it down within industries. For example, the manufacturing industry also includes sub-industries, such as printing, chemicals, and pharmaceuticals. Future research can further examine how state ownership affects the timing of firms’ entry into the CBA wave in terms of the sub-industry level.

Third, because we used the CBA events as the unit of analysis in this paper rather than the CBA firms, we ignored the perceptions of the CBA firms that did not participate in the entry wave, which led to endogeneity issues. In future studies, researchers can address this issue in two stages. First, screen out the companies that participated in the CBA and those that did not. These companies are then matched to investigate their main effects on the wave of entry into the CBA. The comparison deepens the understanding of firm characteristics on entering the CBA wave.

Fourth, the empirical results of the study suggest that an analysis of the impact of SOE property rights may help explain many phenomena related to the internationalization of Chinese enterprises, or at least to the CBA [50]. Based on our research, other strategic management researchers are encouraged to apply the framework of competitive dynamics to other significant strategic events to measure national ownership research better, like international strategic alliances, integrated global supply chains, improving agility and leanness, and investment in translational research and FDI [34], etc.

As competitive dynamics research has developed in various countries and regions around the world, differences in institutions and the maturity of market mechanisms have become essential issues for scholars [71]. More studies on the evolution of the repertoire of competitive actions among different industries and country contexts are needed [33].