A comparative analysis of Chinese and Indian MNEs’ knowledge-intensive acquisitions

in Europe: The impact of institutional distance and host-country experience on

ownership choices

Lucia Piscitello

DIG - Politecnico di Milano

Via R. Lambruschini 4/b, 20156 – Milano, Italy

Tel. +39 02 2399 2740

lucia.piscitello@polimi.it

Vittoria Giada Scalera§

DIG - Politecnico di Milano

Via R. Lambruschini 4/b, 20156 – Milano, Italy

Tel. +39 02 2399 4040

vittoriagiada.scalera@polimi.it

Paper submitted at 4th Copenhagen Conference on ‘Emerging Multinationals’: Outward

Investment from Emerging and Developing Economies, October 9-10, 2014

§ Corresponding author

Paper presented at The 4th Copenhagen Conference on ’Emerging Multinationals’: Outward Investment from Emerging Economies, Copenhagen, Denmark, 9-10 October 2014

A comparative analysis of Chinese and Indian MNEs’ knowledge-intensive acquisitions

in Europe: The impact of institutional distance and host-country experience on

ownership choices

ABSTRACT

This study examines the cross-border acquisition strategies of multinational enterprises

(MNEs) from the main emerging countries, i.e. China and India. Specifically, we present a

comparative analysis of Chinese and Indian ownership choices in knowledge-intensive

acquisitions undertaken in more advanced countries. Within this framework we aim at

understanding how home-country comparative (dis)advantages, institutional distance

between home and host country, and past host-country experience differently influence the

internationalization strategies of the Chinese and Indian MNEs involved in strategic asset-

seeking acquisition in distant and more advanced foreign countries.

We provide original empirical evidence based on a comprehensive dataset that collects

acquisitions by high and medium-high tech Chinese and Indian firms in Europe during the

period between 2003 and 2011, using data from BvD Zephyr and SDC Platinum. Our results

demonstrate that Chinese MNEs prefer to acquire less control on the advanced target

company, compared to their Indian counterpart. Additionally, the positive relationship

between level of control and institutional distance is weaker for Chinese MNEs as compared

to Indian, also under previous host-country experience.

Keywords: Cross-border acquisitions, Ownership choice, Knowledge-intensive investments,

Emerging market multinationals, China, India, Formal institutional distance, host-country

experience

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1. INTRODUCTION

In recent years the global economy has witnessed a growing flow of Foreign Direct

Investments (FDI) from Emerging Market Multinational Enterprises (EMNEs). The latest

World Investment Report has reported that FDI flows from developing and transition

economies have rapidly increased from $ 12 billion in 1990 to nearly $ 481 billion in 2012,

representing the 34.62% of the world total (UNCTAD, 2013). Over the recent years, both

China and India have been involved in a growing process of international expansion through

outward FDI, emerging as leading countries for flows of direct investments directed abroad.

During the period 1990-2012, Chinese outward FDI stock increased from $ 0.83 billion to $

84.22 billion, while Indian outward FDI stock grew from $ 0.06 billion to $ 8.58 billion

(UNCTAD, 2013). India and China have some common characteristics related to their

outward FDI, such as the influence of the government policy in supporting their international

expansion and local innovation, or the propensity to undertake FDI in advanced countries in

order to seek sophisticated technology and know-how to catch-up with Advanced Market

MNEs (AMNEs). Yet, also a number of considerable differences at firm- and home country-

level may have a different impact on their international growing strategies.

Here we explicitly focus on knowledge-intensive acquisitions. In particular, we analyze

EMNEs’ investments in high- and medium-high tech sectors in an advanced country, i.e.

Europe. These investments are likely to aim at augmenting firms’ knowledge base by

exploiting capabilities embedded in the target firm. Knowledge has been recognized as the

main basis for competitive advantage in many technology-intensive sectors, and is thus a

primary motive for international expansion (Martin and Salomon, 2003). To quickly reduce

their technological gap and successfully compete with firms from advanced countries,

EMNEs need to augment their knowledge base through international operations by directly

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accessing resources that can be transferred to the parent company (Child and Rodrigues, 2005;

Luo and Tung, 2007).

In this paper, we present a comparative analysis of Chinese and Indian international

knowledge-sourcing strategies, by comparing the main differences of their ownership choices

when they acquire target companies located in Europe. Within this framework we can

better understand how home-country (dis)advantages, institutional distance and past

host-country experience differently influence the internationalization strategies of the Chinese

and Indian MNEs involved in strategic asset-seeking acquisitions in distant and more

advanced foreign countries. We first review the literature regarding Chinese and Indian

internationalization strategies and then we provide original empirical evidence based on a

comprehensive dataset that collects acquisitions undertaken by high and medium-high tech

Chinese and Indian firms in Europe during the period between 2003 and 2011, using deal-

level data from BvD Zephyr and SDC Platinum (Thomson Reuter). Our main contribution to

the extant literature is to provide empirical evidences on the main differences between

Chinese and Indian ownership choices in their technological upgrading process. In the extant

literature, in fact, only a small numbers of study empirically analyze how MNEs from the two

major emerging economies differ in their internationalization strategies, as they are often

treated as a homogenous cluster to be compared to MNEs from advanced economies

(AMNEs).

The paper is organized as follows. The next section presents our conceptual framework and

the testable hypotheses. The third section presents the empirical setting, including the sample,

variables, descriptive statistics, and the econometric model. In the next section, we illustrate

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and discuss the results of the analysis, while in the final section we summarize the main

contribution of the paper.

2. RESEARCH FRAMEWORK AND HYPOTHESES

One of the key characteristics of EMNEs is that their international expansion is generally not

aimed at exploiting ownership advantages (Dunning, 1993), as traditionally experienced by

AMNEs, but rather at building a sustainable global competitive advantage for leveraging their

network of relationships and their home country advantages (Buckley et al., 2007). When

investing in high-income countries, EMNEs are usually involved in strategic-asset-seeking

FDI (Luo and Tung, 2007) and often choose acquisitions as a mode of entry because it is a

fast way to access technological knowledge and other strategic resources.

EMNEs entering culturally, technologically and geographically distant locations have to deal

with considerable information asymmetries and substantial risks. Within this context, one of

the most critical issues is the degree of the equity ownership in the target company, as that

impacts on several factors, such as the effective access to tacit and intangible assets, and the

risk shared between the acquiring and the target firm (Anderson and Gatignon, 1986;

Barkema and Vermeulen, 1998). As pointed out by Contractor and colleagues (2014), the

right ownership strategy can imply significant economic benefits thanks to a smooth post-

integration and asset synergy. On the contrary, when the ownership acquired is incorrect,

there could be a mismatch between resource commitment and risk, and inefficient integration.

International business and strategic management literature has mainly relied on internalization

theory (Buckley and Casson, 1976; Hennart, 1982) and Resource-based View (RBV) (Barney,

1991; Teece et al., 1997) to explain the main factors that might drive ownership choices in

foreign countries. However, more recent studies (e.g. Filatotchev et al., 2007) have shown,

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that in internationalization strategies information asymmetries and perceived risks need to be

also taken into consideration, especially when firms invest in very dissimilar environment, as

the case of EMNEs investing in advanced countries. Besides the liability of foreigness,

EMNEs often face two main additional disadvantages when entering in advanced countries.

More specifically, they suffer from (i) the liability of emergingness lacking reputation and

legitimacy (Madhok and Keyhani, 2012), and (ii) the knowledge gap with respect to firms in

advanced markets, that may severely limit their absorptive capacity to acquire and incorporate

external knowledge (Cohen and Levinthal, 1990).

We claim that, although Chinese and Indian MNEs have common characteristics as they

originate from emerging economies, their ownership strategies in advanced countries differ

and these dissimilarities might be driven by their home-country (dis)advantages, by formal

institutional differences between home and host country, as well as by prior experience in the

host country.

2.1 Home country comparative (dis)advantages, knowledge seeking and ownership

choices

EMNEs do present some heterogeneity that has been generally overlooked by the empirical

literature. An interesting perspective has been presented by Sun and colleagues (2012),

arguing that Chinese and Indian MNEs have different value curves analyzing their spatial

position in the global value chain. In particular, they highlight that due to comparatively

backward infrastructure, India lags behind China in international trade, especially in labor-

intensive activities such as assembly line production and global manufacturing. On the other

hand, Indian MNEs are superior to their Chinese counterparts in capital-intensive activities,

holding a relative leadership in the internationalization of product design, marketing and

R&D. Namely, compared to Chinese MNEs, Indian companies possess a stronger technical

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knowledge base and higher level of absorptive capacity. Indian companies show a

comparative advantage in the activities of the right side of the smiling curve (Mudambi, 2008;

Sun et al., 2012), being global players in the internationalization of R&D, product design and

engineering services (Athreye and Kapur, 2008). So, Indian companies are more likely to

easily access and transfer knowledge from external sources, as those are embedded in firms

located in developed countries, which possess complex resources and capabilities. On the

contrary, Chinese MNEs investing in knowledge-intensive sectors are more likely to need the

support of local partners in their learning process, especially considering the tacit nature of

high-tech knowledge. Additionally, the cooperation with the foreign target company mitigates

problems arising from cultural differences and knowledge gap between the acquiring and the

target firms (Chen and Hennart, 2004). In fact, a well-known critical issue for Chinese

enterprises managing overseas M&As is handling relationships with skeptical regulators,

unions and other stakeholders before, during, and after the deals (Hirt and Orr, 2006). In order

to learn from the partner the acquiring firm needs to develop trust and relational capital, and

has to encourage people to collaborate and accept different style and behavior (Schreiner at

al., 2009). This might be strategic in the case of Chinese MNEs, which suffer, especially in

advanced countries, from reputation problem and lack in managerial skills (Rossele-

McCauley, 2009; Spigarelli et al., 2013). Thus, Chinese MNEs are likely to perceive

acquisitions in Europe, especially when they are knowledge intensive, more uncertain and

risky than Indian MNEs.

According with these arguments, we expect that Chinese investors might prefer to acquire

lower level of control and rely on the local partner compared to their Indian counterparts.

Specifically, our first hypothesis is the following:

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Hypothesis 1 (H1): In knowledge-intensive acquisitions towards advanced countries,

Chinese MNEs will acquire lower control than Indian companies.

2.2 EMNEs and formal institutional distance: the different impact on Chinese and

Indian ownership choices

Institutional theory has been widely used in the literature to explain the ownership choices in

cross-border acquisitions (e.g. Hennart and Larimo, 1998; Xu and Shenkar, 2002).

Institutions, in fact, provide the formal and informal scenario in which the economic activities

take place, framing firms’ economic behavior and the way they interact (Peng et al., 2008).

Following Contractor et al. (2014), we distinguish between formal and informal institutions.

In particular, we call simply institutions the former, which are related to rules, law and

practices, while informal institutions are related to values and norms of culture, language and

society (Dikova et al., 2010).

Here we talk about institutional distance, referring to the extent of the difference in the formal

institutional environment between the acquiring company’s country and its host country

(Dikova et al., 2010). To be successful in cross-border ventures, MNEs need to possess

knowledge of the host environment, and sever studies have specifically examined how

institutional differences can influence MNEs’ ownership choice. However, in the literature

there is no consensus regarding the effect of institutional distance on the ownership choice

(Morschett et al., 2010). Some studies show a negative relationship between institutional

distance and control; in other words, if home and host country institutional environments are

similar, MNEs will acquire higher control over the target company feeling a sense of

familiarity and perceiving less uncertainty (Hennart and Larimo, 1998; Xu and Shenkar,

2002). On the other hand, other empirical findings show that institutional distance may be

positive correlated with the level of control in foreign activities. For example, Kostova and

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Zaheer (1999) found that distant institutional environments encourage full ownership, as

larger distances might represent a barrier to transfer organizational practices from the parent

to the foreign subsidiary (Kostova, 1999). However, as pointed out by De Beule et al. (2014)

traditional measures only consider the magnitude of distance and are usually applied to

AMNEs investing in emerging or less developed countries. Analyzing the opposite situation,

i.e. EMNEs investing in advanced countries, the authors find that EMNEs do not need to rely

on the local partner to reduce uncertainty due to the distant institutional environment, and they

more likely adopt more control on the target company in case of higher level of distance. They

claim, in fact, that it does not only matter how much countries differ but also how (Zaheer et

al., 2012); in particular, EMNEs investing in more advanced countries face a much more

stable and less risky surrounding environment, and so they don’t need to share equity to

reduce the uncertainty (De Beule et al., 2014).

Here we link the positive relationship between institutional distance and level of control on

the foreign target company with the arguments supporting our H1. In particular, we claim that

the EMNE’s country of original may have a different impact on the direct relationship,

consider the higher propensity of Chinese companies to undertake partial acquisition

compared to Indian MNEs.

Hence, our second hypothesis states as follows:

Hypothesis 2 (H2): In knowledge-intensive acquisitions towards advanced countries,

the positive relationship between control in the target company and institutional

distance is weaker for Chinese MNEs compared to their Indian counterparts.

2.3 The role of experience in different institutional environments

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The literature on MNE’s entry mode (e.g. Guillen, 2003; Gulati and Singh, 1998) has already

widely shown that local experience in the host country is likely to lower the risk and agency

costs associated with the cross-border investments and reduce the perceived distance between

the local partner and the acquiring firm (Filatotchev et al., 2007). In fact, existing studies

suggest that the prior presence in the host location tends to improve firms’ capability to

manage co-ownership with local partners (Gulati and Singh, 1998). The prior presence in the

local environment could be useful to create formal and informal network and to share

information that would seem to be important factors in foreign investments (Gao, 2003).

Thus, prior experience in host country is likely to mitigate the issues arising from cultural and

knowledge distance and reduce information asymmetries providing access to context-specific

knowledge. Therefore, accordingly to the previous findings, we show that local experience

enables EMNEs to mitigate agency costs associated with cross-border acquisitions by

reducing parent’s risk exposure. Namely, we expect that previous local experience in the host

country should be associated with a choice of acquiring a greater ownership into the target

firm.

In addition, Powell and Rhee (2013) find that prior host-country experience increases

confidence in the face of institutional difference and increases the propensity of the acquiring

firm to control a larger share of equity in the foreign subsidiary. This is in line with the

internationalization process model (Johanson and Vahlne, 1977).

In this framework, we claim that the positive moderating role of host-country experience on

the relationship between institutional distance and level of control on the foreign target

company in is different for Chinese and Indian firms. In particular, in line with Yiu and

Makino (2002), we base our argument on the evidence that Indian MNEs are more

experienced in entering Europe with acquisitions than their Chinese counterparts, which on

the contrary prefer to set up new subsidiaries through greenfield investments. Further, the

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distance perceived by Indian and Chinese MNEs towards European countries is generally

different. In fact, as highlighted by Zhang et al. (2012), Indian firms have a longer European

history than Chinese companies. Further, India has historical, cultural and economic linkages

with the UK, which is one of the top recipients of FDI towards Europe. So, Indian MNEs are

more confident when they enter Europe through acquisitions, and the previous host-country

experience contributes to increase their propensity to acquire higher control compared to the

Chinese. Hence:

Hypothesis 3 (H3): In knowledge-intensive acquisitions towards advanced countries,

under previous host-country experience the positive relationship between control in

the target company and institutional distance is weaker for Chinese MNEs compared

to their Indian counterparts.

3. METHODOLOGY

3.1 Sample

The empirical analysis is based on acquisitions undertaken by high and medium-high tech

Chinese and Indian companies in the 27 European countries, throughout the period 2003-

2011. Data on acquisitions come from BvD Zephyr and SDC Platinum databases. These two

databases provide information at the level of the deal (e.g., the type of deal, date, value,

degree of ownership) as well as general information about the target and acquiring companies

(e.g. country, region and city of origin, activities and sectors).

The focus of the empirical analysis is on knowledge-intensive manufacturing acquisitions. In

fact, previous studies have empirically highlighted that investments for knowledge sourcing

are particularly relevant in high tech manufacturing industries (Cloodt et al., 2006), especially

in the case of EMNEs investing in advanced economies (Awate, et al. 2012). Therefore, we

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have identified high and medium-high tech acquiring firms relying on the Eurostat-OECD

(2007) classification. We have included in our sample those companies operating in the

following two-digit manufacturing industries according to the NACE Rev. 2 classification:

pharmaceuticals (20), chemicals (21), computer, electronic and optical products (26),

electrical equipment and components (27), machinery and other equipment (28), motor

vehicles (29) and other transport equipment (30).

The final sample is obtained from the exclusion** of: 1) the deals undertaken by individual or

unknown investors; 2) the operations with undisclosed acquirer and/or target; 3) the

investments in which the acquirer is a sovereign wealth fund (SWF) or the global ultimate

owner (GUO) is not from China or India. Thus, our final sample includes 206 acquisitions: 67

(32%) undertaken by Chinese firms and 139 (68%) by Indian MNEs. Acquisitions involve 22

target European countries with the UK and Germany representing the most favorite locations

for Indian and Chinese companies, respectively.

3.2 Variables

3.2.1 Dependent variable

The dependent variable is the Ownership choice undertaken by the EMNE in the acquisition

of the target company. It is a categorical variable taking value of 1, 2 and 3 for minority,

majority and full ownership, respectively (for a similar approach, see De Beule et al., 2014).

According to Contractor et al. (2014), we define an acquisition as minority when the acquiring

firm buys less then 50% of the target firm’s equity. An acquisition is categorized as majority

when the acquired share is between 50% and 99%, and a deal is defined as full when the

acquirer buys 100% of the target. Thus, the higher the value of the dependent variable, the

higher is the degree of ownership in the target company. Table 1 shows the distribution of the

** An acquirer could have enhanced ownership of the target company over the years, starting from a partial acquisition and subsequent moving to a full one. We included in our sample on the first transaction, avoiding any potential issue.

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acquisitions in our sample, distinguishing between Chinese and Indian acquirers. The table

also reports the values of minimum, maximum, mean and standard deviation of the share of

equity acquired in the target company. The high incidence of complete ownership is very

much consistent with prior research that has pointed out the Chinese and Indian firms’

preference for full ownership control over foreign operations (De Beule et al., 2014; Sun et

al., 2012).

[Insert Table 1 here]

3.2.2 Explanatory variables

The first independent variable is the dummy Chinese, which is equal to 1 if the acquiring

company is Chinese, and 0 if it is Indian. The second independent variable is Institutional

distance (for the year previous to the deal), which was computed by using a procedure similar

to Kogut and Singh (1988) and includes the 9 items of the economic freedom index developed

by the Heritage Foundation in partnership with the Wall Street Journal (Kane et al., 2007; De

Beule et al., 2014). Finally, the third independent variable is Host country experience, which

refers to the local experience of the Chinese and Indian MNE in the host-country context. It is

measured through the variable Host country experience, a dummy taking the value of 1 if the

company has already undertaken at least another investment in the same host country in the

previous 10 years, and 0 otherwise.

3.2.3 Control variables

We control for several characteristics that have been included in similar studies on ownership

choices in cross-border acquisitions.

Since the study utilizes a multi-host, multi-home sample, we considered several measures of

informal institutional distance between the home and the host country to account for the

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different dimensions of psychic distance stimuli (Dow and Karunaratna, 2006; Dow and

Larimo, 2009). Uncertainty avoidance distance has been employed as measure of cultural

distance (see also Contractor et al., 2014). It refers to the distance between uncertainty

avoidance levels of the acquirer and the target country. The measure was computed by using a

procedure similar to Kogut and Singh (1988) for each cross-border acquisition. The

uncertainty avoidance indices were obtained from Hofstede Centre (www.http://geert-

hofstede.com/the-hofstede-centre.html). Education distance and Language distance were

calculated according to the approach of Dow and Karunaratna (2006), measuring the

difference between the home and the host country for each scale. The data come from

Douglas Dow’s website (https://sites.google.com/site/ddowresearch/home/scales). For the

year previous to the acquisition, we introduced GDP pp representing the (logarithm of) gross

domestic product per capita of the target country. Data were obtained from the World Bank

Development Indicators database.

For firm-level controls, we used SOE that is a dummy variable that takes the value of 1 if the

Chinese acquiring company is state-owned, and 0 otherwise. We also included Size,

representing the logarithm of the assets value of the acquiring company as at the previous year

of the deal, and Target manufacturing, which is a dummy variable taking the value of 1 when

the target company operates is a manufacturing sector (2-digt NACE Rev. 2 codes between 10

and 33) and 0 when it is in a service sector (2-digt NACE Rev. 2 codes greater than 33).

For industry-specific effects, we introduced four sectoral dummies (Electronics, Machinery,

and Transport with Chemicals as the benchmark) based on the acquirer’s 2-digit NACE Rev.

2 codes. Data were obtained from BvD Orbis. Finally, we control for the years of the financial

crisis by adding two dummy variables for acquisitions in 2006 or 2007 (Year t for t = 2006,

2007).

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3.3 Model and methodology

Given that our dependent variable is trichotomous, we adopted a robust order probit

regression model, which allows controlling for heteroskedasticity of the sample. To facilitate

the interpretation of the results, we standardized all the continuous predictor variables before

entering them into the regression models (Aiken and West, 1991).

We started from the following basic equation mode (1):

(1 ) Ownership choicei=β0+β1Chinesei+β2 Institutional distance i+β3 Host country experiencei+β4 Controls+εi

where i=1, 2, 3, …206 are the deals; Ownershipchoice is the dependent variable, which has

been measured as the degree of ownership; Chinese is the dummy taking the value of 1 if the

acquiring firm is a Chinese MNEs; Institutional distance refers to the measure of institutional

distance described in the previous section; Host country experience is the dummy variable

taking the value of 1 if the acquiring company has previous local experience; Controls are the

control variables described above, and ε is the error term.

To test our hypotheses H2 and H3, we interacted the dummy variable Chinese with the

variable Institutional distance (model 2), and also then with Host country experience (model

3), as shown in model the following:

(2 ) Ownership choicei=β0+β1Chinesei+β2 Institutional distance i+β3 Host country experiencei+β4 Chinese∗Institutional distance+β5 Controls+εi

(3 ) Ownership choicei=β0+β1Chinesei+β2 Institutional distancei+β3 Host country experience i+β 4Chinese∗Institutional distance∗Host coun try experience+β5Controls+εi

Table 2 reports descriptive statistics and correlations of the study variables. The table shows a

number of correlation at level high enough to raise questions about multicollinearity. Variance

15

Inflation Factors (VIF) were also calculated using pooled multiple regression versions of the

model to evaluate the threat of multicollinarity. As a result, all the VIF were significantly

lower than the commonly used maximum VIF thresholds of 10 and 4 (O’Brien, 2007; Xu et

al., 2004).

[Insert Table 2 about here]

4. RESULTS

Table 3 show the estimated coefficients of the ordered probit models applied to the three

models described above.

[Insert Table 3 about here]

The three models produced statistically significant results (chi2= 50.41 and p<.0 in Model 1,

chi2= 51.19 and p<.0 in Model 2, chi2= 53.83 and p<.0 in Model 3).

Of the control variables, four exhibit significant and stable association with the ownership

choice (Language distance, SOE, Size, Target manufacturing). Model 1 tests H1 that is

supported. In fact, the independent variable Chinese is negatively and significantly correlated

(p<.001) with our dependent variable Ownership choice, confirming that Chinese MNEs

prefer to acquire lower control in the target company, compared to Indian companies. The

empirical analysis also confirms the positive and significant correlation of Institutional

distance (p<.05) and Host country experience (p<.0.01) with the dependent variable

Ownership choice, as predicted by existing literature. These results reinforce the evidence that

EMNEs prefer to acquire higher control in the target company, the higher the formal

institutional distance between the home and host countries, as suggested by De Beule et al.

(2014). Further, our findings also reinforce the argument by Filatotchev and colleagues

16

(2007), showing that EMNEs tend to acquire a higher control in foreign target companies

when they have previous host-market experience.

We employed Model 2 and 3 to test our H2 and H3, respectively, including the interaction

terms to reflect our theoretical argumentations. We calculate the marginal effects and present

a graphical analysis as suggested by Hoetker (2007). Both our interaction terms in Model 2

and 3, i.e. Chinese*Institutional distance and Chinese*Institutional distance*Host-country

experience, seem to be not statistically significant. However, in non-linear models, the

relation of the interaction term with the dependent variable may be more or less pronounced at

varying level of the interacted variables, and a marginal effect only refers to the average

values; so, the probability of an outcome cannot be directly discerned from the variable’s

coefficient (Hoetker, 2007). Therefore, we review different alternative values of Chinese and

Host-country experience in Figure 1 and 2 to obtain a richer and more informative

interpretation of the results.

[Insert Figure 1 and 2 about here]

As regards H2, the displayed graph in Figure 1 suggests that, depending on the home-country

origin, the propensity to undertake a full acquisition is diverse for different levels of formal

institutional distance. In particular, on average Indian MNEs are more likely to acquire higher

control than Chinese; in addiction, the greater the institutional distance, the steeper the line

representing Indian companies, also compared to Chinese observations. This confirms our H2,

showing that the positive relationship between institutional distance and control of the foreign

target company is weaker for Chinese MNEs compared to Indian.

As regards our H3, we use graph presented in Figure 2 to discuss the different impacts of

formal institutional distance on the likelihood a higher level of control in Chinese vs. Indian

acquisitions under previous host-country experience vs. no previous host-country experience.

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The graph confirms that on average Indian MNEs are more likely to acquire higher control

than the Chinese companies, and this relationship is stronger the greater the institutional

distance under prior host-country experience. Conversely, in the case of Chinese MNEs the

previous host-country experience positively influences the relationship between institutional

distance and control; however, for different levels of institutional distance, the slopes of the

two lines (with and without host-country experience) related to Chinese MNEs remain almost

constant, showing that the effect of the experience is weaker. Thus, also H3 seems to find

confirmation from our findings.

6. CONCLUSIONS

In this work we presented a comparative analysis of Chinese and Indian ownership choices in

knowledge-intensive acquisitions towards Europe. As pointed out, EMNEs need to catch-up

with AMNEs and quickly reduce technological gap by augmenting their knowledge base

through international operations and directly accessing resources that can be transferred to the

parent company (Child and Rodrigues, 2005; Luo and Tung, 2007). Therefore, their

expansion abroad, especially in advanced countries, is likely to be driven by the search for

technology, management and strategic skills, brands and commercial knowledge, which often

are lacking in their home countries (Rugman 2009). Cross-border acquisition of companies in

advanced countries is considered the fastest and most effective means of accessing strategic

assets and key capabilities (Chung and Alcacer 2002). It can enable direct access to

sophisticated competences and skilled labour, and allow exploitation of local knowledge and

development of formal and/or informal collaborations and networks with local actors such as

suppliers, customers, universities and research centres (Cantwell and Mudambi, 2011).

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In this framework, we found that Chinese MNEs prefer to acquire lower share of equity,

compared to Indian companies. We argued, in fact, that the substantial dissimilarities in their

home-country (dis)advantages play an important role in differently shaping the ownership

choice decisions in strategic-asset seeking acquisitions. Compared to Indian MNEs, Chinese

companies suffer from comparative disadvantages in value-added and knowledge-intensive

activities, which more likely drive Chinese investors to maintain the local partner in order to

efficiently leverage valuable knowledge and competences embedded in the target company.

Further, Chinese managers often experience a bad reputation for handling good and durable

relationships with local employees and skeptical unions during, and after the overseas

acquisitions. So, in order to reduce the risk of a possible hollowing out of the target firms,

which may be caused by the departure of key local managers and technicians, Chinese

acquires more probably prefer to undertake partial acquisitions and share part of the equity

with the target company. In our second hypothesis, we confirmed the positive relationship

between control in the target company and institutional distance between the home and the

host countries in the case EMNEs’ acquisitions (De Beule et al., 2014). However, relying on

our H1 we pointed out the different behavior of Chinese and Indian MNEs, and we found that

Indian firms more likely tend to acquire higher control on target companies located in more

distant host countries, compared to their Chinese counterparts. Finally, in the third hypothesis,

we analyzed the role of experience, finding support to its effect of reducing the perceived

distance between home and host country. In particular, the positive relationship between

institutional distance and control is strengthened when the acquiring companies has previous

host-market experience, but this moderating effect of experience is stronger in the case of

Indian companies than Chinese.

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Our findings are contributors to the existing literature about EMNEs’ internationalization

strategies and knowledge-sourcing cross-border acquisitions. The arguments contribute to a

better understanding of the differences between Chinese and Indian MNEs in their

internationalization and knowledge-sourcing strategies, complementing other studies on

EMNEs that generally consider them as a homogenous category (e.g. Buckley et al., 2007;

Filatotchev et al., 2007). In fact, as highlighted by existing literature (Athreye and Kapur,

2009; Sun et al., 2012), India and China have some common characteristics related to their

outward FDI, but also a number of considerable differences at firm- and home country-level

that may have different impact on their international growing strategies. We have highlighted

that in the realm of knowledge-intensive cross-border acquisitions, Chinese and Indian MNEs

differ in their ownership choices, considering home-country comparative disadvantages,

formal institutional distance and previous host-country experience.

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FIGURES

Figure 1. Interaction plot, Hypothesis 2 (Ownership choice = Full acquisition)

Figure 2. Interaction plot, Hypothesis 3 (Ownership choice = Full acquisition)

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TABLES

Table 1. Distribution of the 206 acquisitions by Ownership choice (No., %) and Share of equity.China India Total

Ownership choiceMinority (No.) 13 15 28% 19.40 10.79 13.59Majority (No.) 15 20 35% 22.30 14.39 16.99Full (No.) 39 104 143% 58.21 74.82 69.42Total (No.) 67 139 206

Share of equityMean 0.79 0.90 0.86Std. Dev. 0.32 0.23 0.26Min 0.06 0.10 0.06Max 1 1 1

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Table 2. Descriptive statistics and correlation matrix of the variables employed in the analysis(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11)

(1) Ownership choice 1(2) Chinese -0.129 1(3) Institutional distance 0.100 -0.012 1(4) Host country experience 0.150 -0.070 0.205 1(5) SOE 0.140 0.445 0.019 0.018 1(6) Uncertainty avoidance distance -0.099 0.176 -0.631 -0.197 0.086 1

(7) Language distance -0.053 0.538 -0.543 -0.177 0.217 0.536 1(8) Education distance 0.070 -0.490 -0.236 0.006 -0.200 0.099 -0.004 1(9) GDP pp 0.043 0.204 0.462 0.082 0.129 -0.412 -0.179 0.181 1(10) Size -0.125 0.108 -0.032 0.210 0.025 0.081 0.064 -0.072 0.000 1(11) Target manufacturing 0.178 -0.026 -0.032 0.017 0.009 0.010 0.019 -0.044 -0.065 -0.070 1

No. of Obs. 206 206 206 206 206 206 206 206 206 206 206Mean 2.558 0.325 2.907 0.218 0.107 0.001 -0.385 1.493 10.382 12.535 0.806Std. Dev. 0.722 0.469 1.861 0.414 0.31 1.003 1.178 0.295 0.467 1.921 0.397Min 1 0 0.018 0 0 -0.961 -2.433 0.65 8.17 2.4169 0Max 3 1 7.285 1 1 5.114 0.526 2.243 10.937 18.678 1

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Table 3. Robust ordered probit model (dependent variable = Ownership choice)(1) (2) (3)

Uncertainty avoidance distance 0.078 0.029 0.078(0.142) (0.147) (0.142)

Language distance 0.538** 0.771* 0.531*

(0.203) (0.319) (0.209)Education distance -0.105 -0.128 -0.103

(0.152) (0.159) (0.153)GDP pp 0.110 0.094 0.110

(0.120) (0.122) (0.120)SOE 1.316*** 1.356*** 1.322***

(0.337) (0.338) (0.342)Size -0.223* -0.230* -0.222*

(0.107) (0.106) (0.107)Target manufacturing 0.526* 0.502* 0.525*

(0.226) (0.227) (0.226)Institutional distance (ID) 0.428* 0.644* 0.421*

(0.201) (0.294) (0.206)Host country experience (HC exper.) 0.691** 0.719** 0.688*

(0.267) (0.272) (0.268)H1 Chinese -1.380*** -1.686** -1.376***

(0.395) (0.520) (0.396)H2 Chinese*ID -0.382

(0.353)H3 Chinese*ID*HC exper. 0.178

(0.312)Sectorial dummies Yes Yes YesYear dummies Yes Yes Yes

Constant cut1 -1.186** -1.312** -1.187**

(0.393) (0.422) (0.393)Constant cut2 -0.482 -0.605 -0.482

(0.389) (0.415) (0.388)

No. 206 206 206chi2 50.41 51.19 53.83p 0.00 0.00 0.00

Note: Variables have been standardized. Standard errors in parentheses.* p<0.05, ** p<0.01, *** p<0.001.

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