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CATEGORIZING THE LIABILITY OF FOREIGNNESS: OWNERSHIP, LOCATION, AND INTERNALIZATION- SPECIFIC DIMENSIONS NAN ZHOU 1,2 * and MAURO F. GUILLEN 3 1 China Minsheng Bank, Beijing, China 2 Nankai Business School, Nankai University, Tianjin, China 3 Lauder Institute, Management Department, Wharton School, University of Pennsylvania, Philadelphia, Pennsylvania, U.S.A. Plain language summary: This study explains the different types of additional costs faced by multinational firms when they invest abroad. We identify product adaptation cost, discrimination cost, governance cost, and appropriation hazard as important sources of the difficulties that multinationals face. We then link each of these costs to different dimensions of cross-national distance, including economic, cultural, demographic, political, and administrative distance. Finally, we show that the importance of these different distance dimensions differ when multinationals invest abroad for different reasons including market seeking, efficiency seeking, knowledge seeking, and natural resource seeking. Technical summary: This study bridges the literature on the liability of foreignness (LoF) and cross-national distance. Following the ownership-location-internalization paradigm, we categorize the LoF into three dimensions: ownership-specific LoF, location-specific LoF, and internalization-specific LoF, each of which reduces a specific advantage of the multinational firm. We first define the three dimensions of the LoF and then argue that each dimension is related to different types of costs. We further explain that different types of costs are associated with different dimensions of cross-national distance, and firms face different types of the LoF and associated costs when they conduct different types of foreign direct investment. We test these hypotheses in the context of Chinese listed firms investing abroad, finding support for most of the predictions. Copyright © 2016 Strategic Management Society INTRODUCTION The concept of the liability of foreignness (LoF) is the backbone of the fields of international strategy and international business. Stephen Hymer was one of the first scholars to recognize that multinational enterprises (MNEs) face extra costs when doing business in foreign countries compared with local competitors because of their lack of familiarity with local conditions (Hymer, 1960; Hymer, 1976). The LoF is commonly defined as the costs of doing business abroad that result in a competitive disadvan- tage for an MNE subunit broadly defined as all additional costs a firm operating in a market overseas incurs that a local firm would not incur(Zaheer, 1995: 342343). The LoF has great impact on multinationals. Previous studies have found that it influences the internationalization strategy of multinationals, includ- ing the entry mode and performance implications of internationalization (Chen, 2006; Mezias, 2002). Given the importance of the LoF in global strategy, Keywords: liability of foreignness; foreign entry; distance; China; OLI paradigm *Correspondence to: Nan Zhou, China Minsheng Bank, No.13 Zhichun Road, Hang Nan Building, Beijing, China, 100083. E-mail: [email protected] Global Strategy Journal Global Strategy Journal, 6: 309329 (2016) Published online in Wiley Online Library (wileyonlinelibrary.com). DOI: 10.1002/gsj.1140 Copyright © 2016 Strategic Management Society

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Categorizing the Liability of Foreignness: Ownership, Location, and Internalization-Specific Dimensions1China Minsheng Bank, Beijing, China 2Nankai Business School, Nankai University, Tianjin, China 3Lauder Institute, Management Department, Wharton School, University of Pennsylvania, Philadelphia, Pennsylvania, U.S.A.
Plain language summary: This study explains the different types of additional costs faced by multinational firms when they invest abroad. We identify product adaptation cost, discrimination cost, governance cost, and appropriation hazard as important sources of the difficulties that multinationals face. We then link each of these costs to different dimensions of cross-national distance, including economic, cultural, demographic, political, and administrative distance. Finally, we show that the importance of these different distance dimensions differ when multinationals invest abroad for different reasons including market seeking, efficiency seeking, knowledge seeking, and natural resource seeking.
Technical summary: This study bridges the literature on the liability of foreignness (LoF) and cross-national distance. Following the ownership-location-internalization paradigm, we categorize the LoF into three dimensions: ownership-specific LoF, location-specific LoF, and internalization-specific LoF, each of which reduces a specific advantage of the multinational firm. We first define the three dimensions of the LoF and then argue that each dimension is related to different types of costs. We further explain that different types of costs are associated with different dimensions of cross-national distance, and firms face different types of the LoF and associated costs when they conduct different types of foreign direct investment. We test these hypotheses in the context of Chinese listed firms investing abroad, finding support for most of the predictions. Copyright © 2016 Strategic Management Society
INTRODUCTION
The concept of the liability of foreignness (LoF) is the backbone of the fields of international strategy and international business. Stephen Hymer was one of the first scholars to recognize that multinational enterprises (MNEs) face extra costs when doing business in foreign countries compared with local
competitors because of their lack of familiarity with local conditions (Hymer, 1960; Hymer, 1976). The LoF is commonly defined as ‘the costs of doing business abroad that result in a competitive disadvan- tage for an MNE subunit … broadly defined as all additional costs a firm operating in a market overseas incurs that a local firm would not incur’ (Zaheer, 1995: 342–343).
The LoF has great impact on multinationals. Previous studies have found that it influences the internationalization strategy of multinationals, includ- ing the entry mode and performance implications of internationalization (Chen, 2006; Mezias, 2002). Given the importance of the LoF in global strategy,
Keywords: liability of foreignness; foreign entry; distance; China; OLI paradigm *Correspondence to: Nan Zhou, China Minsheng Bank, No.13 Zhichun Road, Hang Nan Building, Beijing, China, 100083. E-mail: [email protected]
Global Strategy Journal Global Strategy Journal, 6: 309–329 (2016)
Published online in Wiley Online Library (wileyonlinelibrary.com). DOI: 10.1002/gsj.1140
Copyright © 2016 Strategic Management Society
scholars have tried to understand its various aspects, such as its definition, source, and how to overcome it (Eden and Miller, 2004; Mezias, 2002; Zaheer, 1995).
Because the LoF is a complex concept, one key stream within the LoF literature is to identify different types of the LoF. For instance, Eden and Miller (2004) broke down the LoF into three specific hazards: unfamiliarity hazards, discrimination hazards, and relational hazards. Our article falls into this literature by introducing a new categorization of different types of the LoF.
Previous studies in this area usually lay out the categorization without specifying its theoretical foundation. This study adopts the ownership– location–internalization (OLI) paradigm to categorize the LoF into ownership-specific (O), location-specific (L), and internalization-specific (I) LoF. Although the OLI paradigm has been applied to explain various aspects of internationalization (Dunning and Lundan, 2008a; Fiss and Hirsch, 2005), it has not been adopted to understand the LoF. Because the OLI paradigm is one of the most well-accepted frameworks in the inter- national business literature (Eden and Dai, 2011; Portugal Ferreira et al., 2011), adopting the OLI para- digm ensures that our categorization considers the dominant factors that influence the internationaliza- tion of multinationals. Further, the OLI paradigm highlights the advantages that encourage firms to go abroad. It corresponds well with the concept of the LoF, which describes the disadvantages multina- tionals face when they go abroad.
Empirically, many studies on classifying different types of the LoF (Bell, Filatotchev, and Rasheed, 2012; Moeller et al., 2013) are largely theoretical without providingmeasurements or empirical support. By measuring different dimensions of the LoF with different dimensions of cross-national distance, our study bridges the literature of the LoF and cross- national distance, which is a key variable determining locational advantages and disadvantages in host coun- tries relative to the home country. These two concepts are closely related to each other because large cross- national distance between the host and home country is usually associated with high LoF.
Similar to the LoF, cross-national distance is also a complex concept with a multidimensional nature (Berry, Guillen, and Zhou, 2010; Ghemawat, 2001). Given the close relationship between cross-national distance and the LoF and the fact that both concepts are aggregated constructs with layers of components, it makes sense to relate these two concepts by categorizing different types of the LoF according to
different dimensions of cross-national distance. Therefore, in this study, we match different types of the LoF with different dimensions of cross-national distance and examine their impact on foreign entry location choice.
Related to the complex nature of the LoF, it is also important to consider the fact that firms face different types of the LoF under different circumstances. There is a lack of consideration of firm heterogeneity when examining different types of the LoF. Firms differ in many aspects, such as their motivations to go abroad. Therefore, it is unrealistic to assume that all firms face the same type of the LoF regardless of the motivation for foreign direct investment (FDI). We argue that the importance of each type of the LoF is not always the same. We hypothesize that the impact of each type of the LoF differs depending on whether the FDI is market, efficiency, strategic asset, or natural resource seeking.
To summarize, we answer three research questions in this study: (1) What are the different types of the LoF?; (2) How do different types of the LoF relate to different dimensions of cross-national distance?; and (3) How do they influence the choice of foreign entry? We adopt the OLI paradigm as the theoretical founda- tion of our categorization (Dunning, 1993; Dunning and Lundan, 2008b). Empirically, we find support for our hypotheses in the context of Chinese listed firms investing abroad from 1999 to 2007.
By answering these three questions, this study makes three contributions. First, it unifies the litera- tures on the LoF and on cross-national distance. Both are important concepts in international business and management. However, the existing literature does not integrate these two streams.We link different types of the LoF to different dimensions of cross-national distance. Creating such a connection helps us better understand the nature of these two concepts and also better explains the pattern of FDI both theoretically and empirically. Besides bridging the literatures on the LoF and cross-national distance, this study also contributes to these two areas separately. It contributes to the literature on the LoF by introducing a new typol- ogy to categorize different types of the LoF and considering firm heterogeneity in examining the effects of the LoF. Adopting the OLI paradigm to categorize the LoF and measuring the categorization by cross-national distance enable a systematic approach to understand the LoF. Classifying the impact of the LoF by foreign direct investment motivation helps us understand the distinctive difficul- ties faced by multinationals when they go abroad.
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Copyright © 2016 Strategic Management Society Global Strategy Journal, 6: 309–329 (2016) DOI: 10.1002/gsj.1140
Finally, this study contributes to the literature on cross- national distance by highlighting the contingency nature of the relationship between distance and the location choice of FDI. The existing research findings on this relationship are not conclusive. Our study shows that the relationship is complex and contingent on the types of the LoF and also the FDI motivations.
CATEGORIZING THE LIABILITY OF FOREIGNNESS
The liability of foreignness
The concept of the LoF describes the additional costs multinationals face relative to host country competi- tors when they operate in foreign countries. Hymer (1960) identified several disadvantages of foreign firms, such as the lack of information about the host country. Building on Hymer’s insights, Zaheer (1995) developed the concept of the LoF, which becomes an important concept in the area of interna- tional business and management.
Since the introduction of the concept, scholars have tried to understand different aspects of the LoF (Eden and Miller, 2001; Hennart, Roehl, and Zeng, 2002; Zaheer and Mosakowski, 1997), including its catego- rization. Scholars have proposed different categoriza- tions of the LoF. In a theoretical piece, Calhoun (2002) identified cultural-driven external and internal sources of the LoF. Eden and Miller (2004) grouped the LoF into three specific hazards: unfamiliarity hazards, discrimination hazards, and relational hazards. Qian, Li, and Rugman (2013) distinguished the liability of country foreignness and the liability of regional foreignness. Similarly, Asmussen and Goerzen (2013) unpacked the LoF into regional, cultural, and institutional dimensions.
Cross-national distance
Existing attempts to categorize the LoF did not systematically incorporate the concept of cross- national distance—which is also an important concept in international business—despite the fact that many studies captured the foreignness of the host country by calculating the distance with the home country (Berry et al., 2010; Kostova, 1996; Xu and Shenkar, 2002; Zhou and Guillén, 2015).
Previous studies on cross-national distance have recognized that it is a multidimensional concept. For example, Xu, Pan, and Beamish (2004) measured
normative and regulative distance. Berry et al. (2010) disaggregated the construct of distance by pro- posing a set of multidimensional measures, including economic, financial, political, administrative, cultural, demographic, knowledge, and global connectedness as well as geographic distance.
There is a large body of literature on the impact of different distance dimensions on the various global strategies, such as entry mode choice (Kogut and Singh, 1988) and subsidiary performance (Barkema, Bell, and Pennings, 1996), among others (for a review of the literature, see Werner, 2002). In this study, we focus on the location choice of FDI, which is one of the most important decisions in foreign expansion. Table 1 summarizes the studies in these areas.
The first half of the table includes some of the most influential papers on distance, while the second half focuses on the studies that investigate the relationship between distance and location choice. The findings of the first half of the studies are not consistent. For in- stance, while some found that large cultural distance encourages wholly owned subsidiaries, other found the opposite. These inconsistent findings suggest that the relationship between distance and global strategy is complicated, and we need to adopt a contingency approach to understand it (Drogendijk and Slangen, 2006; Gaur and Lu, 2007).
Most of the recent studies on distance investigate different dimensions of cross-national distance and also recognize the contingency nature of the complex relationship. For instance, Slangen and Beugelsdijk (2010) found that institutional hazards are more nega- tively related to vertical foreign activity than to horizontal foreign activity; and the impact of governance hazards on each type of foreign activity is more negative than the impact of cultural hazards on that type of activity.
Building on these previous studies, we adopt a contingency perspective to understand the relationship between different distance dimensions and foreign location choice. Different from other studies, we explore the contingency by linking different distance dimensions to different types of the LoF, and we also distinguish different FDI motivations.
In this study, we adopt Berry et al. (2010)’s distance dimensions as our pool of selection for differ- ent distance dimensions and pick up the most relevant distance dimensions for each type of the LoF. We choose this distance classification for both theoretical and empirical reasons. Theoretically, this classifica- tion is comprehensive, and Berry and her colleagues grounded their analyses and choice of dimensions on
Categorizing the Liability of Foreignness 311
Copyright © 2016 Strategic Management Society Global Strategy Journal, 6: 309–329 (2016) DOI: 10.1002/gsj.1140
T ab le 1.
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312 N. Zhou and M. F. Guillen
Copyright © 2016 Strategic Management Society Global Strategy Journal, 6: 309–329 (2016) DOI: 10.1002/gsj.1140
institutional theories of national business, governance, and innovation systems (Henisz and Williamson, 1999; La Porta et al., 1998; Nelson and Rosenberg, 1993; Whitley, 1992), resulting in nine dimensions, including cultural, economic, demographic, political, administrative, financial, knowledge, global connectiveness, and geographic distance.1 They approached cross-national distance from an institu- tional perspective so as to capture the rich diversity of ways in which countries differ, thus following recent institutional theorizing in the field of interna- tional business (Jackson and Deeg, 2008; Pajunen, 2008). Empirically, in order to overcome the limita- tions of the Euclidean approach, they calculated dyadic distances using the Mahalanobis method, which is scale invariant and takes into consideration the variance–covariance matrix.
Categorizing different types of the LoF by the OLI paradigm
The OLI paradigm suggests that the decision to invest internationally and the impact of the investment reflect the joint effects of O-specific, L-specific, and I-specific advantages (Dunning, 1993; Dunning and Lundan, 2008b). O-specific advantage arises from multinationals’ ownership of, or access to, a set of income-generating assets, or capabilities to coordinate these assets, in a way that benefits them relative to their competitors. L-specific advantages refer to spe- cific resources and market conditions of a host country that are potentially available to all firms. I-specific advantage reflects the greater organizational effi- ciency or superior incentive structure of hierarchies, or the ability to exercise monopoly power over the assets under common governance. The OLI paradigm has been used widely by scholars to explain why firms invest abroad and the patterns of FDI across countries (Hill, Hwang, and Kim, 1990; Li et al., 2013; Singh and Kundu, 2002). The paradigm is designed to explain the advantages of multinationals and how these advantages motivate FDI. Few previous studies adopted this paradigm to examine the disadvantages that multinationals face when they invest abroad (Denk, Kaufmann, and Roesch, 2012; Dunning, 2000).
1 In our analyses, we excluded financial, knowledge, and global connectiveness dimensions because of high correlations with other dimensions.T
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Categorizing the Liability of Foreignness 313
Copyright © 2016 Strategic Management Society Global Strategy Journal, 6: 309–329 (2016) DOI: 10.1002/gsj.1140
In this study, we adopt the OLI paradigm to catego- rize different types of the LoF for two reasons. First, the OLI paradigm is a comprehensive framework that synthesizes many theories to explain the globalization of multinationals. It is one of the most well-accepted frameworks in the international business literature (Eden and Dai, 2011; Portugal Ferreira et al., 2011). As we can see from Table 1, many of the studies on distance and foreign direct investment use transaction cost theory, the Uppsala model, and institutional theory. The OLI paradigm is a synthesis of these different theories. For instance, O-specific and I-specific advantages are related to transaction cost theory because the internalization of O-specific advan- tages reduces transaction costs. L-specific advantage is related to the Uppsala model, because locational factors such as cross-national distance determine the path of globalization. Adopting the OLI paradigm ensures that our categorization considers the dominant factors that influence the internationalization of multi- nationals. Second, the OLI paradigm highlights the advantages that encourage firms to go abroad. It is exactly the opposite of the LoF, which describes the disadvantages multinationals face when they go abroad. Such a corresponding relationship between the two concepts enables us to consider the pros and cons of globalization using the same framework.
Ownership-specific LoF refers to the costs that reduce O-specific advantage. An important part of O-specific LoF is product adaptation cost. O-specific advantages are usually exemplified by the superiority of products in terms of quality, price, technology, or special features (Agarwal and Ramaswami, 1992; Anand and Delios, 2002). Differences between host and home countries in terms of consumer demand may reduce O-specific advantage because multina- tionals need to pay additional costs—first to identify the differences and then to adjust their products to suit the demands of local customers. We label such costs as product adaptation costs. For example, Nokia developed handset models specific to India with features such as a flashlight, a dust cover, and a slip-free grip.
Location-specific LoF refers to the costs that reduce L-specific advantage. Discrimination cost is an important part of L-specific LoF. Discrimination costs refer to the costs derived from unfavorable treat- ment by the host country government when multina- tionals try to acquire locational-bound resources in foreign countries. Governments increase discrimina- tion costs by imposing rules and regulations against foreign firms (Kobrin, 1987; Meschi, 2009),
especially when foreign firms try to acquire local nat- ural resources (e.g., minerals, oil, or gas) or technol- ogy (Garcia-Canal and Guillen, 2008; Henisz, Dorobantu, and Nartey, 2014). Biases held by the host country government against foreign firms reduce multinationals’ legitimacy in the foreign country (Brouthers, O’Donnell, and Hadjimarcou, 2005; Kostova and Zaheer, 1999), resulting in unfavorable consequences, such as disapprovals of foreign invest- ments (Ambos and Ambos, 2009), and more stringent requirements on the operation of multinationals (Wang, 2007).
Internalization-specific LoF refers to the costs that reduce MNEs’ internalization advantage. Governance costs and appropriation costs are two important parts of I-specific LoF. Governance costs refer to multina- tionals’ additional costs of managing foreign subsidi- aries because of increased communication and coordination costs (Hennart, 2001). For instance, a foreign manager will spend more time and effort com- municating with his/her local subordinates when they do not share the same language, thus increasing gover- nance costs, which become part of the I-specific LoF.
Appropriation costs are the costs associated with the possibility of expropriation of the foreign invest- ment by the government. Foreign direct investment is more risky than other modes of foreign entry (such as exports or franchising) because it involves direct investment in foreign countries (Tallman, 1991). When firms choose to internalize foreign operations by conducting foreign direct investment, appropria- tion costs become a primary concern. The risk origi- nates from the possibility that once an MNE has sunk the capital necessary to conduct business opera- tions in a country, the government may at some future point face incentives to renegotiate the terms of invest- ment in order to redistribute the MNE’s returns (Henisz and Zelner, 2004). An extreme case would be the seizure of the foreign investment by the govern- ment. The three types of the LoF and the associated costs are summarized in Columns 1 and 2 of Table 2.
DIFFERENT TYPES OF THE LIABILITY OF FOREIGNNESS BY TYPE OF FOR- EIGN DIRECT INVESTMENT
The LoF can influence multinationals in different ways (Miller and Parkhe, 2002). In particular, it affects the process by which multinationals interna- tionalize (Denk et al., 2012): they first enter countries associated with lower degrees of the LoF (Johanson
314 N. Zhou and M. F. Guillen
Copyright © 2016 Strategic Management Society Global Strategy Journal, 6: 309–329 (2016) DOI: 10.1002/gsj.1140
and Wiedersheim-Paul, 1975). Although the three different types of the LoF pose additional costs for all foreign direct investments, their relative impor- tance differs by type.
In his work, Dunning identified four types of foreign direct investment in terms of motivations: market-seeking, efficiency-seeking, strategic asset- seeking, and natural resource-seeking foreign direct investment (Dunning and Lundan, 2008b). Market- seeking FDI is undertaken to sell products in foreign countries. The objective of efficiency-seeking FDI is to gain from the common governance of geographi- cally dispersed activities to reduce costs. Strategic asset-seeking FDI is conducted to promote long-term strategic objectives, such as sustaining or advancing global competitiveness through the acquisition of new capabilities. Natural resource-seeking FDI occurs when multinationals invest abroad to acquire particu- lar and specific resources that do not exist in the home country or are available at a higher quality and/or lower cost in the host country. Although the three types of the LoF are relevant to all four types of foreign direct investment, their relative importance differs, as shown in Columns 3–6 of Table 2. Next, we will explain the rationales in detail.
Market-seeking foreign direct investment
Because the primary objective of market-seeking for- eign direct investment is to sell products in the host country by exploiting the multinationals’ O-specific advantages, differences in product demands between the home and host markets become the major concern of multinationals. Such differences jeopardize the O-specific advantages that multinationals enjoy. Therefore, multinationals need to adjust their products to address the differences. Product adaptation costs are especially important in market-seeking foreign direct investment.
We measure product adaptation costs by different dimensions of cross-national distance. Product adapta- tion costs increase with cross-national distance because it reflects differences in consumer demand and, thus, the need to adapt. As mentioned earlier, we apply multiple distance dimensions developed by Berry et al. (2010) to measure product adaptation costs.
Product adaptation costs are high when consumer demands in host and home countries are different. The most relevant distance dimensions are those closely related to consumer preference: cultural,T
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Categorizing the Liability of Foreignness 315
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economic, and demographic distance. Cultural distance refers to the difference in cultural values and norms, and it creates product adaptation costs by influencing the choices that consumers make because of their preference (Ghemawat, 2001). For example, consumer durable industries are particularly sensitive to differences in consumer tastes and preferences. The Japanese prefer small automobiles and household appliances because of the social norm common in countries where space is highly valued.
Product adaptation costs are also associated with economic distance. Economic distance reflects the difference in consumer purchasing power between two countries. Purchasing power is the ability of consumers to buy. In general, the more economically developed a country, the more purchasing power consumers in that country have. Because before expanding abroad, the firm typically sells goods and services tailored to the characteristics of the home country (Vernon, 1979), differences in purchasing power and other economic characteristics have an impact on demand conditions and, therefore, the need to adapt.
Product adaptation costs are also affected by demo- graphic distance, which captures national difference in terms of the size, growth, and age structure of popula- tion (Berry et al., 2010). These differences have direct implications for market attractiveness and growth potential. Differences in factors such as life expec- tancy, birth rates, and the resulting age structure of the population, among others, attest to fundamental characteristics of the population of countries and may affect consumer behavior and, thus, the need to adapt.
Summarizing these arguments on product adapta- tion costs, we predict that:
Hypothesis 1: Cultural distance, economic dis- tance, and demographic distance reduce market-seeking foreign direct investment.
Efficiency-seeking foreign direct investment
Efficiency-seeking foreign direct investment critically depends on the balance between the advantages gained from spreading value-added activities across various locations and the costs of communication and coordination over distance (Aarland et al., 2007). Because of the relatively low international mobility of labor, wage differentials between home
and host countries can become a major determinant of efficiency-seeking foreign direct investment (Kimino, Saal, and Driffield, 2007). Various empirical studies have supported the prediction that lower wages attract foreign direct investment (Taylor, 2000). Therefore, efficiency-seeking foreign direct invest- ment is conducted to acquire L-specific advantage (low labor cost) in foreign markets. Accordingly, the L-specific LoF is important. Discrimination cost from the actions by the foreign government becomes a major concern for efficiency-seeking foreign direct investment. For example, the government could impose more stringent regulations on the operation of multinationals (Wang, 2007).
Discrimination cost is closely related to political distance, which captures the difference in institutional checks and balances (Demirbag, Glaister, and Tatoglu, 2007; Dow and Karunaratna, 2006; Henisz, 2000), democratic character, the size of the state rela- tive to the economy, and external trade associations (Brewer, 2007; Hirschberg, Sheldon, and Dayton, 1994). For efficiency-seeking foreign direct invest- ments, the primary source of discrimination by host country government is political distance, because discrimination treatment is more likely to happen to multinationals from countries with large political distance because of the host country government’s unfamiliarity with the home country’s political system (Brandt and Li, 2003).
Host country governments can increase discrimina- tion costs by imposing rules and regulations against foreign firms (Kobrin, 1987; Meschi, 2009). Host country governments tend to associate foreign firms with negative images because of unfamiliarity (Ewing, Windisch, and Newton, 2010). Such images reduce foreign multinationals’ legitimacy in foreign countries (Brouthers et al., 2005; Kostova and Zaheer, 1999), resulting in unfavorable consequences such as the reluctance of the host country government to allow foreign investment from emerging markets (Ambos and Ambos, 2009) and more stringent requirements on the operation of foreign multinationals (Wang, 2007). Therefore, discrimination costs faced by efficiency-seeking FDI increase with the political distance between host and home countries.
Efficiency-seeking foreign direct investment is also influenced by I-specific LoF. Because hiring foreign employees with lower wages is an important driver for efficiency-seeking FDI, governance costs associ- ated with managing foreign employees become the primary concern for managers. Governance costs grow with administrative distance, which refers to
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differences in bureaucratic patterns owing to colonial ties, language, religion, and the legal system (Ghemawat, 2001; La Porta et al., 1998; Whitley, 1992). While one could argue that administrative distance is related to cultural distance, we believe it is distinct because it goes beyond it to include both formal and informal institutional arrangements in a society. Administrative distance increases governance costs by raising communication, coordination, and administrative costs. For example, a Chinese manager may find it difficult to communicate with its French subordinates because of language barriers.
Appropriation costs are also important in efficiency-seeking FDI because establishing manufacturing facilities in foreign countries usually involves large investments in plants, equipments, raw materials, and other necessary inputs (Henisz and Delios, 2001). Therefore, the concern about potential appropriation is also a primary consideration in efficiency-seeking foreign direct investment.
Different from other costs that are increased by cross-national distance, appropriation costs are enhanced by political hazards (Delios and Henisz, 2000). Political hazards in a country are high when policy makers can act unilaterally or have high certainty that a subservient or allied legislature and judicial branch will support their actions, because future policies are likely to be particularly volatile in response to exogenous shocks, to changes in the iden- tity of policy makers, or to changes in the preferences of existing policy makers (Delios and Henisz, 2003). When political hazards are high, multinationals face high appropriation costs because the government can easily change policy or, at the extreme, seize the firm’s foreign assets.
Summarizing these arguments on discrimination costs, governance costs, and appropriation costs, we predict:
Hypothesis 2: Political distance, administrative distance, and political hazards reduce efficiency-seeking foreign direct investment.
Strategic asset-seeking foreign direct investment
Strategic asset-seeking FDI is driven by the multina- tionals’ need to access new resources and capabilities in foreign countries. In strategic asset-seeking FDI, there are two primary objectives: to acquire foreign strategic assets such as knowledge and to transfer it
within the multinational (Li et al., 2013; Lu, Liu, and Wang, 2011). While the former is related to dis- crimination cost, the latter is related to governance cost and appropriation cost.
Discrimination costs are important for strategic asset-seeking FDI because multinationals need to obtain approval from the host country government to acquire strategic assets. Strategic assets such as technology and brand are best acquired through ac- quisition (Elango and Pattnaik, 2011; Luo et al., 2011). Discrimination costs are high when acquisi- tions by foreign firms are conceived by local stake- holders as sensitive and undesirable (Graham and Marchick, 2006). The host country government may create barriers by banning acquisitions, because of the fear that national security would be threat- ened. For example, Huawei, a Chinese telecommu- nication device provider, failed in its attempt to acquire 3leaf, an American company, because the U.S. government did not approve the acquisition out of national security concerns. Therefore, discrimination costs are important in strategic asset-seeking foreign direct investment. We have argued earlier that discrimination costs are increased by political distance.
In strategic asset-seeking foreign direct investment, another important consideration is how to transfer the acquired assets or knowledge within the firm effec- tively (Makino and Delios, 1996; Steensma et al., 2000). Therefore, I-specific costs are important. Many scholars have argued that some knowledge is partially tacit and transfer requires frequent interactions within the organization (Almeida, 1996; Kogut and Zander, 1992; Nelson and Winter, 1982). The efficiency of such transfer is closely related to governance costs because external or ‘imported’ knowledge needs to be adapted to different conditions and shared within the MNE (Teece, 1986), and such adaptation and transfer increases the costs of monitoring and manag- ing. We have argued earlier that governance costs are enhanced by administrative distance.
Another component of I-specific LoF is appropria- tion costs. Strategic asset-seeking FDI usually takes the form of mergers and acquisitions (Batson, 2007), and conducting mergers and acquisitions in foreign countries requires a large amount of investment. Therefore, concern of appropriation is also a primary consideration in strategic asset-seeking foreign direct investment.
Summarizing these arguments on discrimination costs, governance costs, and appropriation costs, we predict:
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Hypothesis 3: Political distance, administrative distance, and political hazards reduce asset- seeking foreign direct investment.
Natural resource-seeking foreign direct investment
In natural resource-seeking FDI, the primary goal is to acquire foreign natural resources. Accordingly, dis- crimination costs are crucial. Similar to strategic asset-seeking FDI, it is critical for natural resource- seeking FDI to obtain approval from the host country government. The difficulties frequently faced by multinationals when it comes to obtaining licenses and approvals from the host country government in natural resource industries have been documented extensively in the literature (Globerman and Shapiro, 2009; Henisz et al., 2014). We have argued earlier that discrimination costs increase with political distance. Thus, we expect that:
Hypothesis 4: Political distance reduces natural resource-seeking foreign direct investment.
METHODOLOGY
Empirical setting
To test the hypotheses, we used data on the foreign en- tries made by Chinese listed firms from 1999 to 2007. The data begin in the year of 1999 because the ac- counting rules in China required listed firms to report foreign subsidiaries systematically only after 1999. The data on foreign subsidiaries before 1999 is likely to be unreliable or uncomprehensive. Including data prior to 1999, however, does not change the results we report. This Chinese sample provides an excellent research setting for three reasons. First, China has become one of the largest outward FDI investors in the world. Chinese outward FDI is increasing rapidly, from $0.9 billion in 1991 to $101 billion in 2013 (UNCTAD, 1996, 2014). Second, Chinese firms have invested in a wide array of countries, including 23 developed countries and 52 developing countries in our sample. Third, Chinese firms started to globalize during the 1990s. Examining Chinese firms from the early stage of globalization avoids left-censoring problems.
For each Chinese firm in the sample, we reviewed their annual reports to identify any foreign subsidiary.
In cases in which not enough information was pro- vided, we searched other internet sources or contacted the company. Chinese listed firms are required to dis- close information on major subsidiaries (e.g., country of entry, amount of capital invested, percentage of ownership, and primary business activities or major products) in the appendix of their annual reports. And then, we determined the establishment year of each subsidiary as given in the annual report, on the company’s website, or through further internet searches. We obtained ownership information from Guo Tai An (GTA), a research service center. Finally, we collected financial data from China Stock Market Accounting Research (CSMAR), a database that is part of Wharton Research Data Services. Overall, there are 256 Chinese firms owning 649 foreign subsidiaries in 38 countries from 1999 to 2007.
Variable definitions
Dependent variables
We identified different types of foreign direct invest- ment through the description of subsidiaries’ business activities in the company’s annual report. Market- seeking foreign direct investment includes foreign subsidiaries that sell products in a given host country. Efficiency-seeking foreign direct investment includes foreign subsidiaries that produce but do not sell prod- ucts in a host country. Strategic asset-seeking foreign direct investment includes foreign subsidiaries that conduct research and development activities in a host country. Natural resource-seeking foreign direct in- vestment includes foreign subsidiaries that exploit natural resources, such as mining or fishing, in a host country. It is possible that an MNE enters a foreign country in a year for multiple reasons. In this case, this particular firm-country-year appears in our dataset multiple times, but each type of foreign direct investment appears only once. When the information on foreign subsidiaries is not comprehensive enough to determine the purpose of a foreign subsidiary, we searched the company’s website or did a web search to find out detailed information on the nature of the foreign subsidiary. In some cases, we contacted the company to ask about the particular foreign subsidiary. We hired two research assistants to code the different types of FDI, and the inter-rater reliability correlation coefficient was +0.92. When there was a disagree- ment, one of the authors decided which coding to adopt based on further research on the subsidiary.
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For each Chinese firm, the foreign direct invest- ment dependent variables are dummies that equal to ‘1’ if a firm makes a certain type (market seek- ing, efficiency seeking, strategic asset seeking, or natural resource seeking) of FDI in a certain host country in a certain year, and it is ‘0’ otherwise. The level of analysis is firm-country-year. Because not all parent firms are listed from the beginning of our study period, we have an unbalanced panel dataset.
Independent variables
Cross-national distance measures come from the data- base developed by Berry et al. (2010). Details about
cultural, economic, demographic, political, and administrative distance are summarized in Table 3.
Political hazard is measured by the POLCONV index. This annual time-varying measure obtained from Henisz (2000) quantifies the extent to which any one institutional actor—e.g., the executive or a legislative chamber—in a given country is uncon- strained in its choice of policies. It has been used widely by scholars to measure political hazard (Delios and Henisz, 2003; Holburn and Zelner, 2010; Slangen, 2013).
Control variables
We used the percentage held by the top 10 share- holders to measure ownership concentration. Managers may choose to invest abroad to pursue their own interests rather than shareholders’. High ownership concentration suggests large owners
2 The information in this table is from Berry et al. (2010).
Table 3. Details about distance dimensions2
Dimension Component variables Source
Cultural distance Power distance WVS questions on obedience and respect for authority World Value Survey Uncertainty avoidance WVS questions on trusting people and job security World Value Survey Individualism WVS questions on independence and the
role of government in providing for its citizens World Value Survey
Masculinity WVS questions on the importance of family and work World Value Survey Economic distance Income GDP per capita (in 2000 U.S. dollars) WDI Inflation GDP deflator (% GDP) WDI Exports Exports of goods and services (% GDP) WDI Imports Imports of goods and services (% GDP) WDI Demographic distance Life expectancy Life expectancy at birth, total (years) WDI Birth rate Birth rate, crude (per 1,000 people) WDI Population under 14 Population ages 0–14 (% of total) WDI Population under 65 Population ages 65 and above (% of total) WDI Political distance Policy-making uncertainty Political stability measured by considering independent
institutional actors with veto power POLCON
Democratic character Democracy score Freedom House Size of the state Government consumption (% GDP) WDI WTO member Membership in WTO (GATT before 1993) WTO Regional trade agreement Dyadic membership in the same trade bloc WTO Administrative distance Colonizer-colonized link Whether dyad shares a colonial tie CIA Factbook Common language % population that speaks the same language in the dyad CIA Factbook Common religion % population that shares the same religion in the dyad CIA Factbook Legal system Whether dyad shares the same legal system La Porta et al., 1998
CIA, Central Intelligence Agency; GATT, General Agreement on Tariffs and Trade; GDP, gross domestic product; POLCON, political constraint; WDI, World Development Index; WTO, World Trade Organization; WVS, World Value Survey.
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have more incentive and power to monitor managers’ behavior, thus reducing agency problems (Fama and Jensen, 1983; Jensen and Meckling, 1976).
Product diversification also influences the proba- bility of foreign direct investment in that it is resource consuming and, thus, competes with globalization for scarce resources such as capital. However, the experience generated from product diversification also might be applied to globaliza- tion. Research on the relationship between product diversification and globalization remains inconclu- sive (Doukas and Lang, 2003; Tallman and Li, 1996). We controlled for product diversification using the concentric index developed by Montgom- ery and Wernerfelt (1988).
A firm’s size may influence the pattern of its multinational activity (Swaminathan and Delacroix, 1991) and provide an indicator of its ability to survive in foreign markets. Larger firms should be more likely to go abroad, whereas smaller firms likely lack the knowledge and experience to expand overseas. We measured firm size by the logarithm of total sales.
A firm’s agemay also influence the probability of it investing abroad because older firms may be subject to inertia, which will prevent strategic changes (Hannan and Freeman, 1977). We measured age by the number of years since founding.
Better-performing firms are more likely to invest abroad because they have the necessary resources and capabilities. Therefore, we controlled for firm per- formance by return on assets, or ratio of net profit to total assets.
Because firms can learn from their international experiences (Barkema and Vermeulen, 1998; Delios and Henisz, 2003; Hitt, Li, and Worthington, 2005), we also controlled for a firm’s prior international experience, which is measured by the total number of foreign investments a firm made before the year of a potential entry.
We controlled for geographic distance because it influences transportation costs. It is calculated by using the great circle method. For each type of foreign direct investment, we also control for host country locational advantage. For market-seeking foreign direct investment, we include the size of the population, which is measured by a country’s population. For efficiency-seeking foreign direct investment, we include gross domestic product per capita as a control for the level of labor cost. For strategic asset-seeking foreign direct investment,
we include the number of patents per million people as a control for the stock of knowledge and technol- ogy in a country. For natural resource-seeking foreign direct investment, we include total natural resource rents as a percentage of gross domestic product to control for the stock of natural resource in a country. Total natural resource rents are the sum of oil rents, natural gas rents, coal rents (hard and soft), mineral rents, and forest rents. The data source for these locational factors is the World Development Index.
Finally, to control for possible industry and time effects, we included industry and year dummies in all regressions.
Estimation method
Because the dependent variables are dummy vari- ables, we used logit regression. We constructed the dataset by including all of the possible combinations of firm-country-year observations. Given that only a small proportion of the dependent variable has the value of one, we estimated rare-event logistic regres- sion models. The relogit command in STATA generates approximately unbiased and lower-variance estimates of logit coefficients and their variance–covariance matrix by correcting for small samples and rare events (King and Zeng, 2001). We used the cluster option in STATA to account for intragroup variance. We did not use the conditional logit model because it has several limitations, such as the inability to accommodate or control for the effects of firm-level heterogeneity (Martin, Swaminathan, and Tihanyi, 2007). We also provide additional results using seemingly unrelated regression.
RESULTS
Table 4 provides the means, standard deviations, and correlations for the sample. The mean values of the dependent variables are close to zero, which confirm that our choice of rare-event logit regression is appro- priate. In order to reduce the correlations among different distance dimensions and also to compare coefficients, we normalized them. The correlations of most normalized distance dimensions are not high. We also checked the variance inflation factor scores, and they are lower than 10. Therefore, there is no serious multicollinearity.
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T ab le 4.
M ea ns ,s ta nd ar d de vi at io ns ,a nd
co rr el at io ns
# V ar ia bl es
M ea n
1 2
3 4
5 6
7 8
9 10
11 12
13 14
15 16
1 M ar ke t- se ek in g fo re ig n di re ct in ve st m en t
0. 00 04
0. 02
1. 00
2 E ff ic ie nc y- se ek in g fo re ig n di re ct in ve st m en t
0. 00 00
0. 00
0. 00
1. 00
3 St ra te gi c as se t- se ek in g fo re ig n di re ct in ve st m en t
0. 00 01
0. 01
0. 00
0. 00
1. 00
4 N at ur al re so ur ce -s ee ki ng
fo re ig n di re ct in ve st m en t
0. 00 00
is ta nc e
6 E co no m ic di st an ce
0. 00
1. 00
0. 01
0. 00
0. 02
0. 01
0. 00
1. 00
0. 00
0. 00
0. 01
0. 00
0. 00
1. 00
0. 01
0. 00
0. 01
0. 00
0. 00
1. 00
0. 01
0. 00
0. 01
0. 00
in is tr at iv e di st an ce
0. 00
1. 00
0. 00
0. 00
0. 00
0. 00
0. 39
0. 39
0. 11
0. 22
1. 00
11 O w ne rs hi p co nc en tr at io n
61 .2 3
13 .0 6
iv er si fi ca tio
n 0. 17
as se ts
1. 00
16 Pr io r in te rn at io na le xp er ie nc e
0. 18
2. 00
0. 01
0. 00
0. 00
0. 04
0. 01
1. 00
17 G eo gr ap hi c di st an ce
0. 00
1. 00
0. 00
0. 00
0. 00
0. 00
n = 13 6, 51 3. C or re la tio
ns gr ea te r th an
0. 00 9 ar e si gn if ic an ta tt he
0. 01
le ve l( tw o- ta ile d te st ).
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Table 5 shows the results of the rare-event logit re- gressions for Chinese firms to test Hypotheses 1–4. There are eight model specifications in the table. The dependent variable of Models 1 and 2 in Table 6 is market-seeking FDI; of Models 3 and 4 is efficiency- seeking FDI; of Models 5 and 6 is strategic asset- seeking FDI; and of Models 7 and 8 is natural resource-seeking FDI. Models 1, 3, 5, and 7 are the baseline models that include only control variables. In Models 2, 4, 6, and 8, we entered the distance di- mensions that measure the three different types of the LoF.
First, we focused onmarket-seeking FDI. InModel 2, all three measures of O-specific LoF (product adap- tation costs)—cultural, economic, and demographic distance—are negative and significant, while neither L-specific LoF (discrimination costs: political dis- tance) nor I-specific LoF (appropriation costs: politi- cal hazard; and governance costs: administrative distance) are significant. The results suggest that the three measures of product adaptation costs have greater impact on the location choice of market- seeking foreign direct investment. Therefore, Hypothesis 1 is supported.
In addition to being statistically significant, these effects are also large in magnitude. In Model 2, hold- ing other variables at their mean values, when cultural distance increases from the 25th percentile to the 75th percentile, the probability of investing decreases by 97.7 percent. The same number is 60.3 percent for de- mographic distance and 23.5 for economic distance. The results show that although absolute risk is low, product adaptation costs do have a large impact on the relative risk of foreign direct investment.
In Model 4, political distance, political hazard, and administrative distance are negative and significant, while cultural, economic, and demographic distance are not significant. The results suggest that L-specific LoF and I-specific LoF, not O-specific LoF, are the major obstacles of efficiency-seeking foreign direct investment. Therefore, Hypothesis 2 is supported. In Model 4, holding other variables at their mean values, when political distance, political hazard, and adminis- trative distance increase from the 25th percentile to the 75th percentile, the probability of investing decreases by 11.9 percent, 15.5 percent, and 47.1 percent, respectively.
The results inModel 6 are similar to those inModel 4. Political distance, political hazard, and administra- tive distance are all negative and significant. Therefore, Hypothesis 3 is also supported. In Model 6, holding other variables at their mean values, when political
distance, political hazard, and administrative distance increase from the 25th percentile to the 75th percentile, the probability of investing decreases by 20.3 percent, 8.9 percent, and 37.8 percent, respectively.
In Model 8, only political distance is negative and significant. The results show that discrimination costs are the primary concern for natural resource-seeking foreign direct investment. So, Hypothesis 4 is also supported. In Model 8, holding other variables at their mean values, when political distance increases from the 25th percentile to the 75th percentile, the probabil- ity of investing decreases by 23.6 percent.
Among the control variables, product diversifica- tion is negative and significant in most models. Firms that engage in greater product diversification are less likely to invest abroad, because of resource con- straints. Ownership concentration is negative in some models, suggesting that firms with concentrated owners are less prone to encounter agency problem and, thus, are less likely to invest abroad. Log of sales is positive and significant: larger firms are more likely to invest abroad because they are more likely to pos- sess the resources to support foreign expansion. Firm age is negative and significant, indicating that older firms are subject to greater inertia and less likely to un- dertake strategic changes (Freeman, Carroll, and Hannan, 1983). Return on assets is positive and signif- icant in some models: better-performing firms are more likely to invest abroad. Prior international expe- rience is positive and significant in efficiency-seeking and natural resource-seeking foreign direct invest- ment, showing that prior international experience en- courages firms to conduct these two types of foreign direct investment. Host country locational advantage is positive and significant in most models, indicating that host country locational advantage is indeed an im- portant driver for different types of foreign direct in- vestment. Finally, geographic distance is negative and significant only in efficiency-seeking foreign di- rect investment. In other types of foreign direct invest- ment, geographic distance is insignificant or even positive and significant, meaning that multinationals do overcome physical distance and its associated costs such as transportation costs in market-seeking, strate- gic asset-seeking, and natural resource-seeking foreign direct investment.
Robustness checks
Because it is possible that a multinational enters a for- eign country in a year for multiple motivations, we
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T ab le 5.
R ar e- ev en tl og it re gr es si on s of
di st an ce
di m en si on s on
di ff er en tt yp es
of fo re ig n di re ct in ve st m en t
V ar ia bl es
M od el 1
M od el 2
M od el 3
M od el 4
M od el 5
M od el 6
M od el 7
M od el 8
va ri ab le
I (H
1) E ff ic ie nc y- se ek in g FD
I( H 2)
St ra te gi c as se t- se ek in g FD
I (H
3) N at ur al re so ur ce -s ee ki ng
FD I (H
ar ia bl es
is ta nc e
0 .2 6+
0 .1 2
0 .0 8
0 .0 5
(0 .1 5)
(0 .1 9)
(1 .2 9)
(0 .3 3)
0 .4 1* *
0 .0 9
0 .0 7
0 .0 4
(0 .1 5)
(8 .1 3)
(0 .0 8)
(0 .0 3)
0 .0 7
0 .0 5* **
0 .0 9*
0 .1 8* **
(0 .2 7)
(0 .0 0)
(0 .0 4)
(0 .0 3)
0. 22
in is tr at iv e di st an ce
0 .2 3
0 .4 4* **
0 .2 6*
0 .7 4
(0 .1 6)
(0 .0 8)
(0 .1 2)
(0 .9 2)
n 0
.3 0+
0 .2 9+
1 .2 2
1 .1 9
0 .5 6*
0 .4 9+
1 .3 5
0 .8 2* **
(0 .1 7)
(0 .1 7)
(2 .5 8)
(2 .5 9)
(0 .2 6)
(0 .2 6)
(0 .1 4)
(0 .1 8)
O w ne rs hi p co nc en tr at io n
0 .0 2
0 .0 2
0 .0 3
0 .0 3
0 .0 1
0 .0 1
0 .1 1* **
0 .0 8* **
(0 .0 1)
(0 .0 1)
(0 .0 3)
(0 .0 3)
(0 .0 3)
(0 .0 2)
(0 .0 1)
(0 .0 2)
as se ts
G eo gr ap hi c di st an ce
0. 21 *
0. 13
0 .6 0
0 .8 2* **
0 .0 4
0 .6 3
0 .4 8
0 .3 1
(0 .1 0)
(0 .1 1)
(0 .8 1)
(0 .0 9)
(0 .2 5)
(0 .7 5)
(1 .4 4)
(0 .3 9)
Pr io r in te rn at io na le xp er ie nc e
0 .0 8
0 .0 9
L oc at io na la dv an ta ge
0. 10 **
0. 11
0. 07 *
0. 11 ** *
0. 01 ** *
0. 01
0. 17
0. 28 ** *
3 4. 87 ** *
3 4. 43 ** *
In cl ud ed
In cl ud ed
In cl ud ed
In cl ud ed
In cl ud ed
In cl ud ed
In cl ud ed
In cl ud ed
13 6, 51 3
13 6, 51 3
13 6, 51 3
13 6, 51 3
13 6, 51 3
13 6, 51 3
13 6, 51 3
13 6, 51 3
3 25 .8 9
3 05 .0 9
0. 31
0. 35
0. 20
0. 41
0. 25
0. 30
0. 41
0. 53
R ob us ts ta nd ar d er ro rs ar e in
pa re nt he se s. FD
I, fo re ig n di re ct in ve st m en t.
+ p <
p <
0. 00 1 (t w o- ta ile d te st s) .
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checked for the robustness of our results by simulta- neously estimating the four models of market-seeking, efficiency-seeking, strategic asset-seeking and natural resource-seeking FDI using seemingly unrelated re- gression model. STATA does not support seemingly un- related regression for rare-event logit models. Therefore, we used a logit model instead. The results are summarized in Table 6. The results are largely consistent with those in Table 5. Every distance di- mension that was significant in Table 6 remained neg- ative and significant in Table 6.
DISCUSSION AND CONCLUSION
In this study, we adopted the OLI paradigm and cate- gorized the LoF into three different types: O-specific, L-specific, and I-specific LoF. We linked the three different types of LoF with different dimensions of cross-national distance, and we then argued that mul- tinationals face different types of the LoF (as mea- sured by different dimensions of cross-national distance) when they operate abroad for different rea- sons. The empirical test on a sample of Chinese firms
Table 6. Robustness checks
Dependent variables Market- seeking FDI
Efficiency- seeking FDI
(0.19) (0.87) (0.40) (0.36) Economic distance 0.27+ 0.10 0.02 0.09
(0.15) (0.18) (1.28) (1.41) Demographic distance 0.43** 0.54 0.86 0.09
(0.15) (2.52) (0.83) (0.21) Political distance 0.10 0.15*** 0.07* 0.12***
(0.27) (0.02) (0.03) (0.03) Political hazard 0.26 0.05*** 0.02+ 0.11
(0.18) (0.00) (0.01) (0.19) Administrative distance 0.24 0.43*** 0.48** 0.56
(0.16) (0.09) (0.20) (0.78) Product diversification 0.22 0.19 0.39 1.67***
(0.17) (0.26) (0.28) (0.18) Ownership concentration 0.02 0.04 0.01 0.11***
(0.02) (0.03) (0.03) (0.02) Log of sales 1.37*** 0.68 0.95*** 0.75***
(0.24) (0.60) (0.22) (0.15) Age 0.28*** 0.10 0.41*** 0.02
(0.08) (0.12) (0.12) (0.10) Return on assets 1.02 5.60+ 4.10*** 5.67***
(1.31) (3.33) (1.26) (0.57) Locational advantage 0.10 0.11*** 0.01 0.03
(0.07) (0.01) (0.01) (0.04) Geographic distance 0.14 0.08*** 0.09 1.56***
(0.11) (0.00) (0.08) (0.39) Prior international experience 0.10 0.15 0.32 0.30***
(0.08) (0.17) (0.32) (0.06) Industry and year dummies Included Included Included Included Constant 35.52*** 264.36*** 45.17*** 11.43***
(8.15) (20.45) (7.74) (3.15) Number of observations 136,513 136,513 136,513 136,513
Robust standard errors are in parentheses. + p < 0.1 * p < 0.05 ** p < 0.01 *** p < 0.001 (two-tailed tests).
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supported our hypotheses. Our analyses have both theoretical and practical implications.
Theoretically, we contribute to the literature on the LoF by identifying and measuring different types of the LoF. Although scholars have tried to categorize different types of the LoF, we advance our under- standing of the LoF in three ways. First, we adopted the OLI paradigm as the theoretical foundation of our categorization. Unlike other studies that lack a comprehensive framework to support their categoriza- tion, we adopted the OLI paradigm—one of the most comprehensive and well-accepted theories to explain FDI—as the theoretical foundation for our categoriza- tion. By adopting the OLI paradigm, we also catego- rize the LoF by its impact and not by its source, as most other studies did. Second, we highlighted the role of firm heterogeneity in assessing the impact of the LoF. We showed that firms face different types of the LoF according to different motivations for engaging in foreign direct investment. Our study is one of the first to examine how the various types of the LoF influence foreign entry decisions when multi- nationals invest abroad for different motivations. Third, we also empirically measure different types of the LoF by different dimensions of cross-national distance. Previous attempts to categorize the LoF are largely theoretical. Our study advances our under- standing of the LoF by empiricallymeasuring and test- ing different types of the LoF.
Our study also contributes to the literature on dis- tance by linking distance to the LoF. Although prior studies have recognized the multidimensional nature of cross-national distance, they have not linked it with the concept of the LoF. By creating such a linkage, we advance our understanding of the impact of distance on foreign entry decision. Moreover, the context of this study is firms from emerging markets, while the majority of existing studies on distance focus on firms from developed countries. Thus, this study adds new insights to distance research by exploring new contexts.
The findings of this article provide insights into the recent debate on whether the world is flat (Friedman, 2005), spiky (Florida, 2005), or semi-globalized (Ghemawat, 2003). While proponents of the view that the world is flat believed that the advance in technol- ogy has made the world borderless, believers in the view that the world is spiky or semiglobalized observe that there are still substantial globalization barriers. Our findings support the latter view by showing that the world is still spiky and that different dimensions of cross-national distance still play significant roles
in deterring foreign entries, although the impact of geographic distance itself becomes negligible.
Finally, the findings regarding the role of prior foreign experience on foreign direct investment speak to the validity of staged theories of internationalization (Johanson and Vahlne, 1977, 1990). Although prior experience helps overcome the LoF in efficiency- seeking and natural resource-seeking foreign direct investment, its impact is limited in the other types of foreign direct investment.
Our findings also have practical implications. MNE managers need to carefully assess the extent to which their own firms are affected by each type of the LoF. It is imperative not to simply emulate other firms going abroad. By the same token, policy makers focused on attracting foreign direct investment to the host country would need to carefully analyze what to emphasize as a magnet for foreign multinationals. Our analysis suggests that they need to adopt policies that reduce different types of the LoF for each type of foreign direct investment.
This research suffers from several limitations. First, the sample is from only one home country. Therefore, one should be cautious in generalizing the implica- tions of our findings to firms from other countries without examining the peculiar characteristics of China. Future research could analyze multiple home countries to test the external validity of the results reported in this article. A related point is that, when examining multiple host and home countries, scholars need to recognize the asymmetric nature of cross- national distance, which we did not address in this article because we have only one home country. Third, we focused on only three types of the LoF. It is possi- ble that there are other types of the LoF that hinder for- eign investments. Finally, we did not consider the effects of prior international experience based on prior investments within specific types, which would enable testing if prior experience in efficiency-seeking foreign direct investment, for instance, is relevant for market-seeking or strategic asset-seeking FDI. These limitations offer additional avenues for future research within the systematic framework of analysis proposed in this article.
ACKNOWLEDGEMENTS
The authors are grateful to GSJ Editor Jay Anand and two anonymous reviewers for their invaluable guidance and suggestions during the review process.
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