Discussion: The CAGE Analysis
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Distance factors and target market selection: the moderating
effect of market potential Shavin Malhotra
Ted Rogers School of Management, Ryerson University, Toronto, Canada
K. Sivakumar Lehigh University, Bethlehem, Pennsylvania, USA, and
PengCheng Zhu Eberhardt School of Business, University of the Pacific,
Stockton, California, USA
Abstract
Purpose – The paper is in the domain of marketing strategies of multinational firms. Specifically, it aims to focus on target market selection of multinational firms.
Design/methodology/approach – Using the cultural, administrative, geographic, and economic distance framework proposed by Ghemawat, the authors offer empirical support for the role of different distance factors on firms’ foreign market acquisition behavior. In addition, they examine the moderating role of market potential of a target country on the relationship between distance factors and target market selection. The context of the paper is multinational firms from developing countries. The sample consists of cross-border acquisitions (CBAs) completed by firms from 18 emerging countries between 1990 and 2006. The authors use ordinary least squares and moderated regression analysis to determine the main effect of distance factors and the interaction effect of market potential.
Findings – The authors find that while cultural and geographic distance factors have a significant, negative impact on the number of CBAs, administrative and economic distances have a significant, positive effect. They also find that the market potential of target countries significantly moderates the relation between the distance factors and the number of CBAs.
Research limitations/implications – The results show that the market potential of countries compensates and sometimes even overrides the role of distance. Future studies should expand this research to include industry-specific factors.
Originality/value – The paper provides an empirical illustration of Ghemawat’s distance framework. In addition, the paper highlights several boundary conditions of the impact of distance factors on firms’ internationalization processes. Finally, the study enhances knowledge on foreign market entry behavior of firms from developing countries.
Keywords Market entry, Developing countries, Globalization, Market strategy
Paper type Research paper
The current issue and full text archive of this journal is available at
www.emeraldinsight.com/0265-1335.htm
The authors gratefully acknowledge and express appreciation for the helpful comments on earlier versions of this paper by Kannan Ramaswamy and the IMR reviewers.
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Received April 2008 Revised August 2008,
September 2008 Accepted September 2008
International Marketing Review Vol. 26 No. 6, 2009
pp. 651-673 q Emerald Group Publishing Limited
0265-1335 DOI 10.1108/02651330911001332
Introduction The increasingly competitive environment of today’s business world has compelled a large number of firms to target international markets (Wood and Robertson, 2000). Removal of trade barriers and increasing globalization has further accelerated the number of firms entering new markets/countries. More and more managers today are faced with the decision of which foreign markets to target. This decision is one of the most critical decisions for firms in their internationalization process (Sakarya et al., 2007; Whitelock and Jobber, 2004), as it represents the first step in their objective to go international. Thus, an error in selecting the right target country can have long-term consequences on the firms’ future success. As a case in point, the Enron Development Corporation, a US-based power company, entered India in 1992 to build a $2.8 billion power plant in Maharashtra. Since its inception in 1992, the power plant (which was to become the largest power plant in India) was mired in controversies due to protectionist policies of the then government in the state of Maharashtra (Johansson, 1997), and finally, after investing huge amounts of money and resources, Enron decided to sell its operations in India in 2001 (Davis, 2001). There are several such examples that illustrate the dynamics of foreign market entry behavior.
Researchers in international marketing have long examined the impact of distance factors such as cultural and geographic on firms’ selection of target markets. A review of empirical studies in this domain shows inconsistent results (Davidson, 1980; Dunning, 1973, 1992; Dow, 2000; Green and Allaway, 1985; Johanson and Vahlne, 1977; Johanson et al., 1975; Mitra and Golder, 2002; Ojala and Tyrvainen, 2007; Pothukuchi et al., 2002; Sakarya et al., 2007; Weitzel and Berns, 2006). For example, Edwards and Buckley (1998), Buckley et al. (2007), Clark and Pugh (2001), and Dow (2000) find that cultural and geographic distances have a significant impact on firms’ decisions to select international markets. By contrast, Robertson and Wood (2001), Mitra and Golder (2002), and Terpstra and Yu (1988) find no impact of cultural and geographic distance on firms’ selection of international markets.
This divergence in the impact of distance factors on international market selection behavior of firms is intriguing as theoretically it implies that the observed variability in these empirical studies may be examined by moderating factors (Ellis, 2008). We argue, based on the contingency theory, that the mixed findings may be caused by the fact that the effect of distance factors on target market selection is neither consistently significant nor consistently non-significant, but contingent upon the market potential of the target country (Rothaermel et al., 2006; Turnbull and Ellwood, 1986; Whitelock, 2002a, b). Specifically, we ask whether the effect of distance factors, as measured by cultural, administrative, geographic, and economic (CAGE) distances, on firms’ selection of target markets is influenced by the market potential of the target country. Target country’s market potential has been found to be among the most important determinants of foreign direct investment (FDI; Aharoni, 1966; Mitra and Golder, 2002; Whitelock and Jobber, 2004; Wood and Robertson, 2000), and is also considered an important contingency variable impacting international strategy decisions (Ekeledo and Sivakumar, 1998; Rothaermel et al., 2006; Whitelock, 2002a, b). We posit that managers will undertake market entry decisions based on a trade-off between risks and returns; while distance factors pose a risk to managers, market potential represents opportunities or returns. Thus, if the market potential is large, managers may be willing to take risks by targeting countries that are at larger distances.
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Analyzing a sample of 4,803 cross-border acquisitions (CBAs) in 132 target countries, we find strong empirical support for this line of reasoning. According to the World Investment Report (WIR) (2007), CBAs are the predominant mode of FDI today. “CBAs have increased significantly in 2006, both in value (by 23 percent, to reach $880 billion) and in number (by 14 percent to 6,974), approaching the previous peak in 2000.”
This study makes three important contributions. First, by studying the moderating impact of the target country’s market potential, we make an important conceptual contribution to the existing debate on the relationship between distance factors and market selection because, thus far, empirical evidence has been equivocal. Second, by empirically studying the impact of four distance factors (CAGE) we offer a more comprehensive understanding of the impact of distance factors on firms’ international market selection behavior in the rapidly changing global environment. Third, our study adds to the existing literature on CBAs. Despite the increasing importance of CBAs in firms’ internationalization strategy, they have received limited attention in the international marketing literature (Shimizu and Hitt, 2004; Weitzel and Berns, 2006).
The rest of the paper is organized as follows: in the next section, we describe the theoretical framework that links the distance factors with international market entry behavior and shows the moderating effect of the target countries’ market potential on this link. Then, we develop hypotheses related to the main effect of each of the distance factors on international market entry and the moderating role of market potential on the relationship between distance factors and market entry. The subsequent section describes the methodology, followed by an explanation of the analysis and the results. Finally, we delineate the managerial implications and future research directions that emanate from our findings.
Theoretical framework The theoretical model is shown in Figure 1. We base our framework on a theoretical premise that manager’s decision to select international markets is often bases on a trade-off between risks and returns/opportunities inherent in the target market, a view supported by international market selection and mode-of-entry theories (Papadopoulos et al., 2002; Reid, 1983; Rothaermel et al., 2006):
IMS and mode of entry (MOE) theory suggest that both the “pluses” and “minuses” of the objects under review (in this case, countries) must be considered for effective decisions. These are commonly expressed as tradeoffs between opportunities vs risks, costs vs benefits, or cost vs control (Douglas and Craig, 1983; Anderson and Gatignon, 1986; Ekeledo and Sivakumar, 1998; Papadopoulos et al., 2002, p. 169).
In this study, we express the risk factors as distances between the home and the target countries. Cultural and geographic distances are generally considered sources of risk and/or uncertainty in prior research (Cosset and Roy, 1991; Davidson, 1980; Rothaermel et al., 2006). The larger the distance between the countries, the greater the uncertainty and the costs firms will face in overcoming and integrating these distances will be. We adopt a broad measure of distance, the CAGE distances framework, introduced by Ghemawat (2001). In our review of the internationalization literature, we found most studies used a single measure of distance, namely cultural or geographic. Although these studies are useful, they do not offer a comprehensive and more insightful perspective of different types of inter-country distances; therefore, they may overemphasize the importance of
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geographic and cultural distances in their models (Mitra and Golder, 2002; Ojala and Tyrvainen, 2007). Frankel and Rose (2002) based on a large data of economic and geographic variables for over 200 countries, found that while a 1 percent increase in inter-country physical distance decreases international trade by 1.1 percent, a common currency and a common membership in a trading block increases trade between countries by as much as 340 and 330 percent, respectively. Other distance factors may even be more important than geographic distance. Ghemawat (2001), to the best of our knowledge, provides the most comprehensive framework for examining the role of distance on firms’ internationalization strategy. The CAGE distance framework incorporates the different dimensions of distance between the host country and the target country that may affect a manager’s decision to invest in a new country. The CAGE framework allows the four factors (CAGE) to be viewed as dimensions of the distance construct. Broadly, in this framework, cultural distance refers to differences in social norms, language, and beliefs between the two countries. Administrative distance refers to differences in bureaucratic, working, and political structure prevalent in the two countries. Geographic distance refers to the actual distance in miles or kilometers between the countries. Finally, economic distance refers to differences in economic conditions between the two countries. We believe that studying these distance parameters under a common framework will provide increased insights into the internationalization behavior of firms.
In addition to the risk factors, we express market potential of the target country in terms of possible returns available to firms entering international markets. The theoretical rationale behind the need to account for market potential is accentuated by the fact that different market potential, low potential versus high potential, of the target countries would entail different degrees of importance to the distance factors. Since international market entry decisions cannot be viewed as universal laws that are optimal for all organizations and circumstances, we treat market potential as a contingency variable. Several researchers have considered market potential as
Figure 1. The role of distance in the foreign acquisition behavior of firms from developing countries
Market potential of
target country
H1
H5
H2 H6
H7
H8
H3
H4
International
market
entry
Distance factors*
Economic distance
Cultural distance
Administrative distance
Geographic distance
Source: Ghemawat (2001)
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a prominent contingency variable having a moderating impact on international market entry decisions (Ekeledo and Sivakumar, 1998; Rothaermel et al., 2006; Whitelock, 2002a, b). In the next section, we describe the rationale underlying the relationships among the variables in the proposed framework.
Hypotheses development Cultural distance Many researchers have used and continue to use cultural and psychic distance interchangeably (Dow and Karunaratna, 2006; Ojala and Tyrvainen, 2007; Sousa and Bradley, 2006). However, Sousa and Bradley (2006) argue against this practice. They posit that while psychic distance exists at an individual level, cultural distance should be applied at a national level. Nonetheless, they do find a strong positive significant relationship between the two concepts with cultural distance influencing an individual’s psychic distance. For this review, because we are focusing on national level distances, we confine our discussion to cultural distance. Empirical studies have found that national culture has a significant impact on the internationalization decision of firms. One such decision is the choice of MOE, which, in general, has been shown to be influenced by cultural and other national factors (Chang and Rosenzweig, 2001; Gatignon and Anderson, 1988; Kogut and Singh, 1988). Kogut and Singh (1988) find that differences in culture between home and host countries increased the level of risk in post-acquisition integration, which led firms to select safer entry mode options. Studies in mergers and acquisitions point out that the integration of resources, particularly human, is critical for the success of acquisitions (DePamphilis, 2005). Therefore, high levels of cultural differences may increase post-merger management costs and lower the performance of acquisitions. Gatignon and Anderson (1988) also find that high-cultural distance was associated with partial ownership rather than full ownership. Similarly, several studies have found that the greater the cultural distance, the more a foreign investor may prefer greenfield investments over mergers and acquisitions (Chang and Rosenzweig, 2001; Kogut and Singh, 1988; Weitzel and Berns, 2006).
The preceding results are explained by the uncertainty executives perceive when dealing with different cultures (Gatignon and Anderson, 1988). Firms that have different values and operating methods than those in the target country might shy away from opting for a high-control MOE, such as CBAs (Davidson, 1980; Richman and Copen, 1972; Weitzel and Berns, 2006). In addition, the time and cost involved in overcoming conflicts and increasing cooperation among partners from distant cultures can adversely affect the performance of an international venture (Pothukuchi et al., 2002; Ring and van de Ven, 1994):
H1. The larger the cultural distance between the home country and the target country, the fewer is the number of CBAs by firms from the home country.
Administrative distance Administrative distance, also termed political distance by Ghemawat (2001), exists due to different bureaucratic, working, and political structures prevalent in countries. Different government policies are an important source of administrative distance (Ghemawat, 2001). For example, in China, the government does not favor a majority stake by non-governmental entities in financial institutions. Similarly, the Indian Government maintains tight controls over foreign investment in the domestic retail
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sector. To protect domestic companies, countries may also raise barriers to preempt foreign competition. Such barriers may be in the form of subsidies to domestic manufacturers, Europe’s farmers are a case in point; use of anti-dumping duties, the USA and India are the top two countries that have filed anti-dumping duties against foreign manufacturers; and high-import duties, Japan is a prominent example.
The presence of corruption in target countries, an important barrier to market entry (Weitzel and Berns, 2006), may also increase the administrative distance between countries. Research has shown that countries with weak and corrupt institutional systems will likely prefer FDI from similar countries (Hotchkiss, 1998; Lambsdorff, 2002). Behavioral norms stemming from government regulations and ethical codes of conduct make major investments by firms from developed countries too far removed from behaviors expected in corrupt countries. Indeed, many US firms have often criticized the US Government because it constrains their behavior in dealing with unethical practices abroad. This limits their ability to compete effectively against companies from other countries that are not equally constrained (Trevino and Nelson, 1999).
Government effectiveness also influences administrative distance. An ineffective government with excessive regulations will impede economic activity, which means that managers will need to spend more time and money in overcoming these regulations (Kaufmann et al., 2007). In summary, uncertainty due to administrative distance may cause executives to undervalue foreign investments. They may find it difficult to move their tested management work methods to a dissimilar operating environment (Richman and Copen, 1972). In addition, administrative distance will create high-coordination needs and, thus, high-coordination costs, which firms may want to avoid. Thus, it is reasonable to assume that administrative distance will raise the barrier to entry:
H2. The larger the administrative distance between the home country and the target country, the fewer is the number of CBAs by firms from the home country.
Geographic distance Findings on geographic distance have been somewhat equivocal. Several traditional internationalization theories have suggested that geographic distance plays an important role in the foreign country selection decision (Davidson, 1980; Dunning, 1973, 1992; Johanson and Vahlne, 1977; Johanson et al., 1975; Luostarinen, 1979). Many studies have found empirical support for this relationship (Chetty, 1999; Clark and Pugh, 2001; Dow, 2000; Luostarinen, 1979; Srivastava and Green, 1986). For example, Clark and Pugh (2001) find that the first three target countries selected by British firms are significantly closer than countries they entered subsequently in terms of geographic distance. Similarly, Chetty (1999) and Dow (2000) find that New Zealand and Australian firms favor countries that have close geographical distance. This is primarily because firms incur lower economic and management costs in expanding to geographically closer countries.
It is important to note that in most of these findings, the importance of geographic distance decreases as firms gain more international experience. Thus, geographic distance may be the most significant factor for the first country selection, as previous studies have suggested (Chetty, 1999; Clark and Pugh, 2001; Dow, 2000; Ojala and
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Tyrvainen, 2007), but it becomes less important for entry into subsequent countries. Generally, the further the distance between two countries the harder it will be for firms to conduct business. Apart from inter-country distance, distances within a country, the size of the country, the conditions of roads, and the availability of transportation and communication infrastructure will impact the international firms’ business operations in that country. Research has found poor information infrastructure compounded by large distances between two countries account for reduced cross-border equity flows between the countries (Ghemawat, 2001):
H3. The larger the geographic distance between the home country and the target country, the fewer is the number of CBAs by firms from the home country.
Economic distance Although researchers have investigated cultural and geographic distance variables in internationalization studies, economic distance has received little consideration (Davidson, 1983; Evans et al., 1992; Mitra and Golder, 2002; Nordstrom and Vahlne, 1992; O’Grady and Lane, 1996). Of the few empirical studies on economic distance, Mitra and Golder (2002) find that large economic distance between the host and the target country discourages foreign market entry. They attribute this to the possibility that consumers in countries that have similar gross domestic product (GDP) per capita are likely to have similar consumption patterns and be exposed to similar marketing strategies. In most of the high-income countries, use of credit cards and internet web sites for purchasing products are very common, while in countries such as India, China, and other similar low-income countries purchase by cash and through brick and mortar shops are still the norm. Indeed, research suggests that rich countries carry out most of their cross-border activities with other rich countries, as can be seen by the positive correlation between their per capita GDP and trade flows (Ghemawat, 2001).
Further arguments that support the notion that firms are more likely to succeed by entering countries that have similar economic environments to their home markets include the following: first, firms can more readily transfer their existing business models to countries that have similar economic characteristics to their home market in terms of media, distribution channels, business institutions, and consumer disposable income (Ghemawat, 2001; Mitra and Golder, 2002). Knowledge of these factors can help firms succeed in foreign markets. For example, Wal-Mart has been in the process of setting up a unit in India for several years, but because the economic environment in India is very different from that in the USA, it has not yet finalized a good business model there. However, because Wal-Mart in Canada follows the same business model as that in the USA, it can set up new units in Canada quickly.
Second, by entering countries that are economically similar to their home market, firms can build on their economies of scale, scope, and experience by easily transferring their skills and knowledge from their home market to the new markets. Finally, firms can also enhance their international experience by initially operating in economically similar countries and later expanding to economically more distant countries. On the basis of these arguments, we hypothesize the following:
H4. The larger the economic distance between the home country and the target country, the fewer is the number of CBAs by firms from the home country.
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Moderating role of market potential Most studies have overlooked the impact of target or host country characteristics on the internationalization behavior of firms (Harzing and Sorge, 2003). The theory on market-seeking FDI recognizes host market characteristics as significant determinants of foreign investments (Buckley et al., 2007; United Nations Conference on Trade and Development, 1998). Of the many host country factors, market potential, in particular, is widely considered as one of the most important variables in foreign market evaluation (Ellis, 2008; Kobrin, 1976; Mitra and Golder, 2002; Robertson and Wood, 2001; Terpstra and Yu, 1988; Wood and Robertson, 2000; Wood and Goolsby, 1987). The FDI theory further supports this notion; it proposes that firms invest in foreign markets provided that the expected benefits from these investments will exceed the costs incurred in overcoming difficulties related to entering new markets (Hymer, 1976; Vernon, 1966). These benefits exist largely due to the large market size of the target country (Davidson, 1980; Dunning, 1998; Ellis, 2008; Scaperlanda and Mauer, 1969). Firms from developing countries also seem to show the same relationship. Thus, we can safely conclude that firms in general are likely to choose more prosperous economies.
Empirical studies have found market potential to strongly drive both export market selection and foreign investments (Chakrabarti, 2001; Davidson, 1980; Dow, 2000; Ellis, 2008; Mitra and Golder, 2002; Terpstra and Yu, 1988). Ellis (2008), in one of the very few studies to look at internationalization of firms from a developing country perspective, used both primary and secondary data to investigate the impact of market size on Chinese firms’ entry into new markets. This study finds a strong positive impact of market size on market selection. However, this study relied only on one home country sample; therefore, the results cannot be generalized to other emerging economies. In another study, Robertson and Wood (2001) investigate the relative importance of 93 different types of determinants for market entry from a sample of 275 exporting managers. Managers in this study ranked market potential as the most important determinant for export market selection.
A number of studies have suggested the moderating impact of market potential on international market selection. In one such study, Wood and Robertson (2000) find that cultural information is important to exporters only after a given export market offers evidence of its market potential. Similarly, Mitra and Golder (2002) find that the significance of cultural distance disappears when they control for the economic attractiveness of a country. In addition, in their study on the internationalization of US advertising firms, Terpstra and Yu (1988) find that these firms tend to favor countries that have a larger market size than those that are at a closer geographic distance. Furthermore, Whitelock and Jobber (2004) find market attractiveness to be a substantive discriminator between firms’ decision to enter and not-enter a new foreign market. Rothaermel et al. (2006) is the only study to our best knowledge that investigated specifically the moderating impact of market potential on the relationship between cultural distance and international market entry. Using secondary data for analysis, the authors find that market size significantly reduces the negative relationship between cultural distance and international market entry. However, the study looks at foreign market entry for only US internet firms; therefore, the results cannot be generalized across other firms and to other countries.
These studies show the importance of investigating the moderating role of market potential on the relationship between cultural distance and foreign market entry
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strategy. In addition, existing empirical studies that have not incorporated market potential in their analysis may have overstated the importance of cultural distance (Mitra and Golder, 2002).
Firms are likely to overlook the role of distance, if the host country boasts an attractive market. Firms may be willing to take risks and, thus, to overlook that certain target countries may be highly distant, provided these countries offer attractive markets. Therefore, we argue that the effect of distance between the home and the target countries will be moderated by the market potential of the target country. That is, if the market potential of the target country is high, firms may overlook the distance between the countries. This notion also implies that distance will matter more for target countries with low market potential than for those with high-market potential; however, its importance will decrease with the increasing market potential of the target country. In other words, market potential compensates for the distance factor as a deterrent for CBAs. Thus:
H5. The market potential of the target country moderates the relationship between cultural distance and CBAs. As the market potential of the target country increases, the relationship between cultural distance and the number of CBAs becomes less negative.
H6. The market potential of the target country moderates the relationship between administrative distance and CBAs. As the market potential of the target country increases, the relationship between administrative distance and the number of CBAs becomes less negative.
H7. The market potential of the target country moderates the relationship between geographic distance and CBAs. As the market potential of the target country increases, the relationship between geographic distance and the number of CBAs becomes less negative.
H8. The market potential of the target country moderates the relationship between economic distance and CBAs. As the market potential of the target country increases, the relationship between economic distance and the number of CBAs becomes less negative.
Methodology Sample Data used to test these hypotheses were collected from a sample of CBAs completed by firms from 18 emerging countries between 1990 and 2006. The choice of emerging economies as a research setting was motivated partly by the desire to compensate for the developed country bias as a research setting for existing research on distance factors. Several researchers point out that the characteristics of multinationals from developing countries differ from those from developed countries (Beausang, 2003; Buckley and Mirza, 1988). By studying non-western multinational companies, we hope to collect internationalization data exhibiting meaningful variation on the constructs of interest. CBAs have become a major mode-of-entry for developing-country firms into other countries (Aulakh, 2007). In 2005, CBAs by developing-country firms accounted for 13 percent (approximately US$90 billion) of all global CBAs, and 17 percent in terms of the number of deals, increasing from 4 to 5 percent in 1987, respectively,
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(WIR, 2006). For instance, CBAs by Indian firms in 2006 (149 completed CBAs) increased by 121 percent over the 2004 figures; similarly, the total value of these acquisitions increased to US$21 billion in 2006, an increase of 2,236 percent over the 2004 value of US$0.90 billion (Securities Data Company (SDC) Platinum Database, 2007). Apart from India, other developing countries such as China, Brazil, and Russia also show a similar trend. For instance, the value of CBAs by Chinese firms in 2006 stood at US$12 billion, which is an increase of 73 percent over the previous year (SDC Platinum Database, 2007).
The historical CBA information is collected from the SDC Platinum Database. The emerging countries were based on the Morgan Stanley emerging market index. A particular problem of adopting such an index is that, over time, some countries may be maintained in the index only for continuity purposes, even though they may now be considered developed countries. In such cases, we excluded these countries (e.g. Taiwan, South Korea, and Israel) from our sample. In addition, for some countries, we found few CBA entries in the database, and therefore we decided not to consider these countries in the sample (e.g. Pakistan, Morocco, Jordan, and Peru). The final sample of 18 countries, which is a good representation of the emerging economies, includes the following: Argentina, Brazil, Chili, China (mainland), Columbia, Czech Republic, Egypt, Hungary, India, Indonesia, Malaysia, Mexico, Philippines, Poland, Russia, South Africa, Thailand, and Turkey. As mentioned previously, we focus on the CBAs completed between 1990 and 2006, a period that Gaughan (2002) describes as the fifth merger-and-acquisition wave in the world. This particular merger-and-acquisition period saw increasing numbers of CBAs from firms from developing countries.
The 18 countries completed 4,803 CBAs in the sample period, and these 4,803 CBAs contained 132 target countries ranging from the most developed to the least developed countries in the world. This large sample of target countries provides sufficient variation in the target country characteristics, which is important for the generalizability of the findings of this study.
Dependent variable For the sampling period (1990-2006), we aggregated the number of completed transactions undertaken by country in each of the target countries. The dependent variable, CBA numberi,j, denotes the log-transformed number of CBAs completed by the firms from country j in a target country i over the sampling period. We term this sample the “yearly collapsed” sample. In this study, we also split the dependent variable into yearly samples. More specifically, we calculated the number of CBA transactions completed by firms from country j in the target country i in year t. We used a pooled sample method on the yearly samples for a robustness test. The robustness test provides similar results to those of the “yearly collapsed” sample, which we provide herein. (The results of the robustness test are not included here to conserve space but are available on request.) As mentioned previously, the transaction numbers are collected from the SDC Platinum Database. Some related studies also use transaction value as the dependent variable; however, we find that SDC does not report transaction values for many acquisitions. This is even more prominent for data on CBAs of firms from emerging economies. Therefore, we used the number of transactions as the dependent variable, which is more readily available from SDC and is a good indicator of firms’ behavior profiles. The aggregated sample of transaction
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numbers by acquiring countries in each target country resulted in a sample size of 450 paired-country observations.
Independent variables Cultural distance. We operationalized cultural distance in line with Hofstede’s (1980) cultural index. On the basis of Kogut and Singh’s (1988) formula, we combined Hofstede’s four most common cultural dimensions – individualism, uncertainty avoidance, power distance, and masculinity – into the following composite index:
Cultural distance ¼ X4
j¼1
ðHA; j 2 HT; jÞ 2
4 £ Vj
where:
HA, j – the acquiring country score for Hofstede’s cultural dimension j.
HT, j – the target country score for the corresponding cultural dimension i.
Vj – the variance of the index score of cultural dimension j.
Administrative distance. We operationalized administrative distance by adopting a measure of government effectiveness from Kaufmann et al.’s (2007) study. Kaufmann et al. develop the government effectiveness index to measure competence of bureaucratic procedures and the quality of public service delivery by governments in different countries. To measure administrative distance, we took the absolute difference in scores on the government effectiveness index between the acquiring country j and the target country i. Kaufman et al. provide only biannual measures from 1996 to 2006; therefore, we used the measure for its own year and for the previous year. For example, we used the 2006 government effectiveness measure for CBAs in 2006 and 2005. We used the 1996 measure for any transactions before 1996 (the number of transactions before 1996 is much smaller than that in later years). We averaged the yearly index difference over the sampling period and used it in the statistical analysis. We also conducted a robustness test by using the yearly index difference and running the analysis by each year. The conclusions do not change from those we report herein.
Geographic distance. In line with the approach followed in previous studies (Buckley et al., 2007; Ojala and Tyrvainen, 2007), we calculated geographic distance in terms of the actual distance in kilometers between the capital cities of the acquiring country j and the target country i. We obtained the distance in kilometers from Geobytes Database and used the natural logarithm of this distance.
Economic distance. We measured economic distance as the absolute difference in per capita GDP between the acquiring country j and the target country i. We collected this information from the World Development Indicators Database. Because the per capita GDP is measured on a yearly basis, we took the average of the yearly difference between each pair of countries to represent economic distance. As a robustness test, we also used the yearly difference measure and carried out the analysis by year. Both measures gave similar results.
Moderating variable In line with previous studies (Davidson, 1980; Mitra and Golder, 2002; Terpstra and Yu, 1988), we used GDP of the target country as a measure for market potential.
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We collected the information from World Development Indicators Database. The annual GDP value is presented in US dollars. We took the average of the annual GDP in target country i over the sampling period to measure the market potential of the country. To correct for skewness in the variable, we used logarithm to transform the values.
Results Table I presents the descriptive statistics and the correlation matrix. A review of the correlations between the independent variables indicates that multicollinearity is not a problem. This conclusion is supported by the diagnostic information from the regression models. To check for multicollinearity between the independent variables, we calculated the variance inflation factors and determined that multicollinearity problems were unlikely (the highest variance inflation factor was 2.0, well below the benchmark of 10).
Table II presents the results of testing H1-H8. We used ordinary least squares regression analysis to test the hypotheses. We present six different regression models, and each model is a significant predictor of the number of CBAs, as the F-statistics show. The F-statistics for all six models are significant at p , 0.01. We estimate the main effect of the four distance factors in Model 1. By including all the distance factors in the regression model, we test the conditional explanatory effect of each factor by controlling the effect of the others.
H1 proposes that there is a negative relationship between cultural distance and the number of CBAs. As Model 1 (Table II) shows the coefficient for cultural distance is negative and significant ( p , 0.01). Thus, the results provide support for H1.
H2 proposes that there is a negative relationship between administrative distance and the number of CBAs. We do not find support for this hypothesis. Administrative distance has a positive and significant ( p , 0.01) coefficient (Model 1). Therefore, in contrast to our hypothesis, administrative distance has a positive impact on the number of CBAs.
CBA number
Cultural distance
Administrative distance
Geographic distance
Economic distance
Market potential
CBA number 1.00 Cultural distance 20.09 * 1.00 Administrative distance 0.17 * * 0.36 * * 1.00 Geographic distance 20.15 * * 0.16 * * 0.14 * * 1.00 Economic distance 0.13 * * 0.41 * * 0.34 * * 0.31 * * 1.00 Market potential 0.28 * * 0.20 * * 0.24 * * 0.21 * * 0.43 * * 1.00 Mean 1.08 1.78 1.02 8.34 0.41 25.05 SD 1.11 1.33 0.65 1.00 1.18 2.55
Notes: * p , 0.10; * *p , 0.01
Table I. Correlations, means, and standard deviations
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D ep
en d
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v a ri
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Table II. Regression analysis
results: main effect and interaction effect
Distance factors and target
market selection
663
H3 proposes that there is a negative relationship between geographic distance and the number of CBAs. We find support for this hypothesis. As Model 1 shows, geographic distance has a negative and significant coefficient ( p , 0.01).
H4 proposes that there is a negative relationship between economic distance and the number of CBAs. As Model 1 shows, economic distance has a positive and significant coefficient ( p , 0.05). Thus, the results do not provide support for H4. It should be noted that while we do not find support for H2 and H4, all four distance factors have a statistically significant impact on the number of CBAs. Therefore, we find good support for the use of the CAGE distance framework in our analysis.
Model 2 shows the main effect of the moderating variable (market potential). Market potential has a positive and significant impact ( p , 0.01) on the number of CBAs. In addition, we find that by controlling for market potential in Model 2, economic distance loses its significance. This provides support for our argument that prior studies that did not control for market potential may have overestimated the impact of distance factors on the internationalization of firms.
Models 3-6 provide tests for H5-H8. In line with Hitt et al.’s (2006) approach, we test for each interaction effect separately. H5-H8 propose that market potential moderates the relationship between CAGE distance and the number of CBAs. As Models 3-6 (Table II) show, we find full support for all four hypotheses. The coefficients of the interaction effects between market potential and the four distance factors are positive and significant ( p , 0.01). The positive sign for these interaction effects indicates that as the market potential of the target country increases, the relationship between the distance factors and the number of CBAs becomes less negative (or more positive), providing further support for the hypotheses.
To examine these interaction effects further, in Figure 2, we present the results using the method proposed by Brambor et al. (2006). According to Brambor et al., individual coefficients from regression analysis can throw only limited light on the interaction effects, and many studies wrongly interpret interaction effects (a view also supported by Irwin and McClelland, 2001). In the graphs in Figure 2, we show the marginal effect of the four distance factors on the number of CBAs across the observed range of market potential of the sample target countries. We calculated the marginal effect of each distance factor by taking a partial differential of the full interaction model that includes the interaction effect for that distance factor. For example, the full model showing the interaction effect of market potential and cultural distance is as follows:
CBA number ¼ b0 þ b1 · Cultural distance þ b2 · Geographic distanceþ
b3 · Economic distance þ b4 · Administrative distanceþ
b5 · Market potential þ b6 · Cultural distance · Market potential
þ 1
ð1Þ
A partial differentiation of equation (1) with respect to cultural distance will give the following result:
›ðCBA numberÞ
›ðCultural distanceÞ ¼ b̂1 þ b̂6 £ Market potential ð2Þ
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Based on the estimation of b1 and b6 from equation (2), we plot the marginal effect of cultural distance on the number of CBAs across the observed range of market potential of the target countries. Note that the market potential is shown as the log transformation of the country’s GDP. The log of the market potential values of the sample target countries ranges from approximately 10-35 in our sample, and thus we plot the graphs for this range.
Because equation (2) only provides the point estimates of the marginal effect, in line with Brambor et al.’s (2006) suggestion, we also compute the standard error of the marginal effect and plot the confidence interval (at the 95 percent level) in all four graphs. The standard error in this case can be calculated as follows:
ŝ›ðCBA numberÞ=›ðCultural distanceÞ ¼
ffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi varðb̂1Þ þ Z 2 · varðb̂6Þ þ 2 · Z · covðb̂1b̂6Þ
q ð3Þ
where Z is the value of the market potential variable (in this study, ranging from 10 to 35). The variance of regression coefficients b1 and b6 and their covariance can be obtained from the standard regression model output. By multiplying the critical t-values at the 95 percent confidence interval to the standard error, we can construct the upper- and lower-bound lines of the marginal effect of cultural distance on the number of CBAs (Figure 2).
Figure 2(a) shows the marginal effect of cultural distance. When the market potential of the target country is relatively small (GDP values , 28), the upper-bound line of the marginal effect of cultural distance is below zero, suggesting that cultural distance has a significant, negative relationship to the number of CBAs. However,
Figure 2. Marginal effect of distance variables on the number of
CBAs
–3.0
–2.0
–1.0
0.0
1.0
2.0
10 12 14 16 18 20 22 24 26 28 30 32 34
M ar
gi na
l e ff
ec t o
f cu
lt ra
l d is
ta nc
e
Market potential
Point estimate
Lower bound
Upper bound
– 4.0
–3.0
–2.0
–1.0
0.0
1.0
2.0
3.0
10 12 14 16 18 20 22 24 26 28 30 32 34
M ar
gi na
l ef
fe ct
o f
ad m
in is
tr at
iv e
di st
an ce
Market potential
(a) (b)
– 4.0
–3.0
–2.0
–1.0
0.0
1.0
2.0
10 12 14 16 18 20 22 24 26 28 30 32 34
M ar
gi na
l ef
fe ct
o f
ge og
ra ph
ic d
is ta
nc e
Market potential
Point estimate
Lower bound
Upper bound
Point estimate
Lower bound
Upper bound
Point estimate
Lower bound
Upper bound
–3.0
–2.0
–1.0
0.0
1.0
2.0
10 12 14 16 18 20 22 24 26 28 30 32 34
M ar
gi na
l ef
fe ct
o f
ec on
om ic
d is
ta nc
e
Market potential
(c) (d)
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when the market potential of the target country is large (GDP values . 28), the marginal effect of cultural distance is positive, but the effect is not significant (the lower-bound line is slightly below zero). However, as the market potential of the target country increases, the relationship between cultural distance and the number of CBAs becomes less negative. This provides further support for H5.
By using this same technique for cultural distance, we can explain the marginal effect of the three other distance factors. Figure 2(b) shows that administrative distance has a significant, negative impact on the number of CBAs (both the lower- and the upper-bound lines of the marginal effect of administrative distance are below zero) when market potential of the target country is small (GDP values , 20); however, the relationship is significant and positive for countries with large market potential (GDP values . 26; both the lower- and the upper-bound lines of the marginal effect of administrative distance are above zero). This provides further support for H6.
Figure 2(c) shows that there is a significant, negative relationship between geographic distance and the number of CBAs for target countries with low market potential (GDP values , 26); however, the relationship between cultural distance and the number of CBAs is significant and positive for target countries with large market potential (GDP values . 31), providing further support for H7 (both the lower- and the upper-bound lines of the marginal effect of geographic distance are above zero).
Figure 2(d) shows that though the relationship between economic distance and the number of CBAs is negative, it is not significant (the upper-bound line is above zero for all values of observed market potential). As seen with the other distance factors, when the market potential of the target country is larger (GDP . 28), the relationship between economic distance and the number of CBAs is significant and positive, providing further support for H8.
In summary, the interaction results (Table II) and the computations (Figure 2) show support for the moderating effect of market potential of the target country on the relationship between the distance factors and the number of CBAs. We discuss the implications of these findings in more detail in the next section.
Discussion In this paper, we attempted a more comprehensive examination of the role of distance than has been attempted in prior literature. We did so in the relatively new domain of CBAs by firms from developing countries. Our findings provide support for most of our hypotheses. First, we find that the CAGE distance framework has both an important and a significant impact on the number of CBAs by firms from developing countries. Thus, we find strong support for the use of a more comprehensive measure of distance to study market entry behavior of firms.
Second, cultural and geographic distances have a significant, negative impact on the number of CBAs. This suggests that firms from developing countries prefer to target firms in countries that have a similar culture as their home country. Likewise, these firms prefer to target countries that are closer in distance to their home country. These results support previous findings on multinational corporations from developed countries (Chang and Rosenzweig, 2001; Chetty, 1999; Clark and Pugh, 2001; Dow, 2000; Kogut and Singh, 1988; Weitzel and Berns, 2006).
Third, market potential of the target country significantly moderates the relationship between the distance factors and the number of CBAs. Through a
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detailed analysis of the interaction effect, we find that for target countries that have high-market potential, firms are willing to overlook the importance of distance factors.
Fourth, our results show that economic and administrative distances have a significant, positive impact on the number of CBAs. Thus, firms from developing countries prefer to acquire firms in countries that have different economic and administrative structures from their home country. Three explanations may explain the difference in our findings from those of previous research. First, firms from developing countries have only recently begun to expand internationally, and therefore they need to catch up with firms from developed countries. By acquiring firms in countries that have more distant economic and administrative structures, these firms can possess a diverse set of routines and repertoires that will enhance their chances of competing in an uncertain global environment (Barney, 1986; Morosini et al., 1998). It may be in these firms’ best interest to access a relatively large and diverse pool of routines and structures, thus enabling them to compete with more experienced firms from developed countries. Second, by working in these different routines and repertoires, firms from developing countries can substantially transform their business strategy, structure, and operations to enhance their competitive advantage and performance over time (Ghosal, 1987; Jemison and Sitkin, 1986; Morosini et al., 1998). Third, it is possible that for both these dimensions it may be important to look at directional effects. For instance, firms operating in developing countries are likely to be exposed to poor economic infrastructure and low per capita GDP and also to less developed administrative institutions that may be constrained due to high levels of bureaucracy, corruption, or low government effectiveness. Thus, when these firms expand to international markets, they are likely to save costs and improve their performance by operating in more economically and administratively developed countries. Therefore, it is possible that one needs to look at both these distances in its directional form and not as absolute numbers. To date, all of the existing literature has treated “distance” as a directionless variable – for example, whether a home country has a larger individualism score than the host country or vice versa does not matter in the computation of distance. We followed the same approach in our paper. However, it may be interesting to see whether the direction has any effect on the modeling results (we thank an anonymous reviewer for alerting us to this possibility). Even when we incorporate the direction of the distance, our conclusions are the same.
Theoretical contributions We contribute to and expand the findings related to market entry strategies by researchers such as Ellis (2008) and Rothaermel et al. (2006). While Ellis (2008) focuses on the role of psychic distance and culture on the entry sequence of Chinese firms, our work takes a comprehensive view of distance and involves the more general concept of CBAs and also incorporates samples from a wider variety of developing countries. Similarly, Rothaermel et al. (2006) examine the market entry of US internet firms while our study covers a larger number of industries and a larger number of countries. Therefore, in addition to examining new research questions in market entry strategies, our study also is more generalizable compared to existing studies.
We also offer empirical validation for a more comprehensive measure of distance. We believe that ours is the most comprehensive empirical validation of the measure of distance and the first empirical validation of Ghemawat’s (2001) distance framework.
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Similarly, by examining CBAs from 18 developing countries across 132 target countries, our results are more generalizable than existing research.
Our results make a significant conceptual contribution by demonstrating the role of market potential as a moderating variable to provide some interesting insights on the existing debate on the relationship between distance factors and market selection. Thus, we offer a more comprehensive theoretical explanation for market entry behavior.
Finally, we add to the existing research on the internationalization of firms from developing countries. It is argued that developing country multinationals are investing overseas at a relatively earlier stage in their development than their counterparts from developed countries (WIR, 2006). In addition, some studies have shown that developing country multinationals adopt a market-seeking overseas investment strategy vis-à-vis resource-seeking by developed country multinationals. This study should help strengthen the nascent body of research on the internationalization of firms from developing countries, which, as the Organization for Economic Co-operation and Development (2006) suggests, is “mostly based on a few anecdotal evidence, and deduction and inference from the history of North-South capital flows, rather than a body of systematic research.”
Implications Our results have several implications for managers and researchers. First, we believe that ours is the first comprehensive empirical examination of the CAGE distance framework (Ghemawat, 2001), and we tested it in the emerging domain of strategies by firms from developing countries. Our results demonstrate that previous research focusing exclusively on one distance factor – primarily cultural distance or geographic distance – may not have captured the important role of economic and administrative distances. The significant impact of all four distance factors implies that the use of the CAGE distance framework may offer a broader consideration of the role of distance on foreign market expansion.
Second, the results of our model clearly indicate that the distance between the home and the target countries influences the acquisition behavior of firms from developing countries. When we superimpose the role of market potential of the target country, the results not only are intriguing but also provide additional insights into the context of strategies by firms from emerging economies. Our results show that the large market potential of countries compensates and even overrides the role of distance. It also explains the rather rapid pace of internationalization by developing countries when the market potential is high, which reduces the perceived risk associated with target countries. More broadly, our results emphasize the inter-related nature of factors related to the foreign market acquisition behavior of firms. From our findings, it is clear that a holistic view of firm behavior can offer a richer understanding of the internationalization phenomenon.
Third, the results from this study suggest that companies making foreign acquisitions in today’s globally competitive arena should place less emphasis on distance and focus more on the market attractiveness or the potential of the target country. Management should not be motivated entirely by the potential benefits of investing in countries that are closer in distance and have similar cultural beliefs, but
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rather should pay close attention to how large these markets are for their products and/or services.
Finally, the results suggest that firms from developing countries behave differently than their developed-country counterparts with regard to the internationalization of their operations. Thus, the existing empirical evidence on firms from developed countries should be tested for their applicability to the strategies of firms from developing markets to arrive at a more generalized theory on the internationalization of firms.
Study limitations and future research directions Both the study’s findings and its limitations provide several opportunities for further research. Based on the secondary data sources available, we chose the most appropriate measure of the four distance dimensions of the CAGE framework. Additional research should include other measures of each of the four dimensions of distance to obtain a more fine-tuned understanding and validation of the framework. Ghemawat’s (2001) framework offers several other potential alternatives to approach the different dimensions of distance.
Although we incorporated all four distance factors into our model, further research could focus on the relative role of each factor. For example, some of the distance factors may be more important than others during certain stages of the internationalization process.
Our research focused on the market entry behavior of the firms. While offering very important insights, the obvious next issue to consider is the firm performance. For example, our results show that market potential overcomes some of the distance factors in CBA strategy. It will be interesting to see whether overlooking the distance factor in favor of market potential is good for firm performance. To date, there is no empirical evidence linking distance factors and market potential to financial performance of firms.
Another fruitful avenue for future research is to study the contingency effect of industry type. For example, does the framework we proposed apply to some industries more than others? Is cultural distance more important for service firms than manufacturing firms? Is the moderating role of market potential stronger for high tech products rather than other products?
Finally, the comparative effects should be analytically modeled to derive joint optimization models for market entry decisions. For example, are there combinations of distance dimensions that favor particular entry mode decisions?
References
Aharoni, Y. (1966), “Research roundup: the foreign investment decision process”, The International Executive, Vol. 8 No. 4, pp. 13-14.
Anderson, E. and Gatignon, H. (1986), “Modes of foreign entry: a transaction cost analysis and propositions”, Journal of International Business Studies, Vol. 17 No. 3, pp. 1-26.
Aulakh, P.S. (2007), “Emerging multinationals from developing economies: motivations, paths and performance”, Journal of International Management, Vol. 13 No. 3, pp. 235-40.
Barney, J.B. (1986), “Firm resources and sustained competitive advantage”, Journal of Management, Vol. 17 No. 1, pp. 99-120.
Beausang, F. (2003), Third World Multinationals: Engine of Competitiveness or New Form of Dependency?, Palgrave Macmillan, London.
Distance factors and target
market selection
669
Brambor, T., Clark, W.C. and Golder, M. (2006), “Understanding interaction models: improving empirical analysis”, Political Analysis, Vol. 14 No. 1, pp. 63-82.
Buckley, P.J. and Mirza, H. (1988), “The strategy of Pacific Asian multinationals”, The Pacific Review, Vol. 1 No. 1, pp. 50-62.
Buckley, P.J., Clegg, J., Cross, A., Liu, X., Voss, H. and Zheng, P. (2007), “The determinants of Chinese outward foreign direct investment”, Journal of International Business Studies, Vol. 38, pp. 499-518.
Chakrabarti, A. (2001), “The determinants of foreign direct investments: sensitivity analyses of cross-country regressions”, Kyklos, Vol. 54 No. 1, pp. 89-114.
Chang, S.J. and Rosenzweig, P. (2001), “The choice of entry mode in sequential foreign direct investment”, Strategic Management Journal, Vol. 22 No. 8, pp. 747-76.
Chetty, S.K. (1999), “Dimensions of internationalisation of manufacturing firms in the apparel industry”, European Journal of Marketing, Vol. 33 Nos 1-2, pp. 121-42.
Clark, T. and Pugh, D.S. (2001), “Foreign country priorities in the internationalization process: a measure and an exploratory test on British firms”, International Business Review, Vol. 10 No. 3, pp. 285-303.
Cosset, J.-C. and Roy, J. (1991), “The determinants of country risk ratings”, Journal of International Business Studies, Vol. 22 No. 1, pp. 135-43.
Davidson, W.H. (1980), “The location of foreign direct investment activity: country characteristics and experience effects”, Journal of International Business Studies, Vol. 11 No. 2, pp. 9-22.
Davidson, W.H. (1983), “Market similarity and market selection: implications for international marketing strategy”, Journal of Business Research, Vol. 11, pp. 439-56.
Davis, M. (2001), “Enron to sell offshore oil, gas assets in India to BG group”, The Houston Chronicle, available at: www.chron.com/CDA/archives/archive.mpl?id¼2001_3338792 (accessed October 4, 2001).
DePamphilis, D.M. (2005), Mergers, Acquisitions, and Other Restructuring Activities, Elsevier, Burlington, MA.
Douglas, S.P. and Craig, C.S. (1983), “Examining performance of US multinationals in foreign markets”, Journal of International Business Studies, Vol. 14 No. 3, pp. 51-63.
Dow, D. (2000), “A note on psychological distance and export market selection”, Journal of International Marketing, Vol. 8 No. 1, pp. 51-64.
Dow, D. and Karunaratna, A. (2006), “Developing a multidimensional instrument to measure psychic distance stimuli”, Journal of International Business Studies, Vol. 37 No. 5, pp. 578-602.
Dunning, J.H. (1973), “The determinants of international production”, Oxford Economic Papers, Vol. 25 No. 3, pp. 289-336.
Dunning, J.H. (1992), Multinational Enterprises and the Global Economy, Addison-Wesley, Reading, MA.
Dunning, J.H. (1998), “Location and multinational enterprise: a neglected factor?”, Journal of International Business Studies, Vol. 29 No. 1, pp. 45-66.
Edwards, R. and Buckley, P. (1998), “Choice of location and mode: the case of Australian investors in the UK”, International Business Review, Vol. 7 No. 5, pp. 503-20.
Ekeledo, I. and Sivakumar, K. (1998), “Foreign market entry mode choice of service firms: a contingency perspective”, Journal of the Academy of Marketing Science, Vol. 26, pp. 274-92.
IMR 26,6
670
Ellis, P.D. (2008), “Does psychic distance moderate the market size-entry sequence relationship?”, Journal of International Business Studies, Vol. 39 No. 3, pp. 351-69.
Evans, W., Lane, H. and O’Grady, S. (1992), Border Crossings: Doing Business in the US, Prentice-Hall, Scarborough.
Frankel, J. and Rose, A. (2002), “An estimate of the effect of common currencies on trade and income”, Quarterly Journal of Economics, Vol. 117 No. 2, pp. 437-66.
Gatignon, H. and Anderson, E. (1988), “The multinational corporation’s degree of control over foreign subsidiaries: an empirical test of a transaction cost explanation”, Journal of Law, Economics, and Organization, Vol. 4 No. 2, pp. 304-36.
Gaughan, P.A. (2002), Mergers, Acquisitions, and Corporate Restructuring, 3rd ed., Wiley, New York, NY.
Ghemawat, P. (2001), “Distance still matters”, Harvard Business Review, Vol. 79 No. 8, p. 137.
Ghosal, V. (1987), “Global strategy: an organizing framework”, Strategic Management Journal, Vol. 8, pp. 425-40.
Green, R. and Allaway, A. (1985), “Identification of export opportunities: a shift-share approach”, Journal of Marketing, Vol. 9 No. 1, pp. 83-8.
Harzing, A. and Sorge, A. (2003), “The relative impact of country of origin and universal contingencies in internationalization strategies and corporate control in multinational enterprises: worldwide and European perspectives”, Organization Studies, Vol. 24 No. 2, p. 187.
Hitt, M., Bierman, L., Uhlenbruck, K. and Shimuzu, K. (2006), “The importance of resources in the internationalization of professional service firms: the good, the bad, and the ugly”, Academy of Management Journal, Vol. 49 No. 6, pp. 1137-57.
Hofstede, G. (1980), Culture’s Consequences, Sage, Beverly Hills, CA.
Hotchkiss, C. (1998), “The sleeping dog stirs: new signs of life in efforts to end corruption in international business”, Journal of Public Policy & Marketing, Vol. 17 No. 1, pp. 108-15.
Hymer, S. (1976), The International Operations of National Firms, MIT Press, Cambridge, MA.
Irwin, J. and McClelland, G. (2001), “Misleading heuristics and moderated multiple regression models”, Journal of Marketing Research, Vol. 38 No. 1, pp. 100-9.
Jemison, B. and Sitkin, S. (1986), “Corporate acquisitions: a process perspective”, Academy of Management Review, Vol. 11 No. 1, pp. 145-63.
Johanson, J. and Vahlne, J. (1977), “The internationalization process of the firm: a model of knowledge development and increasing foreign market commitments”, Journal of International Business Studies, Vol. 8 No. 1, pp. 23-32.
Johanson, J., Vahlne, J. and Wiedersheim-Paul, F. (1975), “The internationalization of the firm: four Swedish cases”, Journal of Management Studies, Vol. 12 No. 3, pp. 305-22.
Johansson, J. (1997), Global Marketing, Foreign Entry, Local Marketing and Global Management, McGraw-Hill, Chicago, IL.
Kaufmann, D., Kraay, A. and Mastruzzi, M. (2007), “Governance matters VI: aggregate and individual governance indicators for 1996-2006”, World Bank Policy Research Working Paper No. 4280, The World Bank, Washington, DC.
Kobrin, S. (1976), “The environmental determinants of foreign direct manufacturing investment: an ex post empirical analysis”, Journal of International Business Studies, Vol. 7 No. 2, pp. 29-42.
Kogut, B. and Singh, H. (1988), “The effect of national culture on choice of entry mode”, Journal of International Business Studies, Vol. 19 No. 3, pp. 411-30.
Lambsdorff, J. (2002), “Corruption and rent-seeking”, Public Choice, Vol. 113 Nos 1-2, pp. 97-125.
Distance factors and target
market selection
671
Luostarinen, R. (1979), “Internationalization of the firm”, doctoral dissertation, Helsinki School of Economics, Helsinki.
Mitra, D. and Golder, P. (2002), “Whose culture matters? Near-market knowledge and its impact on foreign market entry timing”, Journal of Marketing Research, Vol. 39 No. 3, pp. 350-65.
Morosini, P., Shane, S. and Singh, H. (1998), Managing Cultural Difference: Effective Strategy and Execution Across Cultures in Global Corporate Alliances, Oxford Press, New York, NY.
Nordstrom, K.A. and Vahlne, J.-E. (1992), “Is the globe shrinking?”, paper presented at the International Trade and Finance Association’s Annual Conference, Laredo, TX, April 22-25.
O’Grady, S. and Lane, H.W. (1996), “The psychic distance paradox”, Journal of International Business Studies, Vol. 27 No. 2, pp. 309-33.
Ojala, A. and Tyrvainen, P. (2007), “Market entry and priority of small and medium-sized enterprises in the software industry: an empirical analysis of cultural distance, geographic distance and size”, Journal of International Marketing, Vol. 15 No. 3, pp. 123-49.
Organization for Economic Co-operation and Development (2006), “Emerging multinationals: who are they? What do they do? What is at stake?”, March 27, available at: www.oecd.org/ document/33/0,3343,de_2649_37413_36223265_1_1_1_37413,00.html (accessed January 24, 2008).
Papadopoulos, N., Chen, H. and Thomas, D.R. (2002), “Toward a tradeoff model for international market selection”, International Business Review, Vol. 11 No. 2, pp. 165-92.
Pothukuchi, V., Damanpour, F., Choi, J., Chen, C.C. and Park, S.H. (2002), “National and organizational cultural differences and international joint-venture performance”, Journal of International Business Studies, Vol. 33 No. 2, pp. 243-65.
Reid, S. (1983), “Export management: an international context/export policy: a global assessment/export development strategies: US promotion policy”, Journal of International Business Studies, Vol. 14 No. 2, pp. 153-6.
Richman, B. and Copen, M. (1972), International Management and Economic Development, McGraw-Hill, New York, NY.
Ring, P. and van de Ven, A. (1994), “Developmental processes of cooperative inter-organizational relationships”, Academy of Management Review, Vol. 19 No. 1, pp. 90-118.
Robertson, K. and Wood, V. (2001), “The relative importance of types of information in the foreign market selection process”, International Business Review, Vol. 10 No. 3, pp. 363-79.
Rothaermel, F., Kotha, S. and Steensma, K. (2006), “International market entry by US internet firms: an empirical analysis of country risk, national culture, and market size”, Journal of Management, Vol. 32 No. 1, pp. 56-82.
Sakarya, S., Eckman, M. and Hyllegard, K. (2007), “Market selection for international expansion; assessing opportunities in emerging markets”, International Marketing Review, Vol. 24 No. 2, pp. 208-38.
Scaperlanda, A. and Mauer, L. (1969), “The determinants of US direct investment in the EEC”, American Economic Review, Vol. 59 No. 4, pp. 558-68.
SDC Platinum Database (2007), Thomson Financial, SDC Platinum Database, London.
Shimizu, K. and Hitt, M.A. (2004), “Strategic flexibility: organizational preparedness to reverse ineffective strategic decisions”, TheAcademyofManagementExecutive, Vol. 18 No. 4, pp. 44-59.
Sousa, C. and Bradley, F. (2006), “Cultural distance and psychic distance: two peas in a pod?”, Journal of International Marketing, Vol. 14 No. 1, pp. 49-70.
Srivastava, R.K. and Green, R.T. (1986), “Determinants of bilateral trade flows”, Journal of Business, Vol. 59 No. 4, pp. 623-40.
IMR 26,6
672
Terpstra, V. and Yu, C. (1988), “Determinants of foreign investment of US advertising agencies”, Journal of International Business Studies, Vol. 19 No. 1, pp. 33-46.
Trevino, L. and Nelson, K. (1999), Managing Business Ethics, 2nd ed., Wiley, New York, NY.
Turnbull, P.W. and Ellwood, S. (1986), “Internationalization in the information technology industry”, in Turnbull, P.W. and Paliwoda, S.J. (Eds), Research in International Marketing, Croom Helm, London.
United Nations Conference on Trade and Development (1998), World Investment Report 1998: Trends and Determinants, United Nations, New York, NY.
Vernon, R. (1966), “International investment and international trade in the product cycle”, The Quarterly Journal of Economics, Vol. 80 No. 2, pp. 190-207.
Weitzel, U. and Berns, S. (2006), “Cross-border takeovers, corruption, and related aspects of governance”, Journal of International Business Studies, Vol. 37 No. 6, pp. 786-806.
Whitelock, J. (2002a), “Entry and co-operative strategies in international business expansion”, International Marketing Review, Vol. 19 No. 6, pp. 681-3.
Whitelock, J. (2002b), “Viewpoint: theories of internationalisation and their impact on market entry”, International Marketing Review, Vol. 19 Nos 4/5, pp. 342-8.
Whitelock, J. and Jobber, D. (2004), “An evaluation of external factors in the decision of UK industrial firms to enter a new non-domestic market: an exploratory study”, European Journal of Marketing, Vol. 38 Nos 11/12, pp. 1437-55.
WIR (2006), “FDI from developing and transition economics: implications for development”, World Investment Report 2007, United Nations Publication, Geneva.
WIR (2007), “FDI from developing and transition economics: implications for development”, World Investment Report 2007, United Nations Publication, Geneva.
Wood, V. and Goolsby, J. (1987), “Foreign market information preferences of established US exporters”, International Marketing Review, Vol. 4 No. 4, pp. 43-52.
Wood, V. and Robertson, K. (2000), “Evaluating international markets: the importance of information by industry, by country of destination, and by type of export transaction”, International Marketing Review, Vol. 17 No. 1, pp. 34-55.
About the authors Shavin Malhotra received PhD at Carleton University, Canada and he is an Assistant Professor in the Department of Global Management Studies at Ted Rogers School of Management, Ryerson University, Canada. His research interests focus on foreign direct investment and international market entry, especially in emerging economies and from a cross-disciplinary perspective incorporating marketing, finance, economics, and other disciplines.
K. Sivakumar (“Siva”) is an Arthur Tauck Chair, Professor of Marketing, and Chairperson of the Department of Marketing at Lehigh University, USA. His research interests include pricing, global marketing, and innovation management. He has over 40 refereed publications and has won several awards for his research. He is on the editorial boards of several scholarly journals. K. Sivakumar is the corresponding author and can be contacted at: [email protected]
PengCheng Zhu is an Assistant Professor of Finance at the Eberhardt School of Business at the University of the Pacific Stockton campus.His research focuses on cross-border mergers and acquisitions, corporate governance, emerging market finance and statistical methods in business research. Dr Zhu is a Chartered Financial Analyst (CFA).
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