entry modes and national systems of innovation

Journal of International Management 16 (2010) 340–353

Contents lists available at ScienceDirect

Journal of International Management

Entry modes and national systems of innovation

Isabel Álvarez a,⁎, Raquel Marín b

a Departamento de Economía Aplicada II, Facultad de Económicas and Instituto Complutense de Estudios Internacionales, Universidad Complutense de Madrid,Campus de Somosaguas. 28223-Pozuelo de Alarcón Madrid, Spainb DepartamentodeEconomíade la Empresa, FacultaddeEconomía,DerechoyEmpresariales,UniversidadEuropeadeMadrid and InstitutoComplutensedeEstudios Internacionales,C/Tajo s/n, Urbanización El Bosque. 28260-Villaviciosa de Odón Madrid, Spain

a r t i c l e i n f o

⁎ Correspondingauthor.DepartamentodeEconomíaApAlarcón Madrid, Spain. Tel.: +34 91 394 24 58; fax: +34

E-mail addresses: [email protected] (I. Ál1 Although a more complete picture of entry mode

major forms of internationalization, namely exports,

1075-4253/$ – see front matter © 2010 Elsevier Inc.doi:10.1016/j.intman.2010.09.005

a b s t r a c t

Article history:Received 17 February 2009Received in revised form 20 November 2009Accepted 20 November 2009Available online 13 October 2010

Multinational enterprises (MNEs) have contributed to the productive and technologicalupgrading of many host economies, whereas discussion about entry modes and developmentaleffects is far from being concluded. We explore the relative importance of national systems ofinnovation in various forms of firm internationalization. We hypothesize that, adopting adynamic perspective, institutional stability and the consolidation of R&D capacities reinforceentrepreneurship and become key driver mechanisms to improve the attraction of foreignentries. The empirical analysis is built upon a sample of countries with dissimilar levels ofdevelopment using longitudinal data for the period 1998–2004. The findings confirm that therelative technological advance of host countries differ for cross-border mergers andacquisitions (M&A) compared to other entry modes, taking into account the diversity of thedeveloping world, the potential of emerging economies and the need to investigate new driversfor the attraction of FDI.

© 2010 Elsevier Inc. All rights reserved.

Keywords:DevelopmentEntry modesMNEM&ANational systems of innovation

1. Introduction

Foreign direct investment (FDI) outflows and inflows have been concentrated in the most developed countries and onlyrecently has there been a shift in the direction of investments also affecting entry modes. In the last few decades, developingcountries have been entering the global scene and cross-border mergers and acquisitions (M&A) show a more dynamic behaviourthan greenfield start-ups (UNCTAD, 2005, 2007). In this paper we study the relationship between entry modes and nationalsystems of innovation through the analysis of entry modes1 in a multi-country framework, differentiating by the level ofdevelopment in host economies. As well as those elements traditionally claimed in the economics literature – i.e. production factorcosts and market imperfections – we explore others more related to the institutional framework and the absorptive capacities oflocations that can also be relevant determinants for the attraction of new foreign entries. Overall, we assume the central role oftechnology and innovation in the theories of multinational enterprises (MNEs) to explore the strength of host national systems ofinnovation and their link with entrepreneurship for explaining the increase in cross-border M&A.

The starting point is the existence of international divergences due to both supply and demand factors and the fact that MNEstrategies can affect the development of countries (Ozawa, 1992; Lall, 2002; Meyer, 2004; Pearce, 2006; Rugman and Doh, 2008).Research on entry modes provided us with explanations based on firms' advantages and the factors affecting their choices, butempirical evidence is less abundant from the point of view of national economies. Fresh research into internationalization anddiverse societal and environmental contexts could suggest some new implications for firmmanagers and policy makers. Available

licada II, FacultaddeEconómicas,UniversidadComplutensedeMadrid, CampusdeSomosaguas. 28223-Pozuelode91 394 24 57.varez), [email protected] (R. Marín).s would also include other forms such as licensing and joint — ventures, we will focus here only on threegreenfield and cross-border M&A.

All rights reserved.

http://dx.doi.org/10.1016/j.intman.2010.09.005

mailto:[email protected]

mailto:[email protected]

http://dx.doi.org/10.1016/j.intman.2010.09.005

http://www.sciencedirect.com/science/journal/10754253

341I. Álvarez, R. Marín / Journal of International Management 16 (2010) 340–353

evidence from the literature on international business and management reveals the relevance of both cultural and institutionalfactors of host locations to explain firms' entry mode decisions (Kogut and Singh, 1988; Rosenzweig and Singh, 1991; Harzing,1999; Davis et al., 2000; Dunning, 2006). Some streams of MNE theories underline the effects of MNEs to provide new productionfacilities, managerial practices and also technology transfer abroad but there are also reverse flows from foreign subsidiaries, sincefirms also look to tap into new knowledge in host locations (Cantwell, 1989, 1995; Barkema and Vermeulen, 1998; Frost, 2001;Piscitello, 2004; McCann and Mudambi, 2005; Singh, 2007; Mudambi, 2008; Yang et al., 2008). These two directions fit theapproach of this paper that highlights the role of national systems of innovation (NSI) in host economies. The NSI conceptualapproach has beenwidely used by both scholars and policymakers to carry out international comparisons between national stylesof management and innovation practices (Freeman, 1987; Lundvall, 1992; Nelson, 1993; Mowery and Oxley, 1995; Cantwell andMolero, 2003) and can also be helpful for the analysis of entry modes.

The complex relationship that is defined by the characteristics of locations and MNE entry modes allow us to observe that,according to the path of imports and FDI inflows, MNEs may be seen in a first stage as a facilitator for the industrialization ofdeveloping economies. Meanwhile, in further stages of development, the technological advance, the entrepreneurial and theinstitutional setting of host countries determine not only higher incoming flows but also a higher diversity of entry modes. Ourmain contribution was to differentiate entry modes in the logic of lesser developed economies and developed countries,respectively. The evolution of countries runs alongside a shift in international flows and accordingly they become more attractivefor cross-border M&A. This underlines the non-static nature of host systems, integrated by vertical linkages of production andmarketing activities, relationships between foreign and domestic firms, and also by consolidation of R&D and institutional settings.We perform a quantitative analysis of three forms of entry: exports, FDI in general2 and M&A in particular, using data for a sampleof both developed and developing economies over a time span of seven years (1998–2004). Panel data are the most appropriatetechnique and UNCTAD and the World Bank are the main sources of statistical information.

The next section is devoted to theoretical background and in the third section we develop our analytical hypotheses. In thefourth section, we proceed with data description by groups of countries. Next, we present an empirical analysis, attempting todetect the importance of host countries' systems of innovation for international flows and, particularly, for cross-border M&A.Finally, we present some conclusions as guidance for management practices and policies as well as for further research.

2. Literature background

2.1. Firms' internationalization and host economies

The economics and business literature on firm entry modes centres round the exploitation of competitive advantages, thereduction of transaction costs and the role of market structures and imperfections. The willingness of companies to afford thecommitment of resources, the assumption of risks and also the expectation of learning abroad provide some of the driving forcesfor firms choosing to internationalize (Agarwal and Ramaswami, 1992; Slangen and Hennart, 2007). These forces are related to theFDI motives that may differ according to the firms' strategies of resource seeking, market seeking, efficiency seeking andknowledge seeking, and these interact with the stage of economic development of countries (Narula, 1996; Dunning, 2006).

The investment development path hypothesis states (Dunning and Narula, 1996) that the different stages of countrydevelopment also define different patterns of FDI behaviour. In fact, some middle-income economies have already becomeattractive for foreign investors and they become active players as investors as well (Meyer, 2004; Cuervo-Cazurra, 2007). In thissense, an important distinction exists betweenmore backward countries –mainly African and those from the low-income group –

and those actively gaining ground in an international context, such as Malaysia and Indonesia among others, and the so-calledBRIC economies — Brazil, Russia, India and China. These differences reinforce the idea that a study of entry modes and thepossibilities for international technology diffusionmay differ between developed and developing economies, and also suggest thatspecial caution is required in the latter group.

From the firms' point of view, a key aspect is that higher fragmentation of the global value chain and the changing locationpatterns of MNEs in knowledge-intensive areas have brought about decentralization of core activities such as R&D as well as therelocation of themore standardized parts in emergingmarket economies (Mudambi, 2008). Themicro foundations of the decisionto centralize or to decentralize key activities such as R&D through its subsidiaries suggests the existence of internationaltechnological flows from the parent to the subsidiary and vice versa. This is the proposition of a recent formal model fororganizational implications of the interaction with host productive systems that decentralization choice would generate (Sanna-Randaccio and Veugelers, 2007). The key issue is that MNEs becomemulti-centric firms exploiting the diversity of location and thenetwork nature implies specific knowledge management (Bartlett and Ghoshal, 1998; Mudambi, 2002). Indeed, the literature onthe contribution of subsidiaries to knowledge flows claims that one of their key roles could be the exploitation of competenciesfrom all over the firm's network, trying to create entirely new competencies and taking advantage of the assets in host countries,making it particularly appropriate to reconsider the traditional notion of competitive advantages (Rugman and Verbeke, 2001).

Regarding the developmental effects of MNEs in host countries, these are very diverse. Apart from their effects on employmentand value added creation, multinational companies can create and trade in intangible assets and their activities can contribute tothe international generation and diffusion of knowledge (Cantwell, 1989; Ozawa, 1992). This can be observed in the possibilities of

2 The available aggregated information for FDI inflows used in this study includes other minor forms of foreign direct investments but throughout this paperwe will use the term “greenfield” or “greenfield investment” to refer to it and to make a clear distinction with regard to cross-border M&A.

342 I. Álvarez, R. Marín / Journal of International Management 16 (2010) 340–353

technology transfer to host locations via technology diffusion of trade in the form of embodied knowledge in goods and services.There are also possible effects of increasing competition due to the presence of foreign-owned firms, an increase in demonstrativeeffects that enhance new productive and technical practices in their vertical linkages and also a greater mobility of highly skilledworkers (Rugman and Doh, 2008).

The consequences from the different forms of internationalization in host countries could thus depend on technologicalcapacities and supplier and entrepreneurial capabilities. In particular, at the subsidiary level, the conceptualization of competence-creating and competence-exploiting mandates (Cantwell and Mudambi, 2005) claim that these two types look differently torecipient economies, and knowledge-related assets gain higher relevance.3 Different industries need different elements from theenvironment, such as those related to knowledge and technical sources, skills from universities and also from other industries andgovernment agencies (Chung and Alcácer, 2002). Then, according to whether the strategies of subsidiaries imply complextechnological activities and knowledge sourcing, the relevance of location characteristics will be greater, such as those related toscience bases, infrastructure level, public research facilities or educational system (Cantwell and Piscitello, 2002).

2.2. Entry modes and host countries' systems of innovation

Asset-exploiting and asset-augmenting strategies of MNEs can relate differently with host countries' systems of innovation(Narula and Dunning, 2000; Cantwell andMolero, 2003). Meanwhile, in making decisions concerning entry modes, firms considervarious conditions in the host economies, including those related to domestic firms and factors at both industry and country levelsas well. We focus here on the reasons why investor firms choose cross-border M&A instead of greenfield ventures. Cross-borderM&A seem to be more likely in multidomestic industries – where competition in each country is independent of competition inother countries – because foreign companies are more dependent on local resources and have greater need to gain legitimacy(Porter, 1986; Harzing, 1999). Horizontal acquisitions are generally driven by the search for new markets, products and brandsrather than cost cutting (Capron, 1999) and consistent with the literature, M&A favour access to vertical linkages in host countries;acquired affiliates are likely to have a higher local content, given their pre-acquisition embeddedness in the host economy asdomestically-owned firms (Belderbos et al., 2001).

Local experience can then be seen as a crucial aspect for learning about the local culture and for this reason acquisitions becomea more likely mode of gaining experience in the host country (Barkema and Vermeulen, 1998). Cultural proximity between homeand host countries and low uncertainty are also factors that increase the likelihood of entry via M&A (Kogut and Singh, 1988;Brouthers and Brouthers, 2000; 2003; Chang and Rosenweig, 2001; Globerman and Shapiro, 2002; Shimizu et al., 2004). Althoughinstitutional business literature has been mainly focused on legal and cultural aspects (Scott, 1981; 1983), the set of elementsintegrating the external environment of the subsidiaries is larger and it includes technology, government regulations, culture andindustrial structure (Rosenzweig and Singh, 1991; Davis et al., 2000). Moreover, these elements of the external environment mayoffer new investment opportunities for MNEs even in culturally distant countries, as is the case of emerging economies (Hitt et al.,2006).

In addition, empirical evidence supports the idea that MNEs choose acquisitions when the geographic scope of thesubsidiary's mandate is broad and when the MNE has greater multinational experience (Mudambi and Mudambi, 2002). Thosefirms more diverse and with lower R&D intensity are more likely to buy technological capabilities in other countries byacquisitions and this propensity increases where local firms have well established distribution systems and a deeper knowledgeof the local market (Harzing, 1999). Entry mode can in turn affect the extent of knowledge transfer since the investment sizeand the subsidiary's role vary with it, as is confirmed in the evidence of Yang et al. (2008) about determinants of conventionaland reverse knowledge transfers in three transition economies in Central and Eastern Europe (CEE) where some significantcountry effects were found.

The NSI approach is suitable for exploring the relationship between entry modes and host country features at an aggregatedlevel. This conceptual approach generally refers to the influence and evolution of production activities and the relationshipwith theinstitutional setting in knowledge generation, considering both informal institutions (such as trust) and formal arrangements (suchas intellectual property rights or contract laws) (Lundvall, 2007). In a broad sense, this includes in a unique analytical frameworkthe combination of more traditional aspects of vertical linkages in the production systems – introducing learning-by-doing andlearning-by-searching–with somemicro assumptions based on the chain-linkedmodel of innovation (Kline andRosenberg, 1986),the sources of innovation (Von Hippel, 1988) and the institutional dimension that enhances interactive learning (Lundvall et al.,2002).

This approach is useful as a general framework to study the differences between productive and research systems of countries,making it possible to analyse absorptive capacities and the learning capability of individuals and organizations that take part in theinnovation processes. This is consistent with available evidence that shows how industrial concentration and the clusters of high-technology provide a knowledge-specialized environment that becomes more attractive for the reception of MNEs (Mudambi,2002; Tihanyi and Roath, 2002; Cantwell andMolero, 2003). In sum, we could say that firms chooseM&A to take advantage of localaccess related to distribution networks, political connections and cultural knowledge, as well as to take advantage of knowledgeconcentration. In this sense, country institutional characteristics are determinants of technology transfer and socioeconomicdevelopment becomes significant to MNEs entering a foreign economy, conditioning even their entry mode.

3 Similarly, effects differ between foreign subsidiaries defined by home base exploiting strategies and home base augmenting, in which the bulk of the activity isoriented to increasing the technological basis through the incorporation of other created assets available in advanced foreign countries (Kuemmerle, 1999).


3. Hypothesis development

In this paper we look at the relationship between entry modes and the development levels of host countries in order to detectwhether cross-border M&A may denote a different and greater interest in host national systems of innovation than other entrymodes. This form of entry implies a greater and faster interaction with domestic capabilities and it can be expected to be moredependent on the higher levels of development achieved by recipient economies. M&A are likely to occur only when there arevaluable targets in the host economy, an aspect that is conditioned by the entrepreneurial capabilities of the host systems ofinnovation as well as by other specific assets related to the existence of specialized knowledge or superior scientific andtechnological capabilities.

Our objective is to assess the relationship between modes of entry and national systems of innovation through three differentcomponents. One refers to the trade form of internationalization assuming that exports imply a lower commitment of resourcescompared to other entry modes (Agarwal and Ramaswami, 1992; Slangen and Hennart, 2007). The second concerns FDI flows thatdo not discriminate between themore qualitative aspects of investments and this will often require the generation of new facilitiesin the foreign location. The third is related to the higher involvement of foreign capital that is measured by the annual volume ofcross-border M&A, assuming that these investments generate a higher degree of interaction in host economies (Xu, 2000).Greenfield ventures usually require the development of intermediate relationships with national partners for access to suppliers,the establishment of distribution channels and even the search for research or technological partners. The great advantage of M&Aentries is direct access to already established vertical linkages with targeted local firms. In fact, acquired affiliates present a higherlocal content that also affects knowledge-related assets, as previous empirical evidence has demonstrated (Belderbos et al., 2001);from the analysis of Japanese firms, Belderbos (2003) shows that there are marked differences in the R&D intensities of foreignmanufacturing affiliates and this depends on their entry mode because acquired affiliates achieve substantially and significantlyhigher R&D intensities than wholly owned new ventures. Moreover, some recent evidence built up from the internationalizationof Swedish MNEs shows that acquired affiliates are more likely to do R&D and, to a larger extent, that M&A were more motivatedby asset-seeking strategies than greenfield operations during the 1990 s (Bertrand et al., 2007).

A key idea is that themost developed countries also have better technological and entrepreneurial capabilities and these can bea determining aspect to being more attractive for takeovers. As a matter of fact, cross-border M&A have accounted for a modestshare of the overall FDI activity in developing economies until now, although firms from these countries are increasingly becominginvolved in M&A (UNCTAD, 2005). Fig. 1 shows the potential relationship between the level of development of host countries andentry modes that is conceived as a dynamic process characterized by two main trends: less diverse incoming flows in lesserdeveloped stages and the increasing attractiveness for M&A in the following stages. Dynamics is crucial to understanding that thepossibilities for participating in the shift of entry modes – M&A gaining more ground – do not define a deterministic process. Inparticular, the importance of the qualitative elements related to the NSI would encourage the shift in FDI flows towards M&A.

There are two main aspects that arise once the time dimension is taken instead of a static view. On the one hand, the evolutionof firm strategies in foreign countries changes over time and companies becomemore integrated in host systems (Pearce, 1999). Inthis sense, the path of foreign companies in local economies provides additional incentives for new inward FDI because MNEsoften prefer to invest in countries where they are already active; their past experience would define a cumulative process of FDIentries (Davidson, 1980; Mudambi, 1995). On the other hand, the relevance of R&D investment, determinant for economicdevelopment, increases the absorptive capabilities of host systems of innovation. This concept of absorptive capabilities has beenadopted from the micro concept formulated by Cohen and Levinthal (1990), being understood as the possibilities of organizationsto benefit from those innovations carried out externally to the firms that come to define a second phase of learning.

Fig. 1. Development level and entry modes.


Therefore, through an empirical analysis according to previous theoretical and empirical evidence, we will test whether thediverse entry modes – exports, greenfield FDI and cross-border M&A – vary with the relative importance of the characteristics ofhost countries' systems of innovation. It can be expected that the more advanced a country's NSI is, the greater the likelihood thatthere will be new incoming flows, and particularly in the form of M&A. In order to operationalize this hypothesis and taking intoaccount that the prior presence of foreign capital, absorptive capacities and stability of the institutional framework in the hosteconomies would be indicators of a more modern and technologically active country, the following hypotheses can be stated:

H1. The prior presence of foreign capital in host economies will positively affect the different entry modes and its effect will begreater in the case of cross-border M&A.

H2. The absorptive capacities in host economies will positively affect investment flows and their effect will be greater in the caseof cross-border M&A.

H3. The institutional framework in host economies will positively affect the different entry modes and its effect will be greater inthe case of cross-border M&A.

It will also be necessary to include some important controls related to several economic factors such as the characteristics of theinternal market, the integration of the country into international markets and the labour conditions. Each of these factors isrepresented by its respective indicator and will be operationalized by the corresponding independent variable in the empiricalanalysis. Hypotheses and control factors as well as expected signs are summarized in Table 1 for each entry mode.

4. Data description

Graph 1 shows the distribution of three entry modes – exports, greenfield investments and cross-border M&A by groups ofcountries, taking natural logarithms of the three variables and usingWorld Bank criteria for the classification of countries according toGDP per capita – income variable – in four different groups.4 Among these, we chose the group of more developed countries in theworld – integrating the high-income level group – and developing countries which are divided into two different groups: upper-middle and lower-middle economies.5 Graph 1 illustrates first the existence of a positive relationship between the three forms ofinternationalization flows and the income levels of countries; second, the larger heterogeneity for cross-border M&A in all groups ofcountries. Trade entrymode shows thehigher values in the threegroups and thedistributionof theseflowsgoes hand inhandwith theincome level of countries. We can also see that there is still a notable gap in trade that is even more pronounced in the case of FDIinflows between more advanced countries and the developing economies. High-income economies present the highest levels of thetwo FDI entry modes, a more homogenous distribution of the two kinds of flows and there are only a few differences between them.For lesser developed economies (upper-middle and lower-middle-income), it is noticeable that M&A present lower levels althoughthe distribution of FDI is similar for the two groups of middle-income countries. However, the heterogeneity of cross-border M&A ismore pronounced for lower-middle-income countries. The emergence of dynamic markets such as India, China and Brazil areintegrating this group, an aspect that would justify the previously specified non-deterministic nature of the relationship.

We have also calculated some basic statistics for the different entry modes, for the features of host countries' systems ofinnovation that might affect them as well as for the economic factors. This enables us to have a descriptive and to observedifferences and similarities by country groups. The statistics are reported for both developed countries – integrated into the high-income level group – and developing countries, which are divided into upper-middle and lower-middle economies (Table 2). Allthe definitions of the variables included can be found in Table 3. Descriptions are also given for the BRICs as particular cases ofemerging economies inside the developing countries group.

The path of foreign capital presence (FDI stock), the institutional setting and the absorptive capacities describe the mainfeatures of the host systems of innovation. National absorptive capacities can bemeasured at an aggregated level through nationalR&D expenditures (Narula et al., 2002) and although it can be seen as an imperfect measurement of them, this indicator reveals theactivities and the efforts that the different units of an economy carry out to create and also to assimilate new knowledge.6 In animperfect manner as well, the institutional framework is measured by the Government Matters Indicator that has been built upunder the auspices of the World Bank.7 We also consider other more conventional factors as controls, such as market size and its

4 We have opted here for the criterion of income level (income per capita) to classify countries according to their level of development. Without any doubtdevelopment is a complex issue and there has been much discussion about its adequacy as an indicator of development (as some participants at the IBRF-2009noted). Nonetheless, income variable shows a high correlation with other aspects of development (such as education or health) that other rankings capture, suchas the Human Development Index (PNUD). Nonetheless, accepting the weakness of the indicator, the purpose here is just to observe differences between thegroups of developed and developing economies, whereas the unit for empirical analysis will be individual countries.

5 We added India to the lower-middle group (its present group of pertinence) because of its economic magnitude, although this country belonged to the low-income group for the years of reference in our analysis. However, we discarded the group of low-income countries for several reasons of data availability and forthe low dynamic impact of FDI in these economies. The list of countries as well as the country groups can be found in the Appendix Table 1A.

6 It must be said that the introduction of some other knowledge output indicators, such as patents, would be very useful — as some anonymous reviewers othe International Business Research Forum at Fox-CIBER-Temple University (IBRF-2009) have suggested. However, data on these indicators for the set of countriesincluded in the sample were not available, so it was not possible to include patents or other output variables in our analysis.

7 The “Governance Matters Indicator”, developed by Kaufmann et al. (2007), is the average of six different indicators: voice and accountability, politicastability, government effectiveness, regulatory quality, rule of law and control of corruption. For each one and for each country, 352 indicators were collectedfrom different sources: international organizations, rating agencies and others.

,

f

l

Graph 1. Distribution of "Exports," FDI and M&A, by groups of countries, 2004.

Table 1Features of host countries' system of innovation affecting entry modes.

Hypothesis scope Indicator of H Expected sign

Trade Greenfield M&A

National systems of innovation H1: Foreign capital + + +H2: Absorptive capacities n.s. + +H3: Institutional stability + + +

ControlsInternal market Size + + +

Dynamism + + +Foreign market Level of openness + + +Labour market Labour costs n.s. − n.s.

Workers' qualifications n.s. + +

n.s. not significant.


dynamism (measured by GDP and GDP growth), labour market aspects, such as wages and human qualifications (the lattermeasured by secondary education enrolment), and the openness level of countries (the weight of foreign trade – exports andimports – as a share of GDP).

We can see that developing countries are not a homogeneous group of economies and, in fact, on the contrary, it is possible toobserve the diversity among them. The heterogeneity between groups is more noticeable in some variables than in others andthere are also intra-group differences for some countries with similar income levels. On the one hand, for trade entry modes, thereare great differences between the most developed countries and the developing economies. The two middle-income groups arerather similar in their mean values although the higher standard deviation corresponds to the least developed (lower-middle-income group). On the other hand, developing countries (lower and upper middle-income) present similar mean values in inwardFDI flows, whereas the developed group shows a notably higher value (Table 2) and the higher dispersion in this indicatorcorresponds to the group of least developed economies. Regarding the profile describing variable M&A, it is remarkable that themost developed countries are less heterogeneous, whereas the highest value of the coefficient of variation in cross-border M&Acorresponds to lower-middle-income countries, demonstrating the notable dispersion of these operations in the group of leastdeveloped economies.

The descriptive statistics also show that accumulation of foreign capital, measured by the FDI stock in host economies, showslarge inter-group differences. The differences between developed and developing countries are even more marked for the other

image of Graph�1

Table 3Summary of variables.

Variable Definition Source

TRADE Imports of goods and services (US$, PPP) measured in natural logarithms World Bank, WDI 2007FDI Foreign Direct Investment (net inflows, $US) measured in natural logarithms UNCTAD, FDI databaseM&A Mergers and Acquisitions (inflows, $US) measured in natural logarithms UNCTAD, FDI databaseFDIStock Stock of FDI ($US, PPP) measured in natural logarithms World Bank, WDI 2007RD Research and Development expenditures (%GDP) measured in natural logarithms World Bank, WDI 2007GMI Governance matters indicator World BankGDP Gross Domestic Product (US$ constant 2000) measured in natural logarithms World Bank, WDI 2007ΔGDP Annual growth rate of GDP measured in natural logarithms World Bank, WDI 2007OP Openness: Exports and imports of goods and services (%GDP) measured in natural logarithms World Bank, WDI 2007W Compensation of employees ($US, PPP) measured in natural logarithms World Bank, WDI 2007HK Human Capital: School enrolment in secondary education (%Total) measured in natural logarithms World Bank, WDI 2007

Table 2Descriptive statistics a, 1998–2004.

High income Upper-middle income Lower-middle income BRIC economies

Mean Std. Dev/Mean

Mean Std. Dev/Mean

Mean Std. Dev/Mean

Mean Std. Dev/Mean

TRADE (millions US$, PPP constant 2000) 204,908.24 1.43 34,545.63 1.26 30,914.21 2.30 138,047.41 1.10FDI (millions US$, PPP constant 2000) 19,345.62 2.05 3285.51 1.42 4219.01 2.55 20,205.08 1.06M&A (millions US$, PPP constant 2000) 17,967.12 2.43 1517.28 1.90 1269.65 2.78 4691.65 1.41FDI stock (millions US$ PPP) 159,698.07 1.58 27,238.53 1.26 22,384.70 2.07 99,188.33 1.29R&D/GDP (%) 1.92 0.55 0.59 0.53 0.44 0.75 0.97 6.18Governance matters 1.32 0.33 0.35 1.49 −0.39 0. 927 −0.33 1.14GDP (millions US$ constant 2000) 828,853.96 2.32 216,823.47 1.38 493,549.93 2.27 2,622,046.23 1.41GDP growth (%) 3.01 0.84 3.67 1.19 4.38 0.87 5.45 1.51Openness (%) 94.54 0.68 98.21 0.47 72.95 0.42 41.10 2.57Wages (millions US$ PPP) 35,575.67 1.72 7326.82 1.40 8412.25 1.50 38,480.00 2.42Human capital (school enrolment insecondary education, %)

109.82 0.19 84.39 0.15 76.91 0.21 78.61 3.38

a The list of countries as well as the country groups can be found in the Appendix (Table 1A). See Table 3 for definitions of variables.


qualitative local factors of FDI attraction, such as educational level and R&D intensity (Table 2). Among the most important factorsdefining the existing gap between developing and high-income countries are precisely those related to technological indicators –R&D, patents – in which inequalities are even more pronounced than in other fields (Álvarez and Magaña, 2007). Regardinginstitutional stability, it is not surprising that the statistics obtained also reveal the existence of a large gap between developed anddeveloping worlds. The mean values for countries in the lower-middle-income group show the lowest stability of the regulatoryframework, and the values are even negative. These statistics illustrate the extreme heterogeneity of the developing world – hererepresented by 43 countries – as well as the potential and the weaknesses the countries in the middle-income group have forcatching-up in the economic globalization process.

Likewise, there is still a significant difference in the level of salaries in developed economies compared to the developingworld – notably higher in the former group – as well as whenwe observe the relative internal market size of the different groupsof countries. The opposite is shown in the dynamism of the market, revealing largest mean values for the countries with lowestlevel of development, although the dispersion of the variable distribution is larger for them. Additionally, in aspects such as theopenness level of both high and upper-middle-income countries, the averages for these two groups are very similar, evengreater for the latter group with a greater dispersion in the former.

Special cases in the group of developing countries are the BRIC economies, which perform better than most other middle-income countries and are becoming especially important for firm internationalization strategies (Hitt et al., 2006). The descriptivestatistics of the different entry mode indicators for this group of countries (last two columns of Table 2) show that the BRICcountries have become active players in the world economy, especially noticeable in the mean values of trade – higher than theother two groups of middle-income countries – and FDI – even higher than the value of developed economies. Regarding M&A,although their mean value is far from that achieved by the high-income group, these kinds of deals are more intense in the BRICgroup than in the middle-income countries. The accumulation of foreign capital is indeed a relevant feature of these economiesand the heterogeneity is lower than that of themost developed economies, according to the value of the coefficient of variation forthis variable. Considering other qualitative factors for the attraction of FDI, the BRIC economies show a higher R&D intensity thanthe developing countries and with regard to institutional stability, this group of countries still shows a mean value that is far fromthat obtained for the high-income group and the highest variance. Finally, in terms of education, the descriptive statistics revealsimilar values to other developing countries, while the main points of difference between the BRICs and the other middle-incomecountries are those related to market size and its dynamism.


5. The empirical analysis

5.1. The empirical model

With this empirical model we try to explain the different entry modes, namely export flows, greenfield investment flows andcross-border M&A, as a function of some features of the host systems of innovation: the cumulative nature of foreign capital(FDIStock), R&D intensity (RD) and institutional framework (GMI).8 Besides these three factors, there are also other importanteconomic aspects such as size and growth of the internal market (GDP and ΔGDP), level of openness (OP), labour costs (W) as wellas human capital level (HK); we have performed controls for them in our model. All these variables are introduced into theestimations taking logarithm transformations, with the exception of GMI.9 In a first model estimation, our dependent variable isexport (TRADE), in the second it is greenfield investment (FDI), and in the third, cross-borderM&A (M&A). Each is regressed againstthe set of factors and controls just mentioned.

Eq. (1) is adopted for the estimation of TRADE, FDI and M&A, separately. Moreover, time and country dummies are alsoincluded to consider those macro impacts not explicitly controlled in the model. The variables and their definitions are listed inTable 3.

log yit

8 Cor9 The

of law a

= α1log FDIStockit + α2log RDit + α3log GMIit + α4log GDPit + α5log ΔGDPit

+ α6log OPit + α7log Wit + α8log HKit + ηdi + υdt + εit

ð1Þ

Estimation method, availability of panel data and time dimension are all crucial elements to test our working hypothesesconcerning the role of NSI features in the explanations of TRADE, FDI and M&A. The model is estimated by following a dynamicapproach where the inherent endogenous structure of the model is taken into account: the dependent variable, present andlagged, may be correlated with the independent variables (determinants); that is, past results may determine the mode of entrynow. A common way of dealing with the problem is to test to what extent national factors affect entry results, as well as toeliminate non-observable effects. The generalized method of moments (GMM) uses first differences transformation to wipe outnon-observable individual effects and all possible lags of regressors as instruments to eliminate possible correlations withindividual effect (Arellano and Bond, 1991). An extension of the GMM estimator considers both the original instruments in levelsfor equations in first differences, as well as instruments in first differences for equations in levels (Arellano and Bover, 1995;Blundell and Bond, 1998). In this estimation procedure, which is called system-GMM, predetermined variables in levels areinstrumented with lags of their own first differences. The system-GMM estimation procedure is the one adopted in estimating ourequations because of its superior performance and its inherent advantages over the first differenced GMM estimator since itexploits all available moment conditions.

5.2. Discussion of the results

The results of the estimation from the dynamic panel allow us to confirm that trade presents a positive relationship with thestock of FDI in the economy as well as with the institutional framework (H1 and H3 confirmed). However, the absorptive capacities(R&D intensity) do not reveal a significant relationship (as was expected for H2) (column 1 of Table 4). Thismode of entry is clearlyconditioned by the size of the domestic market and it is also related to the level of openness to foreign markets, the coefficientscorresponding to these indicators being positive, while market growth and labour market conditions are not significant. Whencontrolling by the level of development, the same results apply and no differences were observed (column 2 of Table 4).

Regarding greenfield FDI, this entry mode is positively related to the previous presence of foreign capital in the economy as wellas to the institutional features of host countries (H1 and H3 confirmed). The size and internal market dynamism are also significantelements of attraction but labour costs act in a negative direction and the degree of openness and human capital level are notsignificant (column 4 of Table 4). On the other hand, themain factor revealing absorptive capacities such as the R&D intensity doesnot seem to have a powerful explanatory capacity (H2 not confirmed). Nonetheless, results in column 5 of Table 4 show thatdifferentiated results arise when controlling by the national level of income per capita. Absorptive capacities become significant,although only at 90 per cent level of confidence, for those countries with a lower level of development, since the interactedvariable (R&D⁎ lower-middle-income) behaves differently compared to the other groups of countries.

Regarding cross-border M&A, the panel estimation also shows that past FDI presence and the institutional framework aresignificant factors positively related to this entry mode and that their effects are higher than in the case of the other two entrymodes. Also, absorptive capacities definitively gain ground in the explanation of this entry mode (H1, H2 and H3 confirmed)(column 7 of Table 4). The dynamism of the domestic market is significant – although only at 90% of confidence – while internalmarket size, labour costs and level of human capital in host economies do not seem to play a significant role for cross-border M&A.Moreover, when the development level of countries is considered (column 8 of Table 4), our findings reveal that R&D intensity

relations among variables can be found in Table 2A of the Appendix.Government Indicator is the average of a set of indicators on voice and accountability, political stability, government effectiveness, regulatory quality, rulend control of corruption.

Table 4GMM estimations.

TRADE FDI M&A

(1) (2) (3) (4) (5) (6) (7) (8) (9)

FDIStock 0.156***(0.047)

0.143***(0.49)

0.134***(0.043)

0.800***(0.068)

0.814***(0.073)

0.874***(0.070)

0.833***(0.143)

0.851***(0.165)

0.865***(0.147)

RD 0.096(0.083)

0.171(0.118)

0.601***(0.220)

GMI 0.314***(0.089)

0.338***(0.089)

0.346***(0.090)

0.214*(0.122)

0.192(0.124)

0.099(0.127)

0.664**(0.277)

0.617**(0. 275)

0.615**(0.299)

GDP 0.775***(0.084)

0.761***(0.075)

0.783***(0.072)

0.296**(0.117)

0.304**(0.121)

0.247(0.245)

0.249(0.242)

0.341(0.252)

0.247(0.245)

ΔGDP −0.169(0.128)

−0.161(0.088)

−0.127(0.095)

0.042**(0.018)

0.041**(0.018)

0.867(1.095)

0.076*(0.043)

0.064*(0.037)

0.867(1.095)

OP 0.597***(0.080)

0.603***(0.091)

0.590***(0.080)

−0.240(0.169)

−0.255(0.175)

−1.123***(0.413)

−1.294***(0.342)

−1.333***(0.378)

−1.123***(0.413)

W 0.027(0.082)

0.049(0.062)

0.044(0.065)

−0.252**(0.127)

−0.278**(0. 134)

−0.225(0.232)

−0.186(0.259)

−0.328(0.241)

−0.225(0.232)

HK −0.157(0.163)

−0.166(0.178)

−0.235(0.168)

−0.264(0.272)

−0.184(0.307)

0.300(0.732)

0.237(0.523)

0.516(0.398)

0.300(0.732)

RD*High 0.115(0.157)

0.042(0.204)

0.108(0.245)

0.042(0.204)

−0.031(0.356)

−0.068(0.335)

RD*UpperMiddle 0.135(0.123)

0.178(0.208)

1.088***(0.400)

RD*LowerMiddle 0.040(0.092)

0.243*(0.139)

1.080**(0.459)

RD*BRIC 1.802(1.507)

−0.628(1.581)

2.580(1.886)

RD*Middle a 0.063(0.096)

0.236*(0.135)

1.096***(0.371)

Hansen test Chi2 36.74 37.06 35.01 48.21 48.38 35.88 53.80 53.92 41.58Arellano-Bond testfor AR(1)

−2.94** −2.95** −2.05** −2.79*** −2.80*** −2.68*** −1.94** −1.95** −1.94**

Arellano-Bond testfor AR(2)

−1.05 −1.27 −0.82 0.35 0.34 −0.63 −0.81 −0.87 −0.77

Number ofobservations

404 404 404 404 404 404 364 364 364

Number ofindividuals

72 72 72 72 72 72 71 71 71

* Significant at 10% level; ** significant at 5% level; ***significant at 1% level.Robust standard errors in parentheses.All variables are in logarithms except the Governance Matters Indicator.

a The BRIC economies have been excluded from the group of middle-income economies.


reinforces our arguments regarding the role of national systems of innovation in the explanation of FDI flowswith a higher level ofcommitment with host economies. This is revealed by the positive and significant R&D coefficient that clearly distinguishes thebehaviour of M&A from the other entry modes, while they have in common the presence of foreign capital in the economy andinstitutional factors such as political stability and the regulatory quality of host NSI.

A particular case in this analysis is the set of countries making up the BRIC group. The BRIC economies are not only hugemarkets with a very dynamic economic growth, becoming very attractive for foreign investment, but they also show somepotentialities related to knowledge assets. Some of these countries have even been able to develop their own technologies (i.e.Brazil in aircraft, electronics, computers; India in computers) and this is the result of a combined action of states, foreign capitaland domestic capital. In fact, it is noteworthy that Brazil, India and China are among the first ten middle-income countries in thecompetitiveness ranking elaborated by the World Economic Forum (Porter and Schwab, 2008). For this reason, an estimation isalso carried out considering the BRIC economies separately (columns 3, 6 and 9 in Table 4). Results show that this group ofcountries performs in a similar way to the high-income ones when the three different entry modes are analysed. In particular,neither of the BRIC coefficients is significant when the three entry modes are regressed against the set of factors defined.Nonetheless, we highlight some main differences that are related. First, the market size factor is still more relevant ininternationalization via trade while the dynamism of the market loses its explanatory capacity as a determinant of cross-borderM&A, although it is still relevant in the case of greenfield investments. Secondly, prior presence of foreign capital and institutionalstability gain in weight in the explanation of both FDI entry modes. These findings confirm the relevance and importance ofqualitative elements related to NSI in the shift from more traditional entry modes to M&A even in developing economies. In fact,the results suggest that absorptive capacities are more important as determining factors explaining cross-border M&A for thoseemerging countries that are still developing their productive and technological systems.

These results justify the fact that, although internationalization via cross-border M&A has to face the difficulty of integratingdifferent business cultures (acquiring and acquired firms), investing companies are more interested in accessing the intermediate


linkages already built up by the acquired unit as well as the intangible assets of the host economy. A valid argument would be thatthe more advanced the national systems of innovation are, the higher the likelihood will be of enhancing user-producerrelationships, which will also favour competitiveness and innovation (Lundvall et al., 2002; Álvarez et al., 2009). These positiveaspects are not so immediate in the case of greenfield ventures because there is not necessarily a direct relationship previouslyestablished between the investors and the national entrepreneur and institutional fabric. On the other hand, M&A seem to berelated negatively with the degree of openness of host economies, while no effect has been found for FDI inflows. Although wehave not explicitly analysed this aspect as a determinant of FDI entry in host economies, a plausible explanation for this negativesign could be linked to the tariff jumping effect that has been shown in previous evidence from Belderbos et al. (2001) about thedifferences in home nationalities; i.e. tariff jumping as a motivation for Japanese manufacturing investments seems to be a likelyexplanation for the differences with European and USmultinationals. This reason could be behind the strong reliance on greenfieldinvestments to expand Japanese manufacturing operations abroad whereas EU and US multinational firms show a greaterpreference for acquisitions. Putting aside the possible home-country effect of the investing company, not controlled in our model,our cross-country analysis confirms that a more protective foreign trade regulation in host economies could become an importantfactor in the direction of cross-border M&A that find greater motivation in the dynamism of the internal market.

These findings satisfactorily confirm our hypotheses; we argue that there are significant elements of differentiation inunderstanding the path of the main entry modes over the last decade. They also indicate the existence of a combination of bothinstitutional and economic factors of host economies in the explanation of worldwide flows. Meanwhile, foreign capital presenceand government indicators are significant determinants for the three forms of entry, although the institutional setting of the NSI ismore evident in M&A. Absorptive capacities are more related to the attraction of investors to take over firms more permanentlyestablished and positioned in host productive systems. In this sense, the significance of the R&D variable should not be understoodhere only as a mere indicator of a higher capacity of knowledge generation in countries but also as the expression of moreadvanced productive and technological systems, with greater entrepreneurship abilities that become more appealing for theforeign investors choosing M&A as the preferable entry mode. In particular, a more R&D intense system can reveal a greaterintensity of university-firm relationships and a more articulated and favourable institutional setting for technological andproductive activities. These aspects could be of great interest to those firms that decide to penetrate foreign markets by acquiringalready existing firms.

From an exploration of the differences that can be seen in the behaviour of entry modes, our findings confirm that thepersistence of world heterogeneity is more noticeable in the case of cross-border M&A; this is clear even when leaving aside theleast developed economies (the low-income group) and considering the intra-group differences existing among middle-incomecountries. The results of our analysis are consistent with the importance that the different level of resource commitment has forthe different entry modes chosen by firms and how this aspect relates to the diverse level of development in recipient economies.Cross-border M&A seem to be an option for companies investing abroad that are more closely determined by the regulatory andinstitutional framework of the host countries, conceding greater importance to knowledge-based aspects such as the R&Dintensity of locations. This is true for the complete sample of countries in our empirical analysis and particularly revealing fordeveloping economies, while the evidence for the BRIC economies reconfirms our arguments. It is possible that these emergingeconomies have succeeded in upgrading their productive, technological and entrepreneurship capabilities, revealing their greaterability to attract new investment flows and especially in the form of M&A.

A significant coefficient for R&D intensitieswas obtained in estimating the generalmodel and itwas reinforcedwhen controllingfor the level of development of countries, notably significant in the case of upper-middle-income economies. This group includessome Asian countries, many European transition economies (Central and Eastern Europe) as well as most of the Latin Americancountries. It is possible that the shift toward greater economic and political stability as well as their growth opportunities give ahigher potential for growing markets. Some of these economies have committed an important amount of resources and specificpolicies to activate their productive and education systems. The group of emerging market economies has been successful inupgrading its national capabilities, becoming more attractive to foreign investors too (Hobday, 1995). Moreover, companies fromemerging economies are also changing their international strategies and becomemore integrated in international flows (Broutherset al., 2005; Singh, 2007). The combination of all these aspects enables us to argue that an evolutionary pathmay be describedby thebehaviour of foreign investments, the development level of countries and the increasing trend of internationalization via M&A. Infact, our findings for the BRICs illustrate their positive path and their similarities with the profile of the high-income group. Thepotential for positive effects in host economies enriches their options for catching-up and for integrating into more advanced anddynamic international markets. Thus, institutional stability and the importance of an innovative environment could be noteworthyfor policy makers in charge of FDI attraction, while some new and further research is required on the differences found in thedeveloping world that could provide new insights for the managers of international companies.

6. Conclusions

The process of business internationalization is intimately related to aspects of national embeddedness as the institutionalismapproach underlines. The increasing role of some emerging and developing economies in international trade and FDI flowsencourages new research that combines management with more national and macro perspectives. This study presents anintegrative framework of entry modes, providing some fresh empirical evidence for a broad sample of countries that includesdeveloped and developing economies under the optic of the national systems of innovation conceptual framework. Our empiricalfindings confirm that the factors regardingmore consolidated systems better explain cross-border M&A trends whereas economic


factors are more related to the behaviour of exports and greenfield investments. In all the entry modes, the relevance of hostinstitutional frameworks is noteworthy. Nonetheless, the differences allow us to observe the interplay between past flows, newentries and the level of economic development. In particular, the factors explaining M&A flows are more related to the qualitativeinstitutional setting of host countries since absorptive capacities could be more appealing for investments of foreign companiesinterested in sharing entrepreneurship, technological activities and interactions and linkages already established in catching-upsystems. Among the implications for managers we find that when knowledge-searching strategies prevail, M&A in countrieswhere clusters of knowledge are located are a good option. Moreover, other M&A entries performed by competitors in the sameindustry show us where knowledge assets are available; then, M&A would also be a better option than greenfield.

Although international investments are still highly concentrated, developing economies are gaining some ground in the worlddistribution of flows and their pathmay differ from developed countries. Nevertheless, the evidence presented here on the diversemodes of entry opens up new questions about the role of national capabilities, both in attracting foreign capital and inunderstanding global learning processes. The findings are illustrative of the different behaviour of entry modes in a heterogeneousgroup of developing countries in which emerging market economies – the BRIC economies among them – are contained. Theresults of this empirical analysis are at least suggestive for broadening the scope of research on the behaviour of MNEs and theirchoice of entry in relation to the level of commitment in host productive economies and their potential impacts. Besides apersistence of international differences between both more developed and developing countries, a noticeable heterogeneity thatcharacterizes the developing world, in which catching-up and laggard economies co-exist with differentiated profiles, is an aspectthat may have specific consequences for company managers and policy makers at both national and regional levels, and even forthe definition of actions by the international community trying to enhance development processes in the more laggard countries.Overall, this is an issue which still deserves further research.

Acknowledgements

The authorswould like to specially thank RamMudambi for the helpful and accurate comments to earlier versions of this paper.Thanks also to the three anonymous referees of the Journal of International Managementwho provided us with interesting insightsand comments, and to the reviewers and participants of the 10th Annual International Business Research Forum (Fox School ofBusiness, CIBER, Temple University), as well as to José Antonio Alonso, José Molero and Antonelo Zanfei for their helpfulsuggestions. Last but not least, the authors acknowledge Susan Lees's help with language editing. The usual disclaimer applies.

Appendix A

Table 1ACountries included in the analysis grouped by their level of GDP per capita.

High Upper-middle Lower-middle

Australia Argentina ArmeniaAustria Chile AzerbaijanBelgium Costa Rica BelarusCanada Croatia BoliviaCyprus Czech Republic BrazilDenmark Estonia BulgariaFinland Hungary ChinaFrance Latvia ColombiaGermany Lithuania EcuadorGreece Malaysia EgyptHong Kong Mauritius El SalvadorIceland Mexico GeorgiaIreland Panama HondurasIsrael Poland IndiaItaly Russia KazakhstanJapan Slovak Republic MacedoniaKorea, South Trinidad and Tobago MoroccoKuwait Turkey ParaguayLuxembourg Uruguay PeruMalta Venezuela RomaniaNew Zealand ThailandNorway TunisiaPortugal UkraineSingaporeSloveniaSpainSwedenSwitzerlandUnited KingdomUnited States

Table 2ARank correlations: FDI, M&A and national factors (1998–2004).

Total sample High Upper-Middle a Lower-middle a BRIC

Trade FDI M&A Trade FDI M&A Trade FDI M&A Trade FDI M&A Trade FDI M&A

Trade 1.000 0.867 ⁎⁎ 0.802 ⁎⁎ 1.000 0.793 ⁎⁎ 0.778 ⁎⁎ 1.000 0.833 ⁎⁎ 0.665 ⁎⁎ 1.000 0.664 ⁎⁎ 0.436 ⁎⁎ 1.000 0.588 ⁎⁎ 0.184FDI 0.867 ⁎⁎ 1.000 0.846 ⁎⁎ 0.793 ⁎⁎ 1.000 0.779 ⁎⁎ 0.833 ⁎⁎ 1.000 0.795 ⁎⁎ 0.664 ⁎⁎ 1.000 0.569 ⁎⁎ 0.588 ⁎⁎ 1.000 0.615 ⁎⁎

M&A 0.802 ⁎⁎ 0.846 ⁎⁎ 1.000 0.778 ⁎⁎ 0.779 ⁎⁎ 1.000 0.665 ⁎⁎ 0.795 ⁎⁎ 1.000 0.436 ⁎⁎ 0.569 ⁎⁎ 1.000 0.184 0.615 ⁎⁎ 1.000FDIStock 0.908 ⁎⁎ 0.907 ⁎⁎ 0.811 ⁎⁎ 0.856 ⁎⁎ 0.876 ⁎⁎ 0.727 ⁎⁎ 0.857 ⁎⁎ 0.868 ⁎⁎ 0.689 ⁎⁎ 0.793 ⁎⁎ 0.794 ⁎⁎ 0.478 ⁎⁎ 0.637 ⁎⁎ 0.900 ⁎⁎ 0.605 ⁎⁎

GDP 0.917 ⁎⁎ 0.790 ⁎⁎ 0.708 ⁎⁎ 0.929 ⁎⁎ 0.689 ⁎⁎ 0.773 ⁎⁎ 0.938 ⁎⁎ 0.804 ⁎⁎ 0.684 ⁎⁎ 0.975 ⁎⁎ 0.701 ⁎⁎ 0.451 ⁎⁎ 0.768 ⁎⁎ 0.599 ⁎⁎ 0.045ΔGDP −0.158 ⁎⁎ −0.100 ⁎ −0.202 ⁎⁎ −0.238 ⁎⁎ −0.032 −0.041 −0.139 −0.155 −0.233 ⁎⁎ 0.033 0.100 −0.096 0.688 ⁎⁎ 0.292 −0.195OP −0.219 ⁎⁎ −0.269 ⁎⁎ −0.281 ⁎⁎ −0.391 ⁎⁎ −0.261 ⁎⁎ −0.454 ⁎⁎ −0.103 −0.210 ⁎ −0.190 ⁎ 0.042 −0.097 −0.131 0.204 −0.027 −0.273W 0.318 ⁎⁎ 0.251 ⁎⁎ 0.217 ⁎⁎ 0.273 ⁎⁎ 0.201 ⁎ 0.268 ⁎⁎ 0.570 ⁎⁎ 0.586 ⁎⁎ 0.342 ⁎⁎ 0.345 ⁎⁎ 0.077 0.009 0.636 ⁎ 0.345 0.336HK 0.427 ⁎⁎ 0.411 ⁎⁎ 0.501 ⁎⁎ −0.028 0.234 ⁎⁎ 0.242 ⁎⁎ −0.055 0.009 0.098 0.189 ⁎ 0.185 ⁎ 0.028 −0.359 0.220 0.641 ⁎⁎

RD 0.669 ⁎⁎ 0.587 ⁎⁎ 0.624 ⁎⁎ 0.235 ⁎⁎ 0.257 ⁎⁎ 0.328 ⁎⁎ 0.490 ⁎⁎ 0.384 ⁎⁎ 0.268 ⁎⁎ 0.204 ⁎ 0.047 −0.135 0.070 0.096 0.301GMI 0.488 ⁎⁎ 0.444 ⁎⁎ 0.519 ⁎⁎ −0.135 0.196 ⁎⁎ 0.131 −0.243 ⁎⁎ −0.169 −0.106 0.327 ⁎⁎ 0.285 ⁎⁎ 0.340 ⁎⁎ −0.234 0.162 0.439 ⁎

a The BRIC economies have been excluded from their respective group.⁎⁎ Correlation is significant at the 0.01 level.⁎ Correlation is significant at the 0.05 level.

351I.Á

lvarez,R.Marín

/Journal

ofInternational

Managem

ent16

(2010)340

–353


References

Agarwal, S., Ramaswami, S., 1992. Choice of foreign market entry mode: impact of ownership, location and internationalization factors. Journal of InternationalBusiness Studies 23 (1), 1–27.

Álvarez, I., Magaña, G., 2007. Technological development in middle-income countries, in: Alonso, J.A. (Ed.), Cooperation with middle-income countries. Ed.Complutense, Madrid, pp. 339–369.

Álvarez, I., Marín, R., Fonfría, A., 2009. The role of networking in the competitiveness of firms. Technological Forecasting & Social Change 76, 410–421.Arellano, M., Bond, S.R., 1991. Some tests of specification for panel data. Journal of Econometrics 59, 87–97.Arellano, M., Bover, O., 1995. Another look at the instrumental variables estimation of error components models. Journal of Econometrics 68, 29–51.Barkema, H.G., Vermeulen, F., 1998. International expansion through start-up or acquisition: a learning perspective. Academy of Management Journal 4 (1), 7–26.Bartlett, C.A., Ghoshal, S., 1998. Managing Across Borders: The Transnational Solution. Harvard Business School Press, Boston.Belderbos, R., 2003. Entry mode, organizational learning, and R&D in foreign affiliates: evidence from Japanese firms. Strategic Management Journal 24, 235–259.Belderbos, R.E., Capannelli, G., Fukao, K., 2001. Backward vertical linkages of foreign manufacturing affiliates: evidence from Japanese multinationals. World

Development 29 (1), 189–208.Bertrand, O., Hakkala, K., Norbäck, P.J., 2007. Cross-Border Acquisition or Greenfield Entry: Does it Matter for Affiliate R&D? Research Institute of Industrial

Economics, Working Paper Series, 693, Stockholm.Blundell, R.W., Bond, S.R., 1998. Initial conditions and moment restrictions in dynamic panel models. Journal of Econometrics 87, 115–143.Brouthers, K.D., Brouthers, L.E., 2000. Acquisition or greenfield start-up? Institutional, cultural and transaction cost influences. Strategic Management Journal 21,

89–97.Brouthers, K.D., Brouthers, L.E., 2003. Why service and manufacturing entry mode choices differ: the influence of transaction cost factors, risk, and trust. Journal of

Management Studies 40, 1179–1204.Brouthers, L.E., O'Donnell, E., Hadjimarcou, J., 2005. Generic product strategies for emerging market exports into triad nation markets: a mimetic isomorphism

approach. Journal of Management Studies 42, 207–225.Cantwell, J., 1989. Technological Innovation and Multinational Corporations. Basil Blackwell, Oxford.Cantwell, J., 1995. The globalization of technology: what remains of the product cycle model? Cambridge Journal of Economics 19 (1), 155–174.Cantwell, J., Molero, J., 2003. Multinational Enterprises, Innovative Strategies and Systems Of Innovation. Edward Elgar, Cheltenham.Cantwell, J., Mudambi, R., 2005. MNE competence-creating subsidiary mandates. Strategic Management Journal 26 (12), 1109–1128.Cantwell, J., Piscitello, L., 2002. The location of technological activities of MNCs in European regions: the role of spillovers and local competencies. Journal of

International Management 8 (1), 69–96.Capron, L., 1999. The long-term performance of horizontal acquisitions. Strategic Management Journal 20, 987–1018.Chang, S.J., Rosenweig, P.M., 2001. The choice of entry mode in sequential foreign direct investment. Strategic Management Journal 22 (8), 747–776.Chung, W., Alcácer, J., 2002. Knowledge seeking and location choice of foreign direct investment in the United States. Management Science 48 (12), 1534–1554.Cohen, W.M., Levinthal, D.A., 1990. Absorptive capacity: a new perspective on learning and innovation. Administrative Science Quarterly 35, 128–152.Cuervo-Cazurra, A., 2007. Sequence of value-added activities in the multinationalization of developing country firms. Journal of International Management

13 (2007), 258–277.Davidson, W.H., 1980. The location of foreign direct investment activity: country characteristics and experience effects. Journal of International Business

Studies 11 (2), 9–22.Davis, P.S., Desai, A.B., Francis, J.D., 2000. Mode of international entry: an isomorphism perspective. Journal of International Business Studies 31 (2), 239–258.Dunning, J.H., 2006. Towards a paradigm of development: implications for the determinants of international business activity. Transnational Corporations 15 (1),

173–227.Dunning, J.H., Narula, R. (Eds.), 1996. Foreign direct investment and governments: Catalysts for economic restructuring. Routledge, London.Freeman, C., 1987. Technology Policy and Economic Performance: Lessons from Japan. Pinter, London.Frost, T., 2001. The geographic sources of foreign subsidiaries' innovations. Strategic Management Journal 22, 101–123.Globerman, S., Shapiro, D., 2002. Global foreign direct investment flows: the role of governance infrastructure. World Development 30 (11), 1899–1919.Harzing, A.W., 1999. Acquisitions versus greenfield investments: international strategy and management of entry modes. Strategic Management Journal 23,

211–227.Hitt, M.A., Franklin, V., Zhu, H., 2006. Culture, institutions and international strategy. Journal of International Management 12, 222–234.Hobday, M., 1995. Innovation in East Asia. Edward Elgar, Aldershot.Kaufmann, D., Kraay, A., Mastruzzi, M., 2007. Governance matters VI: Governance indicators for 1996–2006. World Bank Policy ResearchWorking Paper No. 4280,

World Bank, Washington (http://ssrn.com/abstract=999979).Kline, J., Rosenberg, N., 1986. An overview of innovation. In: Landau, R., Rosenberg, N. (Eds.), The positive sum strategies: Harnessing technology for economic

growth. National Academic Press, Washington DC.Kogut, B., Singh, H., 1988. The effect of national culture on the choice of entry mode. Journal of International Business Studies 19 (3), 411–432.Kuemmerle, W., 1999. Foreign direct investment in industrial research in the pharmaceutical and electronics industries: results from a survey of multinational

firms. Research Policy 28 (2/3), 179–193.Lall, S., 2002. Implications of cross-border mergers and acquisitions by TNCs in developing countries: A beginners' guide. QEH Working Paper No. 88.Lundvall, B.A. (Ed.), 1992. National systems of innovation. Pinter Publishers, London.Lundvall, B.A., 2007. National innovation systems — analytical concept and development tool. Industry and Innovation 14 (1), 95–119.Lundvall, B.A., Johnson, B., Andersen, E.S., Dalum, B., 2002. National systems of production, innovation and competence building. Research Policy 31, 213–231.McCann, P., Mudambi, R., 2005. Analytical differences in the economics of geography: the case of the multinational firm. Environment and Planning A 37,

1857–1876.Meyer, K.E., 2004. Perspectives on multinational enterprises in emerging economies. Journal of International Business Studies 35 (4), 259–276.Mowery, D.C., Oxley, E., 1995. Inward technology transfer and competitiveness: the role of national innovation systems. Cambridge Journal of Economics 19 (1),

67–93.Mudambi, R., 1995. The MNE investment location decision: some empirical evidence. Managerial and Decision Economics 16, 249–257.Mudambi, R., 2002. Knowledge management in multinational firms. Journal of International Management 8, 1–9.Mudambi, R., 2008. Location, control and innovation in knowledge-intensive industries. Journal of Economic Geography 8, 699–725.Mudambi, R., Mudambi, S.M., 2002. Diversification and market entry choices in the context of foreign direct investment. International Business Review 11, 35–55.Narula, R., 1996. Multinational Investments and Economic Structure. Routledge, London.Narula, R., Dunning, J.H., 2000. Industrial development, globalisation and multinational enterprises: new realities for developing countries. Oxford Development

Studies 28 (2), 141–167.Narula, R., Criscuolo, P., Verspagen, B., 2002. The relative importance of home and host innovation systems in the internationalisation ofMNE R&D: a patent citation

analysis. Merit Memorandum MERIT RM 2002-26.Nelson, R., 1993. National Innovation Systems: A Comparative Analysis. Oxford University Press, Oxford.Ozawa, T., 1992. Foreign direct investment and economic development. Transnational Corporation 1 (1), 27–54.Pearce, R., 1999. Decentralised R&D and strategic competitiveness: globalised approaches to generation and use of technology in multinational enterprises

(MNEs). Research Policy 28, 157–178.Pearce, R., 2006. Globalization and development: an international business strategy approach. Transnational Corporations 15 (1), 39–74.Piscitello, L., 2004. Corporate diversification, coherence and economic performance. Industrial and Corporate Change 13 (5), 757–787.

http://ssrn.com/abstract=999979


Porter, M.E., 1986. Changing patterns of international competition. California Management Review 28 (2), 9–40.Porter, M., Schwab, K., 2008. The global competitiveness report 2008–2009. World Economic Forum (www.weforum.org).Rosenzweig, P.M., Singh, J.V., 1991. Organizational environments and the multinational enterprise. Academy of Management Review 16 (2), 340–361.Rugman, A.M., Doh, J.P., 2008. Multinationals and Development. Yale University Press, New Haven. (London).Rugman, A.M., Verbeke, A., 2001. Location, Competitiveness and the Multinational Enterprise. In: Rugman, A.M., Brewer, T.L. (Eds.), The Oxford Handbook of

International Business. Oxford, Oxford University Press.Sanna-Randaccio, F., Veugelers, R., 2007. Multinational knowledge spillovers with decentralised R&D: a game-theoretic approach. Journal of International Business

Studies 38 (1), 47–63.Scott, W.R., 1981. Organizations: Rational, Natural, and Open Systems. Prentice-Hall, Englewood Cliffs, NJ.Scott, W.R., 1983. The Organization of Environments: Network, Cultural, and Historical Elements. In: Meyer, J.W., Scott, W.R. (Eds.), Organizational environments.

Sage, London, pp. 155–175.Shimizu, K., Hitt, M.A., Vaidyanath, D., Pisano, V., 2004. Theoretical foundations of cross-border mergers and acquisitions: a review of current research and

recommendations for the future. Journal of International Management 10, 307–355.Singh, J., 2007. Asymmetry of knowledge spillovers between MNCs and host country firms. Journal of International Business Studies 38, 764–786.Slangen, A., Hennart, J.F., 2007. Greenfield or acquisition entry: a review of the empirical foreign establishment mode literature. Journal of International

Management 13, 403–429.Tihanyi, L., Roath, A.S., 2002. Technology transfer and institutional development in Central and Eastern Europe. Journal of World Business 37, 188–198.UNCTAD, 2005. World Investment Report: Transnational corporations and the internationalization of R&D. United Nations, New York (Geneva).UNCTAD, 2007. World Investment Report: Transnational Corporations, Extractive Industries and Development. United Nations, New York. (Geneva).Von Hippel, E., 1988. The Sources of Innovation. Oxford University Press, Oxford.Xu, B., 2000. Multinational enterprises, technology diffusion, and host country productivity growth. Journal of Development Economics 62, 477–493.Yang, Q., Mudambi, R., Meyer, K.E., 2008. Conventional and reverse knowledge flows in multinational corporations. Journal of Management 34 (5), 882–902.

http://www.weforum.org

entry modes and national systems of innovation

Documents