Academy of International Business Best Paper Proceedings 2008

# AIB2008-0133

What Do We Really Know about Foreign Market Entry Strategy Decisions? A Meta-analysis on the Choice Between Wholly-owned

Subsidiaries and Cooperative Arrangements

Dirk Morschett University of Fribourg

dirk.morschett@unifr.ch

Hanna Schramm-Klein Saarland University

h.schramm@mx.uni-saarland.de

Bernhard Swoboda University of Trier

b.swoboda@uni-trier.de

Paper presented on July 2, 2008

at the AIB Annual Conference, Milan, Italy http://aib.msu.edu/events/2008/

© 2008 Dirk Morschett, Hanna Schramm-Klein, and Bernhard Swoboda. Paper may be downloaded for personal use only and cannot be distributed without the explicit permission of the authors.

What Do We Really Know about Foreign Market Entry Strategy Decisions? A Meta-analysis on the Choice Between Wholly-owned Subsidiaries and Cooperative Arrangements

Dirk Morschett, Hanna Schramm-Klein, and Bernhard Swoboda

Abstract: The choice of a market entry strategy, a crucial decision in the internationalization process, has been addressed by numerous empirical studies. The results are multifaceted, sometimes conflicting, and thus, difficult to interpret and review. The presented meta-analysis summarizes empirical findings from previous research on the decision between wholly-owned subsidiaries and cooperative arrangements. By reviewing 61 studies on this decision, it is examined which influence factors on the decision have been investigated in primary research and which have a significant effect in the cumulative view of the previous results. The article also links the theories that are used in the literature to explain the market entry strategy decision to the findings. Key words: Market Entry Strategy, Cooperation, Transaction Cost Theory, Internationalisation Theories, Meta-Analysis Dirk Morschett Chair for International Management – Liebherr/Richemont Endowed Chair University of Fribourg, Switzerland Boulevard de Pérolles 90 CH-1700 Fribourg dirk.morschett@unifr.ch Hanna Schramm-Klein Department of Management Saarland University, Germany Universität des Saarlandes, Gebaeude A5.4 D-66123 Saarbrücken h.schramm@mx.uni-saarland.de Bernhard Swoboda Department of Marketing and Retailing Trier University, Germany Universitaetsring 15 D-54286 Trier b.swoboda@uni-trier.de

INTRODUCTION

The choice of a market entry strategy (MES) is considered one of the most important internationalization

strategy decisions, since the MES determines the type and intensity of control over the foreign market activity,

the necessary resource transfers as well as the associated risks (Anderson & Gatignon, 1986; Hill, Hwang &

Kim, 1990). Correspondingly, numerous empirical studies have addressed this topic (see the overviews of Sarkar

& Cavusgil, 1996; Kumar & Subramaniam 1997). However, the results of these studies are multifaceted,

sometimes conflicting, and thus, difficult to interpret and review. With this article, we would like to contribute to

the research on determinants of the MES choice by examining previous primary research results in a meta-

analysis (cf., e.g., Glass, 1976).

To explain international market entry mode choice, a number of different theories are used in literature. Most

studies are based on transaction cost economics (TCE) and the related internalization theory (Buckley &

Casson, 1976; Williamson, 1985). Another theory is proposed in the resource-based view (RBV) (cf., e. g.,

Wernerfelt, 1984). Related to that approach, but focused on the resource “capabilities” is the organizational

capability approach (OC) (Kogut & Zander, 1993; Madhok, 1998). The stages models (e.g. Johanson & Vahlne,

1977) are based on the (country-specific) market knowledge of the MNC (Madhok, 1998; Deng, 2003) and

relate that knowledge to the resource commitment of a MNC. Finally, the company strategy approach focuses

on those characteristics of the MES that are necessary to implement the MNC strategy and to fulfill a specific

role of the foreign organizational unit for the MNC (Kogut & Singh, 1988; Kim & Hwang, 1992). Other

approaches include the bargaining power theory (e.g. Lecraw, 1984) and the neo-institutional perspective

(DiMaggio & Powell, 1983).

All of these approaches cannot be discussed in detail in this paper but are extensively treated in the referenced

articles (see for a more extensive review Sarkar & Cavusgil, 1996; Kumar & Subramaniam, 1997). With this

study, we intend to demonstrate which theories are supported by the aggregated findings and we want to point

out where research deficits exist.

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SAMPLE AND METHOD

The first step in a meta-analysis is to collect all relevant studies for a specific research question (Cooper &

Hedges, 1994b). Thereby, it is necessary to have the broadest possible database in order to avoid biased results.

For the present study, at first, the most important journals in which international market entry strategies are

discussed were systematically searched issue by issue for up to the last 30 years (or the first journal issue,

whichever was later). The journals analyzed were Journal of International Business Studies, International

Business Review (from 1992), Management International Review,

Strategic Management Journal (from 1980), Journal of Management, International Marketing Review (from

1983), Journal of International Marketing (from 1993), Organization Science (from 1990), The Service

Industries Journal (from 1981), Journal of International Management (from 1995), Journal of the Academy of

Marketing Science, Academy of Management Journal and Academy of Management Review.

In a second stage, the database ”Business Source Premier“ was searched for studies. To account for the different

terms used in the literature, a broad array of keywords was used (e.g. entry strategy, entry mode, entry form,

market entry, joint venture, cooperation, subsidiaries, institutionalization, etc.).

In a third stage, the reference lists of all studies identified in the first two stages were looked through to find

additional studies.

Next, in order to define a more precise research question, we identified the most frequently analyzed decision in

the identified studies, the ownership decision, and concentrated on this decision in the further analysis. More

specifically, only studies that addressed the decision between a wholly-owned subsidiary (WOS) and a

cooperative arrangement (located in the host market) were included.

By the mentioned procedure, 57 articles with a sum of 61 independent studies were identified for this specific

research question (see appendix and reference list). Comparing this number to other extended literature reviews

(Sarkar & Cavusgil, 1996; Kumar & Subramaniam, 1997), our study seems to provide a quite comprehensive

review of studies. In these 61 studies, 168 different influence factors on the decision “WOS vs. cooperation”

were examined; 26 of those in at least five different studies. Only those 26 variables were then considered in the

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meta-analysis. In Table 1, it is indicated for each variable which direction of influence is argued in the literature

and on which theory the argument is usually based upon.

-----------------------------------------------------------------------------------------------------------------------display Table 1 about here

TABLE 1 OVERVIEW ON VARIABLES INCLUDED IN THE META-ANALYSIS

AND PREDICTED DIRECTION OF EFFECT OF EACH VARIABLE FROM THEORY -----------------------------------------------------------------------------------------------------------------------

Since the considered decision is binary (e.g. cooperation = 0 vs. WOS = 1), the primary studies mainly apply

multivariate binary logistic regression. The effect size is most often in the form of a regression coefficient B

which represents a log odds ratio (e.g. Gatignon & Anderson, 1988; Kogut & Singh, 1988; Erramilli & Rao,

1993). Using beta coefficients from multivariate regressions as effect sizes in a quantitative synthesis is

sometimes considered critical (Lipsey & Wilson, 2001), since beta coefficients are partial coefficients.

Nevertheless, we used those coefficients for a number of reasons. Firstly, by far the largest number of studies for

our research question are based on multivariate methods, and the impact of missing effect sizes on the validity of

meta-analytic conclusions is usually considered problematic. Omitting relevant effect sizes increases the

sampling error, and potentially reduces the representativeness of the included studies, and thus, the

generalizability of the estimates (Pigott, 1994). In narrative literature reviews, coefficients from multivariate

methods are extensively used to support hypotheses. Secondly, and most importantly, Petersen & Brown (2005)

demonstrate in an extensive study with 1,504 beta coefficients and corresponding bivariate correlation

coefficients that the beta coefficients from multivariate regression analyses reveal a strong and robust linear

relationship with the corresponding correlation coefficients. This finding strongly supports the option to use the

present data in the context of a meta-analysis. Thirdly, in our study, we applied statistical tests of homogeneity

for the study results of each variable. The Q-statistic indicated homogeneity for most variables. And finally, we

applied an additional test to examine the adequateness of the coefficients of the meta-analysis: To test whether a

systematic relationship between the number of regressors in the primary study and the effect size (i.e. the beta

coefficient in the primary study) exists, a regression analysis between those two variables was carried out. A

significant relation appeared only for two of the 26 variables (IEXgeneral and CONC). For the other 24

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variables, a significant relationship does not seem to be existent, and thus, using multivariate regression

coefficients does not seem to pose a major problem in our study.

To integrate the previous findings from the primary studies, two methods were applied.

A first method is based on Kulik, Kulik & Cohen (1980) and Kulik, Cohen & Ebeling (1980). Kulik, Kulik &

Cohen (1980) demonstrate the validity of a specific 4-point scale and use it when missing values in the primary

studies pose a problem. Adapting and refining their 4-point scale, we applied a 6-point scale (from -2.5 (negative

coefficient, p<0.01) to +2.5 (positive coefficient, p<0.01)) and transferred all coefficients from previous studies

to that equidistant scale (see Table 2 in the appendix). This is an advanced type of a vote counting procedure

(from now on referred to as “VC scale”). We applied this procedure by testing the significance of the mean of

this VC scale across the different previous studies.

In a second procedure, we combined the effect sizes from the previous studies into a common estimate of the

effect size (Shadish & Haddock, 1994; Lipsey & Wilson, 2001). To combine effect sizes, either fixed-effects

models or random-effects models can be used (Cooper & Hedges, 1994a). For each variable, we calculated the

Q-statistics as a test on homogeneity (Lipsey &Wilson, 2001). A non-significant Q-test (i.e. homogeneity)

indicates that a fixed-effects model can be applied, while in the case of a significant Q-test (i.e. heterogeneity)

literature recommends the use of a random-effects model as a possible consequence (Shadish & Haddock, 1994;

Cooper & Hedges, 1994a). In Table 2, it is indicated for each variable, whether homogeneity or heterogeneity

was considered as a result from the Q-test.

RESULTS

Table 2 displays the study results for each variable and the synthesis of the study results. Due to space

restrictions, not each variable can be discussed individually in this paper. As an example, the analysis for the

variable “Country-Specific International Experience” of the MNC (IEXcountry) is explained in more detail.

-----------------------------------------------------------------------------------------------------------------------display Table 2 about here

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TABLE 2 STUDY RESULTS FROM PRIMARY STUDIES AND SYNTHESIS OF STUDY RESULTS

-----------------------------------------------------------------------------------------------------------------------

IEXcountry is frequently analyzed in empirical studies since the stages models are using this variable as one core

of their explanations (see Table 2 for the results and the synthesis). All in all, 21 studies consider IEXcountry

and the results are quite consistent. Only two studies show a negative relationship with the tendency to establish

a wholly-owned subsidiary, thereby, only one of them with a significant coefficient. On the other side, 19 studies

receive a positive relationship (however, many of them non-significant). Accordingly, the mean of the VC scale

indicates a positive significant relationship.

Only the nine studies displayed in Figure 1 can be used for the combined effect size, because only those nine

primary studies contained sufficient information in the publication. Positive signs indicate that a higher value of

the variable leads to a higher likelihood of a wholly-owned subsidiary. Only when the confidence interval does

not cover zero, a significant effect (on the 5%-level) is given (in the primary studies as well as in the

aggregation). The calculated Q-statistic shows that the results of the nine studies can be considered as

homogeneous. The combined effect size based on the fixed-effects model confirms a positive significant

relationship. Since the results are homogeneous (among other reasons), the confidence interval around the mean

effect size is rather narrow, thus, the precision of the result is high. Thus, it can be concluded that the country-

specific experience of a MNC really exerts a positive influence on the propensity of a MNC to establish a

wholly-owned subsidiary in the specific country.

-----------------------------------------------------------------------------------------------------------------------display Figure 1 about here

FIGURE 1 STANDARDIZED EFFECT SIZES AND CONFIDENCE INTERVALS OF THE STUDIES

ON THE VARIABLE IEXcountry -----------------------------------------------------------------------------------------------------------------------

Figure 1 also demonstrates, how a majority of non-significant results in primary studies (six out of the nine

primary studies display non-significant results) – which would often not be accounted in traditional literature

reviews – might be confirming a non-ambiguous and significant relationship in their aggregation (mainly due to

the increased sample size). Hence, this example lends strong support for the use of meta-analytic methods.

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Figure 2 summarizes the results of the meta-analysis graphically for the combined effect sizes (i.e. the combined

log odds ratios).

-----------------------------------------------------------------------------------------------------------------------display Figure 2 about here

FIGURE 2 COMBINED STANDARDIZED EFFECT SIZES AND CONFIDENCE INTERVALS

FOR THE ANALYZED VARIABLES -----------------------------------------------------------------------------------------------------------------------

Summarizing, the combined estimate of the extant studies indicates a positive and significant influence on the

propensity of a WOS (vs. a cooperative arrangement) for the following determinants (order following the

combined standardized effect size):

• MNC Size (no. of employees) (SIZempl)1

• Power Distance Index of Home Country (PDI)

• Country-specific International Experience of MNC (IEXcountry)

• Advertising Intensity (ADV)

• Export Intensity of MNC (EXPORT).

A significant negative influence on the likelihood to establish a WOS can be found for (order following the

absolute combined standardized effect size):

• Host Country Risk (RISK)

• Legal Restrictions (RESTRICT)

• Market Size (MSIZE)

• Resource Intensity (RESOURCE)

• Market Growth (MGROWTH)1

• International Product Diversification (DIVERSUB).

DISCUSSION OF RESULTS AND EXPLANATORY THEORIES

A problem with the evaluation of different theories based on the presented results stems from the fact that the

same construct is sometimes used in different theories and even the predicted effect is in the same direction, and

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only the explanation paths differ (Gomes-Casseres, 1990), as the overview in Table 1 shows. For example, in

transaction cost based reasoning, R&D intensity is leading to a higher degree of internalization, since the

internal transfer of specific knowledge is considered more efficient, while the bargaining power approach would

predict the same relationship, because the MNC gains ownership advantages via R&D, which enhances its

bargaining power towards a host government (Gomes-Casseres, 1990). While this makes the effort to evaluate

the explanatory power of different theories difficult, nevertheless, we try to interpret the combined empirical

results from the perspective of different theories. We base this reasoning also on the theories listed with the

variables in Table 1.

For some theories, no or only few empirical results exist. This holds true, for example, for the company strategy

approach. Only the variables RESOURCE, DIVERMNC, DIVERSUB and the size of the subsidiary

(SUBSIZabs, SUBSIZrel) can be used to consider the fact that foreign units might play heterogeneous roles in a

MNC (Birkinshaw & Morrison, 1995) or have different relevance for the MNC strategy.

The size of the subsidiary (absolute or relative to the MNC) displayed no clear influence on the MES.

RESOURCE is a variable that indicates that the role of the subsidiary is not necessarily to sell products on the

foreign market (something that is incorrectly implicitly assumed in many MES studies), but the clear results for

this variable indicate that the resource intensity of the foreign activities has a significant influence on the MES,

since the access to foreign resources is often realized via cooperative strategies (Hennart, 1991; Hennart &

Larimo, 1998). Also, the diversification of the MNC and the international product diversification of the foreign

unit put considerations of the company strategy to the fore. While DIVERMNC does not display a relationship

with the MES, DIVERSUB (which is on the level of the specific foreign subsidiary and therefore could well be

expected to exert a stronger influence) has a significant negative influence. Thus, the less the product offer of the

foreign unit is related to that of the parent company, the less likely the foreign unit is to be established as a WOS.

Summarizing, this shows that the company strategy approach has not been examined in detail yet, but that the

first results are promising.

The bargaining power theory has almost been neglected in empirical research. While numerous variables have

been investigated that could shift the power towards the host country government (e.g. market size, income level

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in the host country) or towards the MNC (e.g. R&D intensity, advertising intensity), a true test of the bargaining

power influence would require to analyze differences in the effect of these variables under changing government

influences (restrictive governments vs. liberal governments) and to separate these influences from other country-

specific influences. Gomes-Casseres (1990) shows that this has not been adequately handled in the few studies

on the bargaining power approach (e.g. Lecraw, 1984; Kobrin 1987).

The same neglect can be stated for the neo-institutional perspective. The only variable that can be associated to

this approach is RESTRICT (i.e. legal restrictions in the host country). Yiu & Makino (2002) related this

variable to the neo-institutional approach. But while this variable really can be embedded in this approach as

“coercive isomosphism” (DiMaggio & Powell, 1983), one can hardly argue that the fact that the legal

restrictions in a host country are respected by a MNC, is a confirmation of the more profound ideas of the neo-

institutional approach.

One of the most frequently employed approaches to explain market entry strategies are the stages models.

Variables that are explicitly or implicitly referred to the international experience of the MNC have been

frequently analyzed. In a narrow sense, only the variables IEXcountry, AGESUB and EXPORT are, however, to

be integrated into the stages model as proposed by Johanson & Vahlne (1977). The country-specific experience

of the MNC (IEXcountry) indeed does exert a positive influence on the decision for a WOS, as has been shown

in detail. Experience gained via intensive exporting (EXPORT) exposes the same influence, as the combined

effect size indicates. Both constructs support the central assumption of the stages models.

It is surprising though, that AGESUB (i.e. the age of the subsidiary in the specific country) does not exert any

influence. However, the “age of the subsidiary” already requires a subsidiary to exist at all, i.e. it refers to a later

stage in the establishment chain, while the cumulative experience of the MNC already reaches back to the first

export activities, i.e. it covers all stages. So if age of the subsidiary really does not have an effect, this might

indicate leaps between the stages or it might result from a situation in which cooperative strategies are

potentially final stages as well (Cleeve, 1997). This finding supports the more recent statement that the stages

models are particularly relevant in the early stages of internationalization (Johanson & Vahlne, 1990).

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Also including the experience of a MNC, but in a more general sense, is the organizational capabilities

approach. More experience (country-specific but also multinationally) would lead to better internationalization

capabilities, and thus, to market entry strategies with higher commitment (Johanson & Vahlne, 1990; Madhok,

1998). However, neither the general International Experience (IEXgeneral) nor the Multinational Experience

(IEXmult) display a significant influence in the meta-analysis. For the OC approach,this implies that the

influence of capabilities and of experience has to be considered more detailed, and different facets of the

capabilities have to be analyzed. For example, Madhok (1998) refers to the experience of MNCs with specific

market entry modes and he shows that, e.g., MNCs with more experience with joint ventures can apply joint

ventures more effectively. Thus, different capabilities do not just increase the internationalization capabilities in

general, but they also refer to specific knowledge, resulting in specific strategies in subsequent decisions. This

finding could lead to a more differentiated application of the OC approach for internationalization studies.

The non-significant result for the cultural distance (CULT) can be related to the OC approach, but here, the OC

approach does not predict a non-ambiguous relation. While one can argue that a large cultural distance promotes

to cooperative strategies, because in this case the complementary capabilities of a local partner gain in

importance (Madhok, 1998; Pla-Barber 2001), one could also bring forward that the absorptive capacity of a

local partner is reduced with growing cultural distance, i.e. making internalization the more viable option (Kogut

& Singh, 1988). The non-significant result for CULT in the meta-analysis, thus, can be seen to reflect the

contradictory forces even within the OC approach.

Some results can be considered clearly supportive of the OC approach. The negative influence of market growth

(MGROWTH) on the propensity to establish a WOS can be explained with the higher speed of external learning

via cooperation compared to internal learning and with the high opportunity cost of internal learning in the case

of fast growing markets (Hennart & Reddy, 1997; Chang & Rosenzweig, 2001). And finally, the significant and

negative effect of DIVERSUB on the choice of a WOS supports the thesis that MNCs use the complementary

competences of partners when the activity of the foreign unit is not closely related to the activity of the parent

company.

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All in all, an influence of organizational capabilities seems to be supported. However, core assumptions of the

OC approach that refer to different characteristics of the capabilities to be transferred (Kim & Hwang, 1992;

Kogut & Zander, 1993) were not yet tested in an international context, so that a research deficit can still be

identified.

Like the OC approach, the resource-based view also focuses on company resources, but in a more general sense.

The necessary access to resources in the host country (RESOURCE) leads to an increased use of cooperative

arrangements, supporting the RBV. Considering the MNC size, a variable that is generally considered an

indicator for resource availability within the MNC, the combined results clearly demonstrate that this influence

has to be addressed in more detail. Different studies use different size indicators (sales, employees, assets),

seemingly at random, or at least often without a clear explanation. Singh & Kogut (1989) argue correctly that the

assets of the MNC are most closely related to the theoretical explanation of the influence of company size. In the

meta-analysis, neither SIZassets nor SIZsales display a significant influence on the MES decision. It is

interesting to note that the MNC size, measured by number of employees (SIZempl), does show a significant

positive influence on the likelihood to establish a WOS. This indicates that the RBV might be adequate to

explain the MES decision, however it is not financial assets, but the human resources that are the critical

dimension of resources. This would also match the RBV, since human resources are not easily imitated and not

perfectly mobile between companies (Das & Teng, 1998), thus, HR are displaying core characteristics of true

company resources.

The positive effect of advertising intensity on the propensity to establish a wholly-owned subsidiary – which is

most often argued based on TCE – can also be related to the RBV, because the investment in advertising

accumulates intangible company resources that can be better protected and exploited internally.

Based on transaction cost economics, one would expect a positive influence of asset specificity, transaction

frequency and uncertainty on the propensity to use WOS. The results on market size (MSIZE), which might be

seen as an indicator for transaction frequency, are significantly negative, thus, contracting TCE. The capital

intensity of the foreign activities (CAPINT), which results in higher internalization costs, does not influence the

MES significantly in the meta-analysis, thus, not lending support to TCE. Only a weak influence (on the 10%-

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significance level) can be observed for the level of industry concentration (CONC). Theoretically, CONC might

be related to a situation of “small-number bargaining”, in which case TCE would posit a higher propensity to

internalize, which is also not clearly supported.

However, in the focus of TCE is the influence of asset specificity on the degree of internalization. It is argued

that high specificity (of assets, know-how, etc.) leads to high transaction cost and in this case internalization is a

more efficient option than externalization (and cooperative arrangements are considered more externalized than

hierarchical solutions). A rather general, multi-item based variable, SPECIF, has sometimes been used in

previous studies to analyze this relationship. In addition, R&D intensity (RND) and advertising intensity (ADV)

are usually considered indicators for asset specificity (Gatignon & Anderson, 1988; Yiu & Makino, 2002). Both

have been often analyzed.2

ADV does show the expected positive sign for the combined effect size, but RND and SPECIF do not display a

significant influence on the MES. While the results for SPECIF might be accounted to the low number of studies

referring to this construct, RND has been analyzed very frequently. However, the results are strongly ambiguous,

as Table 2 shows. Kogut & Singh (1988) argue that R&D-intensive MNCs might value the acquisition of

additional, complementary knowledge via cooperation higher than choosing the most efficient transaction form

for existing knowledge, thus, challenging TCE reasoning. Hennart & Larimo (1998) conclude that the contrary

influences of transaction costs and capability-based arguments might lead to non-significant and conflicting

results.

These ambiguous results support the demand of a number of authors to combine TCE with other theories, in

particular the OC approach and the company strategy approach (e.g. Contractor, 1990; Hill et al., 1990; Sarkar &

Cavusgil, 1996; Madhok, 1998), since the results from the meta-analysis seem to question transaction cost

efficiency as the main selection criterion for foreign market entry strategies. An additional finding that promotes

a modification is the result that the attitude of the managers also seems to exert an influence on the MES

decision (thus, lending support to the behavioristic approaches) while a basic assumption of TCE is a rational-

analytic decision (Kumar & Subramaniam, 1997; Brouthers, 2002), even though under bounded rationality

(Williamson, 1985). The fact that the country culture of the home country of the MNC exerts an influence (as

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demonstrated in the variable power distance index of the home country (PDI)) shows that behavioristic

influences should be considered more strongly (Brouthers, 2002). Thus, Granovetter’s (1985) critic, that TCE is

“undersocialized” might be relevant (see also Roberts & Greenwood 1997).

Referring to TCE, we are not fully agreeing with Madhok’s conclusion: “...based on the results of this study at

least, I can state with some confidence that internalization logic seems inadequate in explaining firms’ foreign

market entry preferences” (1998: 280). However, the influence of some variables that are central to TCE has

been shown to be non-significant or even opposing the predicted direction which should at least lead to a

modification or extension by other theories and approaches for the specific research question that has been

analyzed in this paper (WOS vs. cooperative arrangements).

LIMITATIONS

The limitations of our study are first of all to be found in the methodology. In literature, two main problems

related to meta-analysis are the criticism of integrating non-comparable study results and the so called ”file

drawer problem“ (Wolf, 1986; Lipsey & Wilson, 2001; Hunter & Schmidt, 1990). Both aspects are – regarding

our study – shortly discussed.

Firstly, one of the most frequent arguments against meta-analysis is that it combines study results that are so

different that they are not really comparable, the so called “apples and oranges problem” (Hunter & Schmidt,

1990). Studies with very different operationalizations of the independent and the dependent variables would be

synthetisized. However, in the presented meta-analyis, the dependent variable (wholly-owned subsidiary vs.

cooperation) is the same or at least very similar in every study. Concerning the independent variables, the

operationalization really differs slightly in the primary studies. But this is true for only a few variables while

many variables (e.g. IEXcountry or CULT) are measured with the same operationalization in every study

(IEXcountry as number of years that a company is active in a specific country, and CULT with the Kogut-Singh-

Index). Also, all study results were tested for homogeneity which was present in most cases. This also supports

the assumption of comparability of the constructs across the studies.

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The second problem, the ”file drawer problem“ (also called “publication bias“) could result if the selection

mechanisms in the publication process would promote the publication of significant results while non-significant

results are less likely to be published. In that case, besides the published studies, an unknown number of studies

with lower effect sizes and non-significant results might exist (Wolf 1986; Hunter & Schmid, 1990), which

would bias the combined effect size from the meta-analysis.

To address this problem, we analyzed each of the eleven variables that yielded significant results in the synthesis

by looking at their funnel plots (Rosenthal, 1979; Light & Pillemer, 1984). We plotted the sample size of the

primary study on the x-axis and the effect size on the y-axis. If there is no publication bias, the studies should

form the shape of a funnel. For all eleven variables this seemed to be the case which indicates that publication

bias should not pose a serious problem for our results. However, it has to be noted that we almost only included

published studies in our analysis and we are not aware of further, unpublished studies, so that the basic problem

might still be existent.

Thirdly, even though we have argued in detail why we used the effect sizes from multivariate regression

analyses and have shown empirically that the number of regressors in the primary study does not have a

systematic influence on the effect size, the combination of coefficients from multivariate statistics is still not

unproblematic (Lipsey & Wilson, 2001).

Fourthly, it has to be mentioned that the combination of the effect sizes only examined linear relationships. U-

shaped relations (as, e.g., Erramilli (1991) predicts for the country-specific international experience) cannot be

analyzed with this method. And the same holds true for moderating effects. Many primary studies have shown

interaction effects to be relevant for the choice of a MES. But here, meta-analysis has clear limitations. We

analyzed 26 variables – independent from each other – concerning their explanatory power for the choice of a

wholly-owned subsidiary relative to a cooperative arrangement. The interdependence and interaction of these

variables was not analyzed, since no meta-analytic methods exist to combine interaction effects (and since the

number of studies concerning each interaction effect is very low). Still, this has to be seen as a major limitation

of the study.

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CONCLUSION AND FURTHER RESEARCH

The results from the quantitative integration of previous studies are partially surprising and partially even

contradicting statements in narrative literature reviews. This demonstrates the importance of integrating past

study results objectively, via a meta-analysis, if possible. “Science is cumulative“ (Franke, 2001: 186), and the

statistical criteria that are commonly demanded in primary research should more often also be applied to the

literature review of previous studies.

Only 26 variables (of the 168 variables that have been analyzed in total in existing studies on the examined

decision) have been investigated at least five times, showing a general research deficit concerning the whole set

of other variables. For the available effect sizes from previous studies, the results of this meta-analysis show that

only 11 of the 26 examined variables yield a significant influence in their combined effect size.

Firstly, that reveals that for the other 15 variables, existing results are ambiguous and currently, no clear direction

of a potential relationship is really empirically demonstrated.

Secondly, the other 11 variables can now be considered to have a clear influence on the choice of a MES, since

the aggregated results can be considered relatively stable confirmations of an existing relationship. These 11

variables should be considered at least as control variables in future studies.

Considering the theoretical explanations for the choice of a MES, it was shown that many theories have been

rarely tested empirically. This indicates serious research deficits. Regarding the theories that have frequently

been tested, it can be summarized:

• As it is postulated in the company strategy approach, the MNC strategy and the role of the foreign unit for

the MNC that is derived from the MNC strategy have a strong influence on the MES decision. Thus, in the

future, it should be differentiated between different subsidiary roles and different MNC strategies when

analyzing entry mode decisions.

• The stages models are confirmed in their core statement that increasing country-specific experience leads to

market entry strategies with a higher resource commitment.

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• The relevance of the resources and in particular the capabilities of the organization for the MES choice was

demonstrated, even though central constructs of the resource-based view and the organizational capabilities

approach have been rather neglected in extant research.

• The dominant theory, the transaction cost economics, was not fully supported by the integrated results.

Some core constructs did not expose the expected effect across the existing studies, as it was discussed

in detail in the paper.

All in all, the study supports those researchers who consider the different internationalization theories to be

complementary and who demand that a comprehensive explanatory model has to be based on a multi-theoretical

framework. Neither single variables nor groups of variables, but the combined effect of different variables

should be focused on in future research (Hill et al., 1990; Roberts & Greenwood, 1997; Madhok, 2002;

Malhotra, Agarwal & Ulgado, 2004).

In particular, future studies should shift attention to the influence of strategic considerations of the company on

MES choice. Past research often neglected the effectiveness of a MES for the implementation of a certain

company strategy. Pla-Barber (2001: 460) even discusses the influence of company strategy under the title ”A

new firm-specific factor: strategy“. Following this perspective, it seems evident, that market entry strategies are

often not chosen primarily to minimize transaction costs, but to implement corporate strategies and objectives in

the most effective way (cf. Johanson & Vahlne, 1990).

15

ENDNOTES

1 This variable displays a significant influence for the combined effect sizes, but not in the mean of the VC scale.

2 One deficit in previous research is, however, that ADV and RND have frequently been captured as industry averages,

not – as theory would require it – on the level of the specific foreign activity of a specific MNC.

16

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26

APPENDIX

Sorted List of Studies used in the Meta-Analysis

These studies are marked with [MA] in the list of references.

#1 Agarwal, 1994

#2 Agarwal/Ramaswami, 1992

#3 Baek, 2003

#4 Barkema/Vermeulen, 1998

#5 Benito, 1996

#6 Brouthers, 1995

#7 Brouthers, 2002

#8 (a,b) Brouthers/Brouthers, 2003

#9 Brouthers/Brouthers/Werner, 2000

#10 Brouthers/Brouthers/Werner, 2003

#11 Chang/Rosenzweig, 2001

#12 Chen/Hu, 2002

#13 Chen/Hu/Hu, 2002

#14 Cleeve, 1997

#15 Contractor/Kundu, 1998a

#16 Contractor/Kundu, 1998b

#17 Davidson/McFetridge, 1984

#18 (a,b) Delios/Beamish, 1999

#19 Delios/Henisz, 2000

#20 Ekeledo/Sivakumar, 2004

#21 Elango/Sambharya, 2004

#22 Erramilli, 1996

#23 Erramilli/Rao, 1993

#24 Erramilli/Agarwal/Kim, 1997

#25 Fladmoe-Lindquist/Jacque, 1995

#26 Gatignon/Anderson, 1988

#27 Gomes-Casseres, 1989

#28 Gomes-Casseres, 1990

#29 (a,b) Hennart, 1991

#30 Hennart/Reddy, 1997

#31 Hennart/Larimo, 1998

#32 Herrmann/Datta, 2002

#33 Hildebrandt/Weiss, 1997

#34 Kim/Hwang, 1992

#35 Kogut/Singh, 1988

#36 Kogut/Zander, 1993

#37 Lecraw, 1984

#38 Lu, 2002

#39 Madhok, 1998

#40 Makino/Neupert, 2000

#41 Mayrhofer, 2004

#42 Meyer, 2001

#43 Morschett/Schramm-Klein, 2004

#44 Padmanabhan/Cho, 1999

#45 Pak/Park, 2004

#46 Palenzuela/Bobillo, 1999

#47 Pan, 1996

#48 Pan/Tse, 2000

#49 Yiu/Makino, 2002

#50 Randoy/Dibrell, 2002

#51 Shan, 1991

#52 (a,b) Shane, 1992

#53 Shi/Ho/Siu, 2001

#54 Singh/Kogut, 1989

#55 Sun, 1999

#56 Tatoglu/Glaister/Erdal, 2003

#57 Taylor/Zou/Osland, 1998

27

TABLE 1 OVERVIEW ON VARIABLES INCLUDED IN THE META-ANALYSIS AND PREDICTED

DIRECTION OF EFFECT OF EACH VARIABLE FROM THEORY

Predicted Effect (from Theory)

Variable TCE OC RBV Other Explanations

Cultural Distance CULT +/- +/- Country Risk RISK + - Income Level GNPPP - - higher market attractiveness: + Market Size MSIZE + higher market attractiveness: + Market Growth MGROWTH - lower competition intensity: + Industry Concentration CONC + Legal Restrictions RESTRICT neo-institutionalism: - Power Distance Index PDI behavioristic: + Uncertainty Avoidance UAI behavioristic: +/- MNC Sales SIZsales + MNC Employees SIZempl + MNC Assets SIZassets + International Experience (country-specific) IEXcountry + stages models : +

Age of Subsidiary AGESUB + stages models : + Multinational Experience IEXmult + International Experience (general) IEXgeneral +

Export Intensity EXPORT + stages models : + Diversification of MNC DIVERMNC - strategy approach: - Int. Product Diversification DIVERSUB - - strategy approach: - Specificity (general) SPECIF + Advertising Intensity ADV + + R&D Intensity RND + +/- Capital Intensity CAPINT - - Subsidiary Size (absolute) SUBSIZabs - strategy approach: + Subsidiary Size (relative to MNC) SUBSIZrel - strategy approach: +

Resource Intensity RESOURCE - strategy approach: -

28

TABLE 2 STUDY RESULTS FROM PRIMARY STUDIES AND SYNTHESIS OF STUDY RESULTS

Study Results (number of studies) Synthesis of Study Results

Variable -2.5 -1.5 -0.5 0.5 1.5 2.5 n Mean VC-Scale

Combination of Stand. Effect Sizes (n/N)

CULT 7 4 9 2 3 4 29 -0.43 n.s. -0.09 (n.s.), 12/8,892, heter. RISK 11 3 4 4 0 1 23 -1.28*** -0.35*, 8/6,048, homog. GNPPP 2 2 1 4 9 0.50 n.s. 0.06 (n.s.), 4/1,857, heter. MSIZE 4 2 1 7 -1.50* -0.17*, 5/5,982, homog. MGROWTH 2 1 4 2 2 1 12 -0.17 n.s. -0.11*, 6/3,979, homog. CONC 2 3 1 2 8 0.88† 0.12 (n.s.), 4/1,833, heter. RESTRICT 12 4 1 1 18 -1.67*** -0.26*, 13/11,467, heterog. PDI 1 1 3 1 6 1.17* 0.21*, 5/836, homogeneous UAI 1 1 2 1 5 0.30 n.s. 0.31 (n.s.), 3/555, heterog. SIZsales 3 3 2 1 9 -0.61 n.s. 0.00 (n.s.), 4/3,187, homog. SIZempl 2 1 2 4 1 2 12 0.08 n.s. 0.26*, 6/1,294, homog. SIZassets 1 2 2 5 0.50 n.s. n.a. IEXcountry 1 1 10 3 6 21 1.07*** 0.21*, 9/3,556, homog. AGESUB 2 2 1 5 0.30 n.s. n.a. IEXmult 2 6 3 2 13 0.12 n.s. 0.03 (n.s.), 8/8,684, het. IEXgeneral 1 1 2 5 1 3 13 0.50 n.s. -0.10 (n.s.), 5/1,203, het. EXPORT 1 2 4 7 1.79** 0.17*, 3/4,604, homog. DIVERMNC 3 2 5 -0.10 n.s. 0.01 (n.s.), 4/2,208, homog. DIVERSUB 6 1 5 5 17 -0.97** -0.08*, 4/6,075, homog. SPECIF 1 1 2 2 2 8 0.75 n.s. n.a. ADV 1 1 4 6 3 7 22 0.86* 0.19*, 7/7,266, homog. RND 3 6 10 2 6 27 0.46 n.s. 0.06 (n.s.), 13/11,291, het. CAPINT 1 1 2 1 5 -0.90 n.s. n.a. SUBSIZabs 2 1 3 1 2 9 -0.50 n.s. n.a. SUBSIZrel 1 1 2 4 1 1 10 0.10 n.s. n.a. RESOURCE 3 4 3 10 -1.50*** -0.15*, 3/4,603, homog.

Legend: - 2.5 refers to studies with a negative coefficient, p<.01; -1.5 studies with a negative coefficient, p<.05; -0.5 studies with a negative coefficient, non-significant, 0.5 studies with a positive coefficient, non-significant;1.5 studies with a positive coefficient, p<.05; 2.5 studies with a negative coefficient, p<.01.

Each study result represents the influence of the variable on the likelihood of choosing a WOS rather than a cooperation. Positive signs indicate that a higher value of the variable leads to a higher likelihood of a WOS. n: number of studies; N: size of aggregated sample homogeneous/heterogeneous indicates the results of the Q-test for homogeneity of the primary study results. When homogeneity is indicated, a fixed-effects model was calculated, when heterogeneity is indicated, a random-effects model was calculated. n.a. indicates cases in which the method was not applicable. Significance levels: n.s.: not significant; †: 0.1; *: 0.05, **: 0.01, ***: 0.001. For the combination of the standardized effect sizes, it was only tested, whether the combined result is significant on the 5%-level or not.

29

FIGURE 1 STANDARDIZED EFFECT SIZES AND CONFIDENCE INTERVALS OF THE STUDIES ON

THE VARIABLE IEXCOUNTRY

-1.00

-0.50

0.00

0.50

1.00

1.50

2.00

2.50

3.00

#42#30#11#10 #54#8a #8b

#53

#4Mean

ES

Log

Odd

sR

atio

ES(s) 95% CI

Study Number-1.00

-0.50

0.00

0.50

1.00

1.50

2.00

2.50

3.00

#42#42#30#30#11#11#10#10 #54#54#8a#8a #8b#8b

#53#53

#4#4Mean

ES

Log

Odd

sR

atio

ES(s) 95% CI

Study Number

30

FIGURE 2 COMBINED STANDARDIZED EFFECT SIZES AND CONFIDENCE INTERVALS FOR THE

ANALYZED VARIABLES

0.310.26

0.170.12

0.06 0.06 0.03

-0.08 -0.09 -0.10 -0.11

-0.35-0.26

0.19

0.200.210.21

0.000.01

-0.17-0.15

-0.60

-0.40

-0.20

0.00

0.20

0.40

0.60

UAI

SIZe

mpl

PDI

IEXc

ount

ry(S

PEC

IF)

ADV

EXPO

RT

CO

NC

RN

D

GN

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DIV

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OW

THR

ESO

UR

CE

MSI

ZER

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K

Variable

Log

Odd

sR

atio

ES(s) 95% CI

0.310.26

0.170.12

0.06 0.06 0.03

-0.08 -0.09 -0.10 -0.11

-0.35-0.26

0.19

0.200.210.21

0.000.01

-0.17-0.15

-0.60

-0.40

-0.20

0.00

0.20

0.40

0.60

UAI

SIZe

mpl

PDI

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ry(S

PEC

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ADV

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D

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IEXm

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DIV

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ESO

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ZER

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Log

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ES(s) 95% CI

31