and asset specificity influence service providers' entry mode choices because ... choice (which examine either manufacturing or service firms) have shown that.
Journal of Management Studies 40:5 July 2003 0022-2380
Why Service and Manufacturing Entry Mode Choices Differ: The Influence of Transaction Cost Factors, Risk and Trust*
Keith D. Brouthers and Lance Eliot Brouthers Fox School of Business & Management Temple University, Philadelphia; University of Texas El Paso In this study, we suggest that disparities between service and manufacturing firms’ international entry mode choices can be explained by differences in their reaction to transaction cost based variables and by the influence of risk and trust propensity. We find that: (1) due to the investment intensive nature of manufacturing, environmental uncertainties and risk propensity influence manufacturers’ mode choices; while (2) behavioural uncertainties, trust propensity and asset specificity influence service providers’ entry mode choices because of the people-intensive nature of services. Implications for future research are discussed.
INTRODUCTION Previous research identifies three general attributes of transactions that influence transaction cost perceptions (Klein et al., 1990; Rindfleisch and Heide, 1997): (1) asset specificity, (2) environmental uncertainty, and (3) behavioural uncertainty.[1] Transaction cost economics (TCE) studies exploring international entry mode choice (which examine either manufacturing or service firms) have shown that manufacturing and service firms respond differently to these three TCE stimuli (Anderson and Coughlan, 1987; Delios and Beamish, 1999; Erramilli and Rao, 1993; Gatignon and Anderson, 1988; Hennart, 1991; Klein et al., 1990). Why might this be the case? Both the Erramilli and Rao (1993) and Murray and Kotabe (1999) studies suggest that transaction cost theory may affect service and manufacturing firms differently. For that reason, both studies conclude that TCE theory may have to be modified to be applicable to service firms.
Address for reprints: Keith D. Brouthers, Fox School of Business and Management, Temple University, 111 Speakman Hall, 1810 North 13th Street, Philadelphia, PA 19122-6083, USA. © Blackwell Publishing Ltd 2003. Published by Blackwell Publishing, 9600 Garsington Road, Oxford, OX4 2DQ , UK and 350 Main Street, Malden, MA 02148, USA.
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Here we take a different approach. Rather than modifying TCE theory, we propose that TCE-driven international entry mode choice may differ for manufacturing and service firms because service and manufacturing firms may respond differently to the previously mentioned TCE attributes. Previous research suggests that service[2] firms tend to require substantially lower levels of financial investment (Erramilli and Rao, 1993) than manufacturing firms. Services tend to: (1) be produced and delivered simultaneously (Habib and Victor, 1991); and (2) be more people-intensive (Boddewyn et al., 1986; Bowen and Jones, 1986; Erramilli and Rao, 1993) than manufacturing firms (entry into new foreign markets will require high investments in people and relatively low investments in plant, equipment, and inventory). Thus, we posit that service firms respond to the people-oriented component of TCE, behavioural uncertainty (how people behave). Contrary to this, previous research (Bowen and Jones, 1986; Campbell and Verbeke, 1994; Erramilli and Rao, 1993; Gatignon and Anderson, 1988) suggests that manufacturing firms are more investment intensive (entry into a new country requires greater investments in plant, equipment and inventory with relatively low investments in people). Because of this we hypothesize that manufacturing firms will be more responsive to the investment component of TCE, environmental uncertainty, and less sensitive to people-oriented measures than service firms. In this study (the first to examine both manufacturing and service firm mode choice using the same TCE model) we attempt to increase our knowledge about TCE-driven mode choice in three ways. First, we provide a priori theoretically derived hypotheses in an attempt to explain why manufacturing and service firms respond differently. Second we test these hypotheses by using an unmodified TCE based model of mode choice for both service and manufacturing firms.[3] Using the same unmodified TCE-based model to test both manufacturing and service firms will help to determine if the discrepant results identified in past entry mode research were caused by actual differences between manufacturing and service firms or methods/model differences. Third, we include two new control variables, risk and trust propensity. Scholars, such as Ring and van de Ven (1992) and Chiles and McMackin (1996), suggest that these two variables may have an important impact on TCE entry mode choice. However, neither variable (risk propensity, trust propensity) has been included in previous TCE entry mode choice studies. Hence, we develop and test a set of hypotheses that posit manufacturers and service providers react differently to specific transaction cost criteria and thus, make disparate international entry mode choices. More specifically, we hypothesize that: (1) because of the people-intensive nature of services, service firm mode choice is influenced by behavioural uncertainties; while (2) environmental uncertainties influence manufacturers’ choices because of the investment-intensive nature of manufacturing FDI. © Blackwell Publishing Ltd 2003
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ASSET SPECIFICITY AND MODE CHOICE One of the central tenants of TCE is that the specificity of the assets employed in a transaction have a significant impact on the efficiency (transaction costs) of alternative governance structures (Hennart, 1994; Williamson, 1991). Specific assets are investments made that have little value outside the specific transactional relationship (Rindfleisch and Heide, 1997; Williamson, 1991). TCE based international entry mode research suggests that asset specificity is important because of opportunism (Delios and Beamish, 1999; Erramilli and Rao, 1993; Gatignon and Anderson, 1998; Hennart, 1991). Opportunism occurs because firms may have difficulty writing complete contracts or evaluating the performance of partner organizations (Williamson, 1991). Scholars examining the issue of international entry mode choice have proposed that, the greater the specificity of the assets needed in an international investment, the greater the transaction costs created by potential opportunism (Delios and Beamish, 1999; Gatignon and Anderson, 1988; Taylor et al., 1998). These scholars suggest that as asset specificity increases, firms tend to internalize transactions and use wholly owned modes of entry. But as asset specificity decrease, joint venture modes of entry are preferred (Delios and Beamish, 1999; Gatignon and Anderson, 1988; Palenzuela and Bobillo, 1999; Taylor et al., 1998).
Asset Specificity and Services Research suggests that service firms vary with respect to the asset specificity of their service; these variations may result in differences in mode selection (Contractor and Kundu, 1998; Erramilli and Rao, 1993; Fladmoe-Lindquist and Jacque, 1995; Murray and Kotabe, 1999). This scholarship suggests that, because services tend to be people intensive, service firms’ competitive advantage tends to be derived from idiosyncratic assets (such as investments in training and knowledge). Mode choice will vary with the degree of idiosyncratic asset investment (Erramilli and Rao, 1993). When the specificity of the assets is low (low idiosyncratic asset investment), joint venture modes are preferred. However, when the service being provided requires high levels of idiosyncratic asset investment, wholly owned modes are preferred (Contractor and Kundu, 1998; Erramilli and Rao, 1993). Based on this discussion, we posit: Hypothesis 1a: Service firms making high asset specific investments prefer wholly owned modes of entry to joint ventures. We could identify only three service firm international entry mode choice studies that examined asset specificity. Both Fladmoe-Lindquist and Jacque (1995), and Erramilli and Rao (1993) found strong empirical support for the relationship © Blackwell Publishing Ltd 2003
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between asset specificity and mode choice, with high specificity being related to the use of wholly owned modes of entry. Contractor and Kundu’s (1998) measure of asset specificity (importance of training) was not significantly related to mode choice in one analysis but was significant in a second analysis, thus providing additional, though weaker support. Asset Specificity and Manufacturing The consensus among TCE scholars on the impact of asset specificity for international manufacturing mode choice is consistent with basic TCE guidance (Aulakh and Kotabe, 1997; Delios and Beamish, 1999; Gatignon and Anderson, 1988; Hennart, 1991; Hennart and Larimo, 1998; Kim and Hwang, 1992; Taylor et al., 1998). Manufacturing firms that make greater asset specific investments are expected to prefer wholly owned modes of entry over joint ventures while manufacturing firms making less asset specific investments will prefer joint venture modes of entry. We conclude: Hypothesis 1b: Manufacturing firms making high asset specific investments prefer wholly owned modes of entry to joint ventures. The empirical findings for manufacturing firms have been mixed. Only a few studies have found any support for the proposition that asset specificity and mode choice are related positively (Anderson and Coughlan, 1987; Gatignon and Anderson, 1988; Hennart and Larimo, 1998), while other studies actually found a negative relationship (Delios and Beamish, 1999; Palenzuela and Bobillo, 1999). However, most manufacturing studies have found no significant relationship between asset specificity and mode choice (Aulakh and Kotabe, 1997; Delios and Beamish, 1999; Gatignon and Anderson, 1988; Hennart, 1991; Hennart and Larimo, 1998; Kim and Hwang, 1992; Taylor et al., 1998). We suggest that the lack of findings may be due to one of two factors. First, Rindfleisch and Heide (1997, p. 42) suggest that secondary sources of the measure of asset specificity may ‘provide only an approximate specification of the construct, which leads to potential construct validity problems’. Since most of the manufacturing studies use secondary R&D and Marketing intensity measures as proxies for asset specificity, they may suffer from this misspecification problem. To remedy this potential problem our study uses a multi-item scale that Rindfleisch and Heide (1997) suggest may provide a more accurate measure. Our scale includes measures of human asset specificity, proprietary asset specificity, and dedicated asset specificity. Second, Rindfleisch and Heide (1997) also point out that direct measures of asset specificity (such as ours) normally focus on the people-intensive nature of asset specificity. However, many manufacturing investments involve high fixed asset © Blackwell Publishing Ltd 2003
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investment but relatively little people-intensive asset investment (Bowen and Jones, 1986). Thus, asset specificity (when measured as we do) may not be a major driver of manufacturing firm mode choice. ENVIRONMENTAL UNCERTAINTY AND MODE CHOICE Gatignon and Anderson (1988, p. 315) state that environmental uncertainties are ‘generally understood to mean the extent to which a country’s political, legal, cultural, and economic environment threatens the stability of a business operation’. Two differing views have been offered regarding the influence of environmental uncertainty and mode choice. First, Williamson (1991) suggests that hybrid modes (joint ventures) will be used less often in high environmental uncertainty markets because adaptations cannot be made quickly due to the need for consent between parties. Conversely, he and Hennart (1994) suggest that wholly owned modes provide quick adaptation through fiat. The second perspective, put forth by most TCE entry mode scholars (e.g. Aulakh and Kotabe, 1997; Erramilli and Rao, 1993; Gatignon and Anderson, 1988; Kim and Hwang, 1992), is that joint ventures provide firms greater flexibility, which is needed when environmental uncertainty is high in order to speed up adaptation. Environmental Uncertainty and Services Previous service firm entry mode studies used the flexibility argument (Agarwal and Ramaswami, 1992; Erramilli and Rao, 1993; Fladmoe-Lindquist and Jacque, 1995). However, for service firms, Williamson’s consent argument may be more applicable. Services are people intensive (Bowen and Jones, 1986; Erramilli and Rao, 1993). They tend to be inseparable and perishable (Bowen and Jones, 1986; Edgett and Parkinson, 1993). Inseparability means that service firm production and consumption are normally geographically linked; the service firm needs to be present at the time of production and use. Perishability means that services cannot be inventoried. These attributes suggest that service firms require greater control in order to deal with changes in the environment (Bowen and Jones, 1986; Habib and Victor, 1991). When there are changes in the environment, contractual agreements (such as joint venture agreements) may need to be renegotiated and changed (Williamson, 1991). This requires time that the service firm may not have, and reduces flexibility needed to address environmental uncertainties in a timely fashion (Erramilli and Rao, 1993). However, if service firms use wholly owned modes of entry, changes in the environment can be responded to more quickly (through fiat), providing a more timely response to environmental change (Hennart, 1994; Williamson, 1991). Hence, this literature suggests: © Blackwell Publishing Ltd 2003
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Hypothesis 2a: Service firms perceiving high levels of environmental uncertainty will tend to prefer wholly owned modes of entry to joint ventures. Empirical results of past service firm studies offer mixed results. Agarwal and Ramaswami (1992) did not find any significant difference in mode usage based on perceived environmental uncertainty for their sample of service firms. Similarly, Erramilli and Rao’s (1993) analysis shows that environmental uncertainty is not significantly related to mode choice. Fladmoe-Lindquist and Jacque (1995) found mixed results with two uncertainty measures showing a preference for wholly owned modes, one being negatively related to wholly owned modes, and one measure being insignificant. Only Contractor and Kundu (1998) found unequivocal significant results showing increased uncertainty related to the use of wholly owned modes. These empirical findings suggest that environmental uncertainties may not be a major driver of service firm mode choice. Environmental Uncertainty and Manufacturing Gatignon and Anderson (1988, p. 309) suggest that for manufacturing firms, high environmental uncertainty ‘should lead to a need for greater flexibility and therefore to the use of lower-control governance modes’. Further, Kim and Hwang (1992, p. 35) suggest that a manufacturing firm should ‘limit its exposure to such risk by restricting its resource commitments’ and utilize joint venture entry modes. These scholars suggest that, because manufacturing FDI is typically fixed asset intensive, joint venture modes of entry provide the firm with a method to decrease the exposure of fixed assets to the potential hazards of environmental uncertainty (Luo, 2001). Thus, we posit: Hypothesis 2b: Manufacturing firms perceiving high levels of environmental uncertainty tend to prefer joint venture modes of entry to wholly owned subsidiaries. Several studies (Aulakh and Kotabe, 1997; Gatignon and Anderson, 1988; Kim and Hwang, 1992; Luo, 2001) have provided empirical support for this perspective. Each found that high environmental uncertainty was significantly associated with an increased use of joint venture modes, for their samples of manufacturing firms. BEHAVIOURAL UNCERTAINTY AND MODE CHOICE Put simply, behavioural uncertainty and the underlying theory of transaction costs assume that opportunism, bounded rationality and risk all help to create high costs in monitoring and/or controlling the behaviour of partner firms (Hill, 1990; © Blackwell Publishing Ltd 2003
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Williamson, 1991). Hennart (1989, 1994) explains that mode choice is a trade-off between transaction costs and internal oranizational costs. He suggests that wholly owned modes ‘reduce the cost of international coordination between parties located in different countries’ (Hennart, 1989, p. 214), providing firms with transaction cost savings. But he also suggests that internal organizational costs (monitoring) ‘will vary with the nature of the activity’ (Hennart, 1994, p. 195). Hence, Hennart (1989, p. 215) concludes that ‘[i]nternalization replaces therefore one type of cost (transaction costs) by another (internal organization costs)’. Behavioural Uncertainty and Services TCE theory suggests that, as behavioural uncertainties increase, firms prefer wholly owned modes in order to gain control and reduce transaction costs (Chiles and McMackin, 1996; Hill, 1990; Ring and Van De Ven, 1992). Service firms’ people intensity (because they rely on people for the simultaneous production and delivery of the service product) results in greater difficulty in managing foreign operation (incur higher internal organizational costs) than manufacturing firms (Bowen and Jones, 1986; Carney and Gedajlovic, 1991; Erramilli and Rao, 1993; Fladmoe-Lindquist and Jacque, 1995). This research suggests that increased cultural differences or geographic distance may create a situation where service firms incur internal organizational costs that exceed transaction cost savings when using wholly owned modes. Because of this, service firms tend to avoid wholly owned modes of entry as behavioural uncertainties increase (Erramilli and Rao, 1993). To obtain the control they desire, at a lower net cost, service firms prefer to use processes like shared-value systems and contractual arrangements which shift the costs of monitoring/controlling activities to the partner firm, reducing internal organizational costs (Carney and Gedajlovic, 1991; Fladmoe-Lindquist and Jacque, 1995). Hence, for service firms we hypothesize: Hypothesis 3a: Service firms perceiving high levels of behavioural uncertainty tend to prefer joint venture modes of entry to wholly owned subsidiaries. Empirical evidence tends to support this hypothesis. Studies of service firm mode choice suggest that, as behavioural uncertainties increase, service providers reduce the use of wholly owned modes of entry (Agarwal and Ramaswami, 1992; Erramilli and Rao, 1993; Fladmoe-Lindquist and Jacque, 1995). Behavioural Uncertainty and Manufacturing For manufacturing firms, behavioural uncertainties also drive firms to seek control. However, for manufacturing firms control may be obtained at a lower cost through wholly owned modes of entry, because of the lower level of transaction costs and © Blackwell Publishing Ltd 2003
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lower internal organizational costs available through direct control for manufacturing firms (Gatignon and Anderson, 1988; Taylor et al., 1998). For manufacturing firms we hypothesize that: Hypothesis 3b: Manufacturing firms perceiving high levels of behavioural uncertainty tend to prefer wholly owned entry modes to joint ventures. Empirical support for this perspective has been provided in a number of TCE studies that have found manufacturing firms prefer wholly owned modes as behavioural uncertainties increase (Gatignon and Anderson, 1988; Taylor et al., 1998). However, another group of manufacturing firm TCE studies have found no significant relationship between behavioural uncertainty and mode choice (Anderson and Coughlan, 1987; Kim and Hwang, 1992). We suggest that, because of the investment intensive nature of manufacturing, behavioural uncertainties may not be a significant driver of mode choice. METHODOLOGY Data Sources In order to determine the differential impact of transaction cost related variables on manufacturing and service firms’ entry mode strategies, we used samples of western European firms’ entry into central and east Europe (CEE). We selected CEE investment for several reasons. First, behavioural and environmental uncertainties are the main barriers to investment in these countries (Brouthers et al., 1998; Perlaki, 1994; Welch, 1993). The variance in these two factors is expected to be great (ranging from low values in Hungary to high values in Russia). Second, joint ventures and wholly owned modes are most common in these countries, despite potential legal restrictions (Brouthers et al., 1998; Gatling, 1993). Third, CEE markets are commonly characterized by low trust cultures, creating high behavioural uncertainty, an entry barrier for firms wishing to use joint venture modes of entry (Casson, 1994; Perlaki, 1994). Fourth, scholars also maintain that political, social and environmental uncertainties are still perceived as very high in the region (Brouthers et al., 1998; Gatling, 1993; Welch, 1993), providing a barrier to using wholly owned entry modes (Erramilli and Rao, 1993; Gatignon and Anderson, 1988). Hence, CEE provided an excellent location for testing TCE theory. We selected a western European firm sample for two reasons. First, because western Europeans responded early to the changes occurring in CEE, they provide a large base of active investing firms in the region. Second, Meyer (1995) identified western European firms as the largest investors in CEE. Because we could identify no complete lists of western European firms doing business in CEE, we attempted to construct a logical sampling frame from available sources. The Dutch sample of 419 companies came from two sources. First, © Blackwell Publishing Ltd 2003
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we used the REACH CD-ROM database of all Dutch publicly traded companies to identify those firms that had indicated an investment in CEE. Second, we gained access to a list of Dutch firms that attended a seminar on doing business in CEE. Hence, our Dutch sample included known CEE investors as well as firms interested in the region. The German (400 firms) and British (371 firms) samples were simply the largest firms in the country (based on sales) taken from the AMADEUS CD-ROM database (a database that combines REACH type data from all EU countries). Because the AMADEUS database did not disclose CEE investments, we simply sampled the largest firms, based on anecdotal evidence that larger firms were more likely to be CEE investors. We contacted 1190 firms and obtained responses from about 47 per cent of those surveyed (195 Dutch, 174 German and 187 British). Of those, 227 (103 Dutch, 74 German, and 50 British) firms returned completed questionnaires. Those firms that did respond, but did not complete questionnaires, indicated that they did not have operations in CEE and, for that reason, were not included in our study. Questionnaire Design Postal questionnaires were used to collect the Dutch, German and British data. Each firm was requested to indicate their most recent initial entry into CEE and provide details on the mode(s) used, and perceived levels of asset specificity, environmental and behavioural uncertainties. To minimize the impact of recall bias, we asked respondents to discuss only their most recent CEE entry. Previous studies indicate that joint venture and wholly owned modes of entry are the most widely used for CEE investments (Brouthers et al., 1998; Gatling, 1993). Thus, as in previous entry mode studies (Hennart, 1991; Hennart and Larimo, 1998; Hennart and Reddy, 1997; Kogut and Singh, 1988) we restricted our sample to firms using joint venture and wholly owned modes of entry. Respondents were separated into service or manufacturing firms for analysis. In the questionnaire respondents were asked to classify their target organization as either a service firm or manufacturer. In addition, respondents were asked to identify the target market industry. We used the respondent classification to put firms into either the service or manufacturing analysis. Industry type was used to doublecheck the classification. Independent Variables Rindfleisch and Heide (1997) suggest that asset-specificity is a multifaceted attribute. It includes: (1) human asset specificity, ‘ “investment in training” which upgrades the knowledge and organizational capabilities’ of a firm (Contractor and Kundu, 1998, p. 343). Heide and Stump (1995, p. 58) suggest asset specificity © Blackwell Publishing Ltd 2003
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includes ‘investments in the form of training technicians on particular types of equipment’. We captured this facet of asset specificity by asking, ‘How do you rate the training programme in terms of preparing personnel to provide your service or produce your product (1 = well below average, 7 = well above average)?’ (2) Asset specificity also includes the proprietary nature of the products/services provided (Gatignon and Anderson, 1988) which we captured by asking, ‘How do you rate your firm’s potential to create new and creative products or services (1 = well below average, 7 = well above average)?’ (3) Finally, asset specificity may reflect the level of dedicated assets, ‘general purpose investments that would not have been made outside a particular transaction’ (Shelanski and Klein, 1995, p. 341). Because we are concerned with an international entry mode decision, we captured the firm’s ability to make general international investments by asking, ‘How many technological resources does your firm have to handle international expansion (1 = few resources, 7 = many resources)?’ The responses to these three questions were measured using three seven-point Likert-type scales and combined to form a composite index (Cronbach alpha = 0.64). While the reliability of this measure is modest, it compares favourably with past asset specificity measures’ reliabilities such as the 0.64 obtained by Taylor et al. (1998) and Erramilli and Rao (1993) or the reliability of 0.65 found in Klein et al. (1990). Environmental uncertainty was measured using three Likert-type questions (Cronbach alpha = 0.67). Respondents were asked to evaluate the general stability of the political, social, and economic conditions in the target country, the risk of converting and repatriating income from the target country, and the risk of target governmental actions such as nationalization. All three questions were taken from Agarwal and Ramaswami (1992). Behavioural uncertainty arises from the inability of the parent firm to monitor and control the performance of the foreign subsidiary (Hill, 1990; Rindfleisch and Heide, 1997; Williamson, 1991). Because of bounded rationality, it is difficult to write complete contracts (Hill, 1990; Williamson, 1991). We attempted to measure three facets of the monitoring and control issue (Cronbach alpha = 0.65). First, we asked about the cost (difficulty) of writing and enforcing contracts (Agarwal and Ramaswami, 1992). As the literature suggests, writing complete contracts for service providers is more difficult than for manufacturing firms because of the heterogeneity of services (Erramilli and Rao, 1993). Heterogeneity means that: (1) services are hard to standardize; and (2) there is the potential for great variability in service production and delivery (Edgett and Parkinson, 1993). Heterogeneity is created because of the people intensive nature of services. Services are usually provided (by people) at the time of production while manufactured products are less susceptible to the ‘mood’ of the employees (Anand and Delios, 1997; Nicoulaud, 1989). Hence, compared to manufacturing firms: (1) service firms face greater difficulty in writing contracts because the con© Blackwell Publishing Ltd 2003
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tracts require much more detail; and (2) service firms incur greater difficulties in enforcing contracts because of the inseparability of production and consumption (Edgett and Parkinson, 1993). Second, we inquired about the difficulty of monitoring and controlling product/service quality (Agarwal and Ramaswami, 1992). Because services are normally inseparable ( provided at the time of consumption) there is little chance to perform a quality check before the consumer sees the final product. However, for manufacturing firms this is less of a problem; poor quality products can be stopped before reaching the final consumer (Bowen and Jones, 1986; Edgett and Parkinson, 1993). Third, we asked about the potential problems involved in monitoring and controlling the dissemination or misuse of proprietary knowledge (Agarwal and Ramaswami, 1992). Since the competitive advantage of service firms is normally derived from intangibles, it is more difficult to protect ( patent, copyright, etc.) the proprietary input than if the advantage were derived from more tangible assets. However, with manufacturing firms the advantage may come from more tangible, patentable sources (Ekeledo and Sivakumar, 1998; Erramilli and Rao, 1993). Control Variables In addition to the three major transaction cost variables, we included six control variables: risk propensity, trust propensity, the interaction between environmental uncertainty and asset specificity (EUAS), firm size, legal restrictions, and region specific (CEE) experience. Data for the first two control variables were obtained from secondary sources, while data for the other four control variables were obtained from the questionnaires completed by the respondent firms. Scholars such as Ring and van de Ven (1992), and Chiles and McMackin (1996) suggest managers may not be risk and trust neutral, as is assumed by TCE theory. They suggest that for TCE theory to more accurately reflect the way managers make decisions, account must be taken of the risk propensity and trust propensity of the firm. The willingness of a firm to accept different levels of transaction costs may be influenced by a firm’s risk propensity (Sitkin and Pablo, 1992). Risk propensity appears to offer a trade-off between reducing: (1) the risks associated with fixed asset investments (environmental uncertainty); and (2) the risks associated with controlling a foreign operation (behavioural uncertainty) (Erramilli and Rao, 1993; Gatignon and Anderson, 1988). Since, in general, manufacturing FDI requires higher fixed asset investments than does service FDI (Ekeledo and Sivakumar, 1998; Erramilli and Rao, 1993), we suggest that manufacturing firms from low risk propensity cultures will tend to prefer joint venture modes which minimize the fixed asset investment risk (exposure to environmental uncertainties). Kogut and Singh (1988) (for their sample of both manufacturing and service firm) found that © Blackwell Publishing Ltd 2003
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firms from low risk propensity cultures preferred joint ventures over wholly owned modes of entry. Contrary to this, Habib and Victor (1991, p. 594) suggest that service firms may be more sensitive to control risks (behavioural uncertainties) than are manufacturing firms: ‘sensing the changing needs of the consumer introduces additional uncertainty’ which requires the service firm to process information more quickly than a manufacturing firm. Because of this, service firms from low risk propensity cultures tend to prefer wholly owned modes of entry (Klein et al., 1990). Erramilli (1996) found service firms from low risk propensity cultures preferred wholly owned modes of entry. Tse et al. (1997) and others (Erramilli, 1996; Kogut and Singh, 1988) have suggested that Hofstede’s (1980) national cultural variable, uncertainty avoidance, reflects a home country’s risk propensity. For our measure of risk propensity, we used Hofstede’s (1980) uncertainty avoidance measure, which indicates that the Netherlands has an uncertainty avoidance measure of 53, Germany has an uncertainty avoidance measure of 65, and Britain has an uncertainty avoidance measure of 35. Some scholars have suggested that one way to reduce transaction costs is to rely on trust (Chiles and McMackin, 1996; Williamson, 1993). Whether a firm relies on trust to reduce transaction costs may depend on their trust propensity (Blois, 1999; Doney et al., 1998; McKnight et al., 1998; Zaheer and Venkatraman, 1995). McKnight et al. (1998, p. 477) suggest that trust propensity means ‘one believes that, regardless of whether people are reliable or not, one will obtain better interpersonal outcomes by dealing with people as though they are well meaning and reliable’. They suggest that high trust propensity individuals believe ‘that things turn out best when one is willing to depend on others, even though others may or may not be trustworthy’ (1998, p. 478). Expectation of these reciprocal acts (trust behaviours) results in a reduced need for monitoring and control. Hence, it reduces transaction cost perceptions. This leads firms to prefer joint venture modes of entry to wholly owned modes (Chiles and McMackin, 1996; Zaheer and Venkatraman, 1995). Only limited empirical evidence exists in this area. The evidence for both service and manufacturing firms suggests that increases in trust propensity increase the use of joint venture modes over wholly owned modes, while decreases in trust propensity result in wholly owned mode usage (Erramilli, 1996; Tse et al., 1997). Shane (1994) and others (Doney et al., 1998; Erramilli, 1996; Tse et al., 1997) have suggested that Hofstede’s (1980) national cultural attribute, power distance, represents the need for formal controls and the level of trust propensity in a society. Similar to Tse et al. (1997) and Erramilli (1996), we use power distance ratings for the home countries as our measure of trust propensity: Germany (35), the Netherlands (38), and Britain (35) (Hofstede, 1980).
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Several scholars have suggested that asset specificity may moderate a firm’s perceptions of and reaction to environmental uncertainties (Erramilli and Rao, 1993; Gatignon and Anderson, 1988). Firms making high asset specific investments may be more sensitive to environmental uncertainty than firms making low asset specific investments. High asset specific investments expose firms to greater hazards of opportunism (Zaheer and Venkatraman, 1995). For this reason they have a greater need for information (Bowen and Jones, 1986) than do firms making low specificity investments. We suggest that, compared to low specificity investments, firms making high specificity investments in high environmental uncertainty markets typically prefer wholly owned modes of entry (Erramilli and Rao, 1993; Gatignon and Anderson, 1988). We calculated the interaction between environmental uncertainty and asset specificity (EUAS) by taking the standardized scores of both items and multiplying them together. Similarly, firm size has been shown to influence mode selection. Previous scholarship indicates that larger firms tend to prefer wholly owned entry modes (Agarwal and Ramaswami, 1992; Erramilli and Rao, 1993). Wholly owned entry modes are preferred because larger firms tend to have more resources which can be applied to new market entry. Since this study examined firms from several home countries with differing accounting methods and currencies, firm size was measured as the total number of employees worldwide (Gatignon and Anderson, 1988). Legal restrictions may also have an impact on the entry mode selected (Anderson and Coughlan, 1987; Gatignon and Anderson, 1988). Until recently, certain CEE countries restricted foreign investment to joint ventures modes; wholly owned foreign subsidiaries were reserved for domestic owners. We measured the level of legal restrictions at the time of entry using a sevenpoint Likert scale. The question read: ‘At the time you entered this country, were there legal restrictions on the entry method (for example, were foreign investments limited to joint venture operations or licensing only) (1 = no restrictions, 7 = many restrictions)?’ Finally, entry mode choice may be influenced by a firm’s level of multinational experience. Firms with more experience tend to prefer wholly owned entry modes (Agarwal and Ramaswami, 1992; Erramilli, 1991). Erramilli (1991) maintains that, through experience, firms develop systems for dealing with new market entry, thus reducing their risk and costs of entry. Kogut and Singh (1988) posit that two types of experience may be important: general international experience, and country or region specific experience. Our analysis revealed that the general international experience measure and region specific experience measures were highly correlated. To eliminate potential multicollinearity problems, we chose to use only the region specific variable in our
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analyses. Region specific experience was obtained from respondents and was based on the number of years of business experience in CEE (Erramilli, 1991). Questionnaire Administration For each company, key informants were used to provide firm-specific data. To assure that the information obtained related to corporate level decision-makers, not subsidiary manager perceptions, questionnaires were mailed directly to the manager of CEE operations at corporate headquarters. We used three separate mailings of the questionnaires, in an effort to increase response size. For Dutch and German questionnaires, we used translation/back-translation techniques to assure consistency with the original English language version. Analytical Methods Since our dependent variable was dichotomous, we tested our hypotheses using logistic regression analysis (Hennart and Larimo, 1998; Hennart and Reddy, 1997). Hair et al. (1995, p. 130) maintain that logistic regression may be appropriate because it offers the ‘ability to incorporate nonlinear effects and a wide range of diagnostics’. Because the item scales and number of items per construct varied, prior to analysis all variables were converted to standardized z-scores. Furthermore, onetailed tests were utilized because Cohen (1977) suggests that one-tailed tests are more appropriate where hypotheses are testing for directionality. When dependent and independent variables all come from a single respondent there is always the chance of common methods variance bias (Hair et al., 1995). However, in this study we do not believe it is a problem for at least three reasons. First, our dependent variable (entry mode) is not the kind that would create bias (because it is an objective measure rather than a perception). Second, several of our control variables (risk and trust propensity) were obtained from secondary sources. Third, we used the one-factor test suggested by Podsakoff and Organ (1986) to look for potential common methods bias. When we loaded our variables we found that four factors were created. The largest factor explained only 19 per cent of the variance. These results indicate that common methods variance was not a problem in the current data set. FINDINGS Tables I (service firms) and II (manufacturing firms) contain descriptive statistics and correlations for all variables used in the study. With respect to the independent variables, descriptive statistics indicate that substantial variability exists. Although the samples contain a number of statistically significant (at the 0.01 level © Blackwell Publishing Ltd 2003
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Table I. Correlation martix – service firms Variable
Mean
S.D.
1
2
3
4
5
6
7
8
9
1. Size 2. Experience 3. Risk propensity 4. Trust propensity 5. Environmental uncertainty 6. Behavioural uncertainty 7. Asset specifity 8. Legal restrictions 9. EUAS 10. Mode
16,362 34,000 1.00 11.9 16.5 -0.07 48.0 9.7 0.20
1.00 0.18
1.00
63.2
1.5
0.26
0.00
0.13
1.00
9.2
3.1
0.03
0.14
0.12
0.09
1.00
18.0
5.1
-0.01
0.31*
0.31*
-0.11
0.31*
1.00
15.9 4.0
3.0 2.1
0.14 -0.15
-0.27 -0.11
0.01 -0.17
0.05 0.12
-0.25 0.51*
-0.28 -0.06
1.00 -0.08
1.00
-0.2 0.6
0.9 0.5
-0.13 0.31*
-0.31* 0.10
-0.17 -0.03
0.16 -0.10
0.09 -0.23
0.00 -0.11
0.19 0.28
0.16 -0.50*
1.00 0.03
n = 72, * p < 0.01.
or better) correlations between the independent variables, none of these correlations were large enough to suggest that multicollinearity exists (Hair et al., 1995). Results of logistic regression analyses used to test the hypotheses are reported in Table III.[4] Separate regression tests were performed on manufacturing firms and service firms because of hypothesized differences. Service Firms Results With respect to service firms, we hypothesized that increased asset specificity and environmental uncertainty as well as decreased behavioural uncertainty would be related to the use of wholly owned modes of entry. The first regression equation in Table III tested for service firm influences. The model was statistically significant (p = 0.0000) with a high chi-square value (51.61). The model correctly classified 85 per cent of the mode strategies for service firms, far exceeding the 51 per cent[5] expected by chance. We tested our three hypothesized relationships and found that, for service firms, asset specificity (p < 0.05) and behavioural uncertainty (p < 0.05) were statistically significantly related to mode choice, while environmental uncertainty was not. This provided empirical support for: (1) Hypothesis la, service firms making high asset specific investments preferred wholly owned modes of entry; and (2) Hypothesis 3a, service firms perceiving high levels of behavioural uncertainty preferred joint venture entry modes. We found no statistically significant support at the 0.05 level for Hypothesis 2a, although the sign indicates that for service firms increases in environmental uncertainty were related to a preference for wholly owned modes of entry. © Blackwell Publishing Ltd 2003
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Table II. Correlation martix – manufacturing firms Variable
Mean
S.D.
1. Size 2. Experience 3. Risk propensity 4. Trust propensity 5. Environmental uncertainty 6. Behavioural uncertainty 7. Asset specifity 8. Legal restrictions 9. EUAS 10. Mode
40,285 72,239 23.3 28.0 45.2 11.3
1
2 1.00 0.40* 0.03
3
4
1.00 -0.20
1.00
5
6
7
64.0
1.4
-0.17
0.14
-0.12
1.00
9.3
3.6
0.08
-0.03
0.12
-0.16
1.00
15.5
4.5
0.01
0.03
0.26
-0.12
0.59*
1.00
15.8 3.5
3.0 2.0
0.31* 0.36*
0.18 0.19
-0.09 0.00
-0.10 -0.22*
0.06 0.35*
0.04 0.34*
0.1 0.6
1.0 0.5
0.18 0.17
-0.01 0.24*
-0.05 0.12
-0.02 0.10
0.06 -0.14
-0.11 0.06
8
1.00 0.36* -0.08 0.13
9
1.00 -0.02 0.05
1.00 -0.09
n = 146, * p < 0.01.
Table III. Logistic regression models Model
Service firms
Manufacturing firms
b
s.e.
Independent variables Asset specificity Environmental uncertainty Behavioural uncertainty
0.93* 0.86 -0.90*
0.54 0.62 0.48
0.24 -0.52* 0.36
0.22 0.23 0.26
Control variables Risk propensity Trust propensity EUAS Firm size CEE experience Legal restrictions
-0.82 -0.85* 0.47 7.87** 2.42* -1.08**
0.52 0.48 0.45 3.00 1.16 0.32
0.38* 0.25 -0.16 0.24 0.49* -0.02
0.21 0.21 0.19 0.21 0.24 0.11
8.49**
2.36
0.64
0.45
Constant N Chi-square Percent correct Significance
72 51.61 84.72 0.0000
Wholly owned = 1, * p < 0.05, ** p < 0.01 (one-tailed tests).
© Blackwell Publishing Ltd 2003
b
s.e.
146 25.25 73.29 0.0027
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Four of the control variables were statistically significant with increased firm size (p < 0.01) and CEE experience (p < 0.01) linked to increased use of wholly owned subsidiaries while increased trust propensity (p < 0.05) and legal restrictions (p < 0.01) were associated with the use of joint venture modes of entry. Neither risk propensity nor the interaction term (environmental uncertainty and asset specificity (EUAS)) was statistically significant at the 0.05 level. Manufacturing Firms Results We conjectured that manufacturing firms respond differently than services in developing their internationalization strategies. We hypothesized that for manufacturing firms high levels of asset specificity and behavioural uncertainties, and low levels of environmental uncertainty would be related to the use of wholly owned modes of entry. The second regression equation in Table III tested for manufacturing firm mode choice. The model was statistically significant (p = 0.0027) with a moderate chisquare (25.25). The model correctly classified 73 per cent of the mode choices, substantially better than the chance rate of 54 per cent. In testing our three manufacturing model hypotheses, we found that environmental uncertainty (p < 0.05) was statistically significantly related to mode choice while behavioural uncertainty and asset specificity were not. Hence, the manufacturing model provided empirical support for Hypothesis 2b, high environmental uncertainty was related to joint venture usage for manufacturing firms. As Hypothesis 1b suggests, for manufacturing firms increased asset specificity was positively related to wholly owned mode use. However this relationship was not statistically significant at the 0.05 level. Further, as was suggested in Hypothesis 3b, for manufacturing firms, increased behavioural uncertainty was related to the use of wholly owned modes of entry; this relationship was not statistically significant at the 0.05 level. For manufactures only two control variables were statistically significantly related to mode choice at he 0.05 level or better. Manufacturing firms with greater risk propensity (p < 0.05) preferred wholly owned modes of entry as did manufacturing firms with greater CEE experience (p < 0.05). The other control variables (trust propensity, the interaction term (EUAS), firm size, and legal restrictions) were not statistically significantly related to mode choice at the 0.05 level for manufacturing firms. DISCUSSION, LIMITATIONS AND RECOMMENDATIONS Previous transaction cost based international entry mode studies’ results differ depending on whether the study examined manufacturing or service firms (Anderson and Coughlan, 1987; Erramilli and Rao, 1993; Gatignon and Anderson, 1988; © Blackwell Publishing Ltd 2003
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Hennart and Reddy, 1997). We conjectured that these observed differences might be the result of service firms and manufacturers responding to different components of TCE. More specifically, we hypothesized: (1) service firm mode choices would be influenced primarily by behavioural uncertainties (because of the people intensive nature of services); while (2) manufacturing firm mode choices would be primarily influenced by environmental uncertainties (because of manufacturing’s capital intensive nature). Service Firm Mode Choice As hypothesized, we found that services mode choice was influenced by behavioural uncertainty and asset specificity. We found that service firms perceiving high levels of behavioural uncertainty in the target market preferred joint venture modes of entry. This result supports previous work done by Fladmoe-Lindquist and Jacque (1995), Agarwal and Ramaswami (1992), Carney and Gedajlovic (1991), and Bowen and Jones (1986). Second, we found that, for service firms, asset specificity had a significant impact on mode choice. Service firms making high asset specific investments preferred wholly owned modes of entry (possibly to decrease the chances of opportunism and dissemination of competitive advantage). These results provide empirical support for Williamson’s (1991, 1993) TCE theory. Furthermore, we found a positive sign for environmental uncertainty, indicating that service firms entering high environmental uncertainty markets preferred wholly owned modes of entry. As in previous service firm research (Agarwal and Ramaswami, 1992; Erramilli and Rao, 1993) the relationship between environmental uncertainty and mode choice was not statistically significant at the 0.05 level. In addition: (1) we found service firms from high trust propensity cultures preferred joint venture modes, as suggested by Erramilli (1996) and Chiles and McMackin (1996). (2) Similar to Erramilli and Rao (1993), we found that larger service firms preferred wholly owned modes. (3) As suggested by Erramilli (1991), service firms with more region specific experience preferred wholly owned modes of entry, while (4) firms perceiving higher levels of legal restrictions preferred joint venture modes of entry, as suggested by Anderson and Coughlan (1987). Finally, we found neither risk propensity nor the interaction between environmental uncertainty and asset specificity (EUAS) to be related to mode choice. Hence, for service firms the people-oriented aspects of FDI, behavioural uncertainty and trust propensity, as well as asset specificity appear to drive mode choice while the investment related aspects of FDI, environmental uncertainty and risk propensity, do not appear to be as important.
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Manufacturing Firm Mode Choice As hypothesized, we found manufacturing firms’ entry mode strategies were related to their perceptions of environmental uncertainty. Because manufacturing entry requires a high financial commitment, firms appeared to prefer joint venture modes when CEE host country environmental uncertainties were high. These findings support the earlier work of Gatignon and Anderson (1988) who also found that (examining US manufacturing firms’ foreign market entries) manufacturing firms preferred joint venture modes in high-risk markets. Second, as in many previous TCE manufacturing studies (Aulakh and Kotabe, 1997; Delios and Beamish, 1999; Gatignon and Anderson, 1988; Hennart, 1991; Hennart and Larimo, 1998; Kim and Hwang, 1992; Taylor et al., 1998), we failed to find a statistically significant relationship at the 0.05 level between asset specificity and mode choice. However, asset specificity was positively signed, indicating a preference for wholly owned modes when asset specific investments are high. What possibly accounts for the differential impact (between service firms and manufacturers) of asset specificity on mode choice? As discussed earlier, previous research suggests that service firms tend to be more people-intensive (Boddewyn et al., 1986; Bowen and Jones, 1986; Erramilli and Rao, 1993) than manufacturing firms (entry into new foreign markets will require high investments in people and relatively low investments in plant, equipment, and inventory). Thus, service firms may be more sensitive than manufactures to people-oriented components of TCE. Asset specificity does not consist solely of people-oriented components; it includes proprietary and dedicated as well as human components. However both of our measures of proprietary and dedicated components of asset specificity are people-intensive.[6] Hence, asset specificity (as measured in our study) tends to be more people-intensive than investment intensive. Thus, we posit that if service firms are more likely to respond to the people-intensive components of TCE, and our measure of asset specificity is more people-intensive than investment intensive, then it is more likely that service firms will respond to asset specificity than will manufacturers. This may explain our findings. Third, we found a positive sign for behavioural uncertainty, indicating that manufacturing firms preferred wholly owned modes when entering high behavioural uncertainty markets. However, as in previous research (Anderson and Coughlan, 1987; Kim and Hwang, 1992), the relationship between behavioural uncertainty and mode choice was not statistically significant at the 0.05 level. In addition: (1) we found that manufacturing firms from home countries with low risk propensity cultures typically preferred joint venture modes in CEE, possibly in order to help to reduce the financial commitments associated with foreign
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entry. These results were similar to those found in Kogut and Singh’s (1988) study of culture and uncertainty avoidance and those suggested by Chiles and McMackin (1996). (2) Similar to Kim and Hwang (1992), wholly owned modes of entry were preferred by manufacturing firms when they had substantial region specific experience. Finally, we did not find trust propensity, the interaction term EUAS, firm size, or legal restrictions to be statistically significantly related at the 0.05 level to mode choice for manufacturing firms. We conclude that manufacturing firm mode choice appears to be driven by investment aspects of FDI, environmental uncertainty and risk propensity, and not as much by the people-oriented aspects of FDI, such as behavioural uncertainty and trust propensity. Limitations This study has several limitations. First, because no complete lists of Dutch, British or German firms doing business in CEE could be located, we attempted to develop a logical sampling frame. As our response indicated, a large portion of the firms surveyed did not make CEE investments. It was therefore not possible to compare respondents and non-respondents (since we could not determine which firms that had not responded had made CEE investment). Hence, we do not know if those included in this study are representative. Second, because we examined only Dutch, German and British firms our findings may not be generalizable to firms from other countries. Third, because our study is cross-sectional, the longitudinal effects of transaction cost variables on entry mode strategy remain unexplored. It may turn out that the relationships outlined in this study change over time, particularly in rapidly changing regions like CEE. Fourth, in this study we used cultural based measures of both control variables risk and trust propensity. Although consistent with prior entry mode research (e.g. Erramilli, 1996; Tse et al., 1997), future studies may wish to develop more situation-specific measures of risk and trust propensity that can more accurately assess the risk and trust propensity involved in international entry mode decision processes. In addition, because we examined firms from only three home countries, the variance in our trust and risk propensity measures was limited. Future studies can resolve this limitation by using individual measures of trust/risk propensity and/or by examining a greater number of home countries. Finally, CEE countries are changing from command-economies to market-based economies. This may result in a different set of entry mode decision criteria than would result in moves between market-based economies. Hence, our findings may not be applicable to entry in less developed or more developed countries. Future efforts examining other target regions may help to determine if our findings are generalizable. © Blackwell Publishing Ltd 2003
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Conclusions Due to the limitations of this study, our conclusions must be considered tentative. However, our findings point to several potential contributions to the literature. First, unlike past TCE entry mode studies, we included all three components of Williamson’s transaction cost economics theory[1] and showed that the unmodified theory appears to be applicable to both service and manufacturing firm entry mode choices. TCE based mode choices are influenced by both environmental and behavioural uncertainties as well as asset specificity, industry type, and trust and risk propensity. Second, instead of suggesting that Williamson’s TCE model needed to be modified to explain service firm mode choice we were able to show that service firms and manufacturing firms appear to react to different components of transaction cost based uncertainty. Service firm entry seems to be driven by peopleoriented measures of uncertainty: asset specificity, behavioural uncertainty, and trust propensity. In contrast, manufacturing firm entry appears to be driven by investment based uncertainties: environmental uncertainty and risk propensity. Third, we included measures of both trust and risk propensity and found that these control variables had a significant impact on service firm and manufacturing firm entry mode choice. Examining both these potential influences on entry mode decision making helps extend our knowledge of: (1) TCE theory; (2) the applicability of the growing literature on trust and its impact on mode choice; and (3) risk taking and decision making. While much more work needs to be done in these areas, this study provides provocative new insights that may generate new ideas for exploring the international decision making capabilities of managers.
Recommendations for Future Research While our findings tended to support the hypotheses, future research efforts may wish to focus on a number of unexamined issues. First, trust behaviour is now recognized as an important component of joint venture modes of entry (Blois, 1999; Zaheer and Venkatraman, 1995). It has been suggested that in the former second world economies, managers and employees developed a strong distrust for authority (e.g. Casson, 1994). Future studies that address trust behaviour, trust propensity, and the changing attitudes about trust may help us gain a better understanding of how trust influences mode choice. Second, the impact of risk propensity on transaction cost mode choice was found to be significant in this study. Future efforts may wish to build on previous scholarship (e.g. Chiles and McMackin 1996; Harrigan and Newman 1990), and provide more extensive theoretical and empirical testing of how risk propensity influences transaction cost based mode choices. © Blackwell Publishing Ltd 2003
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Third, this study includes risk and trust propensity measures as controls for TCE based mode choice decisions. Future research may wish to: (1) expand the measurement of the constructs, especially situation-specific measurements; and (2) examine both theoretically and empirically the moderating effect of trust and risk propensity on TCE based mode choice decisions to see if our findings hold when situation-specific measures are employed. For example, does trust propensity only moderate the impact of behavioural uncertainty on mode choice and/or does it also moderate the impact of environmental uncertainty and asset specificity on mode choice? Similarly, does risk propensity moderate only the impact of environmental uncertainty on mode choice or does it also moderate the impact of behavioural uncertainty and asset specificity on mode choice? Are there differences in the moderating effects of risk and trust propensity between services and manufacturers? Fourth, as in past studies, we assumed manufacturing investments typically were larger than service firm investments. As in past TCE studies (e.g. Aulakh and Kotabe, 1997; Erramili and Rao, 1993; Gatignon and Anderson, 1988; Kim and Hwang, 1992), we included asset specificity to differentiate between different investment requirements within each industry sector. Thus, we included an investment control (of sorts) and still found differences between manufacturing and services. However, future studies may wish to explore the direct impact of investment size on TCE mode choice decisions. Fifth, we examined differences between the two major industrial sectors, services and manufacturing. Future research may wish to build on the work of Anand and Delios (1997) and extend this line of research by examining whether differences between certain types of services or manufacturing firms may also influence TCE based mode choices. Sixth, future studies may also want to address important measurement issues suggested by Rindfleisch and Heide (1997). These include: (1) expanding measures of asset specificity to include brand name capital and temporal specificity; (2) measuring asset specificity using multi-item measures, not single secondary measures; and (3) developing better secondary measures of behavioural uncertainties. Improvements in the measurement of all three TCE variables will help determine the reliability of past TCE entry mode research. Seventh, in this study we controlled for a number of important TCE influences including risk and trust propensity. Future research efforts may wish to include other control variables such as industry type and cultural distance. Dess et al. (1990) suggest that strategic management studies may benefit from including industry controls because: (1) different industries may respond differently to external factors; and (2) controlling for industry effects helps increase the generalizability of findings. Hence, although it was not feasible for us to include industry controls because of a degrees of freedom problem, future research may wish to include industry control variables. In addition, scholars like Shane (1994) have sug© Blackwell Publishing Ltd 2003
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gested that cultural distance may affect TCE perceptions and, hence, international entry mode choice. Future research efforts can build on these concepts by providing both theoretical and empirical insights into the impact of cultural distance on TCE mode choice. Finally, environmental uncertainties, behavioural uncertainties, asset specificity, and entry mode strategy need to be linked to firm performance. As Woodcock et al. (1994) pointed out, for entry mode selection research to be of use to firm managers, the relationship between entry mode selected and performance must be considered. NOTES *Authors are listed alphabetically. [1] Williamson also suggests that frequency of interactions may influence transaction cost based decisions. Entry mode research assumes that transactions are recurrent between parent and subsidiary organizational units, hence consistent with past entry mode studies, no separate measure of frequency is included (Erramilli and Rao, 1993; Kim and Hwang, 1992; Klein et al., 1990). [2] ‘Services are acts or experiences directed toward consumers or their goods whereas products are objects that are possessed’ (Habib and Victor, 1991, pp. 593–4). For purposes of this paper, the term services is used to refer to all types of service providers. Erramilli and Rao (1993) have shown that within this general classification of services there may be some variation in entry mode selection based on the asset specificity of the particular service industry competitive advantage. We therefore include asset specificity as one of our measures. [3] While it is common for studies of manufacturing firms to use unmodified TCE models, service firm TCE models typically have been modified in previous studies (e.g., Erramilli and Rao, 1993; Murray and Kotabe, 1999). [4] An alternative regression analysis was prepared where we replaced the Hofstede based trust and risk propensity measures with dummy variables. The results of this dummy variable based analysis were similar to the results of the regression analysis included in the paper. Because the Hofstede measures provide more information than would dummy variables, we use the Hofstede measures in the paper. [5] The chance rate is calculated (Hennart and Reddy, 1997; Morrison, 1974) with the formula a2 + (1 - a)2, where a is the portion of wholly owned entry modes. [6] Proprietary asset specificity represents a firm’s ability to generate new products or services. This ability tends to be contingent on a firm’s body of knowledge (Grant, 1996). Previous scholarship suggests such knowledge is embedded in people (Hitt et al., 2001; Thompson et al., 2001). This research suggests that a firm’s proprietary asset specificity is fairly people dependent. Baetjer (2000) suggests that tacit knowledge can be embodied in tools. If new tools can be developed, protected from imitation and marketed as new products, then it could be argued that, in this instance, tacit knowledge may be embedded in the capital product rather than in human beings. Dedicated asset specificity refers to investments made in general purpose assets for a transaction. In our study general dedicated assets were measured as the level of technical resources available within the firm. Technical resources may be both people-intensive (knowledge) and investment intensive (physical equipment).
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