Contextual influences on international subsidiaries' product technology strategy

Journal of International Management 10 (2004) 259 – 286

Contextual influences on international subsidiaries’ product technology strategy Brent B. Allred *, K. Scott Swan

1

School of Business Administration, The College of William & Mary, Williamsburg, VA 23187, USA Available online

Abstract We seek to test a broad range of factors that influence the technology sourcing decision of international subsidiaries in acquiring product technology from outside the firm (i.e., outsourcing) versus internal development. A regression model, used to analyze data from 187 international subsidiaries in six industries and with parents based in 14 countries, identifies the environmental, strategic, configurational, and resource endowment factors that influence the technology sourcing decision. Specifically, the level of product dynamism in the subsidiary’s industry and the distance between the subsidiary’s primary marketing and R&D operations are associated with a greater reliance on outsourcing. A differentiation goal, a low-cost goal, along with the level of the subsidiary’s human and financial resources are associated with a greater reliance on internal development. D 2004 Elsevier Inc. All rights reserved. Keywords: Outsourcing; International subsidiaries; Product technology sourcing strategy

1. Introduction Technology sourcing research is beginning to show signs of maturity. It has begun to move past the point where the field is sustained by a small number of researchers, theories, and functional perspectives. While much has changed in recent years, the objective of a technology sourcing strategy remains to guide the firm in acquiring, developing, and applying technology for competitive advantage. The first step in creating a technology sourcing strategy is to focus attention on those capabilities where * Corresponding author. Tel.: +1-757-221-3266; fax: 1-757-221-2937. E-mail addresses: [email protected] (B.B. Allred), [email protected] (K.S. Swan). 1 Tel.: +1-757-221-2860; fax: +1-757-221-2937. 1075-4253/$ - see front matter D 2004 Elsevier Inc. All rights reserved. doi:10.1016/j.intman.2004.02.003

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the firm seeks a distinctive competitive advantage (Conner, 1991; Dierickx and Cool, 1989; Mahoney and Pandian, 1992). The technology acquisition decision has traditionally examined the firm’s choice either to internally innovate or to acquire technology from outside sources (Fayerweather, 1969; Kotabe, 1992; Murray et al., 1995; Noori, 1980). This technology reliance decision has become progressively more complex with the increased globalization of the worldwide economy. While the internationalization of R&D (Devinney, 1995; Peng and Wang, 2000; Teigland et al., 2000) and international technology management has moved up on the research agenda (Cantwell and Mudambi, 2000; Bartholomew, 1997; Chiesa, 2000; Gassman and von Zedtwitz, 1998; Kotabe and Swan, 1995; Kuemmerle, 1999; McDonough et al., 2001; Medcof, 1997; Meyers et al., 1999; Swamidass, 1993), there is a need for further exploration, integration of current quantitative research, and incorporation of multiple theoretical developments. Technology sourcing research contains ambiguities that require further investigation into the contextual influences on the relative mix of internal development and outsourcing of technology. One view warns against external technology reliance. The costs and consequences of global outsourcing include coordination difficulties, functional mismatches, and external dependence, along with the gradual loss of internal design, manufacturing, and other knowledge-based capabilities (Kotabe and Helsen, 1999). As a result, competitive advantage is more likely to be improved by the development of unique organizational competencies through such means as the accumulation of proprietary technology, rather than by opportunistic deal making (Barney, 1991; Cantwell, 1989; Conner, 1991; Hunt, 1997; Pavitt, 1990; Wernerfelt, 1984). In support of this conclusion, the internal sourcing of key components has been positively associated with market performance (Kotabe and Murray, 1990; Lanctot and Swan, 2000). An alternative view of technology sourcing indicates that an international firm faces a market-oriented imperative to incorporate the ‘‘best’’ technology. Increasingly rapid technological changes lead to a greater degree of external acquisition as even large firms find themselves unable to maintain their own research efforts simultaneously along all technological fronts (Marquis, 1988; Noori, 1980). Subsequently, international firms may resort to acquiring technology from outside sources, although there are potentially debilitating long-term consequences (Ohba, 1996). The purpose of this study is to further develop theoretical justification for a wide range of contextual factors that influence the product technology reliance decision. These factors influence whether the subsidiary will have more of a product innovation mandate and responsibilities or more of a traditional role in downstream activities like sales, service, and assembly. ‘‘[A] subsidiary having a global subsidiary mandate is expected to take a more dominant R&D role for a given product or product line’’ (Roth and Morrison, 1992, p. 721). With the combined theoretical perspectives of transaction cost economics (TCE) and the resource-based view (RBV), we propose that the context factors limit or support the attractiveness of subsidiary product innovation, therefore influencing the technology sourcing decision to either outsource or internally develop product technology.

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2. Sourcing influences and outcomes In an attempt to resolve some past research limitations, we draw upon two theoretical bases: TCE (Williamson, 1985) and the RBV of the firm (Barney, 1991; Hunt, 1997; Wernerfelt, 1984). From both perspectives, hierarchical control systems exist to generate competitive advantages (Barney, 1991). They have an advantage over market control in terms of exploiting asset interdependencies (Conner and Prahalad, 1996). Multinational corporations (MNCs) exist because they have a superior ability to transfer and exploit knowledge within the corporate context over market mechanisms (Gupta and Govindarajan, 1991). The choice of technology sourcing strategy is influenced by the minimization of costs (the focus of TCE) and the opportunity for sustainable competitive advantage (the focus of RBV). TCE and RBV generally complement each other but offer alternative perspectives and concerns (Conner, 1991; Mahoney, 2001; Steensma and Corley, 2001). The general objective of TCE is that the organization of economic activity is driven by the minimization of costs of production, search, information, monitoring, and enforcing contractual performance (Robins, 1987). The superior ability of MNCs to engage in internal knowledge transfer does not imply that such knowledge transfers are necessarily easy, successful, or routine. Because of a range of possible barriers (e.g., imperfect information, bounded rationality, absorptive capacity, tacitness, asset specificity, and causal ambiguity), resources and skills are difficult to imitate and transfer (John and Weitz, 1988; Nelson and Winter, 1982). The inability of management to distinguish prospective opportunistic behavior from cooperative behavior pushes firms toward internalization (Peteraf, 1993; Schroeder et al., 2002; Williamson, 1985). While the environment presents external constraints, the RBV focuses on the MNC’s imperfect ability to leverage its resources into positional advantages (i.e., generically differentiation and low cost) and produce positive outcomes, e.g., improve relative market share, profitability, loyalty, and satisfaction (Day and Wensley, 1988). The RBV portrays the value of a resource, capability, or knowledge as derived from the dynamic interplay of market forces (Amit and Schoemaker, 1993; Collis and Montgomery, 1995; Dickson, 1992; Hunt, 1997; Marquis, 1988; Wernerfelt, 1984). The nature of the firm’s resources and capabilities are critical in both creating and sustaining positional advantages. For a product mandate to be effective, it must be built on distinctive capabilities of the subsidiary (Birkinshaw, 1996). The RBV balances TCE’s focus on minimization of costs by portraying the firm as a positive creator of unique value (Conner, 1991).

3. External technology reliance decision drivers An extensive review of the literature as well as managerial practice suggest that environmental, strategic, configurational, and resource endowment factors affect the technology reliance decision (Kotabe and Murray, 1990; Lanctot and Swan, 2000; Murray et al., 1995; Porter, 1985; Swamidass, 1993). Subsequently, we selected important variables within each of these factors to explore their relative importance. We suggest

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that while TCE and RBV are developed for firm-level analysis, these concepts can also be applied at the subsidiary level (with justified concern of where performance is maximized). Issues regarding internalization and the creation of positional advantages are also of concern to subsidiary managers. In fact, the intricacies and implications of the technology sourcing decision are heightened for a MNC’s subsidiary because they must consider both inter- and intrafirm issues for knowledge transfer in an international setting (Mudambi, 2002). This assumes that subsidiary management is at least partly able to make independent decisions (Birkinshaw and Morrison, 1996). Fig. 1 depicts the proposed relationships of the predictors to external product technology reliance. 3.1. Environmental factors 3.1.1. Product technology dynamism Volatile industries are generally characterized by increasing speed and magnitude of technological change (Bettis and Hitt, 1995). Marquis (1988) and Noori (1980) suggest that greater levels of technological change are associated with increased external reliance. It may be unavoidable to rely on the market for technology that is quickly changing, often

Fig. 1. Product technology sourcing model.

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from innovations outside the industry (Cooper and Schendel, 1976). Subsidiaries may also be forced, because of resource limitations, to become more reliant on external sources for technology. From the RBV, the development or acquisition of critical resources can strengthen the subsidiary’s relative competitive position (Peteraf, 1993). When product designs are fluid, investments in product technology tend to focus on differentiation. Although the subsidiary typically retains the greatest control with internally developed technology, it may be forced to rely on external sources to accommodate the speed and flexibility needed in highly dynamic environments. As the industry’s core product technology becomes more established and less dynamic, investments shift away from product technology to concentrate more on manufacturing process technology (Kotabe, 1992). TCE also supports this perspective because the subsidiary is expected to focus on developing and acquiring assets in the most efficient manner. Environments high in product technology dynamism are characterized by uncertainty and risk. Internal technology development is often limited or curtailed as a result of increasing costs and indeterminate payoffs. A highly dynamic product technology environment results in less motivation to develop technology internally and subsequently utilize more efficient external sources. Therefore, Hypothesis 1A. As product dynamism increases, the reliance on external product technology increases. 3.1.2. Competitive intensity Competitive intensity is high when competitor actions contribute to market uncertainty and customer needs are constantly in flux (Dickson, 1992). In these circumstances, there are typically simultaneous pressures to reduce costs, come to market quickly, and introduce innovative products. From TCE and RBV, subsidiaries seek to reduce costs and risks through increased flexibility and cooperative arrangements. In uncertain environments, often found in highly competitive situations, advantage is gained through increased knowledge assets and decreased fixed assets (Miller and Shamsie, 1996). Although greater technology reliance outside the subsidiary offers more options and flexibility, with less commitment to fixed assets, the associated costs must be considered and a balance struck. From the TCE perspective, competitive intensity may increase barriers to choosing good technology partners. Because the organization of economic activity is driven by the minimization of the costs of production, search, monitoring, and contractual enforcement, the firm must protect itself from external opportunistic behavior (Williamson, 1985). Even with these concerns, a highly competitive marketplace may not allow the subsidiary the time or resources to efficiently develop its own product technology. Thus, greater competitive intensity promotes the use of cooperative and other external arrangements. Even if these cooperative arrangements may be short-term or opportunistic, the necessity for quick response, increased options, and greater flexibility encourages external product technology acquisition. Increased technological changes can lead to heightened external reliance to ameliorate uncertainty and risk (Marquis, 1988; Noori, 1980).

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Although the use of partners outside the firm may result in a loss of control or autonomy, gains in flexibility and responsiveness, as well as access to standard-setting technology, may offset these concerns in a highly competitive environment. Therefore, Hypothesis 1B. As competitive intensity in an industry increases, the reliance on external product technology increases. 3.2. Strategic factors In addition to considering the influence of environmental factors on the technology reliance decision, internal factors should also be evaluated. The RBV suggests that knowledge and assets must be converted to a positional advantage that offers the prospect of positive performance outcomes (Barney, 1991; Day and Wensley, 1988). Subsidiaryspecific strategic priorities are directed by the management through the specification of goal congruence to convert resources to positional advantages (Francis, 1980; Roth and Ricks, 1994). Two generic positional advantage goals, differentiation and low cost, drive the strategic development or adoption of new product technologies (Day and Wensley, 1988; Porter, 1985). By adopting a differentiation goal, the subsidiary attempts to offer products that are of higher value (e.g., more features, higher quality, greater customer satisfaction). A low-cost goal commits the subsidiary to producing and distributing products at a relatively low cost compared with competition. We posit that for multinational organizations, these goals are both possible and increasingly simultaneously pursued (Bower and Hout, 1988; Hayes et al., 1988; Wheelwright and Clark, 1992). Accordingly, they are not necessarily opposite ends of the same scale (Webster, 1992). 3.2.1. The differentiation goal When creating and sustaining positional advantage based on differentiation, internal development improves inimitability and the proprietary nature of the product, while external sourcing typically indicates that the technology is available to competition (Dierickx and Cool, 1989). Internally developed product technology allows the subsidiary to retain control and maintain competitive advantage, particularly for key technologies (Kotabe and Murray, 1990). Because competitors generally have access to the same technology market, the primary source for differentiation-based competitive advantage is through internal development. Additionally, the reliance on externally sourced technology is limited by its association with increased uncertainty, incomplete information, bargaining power, and limits on transferability (Caves et al., 1983). With a differentiation goal, the subsidiary establishes a positional advantage through unique product qualities that provide customer value. Technology development can focus on improving product design and performance features, expand end uses and applications, enhance quality and reliability, and result in a first-mover advantage. At best, external acquisition of technology offers a second-mover position. Accordingly, within the differentiation goal context, internally developed product technology is expected to be most beneficial. Therefore, Hypothesis 2A. As the importance of a differentiation goal increases, the reliance on external product technology decreases.

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3.2.2. The low-cost goal As mentioned above, TCE and RBV suggest that it is difficult to maintain a longterm advantage from acquiring product technology on the market (Dierickx and Cool, 1989). The successful implementation of a low-cost goal requires excellent value-chain management that results in cost minimization within all development and manufacturing activities (Porter, 1985). Subsequently, subsidiaries with a low-cost goal would likely develop internal technology capabilities. While not all product technology is created within, it must all be incorporated into an existing stream of innovation. This adaptation becomes part of the ongoing process of technology generation (Hayes et al., 1988). In support, Capon and Glazer (1997) suggest that internal development of technology is cheaper than external acquisition. Jelinek and Schoonhoven (1990, p. 426) observe that ‘‘where the new technology is central, or provides some crucial advantage, the company may be compelled to purchase it from others perhaps at an exorbitant price (italics added) or exit its chosen markets.’’ Caves et al. (1983) state that because of uncertainty, incomplete information, and limited numbers of buyers, developers of technology could receive much less for their technology than it is worth and be unwilling to sell. Accordingly, buyers may not realize the full benefits of the acquired innovation (Meyers et al., 1999), and successful sellers have their own objectives to meet (Athaide et al., 1996). From a TCE perspective, imperfect markets for innovation may allow technology sellers to appropriate all value or create an atmosphere where buyers may be unwilling to pay market value because of incomplete information and limits on transferability. Subsequently, Hypothesis 2B. As the importance of a low-cost goal increases, the reliance on external product technology decreases. 3.3. Configuration factors Firms that internationalize their operations tend to first enter countries that are either geographically or culturally proximate (Buckley and Casson, 1976; Johanson and Vahlne, 1977). Geographic proximity generally allows for a reduction of transportation and coordination costs. Cultural proximity may lead to improved communication and understanding between operations, even if there is a significant spatial distance between them. With both factors, national cultural differences may affect the technology sourcing strategy and location of R&D operations (Jones and Davis, 2000). 3.3.1. Spatial distance Configuration is concerned with where an organization’s activities are located throughout the world and how they interrelate. Schoenberger (1987, p. 204) argues that ‘‘the spatial separation of the conception of the product and the production process (i.e., design and engineering) from actual production leads to serious problems of implementation and adaptation.’’ The RBV suggests that patterns of communication are influenced by physical location (Allen, 1977; Stock et al., 1996). Communication is hindered as spatial and cultural separation increases between key business units (Asakawa, 1996; Nobel and

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Birkinshaw, 1998). Cooperation between functional areas influences the performance of new product development (Olson et al., 2001). Howells (1990) maintains that the decision of where to locate R&D laboratories has been influenced by the requirements for effective internal communication between firm functions. Therefore, a far-flung configuration of operations may alter the technology reliance decision by increasing the difficulty and, thus, the cost of coordinating and integrating the development, manufacturing, and promotion of a product. Although communication and local understanding are important for a product’s success, they are less effective at greater distances between internal operations. This becomes particularly salient when functional activities are internationally dispersed. As distances among activities within a subsidiary increase, external product technology acquisition, likely locally acquired and adapted, becomes more appealing. Thus, Hypothesis 3A. As the spatial distance separating the key U.S. marketing operations from R&D operations increases, the reliance on external product technology increases. 3.3.2. Cultural distance In addition to considering the influence of the spatial distance between operations, cultural differences or distance may also affect the reliance on internal development versus outsourcing of technology. Cultural distance should not be confused with geographic distance (Shenkar, 2001). In light of recent advances in transportation and telecommunication technology, the challenges associated with increased spatial distances between business activities may be diminishing. The discussion of O’Grady and Lane’s (1996) of The Psychic Distance Paradox highlights the fact that locating operations in countries that are psychically close does not necessarily make them easy to manage. Even with these technology advances, cultural barriers can still exist across international subsidiaries. Where technology may improve the speed and accuracy of communication, language, and cultural obstacles remain. An organization with operations in culturally distanced countries encounters two problems. First, when coordinating and integrating activities, the ability to communicate and gain understanding is diminished. Second, culturally induced mindsets and attitudes may raise the barriers for cooperation, even when an adequate understanding is achieved. Kogut and Singh (1988) found that cultural distance influenced a firm’s mode of entry into other countries. Organizations with operations that have greater cultural distances between them are expected to outsource technology acquisition from either local providers or from sources in countries that are more culturally similar. Therefore, Hypothesis 3B. As the cultural distance separating the key U.S. marketing operations from R&D operations increases, the reliance on external product technology increases. 3.4. Resource endowment factors To ‘‘attain and keep profitable market positions depends on the ability to gain and defend advantageous positions in underlying resources’’ (Conner, 1991, p. 122). Both

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financial and nonfinancial resources have an ‘‘instrumental role in achieving positional advantages’’ (Kerin et al., 1992, pp. 40– 41). Furthermore, the first-mover literature suggests that unless the firm has substantial resources (or can gain access them), it is unlikely to convert environmental opportunities into long-term positional advantages (Robinson et al., 1992; Christensen, 1997; Lieberman and Montgomery, 1998). These resources are the competencies and competitive ingredients used to build product features that appeal to the marketplace (Abernathy and Clark, 1985, p. 57). Teece (1987, p. 70) observes that the possession of complementary asset resources is one of the fundamental building blocks that explain the distribution of innovation outcomes and that ‘‘in almost all cases, the successful commercialization of an innovation requires that the know-how in question be used in conjunction with other capabilities or assets.’’ Finally, resources are important to achieving, through positional advantage, successful performance outcomes (Day and Wensley, 1988; Hunt, 1997). More abundant, complementary resources would be expected to enable a subsidiary to better develop its own technology (Hunt, 1997; Teece, 1987). For example, while the level of human resources provides the intellectual skills needed for technology development, financial resources increase the ability to acquire other critical resources that can be utilized for internal technology development. In addition, as the stock of R&D resources increases, the possession of complementary capabilities is more likely to allow the development of the desired product technology. In sum, as the subsidiary garners the possession of essential human, financial, and R&D resources, it is better able to develop technology internally. Consequently, we should expect that: Hypothesis 4A. As the level of human resources increases (i.e., number of employees), the reliance on external product technology decreases. Hypothesis 4B. As the level of financial resources increases, the reliance on external product technology decreases. Hypothesis 4C. As the level of R&D resources increases, the reliance on external product technology decreases.

4. Data collection and instrument refinement 4.1. Sample Due to the nature of this study, subsidiaries competing in manufacturing industries were the primary target. These firms must continually invest in product technology and face the decision whether to internally develop or outsource their technology acquisition. A twopart data collection process was adopted for this study. First, 1034 U.S. subsidiaries were randomly drawn from the International Directory of Corporate Affiliations. This directory identified approximately 22,000 parent companies throughout the world, with over 50,000 subsidiaries based in the United States. A sampling frame was adopted that selected roughly 2% of the population, or 1 in every 50. Of the initial sample, 67 undeliverable

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letters were returned by the postal service, producing an effective sample of 967. In 1995, a total of 298 executives and managers with significant knowledge of and responsibility for technology was identified. Second, surveys were sent to this group of 298 individuals. A second identical survey was sent to nonrespondents after three weeks. A total of 188 respondents returned the questionnaire. One response was excluded due to incomplete data, leaving a final sample of 187. The response rate was 62.8% (187/298) from those agreeing to participate, or 19.3% (187/967) of the effective sample. The respondents were asked to indicate the country in which their parent company was located and in what industry they primarily competed. From this, the subsidiaries fell into seven broad industrial categories and had parent companies located in 14 different countries. A breakdown of the sample with the country location of parent, size, as measured by sales, and industry is found in Table 1. From the 187 usable questionnaires, the analysis of key constructs of early and late respondents yielded no significant differences, which provides an indication that nonresponse bias is not present (Armstrong and Overton, 1977). Because the data Table 1

Subsidiary characteristics (N = 187) Parent home country United States Canada Japan Taiwan Australia Germany United Kingdom France Switzerland The Netherlands Italy Denmark Not reported

118 2 24 1 3 18 7 3 2 2 1 1 5

Subsidiary’s U.S. sales >US$500 million US$100 M – $499M US$10M – $99M < US$10M Not reported Average sales

18 59 68 28 14 US$321 million

Industry Breakdown: Electronics and electric equipment industry Food and related products industry Industrial equipment/machinery industry Fabricated metal products industry Petroleum and coal products industry Transportation equipment industry Other/not reported

39 16 18 22 47 14 31

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for this study were obtained from a single survey, common method variance is possible (Crampton and Wagner, 1994; Lindell and Whitney, 2001). Various procedures were employed to address these concerns.2 Results from the tests indicate no bias from common method variance in the data. Table 2 includes the mean responses, standard deviations, and a correlation matrix. A summary of the list of measures included in the final scales is available in Table 3, along with the composite reliabilities and Cronbach alphas. 4.2. Instrument development and refinement Multi-item scales were adapted from literature and reflect input from managers and academics. We examined variables for outliers and other departures from normality. No significant outliers, skewness, or kurtosis were found. We subsequently employed confirmatory factor analysis (CFA) to assess validity, unidimensionality, and reliability across a single CFA for all items involved in data reduction. A comparative fit index (CFI) above 0.90, a Tucker – Lewis index (TLI) above 0.90, a root-mean square error of approximation (RMSEA) below 0.10, and v2/df ratio of less than 3.0 are considered indications of good fit (Bagozzi and Yi, 1988; Bentler and Bonett, 1980; Carmines and McIver, 1981; Hair et al., 1998). The overall fit indices for the CFA (CFI: 0.934, TLI: 0.925, RMSEA: 0.050, v2/df: 1.463) indicate that the CFA achieved acceptable fit. Once the overall fit is determined, each individual scale’s reliability is estimated by computing its composite reliability (Werts et al., 1974) and Cronbach alphas (see Table 3). 4.2.1. Convergent and discriminant validity The CFA obtained acceptable convergent validity with individual item loadings in the range of .50– 1.00 for all but 4 of 21 items. All loadings are significant at the P < .001 level. The average composite reliability of the scaled measures is 0.748 and the range is between 0.586 for differentiation goal and 0.866 for product dynamism. Careful content validation, the developmental nature of the scales, and the overall fit of the CFA model provide justification for accepting the measures. 2

As suggested by Podsakoff and Organ (1986), Harman’s one factor test was conducted. In this test, the variables of interest are entered into a factor analysis. ‘‘The basic assumption of this technique is that if a substantial amount of common method variance is present, either (a) a single factor will emerge from the factor analysis, or (b) one ‘general’ factor will account for the majority of the covariance in the interdependent and criterion variables’’ (Podsakoff and Organ, 1986, p. 536). The factor analysis yielded eight factors, with the largest explaining only 16.17% of the variance, indicating that one general factor did not exist. As a second test, a partial correlation procedure was employed (Podsakoff and Organ, 1986). For this test, the first unrotated factor from the previous procedure is entered into the regression models as a control variable. This factor is assumed to ‘‘contain the best approximation of the common method variance if it is a general factor on which all variables load’’ (Podsakoff and Organ, 1986). In a regression analysis for both models in this study, there was no significant change in the R2 when this factor is entered stepwise into the regression equation. Another way to reduce the likelihood of common method variance is in the survey design. Including reverse scored items can reduce the problems of acquiescence and other biases when the instrument is being completed (Lindell and Whiney, 2001). The survey instrument has numerous items across constructs that were reverse coded, thus satisfying this criteria. In fact, five of six constructs contained at least one reverse-coded item, and over one third of all items in these constructs were reversed coded.

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Variable 1. External product technology sourcing 2. Parent region location (North America) 3. Parent region location (Europe) 4. Parent Region Location (Asia/Pacific) 5. Electronics and electric equipment Ind. 6. Food and related products industry 7. Industrial equipment/ machinery industry 8. Fabricated metal products industry 9. Petroleum and coal products industry

Mean S.D. 1

2

3

4

5

6

7

8

9

2.04 0.82

1.00

0.64 0.49

0.07

1.00

0.18 0.39

0.06

0.63***

1.00

0.15 0.36

0.06

0.56***

0.20**

1.00

0.21 0.41

0.16*

0.06

0.14

0.19**

1.00

0.09 0.28

0.06

0.21**

0.10

0.19**

0.16*

1.00

0.10 0.30

0.00

0.06

0.13

0.09

0.17*

0.10

1.00

0.12 0.32

0.01

0.07

0.00

0.11

0.19**

0.11

0.12

1.00

0.25 0.43

0.03

0.15*

0.05

0.11

0.30***

0.18*

0.19**

0.21**

10

1.00

11

12

13

14

15

16

17

18

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Table 2 Correlations and descriptive statistics

N = 187. * P < .05. ** P < .01. *** P < .001.

0.07 0.26

0.05

0.09

0.08

0.01

0.15*

0.09

0.09

0.10

0.17*

1.00

3.18 0.97

0.17*

0.04

0.04

0.00

0.20**

0.05

0.12

0.20**

0.05

0.07

1.00

3.75 0.78

0.02

0.07

0.01

0.07

0.04

0.03

0.03

0.05

0.16*

0.02

0.12

1.00

3.56 0.48

0.21**

0.14

0.05

0.14

0.06

0.10

0.06

0.01

0.05

0.06

0.20**

0.19**

1.00

2.88 0.84 2.14 3.02

0.07 0.22**

0.05 0.20**

0.06 0.05

0.04 0.24**

0.07 0.01

0.08 0.06

0.00 0.11

0.09 0.08

0.07 0.07

0.17* 0.08

0.06 0.01

0.29*** 0.08

0.41*** 0.16*

1.00 0.03

1.00

10.61 19.89

0.11

0.71***

0.04

0.87***

0.19**

0.12

0.05

0.09

0.12

0.03

0.05

0.02

0.10

0.05

0.23**

1.00

6.00 1.74

0.15*

0.23**

0.22**

0.11

0.12

0.03

0.02

0.12

0.12

0.25***

0.10

0.14*

0.19**

0.24***

0.06

0.16* 1.00

3.27 1.14

0.22**

0.12

0.09

0.07

0.03

0.10

0.03

0.19**

0.13

0.08

0.09

0.06

0.20**

0.08

0.07

0.11 0.07 1.00

3.34 0.90

0.17*

0.13

0.02

0.12

0.04

0.24**

0.03

0.09

0.14*

0.04

0.05

0.03

0.30***

0.07

0.05

0.12 0.12 0.58***

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10. Transportation equipment industry 11. Product technology dynamism 12. Competitive intensity 13. Differentiation goal 14. Low-cost goal 15. Spatial distance to primary R&D ops. 16. Cultural distance to primary R&D ops. 17. Human resources (employees logged) 18. Financial resources 19. R&D resources/ capabilities

271

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Table 3

Results of estimating structal equation model Latent variables (composite reliability/Cronbach alpha) External product technology sourcing (0.825/0.828) Y1: My business unit develops the product technology it requires through its own research.a Y2: My business unit spends more on developing its own product technology than on purchasing it from other companies.a Y3: My business unit’s products are based primarily on product technology we developed.a Y4: We are heavily dependent on other companies to supply us with new product technology. Y5: We rely on external sources to provide us with new generations of the product technology we utilize. Y6: Percentage your business unit relies on external sources for product technology (product technology refers to technology that leads to the creation of new products).b Product technology dynamism (0.866/0.864) Questions specifically about the degree of change in product technology in your business and industry. X7: The product technology in our industry is changing rapidly. X8: Product technology changes provide big opportunities in our industry. X9: Product technology developments in our industry are rather minor.a X10: A large number of new product ideas have been made possible through product technological breakthroughs in our industry. Competitive Intensity (0.735/0.718) Questions about the competitive intensity of the industry in which your business unit competes. X11: Competition among firms is based more on price that on product design. X12: Competition in our industry is cut-throat. X13: Price competition is the hallmark of our industry. Differentiation goal (0.586/0.607) X1: Please indicate the degree to which high product quality is important to your business unit.c X2: Rank of high product quality as a business unit goal from 1 to 3 (1 being the most important). a,b X3: Rate your products on each of the following quality and value dimensions relative to your three major competitors during the last 12 months—customer satisfaction.d

Unstandardized parameter estimate

Standardized parameter estimate

0.766

0.720

1.000

0.825

0.893

0.766

0.774

0.679

0.532

0.461

0.509

0.491

0.957

0.793

0.836

0.728

0.964

0.764

1.000

0.862

0.611

0.612

0.510 1.000

0.566 0.880

0.749

0.563

1.000

0.724

0.662

0.414

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Table 3 (continued) Latent variables (composite reliability/Cronbach alpha) Differentiation goal (0.586/0.607) X4: Rate your products on each of the following quality and value dimensions relative to your three major competitors during the last 12 months—number of unique product features.d Low-cost goal (0.684/correlation=0.607) X5: Please indicate the degree to which low product cost is important to your business unit.c X6: Rank of low product cost as a business unit goal from 1 to 3 (1 being the most important). a,b R&D resources (0.790/correlation=0.650) Questions about the strength of resources relative to top three competitors during the past 12 months. X13: Stock of product technology.d X14: R&D capabilities.d

Unstandardized parameter estimate

Standardized parameter estimate

0.508

0.319

0.740

0.579

1.000

0.850

0.961 1.000

0.721 0.890

All items are Likert 1 – 5, 1 = strongly disagree to 5 = stongly agree, unless otherwise noted. a Reverse scored item. b Number requested. c 1 = Least important to 5 = most important. d 1 = Much lower to 5 = much higher.

To establish discriminant validity, the average variance extracted for each factor is compared with and exceeded the squared correlations between that factor and all other factors (Fornell and Larcker, 1981). In addition, a pairwise comparison of the latent factors indicates that all interfactor correlations are significantly different from 1.00 (Challagalla and Shervani, 1996). Thus, the analysis provides support for discriminant validity of these constructs. 4.2.2. Measures The independent variable, product technology sourcing, assesses the degree of reliance on external sources for product technology. This construct is comprised of six measures that seek to capture internal development (reverse scored) versus external reliance on technology. The composite reliability for product technology sourcing is 0.825. Product technology dynamism taps into the degree and pace of change in product technology in an industry. This construct is made up of four items and has a composite reliability of 0.866. Competitive intensity deals with the intensity of competition that exists in a given industry. This construct has three items and has a composite reliability of 0.734. The differentiation and low-cost goals are made up of four and two items, respectively. These constructs attempt to capture the emphasis on strategic goals to develop products that emphasize either differentiation or low costs. The differentiation and low-cost goals have composite reliabilities of 0.586 and 0.684, respectively.

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Spatial distance between marketing and R&D operations is an individual measure of the logged distance between the primary U.S. marketing operations and primary R&D operations. Cultural distance between marketing and R&D operations is calculated following Kogut and Singh (1988).3 Human resources is measured as a logged function of the number of employees. Financial resources is a single measure of the strength of the subsidiary’s financial resources, compared with the three major competitors. R&D resources captures the R&D capabilities and stock of product technology. This construct is made up of two items and offers a composite reliability of 0.790. 4.2.3. Control variables Parent region location was included as a control variable because parent corporate location influences strategy (Gupta and Govindarajan, 1991). The RBV suggests that patterns of communication between divisions of the firm and the parent are influenced by physical location and cultural separation (Allen, 1977; Asakawa, 1996; Nobel and Birkinshaw, 1998; Stock et al., 1996). Ohmae (1995) suggests that the influence of parent location would be regional rather than national. Three dummy-coded controls are included for parent region location that follow the triad classifications of Ohmae (1995; North America, Europe, and Japan/Asia-Pacific). An other category is excluded from the analysis to avoid perfect collinearity among the parent region location controls. Industry effects are also used as controls in the analysis. The industry is initially classified at the two-digit SIC code level, as identified by the survey respondent. From this, seven industrial categories are identified and the miscellaneous category is removed from the analysis to avoid perfect collinearity (see Table 1). In testing for multicollinearity, variance inflation factors (VIF) for the measures in this study averaged 1.42 and ranged from 1.14 to 2.03, well below the threshold levels of 10.0 (Hair et al., 1998). Thus, multicollinearity does not seem to be an issue.

5. Results The premise of this study is to understand a broad range of factors’ influence and importance on the product technology reliance decision. Using hierarchical regression techniques, the product technology sourcing model is significant ( P < .001) and has an R2 of .275. We find general support for the model. Six of the nine product technology sourcing hypotheses are supported. Below, we present the results and follow with discussion and implications (see Table 4). 3 The cultural distance measure of Kogut and Singh (1988) use the original cultural dimensions of power distance, uncertainty avoidance, masculinity, and individualism of Hofstede (1980). It is calculated by taking the average of the squared difference between the two country’s scores on a given dimension divided by the variance of the index of the dimension. Precise country location of the subsidiary’s primary marketing and R&D operations were not identified in the survey. Therefore, we assumed that the primary marketing operations are at the subsidiary HQ and the primary R&D operations are at the parent HQ and use this as a proxy for calculating the cultural distance measure.

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Table 4

Regression analysis for external product technology sourcing model Variables

External product technology sourcing Base model

Constant Parent region location (North America) Parent region location (Europe) Parent region location (Asia/Pacific) Electronics and electric equipment industry Food and related products industry Industrial equipment/machinery industry Fabricated metal products industry Petroleum and coal products industry Transportation equipment industry Product technology dynamism Competitive intensity Differentiation goal Low-cost goal Spatial distance to primary R&D ops. Cultural distance to primary R&D ops. Human resources (employees logged) Financial resources R&D resources/capabilities R2 Adjusted R2 Improvement in R2 F

2.3070*** 0.1160 0.2150 0.3970 0.7230*** 0.6700** 0.4370 0.4410* 0.3830* 0.5760*

0.088 0.041 1.892

Full model 4.1980*** 0.2650 0.0377 0.1630 0.7000*** 0.3460 0.2630 0.1420 0.3380 0.3120 0.1960*** 0.0250 0.4760*** 0.1610* 0.0491* 0.0082 0.0738* 0.1330* 0.0415 0.275 0.198 0.187*** 3.544***

N = 187. * P < .05. ** P < .01. *** P < .001.

5.1. Environmental factors Hypothesis 1A states that as product dynamism increases, the reliance on external product technology increases. The product technology dynamism coefficient is significant and in the hypothesized direction ( P < .001), supporting Hypothesis 1A. Hypothesis 1B predicts that as the competitive intensity in an industry increases, the reliance on external product technology increases. The coefficient is positive as predicted, but not significant, and fails to support Hypothesis 1B. 5.2. Strategic factors Hypothesis 2A suggests that as the importance of a differentiation goal increases, the reliance on external product technology decreases. With the largest standardized estimate, the differentiation goal’s coefficient is significant in the hypothesized negative direction ( P < .001) and supports Hypothesis 2A. Hypothesis 2B states that as the importance of a low-cost goal increases, the reliance on external product technology decreases. The

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coefficient for the low-cost goal is significant in the predicted direction ( P < .05) and supports Hypothesis 2A. 5.3. Configuration Hypothesis 3A predicts that as the spatial distance separating key U.S. marketing operations from R&D operations increases, the reliance on external product technology increases. The spatial distance coefficient is significant ( P < .01) in the positive direction, as forecasted, and supports Hypothesis 3A. Hypothesis 3B posits that that as the cultural distance separating key U.S. marketing operations from R&D operations increases, the reliance on external product technology increases. The coefficient for cultural distance is in the direction forecasted, but not significant, and fails to support Hypothesis 3B.4 5.4. Resource endowment factors Hypothesis 4A states that as the level of human resources increases, i.e., number of employees, the reliance on external product technology decreases. The relationship between the logged number of employees and external product technology is negative and significant ( P < .05) and supports Hypothesis 4A. Hypothesis 4B predicts that as the level of financial resources increases, the reliance on external product technology decreases. The level of financial resources is negatively related to external product technology sourcing, significant ( P < .05), and supports Hypothesis 4B. Hypothesis 4C suggests that as the level of R&D resources increases, the reliance on external product technology decreases. This construct’s coefficient is not significant and, contrary to the prediction, was positive, thus failing to support Hypothesis 4C.

6. Discussion In this study, environmental, strategic, configurational, and resource endowment factors are posited and found to influence the international subsidiary’s technology sourcing decision. The proposed model has good explanatory power for understanding the decision to either internally develop or outsource product technology. Specifically, high product technology dynamism in the subsidiary’s industry is associated with the increased acquisition of external product technology. The spatial distance between the key marketing and R&D operations is also associated with greater use of external sources of product technology. In accordance with TCE and RBV, we found that differentiation and low-cost goals may be best pursued through greater internal development of product technology. Possession of both human and financial, but not R&D, resources is also associated with 4 Shenkar (2001) suggests that the cultural distance measure of Kogut and Singh (1988) should be supplemented to include Hofstede’s fifth culture dimension, Confucian dynamism (introduced in Hofstede and Bond, 1988). Because the scores for Confucian dynamism are not available for 4 of the 14 countries in our study, we elected to use the cultural distance measure that included only the original four cultural dimensions. We did calculate a cultural distance measure using all five dimensions and ran the model for the reduced data set (in terms of subsidiaries and countries) and the results were similar.

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greater internal development of product technology. While subsidiaries may desire a product mandate—some contexts may proscribe the ability to successfully develop product technology. Other contextual factors incorporated into the analysis as controls included parent region location (i.e., location of parent within the Triad), which produced a nonsignificant association with external product technology reliance. This control variable was deemed important because the home country and regional location of an MNC is perceived to influence its subsidiary’s actions. While this may be the case in many aspects of business, we found that it did not influence the use of internal versus external sources of product technology. While the lack of significance may be influenced by the nature of the sample, it is also important to recognize that technology and knowledge flows are not just from the parent to subsidiary. Mudambi (2002) highlight three additional knowledge flows involving MNC subsidiaries: from the subsidiary to parent, location to subsidiary, and subsidiary to location. These flows recognize the fact that the subsidiary and its host location are important for technology development. For the industry control variables, in the base model all industry effects had negative and significant ( P < .05) associations with external product technology sourcing, except for industrial equipment/machinery. This indicates, before considering the other contexts, a general propensity for subsidiaries in all industries to develop technology internally, as would be supported by both TCE and RBV. In the full model, only the electronics and electric equipment industry remained significant ( P < .001). This suggests that in this industry, proprietary product technology is a critical source of advantage. The remaining five industry controls were nonsignificant in the full model. The following discussion is focused on the managerial implications of the study’s findings. The level of product dynamism in the subsidiary’s industry supports an increased use of external product technology sourcing. In environments characterized by increasing uncertainty, speed, and magnitude of technological change in product technology, subsidiaries are more likely to use a greater degree of outsourced technology. In highly dynamic situations, internal development, while providing greater control, can be expensive and time consuming and result in the development of technologies that are not ultimately accepted by the marketplace. While an international subsidiary that develops a standard-setting technology may be poised to reap great rewards, the firstmover advantage does not always result in the highest profitability or even long-term success (Boulding and Christen, 2001; Christensen, 1997). Accordingly, a subsidiary may not have the necessary resources or be able to take such risks. Instead, due to the pace of change and uncertainty, it may be forced to rely on the general market for an increasingly larger portion of their technology. Interestingly, while the level of competitive intensity is positively associated with external product technology sourcing, this relationship is not significant. This may be because competitive intensity usually increases once product standards are established. Therefore, as the competitive intensity increases, strategic imperatives focus less on product design and development and more likely on manufacturing costs and efficiencies. Additional investments in either internally developed or external-acquired product technology, except when disruptive or revolutionary, may not result in performance and positional advantage improvements.

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The findings associated with the positional advantage goals of differentiation and low cost have straightforward implications. If a subsidiary desires an advantage based on differentiation, indications suggest that developing product technology internally may best be suited to achieve this goal. Relying on market-based or external transactions means that similar, if not identical, product technology may be available to competing firms. Internally developed product technology allows the subsidiary to create unique positional advantages and minimize opportunistic concerns about external partners. It also allows the subsidiary to focus on distinctive product characteristics that provide customer value. For example, when GM’s Saturn division created a small car to compete with the Japanese offerings, it developed its technology internally to produce a car that was high in quality, rich in features, and affordable. Similar to the differentiation goal, achieving a low-cost goal may also be best accomplished through internal product technology development. While external product technology acquisition may provide quicker or even less expensive initial solutions, it is difficult to maintain a long-term positional advantage from such sources. Anything acquired externally is not likely to accrue unique benefits to the purchaser and should be easier to imitate or substitute. In addition, while the initial cost of the transaction may be favorable, opportunistic concerns may raise the overall cost through increased monitoring and enforcing. Another factor that promotes external product technology sourcing is when the spatial distance between key functional operations increase the costs associated with internal development. The further apart the primary marketing and R&D operations, the greater the costs associated with travel and transportation. This is particularly critical when this distance crosses national boundaries, as communication and integration barriers also increase costs and encourage the use of external local sources of product technology. When greater spatial distances separate key functional activities, external partners may provide solutions that are more responsive to local consumer needs, and the potential for improved communication may allow for quicker adaptation and increased flexibility. Local techniques, education, and other elements are a confounding factor that can make international technology transfer more difficult than adoption of local technology and could play a role in sourcing strategy decisions. The cultural distance between primary marketing and R&D operations is not significant, although the relationship is in the direction predicted. The lack of significance might be explained by the nature of the proxy measure used for cultural distance. Better quality measures for the country location of marketing and R&D operations will allow for more accurate measures of cultural distance to be calculated and greater insight into the relationship should be realized. Finally, possession of human and financial, but not R&D, resources is positively associated with internal development of product technology. This suggests that when important skills or financial resources are available, an existing technological base is not as critical for making product technology sourcing decisions. While the possession of essential human resources is important for the internal development of key technologies, financial resources can be used to acquire other resources and capabilities that the subsidiary may lack or need to develop its own technology. The finding with respect to R&D resources is counter to theory and intuition but may be explained by the fact that the

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international subsidiary is only part of a larger MNC. It is possible that human and financial resources need to be resident while the subsidiary’s possession of complementary R&D-related resources can be supplied and augmented by the parent company or other subsidiaries. Further research is required to understand this result.

7. Conclusions This study considers the effects of contextual factors on the international subsidiary’s technology sourcing decision. It extends earlier work of the authors (Swan and Allred, 2003) by developing the complementary TCE and RBV theoretical perspectives, as well as introducing categories within the sourcing decision and additional variables influencing the firms’ product technology sourcing strategy. While the ‘‘make-versus-buy’’ decision has been generally researched, this study offers some new insights from exploring a broad range of factors and motivated from a dual theory perspective. This also has implications for subsidiary product mandates. In pursuit of superior differentiation and cost advantages, as well as with increases in human and financial resources, subsidiaries tend to develop their own technology. They tend to rely more on external sources when product dynamism is high and when the distance between key functional activities increase. This information is of importance to the manager making the technology sourcing decision because awareness of the environmental conditions and internal situation can inform the manager whether the internal development or external acquisition of technology is best. Our study contributes to understanding the technology sourcing decision in three ways. First, we attempt to associate sourcing decisions with positional outcomes. While we cannot attribute causality with our data, the theoretical underpinnings of TCE and RBV offer complementary causal mechanisms that seem to be supported by the data. The findings may serve as a benchmark for future sourcing decisions. Managers identify differentiation and cost goals with sourcing strategies to reach those goals. Second, we offer insight through examining these decisions in context. The study suggests that four broad contextual factors influence a subsidiary’s product technology mandate and theory agrees. Because strategy is decision making in uncertainty, the more a manager understands the relationships, outcomes, and relevant contexts, the more likely the decision will produce positive outcomes. Third, we offer new measures derived from an unexplored area of the RBV. The positional advantages of differentiation and low cost are usually assumed, not measured. Managers are more likely to be able to influence their product’s positional advantage than set performance outcomes within the vagaries of the market. Thus, positional advantage measures may better be used to track managerial effectiveness. In addition, the RBV’s primary thesis is that the possession of critical resources can be used to create positional advantages and ultimately performance improvements. The possession of essential human and financial resources may not only supply the ability, but also the means to successfully develop product technology internally. Another interesting measure developed for this study is a continuous measure of product technology sourcing. Rather than consider technology sourcing as a simple

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dichotomous make-versus-buy decision, our measure considers it as a range from wholly developed internally to completely outsourced. The reality, as shown in our data, is that few organizations exclusively innovate or exclusively buy all their technology. Instead, they typically adopt a strategy that optimizes the internal capabilities and external opportunities for product technology with some intermediate position. Accordingly, the mix of technology sources pursued is a function of internal and external contexts, as suggested by this study. As a caveat to these findings, there are limitations to this study. First, additional work would be welcomed to further validate the study’s measures. While the positional advantage items are grounded in theory and the literature, they are developmental. Future work on applying firm-level theory to the subsidiary is required. We make the assumption that the headquarters has controls and rewards in place to align subsidiary action with parent corporation performance desires. Second, while our sample is representative, we do not capture the range of conglomerates and industries. A larger sample size with a greater range of industries- and culture-specific variables would increase the study’s generalizability and, specifically, strengthening the ability to examine cultural differences. Applying our measures and findings to the study of other areas, such as international diversification (Hitt et al., 1997), would be an interesting follow-up study. Third, we do not directly measure product mandate, hence, any implications are tentative. Fourth, this study examines one market respondent context—the U.S. subsidiary. Although no significant difference was found in the behavior of subsidiaries with U.S.- versus other region-based parents, it is not certain that behavior is similar for subsidiaries in markets other than the United States. Alternatively, there is some reason to believe that technology strategies may transcend national boundaries. Future research should look at markets outside of the United States. Fifth, this study was cross-sectional; a critical need in the literature on technology management is to track the performance impact of technology decisions over a greater period of time. Pavitt (1990) and Starr and Ullman (1988) and others suggest that technology reliance decisions have long-term impacts. This contention is supported by evidence that firms follow technological trajectories (Abernathy and Utterback, 1978). ‘‘Technological accumulation’’ highlights the long-term consequences to firms deciding to forego internal development of technological assets. Sixth, the subsidiaries in the sample are only from manufacturing firms. While a broad range of industries are represented, the results may not be generalizable to subsidiaries competing in service or nonprofit industries. While this study must be used with caution, an ability to benchmark against current practice is of managerial interest, especially because improving the competitive position of the firm is contingent on ‘‘the specific mix of internal and external sources of product. . .technology’’ (Wheelwright and Clark, 1992, p. 37). It is also of managerial interest that although the positional goals of differentiation and cost are negatively associated with external technology reliance, they are also opposed to each other. They are dissimilar positional advantage goals that have similar associations with the technology sourcing decision—a classic strategic choice. Predominantly, pursuing one of the positional advantage goals through internal development seems to produce positive results.

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In contrast, and as TCE suggests, when the decision-making process is increasingly characterized as uncertain, volatile, and difficult, organizations become more likely to outsource product technology.

8. Additional future research directions Future research should consider the performance outcome implications of the technology sourcing decision because the RBV indicates that acquiring and developing critical resources and capabilities should lead to superior performance. The two theoretical perspectives did not differ in their predictions of the relationships although they offer unique inclusion of additional variables. Research variables not included in this study may highlight differences between TCE and RBV. Other research directions include the investigation into the management of technology asset bases. It is critical that future research continues to examine knowledge management capabilities that can develop and renew these aspects of the organization. Additionally, there are pressures on MNCs and their subsidiaries to globally integrate and respond to local needs when it comes to technology development (Lindqvist et al., 2000). These distinctions should be further examined in terms of product technology sourcing strategies. Swamidass (1993) offers other relevant variables of research interest: the exchange rate regime, strategy factors (e.g., flexibility, global-rationalization, dependability), and international trade infrastructure issues (e.g., transportation, communication, financing, countertrade, global manufacturing capacity). To develop one of these ideas, specifically the exchange rate regime, researchers of sourcing strategy must be concerned about the problem of joint endogeneity. The literature on optimum currency area focuses on the interrelationships of the extent of trade and, by extension sourcing strategy, the degree to which business cycles are correlated internationally, and a common currency area—the causal relationships are not clear (Frankel and Rose, 1996). Trade expansion through outsourcing is likely to result in highly correlated business cycles and, thus, a common currency area as the alternative causal path. This would be a challenging, but interesting, research stream. A broader range of variables and theoretical perspectives included in sourcing research is likely to offer further surprises and insights. Another factor to consider for research involving MNCs in different countries with subsidiaries dispersed across the world is the influence that the legal mechanisms in both home and host countries have on technology development and sourcing. Additional TCE-related variables could also offer insights. On one hand, transaction costs (e.g., identifying suitable providers, communicating needs, monitoring progress and outputs, and avoiding predatory behavior), along with a lack of shared purpose and identity, are concerns with external sourcing. On the other hand, utilizing sources outside the subsidiary may offer economies of scale, reduced managerial costs of complexity, decreased or reallocated risk, lower politically loaded transactions, and change in management approach and skills (Alexander and Young, 1996). While a more internal or a more external technology reliance strategy can produce many of the same benefits, significant differences in attitudes and perceptions are likely—even the process of

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reviewing the technology reliance decision can generate new insights into internal activities. Tying these TCE variables to sourcing strategies and positional advantages as well as performance outcomes could be interesting next steps in this research stream. Finally, future research should extend the make-versus-buy decision beyond a simple internal development versus external acquisition decision. The international subsidiary of the MNC is playing an increasingly important role in the global success and growth of the firm. The technology sourcing options that an international subsidiary has available to it includes internal development, using another subsidiary within the same MNC, sourcing from a cooperative third-party with which the subsidiary has experience and trust, or outsourcing in the market. While these four choices represent different points along a continuum, rather than a dichotomous choice, the use of each of these sourcing strategies has unique and contextual strategic, as well as performance, implications.

Acknowledgements The authors wish to acknowledge the assistance of Aldor Lanctot, a research grant from the College of William and Mary, two anonymous reviewers, and Mike Kotabe.

References Abernathy, W., Clark, K., 1985. Innovation: mapping the winds of creative destruction. In: Tushman, M.L., Moore, W.L. (Eds.), Readings in the Management of Innovation. Ballinger Publishing, Cambridge, MA, pp. 55 – 78. Abernathy, W.J., Utterback, J.M., 1978. Patterns of industrial innovation. Technol. Rev. 80 (7), 40 – 47. Allen, T., 1977. Managing the Flow of Technology. MIT Press, Cambridge, MA. Alexander, M., Young, D., 1996. Outsourcing: where’s the value? Long Range Plan. 29 (5), 728 – 730. Amit, R., Schoemaker, P., 1993. Strategic assets and organizational rents. Strateg. Manage. J. 14 (1), 3 – 46. Armstrong, J.S., Overton, T., 1977. Estimating non-response bias in mail surveys. J. Mark. Res. 14 (3), 396 – 402. Asakawa, K., 1996. External – internal linkages and overseas autonomy – control tension: the management dilemma of the Japanese R&D in Europe. IEEE Trans. Eng. Manage. 43 (1), 24 – 32. Athaide, G.A., Meyers, P.W., Wilemon, D.L., 1996. Sell – buyer interactions during the commercialization of technological process innovations. J. Prod. Innov. Manag. 13 (5), 406 – 421. Bagozzi, R.P., Yi, Y., 1988. On the evaluation of structural equation modeling. J. Acad. Mark. Sci. 16 (1), 74 – 94. Barney, J., 1991. Firm resources and sustained competitive advantage. J. Manage. 17 (1), 99 – 120. Bartholomew, S., 1997. National systems of biotechnology innovation: complex interdependence in the global system. J. Int. Bus. Stud. 28 (Summer), 241 – 266. Bentler, P.M., Bonett, D.G., 1980. Significance tests of goodness of fit in the analysis of covariance structures. Psychol. Bull. 88, 588 – 606. Bettis, R.A., Hitt, M.A., 1995. The new competitive landscape. Strateg. Manage. J. 16 (Summer Special Issue), 7 – 19.

B.B. Allred, K.S. Swan / Journal of International Management 10 (2004) 259–286

283

Birkinshaw, J., 1996. How multinational subsidiary mandates are gained and lost. J. Int. Bus. Stud. 27 (3), 467 – 495. Birkinshaw, J., Morrison, A., 1996. Configurations of strategy and structure in subsidiaries of multinational corporations. J. Int. Bus. Stud. 26 (4), 729 – 754. Boulding, W., Christen, M., 2001. First-mover disadvantage. Harvard Bus. Rev. 79 (9), 20 – 21. Bower, J.L., Hout, T.M., 1988. Fast-cycle capabilities for competitive power. Harvard Bus. Rev. 66 (6), 108 – 110. Buckley, P.J., Casson, M., 1976. The Future of the Multinational Enterprise. Macmillan, London. Cantwell, J., 1989. Technological Innovation and Multinational Corporations. Basil Blackwell, Oxford. Cantwell, J., Mudambi, R., 2000. The location of MNE R&D activity: the role of investment incentives. Manag. Int. Rev. 40 (1), 127 – 148. Capon, N., Glazer, R., 1997. Marketing and technology: a strategic co-alignment. J. Mark. 51 (3), 1 – 14. Carmines, E., McIver, J., 1981. Analyzing models with unobserved variables: analysis of covariance structure. In: Bohnstedt, G., Borgatta, E. (Eds.), Social Measurement: Current Issues. Sage, Beverly Hills, pp. 65 – 115. Caves, R., Crookell, H., Killing, J.P., 1983. The imperfect market for technology licenses. Oxf. Bull. Econ. Stat. 85 (August), 249 – 267. Challagalla, G.N., Shervani, T.A., 1996. Dimensions and types of supervisory control: effects on salesperson performance and satisfaction. J. Mark. 60 (1), 89 – 105. Chiesa, V., 2000. Global R&D project management and organization: a taxonomy. J. Prod. Innov. Manag. 17 (5), 341 – 359. Christensen, C., 1997. The Innovator’s Dilemma. Harvard Business School Press, Boston, MA. Collis, D.J., Montgomery, C.A., 1995. Competing on resources: strategy in the 1990s. Harvard Bus. Rev. 73 (4), 118 – 128. Conner, K., 1991. A historical comparison of resource-based theory and five schools of thought within industrial organization economics: do we have a new theory of the firm? J. Manage. 17 (1), 121 – 154. Conner, K.R., Prahalad, C.K., 1996. A resource-based theory of the firm: knowledge versus opportunism. Organ. Sci. 7 (5), 477 – 501. Cooper, A.C., Schendel, D., 1976. Strategic responses to technological threats. Bus. Horiz. 19 (1), 61 – 69. Crampton, S.M., Wagner, J.A., 1994. Percept – percept inflation in microorganizational research: an investigation of prevalence and effect. J. Appl. Psychol. 79 (1), 67 – 76. Day, G., Wensley, R., 1988. Assessing advantage: a framework for diagnosing competitive superiority. J. Mark. 52 (2), 1 – 20. Devinney, T.M., 1995. Significant issues for the future of product innovation. J. Prod. Innov. Manag. 12 (1), 70 – 75. Dickson, P., 1992. Toward a general theory of competitive advantage. J. Mark. 56 (1), 69 – 83. Dierickx, I., Cool, K., 1989. An asset stock accumulation and the sustainability of competitive advantage. Manage. Sci. 35 (12), 1504 – 1513. Fayerweather, J., 1969. International Business Management: A Conceptual Framework. McGrawHill, New York. Fornell, C., Larcker, D.F., 1981. Evaluating structural models with unobservable variables and measurement error. J. Mark. Res. 18 (1), 39 – 50. Francis, A., 1980. Company objectives, managerial motivations and the behavior of large firms: an empirical test of the theory of ‘‘managerial capitalism’’. Camb. J. Econ. 4, 349 – 361.

284

B.B. Allred, K.S. Swan / Journal of International Management 10 (2004) 259–286

Frankel, J., Rose, A., 1996. The endogeneity of the optimum currency area criteria. NBER Work. Pap. 5700, 1 – 33. Gassman, O., von Zedtwitz, M., 1998. Organization of industrial R&D on a global scale. R & D Manag. 28 (3), 147 – 161. Gupta, A.K., Govindarajan, V., 1991. Knowledge flows and the structure of control within multinational corporations. Acad. Manage. Rev. 16 (4), 768 – 792. Hair Jr., J.F., Anderson, R.E., Tatham, R.L., Black, W.C. 1998. Multivariate Data Analysis, 5th ed. Prentice-Hall, Englewood Cliffs, NJ. Hayes, R., Wheelwright, S., Clark, K., 1988. Dynamic Manufacturing: Creating the Learning Organization. The Free Press, New York. Hitt, M.A., Hoskisson, R.E., Kim, H., 1997. International diversification: effects on innovation and firm performance in product diversified firms. Acad. Manage. J. 40 (4), 767 – 798. Hofstede, G., 1980. Culture’s Consequences: International Differences in Work-Related Values. Sage, Beverly Hills. Hofstede, G., Bond, M.H., 1988. The Confucius connection: from cultural roots to economic growth. Organ. Dyn. 16 (4), 4 – 21. Howells, J., 1990. The location and organization of research and development: new horizons. Res. Policy 19 (2), 133 – 146. Hunt, S., 1997. Resource-advantage theory: an evolutionary theory of competitive firm behavior? J. Econ. Issues 31 (1), 59 – 77. Jelinek, M., Schoonhoven, C.B., 1990. The Innovation Marathon: Lessons from High Technology Firms. Basil Blackwell, Oxford. Johanson, J., Vahlne, J.E., 1977. The internationalization process of the firm—a model of knowledge development and increasing foreign market commitments. J. Int. Bus. Stud. 8 (1), 22 – 32. John, G., Weitz, B., 1988. Forward integration into distribution: empirical test of transaction cost analysis. J. Law Econ. Organ. 4 (2), 121 – 139. Jones, G.K., Davis, H.J., 2000. National culture and innovation: implications for locating global R&D operations. Manag. Int. Rev. 40 (1), 11 – 39. Kerin, R., Varadarajan, P.R., Peterson, R., 1992. First-mover advantage: a synthesis, conceptual framework, and research propositions. J. Mark. 56 (October), 33 – 52. Kogut, B., Singh, H., 1988. The effect of national culture on the choice of entry mode. J. Int. Bus. Stud. 19 (3), 411 – 432. Kotabe, M., 1992. Global Sourcing Strategy: R&D, Manufacturing, and Marketing Interfaces. Quorum Books, New York. Kotabe, M., Helsen, K., 1999. Global Marketing Management. Wiley, New York. Kotabe, M., Murray, J., 1990. Linking product and process innovation and modes of international sourcing in global competition: a case of foreign multinational firms. J. Int. Bus. Stud. 21 (3), 383 – 408. Kotabe, M., Swan, K.S., 1995. The role of strategic alliances in high technology new product development. Strateg. Manage. J. 16 (8), 621 – 636. Kuemmerle, W., 1999. The drivers of foreign direct investment into research and development: an empirical investigation. J. Int. Bus. Stud. 30 (1), 1 – 18. Lanctot, A., Swan, K.S., 2000. Technology acquisition strategy in an internationally competitive environment. J. Internat. Manag. 6 (3), 187 – 216. Lieberman, M.B., Montgomery, D.B., 1998. First-mover (dis)advantages: retrospective and link with the resource-based view. Strateg. Manage. J. 19 (12), 1111 – 1125. Lindell, M.K., Whitney, D.J., 2001. Accounting for common method variance in cross-sectional research designs. J. Appl. Psychol. 86 (1), 114 – 121.

B.B. Allred, K.S. Swan / Journal of International Management 10 (2004) 259–286

285

Lindqvist, M., Solvell, O., Zander, I., 2000. Technological advantage in the international firm—local and global perspectives on the innovation process. Manag. Int. Rev. 40 (1), 95 – 126. Mahoney, J.T., 2001. A resource-based theory of sustainable rents. J. Manage. 27 (6), 651 – 660. Mahoney, J.T., Pandian, J., 1992. The resource-based view within the conversation of strategic management. Strateg. Manage. J. 13 (5), 363 – 380. Marquis, D., 1988. The anatomy of successful innovations. In: Tushman, M., Moore, W. (Eds.), Readings in the Management of Innovation. Ballinger Publishing, Cambridge, MA, pp. 79 – 87. McDonough, E.F., Kahn, K.B., Barczak, G., 2001. An investigation of the use of global, virtual, and collocated new product development teams. J. Prod. Innov. Manag. 18 (2), 110 – 120. Medcof, J.W., 1997. A taxonomy of internationally dispersed technology units and its implication to management. R & D Manag. 27 (4), 301 – 318. Meyers, P.W., Sivakumar, K., Nakata, C., 1999. Implementation of industrial process innovations: factors, effects, and marketing implications. J. Prod. Innov. Manag. 16 (3), 295 – 311. Miller, D., Shamsie, J., 1996. The resource-based view of the firm in two environments: the Hollywood film studios from 1936 to 1965. Acad. Manage. J. 39 (3), 519 – 543. Mudambi, R., 2002. Knowledge management in multinational firms. J. Internat. Manag. 8 (1), 1 – 9. Murray, J.Y., Wildt, A.R., Kotabe, M., 1995. Global sourcing strategies of U.S. subsidiaries of foreign multinationals. Manag. Int. Rev. 35 (4), 307 – 324. Nelson, R.R., Winter, S.G., 1982. An Evolutionary Theory of Economic Change. Harvard Univ. Press, Cambridge, MA. Nobel, R., Birkinshaw, J., 1998. Innovation in multinational corporations: control and communication patterns in international R&D operations. Strateg. Manage. J. 19 (5), 479 – 496. Noori, H., 1980. Managing the Dynamics of New Technology. Prentice-Hall, Englewood Cliffs, NJ. O’Grady, S., Lane, H.W., 1996. The psychic distance paradox. J. Int. Bus. Stud. 27 (2), 309 – 333. Ohba, S., 1996. Critical issues related to international R&D programs. IEEE Trans. Eng. Manage. 43 (1), 78 – 87. Ohmae, K., 1995. The End of the Nation State: The Rise of Regional Economies. The Free Press, New York. Olson, E.M., Walker, O.C., Ruekert, R.W., Bonner, J.M., 2001. Patterns of cooperation during new product development among marketing, operations and R&D: implications for project performance. J. Prod. Innov. Manag. 18 (4), 258 – 271. Pavitt, K., 1990. What we know about the strategic management of technology. Calif. Manage. Rev. 32 (3), 17 – 26. Peng, M.W., Wang, D.Y., 2000. Innovation capability and foreign direct investment: toward a learning option perspective. Manag. Int. Rev. 4 (1), 79 – 93. Peteraf, M., 1993. The cornerstones of competitive advantage: a resource-based view. Strateg. Manage. J. 14 (3), 179 – 191. Podsakoff, P.M., Organ, D.W., 1986. Self-report in organizational research: problems and prospects. J. Manage. 12 (4), 531 – 544. Porter, M.E., 1985. Competitive Advantage. The Free Press, New York. Robins, J.A., 1987. Organizational economics: notes on the use of transaction cost theory in the study of organizations. Adm. Sci. Q. 32 (1), 68 – 86. Robinson, W.T., Fornell, C., Sullivan, M., 1992. Are market pioneers intrinsically stronger than later entrants? Strateg. Manage. J. 13 (8), 609 – 624. Roth, K., Morrison, A.J., 1992. Implementing global strategy: characteristics of global subsidiary mandates. J. Int. Bus. Stud. 23 (4), 715 – 735. Roth, K., Ricks, D.A., 1994. Goal configuration in a global industry context. Strateg. Manage. J. 15 (2), 103 – 120.

286

B.B. Allred, K.S. Swan / Journal of International Management 10 (2004) 259–286

Schoenberger, E., 1987. Technological and organizational change in automobile production: spatial implications. Reg. Stud. 21 (3), 199 – 214. Schroeder, R.G., Bates, K.A., Junttila, M.A., 2002. A resource-based view of manufacturing strategy and the relationship to manufacturing processes. Strateg. Manage. J. 23 (2), 105 – 117. Shenkar, O., 2001. Cultural distance revisited: towards a more rigorous conceptualization and measurement of cultural differences. J. Int. Bus. Stud. 32 (3), 519 – 535. Starr, M., Ullman, J., 1988. The myth of industrial supremacy. In: Starr, M. (Ed.), Global Competitiveness. W. W. Norton and Company, New York, pp. 43 – 71. Steensma, H.K., Corley, K.G., 2001. Organizational context as a moderator of theories on firm boundaries for technology sourcing. Acad. Manage. J. 44 (2), 271 – 291. Stock, G.N., Greis, N.P., Dibner, M.D., 1996. Parent – subsidiary communication in international biotechnology. IEEE Trans. Eng. Manage. 43 (1), 56 – 68. Swamidass, P., 1993. Import sourcing dynamics: an integrative perspective. J. Int. Bus. Stud. 24 (4), 671 – 691. Swan, K.S., Allred, B.B., 2003. A product and process model of the technology – sourcing decision. J. Prod. Innov. Manag. 20 (6), 485 – 496. Teece, D., 1987. Capturing value from technological innovation: integration, strategic partnering, and licensing decisions. In: Guile, B., Brooks, H. (Eds.), Technology and Global Industry. National Academy Press, Washington, DC, pp. 65 – 95. Teigland, R., Fey, C.F., Birkinshaw, J., 2000. Knowledge dissemination in global R&D operations: an empirical study of multinationals in the high technology electronics industry. Manag. Int. Rev. 40 (1), 49 – 77. Webster, F.E., 1992. The changing role of marketing in the corporation. J. Mark. 56 (4), 1 – 17. Wernerfelt, B., 1984. A resource-based view of the firm. Strateg. Manage. J. 5 (2), 171 – 180. Werts, C.E., Linn, R.L., Joreskog, K.G., 1974. Intraclass reliability estimates: testing structural assumptions. Educ. Psychol. Meas. 34 (1), 25 – 33. Wheelwright, S., Clark, K., 1992. Revolutionizing Product Development: Quantum Leaps in Speed, Efficiency, and Quality. The Free Press, New York. Williamson, O.E., 1985. The Economic Institutions of Capitalism: Firms, Markets, Relational Contracting. The Free Press, New York.