Product Development Strategy, Product Innovation Performance, and ...

Product Development Strategy, Product Innovation Performance, and the Mediating Role of Knowledge Utilization: Evidence from Subsidiaries in China Junfeng Zhang, C. Anthony Di Benedetto, and Scott Hoenig

ABSTRACT This study examines the interplay of product development strategy, knowledge utilization, and product innovation performance in the context of Chinese subsidiaries of multinational companies. When firms strive to develop highly innovative products (breakthrough focus), the amount of resources allocated has a U-shaped relationship to subsequent product innovation performance (i.e., market rewards of new products). When the aim of product development activity is to reinforce and maintain moderately innovative products (platform focus), increased resource allocation shows a positive relationship to product innovation performance. The amount of resources allocated to minor revisions (incremental focus) shows no significant relationship to product innovation performance. Knowledge utilization is an important predictor of the benefits of developing highly and moderately innovative products. Moreover, it helps to mitigate the drawbacks of a breakthrough focus and strengthens the positive impact of a platform focus. Keywords: knowledge utilization, product development strategy, product innovation performance, subsidiaries, China

roduct development involves a complex coupling between market needs and technologies (Dougherty 1992) and is a potential source of competitive advantage for a firm (e.g., Brown and Eisenhardt 1995). With intensified competition, firms increasingly com-

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Junfeng Zhang is Assistant Professor of Marketing, Hong Kong Baptist University (e-mail: [email protected]). C. Anthony Di Benedetto is Professor of Marketing and Senior Washburn Research Fellow, Fox School of Business, Temple University (e-mail: [email protected]). Scott Hoenig is Associate Professor of Marketing, School of Economic and Business Sciences, University of Witwatersrand, Johannesburg, South Africa (e-mail: scott.hoenig@ wits.ac.za).

42 Journal of International Marketing

pete on the basis of a sophisticated research and development (R&D) cooperation network (Roijakkers and Hagedoorn 2006), applying dispersed knowledge from around the world (Chesbrough 2003). In this regard, multinational companies gain an advantage through their globally distributed innovation networks and their ability to assimilate, generate, and integrate knowledge worldwide (e.g., Bartlett and Ghoshal 1989). The ability to harness and leverage knowledge from their dispersed subsidiaries enables firms to develop new prod-

Journal of International Marketing ©2009, American Marketing Association Vol. 17, No. 2, 2009, pp. 42–58 ISSN 1069-0031X (print) 1547-7215 (electronic)

ucts efficiently while still responding to local needs (Subramaniam and Venkatraman 2001). A noticeable development in recent decades has been the increasingly prominent role of subsidiaries in multinational companies’ innovation activities (Mudambi 2002) and their knowledge networks (Cantwell and Mudambi 2004; Makino and Inkpen 2003). Some become sources of corporatewide strength (e.g., Bartlett and Ghoshal 1989; Birkinshaw 1996), or even “centers of excellence” (Foss and Pedersen 2002; Moore and Birkinshaw 1998). As nodes in multinational companies’ knowledge networks (Makino and Inkpen 2003), these subsidiaries help their parents maintain a knowledge advantage (Cantwell and Mudambi 2004), partly by providing a valuable source of new knowledge through the development of new products and technologies (Pearce 1999; Zander 1999). The important role of subsidiaries in multinational companies’ innovation and knowledge network has long been recognized (e.g., Bartlett and Ghoshal 1989; Cantwell and Mudambi 2004; Kotabe et al. 2007), but only limited research has explored knowledge assimilation and innovation activities in subsidiaries (Phene and Almeida 2008). In this stream, researchers have most often studied technological innovation by focusing on patents (Phene and Almeida 2008). This means that subsidiary new product development has largely been overlooked, even though an important feature of subsidiary R&D is its substantial influence in new product development (Forsgren and Pedersen 1998). Moreover, although recent studies have demonstrated empirically that a subsidiary’s success in technological innovation relies on its assimilation of knowledge from different sources and its ability to integrate and use such knowledge (Almeida and Phene 2004; Phene and Almeida 2008), only the direct impact of knowledge assimilation has been examined. The impact of a subsidiary’s strategic initiatives as well as their interplay with knowledge utilization is underresearched. The marketing field’s understanding of such issues is particularly limited in emerging market contexts. The majority of empirical studies of knowledge utilization and innovation have been conducted in developed countries, though there is evidence that multinational companies expand their R&D activities to their overseas subsidiaries, including those in emerging markets, to improve their competitive advantages globally (Zhang et al. 2007). In an effort to fill some of these gaps, we designed this study to investigate the interplay of a subsidiary’s product development strategy with its knowledge utilization

and the resultant product innovation performance. The context is an emerging economy—namely, China. In particular, we examined the direct impact of decisions about resource allocation among different projects (i.e., a subsidiary’s product development strategy) on product innovation performance.1 Then, we examined the mediating role of a subsidiary’s overall knowledge utilization in the relationship between its product development strategy and its product innovation performance.2 We operationalize a subsidiary’s product development strategy as three strategic focuses (i.e., breakthrough, platform, and incremental focuses). Each focus reflects the extent to which resources are allocated to projects that aim to develop new products high, moderate, or low in terms of innovativeness (Cooper and Kleinschmidt 1987). Knowledge utilization by a subsidiary can be described in terms of the extent to which it uses knowledge from various sources, such as suppliers, customers, competitors, outside research organizations and consultants, universities, its parent firm, peer units, and so on, in its product development (Laursen and Salter 2006). Product innovation performance is the market reward for new products in terms of the products’ contributions to subsidiary sales or profits. Prior research has shown that such measures can effectively distinguish best practice firms (Hauser, Tellis, and Griffin 2006). New products include completely new products, new product lines, modifications, and derivatives (Li and Atuahene-Gima 2001). Prior research results suggest that subsidiaries involved in R&D have gradually undertaken greater roles in the overall innovation of multinational companies (Mudambi 2002). Their strategies involve varying degrees of exploration and exploitation (Kuemmerle 1999), which to some extent is reflected in a subsidiary’s three strategic focuses. If these diverse strategies have an impact on a subsidiary’s innovation activities (Almeida and Phene 2004), it is reasonable to assume that the market will reward superior resource allocation among these focuses in some way.3 The exact relationship will depend on the interplay between the resources needed to overcome innovation barriers and the benefits brought by the products of these innovation initiatives. We propose that a breakthrough focus tends to yield a Ushaped relationship to product innovation performance, the platform focus usually has a positive relationship, and the incremental focus has a negative relationship. It is also important to consider any mediating role of overall knowledge utilization in the relationships

Product Development Strategy and Product Innovation Performance 43

between the three strategic focuses and product innovation performance. On the basis of information theory (Galbraith 1973) and the fit-as-mediation strand of contingency theory (Venkatraman 1989), we could argue that the different strategic focuses should have different information requirements that dictate the extent of knowledge needs. Thus, the alignment of such information requirements with proper information-processing capacities (manifested by the extent of knowledge utilization) is likely to result in better product innovation performance. More specifically, the fit between knowledge utilization and the breakthrough or platform focus should lead to better product innovation performance, but the incremental focus relies less on knowledge utilization; therefore, there may be no significant interplay between the two. In this study, we set out to explore these issues in the context of foreign subsidiaries in China. As China moves toward a market economy, foreign companies’ subsidiaries have increased their investments in developing new products to meet consumer preferences (Zhou, Yim, and Tse 2005). Such an unusual context might shed new light on the understanding of subsidiary knowledge utilization and product innovation. Figure 1 presents a model of subsidiary product innovation performance. We formulated and tested specific hypotheses using data collected from 103 Chinese subsidiaries of multinational companies. The findings largely confirm our propositions, except that an incremental focus does not show a

significant relationship to product innovation performance. These findings provide empirical evidence of how resource allocation among different projects affects product innovation performance. In addition, they suggest that knowledge utilization is a mechanism that could help the subsidiary realize the benefits of developing highly and moderately innovative products.

THEORY AND HYPOTHESES DEVELOPMENT Historically, multinational companies have established subsidiaries overseas to apply and exploit resources, including parent company knowledge (Hymer 1976; Vernon 1966). More recently, subsidiaries have undertaken more active roles in the dynamic learning of multinationals (Makino and Inkpen 2003). Subsidiaries increasingly play a role in both exploitation and exploration through innovation (Kuemmerle 2002), as evidenced by an increase in multinational companies conducting R&D abroad to augment their competitive advantage or create new advantage (Bartlett and Ghoshal 1989). The resource-based view of the firm suggests that both a subsidiary’s product development strategy and its knowledge utilization can be regarded as distinctive intangible resources that can give rise to competitive advantage (Barney 1991). Their interplay over time should contribute to a subsidiary’s performance (Amit and Schoemaker 1993; Barney 1991).

Figure 1. Interrelationships Among Product Development Strategy, Knowledge Utilization, and Product Innovation Performance ProductDevelopment Strategy

Breakthrough focus

Platform focus

Incremental focus


Mediator

Outcome

Knowledge utilization

Product innovation

In terms of information theory, product development strategy delineates the resource allocation of a subsidiary among its projects, which manifests a subsidiary’s intention to explore and exploit (March 1991), and accordingly the information-processing requirements of developing products with certain levels of innovativeness (Galbraith 1973). In line with the spirit of this theory, such information-processing requirements dictate the need for certain information-processing mechanisms to reduce the gap between information requirements and information-processing capacity (Galbraith 1973). Such mechanisms represent “lateral linkage devices or structural coordination mechanisms” (Olson, Walker, and Ruekert 1995, p. 49). One example in new product development is using a supplier and customer network to facilitate knowledge utilization in new products (Song, Van der Bij, and Weggeman 2005). This can be effective because a key benefit of such networks is the information they can provide (e.g., Burt 1997; Uzzi 1997). Leveraging these networks to expand a firm’s knowledge resources can strengthen a subsidiary’s competitive advantage and assist with its product development (Hansen, Mors, and Løvås 2005; Inkpen and Tsang 2005; Yli-Renko, Autio, and Sapienza 2001). Subsidiaries are embedded in the internal network of their multinational parent as well as in their external local business network (Forsgren and Pedersen 1998). Such a network position enables them to obtain and exploit knowledge from both their parent and the host country. To the extent that a subsidiary assimilates, uses, or integrates knowledge from both networks, it functions as an information-processing mechanism (Galbraith 1973). Here, information theory converges with the resource-based view of the firm regarding the impact of the interplay of product development strategy and knowledge utilization on a subsidiary’s product innovation performance. That is, a subsidiary can achieve better product innovation performance by aligning its informationprocessing capacity (manifested by its knowledge utilization) with its information-processing requirements (manifested by its product development strategy; Galbraith 1973).

Three Product Development Strategic Focuses and Knowledge Utilization In line with these arguments, a subsidiary’s three product development strategic focuses engender different information-processing requirements. They dictate different knowledge utilization (information-processing mechanisms) to reduce the gap between information

requirements and information-processing capacity (Galbraith 1973). More specifically, a breakthrough focus aims to develop new products and processes, and this involves exploring new possibilities (March 1991). This requires building up technology assets and bridging market demands and technological possibilities. Some important information sources are the parent firm, peer units, and sources in the host country (e.g., Phene and Almeida 2008). To be innovative, a subsidiary must search widely and deeply in its network for knowledge (Laursen and Salter 2006) to cope effectively with the uncertainty inherent in new product development (Olson, Walker, and Ruekert 1995; Song and MontoyaWeiss 1998). Subsequently, the requirements for processing substantial new knowledge continue to increase (Benner and Tushman 2003; March 1991). Therefore, a breakthrough focus should call for intensive knowledge utilization. In contrast, the incremental focus involves minor modifications to existing products that usually require only the extension of prior knowledge (Kleinschmidt and Cooper 1991). There is relatively little need for processing entirely new knowledge and, accordingly, little demand for a processing mechanism aimed at knowledge utilization. The subsidiary usually possesses extensive prior knowledge. In a similar vein, a platform focus emphasizes moderately innovative projects that require small changes in technology and processes but greater integration of new product functions and features and the development of new manufacturing processes. This involves significant information-processing requirements but on a relatively smaller scale than that of the breakthrough focus, because it involves a knowledge search that is shallower and narrower. Therefore, a platform focus should call for a moderate level of subsidiary knowledge utilization. H1: (a) The extent of a subsidiary’s breakthrough focus is positively associated with its knowledge utilization, (b) the extent of a subsidiary’s platform focus is positively associated with its knowledge utilization, and (c) the extent of a subsidiary’s incremental focus is not significantly related to its knowledge utilization.

Three Product Development Strategic Focuses and Product Innovation Performance Companies often develop product plans at the company or product family level by mapping existing products and projects (e.g., Wheelwright and Clark 1992; Wheelwright


and Sasser 1989), and those that have a specific product development strategy usually perform better (Cooper and Kleinschmidt 1995; Griffin 1997). Opting for one or more of the three strategic focuses is likely to improve a subsidiary’s product innovation performance because it helps management plan for product development and allocate adequate resources (Cooper and Kleinschmidt 1995). A breakthrough focus aims to result in innovative products that are superior to those of competitors. Success enables a subsidiary to reap economic rent, and thus better profitability and sales results, from its new products (Calantone, Chan, and Cui 2006). Furthermore, focusing on developing highly innovative products may foster a spirit of innovation (Szymanski, Kroff, and Troy 2007), which encourages learning (Hurley and Hult 1998). This assists a subsidiary with conquering impediments of foreignness, such as higher learning costs and unfamiliarity with local business conditions (Hymer 1976; Zaheer 1995), thereby developing products that better fulfill customers’ needs and wants. However, this focus also erects barriers in a subsidiary that hinder the success of new products. Inadequate technology, weak skills and knowledge, and customer resistance to unfamiliar new products all must be overcome (Bond and Houston 2003; Szymanski, Kroff, and Troy 2007). To overcome the barriers and develop successful new products, subsidiaries may need substantial investment, particularly in marketing and technology (e.g., Cooper and Kleinschmidt 1987). This investment helps them build brand equity to reduce customer unfamiliarity and build barriers to entry to help sustain their competitive advantage (Sorescu, Chandy, and Prabhu 2003). Such investment also facilitates further exploratory activity that encourages learning. Sufficient resource commitment is particularly essential for product innovation in the turbulent environment of an emerging market such as China’s. Subsidiaries there face high costs and risks in maintaining extensive and flexible capabilities to respond to environmental changes (Luo and Park 2001). Therefore, it is likely that the negative effects of various barriers first dominate when the extent of resource allocation is inadequate, but as the resources committed to developing highly innovative products increase, the positive effects (e.g., reduced customer unfamiliarity, enhanced product advantage) eventually begin to outweigh the negative effects. A platform focus involves projects that develop moderately innovative products, such as new product lines, new items in a product line, or significant modifica-


tions to existing products. Such projects are less risky, usually require less resource commitment, and have a shorter development cycle than breakthrough innovations. After testing 79 products from a sample of ten small technology-based companies and rating them with a self-generated “newness index,” Meyer and Roberts (1986) suggest that some newness in the overall project portfolio is better than either no newness at all or a great deal of newness. This suggests the benefit of investing in moderately innovative products (for a different view, see Kleinschmidt and Cooper 1991). Barriers such as inadequate knowledge and customer resistance should be much less serious for moderately innovative products than for highly innovative products. Meanwhile, the development of moderately innovative products involves both exploitative and explorative activities. This facilitates the search for new knowledge, as well as the integration and combination of existing knowledge. In particular, subsidiaries enjoy special knowledge and innovation advantages in that they can obtain support from their parents and leverage knowledge and competences from their global network (Bartlett and Ghoshal 1989). This alleviates the problem of resource barriers to new product development. Moreover, focusing on developing moderately innovative products is likely to result in more successful new products in the Chinese market for two reasons. First, in general, multinational companies can use their strengths and reduce risks by transferring their mature technologies (Luo and Park 2001). Second, subsidiaries in developing economies, specifically in China, can reap potential economic rents because Chinese consumers may perceive many new products developed by foreign companies as innovative (Zhou, Yim, and Tse 2005). If we take all these factors together, it is likely that developing moderately innovative products will reliably contribute to a subsidiary’s product innovation performance. Incremental projects often respond to specific customer needs by adding more features or reducing costs. Such projects usually develop products that involve the extension of prior knowledge (Kleinschmidt and Cooper 1991) and often are associated with low levels of resource commitment and risk and short development cycles. Previous research has shown that the impact of such products on performance can be either positive or negative (e.g., Banbury and Mitchell 1995; Danneels and Kleinschmidt 2001). A subsidiary can reap benefits from taking few risks and committing few resources, but developing only less innovative products constrains its ability to search for and fully use knowledge. This can

limit its product development capabilities and thus limit the potential for competitive advantage (Helfat and Raubitschek 2000). In China, the disadvantages may outweigh the advantages for two reasons. First, an incremental focus may be too conservative for a multinational company because the volatile Chinese market requires a firm to be responsive to change (Luo and Park 2001). Second, one of the strategic roles of a subsidiary with responsibilities in new product development is to create new knowledge for the entire firm (Cantwell and Mudambi 2004; Makino and Inkpen 2003; Pearce 1999; Zander 1999), for which developing incremental products is unlikely to be sufficient. H2: (a) The extent of a subsidiary’s breakthrough focus has a U-shaped relationship to its product innovation performance, (b) the extent of a subsidiary’s platform focus has a positive relationship to its product innovation performance, and (c) the extent of a subsidiary’s incremental focus has a negative relationship to its product innovation performance.

Knowledge Utilization and Product Innovation Performance As discussed previously, the three focuses of a subsidiary’s product development strategy manifest the informationprocessing requirements, whereas its knowledge utilization manifests the information-processing capacity. According to its role as an information-processing network, information theory implies that a subsidiary can achieve better market performance from its new products by striving for good fit between its information requirements and its capacities. This is also consistent with the fit concept in strategy, which suggests that organizational performance depends on the alignment of context, structure, and process (Drazin and Van de Ven 1985). The breakthrough and platform focuses involve exploring new possibilities and integrating such exploration with exploitation. Both involve significant information needs (Benner and Tushman 2003; March 1991). By improving its knowledge utilization, a subsidiary can reduce the level of perceived uncertainties to which it is exposed (Song and Montoya-Weiss 1998), develop a system of knowledge and learning that supports its new products (Helfat and Raubitschek 2000), and create new knowledge resources that help sustain a product advantage by erecting barriers to imitation (McEvily

and Chakarvarthy 2002). Knowledge utilization enables a subsidiary to develop new products that simultaneously enhance product advantage and control customer unfamiliarity, resulting in a greater likelihood of success (Calantone, Chan, and Cui 2006). In contrast, the incremental focus relies on a subsidiary’s ability to exploit currently established certainties. This focus emphasizes meeting the needs of existing customers or markets (Benner and Tushman 2003) and minimizing the need for new knowledge. As a result, aligning this focus with a subsidiary’s knowledge utilization may not be of great benefit to its product innovation performance. H3: Knowledge utilization mediates the relationship between (a) the extent of a breakthrough focus and product innovation performance and (b) the extent of a platform focus and product innovation performance.

METHODS Sample and Data Collection The data for testing these hypotheses were collected from the R&D managers or staff in charge of product development at wholly owned Chinese subsidiaries of multinational companies, primarily from the United States, Japan, Europe, and South Korea. Only wholly owned subsidiaries were surveyed, both for simplicity and because such firms were more likely to be pursuing product innovation in China. Firms with high levels of technological or marketing intangible assets are more likely to adopt the wholly owned subsidiary entry mode (Caves 1996) because shared control risks the dissipation of such assets in countries such as China, where property rights protection is weak (Guillén 2003). We limited the sample to manufacturing firms in the following sectors (based on the classifications used in China): chemicals; machinery; electrical equipment; electronics; communication equipment and computers; food and beverages; software and data services; and instruments, meters, cultural, and office machinery. All the firms are located in eastern China, mainly in the Yangtze River Delta (e.g., Shanghai, Jiangsu), the Pearl River Delta (Guangdong Province), or the Jing-Jin-Tang Economic Zone. We selected these three regions because of the large concentration of foreign investment there, which represented approximately 86% of the total realized foreign direct investment nationwide at the end of 2002 (Ministry of Commerce of the People’s Republic of China 2003).


First, we developed a survey instrument in English, mostly by adapting questions used in previous studies but also including some newly developed questions for this study. We pretested the questionnaire on a director of a U.S.-owned subsidiary in China and on several other U.S. practitioners, asking for their detailed comments on the questionnaire items. Second, a native speaker translated a revised questionnaire into Chinese, and a bilingual native English speaker back-translated it. We conducted further pretests using several MBA students to ensure the questionnaire’s clarity. We commissioned a Chinese research firm to undertake the data collection in China, as recommended in previous studies (Luo and Peng 1999; Murray, Kotabe, and Zhou 2005), and a Web-based interview method was employed. The sample was randomly selected from a mailing list the research company provided. It included each company’s name, telephone number, address, industry, products, nationality, amount of investment, and annual sales. As mentioned, we considered only wholly foreign-invested subsidiaries with parent firms in the United States, Europe, Japan, South Korea, or other developed countries and with sales of more than ¥5 mil-

lion. A total of 6798 such companies were identified, 4089 of which were successfully contacted by telephone and screened according to three criteria: (1) whether the company was a wholly owned subsidiary, (2) whether it had annual sales of more than ¥5 million, and (3) whether it was R&D oriented and had introduced at least two new products in China in the previous three years. Using these criteria, we disqualified 3420 companies. Of these, 446 refused to participate, which left 223 companies in the sample frame. Of the 223 invited companies, 103 usable cases were left for data analysis (46.2% of those invited). As Table 1 depicts, approximately 54% of the sample comprised companies from the Yangtze River Delta, 35% were from the Pearl River Delta or Fujian Province, and 11% were from the Jing-Jin-Tang Economic Zone. Thirty-seven percent were U.S. subsidiaries, 28% were Japanese, 18% were European, and 11% were South Korean. Ninety-two percent had been in operation in China for fewer than 15 years. Fifty-six percent had fewer than 200 employees, 15% had between 200 and 500 employees, and 29% had between 500 and 1000 employees. Of the respondents, 90%

Table 1. Sample Profile Variable

Categories

Frequency

Region

Yangzte River Delta

56

54.4

Pearl River Delta and Fujian Province

36

35.0

Jing-Jin-Tang Economic Zone

11

10.7

Parent nationality

Years in operation

Numbers of employees

Position

Percentage

United States

38

36.9

Japan

29

28.2

Europe

18

17.5

South Korea

11

10.7

Others

7

6.8

≤5 years

31

30.1

6–15 years

64

62.1

≥16 years

8

7.8

1–199

58

56.3

200–499

15

14.6

500–1000

30

29.1

R&D/product development management

59

57.3

Other management (e.g., foreman)

34

33.0

Engineers/staff

10

9.7

103

100.0

Sample total


were managers or directors who were in charge of or overseeing research and product development, and the rest were engineers or staff who indicated that they were responsible for product development.

Measures Product Development Strategy. We categorized a subsidiary’s product development strategy on the basis of its allocation of resources. We developed the measures using the product innovativeness scale Cooper and Kleinschmidt (1987) employed in the Project Newprod studies. The extent of breakthrough focus was indicated by the extent to which resources were allocated to projects with a high level of innovativeness (i.e., projects aiming to develop completely new products). We determined the extent of a platform focus from the extent of resource allocation to projects with moderate innovativeness, whereas incremental focus was indicated by the extent of resource allocation to projects with low innovativeness (i.e., projects that involved only minor modifications of existing products). The respondents were asked to evaluate the extent of resource allocation to a total of seven categories on a fivepoint scale (1 = “none,” and 5 = “extensive”), and we then aggregated the data for each strategic focus. More specifically, for the breakthrough focus, respondents were asked to evaluate the extent of resource allocation to two types of projects that aimed to develop completely new products that would either open up a new market (e.g., nylon) or revolutionize an existing market (e.g., the laser printer). For the platform focus, four categories were evaluated: products new to the company, a new product line, new items, and significant improvements. For the incremental focus, one category of minor product improvements was evaluated. We considered a singleitem measure appropriate and valid because the attribute was concrete and singular (Bergkvist and Rossiter 2007). Knowledge Utilization. With reference to Schulz (2001), we considered three types of knowledge flows: technology, customer, and competition knowledge. We deemed technology knowledge to encompass technological skills, information, and know-how pertaining to product innovations, including manufacturing, engineering, information systems, and product technology knowledge. Customer knowledge covers skills, information, and know-how pertaining to customers (including customer behavior) or marketing and sales (including public relations, advertising, pricing, distribution, products, and branding). Competition knowledge involves

the competitive environment and includes knowledge about competitive intensity, suppliers, industry standards, and regulations. Knowledge sources include suppliers, customers, competitors, consultants, commercial R&D centers, and universities (Laursen and Salter 2006), as well as the parent company and peer subsidiaries of the same parent. The respondents were asked to use a five-point scale (1 = “very little,” and 5 = “extensive”) to rate the extent to which they used each type of knowledge flow from each source. Then, we aggregated the data on each source to obtain a score for each type of knowledge. Overall knowledge utilization was represented by a construct consisting of the utilization of the three types of knowledge (Cronbach’s alpha = .92). Product Innovation Performance. We adapted the product innovation performance construct from the work of Im and colleagues (2003). It measured management’s perception of the market performance of the subsidiary’s new products. The respondents were asked to evaluate the contribution new products (those fewer than three years old) were making to sales volume, profitability, and customer satisfaction relative to their competitors and to their original objectives. We used fivepoint scales that ranged from “strongly disagree” to “strongly agree” (Cronbach’s alpha = .92). Control Variables. In testing the hypotheses, we included controls for subsidiary size and industry type in the analysis. We also controlled for export and R&D intensity because the international business literature suggests that subsidiaries with different strategic roles are associated with different levels of export intensity and R&D intensity and that these roles dictate distinctive orientations in product innovation (Forsgren and Pedersen 1998) and knowledge seeking (Gupta and Govindarajan 1991; Makino and Inkpen 2003).

Measure Reliability and Validity The Appendix details measures and internal reliability statistics. Table 2 presents mean values, standard deviations, and correlations. We used Murray’s procedure (Murray, Kotabe, and Zhou 2005) to examine the reliability and validity of the constructs in the model. Exploratory factor analysis confirmed the unidimensionality of the measurement items and explored the underlying factor structure. We then applied confirmatory factor analysis to establish validity. We used AMOS 5.0 software with a bootstrap procedure to amend the multivariate normality (Byrne 2001). The model fit indexes (χ2 = 34.49, d.f. = 25; Bollen-Stine bootstrap


Table 2. Mean Values, Standard Deviations, and Correlations Variable 1. Breakthrough focus 2. Platform focus 3. Incremental focus 4. Knowledge utilization

1

2

3

4

5

1.00 .15

1.00

–.11

.16

1.00

.41

.23

–.10

1.00

5. Product innovation performance

–.02

.36

–.03

.30

1.00

M

2.09

3.17

2.63

2.82

3.77

SD

1.01

.83

1.00

.66

.80

Notes: Values greater than .23 are significant at the .05 level (two-tailed). Values greater than .30 are significant at the .01 level (two-tailed).

p = .22; normed fit index [NFI] = .95; Tucker–Lewis index [TLI] = .98; comparative fit index [CFI] = .98; and root mean square error of approximation [RMSEA] = .06) indicated that the model fit the data well. All the items measuring a construct had relatively high loadings on that construct, confirming convergent validity, and the estimated correlation (.32) between the two constructs was not excessively high, confirming discriminant validity (Kline 1998). The reliability of both constructs (.92 and .92, respectively) exceeded the recommended level of .60 (Nunnally 1978), and the variances extracted for the measures (.66 and .80, respectively) were higher than the recommended .5 (Hair et al. 2006). To examine whether common method bias might be a problem, we applied Harman’s one-factor test. Podsakoff and Organ (1986) suggest that one general factor will emerge from a factor analysis if common method variance is a serious problem. The factor analysis produced no apparent general factor, which implies that common method variance was not a serious concern. We examined nonresponse bias by comparing early respondents with late respondents across all variables (Armstrong and Overton 1977). More specifically, we employed Yalcinkaya, Calantone, and Griffith’s (2007) method, comparing the first quartile with the last quartile of the sample. The results of the t-tests indicated no significant differences.

ANALYSIS AND RESULTS We tested the hypotheses using structural equation modeling because this method can directly test mediation by


examining relevant paths and taking into account measurement error (see Figure 2) (Baron and Kenny 1986). We used AMOS 5.0 software to conduct 500 bootstraps intended to amend multivariate normality (Byrne 2001). We standardized all the observed variables to reduce any multicollinearity (Cohen and Cohen 1983). Overall, the goodness-of-fit indexes indicated an acceptable fit (χ2 = 151.39, d.f. = 100; Bollen-Stine bootstrap p = .15; NFI = .84; TLI = .92; CFI = .94; and RMSEA = .07). Table 3 reports the path coefficients and their corresponding p-values based on bias-corrected methods. We found that all the independent variables except incremental focus were significantly related to knowledge utilization and product innovation performance. More specifically, both a breakthrough focus (β = .30, p < .01) and a platform focus (β = .18, p < .05) showed a positive and significant relationship to knowledge utilization, whereas an incremental focus showed no significant relationship (β = –.07, n.s.). These results support H1a–c. As Table 3 shows, each product development focus shows a distinctive correlation with product innovation performance. H2a predicts a quadratic relationship (U shaped) between the extent of a breakthrough focus and product innovation performance. The coefficient for a breakthrough focus was significant and negative (β = –.37, p < .01) and that for breakthrough focus squared was significant and positive (β = .30, p < .01), providing strong support for H2a. Noticeably, the results show that the squared term was significant and positive after we accounted for the breakthrough focus itself. The coefficients (–.37 and .30) combined are consistent with the zero-order correlation of –.02.4 The platform focus

Figure 2. Structural Model with Standardized Path Coefficients Product Deveelopment Strategy

Mediator

Breakthrough focus squared

n.s.

Outcome

Knowledge utilization

.28 *

.30 ** Breakthrough focus

.30 ** .18 *

Platform focus

–.37 ** .26 *

n.s.

Product innovation performance

n.s.

Incremental focus *Significant at the .05 level. **Significant at the .01 level. Notes: For the purpose of clarity, we omitted individual indicators, error indicators, control variables, and covariance between independent variables in the model. We calculated correlations between breakthrough focus squared, breakthrough focus, platform focus, and incremental focus, and only the correlation between breakthrough focus and its squared term is significant (r = .44, p < .01). Subsidiary size (log), industry (high-tech = 1), export intensity (log), and R&D intensity (log) were controlled. Among all the control variables, we found that export intensity (β = .47, p < .01) and size (β = –.28, p < .01) significantly affected knowledge utilization, whereas only size showed a significant impact on product innovation performance (β = .24, p < .05). n.s. = not significant.

Table 3. Structural Equation Modeling Results Direct Effects

Standardized Estimate

Breakthrough focus → product innovation performance Breakthrough squared → product innovation performance Platform focus → product innovation performance Incremental focus → product innovation performance Breakthrough focus → knowledge utilization Platform focus → knowledge utilization Incremental focus → knowledge utilization Knowledge utilization → product innovation performance

p-Value

–.37 .30 .26 –.04 .30 .18 –.07 .28