The influences of Internet-based collaboration and intimate interactions in buyer–supplier relationship on product innovation

JBR-08945; No of Pages 8 Journal of Business Research xxx (2016) xxx–xxx

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Journal of Business Research

The influences of Internet-based collaboration and intimate interactions in buyer–supplier relationship on product innovation Jie Wu a,1, Zefu Wu b,⁎, Steven Si c a b c

University of Macau and Huaqiao University, Avenida da Universidade, Taipa, Macau Huaqiao University, Quanzhou city, Fujian Province 362021, China Zhejiang University/Bloomsburg University of Pennsylvania, 866 Yuhangtang Road, Hangzhou, Zhejiang Province 310058, China

a r t i c l e

i n f o

Article history: Received 1 August 2014 Received in revised form 1 September 2015 Accepted 1 December 2015 Available online xxxx Keywords: Customer equity management Buyer–supplier relationship Internet-based collaboration Product innovation

a b s t r a c t With the increasing importance of the Internet in connecting buyer and suppliers, how does Internet-based collaboration affect firm product innovation? This study proposes that Internet-based collaboration positively affects product innovation performance of supplying firms, but too much dependence on it impedes product innovation. That is, Internet-based collaboration has an inverted U-shaped relationship with product innovation performance of supplying firms. This study further posits that face-to-face interaction between buyer and supplier strengthens the positive effect of Internet-based collaboration on product innovation, such that when the degree of face-to-face interaction is high, Internet-based collaboration is associated with better innovation performance. These propositions are tested using data from an original survey data on buyer–supplier relationships in China. The results provide strong supports for the predictions of hypotheses. © 2016 Published by Elsevier Inc.

1. Introduction As the business world is increasingly becoming customer centric, firms have continuously devoted more attentions and resources to existing and potential customers of their organizations and treat them as customer equity (CE). Unfortunately, the effect of the CE management on innovation outcome has been largely neglected. This lacuna is surprising, as in a highly dynamic, competitive environment, innovation output occupies a central position among all organizational outputs and has profound influences on firms' survival, growth and sustainability (Eisenhardt & Tabrizi, 1995). This neglect becomes particularly glaring with the widely adoption of Internet as a platform to connect with key business partners. Internet-based buyer–supplier relationship has quickly emerged as one of the key determinants that enable a firm to identify market niches, generate new features, and attract valuable customers. Understanding the effect of Internet-based collaboration on a firm's ability to produce new ideas and continually innovate thus is an urgent issue in marketing research. The recent researches on marketing strategy in digital era have devoted sustained attention to the consequences of the Internet-based marketing strategy but have failed to reach consensus as to whether it has a negative or positive effect on firm performance (Sultan & Rohm, 2004). Some scholars have suggested that the Internet allows a firm to ⁎ Corresponding author. E-mail addresses: [email protected] (J. Wu), [email protected] (Z. Wu), [email protected] (S. Si). 1 The 1st author's two affiliations are listed equally as the 1st affiliations of this article.

dialog with its buyers in real-time and at a much higher frequency than traditional media, which cements its relationships with buyers and channel members (Sultan & Rohm, 2004). The Internet reflects the opportunities that enable a firm to reach a much broader base of buyers, reduce the cost of buyer engagement, and efficiently create value for buyers (Sawhney, Verona, & Prandelli, 2005). In contrast, other scholars have emphasized the challenges a firm encounters when embracing the Internet. The direct e-commerce initiated by a firm to garner more channel control with its users generates potential conflict with its channel partners (Sultan & Rohm, 2004). Therefore, the innovation performance implications of the usage of the Internet as a collaboration platform between buyers and suppliers remain unclear. This study contributes to the literature in three areas. First, this study fills an important research gap in the marketing literature by examining how the Internet as a platform that facilitates CE management promotes product innovation. In so doing it addressed an important unresolved issue in previous researches—the nature of the relationship between the Internet-based CE and innovation outcome. Studying how the Internet-based collaboration as a form of CE can promote innovation performance can shed light on and contribute scarce empirical evidence to the research on the CE-firm value link. Second, previous studies have examined either the opportunities or challenges offered by the Internet for marketing performance. But this study argues that both perspectives provide insights into the role of the Internet-based collaboration between buyers and suppliers, but neither approach provides a complete explanation. Researchers from the opportunities' perspective have often assumed, implicitly or explicitly,

http://dx.doi.org/10.1016/j.jbusres.2015.12.070 0148-2963/© 2016 Published by Elsevier Inc.

Please cite this article as: Wu, J., et al., The influences of Internet-based collaboration and intimate interactions in buyer–supplier relationship on product innovation, Journal of Business Research (2016), http://dx.doi.org/10.1016/j.jbusres.2015.12.070

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J. Wu et al. / Journal of Business Research xxx (2016) xxx–xxx

that the availability of opportunities offered by the Internet is not a constraint and a firm can benefit from the power of the Internet without a limit. On the other hand, the challenges' perspective has recognized the drawbacks of the Internet in business and marketing, but focused its attention primarily on the negative aspect. This study argued that a combinative view of opportunities and challenges is necessary to resolve the existing controversy. Third, this study proposes that suppliers need to cultivate face-toface interaction with buyers that enables them to maximize the value and minimize the costs of the Internet-based collaboration. In particular, face-to-face interaction with buyers may help engender their trust on the focal supplier, which facilities its acquisition of buyers' in-depth information useful for product innovation. As a result, face-to-face interaction has the potential to strengthen the positive effects of the Internet-based collaboration on product innovation success. The theoretical framework is tested in an empirical analyse of Chinese firms that involve the Internet-based collaborations with customers in developing new products. The results indicate an inverted U-shaped relationship between Internet-based collaboration and product innovation. This study further demonstrates how this nonlinear relationship is moderated by in-person interaction between buyers and suppliers. The results from this study hold implications for reconsidering the role of Internet-based collaboration as an effective way of CE management that is capable of augmenting firm innovation. 2. Theoretical development 2.1. Insights from management perspectives While the CE management provides a very useful tool to effectively manage customer relationships, it has largely ignored two important aspects in customer relationship management. First, it ignores the potential risks in the relationship with customers, which may adopt opportunistic behaviors for their own benefits. Second, the CE literature does not fully take account of social interactions in cultivating trust and commitments between parties. This study proposes that the insights generated from the management perspectives can provide beneficial materials that supplement the CE's explanations. This study focuses on two management perspectives that are most relevant for inter-organizational relationship: the governance perspective, and the social exchange literature. The literature on governance alliance suggests that how to effectively manage the relationship with its suppliers is a fundamental question for a focal firm, as a supplier that often possesses a different goal and operational routine has an incentive to act opportunistically for its own interest at the expense of a buying firm (Birnberg, 1998). As such, a buying firm is often uncertain whether the supplier will act cooperatively (Lee, Jeon, Li, & Park, 2015). Governance is essential to the stability of the relationship development between the members in a supply chain (Benton & Maloni, 2005). The alliance governance literature has identified transactional mechanism and relational mechanism that govern inter-firm relations (Aulakh, Kotabe, & Sahay, 1996). Transactional mechanism is manifested in jointly stipulated contractual clauses and bilateral transaction-specific investment (Williamson, 1985). Contract and transaction-specific investment are expected to supplement each other through monitoring and incentive-based structures (Jap & Anderson, 2003). On the other hand, relational mechanism is manifested in socially embeddedness economic activities and social interactions of parties involved (Granovetter, 1985). Social embedded relationships generate standards of expected behavior and cultivate relational norms, which increase cohesiveness, social solidarity and cooperation in the business relationship (Provan, 1993). The buyer and supplier thereby develop a shared understanding of the utility of mutually beneficial behavior (Lawler & Yoon, 1996), and their values, attitudes, goals and norms will tend to converge (Mizruchi, 1989). As a result, buyers and suppliers are more willing to share ideas or initiate,

solve their conflicts and problems through joint consultations and discussion and participate in joint decision making (Gulati & Sytch, 2007). However, the dependence asymmetry and resulted power disparities in social embeddedness may result in adversarial action and impair the trust between buyers and suppliers. For example, suppliers (buyers) may exploit buyers (suppliers)'s weakness through deliberate opportunistic behavior (Wu, 2012). According to social exchange theory, social interactions between two parties focus on the role of intimate and frequent interactions in economic activities (Emerson, 1976), which increases the exchange cooperative atmosphere and creates an environment that cultivates trust and commitment between two parties (Gulati & Sytch, 2007). High levels of trust serve as a counter to the problem of moral hazard, reducing opportunistic behavior (Williamson, 1985). With increased trust, buyers and suppliers also become more open, show less defensive behavior, and accept more influence from their partners in the evaluation of new ideas, adoption of new technologies, and development of new products (Zand, 1972). Moreover, the heightened trust will make the dyadic relationship more flexible and innovative (Lorenz, 1988). Socially embedded relationship generally provides an environment of shared values, attitudes, goals and norms in inter-organizational relationship within which buyers and supplier can cooperate with each other, but sometimes act opportunistically for private interests. Social interactions create an environment that cultivates trust and reduce moral hazard. As such, this study argues that there will be some complementary effect on mitigating opportunities and improving relational performance when both social embedded relationships and social interactions are jointly used. In this study, social embedded relationships refer to Internet-based connections between buyers and suppliers, and social interactions refer to face-to-face interactions of managers from buyer firms and supplier firms. Relationship performance is defined as an innovation outcome of a buyer–supplier partnership in the form of increase new product sales. 2.2. Internet-based collaboration Over the last several decades, the Internet has achieved unprecedented growth and quickly become a global medium. It creates an open, cost-effective and ubiquitous network that greatly reduces the constraints of geography and distance (Cairncross, 1997). In the physical world, communicating and absorbing rich information require physical proximity for close interactions among parties. Substantial costs and efforts needed limit a firm's ability to engage in a large number of buyers. While a firm can partly overcome the physical constraint through customer survey, this approach is thwarted by the speed of buyer engagement and the limited capacity to tap into the buyer's indepth information. Other traditional market research techniques like focus groups are limited in terms of the frequency with which firms can engage with customers, and the time taken to solicit buyer input. Instead, in the Internet-based network, the physical and cognitive effort needed for the firms as well as buyers is far lower, so the interactions between two parties can be more frequent and more persistent in virtual environments (Sawhney et al., 2005). Moreover, the WWW provides the opportunity for supplying firms to increase their hours of business on a global spectrum. The Web also help ease doing business overseas by avoiding regulations and restrictions that a company must follow if it physically expands to other countries (Kiani, 1998). Flexible accessibility and cost-effective overseas expansion increase the number and coverage of potential buyers. Moreover, the Internet allows a firm to create virtual communities that greatly facilitates buyer engagement. With the creation of virtual environments, buyers can choose, based on their interests, to participate in specific discussion groups, blogs, bulletin boards or communities, and, after participation, they can flexibly decide the time of and the level of involvement with other customers (Hagel & Singer, 1999). The Internet-based virtual environments thus offer buyers a platform

Please cite this article as: Wu, J., et al., The influences of Internet-based collaboration and intimate interactions in buyer–supplier relationship on product innovation, Journal of Business Research (2016), http://dx.doi.org/10.1016/j.jbusres.2015.12.070

J. Wu et al. / Journal of Business Research xxx (2016) xxx–xxx

where they can “interact with firms at different levels of commitment based on their interests and perceived payoffs from interaction, and they can modify their level of participation as their commitment increases over time” (Sawhney et al., 2005). This makes them highly involved in a joint experience of co-creation. Equally importantly, compared to other communication media, the Internet-based interactive communication media has another important advantage—“memory”. It enables firms to contact the buyer firms uniquely in time and space, as the information in terms of what products or services purchased can be captured on the Web for future use by the marketer (Stewart, Pavlou, & Ward, 2002). Hammond, Pluim, and Eynde (1995) suggested that one of the benefits of Internet advertising is that each time a user connects to a Web site, the site provider has a record of the user's electronic address and so it can build lists of early adopters who “browse” the Internet. What is more new is lowcost and high-speed electronic management of dialog (Kiani, 1998). The costs of holding a customer's name, address, and purchase history on-line has been much lowered and electronic marketers can do what a traditional marketing can but with much more flexibility and a better memory. Such easy accountability provides the opportunities for sellers to “create individual relationships, managing markets of one, and addressing each in terms of its stage of development” (Blattberg & Deighton, 1991). A firm using the Web-based media can monitor its buying firms' online activities and learn about their courses of continued purchase behaviors, based on which firms customize and tailor either the product/service or the marketing efforts to one consumer at a time (Kiani, 1998). However, the Internet-based collaboration theory suggests that the key constrain in the Internet-based collaboration between buyer and supplier is the extent of buyer's willingness to participate in interactions (Dutton & Shepherd, 2006; Sawhney et al., 2005). As buyers get closer to the Internet, they encounter various problems such as viruses, spam, disguised information, and obscene mail entailed in the use of the Internet. Virtual environments also expose buyers to a loss of privacy and other risks when online (Dutton & Shepherd, 2006). As a result, buyers cast doubt on the Internet-based communication channel and are less willing to share with their supplier the deep information (Sawhney et al., 2005). Moreover, although the Internet-based virtual network enables a firm to engage in a much larger number of the buyers than the traditional media, the increased scope and diversity of buyers may go beyond a firm's capacity and result in information overload problem. Therefore, firms that engage buyers through the Internet to solicit feedback may find themselves immersed in a sea of information, but unable to effectively absorb and transform the information into a product desired for the latter. 3. Hypotheses 3.1. Internet-based collaboration and product innovation While many communications in B2B is still covered by face-to-face meeting or telephone communication, it is important to notice that in new product development, firms increasingly rely on Internet-based collaboration in communicating ideas across areas, coordinating different team working located in different time zone, and solving the conflicts in technological standards. The level of the Internet-based collaboration in the buyer–supplier relationship thereby affects product innovation performance positively by providing three substantive benefits: access new ideas and concepts generated by buyers, better understand buyer preferences, and reduce uncertainty. First, virtual environments enable buyers to flexibly contribute their innovation ideas throughout the new product development (NPD) process. Many online techniques such as suggestion box, advisory panels and Web-based idea markets allow buyers to contribute their ideas for new products as well as services, as Ben & Jerry did on its Web site by creating a dedicated area called “Suggestion-a-Flavor” where buyers post their ideas and

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suggestions on new product and services (Sawhney et al., 2005). Virtual environments also allow buyers to directly participate in designing and developing new products at the later stage of the NPD process. In an open, virtual community run by and for the users, peer-to-peer collaboration (i.e. buyers collaborate with other buyers) is possible: it brings together buyers who have common interests and engage in online conversations to share their experiences with each other (Kozinets, 1999). Virtual communities are a rich source of socially generated knowledge. In these systems, buyers not only make individual contributions to new product development, but also interact with hundreds and even thousands of other buyers to collectively contribute to the new product development in a community-based effort (Von Krogh & Von Hippel, 2003). Thus, the Internet has shifted one-way knowledge import to a two-way knowledge flow between a supplier firm and its buyer to a multiple-way knowledge share among the focal supplier, its buyer and the buyer's peers. Second, the Internet-based open innovation helps a supplying firm better understand its buyers' preferences and needs. Open innovation model welcomes buyers to participate in different stages of new product developments and, consequently, the supplying firm can access external knowledge possessed by buyers. External information and knowledge acquired from open innovation model via the Internet are quite diverse. The reason is that the users are usually involved in all kinds of forums and provide various feedbacks based on distinct backgrounds. As a result, information and resources accumulated from Internet-based open innovation tend to be broad and diversified, cross-technology, cross-divisions, cross-industry, and cross-products. The supplying firm can sort diversified information and identify complementary components to achieve knowledge synergies and, based on which, it can conduct high-level analyses and integrate the most valuable knowledge with its internal resources and capabilities to develop new products. Moreover, the accountability of the Web enables a supplying firm to trace transaction histories of its buyers over the lifetime, and decide what kind of products or services can best serve each buyer (Kiani, 1998). Some online techniques (e.g., listening in) record and analyze information exchange between individual buyers and virtual experts who provide advice to help buyers identify product concepts that best meet their needs (Urban & Hauser, 2004). They help firms identify emerging needs that buyers are not able to articulate but will become a major trend in a rapidly changing market, which will be used to guide their development and refinement of new concepts and products. A third positive effect of the Internet-based collaboration emerges through uncertainty reduction in new product introductions. The Internet-based platform facilitates market testing of the NPD process. Digital environments enable a firm to significantly simplify its new product testing stage before launching a product on the market. New technologies such as rapid prototyping, simulation, and combinational methods help a firm quickly and efficiently generate and test different product versions through digital media (Thomke, 1998). The Web makes it possible to simultaneously test different product configurations (virtual product testing) as well as different market mixes to complement the supply (virtual market testing) in order to choose the best solution to address changing buyer needs (Dahan & Srinivasan, 2000). However, the positive effect of the Internet-based collaboration on product innovation of supplying firms may decline after it reaches a high level. First, with the increased experience of using the Internet, buyers learn about the complex and difficult-to-manage issues surrounding online reliability, security and privacy. They encounter all sorts of bad experiences such as online fraud, biased information, or misinformation, privacy and secret information at risk (Dutton & Shepherd, 2006). All these increase a sense of the risks entailed in the use of the Internet and result in distrust and conflict in the buyer– supplier relationship. The presence of buyer's distrust on suppliers leads the former to be less willing to disclose key information to the

Please cite this article as: Wu, J., et al., The influences of Internet-based collaboration and intimate interactions in buyer–supplier relationship on product innovation, Journal of Business Research (2016), http://dx.doi.org/10.1016/j.jbusres.2015.12.070

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latter. As a result, the supplying firm finds difficult to tap into social dimensions of buyer knowledge (e.g., past purchase history) that is critical for a customized product or service (Kiani, 1998). Further, the increased size and scope of buyers places a strain on its management and its absorptive capacity. Beyond a certain point the innovation benefits should diminish as the costs of managing and absorbing diverse information derived from a very large number of buyers increase significantly. Not only are firms required to manage information contributed by individual buyers, but they must also integrate social knowledge generated from millions of blogs, discussion groups and bulletin boards across different geographies, culture and ethnic groups. Knowledge from very different contexts are often deeply rooted in a set of rules, procedures, conventions, beliefs, codes and cultures, which may not relate well with each other as well as a firm's existing knowledge structure, organizational practices and culture. However, there is a natural limit to the time and effort that any firm can devote to managing diverse information and knowledge. For firms highly embedded in Internet-based interactions with a large number of buyers, correct understanding and interpreting diverse information become extremely difficult. The costs are likely to rise substantially with the increased information load, which may exceed an organization's capacity, leading to the information overload problem. Therefore, the costs resulting from high levels of information diversity will overtake the benefits and the net impact on product innovation success will become negative (Ozer & Dayan, 2015). Firms dealing with intermediate scope of Internet-based interaction with buyers will have the opportunities of exposure to much new information while keeping the costs of managing diverse information at a reasonable level. These arguments lead to the following hypothesis:

relationship, competency trust gives a buying firm a sense of confidence that its supplier is capable of accomplishing given tasks. It motivates the buying firm to get highly involved in various stages of NPD process through multiple communication channels and actively contribute its ideas and suggestions to co-create new products. Second, frequent face-to-face interaction between a buying firm and a supplying firm offers the former an opportunity of evaluating the latter's intention. When a buying firm feels assured that the supplying firm will cooperate in good faith, good intention and integrity, it engenders the buying firm's goodwill trust on the supplying firm (Das & Teng, 2001). Goodwill trust fosters a closer relationship between the buyer and supplier which encourages the former to participate in information exchange with the latter, which in turn gives the latter a chance to “court” the former (Doney & Cannon, 1997). Thus, face-to-face interaction nurtures a cooperative environment which promotes information flow between buyers and suppliers (Das & Teng, 1998). Coupled with a cooperative environment and the buying firm's willingness to share important information, the supplying firm using the Internet as a channel to communicate with buying firms regarding the new product development is more likely to acquire in-depth information that is useful for product innovation success.

Hypothesis 1. The degree of the Internet-based collaboration for customer equity has an inverted U-shaped relationship with product innovation performance of supplying firms such that their product innovation performance firstly increases but then declines after the level of the Internet-based collaboration crosses some threshold.

4.1. Data and sampling

3.2. Facilitating role of intimate interactions To overcome the drawbacks of the Internet-based collaboration, face-to-face interaction is necessary for firms to boost buying firms' trust. Face-to-face interaction in this study refers to face-to-face interactions between managers of buying firms and managers of supplying firms through which information is transmitted and received. Face-toface interaction has been classified, among a variety of communication methods, to be a complex information-conveying channel that can provide the richest information (Mohr & Nevin, 1990). Empirically, face-toface interaction between managers of buying firms and managers of supplying firms has been shown to be a key determinant of building and maintaining trust in the relationship. For example, in their study of business contacts in the insurance field, Crosby, Evans, and Cowles (1990) found a positive relationship between interpersonal contact intensity and salesperson trust. Doney and Cannon (1997) similarly found that frequent (business and social) face-to-face interaction promotes buying firm's trust. This study thereby argues that face-to-face interaction between managers of buying firms and managers of supplying firms enhances the positive effect of the Internet-based collaboration on product innovation performance. First, strategic alliance scholars have argued that face-to-face interaction enables two partnering firms to identify more commonalities and develop better understanding of mutual needs and capabilities, which cultivates competency trust (confidence on partner's competence or expertise) (Das & Teng, 2001). A firm's reputation of competency suggests a high probability of getting things accomplished successfully and helps its partners to predict the focal firm's successful chance with confidence. With respect to the buyer–supplier

Hypothesis 2. Face-to-face interaction in the buyer–supplier relationship strengthens the positive effect of the Internet-based collaboration for customer equity on product innovation performance of supplying firms.

4. Data and methods

These propositions are tested using data from a survey data on buyer–supplier relationships in China. The survey covers 600 firms operating in China. Before the formal survey, the questionnaire is pilot tested to ensure the questions are properly worded and well understood in the context of Chinese business. The authors contact the Chief Executive Officers to explain the purpose of the study. After one week, they contact the CEOs or their delegates by telephone to ensure their participation in the study and to make appointments for their responses to the survey. The authors design the survey as consisting of two separate questionnaires that are supposed to be answered by three different groups of respondents. The first part is completed by product managers who provided the information on product innovation and their outcomes, and the second part is completed by marketing managers who provide the information on the relationship with customers, and the third part is completed by the accounting managers who provide basic profile information such as about a firm's ownership, labor force size, and the established year and so on. Such a survey methodology ensures access to the right respondents, confirms the correct use and understanding of the terms. After excluding items with missing values, the final sample comprises 499 firms. Of the 499 firms, about 46% are of medium size with between 100 and 1000 employees and 41% are smaller with less than 100 employees. About 35% had been in business between 5 and 10 years, with another 38% aged between 10 and 30 years, 16% older and 11% aged less than 5 years. 4.2. Measures 4.2.1. Dependent variable 4.2.1.1. Product innovation. Product innovation is measured in terms of the percentage of total sales accounted by new products a firm had introduced to the market in 2011. The percentage of new product sales is an important indicator of product innovation because it indicates

Please cite this article as: Wu, J., et al., The influences of Internet-based collaboration and intimate interactions in buyer–supplier relationship on product innovation, Journal of Business Research (2016), http://dx.doi.org/10.1016/j.jbusres.2015.12.070

J. Wu et al. / Journal of Business Research xxx (2016) xxx–xxx

the realized commercial significance of a firm's innovation activities and “most innovations cannot influence firm performance until the ideas have been put into use and introduced to the market” (Katila, 2002: 996). Previous studies have shown that the percentage of new product sales increases market share and market value (Chaney & Devinney, 1992), improves firm performance (Roberts, 1999), and enhances a firm's survival chances (Banbury & Mitchell, 1995). To check the construct validity, the authors have randomly selected thirty percentages of the sampled firms and conducted the face-to-face interview with the managers of these firms. The managers in the interview consistently reported that the new products introduced by their firms are indeed innovative. Product innovation in this study refers significant improvements in features and functions of new products that have not been introduced to the market by other firms before. Minor changes in packages and looking are not considered. This information confirms the construct validity of the measure of the dependent variable.

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effect on innovation (Hu, 2001), so government ownership percentage is another control. Fourth, foreign ownership may serve as an important learning channel through which the focal firm can acquire advanced technologies and develop technological capabilities that they need for product innovation. Thus, foreign ownership is also included, measured by the overall percentage of stakes owned by foreign investors including foreign individuals, foreign institutional investors, foreign firms, and foreign banks. Because the sample includes firms from multiple manufacturing industries, assessing the risk of heteroscedasticity is needed. The authors conduct White's generalized test (Bowen & Wiersema, 1999). The test statistics indicate no heteroscedasticity concerns. Moreover, the authors create “dummy” variables representing industries and cities to model coefficient variations, as this modeling coefficient variation alleviates concerns about possible heteroscedasticity associated with pooling of the data (Greene, 1994). In addition, the authors also include a location dummy variable to control regional effect.

4.2.2. Independent variables 4.3. Statistical modeling 4.2.2.1. Internet-based collaboration (IBC). On the basis of previous work by Sawhney et al. (2005) and by Mohr, Fisher, and Nevin (1996), this study measures Internet-based collaboration between a buying firm and a supplying firm as a composite construct reflecting the extent to which a supplying firm uses the Internet as a media to collaborate and communicate with its buying firms regarding new product development. Specifically, this composite construct consists of three items: (a) the supplier firm engages its buyer firms through the Internet in the process of new product development; (b) the supplier engages its buyer firms through the Internet in testing market responses to its new products; and (c) the supplier collects the feedbacks through the Internet from its buyer firms concerning the strengths and weakness of new products. Following the prior studies (Mohr & Nevin, 1990), face-to-face interaction (FTFI) in this study is measured by a composite construct reflecting the percentage of face-to-face interaction between managers of a buying firm and managers of a supplying firm, out of all sorts of interactions, that managers from two parties spent their time and efforts in connecting and communicating with each other. This composite construct consists of two items: (1) the percentage of time managers of the supplier firm spent with managers of the buyer firm in communicating and discussing new products; and (2) the times of purchase contracts completed between the buyer firm and the supplier firm meet and discuss new products. The authors assess construct validity and reliability in accordance with the approaches recommended by Anderson and Gerbing (1988). Specifically, the authors run exploratory factor analyses for each multi-item construct and the results show that all factor loadings are highly significant (p b 0.001), and the composite reliabilities of all constructs exceed the 0.70 benchmark, and all average variance extracted (AVE) are greater than 0.50. The authors also estimate an overall confirmatory measurement model and the model achieves a satisfactory fit to the data (goodness-of-fit index = 0.92, comparative fit index = 0.93, incremental fit index = 0.92). The authors therefore conclude that these constructs demonstrate strong construct validity and reliability.

The dependent variable, the percentage of total sales accounted by new products introduced, takes non-negative values. Poisson regression or negative binomial regression modeling can be used to analyze this sort of data. However, a Poisson regression model assumes that the mean be equal to the standard deviation. This assumption is not suitable for this dataset. In contrast, the negative binomial regression does not have this strict assumption. The authors thus applied the negative binomial regression in the analyses. The probability density function of negative binomial can be derived from Poisson-gamma mixture model (1) with gamma heterogeneity where the gamma noise has a mean of 1. The gamma mixture accommodates over-dispersed Poisson counts as following: f ðy; λ; μ Þ ¼

e−λi μ i ðλi μ i Þyi : yi !

ð1Þ

The conditional mean of y under gamma heterogeneity is thereby expressed as λμ, and the unconditional distribution of y can be derived from the following expression (2): Z∞ f ðy; x; μ Þ ¼ 0

e−λi μ i ðλi μ i Þyi g ðμ i Þ∂μ i : yi !

ð2Þ

For this model a gamma distribution is given μ = exp(xβ + ε), assigning a mean of 1 to the gamma distribution, thus have Eq. (3): Z∞ f ðy; x; μ Þ ¼ 0

e−λi μ i ðλi μ i Þyi ν ν ν−1 −υμ i μ e ∂μ i : yi ! Γ ðυÞ i

ð3Þ

5. Results 5.1. Main results

4.2.3. Control variables The authors include several variables in the regression models to exclude alternative explanations. First, large firms may have more resources (e.g., human, capital) for product innovation (Eisenhardt & Tabrizi, 1995), so this study thus controls firm size in the analysis, measured by the total number of employees. Second, prior studies provide different predictions about the effect of firm age on innovation performance (e.g., Sorensen & Stuart, 2000), so firm age is included without predicting a specific influence. The study controls for firm age, which is measured by the number of years since the established year. Third, prior studies have shown that government ownership has a negative

Table 1 reports the descriptive statistics for the variables used in the data analyses. A review of the correlations among the independent variables suggests that multicollinearity is not a major concern. This is confirmed with the analysis of variance of inflation (VIF). The VIF values range from 1.17 to 4.41, well below the cutoff threshold of ten, which indicates that there are no serious multicollinearity problems in the models (Hair, Anderson, Tatham, & Black, 1998). Table 2 reports the results of the regression analyses. M1 includes all the controls, M2 adds the main effect of Internet-based collaboration and its squared term, M3 adds the main effect of face-to-face

Please cite this article as: Wu, J., et al., The influences of Internet-based collaboration and intimate interactions in buyer–supplier relationship on product innovation, Journal of Business Research (2016), http://dx.doi.org/10.1016/j.jbusres.2015.12.070

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Table 1 Means, standard deviations and correlations. Variables 1 2 3 4 5 6 7

Product innovation IBC FTFI Firm age Firm size Government ownership Foreign ownership Mean S.D.

1

2

3

4

5

0.06⁎ 0.05⁎ 0.08⁎ 0.18⁎ −0.01

1.00 −0.27⁎ −0.13⁎ 0.08⁎ −0.15⁎

1.00 0.02 −0.07⁎ 0.04

1.00 0.39⁎ 0.32⁎

1.00 0.19⁎

0.05⁎

0.23⁎

−0.15⁎

−0.18⁎

0.08⁎

0.3 0.90

0.1 0.14

13.5 15.03

5.1 1.55

6

7

1.00

0.3 0.26

1.00 −0.20⁎ 0.2 0.39

1.00 0.2 0.29

⁎ Indicates significance at the p ≤ 0.05 level of confidence.

interaction, and M4 is the full model, including all the main effects and interaction terms. To reduce any potential multicollinearity, the predictor and moderator variables are mean-centered before creating the interaction terms (Aiken & West, 1991). The log-likelihood ratios and chi-squares for these models indicate significant explanatory power. The smaller values of Akaike's information criterion (AIC) and the Bayesian information criterion (BIC) as well as the larger value of pseudo R square in M4 suggest that the relative goodness of fit is significantly improved in the full model. Hypothesis 1 predicts that the level of Internet-based collaboration has an inverted U-shaped relationship with product innovation output. As shown in M2 and M4, the coefficient of Internet-based collaboration is positive and significant (β = 5.25, p ≤ 0.01 in M2; β = 13.18, p ≤ 0.001 in M4), whereas the coefficient of Internet-based collaboration2 is negative and significant (β = − 8.88, p ≤ 0.001 in M2; β = − 34.72, p ≤ 0.001 in M4). Therefore, the level of Internet-based collaboration

has an inverted U-shaped relationship with product innovation performance, in support of Hypothesis 1. Hypothesis 2 proposes a moderating role for face-to-face interaction in the relationship between Internet-based collaboration and product innovation performance. As M4 shows, the first-order interaction between Internet-based collaboration and face-to-face interaction positively and significantly (β = 30.94, p ≤ 0.05) predicts innovation output, whereas their second-order interaction is negative and significant (β = −92.81, p ≤ 0.01). These results suggest that face-to-face interaction strengthens the positive relationship between Internet-based collaboration and product innovation output (Aiken & West, 1991). So Hypothesis 2 is also supported. To further facilitate the interpretation, the interaction effects are plotted in Fig. 1 following Aiken and West (1991)'s method for interaction terms. To create this figure, all of the variables in M4 except Internet-based collaboration and face-to-face interaction are constrained to their mean values. Face-to-face interaction is split into two groups—low (one standard deviation below the mean) and high (one standard deviation above the mean)—and the relationship between Internet-based collaboration and innovation performance is estimated separately for each level. Fig. 1 shows that at the high degrees of face-to-face interaction, Internet-based collaboration has a stronger positive relationship with innovation performance; the first-order effect is stronger when the degree of face-to-face interaction is high than when it is low. The optimal level of Internet-based collaboration in low degree of face-to-face interaction is moderate, whereas when face-to-face interaction is more frequently used in connecting with buying firms the optimal level rises. These results suggest that face-to-face interaction strengthens the positive relationship between Internetbased collaboration and product innovation output. Overall, these results are consistent with the predictions of Hypotheses 1 and 2. 5.2. Robustness check

Table 2 Hypothesis testing. Variables

M1

M2

M3

M4

Constant

0.85 (0.49) 0.01 (0.01) 0.53⁎⁎⁎

0.89 (0.50) 0.01 (0.01) 0.50⁎⁎⁎

0.52 (0.52) 0.01 (0.01) 0.50⁎⁎⁎

0.40 (0.54) 0.01 (0.01) 0.49⁎⁎⁎

(0.08) −0.19 (0.25) 0.36 (0.38) (Included) (Included)

(0.08) −0.13 (0.25) 0.30 (0.39) (Included) (Included) 5.25⁎⁎

(0.08) −0.13 (0.25) 0.38 (0.39) (Included) (Included) 5.62⁎⁎

(0.08) −0.12 (0.26) 0.42 (0.39) (Included) (Included) 13.18⁎⁎⁎

(1.76) −8.88⁎⁎⁎ (2.58)

(1.76) −8.99⁎⁎⁎ (2.59) 0.88⁎

(3.39) −34.72⁎⁎⁎ (9.00) 1.25⁎

(0.37)

(0.57) 30.94⁎

Firm age Firm size Government ownership Foreign ownership Industry dummy Location dummy IBC IBC2 FTFI IBC × FTFI IBC2 × FTFI Log-likelihood AIC BIC Degree of freedom χ2 Prob. N χ2 Pseudo R2

−421.00 869.99 944.37 13 128.64 0.00 0.13

−415.01 862.02 947.02 15 140.62 0.00 0.16

−412.12 858.24 948.55 16 146.40 0.00 0.20

One possible concern on Internet-based collaboration could be that the relationships that have been found may vary across different types of collaborations. To alleviate this concern, the authors divide the whole sample into three types of collaborations: R&D-centered collaboration (150); purchasing-centered collaboration (120), and financialcentered collaboration (100), and excluded those collaborations without clear information on the nature of collaboration. The authors then re-run the analyses for each sub-sample and report the results in Table 3. As shown in Models 5, 6, and 7, Internet-based collaboration has an inverted U-shaped relationship with product innovation performance across three types of collaboration, and face-to-face interaction between buying and supplying firms strengthens the positive effect of

(12.99) −92.81⁎⁎ (30.40) −406.78 851.55 952.49 18 157.09 0.00 0.26

N = 499. Robust standard errors are given in parentheses. ⁎ Indicates significance at the p ≤ 0.05 level of confidence (two-tailed tests). ⁎⁎ p ≤ 0.01. ⁎⁎⁎ p ≤ 0.001.

Fig. 1. The joint effect of Internet-based collaboration and face-to-face interaction on firm product innovation.

Please cite this article as: Wu, J., et al., The influences of Internet-based collaboration and intimate interactions in buyer–supplier relationship on product innovation, Journal of Business Research (2016), http://dx.doi.org/10.1016/j.jbusres.2015.12.070

J. Wu et al. / Journal of Business Research xxx (2016) xxx–xxx Table 3 Regression analyses based on different types of relationship between buyer and supplier. Variables

M5 (financial)

M6 (R&D)

M7 (purchase)

Constant

0.74 (0.42) 0.02 (0.01) 0.41⁎⁎⁎ (0.07) −0.14 (0.15) 0.32 (0.44) (Included) (Included) 4.45⁎⁎ (1.67) −6.77⁎⁎⁎

0.42 (0.32) 0.01 (0.01) 0.42⁎⁎⁎ (0.08) −0.16 (0.22) 0.39 (0.42) (Included) (Included) 15.76⁎⁎ (1.44) −17.89⁎⁎⁎

0.33 (0.44) 0.02 (0.01) 0.49⁎⁎⁎ (0.06) −0.13 (0.21) 0.29 (0.36) (Included) (Included) 8.81⁎⁎⁎ (2.49) −14.72⁎⁎⁎

(2.81) 0.41⁎ (0.34) 29.15⁎ (10.25) −44.33⁎⁎ (29.21) −404.71 762.02 417.21 12 135.24 0.00 0.15

(3.11) 0.78⁎ (0.38) 41.44⁎ (11.11) −51.18⁎⁎ (27.41) −422.82 723.42 548.65 14 144.14 0.00 0.16

(4.01) 0.65⁎ (0.46) 30.94⁎ (12.99) −42.81⁎⁎ (30.40) −406.78 741.15 512.91 13 145.01 0.00 0.11

Firm age Firm size Government ownership Foreign ownership Industry dummy Location dummy IBC IBC2 FTFI IBC × FTFI IBC2 × FTFI Log-likelihood AIC BIC Degree of freedom χ2 Prob. N χ2 Pseudo R2

Number of observations in Model 5 is 150; number of observations in Model 6 is 120; number of observations is 100. Robust standard errors are given in parentheses. ⁎ Indicates significance at the p ≤ 0.05 level of confidence (two-tailed tests). ⁎⁎ p ≤ 0.01. ⁎⁎⁎ p ≤ 0.001.

Internet-based collaboration. More interestingly, these effects are more significant for those R&D-centered collaborations (Model 6) than financial-sharing collaboration (Model 5) and purchase-related collaboration (Model 7). These results provide additional supports for the arguments concerning the positive influences of Internet-based collaboration and its interaction with face-to-face interaction effect on product innovation.

6. Discussion and conclusions This study examines the effects of the Internet-based collaboration and face-to-face interaction in the buyer–supplier relationship on product innovation performance. The results show that the level of the Internet-based collaboration between buyers and suppliers has an inverted U-shaped relationship with product innovation performance of supplying firms, and face-to-face interaction enhances the positive relationship between the Internet-based collaboration and product innovation performance. These findings thereby contributed to existing literature in three major ways. First, it contributes to the CE literature by providing two important arguments that have been ignored in the previous studies adopting CE perspective. The emphasis on customer equity results in its inattention to potential opportunistic behaviors and the governance mechanism that can mitigate such opportunistic behaviors. This study draws on the literature on inter-firm relationships to develop a framework that addresses their limitations associated with the CE perspective. In doing so, the study supplements the CE perspective by providing necessary additional theoretical insights that overcome the CE's limitations. Moreover, this study extends this integrative framework to examine the effect of the Internet-based collaboration on firm product innovation. Therefore, this study advances the CE literature by providing this integrative approach. The empirical findings provide the support for

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the linkage between the CE and firm innovation outcome, which has opened a new direction for examining the role of CE for firm value. Second, the findings resolve a debate in previous studies on the relationship between the Internet-based collaboration and product innovation performance. While the Internet-based collaboration with buyers does enhance a firm's product innovation success, this effect rests on the level of Internet-based collaboration: There exists an inverted Ushaped relationship between Internet-based collaboration and product innovation performance in the way that a moderate level of the Internet-based collaboration relates to the highest degree of product innovation success, whereas too high level of the Internet-based collaboration actually inhibits a firm's product innovation. As a firm heavily relies on the Internet as a platform to interact with a large number of buyers, the increased size and diversity of buyers place a strain on its management and absorptive capacity. Beyond a certain point, the innovation benefits will diminish as the costs of managing and absorbing diverse information derived from distinct culture, ethnic groups and markets. Therefore, the positive effect of the Internet-based collaboration with buyers on product innovation declines. These findings enrich extant literature by demonstrating the possible liabilities of the Internet-based collaboration and communication: too much dependence on the Internet as a method to communicate with buyers may expose the focal firm to the risks of distrust between two parties. These findings not only reconcile the conflicting views about the opportunities and challenges offered by the Internet, but also add significantly to the existing anecdotal evidence and case studies that indicate the failure of the Internet-based firms in the face of distrust and conflicts in virtual environments. Third, this study examines the boundary conditions of the CE-firm value by proposing and confirming empirically that face-to-face interaction among managers of buying and supplying firms helps the focal supply build trust with its buyers and get them engaged through the Internet in new product development. Recent researches suggest that interpersonal interaction promotes the trust, encourages commitment and loyalty, and thereby enables firms to acquire useful information from buyers for new product development. This study proposes that face-to-face interaction between managers of buying and supplying firms as an important communication method not only directly affects product innovation success, but also works together with other communication channels in promoting product innovation success. Consistent with this proposition, the results show that face-to-face interaction enhances the positive effect of the Internet-based collaboration between the buying firms and the supplying firms on product innovation performance of supplying firms. This is, face-to-face interaction makes the positive influence of the Internet-based collaboration stronger and shifts its optimal point for innovation from a moderate to a high level. The findings also provide some important managerial implications. Firms must be aware of the limitations of the Internet-based collaboration with buyers in promoting product innovation. Internet-based communication may trap them in virtual environments, lock them in distrust buyer–supplier relationship, and prevent them from acquiring in-depth information. To overcome such challenges, the Internetbased firms should allocate necessary resources to interpersonal interactions with managers of buying firms. Such intimate interaction stimulates greater trust, which may help the focal firm escape the liabilities of virtual environments. To cultivate intimate relationship with buyer firms, companies should redesign organizational structure such as technology-based teams and human-based teams can co-exist within business units and maintain an organizational culture that encourages the absorption and integration of complementary forms of knowledge through different mechanisms. The findings should be interpreted with some caution. First, the analysis of the effects of Internet-based collaboration and face-to-face interaction on product innovation is limited to B2B buyer–supplier relationship. Further research should examine these relationships in other domains (e.g., B2C or C2B) and investigate the role of the different

Please cite this article as: Wu, J., et al., The influences of Internet-based collaboration and intimate interactions in buyer–supplier relationship on product innovation, Journal of Business Research (2016), http://dx.doi.org/10.1016/j.jbusres.2015.12.070

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J. Wu et al. / Journal of Business Research xxx (2016) xxx–xxx

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