Introduction In the past study, the relationship between the power structure of marketing and research and development (R&D) and NPD performance was not consistent (Atuahene-Gima & Evangelista, 2000; Engelen & Brettel, 2012; Li & Atuahene-Gima, 1999, 2001). The inconsistency may result from each study in different industrial contexts. It reflects every NPD project faces different environmental uncertainties. Furthermore, we adopt the external control perspective to glue power structure and NPD performance under a certain external environment together. Therefore, this paper tends to fulfill the gap of prior study, and the main objective of this research is to investigate whether the power structure of marketing and R&D functions have different linear relationships under the different level of environmental uncertainty. A NPD team is like a cross-functional organization that the NPD team is composed of multiple functions, and it has independent budgets. The members in the team will allocate their limited resources like budgets or positions to respond environments and to maximize profits. Theoretical Development When a NPD team faces the high market uncertain situation, marketing function can gather more resources because of its own power. Thus, R&D members in a NPD team may have less determination in the process of NPD. Even though they create a new product, marketing specialists make most decisions in the NPD team. According to function’s contribution argument, the more contribution of a certain function to the NPD process, the more positive related to the new product success (Atuahene-Gima and Evangelista, 2000; Atuahene-Gima and Luca, 2008; Li and Atuahene-Gima, 1999). Therefore, the current study proposes the hypothesis1 described below: H1: Market uncertainty will strengthen the relationship between power structure leaned to marketing and NPD successes. When a NPD team encounters the fast technological change situation, R&D function has more resources because of power. New product teams, however, usually have scare resources, so that another important function like marketing will have fewer resources than R&D function. Thus, marketers in a NPD team may have less determination in the process of NPD. The marketers may have some influence on launch stage like sales and promotion or distribution channels (Hsieh et al., 2008), but R&D specialists make most decisions in a NPD team. Therefore, the current study proposes the hypothesis2described below: H2: Technological uncertainty will strengthen the relationship between power structure leaned to R&D and NPD successes. Eisenhardt and her colleagues indicated that the organizations in high velocity environments have better performance when they decentralize the power structure (Eisenhardt, 1989; Eisenhardt and Bourgeois, 1988). They also described that this firm tended to introduce a new product line, and that its channel partners were fighting with each other by price wars but the dominant marketing function did not have enough time to perform its regular job. To maintain its power and resources, the dominant function may highlight its importance, so it will withhold external information and enable other members to perceive the external environment what dominant function expect them to perceive. When organizations find a lot of environmental changes, it is too late. Therefore, in the beginning organizations adopted decentralized power structure, and allocated resources equally. The members in organizations may not snatch resources, so they may not take political actions also. For the specialists in new product development team, they could not control their unique knowledge to withhold the information and to satisfy their own self-interests. Therefore, the relationship between marketing and R&D power distribution in a NPD team and new product financial performance is weakened in high velocity environments (Eisenhardt and Bourgeois, 1988). The hypothesis3 in the current study is below: H3: the relation between the power distribution in new product development teams and new product development successes is inverted U curve under the high technological and market uncertainty. Coping environment could rely on top manager’s backgrounds like marketing, technology or finance (Hambrick and Mason, 1984). To maintain the status of the dominant function, the dominant function will lead the organization to identify the important problems related to its function. In order to ensure keeping their power, moreover, the dominant function could institute some regulations or create norms. According to resource dependence perspective, if an organization has higher the formalization of power, the dominant function could gather more resources because of legitimacy. Further, the higher formalization of power may strengthen the relationship between power distribution and performance. Thus, our hypothesis 4 is below: H4: Under the higher formalization of power in a new product development team, the stronger relationship between the marketing and R&D power distribution and new product performance than under the lower degree of formalization of power situation. Research Design The current study used questionnaire survey and purposive sampling method to collect data. In order to eliminate the bias of common method variance (CMV), this study conducted multiple sources including project managers, the member charging marketing, and the member charging R&D to administrate questionnaires differently. In order to avoid selection bias, this study, moreover, asked the informants select the most recent new products developed and launched for minimum of twelve months. We sent three types of questionnaires to project managers, the member charging marketing, and the member charging R&D respectively. The current study sent questionnaires to 112 firms, and 69 firms are returned. The response rate is 61.61%. At new product level, there are 207 new product projects, and 100 firms are returned. The response rate is 48.31%. We also do tests of bias due to nonresponse which were conducted by using a comparison of early to late respondents’ all variable means (Armstrong & Overton, 1977). No evidence of a bias was found. The current study applied Moorman’s (1995) operationalization of new product performance is that the extent to which the product has achieved the objective of market share, sales, return on assets, profit margin, and return on investment during the first 12 months of its life in the marketplace. These items were used a 7-point Likert scale where 1 was “low” and 7 was “high”. This research adopted Homburg et al. (1999) scale to measure the power structure between marketing and R&D functions by using 100-point constant-sum scale for each NPD issue, and other previous studies also used issue-based perceptual power scale (Enz, 1989; Hinings et al., 1974; Pfeffer, 1981; Verhoef and Leeflang, 2009). The current study adopted Jaworski and Kohli’s (1993) scale to measure market and technological turbulence. The items were used a 7-point Likert scale where 1 was “extremely disagree” to 7 was “extremely agree”. In order to rule out other effects, we controlled industrial category, firm age, the number of marketing and R&D members involved in the NPD process, environmental hostility. Result and Conclusion The first finding is that under low market uncertainty and high technological uncertainty, balance of power structure tends to swing to the side of R&D function, and achieve better in NPD performance. Take IC design of High-tech industry as an instance, NPD project ends to perform better when the balance of power structure swing to the side of R&D function. The second finding is that under high market uncertainty and low technological uncertainty, NPD formalization helps to strengthen the relationship between marketing and NPD performance. Take frozen dessert in the food industry or leisure and sports fabrics in the textile industry as examples, formalization of NPD process can help marketing-driven NPD projects perform better in market. These findings advanced the understanding of the relationship between the power structure of marketing and R&D and NPD performance, rather than focusing on a single function, marketing or R&D. Furthermore, examining the relationship between the power structure of marketing and R&D and NPD performance in different environment uncertainty situations explained the inconsistency of the relationship between the power structure of marketing and R&D and NPD performance in past studies. Finally, this research conditionally supported the moderating effect of NPD formalization on the relationship between the power structure of marketing and R&D and NPD performance, and this exploration never been found.

How to manage these marketing and R&D functions is very important in the new product development (NPD) process. Which function should have more power to make more decisions? Previous study seldom touched this question. Further, according to strategic contingent theory, perceived uncertainty is very important determinant for power structure in the NPD process (Hickson, Hinings, Schneck, & Pennings, 1971). However, Pfeffer and Salancik (1978) argued that there is indeterminacy between environment and power structure. Thus, is external environmental uncertainty related to power structure in the NPD process? Resource dependence theory gives us a hint to solve this puzzle, that is, the concept of institutionalization (Pfeffer, 1981; Pfeffer and Salancik, 1978). The current study tends to adopt NPD duration reflected institutionalization (Pfeffer, 1981) to examine the moderating effect of NPD duration on the relationship between environmental uncertainty and marketing-R&D power structure in the NPD process. In general, power is defined as that the relation among social actors in which a specific social actor can potentially influence the decision to achieve his or her desire outcomes (Dahl, 1957; Emerson, 1962; Pfeffer, 1981; Salancik & Pfeffer, 1977). This definition also suggested that power is the structure in human aggregates like complex organization (Pfeffer, 1981). Thus, the power structure in the NPD process is defined as the proportion of decision making by marketing and R&D functions in the NPD process. When a NPD team faces the high market uncertainty, marketing function can gather more resources because of its special ability. A new product team has the limited resources, so another important function like R&D will have fewer resources than marketing function. Thus, our first hypothesis is that the higher market uncertainty, the more power marketing function has. R&D members have background knowledge to overcome the difficult of processing technological language and decide the main resolutions. The team will tend to allot more resources to deal with the problems of technological change as such the R&D members can buy the license of new technologies to apply it on their new products and to create the disruptive innovation like smartphones or tablets successfully. Therefore, the second hypothesis is that the higher technology uncertainty, the more power R&D function has. According to resource dependence theory, however, the relationship between environmental uncertainty and power structure does not always exist (Pfeffer, 1981; Pfeffer & Salancik, 1978). Pfeffer and Salancik (1978) indicated that the perceived environmental uncertainty of a subunit is weakly related to subunit’s power structure when an organization is highly institutionalized. When one subunit has more power than others, it tends to maintain the current power structure. So, the subunit makes rules or norm to formalize its power legally. This process is so called institutionalization (Pfeffer, 1981; Pfeffer & Salancik, 1978). In general, as time goes by, organizations will form their own social norms, and some of these norms will become the principles or rules in organizations (Pfeffer, 1981). As a result, when NPD time is long, marketing and R&D functions form norms or official rules. Then, the relationship between their perceived environmental uncertainty and power structure in the NPD process is weaker than the relation in the shorter duration of NPD. Therefore, our hypothesis is that the relationship between environmental uncertainty and power structure in the long-run project time is weaker than the relationship in the short-run project time. The current study used questionnaire survey and purposive sampling method to collect data. In order to eliminate the bias of common method variance (CMV), this study conducted multiple sources including project managers, the member charging marketing, and the member charging R&D to administrate questionnaires differently. In order to avoid selection bias, this study, moreover, asked the informants select the most recent new products developed and launched for minimum of twelve months. We sent three types of questionnaires to project managers, the member charging marketing, and the member charging R&D respectively. The current study sent questionnaires to 112 firms, and 69 firms are returned. The response rate is 61.61%. At new product level, there are 207 new product projects, and 100 firms are returned. The response rate is 48.31%. We also do tests of bias due to nonresponse which were conducted by using a comparison of early to late respondents’ all variable means (Armstrong & Overton, 1977). No evidence of a bias was found. Our variables are included market and technology uncertainty, and power structure which the left side is totally decided by marketing and the right side is totally decided by R&D. Moreover, NPD time is from star-up projects to launch it. In order to rule out other effects, we controlled industrial category, firm age, the number of marketing and R&D members involved in the NPD process, environmental hostility, and NPD process formalization. Every overall fit index in our measurement model is shown that χ(55)^2=71.5259,p-vaule=.066，χ^2/df=1.30<2, goodness of fit index=.90，adjusted goodness of fit index=.84，comparative fit index=.97，normed fit index=.87，non-normed fit index=.95, and root mean square error of approximation=.06. In general, all fit indexes in our measurement model are acceptable, and the average variance extracted (AVE), composite reliability (CR), and Cronbach’s α of all constructs are acceptable. Their ranges are .45-.70, .70-.93, and .75-.93 respectively. The overall model showed that the higher market uncertainty, the more power marketing has (β=-.279, t-value=-3.11, p-value<.050) but technology uncertainty is not significantly related to power structure. We used the mean of the NPD time as the cutting point to split short-run and long-run project time, and the mean is about one year and half in our sample. The result showed that in the short-run group the higher market and technology uncertainty, the more power marketing and R&D function have (β=-.355, t-value=-2.53, p-value<.050; β=.296, t-value=2.23, p-value<.050) . However, in the long-run group the relationship between environmental uncertainty and power structure is statistically insignificant. Additionally, in the long-run group the more NPD process formalization, the more power R&D function has (β=.277, t-value=2.33, p-value<.050). Back to the original puzzle, that is, does external environmental uncertainty determine power structure in the new product development process? The empirical evidence is shown that it is dependent on how long an organization develops new products to the market. Because the dominant subunit involved in the NPD process tends to maintain it power, it institutionalizes rules or norms to have legitimacy in the organization, and this argument is consistent with resource dependence theory (Pfeffer & Salancik, 1978). We also found that in short-run perceived environmental uncertainty are positively related to power structure in the NPD process. Consistent with strategic contingent theory’s proposition, the one subunit enable to reduce or respond external environment pressure, and it can have more power in the organization (Hickson, et al., 1971; Hinings, et al., 1974). We additionally found that in long-run group process formalization is positively related to R&D power. R&D function plays a main role in the NPD process as especially in the manufacturing industry; therefore, R&D function has much motive to maintain its power (Workamn, 1993). So R&D function can use formal rule to maintain its power when R&D function formalize the NPD process. As a consequence, formalizing the NPD process helps R&D function to gain more power in the long run. The contribution of our study is that we tested the proposition in strategic contingent theory, and the empirical evidences supported our hypotheses. Furthermore, our study also is the first study to test and find the support evidence with the institutionalization proposition in resource dependence theory. We not only explored the relationship between environmental uncertainty and power structure in the NPD process, but also extended strategic contingent theory and resource dependence theory to the NPD research. The further study can follow our definition of power structure to find what strategy marketing and R&D function will used to take back or maintain their power (Eisenhardt & Bourgeois, 1988; Li & Atuahene-Gima, 2001; Pfeffer, 1981).

With the advent of Internet era, e-commerce has become the focus of human's life. It leads a new direction of social development . As the representative of traditional industry, shipping industry is confronted with a series of difficulties, which have to break through the traditional and existing model to make their business for survival. With the increasing pricking up of market competition, shipping industry is now facing development bottle neck, but e-commerce provides a new way to solve the problem. This paper firstly describes the existing forms of the e-commerce shipping platform. Secondly analyzes the data for the situation of shipping industry in China, the data for expected functions of an e-commerce shipping platform and the data for how to choose a specific e-commerce shipping platform. Thirdly analyzes the potential risks of establishing e-commerce shipping platform in China. Based on the above researched, the paper provides a suggested model of the shipping e-commerce shipping platform in China.