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).

본 연구는 사내 기업가적 활동, 사회적 네트워크, 환경의 불확실성 그리고 이들 상호간의 상호작용적 영향이 중국 중소기업의 성과에 미치는 영향에 대해 살펴보는 것이다. 연구의 목적을 달성하기 위해 연구자들은 사내 기업가적 활동 그리고 사회적 네트워크가 미치는 영향과 이들의 상호작용이 기업성과에 미치는 영향에 대해 분석하고자 한다. 또한 나아가 지각된 환경의 불확실성이 높을 때 이들의 상호작용이 기업성과에 미치는 영향이 어떻게 달라질 수 있는지를 파악하고자 한다. 실증적 연구는 중국 합비성 안휘시에 있는 첨단 산업의 중소기업을 대상으로 수행되었다. 무작위로 선정된 200개 업체에 설문지를 보내고 응답받은 기업들 중에서 불성실한 것을 제외한 164개의 중소기업체가 최종 표본으로 선정되었다. 가설의 검증은 이들 기업들을 대상으로 이루어졌으며 그 결과 본 연구는 다음과 같은 결론을 도출할 수 있었다. 첫째, 중국 중소기업의 사내 기업가적 활동들은 기업성과에 유의한 긍정적 영향을 미치는 것으로 나타났다. 둘째, 사회적 네트워크는 그 자체로는 기업성과에 유의한 영향을 미치지 않으나 사내 기업가적 활동들 중에서 특히 혁신 및 벤처링 중심의 활동과는 유의한 상호작용적 영향을 미치는 것으로 나타났다. 셋째, 혁신 및 벤처링 활동과 사회적 네트워크의 상호작용은 기업에서 지각하는 환경의 불확실성이 높을 때 기업성과에 더욱 유의한 긍정적 영향을 미치는 것으로 나타났다. 이러한 결과를 토대로 볼 때 기업가적 활동이 기업성과 개선을 위해 중요할 수 있으며, 사회적 네트워크는 기업가적 활동의 내용에 따라서 적절하게 활용되어야 하며, 특히 환경의 불확실성이 높을 때는 외부자원을 최대한 활용하면서 혁신과 벤처링 활동을 강조하는 것이 중국 중소기업에 있어서는 무엇보다 중요할 수 있음을 연구자들은 제시하고자 한다.

이 논문에서는 환경변수의 시계열 분포도 작성과 불확실성 모델링을 위해 시공간영역으로 확장된 다중 가우시안 크리깅을 제안하였다. 다중 가우시안 틀 안에서, 우선 정규점수변환된 환경변수를 결정론적 경향 성분과 확률론적 잔차 성분으로 분해하였다. 그리고 시간 경향 모델 계수의 내삽을 통해 경향 성분의 시계열 공간 분포도를 작성하였다. 정상성 잔차 성분의 시공간 상관 구조는 곱-합 시공간 베리오그램 모델을 이용하여 정량화하였고, 이 베리오그램 모델과 시공간 크리깅을 이용하여 국소적 누적 확률분포함수를 모델링하였다. 이 국소적 누적 확률분포함수로부터 평균값과 조건부 분산을 계산하여 공간분포도 작성과 불확실성 분석에 각각 이용하였다. 제안 기법의 적용성 평가를 위해 인천광역시에서 3년간 13개 관측소에서 측정된 월 평균 미세먼지(PM10) 농도 자료를 이용한 시계열 분포도 작성 사례 연구를 수행하였다. 사례연구 결과, 제안 기법을 통해 기존 공간 정규 크리깅에 비해 작은 편향과 높은 예측 능력을 가진 시계열 미세먼지(PM10) 농도 분포도 작성이 가능함을 확인할 수 있었다. 또한 조건부 분산과 특정 농도값을 초과할 확률값들은 해석을 위한 유용한 보조 정보를 제공하였다.

Micro, Small and Medium Enterprises in Denpasar City still face low mastery of technology and financial management, one of which is the application of technology-based accounting information systems (e-commerce) for small and medium enterprises. The research objective was to determine the relationship between environmental uncertainty, trust and ease of information technology moderating behavior in accounting information systems. Research with a quantitative approach, the method used is multiple linear regression with moderated regression analysis. The study population was 816 small and medium enterprises. The sampling method technique was the incidental sampling approach and the Slovin formula so that a sampling of 100 small and medium enterprises that had used e-commerce was determined in the city of Denpasar. The results of research that have been conducted determine the relationship between user behavior in accounting information systems that affect individual performance, the relationship between environmental uncertainty affects accounting information systems mediated by individual performance, while the ease of information technology and its ability to be mediated by individual performance has an effect on the behavior of using accounting information systems. The application of accounting information systems in small and medium enterprises is expected to improve individual performance so as to increase income.