创新生态系统如何驱动企业微创新——一个组态视角的fsQCA分析

近年来，微创新是创新研究领域的热点，如何驱动企业微创新是相关研究亟需回答的问题。整合创新生态系统3个层面六大要素，运用模糊集定性比较分析（fsQCA）方法，以18个微创新案例为样本，探讨创新生态系统驱动企业微创新的复杂因果机制。结果发现：第一，单个创新生态系统要素并不构成企业高微创新的必要条件。第二，存在3条高微创新驱动路径，即机会识别主导下的用户驱动型、机会识别主导下的环境与用户参与驱动型，以及机会识别主导下的环境、组织学习与领先用户驱动型。此外，非高微创新驱动路径仅有一条，且与高微创新驱动路径存在非对称关系。第三，机会识别能力作为核心条件出现在高微创新的3个组态及非高微创新一个组态中，说明机会识别能力对企业微创新具有重要作用。

How Does Innovation Ecosystem Drives Enterprise Micro-innovation？A Fuzzy Set Qualitative Comparative Analysis Based on Configuration Perspective

In today's Internet era, enterprises are facing rapid changes, great uncertainty and unpredictability in a competitive environment. Consumer demands have become more diverse in contrast to the narrowing differences between similar products. Enterprise competition becomes increasingly intense. While some companies complain about fewer opportunities for technological progress, others have achieved rapid growth relying on accurate understanding of user needs and rapid iteration. This phenomenon has attracted researchers' more attention on micro-innovation. What are the differences between kinds of enterprises on micro-innovation? How do enterprises coordinate various elements to improve micro-innovation? These are important practical problems in urgent need to be solved.#br#In recent years, the research on the mechanism of enterprise micro-innovation has made some achievements.However, there are still three shortcomings in the existing research. First, scholars put forward the driving elements of micro-innovation from different perspectives, but in general, these driving elements were too slightly messy to focus on the core elements of micro-innovation. Second, the existing research failed to systematically discuss the driving paths of enterprise micro-innovation and unable to find which combination of driving elements could successfully achieve micro-innovation. Finally, the research method was deficient. The explorative case study was the common method to study micro-innovation. Although the explorative case study was of great advantage in developing concept and theoretical construction, it was lack of empirical test. Therefore, it was impossible to verify whether the driving elements could really have impact on micro-innovation. In view of the above, this research constructs an enterprise micro-innovational driven mechanism model based on innovation ecosystem theory including six elements, namely environmental uncertainty, environmental competition, opportunity identification capability, organizational learning capability, user participation and lead user. The model tries to explore the complex influence mechanism on how the six elements of innovation ecosystem drive enterprise micro-innovation, and it is tested by fuzzy set qualitative comparative analysis (fsQCA) approach. The fsQCA approach has an advantage on both qualitative and quantitative study. It can make up for lack of empirical research on micro-innovational driving mechanism.#br#Eighteen micro-innovational cases are selected from the database of China Management Case-sharing Center (CMCC). First, the research group members establish a score criterion for each variable item of the model. Next, three senior professors in the field of innovation are invited to grade the same micro-innovational case according to the score criterion. The average score of the three professors is taken as the item score if the item passes internal consistency test. The average score of each item is taken as the variable score for the fsQCA data analysis. The quartile method is used to calibrate all of the variables. At last, the necessity and adequacy data analyses are conducted by fsQCA software.#br#The results show that firstly the necessity of all driving elements is not higher than 0.9. Therefore, single element of innovation ecosystem does not constitute the necessary condition of enterprise micro-innovation. Secondly there are three recipes that can drive high micro-innovation, namely opportunity identification dominant with user driven in the typical case of Tencent's Wechat; opportunity identification dominant with environment and user participation driven, in the typical case of Byte Beating's Tiktok; opportunity identification dominant with environment, organizational learning and lead user driven in the typical case of Alibaba's Alipay. Thirdly only one recipe can generate non-high micro-innovation, which verifies the existence of asymmetric causality relationship compared with the recipes of high micro-innovation. Fourthly opportunity identification capability as core driving element appears in the three configurations of high micro-innovation and one configuration of non-high micro-innovation, which shows that opportunity identification capability plays a more important role in driving enterprise micro-innovation.#br#Different from the lack of systematic theoretical framework for enterprise micro-innovational driving mechanism in the existing study, this research brings six elements from three levels into the analysis framework based on innovation ecosystem theory, which provides a powerful supplement to the existing literature. At the same time, three configurations are found to drive micro-innovation, which opens the black box of micro-innovational driving mechanism, as well as reveals the driving differences among enterprises. These findings are of positive significance on the micro-innovational driving mechanism from the perspective of innovation ecology. In addition, it is the first time to introduce fsQCA approach to micro-innovation research,providing a new attempt to explain the complex causality relationship of micro-innovation. The research conclusions provide managerial implications for enterprises to develop micro-innovational practice.#br#