Research On Crowdsourcing Model Of Enterprise Competitive Intelligence In The Environment Of Big Data

Under the explosive increase of global data, the era of big data has gradually coming, and bring some huge challenges for enterprise’competitive intelligence, urgently need a new model to deal with the big data. Crowdsourcing is a potential problem solving mechanism, which develop with the rising popularity of the Internet and the perfection of the computer technology and provide a new production way for intelligence job. With this new intellectual pattern had been attracted, scholars at home and abroad launched a widely discussion for it. Crowdsourcing’most important is to attract and motivate large users to participate, only in this way can make intelligence warehouse for enterprise and make up the lack of internal resource. Therefore, the focus of this study is to explore and demonstrate the key factors which influence users to participate, and improve the effects. Attempting to provide a set of effective scientific theory basis and guiding opinion for enterpriser launch crowdsourcing activity of competitive intelligence under the big data environment.This article first to review the literature of big data, crowdsourcing and competitive intelligence of big data, mainly introduce their concept, origin and current situation. Then elaborate the operation mechanism of enterprise competitive intelligence crowdsourcing, including logic framework and key measures, then regard the users of crowdsourcing activity as the research object, based on the theory of motivation and behavior from scholars both at home and abroad, combined with the technology acceptance model, social cognitive theory and motivation theory, extracted the research model of the influence factors of users to participate crowdsourcing activity. then design the survey questionnaire and conduct an investigation, and then using SPSS 18.0 and VisualPLS1.04 to analyze the collected data, including reliability and validity analysis, descriptive statistics analysis, correlation analysis and regression analysis, finally using Visual PLS Bootstrap algorithm to calculate each path coefficient of variance and regression of the research model, in order to test the hypothesis of individual driven(perceived entertainment, virtual community, immersive, external reward and self-efficacy),technology driven(perceived usefulness, perceived ease of use),platform driven(crowdsourcing regulations, crowdsourcing activity attribute) on user participation behavior.Research results showed that the perceived entertainment, immersive, external reward and self-efficacy of individual driven had positive influence on user participation behavior, among them, the impact of perceived entertainment and external reward are more significant. but virtual community is not significant. perceived usefulness of technology driven had a direct or indirect effect on participation behavior, and perceived ease of use through self-efficacy indirectly impact on user participation behavior, not directly. crowdsourcing regulations of platform driven are significant influence on user participation behavior.at the same time, the self-efficacy has the partial intermediary effect on the perceived ease of use and user participation behavior. This paper also discussed the result of the above research and proposed the corresponding incentives. In addition, the article finally points out the defects of this study and future research direction.