用户参与众包创新的机会主义行为识别研究

Research on Identification of Users′Opportunistic Behaviors in Crowdsourcing Innovation

众包模式作为企业获取外部网络知识,将创意、智慧、技能转化成商业价值的新型创新模式,存在组织形式松散、参与用户自由自愿、创新目的性强和信息不对称等特征,容易导致用户在参与众包创新过程中出现诸如方案欺诈、知识产权窃取、搭便车等机会主义行为。为打造良好的众包创新环境,降低众包创新风险,需要科学识别和规避用户机会主义行为。结合众包创新实践,通过分析用户参与众包创新的机会主义行为主要表现,构建包括综合工作能力、信誉水平、服务水平和历史交易水平的四维度识别体系,以及基于PCA-BP神经网络的用户机会主义行为识别模型;同时,结合国内典型众包平台——猪八戒网,利用网络爬虫软件GooSeeker获取相关数据开展实证研究,以验证模型的可行性与有效性。

Crowdsourcing,as a new innovation mode for enterprises to acquire external network knowledge and transform creativity,wisdom and skills into business value,is characterized by loose organizational structures,free will of participants,strong innovation goals and information asymmetry,which can easily induce solvers′opportunistic behaviors,such as scheme fraud,intellectual property theft and free-riding.In order to create an attractive and supportive platform environment and to reduce the risk of crowdsourcing,scientifically identifying and avoiding opportunistic users is essential.In this study,the characteristics of users′opportunistic behaviors are analyzed,and a four-dimensional opportunistic users′identification system,including the work ability,the reputation level,the service level and the historical transaction level,is constructed.This article proposes an opportunistic users′identification model based on PCA-BP neural network,combined with a typical crowdsourcing platform zbj.com,and uses the crawler-software GooSeeker to obtain data for empirical research to verify the feasibility and effectiveness of the identification model.