| The in-depth development of the digital economy has promoted the emergence of platform models in various fields,gradually becoming one of the most important business models for socio-economic development.With its breakthrough innovation concept,the online retail platform has subverted the traditional retail business model,changed the business logic and business practices of enterprises,and established new rules for the operation of online retail.Online retail platform enterprises such as Alibaba,JD,and Pinduoduo have rapidly grown into the most promising enterprises using the platform model.The sustained high growth in the transaction size of China’s online retail platform market also indicates the broad development prospects of the online retail market.How to improve the performance level has gradually become a new development task for online retail platforms.This article finds that multiple factors have a synergistic effect on the performance level of online retail platforms through combing relevant academic research on online retail platforms.Therefore,based on the transaction and innovation attributes of the platform,from a holistic and global perspective,this paper uses the method of fuzzy set qualitative comparative analysis(fs QCA)to explore the configuration effects of factors that affect the performance of online retail platforms,with the aim of mining the combination of factors that achieve high platform performance and lead to non high performance levels.Based on configuration theory,resource based view theory,and bilateral market theory,this article expounds the realization process of high performance and non high performance levels of online retail platforms under the combined action of various influencing factors.A configuration effect research model that includes the impact of antecedents on the performance of online retail platforms,including the scale of both sides of the platform’s users(seller’s user scale and buyer’s user scale),the diversity of platform user needs,and platform innovation capabilities,is constructed.The logical assumptions,necessary assumptions,and factor combination assumptions for the research are proposed.Using fs QCA 3.0 software,the performance of 18 online retail platforms was analyzed for configuration effects,identifying two conditional configurations that achieve high performance levels for online retail platforms and three conditional configurations that lead to non high performance of the platform,testing the research assumptions of this article.Research has found that:(1)both high and non high performance levels achieved by online retail platforms are the result of multiple factors working together,rather than being independently caused by a single factor;(2)There are multiple configuration paths to achieve high performance and non high performance in online retail platforms;(3)The conditional configuration of high performance and non high performance levels in online retail platforms does not have symmetry;(4)Obtain two configuration paths to achieve high performance of online retail platforms: an innovation capability compensation path supported by seller users,and a collaborative driving path driven by innovation capability and buyer users supported by seller users.Finally,based on the comparative analysis of typical cases of different configuration paths,suggestions and measures for improving the performance level of online retail platforms are put forward. |
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