Untangling the Performance Impact of E-marketplace Sellers’ Deployment of Platform-Based Functions: A Configurational Perspective

Platform-based functions (PBFs) serve as indispensable tools for enhancing sellers’ performance within the e-marketplace. However, the complexity of their interaction and the determination of optimal configurations pose ongoing challenges. Employing fuzzy-set qualitative comparative analysis on a robust data set comprising 3,300 apparel sellers, our study delves into the intricate interplay of PBFs, revealing the nuanced combinations that exert significant influence on sales outcomes. In our investigation, we underscore the pivotal role of two key elements: the meticulous assessment of seller reputation and the strategic alignment of product positioning. These factors emerge as crucial determinants in shaping effective PBF configurations. Surprisingly, our research uncovers unforeseen drawbacks associated with pricing and marketing functions, particularly for reputable sellers offering high-priced products. Beyond theoretical elucidation, our findings offer pragmatic, actionable insights. We provide concrete strategies for sellers and platform operators to optimize their approaches, fostering a more vibrant and competitive e-marketplace ecosystem. Previous studies have shown great interest in examining the performance impact of platform-based functions (PBFs) used by e-marketplace sellers and the contingent role of salient variables, such as seller reputation, in the e-marketplace. Their findings, however, are fragmented and inconsistent, as they generally focus on the net, separate effect of a single PBF with debatable findings. The theorization of how sellers should configure multiple types of PBFs as a whole to achieve high sales performance lags far behind the booming competition practice. To identify an effective PBF combination, this study takes a configurational perspective to identify appropriate PBF configurations that can achieve high sales performance for sellers with different product positions and reputations. A fuzzy-set qualitative comparative analysis of a longitudinal data set of over 3,300 apparel sellers in a large e-marketplace yields interesting findings. The configuration results reveal recipes for PBF combinations for achieving high sales performance that vary across different levels of seller reputation and product positioning strategies. Our configuration findings suggest that sellers should configure PBFs according to distinctive product strategies accompanied by seller reputation conditions, where the resulting PBF configurations