An increasing number of signals are using to entice solvers to make online purchases by seekers in the competitive online markets today. However, how solution exemplars are in terms of their reputation or competence to improve sales performance has not yet been investigated. Extending signal theory to the online service marketplaces, we analyses the effect of solution exemplars’ structural characteristics on seekers’ sales performance such as quantity, diversity and popularity, exploring the moderating impact of seeker’s reputation and competence. We test the model using data from ZBJ.com, a popular crowdsourcing contest platform in China. Our analysis conducts a series of interesting findings, the impact of exemplar quantity and popularity on sales performance is positively significant, contrary to solution exemplar diversity. Regarding the moderation effects, reputation is proved to be negative, which is opposite to competence. We also elaborate on the theoretical contribution and practical significance.
Zhao, Quanwu; Zhou, Zhiyuan; and Yang, Xi, "Solution Exemplars and Sales Performance of Crowdsourcing Solvers: the Moderating Role of Reputation and Competence" (2021). WHICEB 2021 Proceedings. 76.