题目：Incentives, Peer Influence, and Competitive Strategies in Retail Sales Teams
主讲人：Jia LI? 圣路易斯华盛顿大学商pp电子博士生
时间：2009年11月17日星期二，下午13：30—15：00
地点：经管pp电子 伟伦楼501室
讲座语言：英文
摘要：In retail management, one of the fundamental and critical decisions for managers is how to motivate, staff, and organize their sales force. This task becomes more challenging when employees work in teams so that their productivity will be influenced by peers. Recent work empirically demonstrates peer effects in single-firm work settings under one
compensation structure, but these studies leave important questions unanswered.? We use a three-year dataset of Chinese cosmetic sales transactions to examine how compensation and firm boundaries influence worker productivity spillovers and sales strategies. We demonstrate three important new sets of findings. First, while high-ability workers under the team based compensation system significantly improve the sales productivity of their peers, under individual-based compensation they have a strong negative effect on peers while gaining little in the process. Second, we find that peer effects exist across firm boundaries, with workers at team-based compensation counters more capable in competing against peers at other counters. Third, when faced with high-ability peers, workers under individual-based compensation respond by strategically discounting prices offered to customers and focusing on retaining high-value customers who may
be more brand loyal. Our results suggest that while heterogeneity in worker productivity enhances total team performance under team-based compensation, it impacts firms with individual-based compensation negatively. This paper provides a unique contribution to the literature by being the first to simultaneously estimate peer productivity spillovers both within and across firms under multiple compensation systems. It is also the first identifying how workers respond to peer effects with discretionary strategies, and provides important implications for managerial decisions on staffing, compensation, and pricing discretion. Finally, the paper implements an improved methodology that generates more efficient estimators than those in previous studies.
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