Consumers’ postpurchase evaluations have received much attention due to the strong link between ratings and sales. However, less is known about how herding effects from reference groups (i.e., crowd and friends) unfold in online ratings. This research examines the role of divergent opinions, rater experience, and firm product portfolio in attenuating/amplifying herding influences in online rating environments. Applying robust econometric techniques on data from a community of board gamers, we find that herding effects are significant and recommend a more nuanced view of herding. Highlighting the role of rater experience, the positive influence of the crowd is weakened and friend influences are amplified as the rater gains experience. Furthermore, divergent opinions between reference groups create herding and differentiation depending on the reference group and the rater’s experience level. Finally, firms can influence online opinion through their product portfolio in profound ways. A broad and deep product portfolio not only leads to favorable quality inferences but also attenuates social influence. Implications for online reputation management, rating system design, and firm product strategy are discussed.
Salesperson turnover can have a negative overall effect on a firm. Research on salesperson turnover has conceptually studied the consequences of voluntary turnover on a firm. However, little empirical research has investigated the antecedents of salesperson turnover—specifically, the role of own effects (relative performance, customer satisfaction, and goal realization) and peer effects (peer performance variance and turnover). Therefore, the authors propose a framework to assess the influence of own factors (through identity theory) and of peer factors (through social identity theory) on salesperson turnover. Using a proportional hazard model implemented on data consisting of 6,727 salespeople over two years, the results suggest that in addition to own behaviors, managers need to pay attention to peer behaviors because peer turnover (voluntary and involuntary) greatly increases a salesperson's turnover probability. Furthermore, the results indicate that peer effects have a greater impact than own effects. This research has implications for sales force management because it helps managers (1) identify a salesperson's turnover risk, (2) diagnose the drivers of turnover behavior, and (3) build strategies to prevent salesperson turnover.
Research on sales force evaluation has mostly relied on reflective metrics such as sales volume, revenue, and manager evaluations to assess and manage a sales force. However, businesses are moving from a product-centric to a customer-centric view and from a backward-looking to a forward-looking strategic perspective, so sales organizations must adapt to the ever-changing marketplace to maximize performance. The authors propose a forward-looking and profit-oriented metric to evaluate and demonstrate the effects of training type and incentive type on a salesperson's future value. Using a latent class modeling approach, they identify two distinct segments in the sales force that exhibit different responses to varying levels of training and incentives. This suggests that a one-size-fits-all approach to sales force management may be suboptimal. Finally, the authors also evaluate the magnitude of the proposed effects in the short run as well as the long run and show that the magnitudes of the effects could vary depending on the time horizon being considered. The authors close with a discussion of the implications for research and practice, including sales force evaluation through customer relationship management–based heuristics and optimal training and incentive management.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.