This article investigates the moderating role of review helpfulness on the effects of online review content and linguistic style matching on new product sales. Using data from 105,494 online reviews from a popular website, IMDB.com, following 264 movie releases, the article shows that the impact of review style and content on new product sales is contingent upon review helpfulness. In particular, results suggest that linguistic style matching, positive emotion, and cognitive components of online review content significantly impact new product sales when the reviews are deemed helpful by the readers. These findings collectively suggest that online review research benefits from deeper textual analysis that includes review content and linguistic style compared to traditional methods that rely solely on numerical ratings. Also, review helpfulness plays a critical role in consumer decision‐making considering a rapidly increasing amount of online information is now available to consumers.

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In this article, we examine the antecedent structure of the terminal level of job satisfaction of frontline service employees who have recently quit a firm. The results from the estimation of a latent, finite-mixture model, using data collected from former employees of a large supermarket chain, point to a two-dimensional heterogeneity among exiting employees. We find systematic variation in the relative importance of the drivers of job satisfaction, such as work environment, personality, and demographics, across employee subgroups. We also find that the threshold level of the terminal satisfaction for exiting employees could be high for some and low for others. These findings stand in contrast to the inverse satisfaction-turnover intent link documented for existing employees and provide new explanations for the observed weakness in the relationship. They are also inconsistent with the attraction-selection-attrition model that argues for a convergence in employee dispositions. We suggest that job satisfaction and turnover models can be enhanced by adopting a utility-theoretic perspective that accommodates variations in the structure and threshold levels of terminal satisfaction. To this end, we provide some guidelines for how exiting rather than existing employees can provide an alternative avenue for diagnosing the quitting process and ultimately improving the predictive power of turnover models. Finally, we suggest that the allocation of employee retention resources based on either a common model of job satisfaction, or assuming a monotonic satisfaction-intent relationship, may be inefficient. Instead, we argue for model-based, group-specific retention programs to reduce frontline service employee turnover.

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