Determining Customer Outcomes By Managing Employee Emotional Display: A Multilevel Approach

Abstract

There is extensive evidence that employee emotional display toward customers (EED) is an important determinant of successful service delivery. Previous research has shown that “service with a smile” increases a customer’s service experience and that emotional display is of avail when it comes to influencing customers and achieving higher performance goals. Thus, effectively managing their employees’ emotional display has become a “hot topic” for both service marketing and emotions management scholars. The purpose of our study is threefold: First, we intend to add a more detailed perspective on the emotional display of frontline employees in service organizations, acknowledging its multidimensional structure. We suggest that, in addition to a quantity dimension (i.e. number of smiles), customers’ reaction to EED is also influenced by the employee’s emotional authenticity and effort, which have been mentioned by emotional labor scholars, but were not assessed in the context of EED. Second, we introduce a comprehensive model of EED processes that links management and employee variables with customer and company outcomes; we refer to this model as the “emotion value chain”. We systematically identify the management practices through which service organizations can influence organization- and employee-related key drivers of EED at the level of the individual, the team, and the organization, which in turn will influence EED and customer and company outcomes (e.g., customer satisfaction). Third, based on the emotion value chain, we offer empirical insights on the links between management practices, employee variables, EED dimensions, and customer outcomes. To our knowledge, this study is the first to link drivers of EED, EED itself, and customer outcomes in a common multilevel model.KeywordsCustomer SatisfactionService OrganizationFast Food RestaurantEmotional DisplayService MarketingThese keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.