Despite the increasing attention to customer engagement (CE) by practitioners and academics, extant studies have largely been restricted to conceptualized relationships without empirical testing (So, King, & Sparks, 2014). Drawing on social identity theory and social exchange theory, this study develops a research model delineating the relationship between customer identification (CI), CE and customer purchasing behaviors in virtual communities. The model was tested with structural equation modeling and survey data from 513 members of two virtual tourism communities. Results indicate that both customer-community identification and customer-customer identification (constituting two classifications of CI) have directly positive effect on customer engagement attitude, on which the duration of membership in a community has a moderating effect. Additionally, customer-customer identification influences customer engagement behavior directly and positively, of which customer engagement attitude is the psychological foundation. Finally, customer engagement attitude and customer engagement behavior will promote customers’ purchasing behaviors. The contribution of this paper is that CE has been empirically validated to compose of customer engagement attitude and customer engagement behavior these two separate variables, and CI is testified to be an antecedent rather than a dimension of CE, in line with the standpoints proposed by Algesheimer, Dholakia, and Herrmann (2005).Through the current investigation, empirical studies into the concept connotation and formation mechanism of CE are enriched, and the insight into customer behavior management and CE marketing is intensified.

This study discusses how firm-customer interactions impact customer engagement behaviors in the area of hospitality and tourism services. In the current study, two research questions are raised to answer: 1) what values are perceived by customers through firm-customer interactions during various service encounters? 2) how customer engagement behaviors are led by the customer perceived values? To test the proposed model, a quantitative approach is adopted. Amazon Mechanical Turk is used as data collection platform to collect responses with the aid of Qualtrics as questionnaire development tool. To reach the maximum scope of hospitality and tourism services, hotel guests, restaurant patrons, travelers, airline customers, and theme park travelers are included in the sample. This study adopts a quantitative approach to investigate the factors that contribute to the varied customer engagement behaviors (i.e. online ratings, online reviews, online blogging, and customer-to-customer interactions). Successful industry practices demonstrate that customer engagement brings many benefits and opportunities to maintain business sustainability and profitability.