Abstract

Abstract Our research examines how digital service quality and recovery impact positive and negative word-of-mouth (WOM). From software-as-service (SaaS) firms to ecommerce retailers to everything in-between (including educational institutions), the role of digital service quality and recovery as drivers of competitive advantage cannot be overstated. Given the interconnected, modern digital landscape with which institutions must contend, digital service quality and recovery have the potential to (quickly) impact an organization’s reputation via word-of-mouth diffusion (Cheung and Thadani, 2012). To date, we have collected preliminary data from a digital survey administered by Cloud Research to a sample of students attending universities in a tri-state area (NY, NJ, and CT). The survey featured an attention check question to ensure response quality. A three-item marker variable was included to account for any common method bias. Scale reliability was assessed by computing Cronbach alphas for scale items pertaining to focal constructs. Principle component analysis was conducted (all items loaded on the appropriate factor). Finally, cross-correlations were analyzed for multi-collinearity. We are planning on: (1) conducting additional quantitative analyses, (2) designing and administering a follow-up experimental survey, and (3) collecting qualitative data based on expert field interviews. We are hoping to receive feedback on the above items as well as thoughts regarding future journal positioning. Early results from our structural model show that digital service quality has a stronger relationship to positive than negative WOM, while the process dimension of digital service recovery (i.e., resolution speed) is more strongly associated with negative WOM. The outcome dimension of digital service recovery (i.e., resolution fairness) exhibits a similarly strong relationship with both positive and negative WOM. In light of the destructive impact negative word-of-mouth can exert on a firm’s reputation, our initial findings suggest that the process side of service recovery may be under-researched and under-valued relative to the outcome side (e.g., compensation, etc.). This aligns with and extends the work of Najjar et al. (2022, p. 492) who subscribe to the “fix it fast and fully” mantra of service recovery. In terms of theory, our tentative framework incorporates satisfaction theory, perceived justice theory, and prospect theory. In terms of practice, expedited digital recovery holds the potential to significantly attenuate negative WOM. We are also hoping to receive feedback on theorization and practical implications. References Cheung, C. M., & Thadani, D. R. (2012). The impact of electronic word-of-mouth communication: A literature analysis and integrative model. Decision support systems, 54(1), 461-470. Najjar, M. S., Kettinger, W. J., & Kettinger, L. D. (2022). IS incident recovery and service value: a service-dominant logic view. European Journal of Information Systems, 31(4), 492-524.

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