INTEREST CATEGORY: SERVICE
POSTING TYPE: Calls: Journals

Author: Ming-Hui Huang

Journal of Service Research Special Issue on

Smart Service Failure-Recovery

Co-edited by

Yany Grégoire, HEC Montréal (yany.gregoire@hec.ca), Yves Van Vaerenbergh, KU Leuven (yves.vanvaerenbergh@kuleuven.be), Chiara Orsingher, University of Bologna (chiara.orsingher@unibo.it), and Katja Gelbrich, Catholic University of Eichstätt-Ingolstadt (Katja.Gelbrich@ku.de)

Submission Deadline: Full papers due June 1, 2023

The field of service failure-recovery (SFR) is one of the most established in service. However, recent reviews (see references) attest that this prolific field is now at the crossroads. These reviews have urged researchers to move beyond traditional contexts, the overuse of the same established theories, and the overreliance on basic surveys and scenario-based experiments. To ensure its prosperity, the field of SFR needs some serious out-of-the-box thinking. This is the purpose of this special issue: bringing SFR to the next level.

By “smart” service failure-recovery, we mean any SFR research that solves important real-world problems by using innovative methods and theories. The idea of “being smart” speaks to the importance of reconsidering our “old” ways and encouraging the adoption of up-to-date practices. For instance, we are seeking for innovative SFR taking the following forms:

• New contexts, such as AI-powered digital interfaces, service failure-recovery involving AI, healthcare, governmental services, B2B, service delivery networks, service crises, and corporate irresponsibility.
• New data, being textual, financial, archival, mobile, behavioral, or physiological.
• New theories that go beyond the application of established frameworks (e.g., justice, attribution, satisfaction), and that include new metrics (e.g., firm performance, societal well-being, global integration).
• New methods, such as longitudinal designs, field experiments, dyadic or triadic designs, qualitative research, neuro-physiological studies, event studies, mobile diaries, etc.
• New analytics, including machine learning methods, multilevel analyses, econometrics, longitudinal SEM, meta-analyses, etc.
• Any research that proposes new angles, approaches, technologies, and data pushing the boundaries of the field.

Before submitting their work, we ask researchers to consult the references below. Please contact the special issue co-editors if you have any questions.

References