Year: 2026
Type: article
Abstract: While conventional approaches to Service Failure and Recovery (SFR) predominantly rely on basic surveys and scenario-based experiments, recent advancements in failure recovery found in related fields like Industry 4.0, AI-enabled decision support and digital service systems have presented intriguing possibilities (Wang et al., 2024; Zhang, 2024). Against this backdrop, this study proposes a novel methodology that leverages the rapidly evolving domain of smart maintenance and knowledge-based capability to establish a fresh framework for SFR. The suggested framework consists of seven distinct modules, namely Monitoring, Predictive and Preventive, Service Failure Detection, Failure Report, Diagnosis, Prognosis, and Healing Support. This investigation delineates the key functions and activities associated with each module, elucidates the information flows between them, and outlines their interface with service providers, customers, suppliers, and clients. Additionally, it delves into the considerations and implications arising from the proposed framework.
Source: Journal of the Knowledge Economy
Authors: Yuval Cohen, Shai Rozenes
Institutions: Afeka College of Engineering, Holon Institute of Technology
Language: English
Subfield: Marketing
Domain: Social Sciences
Open Access status: hybrid
Estimated APC paid: $3,390
OpenAlex ID: W7221450328