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Data-driven behavior-based operations management for service-oriented manufacturing: A systematic review
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DOI：10.1007/s42524-026-5382-1.png)
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Abstract
En 中文
The accelerated servitization of manufacturing and the rapid advancements in emerging information technologies have enabled flexible process configuration, efficient resource collaboration, and dynamic value chain reconstruction. However, the complex behavioral interactions among users, firms, and platform systems, alongside massive data flows, pose significant challenges to the operational management of service-oriented manufacturing (SOM). This study conducts a systematic literature review of data-driven, behavior-based SOM using a mixed-methods approach that integrates Bibliometric-Systematic Literature Review (B-SLR) and snowballing techniques. Drawing on an in-depth analysis of 367 core publications from 1988 to April 2026, this study develops a lifecycle-based framework comprising four key operational stages, covering product design, production, smart operations and maintenance, and product lifecycle management, including recycling and remanufacturing. The review synthesizes major findings from both academic and practical perspectives and identifies future research directions across four behavioral dimensions, including value co-creation in design, collaborative sharing in production, human–AI interaction in operations, and multi-agent collaboration in lifecycle management. The findings provide practical insights that advance both research and practice in SOM to support the development of resilient, sustainable, and intelligent manufacturing systems.
Keywords:
service-oriented manufacturing
servitization
product- service system
product lifecycle management
data-driven
behavior-based operations management
Journal
IF:
7.7
Papers:
437
Citations:
1.5K