Effects of different resource-sharing strategies in cloud manufacturing: a Stackelberg game-based approach

Abstract

Cloud manufacturing (CMfg) aims to realise the sharing of manufacturing resources amongst different stakeholders. Resource-sharing strategies of suppliers are essential in achieving this aim. However, current studies on this topic rarely focus on the sharing of management rights over manufacturing resources. To fill this research gap, this study investigates three resource-sharing strategies: independently, as an alliance and by cooperating with a cloud platform operator. This study explores the effects of these different strategies on meeting client requirements in CMfg. The interactions between the operator and suppliers are modelled as a two-stage Stackelberg game that contains a simultaneous subgame. The equilibrium results indicate that players achieve a lower system profit when suppliers share as an alliance rather than independently, which is why the cloud platform operator strongly opposes it. The extended analysis indicates that considering multiple suppliers complicates the allocation of tasks and profits. Low-cost suppliers have significant advantages in terms of tasks and profits when considering different marginal costs. These findings provide insights for suppliers to select appropriate resource-sharing strategies in CMfg.

KEYWORDS:

• cloud manufacturing
• resource sharing
• platform management
• substitutability
• game theory

Acknowledgment

The authors sincerely thank the editor and anonymous reviewers for their constructive comments on this study.

Data availability statement

The authors confirm that the data supporting the findings of this study are available within the article.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Additional information

Funding

This work was supported by the National Social Science Foundation of China (grant number 21AGL015) and the National Natural Science Foundation of China (grant number 61973243).

Notes on contributors

Xiaoning Cao

Xiaoning Cao is a Ph.D. candidate in management science and engineering at Dalian University of Technology. She received her M.S. degree from Kunming University of Science and Technology, China, in 2017 and B.S. degree from Anyang Normal University, China, in 2014. Her research interests include manufacturing resource sharing, cloud manufacturing, game theory, and dual-channel supply chain.

Hongguang Bo

Hongguang Bo is a full professor at the School of Economics and Management, Dalian University of Technology. He received his Ph.D. from Dalian University of Technology, China, in 2007 and M.S. degree from Dalian Maritime University, China, in 2004. His research interests include supply chain management, cloud manufacturing management, and intelligent optimisation algorithm.

Yongkui Liu

Yongkui Liu is an associate professor at the School of Mechano-Electronic Engineering, Xidian University. He received his Ph.D. from Xidian University, China, in 2010. From 2011 to 2018, he worked as a postdoctoral fellow at Beihang University in Beijing, The University of Auckland in New Zealand, and the Royal Institute of Technology in Sweden, respectively. His research interests include cloud manufacturing, intelligent scheduling of manufacturing systems, intelligent robots, digital twin, and big data analytics.

Xiaobing Liu

Liu Xiaobing is a full professor at the School of Economics and Management, Dalian University of Technology. He services as the director of National Local Joint Engineering Laboratory of Manufacturing Management Information Technology and the director of Engineering Research Centre of Ministry of Education for Manufacturing Management Technology. He received his Ph.D. from University of Dortmund, Germany, in 1992 and M.S. degree from Dalian Institute of Technology, China, in 1984. His research interests include logistics, supply chain management, production and manufacturing management for complex equipment manufacturing enterprises, and theirapplication systems.