An evolutionary game analysis on blockchain technology adoption in cross-border e-commerce

Zhou, F., Zhang, C., Chen, T. and Lim, M. K. (2023) An evolutionary game analysis on blockchain technology adoption in cross-border e-commerce. Operations Management Research, (doi: 10.1007/s12063-023-00382-z) (Early Online Publication)

Abstract

Blockchain technology has advantages of decentralization, traceability and tamper-proofing characteristics, supporting to solve the financial security, digital authentication and traceability obstacles in cross-border e-commerce (CBEC) industry. However, little research discusses the adoption behavior of blockchain technology in e-commerce sector. This paper shifts to the blockchain technology adoption in CBEC by formulating an evolutionary game model, consisting of CBEC platforms and the merchants. The decision-making behaviors of CBEC platforms and the merchants are analyzed and discussed regarding on blockchain technology adoption. Besides, the equilibrium solutions are derived, and the numerical simulation test is performed to discover the effect of segmental parameters on the blockchain technology adoption strategy. Results show that when platforms collect smaller profit proportion from merchant, they prefer to adopt blockchain technology, while the platform merchants tend not to blockchain technology adoption at initial stage. With the evolutional game, merchants tend to select blockchain technology strategy. When the platforms collect a higher information cost, both the CBEC platforms and merchants prefer to adopt blockchain technology. The evolutionary analysis and numerical test are performed to help better understanding blockchain technology adoption behavior and the blockchain technology application promotion.

• Item Type: Articles

Additional Information

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e Ministry of Education in PRC (grant no. 22YJC630220); the Key Technologies R&D
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• Status: Early Online Publication
• Refereed: Yes
• Glasgow Author(s) Enlighten ID: Lim, Professor Ming
• Authors: Zhou, F., Zhang, C., Chen, T., and Lim, M. K.
• College/School: College of Social Sciences > Adam Smith Business School > Management
• Journal Name: Operations Management Research
• Publisher: Springer
• ISSN: 1936-9735
• ISSN (Online): 1936-9743
• Published Online: 07 June 2023
• Copyright Holders: Copyright © The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2023
• First Published: First published in Operations Management Research 2023
• Publisher Policy: Reproduced in accordance with the publisher copyright policy