Decency or devilment: the impact of blockchain technology on product line design

ABSTRACT

Blockchain is a secure database shared across a network of all participants, characterised by immutability, openness, transparency, and traceability. Therefore, blockchain technology is widely used in supply chain management, which can increase consumers' understanding of product information when goods arrive at the consumer end and increase the risk of consumer privacy information leakage. Considering a supply chain system that consists of a manufacturer and a platform, this paper studies the strategic interactions between the platform's adoption of blockchain technology and the manufacturer's product line design based on blockchain's positive and negative impacts on consumers. We examine the driving factors of the platform's use of blockchain technology, which are related to the effect of information transparency and privacy concerns caused by blockchain and the marginal production cost coefficient. In particular, a higher marginal production cost coefficient could make the platform more likely to use blockchain technology. We also find that the practice of blockchain technology may incentivize a manufacturer to extend its product line.

KEYWORDS:

• Blockchain technology
• supply chain management
• product line design
• consumer privacy
• information transparency

SUSTAINABLE DEVELOPMENT GOAL:

• SDG 12: Responsible consumption andproduction

Disclosure statement

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

Data availability statement

Data sharing concerns are not applicable to this article, as no new data were created or analysed in this study.

Sustainable development goal keywords

SDG 12: Responsible consumption and production

Notes

1 https://blockchain.jd.com/(accessed date February 6, 2024).

2 https://cointelegraph.com/news/walmarts-foray-into-blockchain-how-is-the-technology-used (accessed date February 6, 2024).

3 https://www.carrefour.com/en/group/food-transition/food-blockchain (accessed date February 6, 2024).

4 https://www.mckinsey.com/capabilities/growth-marketing-and-sales/our-insights/consumer-data-privacy-and-personalization-at-scale (accessed date February 6, 2024).

5 https://www.mckinsey.com/capabilities/risk-and-resilience/our-insights/the-consumer-data-opportunity-and-the-privacy-imperative (accessed date February 6, 2024).

Additional information

Funding

This work was supported by National Natural Science Foundation of China (Nos. 72171219, 72371232, 71971203, 71921001), the Fundamental Research Funds for the Central Universities (WK2040000082, WK2040000059, WK2040000027), and the New Liberal Arts Fund of USTC (FSSF-A-230104).

Notes on contributors

Yu Jiang

Yu Jiang is a postdoctoral fellow in the School of Management at the University of Science and Technology of China, Hefei, China. She received her Ph.D. degree in Management Science and Engineering from the School of Management, University of Science and Technology of China, Hefei, China, in 2023. Her research interests include product line design, price discrimination and supply chain management. She has published several papers in peer-reviewed academic journals such as Annals of Operations Research, Computers & Industrial Engineering, Industrial Management and Data Systems, and Electronic Commerce Research.

Xiang Ji

Xiang Ji is currently an Associate Professor in the School of Management at the University of Science and Technology of China, Hefei, China. He received his B.S. in Mathematics and Applied Mathematics and Ph.D. in Management Science and Engineering from the University of Science and Technology of China, Hefei, China, in 2011 and 2017 respectively. His research interests include supply chain management, data driven decision analytics, and OM-Marketing interface. He has published over 50 papers in peer-refereed academic journals such as European Journal of Operational Research, International Journal of Production Research, International Journal of Production Economics, Annals of Operations Research, and Omega-International Journal of Management Science.

Jie Wu

Jie Wu is currently a professor in the School of Management at the University of Science and Technology of China, Hefei, China. He is also the Vice Dean of the School of Management, University of Science and Technology of China. He received his Ph.D. in Management Science and Engineering from the University of Science and Technology of China, Hefei, China. His research interests include decision science and operations research. He has published over 200 papers in peer-refereed academic journals such as Operations Research, European Journal of Operational Research, International Journal of Production Research, Omega, Journal of the Operational Research Society, and Annals of Operations Research.

Xiaohang Yue

Xiaohang Yue received the Ph.D. degree in operations management from The University of Texas at Dallas, Richardson, TX, USA. He is currently a Professor of Supply Chain/Operations Management with the Lubar School of Business, University of Wisconsin-Milwaukee. He has published more than 50 articles in leading journals, such as Operations Research, Production and Operations Management, Information System Research, Naval Research Logistics, Decision Sciences, IIE Transactions, IEEE Transactions, European Journal of Operational Research, Omega, International Journal of Production Economics and Journal of Business Research. He is currently serving as Senior Editor for Production and Operations Management, and an editorial advisory board for Transportation Research Part E: Logistics and Transportation Review.