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Research on Green Supply Chain Decision-Making Based on Blockchain to Eliminate the Risk of Energy Efficiency Data Fraud

Published: 13 March 2023 Publication History

Abstract

Abstract: Falsification of product energy efficiency data affects the accuracy of carbon footprint tracking in green supply chain, and is not conducive to the achievement of carbon neutrality goals. Therefore, applying blockchain technology to eliminate the risk of fraudulent product energy efficiency data in the green supply chain, and then investigating its impacts on green supply chain decision-making is a new proposition worth studying. By constructing a Stackelberg game model including a manufacturer and a retailer, this paper analyzes the impacts of applying blockchain technology on green supply chain pricing decisions, carbon emission reduction and profit. We find that the increased risk of product energy efficiency data fraud will have negative impacts on product wholesale price, selling price, carbon emission reduction, and order quantity; Furthermore, the improvement of brand credibility brought about by the application of blockchain is conducive to enhancing the level of carbon emission reduction, and has essential impact on the wholesale price and the selling price, while the impacts of the marginal use cost of blockchain are the opposite. Finally, the triple factors including fixed cost, marginal usage cost and degree of brand credibility improvement jointly affect the profits of enterprises when applying blockchain. Our results have important managerial implications for government and companies who intend to improve their financial and environmental performance by applying blockchain technology in green supply chain.

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BDSIC '22: Proceedings of the 2022 4th International Conference on Big-data Service and Intelligent Computation
November 2022
87 pages
ISBN:9781450397070
DOI:10.1145/3578339
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 13 March 2023

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Author Tags

  1. blockchain
  2. brand credibility
  3. carbon emission reduction
  4. energy efficiency data fraud

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  • Research-article
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  • Refereed limited

Funding Sources

  • National Natural Science Foundation, China

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BDSIC 2022

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