Abstract

Irrational transfer of carbon emissions in the supply chain refers to the phenomenon that after the transfer of carbon emissions occurs, the profits of any party in the supply chain are reduced compared to before the transfer. Identifying and optimizing irrational transfers of carbon emissions in supply chains under environmental regulation are the bases for establishing green supply chains. By constructing a manufacturer-led Steinberg model, we obtained identification intervals for such transfers, then analyzed the influences of the changes in various coefficients. Finally, we designed a carbon emission transfer cost-sharing contract to obtain optimized intervals for shifts from irrational to rational transfers and used a Nash bargaining model to obtain the optimal share rates within the intervals. The results indicated irrational transfer intervals existed in supply chains. When a supplier has a low ability to receive transfers, the range of the irrational transfer intervals increases as the supplier’s capacity coefficient for receiving carbon emission transfers, the transfer investment cost coefficient, the emission reduction investment cost coefficient, and the consumer’s low-carbon awareness intensity increase. Otherwise, the range decreases as these coefficients increase when the supplier’s ability to receive transfers has a large coefficient. In this range, a cost-sharing contract can effectively shift the transfers from irrational to rational and an optimal cost-sharing ratio can help the transfers reach the optimal level, which is beneficial in terms of constructing a green supply chain.

Highlights

  • An enterprise in a supply chain does not exist independently but interacts with other enterprises [1,2]

  • It is assumed that the processing cost after the supplier undertakes the carbon emission transfer is C ( T ) = 2θ ( RTm )2, where θ > 0 represents the cost coefficient after the supplier undertakes the carbon emission transfer, which mainly reflects the cost invested by suppliers to offset the transfer of carbon emissions from manufacturers

  • Chain members cannot increase the profits of supply chain members through profit redistribution and other methods. Suppliers realize that they accept the carbon emission transfer in this context, and even if they cooperate with the manufacturer, they will not be able to improve their own profitability, and will not accept the carbon emission transfer of the manufacturer

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Summary

Introduction

An enterprise in a supply chain does not exist independently but interacts with other enterprises [1,2]. Investigating the optimization of irrational behaviors in low-carbon supply chains, Deng, Xie and Xiong improved loss-sharing contracts and optimized retailers’ aversion to loss [45]. Zhai et al applied the repurchase contract theory to optimize the supply chain under the influence of reciprocal altruism, and found that a certain degree of reciprocal altruism can significantly improve the performance of the supply chain [53] Many studies, such as those mentioned above, cover macro-level transfers and micro-level issues relatedsuch to low-carbon supply-chains, few have considered. The main contributions of this study are considered as follows It describes connotations of irrational emission in are supply chains related irrational the transfer behaviors. The maincarbon contributions oftransfers this study as follows It describes the connotations of irrational carbon emission transfers in supply chains emission transfer intervals inintervals. Formulating a cost-sharing contract and applies a Nash bargaining model to determine the optimal shares of emissions

Problem Description
Assumptions of the Model
Identification of Irrational Transfers
Ignoring Carbon Emission Transfers
Identification Interval of Irrational Transfers
Conclusion
Optimization of Irrational Transfers
Interval Optimization of Irrational Transfers
Point Optimization of Irrational Transfers
Numerical Analysis
Interval Identification of Irrational Transfers
Influence Variables Analysis of Irrational Transfer
Optimization
Conclusions
Main Conclusions
Practical Implications
Research Limitations and Future Work

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