Managing Carbon Footprints under the Trade Credit

Chen, Xiaohong; Gong, Weiping; Wang, Fuqiang

doi:10.3390/su9071235

Cited by 9 publications

(5 citation statements)

References 25 publications

(37 reference statements)

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“…They considered inventory policies under carbon cap-and-trade policy and carbon tax policy. Chen, Gong, and Wang (2017) considered the emissions of ordering, storage, and production. They studied how a retailer may adjust the optimal ordering policy under the carbon cap-and-trade mechanism, and how the minimum total cost and carbon emissions change.…”

Section: The Carbon Policymentioning

confidence: 99%

An inventory model of a deteriorating product considering carbon emissions

Chen

Archibald

et al. 2020

Computers & Industrial Engineering

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Section: The Carbon Policymentioning

confidence: 99%

An inventory model of a deteriorating product considering carbon emissions

Chen

Archibald

et al. 2020

Computers & Industrial Engineering

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“…Then, under these model settings, the structural characteristics of the optimal solutions are analyzed with a numerical study. The authors of [24] analyze how a retailer determines her optimal ordering quantity with a CAT system and trade credit. Then, they show that the CAT system and trade credit jointly affect the retailer's optimal ordering quantity.…”

Section: Literature Reviewmentioning

confidence: 99%

The Optimal Emission Decisions of Sustainable Production with Innovative Baseline Credit Regulations

2019

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In the era of the fourth industrial revolution, the international community is striving to establish a coordinated system to prevent fatal climate change in a global sense. As a result of such changes in business environments, a new issue, sustainability, has recently presented a paradigm shift and new research opportunity in which the theories and practices in traditional production and operations management are being reinterpreted and reapplied in relation to this emerging issue. Under this research background, we consider an optimal emission-trading problem under a cap-and-trade (CAT) emission regulation when the customers' demand is given as an arbitrary probability distribution. Such a CAT approach to reduce the amount of emissions is a normative system for the sustainable production of manufacturing firms, which is also closely related to a well-known open innovation in literature of inventory management. Then, we formulate two stochastic inventory optimization models, which can be applied immediately for two famous CAT policies that exist in reality. In particular, our objective is to draw theoretical and practical implications for baseline credit emission regulations, which are innovative and government-led emission regulation policies, with a well-known newsvendor analysis. For our analytical results, we first show that our objective functions are piecewise linear and (quasi)-concave. Thus, it is found that there exists a unique optimal solution to the problem. Second, we successfully obtain the closed-form optimal solutions for the two models considered. Finally, we conduct a sensitivity analysis through a comparative static analysis to examine how the model parameters can affect the optimal solution in each model. All these analytical results and implications are consistent with previous studies in the literature, as well as with our insights for the models.

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“…The carbon quota policy means enterprises can trade the extra carbon credits for low carbon production under a set carbon quota. If their carbon emissions exceed the set quota, they need to enter the carbon trading market to buy them, and the money spent to buy other companies' carbon credits is the so-called carbon trading cost [5]. China has already established a national carbon emissions trading system, and many enterprises are actively participating.…”

Section: Introductionmentioning

confidence: 99%

Study on Low-Carbon Technology Innovation Strategies through Government–University–Enterprise Cooperation under Carbon Trading Policy

Wang

Song

et al. 2022

Sustainability

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This paper focuses on developing low-carbon technology (LCT) innovation in traditional enterprises under carbon trading policies. The Hamilton–Jacobi–Berman equation quantitatively investigates the coordination mechanism and optimal strategy of LCT innovation systems in conventional industries. A three-way dynamic differential game model is constructed to analyze three cases: the Nash disequilibrium game; the Stackelberg master–slave game; and the cooperative game with the optimal effort of universities, traditional enterprises, and local government, the optimal benefits of the three parties, the region, and the regional LCT level. The results are as follows: (1) by changing the government subsidy factor, carbon trading price, and carbon trading tax rate, the optimal effort of universities and traditional enterprises can be significantly increased; (2) cost-sharing contracts do not change the level of effort of local government to manage the environment, and the use of cost-sharing agreements can change the status of action of universities and enterprises; (3) the optimal effort, optimal benefit, and total system benefit of the three parties and the level of LCT of the industry in the cooperative game are better than those in the non-cooperative case. The combined game achieves the Pareto optimum of the system. The study will contribute to both sustainable business development and environmental sustainability.

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Managing Carbon Footprints under the Trade Credit

Cited by 9 publications

References 25 publications

An inventory model of a deteriorating product considering carbon emissions

An inventory model of a deteriorating product considering carbon emissions

The Optimal Emission Decisions of Sustainable Production with Innovative Baseline Credit Regulations

Study on Low-Carbon Technology Innovation Strategies through Government–University–Enterprise Cooperation under Carbon Trading Policy

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