scholarly journals Low carbon warehouse management under cap-and-trade policy

2016 ◽  
Vol 139 ◽  
pp. 894-904 ◽  
Author(s):  
Xu Chen ◽  
Xiaojun Wang ◽  
Vikas Kumar ◽  
Niraj Kumar
Keyword(s):  
Trade Policy ◽  
Low Carbon ◽  
Cap And Trade ◽  
Warehouse Management

scholarly journals Achieve a low carbon supply chain through product mix

2017 ◽  
Vol 117 (10) ◽  
pp. 2468-2484 ◽  
Author(s):  
Xu Chen ◽  
Xiaojun Wang
Keyword(s):  
Supply Chain ◽  
Trade Policy ◽  
Carbon Emissions ◽  
Channel Structure ◽  
Low Carbon ◽  
Cap And Trade ◽  
Product Mix ◽  
Content Type ◽  
Carbon Supply ◽  
Trade Offs

Purpose In the era of climate change, industrial organizations are under increasing pressure from consumers and regulators to reduce greenhouse gas emissions. The purpose of this paper is to examine the effectiveness of product mix as a strategy to deliver the low carbon supply chain under the cap-and-trade policy. Design/methodology/approach The authors incorporate the cap-and-trade policy into the green product mix decision models by using game-theoretic approach and compare these decisions in a decentralized model and a centralized model, respectively. The research explores potential behavioral changes under the cap-and-trade in the context of a two-echelon supply chain. Findings The analysis results show that the channel structure has significant impact on both economic and environmental performances. An integrated supply chain generates more profits. In contrast, a decentralized supply chain has lower carbon emissions. The cap-and-trade policy makes a different impact on the economic and environmental performances of the supply chain. Balancing the trade-offs is critical to ensure the long-term sustainability. Originality/value The research offers many interesting observations with respect to the effect of product mix strategy on operational decisions and the trade-offs between costs and carbon emissions under the cap-and-trade policy. The insights derived from the analysis not only help firms to make important operational and strategic decisions to reduce carbon emissions while maintaining their economic competitiveness, but also make meaningful contribution to governments’ policy making for carbon emissions control.

scholarly journals A Flexible Cap-and-Trade Policy and Limited Demand Information Effects on a Sustainable Supply Chain

2021 ◽  
Vol 13 (19) ◽  
pp. 10746
Author(s):  
Ying Gao ◽  
Jianteng Xu ◽  
Huixin Xu
Keyword(s):  
Trade Policy ◽  
Carbon Emission ◽  
Stackelberg Game ◽  
The Other ◽  
Limited Information ◽  
Low Carbon ◽  
Cap And Trade ◽  
Distribution Free ◽  
Demand Information ◽  
Limited Demand

Carbon emission reduction is increasingly becoming a public consensus, with governments formulating carbon emission policies, enterprises investing in emission abatement equipment, and consumers having a low-carbon preference. On the other hand, it is difficult for industry managers to obtain all the demand information. Based on this, this paper aims to investigate operations and coordination for a sustainable system with a flexible cap-and-trade policy and limited demand information. Newsvendor and distribution-free newsvendor models are formulated to show the validity of limited information. Stackelberg game is exploited to derive optimal abatement and order quantity solutions under centralized and decentralized systems. The revenue-sharing and two-part tariff contracts are then proposed to coordinate the decentralized system with limited demand information. Numerical analyses complement the theoretical results. We list some major findings. Firstly, we discover that using abatement equipment can effectively reduce emissions and increase profits. Secondly, the distribution-free approach is effective and acceptable for a system where only mean and variance information is informed. Thirdly, the mean parameter has a greater impact on profits and emissions comparing with the other seven parameters. Finally, we show that both contracts may achieve perfect coordination, and the two-part tariff contract is more robust.

scholarly journals The Impact of Transport Mode and Carbon Policy on Low-Carbon Retailer

2015 ◽  
Vol 2015 ◽  
pp. 1-12 ◽  
Author(s):  
Yi Zheng ◽  
Xue Yang ◽  
Wen Jiang
Keyword(s):  
Trade Policy ◽  
Developing Economies ◽  
Optimal Decision ◽  
Low Carbon ◽  
Cap And Trade ◽  
Transportation Mode ◽  
Carbon Policy ◽  
Transport Mode ◽  
Maximum Profit ◽  
The Impact

Low-carbon retail has become a strategic target for many developed and developing economies. This study discusses the impact of transport mode and carbon policy on achieving this objective. We investigated the retailer transportation mode, pricing, and ordering strategy, which all consider carbon-sensitive demand under the carbon cap-and-trade policy. We analyzed the optimal decision of retailer and their maximum profit affected by transport mode and cap-and-trade policy parameters. Results show that the two elements (cap-and-trade policy and consumer low-carbon awareness) could encourage the retailer to choose low-carbon transportation. The two elements also influence the profit and optimal decision of retailer. Finally, a numerical example is presented to illustrate the applicability of the model.

Joint Production and Pricing Strategy under Carbon Cap-and-Trade Policy

ICLEM 2014 ◽  
2014 ◽  
Author(s):  
Changsong Ma ◽  
Li Tan ◽  
Shucheng Zhou ◽  
Xiang Wang ◽  
Xinyi Zhang
Keyword(s):  
Trade Policy ◽  
Pricing Strategy ◽  
Joint Production ◽  
Cap And Trade

scholarly journals Pricing Strategy and Carbon Emission Abatement under Cap-and-Trade Regulation Considering Social Learning

2019 ◽  
Vol 2019 ◽  
pp. 1-17 ◽  
Author(s):  
Bin Chen ◽  
Man Yu
Keyword(s):  
Social Learning ◽  
Carbon Emission ◽  
Pricing Strategy ◽  
High Price ◽  
Low Carbon ◽  
Cap And Trade ◽  
Carbon Product ◽  
Trade Regulation ◽  
Emission Abatement ◽  
Period 2

In an uncertainty market, social learning plays a significant role in obtaining information to make better decisions. Under cap-and-trade regulation, this paper aims to investigate firms’ pricing and carbon emission abatement issues considering the impact of social learning. This paper establishes a two-period model in a market consisting of a manufacturer and heterogeneous consumers. The manufacturer produces two alternatives (ordinary product and low-carbon product) and makes decisions on sales prices and carbon emission abatement levels. Consumers make decisions on whether and which product to buy. Consumers are not sure about their valuations of products and have the opportunity to discover their true valuation by social learning. The results show that the emission abatement level on ordinary product is affected by the pricing strategy for both types of products. However, the emission abatement level on low-carbon product is only affected by its own pricing strategy. It also shows that social learning lowers the emission abatement level on ordinary product, whereas it improves the emission abatement level on low-carbon product when charging a high price for low-carbon product. Moreover, the price of ordinary product in period 1 is no less than that in period 2. In contrast, the price of low-carbon product in period 2 is higher than that in period 1.

Vehicle routing analyses with integrated order picking and delivery problem under carbon cap and trade policy

2019 ◽  
Vol 43 (2) ◽  
pp. 223-243 ◽  
Author(s):  
Sanjay Jharkharia ◽  
Chiranjit Das
Keyword(s):  
Sensitivity Analysis ◽  
Trade Policy ◽  
Vehicle Routing ◽  
Carbon Footprint ◽  
Order Picking ◽  
Mixed Integer ◽  
Vehicle Speed ◽  
Cap And Trade ◽  
Content Type ◽  
Total Cost

Purpose The purpose of this study is to model a vehicle routing problem with integrated picking and delivery under carbon cap and trade policy. This study also provides sensitivity analyses of carbon cap and price to the total cost. Design/methodology/approach A mixed integer linear programming (MILP) model is formulated to model the vehicle routing with integrated order picking and delivery constraints. The model is then solved by using the CPLEX solver. Carbon footprint is estimated by a fuel consumption function that is dependent on two factors, distance and vehicle speed. The model is analyzed by considering 10 suppliers and 20 customers. The distance and vehicle speed data are generated using simulation with random numbers. Findings Significant amount of carbon footprint can be reduced through the adoption of eco-efficient vehicle routing with a marginal increase in total transportation cost. Sensitivity analysis indicates that compared to carbon cap, carbon price has more influence on the total cost. Research limitations/implications The model considers mid-sized problem instances. To analyze large size problems, heuristics and meta-heuristics may be used. Practical implications This study provides an analysis of carbon cap and price model that would assist practitioners and policymakers in formulating their policy in the context of carbon emissions. Originality/value This study provides two significant contributions to low carbon supply chain management. First, it provides a vehicle routing model under carbon cap and trade policy. Second, it provides a sensitivity analysis of carbon cap and price in the model.

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