Low carbon warehouse management under cap-and-trade policy

Chen, Xu; Wang, Xiaojun; Kumar, Vikas; Kumar, Niraj

doi:10.1016/j.jclepro.2016.08.089

Cited by 80 publications

(40 citation statements)

References 49 publications

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“…According to the properties of the CDF, we know that γ > 0 when p−w+s p+h+s > 0.5, so Substituting Equations (16) and (17) into Equation (1), we can obtain This completes the proof.…”

Section: Proposition 2 (I)mentioning

confidence: 66%

“…Toptal et al [15] found that carbon emission reduction investment, additional to reducing emissions as per regulations, further reduce carbon emissions while reducing costs.Żuchowski [16] put forward sustainable solutions to reduce emissions, consequently, in the long run, leading to a "green" warehouse. Chen et al [17] analysed the impact of emission reduction investment on the warehouse management decisions and performances.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Joint Decisions on Emission Reduction and Inventory Replenishment with Overconfidence and Low-Carbon Preference

Zhao

Peng

2018

Sustainability

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This paper presents a game-theoretical analysis of joint decisions on carbon emission reduction and inventory replenishment with overconfidence and consumer's low-carbon preference for key supply chain players when facing effort-dependent demand. We consider respectively the overconfidence of a supplier who overestimates the impacts of his emission reduction efforts on product demand and the overconfidence of a retailer who underestimates the variability of the stochastic demand. We find, surprisingly, that the supplier's overconfidence can mitigate "double marginalization" but hurt self-profit, while the retailer's overconfidence can be an irrelevant factor for self-profit. The retailer aiming at short-term trading should actively seek an overconfident supplier, while the supplier should actively seek a rational retailer for whom the critical fractile is more than 0.5, whereas for an overconfident retailer, the critical fractile is less than or equal to 0.5. The study also underlines the effect of regulation parameters as an important contextual factor influencing low-carbon operations.

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“…According to the properties of the CDF, we know that γ > 0 when p−w+s p+h+s > 0.5, so Substituting Equations (16) and (17) into Equation (1), we can obtain This completes the proof.…”

Section: Proposition 2 (I)mentioning

confidence: 66%

Section: Introductionmentioning

confidence: 99%

Joint Decisions on Emission Reduction and Inventory Replenishment with Overconfidence and Low-Carbon Preference

Zhao

Peng

2018

Sustainability

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“…Rosič and Jammernegg [15] provided a newsvendor model taking the environmental impact of transport into account given the exogenous carbon cap and price, and showed that a carbon trading scheme is better performed than a carbon taxing scheme in transport. Under the carbon cap and trade for warehouse management and technology investment, Chen et al [16] provided the trade-off thresholds between the economic and environmental objectives.…”

Section: Production and Operational Modelmentioning

confidence: 99%

Operational Decision Model with Carbon Cap Allocation and Carbon Trading Price

Lee

2019

Journal of Open Innovation: Technology, Market, and Complexity

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This paper considers a carbon emission cap and trade market, where the carbon emission cap for each entity (either government or firm) is allocated first and then the carbon trading price is decided interdependently in the carbon trading market among the non-cooperative entities which make their production decision. We assume that there are n entities emitting carbon during the production process. After allocating the carbon (emission) cap for each participating entity in the carbon cap and trade market, each participant makes a production decision using the Newsvendor model given carbon trading price determined in the carbon trading market and trades some amount of its carbon emission, if its carbon emission is below or above its own carbon cap. Here, the carbon trading price depends on how carbon caps over the entities are allocated, since the carbon trading price is determined through the carbon (emission) trading market, which considers total amount of carbon emission being equal to total carbon caps over entities and some fraction of total carbon emission should be from each entity participating in the carbon cap and trade market. Thus, we can see the interdependency among the production decision, carbon cap and carbon trading price. We model this as a non-cooperative Stackelberg game in which carbon cap for each entity is allocated in the first stage and each entity’s production quantity is decided in the second stage considering the carbon trading price determined in the carbon trading market. First, we show the monotonic property of the carbon trading price and each entity’s production over the carbon cap allocation. In addition, we show that there exists an optimality condition for the carbon cap allocation. Using this optimality condition, we provide various results for carbon cap and trade market.

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“…Another stream of research related to this study focuses on governmental incentive schemes for sustainable operations and the EV market. An increasing number of studies discuss sustainable operations under governmental incentive policy (e.g., Benjaafar et al [13], Drake et al [14], Chen et al [15], Zhou et al [16], Wang and Huang [17], Yuan et al [18], Zhang et al [19], Tsai and Jhong [20], Siddiqui [21], and Gonseth et al [22]). Benjaafar et al [13] highlighted the effect of operational decisions on carbon emissions and the importance of operational models in evaluating the impact of different regulatory policies, such as mandatory emission caps, taxes on carbon emissions, and emission cap and trade.…”

Section: Introductionmentioning

confidence: 99%

“…Benjaafar et al [13] highlighted the effect of operational decisions on carbon emissions and the importance of operational models in evaluating the impact of different regulatory policies, such as mandatory emission caps, taxes on carbon emissions, and emission cap and trade. Following the study of Benjaafar et al [13], Drake et al [14] investigated the effects of emissions tax and emissions cap-and-trade regulation on a firm's technology choice and capacity decisions; Chen et al [15] analyzed the optimal strategies for warehouse management and technology investment under the cap-and-trade emission policy; Zhou et al [16] focused on how carbon tax policy affects the pricing decisions of supply chain parties and social welfare by incorporating consumer environmental awareness; and Wang and Huang [17] studied the optimal strategies regarding carbon reduction level and online return for a firm that sells green products via an e-commerce platform under carbon tax policy. Unlike these studies, this study focused on the interaction between the government subsidy and an EV manufacturer's battery recycling strategy.…”

Section: Introductionmentioning

confidence: 99%

Optimal Battery Recycling Strategy for Electric Vehicle under Government Subsidy in China

et al. 2018

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Motivated by the increasing environmental concerns about the used electric vehicle batteries in China, an electric vehicle manufacturer’s battery recycling strategy under government subsidy was studied. A consumer utility function was used to capture consumer environmental awareness associated with battery recycling and the game-theoretical approach was applied to analyze the interaction between the government and the manufacturer. It was found that, with an exogenous government subsidy, the manufacturer either recycles all the batteries, or it does not recycle any batteries if the impact of the recycling scale on costs is unremarkable; otherwise, the manufacturer recycles some used batteries when the benefit from recycling is moderate. Interestingly, an increased subsidy causes the manufacturer’s battery recycling rate to decrease if the subsidy is sufficiently large. When the government subsidy is endogenously, either full recycling, no recycling, or partial recycling can still arise. The optimal battery recycling rate and social welfare are lower in a non-cooperative game than in a cooperative game if the benefit from recycling is relatively low. The main findings were numerically justified with realistic subsidy data in China. The numerical results indicate: (1) the optimal battery recycling rate locates in a closed interval from 0 to 1 given an exogenous or an endogenous government subsidy, and it decreases with the subsidy when the subsidy is not less than 50% of the production cost of electric vehicle; (2) the social welfare first increases to a maximum value and then decreases as the subsidy increases; and (3) the optimal battery recycling rate increases significantly and the social welfare is improved when there is cooperation between the government and the manufacturer.

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Low carbon warehouse management under cap-and-trade policy

Cited by 80 publications

References 49 publications

Joint Decisions on Emission Reduction and Inventory Replenishment with Overconfidence and Low-Carbon Preference

Joint Decisions on Emission Reduction and Inventory Replenishment with Overconfidence and Low-Carbon Preference

Operational Decision Model with Carbon Cap Allocation and Carbon Trading Price

Optimal Battery Recycling Strategy for Electric Vehicle under Government Subsidy in China

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