An Evolutionary Game Study of Consumers' Low‐Carbon Travel Behavior Under Carbon‐Inclusive Policy

ABSTRACT Carbon‐inclusive policy is regarded as an incentive measure to personal low‐carbon actions. However, its impacts are various for different parties under the government‐led (including government and consumer) mode and the enterprise‐led (including government, consumer and the enterprise) mode, while few studies reveal their difference and give reasonable implications. To fill these gaps, taking consumer's low‐carbon travel as an example, this study develops two evolutionary game models—a two‐party model (based on government‐led adoption) and a tripartite model (based on enterprise‐led adoption)—to investigate the effects of carbon‐inclusive policy. The findings show that (1) the policy benefits all parties in both models, but the participation of the enterprise enhances the effectiveness of the policy; (2) the enterprise‐led mode, that is, the operation of the carbon‐inclusive platform by the enterprise is preferred because all parties have higher payoff, compared with the government‐led mode; and (3) subsidies from the government has a greater impact for consumers' low‐carbon behaviours. However, it has a less impact for the enterprise, which indicates the strategic action of the government is to establish a reasonable consumer subsidy system while reducing subsidies for the enterprise. This study offers a novel perspective on the effects of the carbon‐inclusive policy on consumers' low‐carbon behaviour, and enriches the practice of personal carbon trading.

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Publication Details

Journal
Expert Systems
Published
2024-11-29
DOI
https://doi.org/10.1111/exsy.13804
Primary Topic
Energy, Environment, and Transportation Policies
Type
article
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article

An Evolutionary Game Study of Consumers' Low‐Carbon Travel Behavior Under Carbon‐Inclusive Policy

Daniel S. da Silva, Victor Hugo C. de Albuquerque, Xi Chen, Ke Li et al.
Expert Systems
Energy, Environment, and Transportation Policies
article

An Evolutionary Game Study of Consumers' Low‐Carbon Travel Behavior Under Carbon‐Inclusive Policy

Daniel S. da Silva, Victor Hugo C. de Albuquerque, Xi Chen, Ke Li, Yaqin Liu, Mengya Zhang
article en

Abstract

ABSTRACT Carbon‐inclusive policy is regarded as an incentive measure to personal low‐carbon actions. However, its impacts are various for different parties under the government‐led (including government and consumer) mode and the enterprise‐led (including government, consumer and the enterprise) mode, while few studies reveal their difference and give reasonable implications. To fill these gaps, taking consumer's low‐carbon travel as an example, this study develops two evolutionary game models—a two‐party model (based on government‐led adoption) and a tripartite model (based on enterprise‐led adoption)—to investigate the effects of carbon‐inclusive policy. The findings show that (1) the policy benefits all parties in both models, but the participation of the enterprise enhances the effectiveness of the policy; (2) the enterprise‐led mode, that is, the operation of the carbon‐inclusive platform by the enterprise is preferred because all parties have higher payoff, compared with the government‐led mode; and (3) subsidies from the government has a greater impact for consumers' low‐carbon behaviours. However, it has a less impact for the enterprise, which indicates the strategic action of the government is to establish a reasonable consumer subsidy system while reducing subsidies for the enterprise. This study offers a novel perspective on the effects of the carbon‐inclusive policy on consumers' low‐carbon behaviour, and enriches the practice of personal carbon trading.

Expert SystemsVol. 42(2)
Hunan Normal University (CN), Universidade Federal do Ceará (BR)
Openalex Percentile: Top 87%
Energy, Environment, and Transportation Policies
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An Evolutionary Game Study of Consumers' Low‐Carbon Travel Behavior Under Carbon‐Inclusive Policy — Daniel S. da Silva, Victor Hugo C. de Albuquerque, et al. · Expert Systems (2024) | TGRS Research Map | TGRS