Abstract
Currently, against the background of carbon trading policies, carbon dioxide is attributed commodity properties for market trading within carbon trading. Relevant data show that, in recent years, logistics enterprises have been facing continuously growing demand and carbon emissions have continuously increased; therefore, enterprises urgently need to strengthen their green transformation. Scientific and rational decision-making tools play a meaningful role in helping enterprises improve their competitiveness. In this context, a new three-way decision-making model based on attribute reduction and hesitation degree is proposed. First, an attribute reduction is performed. The attributes of three types of logistics enterprises are simplified according to the carbon emission evaluation attributes proposed in this study to determine their respective minimum attribute sets. Subsequently, the decision and loss function matrices are established considering the hesitation degree. The conditional probability is calculated using intuitionistic fuzzy similarity, and the probability threshold is calculated using the loss function matrix considering the hesitation degree. Finally, case studies and comparative analyses are conducted to illustrate the practicality and rationality of the proposed method.
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