A Supply Chain Model Based on Data-Driven Demand Uncertainty under the Influence of Carbon Tax Policy

Abstract

The era of digital economy has spawned new factors of production represented by big data. Data-driven sustainable growth and innovative development is the main line of enterprise digital transformation. In view of the uncertainty of supply chain demand, the optimization of supply chain management under the influence of carbon tax policy is studied from the low-carbon perspective. By introducing the fuzzy theory and a membership function to describe the need for uncertainty, a supply chain optimization model considering the influence of carbon emissions is constructed. Carbon tax policy is regarded as the constraint condition of external production. In the case of fuzzy cost changes, the optimization decision of enterprise supply chain management under carbon tax policy is explored. A trapezoidal fuzzy number is used to determine model fuzziness, and the trapezoidal fuzzy number combined with a genetic algorithm is used to solve the model. Furthermore, taking a certain enterprise as an example, the validity of the model is verified by the mathematical programming model method, considering the data driven and taking the data as the means of production.

Retracted: A Supply Chain Model Based on Data-Driven Demand Uncertainty under the Influence of Carbon Tax Policy

“…Tis article has been retracted by Hindawi, as publisher, following an investigation undertaken by the publisher [1]. Tis investigation has uncovered evidence of systematic manipulation of the publication and peer-review process.…”