Maintaining energy efficiencies and reducing carbon emissions under a sustainable supply chain management

Abstract

Currently, most countries are moving towards digitalization, and their energy consumption is increasing daily. Thus, power networks face major challenges in controlling energy consumption and supplying huge amounts of electricity. Again, using excessive power reduces the stored fossil fuels and affects the environment in terms of $ {\rm CO_{2}} $ emissions. Keep these issues in mind; this study focuses on energy-efficient products in an energy supply chain management model under credit sales, variable production, and stochastic demand. Here, the manufacturer grants a credit period for the retailer to get more orders; thus, the order quantity is related to the credit period envisaged in this model. Considering such components, supply chain members can reduce negative environmental impacts and significant energy consumption, achieve optimal results and avoid drastic financial losses. Additionally, including a credit period increases the possibility of default risk, for which a certain interest is charged. The marginal reduction cost for limiting carbon emissions, flexible production to meet fluctuating demand, and continuous investment to improve product quality are considered here. The global optimality of system profit function and decision variables (credit period, quality improvement, and production rate) is ensured through the classical optimization method. Interpretive sensitivity analyses and numerical investigations are performed to validate the proposed model. The results demonstrate that the idea of credit sales, flexible production, and quality improvement increases total system profit by $ 28.64\% $ and marginal reduction technology reduces $ {\rm CO_{2}} $ emissions up to $ 4.01\% $.

Cite this work

No public copy is stored for this record, so only the metadata is cited.

Stored only when both papers are in the corpus — 19 citations exist upstream.

Papers that cite the same references — the relational fallback while embeddings are still backfilling.