| Abstract |
With the booming development of e-commerce, the importance of controlling carbon emissions has become increasingly prominent in Taiwan. This study explores the trade-offs among time, cost, quality, and carbon emissions (TCQCE) in e-commerce logistics. Will carbon emissions mitigation lead to decreased logistics efficiency and increased costs? This article differs from other studies that use precise numbers and linear model situations. This study adopts fuzzy theory, nonlinear methods, and multi-objective programming models closer to the actual situation to study the decision-making between delayed logistics delivery times and reduced carbon emissions. This article also uses Project D as a case to enhance readers' understanding of decision-making methods in real-life e-commerce logistics cases. The results show that extended delivery times could significantly reduce carbon emissions, ranging from 5259.31 to 419,199.60 tons, and reduce delivery quality under the 90.00% threshold and even under 75.25%. Extending delivery times is a viable business strategy, particularly by extending delivery to push carbon reduction policies to minimize environmental impact. However, consumer acceptance is crucial, as consumers willing to embrace longer wait times can significantly contribute to emission mitigation and support businesses committed to sustainability. This research uses a fuzzy nonlinear multi-objective programming model (FNMOPM) to contribute novel time management to mitigate carbon emissions. Moreover, this study uses a fuzzy and nonlinear approach to fill in the gaps of previous research to balance the efficiency and carbon emission mitigation goals of ESG (environmental, social, and governance) principles. The framework presented in this article solves the complex trade-off situations in the TCQCE issues. This article provides practical, actionable guidance for decision-making regarding sustainable e-commerce logistics, instilling confidence in its implementation. |