Bridging the sustainable circular economy in cosmetic cross-supply chain practices under uncertainties: a data-driven influential model

Abstract

Cross-supply chains (CSCs), possessing complexity and uncertainties, constitute a dilemma impeding the achievement of cosmetics firms in their efforts to create a sustainable circular economy (SCE). To address this dilemma, this study adopts a data-driven approach, embracing different data types by performing an exploratory factor analysis and reliability test (EFA&RT, and integrating the fuzzy synthetic method (FSM) with the decision-making trial and evaluation laboratory (DEMATEL) to develop an influential model for these practices. This study therefore contributes to the literature by (1) strengthening its theoretical basis, promoting this understanding by bridging the SCE with cosmetic cross-supply chains (CCSCs); (2) proposing a hybrid method for overcoming the dilemma among cross-supply chains; and (3) providing a visual and data-driven analysis that offers a precise direction for making improvements toward the SCE. Specifically, the results show that co-benefit exploration in recycling collaboration, natural resource dependence reduction, and cross-supply chain synchronization via digital technology sharing are the main causal aspects influencing the achievement of a SCE. In practice, material and waste recycling, cost savings, knowledge and information sharing, and sustainable resource management are therefore the driving factors in addressing the cosmetic cross-supply chain dilemma