Sustainable fuzzy inventory model for deteriorating item with partial backordering along with social and environmental responsibility under the effect of learning

Abstract

Mitigating carbon emissions and waste, along with economic objectives, are the major concerns for businesses and industries today. Current studies have underlined the requirement to shift the company from entrepreneur to ecopreneur with three goals, i.e., social, economic, and environmental sustainability. This paper investigates an economic order quantity model for deteriorating items with partial backordering on integrating the factors that affect the environment and society. Carbon emissions linked to operational activities of inventory can be reduced with the help of investment in green technology. Deterioration is controlled here with the help of investment in preservation technology. Dumping of waste without the proper mechanism has a hazardous effect on society. So, the cost is also included in this study to adopt the appropriate means to dispose of the wastage. Here, imprecise demand with selling price and advertisement cost-dependent demand is considered. This paper provides some theoretical results related to the concavity of the objective function and solution algorithm to obtain the optimal values of decision variables. A numerical analysis is presented to validate the model. Concavity is demonstrated graphically by considering the decision variables in a pair. Results indicate that as the capital investment in preservation technology rises from 3 to 8 units, around 83% and 90% declines in deterioration rate and disposable cost are observed, respectively. Due to the investment in preservation technology, the disposable cost reduces and profit increases to a certain level. A decline of 4% in carbon footprints is observed due to enhancing the investment in green technology by 33%. In the end, sensitivity analysis has been performed and managerial insights have been provided.