The impact of capacity planning on product lifecycle for performance on sustainability dimensions in Reverse Logistics Social Responsibility

Abstract

Reverse Logistics Social Responsibility (RLSR) is preferred as a social responsibility activity in the supply chain since it involves most of the supply chain actors who have an impact on social responsibility. So here, a single-product System Dynamics (SD) model of the supply chain with RLSR is developed. The product lifecycle with its inherited uncertainties, such as the length of the product lifecycle, pattern of the product lifecycle, and residence index, is adopted by considering interrelated sustainability dimensions. Efficient flexible capacity planning is established as a policy option by considering a social responsibility fund from the premium price that is contributed by consumers. The Taguchi design of experiment is used for analysis of the numerical simulation. Finally, the significance with its power is measured to show the power of the relationship between policy and uncertainty for the sustainability dimensions performance. These features will be used to analyze the impact of capacity planning on product lifecycle for performance on sustainability dimensions in RLSR by using an SD approach. The findings show that the policy parameters have an effect on any measured performances and uncertainties with some conditional exceptions. These findings reveal three interesting facts regarding RLSR due to the considered model features. First, the economic performance is a result of a direct influence of policy. Second, the environmental performance results from the indirect effect of the policy. Third, the social performance is the performance that is hardest to influence by policy. Therefore, the findings underscore this paper's contributions to the relatively limited academic knowledge on the examination of the impact of behavior in reverse logistics as a social responsibility due to capacity planning and the product lifecycle with its inherited uncertainties. These contributions offer managers a better understanding of the relationship between capacity planning, product lifecycle with its inherited uncertainties, and sustainability performance. This better understanding will lead to better capacity planning to tackle product lifecycle with its inherited uncertainties for sustainable RLSR.