| Abstrakt: |
This paper develops an innovative game theory analytics that academics and practitioners can adopt to develop intelligent technologies for the efficient and robust supply chain management. Long-period disruptions were new to the global supply chains, and the disruptions associated with COVID-19 were an actual check on the robustness claim of supply chains. Unavailability of raw materials and workers, poor logistic facilities, etc., created unparalleled disruptions for production units during the lock-down period of COVID-19. Many studies analyze and model Dual-Channel Supply Chain (DCSC) and the associated disruptions. However, there is no existing literature in the field of COVID -19 related disruptions in the DCSC consisting of retailers and e-tailers. Moreover, there is no literature in this area where a game theory framework, the most suitable framework for modelling the DCSC, has been used for analyzing disruptions in DCSC consisting of retailers and e-tailers as downstream partners. In this study, we check the impact of lock-down induced production disruptions on DCSC comprising of a manufacturer, retailer, and e-tailer. The researchers employed the game theory framework to model the interaction for developing supply chain analytics for robust supply chains. We have obtained the channel partner's optimal pricing decisions, order quantity, and profitability during the pre-lock-down and lock-down periods. After that, we compare the models to quantify the increase or decrease in optimal decisions. We observed that the optimal price increased, and optimal order quantity and profit decreased for all the channel partners. Academics and practitioners can adopt the proposed game theory analytics to develop intelligent technologies for the efficient and robust supply chain management. The proposed Stackelberg and Nash algorithm can be implanted by Python game theory software to develop an intelligent system. [ABSTRACT FROM AUTHOR] |
