Intelligent servicing strategy for an online-to-offline (O2O) supply chain under demand variability and controllable lead time

With the advancement of technologies, industries tries to adopt the advantages of the technology. Customers are busy in their daily life, and the online platform is the best option for retail, whereas traditional customers still prefer to visit the retail shop. Few customers choose the product online but buy it offline or vice-versa . Owing to all those circumstances, current study focuses on an intelligent dual channel (online-to-offline) strategy in industry to arrange the optimal services for customers. The selling price of the product vary with different channel, which helps to determine the demand of product for entire supply chain. Two important factors, backorder and lead-time are examined precisely through marginal value which helps to arrange optimal service and calculate the exact profit. The profit for a centralized and decentralized case are computed for both the players. Some propositions are developed to prove the global optimality. Numerical results prove that a centralized case provides 7.77% better profit than a decentralized case due to bonding between the players.