Evolving a bi-objective optimization model for an after sales supply chain in presence of information asymmetry and service level requirement

Abstract

Optimization of resources related to man, money, manpower and those related to organization is critical in context of after-sales supply chains. Many times, organizational objectives in terms of resource optimization and providing superior customer experience might be conflicting, however. One such instance is when customers expect near 100% service level in which case the organizational costs to meet such high service level goes up significantly. To this end, in this research a novel bi-objective optimization model has been evolved for a typical after-sales service supply chain network constituted of the manufacturer, the retailer and the customer. The first objective function pertains to maximization of the manufacturer's and the retailer's profit. The second objective function is related to the minimization of tardiness of order fulfilment (by the retailer) for the customer. Employing a small problem instance, the authors generate a number of findings related to service level and information asymmetry. In particular, the authors observe that achieving best possible manufacturer-retailer profit and at the same time 100% service level is a mathematical impossibility. Furthermore, reducing information asymmetry between the customer and the retailer (as opposed to reducing information asymmetry between the retailer and the manufacturer) actually yields higher profits for the manufacturer-retailer pair. This research describes the mathematical structure of a three-tier after-sales supply chain wherein information quality and service level requirements are key constraints. Furthermore, the study evolves the bi-objective optimization model as a formulation that can drive the operational decisions of manufacturers and retailers who are part of such after-sales service supply chains.