Most of the supply chain models have been developed under symmetric information structure i.e. players have complete knowledge of each other’s policies. But in most of the cases, players do not have complete information about the other players i.e. some information regarding their businesses is hidden. This paper studies supply chain model of imperfect quality items under asymmetric information in which unit price taken by the buyer and unit marketing expenditure are influencing product’s demand. This information is hidden to seller. The seller delivers the supply to the buyer. Each delivered lot goes through an inspection process at the buyer’s side. In the inspection process, the items are divided into two categories. The first category is perfect quality items while the second category is of imperfect quality items. After the inspecting the lots, the perfect quality commodities are to be sold at selling price and the imperfect items are supposed to get sold at a discounted price. The interaction between two constituents of the supply chain is modeled by non-cooperative Seller Stackelberg game approach in which the role of leader is played by the seller while the role of follower is played by the buyer. In our proposed model, the seller does not have information related to market demand but the buyer does. Numerical examples and sensitivity analysis explain the significance of the theory.

The outset of new technologies, systems and applications in manufacturing sector has no doubt lighten up our workload, yet the chance causes of variation in production system cannot be eliminated completely. Every produced/ordered lot may have some fraction of defectives which may vary from process to process. In addition the situation is more susceptible when the items are deteriorating in nature. However, the defective items can be secluded from the good quality lot through a careful inspection process. Thus, a screening process is obligatory in today’s technology driven industry which has the customer satisfaction as its only motto. Moreover, in order to survive in the current global markets, credit financing has been proven a very influential promotional tool to attract new customers and a good inducement policy for the retailers. Keeping this scenario in mind, the present paper investigates an inventory model for a retailer dealing with imperfect quality deteriorating items under permissible delay in payments. Shortages are allowed and fully backlogged. This model jointly optimizes the order quantity and shortages by maximizing the expected total profit. A mathematical model is developed to depict this scenario. Results have been validated with the help of numerical example. Comprehensive sensitivity analysis has also been presented.

Timely identification of newly emerging trends is needed in business process. Data mining techniques like clustering, association rule mining, classification, etc. are very important for business support and decision making. This paper presents a method for redesigning the ordering policy by including cross-selling effect. Initially, association rules are mined on the transactional database and EOQ is estimated with revenue earned. Then, transactions are clustered to obtain homogeneous clusters and association rules are mined in each cluster to estimate EOQ with revenue earned for each cluster. Further, this paper compares ordering policy for imperfect quality items which is developed by applying rules derived from apriori algorithm viz. a) without clustering the transactions, and b) after clustering the transactions. A numerical example is illustrated to validate the results.