LEARNING EFFECTS ON RETAILER ORDERING POLICY FOR IMPERFECT QUALITY ITEMS UNDER TRADE CREDIT FINANCING WITH PRICING STRATEGIES
By
A. R. Nigwal1, U. K. Khedlekar2 and N. Gupta3
1Department of Mathematics, Ujjain Engineering College, Ujjain-456010, Madhya Pradesh, India
2,3Department of Mathematics and Statistics, Dr. Harisingh Gour Vishwavidyalaya(A Central University), Sagar-470003, Madhya Pradesh, India
Email: arnw@rediffmail.com, uvkkcm@yahoo.co.in, neeleshgupta12414@gmail.com
(Received: April 11, 2021; In format: June 17, 2021; Revised: June 11, 2022; Accepted: August 31, 2022)
DOI: https://doi.org/10.58250/jnanabha.2022.52201
Abstract
Nowadays customer service, pricing strategies and trade credit financing scheme are effective, essential and survival parameters for any kind of business setup in the market. In this study we have developed retailer’s ordering policy for imperfect production in which we have applied the learning effect on inspection process on each and every batch of imperfect product. To stimulate sales of product and to study the effects of trade credit financing scheme on retailers business policy we have applied trade credit financing scheme on retailers ordering policy. In this paper, we have developed, an economical order quantity (EOQ) model for retailer’s price sensitive demand of product under two stage trade credit financing scheme. In the trade credit financing scheme we have assumed that the supplier offers to the retailer a fixed credit period of payment and the retailer also offers t a fixed credit period of payment o his customers. An optimal total profit function per unit time has been formulated under the different
trade credit financing periods of payment with different costs and related parameters. A numerical example has been designed to verify the optimum results also we have done sensitive analysis through tables and graphically.
2020 Mathematical Sciences Classification: 90B05, 90B30, 90B50.
Keywords and Phrases: Learning Effect, Pricing, Imperfect quality items, Trade credit policy.