Abstract
PURPOSE: This study aimed to optimize the trade-in pricing strategy. To leverage market share, many sellers adopt trade-in strategy for advance selling, Customers can return their old products at a discount price when they buy new products. This can help increase the market share and decrease natural resource consumption. DESIGN/METHODOLOGY/APPROACH: We consider a seller who sells new-generation products over two periods: advance selling and regular selling. Based on the rational expectation equilibrium, we adopt dynamic programming to construct a two-period pricing model with three different trade-in strategies-only in period 2, in both periods, and not at all-explaining the trade-in strategy as a promotion tool used by a monopolist to discriminate for advance selling between new and old customers. FINDINGS: The results suggest that the optimal price is determined by the proportion of old customers, discount factor and product innovation level. Whether and when to give a trade-in rebate to old customers depends on these parameters. The seller's choice of optimal trade-in strategy depends on the threshold value of the new customer demand and trade-in demand. ORIGINALITY/VALUE: Most existing literature focuses on advance selling strategies and trade-in strategies. To the best of our knowledge, this is a pioneering study that adopts trade-in as part of the advance selling strategy.