Optimal Strategies for Advance Selling With Random Rewards

Abstract

Advance selling helps retailers who often face a newsvendor problem to reduce demand uncertainty. With the development of e-commerce and promotion, retailers are no longer limited to a single advance selling strategy. Random rewards promotion becomes increasingly easy to apply with the support of network and information technology. Advance selling strategy considering random rewards is favoured by retailers because it not only caters to the psychological needs of strategic consumers but also helps retailers reduce the uncertainty of demand. The advance selling strategy considering random rewards is an optimization model that is established on the basis of single advance selling strategy model. The objective function of the model is retailer’s total profit. The random rewards mechanism is modelled according to the actual situation. The expected utility of consumers’ random rewards adopts a power function of risk aversion type based on strategic consumer reactions. This study analytically examines the optimal total profit of a retailer under the two advance selling strategy models and finds that there is threshold that determines whether an advance selling strategy considers random rewards. In addition, we compare and analyse the advance selling price and consumer utility under the two strategies. Results comparison reveals that the difference between the amount of discount and the size of the winning prize’s expected utility under single advance selling strategy determines whether the advance selling price adopts a discount sales strategy. Numerical analysis further validates the results of the study.

Keywords: Advance selling, Random rewards, Newsvendor, Strategic consumer, Risk aversion