Performance of weather-conditional rebates under different risk preferences

Research output: Contribution to journalArticle

20 Scopus citations

Abstract

Retailers who sell seasonal products often face challenges in demand management due to weather uncertainty. In many cases, they make their ordering and pricing decisions prior to the regular selling season but the vast majority of sales do not occur until after the season starts, during which unfavorable weather conditions may result in high monetary losses. To protect against such adverse financial outcomes, retailers may offer weather-linked promotions such as weather rebates and induce customers to make early purchases. Specifically, weather-conditional rebates are incentives offered in an advance promotional period to be paid to the early buyers if the weather state in the regular season is unfavorable. In the presence of seasonal weather uncertainty, risk attitudes of retailers and buyers may play an important role on the effectiveness of these promotions. In this paper, we analyze the performance of weather-conditional rebates by explicitly considering the impact of different risk behaviors. First, we study the case in which the retailer and customers are risk-neutral and show that the weather-conditional rebates are effective in increasing the retailer's profits. Under the assumption of the retailer's risk-neutrality, we conduct a simulation study to investigate the impact of customers' alternative early-purchase behaviors on the performance of the rebate program. Next, we consider a risk-averse retailer. We model the retailer's risk aversion primarily in the mean-variance framework and find that the rebate program can be designed to increase the mean profit and reduce the profit variance simultaneously. Furthermore, by combining the rebate program with a financial instrument such as binary weather options, the retailer can obtain greater benefits from weather-conditional rebates.

Original languageEnglish (US)
Pages (from-to)1053-1067
Number of pages15
JournalOmega (United Kingdom)
Volume41
Issue number6
DOIs
StatePublished - Dec 1 2013

All Science Journal Classification (ASJC) codes

  • Strategy and Management
  • Management Science and Operations Research
  • Information Systems and Management

Fingerprint Dive into the research topics of 'Performance of weather-conditional rebates under different risk preferences'. Together they form a unique fingerprint.

  • Cite this