动态定价
收益管理
定价策略
收入
支付意愿
业务
营销
微观经济学
环境经济学
经济
会计
作者
Michael Scholz,Roman-David Kulko
出处
期刊:British Food Journal
[Emerald (MCB UP)]
日期:2021-09-27
卷期号:124 (5): 1609-1621
被引量:2
标识
DOI:10.1108/bfj-03-2021-0294
摘要
Purpose The purpose of this paper is to (1) investigate the effect of freshness on consumers' willingness to pay, (2) derive static and dynamic pricing strategies and (3) compare the effect of these pricing strategies on a retailer's revenue and food waste. This investigation helps to reveal the potentials of dynamic pricing strategies for building more sustainable business models. Design/methodology/approach The authors conduct an online experiment to measure consumers' willingness to pay for fresh and three-days’ old strawberries. The impact of freshness on willingness to pay is analysed using univariate tests and regression analysis. Pricing strategies are compared using a Monte Carlo simulation. Findings The results of this study show that freshness largely determines consumers' willingness to pay and price sensitivity. This renders dynamic pricing a promising strategy from an economic point of view. The results of the simulation study show that food waste can be reduced by up to 53.6% with a dynamic pricing instead of a static pricing strategy in the case that there are as many consumers as strawberry packages in the inventory. Revenue can be increased by up to 10% compared to a static pricing strategy based on fresh strawberries. Practical implications This study suggests that food retailers can improve their revenue when switching from static to dynamic pricing. Furthermore, in most cases, food retailers can reduce food waste with a dynamic instead of a static-pricing strategy, which might help to improve their image through a more sustainable business model and attract additional consumers. Originality/value This study is the first to analyse the possibility of using food freshness to design a dynamic pricing strategy and to analyse the impact of such a pricing strategy on both, a retailer's revenue and a retailer's food waste.
科研通智能强力驱动
Strongly Powered by AbleSci AI