Information vs. Automation and Implications for Dynamic Pricing

• 成果类型: Article
• 署名作者: Bollinger, Bryan K.; Hartmann, Wesley R.
• 署名单位: New York University; Stanford University
• 刊物名称: MANAGEMENT SCIENCE
• ISSN/ISSBN: 0025-1909
• DOI: 10.1287/mnsc.2018.3225
• 发表日期: 2020
• 页码: 290-314
• 关键词: automation technology; Demand Response; short-run elasticities; UTILITIES; energy; electricity; field experiments

摘要

Essential resources, like electricity and water, can experience rapidly changing demand or supply while the other side of the market is unchanged. Short-run price variation could efficiently allocate resources at these critical times but only if consumers exhibit short-run demand elasticity. The question for firms in these markets has always been how to enable this response. Randomized control trials are increasingly used to test dynamic pricing and technologies that can assist in response by providing information and/or automated response. However, the trials typically do not randomize short-run prices. This paper illustrates how demand from a randomly assigned control group can be used to test the effectiveness of different technologies in increasing short-term price elasticity. To do so, we use a nonparametric control function approach that eliminates the bias inherent in estimating short-term price response using only household random assignment. We find that only automation technology leads to the short-term price elasticity needed to justify real-time pricing.