The Reference Effect of Delay Announcements: A Field Experiment

反事实思维 损失厌恶 计算机科学 领域(数学) 点(几何) 呼叫中心 前景理论 延缓 计量经济学 运筹学 微观经济学 经济 电信 心理学 数学 社会心理学 精神科 工程类 纯数学 几何学
作者
Qiuping Yu,Gad Allon,Achal Bassamboo
出处
期刊:Management Science [Institute for Operations Research and the Management Sciences]
卷期号:67 (12): 7417-7437 被引量:23
标识
DOI:10.1287/mnsc.2020.3870
摘要

We explore whether customers are loss averse in time and how delay information may impact such reference-dependent behavior using observational and field experiment data from two call centers of an Israeli bank. We consider settings with no announcements and announcements of different accuracy levels. We face two key challenges: (1) we do not observe the reference points customers use in our data, as any other field studies, and (2) it is difficult to separate the reference-dependent behavior from the potential nonlinear waiting cost of customers. To address these challenges, we develop a dynamic decision model with consumer learning, through which we infer the reference point each customer used during any given call. The reference points may be different across different customers and evolve across different calls of the same customers. We also exclude the alternative explanation by showing that our main reference-dependent models better explain the observed customer abandonment than models where customers have nonlinear waiting cost. Our results indicate that customers are loss averse regardless of the availability or accuracy of the announcements when their waiting time is relatively long (≥ 90s). Although delay announcements do not alter the nature that customers are loss averse, accurate announcements may affect customers’ belief about the offered waiting time and thus, impact the reference points. Through counterfactual studies, we demonstrate that providing delay announcements improves the call center performance given the loss aversion behavior observed in our data. Interestingly, as customers become more loss averse, the value of providing delay announcements decreases. This paper was accepted by Terry Taylor, operations management.
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