实证研究
运营管理
业务
营销
计算机科学
广告
心理学
经济
统计
数学
作者
Jimmy Qin,Carri W. Chan,Jing Dong,Shunichi Homma,Siqin Ye
标识
DOI:10.1287/msom.2023.0365
摘要
Problem definition: The adoption of online services, such as telemedicine, has increased rapidly over the last few years. To better manage online services and effectively integrate them with in-person services, we need to better understand customer behaviors under the two service modalities. Utilizing data from two large internal medicine outpatient clinics, we take an empirical approach to study service incompletion, which can be because of either patient no-show or leaving without being seen. Methodology/results: We focus on estimating the causal effect of whether the provider has cleared prior appointments—used as a proxy of intraday delay—on service incompletion for in-person and telemedicine appointments, respectively. When providers have not cleared prior appointments, patients may have to wait, making them more likely to leave without being seen, leading to a higher service incompletion rate. We introduce a multivariate probit model with instrumental variables to handle estimation challenges because of endogeneity, sample selection, and measurement error. We also conduct a numerical analysis of the intraday sequencing rule when having both telemedicine and in-person patients. Our estimation results show that intraday delay increases the telemedicine service incompletion rate by 7.40%, but it does not have a significant effect on the in-person service incompletion rate. Managerial implications: Our study suggests that telemedicine patients may leave without being seen, whereas in-person patients are not sensitive to intraday delay. More importantly, failing to properly distinguish between incompletions caused by intraday delays and those resulting from no-shows can lead to highly inferior patient sequencing decisions. Supplemental Material: The online appendix is available at https://doi.org/10.1287/msom.2023.0365 .
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