JOURNAL ARTICLE

Should Doctors Open Online Consultation Services? An Empirical Investigation of Their Impact on Offline Appointments.

  • Published In: Information Systems Research (INFORMS), 2023, v. 34, n. 2. P. 629 1 of 3

  • Database: Business Source Ultimate 2 of 3

  • Authored By: Fan, Wenjuan; Zhou, Qiqi; Qiu, Liangfei; Kumar, Subodha 3 of 3

Abstract

This article investigates the impact of doctors offering online consultation services on the number of their offline appointments, using data from two major Chinese healthcare portals: Haodf.com (online consultations) and Guahao.com (offline appointment bookings). The study finds that doctors who open online consultation services experience a significant increase in offline appointments, supporting the idea that online consultations serve as a signal of doctors’ willingness and ability to communicate effectively with patients. Furthermore, this signaling effect is moderated by factors such as doctors’ recommendation heat (popularity), job title, hospital ranking, affiliation with key hospital departments, and the economic development level of the doctor’s region, with stronger effects observed among doctors with higher status or from more developed areas. Robustness checks, including instrumental variable analysis and propensity score matching, confirm these findings, which have implications for healthcare providers, policy makers, and platform managers aiming to integrate online and offline healthcare channels effectively.

Additional Information

  • Source:Information Systems Research (INFORMS). 2023/06, Vol. 34, Issue 2, p629
  • Document Type:Article
  • Subject Area:Computer Science
  • Publication Date:2023
  • ISSN:1047-7047
  • DOI:10.1287/isre.2022.1145
  • Accession Number:164615174
  • Copyright Statement:Copyright of Information Systems Research (INFORMS) is the property of INFORMS: Institute for Operations Research & the Management Sciences and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

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