Abstract

(1) Background: Traditional one-to-one online consultations with doctors often fail to provide timely and accurate treatment plans; consequently, creating cross-hospital and cross-regional teams has become a new pattern for doctors aiming to offer Internet medical services. Because the online doctor team is a new virtual organizational model, it remains to be explained and investigated. (2) Methods: Combining the information processing view and the social categorization view, this study takes the perspective of team diversity and empirically investigates the effect of team diversity on team performance. We consider four kinds of team diversity, including status capital diversity, decision capital diversity, online reputation diversity, and professional knowledge diversity, and we investigate how team composition from the diversity perspective affects online doctor team performance and how leader reputation moderates the effect of team diversity on team performance. We use secondary data from a leading online medical consultation platform in China (Good Doctor), and our research data include 1568 teams with a total of 5481 doctors. (3) Results: The results show that status capital diversity and decision capital diversity negatively affect team performance; diversity in terms of online reputation and professional knowledge positively affect team performance; and leader reputation moderates the impact of status capital diversity and online reputation on team performance. (4) Conclusions: Our study offers management suggestions on how to form a high-performance doctor team and provides advice for the future development of online doctor teams.

Highlights

  • The rapid development of the Internet has greatly facilitated patients’ acquisition of medical knowledge, and the sharing of medical information on the Internet has become an inevitable trend [1].According to the “2018 Internet Development Report of China”, as of December 2017, China’s Internet medical users increased to 253 million, an annual increase of 29.7%, accounting for 32.8% of all Internet users

  • (3) Results: The results show that status capital diversity and decision capital diversity negatively affect team performance; diversity in terms of online reputation and professional knowledge positively affect team performance; and leader reputation moderates the impact of status capital diversity and online reputation on team performance

  • The results show that team longevity, team size, team average level (Ln), and leader reputation are significantly positively correlated with team performance (Ln)

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Summary

Introduction

The rapid development of the Internet has greatly facilitated patients’ acquisition of medical knowledge, and the sharing of medical information on the Internet has become an inevitable trend [1]. According to the “2018 Internet Development Report of China”, as of December 2017, China’s Internet medical users increased to 253 million, an annual increase of 29.7%, accounting for 32.8% of all Internet users Internet medical services, such as online appointments and online consultations, are the most commonly used services, and difficulties in registration and expensive medical treatment have consistently presented the most worrisome problems for patients. To solve these problems, many hospitals have undergone reforms and established well-known doctor teams. The main purpose of the online doctor team is to connect patients, doctors, and hospitals through the Internet and promote the efficient sharing of medical information between the three entities. This paper empirically tests how four different types of diversity affect doctor team performance under the influence of a leader’s reputation through second-hand data, which broadens the application scope of diversity theory and provides practical guidance for the formation of an efficient doctor team

Doctor Teams and Medical Collaboration
Diversity and Team Performance
Research Gap
Development of Hypotheses
Leader Reputation as a Moderator
Methodology
Dependent Variable
Independent Variables
Control Variables
11. Professional knowledge diversity
Findings
Leader reputation
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