Considerations for development and use of AI in response to COVID-19.

Artificial intelligence (AI) is playing a key supporting role in the fight against COVID-19 and perhaps will contribute to solutions quicker than we would otherwise achieve in many fields and applications. Since the outbreak of the pandemic, there has been an upsurge in the exploration and use of AI, and other data analytic tools, in a multitude of areas. This paper addresses some of the many considerations for managing the development and deployment of AI applications, including planning; unpredictable, unexpected, or biased results; repurposing; the importance of data; and diversity in AI team membership. We provide implications for research and for practice, according to each of the considerations. Finally we conclude that we need to plan and carefully consider the issues associated with the development and use of AI as we look for quick solutions.

How to Manage Diversity and Enhance Team Performance: Evidence from Online Doctor Teams in China.

(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: www.haodf.com), 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.

Why and When Team Reflexivity Contributes to Team Performance: A Moderated Mediation Model.

Team reflexivity has gained popularity as a phenomenon of interest in team research, but mixed theorizing around the relationship between team reflexivity and team performance indicates that the relationship is not fully understood. In an effort to improve our understanding and explain why and when team reflexivity will be conducive to team performance, we examine the role of team diversity as a possible boundary condition and of team decision quality as an explanatory mechanism. Using survey data from 82 teams with 82 leaders and 194 team members, we find that team decision quality is a partial mediator of the relationship between team reflexivity and team performance and that team diversity strengthens this mediating relationship. We also find that team diversity moderates the relationship between team reflexivity and decision quality. Taken together, these findings suggest that reflexivity is most effective in conditions of informational richness, such as when teams have high diversity, as the reflective process allows team members to capitalize on their varied perspectives to improve the quality of their decisions and, thus, their performance.