التفاصيل البيبلوغرافية
| العنوان: |
The Symphony of Team Flow in Virtual Teams. Using Artificial Intelligence for Its Recognition and Promotion |
| المؤلفون: |
Corinna Peifer, Anita Pollak, Olaf Flak, Adrian Pyszka, Muhammad Adeel Nisar, Muhammad Tausif Irshad, Marcin Grzegorzek, Bastian Kordyaka, Barbara Kożusznik |
| المصدر: |
Frontiers in Psychology, Vol 12 (2021) |
| بيانات النشر: |
Frontiers Media S.A., 2021. |
| سنة النشر: |
2021 |
| المجموعة: |
LCC:Psychology |
| مصطلحات موضوعية: |
team flow, team effectiveness, virtual teams, machine learning, collective communication, Psychology, BF1-990 |
| الوصف: |
More and more teams are collaborating virtually across the globe, and the COVID-19 pandemic has further encouraged the dissemination of virtual teamwork. However, there are challenges for virtual teams – such as reduced informal communication – with implications for team effectiveness. Team flow is a concept with high potential for promoting team effectiveness, however its measurement and promotion are challenging. Traditional team flow measurements rely on self-report questionnaires that require interrupting the team process. Approaches in artificial intelligence, i.e., machine learning, offer methods to identify an algorithm based on behavioral and sensor data that is able to identify team flow and its dynamics over time without interrupting the process. Thus, in this article we present an approach to identify team flow in virtual teams, using machine learning methods. First of all, based on a literature review, we provide a model of team flow characteristics, composed of characteristics that are shared with individual flow and characteristics that are unique for team flow. It is argued that those characteristics that are unique for team flow are represented by the concept of collective communication. Based on that, we present physiological and behavioral correlates of team flow which are suitable – but not limited to – being assessed in virtual teams and which can be used as input data for a machine learning system to assess team flow in real time. Finally, we suggest interventions to support team flow that can be implemented in real time, in virtual environments and controlled by artificial intelligence. This article thus contributes to finding indicators and dynamics of team flow in virtual teams, to stimulate future research and to promote team effectiveness. |
| نوع الوثيقة: |
article |
| وصف الملف: |
electronic resource |
| اللغة: |
English |
| تدمد: |
1664-1078 |
| Relation: |
https://www.frontiersin.org/articles/10.3389/fpsyg.2021.697093/full; https://doaj.org/toc/1664-1078 |
| DOI: |
10.3389/fpsyg.2021.697093 |
| URL الوصول: |
https://doaj.org/article/ac3407ca727e4f65beb780be807b9a1c |
| رقم الانضمام: |
edsdoj.3407ca727e4f65beb780be807b9a1c |
| قاعدة البيانات: |
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