Abstract
Organizations have widely begun to adopt remote working since the COVID-19 pandemic. However, the effect of remote work on team performance remains unknown. A multi-layer interaction system based on organizational systems theory was designed to assess how remote working affects team performance. Individual performance was computed using a positively skewed stochastic performance model and a modified NK model was used to simulate the team performance under specialized and collaborative conditions. The results showed a complex relationship between task complexity and remote rate and that collaborative teams require a higher remote rate when the probability of employees benefiting from remote work is low to avoid potential detriments from excessive competition. Further results considering agent heterogeneity suggest that individual-level gains are magnified or reduced at the team level and that assessing individual heterogeneity and task complexity is significant for designing remote strategies. In addition, differential mechanisms in team structure and the hierarchy of authority are discussed. This study presents the design and application of a novel business system that helps teams make optimal remote decisions in addition to responding to conflicting discussions in the literature and in practice and providing new insights into decision-making systems in a digital context.
Original language | English |
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Article number | 121372 |
Journal | Expert Systems with Applications |
Volume | 236 |
DOIs | |
Publication status | Published - Feb 2024 |
Keywords
- Interactive system
- NK model
- Remote working
- Specialization and collaboration
- Task complexity
- Team performance