人-自动化团队的团队沟通行为

Mustafa Demir, Nathan J. Mcneese, Nancy J. Cooke
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引用次数: 35

摘要

如果将合成队友视为“团队玩家”,那么他们必须更好地处理与人类队友之间的微妙沟通和协调。在本研究中,分析了一个人-自动化团队的团队沟通行为,以确定哪些是团队绩效的最佳预测因子。使用LASSO(最小绝对收缩和选择算子)方法选择最能预测团队绩效的团队沟通行为,最终将16种与角色相关的沟通行为(在角色和条件层面)包含在最终模型中。研究结果表明,总体而言,消极感知的沟通行为是消极团队绩效的预测因子。通过这项研究,我们还了解到,即使人类团队成员在与合成团队成员沟通时遵循他们的最佳和期望的沟通行为,这些行为仍然是负面团队绩效的预测因素。这一发现对未来有重要意义:即使人类团队成员与合成团队成员进行了适当的沟通,后者的错误和缺乏类似人类的行为仍然会导致团队表现不佳。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Team communication behaviors of the human-automation teaming
If synthetic teammates are to be considered “team players”, then they must be better equipped to handle the subtleties of communication and coordination with their human teammates. In this study, the team communication behaviors of a human-automation team were analyzed for the identification of which are the best predictors of team performance. The LASSO (Least Absolute Shrinkage and Selection Operator) method was used to select the team communication behaviors that were the best predictors of team performance and, in the end, 16 such role related communication behaviors (at both the role and condition level) were included in the final model. Findings indicate that in general, negatively perceived communication behaviors are predictors of negative team performance. Through this study, we also learned that even when human team members follow their optimal and expected communication behaviors when communicating with a synthetic teammate, these behaviors are still predictors of negative team performance. This finding holds important future considerations: even if human team members are properly communicating with a synthetic teammate, the errors and lack of human-like behavior on the part of the latter can still result in a negative team performance.
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