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Realizing the effects of trust and personality in cross functional teams using ANFIS classification framework
Computational and Mathematical Organization Theory ( IF 1.8 ) Pub Date : 2017-07-04 , DOI: 10.1007/s10588-017-9256-2
R. Krishankumar , K. S. Ravichandran

Social behaviors are an integral part of team building. In this context, we propose a novel classification model that chooses an optimal classifier from the pool of classifiers for predicting the overall performance (OP). Secondly, the chosen classifier is used to investigate the impact of trust and personality on OP. To achieve these goals a pilot study with real time data from 442 respondents are collected from cross functional teams (CFTs) in India using an E-Questionnaire system. The results indicate that the adaptive neuro fuzzy inference system (ANFIS) method is an optimal classifier (A = 89.14%) with respect to other classifiers. We also infer that the predictors, trust and personality are most suitable for predicting OP with a direct relationship to OP and play an indispensable role; as a catalyst; for boosting OP.

中文翻译:

使用ANFIS分类框架在跨职能团队中实现信任和个性的效果

社会行为是团队建设不可或缺的一部分。在这种情况下,我们提出了一种新颖的分类模型,该模型从分类器池中选择一个最佳分类器来预测整体性能(OP)。其次,选择的分类器用于调查信任和个性对OP的影响。为了实现这些目标,使用电子问卷系统从印度跨职能团队(CFT)收集了442位受访者的实时数据进行了一项初步研究。结果表明,相对于其他分类器,自适应神经模糊推理系统(ANFIS)方法是最佳分类器(A = 89.14%)。我们还推断,预测因素,信任和人格最适合预测与OP有直接关系的OP,并且起着不可或缺的作用。作为催化剂;用于提高OP。
更新日期:2017-07-04
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