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Realizing the effects of trust and personality in cross functional teams using ANFIS classification framework

R. Krishankumar () and K. S. Ravichandran
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R. Krishankumar: SASTRA University
K. S. Ravichandran: SASTRA University

Computational and Mathematical Organization Theory, 2018, vol. 24, issue 2, No 5, 243-276

Abstract: Abstract 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.

Keywords: Teamwork; ANFIS; Ensemble tree; Support vector machine; Decision tree and artificial neural network (search for similar items in EconPapers)
Date: 2018
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DOI: 10.1007/s10588-017-9256-2

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