Due to the increased research funding which academic institutions receive to perform advanced R&D, there is an indispensable need to have a systematic approach for selecting competent academicians capable of leading such projects. This paper aims to propose an approach to develop a system for Research Project Leadership Stipulation in finding such academicians.
The system was developed using a decision tree model for leader selection and a neural network model for leader performance prediction, and validated through quantitative and empirical analysis by exercising it on a Research University's Human Resource dataset.
In contrast with common perception, the results showed that the level of an academic leadership expertise does not alone determine R&D project success. Managerial and intellectual competencies complemented by soft skills are more influencing factors on the success of a research project.
This paper provides a comparative analysis of selection criteria and influencing factors on research project leader's performance in terms of their hard and soft skills. The developed system by this research, selects and intelligently predicts the performance of an academician who possesses optimum ability to lead projects with a high confidence level of successful delivery.
Taghavi, M., Taghavi, H. and Taghavi, M. (2013), "Research project leadership stipulation system", Campus-Wide Information Systems, Vol. 30 No. 4, pp. 266-287. https://doi.org/10.1108/CWIS-03-2013-0015
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