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Leadership Evaluation: A Fuzzy Logic based proposed approach


FEATURED PAPER

Ashwani Kharola, Musheer Ahmed Ansarie and Punit Namdeo

Institute of Technology Management (ITM)
Defence Research & Development Organisation (DRDO)
Ministry of Defence, Govt. of India

Landour Cantt, Mussoorie, Uttarakhand, India

 


 

Abstract

This paper presents a stage-wise fuzzy logic based model for effective evaluation of overall leadership. The study illustrates a model based on emotional, intelligent and spiritual quotient for determining true leadership rating. Various attributes of leader under each quotient has been considered for designing of the proposed model. The paper highlights the applicability of fuzzy reasoning in determining relationship among different attributes and quotients in terms of if-then fuzzy rules. A Matlab-Simulink model can be built based on the proposed model and simulation can be further performed.

Keywords: EQ, IQ, SQ, fuzzy logic, Matlab, Simulink

1.0 Introduction

Intelligent quotient (IQ), Emotional quotient (EQ) and Spiritual quotient (SQ) represents the complete combination of human intelligence and performance [1]. Past literature showed that there are significant effects of IQ, EQ and SQ on employee behaviour and performance [2]. Various competencies model of IQ, EQ and SQ has been built and applied to working performance of managers/leaders [3-5]. IQ is a term coined by psychologist William stern and it is determined by a number of factors which includes both genetic and non-genetic factors [6]. It is basically a score derived from one of the several different standardisation tests designed to assess relative intelligence [7]. IQ is an ability of a person to solve an objective problem and can be used to make a person competent enough. Yadav and Singh [8] proposed a fuzzy expert system for evaluation of students performance evaluation. The authors discussed a fuzzy inference system and associated rules. Further a practical method has been proposed and compared with existing statistical method. Pavani et al. [9] evaluated teachers’ performance using fuzzy inference system. The authors compared two different membership functions to achieve the shape of membership function which plays more important role in evaluating performance. Haji et al [10] predicted Intelligence, emotional and spiritual quotients (IESQ) to predict personal quality of corporate managers. The study considered data collected from 237 enterprises managers through questionnaires. The paper also showed structural models of personal quality predicted by IESQ.

The subject emotional intelligence was originated in 1980’s. In the last decade Emotional intelligence has done significant progress in experimental psychology [11]. EQ is the competency to identify and express emotions, understanding emotions, assimilate emotions in thought and regulate emotions in the self and in others [12]. It seems to have significant impact on individual from view point of cognitive ability. Therefore people with a high level of emotional intelligence may not have high intelligent quotient [13, 14]. It further contributes to a leaders capacity to manage challenges and barriers that the leader may face through the leadership process within organisation. Bouslama et al. [15] proposed a fuzzy based emotional intelligence model and framework to capture uncertainties in surveys of new intakes. The proposed system was expected to help HCT Dubai colleges for better design, prepare orientation and counseling sessions for students. Austin et al [16] performed measure of emotional intelligence on 156 first year medical students. The results showed that females scored significantly higher than males. Structural equation modeling showed direct effects of gender on EQ. The findings provided limited evidence for a link between EQ and academic performance of students. Patel et al [17] explored the use of Artificial Intelligence for enhancing students IQ and EQ levels. The knowledge for the system has been documented which can be easily transferred and can be very useful for measuring mental age correctly.

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About the Authors

pmwj40-Nov2015-Kharola-PHOTOAshwani Kharola

Institute of Technology Management
Ministry of Defence, Govt. of India
Uttarakhand, India

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Ashwani Kharola
received B.Tech (with Honors) in Mechanical Engineering from Dehradun Institute of Technology, Dehradun in 2010 and M.Tech in CAD/CAM & Robotics from Graphic Era University, Dehradun in 2013. He is a Silver Medalist for M.Tech (2011-13) batch. Currently he is working as Senior Research Fellow (SRF) in Institute of Technology Management (ITM), One of premier training institute of Defence Research & Development Organisation (DRDO), Ministry of Defence, Govt. of India. He is also pursuing PhD in Mechanical Engineering from Graphic Era University (Deemed University), Dehradun. He has published many papers in National/International peer reviewed ISSN Journals and IEEE Conferences. His current areas of work includes Fuzzy logic reasoning, Adaptive Neuro-fuzzy inference system (ANFIS) control, Neural Networks, Mathematical Modeling & Simulation of variants of highly non-linear Inverted pendulum(IP)systems etc. He can be contacted at [email protected]

 

pmwj44-Mar2016-Kharola-PHOTO2 ANSARIEMusheer Ahmed Ansarie

Institute of Technology Management
Ministry of Defence, Govt. of India
Uttarakhand, India

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Musheer Ahmed Ansarie
received B Tech in Electronics and Communication from UPTU, Diploma in Management, PGDM from IGNOU and pursuing MBA (Operations Research) from IGNOU. Worked in HCL as a Network Tester, currently working in ITM as a Senior Research Fellow. Research on Project Management (Project Planning, Network Diagram, Probability of Completion of Projects, Scheduling of Activities – Single time and Multiple time) and also involved in regimental activities in Admin and Works Department. He can be contacted at [email protected]

 

pmwj44-Mar2016-Kharola-PHOTO3Punit Namdeo

Institute of Technology Management
Ministry of Defence, Govt. of India
Uttarakhand, India

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Punit Namdeo
is presently working as Research Associate in Institute of Technology Management (ITM), one of the premier training institutes of the Defence Research & Development Organisation (DRDO), Government of India. Earlier he was eminent faculty in department of Electronics and Communication, Adina Institute of Science and Technology (AIST), Sagour, Madhya Pradesh. He has over 5 years of teaching experience in the field of electronics, embedded system and communication engineering. Presently he is pursuing a Ph.D. from Uttarakhand Technical University (UTU), Dehradun, Uttarakhand. He can be contacted at [email protected]