Title: An interpretive structural modelling approach for modelling the practices of total quality management in service sector

Authors: Faisal Talib, Zillur Rahman, M.N. Qureshi

Addresses: Mechanical Engineering Section, University Polytechnic, Faculty of Engineering and Technology, Aligarh Muslim University, Aligarh-202002, (U.P.) India. ' Department of Management Studies, Indian Institute of Technology, Roorkee-247667 (U.Kh.), India. ' Department of Mechanical Engineering, Faculty of Technology and Engineering, M.S. University of Baroda, Vadodara-390001 (Gujarat), India

Abstract: Service sector is one of the fastest growing sectors in the world and is facing immense pressure to improve their quality of products and services to compete and achieve a leading position in the global market. The issues related to quality therefore, need to be addressed for better understanding the relationships among the quality practices which could enhance the organisation|s performance. The purpose of this research study is to model the key total quality management (TQM) practices relationship by understanding the dynamics between them that will help service organisations to implement TQM successfully. The present paper utilises the interpretive structural modeling (ISM) methodology to understand the mutual relationships among the TQM practices and presents a hierarchy-based model of the practices. The research shows that there exists a group of practices of TQM having a high driving power and low dependence requiring attention and of strategic importance while another group consists of those practices which have high dependence and are the resultant actions. There also exists a group having high driving power and high dependence. They acts as linkage and influence some of the practices of TQM. The paper ends with a discussion on implications for research as well as practice.

Keywords: total quality management; TQM practices; service organisations; interpretive structural modelling; ISM; services.

DOI: 10.1504/IJMOM.2011.039528

International Journal of Modelling in Operations Management, 2011 Vol.1 No.3, pp.223 - 250

Published online: 14 Jan 2015 *

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