Asian Journal of Information Technology
ISSN: Online 1993-5994ISSN: Print 1682-3915
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Abstract
Achieving a high quality of working life is essential for employees working in organizations. A different conception for studying the quality of working life practice in information technology industries, based on structural equation modeling and the fuzzy approach is propounded by authors of the study. The study is worked out in two sections. In the first section a structural equation model is developed and based on the model hypotheses are framed. These hypotheses mainly measure the impact of quality of working life on organization commitment and the impact of organization commitment on turnover intention. In order to test the model and these hypotheses, a study was conducted among 1030 information technology professionals in the state of Tamil Nadu in India. On the research revealed that quality of working life has a positive impact on organization commitment and organization commitment has a negative impact on turnover intention. Also, the absolute fit indices fit the sample data and reveals that the proposed model has the acceptable fit, by way of satisfying the recommended values. Based on results of the study researchers construct rule statements in the second section which are then converted into fuzzy rules and a fuzzy inference system for this process is constructed with the help of graphical user interface tools of the fuzzy logic toolbox built using MATLAB numeric computing environment. In Mamdani-type inference the output membership functions are expected to be fuzzy sets and the implication of the process is shown as plotted by the toolbox in surface and rule views. Based on these results the study argues that quality of working life is an important factor in determining the organization commitment and turnover intention among information technology professionals.
How to cite this article:
T. Ramya and Sudhakara Pandian. Quality of Working Life organization Commitment and Turnover
Intention in Information Technology Industries: Structural Equation
Modeling and Fuzzy Approach.
DOI: https://doi.org/10.36478/ajit.2016.4790.4799
URL: https://www.makhillpublications.co/view-article/1682-3915/ajit.2016.4790.4799