Online from: 2006
Subject Area: Management Science/Management Studies
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|Title:||Assessment of occupational health practices in Indian industries: A neural network approach|
|Author(s):||Gouri Shankar Beriha, (Department of Humanities and Social Sciences, National Institute of Technology, Rourkela, India), Bhaswati Patnaik, (Department of Humanities and Social Sciences, National Institute of Technology, Rourkela, India), Siba Shankar Mahapatra, (Department of Humanities and Social Sciences, National Institute of Technology, Rourkela, India)|
|Citation:||Gouri Shankar Beriha, Bhaswati Patnaik, Siba Shankar Mahapatra, (2012) "Assessment of occupational health practices in Indian industries: A neural network approach", Journal of Modelling in Management, Vol. 7 Iss: 2, pp.180 - 200|
|Keywords:||Construction industry, Factor analysis, India, Neural networks, Occupational Health and Safety, Perceptions, Working practices|
|Article type:||Research paper|
|DOI:||10.1108/17465661211242804 (Permanent URL)|
|Publisher:||Emerald Group Publishing Limited|
|Acknowledgements:||The authors express their deep sense of gratitude to the Editor-in-Chief and anonymous reviewer(s) for constructive suggestions that helped to improve the literal and technical content of the paper.|
Purpose – The purpose of this paper is to assess the perceptions of safety officers on Occupational Health and Safety (OHS) norms extended to the workforce in Indian industries, understand implementation levels and find out deficiencies existing therein.
Design/methodology/approach – In this study, the authors utilized factor analysis to develop an instrument specifically responsible for assessing OHS norms in three major industrial sectors through a broad-based questionnaire survey. The pattern of influence of input parameters on outputs such as injury level and material damage is difficult to establish, possibly due to existence of some nonlinear relationship among them. Therefore, a neural network approach is adopted to carry out sensitivity analysis and identify important deficient items.
Findings – Exploratory factor analysis has been carried out on the responses to the designed questionnaire. In total, nine factors with 23 items have been extracted and interpreted. As neural networks are capable of mimicking human cognitive process, the perceptions mechanism of safety officers can be easily modeled via neural networks. Sector-wise deficient items have been identified and strategies for their improvement have been proposed.
Research limitations/implications – The major limitation may be the number of industrial sectors considered in the study. Although the proposed model is quite generic, its performance needs to be tested with other categories of industries.
Practical implications – Although perceptions of safety officers on their immediate work environment help to formulate constructive safety policy and procedures, involvement of a few representatives from the workforce during the implementation level may assist to substantially reduce injury level and material damage, since the workers are more conversant with work practices, are exposed to risk environments and can sustain injuries if accidents occur.
Originality/value – The paper uses advanced statistical and intelligent techniques for assessment of OHS practices. A comparative evaluation of present practices among three major types of Indian industry has been made. Further, the paper proposes an OHS instrument for Indian industry. The paper offers new directions for researchers to devise a comprehensive methodology that aims at reducing occupational health risks.
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