Determinants of manufacturing productivity: Pilot study on labor-intensive industries

Purpose – The purpose of this study is to address the impact of three issues: degree of skills, favorable working environment and R&D on manufacturing productivity of labor-intensive industries. Design/methodology/approach – Convenience sampling method has been used to conduct this study. Three categories of labor-intensive manufacturing industries (A, B and C) have been chosen to perform this research. Industrial category A represents the manufacturing operations which are based on skill of labor. Category B is a group of industries which provides a favorable working environment to utilize the potential of skill in manufacturing process. Category C is a specialized group of industries and its manufacturing process is dependent on R&D. Input–output data for manufacturing operations of the sample industries have been analyzed by using standard statistical techniques to establish the relationship between dependent and independent variables. Findings – The degree of skill and productivity is positively correlated, but not strongly (r0.5) associated with favorable working environment. However, a significantly positive correlation (r>0.7) is found between R&D expenditure and productivity. The study concludes that a higher degree of skills, favorable working environment and R&D are important inputs to a labor-intensive manufacturing process, which is positively associated with productivity. Research limitations/implications – Manufacturing productivity is an important parameter of industrial growth, and this paper addresses this issue. The current work addresses the garments sector, i.e. a part of the labor-intensive industries. Though this work is focused on only one part of this sector; the findings of this study have significant policy implications. The results would be useful for manufacturing business executives and policy makers. Originality/value – This study addresses the important issue of productivity of labor-intensive manufacturing industries, and generates quantitative evidence of the impact of degree of skills, favorable working environment and R&D on productivity. The generated information enriches the present knowledge stock of manufacturing systems. The findings could be the basis for further academic research on manufacturing systems