This study presents a rigorous analysis of productive efficiency within the manufacturing sector of Himachal Pradesh, India, using the non-parametric linear programming technique of data envelope analysis (DEA) [6]. The unique industrial ecosystem of the state, characterized by its special category status and challenging topography, necessitates a focused evaluation of resource utilization. Utilizing an input-oriented BCC model under Variable Returns to Scale (VRS) [4], this research computes technical, pure technical, and scale efficiencies for a stratified sample of 50 firms across Pharmaceuticals, Textiles, Food Processing, and Electronics sectors. Input variables are capital employed and labour, while output is measured by sales value. Results indicate a mean technical efficiency of 0.783, signifying substantial potential for resource optimization. Decomposition reveals scale inefficiency as the primary constraint, with a majority of firms (64.7%) operating under Increasing Returns to Scale (IRS). The study identifies benchmark firms, provides targeted input reduction pathways for inefficient units, and offers stratified policy prescriptions aimed at enhancing sectoral competitiveness through improved managerial practices and optimal scale operations.
Productive Efficiency, Data Envelopment Analysis, Linear Programming, Himachal Pradesh, Technical Efficiency, Scale Efficiency, BCC Model.
. Productive Efficiency of Manufacturing Industries In Himachal Pradesh Via Data Envelopment Analysis. Indian Journal of Modern Research and Reviews. 2025; 3(3):41-47
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