Technical Efficiency and its Determinants of Cane and Bamboo Enterprise in Assam: A Conventional DEA, Double Bootstrap DEA, and SFA Approach

Abu Daud Pathan ()
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Abu Daud Pathan: National Institute of Technology Silchar

SN Operations Research Forum, 2025, vol. 6, issue 3, 1-27

Abstract: Abstract Estimating technical efficiency (TE) is crucial for measuring a firm's performance. Most previous researchers used secondary data; thus, they extensively examined the firm-specific variables affecting the TE of micro and small enterprises (MSEs). However, they overlooked how the determinants, including entrepreneur, firm, and environmental-related variables, influence the TE of micro-based cane and bamboo firms in Assam. The present paper intends to fill this void. A multistage stratified random sampling technique was used to collect 360 household data from four selected districts of Assam to estimate the TE and its determinants using the conventional data envelopment analysis (DEA), double bootstrap DEA, and stochastic frontier analysis (SFA) approach. The estimated average TE is 0.7456 and 0.6622 using the conventional DEA and double bootstrap DEA approach. The mean TE is significantly higher (0.9205) using the SFA approach. The empirical results revealed that the entrepreneur-specific (age, gender, education level, working experience, and training facility), firm-specific (family type, family labor, hired labor, bank loan, technological support, and government assistance), and environmental-related variables (family business, firm location, and selling destination) significantly affect the firm's TE using ordinary least squares (OLS) using conventional DEA, truncated regression using the double bootstrap DEA, and maximum likelihood estimation (MLE) using SFA methods. The firm's efficiency may be improved by implementing appropriate policies through government agencies, such as organizing training programs, trade fairs & exhibitions, low-interest credit facilities, and tools and machinery support.

Keywords: Technical efficiency; Entrepreneur variables; Firm characteristics; Environmental variables; Double bootstrap data envelopment analysis; Stochastic frontier analysis (search for similar items in EconPapers)
Date: 2025
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DOI: 10.1007/s43069-025-00545-7

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