Publication Details
Abstract
This study evaluates the export efficiency of 45 small and medium-sized enterprises (SMEs) operating in Uzbekistan's textile sector using Data Envelopment Analysis (DEA), aiming to identify operational benchmarks and structural determinants that drive export performance disparities. We apply both the Charnes–Cooper–Rhodes (CCR) model under constant returns to scale (CRS) and the Banker–Charnes–Cooper (BCC) model under variable returns to scale (VRS) to decompose overall technical efficiency (TE) into pure technical efficiency (PTE) and scale efficiency (SE). A two-stage Tobit regression model is subsequently employed to identify firm-level and institutional determinants. Panel data covering 2019–2023 were drawn from the State Statistics Committee, the Ministry of Investment, Industry and Trade, and enterprise-level financial statements. Mean CCR efficiency is 0.782, indicating that firms produce only 78.2% of frontier-achievable export output. Six firms (13.3%) operate on the efficient frontier; 88.9% exhibit increasing returns to scale (IRS). Tobit regression identifies export market diversification, international certification, technology adoption, regional cluster membership, and government support as significant positive efficiency determinants; small firm size and cotton price volatility exert significant negative effects. This is the first large-N DEA study applied specifically to textile SME export efficiency in Central Asia using enterprise-level microdata, contributing a frontier benchmarking framework to the nascent literature on transition-economy export competitiveness.