Purpose This study aims to assess the performance of leather tanneries in India by measuring their technical efficiency (TE) and identifying the impact of firm size and other factors that may be responsible for variations in efficiency. Design/methodology/approach This study uses cross-sectional data from five consecutive years (2017–2018, 2018–2019, 2019–2020, 2020–2021 and 2021–2022) provided by the Annual Survey of Industry (ASI) to fit the Cobb–Douglas-type stochastic frontier function. In addition to estimating the frontier function, an inefficiency model is also used to assess the impact of the firm’s size and other determinants. Findings The result of this study shows that in the current economic scenario, the Indian leather tanneries are working at an average efficiency level between 72% and 80%, spanning over the sample years. The significant coefficient of labor and intermediate inputs indicates that the leather industry is labor-intensive, whereas capital has an insignificant contribution in determining production behavior. Furthermore, the size of the firm has a positive impact on the firm’s efficiency, and there is no clear relationship between the age of the firm and its level of TE. Research limitations/implications This study only uses data from registered firms, as the ASI exclusively surveys registered manufacturing firms in India. In addition, this study is based on cross-sectional data from each of the five years, and some qualitative factors – such as owner education, managerial practices, innovation strategies or marketing efforts – are absent from the ASI data, limiting the ability to explain variations in efficiency. Originality/value The unique aspect of this study is its utilization of a five-digit National Industrial Classification (NIC) code to identify companies in the leather tanneries from the ASI. Previous studies on the leather industry have not used this approach, as they have typically used three-digit or four-digit NIC codes, only measuring TE at the overall industry level. In addition, this study uses two proxies to gauge the size of the firm and evaluate their impact on the firm’s efficiency.
Taj et al. (2025) studied this question.