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Estimation of technical efficiency of chemical-free farming using data envelopment analysis and machine learning: evidence from India by Ujjwal Kanti Paul is a Business, Management and Accounting article available to read on EtoBox.

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Purpose This study aims to examine the technical efficiency of the chemical-free farming system in India using a hybrid combination of data envelopment analysis (DEA) and machine learning (ML) approaches. Design/methodology/approach The study used a two-stage approach. In the first stage, the efficiency scores of decision-making units’ efficiency (DMUs) are obtained using an input-oriented DEA model under the assumption of a variable return to scale. Based on these scores, the DMUs are classified into efficient and inefficient categories. The 2nd stage of analysis involves the identification of the most important predictors of efficiency using a random forest model and a generalized logistic regression model. Findings The results show that by using their resources efficiently, growers can reduce their inputs by 34 percent without affecting the output. Orchard's size, the proportion of land, grower's age, orchard's age and family labor are the most important determinants of efficiency. Besides, growers' main occupation and footfall of intermediaries at the farm gate also demonstrate significant influence on efficiency. Research limitations/implications The study used only one output

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Author

Ujjwal Kanti Paul

Publisher

Emerald

Published

2023

Language

EN

Field

Business, Management and Accounting (Social Sciences)