Rice (Oryza spp.) is the major staple food for most countries in West Africa, but local
production does not meet demand. Rice is grown mainly by smallholder farmers, and yields …

This paper introduces a new methodology for the estimation of production functions
satisfying some classical production theory axioms, such as monotonicity and concavity …

Among recent methodological proposals for efficiency measurement, machine learning
methods are playing an important role, particularly in the reduction of overfitting in classical …

We introduce a new method for the estimation of production technologies in a multi-input
multi-output context, based on OneClass Support Vector Machines with piecewise linear …

This paper aims to show how to calculate different efficiency measures using a technology
estimator defined through the adaptation of the Gradient Tree Boosting algorithm. This …

This paper contributes by develo** new models for assessing dynamic inefficiency that
incorporate machine learning techniques. In particular, the new approaches apply decision …

In this paper, we introduce an unsupervised machine learning method for production frontier
estimation. This new approach satisfies fundamental properties of microeconomics, such as …

More than 60% of phosphorus (P) taken up by rice (Oryza spp.) is accumulated in the grains
at harvest and hence exported from fields, leading to a continuous removal of P. If P …

This paper presents a novel approach to conduct non‐parametric estimations of production
technologies that adhere to the basic assumptions of production theory axioms, including …

This paper introduces EATBoosting, a novel application of gradient tree boosting within the
Data Envelopment Analysis (DEA) framework, designed to address undesirable outputs in …