Goal programming associated with the non-archimedean infinitesimal: a case study applied in the agricultural sector

Abstract

Paper aims: This work presents a multi-objective method based on goal programming associated with non-Archimedean infinitesimal (NAI) (Improved Weighted Goal Programming method, input-oriented IWGP-MCDEA-BCC). Originality: The MCDEA is applied for the first time in a large agricultural company (over 11 hectares). A new method is proposed which consists of an improvement on input-oriented WGP-MCDEA-BCC approaches. Research method: The performance of the proposed method was compared to the classic Data Envelopment Analysis and the Weighted sum Goal Programming methods. The case study comprises an agricultural company located in the São Francisco Valley (Brazil). Main findings: The proposed method can help decision makers to improve efficiency in the production of different types of fruits. Implications for theory and practice: The proposed model is capable of overcoming the deficiencies associated with classical DEA and allows the company to identify effective ways to increase productivity by reducing input costs.