Work

Data-Driven Decision Support for Dairy Producer Selection

Year: 2025

Type: article

Abstract: This study addresses the challenge of value co-creation in the global dairy supply chain by developing a data-driven decision-support tool for selecting dairy producers. Using data from 201 Brazilian dairy professionals, the research employs Exploratory Factor Analysis (EFA), Confirmatory Factor Analysis (CFA), and regression analysis to identify key selection criteria encompassing economic, production, and social factors. These criteria are integrated into an Analytic Hierarchy Process (AHP) framework to facilitate informed producer selection, promoting sustainable practices and enhancing the dairy industry’s competitive advantage.

Source: IFAC-PapersOnLine

DOI: 10.1016/j.ifacol.2025.09.117

Authors: Thiago Cerqueira Vieira, Andrei Bonamigo, Helio Aisenberg Ferenhof, Vasco Sanchez Rodrigues

Institutions: Universidade Federal Fluminense, Centro Universitário Cesusc – UNICESUSC, Cardiff University

Language: English

Topic: Multi-Criteria Decision Making

Subfield: Management Science and Operations Research

Field: Decision Sciences

Domain: Social Sciences

SDGs: Zero hunger, Industry, innovation and infrastructure

Open Access status: diamond

Funder: Conselho Nacional de Desenvolvimento Científico e Tecnológico