Explaining olive growers’ participation in Producer Organisations: insights from a machine learning technique
Author(s)
Tamborrino, Camilla
Pupo D’Andrea, Maria Rosaria
Henke, Roberto
Date Issued
2026
Type
article
Volume
14
Issue
7
Start Page
1
End Page
31
Journal
Abstract
Although Italy is among the leading global producers of olives and olive oil, the sector remains structurally fragmented, posing challenges for farmers in terms of scaling production, improving bargaining power, and managing market risks. To address these issues, the Common Agricultural Policy (CAP) has promoted the formation of Producer Organisations (POs) to enhance competitiveness. Despite institutional incentives, however, many Italian olive growers still refrain from joining POs. This study identifies the key characteristics that distinguish PO-affiliated olive growers from non-members in Italy. Drawing on both theoretical and empirical literature on farmer aggregation and employing machine learning (ML) techniques, the research offers a data-driven approach to complement traditional theory-based models. While many findings align with existing studies, the analysis also reveals new variables, particularly those relatedcto asset specificity, that influence the likelihood of PO participation. The study presentscboth policy and methodological implications. First, the results can help policymakerscand PO managers better target specific groups of farmers who may require additional support to achieve CAP objectives. Second, it demonstrates the value of ML-based variable selection and preprocessing in agricultural economics, offering a replicable method for identifying relevant factors in complex, high-variability sectors.
Additional information
Author Contributions (Authorship Statement)
Explaining olive growers’ participation in Producer Organisations: insights from a machine learning technique
Camilla Tamborrino (CT) - Corresponding Author
• Conceptualization (con LC, AS, MRPA, RH, LB)
• Data Curation (con LB)
• Formal Analysis (con LB)
• Methodology (con LB)
• Software (con LB)
• Validation (con LC, AS, MRPA, RH, LB)
• Investigation (con LB)
• Writing -- Original Draft (con LC, LB)
• Writing -- Review & Editing
Luca Cacchiarelli (LC)
• Conceptualization (con CT, AS, MRPA, RH, LB)
• Supervision
• Validation (con CT, AS, MRPA, RH, LB)
• Writing -- Original Draft (con CT, LB)
• Writing -- Review & Editing
Alessandro Sorrentino (AS)
• Conceptualization (con CT, LC, MRPA, RH, LB)
• Supervision
• Validation (con CT, LC, MRPA, RH, LB)
• Writing -- Review & Editing
Maria Rosaria Pupo D'Andrea (MRPA)
• Conceptualization (con CT, LC, AS, RH, LB)
• Supervision
• Validation (con CT, LC, AS, RH, LB)
• Resources
• Writing -- Review & Editing
Roberto Henke (RH)
• Conceptualization (con CT, LC, AS, MRPA, LB)
• Supervision
• Validation (con CT, LC, AS, MRPA, LB)
• Resources
• Writing -- Review & Editing
Luigi Biagini (LB)
• Conceptualization (con CT, LC, AS, MRPA, RH)
• Data Curation (con CT)
• Formal Analysis (con CT)
• Methodology (con CT)
• Software (con CT)
• Validation (con CT, LC, AS, MRPA, RH)
• Investigation (con CT)
• Writing -- Original Draft (con CT, LC)
• Writing -- Review & Editing
Explaining olive growers’ participation in Producer Organisations: insights from a machine learning technique
Camilla Tamborrino (CT) - Corresponding Author
• Conceptualization (con LC, AS, MRPA, RH, LB)
• Data Curation (con LB)
• Formal Analysis (con LB)
• Methodology (con LB)
• Software (con LB)
• Validation (con LC, AS, MRPA, RH, LB)
• Investigation (con LB)
• Writing -- Original Draft (con LC, LB)
• Writing -- Review & Editing
Luca Cacchiarelli (LC)
• Conceptualization (con CT, AS, MRPA, RH, LB)
• Supervision
• Validation (con CT, AS, MRPA, RH, LB)
• Writing -- Original Draft (con CT, LB)
• Writing -- Review & Editing
Alessandro Sorrentino (AS)
• Conceptualization (con CT, LC, MRPA, RH, LB)
• Supervision
• Validation (con CT, LC, MRPA, RH, LB)
• Writing -- Review & Editing
Maria Rosaria Pupo D'Andrea (MRPA)
• Conceptualization (con CT, LC, AS, RH, LB)
• Supervision
• Validation (con CT, LC, AS, RH, LB)
• Resources
• Writing -- Review & Editing
Roberto Henke (RH)
• Conceptualization (con CT, LC, AS, MRPA, LB)
• Supervision
• Validation (con CT, LC, AS, MRPA, LB)
• Resources
• Writing -- Review & Editing
Luigi Biagini (LB)
• Conceptualization (con CT, LC, AS, MRPA, RH)
• Data Curation (con CT)
• Formal Analysis (con CT)
• Methodology (con CT)
• Software (con CT)
• Validation (con CT, LC, AS, MRPA, RH)
• Investigation (con CT)
• Writing -- Original Draft (con CT, LC)
• Writing -- Review & Editing