TITLE:
Ranking of Greenhouse Vegetable Suppliers across Three Canadian Provinces Using Data Envelopment Analysis with Multiple Inputs and Outputs
AUTHORS:
Mazyar Zahedi-Seresht, Sonali Maldini Rajasekara
KEYWORDS:
Data Envelopment Analysis (DEA), Efficiency, Ranking, Multiple Scenario, Supplier Selection, Green House Production, Decision Making Unit (DMU)
JOURNAL NAME:
American Journal of Industrial and Business Management,
Vol.14 No.10,
October
25,
2024
ABSTRACT: This study explores the application of Data Envelopment Analysis (DEA) as a tool for evaluating the operational efficiency of agricultural operations in Canada under varying conditions. While traditional DEA models are designed for precise input-output data, they may not adequately address uncertainties present in real-world scenarios. This research extends the conventional DEA framework to accommodate multiple scenarios, specifically assessing greenhouse, sod, and nursery operations in British Columbia, Ontario, and Quebec from 2019 to 2023. Utilizing a modified DEA model that remains linear and computationally efficient, this study evaluates efficiency based on various input and output metrics, including operational expenses and product value. Findings indicate that Quebec achieved full operational efficiency consistently, whereas Ontario and British Columbia showed improvement over time but did not match Quebec’s performance. Introducing a multi-scenario approach enhances the robustness of efficiency analysis in agricultural contexts. However, the study notes certain limitations, such as the static nature of the analysis and the exclusion of qualitative factors.