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Translating Sustainable Development Goals into Veterinary Action: A Structured Priority-Setting Framework
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Department of Veterinary Biostatistics, Faculty of Veterinary Medicine, Selcuk University, Konya 42130, Türkiye
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Department of Statistics, Faculty of Science, Selcuk University, Konya 42130, Türkiye
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Department of Anatomy, Faculty of Veterinary Medicine, Selcuk University, Konya 42130, Türkiye
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Author to whom correspondence should be addressed.
Vet. Sci. 2026, 13(9), 912; https://doi.org/10.3390/vetsci13090912
Submission received: 4 August 2026
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Revised: 28 August 2026
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Accepted: 2 September 2026
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Published: 4 September 2026
(This article belongs to the Section Veterinary Education, Veterinary Communication and Animal Behavior)
Simple Summary
Veterinary institutions can contribute to sustainable development in many ways, but broad global goals do not indicate which actions should be implemented first. We developed a transparent priority-setting approach that converts relevant global sustainability targets into 27 veterinary actions and compares them according to budgetary burden, accessibility and scope, implementation timeline, and expected sustainability impact. Within the present five-member internal expert panel, Prevention of Zoonotic Diseases received the highest relative implementation priority. The main contribution is therefore not a universal ranking of veterinary actions, but an auditable planning approach that institutions can adapt using broader stakeholder participation and local evidence on resource requirements, reach, implementation conditions, and expected sustainability outcomes.
Abstract
Veterinary institutions need practical methods to translate the Sustainable Development Goals (SDGs) into profession-specific priorities. This study developed a two-phase priority-setting framework linking systematic SDG screening with multi-criteria decision analysis. First, all 169 SDG targets were screened using four veterinary-relevant dimensions. The 48 retained targets were synthesized into 27 preliminary concepts, refined through two rounds of structured internal expert evaluation, and harmonized by the research team into 27 final decision alternatives. Second, Budgetary Burden, Accessibility and Scope, Implementation Timeline, and Sustainability Impact were weighted using the Analytic Hierarchy Process (AHP), and the 27 alternatives were ranked using TOPSIS. Robustness was assessed through Monte Carlo criterion-weight perturbation, score aggregation, and leave-one-expert-out analyses. Budgetary Burden (0.4025) and Sustainability Impact (0.3526) received the largest weights. Prevention of Zoonotic Diseases ranked first (Ci = 0.8272), followed by Awareness-Raising Campaigns, Animal Welfare Inspections on Commercial Animal Farms, and Audits of Food Safety and Production Process Compliance Standards. Criterion-weight perturbation and score aggregation largely preserved the highest-priority set, whereas leave-one-expert-out analysis showed greater sensitivity to panel composition. The framework should therefore be interpreted as a transparent, context-dependent, priority-setting tool rather than as an externally validated or universally applicable hierarchy.
