Optimization of preparatory actions in university public procurement: an integrated prescriptive framework AHP–DEA–ILP

Purpose – This study aims to analyze the effect of the quality of preparatory actions, operational efficiency and optimal process allocation on the performance of university public procurement. Design/methodology/approach – A mixed nonexperimental methodological approach was adopted, integrating inferential statistical analysis, multicriteria prioritization, efficiency evaluation and mathematical optimization. The data comes from surveys of 152 public servants, a document review of the Annual Procurement Plan and records from the State Electronic Procurement System for the period 2019–2024, as well as ex post control reports. Preparatory actions were prioritized using the analytic hierarchy process (AHP), technical efficiency was evaluated using data envelopment analysis (DEA) and the optimal allocation of processes was estimated using integer linear programming (ILP). Findings – This study proposes a prescriptive and replicable analytical framework that links diagnosis, prioritization and optimization, providing empirical evidence to strengthen decision-making and improve the performance of public procurement in decentralized public universities. Research limitations/implications – This study was based on information corresponding to a public university and a specific period (2019–2024), which may limit the direct generalization of the results to other institutional contexts. Furthermore, although the integrated AHP–DEA–ILP approach allows for robust analysis, the results depend on the quality of the available data and the assumptions inherent in each method. Future studies could expand the analysis by incorporating multiple institutions, more extensive longitudinal evaluations or dynamic optimization approaches. Practical implications – The results provide operational evidence for public universities to reorient the allocation of hiring processes without requiring budget increases. The proposed framework allows for the identification of bottlenecks, the prioritization of preparatory actions and the redistribution of operational burdens toward more efficient modalities, constituting a concrete tool to support decision-making for public managers and planning officials. Social implications – By improving the efficiency and execution of university procurement, the proposed approach indirectly contributes to better provision of public goods and services, reducing delays, economic losses and risks of regulatory noncompliance. This promotes more responsible use of public resources and strengthens public confidence in institutional management. Originality/value – This study provides a prescriptive and integrated approach that links diagnosis, prioritization, efficiency and optimization in the analysis of university public procurement. Unlike predominantly descriptive studies, it proposes a replicable framework that translates performance evaluation into concrete operational decisions, contributing both to the literature on public management and to the practice of evidence-based institutional planning.