4.6 Article

Centralised resource allocation using Lexicographic Goal Programming. Application to the Spanish public university system

Journal

SOCIO-ECONOMIC PLANNING SCIENCES
Volume 84, Issue -, Pages -

Publisher

ELSEVIER SCIENCE INC
DOI: 10.1016/j.seps.2022.101419

Keywords

Centralised DEA; Resource allocation; Target setting; Lexicographic goal programming; Spanish public universities

Funding

  1. Spanish Ministry of Economy and Competitiveness [PID2019-104263RB-C41, PGC2018-095786-B-IOO]
  2. Ministry of Economy, Knowledge, Business and University, of the Andalusian Government
  3. Universidad Pablo de Olavide/CBUA
  4. FEDER
  5. [UPO-1380624]

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This paper introduces a new approach of using Data Envelopment Analysis (DEA) in a centralised setting, which adopts a global system-wide perspective in resource allocation and target setting and is more effective than other approaches.
This paper deals with Data Envelopment Analysis (DEA) in centralised settings in which the operating units belong to the same organisation. In such a scenario, a global system-wide perspective may be adopted as regards resource allocation and target setting. In this paper, a new Lexicographic Goal Programming (lexGP) approach is proposed using three priority levels: the aggregated input consumption and output production goals; the input and output goals of the individual operating units; and the technical efficiency of the computed targets. It is assumed that the goals for the overall organisation are established by the Central Decision-Maker (CDM) and that they are consistent with those of the individual operating units. The proposed approach has been applied to the Spanish public university system, comprising 47 institutions. Given the CDM preferences in terms of input and output aggregate goals and relative importance weights, specific technical efficient targets have been computed for each university. The results show that the proposed approach is more suitable than the non-centralised DEA approach and produces targets that are more effective than other centralised resource allocation approaches in the sense that they are much closer to both the aggregate goals of the CDM and the specific goals of each university.

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