Regional Efficiency Improvement by Means of Data Envelopment Analysis through Euclidean Distance Minimization Including Fixed Input Factors: An Application to Tourist Regions in Italy

S. Suzuki, P. Nijkamp, P. Rietveld

Research output: Contribution to JournalArticleAcademicpeer-review

Abstract

Standard Data Envelopment Analysis (DEA) is characterized by uniform proportional input reduction or output augmentation in calculating improvement projections. This paper develops a new Euclidean Distance Minimization model in the context of DEA in order to derive a more appropriate efficiency-improving projection model by means of a weighted projection function. The model is extended to the situation where some factor inputs are fixed, for instance, due to lumpiness or natural constraints. The extended DEA model is illustrated in the context of regional planning by using a data set on Italian tourist destination regions. © 2010 the author(s). Journal compilation © 2010 RSAI.
Original languageEnglish
Pages (from-to)67-89
Number of pages22
JournalPapers in Regional Science
Volume90
Issue number1
DOIs
Publication statusPublished - 2011

Fingerprint

Dive into the research topics of 'Regional Efficiency Improvement by Means of Data Envelopment Analysis through Euclidean Distance Minimization Including Fixed Input Factors: An Application to Tourist Regions in Italy'. Together they form a unique fingerprint.

Cite this