Title: A complete information PCA-imprecise DEA approach for constructing composite indicator with interval data: an application for finding development degree of cities
Authors: Kolsoom Zamani; Hashem Omrani
Addresses: Faculty of Industrial Engineering, Urmia University of Technology, Urmia, Iran ' Faculty of Industrial Engineering, Urmia University of Technology, Urmia, Iran
Abstract: Composite indicator approach is widely used for finding development degree of regions. One of the most important models for constructing composite indicator is data envelopment analysis (DEA) model. This paper presents a complete information principal component analysis (CIPCA)-imprecise DEA (IDEA) approach for finding development degree of cities with uncertain data. CIPCA is applied to reduce the number of indicators. The output of the CIPCA is a set of new indicators with lower and upper bounds. These indicators are considered as indicators of IDEA and final ranks of cities are calculated by IDEA model. To illustrate the capability of CIPCA-IDEA approach, the development degrees of cities in Kurdistan province of Iran are calculated. First, 62 development indicators are selected and the related interval data for year 2015 are gathered. Then, the proposed approach is applied for nine cities of Kurdistan province and development degree for each city is finally calculated. The results indicate that in the overall ranking, Bijar City is ranked first in the development and Baneh is ranked as ninth city.
Keywords: composite indicator; CIPCA; imprecise data envelopment analysis; IDEA; development degree.
International Journal of Operational Research, 2022 Vol.44 No.4, pp.522 - 549
Received: 06 Oct 2019
Accepted: 01 Dec 2019
Published online: 31 Aug 2022 *