Economics at your fingertips  

Capacity utilization change over time

Yao-yao Song, Xian-tong Ren and Guo-liang Yang ()
Additional contact information
Yao-yao Song: Capital University of Economics and Business
Xian-tong Ren: Shandong University
Guo-liang Yang: Chinese Academy of Sciences

Journal of Productivity Analysis, 2023, vol. 59, issue 1, No 4, 78 pages

Abstract: Abstract Frontier-based capacity utilization (CU) measures are the mainstream in CU evaluation of either firms or productive units in various fields. Traditional CU models have not developed a reasonable way to solve the incomparability problem, since efficiencies of the decision making units (DMUs) under a given production technology are not comparable to those of other DMUs under a different technology, which exists especially in data envelopment analysis (DEA) methods. To solve this problem, this paper proposes a systematic solution for the measurement of CU change over time, which reveals the variation of CU among different periods. To overcome the prevalent infeasibility problem since one or more DMUs cannot be projected onto the frontier in a certain direction, we further incorporate fixed-base global and overall techniques in redefining CU and CU change indices. To illustrate the effectiveness of our proposed models, we also employ a sample of Chinese universities to conduct the empirical analysis.

Keywords: Capacity utilization change; Data envelopment analysis; Global technique; Overall technique (search for similar items in EconPapers)
Date: 2023
References: View references in EconPapers View complete reference list from CitEc
Citations: Track citations by RSS feed

Downloads: (external link) Abstract (text/html)
Access to full text is restricted to subscribers.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link:

Ordering information: This journal article can be ordered from
http://www.springer. ... cs/journal/11123/PS2

DOI: 10.1007/s11123-022-00654-z

Access Statistics for this article

Journal of Productivity Analysis is currently edited by William Greene, Chris O'Donnell and Victor Podinovski

More articles in Journal of Productivity Analysis from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().

Page updated 2023-02-04
Handle: RePEc:kap:jproda:v:59:y:2023:i:1:d:10.1007_s11123-022-00654-z