Measuring the capacity utilization of the 48 largest iron and steel enterprises in China

Hirofumi Fukuyama (), Hui-hui Liu, Yao-yao Song and Guo-liang Yang

European Journal of Operational Research, 2021, vol. 288, issue 2, 648-665

Abstract: This paper aims to investigate the capacity utilization (CU) of selected large Chinese iron and steel enterprises by using the data envelopment analysis (DEA) approach. In this paper, we first propose a DEA model with an unrestricted capacity directional output distance function by incorporating two joint cost disposability relations and differentiating between non-emission-causing inputs and emission-causing inputs. Second, we define the status of decision-making units (DMUs) with excess capacity and design a method to identify insufficient variable inputs. We use a group of 48 largest Chinese iron and steel enterprises as our sample to investigate their performance in terms of CU indicator. The main findings are summarised and can be used to support the corresponding policymaking for the managers of both government and enterprises.

Keywords: Data envelopment analysis; Capacity utilization; Iron and steel enterprises; Sustainable development (search for similar items in EconPapers)
Date: 2021
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (11)

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0377221720305555
Full text for ScienceDirect subscribers only

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: https://EconPapers.repec.org/RePEc:eee:ejores:v:288:y:2021:i:2:p:648-665

DOI: 10.1016/j.ejor.2020.06.012

Access Statistics for this article

European Journal of Operational Research is currently edited by Roman Slowinski, Jesus Artalejo, Jean-Charles. Billaut, Robert Dyson and Lorenzo Peccati

More articles in European Journal of Operational Research from Elsevier
Bibliographic data for series maintained by Catherine Liu ().