Quality assessment of enterprise risk management programs
Abroon Qazi and
Mecit Can Emre Simsekler
Journal of Risk Research, 2021, vol. 25, issue 1, 92-112
Abstract:
Enterprise risk management (ERM) is an important process for organizations to manage risks and identify opportunities in a holistic manner. Earlier studies have explored antecedents and consequences of ERM programs considering organizational, procedural, technical, and other related factors. However, limited evidence is available regarding the effectiveness of ERM programs. Using semi-structured interviews with ERM experts, this paper explores how experts assess the efficacy and quality of ERM programs and whether they adopt project management (PM) and total quality management (TQM) tools for implementing and improving the ERM program. Further, the Interpretive Structural Modeling (ISM) technique is used to explore causality among factors influencing the efficacy of an ERM program. The findings of this study provide useful insights to both practitioners and researchers to better understand the importance of assessing and enhancing the quality of ERM programs, and establish cause-effect relationships across factors influencing the efficacy of such programs.
Date: 2021
References: Add references at CitEc
Citations: View citations in EconPapers (1)
Downloads: (external link)
http://hdl.handle.net/10.1080/13669877.2021.1913633 (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: https://EconPapers.repec.org/RePEc:taf:jriskr:v:25:y:2021:i:1:p:92-112
Ordering information: This journal article can be ordered from
http://www.tandfonline.com/pricing/journal/RJRR20
DOI: 10.1080/13669877.2021.1913633
Access Statistics for this article
Journal of Risk Research is currently edited by Bryan MacGregor
More articles in Journal of Risk Research from Taylor & Francis Journals
Bibliographic data for series maintained by Chris Longhurst ().