{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,21]],"date-time":"2026-10-21T00:16:37Z","timestamp":1792541797704,"version":"4.5.0"},"reference-count":26,"publisher":"MDPI AG","issue":"5","license":[{"start":{"date-parts":[[2020,5,2]],"date-time":"2020-05-02T00:00:00Z","timestamp":1588377600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Algorithms"],"abstract":"<jats:p>Risk maturity evaluation is an efficient tool which can assist construction organizations in the identification of their strengths and weaknesses in risk management processes and in taking necessary actions for the improvement of these processes. The accuracy of its results relies heavily on the quality of responses provided by participants specialized in these processes across the organization. Risk maturity models reported in the literature gave equal importance to participants\u2019 responses during the model development, neglecting their level of authority in the organization as well as their level of expertise in risk management processes. Unlike the existing models, this paper presents a new risk maturity model that considers the relative importance of the responses provided by the participants in the model development. It considered their authority in the organization and their level of involvement in the risk management processes for calculating the relative weights associated with the risk maturity attributes. It employed an analytic network process (ANP) to model the interdependencies among the risk maturity attributes and utilizes the fuzzy set theory to incorporate the uncertainty associated with the ambiguity of the responses used in the model development. The developed model allows the construction organizations to have a more accurate and realistic view of their current performance in risk management processes. The application of the developed model was investigated by measuring the risk maturity level of an industrial partner working on civil infrastructure projects in Canada.<\/jats:p>","DOI":"10.3390\/a13050115","type":"journal-article","created":{"date-parts":[[2020,5,4]],"date-time":"2020-05-04T03:29:39Z","timestamp":1588562979000},"page":"115","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":13,"title":["A Fuzzy-Based Decision Support Model for Risk Maturity Evaluation of Construction Organizations"],"prefix":"10.3390","volume":"13","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-3924-8375","authenticated-orcid":false,"given":"Mohammadjavad Arabpour","family":"Roghabadi","sequence":"first","affiliation":[{"name":"Department of Building, Civil and Environmental Engineering, Concordia University, Sir George Williams Campus, 1455 De Maisonneuve Blvd. W., Montr\u00e9al, QC H3G 1M8, Canada"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Osama","family":"Moselhi","sequence":"additional","affiliation":[{"name":"Centre for Innovation in Construction and Infrastructure Engineering and Management (CICIEM), Department of Building, Civil and Environmental Engineering, Concordia University, 1455 de Maisonneuve Blvd, W., Montreal, QC H3G 1M8, Canada"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2020,5,2]]},"reference":[{"key":"ref_1","unstructured":"Salah, A. 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