{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,3]],"date-time":"2026-04-03T14:51:29Z","timestamp":1775227889781,"version":"3.50.1"},"reference-count":51,"publisher":"MDPI AG","issue":"9","license":[{"start":{"date-parts":[[2020,8,21]],"date-time":"2020-08-21T00:00:00Z","timestamp":1597968000000},"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>Organizations have been trying to increase their efficiency and improve their performance in order to achieve their goals. Various factors determine organizational success. The construction industry is a project-based industry which is exceptionally dynamic. The need to identify the weak points and search for solutions to improve the performance of the construction organization is extremely crucial. The industry has always focused on the measure of project success. Previous research works have primarily focused on the measurement of financial or tangible assets. However, there is a lack of understanding of qualitative factors and their combined effect on organizational performance. Therefore, the objectives of this paper are to identify and study the success factors\u2014both financial and non-financial factors. The potential success factors are collected from the literature review and construction experts through a questionnaire to evaluate their effect on organizational performance. The collected data have been analyzed using the Analytic Hierarchy Process (AHP) to shortlist the critical success factors. Thereafter, the Hierarchical Fuzzy Expert System has been used to build a prediction model based on the selected factors. The developed research\/model benefits both researchers and practitioners to predict accurate company performance.<\/jats:p>","DOI":"10.3390\/a13090205","type":"journal-article","created":{"date-parts":[[2020,8,21]],"date-time":"2020-08-21T09:21:51Z","timestamp":1598001711000},"page":"205","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":8,"title":["Hierarchical Fuzzy Expert System for Organizational Performance Assessment in the Construction Industry"],"prefix":"10.3390","volume":"13","author":[{"given":"Zenith","family":"Rathore","sequence":"first","affiliation":[{"name":"DPR Construction, Redwood City, CA 94061, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Emad","family":"Elwakil","sequence":"additional","affiliation":[{"name":"School of Construction Management, Purdue University, West Lafayette, IN 47907, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2020,8,21]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"455","DOI":"10.1061\/(ASCE)ME.1943-5479.0000157","article-title":"Analysis of construction innovation process at project level","volume":"29","author":"Ozorhon","year":"2013","journal-title":"J. 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