文献类型：期刊文献

英文题名：Optimizing Engineering Transaction Mode for Megaprojects Under Intelligent Construction: A Pythagorean Fuzzy-Prospect Decision-Making Approach

作者：Liu, Xun[1];Yang, Ruonan[1];Lin, Sen[2]

机构：[1]Suzhou Univ Sci & Technol, Sch Civil Engn, Suzhou 215011, Peoples R China;[2]East China Univ Sci & Technol, Sch Business, Shanghai 200237, Peoples R China

年份：2026

卷号：16

期号：2

外文期刊名：BUILDINGS

收录：;EI(收录号：20260519995807);WOS:【SCI-EXPANDED(收录号:WOS:001670858900001)】；

基金：This research was funded by [Shanghai Talent Program Pujiang Project] grant number [24PJC017], [the Fundamental Research Funds for the Central Universities], [Suzhou Science and Technology Plan (Basic Research) Project] grant number [SJC2023002], and [Major Project of Philosophy and Social Science Research in Colleges and Universities of Jiangsu Province] grant number [2025SJYB1055].

语种：英文

外文关键词：project management; intelligent construction; Engineering Transaction Mode; Pythagorean fuzzy sets; prospect theory

摘要：The diffusion of intelligent construction technologies has improved construction efficiency and information integration, while also increasing the complexity and uncertainty of governance decisions in megaprojects. In particular, selecting an appropriate Engineering Transaction Mode (ETM) under intelligent construction involves multiple conflicting criteria, expert judgments, and loss-averse risk preferences, which are not fully captured by conventional multi-criteria decision-making methods. This study proposes a decision-making model that combines Pythagorean fuzzy sets (PFSs) and prospect theory to support ETM selection for megaprojects under intelligent construction. The model constructs an ETM evaluation system grounded in a systematic literature review and questionnaire evidence, encodes expert judgments using PFSs, determines expert and criterion weights via information-utility and fuzzy-entropy measures, and aggregates perceived gains and losses relative to positive and negative ideal solutions through prospect theory. A mega-pumping station project with four ETM alternatives is used for validation. Results indicate that "Self-management + Network-based integrated application + Consultant assistance" achieves the highest prospect value and is consistently ranked first; the same ordering is obtained using TOPSIS and a fuzzy comprehensive evaluation method, demonstrating robustness. The study contributes to theory by coupling hybrid fuzzy representation with loss-aversion-based behavioral aggregation for ETM governance under intelligent construction and provides practitioners with a transparent, replicable decision tool to support ETM selection in complex, uncertainty-laden megaprojects.