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Bingsheng Liu,Tengfei Huo,Pin-Chao Liao,Jingfeng Yuan,Jiong Sun,Xuan Hu 대한토목학회 2017 KSCE JOURNAL OF CIVIL ENGINEERING Vol.21 No.3
Large construction projects involve massive capital investments, lengthy execution period, and enormous management uncertainties. Therefore, the task of selecting a capable contractor for smooth project delivery is challenging. Although previous studies have attempted to improve the methods of bidding evaluation, limitations still exist. First, the evaluation results might be biased due to the heterogeneity in a small group of experts with different professional experience and capabilities. Second, multi-correlation can reduce the validity of the weightings of the indexes and evaluation results. Third, the subjectivity of the weightings can be a crucial hurdle to the selection of a suitable contractor for a specific project. To overcome these shortcomings, this study introduces Partial Least Squares (PLS) path modeling and develops a Sequence-Multi-Criteria System which can aggregate the evaluation results from different professional practitioners without the use of pre-defined weighting schemes, thus providing a reliable reference for bid evaluation. We incorporated this approach into an evaluation procedure stipulated in the procurement documents of the World Bank and specifically aimed at selecting suitable contractors for large construction projects. A case study was conducted via comparisons across various scenarios, and the validity of this approach was subsequently proved.
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Ting Yuan,Tengfei Huo,Haie Huo,Xianjie Fang,Lilin Li,Miao Chen,Li Yu 대한토목학회 2023 KSCE Journal of Civil Engineering Vol.27 No.11
Social stability risk posed by energy infrastructure projects can seriously affect urban sustainable development. There is thus a need to better understand how risk strategies are designed. However, there is few considerations on risk strategy design by breaking causal relationships. This research innovatively explores social stability risk variables by content mining, develops causal relationships of the social stability risk variables via Fault Tree Analysis (FTA) method, explores core risk variables and critical causal relationships by social network analysis (SNA) method, designs and validates risk strategies. The findings show that: 1) From the overall risk network perspective, the risk network contain 8 core risk variables. 2) From individual risk network perspective, there are 75 critical causal relationships. The top 3 critical causal relationships contain: projects that destroy the cultural landscape would be regarded as threating national security, which often inspires demonstrations among the local people and the line betweenness is the largest (35.589). Traffic congestion by the project is the main reason to cause local small-scale public petition, and the line betweenness is 35.075. Projects that threaten the ecological environment often bring psychological rejection of the project by the local public, and the line betweenness is 30.837. 3) Two scenarios are evaluated in terms of basic scenario and the experiment group scenario. Compared with the basic scenario, risk strategies considering causal relationships have significant effectiveness. The overall risk network density has reduced by 35.22%. The clustering coefficients has decreased by 16.20%. Intermediate central potential has reduced by 9.49%. This study offers a good reference for project managers to complete the sustainable risk control.
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