A platform for research: civil engineering, architecture and urbanism
A platform for research: civil engineering, architecture and urbanism
Analysis of Differing Site Condition (DSC) Litigation Reasoning Through Statistical Modeling
Differing Site Conditions (DSC) is considered to be one of the most prominent reasons for claims within the construction industry. Thus, the purpose of this article is to facilitate decision making related to DSC claims through analysis of the judicial reasoning in such cases by identifying significant legal concepts and implementing statistical modeling. The implemented methodology utilizes 60 DSC cases from the Federal Court of New York, extracts legal concepts upon which verdicts are based through content analysis, and develops a binary choice probit regression model to identify (1) the effect of each concept, (2) the associations and precedence of concepts to each other, and (3) the probabilistic change due to parametric variation in these concepts. The findings provide better means of assessing the legal ramifications based on the identified factors. Such evaluation allows disputing parties to make more informed decision about their dispute resolution strategies. In addition, the current research provides knowledge to contractors about factors to which emphasis should be given while bidding for new projects and upon which control should be maintained while performing a project. Finally, this research creates a solid foundation for the development of robust construction legal decision support systems for DSC disputes.
Analysis of Differing Site Condition (DSC) Litigation Reasoning Through Statistical Modeling
Differing Site Conditions (DSC) is considered to be one of the most prominent reasons for claims within the construction industry. Thus, the purpose of this article is to facilitate decision making related to DSC claims through analysis of the judicial reasoning in such cases by identifying significant legal concepts and implementing statistical modeling. The implemented methodology utilizes 60 DSC cases from the Federal Court of New York, extracts legal concepts upon which verdicts are based through content analysis, and develops a binary choice probit regression model to identify (1) the effect of each concept, (2) the associations and precedence of concepts to each other, and (3) the probabilistic change due to parametric variation in these concepts. The findings provide better means of assessing the legal ramifications based on the identified factors. Such evaluation allows disputing parties to make more informed decision about their dispute resolution strategies. In addition, the current research provides knowledge to contractors about factors to which emphasis should be given while bidding for new projects and upon which control should be maintained while performing a project. Finally, this research creates a solid foundation for the development of robust construction legal decision support systems for DSC disputes.
Analysis of Differing Site Condition (DSC) Litigation Reasoning Through Statistical Modeling
Mahfouz, Tarek (author) / Davlyatov, Sukhrob (author) / Kandil, Amr (author)
International Journal of Construction Education and Research ; 12 ; 285-302
2016-10-01
18 pages
Article (Journal)
Electronic Resource
English
Litigation Outcome Prediction of Differing Site Condition Disputes through Machine Learning Models
| British Library Online Contents | 2012
Litigation Outcome Prediction of Differing Site Condition Disputes through Machine Learning Models
| Online Contents | 2012
Lake Merced Transport - Tunneling Through a Differing Site Condition
| British Library Conference Proceedings | 1993
Managing Delays Caused by Differing Site Condition
| British Library Conference Proceedings | 2003