Litigation Outcome Prediction of Differing Site Condition Disputes through Machine Learning Models

A support vector machine method for bid/no bid decision making

“…Support vector machines have been successfully applied to many real world classification problems. Examples of support vector machines in construction management include: contractor prequalification decision (Lam et al 2009), project success prediction , contractor default prediction (Tserng et al 2011), cash flow prediction (Cheng, Roy 2011;Cheng et al 2015a), project at completion estimation (Cheng, Roy 2010;Cheng et al 2012;Cheng, Hoang 2014a), conceptual cost estimation (Cheng, Roy 2010), litigation outcome prediction (Mahfouz, Kandil 2012), enterprise resource planning software effort forecasting , dispute prediction (Chou 2012;Chou, Lin 2012;Chou et al 2013Chou et al , 2014, construction cost index estimation (Cheng et al 2013), contractor default prediction (Cheng et al 2014), bridge-maintenance risk score prediction (Cheng, Hoang 2014b), change order productivity loss prediction (Cheng et al 2015b). Despite the success of support vector machines in different construction management related classification problems, to the best of our knowledge, application of these methods have not been explored for bid/no bid decision making, which is the main focus of this study.…”

Ontology in the AEC Industry

“…This shallowness mainly manifests itself in the inability of representing the concepts themselves. All of these expert systems do not represent knowledge from the base level of legal concepts that govern litigation outcomes (Mahfouz and Kandil 2012). To make up for this defect, the common practice used with expert systems is just throwing this problem back at the user by simply asking the user to figure out the concept interpretation and judgment.…”

Intelligent Systems Research in the Construction Industry

“…Moreover, the increase in the use of intelligent systems can be attributed to the fact that today's business environment is progressively transforming to a state of hyper-competitiveness. In this context, construction organisations need to continually explore innovative ways to re-orchestrate their products and services for their customers (Park et al, 2011;Sonmez, 2011;Chen et al, 2011;Mahfouz & Kandil, 2012). 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009…”

“…An industry of this size and magnitude, therefore, has across-the-board effects on the development and affluence of nations. The construction industry's contribution to the nation's economy is, however, inhibited by an increasing number of problems that unfold and often intensify as projects progress (Mahfouz & Kandil, 2012). In order to understand and address the complex problems in the construction industry many academics and practitioners have conceptually and empirically researched the intelligent systems area within different contexts.…”