Research On Risk Management For Subcontracting Of Construction General Contractor

In order to fit the market and meet their own needs, the general contractor alwaystransfers the professional engineering and labor services to subcontractors. Necessarysubcontracting is beneficial to specialized construction, it also does favor to theexertion of the advantages of the general contractor. Currently, subcontracting hasbecome to an important part of construction and penetrates into all aspects ofconstruction engineering. Because of the low qualification of subcontractors and theexternal threats coming from man or nature, the general contractor is confronted withrisk factors during construction subcontracting. Once the hazardous events happened,the general contractor will suffer losses, and even fatal threat will be brought to theentire project. So the general contractor should strengthen the risk management ofsubcontracting.Taken A commercial estate in Zhengzhou as research object, the risk situation ofsubcontracting faced by H company who is the general contractor was studied in thisthesis. On the basis of theoretical knowledge of risk management, using investigationand data analysis as main research method and referenced to previous achievements,the author proposed some insights on risk management of subcontracting for Hcompany.And then adhering to the concept of innovation, establishe the empowermentmodel based on analysis algorithm of group order relation. In this paper to evaluate theoverall risk in the process of the sub-contract degrees, based on support vector machine(SVM) theory, established evaluation model of overall risk for A building project inthe process of the subcontract.Majority of subcontract risk management often stays in the recognition stage, thisarticle is research on building construction general contractor, subcontractor, riskmanagement, an exploration is of certain practical value. Empowerment modelcompared to the established order relation, this paper analyses the algorithm of hisalgorithm has stronger objectivity. Establish the risk degree evaluation model based onsupport vector machine (SVM), provides reference tools for further risk assessmentwork.