A model for contractors’ selection in Nigeria

Construction projects in Nigeria are generally characterized by cost and time overrun, substandard work, disputes and abandonment; emanating from several factors of which the wrong choice of contractors is a key factor. This study evaluated the criteria adopted by clients and consultants in contractors’ selection in Nigeria. Data were collected with the aid of questionnaire administered on clients and consultants within the Nigerian construction industry. Also prequalification/bid evaluation scores for eighty contractors were collected based on the criteria used in assessing them. The data collected were analysed with the aid of mean score and regression analysis. The result showed that past performance; contractors’ experience; workmanship quality; tender sum; and plant and equipment were the most important criteria for contractors’ prequalification/bid evaluation in Nigeria. A contractors’ selection model was eventually derived based on some of the identified factors. The goodness of fit of the model as defined by the value of r2 was found to be 99%. This therefore implies that only 1% is explained by other independent variables not included in the regression equation; hence the suitability of the model for contractors’ selection in Nigeria.

[1]  Miroslaw J. Skibniewski,et al.  DECISION CRITERIA IN CONTRACTOR PREQUALIFICATION , 1988 .

[2]  Zedan Hatush,et al.  Evaluating contractor prequalification data: selection criteria and project success factors , 1997 .

[3]  Y. Ilker Topcu,et al.  A decision model proposal for construction contractor selection in Turkey , 2004 .

[4]  Chee Hong Wong,et al.  Contractor Performance Prediction Model for the United Kingdom Construction Contractor: Study of Logistic Regression Approach , 2004 .

[5]  Thomas S. Ng,et al.  CP-DSS: Decision support system for contractor prequalification , 1995 .

[6]  G. D. Holt,et al.  Factors influencing U.K. construction clients' choice of contractor , 1994 .

[7]  Jeffrey S. Russell,et al.  Decision models for analysis and evaluation of construction contractors , 1992 .

[8]  Gary David Holt,et al.  Applying Cluster Analysis to Construction Contractor Classification , 1996 .

[9]  Ivor H. Seeley,et al.  Quantity Surveying Practice , 1984 .

[10]  Dennis F. Dolan The Quantity Surveyor , 1979 .

[11]  J. W Ramus,et al.  Contract Practice for Quantity Surveyors , 1981 .

[12]  R. M. Skitmore,et al.  Prequalification and c-competitiveness , 1993 .

[13]  S. Thomas Ng,et al.  Contractor selection criteria: a cost-benefit analysis , 2001, IEEE Trans. Engineering Management.

[14]  Hal W. Hunt,et al.  Contract Award Practices , 1966 .

[15]  Gary David Holt,et al.  Evaluating prequalification criteria in contractor selection , 1994 .

[16]  Patrick S. W. Fong,et al.  Final contractor selection using the analytical hierarchy process , 2000 .

[17]  Jian-Bo Yang,et al.  Applying Evidential Reasoning to Prequalifying Construction Contractors , 2002 .

[18]  Mohan Raj Manavazhi,et al.  Productivity oriented analysis of design revisions , 2001 .

[19]  Tiesong Hu,et al.  A fuzzy neural network approach for contractor prequalification , 2001 .

[20]  Jeffrey S. Russell,et al.  Predicting contractor failure using stochastic dynamics of economic and financial variables , 1996 .

[21]  Jeffrey S. Russell,et al.  QUALIFIER-1: CONTRACTOR PREQUALIFICATION MODEL , 1990 .