Prediction of quality performance using artificial neural networks: Evidence from Indian construction projects

Purpose – The purpose of this paper is to enable construction project team members to understand the factors that they must closely monitor to complete projects with a desired quality and also to predict quality performance during the course of a project. With quality being one of the prime concerns of clients in their construction projects, there is a definite need to monitor its performance.Design/methodology/approach – The study discussed here is an extension of past research in which 55 project performance attributes were identified based on expert's opinion and literature survey which after analysis resulted in 20 factors (11 success and nine failure). The results of the second stage questionnaire survey conducted have been used to develop the quality performance prediction model based on artificial neural networks (ANN).Findings – The analyses of the responses led to the conclusion that factors such as project manager's competence, monitoring and feedback by project participants, commitment of all p...

[1]  Abdulaziz A. Bubshait,et al.  ISO 9000 QUALITY STANDARDS IN CONSTRUCTION , 1999 .

[2]  Min Liu,et al.  Using neural network to predict performance of design-build projects in Singapore , 2004 .

[3]  A. T. C. Goh,et al.  Back-propagation neural networks for modeling complex systems , 1995, Artif. Intell. Eng..

[4]  Keith R. Molenaar,et al.  MODEL FOR PUBLIC SECTOR DESIGN-BUILD PROJECT SELECTION , 1998 .

[5]  Y. C. Kog,et al.  Neural networks for construction project success , 1997 .

[6]  Kumar Neeraj Jha,et al.  Commitment, coordination, competence and the iron triangle , 2007 .

[7]  Dov Dvir,et al.  Critical managerial factors affecting defense projects success: A comparison between neural network and regression analysis , 2006, Eng. Appl. Artif. Intell..

[8]  Susan Rebaño-Edwards.  Modelling perceptions of building quality—A neural network approach , 2007 .

[9]  David Arditi,et al.  FACTORS THAT AFFECT PROCESS QUALITY IN THE LIFE CYCLE OF BUILDING PROJECTS , 1998 .

[10]  Anton de Wit,et al.  Measurement of project success , 1988 .

[11]  Florence Yean Yng Ling,et al.  Predicting Performance of Design-Build and Design-Bid-Build Projects , 2004 .

[12]  Anil K. Jain,et al.  Artificial Neural Networks: A Tutorial , 1996, Computer.

[13]  Kumar Neeraj Jha,et al.  Critical Factors Affecting Schedule Performance: Evidence from Indian Construction Projects , 2006 .

[14]  T. T. Soong,et al.  Fundamentals of Probability and Statistics for Engineers , 2004 .

[15]  Mark Konchar,et al.  Comparison of U.S. Project Delivery Systems , 1998 .

[16]  Sai On Cheung,et al.  Predicting project performance through neural networks , 2006 .

[17]  David C. Hoaglin,et al.  Some Implementations of the Boxplot , 1989 .

[18]  K. N. Jha,et al.  Factors affecting cost performance: evidence from Indian construction projects , 2005 .

[19]  Roger Atkinson,et al.  Project management: cost, time and quality, two best guesses and a phenomenon, its time to accept other success criteria , 1999 .

[20]  Danny C. K. Ho,et al.  Design and Build Project Success Factors: Multivariate Analysis , 2001 .

[21]  Jacek M. Zurada,et al.  Introduction to artificial neural systems , 1992 .

[22]  K. N. Jha,et al.  Critical Factors Affecting Quality Performance in Construction Projects , 2006 .

[23]  Y. C. Kog,et al.  Critical Success Factors for Different Project Objectives , 1999 .

[24]  F. Ling,et al.  Key project management practices affecting Singaporean firms’ project performance in China , 2009 .

[25]  Low Sui Pheng,et al.  Implementing Total Quality Management in Construction Firms , 2004 .

[26]  Stuart D. Anderson,et al.  Project quality and project managers , 1992 .