Developing a Model For Forecasting the Success of Construction Projects Integration Taguchi Design (DOE) And TAXONOMY

Document Type : Research Article

Authors

1 Economic, Accounting & Management Faculty, Yazd University, Yazd, Iran

2 Management & Accounting Faculty, Allameh Tabatabaee University, Tehran, Iran

3 Management Faculty, Tehran University, Tehran, Iran

Abstract

The construction industry is the largest industry in the world. It is more of a service than a manufacturing industry. The success of construction projects is a fundamental issue for most governments, users and communities. Multi Criteria Decision Making is an approach that can be used to deal complex problems. In this paper, to treat multi criteria decision making problems in uncertain condition a model based on grey theory-including grey relational analysis and grey numbers is proposed. The scope of research about gray theory and multiple criteria decision making is relatively new field, so in this study we used the integration of Taguchi and Taxonomy with gray theory to forecasting the success of construction projects. Using Taguchi method and gray theory, weight of each criterion was determined. Finally, using Taxonomy and gray theory the success of thirteen construction projects was forecasted. Findings of this study provide clear understanding of constuction project and could potentially enhance existing knowledge of construction project success.

Keywords

Main Subjects

References

[1] S. A. R., Safavi, M. A., Shayanfar, S. M., Nasr Azadani, E. E., Eshtharian; Investigating the Causes of Delay in Implementation of Urban construction Projects according to Project Factors, 6th International Project Management Conference, 2010 (in Persian).
[2] A. K., Munns; B. F., Bjeirmi; The Role of Project Management in Achieving Project Success, International Journal of Project Management, Vol. 14, No. 2, pp.81‑87, 1997.
[3] S. R., Toor; S. O., Ogunlana; Construction Professionals’ Perception of Critical Successfactors for Large-scale Construction Projects, Construction Innovation, Vol. 9,No. 2, pp. 149‑167, 2009.
[4] G., Dong; D., Yamaguchi; M., Nagai; A Grey-Based Decisionmaking Approach to the Supplier Selection Problem, Mathematical and Computer Modeling,Vol. 46, pp. 573‑581, 2006.
[5] N. D., Long; S., Ogunlana; T., Quang; K. C., Lam; Large Construction Projects in Developing Countries: A Case Study from Vietnam, International Journal of Project Management, Vol. 22, pp. 553‑561, 2004.
[6] R. F., Aziz; Ranking of Delay Factors in Construction Projects after Egyptian Revolution, Alexandria Engineering Journal, Vol. 52, pp. 387‑406, 2013.
[7] F., Olabosipo; O., Ayodeji; O., James; Factors Affecting the Performance of LA, Mediterranean Journal of Social Sciences, Vol. 2, No. 2, pp. 251‑257, 2011.
[8] H., Doloi; A., Sawhney; K. C., Iyer; S., Rentala; Analysing Factors Affecting Delays in Indian Construction Projects, International Journal of Project Management, Vol. 30,pp. 479‑489, 2012.
[9] K. C., Iyer; K. N., Jha; Factors Affecting Cost Performance: Evidence from Indian Construction Projects, International Journal of Project Management, Vol. 23, pp. 283‑295, 2005.
[10] M. A., Guerrero; Y., Villacampa; A., Montoyo; Modeling Construction Time in Spanish Building Projects, International Journal of Project Management, Vol. 32, pp. 861‑873, 2013.
[11] A. P. C., Chan; D. W. M., Chan; Developing a Benchmark Model for Project Construction Time Performance in Hong Kong, Building and Environment, Vol. 39, pp. 339‑349, 2004.
[12] D. K. H., Chua; P. K., Loh; Y. C., Kog; E. J., Jaselskis; Neural Network for Construction Project Success, Expert Systems with Applications, Vol. 13, No. 4, pp. 317‑328,1997.
[13] W., Pewdum; T., Rujirayanyong; V., Sooksatra; Forecasting Final Budget and Duration of Highway Construction Projects, Engineering, Construction and Architectural Management, Vol. 16, No. 6, pp. 544‑557, 2009.
[14] H., Odeyinka; J., Lowe; A., Kaka; Regression Modelling of Risk Impacts on Construction Cost Flow Forecast, Journal of Financial Management of Property and Construction, Vol. 17, pp. 203‑221, 2012.
[15] S., Liu; Y., Lin; Grey Information Theory and Practical Applications, Springer, London, 2006.
[16] L. V., Utkin; Multi-Criteria Decision Making with a Special Type of Information about Importance of Groups of Criteria, 6th International Symposium on Imprecise Probability: Theories and Applications, 2009.
[17] M., Masoud; M., Moezi; S. N., Bashiri; Degree of Underdevelopment of the Province of Esfehan with Numerical Taxonomy, Urban and Regional Studies,Vol. 2, No. 8, pp. 39‑54, 2011.
[18] D., Golmohamadi; M., Melat-parast; Developinga Grey-based Decision-making Model for SupplierSelection, Int. J. Production Economics, Vol. 137, pp.191‑200, 2012.
[19] B. T. H. T., Baharudin; M. R., Ibrahim; N., Ismail; Z., Leman; M. K. A., Ariffin; D. L., Majid; Experimental Investigation of HSS Face Milling to AL6061 Using Taguchi Method, Procedia Engineering, Vol. 50, pp.933‑941, 2012.
[20] J., Antony; Design of Experiments for Engineers and Scientists, Elsevier Science and Technology Books, 2003.
[21] S., Kamaruddin; A. K., Zahid; S. H., Foong; Application of Taguchi Method in the Optimization of Injection Moulding Parameters for Manufacturing Products from Plastic Blend, IACSIT International Journal of Engineering and Technology, Vol. 2, No. 6, pp. 574‑580,2010.
[22] I., Jaman; M. W., Alzahrani; The Impact of Contractors’ Attributes on Construction Project Success: A Post Construction Evaluation, International Journal of Project Management, Vol. 31, pp. 313‑322, 2013.
[23] H., Golpira, V., Moradi; New Method for Calculating the Projects Progress Based on Multi-criteria Decision Making, Journal of Industrial Management, Vol. 5, No.14, pp. 31-42, 2010 (in Persian).
[24] P., Nejadsabzi; Investigation and Identification of Effective Factors on Delay execution in Marouk Dam Project, Design Research Plan, Lorestan Regional Water Company, 2010 (in Persian).
[25] E., Shakeri, A., Ghorbani; Project Management and Understanding the Major Causes of Claims Contractors for construction Projects, The 2nd International Project Management Conference, 2010 (in Persian).
[26] M., Ravanshadia, B., Esmaili, M. T., Banki; Prediction Cash Flow of Construction Projects, National Conference on the Development of the Executive System of Urban Construction Projects, 2007 (in Persian).
[27] R., Abbassnia, E. E., Eshteharian, F., Zamani; Prediction Preparing and Maintaining the Cost of Materials for Construction Projects using Neural Networks to Reduce Costs, International Conference on Strategic Project Management, 2010 (in Persian).
[28] E., Zeynali; Design Experiment with Tughuchi Method using Qualitek Software, Research & Technology Company: Tehran, 2008 (in Persian).
Amirkabir Journal of Civil Engineering
Volume 49, Issue 1
June 2017
Pages 185-196

Files

Share

How to cite

Statistics