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Level of Importance of Performance-based Tender Evaluation Indicators

Affiliations

  • Department of Quantity Surveying, Faculty of Built Environment, University Technology Malaysia, 81310 Johor, Malaysia
  • School of Management, University of Tasmania, Locked Bag 1316, Launceston, 7250 Australia, Malaysia

Abstract


Objectives: The objective of this paper is to identify level of importance of performance-based tender evaluation indicators required to stimulate the effectiveness of current tendering practice in Malaysian Public Sector. Methods/Statistical Analysis: This paper presents a case study conducted at Public Works Department (PWD) of Malaysia. The Quantity Surveyors are examined with a concern of the implementation of performance-based tender evaluation indicators. The research also questioned the level of importance of 11 past performance indicators and 11 potential performance indicators. The quantitative research method was adopted by developing a questionnaire survey and data collection in PWD. Findings: Evaluating contractor based on performance has positively help to select the right contractor. This study aims at finding out drawbacks on current tender evaluation practice, developing the performancebased indicators, identify level of importance of each indicators and seeking opinions of PWD. Relatively, the setbacks have been observed in their criteria of tender evaluation with the lack of past performance and potential performance being measured. Ironically, the findings indicate that the quality of workmanship on past project and customers’ satisfaction are the most important indicators but none of the indicators are considered in the current tender evaluation practiced by PWD. The result of this study provides an important contribution as a guide that helps the public sector to select a competent contractor based on performance indicators. Measuring performance based contractor selection is rather new and implementation is still limited. Application/Improvements: Comprehensive contributing factors of performance indicators developed in this research may help the client to improve their contractor selection by using the performance indicators identified.

Keywords

Contractor Evaluation, Level of Importance, Performance-based, Performance Indicators, Tender Evaluation

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References


  • Hatush Z, Skitmore M. Evaluating contractor prequalification data: Selection criteria and project success factors. Construction Management and Economics. 1997; 15(2):129–47.
  • Stein A, Hawking P, Wyld DC. The 20% solution? A case study on the efficiency of reverse auctions. Management Resources News. 2003; 26(5):1–20.
  • Koushki PA, Al-Rashid K, Kartam N. Delays and cost increases in the construction of private residential projects in Kuwait. Construction Management and Economics. 2005 Mar; 23(3):285–94.
  • Abedi M. Effects of construction delays on construction project objectives. The First Iranian Students Scientific Conference in Malaysia; 2011.
  • El-Abassy MS, Zayed T, Ahmed M, Alzraiee H, Abouhamad M. Contractor selection models for highway projects using integrated simulation and analytic network process. Journal of Construction Engineering and Management. 2013 Jul; 139(7):755–67.
  • Holt GD, Olomolaiye PO, Harris FC. A review of contractor selection practice in the U.K. construction industry. Building and Environment. 1995 Oct; 30(4):553–61.
  • Shehu Z, Endut IR. Factors contributing to project time and hence cost overrun in the Malaysian construction industry. Journal of Financial Management of Property and Construction. 2014; 19(1):55–75.
  • JKR Malaysia. 2016. Available from: https://en.wikipedia.org/wiki/JKR
  • Takim R, Akintoye A. Performance indicators for successful construction project performance. 18th Annual ARCOM Conference; University of Northumbria. 2002 Sep 2.p. 545–55.
  • Alzahrani JI, Emsley MW. The impact of contractors’ indicators on construction project success: A post construction evaluation. International Journal of Project Management.2013; 31(2):313–22.
  • Cheng EWL, Li H. Contractor selection using the analytic network process. Construction Management and Economics. 2004 Jan; 22(10):1021–32.
  • Xiao H, Proverbs D. Factors influencing contractor performance: An international investigation. Engineering, Construction and Architectural Management. 2003 Oct; 10(5):322–32.
  • Singh D, Tiong RLK. Contractor selection criteria : Investigation of opinions of Singapore Construction Practitioners. Journal of Construction Engineering and Management. 2006 Sep; 132(1):998–1008.
  • Ramanathan C, Potty NS. Arazi B. Analysis of time and cost overrun in Malaysian construction. Advanced Materials Research. 2012 Jan; 452-453:1002–8.
  • Othman R, Zakaria H, Nordin N, Shahidan Z, Jusoff K. The Malaysian public procurement’s prevalent system and its weaknesses. American Journal of Economics and Business Administration. 2010 Jan; 2(1):6–11.
  • Muhamad Halil F. Contractors’ perceptions on the use of statistical approach in the tender evaluation at the Public Work Department, Malaysia. American Journal of Applied Sciences. 2007 Dec; 4(12):1084–9.
  • Jaafar M, Abdul Aziz AR, Ismail A. Non Price Factors (NPF) and contractors’ selection: An application in the Public Sector Malaysia. Proceeding of 5th IEEE International Conference of Cognitive Informatics; 2006. p. 1–5.
  • Doloi H, Iyer KC, Sawhney A. Structural equation model for assessing impacts of contractor’s performance on project success. International Journal of Project Management. 2011 Aug; 29(6):687–95.
  • Mills JA. The impact of client attitudes on the selection of contractors. Malaysian Construction Research Journal. 2011; 8(1):88–102.
  • Yilmaz A, Ergonul S. Selection of contractors for middlesized projects in Turkey. Gazi University Journal of Science. 2011 Feb; 24(3):477–85.
  • Yasamis F, Arditi D, Mohammadi J. Assessing contractor quality performance. Construction Management and Economics. 2002; 20(3):211–23.
  • Elyamany A, Abdelrahman M. Contractor performance evaluation for the best value of Superpave Projects. Journal of Construction Engineering and Management. 2010 May; 136(5):606–14.
  • Salama M, Aziz HA, El Sawah H, El Samadony A. Investigating the criteria for contractors’ selection and bid evaluation in Egypt. Proceedings 22nd Annual ARCOM Conference; 2006 Sep. p. 531–40.
  • Choudhry RM, Hinze JW, Arshad M, Gabriel HF. Subcontracting practices in the construction industry of Pakistan. Journal of Construction Engineering and Management. 2012 Dec; 138(12):1353–9.
  • Ko C. Predicting subcontractor performance using webbased evolutionary fuzzy neural networks. The Scientific World Journal. 2013 Jun; 2013:1–9.
  • Toor SR, Ogunlana SO. Beyond the iron triangle: Stakeholder perception of key performance indicators (KPIs) for large-scale Public Sector Development projects. International Journal of Project Management. 2010 Apr; 28(3):228–36.
  • Abu Nemeh MH. Multi-criteria decision making model for the selection of a construction contractor in Saudi Arabia. [Master Thesis]. King Fadh University of Petroleum and Minerals; 2012. p. 1–186.
  • Horta IM, Camanho AS, Lima AF. Design of performance assessment system for selection of contractors in construction industry e-market places. Journal of Construction Engineering and Management. 2013 Feb; 139(8):910–7.
  • Xu J, Liu Y, Luo L. A trust-based method in construction industry. Applied Mechanics and Materials. 2014 Jul; 539:762–8.30. Nanda Kumaar A, Deventhiran K, Santhana Kumar M, Manoj Kumar M, Suresh R. A study on targeted relationships between contractors and consultants in construction industry. Indian Journal of Science and Technology. 2016 Apr; 9(16):1–7.
  • Costa AA, Tavares LV. Advanced multi-criteria models to promote quality and reputation in public construction e-market places. Automation in Construction. 2013 Mar; 30:205–15.
  • El-Mashaleh M, Minchin R, O’Brien W. Management of construction firm performance using benchmarking. Journals of Management Engineering. 2007 Jan; 23(1):10–7.
  • Yang J, Peng S. Development of a customer satisfaction evaluation model for construction project management. Building and Environment. 2008 Apr; 43(4):458–68.
  • Tao L, Kumaraswamy M. Unveiling relationships between contractor inputs and performance outputs. Construction Innovation: Information, Process, Management. 2012 Jun; 12(1):86–98.
  • Bradshaw J, Chang S. Past performance as an indicator of future performance: Selecting an industry partner to maximize the probability of program success The 9th Annual Acquisition Research Symposium; 2012 Sep. p. 1–24.
  • Florez L, Castro D, Medaglia AL. Maximizing labor stability as a sustainability performance indicator in project scheduling. Construction Research Congress; 2012. p. 465–74.
  • Wong CH. Contractor performance prediction model for the United Kingdom construction contractor: Study of logistic regression approach. Journal of Construction Engineering and Management. 2004 Oct; 130(5):691–8.
  • Khoshgoftar M, Bakar AHA, Osman O. Causes of delays in Iranian Construction Projects. International Journal of Construction Management. 2010; 10(2):53–69.
  • Yasamis-Speroni F, Lee DE, Arditi D. Evaluating the quality performance of pavement contractors. Journal of Construction Engineering and Management. 2012 Oct; 138(10):1114–24.
  • Jafari A. A contractor pre-qualification model based on the quality function deployment method. Construction Management and Economics. 2013 Sep; 31(7):746–60.
  • Fellows R, Liu A. Research methods for construction. 3rd ed. Chichester: Wiley-Blackwell; 2008 Aug.
  • Holt GD, Olomolaiye PO, Harris FC. Factors influencing UK construction clients’ choice of contractor. Building and Environment. 1994 May; 29(2):241–8.
  • Esetova AM, Pavliuchenko EI, Ismailova CT, Levitsky TY. System restructuring as a factor of increasing management efficiency in construction. Indian Journal of Science and Technology. 2015 Dec; 8(S10):1–9.
  • Dineshkumar B, Dhivyamenaga T. Study on lean principles application in construction industry. Indian Journal of Science and Technology. 2016 Jan; 9(2):1–5.

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