Korean Journal of Construction Engineering and Management (한국건설관리학회논문집)

Korea Institute of Construction Engineering and Management (한국건설관리학회)
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Investigation of Key Factors to measure on-site Performance of a Construction firm

  • Published : 2007.12.31
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Abstract

The performance of projects has always been an area of interest in the construction industry. Roles of all construction supply chain partners are necessary; however the role of a contractor firm in the construction project is pivotal. So, this research intended to explore a Construction Firm's performance criteria which could measure the level of performance of that firm in an ongoing project. Data was collected from construction professionals working in three principal project participant organizations, namely Owner, Consultant and Contractor. A total of 113 nos. of performance measuring items were sorted from literature review and used to collect data. Statistical tools processed by SPSS program was employed to analyze the data. Out of total 113 items, only 65 nos. of variables were found to be acceptable to every population group of this study. Factor analysis revealed 12 key performance predicting factors (KPPF) with 53 predictive indicators. 12 KPPFS with index weight are: work progress and smoothening (9.3%), change order management and work accuracy (9.1%), business relationship building (8.1%), adequacy of construction work procedure (8.6%), quality performance (8.0%), health and site safety adequacy (8.8%), Innovative contractor (8.0%), adequacy of construction site information (6.8%), compliance with contract plan/specification requirements (8.9%), creditworthiness and financial capability (8.3%), intra-agency relationship and responsiveness (7.0%) and resource management (9.2%). These results could be useful to project management body to evaluate performance of its contractor firm on site as well as the contractor itself to assess own performance and its subcontractors on-site.

Keywords

References

  1. Acharya, N.K., Lee, Y.D., and Choi, D.S. (2006), 'Key attitude indicators (KAI) for measuring attitude of contractors in construction projects,' KSCE J. Civil Eng., 10 (3), 151-163 https://doi.org/10.1007/BF02824056
  2. Bassioni, H.A., Price, A.D.F. and Hassan, T.M. (2004), 'Performance management in construction,' J. Manage. Eng. (ASCE), 20 (2), 42-50 https://doi.org/10.1061/(ASCE)0742-597X(2004)20:2(42)
  3. Chan, A.P.C., Scott, D., and Chan, A.P.L. (2004), 'Factors affecting the success of a construction project,' J. Constr. Eng. Manage. (ASCE), 130 (1), 153-165 https://doi.org/10.1061/(ASCE)0733-9364(2004)130:1(153)
  4. Chua, D.K.H., Kog, Y.C., and Loh, P.K. (1999), 'Critical success factors for different project objectives,' J. Constr. Eng. Manage. (ASCE), 125 (3), 142-150 https://doi.org/10.1061/(ASCE)0733-9364(1999)125:3(142)
  5. Coetzee, M. (2005), 'The fairness of affirmative action: an organizational justice perspective,' PhD. Thesis, University of Pretoria, South Africa,
  6. Dikmen, I., Birgonul, M.T., and Kiziltas, S. (2005), 'Prediction of organizational effectiveness in construction companies,' J. Constr. Eng. Manage. (ASCE), 131 (2), 252-261 https://doi.org/10.1061/(ASCE)0733-9364(2005)131:2(252)
  7. El-Mashaleh, M.S., Minchin, R.E., and O'Brien, W.J. (2007), ' Management of construction firm performance using benchmarking,' J. Constr. Eng. Manage. (ASCE), 23 (1), 10-17
  8. Field, A.P. (2005), Discovering statistics using SPSS, Accessed from http://www.sussex.ac.uk/Users/andyf/factor.pdf (Factor analysis using SPSS)
  9. Hatush, Z. and Skitmore, M. (1998), 'Contractor selection using multi-criteria utility theory: an additive model,' Build.Enviro. (Elsevier), 33 (2), 105-115 https://doi.org/10.1016/S0360-1323(97)00016-4
  10. Jung, D.R., and Kim, J.J. (2004), 'A study on competitive factor of domestic construction firm,' Proc. of The 5th KICEM Ann. Conf., 584-587
  11. Kagioglou, M., Cooper, R., and Aouad, G. (2001), 'Performance management in construction: a conceptual framework,' Const. Manage. Econ. (T &F), 19, 85-95 https://doi.org/10.1080/01446190010003425
  12. Kashiwagi, D., and Parmar, D. (2004), 'Past Performance Information in the Construction Industry' ASC Proceedings of the 40th Annual Conference, April 8 - 10, Utah (USA), 2004
  13. Keytone, J. (2001), Communication research: asking questions, finding answers, (2nd Ed.), McGraw-Hill
  14. Kim, D.Y., and Lee, J.S. (2004), 'Research on performance measurement of construction projects using balanced scoreboard (BSC),' Proc. of The 5th KICEM Ann. Conf., 494-499
  15. Lim, E.H. and Ling, F.Y.Y. (2002), 'Model for predicting clients'contribution to project success,' Eng. Constr. Archi. Manage. (Blackwell), 9 (5/6), 388-395 https://doi.org/10.1046/j.1365-232X.2002.00268.x
  16. Lin, G., and Shen, Q. (2007), 'Measuring the performance of value management studies in construction: Critical review,' J. Manage. Eng. (ASCE), 23 (1), 2-9 https://doi.org/10.1061/(ASCE)0742-597X(2007)23:1(2)
  17. Love, P.E.D., and Holt, G.D. (2000), 'Construction business performance measurement: the SPM alternative,' Bus. Process Manage. J., (Emerald), 6 (5), 408-416 https://doi.org/10.1108/14637150010352417
  18. Ng, S.T., and Skitmore, M. (1999), 'Client and consultant perspectives of prequalification criteria,' Build. Envir. (Elsevier), 34, 607-621 https://doi.org/10.1016/S0360-1323(98)00050-X
  19. Phua, F.T.T. (2004), 'Modelling the determinants of multi-firm project success: a grounded exploration of differing participant perspectives,' Const. Manage. Econ. (T & F), 22, 451-459 https://doi.org/10.1080/0144619042000190243
  20. Pongpeng J., and J. Liston. (2003), 'Contractor ability criteria: a view from the Thai construction industry', Const. Manage. Econ. (T & F), 21, 267- 282 https://doi.org/10.1080/0144619032000049647
  21. Shehnar, A.J., Dvir, D., Levy, O. and Maltz, A.C. (2001), 'Project success: a multidimensional strategic concept', Long Range Planning (Elsevier), 34, 699-725 https://doi.org/10.1016/S0024-6301(01)00097-8
  22. Shen, L.Y., Lu, W.S., and Yam, M.C.H. (2006), 'Contractor key competitiveness indicators: A China study,' J. Constr. Eng. Manage. (ASCE), 132 (4), 416-424 https://doi.org/10.1061/(ASCE)0733-9364(2006)132:4(416)
  23. Singh, D., and Tiong, R.L.K. (2006), 'Contractor selection criteria: investigation of opinions of Singapore construction practitioners,' J. Constr. Eng. Manage. (ASCE), 132 (9), 998-1008 https://doi.org/10.1061/(ASCE)0733-9364(2006)132:9(998)
  24. Soetanto, R. and Proverbs, D.G. (2002), 'Modeling the satisfaction of contractors: the impact of client performance,' Eng. Constr. Arch. Manage. (Blackwell), 9 (5/6), 453-465 https://doi.org/10.1046/j.1365-232X.2002.00278.x
  25. Yu, I.H., Kim, K.R., Jung, Y.S. and Chin, S.Y. (2006),' Analysis of quantified characteristics of the performance indicators for construction companies,' KICEM J. Constr. Eng. Manage. 7 (4), 154-163
  26. Wong, C.H. (2004), 'Contractor performance prediction model for the United Kingdom construction: study of logistic regression approach', J. Constr. Eng. Manage. (ASCE), 130 (5), 691-698 https://doi.org/10.1061/(ASCE)0733-9364(2004)130:5(691)
  27. Unahabhokha, C., Platts, K., and Tan, K.H., (2007). 'Predictive performance measurement system: A fuzzy expert system approach,' Benchmarking: Int. J., (Emerald), 14 (1), 77-91 https://doi.org/10.1108/14635770710730946