Competition rule of the multi-criteria approach: what contractors in China really want?
Abstract
Recent years have witnessed the diversifying means of competitive bidding, where the client plays a critical role in the determination of competition rule. It is widely recognized that the competition rule should be placed on a win-win basis to ensure that both the client and contractors are well considered with respect to their interests. Nevertheless, a vast majority of biddings fail to take account of what contractors really want. Using the methods of literature review and content analysis, 34 tender evaluation factors are proposed to compose the competition rule in China. Contractors’ opinions on these factors are collected by virtue of questionnaire survey. Based on the Pareto law, it is found that the competition rule encompasses eleven key factors, and the composition varies slightly between public and private sectors. The Hotelling’s T test is conducted on those key factors in common. The implication is that contractors can use indifferent factors (e.g., credit rating, construction plan, completeness of bid components, timely payment to workers) to improve competitiveness, while the client may utilize different factors to diversify the competition rule. This paper probably presents an earliest effort put to examine the acceptability of competition rule in the construction context.
Keyword : competition rule, competitive tendering, perception, project type, China
How to Cite
Ye, K., Zeng, D., & Wong, J. (2018). Competition rule of the multi-criteria approach: what contractors in China really want?. Journal of Civil Engineering and Management, 24(2), 155-166. https://doi.org/10.3846/jcem.2018.459
This work is licensed under a Creative Commons Attribution 4.0 International License.
References
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Kog, F.; Yaman, H. 2014. A meta classification and analysis of contractor selection and prequalification, Procedia Engineering 84: 302–310. https://doi.org/10.1016/j.proeng.2014.10.555
Labuschagne, C.; Brent, A. C. 2005. Sustainable project life cycle management: The need to integrate life cycles in the manufacturing sector, International Journal of Project Management 23(2): 159–168. https://doi.org/10.1016/j.ijproman.2004.06.003
Lambropoulos, S. 2013. Objective construction contract award using cost, time and durability utility, Procedia – Social and Behavioral Sciences 74: 123–133. https://doi.org/10.1016/j.sbspro.2013.03.052
Littlechild, S. 2017. Regulation and the nature of competition, Journal of Air Transport Management 67: 211–223.
Liu, B. S.; Huo, T. F.; Liao, P. C.; Yuan, J. F.; Sun, J.; Hu, X. 2016. A Special Partial Least Squares (PLS) path decision modeling for bid evaluation of large construction projects, KSCE Journal of Civil Engineering, 1–14.
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Liu, B. S.; Yang, X. D.; Huo, T. F.; Shen, Q. P.; Wang, X. Q. 2017. A linguistic group decision-making framework for bid evaluation inmega public projects considering carbon dioxide emissions reduction, Journal of Cleaner Production 148: 811–825. https://doi.org/10.1016/j.jclepro.2017.02.044
Lu, W. S.; Shen, L. Y.; Yam, M. C. H. 2008. Critical success factors for competitiveness of contractors: China study, Journal of Construction Engineering and Management 134(12): 972–982. https://doi.org/10.1061/(ASCE)0733-9364(2008)134:12(972)
Mesa, H. A.; Molenaar, K. R.; Alarcón, L. F. 2016. Exploring performance of the integrated project delivery process on complex building projects, International Journal of Project Management 34(7): 1089–1101. https://doi.org/10.1016/j.ijproman.2016.05.007
Newcombe, R. 1990. Construction management 1: Organisation systems. London: Mitchell Publishing Co.
Ng, S. T.; Skitmore, R. M. 1999. Client and consultant perspectives of prequalification criteria, Building and Environment 34(5): 607–621. https://doi.org/10.1016/S0360-1323(98)00050-X
Nieto-Morote, A.; Ruz-Vila, F. 2012. A fuzzy multi-criteria decision-making model for construction contractor prequalification, Automation in Construction 25(18): 8–19. https://doi.org/10.1016/j.autcon.2012.04.004
Oo, B. L.; Drew, D. S.; Lo, H. P. 2008. A comparison of contractors’ decision to bid behaviour according to different market environments, International Journal of Project Management 26(4): 439–447. https://doi.org/10.1016/j.ijproman.2007.06.001
Shash, A. A. 1993. Factors considered in tendering decisions by top UK contractors, Construction Management and Economics 11(2): 111–118. https://doi.org/10.1080/01446199300000004
Smith, A. 1776. The wealth of nations. London: Stratton and Cadell.
Tang, S. L.; Lu, M.; Chan, Y. L. 2003. Achieving client satisfaction for engineering consulting firms, Journal of Management in Engineering 19(4): 166–172. https://doi.org/10.1061/(ASCE)0742-597X(2003)19:4(166)
Torres, R.; Heyman, R.; Munoz, S.; Apgar, L.; Timm, E.; Tzintzun, C.; Hale, C. R.; Gonzalez, J. M.; Speed, S.; Tang, E. 2013. Building Austin, building justice: Immigrant construction workers, precarious labor regimes and social citizenship, Geoforum 45: 145–155. https://doi.org/10.1016/j.geoforum.2012.10.012
Watt, D. J.; Kayis, B.; Willey, K. 2009. Identifying key factors in the evaluation of tenders for projects and services, International Journal of Project Management 27(3): 250–260. https://doi.org/10.1016/j.ijproman.2008.03.002
Watt, D. J.; Kayis, B.; Willey, K. 2010. The relative importance of tender evaluation and contractor selection criteria, International Journal of Project Management 28(1): 51–60. https://doi.org/10.1016/j.ijproman.2009.04.003
Wong, C. H.; Holt, G. D.; Cooper, P. A. 2000. Lowest price or value? Investigation of UK construction clients’ tender selection process, Construction Management and Economics 18: 767–774. https://doi.org/10.1080/014461900433050
Wong, C. H.; Holt, G. D.; Harris, P. 2001. Multi-criteria selection or lowest price? Investigation of UK construction clients’ tender evaluation preferences, Engineering, Construction and Architectural Management 8(4): 105–115.
Wright, R. 2000. Nonzero: the logic of human destiny, Quarterly Review of Biology 5(3).
Wu, I. C.; Borrmann, A.; Beißert, U.; König, M.; Rank, E. 2010. Bridge construction schedule generation with pattern-based construction methods and constraint-based simulation, Advanced Engineering Informatics 24(4): 379–388. https://doi.org/10.1016/j.aei.2010.07.002
Yan, H. Y. 2011. The construction project bid evaluation based on gray relational model, Procedia Engineering 15: 4553–4557. https://doi.org/10.1016/j.proeng.2011.08.855
Yang, J. B.; Wang, H. H.; Wang, W. C.; Ma, S. M. 2016. Using data envelopment analysis to support best-value contractor selection, Journal of Civil Engineering & Management 22(2): 199–209. https://doi.org/10.3846/13923730.2014.897984
Ye, K. H.; Shen, L. Y.; Xia, B.; Li, B. H. 2014. Key attributes underpinning different markup decision between public and private projects: A China study, International Journal of Project Management 32(3): 461–472. https://doi.org/10.1016/j.ijproman.2013.06.001
Ye, K. H.; Zhu, W. N.; Shan, Y. W.; Li, S. 2015. Effects of market competition on the sustainability performance of the construction industry: China case, Journal of Construction Engineering and Management 141(9), 04015025(1-10).
Zhang, Y.; Luo, H.; He, Y. 2015. A system for tender price evaluation of construction project based on big data, Procedia Engineering 123: 606–614. https://doi.org/10.1016/j.proeng.2015.10.114
Ballesteros-Pérez, P.; Skitmore, M.; Pellicer, E.; Zhang, X. 2016. Scoring rules and competitive behavior in best-value construction auctions, Journal of Construction Engineering and Management 142(9). https://doi.org/10.1061/(ASCE)CO.1943-7862.0001144
Bayraktar, M. E.; Cui, Q.; Hastak, M.; Minkarah, I. 2004. State-of-practice of warranty contracting in the United States, Journal of Infrastructure Systems 10(2): 60–68. https://doi.org/10.1061/(ASCE)1076-0342(2004)10:2(60)
Bereskin, F. L.; Kim, B.; Oh, F. D. 2015. Do credit rating concerns lead to better corporate governance? Evidence from Korea, Pacific-Basin Finance Journal 35, Part B, 592–608.
Biruk, S.; Jaśkowski, P.; Czarnigowska, A. 2017. Modeling contractor’s bidding decisions, Procedia Engineering 182: 91–98. https://doi.org/10.1016/j.proeng.2017.03.125
Bottani, E.; Rizzi, A. 2008. An adapted multi-criteria approach to suppliers and products selection – An application oriented to lead-time reduction, International Journal of Production Economics 111: 763–781. https://doi.org/10.1016/j.ijpe.2007.03.012
Chen, Y. S.; Chong, P. P.; Tong, Y. G. 1994. Mathematical and computer modelling of the Pareto principle, Mathematical and Computer Modelling 19(9): 61–80. https://doi.org/10.1016/0895-7177(94)90041-8
Cheng, M. Y.; Hsiang, C. C.; Tsai, H. C.; Do, H. L. 2011. Bidding decision making for construction company using a multi-criteria prospect model, Journal of Civil Engineering and Management 17(3): 424–436. https://doi.org/10.3846/13923730.2011.598337
Chotibhongs, R.; Arditi, D. 2012. Analysis of collusive bidding behavior, Construction Management and Economics 30(3): 221–231. https://doi.org/10.1080/01446193.2012.661443
Christodoulou, S. 2010. Bid mark-up selection using artificial neural networks and an entropy metric, Engineering, Construction and Architectural Management 17(4): 424–439. https://doi.org/10.1108/09699981011056600
Drew, D. S.; Skitmore, R. M. 1992. Competitiveness in bidding: a consultant's perspective, Construction Management and Economics 10: 227–247. https://doi.org/10.1080/01446199200000020
Drew, D.; Skitmore, M. 1997. The effect of contract type and size on competitiveness in bidding, Construction Management & Economics 15(5): 469–489. https://doi.org/10.1080/014461997372836
Egemen, M.; Mohamed, A. N. 2005. Clients’ needs, wants and expectations from contractors and approach to the concept of repetitive works in the Northern Cyprus construction market, Building and Environment 41(5): 602–614. https://doi.org/10.1016/j.buildenv.2005.02.021
Fu, W. K.; Drew, D. S.; Lo, H. P. 2003. Competitiveness of inexperienced and experienced contractors in bidding, Journal of Construction Engineering and Management 129(4): 388–395. https://doi.org/10.1061/(ASCE)0733-9364(2003)129:4(388)
Hatush, Z.; Skitmore, M. 1997. Evaluating contractor prequalification data: selection criteria and project success factors, Construction Management and Economics 15(2): 129–147. https://doi.org/10.1080/01446199700000002
Hatush, Z.; Skitmore, M. 1998. Contractor selection using multicriteria utility theory: An additive model, Building and Environment 33(2–3): 105–115. https://doi.org/10.1016/S0360-1323(97)00016-4
Ho, W.; Xu, X.; Dey, P. K. 2010. Multi-criteria decision making approaches for supplier evaluation and selection: A literature review, European Journal of Operational Research 202(1): 16–24. https://doi.org/10.1016/j.ejor.2009.05.009
Holt, G. D.; Olomolaiye, P. O.; Harris, F. C. 1995. A review of contractor selection practice in the U.K. construction industry, Building and Environment 30(4): 553–561. https://doi.org/10.1016/0360-1323(95)00008-T
Hwang, B. G.; Liao, P. C.; Leonard, M. P. 2011. Performance and practice use comparisons: Public vs. Private owner projects, KSCE Journal of Civil Engineering 15(6): 957–963. https://doi.org/10.1007/s12205-011-1115-y
Kassarjian, H. H. 1977. Content analysis in consumer research, Journal of Consumer Research 4: 8–18. https://doi.org/10.1086/208674
Kim, H.-J.; Reinschmidt, K. F. 2011. Effects of contractors’ risk attitude on competition in construction, Journal of Construction Engineering and Management 137(4): 275–283. https://doi.org/10.1061/(ASCE)CO.1943-7862.0000284
Kog, F.; Yaman, H. 2014. A meta classification and analysis of contractor selection and prequalification, Procedia Engineering 84: 302–310. https://doi.org/10.1016/j.proeng.2014.10.555
Labuschagne, C.; Brent, A. C. 2005. Sustainable project life cycle management: The need to integrate life cycles in the manufacturing sector, International Journal of Project Management 23(2): 159–168. https://doi.org/10.1016/j.ijproman.2004.06.003
Lambropoulos, S. 2013. Objective construction contract award using cost, time and durability utility, Procedia – Social and Behavioral Sciences 74: 123–133. https://doi.org/10.1016/j.sbspro.2013.03.052
Littlechild, S. 2017. Regulation and the nature of competition, Journal of Air Transport Management 67: 211–223.
Liu, B. S.; Huo, T. F.; Liao, P. C.; Yuan, J. F.; Sun, J.; Hu, X. 2016. A Special Partial Least Squares (PLS) path decision modeling for bid evaluation of large construction projects, KSCE Journal of Civil Engineering, 1–14.
Liu, B. S.; Huo, T. F.; Wang, X. Q.; Shen, Q. P.; Chen, Y. 2013.The decision model of the intuitionistic fuzzy group bid evaluation for urban infrastructure projects considering social costs, Canadian Journal of Civil Engineering 40(3): 263–273. https://doi.org/10.1139/cjce-2012-0283
Liu, B. S.; Yang, X. D.; Huo, T. F.; Shen, Q. P.; Wang, X. Q. 2017. A linguistic group decision-making framework for bid evaluation inmega public projects considering carbon dioxide emissions reduction, Journal of Cleaner Production 148: 811–825. https://doi.org/10.1016/j.jclepro.2017.02.044
Lu, W. S.; Shen, L. Y.; Yam, M. C. H. 2008. Critical success factors for competitiveness of contractors: China study, Journal of Construction Engineering and Management 134(12): 972–982. https://doi.org/10.1061/(ASCE)0733-9364(2008)134:12(972)
Mesa, H. A.; Molenaar, K. R.; Alarcón, L. F. 2016. Exploring performance of the integrated project delivery process on complex building projects, International Journal of Project Management 34(7): 1089–1101. https://doi.org/10.1016/j.ijproman.2016.05.007
Newcombe, R. 1990. Construction management 1: Organisation systems. London: Mitchell Publishing Co.
Ng, S. T.; Skitmore, R. M. 1999. Client and consultant perspectives of prequalification criteria, Building and Environment 34(5): 607–621. https://doi.org/10.1016/S0360-1323(98)00050-X
Nieto-Morote, A.; Ruz-Vila, F. 2012. A fuzzy multi-criteria decision-making model for construction contractor prequalification, Automation in Construction 25(18): 8–19. https://doi.org/10.1016/j.autcon.2012.04.004
Oo, B. L.; Drew, D. S.; Lo, H. P. 2008. A comparison of contractors’ decision to bid behaviour according to different market environments, International Journal of Project Management 26(4): 439–447. https://doi.org/10.1016/j.ijproman.2007.06.001
Shash, A. A. 1993. Factors considered in tendering decisions by top UK contractors, Construction Management and Economics 11(2): 111–118. https://doi.org/10.1080/01446199300000004
Smith, A. 1776. The wealth of nations. London: Stratton and Cadell.
Tang, S. L.; Lu, M.; Chan, Y. L. 2003. Achieving client satisfaction for engineering consulting firms, Journal of Management in Engineering 19(4): 166–172. https://doi.org/10.1061/(ASCE)0742-597X(2003)19:4(166)
Torres, R.; Heyman, R.; Munoz, S.; Apgar, L.; Timm, E.; Tzintzun, C.; Hale, C. R.; Gonzalez, J. M.; Speed, S.; Tang, E. 2013. Building Austin, building justice: Immigrant construction workers, precarious labor regimes and social citizenship, Geoforum 45: 145–155. https://doi.org/10.1016/j.geoforum.2012.10.012
Watt, D. J.; Kayis, B.; Willey, K. 2009. Identifying key factors in the evaluation of tenders for projects and services, International Journal of Project Management 27(3): 250–260. https://doi.org/10.1016/j.ijproman.2008.03.002
Watt, D. J.; Kayis, B.; Willey, K. 2010. The relative importance of tender evaluation and contractor selection criteria, International Journal of Project Management 28(1): 51–60. https://doi.org/10.1016/j.ijproman.2009.04.003
Wong, C. H.; Holt, G. D.; Cooper, P. A. 2000. Lowest price or value? Investigation of UK construction clients’ tender selection process, Construction Management and Economics 18: 767–774. https://doi.org/10.1080/014461900433050
Wong, C. H.; Holt, G. D.; Harris, P. 2001. Multi-criteria selection or lowest price? Investigation of UK construction clients’ tender evaluation preferences, Engineering, Construction and Architectural Management 8(4): 105–115.
Wright, R. 2000. Nonzero: the logic of human destiny, Quarterly Review of Biology 5(3).
Wu, I. C.; Borrmann, A.; Beißert, U.; König, M.; Rank, E. 2010. Bridge construction schedule generation with pattern-based construction methods and constraint-based simulation, Advanced Engineering Informatics 24(4): 379–388. https://doi.org/10.1016/j.aei.2010.07.002
Yan, H. Y. 2011. The construction project bid evaluation based on gray relational model, Procedia Engineering 15: 4553–4557. https://doi.org/10.1016/j.proeng.2011.08.855
Yang, J. B.; Wang, H. H.; Wang, W. C.; Ma, S. M. 2016. Using data envelopment analysis to support best-value contractor selection, Journal of Civil Engineering & Management 22(2): 199–209. https://doi.org/10.3846/13923730.2014.897984
Ye, K. H.; Shen, L. Y.; Xia, B.; Li, B. H. 2014. Key attributes underpinning different markup decision between public and private projects: A China study, International Journal of Project Management 32(3): 461–472. https://doi.org/10.1016/j.ijproman.2013.06.001
Ye, K. H.; Zhu, W. N.; Shan, Y. W.; Li, S. 2015. Effects of market competition on the sustainability performance of the construction industry: China case, Journal of Construction Engineering and Management 141(9), 04015025(1-10).
Zhang, Y.; Luo, H.; He, Y. 2015. A system for tender price evaluation of construction project based on big data, Procedia Engineering 123: 606–614. https://doi.org/10.1016/j.proeng.2015.10.114