References
- Al-Tmeemy, S.; Abdul-Rahman, H.; Harun, Z. 2011. Future criteria for success of building projects in Malaysia, International Journal of Project Management 29(3): 337–348. http://dx.doi.org/10.1016/j.ijproman.2010.03.003
- Bai, J.; Yang, X.; Tao, L. 2011. Research on construction project process performance measurement, in 2011 IEEE 18th International Conference on Industrial Engineering and Engineering Management, September 3–5 2011, Changchun, China, 1915–1918.
- Carr, V.; Tah, J. 2001. A fuzzy approach to construction project risk assessment and analysis: construction project risk management system, Advances in Engineering Software 32(10–11): 847–857. http://dx.doi.org/10.1016/S0965-9978(01)00036-9
- Cha, H.; Kim, C. 2011. Quantitative approach for project performance measurement on building construction in South Korea, KSCE Journal of Civil Engineering 15(8): 1319–1328. http://dx.doi.org/10.1007/s12205-011-1323-5
- Chan, A.; Scott, D.; Chan, A. 2004. Factors affecting the success of a construction project, Journal of Construction Engineering and Management 130(1): 153–155. http://dx.doi.org/10.1061/(ASCE)0733-9364(2004)130:1(153)
- Cheung, S. 2004. PPMS: a web-based construction project performance monitoring system, Automation in Construction 13(3): 361–376. http://dx.doi.org/10.1016/j.autcon.2003.12.001
- Chiu, Y.; Shyu, J.; Tzeng, G. 2004. Fuzzy MCDM for evaluating the e-commerce strategy, International Journal of Computer Applications in Technology 19(1): 12–22. http://dx.doi.org/10.1504/IJCAT.2004.003656
- Choquet, G. 1953. Theory of capacities, Annales de l'institut Fourier 5: 131–295.
- Clivillé, V.; Berrah, L.; Mauris, G. 2007. Quantitative expression and aggregation of performance measurements based on the MACBETH multi-criteria method, International Journal of Production Economics 105(1): 171–189. http://dx.doi.org/10.1016/j.ijpe.2006.03.002
- Dainty, A.; Cheng, M.; Moore, D. 2003. Redefining performance measures for construction project managers: an empirical evaluation, Construction Management and Economics 21(2): 209–218. http://dx.doi.org/10.1080/0144619032000049737
- Fayek, A.; Sun, Z. 2001. A Fuzzy Expert System for design performance prediction and evaluation, Canadian Journal of Civil Engineering 28(1): 1–25. http://dx.doi.org/10.1139/l00-075
- Fayek, A.; Oduba, A. 2005. Predicting industrial construction labor productivity using fuzzy expert systems, Journal of Construction Engineering and Management 131(8): 938–941. http://dx.doi.org/10.1061/(ASCE)0733-9364(2005)131:8(938)
- Freudenberg, M. 2003. Composite indicators of country performance: a critical assessment. OECD Science, Technology and Industry Working Papers, OECD, Directorate for Science, Technology and Industry [online], [cited 15 October 2012]. Available from Internet: http://econpapers.repec.org/paper/oecstiaaa/2003_2f16-en.htm
- Grabisch, M. 1996. The application of fuzzy integrals in multicriteria decision making, European Journal of Operational Research 89(3): 445–456. http://dx.doi.org/10.1016/0377-2217(95)00176-X
- Grabisch, M. 1997. K-Order additive discrete fuzzy measures and their representation, Fuzzy Sets and Systems 92(2): 167–189. http://dx.doi.org/10.1016/S0165-0114(97)00168-1
- Hand, D. 2004. Measurement theory and practice: the world through quantification. John Wiley & Sons Ltd. 512 p.
- Kumaraswamy, M.; Thorpe, A. 1996. Systematizing construction project evaluations, Journal of Management in Engineering 12(1): 34–39. http://dx.doi.org/10.1061/(ASCE)0742-597X(1996)12:1(34)
- Landy, F.; Farr, J. 1983. The measurement of work performance: methods, theory, and applications. London: Academic Press. 342 p.
- Lauras, M.; Marques, G.; Gourc, D. 2010. Towards a multidimensional project performance measurement system, Decision Support Systems 48(2): 342–353. http://dx.doi.org/10.1016/j.dss.2009.09.002
- Leszczyński, K.; Penczek, P.; Grochulski, W. 1985. Sugeno's fuzzy measure and fuzzy clustering, Fuzzy Sets and Systems 15(2): 147–158. http://dx.doi.org/10.1016/0165-0114(85)90043-0
- Liginlal, D.; Ow, T. 2006. Modeling attitude to risk in human decision processes: an application of fuzzy measures, Fuzzy Sets and Systems 157(23): 3040–3054. http://dx.doi.org/10.1016/j.fss.2006.06.010
- Lim, C.; Mohamed, M. 1999. Criteria of project success: an exploratory re-examination, International Journal of Project Management 17(4): 243–248. http://dx.doi.org/10.1016/S0263-7863(98)00040-4
- Marques, G.; Gourc, D.; Lauras, M. 2011. Multi-criteria performance analysis for decision making in project management, International Journal of Project Management 29(8): 1057–1069. http://dx.doi.org/10.1016/j.ijproman.2010.10.002
- Murofushi, T.; Sugeno, M. 1989. An interpretation of fuzzy measures and the Choquet integral as an integral with respect to a fuzzy measure, Fuzzy sets and Systems 29(2): 201–227. http://dx.doi.org/10.1016/0165-0114(89)90194-2
- Nardo, M; Saisana, M; Saltelli, A; Tarantola, S 2005. Tools for composite indicators building. European Commission-Joint Research Centre, EUR, Citeseer, 21682 [online], [cited 10 October 2012]. Available from Internet: http://collection.europarchive.org/dnb/20070702132253/ http://farmweb.jrc.ec.europa.eu/ci/Document/EUR%2021682%20EN.pdf
- Pham, T.; Yan, H. 1997. A quasi-linear fuzzy measure of multiattributes, Fuzzy Sets and Systems 90: 255–266. http://dx.doi.org/10.1016/S0165-0114(96)00146-7
- Park, M.; Kim, N.; Lee, H.; Ahn, C.; Lee, K. 2009. Construction project performance management using BSC and data warehouse, Journal of Korean Institute of Construction Engineering and Management 10(2): 14–25.
- Saisana, M.; Tarantola, S. 2002. State-of-the-art report on current methodologies and practices for composite indicator development. European Commission, Joint Research Centre, Institute for the Protection and the Security of the Citizen, Technological and Economic Risk Management Unit. 214 p.
- Saltelli, A. 2006. Composite indicators between analysis and advocacy, Social Indicators Research 81(1): 65–77. http://dx.doi.org/10.1007/s11205-006-0024-9
- Schuyler, J. 1996. Decision analysis in projects. Pennsylvania: Project Management Institute. 115 p.
- Shen, C.; Hsieh, K. 2010. Enhance the evaluation quality of project performance based on fuzzy aggregation weight effect, Quality & Quantity 45(4): 845–857. http://dx.doi.org/10.1007/s11135-010-9377-x
- Shenhar, A.; Levy, O.; Dvir, D. 1997. Mapping the dimensions of project success, Project Management Journal 28(2): 5–13.
- Shouke, C.; Zhuobin, W.; Jie, L. 2010. Comprehensive evaluation for construction performance in concurrent engineering environment, International Journal of Project Management 28(7): 708–718. http://dx.doi.org/10.1016/j.ijproman.2009.11.004
- Sugeno, M. 1974. Theory of fuzzy integrals and its applications. PhD Thesis. Tokyo: Tokyo Institute of Technology.
- Sun, C.; Bi, R. 2010. Study on disaster reconstruction project performance evaluation based on Fuzzy Analytic Network Process, in International Symposium on Computer, Communication, Control and Automation (3CA), May 5–7 2010, Tainan, Taiwan. 338–341.
- Tzeng, G.; Ouyang, Y.; Lin, C.; Chen, C. 2005. Hierarchical MADM with fuzzy Integral for evaluating enterprise intranet web sites, Information Sciences 169(3–4): 409–426. http://dx.doi.org/10.1016/j.ins.2004.07.001
- Yang, R.; Wang, Z.; Heng, P.; Leung, K. 2005. Fuzzy numbers and fuzzification of the Choquet integral, Fuzzy Sets and Systems 153(1): 95–113. http://dx.doi.org/10.1016/j.fss.2004.12.009