ASSESSMENT OF PROJECT CHARACTERISTICS AFFECTING RISK OCCURRENCES IN CONSTRUCTION PROJECTS USING FUZZY AHP

The performance of the construction industry has been widely criticized in the literature due to substantial delays and cost overruns. The dynamic, turbulent, and complex environment of the construction industry can lead to poor performance causing occurrence of numerous risks that can adversely affect the performance of the projects. Risk management plays an important role in the improvement of performance of construction projects. However, performance of risk management is challenging due to limited availability of information, particularly during the risk identification stage. This study aims to identify the characteristics of the construction projects that are critical in the occurrence of the risks. For that purpose, an in-depth literature review was conducted to extract characteristics of the construction projects in the first step of the study. Then, a questionnaire survey was prepared to collect expert opinions. Finally, a MATLAB script was developed in-house to perform a fuzzy AHP method to analyze the gathered data. The findings show that the contract-related characteristics, contract type, project value, and construction-related characteristics are the most critical characteristics of construction projects related to risk occurrence cases.

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  • [1] Sexton, M., P. Barret, (2003), “A literature synthesis of innovation in small construction firms: insights, ambiguities and questions,” Construction Management and Economics, 21 (6), 613–622.
  • [2] Barrett, P., M. Sexton, (2006), “Innovation in small, project-based construction firms,” British Journal of Management, 17 (4), 331–346.
  • [3] Rezgui, Y., A. Zarli, (2006), “Paving the way to the vision of digital construction: A strategic roadmap,” Journal of Construction Engineering and Management, 132 (7), 767–776.
  • [4] Beatham, S., C. Anumba, T. Thorpe, I. Hedges, (2004), “KPIs: A critical appraisal of their use in construction,” Benchmarking: An International Journal, 11 (1), 93–117.
  • [5] Alinaitwe, H., J. A. Mwakali, B. Hansson, (2009), “Organizational effectiveness of Ugandan building firms as viewed by craftsmen,” Journal of Civil Engineering and Management, 15 (3), 281–288.
  • [6] Rivas, R. A., J. D. Borcherding, V. González, L. F. Alarcón, (2011), “Analysis of factors influencing productivity using craftsmen questionnaires: Case study in a Chilean construction company,” Journal of Construction Engineering and Management, 137 (4), 312–320.
  • [7] Fidan, G., I. Dikmen, A. M. Tanyer, M. T. Birgonul, (2011), “Ontology for Relating Risk and Vulnerability to Cost Overrun in International Projects,” Journal of Computing in Civil Engineering, 25 (4), 302–315.
  • [8] Zhi, H., (1995), “Risk management for overseas construction projects,” International Journal of Project Management, 13 (4), 231–237.
  • [9] Wang, S. Q., M. F. Dulaimi, M. Y. Aguria, (2004), “Risk management framework for construction projects in developing countries,” Construction Management and Economics, 22 (3), 237–252.
  • [10] Han, S. H., D. Y. Kim, H. Kim, W. S. Jang, (2008), “A web-based integrated system for international project risk management,” Automation in Construction, 17 (3), 342–356.
  • [11] Dikmen, I., C. Budayan, ; M Talat Birgonul, E. Hayat, C. Eng, (2018), “Effects of Risk Attitude and Controllability Assumption on Risk Ratings: Observational Study on International Construction Project Risk Assessment.”
  • [12] Kamara, J. M., C. J. Anumba, P. M. Carrillo, N. Bouchlaghem, “Conceptual framework for live capture and reuse of project knowledge,” in CIB W78 International Conference on Information Technology for Construction, 2003, 178–185.
  • [13] Dikmen, I., M. T. Birgonul, C. Anac, J. H. M. Tah, G. Aouad, (2008), “Learning from risks: A tool for post-project risk assessment,” Automation in Construction, 18 (1), 42–50.
  • [14] Ozorhon, B., I. Dikmen, M. T. Birgonul, M. Talat Birgonul, (2005), “Organizational memory formation and its use in construction,” Building Research and Information, 33 (1), 67–79.
  • [15] Fan, Z.-P. P., Y.-H. H. Li, Y. Zhang, (2015), “Generating project risk response strategies based on CBR: A case study,” Expert Systems with Applications, 45 (6), 2870–2883.
  • [16] Zhang, L., N. M. El-Gohary, “Epistemic Modeling for Sustainability Knowledge Management in Construction,” in Computing in Civil Engineering, 2013, 202–209.
  • [17] Li Bing, B., R. L. K Tiong, (1999), “Risk Management Model for International Construction Joint Ventures,” Journal of Construction Engineering and Management, 125 (5), 377–384.
  • [18] Ling, F. Y. Y., S. L. Chan, E. Chong, L. P. Ee, (2004), “Predicting Performance of Design-Build and Design-Bid-Build Projects,” Journal of Construction Engineering and Management, 75 (1), 75–83.
  • [19] Ozorhon, B., D. Arditi, I. Dikmen, M. T. Birgonul, (2007), “Effect of host country and project conditions in international construction joint ventures,” International Journal of Project Management, 25 (8), 799–806.
  • [20] Han, S. H. et al., (2007), “Causes of Bad Profit in Overseas Construction Projects,” Journal of Construction Engineering and Management, 133 (12), 932–943.
  • [21] Cho, K. M., T. H. Hong, C. T. Hyun, (2009), “Effect of project characteristics on project performance in construction projects based on structural equation model,” Expert Systems with Applications, 36 (7), 10461–10470.
  • [22] Eybpoosh, M., I. Dikmen, M. T. Birgonul, (2011), “Identification of risk paths in international construction projects using structural equation modeling,” Journal of Construction Engineering and Management, 137 (12), 1164–1175.
  • [23] Nguyen, A. T., L. D. Nguyen, L. Le-Hoai, C. N. Dang, (2015), “Quantifying the complexity of transportation projects using the fuzzy analytic hierarchy process,” International Journal of Project Management, 33 (6), 1364–1376.
  • [24] Liu, B., T. Huo, ; Yan Liang, Y. Sun, X. Hu, (2016), “Key Factors of Project Characteristics Affecting Project Delivery System Decision Making in the Chinese Construction Industry: Case Study Using Chinese Data Based on Rough Set Theory,” Journal of Professional Issues in Engineering Education and Practice, 142 (5), 05016003.
  • [25] Nguyen, L. D., L. Le-Hoai, D. Q. Tran, C. N. Dang, C. V Nguyen, (2019), “Effect of project complexity on cost and schedule performance in transportation projects,” Construction Management and Economics, 37 (7), 384–399.
  • [26] Peñaloza, G. A., T. A. Saurin, C. T. Formoso, (2020), “Monitoring complexity and resilience in construction projects: The contribution of safety performance measurement systems,” Applied Ergonomics, 82 (1), 102978.
  • [27] Luo, L., L. Zhang, (2020), “Linking project complexity to project success: a hybrid SEM-FCM method,” Engineering, Construction and Architectural Management, ahead-of-p (ahead-of-print).
  • [28] Zadeh, L., (1965), “Fuzzy sets,” Information Control, 8 (1), 338–353.
  • [29] Kahraman, C., U. Cebeci, Z. Ulukan, (2003), “Multi‐criteria supplier selection using fuzzy AHP,” Logistics Information Management, 16 (6), 382–394.
  • [30] Saaty, T. L., The analytic hierarchy process. New York: McGraw-Hill, 1980.
  • [31] Rao, R. V., Decision Making in the Manufacturing Environment, 1st ed. London: Springer-Verlag London, 2007.
  • [32] Gurgun, A. P., K. Koc, (2020), “Contractor prequalification for green buildings—evidence from Turkey,” Engineering, Construction and Architectural Management, ahead-of-p (ahead-of-print).
  • [33] Chang, D.-Y., (1996), “Applications of the extent analysis method on fuzzy AHP,” European Journal of Operational Research, 95 (3), 649–655.
  • [34] Ayhan, M. B., (2013), “A Fuzzy Ahp Approach For Supplier Selection Problem: A Case Study In A Gearmotor Company,” International Journal of Managing Value and Supply Chains, 4 (3), 11–23.
  • [35] Ericcson, K. A., H. A. Simon, Protocol analysis: Verbal reports on data. MIT Press, Cambridge, Mass, 1984.
  • [36] Greenwell, M., Knowledge engineering for expert system. New York: Halstad Press, 1988.
  • [37] Davies, M., S. Hakiel, (1988), “Knowledge harvesting: A practical guide to interviewing,” Expert Systems with Applications, 5 (5), 42–49.
  • [38] Karwowski, W., A. Mital, “Applications of Approximate Reasoning in Risk Analysis,” in Applications of Fuzzy Set Theory in Human Factors, 6, 1986, 227–243.
  • [39] Saaty, T. L., M. S. Özdemir, (2014), “How Many Judges Should There Be in a Group ?,” Annals of Data Science, 1 (3–4), 359–368.
  • [40] Wong, J. K. W., H. Li, (2008), “Application of the analytic hierarchy process (AHP) in multi-criteria analysis of the selection of intelligent building systems,” Building and Environment, 43 (1), 108–125.
  • [41] Cheng, E. W. L., H. Li, (2002), “Construction Partnering Process and Associated Critical Success Factors: Quantitative Investigation,” Journal of Management in Engineering, 18 (4), 194–202.
  • [42] Thanki, S., K. Govindan, J. Thakkar, (2016), “An investigation on lean-green implementation practices in Indian SMEs using analytical hierarchy process (AHP) approach,” Journal of Cleaner Production, 135, 284–298.
  • [43] Xu, Z., (2000), “On consistency of the weighted geometric mean complex judgement matrix in AHP,” European Journal of Operational Research, 126 (3), 683–687.
  • [44] Büyüközkan, G., G. Çifçi, (2012), “A novel hybrid MCDM approach based on fuzzy DEMATEL, fuzzy ANP and fuzzy TOPSIS to evaluate green suppliers,” Expert Systems with Applications, 39 (3), 3000–3011.
  • [45] Işik, Z., H. Aladağ, (2017), “A fuzzy AHP model to assess sustainable performance of the construction industry from urban regeneration perspective,” Journal of Civil Engineering and Management, 23 (4), 499–509.
  • [46] Çevikbaş, M., A. Köksal, (2018), “An Investigation of Litigation Process in Construction Industry in Turkey,” Teknik Dergi, 29 (6), 8715–8730.
  • [47] M. Çevikbaş, A. Köksal, (2019), “Evaluation of Litigation Process in Turkish Construction Industry from the Perspective of Judicial Actors,” Tamap Journal of Engineering, 2019 (1), 1–7.
  • [48] Ustinovichius, L., A. Barvidas, A. Vishnevskaja, I. V Ashikhmin, (2009), “Multicriteria Verbal Analysis for the Decision of Construction Problems,” Technological and Economic Development of Economy, 15 (2), 326–340.
  • [49] Serag, E., “Semantic Detection of Risks and Conflicts in Construction Contracts,” in Proceedings of the CIB W78 2010: 27th International Conference, 2010, 16–18.
  • [50] Besaiso, H., P. Fenn, M. Emsley, D. Wright, (2018), “A comparison of the suitability of FIDIC and NEC conditions of contract in Palestine,” Engineering, Construction and Architectural Management, 25 (2), 241–256.
  • [51] Centers for Disease Control and Prevention, “Contract Types,” 2020. .
  • [52] Qazi, A., J. Quigley, A. Dickson, K. Kirytopoulos, (2016), “Project Complexity and Risk Management (ProCRiM): Towards modelling project complexity driven risk paths in construction projects,” International Journal of Project Management, 34 (7), 1183–1198.
  • [53] Fang, C., F. Marle, (2012), “A simulation-based risk network model for decision support in project risk management,” Decision Support Systems.
  • [54] Fang, C., F. Marle, (2013), “Dealing with project complexity by matrix-based propagation modelling for project risk analysis,” Journal of Engineering Design, 24 (4), 239–256.
  • [55] Kartam, N. A., S. A. Kartam, (2001), “Risk and its management in the Kuwaiti construction industry: a contractors’ perspective,” International Journal of Project Management, 19 (6), 325–335.
  • [56] Hassim, S., M. S. Jaafar, S. A. A. H. Sazalli, (2009), “The Contractor Perception Towers Industrialised Building System Risk in Construction Projects in Malaysia,” American Journal of Applied Sciences, 6 (5), 938–942.
  • [57] Bygballe, L. E., M. Ingemansson, (2014), “The logic of innovation in construction,” Industrial Marketing Management.
  • [58] Yusof, A., K. Seng Lai, U. Sains Malaysia, E. Mustafa Kamal, (2017), “Characteristics of innovation orientations in construction companies,” Journal of Engineering, Design and Technology, 15 (4), 436–455.
  • [59] Pérez-Luño, A., J. Wiklund, R. V. Cabrera, (2011), “The dual nature of innovative activity: How entrepreneurial orientation influences innovation generation and adoption,” Journal of Business Venturing, 26 (5), 555–571.
  • [60] Lin, J. J.-C., C.-E. Yang, W.-H. Hung, S.-C. Kang, (2013), “Accessibility evaluation system for site layout planning – a tractor trailer example,” Visualization in Engineering, 1 (1), 12.
  • [61] Su, X., A. R. Andoh, H. Cai, J. Pan, A. Kandil, H. M. Said, (2012), “GIS-based dynamic construction site material layout evaluation for building renovation projects,” Automation in Construction, 27 (1), 40–49.