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Alshibani, A, El Ghazzawi, Y A, Mohammed, A, Ghaithan, A M and Hassanain, M A (2024) A multi-criteria decision-making model for heavy construction equipment replacement in Saudi Arabia. Journal of Financial Management of Property and Construction, 29(03), 485–511.
Amadi, A I (2024) Investigating ground-related design deficiencies as potential triggers to cost overruns in highway projects. Journal of Financial Management of Property and Construction, 29(03), 349–71.
Atapattu, C N, Domingo, N and Sutrisna, M (2024) A conceptual cost estimation model for the pre-design stage of road projects using multiple regression analysis. Journal of Financial Management of Property and Construction, 29(03), 388–404.
Badamasi, A A, Aryal, K R, Makarfi, U U and Dodo, M (2022) Drivers and barriers of virtual reality adoption in UK AEC industry. Engineering, Construction and Architectural Management, 29(03), 1307-18.
Barrientos-Orellana, A, Ballesteros-Pérez, P, Mora-Melia, D, González-Cruz, M C and Vanhoucke, M (2022) Stability and accuracy of deterministic project duration forecasting methods in earned value management. Engineering, Construction and Architectural Management, 29(03), 1449-69.
Bon, R and Crosthwaite, D (2001) The future of international construction: some results of 1992-1999 surveys. Building Research & Information, 29(03), 242–7.
Chandra, V and Loosemore, M (2011) Communicating about organizational culture in the briefing process: case study of a hospital project. Construction Management and Economics, 29(03), 223–31.
Choi, J O, Shrestha, B K, Kwak, Y H and Shane, J (2022) Exploring the benefits and trade-offs of design standardization in capital projects. Engineering, Construction and Architectural Management, 29(03), 1169-93.
Chowdhury, A N, Chen, P-H and Tiong, R L K (2011) Analysing the structure of public-private partnership projects using network theory. Construction Management and Economics, 29(03), 247–60.
Davidson, C H (2001) Technology watch in the construction sector: why and how?. Building Research & Information, 29(03), 233–41.
Demirkesen, S and Tezel, A (2022) Investigating major challenges for industry 4.0 adoption among construction companies. Engineering, Construction and Architectural Management, 29(03), 1470-503.
Eghbali-Zarch, M, Tavakkoli-Moghaddam, R, Dehghan-Sanej, K and Kaboli, A (2022) Prioritizing the effective strategies for construction and demolition waste management using fuzzy IDOCRIW and WASPAS methods. Engineering, Construction and Architectural Management, 29(03), 1109-38.
Guo, J, Chen, J and Xie, Y (2022) Determining a reasonable concession period for risky transportation BOT projects with government subsidies based on cumulative prospect theory. Engineering, Construction and Architectural Management, 29(03), 1396-426.
- Type: Journal Article
- Keywords: build-operate-transfer (bot); concession period; cumulative prospect theory; government subsidy; loss-averse behavior; monte-carlo simulation
- ISBN/ISSN:
- URL: https://doi.org/10.1108/ECAM-11-2019-0612
- Abstract:
Purpose: This paper explores the impact of both government subsidies and decision makers’ loss-averse behavior on the determination of transportation build-operate-transfer (BOT) concession periods based on cumulative prospect theory (CPT). The prospect value of a transportation project under traffic risk can be formulated according to the value function for gains and losses and the decision weight for gains and losses. As an extra income for investors, government subsidy is designed for highly risky aspects of BOT transportation projects: uncertain initial traffic volumes and fluctuating growth rates. Design/methodology/approach: A decision-making model determining the concession period of a transportation BOT project is proposed by using the Monte-Carlo simulation method based on CPT, and the effects of risky behaviors of private investors on concession period decision making are analyzed. A subsidy method related to the internal rate-of-return (IRR) corresponding to a specific initial traffic volume and growth rate is proposed. The case of an actual BOT highway project is examined to illustrate how the method proposed can be used to determine the concession period of a transportation BOT project considering decision makers’ loss-averse behavior and government subsidy. Contingency analysis is discussed to cope with possible misestimating of key factors such as initial traffic volume and cost coefficients. Sensitivity analysis is employed to investigate the impact of CPT parameters on the concession period decisions. An actual BOT case which failed to attract private capital is introduced to show the practical application. The results are then interpreted to conclude this paper. Findings: Based on comparisons drawn between a concession period decision-making model considering the psychological behaviors of decision makers and a model not considering them, the authors conclude that the concession period based on CPT is distinctly different from that of the loss-neutral model. The concession period based on CPT is longer than the loss-neutral concession period. That is, loss-averse private investors tend to ask for long concession periods to make up for losses they will face in the future. Government subsidies serve as extra income for investors, allowing appointed profits to be secured sooner. For the benefit side of contingency variables, the normal state of initial traffic volume, average annual traffic growth rate and bias degree and the government subsidy need to be paid close attention during the project life span. For the cost side of contingency variables, the annual operating cost variable has a significant impact on the length of predicted concession period, while the large-scale cost variable has minor impact. Originality/value: With an actual BOT highway project, the determination of transportation BOT concession periods based on the psychological behaviors of decision makers is analyzed in this paper. As the psychological behaviors of decision makers heavily impact the decision-making process, the authors analyze their impacts on concession period decision making. Government subsidy is specifically designed for various states of initial traffic volume and fluctuating growth rates to cope with corresponding high risks and mitigate private investors’ loss-averse behaviors. Contingency analysis and sensitivity analysis are discussed as the estimated values of parameters may not be authentic in actual situations.
Hernández-Nicolás, C M, Martín-Ugedo, J F and Minguez-Vera, A (2022) Women CEOs and firm performance in the construction industry: evidence from Spain. Engineering, Construction and Architectural Management, 29(03), 1343-57.
Jawad, S and Ledwith, A (2022) A measurement model of project control systems success for engineering and construction projects case study: contractor companies in Saudi's petroleum and chemical industry. Engineering, Construction and Architectural Management, 29(03), 1218-40.
Kadan, R, Omotayo, T S, Boateng, P, Nani, G and Wilson, M (2024) The application of Bayesian network analysis in demystifying construction project subcontracting complexities for developing countries. Journal of Financial Management of Property and Construction, 29(03), 444–69.
Koolwijk, J, van Oel, C and Bel, M (2022) The interplay between financial rules, trust and power in strategic partnerships in the construction industry. Engineering, Construction and Architectural Management, 29(03), 1089-108.
Koskela, L and Vrijhoef, R (2001) Is the current theory of construciton a hindrance to innovation?. Building Research & Information, 29(03), 197–207.
Laryea, S (2011) Quality of tender documents: case studies from the UK. Construction Management and Economics, 29(03), 275–86.
Li, H, Guo, H L, Skitmore, M, Huang, T, Chan, K Y N and Chan, G (2011) Rethinking prefabricated construction management using the VP-based IKEA model in Hong Kong. Construction Management and Economics, 29(03), 233–45.
Lin, Y and Yang, W (2022) Tri-optimization of building shape and envelope properties using Taguchi and constraint limit method. Engineering, Construction and Architectural Management, 29(03), 1284-306.
Maina, J J (2024) Modelling business performance from marketing practices of architecture firms in Nigeria. Journal of Financial Management of Property and Construction, 29(03), 425–43.
Mbachu, J and Frei, M (2011) Diagnosing the strategic health of an organization from SWOT analysis results: case study of the Australasian cost management profession. Construction Management and Economics, 29(03), 287–303.
Naveed, F and Khan, K I A (2022) Investigating the influence of information complexity on construction quality: a systems thinking approach. Engineering, Construction and Architectural Management, 29(03), 1427-48.
Ndekugri, I, Silverio, A K and Mason, J (2024) Enforcing payment obligations under construction contracts by insolvency proceedings. Journal of Financial Management of Property and Construction, 29(03), 372–87.
Ni, G, Zhang, Z, Yuan, Z, Huang, H, Xu, N and Deng, Y (2022) Transformation paths and influencing factors of tacit knowledge into explicit knowledge in real estate companies: a qualitative study. Engineering, Construction and Architectural Management, 29(03), 1319-42.
Ogunseiju, O, Olayiwola, J, Akanmu, A and Olatunji, O A (2022) Evaluation of postural-assist exoskeleton for manual material handling. Engineering, Construction and Architectural Management, 29(03), 1358-75.
Oke, A E, Aliu, J, Ehiosun, L U, Ebekozien, A and Rotimi, A A (2024) From hurdles to heights: Blueprint for tackling distributed ledger technology challenges in the construction sector of a developing economy. Journal of Financial Management of Property and Construction, 29(03), 405–24.
Olawumi, T O and Chan, D W M (2022) Developing project evaluation models for smart sustainable practices implementation in construction projects: a comparative study between Nigeria and Hong Kong. Engineering, Construction and Architectural Management, 29(03), 1522-52.
Oraee, M, Hosseini, M R, Edwards, D and Papadonikolaki, E (2022) Collaboration in BIM-based construction networks: a qualitative model of influential factors. Engineering, Construction and Architectural Management, 29(03), 1194-217.
Rajhans, R K (2024) Promoters’ equity pledging, policy uncertainty and firm-level cash holding: Evidence from an emerging market. Journal of Financial Management of Property and Construction, 29(03), 470–84.
Seaden, G and Manseau, A (2001) Public policy and construction innovation. Building Research & Information, 29(03), 182–96.
Shan, Y, Goodrum, P M, Zhai, D, Haas, C and Caldas, C H (2011) The impact of management practices on mechanical construction productivity. Construction Management and Economics, 29(03), 305–16.
Sharma, V, Zaki, M, Jha, K N and Krishnan, N M A (2022) Machine learning-aided cost prediction and optimization in construction operations. Engineering, Construction and Architectural Management, 29(03), 1241-57.
Slaughter, E S (2001) Design strategies to increase building flexibility. Building Research & Information, 29(03), 208–17.
Stouffs, R (2001) Visualizing information structures and its impact on project teams: an information architecture for the virtual AEC company. Building Research & Information, 29(03), 218–32.
Tabish, S Z S and Jha, K N (2011) Analyses and evaluation of irregularities in public procurement in India. Construction Management and Economics, 29(03), 261–74.
Toosi, H, Ghaaderi, M A and Shokrani, Z (2022) Comparative study of academic research on project management in Iran and the World with text mining approach and TF–IDF method. Engineering, Construction and Architectural Management, 29(03), 1553-83.
Umar, T (2022) Challenges of BIM implementation in GCC construction industry. Engineering, Construction and Architectural Management, 29(03), 1139-68.
Wang, Y, Ye, G, Zheng, C and Zhang, S (2022) Total factor productivity growth and its decomposition in the Chinese construction industry since China's accession to the World Trade Organization. Engineering, Construction and Architectural Management, 29(03), 1258-83.
Yu, J, Ma, G, Ding, W, Mao, J and Wang, J (2022) Structural model for the relationships between age-friendly communities and quality of life of older adults in Hefei, China. Engineering, Construction and Architectural Management, 29(03), 1376-95.