Risk analysis of BOT contracts using soft computing

Shahrara, Neda; Çelik, Tahir; Gandomi, Amir H.

doi:10.3846/13923730.2015.1068844

Cited by 10 publications

(8 citation statements)

References 33 publications

(42 reference statements)

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“…Artificial neural network models have been widely employed to develop nonlinear data relationships and improve estimates. Shahrara et al (2017) used artificial neural network models to reveal the relationship between the project's important parameters or risk variables.…”

Section: Literature Analysismentioning

confidence: 99%

Systematic analysis of PPP research in construction journals: from 2009 to 2019

Zhang

Luo

Shan

et al. 2020

ECAM

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PurposeThe aims of this study are to conduct a systematic review of public–private partnership (PPP) studies published from 2009 to 2019, to compare the results with Ke et al. (2009) who reviewed the PPP literature published from 1998 to 2008, and to trace the evolution of the PPP knowledge in the past two decades. This study also presents the possible directions that the PPP research may go towards in the future, arguably.Design/methodology/approachThis study carried out a top journal-based search to identify the quality PPP articles published from 2009 to 2019. A total of 12 top-tier construction journals were systematically searched in the database of web of science (WOS), from which 279 PPP articles were identified for review.FindingsThe number of the identified articles, the titles of the journals, institutions, the most cited papers, and prevalent research methods were analyzed and compared. The existing PPP studies in construction journals were classified into seven streams. Through analysis of the PPP research status and gaps, five future research directions were revealed.Originality/valueThis study contributes to the current body of knowledge by revealing the research trend of PPP from 2009 to 2019. It presents the change of PPP development trend in the past decade through comparison with Ke et al. (2009). It also reveals the major research streams and points out the directions that the PPP research may go towards in the future. Moreover, this study is helpful to the practice as well. It can enhance the practitioners' understanding of the PPP development in the past decade. In addition, it identified the research institutions contributing the most in the area of PPP, which may serve as valuable reference for practitioners to locate the best institutions for consultancy or collaboration.

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Section: Literature Analysismentioning

confidence: 99%

Systematic analysis of PPP research in construction journals: from 2009 to 2019

Zhang

Luo

Shan

et al. 2020

ECAM

View full text Add to dashboard Cite

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“…Tsai [21] used the Analytical Hierarchical Process (AHP) to establish relative weightings of the individual risk factors. Shahrara et al [22] used a soft computing model to analyze the risk on the BOT contracts. Moreover, Doloi [23] revealed that site conditions and design complexity are among the most critical risk attributes influencing time performance in construction projects.…”

Section: Risk Managementmentioning

confidence: 99%

Evaluating Ancillary Business Scale for PPP-BOT Projects: A Social Housing BOT Case in Taiwan

Huang

Dzeng

2019

Sustainability

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Due to budgetary constraints, the government releases the right to ancillary business development for private investors to increase profits in PPP projects. However, the ancillary business scale is not specified in the regulations, and there is little relevant research on modeling the scale. Thus, our research aims to create a model with mathematical analysis to evaluate the ancillary business scale. The model is constructed based on the discounted cash flow model to calculate the ancillary business scale attracting private investors with a case study of a social housing project. For this case, the calculated ancillary business minimum scale (ratio of ancillary business to project in total floor area) based on the 7-year (2009–2016) and 17-year (2000–2016) data are 30.81% and 52.79%, respectively; neither is able to meet the scale listed in the tender condition regulated by the government, i.e., 25%. Moreover, this study performs a sensitivity analysis on the expected rate of return and rent discount of the case. The government needs to raise the proportion of ancillary businesses or to increase the rent of social housing to successfully attract private investors.

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“…The Build-Operate-Transfer (BOT) scheme has been used effectively to alleviate the government's financial burden by attracting the private sector to participate in public facilities (Shahrara, ÃElik, & Gandomi, 2017). As an important content of BOT contract, concession period defines the time span in which the private sector has the right to commercially operate the BOT project before it is transferred back to the government (Y.…”

Section: Introductionmentioning

confidence: 99%

Concession Model for Fair Distribution of Benefits and Risks in Build-Operate-Transfer Road Projects

Xue

Chong

Zhou

et al. 2019

Journal of Civil Engineering and Management

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A fair distribution of benefits and risks is not only one of the key factors in deciding concession period but also an important prerequisite for good cooperation between the government and the private sector in a Build-Operate-Transfer (BOT) road project. Considering the psychological characteristic of decision makers’ fairness preference, this study innovatively introduces the inequity aversion theory into the concession model, which provides a novel perspective to investigate the distribution of benefits and risks. In the improved model, the decision makers’ investment utility involves their economic benefits as well as their disutility due to inequity. Furthermore, the equilibrium principle of benefits and risks in this model has changed to minimize the gap between the investment utility-risk ratios of the government and the private sector. Based on Monte Carlo simulation, this study verifies the application of the model to a BOT road project in China. The results show that the concession period with fairness preference can effectively narrow the gap between the investment utility-risk ratios of the government and the private sector, thus guaranteeing the fair distribution of benefits and risks in the BOT road project.

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Risk analysis of BOT contracts using soft computing

Cited by 10 publications

References 33 publications

Systematic analysis of PPP research in construction journals: from 2009 to 2019

Systematic analysis of PPP research in construction journals: from 2009 to 2019

Evaluating Ancillary Business Scale for PPP-BOT Projects: A Social Housing BOT Case in Taiwan

Concession Model for Fair Distribution of Benefits and Risks in Build-Operate-Transfer Road Projects

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