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Frontiers of Engineering Management

ISSN 2095-7513

ISSN 2096-0255(Online)

CN 10-1205/N

邮发代号 80-905

Frontiers of Engineering Management  2017, Vol. 4 Issue (4): 437-450   https://doi.org/10.15302/J-FEM-2017068
  本期目录
基于鲁棒公私合作策略的铁路与房地产开发
Fai NG Ka, K. LO Hong(), HUAI Yue
香港科技大学土木及环境工程系
Robust public-private partnerships for joint railway and property development
Ka Fai NG, Hong K. LO(), Yue HUAI
Department of Civil and Environmental Engineering, The Hong Kong University of Science and Technology, Hong Kong, China
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摘要:

私营部门参与基础设施项目的建设或运营,有利于提高项目财务的可行性。公私合作关系(PPP)可利用私营公司的实力,将某些项目风险从公共部门转移到可更好处理这些风险的私营公司。在铁路和房地产联合开发的情况下,捆绑铁路和房地产开发(R&HD)不仅使巨大的铁路建设成本与利润丰厚的房屋租赁收入之间进行交叉补贴,而且还提高了PPP模式的灵活性。其通过分配铁路和住房收入及成本,降低了公共和私营部门的内在风险。在本研究中,基于Ng和Lo(2015)的理论框架,我们将对各种PPP模式的鲁棒性进行研究。在人口或需求增长以及铁路建设成本不确定性的情况下,利益相关者的风险和回报如何受到各种PPP模式的影响?特定PPP模式的最终结果是什么?另外,随着时间的推移,高度波动的人口和铁路建设成本会如何改变最佳PPP模式?是否存在鲁棒的PPP模式?上述研究对管控风险可起到至关重要的作用,也有助于形成适用于铁路和房地产开发的有效PPP模式。

Abstract

The involvement of the private sector in the construction or operation of an infrastructure project may enhance the financial viability of projects, which facilitates the formation of public-private partnership (PPP) for project delivery. PPP exploits the strength of the private sector by shifting certain project risks from the public party to the private sector who can efficiently manage certain risks. In joint railway and housing development, the approach of bundling railway and housing development (R&HD) allows cross-subsidization between immense railway construction cost and profitable housing rental revenue. This approach also provides flexibility in incorporating PPP models by distributing railway and housing revenues and costs and their inherent risks properly to the public and private sectors. Ng and Lo (2015a) developed an evaluation framework for joint railway and property development, which evaluates PPPs based on financial and construction criteria for selecting the best suitable PPP for a particular project. This study, which is based on the framework in Ng and Lo (2015a), aims to examine the robustness of various PPP configurations. This study analyzes the effects of PPP configurations on stakeholders’ risks and returns under population or demand growth and railway construction cost uncertainties. The eventual outcome of particular PPP configurations is also examined. This study also seeks to answer the following questions: How would optimal configuration change under highly volatile population and railway construction cost? Are there PPP configurations that are robust to these uncertainties and those that are sensitive to a particular uncertainty? This understanding is critical for managing risks and facilitating the formation of appropriate PPP for R&HD.

Key wordspublic-private partnership    BFOOD    housing and railway development
收稿日期: 2017-08-23      出版日期: 2017-12-14
通讯作者: K. LO Hong     E-mail: cehklo@ust.hk
Corresponding Author(s): Hong K. LO   
 引用本文:   
Fai NG Ka, K. LO Hong, HUAI Yue. 基于鲁棒公私合作策略的铁路与房地产开发[J]. Frontiers of Engineering Management, 2017, 4(4): 437-450.
Ka Fai NG, Hong K. LO, Yue HUAI. Robust public-private partnerships for joint railway and property development. Front. Eng, 2017, 4(4): 437-450.
 链接本文:  
https://academic.hep.com.cn/fem/CN/10.15302/J-FEM-2017068
https://academic.hep.com.cn/fem/CN/Y2017/V4/I4/437
Fig.1  
PPP modelsBuild (B)Fund (F)Own (O)Operate (O)Develop property (D)MPGTPC
BRFRORORDRRRRRR/R→G
BRFRORORDGRRRRGG→RR→G
BRFGOGORDRRGGRR/R→G
BGFGOGORDGGGGRGG→R/
BGFGOGOGDGGGGGG//
Tab.1  
PPP modelsPrivate CompanyGovernment
BRFRORORDRPh+PrCrcTPCY1TPCY1
BRFRORORDGPrCrcTPCY1+MPGX1Ph+TPCY1MPGX1
BRFGOGORDRPh+PrTPCY2TPCY2Crc
BGFGOGORDGPr+MPGX1PhCrcMPGX1
BGFGOGOGDG/Ph+PrCrc
Tab.2  
PPP modelsμDσDμKσKυr4υh1XMPGYTPC
BRFRORORDRμDσDμKσKυr4υh1/Y1
BRFRORORDGμDσDμKσKυr4υh1X1Y1
BRFGOGORDRμDσDμKσKυr4υh1/Y2
BGFGOGORDGμDσDμKσKυr4υh1X1/
BGFGOGOGDGμDσDμKσKυr4υh1//
Tab.3  
Fig.2  
ModelPrivate company (R)Government (G)Consumer surplus
Expected value/(107 HKD)Standard deviation/(107 HKD)COV/%Expected value/(107 HKD)Standard deviation/(107 HKD)COV/%Expected value/(109 HKD)Standard deviation/(108 HKD)COV/%
126.3002.74010.435.3300.4348.141.2403.50028.16
20.5200.986189.7330.2002.2007.291.6705.38032.13
325.0002.4209.706.6100.67210.151.2603.67029.20
42.1101.19056.4128.7002.2807.961.6905.20030.76
529.9002.2607.551.7105.39031.60
Tab.4  
Fig.3  
Fig.4  
Fig.5  
Fig.6  
Fig.7  
CaseModel 1Model 2Model 3Model 4Model 5
RGRGRGRGRG
Case 126.255.330.5230.2224.976.612.1128.67029.92
Case 227.135.261.3028.6225.536.633.0926.66029.14
Case 327.875.152.2924.8626.316.684.3922.30025.92
Case 428.494.963.8116.1127.076.546.4912.87018.50
Tab.5  
CaseModel 1Model 2Model 3Model 4Model 5
RGRGRGRGRG
Case 110.48.1189.77.39.710.256.48.07.5
Case 29.510.492.013.28.910.449.716.510.9
Case 39.212.459.126.58.410.342.233.422.9
Case 48.515.240.862.87.413.532.786.651.1
Tab.6  
Fig.8  
Fig.9  
Fig.10  
Fig.11  
Fig.12  
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