广东工业大学学报 ›› 2018, Vol. 35 ›› Issue (03): 79-86.doi: 10.12052/gdutxb.170160

• 综合研究 • 上一篇    下一篇

基于贝叶斯网络的公众参与PPP项目决策研究

方媛, 刘俊槐, 谢晶珠, 卢晓晴, 曾妍倩, 谢汉雄   

  1. 广东工业大学 土木与交通工程学院, 广东 广州 510006
  • 收稿日期:2017-11-30 出版日期:2018-05-09 发布日期:2018-05-24
  • 作者简介:方媛(1978-),女,讲师,博士,硕士生导师,主要研究方向为建设项目投融资与决策,绿色施工.E-mail:carolynfang@gdut.edu.cn
  • 基金资助:
    国家自然科学基金资助项目（51608132）；广东省大学生创新创业训练项目（201711845132）；广东工业大学大学生创新实验项目（yj201511845082）

Public Participation in Decision-making of PPP Project Based on Bayesian Network

Fang Yuan, Liu Jun-huai, Xie Jing-zhu, Lu Xiao-qing, Zeng Yan-qian, Xie Han-xiong   

  1. School of Civil and Transportation Engineering, Guangdong University of Technology, Guangzhou 510006, China
  • Received:2017-11-30 Online:2018-05-09 Published:2018-05-24
  • Supported by:
     

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摘要： 目前PPP项目决策论证只注重项目的财务分析，探求公共部门与私人投资者的利益合作，忽视了PPP项目另一利益主体——社会公众的需求，从而造成了许多PPP项目最终的社会满意度不高、国民经济评价不佳等问题.本文在研究公众参与PPP项目决策的可行性和有效性的基础上，以贝叶斯网络为手段建立了一个多目标决策模型，辅助公众参与PPP项目规划决策.最后，通过对某商业性PPP项目决策模型的模拟运算，分析了该模型结果的获得过程.

关键词: 公私合营, 贝叶斯网络模型, 公众参与, 决策支持系统

Abstract: The decision making process of PPP projects always focuses on the profitability and meeting the interest of government sectors and private investors. The decision maker paid little attention to the requirement and preference of the public users, resulting in low social satisfaction and poor national economic effect. In order to reduce the risk of social stability which always comes from project's low social satisfaction, the feasibility and effectiveness of the public participating in the decision-making of PPP projects are discussed. Then a multi-objective decision making model based on Bayesian theory is established to help the decision maker adopting the method of adding the public factors in the planning stage of PPP project. The simulation process is introduced and the simulation results are analyzed through an assumed commercial project. The results show that the public and investor's satisfaction are both considered in the decision making process of project implement scheme. The decision making system based on Bayesian model offers a quantitative way to assist the decision maker in getting a reasonable result with good public participation.

Key words: Public Private Partnership, Bayesian network model, public participation, decision support system

中图分类号: 

  • F282
[1] CHAMBERS R. Participatory Rural Appraisal (PRA):analysis of challenges, potentials and paradigms[J]. World Development, 1994, 22(10):1437-1454.
[2] CREIGHTON J L. The public participation handbook:making better decisions through citizen involvement[J]. San Francisco, 2005,:288
[3] 佟贺丰. 丹麦公众参与科学事务模式综述[J]. 科学学与科学技术管理, 2004, 25(12):123-126. 2004, 25(12):123-126.
[4] ALEDO-TUR A, DOMÍNGUEZ-GÓMEZ J A. Social Impact Assessment (SIA) from a multidimensional paradigmatic perspective:challenges and opportunities[J]. Journal of Environmental Management, 2017, 195(Part 1):56-61.
[5] LI H Y, ZHANG X, NG S T, et al. Quantifying stakeholder influence in decision/evaluations relating to sustainable construction in China - A Delphi approach[J]. Journal of Cleaner Production, 2018, 173:160-170.
[6] AGA D A, NOORDERHAVEN N, VALLEJO B. Project beneficiary participation and behavioral intentions promoting project sustainability:the mediating role of psychological ownership[J]. Development Policy Review, 2017,
[7] AL-KODMANY K. Using visualization techniques for enhancing public participation in planning and design:process, implementation, and evaluation[J]. Landscape & Urban Planning, 1999, 45(1):37-45.
[8] PREVOST D L. Geography of public participation:using geographic information systems to evaluate public outreach program of transportation planning studies[M]. Orlando:Metapress, 2006.
[9] COUNSELL J, SMITH S, BATES-BRKLJAC N. Web 3D based dialogue for public participation and the VEPs Project[C]//Conference on Information Visualization. London:IEEE, 2006:343-348.
[10] FANG Y, LI H Y, LU X Q. Passive public participation mechanism for construction project decision based on mobile Internet[C]//International Conference on Construction and Real Estate Management. Melbourne:IEEE, 2017, 107-115.
[11] MARAKAS G M. Decision support systems in the twenty-first century[M]. New Jersey. Prentice Hall, 1999.
[12] AYCRIGG M. Participation and the World Bank:successes, constraints, and responses[J]. Environment & Planning A, 2010, 8(7):839-841.
[13] SHERRY R. A ladder of citizen participation[J]. Journal of the American Planning Association, 1969, 35(4):216-224.
[14] LIZARRALDE G. Stakeholder participation and incremental housing in subsidized housing projects in Colombia and South Africa[J]. Habitat International, 2011, 35(2):175-187.
[15] WOLTJER J. Concepts of participatory decision-making in Dutch infrastructure planning[M]. Berlin:Springer Netherlands, 2009:153-163.
[16] VAROL C, ERCOSKUN O Y, GURER N. Local participatory mechanisms and collective actions for sustainable urban development in Turkey[J]. Habitat International, 2011, 35(1):9-16.
[17] THE WORLD BANK, Environmentally sustainable development. The World Bank Participation Sourcebook[M]. Washington, D. C.:the World Bank, 1996.
[18] 杨秋波, 张水波. 世行项目管理中公众参与的技术与工具[J]. 项目管理技术, 2008,(9):13-17. 2008,(9):13-17.
[19] LI H Y, NG S T, SKITMORE M. Public participation in infrastructure and construction projects in China:from an EIA-based to a whole-cycle process[J]. Habitat International, 2012, 36(1):47
[20] LIU W L, ZHANG J Y, BLUEMLING B, et al. Public participation in energy saving retrofitting of residential buildings in China[J]. Applied Energy, 2015, 147:287-296.
[21] YATES J K. Construction decision support system for delay analysis[J]. Journal of Construction Engineering & Management, 1993, 119(2):226-244.
[22] HANNA A S, RUSSELL J S, TAHA M A, et al. Application of neural networks to owner-contractor prequalification[M]//Artificial Neural Networks for Civil Engineers:Fundamentals and Applications:ASCE, 2015.
[23] MOHEMAD R, HAMDAN A R, OTHMAN Z A, et al. Decision Support Systems (DSS) in Construction Tendering Processes[J]. International Journal of Computer Science Issues, 2010, 7(2):35-45.
[24] HASTAK M, CUI Q, SAFI B, et al. A Decision Support System for Infrastructure Rehabilitation Planning[C]//International Conference on Computing in Civil Engineering. Cancun:ASCE, 2005(179):1-10.
[25] 侯立铎. 决策树算法在工程质量监督决策支持系统中的应用研究[D]. 贵州:贵州大学计算机科学与技术学院, 2016.
[26] YOON Y, JUNG J, HYUN C. Decision-making support systems using case-based reasoning for construction project delivery method selection:focused on the road construction projects in Korea[J]. Open Civil Engineering Journal, 2016, 10(1):500-512.
[27] HAAG S, CUMMINGS M, Mccubbrey D J. Management information systems for the information age[J]. Information Technology & People, 2007, 13(2):87-89.
[28] KJRULFF U B, MADSEN A L. Bayesian networks and influence diagrams:a guide to construction and analysis[M]. Berlin:Springer, 2008, 22(487):1273-1274.
[29] AGNIESZKA ONIŚKO, DRUZDZEL M J, WASYLUK H. Learning Bayesian network parameters from small data sets:application of Noisy-OR gates[J]. International Journal of Approximate Reasoning, 2001, 27(2):165-182.
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