Document Type : Research Paper
Authors
College of Management and Accounting, Allameh Tabataba’i University, Tehran, Iran.
Abstract
The restrictions of government resources and the recent alterations in the economy have prompted government agencies to employ the capacities of private sector in all infrastructures. In this regard, a variety of financing methods, including the participatory models, have been applied for many years in the water and wastewater industry of Iran. The aim of this study is to identify and prioritize the Public-Private Partnership (PPP) indicators in the water and wastewater industry of Iran via machine learning techniques. To this end, after collecting, preparing and preprocessing the data, weighted indexing techniques including information gain and Gini index were utilized to prioritize the PPP factors. The results indicated that 93% of the indicators were effective in predicting the success of the projects. To compare the two methods, the precision of Naïve Bayes and Random Forest classifiers were taken into account and the information gain method yielded more reasonable findings with one percent difference. The evaluation of indicators elucidated that "complaints about service quality," "contract type," and "Conventional tariffs" revealed a huge impact on the success of collaborative projects. Among the 15 indicators, eight were directly pertinent to the project financing which is the main concern in this industry.
Keywords
Article Title [Persian]
شناسایی و اولویت‌بندی شاخص‌های مشارکت عمومی- خصوصی در صنعت آب و فاضلاب ایران با استفاده از الگوریتم‌های داده‌کاوی
Authors [Persian]
- ملیحه اسکندری
- محمد تقی تقوی فرد
- ایمان رئیسی وانانی
- سروش قاضی نوری
دانشکده مدیریت و حسابداری. دانشگاه علامه طباطبایی. تهران. ایران
Abstract [Persian]
محدودیت منابع دولتی، لزوم استفاده از ظرفیت‌های بخش خصوصی را به یک ضرورت تبدیل نموده است. در این راستا استفاده از انواع روش‌های تأمین منابع مالی ازجمله مدل‌های مشارکتی، سالیانی است که در صنعت آب و فاضلاب در حال استفاده میباشد. هدف این پژوهش مرور ادبیات و اولویت‌بندی شاخص‌های مشارکت عمومی- خصوصی در صنعت آب و فاضلاب با استفاده از تکنیک‌های داده‌کاوی میباشد. به‌منظور تحقق این امر، پس از جمع‌آوری، آماده‌سازی و پیش‌پردازش داده، از تکنیک‌های شاخص وزن دهی شامل شاخص سود اطلاعاتی و شاخص جینی جهت استخراج فاکتورهای مشارکت عمومی و خصوصی استفاده شده است. ارزیابی شاخص‌ها، گزارش داد که ۹۸ درصد شاخص‌ها در پیش‌بینی شکست و یا موفقیت پروژه‌ها تأثیر دارند. برای مقایسه دو روش انتخاب ویژگی از دقت دسته‌بندهای جنگل تصادفی و بیز ساده استفاده شد. نتایج پژوهش مشخص کرد که شکایات مربوط به خدمات، قالب قراردادی و تعرفه‌های متفاوت تأثیر بسیار زیادی در موفقیت و یا شکست پروژه‌های مشارکتی دارند. در بین 15 شاخص کلیدی موفقیت پروژه های مشارکتی این صنعت، 8 شاخص آن به طور مستقیم با مسائل مربوط به تامین مالی طرح ها در ارتباط میباشند و این امر بیانگر این است که همچنان دغدغه اصلی در این صنعت، تامین مالی طرح ها میباشد.
Keywords [Persian]
- مشارکت عمومی- خصوصی
- سرمایه‌گذاری
- شاخص کلیدی عملکرد
- صنعت آب و فاضلاب
- داده‌کاوی
- Abdul-Aziz, A.R., (2001). Unraveling of BOT scheme: Malaysia's Indah water konsortium. Journal of construction engineering and management, 127(6), 457-460.
- Akintoye, A., (2003). Achieving best value in private finance initiative project procurement. Construction Management and Economics, 21(5), p. 461-470.
- Böhl, C.G.P. (2007). Development of a knowledge based decision support system for private sector participation in water and sanitation utilities. Oldenbourg Industrieverlag, 189.
- Brune, N.G., Garrett, & Kogut, B. (2004). The International Monetary Fund and the global spread of privatization. IMF Staff Papers, 195-219.
- Commission, E. (2003). Guidelines for successful public-private partnerships. DG Regional Policy.
- Company, i. (2009). National Wastewater Finanving and investment strategy Report.
- Delmon, J. (2015). Creating a Framework for Public-Private Partnership Programs.
- Dorian, J.P. (2006). Central Asia: A major emerging energy player in the 21st century. Energy Policy, 34(5), 544-555
- Golabchi, M., Nourzaee. (2015). Selecting the best PPP method in rail projects by using AHP methods. Journal of Transportation Engineering, No.6
- Hall, D., Lobina. E. (2005). The relative efficiency of public and private sector water. PSIRU Reports.
- Han, J., Jian, P., & Kamber, M. (2011). Data mining: concepts and techniques, Elsevier.
- Hodge, G.A., Greve, C., & Boardman, A.E. (2010). International Handbook on Public-Private Partnership. Edward Elgar Publishing
- Li, B. (2005). Critical success factors for PPP/PFI projects in the UK construction industry. Construction management and economics, 23(5), 459-471.
- Liu, Haoyue, MengChu, Zhou, Xiaoyu, Sean Lu. & Cynthia Yao. (2018). Weighted Gini index feature selection method for imbalanced data. In 2018 IEEE 15th International Conference on Networking, Sensing and Control (ICNSC). 1-6. IEEE.
- Marzouk, M. Emad Fayez. (2018). PUBLIC PRIVATE PARTNERSHIP PROJECTS: CONCESSIONAIRE PERFORMANCE MEASUREMENT. Journal of Al Azhar University Engineering Sector
- Penelope, B.J., Cowen, B. (1997). The private sector in water and sanitation–how to get started. Washington: Bank, p. 89-92.
- Qiao, L. (2001). Framework for critical success factors of BOT projects in China. The Journal of Structured Finance, 7(1). p. 53-61.
- Sachs, T., Tiong, R.. & Qing, S. (2007). Analysis of political risks and opportunities in public private partnerships (PPP) in China and selected Asian countries: Survey results. Chinese Management Studies, 1(2). p. 126-148.
- Salman, A.F., Skibniewski. M.J., & Basha, I. (2007). BOT viability model for large-scale infrastructure projects. Journal of Construction Engineering and Management, 133(1), 50-63.
- Savas, E.S. (2000). Privatization and public-private partnerships. Chatham House New York.
- Sun, J., Wanga, R., Wanga, X., & Pinga. J. (2014). Spatial cluster analysis of bursting pipes in water supply networks. Procedia Engineering , 70,1610 – 1618
- Tang, L., Shen, Q., & Cheng, E.W. (2010). A review of studies on public–private partnership projects in the construction industry. International Journal of Project Management, 28(7), 683-694.
- Tina, R., Patil, S., & Sherekar, S. (2013). Performance Analysis of Naive Bayes and J48 Classification Algorithm for Data Classification
- Wei, Y. (2011). Regulating Municipal Water Supply Concessions. p. 1-0.
- Wen,Y., Huang, W., & Wu, J. (2013). Water Consumption analysis System Based On data Mining, Mechanics and Materials, 241-244, 1093-1097
- Yong Qiu., Ji. Li., Xia, Huang., & Hanchang, Shi. (2018). A Feasible Data-Driven Mining System to Optimize Wastewater Treatment Process Design and Operation
- Yu, I. (2007). Comparable performance measurement system for construction companies. Journal of Management in Engineering, 23(3), 131-139.
- Yuan, J. (2009). Performance objectives selection model in public-private partnership projects based on the perspective of stakeholders. Journal of Management in Engineering.
- Yuan, J. (2011). Developing key performance indicators for public-private partnership projects: questionnaire survey and analysis. Journal of Management in Engineering, 28(3),. 252-264.
- . Zhang, X. (2005). Critical success factors for public–private partnerships in infrastructure development. Journal of construction engineering and managemen.
)