بررسی کارکرد تحلیل شبکه اجتماعی در مدیریت ریسک با رویکرد ذینفعان (پروژههای مترو تهران)
محورهای موضوعی : مطالعات مدیریت شهریهانی اربابی 1 , ستاره ولی نواز 2 , محمد حسین صبحیه 3
1 - استادیار، هیات علمی دانشگاه تربیت مدرس، گروه مدیریت پروژه و ساخت (مسئول مکاتبات)
2 - دانشآموخته کارشناسی ارشد مدیریت پروژه و ساخت، دانشگاه نربیت مدرس setare.valinavaz@gmail.com
3 - دانشیار، هیات علمی دانشگاه تربیت مدرس، گروه مدیریت پروژه و ساخت sobhiyah@modares.ac.ir
کلید واژه: مدیریت ریسک, ذینفعان, تحلیل شبکه اجتماعی, پروژه های مترو تهران,
چکیده مقاله :
مقدمه و هدف پژوهش: پروژههای مترو، شرایط پیچیده ای دارند که منجر به افزایش عدمقطعیت در آنها می شود. شرایط غیرقابلپیش بینی پروژههای زیرزمینی، اندازه بزرگ پروژه، حجم عظیم سرمایهگذاری، زمان طولانی، ذینفعان متعدد و روشهای ساخت پیچیده، وجود ریسکهای بالقوه را در این پروژه ها آشکار می سازد. با توجه به ذینفعان مختلفی که درگیر پروژه های مترو هستند، الگوها و روابط اجتماعی این ذی نفعان، پدیده مدیریت ریسک را در این پروژه ها بیش از پیش پیچیده می سازد. با توجه به خلا دانشی موجود در این زمینه، محققان با اتخاذ رویکرد شبکه های اجتماعی، به تحلیل ریسکهای ذینفعان پروژه بهعنوان عناصری بههم پیوسته که دارای روابط علت و معلولی هستند، پرداخته اند. هدف از پژوهش حاضر، یافتن ریسکهای بحرانی ذینفعان به روش تحلیل شبکه اجتماعی در مدیریت ریسک ذینفعان پروژههای مترو تهران است. روش پژوهش: پژوهش حاضر از نوع کیفی و با استراتژی مصاحبه میباشد. پس از جمع آوری دادهها توسط مصاحبههای نیمهساختاریافته، از 30 ذینفع در شش دسته، با استفاده از نرمافزار تحلیل شبکههای اجتماعی، به تحلیل دادهها پرداخته شد و شبکه ریسک های ذینفعان ترسیم شد. یافتهها: ریسکهای انسانیمدیریتی، برنامهریزی، مالی اقتصادی، قانونی و ریسک تاخیرات ساخت بهعنوان ریسکهای کلیدی شناخته شدند. نتیجهگیری: با توجه به یافتههای بهدست آمده، چنین نتیجهگیری میشود که همیشه ریسکهای مالی و اقتصادی، در اولویت ریسکهای پروژهها نیستند و باید به ریسکهای انسانی و مدیریتی، در کنار دیگر ریسکها توجه ویژهای نمود.
Introduction & Objective: Metro construction projects are typically complicated and associated with large uncertainties. Underground construction projects face characteristics like underground situations, the large size, large amount of funding, various stakeholders, long project duration, and complicated construction techniques. As various stakeholders are involved in metro projects, the interaction among stakeholders lead to complicated risk management process in these type of projects. Therefore, we used social network analysis to investigate social risks related to metro construction projects, from a stakeholder perspective. Method: Using qualitative research approach and interview strategy, we gathered the data from 30 stakeholders that classified in six stakeholder groups. The data were analyzed using social network analysis seawares and the social network of stakeholder’s risks were depicted. Results: Human-management, planning, financial-economic, legal, and project delays are the most critical risks in metro projects. Conclusion: Based on the findings, it is concluded that financial and economic risks are not always prioritized over project risks, and special attention should be paid to human and managerial risks, along with other risks.
_||_
Allan, N., & Yin, Y. (2010). Development of a methodology for understanding the potency of risk connectivity. Journal of Management in Engineering, 27(2), 75-79.
Cantarelli, C. C., Flybjerg, B., Molin, E. J., & Van Wee, B. (2013). Cost overruns in large-scale transportation infrastructure projects: Explanations and their theoretical embeddedness. arXiv preprint arXiv:1307.2176.
Carrington, P. J., Scott, J., & Wasserman, S. (2005). Models and methods in social network analysis (Vol. 28): Cambridge university press.
Chapman, R. J. (2001). The controlling influences on effective risk identification and assessment for construction design management. International journal of project management, 19(3), 147-160.
Chinowsky, P., Diekmann, J., & Galotti, V. (2008). Social network model of construction. Journal of Construction Engineering and Management, 134(10), 804-812.
Chinyio, E., & Olomolaiye, P. (2010). Construction stakeholder management. Chennai, India: Wiley-Blackwell
Choi, H.-H., Cho, H.-N., & Seo, J.-W. (2004). Risk assessment methodology for underground construction projects. Journal of Construction Engineering and Management, 130(2), 258-272.
Ding, L., Yu, H., Li, H., Zhou, C., Wu, X., & Yu, M. (2012). Safety risk identification system for metro construction on the basis of construction drawings. Automation in construction, 27, 120-137.
Eskesen, S. D., Tengborg, P., Kampmann, J., & Veicherts, T. H. (2004). Guidelines for tunnelling risk management: international tunnelling association, working group No. 2. Tunnelling and Underground Space Technology, 19(3), 217-237.
Ghosh, S., & Jintanapakanont, J. (2004). Identifying and assessing the critical risk factors in an underground rail project in Thailand: a factor analysis approach. International journal of project management, 22(8), 633-643.
Ghosh, S., & Jintanapakanont, J. (2004). Identifying and assessing the critical risk factors in an underground rail project in Thailand: a factor analysis approach. International journal of project management(22), 633-643.
Glickman, T. S., & Khamooshi, H. (2005). Using hazard networks to determine risk reduction strategies. Journal of the Operational Research Society, 56(11), 1265-1272.
Hanna, A. S., Thomas, G., & Swanson, J. R. (2013). Construction risk identification and allocation: Cooperative approach. Journal of Construction Engineering and Management, 139(9), 1098-1107.
Ka Yan Mok , G. Q. S., Jing Yang. (2015). Stakeholder management studies in mega construction projects: A review and future directions. International journal of project management.
Li, M., Yu, H., Jin, H., & Liu, P. (2018). Methodologies of safety risk control for China’s metro construction based on BIM. Safety science, 110, 418-426.
Mok, K. Y., Shen, G. Q., & Yang, J. (2015). Stakeholder management studies in mega construction projects: A review and future directions. International journal of project management, 33(2), 446-457.
Nouroozi, a.-H., Tohidi, M., & Sardorrod, J. (2017). Project risk management in civil prijects usig risk breakdown structure in Metro stations. Paper presented at the 2nd national conference in applied researches in structural engineering and construction management.
Park, B. I., Chidlow, A., & Choi, J. (2014). Corporate social responsibility: Stakeholders influence on MNEs’ activities. International Business Review, 23(5), 966-980.
Pirhadi-Tavandashti, M. (2013). Identification and analysis of Tehran Metro Risk Projects. (Master), Shahid Beheshti University, Tehran.
Pirouz, H. (2016). Project risk evaluation using automated excavation system with probablity-imapct matrix. (Master), Islamic Azad University, Ahwaz.
PMI. (2017). A guide to the project managment body of knowledge(PMBOK guide) (Vol. sixth Edition). Newtown Square, Pennsylvania: Project Management Institute, Inc.
Prum, D. A., & Del Percio, S. (2009). Green building claims: what theories will a plaintiff pursue, who has exposure, and a proposal for risk mitigation. Real Estate Law Journal, 37(4).
Pryke, S., Badi, S., & Bygballe, L. (2017). Editorial for the special issue on social networks in construction. Construction Management and Economics, 35(8-9), 445-454.
Qin, X., Mo, Y., & Jing, L. (2016). Risk perceptions of the life-cycle of green buildings in China. Journal of cleaner production, 126, 148-158.
Reilly, J. (2000). The management process for complex underground and tunneling projects. Tunnelling and Underground Space Technology, 15(1), 31-44.
Ren, H. (1994). Risk lifecycle and risk relationships on construction projects. International journal of project management, 12(2), 68-74.
Robichaud, L. B., & Anantatmula, V. S. (2010). Greening project management practices for sustainable construction. Journal of Management in Engineering, 27(1), 48-57.
Sarkar, D. (2012). Decision tree analysis for project risk mitigation options for underground metro rail project. International Journal of Decision Sciences, Risk and Management, 4(1-2), 25-37.
Sarkar, D. (2015). Application of fuzzy failure mode effect analysis and expected value method for project risk analysis of elevated corridor metro rail projects. International Journal of Decision Sciences, Risk and Management, 6(1), 34-62.
Sousa, R. L., & Einstein, H. H. (2012). Risk analysis during tunnel construction using Bayesian Networks: Porto Metro case study. Tunnelling and Underground Space Technology, 27(1), 86-100.
Taherkhani, F., Mirzaebrahim tehrani, M., & Malmasi, S. (2017). safety risk management based on fuzzy logic at underground projects. Journal of Occupational Hygiene Engineering, 4(3), 49-62. doi:10.21859/johe.4.3.49
Wang, X., Xia, N., Zhang, Z., Wu, C., & Liu, B. (2017). Human safety risks and their interactions in china’s subways: stakeholder perspectives. Journal of Management in Engineering, 33(5), 05017004.
X.W.Zou, P., & LI, J. (2010). Risk Identification and assessment in subway project: case study of Nanjing Subway Line 2. Construction Management and Economics, 28, 1219-1238.
Yang, J., Shen, G. Q., Ho, M., Drew, D. S., & Xue, X. (2011). Stakeholder management in construction: An empirical study to address research gaps in previous studies. International journal of project management, 29(7), 900-910.
Yang, R. J. (11 NOvember 2013). An Investigation analysis in urban development project:Emprical or rationalistic perspectives. International journal of project management.
Yang, R. J., & Zou, P. X. W. (25 December 2013). Stakeholder-Associated Risks and their Interactions in Complex Green Building Projects: A Social Network Model. Building and Environment.
Yang, R. J., Zou, P. X. W., & Wang, J. (18 September 2015). Modelling stakeholder-associated risk networks in green building projects. International journal of project management.
Yu, Q., Ding, L., Zhou, C., & Luo, H. (2014). Analysis of factors influencing safety management for metro construction in China. Accident Analysis & Prevention, 68, 131-138.
Yu, T., Shen, G. Q., Shi, Q., Lai, X., Li, C. Z., & Xu, K. (2017). Managing social risks at the housing demolition stage of urban redevelopment projects: A stakeholder-oriented study using social network analysis. International journal of project management.
Zhou, H.-b., & Zhang, H. (2011). Risk assessment methodology for a deep foundation pit construction project in Shanghai, China. Journal of Construction Engineering and Management, 137(12), 1185-1194.
Zhou, Y., Li, S., Zhou, C., & Luo, H. (2018). Intelligent Approach Based on Random Forest for Safety Risk Prediction of Deep Foundation Pit in Subway Stations. Journal of Computing in Civil Engineering, 33(1), 05018004.