Research on the Dynamic Evolution of Social Risks in Community Renewal Projects: Considering the Coupling Effects of Factors
Publication: Journal of Management in Engineering
Volume 40, Issue 5
Abstract
The social risk of a community renewal project is a macro concept, which is composed of many micro social risk factors. Community renewal projects involve a large number of stakeholder subjects, and the relationship between the subjects is intricate and complex, which leads to a more diversified source of social risk factors behind community renewal projects. There are interactions and interdependence among many factors, and complex interactions form a coupled relationship between the factors. In this paper, an original corpus is constructed based on online and offline data, and 19 risk factors of community renewal projects and the coupling effects of the factors are identified through the grounded theory. The factor weights are solved through the analytic network process (ANP). The dynamic evolution model of social risks is constructed through the system dynamics model based on the factors, the coupling effects of the factors, and the factor weights, so as to simulate the dynamic evolution process of the social risks. The results show that factors such as the management mechanism soundness have larger weights, and in the process of social risks evolution, core factors such as unsound management mechanism will trigger a series of other risk factors, which will increase the overall social risks. This paper identifies the key factors of social risks, clarifies the complex coupling relationship between the factors, provides a dynamic evolution model, reveals the dynamic evolution process of social risks, and provides theoretical basis and countermeasure suggestions for efficiently identifying and controlling the social risks of community renewal projects.
Practical Applications
Community renewal projects involve numerous stakeholders, including the government, enterprises, and residents. These stakeholders interact frequently, creating complex relationships that significantly impact the project. The diverse factors from these stakeholders can lead to significant social risks in community renewal projects, with these factors influencing and interacting with each other. This paper constructs a dynamic evolution model of social risks, which can reveal how social risk factors from diverse entities evolve dynamically. It uncovers the micro-level components behind the macro concept of social risks, helping managers and practitioners clarify the constituent factors of social risks and their dynamic interrelationships. By predicting social risks and their evolution in community renewal projects, this model provides a theoretical basis and feasible suggestions for efficiently identifying, evaluating, analyzing, and controlling social risks. Ultimately, it contributes to enhancing the efficiency and sustainability of community renewal projects.
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Data Availability Statement
Some data, models, or code that support the findings of this study are available from the corresponding author upon reasonable request. These include some data and models used in the process of applying grounded theory, ANP, and system dynamics to construct the social risk evolution model.
Acknowledgments
The authors gratefully acknowledge the financial support by the National Natural Science Foundation of China (No. 72271183) and Tianjin Research Innovation Project for Postgraduate Students (No. 2022BKY123).
References
Cao, Y., and X. Tang. 2022. “Evaluating the effectiveness of community public open space renewal: A case study of the Ruijin community, Shanghai.” Land 11 (4): 476. https://doi.org/10.3390/land11040476.
Cheng, Y. 2014. “An exploration into cost-influencing factors on construction projects.” Int. J. Project Manage. 32 (5): 850–860. https://doi.org/10.1016/j.ijproman.2013.10.003.
Craglia, M., and J. Cullen. 2019. “Do technical improvements lead to real efficiency gains? Disaggregating changes in transport energy intensity.” Energy Policy 134 (Nov): 110991. https://doi.org/10.1016/j.enpol.2019.110991.
Dicks, B. 2014. “Participatory community regeneration: A discussion of risks, accountability and crisis in devolved Wales.” Urban Stud. 51 (5): 959–977. https://doi.org/10.1177/0042098013493023.
Du, T., S. Du, and R. Wang. 2022. “Social factors and residential satisfaction under urban renewal background: A comparative case study in Chongqing, China.” J. Urban Plann. Dev. 148 (4): 05022030. https://doi.org/10.1061/(ASCE)UP.1943-5444.0000869.
Estiri, S. N., A. H. Jalilvand, S. Naderi, M. H. Najafi, and M. Fazeli. 2022. “A low-cost stochastic computing-based fuzzy filtering for image noise reduction.” In Proc., 2022 IEEE 13th IGSC, 1–6. New York: IEEE. https://doi.org/10.1109/IGSC55832.2022.9969358.
Hasan, A. S. M. M., and A. Trianni. 2020. “A review of energy management assessment models for industrial energy efficiency.” Energies 13 (21): 5713. https://doi.org/10.3390/en13215713.
Huang, G., D. Li, X. Zhu, and J. Zhu. 2021. “Influencing factors and their influencing mechanisms on urban resilience in China.” Sustainable Cities Soc. 74 (Nov): 103210. https://doi.org/10.1016/j.scs.2021.103210.
Huang, L., H. Xiao, and J. Xu. 2011. “Urban cultural route: New idea for urban community renewal—Case study on Yuzhong District in Chongqing.” Appl. Mech. Mater. 71–78 (Jul): 1749–1755. https://doi.org/10.4028/www.scientific.net/AMM.71-78.1749.
Islam, M. S., S. R. Mohandes, A. Mahdiyar, A. Fallahpour, and A. O. Olanipekun. 2022. “A coupled genetic programming Monte Carlo simulation–based model for cost overrun prediction of thermal power plant projects.” J. Constr. Eng. Manage. 148 (8): 04022073. https://doi.org/10.1061/(ASCE)CO.1943-7862.0002327.
Kim, S. G. 2010. “Risk performance indexes and measurement systems for mega construction projects.” J. Civ. Eng. Manage. 16 (4): 586–594. https://doi.org/10.3846/jcem.2010.65.
Koc, K., and O. Okudan. 2021. “Assessment of life cycle risks of deconstruction in urban regeneration projects.” J. Civ. Eng. Manage. 147 (10): 04021137. https://doi.org/10.1061/(ASCE)CO.1943-7862.0002161.
Li, D., B. Du, and J. Zhu. 2021. “Evaluating old community renewal based on energy analysis: A case study of Nanjing.” Ecol. Modell. 449 (Jun): 109550. https://doi.org/10.1016/j.ecolmodel.2021.109550.
Li, Y., S. Zhang, and D. Zhu. 2023. “Co-creation of community micro-renewals: Model analysis and case studies in Shanghai, China.” Habitat Int. 142 (Dec): 102951. https://doi.org/10.1016/j.habitatint.2023.102951.
Liu, K., Y. Liu, Y. Kou, X. Yang, and G. Xu. 2024. “Efficiency of risk management for tunnel security of megaprojects construction in China based on system dynamics.” J. Asian Archit. Build. 23 (2): 712–724. https://doi.org/10.1080/13467581.2023.2223696.
Liu, Z., Z. Zhu, H. Wang, and J. Huang. 2016. “Handling social risks in government-driven mega project: An empirical case study from West China.” Int. J. Project Manage. 34 (2): 202–218. https://doi.org/10.1016/j.ijproman.2015.11.003.
Lotfi, R., B. Kargar, A. Gharehbaghi, M. Afshar, M. S. Rajabi, and N. Mardani. 2022. “A data-driven robust optimization for multi-objective renewable energy location by considering risk.” In Environment, development and sustainability, 1–22. Berlin: Springer. https://doi.org/10.1007/s10668-022-02448-7.
Lu, M., Z. Tan, Z. Jin, Y. Wu, and N. Hua. 2023. “Post-unit community resilience assessment and enhancement strategies for risk response.” [In Chinese.] Urban Stud. 30 (8): 116–125.
Mai, Y., J. Wu, Q. Zhang, Q. Liang, Y. Ma, and Z. Liu. 2022. “Confront or comply? Managing social risks in China’s urban renewal projects.” Sustainability 14 (19): 12553. https://doi.org/10.3390/su141912553.
Miao, C., M. Duan, X. Sun, and X. Wu. 2020. “Safety management efficiency of China’s coal enterprises and its influencing factors—Based on the DEA-Tobit two-stage model.” Process Saf. Environ. Prot. 140 (Aug): 79–85. https://doi.org/10.1016/j.psep.2020.04.020.
Morteza, A., M. Sadipour, R. S. Fard, S. Taheri, and A. Ahmadi. 2023a. “A dagging-based deep learning framework for transmission line flexibility assessment.” IET Renewable Power Gener. 17 (5): 1092–1105. https://doi.org/10.1049/rpg2.12663.
Morteza, A., A. A. Yahyaeian, M. Mirzaeibonehkhater, S. Sadeghi, A. Mohaimeni, and S. Taheri. 2023b. “Deep learning hyperparameter optimization: Application to electricity and heat demand prediction for buildings.” Energy Build. 289 (Jun): 113036. https://doi.org/10.1016/j.enbuild.2023.113036.
Naouar, W. B. A. 2016. “Contribution of the management system and the institutional framework to the efficiency of values-based management: Case of the Tunisian food processing industry.” J. Bus. Ethics 135 (4): 787–796. https://doi.org/10.1007/s10551-014-2503-2.
Nasab, A. R., H. Malekitabar, H. Elzarka, A. N. Tak, and K. Ghorab. 2023. “Managing safety risks from overlapping construction activities: A BIM approach.” Buildings 13 (10): 2647. https://doi.org/10.3390/buildings13102647.
Oliveira, A. C. M. D. 2021. “When risky decisions generate externalities.” J. Risk Uncertainty 63 (1): 59–79. https://doi.org/10.1007/s11166-021-09357-6.
Ourang, S. 2022. “Evaluation of inter-organizational coordination of housing services in rural Alaska through social network analysis.” Master’s thesis, Dept. of Civil, Construction, and Environmental, Iowa Statement Univ.
Patel, S., R. Sliuzas, and N. Mathur. 2015. “The risk of impoverishment in urban development-induced displacement and resettlement in Ahmedabad.” Environ. Urbanization 27 (1): 231–256. https://doi.org/10.1177/0956247815569128.
Pierre, J. 2014. “Can urban regimes travel in time and space? Urban regime theory, urban governance theory, and comparative urban politics.” Urban Aff. Rev. 50 (6): 864–889. https://doi.org/10.1177/1078087413518175.
Rajabi, M. S., A. R. Radzi, M. Rezaeiashtiani, A. Famili, M. E. Rashidi, and R. A. Rahman. 2022a. “Key assessment criteria for organizational BIM capabilities: A cross-regional study.” Buildings 12 (7): 1013. https://doi.org/10.3390/buildings12071013.
Rajabi, M. S., M. Rezaeiashtiani, A. R. Radzi, A. Famili, A. Rezaeiashtiani, and R. A. Rahman. 2022b. “Underlying factors and strategies for organizational BIM capabilities: The case of Iran.” Appl. Syst. Innovation 5 (6): 109. https://doi.org/10.3390/asi5060109.
Renzaho, A. M. N., B. Richardson, and C. Strugnell. 2012. “Resident well-being, community connections, and neighbourhood perceptions, pride, and opportunities among disadvantage metropolitan and regional communities: Evidence from the Neighbourhood Renewal Project.” J. Community Psychol. 40 (7): 871–885. https://doi.org/10.1002/jcop.21500.
Siraj, N. B., and A. R. Fayek. 2019. “Risk identification and common risks in construction: Literature review and content analysis.” J. Constr. Eng. Manage. 145 (9): 03119004. https://doi.org/10.1061/(ASCE)CO.1943-7862.0001685.
Wallace, D., and R. Wallace. 2011. “Consequences of massive housing destruction: The New York City fire epidemic.” Build. Res. Inf. 39 (4): 395–411. https://doi.org/10.1080/09613218.2011.567385.
Wang, D., M. Wu, J. Qu, and Y. Fan. 2022a. “How to motivate planners to participate in community micro-renewal: An evolutionary game analysis.” Front. Psychol. 13 (Aug): 943958. https://doi.org/10.3389/fpsyg.2022.943958.
Wang, G., M. Liu, D. Cao, and D. Tan. 2022b. “Identifying high-frequency–low-severity construction safety risks: An empirical study based on official supervision reports in Shanghai.” Eng. Constr. Archit. Manage. 29 (2): 940–960. https://doi.org/10.1108/ECAM-07-2020-0581.
Wang, S., E. H. K. Yung, Y. Yu, and J. Tsou. 2022c. “Right to the city and community facility planning for elderly: The case of urban renewal district in Hong Kong.” Land Use Policy 114 (Mar): 105978. https://doi.org/10.1016/j.landusepol.2022.105978.
Yu, K., Q. Cao, C. Xie, N. Qu, and L. Zhou. 2019. “Analysis of intervention strategies for coal miners’ unsafe behaviors based on analytic network process and system dynamics.” Saf. Sci. 118 (Oct): 145–157. https://doi.org/10.1016/j.ssci.2019.05.002.
Zhang, W., M. Zhang, W. Zhang, Q. Zhou, and X. Zhang. 2020. “What influences the effectiveness of green logistics policies? A grounded theory analysis.” Sci. Total Environ. 714 (Apr): 136731. https://doi.org/10.1016/j.scitotenv.2020.136731.
Zhang, Z., J. Yu, and J. Tian. 2023. “Community participation, social capital cultivation and sustainable community renewal: A case study from Xi’an’s southern suburbs, China.” J. Knowl. Econ. 1–34. https://doi.org/10.1007/s13132-023-01536-x.
Zhou, M., L. Huang, and Z. Shen. 2018. “Community renewal strategy from the perspective of cultural planning a case study on Caohuajie community in Chongqing.” Int. Rev. Spatial Plann. Sustainable Dev. 6 (1): 1–16. https://doi.org/10.14246/irspsd.6A.1_1.
Zhou, Y., F. Lan, and T. Zhou. 2021. “An experience-based mining approach to supporting urban renewal mode decisions under a multi-stakeholder environment in China.” Land Use Policy 106 (Jul): 105428. https://doi.org/10.1016/j.landusepol.2021.105428.
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Published In
Journal of Management in Engineering
Volume 40 • Issue 5 • September 2024
Copyright
© 2024 American Society of Civil Engineers.
History
Received: Nov 6, 2023
Accepted: Mar 28, 2024
Published online: Jul 9, 2024
Published in print: Sep 1, 2024
Discussion open until: Dec 9, 2024
ASCE Technical Topics:
- Business management
- Computer networks
- Computing in civil engineering
- Construction engineering
- Construction management
- Coupling
- Disaster risk management
- Dynamic models
- Engineering fundamentals
- Internet
- Models (by type)
- Practice and Profession
- Project management
- Risk management
- Simulation models
- Social factors
- Structural engineering
- Structural members
- Structural systems
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