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http://hdl.handle.net/10397/69927
Title: | Managing social risks at the housing demolition stage of urban redevelopment projects : a stakeholder-oriented study using social network analysis | Authors: | Yu, T Shen, GQP Shi, Q Lai, XD Li, CZD Xu, KX |
Issue Date: | Aug-2017 | Source: | International journal of project management, Aug. 2017, v. 35, no. 6, p. 925-941 | Abstract: | In China, the social risks associated with housing demolition increasingly challenge the success of urban redevelopment projects. In practice, these risks are interacting and are associated with various stakeholders. Previous studies have largely focused on risk identification and evaluation without giving sufficient consideration to stakeholders and their linkages with risks. Therefore, we used social network analysis to investigate social risks related to housing demolition, from a stakeholder perspective. Stakeholder-associated risks and their interrelations were investigated based on a literature analysis and interviews with key stakeholders. Using a network analysis we identified critical risks and their corresponding stakeholders. Social security schemes, efficient financial management, multi-dimensional impact assessments, policy analyses and adherence to laws, and public participation were proposed to mitigate risks. The effectiveness of these solutions was quantified based on a network simulation. This study contributes to the body of knowledge on social risk management via linking social risks with stakeholders. | Keywords: | Housing demolition Social risk Social network analysis Stakeholder perspective Urban redevelopment project |
Publisher: | Pergamon Press | Journal: | International journal of project management | ISSN: | 0263-7863 | EISSN: | 1873-4634 | DOI: | 10.1016/j.ijproman.2017.04.004 | Rights: | © 2017 Published by Elsevier Ltd. © 2017. This manuscript version is made available under the CC-BY-NC-ND 4.0 license http://creativecommons.org/licenses/by-nc-nd/4.0/. |
Appears in Collections: | Journal/Magazine Article |
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Yu_Tao_2017a.pdf | Pre-Published version | 1.34 MB | Adobe PDF | View/Open |
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