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System dynamic simulation: A new method in social impact assessment (SIA)
Institution:1. Agricultural Extension and Education, Shiraz University, Iran;2. Creative Industries Faculty, School of Design, Queensland University of Technology, Australia;1. Global Sustainability Institute, Anglia Ruskin University, Cambridge, UK;2. School of Water, Energy & Environment, Cranfield University, Cranfield, UK;3. Biodiversity Conservation Laboratory, Department of Environment, University of the Aegean, 81100 Mytilene, Lesbos Island, Greece;1. School for Resource and Environmental Studies, Dalhousie University, Halifax, NS B3H 4R2, Canada;2. Department of Resource Economics and Environmental Sociology, University of Alberta, Edmonton, AB T6G 2H1, Canada;3. School of Information Management, Dalhousie University, Halifax, NS B3H 4R2, Canada;4. Department of History, Dalhousie University, Halifax, NS B3H 4R2, Canada
Abstract:Many complex social questions are difficult to address adequately with conventional methods and techniques, due to the complicated dynamics, and hard to quantify social processes. Despite these difficulties researchers and practitioners have attempted to use conventional methods not only in evaluative modes but also in predictive modes to inform decision making. The effectiveness of SIAs would be increased if they were used to support the project design processes. This requires deliberate use of lessons from retrospective assessments to inform predictive assessments. Social simulations may be a useful tool for developing a predictive SIA method. There have been limited attempts to develop computer simulations that allow social impacts to be explored and understood before implementing development projects. In light of this argument, this paper aims to introduce system dynamic (SD) simulation as a new predictive SIA method in large development projects. We propose the potential value of the SD approach to simulate social impacts of development projects. We use data from the SIA of Gareh-Bygone floodwater spreading project to illustrate the potential of SD simulation in SIA. It was concluded that in comparison to traditional SIA methods SD simulation can integrate quantitative and qualitative inputs from different sources and methods and provides a more effective and dynamic assessment of social impacts for development projects. We recommend future research to investigate the full potential of SD in SIA in comparing different situations and scenarios.
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