Abstract
Multiple criteria decision analysis (MCDA) methods have shown advantages in supporting decision-making with problems that confront conflicting objectives. However, current applications to complex environmental problems featuring the dynamic social sphere, particularly problems involving cultural heritage and nature, have yet to substantially reflect this. The dynamic social sphere reflects the demand for scenario forecasting in decision-making support. This knowledge gap has not been addressed sufficiently in MCDA research. A participatory MCDA method is hence proposed as a merger with Contingent Valuation Method (CVM) as the scenario forecasting. The MCDA is then carried out to tackle a complex environmental problem caused by traditional food production in a historic town, Daxi in Taiwan. The result reveals a remarkable willingness to support this issue of a historically significant industry causing detriment to environment (with WTP estimate of 128,700,000 USD from the public) and suggests a plan that applies multiple policy instruments rather than following a potentially adverse polluter-pays principle. This manifests the authors’ argument that recognition of heritage significance has dramatically affected selection of policy instruments and provides a critical recommendation to the local government which has struggled to find solutions. The proposed MCDA also highlights its participatory aspect for addressing issues involving cultural heritage, supported by several key steps, in particular the intervention-impact value tree building, the scenario forecasting and the sensitivity analysis.
Highlights
Multiple criteria decision analysis (MCDA) has been developed rapidly over the past quarter century with a variety of theories and models
Our research focuses on how to employ economic valuation method as scenario forecasting, which involves both of these unknowns and how to integrate the scenario forecasting approach into a MCDA
The willingness to pay (WTP) estimate represents the amount of money the public allows the government to spend, supporting cultural heritage to deal with pollution
Summary
Multiple criteria decision analysis (MCDA) has been developed rapidly over the past quarter century with a variety of theories and models. As there emerge more and more complex environmental problems featuring dynamic characteristics, namely the unknown responses of society and policy recipients, towards the implementation of policy [3], without some proper adaptions it appears impractical to employ MCDA in these cases. Unlike ‘static’ problems that dominate existing MCDA literature [4,5]; such as ranking sites, plans and products with the assessment of criteria based on known conditions of facts or of something happened (e.g., cost, size, age, distance, functionality and accessibility, etc.); dynamic problems usually involve policy instruments that need to be assessed (i.e., scoring) based on future outcomes (what we refer to as the scenarios of this research) to be logically forecasted and agreed before the policy instruments are chosen and implemented. How to apply MCDA to dynamic problems with scenario forecasting has yet to be demonstrated in the real world, which reveals a significant knowledge gap and is the focus of this research
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
