This paper is motivated by observations on the decision process for prioritizing adaptation options using Multi-criteria decision analysis (MCDA) in Korea. To overcome the drawbacks of MCDA such as weighting and handling uncertainty, this paper formulates the problem of prioritizing climate change adaptation options as a DEA-like model. The decisions on how to assess such adaptation options involve qualitative evaluations that rely on subjective judgements, which results in data uncertainty. We propose a Monte-Carlo simulation-based method to provide robust analysis against the data uncertainty. The proposed method is applied to a case study in which 11 adaptation options in water sector are evaluated. Whereas a conventional deterministic approach that ignores data uncertainty may mislead decision-makers, a stochastic approach provides more reliable information because of its statistical evidence.
Bibliographical noteFunding Information:
This paper partially used the data from the research project, entitled “Promising Adaptation Technologies and Evaluation Framework in Response to Demand from Developing Countries (No. 2016-011)”, which was supported by the Green Technology Center (GTC) and Ministry of Science and ICT of South Korea (MSIT).
This work was supported by the Ministry of Education of the Republic of Korea and the National Research Foundation of Korea (NRF-2017S1A5A2A03067552)
© 2019 KIIE.
- Climate change adaptation
- Data envelopment analysis
- Simulation-based approach
- Technology evaluation
- Uncertain data