Abstract
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.
Original language | English |
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Pages (from-to) | 260-273 |
Number of pages | 14 |
Journal | Industrial Engineering and Management Systems |
Volume | 18 |
Issue number | 2 |
DOIs | |
State | Published - 2019 |
Bibliographical note
Funding 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).
Funding Information:
This work was supported by the Ministry of Education of the Republic of Korea and the National Research Foundation of Korea (NRF-2017S1A5A2A03067552)
Publisher Copyright:
© 2019 KIIE.
Keywords
- Climate change adaptation
- Data envelopment analysis
- Simulation-based approach
- Technology evaluation
- Uncertain data