PROSPECTIVE MADM AND SENSITIVITY ANALYSIS OF THE EXPERTS BASED ON CAUSAL LAYERED ANALYSIS (CLA)

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Name and surname of author:

Sarfaraz Hashemkhani Zolfani, Morteza Yazdani, Edmundas Kazimieras Zavadskas, Hamidreza Hasheminasab

Year:

2020

Volume:

23

Issue:

3

Keywords:

Prospective Multiple Attribute Decision Making (PMADM), sensitivity analysis, experts, Causal Layered Analysis (CLA), Best Worst Method (BWM), COmbined COmpromise SOlution (CoCoSo)

JEL clasification:

C91 - Design of Experiments: Laboratory, Individual, Q48 - Energy: Government Policy, Q56 - Environment and Development - Environment and Trade - Sustainability - Environmental Accounts and Accounting - Environmental Equity - Population Growth

DOI (& full text):

https://doi.org/10.15240/tul/001/2020-3-013

Anotation:

Multiple Attribute Decision Making (MADM) methods have been working by real data and qualitative analysis of experts’ ideas. It is really difficult and complicated to find more related experts to a topic which is solving but still there is a bigger challenge which is experts’ backgrounds. In so many cases there are somany experienced experts but their attitudes are very dissimilar and diverse. It can be said that none of their ideas are incorrect but do they have a well-defined perspective to the main subject? Maybe based on so many limitations there is not enough chance to check their consistency rate about an issue but it is possible to make a higher consistency based on a pre-plan. Mostly, only investigators have enough knowledge about a new research because they are defining and illustrating it in different dimensions of the topic. Usually, for solving multi-attribute problems, investigators do not explain and express their exact ideas to the experts because of so many challenges and limitations such as time and other topics.

Section:

Information management