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


Informační management

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

“Multiple Attribute Decision Making (MADM)” is an expert based field which is working based on real data and experts’ opinions. So many studies have been doing based on MADM methods which they usually use qualitative data based on experts’ ideas. Decisions based on the experts’ opinion shall be carefully designed to cope the real problems uncertainty. This uncertainty will be even more intricate if combining the problem with the ambiguity of the future study. Prospective MADM is a future based type of MADM field which is concentrating on decision making and policy making about the future. Prospective MADM (PMADM) can have both explorative and descriptive paradigms in the studies but it will more useful to be applied for strategic planning. In this regard, experts’ role would be even more challenging because one/some possible future/futures will be partially designed based on their opinions. Future and prediction always complicates the decision environment, especially methodologies founded on experts’ judgement. Considering experts’ preferences, attitude, and background, they may be a major source of inaccurate results. Causal Layered Analysis (CLA) is well-known “Futures Studies” method which is qualitative and usually is supporting other methods such as “Backcasting” and “Scenario Planning”. CLA has a deep point of view to the subjects to support a future with all those changes which are necessary for the main goal/goals. In this study, this idea will be proposed that CLA can be added to PMADM outline to decrease the risk of unsuitable decisions for the future and for this aim a case study about energy and CO2 consumption in policy making level proposed and a hybrid MADM method based on BWM-CoCoSo applied in the PMADM outline for the procedure.
Jméno a příjmení autora:

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

Rok:
2020
Ročník:
23
Číslo:
3
Klíčová slova:
Prospective Multiple Attribute Decision Making (PMADM), sensitivity analysis, experts, Causal Layered Analysis (CLA), Best Worst Method (BWM), COmbined COmpromise SOlution (CoCoSo)
DOI (& full text):
Anotace:
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…více
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.
Sekce:
Informační management

?
NAPOVEDA
povinné
Jazyk