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Sustainability and risk assessment of data center locations under a fuzzy environment.

Authors :
Erdem, Mehmet
Özdemir, Akın
Source :
Journal of Cleaner Production. Apr2024, Vol. 450, pN.PAG-N.PAG. 1p.
Publication Year :
2024

Abstract

In the age of digitalization, data centers are critical facilities that help people and businesses in many sectors. Data centers, like other assets requiring high investment, face several risks during their operation. Also, data centers seek sustainable sources to boost their operations when selecting the most appropriate location. Therefore, the location of a data center is chosen based on sustainability and risk assessment. To the best of our knowledge, no study has been conducted for data center risk evaluation with environmental and sustainability assessment. This paper evaluates the eight main criteria and the forty-five sub-criteria for selecting the most appropriate location for the data center when considering the fifty different economies in different business regions. For this particular purpose, the continuous intuitionistic fuzzy sets (CIFS)-based analytical hierarchy process (AHP) is presented to define the weights of each criterion and sub-criterion. Then, the CIFS-based technique for order of preference by similarity to the ideal solution (TOPSIS) is developed to rank the fifty economies integrated with the weights from the CIFS-based AHP. Moreover, eight different scenarios were conducted, and comparison studies were presented. Finally, Denmark, Switzerland, and The Netherlands are the top three selections based on the criteria. [Display omitted] • Fuzzy multi-criteria methods are developed to evaluate data center locations. • Natural, energy, and infrastructure risks are the top three pillars. • Economies are ranked based on the eight scenarios with sustainability and risks. • Denmark tops the charts with the highest score associated with fifty economies. • Based on each income level, Denmark, Brazil, and Tunisia are suitable locations. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
09596526
Volume :
450
Database :
Academic Search Index
Journal :
Journal of Cleaner Production
Publication Type :
Academic Journal
Accession number :
176500134
Full Text :
https://doi.org/10.1016/j.jclepro.2024.141982