The Sustainability of Smart Cities: Improving Evaluation by Combining MCDA and PROMETHEE

Ibrahim Mutambik ()
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Ibrahim Mutambik: Department of Information Science, College of Humanities and Social Sciences, King Saud University, Riyadh P.O. Box 11451, Saudi Arabia

Land, 2024, vol. 13, issue 9, 1-28

Abstract: Evaluating the sustainability of smart cities is crucial for promoting sustainable development. Traditionally, this evaluation process has traditionally been carried out using the Multi-Criteria Decision Analysis approach. However, this approach relies upon a unified input dataset, which can lead to oversimplification, particularly in the context of sustainability. Further, the Multi-Criteria Decision Analysis approach does not take account of how sustainability evolves over time. This paper introduces a time-based sustainability assessment technique that combines the Multi-Criteria Decision Analysis approach with an established method of assessing performance variability, recognized as the Preference Ranking Organization Method for Enrichment Evaluations. The resulting framework, called Enhanced Preference Ranking Organization Method for Enrichment Evaluations, was used to evaluate the sustainability of smart cities and communities across the G20 countries, based on aggregated data, individual sustainability dimensions, and scenarios. The results demonstrate the effectiveness, relevance, and applicability of the new approach, which provides a significant advance in the field of sustainable city evaluation by facilitating multi-period evaluations of sustainable cities and enabling multi-perspective evaluations of sustainability assessments.

Keywords: sustainability assessment; smart cities; multi-criteria decision analysis (MCDA); enhanced PROMETHEE; G20 countries (search for similar items in EconPapers)
JEL-codes: Q15 Q2 Q24 Q28 Q5 R14 R52 (search for similar items in EconPapers)
Date: 2024
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)

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