MCDM Assessment of a Healthy and Safe Built Environment According to Sustainable Development Principles: A Practical Neighborhood Approach in Vilnius

Edmundas Kazimieras Zavadskas, Fausto Cavallaro, Valentinas Podvezko, Ieva Ubarte and Arturas Kaklauskas
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Edmundas Kazimieras Zavadskas: Department of Construction Technology and Management, Sauletekis ave.11, Vilnius LT-10223, Lithuania
Fausto Cavallaro: Department of Economics, Management, Society and Institutions (EGSI), University of Molise, Via De Sanctis, Campobasso 86100, Italy
Valentinas Podvezko: Department of Mathematical Statistics, Sauletekis ave.11, Vilnius LT-10223, Lithuania
Ieva Ubarte: Research Institute of Smart Building Technologies, Sauletekis ave.11, Vilnius LT-10223, Lithuania
Arturas Kaklauskas: Department of Construction Economics and Property Management, Sauletekis ave.11, Vilnius LT-10223, Lithuania

Sustainability, 2017, vol. 9, issue 5, 1-30

Abstract: Urbanization has a massive effect on the environment, both locally and globally. With an ever-increasing scale of construction and manufacturing and misuse of energy resources come poorer air quality, growing mortality rates and more rapid climate change. For these reasons, a healthy and safe built environment is ever more in demand. Global debates focus on sustainable development of the built environment; a rational approach to its analysis is multiple criteria decision making (MCDM) methods. Alternative MCDM methods applied to the same problem often produce different results. In the search for a more reliable tool, this study proposes that a system of MCDM methods should be applied to a single problem. This article assesses 21 neighborhoods in Vilnius in the context of a healthy and safe built environment in view of the principles of sustainable development. MCDM methods were used for this purpose: entropy, Criterion Impact LOSs (CILOS) and Integrated Determination of Objective Criteria Weights (IDOCRIW) methods were used to determine the objective weights of the criteria, while expert judgement determined the subjective weights. With the overall weights determined, the Vilnius neighborhoods were assessed through the application of COmplex PRoportional ASsessment (COPRAS), Simple Additive Weighting (SAW), Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) and Evaluation based on Distance from Average Solution (EDAS) methods. The final results were then processed using the rank average method, Borda count and Copeland’s method.

Keywords: healthy and safe built environment; sustainable development; MCDM methods; neighborhoods; Vilnius (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2017
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (21)

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