Název:	Sustainable construction supplier selection by a multiple criteria decision-making method with hesitant linguistic information
Autoři:	Liao, Huchang Ren, Ruxue Antucheviciene, Jurgita Šaparauskas, Jonas Al-Barakati, Abdullah
Citace zdrojového dokumentu:	E+M. Ekonomie a Management = Economics and Management. 2020, roč. 23, č. 4, s. 119-136.
Datum vydání:	2020
Nakladatel:	Technická univerzita v Liberci
Typ dokumentu:	článek article
URI:	http://hdl.handle.net/11025/42230
ISSN:	1212-3609 (Print) 2336-5604 (Online)
Klíčová slova:	udržitelný dodavatel;Vícekriteriální analýza variant (VAV);měření vzdálenosti;Stepwise Weight Assessment Ratio Analysis (SWARA);Metoda DNMA (Double Normisation-based Multi-Aggregation)
Klíčová slova v dalším jazyce:	sustainable supplier;Multiple Criteria Decision Making (MCDM);distance measure;Stepwise Weight Assessment Ratio Analysis (SWARA);Double Normalization-based Multi-Aggregation (DNMA) method
Abstrakt v dalším jazyce:	Within the context of resource constraints and ecological environment imbalance, the adoption of green suppliers can help construction enterprises achieve sustainable development and improve their competitiveness. The selection of sustainable construction suppliers is a multi-criteria decision-making problem since multiple factors should be considered. The increasingly complex decision-making environment makes it difficult for evaluators to give accurate evaluation values. In this regard, the hesitant fuzzy linguistic term set is a qualitative evaluation tool to represent the comprehensive linguistic evaluation values of experts by considering the hesitancy behaviors of experts. In this paper, a scientific multi-criteria decision-making model based on the improved Stepwise Weight Assessment Ratio Analysis (SWARA) method and the double normalizationbased multi-aggregation (DNMA) method in the hesitant fuzzy linguistic environment is proposed. A new distance measure is proposed to measure the differences between hesitant fuzzy linguistic term sets with different lengths without changing the original evaluation information of experts. The proposed distance measure is applied to the proposed multi-criteria decision-making model. After improving the calculation steps of the traditional SWARA method, we can determine the weights of criteria effectively through our proposed model. To verify the applicability of the proposed method, we implement it to select sustainable building suppliers. The effectiveness of the method is verified by sensitivity analysis. We also compare the results obtained by our method and those derived by the Weight Aggregated Sum Product ASsessment (WASPAS) method and the Technique for Order Preference by Similarity to an Ideal Solution (TOPSIS) method. The proposed method have a strong applicability to solve the sustainability-related decision problems given that it can effectively determine the weights of criteria and flexibly meet the needs of decision-makers by adjusting the coefficient.
Práva:	CC BY-NC 4.0
Vyskytuje se v kolekcích:	Číslo 4(2020) Číslo 4(2020)

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