Sustainable Construction Supplier Selection by a Multiple Criteria Decision-making Method with Hesitant Linguistic Information
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-makin...
Gespeichert in:
Veröffentlicht in: | E+M ekonomie a management 2020-10, Vol.23 (4), p.119-136 |
---|---|
Hauptverfasser: | , , , , |
Format: | Artikel |
Sprache: | eng |
Schlagworte: | |
Online-Zugang: | Volltext |
Tags: |
Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
|
container_end_page | 136 |
---|---|
container_issue | 4 |
container_start_page | 119 |
container_title | E+M ekonomie a management |
container_volume | 23 |
creator | Liao, Huchang Ren, Ruxue Antucheviciene, Jurgita Šaparauskas, Jonas Al-Barakati, Abdullah |
description | 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 normalization-based 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. |
doi_str_mv | 10.15240/tul/001/2020-4-008 |
format | Article |
fullrecord | <record><control><sourceid>gale_proqu</sourceid><recordid>TN_cdi_proquest_journals_2515780903</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><galeid>A643819710</galeid><sourcerecordid>A643819710</sourcerecordid><originalsourceid>FETCH-LOGICAL-c431t-50a1ff5685c70e8466a59f32849a4f69c6bedca781e5d9bf950de8a595bdaa8f3</originalsourceid><addsrcrecordid>eNpVkUtvEzEQxy0EElHbT8DFEle28TveYxUerZSKQ-Bseb3jxGXjXfwQ6oXPjkM40LE0Y838ZsbWH6F3lNxSyQRZlzqtCaFrRhjpREeIfoVWjHPVSaLEa7SijLKOK9K_RTc5P5FmSivB9Ar93tdcbIh2mABv55hLqq6EOeJ9XZYpQMJ7mOCSGp6xxY91KmE50ykUSMHij-BCbvXuZH-EeMCPUI7ziH-FcsT3kEOxseBdq9SQS3D4Ifo5nex55DV64-2U4eZfvELfP3_6tr3vdl-_PGzvdp0TnJb2D0u9l0pLtyGghVJW9p4zLXorvOqdGmB0dqMpyLEffC_JCLoxchit1Z5fofeXuUuaf1bIxTzNNcW20jBJ5UaTnvBG3V6og53AhPbMkqxrZ4RTcHMEH1r-Tgmuab-hpDV8-K9hqDlEyM3lcDiWfLA155c4v-AuzTkn8GZJ4WTTs6HE_NXSNC1N09KctTSiXTX_A9XVlMw</addsrcrecordid><sourcetype>Aggregation Database</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>2515780903</pqid></control><display><type>article</type><title>Sustainable Construction Supplier Selection by a Multiple Criteria Decision-making Method with Hesitant Linguistic Information</title><source>Elektronische Zeitschriftenbibliothek - Frei zugängliche E-Journals</source><creator>Liao, Huchang ; Ren, Ruxue ; Antucheviciene, Jurgita ; Šaparauskas, Jonas ; Al-Barakati, Abdullah</creator><creatorcontrib>Liao, Huchang ; Ren, Ruxue ; Antucheviciene, Jurgita ; Šaparauskas, Jonas ; Al-Barakati, Abdullah</creatorcontrib><description>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 normalization-based 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.</description><identifier>ISSN: 1212-3609</identifier><identifier>EISSN: 2336-5064</identifier><identifier>DOI: 10.15240/tul/001/2020-4-008</identifier><language>eng</language><publisher>Liberec: Technical University of Liberec</publisher><subject>Competitiveness ; Construction industry ; Decision makers ; Decision making ; Decision making models ; Environmental protection ; Experts ; Fuzzy sets ; Green market ; Imbalance ; Linear programming ; Linguistics ; Manufacturing ; Methods ; Multiple criteria decision making ; Normalization ; Product life cycle ; Reverse logistics ; Sensitivity analysis ; Suppliers ; Supply chain management ; Sustainability ; Sustainable development ; Values</subject><ispartof>E+M ekonomie a management, 2020-10, Vol.23 (4), p.119-136</ispartof><rights>COPYRIGHT 2020 Technical University of Liberec</rights><rights>Copyright Technical University of Liberec 2020</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c431t-50a1ff5685c70e8466a59f32849a4f69c6bedca781e5d9bf950de8a595bdaa8f3</citedby></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>314,780,784,27923,27924</link.rule.ids></links><search><creatorcontrib>Liao, Huchang</creatorcontrib><creatorcontrib>Ren, Ruxue</creatorcontrib><creatorcontrib>Antucheviciene, Jurgita</creatorcontrib><creatorcontrib>Šaparauskas, Jonas</creatorcontrib><creatorcontrib>Al-Barakati, Abdullah</creatorcontrib><title>Sustainable Construction Supplier Selection by a Multiple Criteria Decision-making Method with Hesitant Linguistic Information</title><title>E+M ekonomie a management</title><description>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 normalization-based 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.</description><subject>Competitiveness</subject><subject>Construction industry</subject><subject>Decision makers</subject><subject>Decision making</subject><subject>Decision making models</subject><subject>Environmental protection</subject><subject>Experts</subject><subject>Fuzzy sets</subject><subject>Green market</subject><subject>Imbalance</subject><subject>Linear programming</subject><subject>Linguistics</subject><subject>Manufacturing</subject><subject>Methods</subject><subject>Multiple criteria decision making</subject><subject>Normalization</subject><subject>Product life cycle</subject><subject>Reverse logistics</subject><subject>Sensitivity analysis</subject><subject>Suppliers</subject><subject>Supply chain management</subject><subject>Sustainability</subject><subject>Sustainable development</subject><subject>Values</subject><issn>1212-3609</issn><issn>2336-5064</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2020</creationdate><recordtype>article</recordtype><sourceid>N95</sourceid><sourceid>ABUWG</sourceid><sourceid>AFKRA</sourceid><sourceid>BENPR</sourceid><sourceid>CCPQU</sourceid><sourceid>DWQXO</sourceid><recordid>eNpVkUtvEzEQxy0EElHbT8DFEle28TveYxUerZSKQ-Bseb3jxGXjXfwQ6oXPjkM40LE0Y838ZsbWH6F3lNxSyQRZlzqtCaFrRhjpREeIfoVWjHPVSaLEa7SijLKOK9K_RTc5P5FmSivB9Ar93tdcbIh2mABv55hLqq6EOeJ9XZYpQMJ7mOCSGp6xxY91KmE50ykUSMHij-BCbvXuZH-EeMCPUI7ziH-FcsT3kEOxseBdq9SQS3D4Ifo5nex55DV64-2U4eZfvELfP3_6tr3vdl-_PGzvdp0TnJb2D0u9l0pLtyGghVJW9p4zLXorvOqdGmB0dqMpyLEffC_JCLoxchit1Z5fofeXuUuaf1bIxTzNNcW20jBJ5UaTnvBG3V6og53AhPbMkqxrZ4RTcHMEH1r-Tgmuab-hpDV8-K9hqDlEyM3lcDiWfLA155c4v-AuzTkn8GZJ4WTTs6HE_NXSNC1N09KctTSiXTX_A9XVlMw</recordid><startdate>20201001</startdate><enddate>20201001</enddate><creator>Liao, Huchang</creator><creator>Ren, Ruxue</creator><creator>Antucheviciene, Jurgita</creator><creator>Šaparauskas, Jonas</creator><creator>Al-Barakati, Abdullah</creator><general>Technical University of Liberec</general><scope>AAYXX</scope><scope>CITATION</scope><scope>N95</scope><scope>XI7</scope><scope>0U~</scope><scope>1-H</scope><scope>3V.</scope><scope>4T-</scope><scope>4U-</scope><scope>7WY</scope><scope>7WZ</scope><scope>7XB</scope><scope>87Z</scope><scope>8BJ</scope><scope>8FK</scope><scope>8FL</scope><scope>ABUWG</scope><scope>AFKRA</scope><scope>BENPR</scope><scope>BEZIV</scope><scope>BYOGL</scope><scope>CCPQU</scope><scope>DWQXO</scope><scope>FQK</scope><scope>FRNLG</scope><scope>F~G</scope><scope>JBE</scope><scope>K60</scope><scope>K6~</scope><scope>L.-</scope><scope>L.0</scope><scope>M0C</scope><scope>PQBIZ</scope><scope>PQBZA</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>PRINS</scope><scope>Q9U</scope></search><sort><creationdate>20201001</creationdate><title>Sustainable Construction Supplier Selection by a Multiple Criteria Decision-making Method with Hesitant Linguistic Information</title><author>Liao, Huchang ; Ren, Ruxue ; Antucheviciene, Jurgita ; Šaparauskas, Jonas ; Al-Barakati, Abdullah</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c431t-50a1ff5685c70e8466a59f32849a4f69c6bedca781e5d9bf950de8a595bdaa8f3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2020</creationdate><topic>Competitiveness</topic><topic>Construction industry</topic><topic>Decision makers</topic><topic>Decision making</topic><topic>Decision making models</topic><topic>Environmental protection</topic><topic>Experts</topic><topic>Fuzzy sets</topic><topic>Green market</topic><topic>Imbalance</topic><topic>Linear programming</topic><topic>Linguistics</topic><topic>Manufacturing</topic><topic>Methods</topic><topic>Multiple criteria decision making</topic><topic>Normalization</topic><topic>Product life cycle</topic><topic>Reverse logistics</topic><topic>Sensitivity analysis</topic><topic>Suppliers</topic><topic>Supply chain management</topic><topic>Sustainability</topic><topic>Sustainable development</topic><topic>Values</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Liao, Huchang</creatorcontrib><creatorcontrib>Ren, Ruxue</creatorcontrib><creatorcontrib>Antucheviciene, Jurgita</creatorcontrib><creatorcontrib>Šaparauskas, Jonas</creatorcontrib><creatorcontrib>Al-Barakati, Abdullah</creatorcontrib><collection>CrossRef</collection><collection>Gale Business: Insights</collection><collection>Business Insights: Essentials</collection><collection>Global News & ABI/Inform Professional</collection><collection>Trade PRO</collection><collection>ProQuest Central (Corporate)</collection><collection>Docstoc</collection><collection>University Readers</collection><collection>ABI/INFORM Collection</collection><collection>ABI/INFORM Global (PDF only)</collection><collection>ProQuest Central (purchase pre-March 2016)</collection><collection>ABI/INFORM Global (Alumni Edition)</collection><collection>International Bibliography of the Social Sciences (IBSS)</collection><collection>ProQuest Central (Alumni) (purchase pre-March 2016)</collection><collection>ABI/INFORM Collection (Alumni Edition)</collection><collection>ProQuest Central (Alumni Edition)</collection><collection>ProQuest Central UK/Ireland</collection><collection>ProQuest Central</collection><collection>Business Premium Collection</collection><collection>East Europe, Central Europe Database</collection><collection>ProQuest One Community College</collection><collection>ProQuest Central Korea</collection><collection>International Bibliography of the Social Sciences</collection><collection>Business Premium Collection (Alumni)</collection><collection>ABI/INFORM Global (Corporate)</collection><collection>International Bibliography of the Social Sciences</collection><collection>ProQuest Business Collection (Alumni Edition)</collection><collection>ProQuest Business Collection</collection><collection>ABI/INFORM Professional Advanced</collection><collection>ABI/INFORM Professional Standard</collection><collection>ABI/INFORM Global</collection><collection>ProQuest One Business</collection><collection>ProQuest One Business (Alumni)</collection><collection>ProQuest One Academic Eastern Edition (DO NOT USE)</collection><collection>ProQuest One Academic</collection><collection>ProQuest One Academic UKI Edition</collection><collection>ProQuest Central China</collection><collection>ProQuest Central Basic</collection><jtitle>E+M ekonomie a management</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Liao, Huchang</au><au>Ren, Ruxue</au><au>Antucheviciene, Jurgita</au><au>Šaparauskas, Jonas</au><au>Al-Barakati, Abdullah</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Sustainable Construction Supplier Selection by a Multiple Criteria Decision-making Method with Hesitant Linguistic Information</atitle><jtitle>E+M ekonomie a management</jtitle><date>2020-10-01</date><risdate>2020</risdate><volume>23</volume><issue>4</issue><spage>119</spage><epage>136</epage><pages>119-136</pages><issn>1212-3609</issn><eissn>2336-5064</eissn><abstract>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 normalization-based 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.</abstract><cop>Liberec</cop><pub>Technical University of Liberec</pub><doi>10.15240/tul/001/2020-4-008</doi><tpages>18</tpages><oa>free_for_read</oa></addata></record> |
fulltext | fulltext |
identifier | ISSN: 1212-3609 |
ispartof | E+M ekonomie a management, 2020-10, Vol.23 (4), p.119-136 |
issn | 1212-3609 2336-5064 |
language | eng |
recordid | cdi_proquest_journals_2515780903 |
source | Elektronische Zeitschriftenbibliothek - Frei zugängliche E-Journals |
subjects | Competitiveness Construction industry Decision makers Decision making Decision making models Environmental protection Experts Fuzzy sets Green market Imbalance Linear programming Linguistics Manufacturing Methods Multiple criteria decision making Normalization Product life cycle Reverse logistics Sensitivity analysis Suppliers Supply chain management Sustainability Sustainable development Values |
title | Sustainable Construction Supplier Selection by a Multiple Criteria Decision-making Method with Hesitant Linguistic Information |
url | https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-01-08T17%3A38%3A10IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-gale_proqu&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=Sustainable%20Construction%20Supplier%20Selection%20by%20a%20Multiple%20Criteria%20Decision-making%20Method%20with%20Hesitant%20Linguistic%20Information&rft.jtitle=E+M%20ekonomie%20a%20management&rft.au=Liao,%20Huchang&rft.date=2020-10-01&rft.volume=23&rft.issue=4&rft.spage=119&rft.epage=136&rft.pages=119-136&rft.issn=1212-3609&rft.eissn=2336-5064&rft_id=info:doi/10.15240/tul/001/2020-4-008&rft_dat=%3Cgale_proqu%3EA643819710%3C/gale_proqu%3E%3Curl%3E%3C/url%3E&disable_directlink=true&sfx.directlink=off&sfx.report_link=0&rft_id=info:oai/&rft_pqid=2515780903&rft_id=info:pmid/&rft_galeid=A643819710&rfr_iscdi=true |