Emission strategy selection for the circular economy-based production investments with the enhanced decision support system

The purpose of this study is to identify appropriate strategies to minimize carbon emission problem with a novel fuzzy decision-making model. First, the missing expert decisions are imputed for selecting the emission strategies of circular economy-based production investments. Secondly, the emission...
Ausführliche Beschreibung

Gespeichert in:

Autor*in:	Niu, Xiaoqin [verfasserIn] Yüksel, Serhat [verfasserIn] Dinçer, Hasan [verfasserIn]

Format:	E-Artikel
Sprache:	Englisch

Erschienen:	2023

Schlagwörter:	Emission reduction Strategy selection Production investments Decision support system

Übergeordnetes Werk:	Enthalten in: Energy - Amsterdam [u.a.] : Elsevier Science, 1976, 274
Übergeordnetes Werk:	volume:274

DOI / URN:	10.1016/j.energy.2023.127446

Katalog-ID:	ELV063122367

Internformat


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520			\|a The purpose of this study is to identify appropriate strategies to minimize carbon emission problem with a novel fuzzy decision-making model. First, the missing expert decisions are imputed for selecting the emission strategies of circular economy-based production investments. Secondly, the emission strategy perspectives of circular economy-based production investments are weighted with multi stepwise weight assessment ratio analysis (M-SWARA) methodology based on bipolar q-rung orthopair fuzzy sets (q-ROFSs). Finally, the industry alternatives are ranked by bipolar q-ROFS the elimination and choice translating reality (ELECTRE). The main novelty of this study is to generate optimal strategies to reduce carbon emissions with a new fuzzy decision-making model. Furthermore, all calculations are also made by using intuitionistic fuzzy sets (IFSs) and Pythagorean fuzzy sets (PFSs) with the aim of making comparative evaluations. It is concluded that the results are quite similar for both weighting the perspectives and ranking the alternatives. Hence, it is understood that the findings of the proposed model are coherent and reliable. It is identified that the best emission strategy is the long-term growth with the global sustainability by the combination of the perspective 1 (globalization) and perspective 4 (environment). It is also determined that textile is the most critical industry to cope with the carbon emission problem. In this context, it is necessary to introduce some legal regulations to prevent the increased trade volume from causing carbon emissions. In this framework, using filters or carbon capture technology will contribute to the solution of this problem. Such applications will create extra costs for businesses. Therefore, it would not be right to leave such applications to the decision of the enterprises. Hence, these applications should be made compulsory by legal regulations.
650		4	\|a Emission reduction
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650		4	\|a Production investments
650		4	\|a Decision support system
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700	1		\|a Dinçer, Hasan \|e verfasserin \|0 (orcid)0000-0002-8072-031X \|4 aut
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publishDate	2023
allfields	10.1016/j.energy.2023.127446 doi (DE-627)ELV063122367 (ELSEVIER)S0360-5442(23)00840-X DE-627 ger DE-627 rda eng 600 VZ 50.70 bkl Niu, Xiaoqin verfasserin aut Emission strategy selection for the circular economy-based production investments with the enhanced decision support system 2023 nicht spezifiziert zzz rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier The purpose of this study is to identify appropriate strategies to minimize carbon emission problem with a novel fuzzy decision-making model. First, the missing expert decisions are imputed for selecting the emission strategies of circular economy-based production investments. Secondly, the emission strategy perspectives of circular economy-based production investments are weighted with multi stepwise weight assessment ratio analysis (M-SWARA) methodology based on bipolar q-rung orthopair fuzzy sets (q-ROFSs). Finally, the industry alternatives are ranked by bipolar q-ROFS the elimination and choice translating reality (ELECTRE). The main novelty of this study is to generate optimal strategies to reduce carbon emissions with a new fuzzy decision-making model. Furthermore, all calculations are also made by using intuitionistic fuzzy sets (IFSs) and Pythagorean fuzzy sets (PFSs) with the aim of making comparative evaluations. It is concluded that the results are quite similar for both weighting the perspectives and ranking the alternatives. Hence, it is understood that the findings of the proposed model are coherent and reliable. It is identified that the best emission strategy is the long-term growth with the global sustainability by the combination of the perspective 1 (globalization) and perspective 4 (environment). It is also determined that textile is the most critical industry to cope with the carbon emission problem. In this context, it is necessary to introduce some legal regulations to prevent the increased trade volume from causing carbon emissions. In this framework, using filters or carbon capture technology will contribute to the solution of this problem. Such applications will create extra costs for businesses. Therefore, it would not be right to leave such applications to the decision of the enterprises. Hence, these applications should be made compulsory by legal regulations. Emission reduction Strategy selection Production investments Decision support system Yüksel, Serhat verfasserin (orcid)0000-0002-9858-1266 aut Dinçer, Hasan verfasserin (orcid)0000-0002-8072-031X aut Enthalten in Energy Amsterdam [u.a.] : Elsevier Science, 1976 274 Online-Ressource (DE-627)320597903 (DE-600)2019804-8 (DE-576)116451815 1873-6785 nnns volume:274 GBV_USEFLAG_U GBV_ELV SYSFLAG_U GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_150 GBV_ILN_151 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_370 GBV_ILN_602 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2034 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2088 GBV_ILN_2106 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2470 GBV_ILN_2507 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4242 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 50.70 Energie: Allgemeines VZ AR 274
spelling	10.1016/j.energy.2023.127446 doi (DE-627)ELV063122367 (ELSEVIER)S0360-5442(23)00840-X DE-627 ger DE-627 rda eng 600 VZ 50.70 bkl Niu, Xiaoqin verfasserin aut Emission strategy selection for the circular economy-based production investments with the enhanced decision support system 2023 nicht spezifiziert zzz rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier The purpose of this study is to identify appropriate strategies to minimize carbon emission problem with a novel fuzzy decision-making model. First, the missing expert decisions are imputed for selecting the emission strategies of circular economy-based production investments. Secondly, the emission strategy perspectives of circular economy-based production investments are weighted with multi stepwise weight assessment ratio analysis (M-SWARA) methodology based on bipolar q-rung orthopair fuzzy sets (q-ROFSs). Finally, the industry alternatives are ranked by bipolar q-ROFS the elimination and choice translating reality (ELECTRE). The main novelty of this study is to generate optimal strategies to reduce carbon emissions with a new fuzzy decision-making model. Furthermore, all calculations are also made by using intuitionistic fuzzy sets (IFSs) and Pythagorean fuzzy sets (PFSs) with the aim of making comparative evaluations. It is concluded that the results are quite similar for both weighting the perspectives and ranking the alternatives. Hence, it is understood that the findings of the proposed model are coherent and reliable. It is identified that the best emission strategy is the long-term growth with the global sustainability by the combination of the perspective 1 (globalization) and perspective 4 (environment). It is also determined that textile is the most critical industry to cope with the carbon emission problem. In this context, it is necessary to introduce some legal regulations to prevent the increased trade volume from causing carbon emissions. In this framework, using filters or carbon capture technology will contribute to the solution of this problem. Such applications will create extra costs for businesses. Therefore, it would not be right to leave such applications to the decision of the enterprises. Hence, these applications should be made compulsory by legal regulations. Emission reduction Strategy selection Production investments Decision support system Yüksel, Serhat verfasserin (orcid)0000-0002-9858-1266 aut Dinçer, Hasan verfasserin (orcid)0000-0002-8072-031X aut Enthalten in Energy Amsterdam [u.a.] : Elsevier Science, 1976 274 Online-Ressource (DE-627)320597903 (DE-600)2019804-8 (DE-576)116451815 1873-6785 nnns volume:274 GBV_USEFLAG_U GBV_ELV SYSFLAG_U GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_150 GBV_ILN_151 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_370 GBV_ILN_602 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2034 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2088 GBV_ILN_2106 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2470 GBV_ILN_2507 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4242 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 50.70 Energie: Allgemeines VZ AR 274
allfields_unstemmed	10.1016/j.energy.2023.127446 doi (DE-627)ELV063122367 (ELSEVIER)S0360-5442(23)00840-X DE-627 ger DE-627 rda eng 600 VZ 50.70 bkl Niu, Xiaoqin verfasserin aut Emission strategy selection for the circular economy-based production investments with the enhanced decision support system 2023 nicht spezifiziert zzz rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier The purpose of this study is to identify appropriate strategies to minimize carbon emission problem with a novel fuzzy decision-making model. First, the missing expert decisions are imputed for selecting the emission strategies of circular economy-based production investments. Secondly, the emission strategy perspectives of circular economy-based production investments are weighted with multi stepwise weight assessment ratio analysis (M-SWARA) methodology based on bipolar q-rung orthopair fuzzy sets (q-ROFSs). Finally, the industry alternatives are ranked by bipolar q-ROFS the elimination and choice translating reality (ELECTRE). The main novelty of this study is to generate optimal strategies to reduce carbon emissions with a new fuzzy decision-making model. Furthermore, all calculations are also made by using intuitionistic fuzzy sets (IFSs) and Pythagorean fuzzy sets (PFSs) with the aim of making comparative evaluations. It is concluded that the results are quite similar for both weighting the perspectives and ranking the alternatives. Hence, it is understood that the findings of the proposed model are coherent and reliable. It is identified that the best emission strategy is the long-term growth with the global sustainability by the combination of the perspective 1 (globalization) and perspective 4 (environment). It is also determined that textile is the most critical industry to cope with the carbon emission problem. In this context, it is necessary to introduce some legal regulations to prevent the increased trade volume from causing carbon emissions. In this framework, using filters or carbon capture technology will contribute to the solution of this problem. Such applications will create extra costs for businesses. Therefore, it would not be right to leave such applications to the decision of the enterprises. Hence, these applications should be made compulsory by legal regulations. Emission reduction Strategy selection Production investments Decision support system Yüksel, Serhat verfasserin (orcid)0000-0002-9858-1266 aut Dinçer, Hasan verfasserin (orcid)0000-0002-8072-031X aut Enthalten in Energy Amsterdam [u.a.] : Elsevier Science, 1976 274 Online-Ressource (DE-627)320597903 (DE-600)2019804-8 (DE-576)116451815 1873-6785 nnns volume:274 GBV_USEFLAG_U GBV_ELV SYSFLAG_U GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_150 GBV_ILN_151 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_370 GBV_ILN_602 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2034 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2088 GBV_ILN_2106 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2470 GBV_ILN_2507 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4242 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 50.70 Energie: Allgemeines VZ AR 274
allfieldsGer	10.1016/j.energy.2023.127446 doi (DE-627)ELV063122367 (ELSEVIER)S0360-5442(23)00840-X DE-627 ger DE-627 rda eng 600 VZ 50.70 bkl Niu, Xiaoqin verfasserin aut Emission strategy selection for the circular economy-based production investments with the enhanced decision support system 2023 nicht spezifiziert zzz rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier The purpose of this study is to identify appropriate strategies to minimize carbon emission problem with a novel fuzzy decision-making model. First, the missing expert decisions are imputed for selecting the emission strategies of circular economy-based production investments. Secondly, the emission strategy perspectives of circular economy-based production investments are weighted with multi stepwise weight assessment ratio analysis (M-SWARA) methodology based on bipolar q-rung orthopair fuzzy sets (q-ROFSs). Finally, the industry alternatives are ranked by bipolar q-ROFS the elimination and choice translating reality (ELECTRE). The main novelty of this study is to generate optimal strategies to reduce carbon emissions with a new fuzzy decision-making model. Furthermore, all calculations are also made by using intuitionistic fuzzy sets (IFSs) and Pythagorean fuzzy sets (PFSs) with the aim of making comparative evaluations. It is concluded that the results are quite similar for both weighting the perspectives and ranking the alternatives. Hence, it is understood that the findings of the proposed model are coherent and reliable. It is identified that the best emission strategy is the long-term growth with the global sustainability by the combination of the perspective 1 (globalization) and perspective 4 (environment). It is also determined that textile is the most critical industry to cope with the carbon emission problem. In this context, it is necessary to introduce some legal regulations to prevent the increased trade volume from causing carbon emissions. In this framework, using filters or carbon capture technology will contribute to the solution of this problem. Such applications will create extra costs for businesses. Therefore, it would not be right to leave such applications to the decision of the enterprises. Hence, these applications should be made compulsory by legal regulations. Emission reduction Strategy selection Production investments Decision support system Yüksel, Serhat verfasserin (orcid)0000-0002-9858-1266 aut Dinçer, Hasan verfasserin (orcid)0000-0002-8072-031X aut Enthalten in Energy Amsterdam [u.a.] : Elsevier Science, 1976 274 Online-Ressource (DE-627)320597903 (DE-600)2019804-8 (DE-576)116451815 1873-6785 nnns volume:274 GBV_USEFLAG_U GBV_ELV SYSFLAG_U GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_150 GBV_ILN_151 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_370 GBV_ILN_602 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2034 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2088 GBV_ILN_2106 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2470 GBV_ILN_2507 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4242 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 50.70 Energie: Allgemeines VZ AR 274
allfieldsSound	10.1016/j.energy.2023.127446 doi (DE-627)ELV063122367 (ELSEVIER)S0360-5442(23)00840-X DE-627 ger DE-627 rda eng 600 VZ 50.70 bkl Niu, Xiaoqin verfasserin aut Emission strategy selection for the circular economy-based production investments with the enhanced decision support system 2023 nicht spezifiziert zzz rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier The purpose of this study is to identify appropriate strategies to minimize carbon emission problem with a novel fuzzy decision-making model. First, the missing expert decisions are imputed for selecting the emission strategies of circular economy-based production investments. Secondly, the emission strategy perspectives of circular economy-based production investments are weighted with multi stepwise weight assessment ratio analysis (M-SWARA) methodology based on bipolar q-rung orthopair fuzzy sets (q-ROFSs). Finally, the industry alternatives are ranked by bipolar q-ROFS the elimination and choice translating reality (ELECTRE). The main novelty of this study is to generate optimal strategies to reduce carbon emissions with a new fuzzy decision-making model. Furthermore, all calculations are also made by using intuitionistic fuzzy sets (IFSs) and Pythagorean fuzzy sets (PFSs) with the aim of making comparative evaluations. It is concluded that the results are quite similar for both weighting the perspectives and ranking the alternatives. Hence, it is understood that the findings of the proposed model are coherent and reliable. It is identified that the best emission strategy is the long-term growth with the global sustainability by the combination of the perspective 1 (globalization) and perspective 4 (environment). It is also determined that textile is the most critical industry to cope with the carbon emission problem. In this context, it is necessary to introduce some legal regulations to prevent the increased trade volume from causing carbon emissions. In this framework, using filters or carbon capture technology will contribute to the solution of this problem. Such applications will create extra costs for businesses. Therefore, it would not be right to leave such applications to the decision of the enterprises. Hence, these applications should be made compulsory by legal regulations. Emission reduction Strategy selection Production investments Decision support system Yüksel, Serhat verfasserin (orcid)0000-0002-9858-1266 aut Dinçer, Hasan verfasserin (orcid)0000-0002-8072-031X aut Enthalten in Energy Amsterdam [u.a.] : Elsevier Science, 1976 274 Online-Ressource (DE-627)320597903 (DE-600)2019804-8 (DE-576)116451815 1873-6785 nnns volume:274 GBV_USEFLAG_U GBV_ELV SYSFLAG_U GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_150 GBV_ILN_151 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_370 GBV_ILN_602 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2034 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2088 GBV_ILN_2106 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2470 GBV_ILN_2507 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4242 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 50.70 Energie: Allgemeines VZ AR 274
language	English
source	Enthalten in Energy 274 volume:274
sourceStr	Enthalten in Energy 274 volume:274
format_phy_str_mv	Article
bklname	Energie: Allgemeines
institution	findex.gbv.de
topic_facet	Emission reduction Strategy selection Production investments Decision support system
dewey-raw	600
isfreeaccess_bool	false
container_title	Energy
authorswithroles_txt_mv	Niu, Xiaoqin @@aut@@ Yüksel, Serhat @@aut@@ Dinçer, Hasan @@aut@@
publishDateDaySort_date	2023-01-01T00:00:00Z
hierarchy_top_id	320597903
dewey-sort	3600
id	ELV063122367
language_de	englisch
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author	Niu, Xiaoqin
spellingShingle	Niu, Xiaoqin ddc 600 bkl 50.70 misc Emission reduction misc Strategy selection misc Production investments misc Decision support system Emission strategy selection for the circular economy-based production investments with the enhanced decision support system
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topic_title	600 VZ 50.70 bkl Emission strategy selection for the circular economy-based production investments with the enhanced decision support system Emission reduction Strategy selection Production investments Decision support system
topic	ddc 600 bkl 50.70 misc Emission reduction misc Strategy selection misc Production investments misc Decision support system
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title	Emission strategy selection for the circular economy-based production investments with the enhanced decision support system
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title_full	Emission strategy selection for the circular economy-based production investments with the enhanced decision support system
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title_sort	emission strategy selection for the circular economy-based production investments with the enhanced decision support system
title_auth	Emission strategy selection for the circular economy-based production investments with the enhanced decision support system
abstract	The purpose of this study is to identify appropriate strategies to minimize carbon emission problem with a novel fuzzy decision-making model. First, the missing expert decisions are imputed for selecting the emission strategies of circular economy-based production investments. Secondly, the emission strategy perspectives of circular economy-based production investments are weighted with multi stepwise weight assessment ratio analysis (M-SWARA) methodology based on bipolar q-rung orthopair fuzzy sets (q-ROFSs). Finally, the industry alternatives are ranked by bipolar q-ROFS the elimination and choice translating reality (ELECTRE). The main novelty of this study is to generate optimal strategies to reduce carbon emissions with a new fuzzy decision-making model. Furthermore, all calculations are also made by using intuitionistic fuzzy sets (IFSs) and Pythagorean fuzzy sets (PFSs) with the aim of making comparative evaluations. It is concluded that the results are quite similar for both weighting the perspectives and ranking the alternatives. Hence, it is understood that the findings of the proposed model are coherent and reliable. It is identified that the best emission strategy is the long-term growth with the global sustainability by the combination of the perspective 1 (globalization) and perspective 4 (environment). It is also determined that textile is the most critical industry to cope with the carbon emission problem. In this context, it is necessary to introduce some legal regulations to prevent the increased trade volume from causing carbon emissions. In this framework, using filters or carbon capture technology will contribute to the solution of this problem. Such applications will create extra costs for businesses. Therefore, it would not be right to leave such applications to the decision of the enterprises. Hence, these applications should be made compulsory by legal regulations.
abstractGer	The purpose of this study is to identify appropriate strategies to minimize carbon emission problem with a novel fuzzy decision-making model. First, the missing expert decisions are imputed for selecting the emission strategies of circular economy-based production investments. Secondly, the emission strategy perspectives of circular economy-based production investments are weighted with multi stepwise weight assessment ratio analysis (M-SWARA) methodology based on bipolar q-rung orthopair fuzzy sets (q-ROFSs). Finally, the industry alternatives are ranked by bipolar q-ROFS the elimination and choice translating reality (ELECTRE). The main novelty of this study is to generate optimal strategies to reduce carbon emissions with a new fuzzy decision-making model. Furthermore, all calculations are also made by using intuitionistic fuzzy sets (IFSs) and Pythagorean fuzzy sets (PFSs) with the aim of making comparative evaluations. It is concluded that the results are quite similar for both weighting the perspectives and ranking the alternatives. Hence, it is understood that the findings of the proposed model are coherent and reliable. It is identified that the best emission strategy is the long-term growth with the global sustainability by the combination of the perspective 1 (globalization) and perspective 4 (environment). It is also determined that textile is the most critical industry to cope with the carbon emission problem. In this context, it is necessary to introduce some legal regulations to prevent the increased trade volume from causing carbon emissions. In this framework, using filters or carbon capture technology will contribute to the solution of this problem. Such applications will create extra costs for businesses. Therefore, it would not be right to leave such applications to the decision of the enterprises. Hence, these applications should be made compulsory by legal regulations.
abstract_unstemmed	The purpose of this study is to identify appropriate strategies to minimize carbon emission problem with a novel fuzzy decision-making model. First, the missing expert decisions are imputed for selecting the emission strategies of circular economy-based production investments. Secondly, the emission strategy perspectives of circular economy-based production investments are weighted with multi stepwise weight assessment ratio analysis (M-SWARA) methodology based on bipolar q-rung orthopair fuzzy sets (q-ROFSs). Finally, the industry alternatives are ranked by bipolar q-ROFS the elimination and choice translating reality (ELECTRE). The main novelty of this study is to generate optimal strategies to reduce carbon emissions with a new fuzzy decision-making model. Furthermore, all calculations are also made by using intuitionistic fuzzy sets (IFSs) and Pythagorean fuzzy sets (PFSs) with the aim of making comparative evaluations. It is concluded that the results are quite similar for both weighting the perspectives and ranking the alternatives. Hence, it is understood that the findings of the proposed model are coherent and reliable. It is identified that the best emission strategy is the long-term growth with the global sustainability by the combination of the perspective 1 (globalization) and perspective 4 (environment). It is also determined that textile is the most critical industry to cope with the carbon emission problem. In this context, it is necessary to introduce some legal regulations to prevent the increased trade volume from causing carbon emissions. In this framework, using filters or carbon capture technology will contribute to the solution of this problem. Such applications will create extra costs for businesses. Therefore, it would not be right to leave such applications to the decision of the enterprises. Hence, these applications should be made compulsory by legal regulations.
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title_short	Emission strategy selection for the circular economy-based production investments with the enhanced decision support system
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doi_str	10.1016/j.energy.2023.127446
up_date	2024-07-06T19:26:08.968Z
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Emission strategy selection for the circular economy-based production investments with the enhanced decision support system

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