A Novel Methodology for Prioritizing Zero-Carbon Measures for Sustainable Transport

Abstract Achieving a zero-carbon city requires a long-term strategic perspective. Transport emissions are a major source of carbon emissions, and cities grapple with reducing carbon emissions, and improving the air quality for their citizens. London's new transport strategy document, called Mayor's Transport Strategy 2018, aims to achieve a zero-carbon city by 2050 and set out many actions to facilitate this transition. However, London needs a prioritisation framework which would take into account the financial, environmental and social impacts of these actions. Considering the uncertainties around these actions, which has been now significantly more crucial during the COVID-19 pandemic, this study proposes a novel extension of Best-Worst Method (BWM) and extension of the TODIM (an acronym in Portuguese for Iterative Multi-Criteria Decision Making (MCDM)) method using D numbers. This TODIM-D based fuzzy MCDM approach provides a prioritisation framework for the actions associated with zero-carbon city policies set out in London's strategy document. According to the results of the proposed method, “introducing zero-emission zones” should be selected as the first initiative to implement. The prioritization of this initiative allows London to achieve a zero-carbon transport by having the greatest impact on the modal shift from cars to sustainable mobility modes with a lower operational and implementation cost as well as having greater public support. The proposed method used in this study can be transferred to other cities which aim to achieve a zero-carbon transport.

[1]  Peide Liu,et al.  An Extended TODIM Method for Group Decision Making with the Interval Intuitionistic Fuzzy Sets , 2015 .

[2]  Zeshui Xu,et al.  Pythagorean fuzzy VIKOR approaches based on TODIM for evaluating internet banking website quality of Ghanaian banking industry , 2019, Appl. Soft Comput..

[3]  Mohsen Sadeghi-Dastaki,et al.  A fully fuzzy best-worst multi attribute decision making method with triangular fuzzy number: A case study of maintenance assessment in the hospitals , 2020, Appl. Soft Comput..

[4]  Herzegovina,et al.  The selection of a location for potential roundabout construction – A case study of Doboj , 2020 .

[5]  Dragan Pamučar,et al.  A Sensitivity analysis in MCDM problems: A statistical approach , 2018, Decision Making: Applications in Management and Engineering.

[6]  Marko Radovanović,et al.  A HYBRID LBWA - IR-MAIRCA MULTI-CRITERIA DECISION-MAKING MODEL FOR DETERMINATION OF CONSTRUCTIVE ELEMENTS OF WEAPONS , 2020 .

[7]  Jiu-Ying Dong,et al.  Fuzzy best-worst method based on triangular fuzzy numbers for multi-criteria decision-making , 2021, Inf. Sci..

[8]  Hu-Chen Liu,et al.  A new integrated MCDM model for sustainable supplier selection under interval-valued intuitionistic uncertain linguistic environment , 2019, Inf. Sci..

[9]  Md. Abdul Moktadir,et al.  An innovative decision-making framework for evaluating transportation service providers based on sustainable criteria , 2020, Int. J. Prod. Res..

[10]  Krishnarti De,et al.  A green public transportation system using E-buses: A technical and commercial feasibility study , 2019, Sustainable Cities and Society.

[11]  Ming Li,et al.  Evaluating community question-answering websites using interval-valued intuitionistic fuzzy DANP and TODIM methods , 2020, Appl. Soft Comput..

[12]  Kieran P. Donaghy,et al.  Impacts and implications of climatic extremes for resilience planning of transportation energy: A case study of New York city , 2018 .

[13]  Arthur P. Dempster,et al.  Upper and Lower Probabilities Induced by a Multivalued Mapping , 1967, Classic Works of the Dempster-Shafer Theory of Belief Functions.

[14]  Zhiliang Ren,et al.  A Hesitant Fuzzy Linguistic TODIM Method Based on a Score Function , 2015, Int. J. Comput. Intell. Syst..

[15]  Miles Tight,et al.  Personal Transport Emissions within London: Exploring Policy Scenarios and Carbon Reductions Up to 2050 , 2011 .

[16]  Fatih Ecer,et al.  PRIORITIZING THE WEIGHTS OF THE EVALUATION CRITERIA UNDER FUZZINESS: THE FUZZY FULL CONSISTENCY METHOD – FUCOM-F , 2020 .

[17]  Jindong Qin,et al.  Interval Type-2 Fuzzy Group Decision Making by Integrating Improved Best Worst Method with COPRAS for Emergency Material Supplier Selection , 2019 .

[18]  Yu-Han Huang,et al.  TODIM method for Pythagorean 2-tuple linguistic multiple attribute decision making , 2018, J. Intell. Fuzzy Syst..

[19]  Hannan Amoozad Mahdiraji,et al.  A hybrid fuzzy BWM-COPRAS method for analyzing key factors of sustainable architecture , 2018 .

[20]  Hong-yu Zhang,et al.  Multi-Criteria Decision-Making Method Based on Distance Measure and Choquet Integral for Linguistic Z-Numbers , 2017, Cognitive Computation.

[21]  Yucel R. Kahraman,et al.  Robust Sensitivity Analysis for Multi-Attribute Deterministic Hierarchical Value Models , 2012 .

[22]  Yanping Jiang,et al.  An I-TODIM method for multi-attribute decision making with interval numbers , 2017, Soft Comput..

[23]  Renato A. Krohling,et al.  Combining prospect theory and fuzzy numbers to multi-criteria decision making , 2012, Expert Syst. Appl..

[24]  Elizabeth Chang,et al.  ZBWM: The Z-number extension of Best Worst Method and its application for supplier development , 2018, Expert Syst. Appl..

[25]  Sen Guo,et al.  Fuzzy best-worst multi-criteria decision-making method and its applications , 2017, Knowl. Based Syst..

[26]  Zeshui Xu,et al.  The TODIM analysis approach based on novel measured functions under hesitant fuzzy environment , 2014, Knowl. Based Syst..

[27]  Yejun Xu,et al.  Fuzzy best-worst method and its application in initial water rights allocation , 2020, Appl. Soft Comput..

[28]  Anish Sachdeva,et al.  Risk analysis of cutting system under intuitionistic fuzzy environment , 2020 .

[29]  Huayou Chen,et al.  An integrated approach to green supplier selection based on the interval type-2 fuzzy best-worst and extended VIKOR methods , 2019, Inf. Sci..

[30]  Thomas L. Saaty,et al.  When is a Decision-Making Method Trustworthy? Criteria for Evaluating Multi-Criteria Decision-Making Methods , 2015, Int. J. Inf. Technol. Decis. Mak..

[31]  Bonifacio Llamazares,et al.  An analysis of the generalized TODIM method , 2018, Eur. J. Oper. Res..

[32]  J. Rezaei Best-worst multi-criteria decision-making method: Some properties and a linear model , 2016 .

[33]  Fuyuan Xiao,et al.  A novel multi-criteria decision making method for assessing health-care waste treatment technologies based on D numbers , 2018, Eng. Appl. Artif. Intell..

[34]  Peide Liu,et al.  A Multicriteria Decision-Making Approach with Linguistic D Numbers Based on the Choquet Integral , 2019, Cognitive Computation.

[35]  Glenn Shafer,et al.  A Mathematical Theory of Evidence , 2020, A Mathematical Theory of Evidence.

[36]  Lili Rong,et al.  Double hierarchy hesitant fuzzy linguistic entropy-based TODIM approach using evidential theory , 2021, Inf. Sci..

[37]  A. Saltelli,et al.  Sensitivity Anaysis as an Ingredient of Modeling , 2000 .

[38]  Dmitri Muravev,et al.  A Novel Integrated Provider Selection Multicriteria Model: The BWM-MABAC Model , 2020, Decision Making: Applications in Management and Engineering.

[39]  Xinwang Liu,et al.  An interval type-2 fuzzy sets-based TODIM method and its application to green supplier selection , 2016, J. Oper. Res. Soc..

[40]  Gui-Wu Wei,et al.  TODIM Method for Single-Valued Neutrosophic Multiple Attribute Decision Making , 2017, Inf..

[41]  Yanbing Ju,et al.  The waste-to-energy incineration plant site selection based on hesitant fuzzy linguistic Best-Worst method ANP and double parameters TOPSIS approach: A case study in China , 2020 .

[42]  Miloš Madić,et al.  COMPARISON OF THREE FUZZY MCDM METHODS FOR SOLVING THE SUPPLIER SELECTION PROBLEM , 2019 .

[43]  Prasenjit Chatterjee,et al.  Sustainable supplier selection using combined FUCOM – Rough SAW model , 2020 .

[44]  Tapan Kumar Roy,et al.  NC-TODIM-Based MAGDM under a Neutrosophic Cubic Set Environment , 2017, Inf..

[45]  Prasenjit Chatterjee,et al.  Comparative Evaluation of Sustainable Design Based on Step-Wise Weight Assessment Ratio Analysis (SWARA) and Best Worst Method (BWM) Methods: A Perspective on Household Furnishing Materials , 2019, Symmetry.

[46]  Zhen Zhang,et al.  Extended TODIM for multi-criteria group decision making based on unbalanced hesitant fuzzy linguistic term sets , 2017, Comput. Ind. Eng..

[47]  A. Tversky,et al.  Prospect theory: analysis of decision under risk , 1979 .

[48]  Javed Malek,et al.  Prioritization of sustainable manufacturing barriers using Best Worst Method , 2019, Journal of Cleaner Production.

[49]  Theodor J. Stewart,et al.  Integrating multicriteria decision analysis and scenario planning—Review and extension , 2013 .

[50]  Rodolfo Lourenzutti,et al.  A study of TODIM in a intuitionistic fuzzy and random environment , 2013, Expert Syst. Appl..

[51]  Kazem Askarifar,et al.  An investment development framework in Iran's seashores using TOPSIS and best-worst multi-criteria decision making methods , 2018 .

[52]  Yunna Wu,et al.  A DEMATEL-TODIM based decision framework for PV power generation project in expressway service area under an intuitionistic fuzzy environment , 2020 .

[53]  Guiwu Wei,et al.  TODIM Method for Multiple Attribute Group Decision Making under 2-Tuple Linguistic Neutrosophic Environment , 2018, Symmetry.

[54]  Islam Safak Bayram,et al.  Impact assessment of supply-side and demand-side policies on energy consumption and CO2 emissions from urban passenger transportation: The case of Istanbul , 2019, Journal of Cleaner Production.

[55]  J. Rezaei Best-worst multi-criteria decision-making method , 2015 .

[56]  Luís Alberto Duncan Rangel,et al.  An application of the TODIM method to the multicriteria rental evaluation of residential properties , 2009, Eur. J. Oper. Res..

[57]  Yalin Lei,et al.  Path analysis of factors in energy-related CO2 emissions from Beijing’s transportation sector , 2017 .

[58]  Sankaran Mahadevan,et al.  Environmental impact assessment based on D numbers , 2014, Expert Syst. Appl..

[59]  Daijun Wei,et al.  Investment decision using D numbers , 2016, 2016 Chinese Control and Decision Conference (CCDC).

[60]  Jian Guo,et al.  Extended TODIM method for CCUS storage site selection under probabilistic hesitant fuzzy environment , 2020, Appl. Soft Comput..

[61]  Oscar Castillo,et al.  Finite-interval-valued Type-2 Gaussian fuzzy numbers applied to fuzzy TODIM in a healthcare problem , 2020, Eng. Appl. Artif. Intell..

[62]  Stefano Tarantola,et al.  Sensitivity Analysis as an Ingredient of Modeling , 2000 .

[63]  Zeshui Xu,et al.  Pythagorean fuzzy TODIM approach to multi-criteria decision making , 2016, Appl. Soft Comput..

[64]  Yu-Han Huang,et al.  TODIM method for interval-valued Pythagorean fuzzy multiple attribute decision making , 2018, Int. J. Knowl. Based Intell. Eng. Syst..

[65]  T. Saaty,et al.  The Analytic Hierarchy Process , 1985 .

[66]  Fuyuan Xiao,et al.  An improved distance-based total uncertainty measure in belief function theory , 2017, Applied Intelligence.

[67]  Tabasam Rashid,et al.  Hesitant fuzzy best‐worst multi‐criteria decision‐making method and its applications , 2019, Int. J. Intell. Syst..

[68]  Omer Tatari,et al.  Investigating carbon footprint reduction potential of public transportation in United States: A system dynamics approach , 2016 .

[69]  Renato A. Krohling,et al.  IF-TODIM: An intuitionistic fuzzy TODIM to multi-criteria decision making , 2013, Knowl. Based Syst..

[70]  Sunil Luthra,et al.  Developing a sustainable smart city framework for developing economies: An Indian context , 2019, Sustainable Cities and Society.

[71]  Jicheng Liu,et al.  Research on clean energy power generation-energy storage-energy using virtual enterprise risk assessment based on fuzzy analytic hierarchy process in China , 2019, Journal of Cleaner Production.

[72]  Aijun Liu,et al.  The selection of 3PRLs on self-service mobile recycling machine: Interval-valued pythagorean hesitant fuzzy best-worst multi-criteria group decision-making , 2019, Journal of Cleaner Production.

[73]  Lóránt Tavasszy,et al.  Evaluation of the external forces affecting the sustainability of oil and gas supply chain using Best Worst Method , 2017 .

[74]  Zeshui Xu,et al.  An intuitionistic fuzzy multiplicative best-worst method for multi-criteria group decision making , 2016, Inf. Sci..

[75]  Nabankur Mandal,et al.  Performance evaluation of an insurance company using an integrated Balanced Scorecard (BSC) and Best-Worst Method (BWM) , 2020, Decision Making: Applications in Management and Engineering.

[76]  Jafar Rezaei,et al.  Consistency issues in the best worst method: Measurements and thresholds , 2020 .

[77]  Witold Pedrycz,et al.  An extended TODIM multi-criteria group decision making method for green supplier selection in interval type-2 fuzzy environment , 2017, Eur. J. Oper. Res..

[78]  Witold Pedrycz,et al.  Hesitant 2-tuple linguistic Bonferroni operators and their utilization in group decision making , 2019, Appl. Soft Comput..

[79]  Xin Guo Ming,et al.  A rough-fuzzy approach integrating best-worst method and data envelopment analysis to multi-criteria selection of smart product service module , 2020, Appl. Soft Comput..