An evaluation for sustainable mobility extended by D numbers

    Hongming Mo Affiliation
    ; Yong Deng Affiliation


How to evaluate the impact of transport measures on city sustainability effectively is still an open issue, and it can be abstracted as one of the multiple criteria decision making problems. In this paper, a new method based on D numbers is proposed to evaluate the sustainable mobility of city. D number is a new mathematical tool to represent and deal uncertain information. The property of integration of D numbers is employed to fusion information. A numerical example of carsharing demonstrates the effectiveness of the proposed method.

First published online 31 May 2019

Keyword : belief function, D numbers, evidence theory, sustainability, decision making

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Mo, H., & Deng, Y. (2019). An evaluation for sustainable mobility extended by D numbers. Technological and Economic Development of Economy, 25(5), 802-819.
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May 31, 2019
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This work is licensed under a Creative Commons Attribution 4.0 International License.


Akyelken, N., Banister, D., & Givoni, M. (2018). The sustainability of shared mobility in London: The dilemma for governance. Sustainability, 10(2), 420.

Amegah, A. K., & Agyei-Mensah, S. (2017). Urban air pollution in Sub-Saharan Africa: Time for action. Environmental Pollution, 220(Part A), 738-743.

Ampudia-Renuncio, M., Guirao, B., & Molina, R. (2018). The impact of free-floating carsharing on sustainable cities: analysis of first experiences in Madrid with the university campus. Sustainable Cities and Society, 43, 462-475.

Anand, S., & Sen, A. (2000). Human development and economic sustainability. World Development, 28(12), 2029-2049.

Awasthi, A., & Chauhan, S. S. (2011). Using AHP and Dempster–Shafer theory for evaluating sustainable transport solutions. Environmental Modelling & Software, 26(6), 787-796.

Awasthi, A., & Chauhan, S. S. (2012). A hybrid approach integrating Affinity Diagram, AHP and fuzzy TOPSIS for sustainable city logistics planning. Applied Mathematical Modelling, 36(2), 573-584.

Awasthi, A., Chauhan, S. S., Hurteau, X., & Breuil, D. (2008). An analytical hierarchical process-based decision-making approach for selecting car-sharing stations in medium size agglomerations. International Journal of Information and Decision Sciences, 1(1), 66-97.

Bachmann, F., Hanimann, A., Artho, J., & Jonas, K. (2018). What drives people to carpool? Explaining carpooling intention from the perspectives of carpooling passengers and drivers. Transportation Research Part F: Traffic Psychology and Behaviour, 59(Part A), 260-268.

Banister, D. (2008). The sustainable mobility paradigm. Transport Policy, 15(2), 73-80.

Belenky, A. S. (2013). Operations research in transportation systems: Ideas and schemes of optimization methods for strategic planning and operations management (Vol. 20). Springer Science & Business Media.

Bian, T., Zheng, H., Yin, L., & Deng, Y. (2018). Failure mode and effects analysis based on D numbers and TOPSIS. Quality and Reliability Engineering International, 34(4), 501-515.

Browne, D., O’Regan, B., & Moles, R. (2008). Use of ecological footprinting to explore alternative transport policy scenarios in an Irish city-region. Transportation Research Part D: Transport and Environment, 13(5), 315-322.

Burton, I. (1987). Report on reports: Our common future: The world commission on environment and development. Environment: Science and Policy for Sustainable Development, 29(5), 25-29.

Car2go blog. (2018). “We are 3 million!”. Retrieved from

Carteni, A. (2017). A new look in designing sustainable city logistics road pricing schemes. WIT Transactions on Ecology and the Environment, 223, 171-181.

Carteni, A. (2018). A cost-benefit analysis based on the carbon footprint derived from plug-in hybrid electric buses for urban public transport services. Wseas Transactions on Environment and Development, 14, 125-135. Retrieved from

Cartenì, A., Cascetta, E., & de Luca, S. (2016). A random utility model for park & carsharing services and the pure preference for electric vehicles. Transport Policy, 48, 49-59.

Cartenì, A., De Guglielmo, M. L., & Pascale, N. (2018). Congested urban areas with high interactions between vehicular and pedestrian flows: A cost-benefit analysis for a sustainable transport policy in Naples, Italy. The Open Transportation Journal, 12(1), 273-288.

Cartenì, A., De Guglielmo, M. L., Pascale, N., & Calabrese, M. (2017). An adaptive rational decisionmaking process for developing sustainable urban mobility plans. International Journal of Civil Engineering and Technology, 8(7), 1147-1156.

Cascetta, E. (2009). Transportation systems analysis: models and applications (Vol. 29). Springer Science & Business Media.

Cascetta, E., & Pagliara, F. (2013). Public engagement for planning and designing transportation systems. Procedia-Social and Behavioral Sciences, 87, 103-116.

Cascetta, E., Carteni, A., & Henke, I. (2017). Acceptance and equity in advanced path-related road pricing schemes. In 5th IEEE International Conference Models and Technologies for Intelligent Transportation Systems (MT-ITS) (pp. 492-496). IEEE.

Cascetta, E., Carteni, A., Pagliara, F., & Montanino, M. (2015). A new look at planning and designing transportation systems: A decision-making model based on cognitive rationality, stakeholder engagement and quantitative methods. Transport Policy, 38, 27-39.

Chen, L., & Deng, X. (2018a). A modified method for evaluating sustainable transport solutions based on AHP and Dempster–Shafer evidence theory. Applied Sciences, 8(4), 563.

Chen, L., & Deng, Y. (2018b). A new failure mode and effects analysis model using Dempster–Shafer evidence theory and grey relational projection method. Engineering Applications of Artificial Intelligence, 76, 13-20.

Cleary, J. (2009). Life cycle assessments of municipal solid waste management systems: A comparative analysis of selected peer-reviewed literature. Environment International, 35(8), 1256-1266.

Cordera, R., dell’Olio, L., Ibeas, A., & Ortúzar, J. D. D. (2018). Demand for environmentally friendly vehicles: A review and new evidence. International Journal of Sustainable Transportation, 13(3), 210-223.

Dempsey, N., Bramley, G., Power, S., & Brown, C. (2011). The social dimension of sustainable development: Defining urban social sustainability. Sustainable Development, 19(5), 289-300.

Dempster, A. P. (2008). Upper and lower probabilities induced by a multivalued mapping. In Classic works of the Dempster–Shafer theory of belief functions (pp. 57-72). Springer, Berlin, Heidelberg.

Deng, X., & Deng, Y. (2018). D-AHP method with different credibility of information. Soft Computing, 23(2), 683-691.

Deng, Y. (2012). D numbers: theory and applications. Journal of Information & Computational Science, 9(9), 2421-2428.

Domarchi, C., Coeymans, J. E., & de Dios Ortúzar, J. (2018). Shared taxis: modelling the choice of a paratransit mode in Santiago de Chile. Transportation, 1-26.

Eliasson, J. (2009). A cost–benefit analysis of the Stockholm congestion charging system. Transportation Research Part A: Policy and Practice, 43(4), 468-480.

Fan, G., Zhong, D., Yan, F., & Yue, P. (2016). A hybrid fuzzy evaluation method for curtain grouting efficiency assessment based on an AHP method extended by D numbers. Expert Systems with Applications, 44, 289-303.

Fei, L., & Deng, Y. (2018). A new divergence measure for basic probability assignment and its applications in extremely uncertain environments. International Journal of Intelligent Systems, 34(4), 584600.

Fei, L., Deng, Y., & Hu, Y. (2018). DS-VIKOR: A new multi-criteria decision-making method for supplier selection. International Journal of Fuzzy Systems, 21(1), 157-175.

Guan, X., Liu, H., Yi, X., & Zhao, J. (2018). The improved combination rule of D Numbers and its application in radiation source identification. Mathematical Problems in Engineering, 2018, ID 6025680.

Han, Y., & Deng, Y. (2018a). An enhanced fuzzy evidential DEMATEL method with its application to identify critical success factors. Soft Computing, 22(15), 5073-5090.

Han, Y., & Deng, Y. (2018b). A hybrid intelligent model for assessment of critical success factors in high-risk emergency system. Journal of Ambient Intelligence and Humanized Computing, 9(6), 19331953.

Han, Y., & Deng, Y. (2018c). An evidential fractal analytic hierarchy process target recognition method. Defence Science Journal, 68(4), 367-373.

Hashemkhani Zolfani, S., Maknoon, R., & Zavadskas, E. K. (2016). An introduction to prospective multiple attribute decision making (PMADM). Technological and Economic Development of Economy, 22(2), 309-326.

Johnson, E. M., & Huber, G. P. (1977). The technology utility assessment. IEEE Transactions on Systems, Man, and Cybernetics, 7(5), 311-325.

Kaklauskas, A., Herrera-Viedma, E., Echenique, V., Zavadskas, E. K., Ubarte, I., Mostert, A., Podvezko, V., Binkyte, A., & Podviezko, A. (2018). Multiple criteria analysis of environmental sustainability and quality of life in post-Soviet states. Ecological Indicators, 89, 781-807.

Katzev, R. (2003). Car sharing: A new approach to urban transportation problems. Analyses of Social Issues and Public Policy, 3(1), 65-86.

Keeney, R. L., Raiffa, H., & Rajala, D. W. (1979). Decisions with multiple objectives: Preferences and value trade-offs. IEEE Transactions on Systems, Man, and Cybernetics, 9(7), 403-403.

Keshavarz Ghorabaee, M., Zavadskas, E. K., Amiri, M., & Turskis, Z. (2016). Extended EDAS method for fuzzy multi-criteria decision-making: an application to supplier selection. International Journal of Computers Communications & Control, 11(3), 358-371.

Kunreuther, H., Grossi, P., Seeber, N., & Smyth, A. (2003). A framework for evaluating the cost-effectiveness of mitigation measures. Columbia University, USA.

Larson, E. D. (2006). A review of life-cycle analysis studies on liquid biofuel systems for the transport sector. Energy for Sustainable Development, 10(2), 109-126.

Lazauskas, M., Zavadskas, E. K., & Šaparauskas, J. (2015). Ranking of priorities among the Baltic capital cities for the development of sustainable construction. E & M Ekonomie a Management, 18(2), 15-24.

Li, M., Zhang, Q., & Deng, Y. (2018). Evidential identification of influential nodes in network of networks. Chaos, Solitons & Fractals, 117, 283-296.

Li, X., & Chen, X. (2018). D-Intuitionistic hesitant fuzzy sets and their application in multiple attribute decision making. Cognitive Computation, 10(3), 496-505.

Li, Y., & Deng, Y. (2018). Generalized ordered propositions fusion based on belief entropy. International Journal of Computers, Communications & Control, 13(5), 792-807.

Lin, S., Li, C., Xu, F., Liu, D., & Liu, J. (2018). Risk identification and analysis for new energy power system in China based on D numbers and decision-making trial and evaluation laboratory (DEMATEL). Journal of Cleaner Production, 180, 81-96.

Litman, T., & Burwell, D. (2006). Issues in sustainable transportation. International Journal of Global Environmental Issues, 6(4), 331-347. :p:331-347

Liu, H. C., You, J. X., Fan, X. J., & Lin, Q. L. (2014). Failure mode and effects analysis using D numbers and grey relational projection method. Expert Systems with Applications, 41(10), 4670-4679.

Mo, H., & Deng, Y. (2016). A new aggregating operator for linguistic information based on D numbers. International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems, 24(06), 831-846.

Mo, H., & Deng, Y. (2018). A new MADA methodology based on D numbers. International Journal of Fuzzy Systems, 20(8), 2458-2469.

Moya-Gómez, B., & García-Palomares, J. C. (2017). The impacts of congestion on automobile accessibility. What happens in large European cities?. Journal of Transport Geography, 62, 148-159.

Naess, P. (2001). Urban planning and sustainable development. European Planning Studies, 9(4), 503524.

Nordlund, A. M., & Garvill, J. (2003). Effects of values, problem awareness, and personal norm on willingness to reduce personal car use. Journal of Environmental Psychology, 23(4), 339-347.

Ogilvie, D., Egan, M., Hamilton, V., & Petticrew, M. (2004). Promoting walking and cycling as an alternative to using cars: systematic review. BMJ, 329, 763.

Opricovic, S., & Tzeng, G. H. (2007). Extended VIKOR method in comparison with outranking methods. European Journal of Operational Research, 178(2), 514-529.

Ortuzar, J., & Willumsen, L. G. (2011). Modelling transport (4th ed.). John Wiley & Sons.

Rai, H. B., van Lier, T., Meers, D., & Macharis, C. (2017). Improving urban freight transport sustainability: Policy assessment framework and case study. Research in Transportation Economics, 64, 26-35.

Rehermann, F., & Pablo-Romero, M. (2018). Economic growth and transport energy consumption in the Latin American and Caribbean countries. Energy Policy, 122, 518-527.

Reisi, M., Aye, L., Rajabifard, A., & Ngo, T. (2014). Transport sustainability index: Melbourne case study. Ecological Indicators, 43, 288-296.

Saltelli, A., Chan, K., & Scott, E. M. (Eds.). (2000). Sensitivity analysis (Vol. 1). New York: Wiley.

Shafer, G. (1976). A mathematical theory of evidence (Vol. 42). Princeton University Press.

Shaheen, S. A., Sperling, D., & Wagner, C. (1999). A short history of Carsharing in the 90’s. The Journal of World Transport Policy & Practice, 5, 18-40. Retrieved from item/6p3305b0

Siksnelyte, I., Zavadskas, E. K., Bausys, R., & Streimikiene, D. (2019). Implementation of EU energy policy priorities in the Baltic Sea Region countries: Sustainability assessment based on neutrosophic MULTIMOORA method. Energy Policy, 125, 90-102.

Siksnelyte, I., Zavadskas, E., Streimikiene, D., & Sharma, D. (2018). An overview of multi-criteria decision-making methods in dealing with sustainable energy development issues. Energies, 11(10), 2754.

Singh, R. K., Murty, H. R., Gupta, S. K., & Dikshit, A. K. (2009). An overview of sustainability assessment methodologies. Ecological Indicators, 9(2), 189-212.

Singh, S., Olugu, E. U., Musa, S. N., Mahat, A. B., & Wong, K. Y. (2016). Strategy selection for sustainable manufacturing with integrated AHP-VIKOR method under interval-valued fuzzy environment. The International Journal of Advanced Manufacturing Technology, 84(1-4), 547-563.

Smets, P., & Kennes, R. (1994). The transferable belief model. Artificial Intelligence, 66(2), 191-234.

Social network of Alumniportal Deutschland. (2015). Mobile, flexible and eco-friendly the car sharing boom is not limited to Germany alone. Retrieved from en/globalgoals/sdg-12-consumption/car-sharing/

Soria-Lara, J. A., & Banister, D. (2018). Evaluating the impacts of transport backcasting scenarios with multi-criteria analysis. Transportation Research Part A: Policy and Practice, 110, 26-37.

Steenberghen, T., & Lopez, E. (2008). Overcoming barriers to the implementation of alternative fuels for road transport in Europe. Journal of Cleaner Production, 16(5), 577-590.

Su, C. M., Horng, D. J., Tseng, M. L., Chiu, A. S., Wu, K. J., & Chen, H. P. (2016). Improving sustainable supply chain management using a novel hierarchical grey-DEMATEL approach. Journal of Cleaner Production, 134(Part B), 469-481.

Thill, J. C., Rogova, G., & Yan, J. (2004). Evaluating benefits and costs of intelligent transportation systems elements from a planning perspective. Research in Transportation Economics, 8, 571-603.

Toledo, T., & Koutsopoulos, H. N. (2004). Statistical validation of traffic simulation models. Transportation Research Record, 1876(1), 142-150.

Venables, A. J. (2007). Evaluating urban transport improvements: cost–benefit analysis in the presence of agglomeration and income taxation. Journal of Transport Economics and Policy (JTEP), 41(2), 173-188.

Wei, G., Alsaadi, F. E., Hayat, T., & Alsaedi, A. (2018). Bipolar fuzzy Hamacher aggregation operators in multiple attribute decision making. International Journal of Fuzzy Systems, 20(1), 1-12.

Wellar, B. (2009). Sampler of commentaries on methods and techniques that could be used in making decisions about identifying, Adopting or implementing sustainable transport practices. Canada: Wellar Consulting Inc.

Wellmann, T., Govindswamy, K., & Tomazic, D. (2013). Integration of engine start/stop systems with emphasis on NVH and launch behavior. SAE International Journal of Engines, 6(2), 1368-1378.

World Carshare Consortium. (2009). One Thousand World Carshare Cities in 2009. Retrieved from

Xiao, F. (2018). A novel multi-criteria decision making method for assessing health-care waste treatment technologies based on D numbers. Engineering Applications of Artificial Intelligence, 71, 216225.

Yang, H., Deng, Y., & Jones, J. (2018). Network division method based on cellular growth and Physarum-inspired network adaptation. International Journal of Unconventional Computing, 13(6), 477-491. Retrieved from

Yin, L., Deng, X., & Deng, Y. (2019). The negation of a basic probability assignment. IEEE Transactions on Fuzzy Systems, 27(1), 135-143.

Zavadskas, E. K., Antuchevičienė, J., & Chatterjee, P. (2019). Multiple-Criteria Decision-Making (MCDM) techniques for business processes information management. Information, 10(1), 1-7.

Zavadskas, E. K., Kalibatas, D., & Kalibatiene, D. (2016). A multi-attribute assessment using WASPAS for choosing an optimal indoor environment. Archives of Civil and Mechanical Engineering, 16(1), 76-85.

Zhang, H., & Deng, Y. (2018). Engine fault diagnosis based on sensor data fusion considering information quality and evidence theory. Advances in Mechanical Engineering, 10(11), 1687814018809184.