Evaluation of the innovative value proposition for the rail freight transport: an integrated DEMATEL–ANP approach

    Miloš Milenković Affiliation
    ; Susana Val Affiliation
    ; Dejan Lutovac Affiliation
    ; Nebojša Bojović Affiliation
    ; Nikola Knežević Affiliation


Freight transport represents a very dynamic and competitive market with high requirements for reliability, lead time, cost, flexibility and visibility of transport service. Rationalization of transport service, reduced travelling time and reliable delivery times represent the main prerequisites for lowering the costs and increasing the efficiency of entire transport chain. These performance indicators actually represent the main factors affecting the shipper’s mode choice. Improvement of these factors could be achieved by improved coordination between rail and non-rail-related stakeholders involved in freight transport service planning and realization. Since this solution requires a multi-stakeholder collaboration, it is needed to evaluate the interests of each of them in order to derive a preferred set of indicators, which will facilitate a collectively accepted solution and value alignment of all involved actors. In this paper, the preferred set of indicators was selected by using the DEcision MAking Trial and Evaluation Laboratory (DEMATEL) model technique integrated with the Analytic Network Process (ANP). DEMATEL is applied to analyse the causal relationships among the relevant dimensions and among the criteria within each dimension. The causal relationships are then used in ANP for determining the weights of the criteria. An empirical case study based on implementation of information sharing platform in rail intermodal transport chain is presented to demonstrate the effectiveness of the proposed approach. Based on this study the attributes that belong to reliability (“departing / arriving on-time”, “cancelled services”), lead time (“idle time”) and investment cost (“organizational culture”, “business process redesign”) dimensions represent five the most critical factors for obtaining a collectively accepted solution. This effective evaluation model enables policy makers and stakeholders in transportation / logistics to understand and conduct appropriate actions towards fulfilling the objectives for greener transportation.

First published online 2 April 2021

Keyword : DEMATEL, ANP, rail intermodal transport chain, information sharing platform

How to Cite
Milenković, M., Val, S., Lutovac, D., Bojović, N., & Knežević, N. (2021). Evaluation of the innovative value proposition for the rail freight transport: an integrated DEMATEL–ANP approach. Transport, 36(5), 406-432.
Published in Issue
Dec 28, 2021
Abstract Views
PDF Downloads
Creative Commons License

This work is licensed under a Creative Commons Attribution 4.0 International License.


Bongo, M. F.; Alimpangog, K. M. S.; Loar, J. F.; Montefalcon, J. A.; Ocampo, L. A. 2018. An application of DEMATEL-ANP and PROMETHEE II approach for air traffic controllers’ workload stress problem: a case of Mactan civil aviation authority of the Philippines, Journal of Air Transport Management 68: 198–213.

Bongo, M. F.; Ocampo, L. A. 2017. A hybrid fuzzy MCDM approach for mitigating airport congestion: a case in Ninoy Aquino international airport, Journal of Air Transport Management 63: 1–16.

Brooks, M. R.; Puckett, S. M.; Hensher, D. A.; Sammons, A. 2012. Understanding mode choice decisions: a study of Australian freight shippers, Maritime Economics & Logistics 14(3): 274–299.

Buyukozkan, G.; Guleryuz, S. 2016. An integrated DEMATEL-ANP approach for renewable energy resources selection in Turkey, International Journal of Production Economics 182: 435–448.

Chen, F.-H.; Hsu, T.-S.; Tzeng, G.-H. 2011. A balanced scorecard approach to establish a performance evaluation and relationship model for hot spring hotels based on a hybrid MCDM model combining DEMATEL and ANP, International Journal of Hospitality Management 30(4): 908-932.

Chen, I.-S. 2016. A combined MCDM model based on DEMATEL and ANP for the selection of airline service quality improvement criteria: a study based on the Taiwanese airline industry, Journal of Air Transport Management 57: 7–18.

Clusters 2.0. 2019. D.2.5: Handbook for Smart Clusters Development. Clusters 2.0 – Open Network of Hyper Connected Logistics Clusters Towards Physical Internet. European Union’s Horizon 2020 Research and Innovation Programme under Grant Agreement No 723265. 57 p. Available from Internet:

Combes, F. 2012. Empirical evaluation of economic order quantity model for choice of shipment size in freight transport, Transportation Research Record: Journal of the Transportation Research Board 2269: 92–98.

Dalvi-Esfahani, M.; Niknafs, A.; Kuss, D. J.; Nilashi, M.; Afrough, S. 2019. Social media addiction: applying the DEMATEL approach, Telematics and Informatics 43: 101250.

Danielis, R.; Marcucci, E.; Rotaris, L. 2005. Logistics managers’ stated preferences for freight service attributes, Transportation Research Part E: Logistics and Transportation Review 41(3): 201–215.

Dehdasht, G.; Zin, R. M.; Ferwati, M. S.; Abdullahi, M. M.; Keyvanfar, A.; McCaffer, R. 2017. DEMATEL-ANP risk assessment in oil and gas construction projects, Sustainability 9(8): 1420.

Dincer, H.; Hacıoğlu, U.; Yuksel, S. 2017. Balanced scorecard based performance measurement of European airlines using a hybrid multicriteria decision making approach under the fuzzy environment, Journal of Air Transport Management 63: 17–33.

Fontela, E.; Gabus, A. 1974. DEMATEL: Innovative Methods. Science and Human Affairs Program of the Battelle Memorial Institute of Geneva, Geneva, Switzerland.

Fontela, E.; Gabus, A. 1976. The DEMATEL Observer. Science and Human Affairs Program of the Battelle Memorial Institute of Geneva, Geneva, Switzerland.

Garcia-Menendez, L.; Martinez-Zarzoso, I.; Perez-Garcia, E. M. 2006. Transport Logistics and Modal Split of Spanish Exports to Europe: Empirical Evidence. Social Science Research Network (SSRN). 26 p.

Gleave, S. D.; Dionori, F.; Casullo, L.; Ellis, S.; Ranghetti, D.; Bablinski, K.; Vollath, C.; Soutra, C. 2015. Freight on Road: Why EU Shippers Prefer Truck to Train. European Parliament’s Committee on Transport and Tourism, European Union. 78 p. Available from Internet:

Golcuk, İ.; Baykasoğlu, A. 2016. An analysis of DEMATEL approaches for criteria interaction handling within ANP, Expert Systems with Applications 46: 346–366.

Gudiel Pineda, P. J.; Liou, J. J. H.; Hsu, C.-C.; Chuang, Y.-C. 2018. An integrated MCDM model for improving airline operational and financial performance, Journal of Air Transport Management 68: 103–117.

Ha, M.-H.; Yang, Z. 2017. Comparative analysis of port performance indicators: independency and interdependency, Transportation Research Part A: Policy and Practice 103: 264–278.

Ha, M.-H.; Yang, Z.; Notteboom, T.; Ng, A. K. Y.; Heo, M.-W. 2017. Revisiting port performance measurement: a hybrid multi-stakeholder framework for the modelling of port performance indicators, Transportation Research Part E: Logistics and Transportation Review 103: 1–16.

Hsu, C.-C.; Liou, J. J. H. 2013. An outsourcing provider decision model for the airline industry, Journal of Air Transport Management 28: 40–46.

Hsu, C.-C.; Liou, J. J. H.; Lo, H.-W.; Wang, Y.-C. 2018. Using a hybrid method for evaluating and improving the service quality of public bike-sharing systems, Journal of Cleaner Production 202: 1131–1144.

Ishfaq, R. 2012. Resilience through flexibility in transportation operations, International Journal of Logistics Research and Applications: a Leading Journal of Supply Chain Management 15(4): 215–229.

Kaplinsky, R.; Morris, M. 2001. A Handbook for Value Chain Research. International Development Research Centre, Ottawa, Canada. 113 p.

Karaşan, A.; Kahraman, C. 2019. A novel intuitionistic fuzzy DEMATEL–ANP–TOPSIS integrated methodology for freight village location selection, Journal of Intelligent & Fuzzy Systems 36(2): 1335–1352.

Kheybari, S.; Rezaie, F. M.; Farazmand, H. 2020. Analytic network process: an overview of applications, Applied Mathematics and Computation 367: 124780.

Kijewska, K.; Torbacki, W.; Iwan, S. 2018. Application of AHP and DEMATEL methods in choosing and analysing the measures for the distribution of goods in Szczecin region, Sustainability 10(7): 2365.

Kim, H.-C.; Nicholson, A.; Kusumastuti, D. 2017. Analysing freight shippers’ mode choice preference heterogeneity using latent class modelling, Transportation Research Procedia 25: 1109–1125.

Kumar, A.; Anbanandam, R. 2020. Analyzing interrelationships and prioritising the factors influencing sustainable intermodal freight transport system: a grey-DANP approach, Journal of Cleaner Production 252: 119769.

Kundakcı, N.; Adalı, E. A.; Işık, A. T. 2014. Combination of DEMATEL and ANP for the cargo shipping company selection problem, International Journal of Engineering Management and Economics 4(2): 99–116.

Lee, K.-C.; Tsai, W.-H.; Yang, C.-H.; Lin, Y.-Z. 2018. An MCDM approach for selecting green aviation fleet program management strategies under multi-resource limitations, Journal of Air Transport Management 68: 76–85.

Lin, C.-L.; Hsieh, M.-S.; Tzeng, G.-H. 2010. Evaluating vehicle telematics system by using a novel MCDM techniques with dependence and feedback, Expert Systems with Applications 37(10): 6723–6736.

Liou, J. J. H.; Hsu, C.-C.; Chen, Y.-S. 2014. Improving transportation service quality based on information fusion, Transportation Research Part A: Policy and Practice 67: 225–239.

Liou, J. J. H.; Tzeng, G.-H.; Chang, H.-C. 2007. Airline safety measurement using a hybrid model, Journal of Air Transport Management 13(4): 243–249.

Liu, C.-H.; Tzeng, G.-H.; Lee, M.-H.; Lee, P.-Y. 2013. Improving metro–airport connection service for tourism development: using hybrid MCDM models, Tourism Management Perspectives 6: 95–107.

Lu, M.-T.; Hsu, C.-C.; Liou, J. J. H.; Lo, H.-W. 2018. A hybrid MCDM and sustainability-balanced scorecard model to establish sustainable performance evaluation for international airports, Journal of Air Transport Management 71: 9–19.

Moschovou, T. P.; Giannopoulos, G. A. 2012. Modeling freight mode choice in Greece, Procedia – Social and Behavioral Sciences 48: 597–611.

Ossadnik, W.; Schinke, S.; Kaspar, R. H. 2016. Group aggregation techniques for analytic hierarchy process and analytic network process: a comparative analysis, Group Decision and Negotiation 25(2): 421–457.

Pamučar, D.; Ćirović, G. 2015. The selection of transport and handling resources in logistics centers using multi-attributive border approximation area comparison (MABAC), Expert Systems with Applications 42(6): 3016–3028.

Pamučar, D.; Đorović, B.; Božanić, D.; Ćirović, G. 2012. Modification of the dynamic scale of marks in analytic hierarchy process (AHP) and analytic network approach (ANP) through application of fuzzy approach, Scientific Research and Essays 7(1): 24–37.

Patterson, Z.; Ewing, G. O.; Haider, M. 2007. Shipper preferences suggest strong mistrust of rail: results from stated preference carrier choice survey for Quebec City–Windsor Corridor in Canada, Transportation Research Record: Journal of the Transportation Research Board 2008: 67–74.

Quezada, L. E.; Lopez-Ospina, H. A.; Palominos, P. I.; Oddershede, A. M. 2018. Identifying causal relationships in strategy maps using ANP and DEMATEL, Computers & Industrial Engineering 118: 170–179.

Ranjan, R.; Chatterjee, P.; Chakraborty, S. 2015. Evaluating performance of engineering departments in an Indian University using DEMATEL and compromise ranking methods, OPSEARCH 52(2): 307–328.

Ranjan, R.; Chatterjee, P.; Chakraborty, S. 2016. Performance evaluation of Indian railway zones using DEMATEL and VIKOR methods, Benchmarking: an International Journal 23(1): 78–95.

Saaty, T. L. 2008. Decision making with the analytic hierarchy process, International Journal of Services Sciences 1(1): 83–98.

Saaty, T. L.; Vargas, L. G. 2006. Decision Making with the Analytic Network Process: Economic, Political, Social and Technological Applications with Benefits, Opportunities, Costs and Risks. Springer. 280 p.

Samimi, A.; Mohammadian, A.; Kawamura, K. 2010. A behavioral freight movement microsimulation model: method and data, Transportation Letters: the International Journal of Transportation Research 2(1): 53–62.

Shaik, M. N.; Abdul-Kader, W. 2018. A hybrid multiple criteria decision making approach for measuring comprehensive performance of reverse logistics enterprises, Computers & Industrial Engineering 123: 9–25.

Shin, S.; Roh, H.-S.; Hur, S. H. 2019. Characteristics analysis of freight mode choice model according to the introduction of a new freight transport system, Sustainability 11(4): 1209.

Smart-Rail. 2016. D7.4: Alignment of the Value Case of Involved Stakeholders. Document ID: Smart-Rail-D7.4-v1.0. Smart-Rail: Smart Supply Chain Oriented Rail Freight Services. European Union’s Horizon 2020 Research and Innovation Programme under Grant Agreement No 636071. 52 p. Available from Internet:

Solakivi, T.; Ojala, L. 2017. Determinants of carrier selection: updating the survey methodology into the 21st century, Transportation Research Procedia 25: 511–530.

Supeekit, T.; Somboonwiwat, T.; Kritchanchai, D. 2016. DEMATEL-modified ANP to evaluate internal hospital supply chain performance, Computers & Industrial Engineering 102: 318–330.

Tafreshi, P. F.; Aghdaie, M. H.; Behzadian, M.; Abadi, M. G. 2016. Developing a group decision support system for advertising media evaluation: a case in the Middle East, Group Decision and Negotiation 25(5): 1021–1048.

Vujanović, D.; Momčilović, V.; Bojović, N.; Papić, V. 2012. Evaluation of vehicle fleet maintenance management indicators by application of DEMATEL and ANP, Expert Systems with Applications 39(12): 10552–10563.

Wambua, J.; Mukulu, E.; Waiganjo, E. 2017. Cost as a factor of outsourcing third-party logistics providers and the performance of food and beverages manufacturing companies in Kenya, International Journal of Academic Research in Business and Social Sciences 7(2): 343–356.

Yang, J. L.; Tzeng, G.-H. 2011. An integrated MCDM technique combined with DEMATEL for a novel cluster-weighted with ANP method, Expert Systems with Applications 38(3): 1417–1424.

Yazdani, M.; Chatterjee, P.; Zavadskas, E. K.; Hashemkhani Zolfani, S. 2017. Integrated QFD-MCDM framework for green supplier selection, Journal of Cleaner Production 142: 3728–3740.

Yazdani, M.; Pamucar, D.; Chatterjee, P.; Chakraborty, S. 2020. Development of a decision support framework for sustainable freight transport system evaluation using rough numbers, International Journal of Production Research 58(14): 4325–4351.

Zhan, Q.; Zheng, W.; Zhao, B. 2017. A hybrid human and organizational analysis method for railway accidents based on HFACS-railway accidents (HFACS-RAs), Safety Science 91: 232–250.