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A Methodological Framework Based on a Quantitative Assessment of New Technologies to Boost the Interoperability of Railways Services

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  • Mehdi Zarehparast Malekzadeh

    (AITEC Asesores Internacionales S.r.l., Parque Tecnológico, C/Charles Robert Darwin 20, 46980 Paterna, Valencia, Spain)

  • Francisco Enrique Santarremigia

    (AITEC Asesores Internacionales S.r.l., Parque Tecnológico, C/Charles Robert Darwin 20, 46980 Paterna, Valencia, Spain)

  • Gemma Dolores Molero

    (AITEC Asesores Internacionales S.r.l., Parque Tecnológico, C/Charles Robert Darwin 20, 46980 Paterna, Valencia, Spain)

  • Ashwani Kumar Malviya

    (AITEC Asesores Internacionales S.r.l., Parque Tecnológico, C/Charles Robert Darwin 20, 46980 Paterna, Valencia, Spain)

  • Rosa Arroyo

    (Transport Department, UPV (Polytechnic University of Valencia), Camino de Vera s/n, 46022 València, Valencia, Spain)

  • Tomás Ruiz Sánchez

    (Transport Department, UPV (Polytechnic University of Valencia), Camino de Vera s/n, 46022 València, Valencia, Spain)

Abstract

Concerning the increase in the number of trips and tourists after the COVID-19 pandemic, TSPs (Transport Service Providers) and transport organizations are trying to improve their operability to answer the needs and expectations of passengers. This paper presents a methodology to assess and evaluate to what extent innovative technologies meet the needs of tourists and TSPs involved in the digital ecosystem for door-to-door trips in Europe, making railways and public transport more attractive and consequently encouraging people to use more intermodal solutions in public transport. In this study, two kinds of quantitative data are used: operational KPIs (Key Performance Indicators) and USI (User Satisfaction Index) surveys. The Effectiveness concept, as a metric of the capacity to meet these needs and expectations by the innovative technology, is calculated by merging both types of quantitative data. The method considers tourists’ socio-demographic profiles, allowing comparisons among TSPs and profiles for a specific technology, and it is extended to figure out correlations among variables through regression and Bayesian Networks analysis. In addition, specific socio-demographic data relevant to the needs and expectations were studied through the ANOVA test. This work belongs to the methodological framework of the IP4MaaS (Innovation Program 4 Mobility as a Service) project, which sets six demo sites on which this assessment method will be applied in a further stage. The concept of Effectiveness is applied in all the above-mentioned demo sites for the final assessment. Some IT innovations such as Location-Based Experience and Journey Planning have shown high Effectiveness. This work could be interesting for TSPs and IT (Information Technology) developers, researchers, policymakers, and organizations in the transport sector.

Suggested Citation

  • Mehdi Zarehparast Malekzadeh & Francisco Enrique Santarremigia & Gemma Dolores Molero & Ashwani Kumar Malviya & Rosa Arroyo & Tomás Ruiz Sánchez, 2023. "A Methodological Framework Based on a Quantitative Assessment of New Technologies to Boost the Interoperability of Railways Services," Sustainability, MDPI, vol. 15(13), pages 1-23, July.
    • Handle: RePEc:gam:jsusta:v:15:y:2023:i:13:p:10636-:d:1187762
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    References listed on IDEAS

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    1. Bamberg, Sebastian & Fujii, Satoshi & Friman, Margareta & Gärling, Tommy, 2011. "Behaviour theory and soft transport policy measures," Transport Policy, Elsevier, vol. 18(1), pages 228-235, January.
    2. M. Eugenia López-Lambas & Andrea Alonso, 2019. "The Driverless Bus: An Analysis of Public Perceptions and Acceptability," Sustainability, MDPI, vol. 11(18), pages 1-15, September.
    3. Gemma Dolores Molero & Sara Poveda-Reyes & Ashwani Kumar Malviya & Elena García-Jiménez & Maria Chiara Leva & Francisco Enrique Santarremigia, 2021. "Computational Solutions Based on Bayesian Networks to Hierarchize and to Predict Factors Influencing Gender Fairness in the Transport System: Four Use Cases," Sustainability, MDPI, vol. 13(20), pages 1-22, October.
    4. Amir Ahmadi-Javid & Pedram Hooshangi-Tabrizi, 2015. "A mathematical formulation and anarchic society optimisation algorithms for integrated scheduling of processing and transportation operations in a flow-shop environment," International Journal of Production Research, Taylor & Francis Journals, vol. 53(19), pages 5988-6006, October.
    5. Bing Han & Min Wan & Yu Zhou, 2020. "Evaluation of Multimodal Transport in China Based on Hesitation Fuzzy Multiattribute Decision-Making," Mathematical Problems in Engineering, Hindawi, vol. 2020, pages 1-9, September.
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    1. Mehdi Zarehparast Malekzadeh & Francisco Enrique Santarremigia & Gemma Dolores Molero & Ashwani Kumar Malviya & Aditya Kapoor & Rosa Arroyo & Tomás Ruiz Sánchez, 2024. "An Assessment Methodology about the Effectiveness of Mobility IT Solutions: Application to Six Demo Sites," Sustainability, MDPI, vol. 16(5), pages 1-34, March.

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