IDEAS home Printed from https://ideas.repec.org/a/gam/jmathe/v12y2024i6p791-d1353292.html
   My bibliography  Save this article

Analysing the Hidden Relationship between Long-Distance Transport and Information and Communication Technology Use through a Fuzzy Clustering Eco-Extended Apostle Model

Author

Listed:
  • Panayotis Christidis

    (Joint Research Centre, European Commission, 41092 Seville, Spain)

  • Juan Carlos Martín

    (Institute of Tourism and Sustainable Economic Development, University of Las Palmas de Gran Canaria, 35017 Las Palmas, Spain)

  • Concepción Román

    (Institute of Tourism and Sustainable Economic Development, University of Las Palmas de Gran Canaria, 35017 Las Palmas, Spain)

Abstract

The study analyses the hidden relationship between transport and ICT use for an extensive sample of 26,500 EU citizens. To that aim, a fuzzy clustering Eco-extended apostle model is applied to both latent variables: interurban transport trips and ICT use. The interurban long-distance trip (LDT) latent variable is measured by four different indicators (long- and medium-distance trips for work and leisure in the past twelve months), and the ICT use is based on a ten-item scale that provides information on different transport modes. The fuzzy Eco-extended apostle model is compared with the classical apostle model, translating the satisfaction and loyalty dimensions to our case. The fuzzy clustering model shows that most EU citizens are similar to the representative citizen who moved and used ICT at very low rates (56.5 and 50.4 per cent, respectively). The classical apostle model shows that the quadrants low LDT–high ICT and low LDT–low ICT are more represented by 38.5 and 35.2 per cent, respectively. However, the Eco-extended apostle model reinforces the results of the quadrant of low LDT–low ICT (40.22%) but softens those obtained in the quadrant of low LDT–high ICT (21.01%). Interesting insights of the effects of gender, age, education, and employment status are discussed.

Suggested Citation

  • Panayotis Christidis & Juan Carlos Martín & Concepción Román, 2024. "Analysing the Hidden Relationship between Long-Distance Transport and Information and Communication Technology Use through a Fuzzy Clustering Eco-Extended Apostle Model," Mathematics, MDPI, vol. 12(6), pages 1-21, March.
    • Handle: RePEc:gam:jmathe:v:12:y:2024:i:6:p:791-:d:1353292
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2227-7390/12/6/791/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2227-7390/12/6/791/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. D'Urso, Pierpaolo & Disegna, Marta & Massari, Riccardo & Osti, Linda, 2016. "Fuzzy segmentation of postmodern tourists," Tourism Management, Elsevier, vol. 55(C), pages 297-308.
    2. David Banister & Dominic Stead, 2004. "Impact of information and communications technology on transport," Transport Reviews, Taylor & Francis Journals, vol. 24(5), pages 611-632, January.
    3. Aultman-Hall, Lisa, 2018. "Incorporating Long-Distance Travel into Transportation Planning in the United States," Institute of Transportation Studies, Working Paper Series qt0ft8b3b5, Institute of Transportation Studies, UC Davis.
    4. Martin-Domingo, Luis & Martín, Juan Carlos, 2016. "Airport mobile internet an innovation," Journal of Air Transport Management, Elsevier, vol. 55(C), pages 102-112.
    5. Juan Martín & Gustavo Nombela, 2007. "Microeconomic impacts of investments in high speed trains in Spain," The Annals of Regional Science, Springer;Western Regional Science Association, vol. 41(3), pages 715-733, September.
    6. Shaila Jamal & Muhammad Ahsanul Habib, 2019. "Investigation of the use of smartphone applications for trip planning and travel outcomes," Transportation Planning and Technology, Taylor & Francis Journals, vol. 42(3), pages 227-243, April.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Wang, Yunmin & Cao, Guohua & Yan, Youliang & Wang, Jingjing, 2022. "Does high-speed rail stimulate cross-city technological innovation collaboration? Evidence from China," Transport Policy, Elsevier, vol. 116(C), pages 119-131.
    2. Ren, Xiaohang & Zeng, Gudian & Dong, Kangyin & Wang, Kun, 2023. "How does high-speed rail affect tourism development? The case of the Sichuan-Chongqing Economic Circle," Transportation Research Part A: Policy and Practice, Elsevier, vol. 169(C).
    3. Halpern, Nigel & Mwesiumo, Deodat & Suau-Sanchez, Pere & Budd, Thomas & Bråthen, Svein, 2021. "Ready for digital transformation? The effect of organisational readiness, innovation, airport size and ownership on digital change at airports," Journal of Air Transport Management, Elsevier, vol. 90(C).
    4. Banister, David, 2011. "Cities, mobility and climate change," Journal of Transport Geography, Elsevier, vol. 19(6), pages 1538-1546.
    5. Bo Wendy Gao & Chris Zhu & Hongmei Song & Ianthe M. Belisle Dempsey, 2022. "Interpreting the perceptions of authenticity in virtual reality tourism through postmodernist approach," Information Technology & Tourism, Springer, vol. 24(1), pages 31-55, March.
    6. Albalate, Daniel & Fageda, Xavier, 2016. "High speed rail and tourism: Empirical evidence from Spain," Transportation Research Part A: Policy and Practice, Elsevier, vol. 85(C), pages 174-185.
    7. Capozza, Claudia, 2015. "The effect of rail travel time on airline fares: first evidence from the Italian passenger market," Working Papers 15_3, SIET Società Italiana di Economia dei Trasporti e della Logistica.
    8. Pierpaolo D’Urso & Marta Disegna & Riccardo Massari, 2020. "Satisfaction and Tourism Expenditure Behaviour," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 149(3), pages 1081-1106, June.
    9. Bergantino, Angela S. & Capozza, Claudia & Capurso, Mauro, 2015. "The impact of open access on intra- and inter-modal rail competition. A national level analysis in Italy," Transport Policy, Elsevier, vol. 39(C), pages 77-86.
    10. Daniel Albalate del sol, 2015. "Evaluating HSR availability on Tourism: Evidence from Spanish Provinces and Cities," ERSA conference papers ersa15p288, European Regional Science Association.
    11. Capozza, Claudia, 2016. "The effect of rail travel time on airline fares: First evidence from the Italian passenger market," Economics of Transportation, Elsevier, vol. 6(C), pages 18-24.
    12. Pierpaolo D’Urso & Livia Giovanni & Marta Disegna & Riccardo Massari & Vincenzina Vitale, 2021. "A Tourist Segmentation Based on Motivation, Satisfaction and Prior Knowledge with a Socio-Economic Profiling: A Clustering Approach with Mixed Information," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 154(1), pages 335-360, February.
    13. Oliver, Atara Stephanie, 2013. "Information Technology and Transportation: Substitutes or Complements?," MPRA Paper 46548, University Library of Munich, Germany.
    14. Francesca Cellina & Dominik Bucher & Francesca Mangili & José Veiga Simão & Roman Rudel & Martin Raubal, 2019. "A Large Scale, App-Based Behaviour Change Experiment Persuading Sustainable Mobility Patterns: Methods, Results and Lessons Learnt," Sustainability, MDPI, vol. 11(9), pages 1-23, May.
    15. Borsati, Mattia & Albalate, Daniel, 2020. "On the modal shift from motorway to high-speed rail: evidence from Italy," Transportation Research Part A: Policy and Practice, Elsevier, vol. 137(C), pages 145-164.
    16. Euijune Kim & Seung‐Woon Moon & Yoojin Yi, 2021. "Analyzing spillover effects of development of Asian highway on regional growth of Northeast Asian countries," Review of Development Economics, Wiley Blackwell, vol. 25(3), pages 1243-1266, August.
    17. Daniel Albalate & Javier Campos & Juan Luis Jiménez, 2015. "“Tourism and high speed rail in Spain: Does the AVE increase local visitors?”," IREA Working Papers 201527, University of Barcelona, Research Institute of Applied Economics, revised Dec 2015.
    18. Chen, Peng & Yang, Xiankui, 2023. "Revisit employer-based travel demand management: A longitudinal analysis," Transport Policy, Elsevier, vol. 131(C), pages 22-31.
    19. Bursa, Bartosz & Mailer, Markus & Axhausen, Kay W., 2022. "Travel behavior on vacation: transport mode choice of tourists at destinations," Transportation Research Part A: Policy and Practice, Elsevier, vol. 166(C), pages 234-261.
    20. S. Mahmuda & T. Sigler & E. Knight & J. Corcoran, 2020. "Sectoral evolution and shifting service delivery models in the sharing economy," Business Research, Springer;German Academic Association for Business Research, vol. 13(2), pages 663-684, July.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jmathe:v:12:y:2024:i:6:p:791-:d:1353292. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.