IDEAS home Printed from https://ideas.repec.org/p/hal/journl/hal-04811280.html
   My bibliography  Save this paper

Optimizing shared recreational vehicle service areas: A multi-strategy approach for economic performance and user satisfaction

Author

Listed:
  • Daniel Thiel

    (Université Sorbonne Paris Nord, CEPN - Centre d'Economie de l'Université Paris Nord - CNRS - Centre National de la Recherche Scientifique - Université Sorbonne Paris Nord)

  • Erick Leroux

    (Université Sorbonne Paris Nord, CEPN - Centre d'Economie de l'Université Paris Nord - CNRS - Centre National de la Recherche Scientifique - Université Sorbonne Paris Nord)

  • Emmanuel Labarbe

    (UBM - Université Bordeaux Montaigne, D2iA - Dynamiques, Interactions, Interculturalité Asiatiques - ULR - La Rochelle Université - UBM - Université Bordeaux Montaigne, MICA - Médiation, Information, Communication, Art - UBM - Université Bordeaux Montaigne)

Abstract

In order to reduce overtourism and traffic congestion, local authorities may have to divert recreational vehicle traffic to off-site service areas. The problem that will arise is how best to accommodate different types of users with opposing preferences in the same area, some wanting to be as close as possible to the major site to be visited, others seeking peace and quiet. We have represented their specific attitudes using a two-stage decision-making process via a conjunctive model followed by a compensatory model. We then propose to model three strategies, seeking either to optimise customer attractiveness, or profit, or space occupation, in order to define a location, capacity and price for this shared area. Using a realistic data set, the results show that economic performance follows a concave curve as a function of the population mix. Moreover, only the strategy of maximising attractiveness suggests always mixing users in the same area.

Suggested Citation

  • Daniel Thiel & Erick Leroux & Emmanuel Labarbe, 2023. "Optimizing shared recreational vehicle service areas: A multi-strategy approach for economic performance and user satisfaction," Post-Print hal-04811280, HAL.
  • Handle: RePEc:hal:journl:hal-04811280
    DOI: 10.1177/13548166231214573
    Note: View the original document on HAL open archive server: https://hal.science/hal-04811280v1
    as

    Download full text from publisher

    File URL: https://hal.science/hal-04811280v1/document
    Download Restriction: no

    File URL: https://libkey.io/10.1177/13548166231214573?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. Hartman, Stefan, 2021. "Adaptive tourism areas in times of change," Annals of Tourism Research, Elsevier, vol. 87(C).
    2. Alessandro Capocchi & Cinzia Vallone & Mariarita Pierotti & Andrea Amaduzzi, 2019. "Overtourism: A Literature Review to Assess Implications and Future Perspectives," Sustainability, MDPI, vol. 11(12), pages 1-18, June.
    3. Timothy J. Gilbride & Greg M. Allenby, 2004. "A Choice Model with Conjunctive, Disjunctive, and Compensatory Screening Rules," Marketing Science, INFORMS, vol. 23(3), pages 391-406, October.
    4. Juan Li & Jing Ye & Qinglian He & Chunfu Shao, 2016. "A Novel Scheme to Relieve Parking Pressure at Tourist Attractions on Holidays," Sustainability, MDPI, vol. 8(2), pages 1-11, February.
    5. Mihalic, Tanja, 2020. "Conceptualising overtourism: A sustainability approach," Annals of Tourism Research, Elsevier, vol. 84(C).
    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. Daniel Thiel & Erick Leroux & Emmanuel Labarbe, 2024. "Optimizing shared recreational vehicle service areas: A multi-strategy approach for economic performance and user satisfaction," Tourism Economics, , vol. 30(6), pages 1465-1491, September.
    2. Santos-Rojo, Cristina & Llopis-Amorós, Malar & García-García, Juan Manuel, 2023. "Overtourism and sustainability: A bibliometric study (2018–2021)," Technological Forecasting and Social Change, Elsevier, vol. 188(C).
    3. Mahmut Barakazı, 2023. "Unsustainable Tourism Approaches in Touristic Destinations: A Case Study in Turkey," Sustainability, MDPI, vol. 15(6), pages 1-17, March.
    4. Sook Rei Tan & Jacob Wood & Haejin Jang & Caroline Wong & Changtai Li, 2024. "Tourism‐induced growth and quality of life: the Singapore story," Asian-Pacific Economic Literature, The Crawford School, The Australian National University, vol. 38(1), pages 204-224, May.
    5. Hyowon Kim & Dong Soo Kim & Greg M. Allenby, 2020. "Benefit Formation and Enhancement," Quantitative Marketing and Economics (QME), Springer, vol. 18(4), pages 419-468, December.
    6. James Agarwal & Wayne DeSarbo & Naresh K. Malhotra & Vithala Rao, 2015. "An Interdisciplinary Review of Research in Conjoint Analysis: Recent Developments and Directions for Future Research," Customer Needs and Solutions, Springer;Institute for Sustainable Innovation and Growth (iSIG), vol. 2(1), pages 19-40, March.
    7. Rasmussen, Thomas Kjær & Duncan, Lawrence Christopher & Watling, David Paul & Nielsen, Otto Anker, 2024. "Local detouredness: A new phenomenon for modelling route choice and traffic assignment," Transportation Research Part B: Methodological, Elsevier, vol. 190(C).
    8. Charles Cunningham & Ken Deal & Yvonne Chen, 2010. "Adaptive Choice-Based Conjoint Analysis," The Patient: Patient-Centered Outcomes Research, Springer;International Academy of Health Preference Research, vol. 3(4), pages 257-273, December.
    9. Bart Neuts & Senne Kimps & Jan van der Borg, 2021. "Resident Support for Tourism Development: Application of a Simplified Resident Empowerment through Tourism Scale on Developing Destinations in Flanders," Sustainability, MDPI, vol. 13(12), pages 1-19, June.
    10. Stefano Duglio & Alessandro Bonadonna & Marilisa Letey & Giovanni Peira & Laura Zavattaro & Giampiero Lombardi, 2019. "Tourism Development in Inner Mountain Areas—The Local Stakeholders’ Point of View through a Mixed Method Approach," Sustainability, MDPI, vol. 11(21), pages 1-19, October.
    11. Jelena DURKIN BADURINA & Daniela SOLDIC FRLETA & Larry DWYER, 2022. "Meet Sceptics, Neutrals And Believers: An Alternative Approach To Analysing Residents’ Attitudes Towards Tourism In Urban Destinations," Theoretical and Empirical Researches in Urban Management, Research Centre in Public Administration and Public Services, Bucharest, Romania, vol. 17(1), pages 24-44, February.
    12. Chen, Xuqi & Shen, Meng & Gao, Zhifeng, 2017. "Impact of Intra-respondent Variations in Attribute Attendance on Consumer Preference in Food Choice," 2017 Annual Meeting, July 30-August 1, Chicago, Illinois 258509, Agricultural and Applied Economics Association.
    13. Steven M. Shugan, 2007. "Editorial—The Anna Karenina Bias: Which Variables to Observe?," Marketing Science, INFORMS, vol. 26(2), pages 145-148, 03-04.
    14. Hugo Padrón-Ávila & Raúl Hernández-Martín, 2019. "Preventing Overtourism by Identifying the Determinants of Tourists’ Choice of Attractions," Sustainability, MDPI, vol. 11(19), pages 1-17, September.
    15. Vishal Narayan & Vithala R. Rao & Carolyne Saunders, 2011. "How Peer Influence Affects Attribute Preferences: A Bayesian Updating Mechanism," Marketing Science, INFORMS, vol. 30(2), pages 368-384, 03-04.
    16. Guang Li & Paat Rusmevichientong & Huseyin Topaloglu, 2015. "The d -Level Nested Logit Model: Assortment and Price Optimization Problems," Operations Research, INFORMS, vol. 63(2), pages 325-342, April.
    17. Crawford, Gregory S. & Griffith, Rachel & Iaria, Alessandro, 2021. "A survey of preference estimation with unobserved choice set heterogeneity," Journal of Econometrics, Elsevier, vol. 222(1), pages 4-43.
    18. Gael M. Martin & David T. Frazier & Ruben Loaiza-Maya & Florian Huber & Gary Koop & John Maheu & Didier Nibbering & Anastasios Panagiotelis, 2023. "Bayesian Forecasting in the 21st Century: A Modern Review," Monash Econometrics and Business Statistics Working Papers 1/23, Monash University, Department of Econometrics and Business Statistics.
    19. Rick L. Andrews & Andrew Ainslie & Imran S. Currim, 2008. "On the Recoverability of Choice Behaviors with Random Coefficients Choice Models in the Context of Limited Data and Unobserved Effects," Management Science, INFORMS, vol. 54(1), pages 83-99, January.
    20. Crabolu, Gloria & Font, Xavier & Eker, Sibel, 2023. "Evaluating policy complexity with Causal Loop Diagrams," Annals of Tourism Research, Elsevier, vol. 100(C).

    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:hal:journl:hal-04811280. 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: CCSD (email available below). General contact details of provider: https://hal.archives-ouvertes.fr/ .

    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.