IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v12y2020i11p4737-d369697.html
   My bibliography  Save this article

The Distribution of Rural Accommodation in Extremadura, Spain-between the Randomness and the Suitability Achieved by Means of Regression Models (OLS vs. GWR)

Author

Listed:
  • José-Manuel Sánchez-Martín

    (Faculty of Business, Finance and Tourism, University of Extremadura, 10071 Cáceres, Spain)

  • José-Luis Gurría-Gascón

    (Faculty of Letters, University of Extremadura, 10071 Cáceres, Spain)

  • Juan-Ignacio Rengifo-Gallego

    (Faculty of Letters, University of Extremadura, 10071 Cáceres, Spain)

Abstract

There are multiple types of regression, the essential task of which is the obtaining of models which, starting from a set of regressive values, are capable of finding explanations for the variability of a dependent. However, in many cases, the territorial criterion is not considered to be a noteworthy factor of analysis, owing to which this deficiency has encouraged the arising of spatial statistics. Nevertheless, given the variety of regressions, it is not clear which can best be adapted to the analysis of tourism. In this sector, when the supply of accommodation is analysed, it is understood that it must be strongly related to the presence of resources, owing to which it has been taken as an example of an application between two differentiated regression techniques: ordinary least squares (OLS) and geographically weighted regression (GWR), with the objective of determining which of the two is best adapted to this type of analysis. The model has been drawn up based on various methods, although it has been shown that it is more efficient to resort to the declared preferences of the rural tourist, with the starting point being a survey made of the tourists. These aspects have been taken as independent variables with the aim of explaining the distribution of accommodation establishments. The results obtained show that the configuration of the spatial relations between the variable included in the model encourages the explanation of the latter, owing to which GWR is much more suitable than OLS, even when a system as complex as the distribution of accommodation establishments is analysed. Likewise, it is noteworthy that the distribution of accommodation does not also follow the guidelines marked by demand; far from it, it appears that in some areas, it is of a random nature.

Suggested Citation

  • José-Manuel Sánchez-Martín & José-Luis Gurría-Gascón & Juan-Ignacio Rengifo-Gallego, 2020. "The Distribution of Rural Accommodation in Extremadura, Spain-between the Randomness and the Suitability Achieved by Means of Regression Models (OLS vs. GWR)," Sustainability, MDPI, vol. 12(11), pages 1-29, June.
    • Handle: RePEc:gam:jsusta:v:12:y:2020:i:11:p:4737-:d:369697
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/12/11/4737/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2071-1050/12/11/4737/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Fabio Gaetano Santeramo & Mariangela Morelli, 2016. "Modelling tourism flows through gravity models: a quantile regression approach," Current Issues in Tourism, Taylor & Francis Journals, vol. 19(11), pages 1077-1083, September.
    2. Gutiérrez, Javier & García-Palomares, Juan Carlos & Romanillos, Gustavo & Salas-Olmedo, María Henar, 2017. "The eruption of Airbnb in tourist cities: Comparing spatial patterns of hotels and peer-to-peer accommodation in Barcelona," Tourism Management, Elsevier, vol. 62(C), pages 278-291.
    3. Pasquale De Toro & Francesca Nocca & Andrea Renna & Luigi Sepe, 2020. "Real Estate Market Dynamics in the City of Naples: An Integration of a Multi-Criteria Decision Analysis and Geographical Information System," Sustainability, MDPI, vol. 12(3), pages 1-24, February.
    4. Chatzigeorgiou, Chryssoula & Christou, Evangelos, 2020. "Adoption of social media as distribution channels in tourism marketing: A qualitative analysis of consumers’ experiences," EconStor Open Access Articles and Book Chapters, ZBW - Leibniz Information Centre for Economics, vol. 6(1), pages 25-32.
    5. Brida, Juan Gabriel & Scuderi, Raffaele, 2012. "Determinants of tourist expenditure: a review of microeconometric models," MPRA Paper 38468, University Library of Munich, Germany.
    6. Namhyun Kim & HakJun Song & Ju Hyun Pyun, 2016. "The relationship among tourism, poverty, and economic development in developing countries," Tourism Economics, , vol. 22(6), pages 1174-1190, December.
    7. Arthur Getis & J. Keith Ord, 2010. "The Analysis of Spatial Association by Use of Distance Statistics," Advances in Spatial Science, in: Luc Anselin & Sergio J. Rey (ed.), Perspectives on Spatial Data Analysis, chapter 0, pages 127-145, Springer.
    8. Carlos Santos & José Cabral Vieira, 2012. "An Analysis of Visitors' Expenditures in a Tourist Destination: OLS, Quantile Regression and Instrumental Variable Estimators," Tourism Economics, , vol. 18(3), pages 555-576, June.
    9. Dogru, Tarik & Sirakaya-Turk, Ercan, 2017. "Engines of tourism's growth: An examination of efficacy of shift-share regression analysis in South Carolina," Tourism Management, Elsevier, vol. 58(C), pages 205-214.
    10. Yang, Yang & Zhang, Honglei, 2019. "Spatial-temporal forecasting of tourism demand," Annals of Tourism Research, Elsevier, vol. 75(C), pages 106-119.
    11. Chen Xu & Calvin Jones & Max Munday, 2020. "Tourism inward investment and regional economic development effects: perspectives from tourism satellite accounts," Regional Studies, Taylor & Francis Journals, vol. 54(9), pages 1226-1237, September.
    12. Thrane, Christer, 2016. "Students' summer tourism: Determinants of length of stay (LOS)," Tourism Management, Elsevier, vol. 54(C), pages 178-184.
    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. António Almeida & Brian Garrod, 2017. "Insights from analysing tourist expenditure using quantile regression," Tourism Economics, , vol. 23(5), pages 1138-1145, August.
    2. Salvatore Costantino & Maria Francesca Cracolici & J. Paul Elhorst, 2023. "A spatial origin‐destination approach for the analysis of local tourism demand in Italy," Papers in Regional Science, Wiley Blackwell, vol. 102(2), pages 393-419, April.
    3. Christer Thrane, 2016. "The Determinants of Norwegians' Summer Tourism Expenditure: Foreign and Domestic Trips," Tourism Economics, , vol. 22(1), pages 31-46, February.
    4. Jorge V. Pérez-Rodríguez & Heiko Rachinger & Rafael Suárez-Vega, 2024. "Is peer-to-peer demand cointegrated at the listing level?," Empirical Economics, Springer, vol. 66(5), pages 2249-2275, May.
    5. Juan Brida & Marta Disegna & Raffaele Scuderi, 2014. "The behaviour of repeat visitors to museums: review and empirical findings," Quality & Quantity: International Journal of Methodology, Springer, vol. 48(5), pages 2817-2840, September.
    6. Mehmet Ronael & Tüzin Baycan, 2022. "Place-based factors affecting COVID-19 incidences in Turkey," Asia-Pacific Journal of Regional Science, Springer, vol. 6(3), pages 1053-1086, October.
    7. Martin Falk & Eva Hagsten, 2018. "Winter Weather Anomalies and Individual Destination Choice," Sustainability, MDPI, vol. 10(8), pages 1-14, July.
    8. Bresciani, Stefano & Ferraris, Alberto & Santoro, Gabriele & Premazzi, Katia & Quaglia, Roberto & Yahiaoui, Dorra & Viglia, Giampaolo, 2021. "The seven lives of Airbnb. The role of accommodation types," Annals of Tourism Research, Elsevier, vol. 88(C).
    9. Canh Phuc Nguyen & Su Dinh Thanh & Bach Nguyen, 2022. "Economic uncertainty and tourism consumption," Tourism Economics, , vol. 28(4), pages 920-941, June.
    10. IJspeert, Ruth & Hernandez-Maskivker, Gilda, 2020. "Active sport tourists: Millennials vs baby boomers," EconStor Open Access Articles and Book Chapters, ZBW - Leibniz Information Centre for Economics, vol. 6, pages 12-20.
    11. Lauriane Belloy, 2022. "Short-term rental revenues after the lockdown : An advantage for natural areas but always in dense rental spaces," Working papers of Transitions Energétiques et Environnementales (TREE) hal-03671537, HAL.
    12. Felipe Santos‐Marquez & Carlos Mendez, 2021. "Regional convergence, spatial scale, and spatial dependence: Evidence from homicides and personal injuries in Colombia 2010–2018," Regional Science Policy & Practice, Wiley Blackwell, vol. 13(4), pages 1162-1184, August.
    13. Jianwei Qi & Yayan Lu & Fang Han & Xuankai Ma & Zhaoping Yang, 2022. "Spatial Distribution Characteristics of the Rural Tourism Villages in the Qinghai-Tibetan Plateau and Its Influencing Factors," IJERPH, MDPI, vol. 19(15), pages 1-21, July.
    14. José Cabral Vieira & Marcos Carolino Antunes, 2017. "Touristic big-game fishing in Saint Michael Island (Azores)," Tourism Economics, , vol. 23(6), pages 1362-1368, September.
    15. Chih-Wen Yang & Cheng-Lung (Richard) Wu & Jin-Long Lu, 2021. "Exploring the interdependency and determinants of tourism participation, expenditure, and duration: An analysis of Taiwanese citizens traveling abroad," Tourism Economics, , vol. 27(4), pages 649-669, June.
    16. Joconiah Chirenda & Isaiah Gwitira & Robin M Warren & Samantha L Sampson & Amon Murwira & Collen Masimirembwa & Kudzanai M Mateveke & Cremence Duri & Prosper Chonzi & Simbarashe Rusakaniko & Elizabeth, 2020. "Spatial distribution of Mycobacterium Tuberculosis in metropolitan Harare, Zimbabwe," PLOS ONE, Public Library of Science, vol. 15(4), pages 1-16, April.
    17. Marrocu, Emanuela & Paci, Raffaele & Zara, Andrea, 2015. "Micro-economic determinants of tourist expenditure: A quantile regression approach," Tourism Management, Elsevier, vol. 50(C), pages 13-30.
    18. Maria Giovanna Brandano & Linda Osti & Manuela Pulina, 2016. "An investigation on tourism farms in South Tyrol," BEMPS - Bozen Economics & Management Paper Series BEMPS35, Faculty of Economics and Management at the Free University of Bozen.
    19. María-Jesús Perles & Juan F. Sortino & Matías F. Mérida, 2021. "The Neighborhood Contagion Focus as a Spatial Unit for Diagnosis and Epidemiological Action against COVID-19 Contagion in Urban Spaces: A Methodological Proposal for Its Detection and Delimitation," IJERPH, MDPI, vol. 18(6), pages 1-24, March.
    20. Fasone, Vincenzo & Kofler, Lukas & Scuderi, Raffaele, 2016. "Business performance of airports: Non-aviation revenues and their determinants," Journal of Air Transport Management, Elsevier, vol. 53(C), pages 35-45.

    More about this item

    Keywords

    ;
    ;
    ;
    ;
    ;

    Statistics

    Access and download statistics

    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:jsusta:v:12:y:2020:i:11:p:4737-:d:369697. 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.