Efficient access to tourist spots is necessary for enhancing the overall travel experience, especially in urban environments. This study investigates the accessibility of key tourist spots in Budapest through different transportation modes (e.g., walking, cycling, and public transport) across various time intervals. Using spatial-temporal travel time maps and detailed statistical analysis, the research highlighted significant differences in how these modes connect tourists to their attractions. Cycling stands out as the most efficient transportation option, providing rapid access to a wide range of tourist spots, while public transport ranks second. However, the study also reveals disparities in accessibility, with central areas being well-served, while outer ones, especially in the northwest, remain less accessible. These findings highlight the need for targeted transportation improvements to ensure that all areas of the city are equally reachable. The results offer valuable insights for urban planners and policymakers aiming to enhance tourism infrastructure and improve the visitor experience in Budapest.

TRANSLATE with xEnglishArabicHebrewPolishBulgarianHindiPortugueseCatalanHmong DawRomanianChinese SimplifiedHungarianRussianChinese TraditionalIndonesianSlovakCzechItalianSlovenianDanishJapaneseSpanishDutchKlingonSwedishEnglishKoreanThaiEstonianLatvianTurkishFinnishLithuanianUkrainianFrenchMalayUrduGermanMalteseVietnameseGreekNorwegianWelshHaitian CreolePersian   TRANSLATE with COPY THE URL BELOW BackEMBED THE SNIPPET BELOW IN YOUR SITE Enable collaborative features and customize widget: Bing Webmaster PortalBack

tourism attractions; urban mobility; spatial temporal analysis; circular urban tourism; Hungary

Aall, C., & Koens, K. (2019). The Discourse on Sustainable Urban Tourism: The Need for Discussing More Than Overtourism. Sustainability, 11(15), 4228. https://doi.org/10.3390/su11154228

Agresti, A. (2018). Statistical Methods for the Social Sciences (5th Global Edition). Pearson.

Alreahi, M., Bujdosó, Z., Lakner, Z., Pataki, L., Zhu, K., Dávid, L. D., & Kabil, M. (2023). Sustainable Tourism in the Post-COVID-19 Era: Investigating the Effect of Green Practices on Hotels Attributes and Customer Preferences in Budapest, Hungary. Sustainability, 15(15), 11859. https://doi.org/10.3390/su151511859

Ashworth, G., & Page, S. J. (2011). Urban tourism research: Recent progress and current paradoxes. Tourism Management, 32(1), 1–15. https://doi.org/10.1016/j.tourman.2010.02.002

BKK. (2024). Centre for Budapest Transport (BKK) [Official government website]. Budapesti Közlekedési Központ. https://bkk.hu/

Bouchon, F., & Rauscher, M. (2019). Cities and tourism, a love and hate story; towards a conceptual framework for urban overtourism management. International Journal of Tourism Cities, 5(4), 598–619. https://doi.org/10.1108/IJTC-06-2019-0080

Bucsky, P. (2020). Modal share changes due to COVID-19: The case of Budapest. Transportation Research Interdisciplinary Perspectives, 8, 100141. https://doi.org/10.1016/j.trip.2020.100141

Budapest Főváros Önkormányzata. (2024). Buadpest [Official government website]. https://archiv.budapest.hu/sites/english/Lapok/default.aspx

Chaitanya, A. K., & Swain, S. K. (2024). Economic leakages in tourism: A comprehensive review of theoretical and empirical perspectives. Tourism Economics, 30(5), 1306–1323. https://doi.org/10.1177/13548166231204648

Dalvi, M. Q., & Martin, K. M. (1976). The measurement of accessibility: Some preliminary results. Transportation, 5(1), 17–42. https://doi.org/10.1007/BF00165245

Dodds, R., & Butler, R. (2019). The phenomena of overtourism: A review. International Journal of Tourism Cities, 5(4), 519–528. https://doi.org/10.1108/IJTC-06-2019-0090

Edwards, D., Griffin, T., & Hayllar, B. (2008). Urban Tourism Research. Annals of Tourism Research, 35(4), 1032–1052. https://doi.org/10.1016/j.annals.2008.09.002

Ferenc Liszt International Airport. (2023). Facts About bud. https://www.bud.hu/en

Fink, C., Willberg, E., Klein, R., Heikinheimo, V., & Toivonen, T. (2024). A travel time matrix data set for the Helsinki region 2023 that is sensitive to time, mode and interpersonal differences, and uses open data and novel open-source software. Scientific Data, 11(1), 858. https://doi.org/10.1038/s41597-024-03689-z

Flügel, S., Halse, A. H., Hartveit, K. J. L., & Ukkonen, A. (2022). Value of travel time by road type. European Transport Research Review, 14(1), 35. https://doi.org/10.1186/s12544-022-00554-1

Garrigós-Simón, F. J., Galdón-Salvador, J. L., & Gil-Pechuán, I. (2015). The Economic Sustainability of Tourism Growth through Leakage Calculation. Tourism Economics, 21(4), 721–739. https://doi.org/10.5367/te.2014.0372

Graells-Garrido, E., Serra-Burriel, F., Rowe, F., Cucchietti, F. M., & Reyes, P. (2021). A city of cities: Measuring how 15-minutes urban accessibility shapes human mobility in Barcelona. PLOS ONE, 16(5), e0250080. https://doi.org/10.1371/journal.pone.0250080

Harsha, M. M., & Mulangi, R. H. (2022). Probability distributions analysis of travel time variability for the public transit system. International Journal of Transportation Science and Technology, 11(4), 790–803. https://doi.org/10.1016/j.ijtst.2021.10.006

He, B., Liu, K., Xue, Z., Liu, J., Yuan, D., Yin, J., & Wu, G. (2021). Spatial and Temporal Characteristics of Urban Tourism Travel by Taxi—A Case Study of Shenzhen. ISPRS International Journal of Geo-Information, 10(7), 445. https://doi.org/10.3390/ijgi10070445

Hocevar, M., & Bartol, T. (2021). Mapping urban tourism issues: Analysis of research perspectives through the lens of network visualization. International Journal of Tourism Cities, 7(3), 818–844. https://doi.org/10.1108/IJTC-05-2020-0110

Hristov, M., Danilovic-Hristic, N., & Stefanovic, N. (2021). Impact of overtourism on urban life. Spatium, 45, 59–66. https://doi.org/10.2298/SPAT2145059H

Hungarian Central Statistical Office - KSH. (2024). Tourist arrivals at tourist accommodation establishments [Official government website]. https://www.ksh.hu/en/first-releases/tsz/etsz2406.html

Hungarian Tourist Agency. (2023). National Tourism Development Strategy 2030 – Tourism 2.0 [Official government website]. https://mtu.gov.hu/cikkek/strategia/

Jaber, A., Csonka, B., & Juhasz, J. (2022). Long Term Time Series Prediction of Bike Sharing Trips: A Cast Study of Budapest City. 2022 Smart City Symposium Prague (SCSP), 1–5. https://doi.org/10.1109/SCSP54748.2022.9792540

Kellner, L., & Egger, R. (2016). Tracking Tourist Spatial-Temporal Behavior in Urban Places, A Methodological Overview and GPS Case Study. In A. Inversini & R. Schegg (Eds.), Information and Communication Technologies in Tourism 2016 (pp. 481–494). Springer International Publishing.

Kim, S., Filimonau, V., & Dickinson, J. E. (2023). Tourist Perception of the Value of Time on Holidays: Implications for the Time Use Rebound Effect and Sustainable Travel Practice. Journal of Travel Research, 62(2), 362–381. https://doi.org/10.1177/00472875211064636

Lacher, R. G., & Nepal, S. K. (2010). From Leakages to Linkages: Local-Level Strategies for Capturing Tourism Revenue in Northern Thailand. Tourism Geographies, 12(1), 77–99. https://doi.org/10.1080/14616680903493654

Li, J., Guo, X., Lu, R., & Zhang, Y. (2022). Analysing Urban Tourism Accessibility Using Real-Time Travel Data: A Case Study in Nanjing, China. Sustainability, 14(19), 12122. https://doi.org/10.3390/su141912122

Masiero, L., & Hrankai, R. (2022). Modeling tourist accessibility to peripheral attractions. Annals of Tourism Research, 92, 103343. https://doi.org/10.1016/j.annals.2021.103343

Mátrai, T., Tóth, J., & Cruz, J. (2020). How Cycling is Perceived in Budapest Based on Household Survey Results. Periodica Polytechnica Civil Engineering. https://doi.org/10.3311/PPci.14961

Michalkó, G., Bal, D., & Erdélyi, É. (2022). Repositioning Budapest’s tourism milieu for a post-Covid-19 period: Visual content analysis. European Journal of Tourism Research, 32, 3204. https://doi.org/10.54055/ejtr.v32i.2602

Miller, D., Merrilees, B., & Coghlan, A. (2015). Sustainable urban tourism: Understanding and developing visitor pro-environmental behaviours. Journal of Sustainable Tourism, 23(1), 26–46. https://doi.org/10.1080/09669582.2014.912219

Mokhtarian, P. L., & Salomon, I. (2001). How derived is the demand for travel? Some conceptual and measurement considerations. Transportation Research Part A: Policy and Practice, 35(8), 695–719. https://doi.org/10.1016/S0965-8564(00)00013-6

Morrison, A. M., & Maxim, C. (2021). World Tourism Cities: A Systematic Approach to Urban Tourism. Routledge Taylor & Francis Group.

Nesmachnow, S., Massobrio, R., Guridi, S., Olmedo, S., & Tchernykh, A. (2023). Big Data Analysis for Travel Time Characterization in Public Transportation Systems. Sustainability, 15(19), 14561. https://doi.org/10.3390/su151914561

Nilsson, J. H. (2020). Conceptualizing and contextualizing overtourism: The dynamics of accelerating urban tourism. International Journal of Tourism Cities, 6(4), 657–671. https://doi.org/10.1108/IJTC-08-2019-0117

OpenStreetMap contributor. (2024). OpenStreetMap. https://www.openstreetmap.org

Pearce, D. G. (2001). An integrative framework for urban tourism research. Annals of Tourism Research, 28(4), 926–946. https://doi.org/10.1016/S0160-7383(00)00082-7

Pérez Garrido, B., Sebrek, S. S., Semenova, V., Bal, D., & Michalkó, G. (2022). Addressing the Phenomenon of Overtourism in Budapest from Multiple Angles Using Unconventional Methodologies and Data. Sustainability, 14(4), 2268. https://doi.org/10.3390/su14042268

Pinke-Sziva, I., Smith, M., Olt, G., & Berezvai, Z. (2019). Overtourism and the night-time economy: A case study of Budapest. International Journal of Tourism Cities, 5(1), 1–16. https://doi.org/10.1108/IJTC-04-2018-0028

QGIS Development Team. (2024). QGIS Geographic Information System. https://qgis.org/

Şahin Körmeçli, P. (2024). Accessibility of Urban Tourism in Historical Areas: Analysis of UNESCO World Heritage Sites in Safranbolu. Sustainability, 16(6), 2485. https://doi.org/10.3390/su16062485

Smith, M. K., Sziva, I. P., & Olt, G. (2019). Overtourism and Resident Resistance in Budapest. Tourism Planning & Development, 16(4), 376–392. https://doi.org/10.1080/21568316.2019.1595705

Tenkanen, H., & Toivonen, T. (2020). Longitudinal spatial dataset on travel times and distances by different travel modes in Helsinki Region. Scientific Data, 7(1), 77. https://doi.org/10.1038/s41597-020-0413-y

Timur, S., & Getz, D. (2008). A network perspective on managing stakeholders for sustainable urban tourism. International Journal of Contemporary Hospitality Management, 20(4), 445–461. https://doi.org/10.1108/09596110810873543

TransitFeeds. (2024). TransitFeeds: Public Transit Data Sharing. https://transitfeeds.com/

Turner, S. M., Eisele, W. L., Benz, R. J., & Holdener, D. J. (1998). Travel Time Data Collection Handbook (FHWA-PL-98-035; p. 348). Texas Transportation Institute and The Texas A&M University System. https://www.fhwa.dot.gov/ohim/tvtw/natmec/00020.pdf

UNESCO. (2024). World Heritage List [Official UNESCO website]. https://whc.unesco.org/en/list/400/

United Nations Development Programme. (2021). What are the Sustainable Development Goals? https://www.undp.org/sustainable-development-goals?utm_source=EN&utm_medium=GSR&utm_content=US_UNDP_PaidSearch_Brand_English&utm_campaign=CENTRAL&c_src=CENTRAL&c_src2=GSR&gclid=EAIaIQobChMI7Pin2_OY9AIVSoxoCR1s8wKfEAAYAiAAEgLqy_D_BwE

Wan, J., Yan, J., Wang, X., Liu, Z., Wang, H., & Wang, T. (2019). Spatial-Temporal Pattern and Its Influencing Factors on Urban Tourism Competitiveness in City Agglomerations Across the Guanzhong Plain. Sustainability, 11(23), 6743. https://doi.org/10.3390/su11236743

Zhang, Y., Jiao, L., Yu, Z., Lin, Z., & Gan, M. (2020). A Tourism Route-Planning Approach Based on Comprehensive Attractiveness. IEEE Access, 8, 39536–39547. https://doi.org/10.1109/ACCESS.2020.2967060