Modelos e determinantes da demanda turística internacional
perspectivas a partir da revisão sistemática da literatura para o período de 2000-2020
DOI:
https://doi.org/10.7784/rbtur.v16.2478Palavras-chave:
Economia do Turismo, Demanda Turística, Revisão Sistemática da Literatura, Modelo de Demanda Turística, Determinantes da Demanda TurísticaResumo
O entendimento do processo de evolução das metodologias e do uso das variáveis que explicam a demanda turística é fundamental para compreender seus determinantes. Alguns estudos bibliométricos procuraram entender esse processo de evolução: Johnson e Ashworth (1990); Li, Song e Witt (2005) e Song, Qui e Park (2019). A maioria desses estudos tem se concentrado na discussão da evolução e eficiência dos modelos utilizados na análise e na previsão da demanda, dedicando pouca atenção às variáveis. Este artigo contribui para essa discussão avaliando a relação entre os modelos e as variáveis utilizadas na análise da demanda turística. Para isso, foi realizado um estudo bibliométrico nas principais bases de pesquisa internacional: Web of Science, Redalyc, Scielo, Spell e Publicações de Turismo, entre 2000 e 2020 (março) procurando responder duas perguntas: 1. Existe alguma relação entre a seleção dos modelos e o conjunto de variáveis utilizadas na demanda turística? 2. Existe alguma tendência na utilização de novas variáveis? O estudo constatou que, independente do modelo utilizado, a variável número de chegadas tem sido a mais utilizada para representar a demanda turística. Também foi observado que as variáveis independentes renda, preço e taxa de câmbio foram as mais recorrentes na literatura, havendo uma tendência para a incorporação de novas variáveis
Downloads
Referências
Agyeiwaah, E., & Adongo, R. (2016). Identifying core determinants of tourism demand in Hong Kong inbound markets. International Journal of Tourism Cities, 2(1), p. 17–28. https://doi.org/10.1108/IJTC-07-2015-0015
Ahmed, Y. A. (2015). Analytical Review of Tourism Demand Studies from 1960 to 2014. International Journal of Science and Research (IJSR), 14(1), p. 2319–7064. www.ijsr.net
Akter, H., Akhtar, S., & Ali, S. (2017). Tourism demand in Bangladesh: Gravity model analysis. Turizam: Međunarodni Znanstveno-Stručni Časopis, 65(3), p. 346–360.
Álvarez-Díaz, M., González-Gómez, M., & Otero-Giraldez, M. S. (2016). Modeling the tourism demand of emerging economies: The case of Russian tourist arrivals to Spain. Cuadernos de Economia-Spain, 39(110), p. 112–125. https://doi.org/10.1016/j.cesjef.2015.10.001
Athanasopoulos, G., & Hyndman, R. J. (2008). Modelling and forecasting Australian domestic tourism. Tourism Management, 29(1), p. 19–31. https://doi.org/10.1016/j.tourman.2007.04.009
Balli, F., Balli, H. O., & Tangaroa, N. (2015). Research note: The impact of marketing expenditure on international tourism demand for the Cook Islands. Tourism Economics, 21(6), p. 1331–1343. https://doi.org/10.5367/te.2014.0407
Cho, V. (2010). A Study the Non-economic Determinants in Tourism Demand. International Journal Of Tourism Research, 12(July 2009), p. 307–320. https://doi.org/10.1002/jtr.749
Croes, R. R., & Vanegas, M. (2005). An econometric study of tourist arrivals in Aruba and its implications. Tourism Management, 26(6), p. 879–890. https://doi.org/10.1016/j.tourman.2004.04.007
Crouch, G. I. (1994a). The Study of International Tourism Demand: A Review of Findings. Journal of Travel Research, 33(1), p. 12–23. https://doi.org/10.1177/004728759403300102
Crouch, G. I. (1994b). The Study of International Tourism Demand: A Review of Findings. Journal of Travel Research, 33(1), p. 12–23. https://doi.org/10.1177/004728759403300102
Crouch, G. I. (1995). A meta-analysis of tourism demand. Annals of Tourism Research, 22(1), p. 103–118. https://doi.org/10.1016/0160-7383(94)00054-V
Dogru, T., Bulut, U., & Sirakaya-Turk, E. (2019). Modeling tourism demand: Theoretical and empirical considerations for future research. Tourism Economics, p. 1–16. https://doi.org/10.1177/1354816619894460
Durbarry, R. (2008). Tourism taxes: Implications for tourism demand in the UK. Review of Development Economics, 12(1), p. 21–36. https://doi.org/10.1111/j.1467-9361.2008.00432.x
Falk, M., & Vieru, M. (2019). International tourism demand to Finnish Lapland in the early winter season. Current Issues in Tourism, 22(11), p. 1312–1326. https://doi.org/10.1080/13683500.2017.1412406
Gani, A., & Clemes, M. D. (2017). The main determinants effecting international visitor arrivals in New Zealand: Some empirical evidence. Tourism Economics, 23(5), p. 921–940. https://doi.org/10.1177/1354816616656417
Garin-Munoz, T. (2009). Tourism in Galicia: domestic and foreign demand. Tourism Economics, 15(4), p. 753–769. https://doi.org/10.5367/000000009789955107
Garín-Muñoz, T., & Montero-Martín, L. F. (2007). Tourism in the Balearic Islands: A dynamic model for international demand using panel data. Tourism Management, 28(5), p. 1224–1235. https://doi.org/10.1016/j.tourman.2006.09.024
Ghalehkhondabi, I., Ardjmand, E., Young, W. A., & Weckman, G. R. (2019). A review of demand forecasting models and methodological developments within tourism and passenger transportation industry. Journal of Tourism Futures, 5(1), p. 75–93. https://doi.org/10.1108/JTF-10-2018-0061
Goh, C., & Law, R. (2011). The methodological progress of tourism demand forecasting: A review of related literature. Journal of Travel and Tourism Marketing, 28(3), p. 296–317. https://doi.org/10.1080/10548408.2011.562856
Habibi, F. (2017). The determinants of inbound tourism to Malaysia: a panel data analysis. Current Issues in Tourism, 20(9), p. 909–930. https://doi.org/10.1080/13683500.2016.1145630
Hu, M., & Song, H. (2019). Data source combination for tourism demand forecasting. Tourism Economics, 26(7), p. 1248–1265. https://doi.org/10.1177/1354816619872592
Husein, J., & Kara, S. M. (2020). Nonlinear ARDL estimation of tourism demand for Puerto Rico from the USA. Tourism Management, 77. https://doi.org/10.1016/j.tourman.2019.103998
Jerabek, T. (2019). The Effects of Selected Macroeconomic Variables on Tourism Demand for the South Moravian Region of the Czech Republic from Germany, Poland, Austria, and Slovakia. Comparative Economic Research-Central and Eastern Europe, 22(3), p. 25–43. https://doi.org/10.2478/cer-2019-0021
Johnson, P., & Ashworth, J. (1990). Modelling tourism demand: A summary review. Leisure Studies, 9(2), p. 145– 161. https://doi.org/10.1080/02614369000390131
Kronenberg, K., Fuchs, M., Salman, K., Lexhagen, M., & Hopken, W. (2016). Economic effects of advertising expenditures - a Swedish destination study of international tourists. Scandinavian Journal of Hospitality and Tourism, 16(4), p. 352–374. https://doi.org/10.1080/15022250.2015.1101013
Kulendran, N., & Wong, K. K. F. (2011). Determinants versus Composite Leading Indicators in Predicting Turning Points in Growth Cycle. Journal of Travel Research, 50(4), p. 417–430. https://doi.org/10.1177/0047287510373280
Li, G., Song, H., & Witt, S. F. (2005). Recent developments in econometric modeling and forecasting. Journal of Travel Research, 44(1), 82–99. https://doi.org/10.1177/0047287505276594
Li, G., Wong, K. K. F., Song, H., & Witt, S. F. (2006). Tourism Demand Forecasting: A Time Varying Parameter Error Correction Model. Journal of Travel Research, 45(2), p. 175–185. https://doi.org/10.1177/0047287506291596
Lim, C., & Zhu, L. (2018). Examining the link between meetings, incentive, exhibitions, and conventions (MICE) and tourism demand using generalized methods of moments (GMM): the case of Singapore. Journal of Travel & Tourism Marketing, 35(7), p. 846–855. https://doi.org/10.1080/10548408.2018.1435334
Moro, S., & Rita, P. (2016). Forecasting tomorrow’s tourist. Worldwide Hospitality and Tourism Themes, 8(6), 643– 653. https://doi.org/10.1108/WHATT-09-2016-0046
Moura, F. A., & Montini, A. D. Á. (2010). Modelagem da Demanda Turística Internacional para o Estado de São Paulo. Sociedade, Contabilidade e Gestão, 5(2), p. 133–147. https://doi.org/10.21446/scg_ufrj.v5i2.13207
Naudé, W. A., & Saayman, A. (2005). Determinants of tourist arrivals in Africa: A panel data regression analysis. Tourism Economics, 11(3), p. 365–391. https://doi.org/10.5367/000000005774352962
Nouri, B. A., & Soltani, M. (2017). Forecasting of Tourism Demand for Cyprus: Generalized Method of Moments. Journal of Applied Economics and Business Research, 7(2), p. 83–96. Onafowora, O. A., & Owoye, O. (2012). Modelling international tourism demand for the Caribbean. TOURISM ECONOMICS, 18(1), p. 159–180. https://doi.org/10.5367/te.2012.0102
Seetanah, B., Durbarry, R., & Ragodoo, J. F. N. (2010). Using the panel cointegration approach to analyse the determinants of tourism demand in South Africa. Tourism Economics, 16(3), p. 715–729. https://doi.org/10.5367/000000010792278437
Seetanah, B., & Sannassee, R. V. (2015). Marketing Promotion Financing and Tourism Development: The Case of Mauritius. Journal of Hospitality Marketing & Management, 24(2), p. 202–215. https://doi.org/10.1080/19368623.2014.914359
Sharma, C., & Pal, D. (2020). Exchange Rate Volatility and Tourism Demand in India: Unraveling the Asymmetric Relationship. Journal of Travel Research, 59(7), p. 1282–1297. https://doi.org/10.1177/0047287519878516
Song, H., Kim, J. H., & Yang, S. (2010). CONFIDENCE INTERVALS FOR TOURISM DEMAND ELASTICITY. Annals of Tourism Research, 37(2), p. 377–396. https://doi.org/10.1016/j.annals.2009.10.002
Song, H., & Li, G. (2008). Tourism demand modelling and forecasting: A review of recent research. Tourim Management, 29(2), p. 203–220. https://doi.org/10.1016/j.tourman.2007.07.016
Song, H., Li, G., Witt, S. F., & Fei, B. (2010). Tourism demand modelling and forecasting: how should demand be measured? Tourism Economics, 16(1, SI), p. 63–81. https://doi.org/10.5367/000000010790872213
Song, H., Qiu, R. T. R., & Park, J. (2019). A review of research on tourism demand forecasting. Annals of Tourism Research, 75(September 2018), p. 338–362. https://doi.org/10.1016/j.annals.2018.12.001
Song, H., Romilly, P., & Liu, X. (2000). An empirical study of outbound tourism demand in the UK. Applied Economics, 32(5), p. 611–624. https://doi.org/10.1080/000368400322516
Song, H., Witt, S. F., & Li, G. (2003). Modelling and forecasting demand for Thai tourism. Tourism Economics, 9(4), p. 363–387. https://doi.org/10.5367/000000003322663186
Song, H., Witt, S. F., & Zhang, X. (2008). Developing a Web-based tourism demand forecasting system. Tourism Economics, 14(3), p. 445–468. https://doi.org/10.5367/000000008785633578
Tavares, J. M., & Leitao, N. C. (2017). The determinants of international tourism demand for Brazil. Tourism Economics, 23(4), p. 834–845. https://doi.org/10.5367/te.2016.0540
Ulucak, R., Yucel, A. G., & Ilkay, S. C. (2020). Dynamics of tourism demand in Turkey: Panel data analysis using gravity model. Tourism Economics, 26(8), p. 1394–1414. https://doi.org/10.1177/1354816620901956
UNWTO. (2020). UNWTO World Tourism Barometer: May 2020 – Special focus on the Impact of COVID-19. UNWTO World Tourism Barometer, May 2020 – Special Focus on the Impact of COVID-19, May. https://doi.org/10.18111/9789284421930
UNWTO. (2021). Tourist arrivals down 87% in january 2021 as UNWTO calls for stronger coordination to restart Tourism. https://www.unwto.org/taxonomy/term/347
Vanegas, M., & Croes, R. R. (2000). Evaluation of demand : US Tourists to Aruba. Annals of Tourism Research, 27(4), p. 946–963. https://doi.org/10.1016/S0160-7383(99)00114-0
Varian, H. R. (2010). Intermediate Microeconomics (J. Repcheck (ed.); 8th ed.). A modern Approach. Witt, S. F., & Witt, C. A. (1995). Forecasting tourism demand: A review of empirical research. International Journal of Forecasting, 11(3), p. 447–475. https://doi.org/10.1016/0169-2070(95)00591-7
Xu, L., Wang, S., Li, J., Tang, L., & Shao, Y. (2019). Modelling international tourism flows to China: A panel data analysis with the gravity model. Tourism Economics, 25(7), p. 1047–1069. https://doi.org/10.1177/1354816618816167
Zhang, Y. (2015). International arrivals to Australia: Determinants and the role of air transport policy. Journal of Air Transport Management, 44–45, p. 21–24. https://doi.org/10.1016/j.jairtraman.2015.02.004
Zhang, H. Q., & Kulendran, N. (2017). The Impact of Climate Variables on Seasonal Variation in Hong Kong Inbound Tourism Demand. Journal of Travel Research, 56 (1), p. 94–107. https://doi.org/10.1177/0047287515619692
Zhu, L., Lim, C., Xie, W., & Wu, Y. (2018). Modelling tourist flow association for tourism demand forecasting. Current Issues in Tourism, 21(8), p. 902–916. https://doi.org/10.1080/13683500.2016.1218827
Downloads
Publicado
Como Citar
Edição
Seção
Licença
Copyright (c) 2022 Isabela Lima Pinheiro da Camara, João Evangelista Dias Monteiro, Osiris Marques
Este trabalho está licenciado sob uma licença Creative Commons Attribution 4.0 International License.
Autores que publicam nesta revista concordam com os seguintes termos:
a. Autores mantém os direitos autorais e concedem à revista o direito de primeira publicação, com o trabalho simultaneamente licenciado sob a Licença Pública Creative Commons Atribuição 4.0 Internacional (CC BY 4.0) que permite o compartilhamento do trabalho com reconhecimento da autoria e publicação inicial nesta revista.
b. Autores têm autorização para assumir contratos adicionais separadamente, para distribuição não-exclusiva da versão do trabalho publicada nesta revista (ex.: publicar em repositório institucional ou como capítulo de livro), com reconhecimento de autoria e publicação inicial nesta revista.
c. Autores têm permissão e são estimulados a publicar e distribuir seu trabalho online (ex.: em repositórios institucionais ou na sua página pessoal) a qualquer ponto antes ou durante o processo editorial, já que isso pode gerar alterações produtivas, bem como aumentar o impacto e a citação do trabalho publicado (Veja O Efeito do Acesso Livre).
