Construction of a forecasting model for tourist attraction footfall

[1] Song, H., Wang, C., Meng, X., Siriwardana, M., & Pham, T. (2022). The impact of covid-19 on the chinese tourism industry:. Tourism Economics, 28(1), 131-152. Search in Google Scholar

[2] Erku-ztürk, & Hilal. (2017). Related variety and innovation: evidence from the tourism industry. Tijdschrift voor economische en sociale geografie. Search in Google Scholar

[3] Erol, I., Neuhofer, I. O., Dogru, T. T., Oztel, A., Searcy, C., & Yorulmaz, A. C. (2022). Improving sustainability in the tourism industry through blockchain technology: challenges and opportunities. Tourism management. Search in Google Scholar

[4] Li, Z., & Liu, H. (2022). How tourism industry agglomeration improves tourism economic efficiency?. Tourism Economics, 28. Search in Google Scholar

[5] Hu, M., Li, H., Song, H., Law, R., & Li, X. (2022). Tourism demand forecasting using tourist-generated online review data. Tourism management(Jun.), 90. Search in Google Scholar

[6] María Dolores Sánchez-Fernández, Lvarez-Bassi, D., & José Ramón-Cardona. (2020). Management of tourist destinations: the expectations of guests on ewom generation in maldonado (uruguay). Sustainability, 12(17), 6825. Search in Google Scholar

[7] Wen, L., Liu, C., Song, H., & Liu, H. (2020). Forecasting tourism demand with an improved mixed data sampling model. Journal of Travel Research, 60(3), 004728752090622. Search in Google Scholar

[8] Liu, P., Zhang, H., Zhang, J., Sun, Y., & Qiu, M. (2019). Spatial-temporal response patterns of tourist flow under impulse pre-trip information search: from online to arrival. Tourism Management, 73(AUG.), 105-114. Search in Google Scholar

[9] Zhang, B., Li, N., Law, R., & Liu, H. (2022). A hybrid midas approach for forecasting hotel demand using large panels of search data. Tourism Economics, 28. Search in Google Scholar

[10] Li, X., Ye, R., Fang, Z., Xu, Y., & Han, X. (2020). Uni- and bidirectional pedestrian flows through zigzag corridor in a tourism area: a field study. Adaptive Behavior, 105971232090223. Search in Google Scholar

[11] Athanasopoulos, G., Song, H., & Sun, J. A. (2018). Bagging in tourism demand modeling and forecasting:. Journal of Travel Research, 57(1), 52-68. Search in Google Scholar

[12] Zhang, Y., Li, X. R., David A. Cárdenas, & Liu, Y. (2022). Calculating theme parks’ tourism demand and attractiveness energy: a reverse gravity model and particle swarm optimization:. Journal of Travel Research, 61(2), 314-330. Search in Google Scholar

[13] Trull, O., Angel Peiró-Signes, & J. Carlos García-Díaz. (2019). Electricity forecasting improvement in a destination using tourism indicators. Sustainability, 11. Search in Google Scholar

[14] Bi, D., Xing, G., Sun, S., Ju‐e Guo, & Wang, S. (2022). Seasonal and trend forecasting of tourist arrivals: an adaptive multiscale ensemble learning approach. International Journal of Tourism Research, 24(3), 425-442. Search in Google Scholar

[15] Volchek, K., Liu, A., Song, H., & Buhalis, D. (2019). Forecasting tourist arrivals at attractions: search engine empowered methodologies. Tourism Economics, 25. Search in Google Scholar

[16] Tang, L., Zhang, C., Li, T., & Li, L. (2021). A novel bemd-based method for forecasting tourist volume with search engine data. Tourism Economics, 27. Search in Google Scholar

[17] Hu, M., Xiao, M., & Li, H. (2021). Which search queries are more powerful in tourism demand forecasting: searches via mobile device or pc?. International Journal of Contemporary Hospitality Management, ahead-of-print(ahead-of-print). Search in Google Scholar

[18] Saayman, A., & Klerk, J. D. (2019). Forecasting tourist arrivals using multivariate singular spectrum analysis. Tourism Economics, 25(3), 330-354. Search in Google Scholar

[19] Wu, D. C. W., Ji, L., He, K., & Tso, K. F. G. (2020). Forecasting tourist daily arrivals with a hybrid sarima–lstm approach. Journal of Hospitality & Tourism Research, 45(1), 109634802093404. Search in Google Scholar

[20] Danbatta, S. J., & Varol, A. (2022). Ann–polynomial–fourier series modeling and monte carlo forecasting of tourism data. Journal of Forecasting, 41. Search in Google Scholar

[21] Zubiaga, M., Izkara, J. L., Gandini, A., Alonso, I., & Saralegui, U. (2019). Towards smarter management of overtourism in historic centres through visitor-flow monitoring. Sustainability, 11. Search in Google Scholar