MODELING TOURIST ARRIVALS IN THE ISLAND GARDEN CITY OF SAMAL: IMPLICATIONS TO BUSINESS OPERATIONS OF TOURISM-RELATED INDUSTRY
Abstract
This study aimed to model the tourist arrivals in the Island Garden City of Samal (IGaCoS) by utilizing the autoregressive integrated moving average (ARIMA) method. Specifically, this paper sought to determine whether there was a statistically appropriate forecasting model using the ARIMA approach, based on which it would be possible to reasonably forecast the number of tourist arrivals in IGaCoS. Quantitative secondary data were analyzed by employing the Box-Jenkins ARIMA. The time series plot was characterized by an apparent increasing trend combined with intermittent sinusoidal oscillations. The time series revealed a steady, gradual increase up until 2020. Next, a sharp decline was observed midway through 2020, indicative of the ill effects of the COVID-19 pandemic. A gradual increase was noted once more, starting in 2021, with some fluctuations. The Augmented Dickey-Fuller (ADF) test revealed that the time series was non-stationary at level— but was made stationary after differenced twice. The ARIMA (1,2,1) model was found to be statistically significant. The fitted model initially showed some notable deviations from the original data, but, with time, converged closely to the actual values, proving it is a reliable way to represent underlying patterns. The ARIMA (1,2,1) model, selected for having the lowest AIC and BIC values and a MAPE within the acceptable range for reasonable forecasting, was used to predict tourist arrivals in IGaCoS over the next six months. The forecasted values suggested a mix of fluctuations and stability. There was a noticeable upward trajectory at the beginning, which was followed by a slight decline at the end that yet remained stable. The forecasted results from the ARIMA (1,2,1) model may provide businesses with a roadmap for comprehensive planning in terms of operational and strategic concerns. This study helped address Sustainable Development Goal (SDG) No. 8, Decent Work and Economic Growth.
JEL: L83, R11, C53
Article visualizations:
Keywords
Full Text:
PDFReferences
Abdou, M, Musabanganji, E & Musahara, H, 2021. Tourism Demand Modelling and Forecasting: A Review of Literature. African Journal of Hospitality, Tourism and Leisure, vol. 10, no. 4, pp. 1370-1393. https://doi.org/10.46222/ajhtl.19770720-168
Abellana D, Rivero D, Aparente ME & Rivero, R, 2021. Hybrid SVR-SARIMA model for tourism forecasting using PROMETHEE II as a selection methodology: a Philippine scenario. Journal of Tourism Futures, vol. 7, no. 1. http://dx.doi.org/10.1108/JTF-07-2019-0070
Abing, AG, 2024. Exploring Tourists’ Perspective on Environmental Fees in The Island Garden City of Samal. International Journal of Progressive Research in Engineering Management and Science (IJPREMS), vol. 4, no. 6, pp: 173-176. Retrieved from https://www.ijprems.com/uploadedfiles/paper//issue_6_june_2024/34750/final/fin_ijprems1717605288.pdf
Agada, IO, Eweh, EJ & Aondoakaa, SI, 2021. Time series ARIMA model for predicting monthly net radiation. Fudma Journal of Sciences, vol. 5, no. 4, pp.182-193. https://doi.org/10.33003/fjs-2021-0504-805
Almeida, A, Brás, S, Oliveira, I & Sargento, S, 2022. Vehicular traffic flow prediction using deployed traffic counters in a city. Future Gener. Comput. Syst. 2022, vol. 128, pp. 429–442. http://dx.doi.org/10.1016/j.future.2021.10.022
Andulana, DD, Calijan, MT & Albina, AC, 2021. Challenges and Opportunities in Philippine Tourism amid the COVID-19 Pandemic, December 2021. http://dx.doi.org/10.32871/rmrj.2109.02.08
Angelaccio, M, 2019. Forecasting Public Electricity Consumption with ARIMA Model: A Case Study from Italian Municipalities Energy Data, 2019. International Symposium on Advanced Electrical and Communication Technologies (ISAECT), 1-3. Retrieved from https://ieeexplore.ieee.org/document/9069696
Anisa, MP, Irawan, H & Widiyanesti, S, 2021. Forecasting demand factors of tourist arrivals in Indonesia’s tourism industry using recurrent neural network. IOP Conf. Series: Materials Science and Engineering 1077 (2021) 012035 IOP Publishing. http://dx.doi.org/10.1088/1757-899X/1077/1/012035
Anu, A, Gautam, N, Gautam, PK, Singh, J, Sharma, S, Kaushik, A & Obaid, AJ, 2022. Impact of post-COVID-19 on the hospitality tourism: Impact evaluation, survive, revive and thrive. International Journal of Health Sciences, vol. 6(S2), pp. 7152–7172. https://doi.org/10.53730/ijhs.v6nS2.6780
Arowosafe, FC, Akinwotu, O, Tunde-Ajayi, OA, Omosehin, OO & Osabuohien, ES, 2021. Push and pull motivation factors: a panacea for tourism development challenges in Oluminrin waterfalls, Nigeria. Journal of Policy Research in Tourism, Leisure and Events, vol. 14, pp. 63 – 74. http://dx.doi.org/10.1080/19407963.2021.2017729
Atasoy, E, Kabıyev, Y, Alıaskarov, DT & Kaimuldinova, Kvd, 2022. The South Tourism Regions of the Island of Mindanao from the Perspective of Tourism Geography. Uluslararası Yönetim Akademisi Dergisi, vol. 5, no. 2, pp. 267-293. https://doi.org/10.33712/mana.1147467
Bakar, NA & Rosbi, S, 2020. Effect of Coronavirus disease (COVID-19) to tourism industry. International Journal of Advanced Engineering Research and Science, vol. 7, no. 4, pp. 189–193. https://doi.org/10.22161/ijaers.74.23
Bartik, AW, Bertrand, M, Cullen, Z, Glaeser, E, Luca, M & Stanton, C, 2020. The impact of COVID-19 on small business outcomes and expectations. Proceedings of the National Academy of Sciences 117: 17656–66. https://doi.org/10.1073/pnas.2006991117
Bespalova, OG, 2022. Modeling and Forecasting Monthly Tourism Arrivals Since the COVID-19 Pandemic: Aruba Case. IMF Working Papers 2022/226, International Monetary Fund. Retrieved January 14, 2023, from https://www.imf.org/en/Publications/WP/Issues/2022/11/11/Modeling-and-Forecasting-Monthly-Tourism-Arrivals-to-Aruba-Since-COVID-19-Pandemic-525638
Bhowmik, D, 2020. Trends, Cycles and Seasonal Variations of Ukrainian Gross Domestic Product. Financial Markets, Institutions and Risks, vol. 4, no. 3, pp. 80-94. http://dx.doi.org/10.21272/fmir.4(3).80-94.2020
Bi, JW, Liu, Y & Li, H, 2020. Daily tourism volume forecasting for tourist attractions.
Annals of Tourism Research, vol. 83. Retrieved July 16, 2024, from https://doi.org/10.1016/j.annals.2020.102923
Botero, CM, Cabrera, JA, Mercadé, S, Bombana, B, 2020. Análisis general y recomendaciones para afrontar la crisis de la COVID-19 en el turismo de sol y playa, In El Turismo de sol y Playa en el Contexto de la COVID-19. Escenarios y Recomendaciones; Eds.; Red Iberoamericana Proplayas: Santa Marta, Colombia, 2020, pp. 10–31. Retrieved from https://ri.conicet.gov.ar/bitstream/handle/11336/140731/CONICET_Digital_Nro.3952a361-cd77-47e4-90a2-f5e173bdc959_A.pdf?sequence=2
Caynila, KA, Luna, K & Milla, SA, 2022. The Philippine Tourism Sector Amid the Pandemic: Developments and Prospects. Economic Newsletter, no. 22-02. Retrieved June 18, 2023, from https://www.bsp.gov.ph/Media_And_Research/Publications/EN22-02.pdf
Centeno, R & Marquez, J, 2020. How much did the Tourism Industry Lost? Estimating Earning Loss of Tourism in the Philippines, Retrieved February 12, 2023, from https://arxiv.org/abs/2004.09952
Chipumuro, M & Chikobvu, D, 2022. Modelling Tourist Arrivals in South Africa To Assess the Impact of the COVID-19 Pandemic on the Tourism Sector. African Journal of Hospitality, Tourism and Leisure, vol. 11, no. 4, pp. 1381-1394. https://doi.org/10.46222/ajhtl.19770720.297
Cordero, T, 2021. Foreign tourist arrivals in Philippines plunge 83.7% in 2020, amid COVID-19 pandemic. GMA News Online. Retrieved February 04, 2023, from https://www.gmanetwork.com/news/money/economy/771410/foreign-touristarrivals-in-philippines-plunge-83-7-in-2020-amid-covid-19-pandemic/story/
Çuhadar, M, 2020. Modelling and forecasting inbound tourism demand to Croatia using artificial neural networks: a comparative study. Journal of Tourism and Services, vol. 11, no. 21, pp. 55-70. https://doi.org/10.29036/jots.v11i21.171
Dalagan, AM & Sy, Jr M, 2023. Post-Pandemic Business Recovery Experiences of Samal Island Beach Resorts Owners: A Hermeneutic Phenomenological Inquiry. International Journal of Research and Innovation in Social Science, pp. 475-491. Retrieved September 11, 2024, from https://dx.doi.org/10.47772/IJRISS.2023.7012040
Dann, GMS, 1977. Anomie, Ego-Enhancement and Tourism. Annals of Tourism Research, vol. 4, no. 4, pp. 184-194. https://doi.org/10.1016/0160-7383(77)90037-8
Department of Tourism, 2019. Philippine Tourism Statistics, PowerPoint Presentation, March 2020, Butuan City, Philippines. Retrieved February 22, 2023, from http://www.tourism.gov.ph/industry_performance/Dissemination_forum/2019_Tourism_Industry_Report.pdf
Diunugala, HP & Mombeuil, C, 2020. Modeling and predicting foreign tourist arrivals to Sri Lanka: A comparison of three different methods. Journal of Tourism, Heritage & Services Marketing, vol. 6, is. 3, pp. 3-13. http://doi.org/10.5281/zenodo.4055960.
Doğan, B, Ghosh, S, Tiwari, AK & Abakah, EJ, 2022. The effect of global volatility, uncertainty and geopolitical risk factors on international tourist arrivals in Asia. International Journal of Tourism Research, vol. 25, no. 1, pp. 1-62. Retrieved September 04, 2024, from https://doi.org/10.1002/jtr.2550
Eleni, S, 2020. Forecasting tourism demand in Greece by using Time-series. Retrieved January 06, 2023, from https://repository.ihu.edu.gr/xmlui/bitstream/handle/11544/29915/Forecasting20Tourism%20Demand%20In%20Greece_Saltsidou.pdf?sequence=1
Esquivas, MA, Sugiharti, L, Rohmawati, H & Sethi, N, 2021. Impacts and implications of a pandemic on tourism demand in Indonesia. Economics and Sociology, vol. 14, no. 4, pp. 133-150. http://dx.doi.org/10.14254/2071-789X.2021/14-4/8
Ete, AA, Suhartono, R & Atok, M, 2020. SSA and ARIMA for Forecasting Number of Foreign Visitor Arrivals to Indonesia. INFERENSI, vol. 3, no. 1. Retrieved June 22, 2024, from https://www.semanticscholar.org/paper/SSA-and-ARIMA-for-Forecasting-Number-of-Foreign-to-Ete-Suhartono/9f47484efd8677592c1ef1eb44c8d947122eec48
European Chamber of Commerce of the Philippines (ECCP), 2022. The Future of Tourism: Exploring the Glamour of Samal Island. Retrieved March 06, 2023, from https://www.eccp.com/events/1216#:~:text=As%20a%20response%2C%20the%20European,to%20discuss%20the%20awaiting%20opportunities
Fatima, N, Alamgir, A & Khan, MA, 2022. Rainfall forecast using SARIMA model along the coastal areas of Sindh Province. International Journal of Economic and Environmental Geology, vol. 13, no. 4, pp. 35-41. http://dx.doi.org/10.46660/ijeeg.v13i4.51
Gaetano, P, 2022. Using the SARIMA Model to Forecast the Fourth Global Wave of Cumulative Deaths from COVID-19: Evidence from 12 Hard-Hit Big Countries. Econometrics, vol. 10, no. 18. https://doi.org/10.3390/econometrics10020018
Ghalehkhondabi, I, Ardjmand, E, Young, WA & Weckman, GR, 2019. A review of demand forecasting models and methodological developments within tourism and passenger transportation industry. Journal of Tourism Futures, vol. 5, no. 1, pp. 75-93. https://doi.org/10.1108/JTF-10-2018-0061
Gössling, S, Scott, D & Hall, CM, 2021. Pandemics, tourism and global change: A rapid assessment of COVID-19. J. Sustain. Tour., pp. 1–20. Retrieved from https://portal.research.lu.se/en/publications/pandemics-tourism-and-global-change-a-rapid-assessment-of-covid-1
Goumas, S & Kontakos, S, 2021. Modeling and Forecasting of Tourist Arrivals in Crete Using Statistical Models and Models of Computational Intelligence: A Comparative Study. International Journal of Operations Research and Information Systems, vol. 12, no. 1. http://dx.doi.org/10.4018/IJORIS.2021010105
Gričar, S, 2023. Tourism Forecasting of “Unpredictable” Future Shocks: A Literature Review by the PRISMA Model. Journal of Risk and Financial Management, vol. 16, no. 493. http://dx.doi.org/10.3390/jrfm16120493
Gričar, S, Šugar, V & Baldigara, T, 2022. Some considerations about tourist arrivals and the COVID-19 pandemic – evidence from Slovenia and Croatia. Economic Research-Ekonomska Istraživanja. Retrieved March 12, 2023, from DOI: 10.1080/1331677X.2022.2053781. https://doi.org/10.1080/1331677X.2022.2053781
Guleria, S, 2019. Rationale of Push and Pull Theory Through IT in Tourist Motivations and Destination Attributes: A Case Study of Mcleodganj (HP) As Tourist Destination. Proceedings of 10th International Conference on Digital Strategies for Organizational Success, pp. 921-934. https://dx.doi.org/10.2139/ssrn.3317772
Haryanto, T, 2020. COVID-19 pandemic and international tourism demand. JDE (Journal of Developing Economies), vol. 5, pp. 1–5. Retrieved from https://e-journal.unair.ac.id/JDE/article/download/19767/10766/74189
Hassouna, F & Al-Sahili, K, 2020. Practical Minimum Sample Size for Road Crash Time-Series Prediction Models. Advances in Civil Engineering, vol. 2020. Retrieved March 12, 2023, from https://doi.org/10.1155/2020/6672612
Höpken, W, Eberle, T, Fuchs, M, & Lexhagen, M, 2021. Improving Tourist Arrival Prediction: A Big Data and Artificial Neural Network Approach. Journal of Travel Research, vol. 60, no. 5, pp. 998-1017. Retrieved March 02, 2023, from https://doi.org/10.1177/0047287520921244
Hossen, SM, Ismail, TM, Tabash, MI & Abousamak, A, 2021. Accrued Forecasting On Tourist’s Arrival in Bangladesh for Sustainable Development. GeoJournal of Tourism and Geosites, vol. 36(2spl), pp. 708–714. https://doi.org/10.30892/gtg.362spl19-701
Hu, H, Yang, Y & Zhang, J, 2021. Avoiding panic during pandemics: COVID-19 and tourism-related businesses. Tourism Management, vol. 86. Retrieved from https://doi.org/10.1016/j.tourman.2021.104316
Hussain, JN, 2021. Using Transformations to Predict and Smooth Time Series. Turkish Journal of Computer and Mathematics Education (TURCOMAT), vol. 12, no. 4, pp. 647-653. Retrieved from https://turcomat.org/index.php/turkbilmat/article/view/548
Huynh, DV, Truong, TTK, Duong, LH, Nguyen, NT, Dao, GVH & Dao, CN, 2021. The COVID-19 Pandemic and Its Impacts on Tourism Business in a Developing City: Insight from Vietnam. Economies, vol. 9, no. 4, p. 172. https://doi.org/10.3390/economies9040172
Ilmayasinta, N, 2021. Peramalan Kedatangan Wisatawan Asing Menggunakan Seasonal Arima Box-Jenkins. Barekeng: J. Il. Mat. & Ter., vol. 15, no. 02, pp. 223-230, June 2021. https://doi.org/10.30598/barekengvol15iss2pp223-230
Imam, A, 2020. Investigation of Parameter Behaviors in Stationarity of Autoregressive and Moving Average Models through Simulations. Asian Journal of Mathematical Sciences 4(4). https://doi.org/10.22377/ajms.v4i4.295
Sciences, vol. 4, is. 4 International Trade Centre, 2020. SME Competitiveness Outlook 2020: Covid-19: Great Lockdown and its Impact on Small Business. ITC, Geneva. Retrieved from http://www.intracen.org/SMEOutlook/
Jackson, EA & Tamuke, E, 2019. Predicting disaggregated tourist arrivals in Sierra Leone using ARIMA model. Theoretical and Practical Research in Economic Fields, vol. 10, no. 2, pp.132-142. https://doi.org/10.14505/tpref.v10.2(20).06
Jaffur, ZK, Tandrayen-Ragoobur, V, Seetanah, B & Gopy-Ramdhany, N, 2022. Impact of COVID-19 on a tourist-dependent economy and policy responses: the case of Mauritius. Journal of Policy Research in Tourism, Leisure and Events. http://dx.doi.org/10.1080/19407963.2022.2113090
Jamal, NF, Abdul Ghafar, NM, Chek, MZA & Ismail, IL, 2019. Research of Forecasting on Tourist Arrivals to Malaysia. International Journal of Innovative Technology and Exploring Engineering (IJITEE), vol. 8, no. 12, pp. 686-689. Retrieved from https://www.ijitee.org/wp-content/uploads/papers/v8i12S2/L111910812S219.pdf
Jaya, GN & Sunengsih, N, 2022. Forecasting For the Arrival of International Tourists After Two Years of The Covid-19 Pandemic in Indonesia. International Journal of Applied Research in Social Sciences, vol. 4, no. 1, pp. 1-8. https://doi.org/10.51594/ijarss.v4i1.297
Johar, K, Tan, D, Maung, Y & Douglas, I, 2022. Destination Marketing: Optimizing Resource Allocation Using Modern Portfolio Theory. Journal of Travel Research, vol. 61, no. 6, pp. 1358-1377. https://doi.org/10.1177/00472875211025099
Juznik Rotar, L, Kontosic Pamic, R & Bojnec, S, 2019. Contributions of small and medium enterprises to employment in the European Union countries. Economic Research-Ekonomska Istrazivanja, vol. 32, no. 1, pp. 3302–3314. https://doi.org/10.1080/1331677X.2019.1658532
Kaewmanee, P, Muangprathub, J & Sae-jie, W, 2021. Forecasting Tourist Arrivals with Keyword Search using Time Series. 2021 18th International Conference on Electrical Engineering/Electronics, Computer, Telecommunications and Information Technology (ECTI-CON), pp. 171-174. https://doi.org/10.1109/ECTI-CON51831.2021.9454824
Ke, W, 2024. Tourism Demand Forecast and Future Market Trend Research. Advances in Politics and Economics, vol. 7, no. 2, pp. 202-210. http://dx.doi.org/10.22158/ape.v7n2p202
Khan, A, Bibi, S, Lorenzo, A, Lyu, J & Babar, ZU, 2020. Tourism and Development in Developing Economies: A Policy Implication Perspective. Sustainability 2020, vol. 12, no. 1618. https://doi.org/10.3390/su12041618
Kiran, N & Reddy, M, 2022. Forecasting Analysis of International Tourist Arrivals to Hyderabad, India, Using ARIMA Model. Mathematical Statistician and Engineering Applications, vol. 71, no. 4, pp. 3801-3812. https://doi.org/10.17762/msea.v71i4.944
Kourentzes, N, Saayman, A, Jean-Pierre, P, Provenzano, D, Sahli, M, Seetaram, N & Volo, S, 2021. Visitor arrivals forecasts amid COVID-19: A Perspective from the Africa team. Annals of Tourism Research, vol. 88. https://doi.org/10.1016/j.annals.2021.103197
Kyriakaki, A, Stavrinoudis, T & Daskalopoulou, G, 2020. Investigating the Key Factors Influencing the International Tourists’ Decision-Making on Choosing a Destination, Springer Proceedings in Business and Economics, pp. 335-352. Retrieved from https://www.researchgate.net/publication/338913720_Investigating_the_Key_Factors_Influencing_the_International_Tourists'_Decision-making_on_Choosing_a_Destination
Lakshmi, MM, Sandhyai, D & Rakesh, P, 2024. Supply Chain Management Enhance NG Efficiency and Collaboration Industry Company. International Research Journal on Advanced Engineering and Management (IRJAEM), vol. 2, no. 5, pp. 1762-1765. http://dx.doi.org/10.47392/IRJAEM.2024.0261
Law, R, Li, G, Fong, DKC & Han, X, 2019. Tourism demand forecasting: A deep learning approach. Annals of Tourism Research, vol. 75, pp. 410-423. https://doi.org/10.1016/j.annals.2019.01.014
Li, G & Wu, DC, 2019. Introduction to the special issue: Tourism forecasting – New trends and issues. Tourism Economics, vol. 25, no. 3, pp. 305–308. https://doi.org/10.1177/1354816618816809
Lin, S, 2023. Forecasting the trend of the tourism industry in the United States: using ARIMA model and ETS model. Highlights in Business, Economics and Management, vol. 10, pp. 111-121. Retrieved from http://dx.doi.org/10.54097/hbem.v10i.7964
Liu, A, Vici, L, Ramos, V, Giannoni, S & Blake, A, 2021. Visitor arrivals forecasts amid COVID-19: A perspective from the Europe team. Annals of Tourism Research, vol. 88. https://doi.org/10.1016/j.annals.2021.1031820160-7383
Makoni, T & Chikobvu, D, 2021. Modelling International Tourist Arrivals Volatility in Zimbabwe Using a GARCH Process. African Journal of Hospitality, Tourism and Leisure, vol. 10, no. 1, pp. 639-653. https://doi.org/10.46222/ajhtl.19770720-123
Makoni, T, Mazuruse, G & Nyagadza, B, 2023. International tourist arrivals modelling and forecasting: A case of Zimbabwe. Sustainable Technology and Entrepreneurship, vol. 2, no. 1. http://dx.doi.org/10.1016/j.stae.2022.100027
Malangalila, SR & Mhache, EP, 2023. The Role of Local Government in the Development of Tourism in Iringa Region, Tanzania. International Journal for Multidisciplinary Research, vol. 5, no. 5, pp. 1-13. http://dx.doi.org/10.1080/09709274.2013.11906553
Maliberan, R, 2019. Forecasting Tourist Arrival in the Province of Surigao del Sur, Philippines, using Time Series Analysis. International Journal on Informatics Visualization, vol. 3, no. 3. Retrieved from http://dx.doi.org/10.30630/joiv.3.3.268
Mammen, J, Alessandri, TM & Weiss, M, 2019. The risk implications of diversification: Integrating the effects of product and geographic diversification. Long Range Planning, vol. 54, no. 1. https://doi.org/10.1016/j.lrp.2019.101942
Michael, N, Nyadzayo, MW, Michael, I & Balasubramanian, S, 2020. Differential roles of push and pull factors on escape for travel: Personal and social identity perspectives. International Journal of Tourism Research, vol. 22, pp. 464-478. https://doi.org/10.1002/jtr.2349
Msofe, ZA & Mbago, MC, 2019. . Gen. Lett. Math. 2019, vol. 7, pp. 100– 107Forecasting international tourist arrivals in Zanzibar using Box–Jenkins SARIMA model. Retrieved from https://www.refaad.com/Files/GLM/7-2-6.pdf
Murodova, N, 2024. Tourism Pricing Strategies. European International Journal of Multidisciplinary Research and Management Studies, vol. 4, no. 4, pp. 216-222. Retrieved from https://www.eipublication.com/index.php/eijmrms/article/view/1762
Mursalina, R, Masbar & Suriani, 2022. Impact of Covid-19 Pandemic on Economic Growth of the Tourism Sector in Indonesia. International Journal of Quantitative Research and Modeling, vol. 3, no. 1, pp. 18-28. Retrieved April 08, 2023, from https://journal.rescollacomm.com/index.php/ijqrm/index
Nagendrakumar, N, Lokeswara, AA, Gunawardena, SADCK, Kodikara, UP, Rajapaksha, RWNH & Ratnayake, KRMCS, 2021. Modeling and forecasting tourist arrivals in Sri Lanka. SLIIT Business Review, vol. 1, no. 2, pp. 95-120. https://doi.org/10.54389/GKED9337
Nguyen, KT, 2020. Safety Plan during Covid-19 Pandemic in Restaurant Industry: Case Study: KOKORO Sushi. Vantaa: Laurea University, pp. 1-39. Retrieved from https://www.theseus.fi/bitstream/handle/10024/354657/Nguyen_Thanh.pdf?sequence=2
Nikitenko, K, 2024. The Specifics of Tourism Business Management in The Conditions of Global Instability. Actual Problems of Economics, vol. 1, no. 275, pp. 34-40
Nwokike, CC, Offorha, BC, Maxwell, O, Uche-Ikonne, O & Onwuegbulam, CC, 2020. ARIMA Modelling of Neonatal Mortality in Abia State of Nigeria. Asian Journal of Probability and Statistics, vol. 6, no. 2, pp. 54-62. https://doi.org/10.9734/ajpas/2020/v6i230158
Nyagadza, B & Chigora, F, 2022. Futurology of ethical tourism digital & social media marketing post-COVID-19, In A. Sharma, A. Hassan, P. Mohanty (Eds.), Chapter 6 in COVID-19 and Tourism Sustainability: Ethics, Responsibilities, Challenges and New Directions Eds. Routledge, Taylor & Francis, Abingdon, United Kingdom (UK). Retrieved from https://www.routledge.com/COVID-19-and-the-Tourism-Industry-Sustainability-Resilience-and-New-Directions/Sharma-Hassan-Mohanty/p/book/9781032075129
OECD, 2020. Tourism Policy Responses to the coronavirus (COVID-19). Retrieved January 20, 2023. from https://www.oecd.org/coronavirus/policy-responses/tourism-policyresponses-to-the-coronavirus-covid-19-6466aa20/
Polintan SN, Cabauatan LL, Nepomuceno JP, Mabborang RC & Lagos JC, 2023. Forecasting Gross Domestic Product in the Philippines Using Autoregressive Integrated Moving Average (ARIMA) Model. European Journal of Computer Science and Information Technology, vol.11, no.2, pp.100-124. Retrieved from https://doi.org/10.37745/ejcsit.2013/vol11n2100124
Prastyadewi, MI, Tantra, IGLP & Pramandari, PY, 2023. Digitization and Prediction of The Number of Tourist Visits in The Bali Province. Jurnal Ekonomi dan Bisnis Jagaditha, vol. 10, no. 1, pp. 89-97. http://dx.doi.org/10.22225/jj.10.1.2023.89-97
PricewaterhouseCoopers (PWC), 2020. Impact of COVID-19 on the Philippine tourism industry. Retrieved November 18, 2020, from https://www.pwc.com/ph/en/publications/tourism-pwc-philippines/tourism-covid-19.html
Priyadarshini, E, Preethi, ES, Vidhya, M, Chakkravarthi, S & Govindarajan, A, 2022. Modeling and forecasting using auto-regressive integrated moving average. 2nd International Conference on Mathematical Techniques and Applications: ICMTA2021. http://dx.doi.org/10.1063/5.0108756
Rodrı´guez, RP & Gallego, MS, 2020. Modelling tourism receipts and associated risks using long-range dependence models. Tourism Economics 2020, vol. 26, no. 1, pp. 70–96. https://doi.org/10.1177/1354816619828170
Rosli, S & Jamil, N, 2020. Conceptual Framework Related to The Impact of Coronavirus Disease 2019 (Covid-19) on Malaysian Private Entity Reporting Standard (MPERS) Adoption by Small and Medium Enterprises (SMES) In Malaysia. Penang: Universiti Sains Islam Malaysia. https://doi.org/10.33102/uij.vol33noS4.413
Ruiz Reina, MÁ, 2021. Entropy Method for Decision-Making: Uncertainty Cycles in Tourism Demand. Entropy 2021, vol. 23, no. 1370. https://doi.org/10.3390/e23111370
Ryan, O, Haslbeck, J & Waldorp, L, 2023. Non-Stationarity in Time-Series Analysis: Modeling Stochastic and Deterministic Trends. Retrieved February 20, 2024, from: https://osf.io/z7ja2/download
Sadhale, M & Sathe, S, 2020. A Study of Push and Pull Factors Influencing Travel Preferences of Gen X Travelers from Pune City. International Journal of Disaster Recovery and Business Continuity, vol.11, no. 1, pp. 536-551. Retrieved from http://sersc.org/journals/index.php/IJDRBC/article/view/7501
Santamaria, ER, 2020. Sustainable Local Tourism Industry in BLOM Areas. International Association of Scholarly Publishers, Editors and Reviewers, Inc., vol. 20. Retrieved from https://aseanresearch.org/downloads/iasper/publication/13/4_EDRICK%20RAY%20S%20SANTAMARIA.pdf
Segal, UA, 2019. Globalization, migration, and ethnicity. Public health, vol. 172, pp. 135-142. https://doi.org/10.1016/j.puhe.2019.04.011
Šenková, A, Košíková, M, Matušíková, D, Šambronská, K, Kravˇcáková Vozárová, I & Kotuliˇc, R, 2021. Time Series Modeling Analysis of the Development and Impact of the COVID-19 Pandemic on Spa Tourism in Slovakia. Sustainability 2021, vol. 13, no. 11476. https://doi.org/10.3390/su132011476
Serrona, KRB, Yu, J & Camarin, MJA, 2022. Addressing Marine Litter through Sustainable Tourism: The Case of the Siargao Islands in the Southern Philippines, ADBI Working Paper 1302, Tokyo: Asian Development Bank Institute. Retrieved March 15, 2023, from https://www.adb.org/publications/addressing-marine-litter-through-sustainable-tourism-thecase-of-the-siargao-islands-in-the-southern-philippines
Sigala, M, 2020. Tourism and COVID-19: Impacts and implications for advancing and resetting industry and research. Journal of Business Research (2020), vol. 117, pp. 312-321. Retrieved from http://dx.doi.org/10.1016/j.jbusres.2020.06.015
Song, H, Qiu, R & Park, J, 2019. A review of research on tourism demand forecasting: launching the annals of tourism research curated collection on tourism demand forecasting. Annals of Tourism Research, vol. 75, pp. 338-362. https://doi.org/10.1016/j.annals.2018.12.001
Sonobe, TA, Takeda, S, Yoshida & HT Truong, 2021. The Impacts of the COVID-19 Pandemic on Micro, Small, and Medium Enterprises in Asia and Their Digitalization Responses. ADBI Working Paper 1241, Tokyo: Asian Development Bank Institute. Retrieved January 13, 2023, from https://www.adb.org/publications/impacts-covid-19-pandemic-msme-asia-their-digitalizationresponses
Subramaniam, G & Muthukumar, I, 2020. Efficacy of time series forecasting (ARIMA) in post-COVID econometric analysis. International Journal of Statistics and Applied Mathematics, vol 5, no. 6, pp. 20-27. http://dx.doi.org/10.22271/maths.2020.v5.i6a.609
Tan, CV, Singh, S, Lai, CH, Zamri, ASSM, Dass, SC, Aris, TB, Ibrahim, HM & Gill, BS, 2022. Forecasting COVID-19 Case Trends Using SARIMA Models during the Third Wave of COVID-19 in Malaysia. Int. J. Environ. Res. Public Health 2022, vol. 19, no. 1504. https://doi.org/10.3390/ijerph19031504
Tharu, NK, 2019. Forecasting International Tourists Arrival in Nepal: An Application of ARIMA. Department of Statistics. Retrieved May 06, 2023, from https://www.researchgate.net/publication/342354362
Thushara SC, Su, J & Bandara JS, 2019. Forecasting international tourist arrivals in formulating tourism strategies and planning: The case of Sri Lanka. Cogent Economics & Finance (2019), 7:1699884. https://doi.org/10.1080/23322039.2019.1699884
Turtureanu, AG, Pripoaie, R, Cretu, CM, Sirbu, CG, Marinescu, ES, Talaghir, LG & Chit, F, 2022. A Projection Approach of Tourist Circulation under Conditions of Uncertainty. Sustainability 2022, vol. 14, no. 1964. https://doi.org/10.3390/su14041964
Upadhayaya, RP, 2021. Forecasting International Tourists Arrival to Nepal Using Autoregressive Integrated Moving Average (ARIMA). Janapriya Journal of Interdisciplinary Studies, vol. 10, no. 01, pp.107-117. Retrieved from https://www.nepjol.info/index.php/JJIS/article/view/42614/32450
Velos, SP, Go, MB, Bate, GP & Joyohoy, EB, 2020. A Seasonal Autoregressive Integrated Moving Average (SARIMA) Model to Forecasting Tourist Arrival in the Philippines: A Case Study in Moalboal, Cebu (Philippines). Recoletos Multidiscipline Res J., vol. 8, no. 1, pp. 67–78. Retrieved from https://doi.org/10.32871/rmrj2008.01.05
Velu, SR, Ravi, V & Tabianan, K, 2022. Predictive analytics of COVID 19 cases and tourist arrivals in ASEAN based on covid 19 cases. Health and Technology, vol. 12, pp. 1237–1258. Retrieved June 02, 2023, from https://doi.org/10.1007/s12553-022-00701-7
Waluyo, JE, 2019. Peramalan Kedatangan Wisatawan Manca Negara Melalui Bandara Husein Sastra Negara Bandung Dengan Menggunakan Metode Arima (Autoregressive Integreted Moving Average). Jurnal Kepariwisataan: Destinasi, Hospitalitas dan Perjalanan. https://doi.org/10.34013/jk.v3i1.32
Wen, J, Wang, W, Kozak, M, Liu, X & Hou, H, 2020. Many brains are better than one: The importance of interdisciplinary studies on COVID-19 in and beyond tourism. Tour. Recreat. Res. 2020, p. 1–4. https://doi.org/10.1080/02508281.2020.1761120
Wieprow, J & Gawlik, A, 2021. The Use of Discriminant Analysis to Assess the Risk of Bankruptcy of Wen Enterprises in Crisis Conditions Using the Example of the Tourism Sector in Poland. Risks, vol. 9, p. 78. https://doi.org/10.3390/risks9040078
Williams, AM, Rodríguez Sánchez, I & Škokić, V 2021, Innovation, risk, and uncertainty: A study of tourism entrepreneurs, Journal of Travel Research, vol. 60, no. 2, pp. 293-311. https://doi.org/10.1177/0047287519896012
Wu, DCW, Ji, L, He, K & Tso, KFG, 2021. Forecasting Tourist Daily Arrivals with A Hybrid Sarima– Lstm Approach. Journal of Hospitality & Tourism Research, vol. 45, no. 1, pp. 52–67. https://doi.org/10.1177/1096348020934046
Yang, R, Liu, K, Su, C, Takeda, S, Zhang, J & Liu, S, 2023. Quantitative Analysis of Seasonality and the Impact of COVID-19 on Tourists’ Use of Urban Green Space in Okinawa: An ARIMA Modeling Approach Using Web Review Data. Land 2023, vol. 12, no. 1075. https://doi.org/10.3390/land12051075
Yap, DJ, 2020. Duterte Hit for Delay of Bayanihan 2. Philippine Daily Inquirer, 5 September 2020. Retrieved January 13, 2023, from https://newsinfo.inquirer.net/1331449/duterte- hit-for-delay-of-bayanihan-2
Yollanda, M & Devianto, D, 2020. Hybrid model of seasonal ARIMA-ANN to forecast tourist arrivals through Minangkabau International Airport. In Proceedings of the 1st International Conference on Statistics and Analytics, ICSA 2019, 2-3 August 2019, Bogor, Indonesia. Retrieved from https://eudl.eu/doi/10.4108/eai.2-8-2019.2290473
Zhang, B, 2022. Based on HP-ARIMA Method Automotive Industry Stock Net Value Valuation Analysis-Taking 10,908 samples from 9 enterprises as examples. 2022 6th International Conference on Education, Management and Social Science (EMSS 2022), pp. 72-76. Retrieved February 15, 2024, from https://www.clausiuspress.com/conferences/AETP/EMSS%202022/ES013.pdf
Zhang, Y, Choo, WC, Ho, JS & Wan, CK, 2022. Single or Combine? Tourism Demand Volatility Forecasting with Exponential Weighting and Smooth Transition Combining Methods. Computation 2022, vol. 10, no. 137. https://doi.org/10.3390/computation10080137
Zielinski, S & Botero, C, 2020. Beach Tourism in Times of COVID-19 Pandemic: Critical Issues, Knowledge Gaps and Research Opportunities. Int. J. Environ. Res. Public Health 2020, vol. 17, p.7288. https://doi.org/10.3390/ijerph17197288
Zlatkou, P, 2021. Prediction of Tourism Demand in Greece Using Time Series. A thesis
submitted for the degree of Master of Science (MSc) in Data Science, pp. 1-28. Retrieved March 05, 2024, from: https://repository.ihu.edu.gr/xmlui/bitstream/handle/11544/29762/New%20-PREDICTION%20OF%20TOURISM%20DEMAND%20IN%20GREECE%20USING%20TIME%20SERIES%20FORECASTING.pdf
DOI: http://dx.doi.org/10.46827/ejefr.v8i6.1847
Refbacks
- There are currently no refbacks.
Copyright (c) 2024 Lemuel B. Asdang, Stilo Floyd P. Schneider
This work is licensed under a Creative Commons Attribution 4.0 International License.
The research works published in this journal are free to be accessed. They can be shared (copied and redistributed in any medium or format) and\or adapted (remixed, transformed, and built upon the material for any purpose, commercially and\or not commercially) under the following terms: attribution (appropriate credit must be given indicating original authors, research work name and publication name mentioning if changes were made) and without adding additional restrictions (without restricting others from doing anything the actual license permits). Authors retain the full copyright of their published research works and cannot revoke these freedoms as long as the license terms are followed.
Copyright © 2016 - 2023. European Journal of Economic and Financial Research (ISSN 2501-9430) is a registered trademark of Open Access Publishing Group. All rights reserved.
This journal is a serial publication uniquely identified by an International Standard Serial Number (ISSN) serial number certificate issued by Romanian National Library. All the research works are uniquely identified by a CrossRef DOI digital object identifier supplied by indexing and repository platforms. All the research works published on this journal are meeting the Open Access Publishing requirements and standards formulated by Budapest Open Access Initiative (2002), the Bethesda Statement on Open Access Publishing (2003) and Berlin Declaration on Open Access to Knowledge in the Sciences and Humanities (2003) and can be freely accessed, shared, modified, distributed and used in educational, commercial and non-commercial purposes under a Creative Commons Attribution 4.0 International License. Copyrights of the published research works are retained by authors.
