Forecasting Tourist Arrivals in Nepal: A Comparative Analysis of Seasonal Models and Implications

被引:0
作者
Paudel, Tulsi [1 ]
Li, Wenya [1 ]
Dhakal, Thakur [2 ]
机构
[1] Sanming Univ, Entrepreneurial Management Coll, Sanming 365000, Fujian, Peoples R China
[2] Yeungnam Univ, Dept Life Sci, Gyongsan 38541, South Korea
来源
JOURNAL OF STATISTICAL THEORY AND APPLICATIONS | 2024年 / 23卷 / 03期
关键词
Time series; Tourist arrivals; SARIMA; Tourism demand; Nepal; Forecasting;
D O I
10.1007/s44199-024-00079-7
中图分类号
O21 [概率论与数理统计]; C8 [统计学];
学科分类号
020208 ; 070103 ; 0714 ;
摘要
Tourist arrivals play a vital role in the broader tourism ecosystem, substantially contributing to the economy. The global landscape has witnessed significant growth in international arrivals over the years, and Nepal has not been an exception to this trend, experiencing a steady influx of inbound tourists. Although tourist numbers are increasing, the lack of research in forecasting future arrivals is evident, highlighting the pressing need for comprehensive forecasting mechanisms to efficiently manage tourism resources and sustainably accommodate the growing influx of visitors. In order to gain insights into the dynamics of international tourist arrivals in Nepal, we conducted a comparative analysis using two distinct forecasting techniques: Seasonal Autoregressive Integrated Moving Average (SARIMA) and the Exponential Smoothing technique. Our analysis spanned from January 1992 to December 2023, enabling us to formulate forecasts for the upcoming months up to December 2030. The findings of our study underscore the suitability of all three models-namely, SARIMA, Winter Additive, and Winter Multiplicative-as effective tools for projecting international arrivals in Nepal. However, upon careful examination, the Winter Multiplicative model emerged as the most appropriate model for forecasting Nepal's international arrivals. This model aligned strongly with the observed data, enhancing its predictive accuracy. The implications of our research are far-reaching, offering valuable insights for various stakeholders within Nepal's tourism industry. These insights can guide tourism planners, policymakers, and other relevant entities in formulating well-informed strategies to strengthen and sustain the growth of the tourism sector in Nepal. As the nation continues to position itself on the global tourism map, equipped with data-driven forecasts, we believe that our study provides an essential resource for shaping the trajectory of Nepal's tourism industry in a positive direction.
引用
收藏
页码:206 / 223
页数:18
相关论文
共 50 条
  • [41] A Macro Analysis of Tourist Arrival in Nepal
    Paudel, Tulsi
    Dhakal, Thakur
    Li, Wen Ya
    Kim, Yeong Gug
    JOURNAL OF ASIAN FINANCE ECONOMICS AND BUSINESS, 2021, 8 (01): : 207 - 215
  • [42] Forecasting emergency department arrivals using INGARCH models
    Juan C. Reboredo
    Jose Ramon Barba-Queiruga
    Javier Ojea-Ferreiro
    Francisco Reyes-Santias
    Health Economics Review, 13
  • [43] Grey models in seasonal time series forecasting
    Wang, Jean-Shyan
    Pai, Ping-Feng
    Lin, Yen-Hung
    JOURNAL OF STATISTICS & MANAGEMENT SYSTEMS, 2005, 8 (03) : 459 - 476
  • [44] Comparative Analysis of ARMA and GARMA Models in Forecasting
    Pillai, Thulasyammal Ramiah
    Sambasivan, Murali
    ADVANCES IN TIME SERIES ANALYSIS AND FORECASTING, 2017, : 119 - 132
  • [45] Forecasting intraday call arrivals using the seasonal moving average method
    Barrow, Devon K.
    JOURNAL OF BUSINESS RESEARCH, 2016, 69 (12) : 6088 - 6096
  • [46] Forecasting of Indian and foreign tourist arrivals to Himachal Pradesh using Decomposition, Box-Jenkins, and Holt-Winters exponential smoothing methods
    Manisha, Keerti
    Singh, Inderpal
    ASIA-PACIFIC JOURNAL OF REGIONAL SCIENCE, 2024, 8 (03) : 879 - 909
  • [47] FORECASTING TOURIST ARRIVALS IN GREECE AND THE IMPACT OF MACROECONOMIC SHOCKS FROM THE COUNTRIES OF TOURISTS' ORIGIN
    Gounopoulos, Dimitrios
    Petmezas, Dimitris
    Santamaria, Daniel
    ANNALS OF TOURISM RESEARCH, 2012, 39 (02) : 641 - 666
  • [48] A Hybrid Model by Empirical Mode Decomposition and Support Vector Regression for Tourist Arrivals Forecasting
    Lai, Ming-Cheng
    Yeh, Ching-Chiang
    Shieh, Lon-Fon
    JOURNAL OF TESTING AND EVALUATION, 2013, 41 (03) : 351 - 358
  • [49] Particle Swarm Optimization-Based Support Vector Regression for Tourist Arrivals Forecasting
    Liu, Hsiou-Hsiang
    Chang, Lung-Cheng
    Li, Chien-Wei
    Yang, Cheng-Hong
    COMPUTATIONAL INTELLIGENCE AND NEUROSCIENCE, 2018, 2018
  • [50] Prediction of influenza outbreaks in Fuzhou, China: comparative analysis of forecasting models
    Chen, Qingquan
    Zheng, Xiaoyan
    Shi, Huanhuan
    Zhou, Quan
    Hu, Haiping
    Sun, Mengcai
    Xu, Youqiong
    Zhang, Xiaoyang
    BMC PUBLIC HEALTH, 2024, 24 (01)