{"title":"使用分解法、Box-Jenkins 法和 Holt-Winters 指数平滑法预测喜马偕尔邦的印度游客和外国游客抵达人数","authors":"Keerti Manisha, Inderpal Singh","doi":"10.1007/s41685-024-00344-8","DOIUrl":null,"url":null,"abstract":"<div><p>Himachal Pradesh offers many tourist experiences to Indian and foreign visitors. The mountainous state experiences a high degree of tourism seasonality, interrupting the efficient operation of the tourism infrastructure. Fundamental requirements for tourism planning are accurate projections of tourist demands. However, estimating future demands becomes challenging because of the high degree of seasonality. The compound and annual growth rate methods are used in state-level tourism research to forecast future growth. Since these models cannot manage seasonality and trends in data series, they inaccurately predict future demand. In this context, forecasting models such as the Decomposition, Box–Jenkins, and Holt–Winters exponential smoothing methods were used to forecast the seasonal tourism demands in the study area. The dataset utilized for the analysis was the monthly Indian and foreign tourist arrivals from 2008 to 2018. Root Mean Square Error (RMSE), Mean Absolute Percentage Error (MAPE), and Theil’s U1 coefficients validated that the forecast models produced accurate results. The Box–Jenkins model accurately forecasted the tourist arrivals (2019 to 2031) as reflected by the lowest error metrics (Indian: RMSE 36833.8, MAPE 3.0, Theil's U1 0.023; Foreign: RMSE 6907.59, MAPE 15.51, Theil's U1 0.10). This approach outperformed the traditional seasonal data series forecasting techniques and contributed to the literature on univariate tourist demand forecasting for hilly areas experiencing a high degree of seasonality. Estimating maximum tourist arrivals is crucial in long-term strategic planning for tourism expansion to withstand maximum loads and ensure efficient business flow, higher investment, enhanced economic growth, and environmental protection in the state. This study is a pioneer in examining tourism demands for stakeholders, tourism operators, and planners to plan the fluctuating tourism in Himachal Pradesh while adhering to sustainability principles. Furthermore, it provides inputs for effective planning and policy formulations specific to the tourism industry based on future demand assessments.</p></div>","PeriodicalId":36164,"journal":{"name":"Asia-Pacific Journal of Regional Science","volume":"8 3","pages":"879 - 909"},"PeriodicalIF":1.9000,"publicationDate":"2024-07-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Forecasting of Indian and foreign tourist arrivals to Himachal Pradesh using Decomposition, Box–Jenkins, and Holt–Winters exponential smoothing methods\",\"authors\":\"Keerti Manisha, Inderpal Singh\",\"doi\":\"10.1007/s41685-024-00344-8\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><p>Himachal Pradesh offers many tourist experiences to Indian and foreign visitors. The mountainous state experiences a high degree of tourism seasonality, interrupting the efficient operation of the tourism infrastructure. Fundamental requirements for tourism planning are accurate projections of tourist demands. However, estimating future demands becomes challenging because of the high degree of seasonality. The compound and annual growth rate methods are used in state-level tourism research to forecast future growth. Since these models cannot manage seasonality and trends in data series, they inaccurately predict future demand. In this context, forecasting models such as the Decomposition, Box–Jenkins, and Holt–Winters exponential smoothing methods were used to forecast the seasonal tourism demands in the study area. The dataset utilized for the analysis was the monthly Indian and foreign tourist arrivals from 2008 to 2018. Root Mean Square Error (RMSE), Mean Absolute Percentage Error (MAPE), and Theil’s U1 coefficients validated that the forecast models produced accurate results. The Box–Jenkins model accurately forecasted the tourist arrivals (2019 to 2031) as reflected by the lowest error metrics (Indian: RMSE 36833.8, MAPE 3.0, Theil's U1 0.023; Foreign: RMSE 6907.59, MAPE 15.51, Theil's U1 0.10). This approach outperformed the traditional seasonal data series forecasting techniques and contributed to the literature on univariate tourist demand forecasting for hilly areas experiencing a high degree of seasonality. Estimating maximum tourist arrivals is crucial in long-term strategic planning for tourism expansion to withstand maximum loads and ensure efficient business flow, higher investment, enhanced economic growth, and environmental protection in the state. This study is a pioneer in examining tourism demands for stakeholders, tourism operators, and planners to plan the fluctuating tourism in Himachal Pradesh while adhering to sustainability principles. Furthermore, it provides inputs for effective planning and policy formulations specific to the tourism industry based on future demand assessments.</p></div>\",\"PeriodicalId\":36164,\"journal\":{\"name\":\"Asia-Pacific Journal of Regional Science\",\"volume\":\"8 3\",\"pages\":\"879 - 909\"},\"PeriodicalIF\":1.9000,\"publicationDate\":\"2024-07-23\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Asia-Pacific Journal of Regional Science\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://link.springer.com/article/10.1007/s41685-024-00344-8\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"ECONOMICS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Asia-Pacific Journal of Regional Science","FirstCategoryId":"1085","ListUrlMain":"https://link.springer.com/article/10.1007/s41685-024-00344-8","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"ECONOMICS","Score":null,"Total":0}
Forecasting of Indian and foreign tourist arrivals to Himachal Pradesh using Decomposition, Box–Jenkins, and Holt–Winters exponential smoothing methods
Himachal Pradesh offers many tourist experiences to Indian and foreign visitors. The mountainous state experiences a high degree of tourism seasonality, interrupting the efficient operation of the tourism infrastructure. Fundamental requirements for tourism planning are accurate projections of tourist demands. However, estimating future demands becomes challenging because of the high degree of seasonality. The compound and annual growth rate methods are used in state-level tourism research to forecast future growth. Since these models cannot manage seasonality and trends in data series, they inaccurately predict future demand. In this context, forecasting models such as the Decomposition, Box–Jenkins, and Holt–Winters exponential smoothing methods were used to forecast the seasonal tourism demands in the study area. The dataset utilized for the analysis was the monthly Indian and foreign tourist arrivals from 2008 to 2018. Root Mean Square Error (RMSE), Mean Absolute Percentage Error (MAPE), and Theil’s U1 coefficients validated that the forecast models produced accurate results. The Box–Jenkins model accurately forecasted the tourist arrivals (2019 to 2031) as reflected by the lowest error metrics (Indian: RMSE 36833.8, MAPE 3.0, Theil's U1 0.023; Foreign: RMSE 6907.59, MAPE 15.51, Theil's U1 0.10). This approach outperformed the traditional seasonal data series forecasting techniques and contributed to the literature on univariate tourist demand forecasting for hilly areas experiencing a high degree of seasonality. Estimating maximum tourist arrivals is crucial in long-term strategic planning for tourism expansion to withstand maximum loads and ensure efficient business flow, higher investment, enhanced economic growth, and environmental protection in the state. This study is a pioneer in examining tourism demands for stakeholders, tourism operators, and planners to plan the fluctuating tourism in Himachal Pradesh while adhering to sustainability principles. Furthermore, it provides inputs for effective planning and policy formulations specific to the tourism industry based on future demand assessments.
期刊介绍:
The Asia-Pacific Journal of Regional Science expands the frontiers of regional science through the diffusion of intrinsically developed and advanced modern, regional science methodologies throughout the Asia-Pacific region. Articles published in the journal foster progress and development of regional science through the promotion of comprehensive and interdisciplinary academic studies in relationship to research in regional science across the globe. The journal’s scope includes articles dedicated to theoretical economics, positive economics including econometrics and statistical analysis and input–output analysis, CGE, Simulation, applied economics including international economics, regional economics, industrial organization, analysis of governance and institutional issues, law and economics, migration and labor markets, spatial economics, land economics, urban economics, agricultural economics, environmental economics, behavioral economics and spatial analysis with GIS/RS data education economics, sociology including urban sociology, rural sociology, environmental sociology and educational sociology, as well as traffic engineering. The journal provides a unique platform for its research community to further develop, analyze, and resolve urgent regional and urban issues in Asia, and to further refine established research around the world in this multidisciplinary field. The journal invites original articles, proposals, and book reviews.The Asia-Pacific Journal of Regional Science is a new English-language journal that spun out of Chiikigakukenkyuu, which has a 45-year history of publishing the best Japanese research in regional science in the Japanese language and, more recently and more frequently, in English. The development of regional science as an international discipline has necessitated the need for a new publication in English. The Asia-Pacific Journal of Regional Science is a publishing vehicle for English-language contributions to the field in Japan, across the complete Asia-Pacific arena, and beyond.Content published in this journal is peer reviewed (Double Blind).