Seasonality in Tourism and Forecasting Foreign Tourist Arrivals in India

Document Type: Research Paper


1 Central University of Punjab, Bathinda, Punjab, India

2 Siksha ‘O’ Anusandhan, Deemed to be University, Bhubaneswar, Odisha, India


In the present age of globalization, technology-revolution and sustainable development, the presence of seasonality in tourist arrivals is considered as a key policy issue that affects the global tourism industry by creating instability in the demand and revenues. The seasonal component in a time-series distorts the prediction attempts for policy-making. In this context, it is quintessential to suggest an accurate method of producing the reliable forecast of foreign tourist arrivals. This paper evaluated the performance of Holt-Winters’ and Seasonal ARIMA models for forecasting foreign tourist arrivals in India. The data on India’s inbound tourism from Jan-2001 to June-2018 were used for preparing the forecast for the period July-2018 to June-2020. On the basis of Mean Absolute Error, Mean Absolute Percentage Error and Mean Square Error, the findings infer the relative efficiency of Holt-Winters’ model over Seasonal ARIMA model in forecasting the foreign tourist arrivals in India. Thus, to reduce the perceived negative impacts of seasonality in Indian inbound tourism and to ensure foreign tourist visits round the year, niche products best suitable for Indian climatic and socio-cultural-institutional conditions need to be introduced and promoted in a large scale both at the national and global levels. 


Main Subjects

Article Title [Persian]

فصلی بودن در گردشگری و پیش بینی ورود گردشگران خارجی در هندوستان

Authors [Persian]

  • پ.ک. میشرا 1
  • هیمنشو. ب. روت 2
  • ب. پردهان 2
1 دانشگاه مرکزی پنجاب – باتیندا، هندوستان
2 دانشگاه بوبانسور ادیشا، هندوستان
Abstract [Persian]

در عصر حاضر جهانی شدن، انقلاب فناوری و توسعه پایدار، تکرار آمدن گردشگر فصلی به عنوان یک مسئله سیاست کلیدی  درنظر گرفته شده که با ایجاد بی ثباتی در تقاضا و درآمد، صنعت گردشگری جهانی را تحت تاثیر قرار می دهد. مولفه فصلی بودن گردشگری در یک سری زمانی، تلاشهای پیش بینی شده برای سیاست گذاری را تحریف می کند. در این زمینه، نکته حائز اهمیت، پیشنهاد یک روش دقیق برای ارائه پیش بینی قابل اعتماد از ورود گردشگران خارجی وجود دارد. در این مقاله عملکرد مدل هولت وینترس (Holt-Winters model)  و مدل سیزونال آریما (Seasonal ARIMA model)  برای پیش بینی ورود گردشگران خارجی درهندوستان مورد بررسی قرار گرفته است. اطلاعات مربوط به ورود گردشگران از ژانویه 2001 تا جون 2018 برای تهیه پیش بینی دوره جولای 2018 تا جون 2020 مورد استفاده قرار گرفته است. بر اساس میانگین خطای مطلق، میانگین درصد خطای مطلق و میانگین خطای مربع، یافته ها استنتاج از کارایی نسبی از مدل هولت وینترس (Holt-Winters model)  بر مدل سیزونال آریما (Seasonal ARIMA model)  در پیش بینی ورود گردشگرخارجی به هندوستان می باشد. بنابراین، برای کاهش اثرات منفی از فصلی بودن گردشگری به هندوستان و همچنین برای تضمین بازدید گردشگران خارجی در طول سال، محصولات ویژه و خاص هندوستان امتیاز به سزایی را در شرایط اقلیمی، اجتماعی، فرهنگی وسازمانی و همچنین در مقیاس وسیع همچون سطوح ملی و جهانی نیاز به معرفی و رشد می باشد.

Keywords [Persian]

  • فصلی بودن
  • گردشگری
  • پیش بینی
  • ورود گردشگران خارجی
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