International Research Journal of Engineering and Technology (IRJET)
e-ISSN: 2395-0056
Volume: 12 Issue: 12 | Dec 2025
p-ISSN: 2395-0072
www.irjet.net
Forecasting Tourism Trends Using ARIMA: A Data-Driven Approach for Economics and Policy Insights Rajesh Sharma1, Preetvanti Singh2 1,2 Physics and computer science Dayalbagh Educational
Institute Agra, Uttar Pradesh India -----------------------------------------------------------------------------***--------------------------------------------------------------------
Abstract: The tourism industry is widely recognized as among the rapidly developing industries in the world. Its growth outpaces many other industries, motivated by the enhanced worldwide travelling, rising disposable income, and the necessity to have distinct travelling experiences. As more people seek to explore new destinations and cultures, the tourism sector has experienced substantial increases in both international and domestic travel. This remarkable expansion has significant economic implications, contributing to job creation, foreign exchange earnings, and regional development, making tourism a crucial driver of economic growth worldwide. To mitigate potential losses, recommendations are offered to both government and industry professionals. This paper demonstrates the application of the autoregressive integrated moving average (ARIMA) model for forecasting tourist arrivals. The Autocorrelation Function (ACF) and partial autocorrelation function (PACF), along with the Ljung-Box test, have been utilized to assess stationary. Keywords: Tourist Arrivals Forecasting, ARIMA, substantial, Ljung-Box test, ACF, PACF
1. INTRODUCTION India is a vast and unique country with heavy cultural and natural variabilities, probably second to none in the global tourism market. From the snow-laden peaks of the Himalayas in the north down to the tropical beaches bordering the Indian Ocean, from the spiritually enlightened city of Varanasi to fast-paced, modern cities like Mumbai, India has much to offer international visitors. But this turnaround notwithstanding, India still accounts for a relatively small share of international tourist arrivals, implying immense scope for tourism growth. Increasing foreign tourist arrivals(FTA) is vital to achieve economic growth, jobs, and cross-cultural exchange. The arrival of tourists is very important from social and economic views as it drives economic growth, creates jobs, and faster cultural exchange. A comprehensive analysis can delve into strategies for enhancing tourist arrivals. Leveraging advanced data analysis tools can identify key trends, patterns, and drivers within the tourism sector that can significantly impact the arrival of tourists. Basnayake & Chandrasekara (2022) proposed tourism as a process whereby people move from one place to another for enjoyment and to spend time. It plays a great role in the development of a country. Following are the main contributions of this paper. First, the weaknesses of the tourism industry in various market segments are discussed. The effect of disturbance types on various tourist groups and on different geographical destinations has not been previously investigated thus; the findings proposed in this paper are novel and contribute to the existing literature. The paper also focuses on the resilience of foreign tourism industry in various states in India. A new technique is developed and presented for investigating how resilient a certain destination is, with fluctuations in terms of anticipated arrival patterns. Through these findings, a new understanding of the vulnerability and resilience of international tourists and their differences among various states in India will be developed which is also the novelty of the paper. This paper presents an analysis of tourist data arriving in India that serves as a roadmap for leveraging data-driven insights to maximize tourism. Analytical methods are applied and integrated with ARIMA modeling to assess the patterns of international tourist arrivals in India, perform FTAs demographic analysis, and future trend analysis based on travel purpose. Thus, this paper provides evidence-based recommendations that can enhance the tourism appeal of India and attract a higher volume of foreign tourists as well as domestic tourist arrivals. The rest of the paper is organized as follows. Section 2 reviews the literature to discover the tourist arrivals in India, impact on tourist industry and forecast modeling. Section 3 describes the methodological approach and the data to carry out the study. Section 4 presents the analysis, and the results are discussed in Section 5. Section 6 shows the implications of this study, followed by limitations and future research. The last section concludes the paper as presented in Section 7.
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