Measurement of Seasonal Indices and Forecasting of Tourist Arrivals in Purba Medinipur, West Bengal

Dr. Archita Nayak; Prof. Kanti Paul

doi:https://doi.org/10.58419/gbs.v11i2.1122505

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Measurement of Seasonal Indices and Forecasting of Tourist Arrivals in Purba Medinipur, West Bengal

Archita Nayak, Kanti Paul

https://doi.org/10.58419/gbs.v11i2.1122505

Published Online: February 02, 2026

Author Details ( * ) denotes Corresponding author

1. * Archita Nayak, Faculty, Commerce, Kalipada Ghosh Tarai Mahavidyalaya, Siliguri, West Bengal, India (archita.nayak@gmail.com)

2. Kanti Paul, Faculty, Commerce, Kalipada Ghosh Tarai Mahavidyalaya, Siliguri, West Bengal, India (kantipaul@gmail.com)

Purba Medinipur, a coastal district in West Bengal, serves as a vital hub for religious, historical, and beach-based tourism. Despite its popularity, the region faces challenges due to significant seasonal fluctuations in tourist arrivals, leading to resource strain during peak periods and under-utilization during lean months. This study utilizes monthly secondary data from 2011 to 2024 to measure seasonal indices and develop a Seasonal Autoregressive Integrated Moving Average (SARIMA) econometric model for forecasting tourist inflows. By identifying peak, shoulder, and lean seasons, the research aims to provide actionable insights for tourism management, infrastructure planning, and sustainable economic growth. The analysis highlights the impact of the COVID-19 pandemic and the disproportionately low share of foreign tourist arrivals compared to domestic visitors. The findings serve as a strategic tool for stakeholders to stabilize revenue, minimize environmental degradation, and enhance the overall visitor experience through informed decision-making.

Keywords

Seasonal Autoregressive Integrated Moving Average (SARIMA); Autocorrelation Function (ACF); Partial Autocorrelation Function (PACF); Seasonal Index; Geo-ecotourism; Experimental Tourism

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