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Journal of International Technology and Information Management

Document Type

Article

Abstract

India's aviation sector, a key contributor to the nation's economy, has experienced rapid growth, supporting nearly 7.5 million jobs and contributing approximately $30 billion annually to the GDP (Gross Domestic Product). The growth, driven by increased demand for air travel and government incentives, has resulted in more competition among carriers. In the competitive market, it is necessary to understand customer preferences to enhance the quality of service and maintain a competitive edge. The dissemination of customer opinions on social media and review platforms offers airlines the opportunity to access passenger views. However, extracting useful information from this unstructured data is challenging. Previous studies had not accounted for variables such as seasonal fluctuation in opinion and the impact of specific service features on customer satisfaction. This study fills the gaps by employing sentiment analysis tools, including TextBlob and VADER (Valence Aware Dictionary for Sentiment Reasoning), to analyse customer opinions from platforms like X, Skytrax, and TripAdvisor. The study process involves data collection through automated web scraping tools, followed by data cleaning and text analysis to tag sentiments and identify variables influencing customer emotions. Key findings indicate that carriers like IndiGo and Vistara are highly rated by customers for punctuality, service quality, and operational consistency. Conversely, Air India and SpiceJet are faulted for delays and inefficiency. Seasonal patterns further indicate that negative sentiments are greater during peak travel seasons. The study highlights the importance of customer-centric initiatives, operational efficiency, and advanced analytics to boost brand loyalty in a highly competitive market.

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