Abstract:

The growing number of wellness care facilities in India has raised concern over the service quality that is being provided to the tourists. This research targets to explore the dimensions of wellness tourism service quality based on customers’ quality perception. Social media platforms such as Google reviews and hotel review blogs/websites were used to gather 400 public reviews. A Naïve Bayes machine learning Sentiment Analysis approach was used to identify critical areas to improve service delivery, customer relationship, and hospitality management in wellness resorts. Tangibility was identified as the most important dimension followed by empathy, assurance, reliability, and responsiveness. Assurance, empathy, and reliability have the most negative sentiments shared by tourists. Food quality, rooms and accommodation facilities, safety and security, attitude towards customer complaints, the behaviour of the staff, error-free services, and proper training are areas upon which Indian wellness resorts should focus. This study intends to identify additional constructs in future research and build robust models to actively rank the important factors for better customer engagement. Research findings may support managers and policymakers to identify areas of improvement to help them develop the wellness resorts in India.

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