How Delightful is Indian Wellness Tourism? A Netnographic Study

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.

The importance of food and beverages in wellness experiences: a cross-continental analysis of tourists' perceptions

“…Rodrigues et al (2020) emphasize that in Hotel Spas in Portugal the factors that positively influence guest satisfaction are rooms, nature, food, location and value for money. Additionally, a growing number of international contributions from China, Canada and India highlight the role of food in the holistic wellness products offered by Spa Retreats (Kim and Yang, 2021;Mishra and Panda, 2021).…”

Online complaint handling: a text analytics-based classification framework

“…Chittiprolu et al (2021) reviewed online hotel reviews by using unsupervised text mining techniques, and results put forth that satisfied customers mention tangible features, whereas dissatisfied customers complain about intangible service problems. Likewise, Mishra and Panda (2021) reviewed wellness facility reviews, and tangibility was found to be the most important dimension.…”

“…The proposed ensemble classifier and deep learning models provide better classification accuracy Chittiprolu et al (2021) To comprehend the dimensions of service appreciation and complaints by comparing positive and negative reviews Satisfied customers mentioned about tangible features of the hotel stay, whereas complaints are about intangible service problems Mishra and Panda (2021) To explore the service quality dimensions of wellness tourism industry based on customers' quality perception Tangibility was found to be the most important dimension followed by empathy, assurance, reliability and responsiveness Complaint Management Focus Ravi et al (2017) To propose a hybrid complaint analytics model based on fuzzy formal concept analysis and sentiment analysis With the proposed model, complaints can be ranked and visualized according to the negative sentiment score Leem and Eum (2021) To propose a method of measuring service quality and detecting complaints through analysis of customer online reviews…”

AHRC Efforts Action to Reduce Racial Discrimination Cases Occur in Australia

“…From the explanation above, it can be seen that the highest number of questions received by AHRC in 2015-2016 were two matters, namely disability discrimination and racial discrimination. (Mishra & Panda, 2021) The number of questions related to racial discrimination in 2015-2016 was 21% of the 16,836 questions. This means that there were 3,535 questions submitted regarding racial discrimination.…”