How can we improve tourism service experiences: insights from multi-stakeholders’ interaction

Arpan Kumar Kar (), Shweta Kumari Choudhary () and P. Vigneswara Ilavarasan
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Arpan Kumar Kar: Indian Institute of Technology Delhi
Shweta Kumari Choudhary: Indian Institute of Technology Delhi
P. Vigneswara Ilavarasan: Indian Institute of Technology Delhi

DECISION: Official Journal of the Indian Institute of Management Calcutta, 2023, vol. 50, issue 1, No 6, 73-89

Abstract: Abstract We examine factors influencing tourism service experience based on social media discussions using a lens of adoption, service quality, and attribution theories. We identified the most prominent themes and formulated seven propositions using social media data followed by sentiment analysis, topic modeling, clustering, and netnography-based analysis. In addition, we validated our proposition using the interview data from service providers. Our findings demonstrate that tourist opinions are related to affordability (i.e., dynamic price), local environment (for example, infrastructure, accommodation), interpersonal inclination (for example, climate, attractions), security and confidentiality-integrity-accessibility at the destination. In addition, we provide critical insights which may help formulate policies for improving tourism sector services. The major imperative implication of this study is twofold: (1) we found seven major constructs related to tourism experience in India; (2) we inductively developed an integrated framework for tourism service experience by exploring the various latent variables and further incorporating these with service quality model, external attribution theory, and extended adoption literature to improve service delivery and experience. This paper presents the role of digitalization in improving the tourism service experience using real-time data from twitter to extract the information instantly without any time lag which help in mining collective intelligence from honest signals of service consumers. We have established the relationship between the various outcomes of tourist posts and digital services using twitter posts to model real-time concerns surrounding digital tourism.

Keywords: Social media; Text mining; Digital tourism; Tourism service experience; Sentiment analysis; Netnography (search for similar items in EconPapers)
Date: 2023
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DOI: 10.1007/s40622-023-00338-z

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