Hospitality and Tourism Value Co-Creation in the Light of Artificial Intelligence

Hospitality and Tourism Value Co-Creation in the Light of Artificial Intelligence

Copyright: © 2024 |Pages: 20
DOI: 10.4018/979-8-3693-2367-0.ch005
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Abstract

The hotel and tourism industry is undergoing significant changes due to the widespread adoption of digital technologies that enable instant client communication and data gathering. The aim of the chapter was to do a review to understand the AI technologies that influence value co-creation in the hospitality and tourism industry. The author found AI influencing VCC to include natural language processing, chatbot, intelligent agents, voice-activated digital support, personal digital assistants that aid online visitors, ML, etc. The DART model was selected as the primary framework due to its status as a prominent theory and its widespread application in the study of VCC. It was noticed that AI can facilitate dialogue, access, risk, and transparency, leading to customer/guests/visitor engagement. Future research should focus on AI for marketing and promotion. It was concluded that AI technology provides compelling prospects for engaging interactions and virtual gatherings.
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Introduction

In 2020, the hotels and restaurants industry contributed approximately 3.9 billion Ghanaian cedis (GHS) to the country's GDP, equivalent to around 640.9 million US dollars. This was a significant decrease compared to the previous years, likely due to the impact of the COVID-19 pandemic. In 2019, the industry reached a peak of nearly six billion GHS, equivalent to around 985.8 million US dollars, continuing the upward trend observed since 2014. Overall, the total consumer spending on hotels and restaurants in Ghana was projected to reach over 2.43 billion US dollars in 2021, as stated by Sasu (2022).

Businesses in the tourist and hospitality sector have had to adapt to new ways of doing things and interacting with consumers as a result of numerous modifications brought about by the rise of digital technology (Pencarelli, 2020). The idea of value co-creation, in which a company and its customers work together to build and share value, is one example of this shift (Carvalho & Alves, 2022). Technology that allows everybody with an interest, particularly businesses and customers, to participate is crucial for the travel and hospitality industry's value co-creation process [4, 5]. Therefore, technology is an essential tool for facilitating value co-creation. Because it allows customers and businesses to create and trade value, cutting-edge technology can play a pivotal role in co-creation value processes in the tourist and hospitality industry (Samala et al., 2020). How exactly AI will continue to revolutionize businesses is an open subject in light of the current rate of development. There is research that discusses the evolution of AI and its potential effects on the tourism industry (Lv et al., 2022; Mariani et al., 2022; Tussyadiah, 2020). This includes studies on the topic of AI in general. (Kong et al., 2022) These investigations are theoretical, broad in scope, and full of speculation. Few studies describe how AI may affect certain sectors or business functions. Grundner and Neuhofer (2021) and Saydam et al. (2022) explored tourism destinations and hospitality, respectively. In response to the call for further research on AI and its application to the tourism sector made by Samala et al. (2020), this three-part study investigates the possible effects of AI on hotels' marketing functions in order to gain a better understanding of AI's likely effects and its impact on organizations. Among the factors propelling the Fourth Industrial Revolution is artificial intelligence (AI), which is predicted to possess transformational and substitutive capabilities comparable to those of machines or information technology (IT) (Dwivedi et al., 2021). (Schwab, 2017). Along with big data, artificial intelligence is seen as the next generation of general-purpose technology. It has the ability to greatly influence businesses, according to Marinchak et al. (2018) and Magistrati et al. (2019).

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