Akıllı Turizmin ChatGPT Tarafından Değerlendirilmesi (Evaluation of Smart Tourism by ChatGPT)

Authors

  • Ahmet ERDEM

DOI:

https://doi.org/10.21325/jotags.2023.1343

Keywords:

ChatGPT, Chatbot, Smart tourism, Artificial intelligence

Abstract

The aim of the research is to analyze the responses of the ChatGPT application, an artificial intelligence chatbot, regarding smart tourism. ChatGPT is a type of chatbot developed by OpenAI that uses the Generative Pre-trained Transformer (GPT) language model to understand natural language inputs and provide responses. In this context, ChatGPT, an AI-powered chatbot, was asked five open-ended questions to evaluate smart tourism. Following the general assessment by ChatGPT, several themes emerged, including experience, efficiency, management, and sustainability. Regarding tourism attractions, it was identified that technology infrastructure, data analytics, artificial intelligence, personalization and customer experience, mobile applications and interactive tools, sustainability and environmental awareness, as well as security and data privacy, are essential elements to be present. When considering smart tourism technologies from the perspective of tourists, it was determined that they provide advantages such as convenience, enriched experiences, utilization of new technologies, and quick access to information. However, it is necessary to address challenges related to decreased human interaction, concerns about data security, and resolving dependency on technology. Finally, smart tourism technologies offer opportunities for increased efficiency, providing decision support services, facilitating business processes, enhancing customer service, enabling data analysis and improvement, fostering innovation, and supporting skill development from the perspective of employees and managers.

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Published

01/01/2024

How to Cite

ERDEM , A. (2024). Akıllı Turizmin ChatGPT Tarafından Değerlendirilmesi (Evaluation of Smart Tourism by ChatGPT). Journal of Tourism & Gastronomy Studies, 11(4), 3298–3313. https://doi.org/10.21325/jotags.2023.1343