The Impact of AI-Driven Tourism Recommendations on Travel Decision-Making in Abuja
- Project Research
- 1-5 Chapters
- Abstract : Available
- Table of Content: Available
- Reference Style:
- Recommended for :
- NGN 5000
Artificial intelligence (AI) has revolutionized multiple industries, including tourism, by providing personalized recommendations that enhance travel experiences. AI-driven tourism recommendation systems leverage data analytics, machine learning, and user preferences to suggest destinations, accommodations, and activities that align with travelers’ interests (Gómez et al., 2023). In Abuja, a growing number of tourists rely on digital platforms such as TripAdvisor, Google Travel, and AI-powered chatbots to make informed travel decisions. These AI-driven recommendations have influenced tourist behavior by simplifying the planning process and providing real-time, data-driven suggestions. However, while the global impact of AI on tourism is widely documented, there is limited research on its specific influence on travel decision-making in Abuja. Understanding how AI-driven recommendations shape tourists’ choices can provide valuable insights for tourism operators and policymakers aiming to enhance Abuja’s attractiveness as a travel destination.
Statement of the Problem
Despite the increasing use of AI-powered travel platforms, there is limited research on their influence on tourist behavior in Abuja. Many travelers in Nigeria still rely on traditional travel agencies or word-of-mouth recommendations, potentially missing out on AI-driven insights that could enhance their experience (Adeyemi & Nwachukwu, 2024). Additionally, concerns about data privacy and algorithm bias may affect the adoption of AI-driven tourism tools. Investigating how AI influences travel decisions in Abuja is crucial for optimizing digital tourism strategies and addressing challenges associated with AI adoption.
Objectives of the Study
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To assess the impact of AI-driven tourism recommendations on travel decision-making in Abuja.
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To examine the factors influencing tourists' trust and adoption of AI-based travel recommendations.
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To identify challenges and opportunities associated with AI-driven tourism recommendations in Abuja.
Research Questions
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How do AI-driven tourism recommendations influence travel decision-making in Abuja?
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What factors affect tourists' trust and adoption of AI-powered travel recommendations?
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What challenges and opportunities exist in utilizing AI-driven tourism recommendations in Abuja?
Research Hypotheses
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AI-driven tourism recommendations do not significantly influence travel decision-making in Abuja.
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There is no significant relationship between tourists’ trust and the adoption of AI-powered travel recommendations.
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There are no significant challenges or opportunities in utilizing AI-driven tourism recommendations in Abuja.
Scope and Limitations of the Study
This study focuses on the influence of AI-driven tourism recommendations on travel decision-making in Abuja. It will assess how AI-based platforms, such as recommendation systems and chatbots, impact tourists' choices regarding destinations, accommodations, and activities. The study will also examine trust factors influencing AI adoption and the challenges associated with integrating AI into the tourism industry. Limitations may include restricted access to user data from AI-powered platforms and potential biases in self-reported tourist experiences.
Definitions of Terms
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AI-Driven Tourism Recommendations: Travel suggestions generated by artificial intelligence algorithms based on user data, preferences, and past behaviors.
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Travel Decision-Making: The process through which individuals select destinations, accommodations, and activities based on various influencing factors, including AI recommendations.
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Tourist Trust in AI: The degree of confidence tourists have in AI-powered platforms for travel-related decision-making.
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Algorithm Bias: The tendency of AI systems to produce outcomes that reflect existing biases in training data, potentially affecting recommendation accuracy.
