Assessing the interplay of trust dynamics, personalization, ethical AI practices, and tourist behavior in the adoption of AI-driven smart tourism technologies

This research aims to explore the intricate dynamics influencing the adoption of AI-driven smart tourism technologies within the specific context of the United Arab Emirates. It seeks to address the following key questions: How do ethical AI practices and personalization impact tourist behavior in the adoption of these technologies? What role does trust dynamics play in mediating these relationships? Additionally, how does the perceived value of smart technologies in the tourism experience moderate these associations? By employing a quantitative approach, data was collected from a sample comprising 319 tourists in the UAE. The research methodology relied on Stata SEM for analysis. This method facilitated the assessment of intricate and interdependent relationships between multiple constructs. Utilizing validated scales, the present study ensured a comprehensive evaluation of the proposed model, encompassing ethical AI practices, personalization, trust dynamics, perceived value, and tourist behavior in the adoption of AI-driven smart tourism technologies. The findings are aligned with the hypotheses posited in the study. Ethical AI practices exhibit a significant impact on influencing tourist behavior in the adoption of AI-driven smart tourism technologies. Similarly, personalization was identified as a significant determinant in shaping tourist behavior in technology adoption within the tourism domain. Moreover, the study found that trust dynamics play a pivotal mediating role in the relationships between ethical AI practices/personalization and subsequent tourist behavior. Additionally, the perceived value of smart technology in the tourism experience plays a crucial moderating role, influencing the strength and direction of the aforementioned relationships. This research uncovers the complex dynamics of AI-driven smart tourism technology to improve tourism theory and practice. The findings emphasize the importance of ethical concerns and user-centric design principles in technology development and implementation, as well as trust dynamics and perceived value in technology adoption. These findings affect tourism service providers, governments, and technology developers looking to improve user experiences and innovate.

Authors

Institutions

Publication Details

Journal
Journal of Open Innovation Technology Market and Complexity
Published
2024-12-11
DOI
https://doi.org/10.1016/j.joitmc.2024.100455
Citations
29
Primary Topic
Organizational and Employee Performance
Type
article
Field-Weighted Citation Impact
10.07
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Assessing the interplay of trust dynamics, personalization, ethical AI practices, and tourist behavior in the adoption of AI-driven smart tourism technologies

Umer Zaman, Inhyouk Koo, Hojung Ha, Shahid Nawaz
29 citations
Journal of Open Innovation Technology Market and Complexity
Organizational and Employee Performance
10.07
article

Assessing the interplay of trust dynamics, personalization, ethical AI practices, and tourist behavior in the adoption of AI-driven smart tourism technologies

Umer Zaman, Inhyouk Koo, Hojung Ha, Shahid Nawaz
article en
29 citations

Abstract

This research aims to explore the intricate dynamics influencing the adoption of AI-driven smart tourism technologies within the specific context of the United Arab Emirates. It seeks to address the following key questions: How do ethical AI practices and personalization impact tourist behavior in the adoption of these technologies? What role does trust dynamics play in mediating these relationships? Additionally, how does the perceived value of smart technologies in the tourism experience moderate these associations? By employing a quantitative approach, data was collected from a sample comprising 319 tourists in the UAE. The research methodology relied on Stata SEM for analysis. This method facilitated the assessment of intricate and interdependent relationships between multiple constructs. Utilizing validated scales, the present study ensured a comprehensive evaluation of the proposed model, encompassing ethical AI practices, personalization, trust dynamics, perceived value, and tourist behavior in the adoption of AI-driven smart tourism technologies. The findings are aligned with the hypotheses posited in the study. Ethical AI practices exhibit a significant impact on influencing tourist behavior in the adoption of AI-driven smart tourism technologies. Similarly, personalization was identified as a significant determinant in shaping tourist behavior in technology adoption within the tourism domain. Moreover, the study found that trust dynamics play a pivotal mediating role in the relationships between ethical AI practices/personalization and subsequent tourist behavior. Additionally, the perceived value of smart technology in the tourism experience plays a crucial moderating role, influencing the strength and direction of the aforementioned relationships. This research uncovers the complex dynamics of AI-driven smart tourism technology to improve tourism theory and practice. The findings emphasize the importance of ethical concerns and user-centric design principles in technology development and implementation, as well as trust dynamics and perceived value in technology adoption. These findings affect tourism service providers, governments, and technology developers looking to improve user experiences and innovate.

Journal of Open Innovation Technology Market and ComplexityVol. 11(1)
Islamia University of Bahawalpur (PK), Sookmyung Women's University (KR), Woosong University (KR)
Decent work and economic growth
Openalex Percentile: Top 1%
Organizational and Employee Performance
10.07
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.