Back to Search
Start Over
From crisis to prosperity: Leveraging robots, artificial intelligence, and service automation for sustainable tourism in Zimbabwe.
- Source :
- Business Strategy & Development; Jun2024, Vol. 7 Issue 2, p1-18, 18p
- Publication Year :
- 2024
-
Abstract
- In an increasingly digital and interconnected world, the integration of advanced technologies such as robotics, artificial intelligence (AI), and service automation has become pivotal for shaping the future of various industries, including tourism. The paper investigates complex relationship between three independent variables: (robotic adoption, AI adoption, and service automation adoption) and three dependent variables: (social sustainability, economic sustainability, and environmental sustainability). Employing a quantitative research approach, the study gathered data from 608 randomly selected tourism supply chain stakeholders using the Krejcie and Morgan table to determine the sample size. Data collection was facilitated through Google Forms questionnaires, and the analysis relied on structural equation modeling. The statistical findings highlight positive direct significant relationships among these variables, as evidenced by t‐statistic values surpassing the threshold of 1.96. These values ranged from a minimum of 2.156 to a maximum of 10.083. These results suggest that by strategically integrating these technologies, tourism businesses and policymakers in Zimbabwe can enhance tourist experience, the industry's long‐term viability and its positive impact on society, the economy, and the environment. This study's outcomes provide a compelling foundation for informed decision‐making and the development of targeted strategies aimed at advancing sustainability objectives within the Zimbabwean tourism landscape. [ABSTRACT FROM AUTHOR]
Details
- Language :
- English
- ISSN :
- 25723170
- Volume :
- 7
- Issue :
- 2
- Database :
- Complementary Index
- Journal :
- Business Strategy & Development
- Publication Type :
- Academic Journal
- Accession number :
- 178092984
- Full Text :
- https://doi.org/10.1002/bsd2.380