Adaptive engagement in smart tourism: a context-sensitive multi-condition model for older adults
Purpose This study aims to develop a theoretical model to explain how older adults engage with smart tourism services by examining five key conditions: user-related, technological, tourism-specific, social mechanisms and experiential feedback. It aims to capture the adaptive strategies older adults adopt in navigating digital tourism environments. Design/methodology/approach Using a grounded theory approach, this study conducted 50 in-depth interviews with older Chinese adults (users and non-users). Theoretical sampling guided data collection and open, axial and selective coding generated a context-sensitive multi-condition adaptation engagement model. Findings The model reveals that engagement behavior emerges from dynamic interactions among the five condition clusters. These interactions generate three adaptive outcomes: active use, limited use and non-use. Social support, norms, economic incentives and feedback from prior experiences serve as key mechanisms moderating these trajectories. Originality/value By integrating structural, social and experiential factors, this model extends beyond conventional technology adoption frameworks (e.g. technology acceptance model, unified theory of acceptance and use of technology), offering a comprehensive understanding of older adults’ digital engagement in tourism. It provides conceptual and practical insights for designing age-inclusive smart tourism services and policies that respond to the lived realities of aging users.
Authors
- Derong Lin
- Zhao Shi
- Rakesh Gupta
- Yingying Chen
Institutions
- University of Economics Ho Chi Minh City (VN)
- Xiamen University (CN)
- Xiamen Tobacco Industry (China) (CN)
- Xiamen University of Technology (CN)
Publication Details
- Journal
- Journal of Hospitality and Tourism Technology
- Published
- 2026-02-10
- DOI
- https://doi.org/10.1108/jhtt-05-2025-0395
- Primary Topic
- Technology Use by Older Adults
- Type
- article
- Field-Weighted Citation Impact
- 0.00