Augmented Reality for Heritage Tourism Management and Community Engagement

Thesis Abstract

This study addresses the escalating gap between heritage site preservation and visitor engagement in the context of rapid digital transformation, focusing on how augmented reality (AR) can enhance heritage tourism management and community involvement while mitigating risks to site integrity. The aim is to develop and empirically test an AR-enabled framework that integrates visitor experience, site management, and local community participation for sustainable heritage tourism. Specific objectives are (1) to design an AR-enabled interpretive system that integrates spatial storytelling, contextualized artifact information, and multilingual interfaces; (2) to evaluate the system’s impact on visitor satisfaction, perceived learning, and behavioral intentions; (3) to assess effects on community engagement, including local perceptions of tourism benefits and involvement in site governance; (4) to identify operational, ethical, and technical constraints impacting deployment; and (5) to develop an implementation blueprint for heritage managers and policymakers. The methodology combines a mixed-methods design conducted at three case study sites with distinct heritage typologies (an urban archaeological precinct, a hillside fortress, and a coastal historic port). The population comprises adult visitors (ages 18–65) and resident stakeholders (n = 420 visitors; n = 60 community representatives), selected through stratified sampling. A quasi-experimental approach compares outcomes between treatment groups using AR-enabled tours (n = 210 visitors) and conventional tours (n = 210 visitors) over a six-month field trial. Data collection instruments include standardized surveys addressing visit motivation, satisfaction, learning outcomes, and pro-social intentions; semi-structured interviews with community representatives; focus groups with guides and site managers; AR system usage logs; and observational checklists. Validity and reliability are ensured via pilot testing (n = 40) and Cronbach’s alpha analyses (? > 0. Eight). Data analysis employs a combination of regression analysis to test determinants of visitor satisfaction and learning (hierarchical linear modeling to account for nested data), structural equation modeling to examine the AR framework’s latent constructs, thematic analysis for interview and focus group data, and content analysis for usage logs to identify engagement patterns. Theoretical grounding leverages the Technology Acceptance Model (TAM) extended with perceived value and flow theory, and Social Practice Theory to illuminate community engagement dynamics. Key expected findings include (i) AR-enhanced interpretive experiences significantly increase visitor satisfaction (? = 0.28, p < 0.01) and perceived learning (? = 0.34, p < 0.001) compared to traditional tours; (ii) higher intention to revisit and recommend the site among AR participants (OR = 2.1, p < 0.05); (iii) improved perceived community benefits and increased resident participation in site governance processes (theme-based results converging with quantitative indicators, p < 0.05); (iv) critical success factors identified as usability, content accuracy, cultural sensitivity, device accessibility, and robust data governance; and (v) measurable reductions in physical wear on sensitive artefacts due to guided AR paths that distribute attention across multiple interpretive points. The study contributes to knowledge by operationalizing an integrative AR framework that aligns visitor experience design with heritage management imperatives and community co-creation, empirically validating the relationship between augmented interpretation, learning outcomes, and local empowerment. It advances theory by extending TAM with perceived value and combining Social Practice Theory with AR-mediated engagement to capture the socio-technical complexities of heritage tourism. Practically, the research delivers an implementable blueprint for scalable AR deployment, including content governance guidelines, interoperability standards, data privacy protocols, and a cost-benefit model for heritage organizations. The main conclusion posits that thoughtfully designed AR interventions can harmonize visitor engagement with conservation goals and community interests, provided that content accuracy, accessibility, participatory governance, and ethical considerations are embedded from the inception. Recommended policy and practice include establishing co-design partnerships with local stakeholders, adopting modular AR content with multilingual support, enforcing strict provenance and rights management for digital artefacts, and implementing ongoing monitoring using key performance indicators such as visitor learning scores, satisfaction indices, and community participation metrics to ensure sustained impact.