Tourism Faces Digital and Sustainability Challenges
The global tourism sector is changing rapidly as travelers increasingly rely on digital services and destinations adopt technologies such as artificial intelligence, Internet of Things (IoT), big data, and digital information systems.
At the same time, tourism destinations face persistent challenges. Growing visitor numbers can create overtourism, environmental degradation, pressure on natural resources, and unequal distribution of economic benefits. These challenges have increased interest in smart destination management, which uses digital technology and real-time data to improve tourism decisions.
However, the researchers point out that smart tourism has often focused on service efficiency, digital promotion, and visitor satisfaction. Less attention has been given to whether digital transformation can help destinations recover their environmental and social ecosystems. This gap is particularly relevant in developing destinations, including Indonesia.
The concept of regenerative tourism provides a broader approach. Rather than simply reducing tourism's negative impacts, regenerative tourism seeks to restore environmental, social, and economic systems while strengthening local communities.
Study Examines 200 Tourism Technology Users
The researchers used a quantitative, cross-sectional research design to examine relationships between three key elements: smart destinations, human-AI collaboration, and regenerative tourism.
The research involved 200 respondents in Indonesia, consisting of 140 tourists, or 70 percent, and 60 destination managers, or 30 percent. Participants were selected because they had used digital tourism services and had visited a destination within the previous 12 months.
Data were collected through structured questionnaires using a five-point scale. The questionnaire was first tested with 30 respondents before being distributed to the main sample through online and offline channels. The researchers then analyzed the relationships among the variables using SmartPLS 4, examining both direct effects and the role of human-AI collaboration as a mediator.
Respondents generally had positive perceptions of all three concepts. Smart Destination recorded an average score of 4.12, Human-AI Collaboration 3.98, and Regenerative Tourism 4.05, all categorized as high.
Smart Destinations Have a Strong Link to Human-AI Collaboration
The results showed significant positive relationships across all four hypotheses tested.
The main findings were:
- Smart Destination had a positive effect on Human-AI Collaboration, with a coefficient of 0.62.
- Smart Destination had a positive effect on Regenerative Tourism, with a coefficient of 0.41.
- Human-AI Collaboration had a positive effect on Regenerative Tourism, with a coefficient of 0.48.
- Human-AI Collaboration partially mediated the relationship between Smart Destination and Regenerative Tourism, with an indirect effect of 0.30.
The strongest relationship was between Smart Destination and Human-AI Collaboration. This indicates that better digital systems, tourism information platforms, data use, and AI integration can create greater opportunities for people and AI to work together in tourism decision-making.
The findings also show that technology alone is insufficient. AI can identify visitor patterns, predict tourist density, detect potential environmental risks, and generate recommendations. Human decision-makers, however, remain responsible for interpreting local social and cultural conditions, determining conservation priorities, and ensuring that tourism benefits are distributed appropriately.
Technology Should Support People, Not Replace Them
For Mita Erdiaty Takaendengan and her colleagues at Politeknik Negeri Manado, Politeknik Perikanan Negeri Tual, and Universitas Sam Ratulangi Manado, the findings suggest that smart tourism should be understood as a socio-technical system.
The researchers explain that digital infrastructure, tourism applications, sensors, and information systems do not automatically create regenerative tourism. Their value depends on people's ability to interpret data, understand local socio-ecological conditions, and translate technological recommendations into appropriate policies and actions.
This perspective is important because it challenges a technology-centered approach to tourism development. AI should function as an enabler of better decisions, while humans remain central to destination governance.
The approach could help tourism managers use technology for purposes beyond marketing. Integrated tourism data could support monitoring of visitor capacity, environmental quality, tourist behavior, and local economic impacts. AI could also assist managers in controlling overtourism, protecting natural resources, and improving the distribution of tourism benefits to local communities and small businesses.
Implications for Indonesian Tourism
The findings have potential implications for local governments, tourism businesses, destination managers, communities, and policymakers.
Local governments could develop integrated tourism data systems that combine information about visitor flows, environmental conditions, and economic impacts. Destination managers could use AI to identify risks and support decisions about resource conservation rather than relying on technology solely for visitor promotion.
The researchers also emphasize the need to strengthen digital literacy, infrastructure, AI governance, data ethics, and institutional readiness. Local communities and small businesses should be involved so that digital transformation does not create new inequalities.
The study nevertheless has limitations. Its cross-sectional design cannot capture long-term changes, while purposive sampling limits the extent to which the findings can be generalized to all Indonesian destinations. The research also relies heavily on respondent perceptions and does not fully measure objective indicators such as ecosystem recovery, environmental quality, local income distribution, or changes in community capacity.
The authors therefore recommend future longitudinal and mixed-method research that combines surveys with interviews, destination observations, and objective environmental and economic data.
Author Profiles
Mita Erdiaty Takaendengan — Prodi Global Tourism Management, Politeknik Negeri Manado. Her affiliation places her research within global tourism management.
Jamaludin Kabalmay — Prodi Agrowisata Bahari, Politeknik Perikanan Negeri Tual, with an academic affiliation in marine-based agro-tourism.
Deby Christinani Sendow — Prodi Teknik Jalan dan Jembatan, Politeknik Negeri Manado, affiliated with road and bridge engineering.
Mahardika Inra Takaendengan — Prodi Sistem Informasi, Universitas Sam Ratulangi Manado, affiliated with information systems.
The published article does not provide the authors' academic degrees or detailed individual biographies. Therefore, their degrees cannot be stated accurately from the available source.
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