Recommender systems for hiking and mountaineering: A conceptual framework and evaluation of leading outdoor apps

The growing popularity of outdoor recreation, together with the expansion of mobile applications, is transforming the way people interact with natural environments. In this context, recommender systems (RS) play an increasingly significant role, not only in planning itineraries and supporting decision-making during recreational activities, but also by mediating the recreational experience itself. This study analyses how these systems operate in hiking and mountaineering applications. Its objective is to produce a conceptual framework that synthesises the key elements of personalisation and contrasts them with the declared functionalities of the main commercial platforms on the market. The investigation was developed in three stages: firstly, reviewing literature that categorises the different types of RS and the data they require; secondly, designing a structured model around four dimensions (user, content, context, and community); and finally, a documented analysis of five commonly used apps (Komoot, Outdooractive, Strava, Wikiloc, and AllTrails) to compare them with the model. The results reveal notable differences between the platforms. Strava and AllTrails are the only ones that integrated all the components of the model. The rest show gaps in incorporating user-specific information and their collective behavioural data. Furthermore, the tendency to prioritise popular content can limit diverse recommendations and lead to territorial impacts. These findings provide relevant evidence for the management of natural areas, showing how the design of these systems may influence visitor flows and the sustainability of outdoor recreational activities.

Implications for management

The results reveal key challenges and opportunities in integrating AI-based recommender systems into outdoor recreation applications, with direct implications for the management of protected areas.

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  Digitisation of recreational experiences is transforming visitor behaviour and expectations; digital technologies should be recognised as strategic tools for environmental communication.
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  The aggregation of individual decisions and the use of automated recommendations can lead to visitor concentration in specific locations, increasing environmental pressure and compromising sustainable management goals.
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  These systems tend to reinforce dominant spatial representations, limiting both territorial and cultural diversity and potentially undermining conservation and heritage values.
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  Effective collaboration between protected area managers and app developers is essential to improve the quality, diversity, and sustainability of recommendations.
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  Empirical models that explain how these systems operate in practice are critical to anticipating their impacts, designing appropriate interventions, and supporting evidence-based territorial planning.