Abstract
The importance of data and evidence has increased considerably in policy planning, implementation, and evaluation. There is unprecedented availability of open and big data, and there are rapid developments in intelligence gathering and the application of analytical tools. While cultural heritage holds many tangible and intangible values for local communities and society in general, there is a knowledge gap regarding suitable methods and data sources to measure the impacts and develop data-driven policies of cultural tourism. In the tourism sector, rapid developments are particularly taking place around novel uses of mobile positioning data, web scraping, and open application programming interface (API) data, data on sharing, and collaborative economy and passenger data. Based on feedback from 15 European cultural tourism regions, recommendations are developed regarding the use of innovative tools and data sources in tourism management. In terms of potential analytical depth, it is especially advisable to explore the use of mobile positioning data. Yet, there are considerable barriers, especially in terms of privacy protection and ethics, in using such data. User-generated big data from social media, web searches, and website visits constitute another promising data source as it is often publicly available in real time and has low usage barriers. Due to the emergence of new platform-based business models in the travel and tourism sector, special attention should be paid to improving access and usage of data on sharing and collaborative economy.
Highlights
Cultural tourism as a sub-sector of tourism has been defined as a “type of tourism activity in which the visitor’s essential motivation is to learn, discover, experience and consume the tangible and intangible cultural attractions/products in a tourism destination” [1]
Cultural tourism is increasingly driven by language tourism and the search for cultural experiences based on the lifestyles and habits of the places visited [4]
Mobile network operators (MNO) automatically collect, for network management purposes, the data that is created when using mobile phones for calling, sending messages, or using Internet. Such data includes the time and location of all call events done on the network cell level. This kind of data is referred to as mobile positioning data (MPD), which means any type of mobile phone event data that includes a subscriber identifier, time attribute, and location [53]
Summary
Cultural tourism as a sub-sector of tourism has been defined as a “type of tourism activity in which the visitor’s essential motivation is to learn, discover, experience and consume the tangible and intangible cultural attractions/products in a tourism destination” [1]. Rapid advances in ICTs in recent decades have opened several new possibilities for collecting data about tourists and their behavior, movement, and preferences, thereby allowing the evaluation of the impact of tourism to specific destinations. One example of this is the widespread distribution of mobile phones. Mobile network operators (MNO) automatically collect, for network management purposes, the data that is created when using mobile phones for calling, sending messages, or using Internet Such data includes the time and location of all call events done on the network cell level. To understand whether and how cultural tourism regions use these novel data sources in practice, 15 IMPACTOUR pilots informed this research. Route of the Romanesque (Sousa, Tâmega and Douro) Route of the Romanesque (Saxony-Anhalt) Sassi (city of Matera) Tartu county Trebinje
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