Smart Tourism: Towards the Concept of a Data-Based Travel Experience
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designed to transform recorded experiences into exciting narratives (digital storytelling). Impulsive recording and sharing obviously arouses the interest of marketers
as an unprecedented source of data and multimedia content. It can be used to gather
a user’s psychographic data and promote places, brands, lifestyles, and symbolic
content.
One of the consequences of the global dissemination of ICT is that a huge number
of digital records are created continuously and much of this data can be collected,
stored, processed and analysed. We are being moved toward an increasingly datadriven ‘sensor society’ wherein an individual leaves a huge data footprint during
the course of his/her everyday life, creating opportunities for business development
(Andrejevic and Burdon 2014). The data include log files (e.g. web servers record
in log files, click-through-rates, and other property records of web users), records of
credit card transactions, search engine traffic statistics, etc. Social platforms collect
data on all aspects of our lives and activities: from taste to actual actions. Web
intelligence applications help to address the big data challenge and answer plenty of
questions (e.g., What are the driving factors that affect the reputation of a destination
among social media users? Are there relevant events that should be tracked? Who
are the most influential online voices reporting on these events?).
SoLoMo (Social-Local-Mobile) applications enable simultaneous involvement
in mobile and georeferential blogging (Helal and Ozuem 2019). Wearable devices
(e.g., the Apple iWatch, fitness bands, etc.) have been widely adopted by consumers
owing to their usability for travel purposes (Tussyadiah 2013). Each airline, hotel
or car reservation is a digital footprint, irrelevant when isolated from context, but
when analysed together with the entire data set, it provides useful analyses of tourists’
behaviour and desires, enables forecasting, and can become the basis for management
decisions (Davenport et al. 2012; Mariani et al. 2018). Thanks to daily mass visits
of mobile users, analytical applications formulate and verify emerging consumer
trends. The reach and effectiveness of these communities strengthen the dynamics of
social learning processes and the pace of information flow (Mariani et al. 2018). The
mass connection of physical devices equipped with sensors that can send records to
the cloud system (IoT) that are embedded within tourism destination environments
allows for the collection and analysis of large amounts of data. The informationintensive nature of the tourism industry makes it an ideal match for the use of data
analysis (Mariani et al. 2018).
Data remains useless without proper data mining and analysis, which comprises
techniques and algorithms for determining interesting patterns in user behaviour.
This process includes: market segmentation, custom churn; fraud detection; direct
marketing; interactive and predictive marketing, market basket analysis and trend
analysis (Du 2010). The era of ‘smartness’ goes one step further in the recognition
of the impact of ICTs in tourism. Smart tourism destination (STD) is the offspring of
the technological foundations of smart cities, benefiting from the interplay with other
technological environments based on big data analytics. A common assumption is the
belief that the wide and ubiquitous use of technology itself makes the region ‘intelligent’. However, the main target for developing STD is to pursue the convenience of
public services, the delicacy of destination management, sustainability, smartness of
293
designed to transform recorded experiences into exciting narratives (digital storytelling). Impulsive recording and sharing obviously arouses the interest of marketers
as an unprecedented source of data and multimedia content. It can be used to gather
a user’s psychographic data and promote places, brands, lifestyles, and symbolic
content.
One of the consequences of the global dissemination of ICT is that a huge number
of digital records are created continuously and much of this data can be collected,
stored, processed and analysed. We are being moved toward an increasingly datadriven ‘sensor society’ wherein an individual leaves a huge data footprint during
the course of his/her everyday life, creating opportunities for business development
(Andrejevic and Burdon 2014). The data include log files (e.g. web servers record
in log files, click-through-rates, and other property records of web users), records of
credit card transactions, search engine traffic statistics, etc. Social platforms collect
data on all aspects of our lives and activities: from taste to actual actions. Web
intelligence applications help to address the big data challenge and answer plenty of
questions (e.g., What are the driving factors that affect the reputation of a destination
among social media users? Are there relevant events that should be tracked? Who
are the most influential online voices reporting on these events?).
SoLoMo (Social-Local-Mobile) applications enable simultaneous involvement
in mobile and georeferential blogging (Helal and Ozuem 2019). Wearable devices
(e.g., the Apple iWatch, fitness bands, etc.) have been widely adopted by consumers
owing to their usability for travel purposes (Tussyadiah 2013). Each airline, hotel
or car reservation is a digital footprint, irrelevant when isolated from context, but
when analysed together with the entire data set, it provides useful analyses of tourists’
behaviour and desires, enables forecasting, and can become the basis for management
decisions (Davenport et al. 2012; Mariani et al. 2018). Thanks to daily mass visits
of mobile users, analytical applications formulate and verify emerging consumer
trends. The reach and effectiveness of these communities strengthen the dynamics of
social learning processes and the pace of information flow (Mariani et al. 2018). The
mass connection of physical devices equipped with sensors that can send records to
the cloud system (IoT) that are embedded within tourism destination environments
allows for the collection and analysis of large amounts of data. The informationintensive nature of the tourism industry makes it an ideal match for the use of data
analysis (Mariani et al. 2018).
Data remains useless without proper data mining and analysis, which comprises
techniques and algorithms for determining interesting patterns in user behaviour.
This process includes: market segmentation, custom churn; fraud detection; direct
marketing; interactive and predictive marketing, market basket analysis and trend
analysis (Du 2010). The era of ‘smartness’ goes one step further in the recognition
of the impact of ICTs in tourism. Smart tourism destination (STD) is the offspring of
the technological foundations of smart cities, benefiting from the interplay with other
technological environments based on big data analytics. A common assumption is the
belief that the wide and ubiquitous use of technology itself makes the region ‘intelligent’. However, the main target for developing STD is to pursue the convenience of
public services, the delicacy of destination management, sustainability, smartness of