Page 34 - Management 19 (2024), številka 1

Fabrizio Gritta | The Use of Social Big Data in Small Hospitality Businesses

the potential of Big Data. However, implementa- • Data as the new ‘Intel Inside’, highlighting
tion is limited, which highlights an underexplo- the importance of user-collected data and
red area in mega-data analysis and AI. their role in creating value for web applica-
tions;
Literature Analysis • User experiences, which enhance the intera-
The theme of Social Big Data encompasses vari- ctivity and usability of web applications.
ous characteristics that have been explored and
detailed through selected contributions and em- A number of authors have identified the ad-
pirical research. The literature on this subject is vantages of Web 2.0 and ICTs for the hospitality
evolving, due to the ongoing impact of emerging sector. Lim et al. (2011), for instance, have high-
technologies. This can be attributed to two main lighted the potential for innovations in customer
streams of thought that trace the use of social self-service and community building. The advent
media in the tourism industry: of Web 2.0 has had a profound impact on the cho-
ices made by travellers, with social platforms, re-
• The evolution of Web 2.0, analysing how view portals and online booking sites all playing
the advent of social media has contributed a significant role (Cozzi 2010). User reviews are
to market approach development (Buhalis of significant importance in shaping the image
and O’Connor 2005; Cozzi 2010; Lim et al. of hotels and influencing potential guests’ per-
2011; Meini and Spinelli 2012; Scott and Orli- ceptions (Moretta Tartaglione, Berné Manero,
kowski 2012; Leung et al. 2013; Moretta Tar- and Vicuta Ciobanu 2018). Social media has been
taglione, Berné Manero, and Vicuta Ciobanu identified as the most impactful form of Web
2018; Tuten and Solomon 2012; Bizirgianni 2.0, and it is therefore essential for the promo-
and Dionysopoulou 2013; Panahande 2021); tion of tourist destinations, the management of
• The use of Big Data originating from media online reputations, and the creation of engaging
(Mayer-Schönberger and Cukier 2013; Jin- travel experiences (Leung et al. 2013). Young to-
gjing et al. 2018; Del Vecchio et al. 2018; Si- urists actively influence the structure of tourist
gala, Rahimi, and Thelwall 2019; Belias et al. offerings based on online opinions (Bizirgianni
2021; Blanco-Moreno et al. 2023; Das, Taluk- and Dionysopoulou 2013). The influence of plat-
der, and Pego 2024). forms such as TripAdvisor on the tourism sector
is considerable, with implications for the success
and challenges faced by businesses (Scott and Or-
Since the mid-1990s, with the advent of online
distribution processes, the Internet has transfor- likowski 2012). In their 2012 study, Kastner and
med the tourism sector. By the early 2000s, with Stangl investigated the impact of user-generated
the emergence of Web 2.0, tourism businesses be- content (UGC) and specific tourism web applica-
gan to focus on the development of relationships tions on consumer behaviour and travel experi-
with consumers, the enhancement of interacti- ences. They posited that such platforms enable
vity, and the reengineering of the development, extensive information sharing and the aggrega-
management, and marketing of tourism products tion of personal experiences, which in turn shape
(Kotler and Keller 2007; Buhalis and O’Connor consumer behaviour and travel experiences.
2005). The term ‘Web 2.0’ was coined by Tim The proliferation of data and large-scale pro-
O’Reilly to describe the shift from static, one-way cessing has given rise to the phenomenon of Big
communication websites to dynamic, interactive Data,defined by Mayer-Schönberger and Cukier
(2013, 66) as ‘data that can be processed at a lar-
platforms. This new paradigm places a premium ge scale but not at a smaller scale, with the aim
on interaction between industry operators and of extracting new insights or creating new forms
users, thereby fundamentally transforming the of value’. Hotel managers can identify customer
manner in which tourism services are promoted trends and preferences (Wu 2016) and, with the
and offered (O’Reilly 2007). According to O’Reilly aid of AI and machine learning, improve decisio-
(2007), the new paradigm is based on principles of n-making, personalise marketing strategies, en-
interaction among industry operators, including:
hance transparency and trust, and develop new
• The network as a platform; business models (Del Vecchio et al. 2018). The
• Collective intelligence, which relies on user advent of Big Data has led to a revolution in the
contributions to create and improve content field of tourism research, offering insights into
and services; tourist behaviours and market dynamics that

34 management 19 (2024) številka 1