- Tytuł:
- Mapping research on user-generated content in the service sector — a bibliometric analysis
- Autorzy:
- Wąsowicz-Zaborek, Elżbieta
- Powiązania:
- https://bibliotekanauki.pl/articles/11542305.pdf
- Data publikacji:
- 2023-09-30
- Wydawca:
- Sieć Badawcza Łukasiewicz - Instytut Lotnictwa
- Tematy:
-
UGC
user-generated content
customer behaviour research
service sector
literature review - Opis:
- The Web 2.0 era and the following phases of web development bring new challenges to businesses, but also new opportunities to establish and maintain relationships with market participants, indulge in direct contact with customers and learn about their needs, emotions and opinions. The advancement of content creation and sharing technologies creates an opportunity to collect information from anyone with access to the Internet. User-generated content (UGC) information is increasingly supporting decision-making and analysis for various types of business, management or marketing activities. Such information is also increasingly used as a source of data in scientific research. The present study seeks to evaluate the relevance of UGC in scientific research and the scope and ways in which content created by Internet users can be used by researchers of phenomena existing in the service sector. To achieve this goal, a bibliometric literature review (quantitative analysis of publications, identification of research collaborators, co-author analysis, co-citation analysis and co-word analysis) was conducted covering articles between 2012 and 2022 published in journals indexed in the Scopus database. The analysis used descriptive statistics and text and content analysis. A significant increase was observed in publications between 2020 and 2022. Among the various service branches, the researchers most often chose data sets in the form of comments posted online by customers of tourism industries, mainly those using accommodation services, but also restaurants. TripAdvisor was observed to be the most frequently used data source. In their analysis, the authors used both qualitative and quantitative methods, as well as a combination of them. It is observed that more sophisticated machine learning algorithms have been implemented for text analysis. Finally, the paper also presents future research recommendations.
- Źródło:
-
Marketing Instytucji Naukowych i Badawczych; 2023, 49, 3; 65-100
2353-8414 - Pojawia się w:
- Marketing Instytucji Naukowych i Badawczych
- Dostawca treści:
- Biblioteka Nauki
Artykuł