Suchergebnisse

The transformation of society and the development of digital technologies have significantly affected consumer behavior: consumer identity is now spreading to digital environment, with a new segment of digital consumers being developed. As a result of digitalization, new business models are emerging, for example, commercial sharing systems, the full functioning of which is impossible without the existence of digital platforms and the Internet. Despite the popularity of the topic of commercial sharing systems in the research environment and a wide range of tools used in research, at the moment no attempts have been made to study a digital profile of commercial sharing services users based on the analysis of their social networks profiles. Social network data are one of the most extensive sources of information about consumers: the ability to analyze consumer behavior in social networks can become a significant competitive advantage for companies, as it allows them to quickly extract objective information about the users. The objective of the study is to develop digital profiles of commercial sharing systems' users based on their digital footprint data. The empirical basis of the study is the publications (posts) of commercial sharing communities' subscribers on a popular Russian social network VKontakte. The information posted by users in social networks was collected using Python (the API, Application Programming Interface are used), the sample size comprises 24,000 profiles. The collected data have been processed and analyzed using the topic modeling method, as a result of the analysis, 12 main topics are identified characterizing users' interests. Based on individual topic profiles, topic profiles of communities are formed, furthermore, differences in the digital behavior commercial sharing systems profiles were identified. The application of data on user behavior in digital environment creates new opportunities for digital companies and can become the basis for improving the performance of personalization services, timely adaptation of product offers and approaches to interaction with customers, as well as become the basis for the development of ecosystems.

Digital transformation and rapid development of Internet technologies in the past decade have contributed to the emergence of an innovative business model of collaborative consumption [Sheresheva, Katsoni, 2019] and the spread of collaborative consumption services (CCS). This study attempts to identify the factors that influence consumers' decision to use CCS, drawing on generation differences formulated on the basis of generation theory, with a particular focus on Russian consumers. The factors highlighted as a result of systematization of existing studies have been tested on the data of a quantitative study conducted in the form of an online survey with a sample of 3635 Russian users of CCS. An explanatory factor analysis (EFA) helps the authors construct the framework of factors that influence the decision of three generations of consumers (X, Y, and Z) to use CCS. The analysis of variance between the groups (ANOVA) highlights the generation differences that affect the decision to use the CCS by representatives of three generations. The identified generation features are of both theoretical significance, serving as a basis for further research, and practical value for business, mitigating the risks of introducing new CCS to the market, allowing for the needs of various generations of users.