Risk Aversion, Age, and Gender as Predictors of New Media Adoption: Evidence from LinkedIn, Twitter, Skype, and Viber

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dc.contributor.authorSudzina, Frantisek
dc.contributor.authorPavlicek, Antonin
dc.contributor.authorRozmberska, Lucie
dc.contributor.otherEkonomická fakultacs
dc.date.accessioned2025-10-02T10:24:24Z
dc.date.available2025-10-02T10:24:24Z
dc.description.abstractThis study investigates how risk aversion, age, and gender influence the adoption and use of new media platforms, specifically LinkedIn, Twitter, Skype, and Viber. Drawing on data from a web-based survey conducted via 1ka.si, we analyzed responses from 529 university students (289 men and 240 women), the vast majority of whom were 24 years old or younger. The questionnaire measured frequency of platform use, demographic characteristics, and self-assessed risk aversion levels. Our findings reveal significant associations between individual risk profiles and platform usage, with more risk-averse individuals showing lower engagement on socially and professionally open networks such as LinkedIn and Twitter. Age and gender were also found to be important moderating factors, shaping both the likelihood of adoption and patterns of usage across platforms. These results offer valuable insights into the psychological and demographic determinants of digital behavior and highlight the importance of tailoring digital communication strategies to diverse user profiles..en
dc.formattext
dc.identifier.doi10.15240/tul/009/lef-2025-17
dc.identifier.isbn978-80-7494-747-6
dc.identifier.urihttps://dspace.tul.cz/handle/15240/178045
dc.language.isoen
dc.publisherTechnická Univerzita v Libercics
dc.publisherTechnical university of Liberec, Czech Republicen
dc.publisher.abbreviationTUL
dc.relation.isbasedonAIOLFI, S., BELLINI, S., & PELLEGRINI, D. (2021). Data-driven digital advertising: Benefits and risks of online behavioral advertising. International Journal of Retail & Distribution Management, 49(7), 1089–1110. https://doi.org/10.1108/IJRDM-10-2020-0410 APAU, R., & LALLIE, H. S. (2022). Measuring user perceived security of mobile banking applications. arXiv (Cornell University). https://doi.org/10.48550/arxiv.2201.03052 ÇERA, G., PHAN, Q. P. T., ANDRONICEANU, A., & ÇERA, E. (2020). Financial capability and technology implications for online shopping. E+M Ekonomie a Management, 23(2), 156–172. https://doi.org/10.15240/tul/001/2020-2-011 GIL-CLAVEL, S., & ZAGHENI, E. (2019). Demographic differentials in Facebook usage around the world. arXiv (Cornell University). https://doi.org/10.48550/arxiv.1905.09105 GRANIĆ, A. (2023). Technology adoption at individual level: Toward an integrated overview. Universal Access in the Information Society, 23(2), 843–858. https://doi.org/10.1007/s10209-023-00974-3 KIRCABURUN, K., JONASON, P. K., & GRIFFITHS, M. D. (2018). The Dark Tetrad traits and problematic social media use: The mediating role of cyberbullying and cyberstalking. Personality and Individual Differences, 135, 264–269. https://doi.org/10.1016/j.paid.2018.07.034 LIN, T. T. C., CHIU, V., & LIM, W. (2011). Factors affecting the adoption of social network sites: Examining four adopter categories of Singapore’s working adults. Asian Journal of Communication, 21(3), 221–242. https://doi.org/10.1080/01292986.2011.559256 RAUNIAR, R., RAWSKI, G., YANG, J., & JOHNSON, B. (2014). Technology acceptance model (TAM) and social media usage: An empirical study on Facebook. Journal of Enterprise Information Management, 27(1), 6–30. https://doi.org/10.1108/JEIM-04-2012-0011 SINGH, S., SAHNI, M. M., & KOVID, R. K. (2020). What drives FinTech adoption? A multi-method evaluation using an adapted technology acceptance model. Management Decision, 58(8), 1675–1697. https://doi.org/10.1108/MD-09-2019-1318 STUMP, R. L., & GONG, W. (2017). Social networking sites: An exploration of the effect of national cultural dimensions on country adoption rates and usage patterns. International Journal of Electronic Business, 13(2–3), 117 -142. https://doi.org/10.1504/IJEB.2017.083288 SUDZINA, F. (2016). Do gender and personality traits influence frequency of use of deal sites? In Proceedings of the 29th Bled eConference.
dc.relation.ispartofLiberecké ekonomické fórum 2025cs
dc.relation.ispartofLiberec Economic Forum 2025en
dc.subjectNew Media Adoptionen
dc.subjectRisk Aversionen
dc.subjectAge and Genderen
dc.subjectSocial Networkingen
dc.subjectDigital Behavioren
dc.subject.classificationL86
dc.subject.classificationD81
dc.titleRisk Aversion, Age, and Gender as Predictors of New Media Adoption: Evidence from LinkedIn, Twitter, Skype, and Viberen
dc.typeproceeding paperen
local.accessopen
local.citation.epage286
local.citation.spage277
local.facultyFaculty of Economics
local.fulltextyes
local.relation.abbreviationLEFcs
local.relation.abbreviationLEFen
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