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Modelling Users` Trust in Online Social Networks

Author

Listed:
  • Iacob Catoiu

    (Academia de Studii Economice Bucuresti)

  • Mihai Orzan

    (Academia de Studii Economice Bucuresti)

  • Octav-Ionut Macovei

    (Universitatea Europei de Sud-Est, Lumina)

  • Claudia Iconaru

    (Academia de Studii Economice Bucuresti)

Abstract

Previous studies (McKnight, Lankton and Tripp, 2011; Liao, Lui and Chen, 2011) have shown the crucial role of trust when choosing to disclose sensitive information online. This is the case of online social networks users, who must disclose a certain amount of personal data in order to gain access to these online services. Taking into account privacy calculus model and the risk/benefit ratio, we propose a model of users` trust in online social networks with four variables. We have adapted metrics for the purpose of our study and we have assessed their reliability and validity. We use a Partial Least Squares (PLS) based structural equation modelling analysis, which validated all our initial assumptions, indicating that our three predictors (privacy concerns, perceived benefits and perceived risks) explain 48% of the variation of users` trust in online social networks, the resulting variable of our study. We also discuss the implications and further research opportunities of our study.

Suggested Citation

  • Iacob Catoiu & Mihai Orzan & Octav-Ionut Macovei & Claudia Iconaru, 2014. "Modelling Users` Trust in Online Social Networks," The AMFITEATRU ECONOMIC journal, Academy of Economic Studies - Bucharest, Romania, vol. 16(35), pages 289-289, February.
    • Handle: RePEc:aes:amfeco:v:1:y:2014:i:35:p:289
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    References listed on IDEAS

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    Cited by:

    1. Liu, Yu-li & Yan, Wenjia & Hu, Bo, 2021. "Resistance to facial recognition payment in China: The influence of privacy-related factors," Telecommunications Policy, Elsevier, vol. 45(5).
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    3. Jain, Lokesh, 2022. "An entropy-based method to control COVID-19 rumors in online social networks using opinion leaders," Technology in Society, Elsevier, vol. 70(C).
    4. Szabolcs Nagy & Noemi Hajdu, 2021. "Consumer Acceptance of the Use of Artificial Intelligence in Online Shopping: Evidence From Hungary," The AMFITEATRU ECONOMIC journal, Academy of Economic Studies - Bucharest, Romania, vol. 23(56), pages 155-155, February.

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    More about this item

    Keywords

    social media; users trust; online privacy; structural equation;
    All these keywords.

    JEL classification:

    • M31 - Business Administration and Business Economics; Marketing; Accounting; Personnel Economics - - Marketing and Advertising - - - Marketing
    • L82 - Industrial Organization - - Industry Studies: Services - - - Entertainment; Media

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