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The role of attitude toward chatbots and privacy concern on the relationship between attitude toward mobile advertising and behavioral intent to use chatbots

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  • Lucrezia Maria Cosmo

    (University of Bari “Aldo Moro”)

  • Luigi Piper

    (University of Bari “Aldo Moro”)

  • Arianna Vittorio

    (University of Bari “Aldo Moro”)

Abstract

Chatbots are technological tools equipped with artificial intelligence that allow companies to interact with their consumers. Through their computers or mobile devices, consumers can use this technology to search for information, make purchases or request after-sales services. This study aims to identify the role of attitude toward chatbots and privacy concern in the relationship between attitude toward mobile advertising and behavioral intent to use chatbots. After reviewing the literature, the study proposes a moderated mediation model. Through a survey, the study shows that attitude toward mobile advertising does not have a direct effect on the behavioral intent to use chatbot, but is rather mediated by one’s attitude toward chatbots. In fact, the interactivity is unidirectional in the case of mobile advertising (from the company to the consumer), but bidirectional in the case of chatbots (in which consumers have an active role in communication). In line with these assumptions, the data analysis shows that internet privacy concerns only negatively moderate the relationship between attitude toward chatbots and behavioral intent to use this technology. These results can be useful for companies and researchers in terms of developing and testing new digital marketing strategies. The paper concludes with a discussion of the results’ theoretical and managerial implications.

Suggested Citation

  • Lucrezia Maria Cosmo & Luigi Piper & Arianna Vittorio, 2021. "The role of attitude toward chatbots and privacy concern on the relationship between attitude toward mobile advertising and behavioral intent to use chatbots," Italian Journal of Marketing, Springer, vol. 2021(1), pages 83-102, June.
    • Handle: RePEc:spr:ijmark:v:2021:y:2021:i:1:d:10.1007_s43039-021-00020-1
    DOI: 10.1007/s43039-021-00020-1
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    Cited by:

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    2. Ahmad M. Alghamdi & Salvatore Flavio Pileggi & Osama Sohaib, 2023. "Social Media Analysis to Enhance Sustainable Knowledge Management: A Concise Literature Review," Sustainability, MDPI, vol. 15(13), pages 1-30, June.
    3. Schillaci, Carmela Elita & de Cosmo, Lucrezia Maria & Piper, Luigi & Nicotra, Melita & Guido, Gianluigi, 2024. "Anthropomorphic chatbots' for future healthcare services: Effects of personality, gender, and roles on source credibility, user satisfaction, and intention to use," Technological Forecasting and Social Change, Elsevier, vol. 199(C).
    4. Andrea Mauro & Andrea Sestino & Andrea Bacconi, 2022. "Machine learning and artificial intelligence use in marketing: a general taxonomy," Italian Journal of Marketing, Springer, vol. 2022(4), pages 439-457, December.
    5. James Lappeman & Siddeeqah Marlie & Tamryn Johnson & Sloane Poggenpoel, 2023. "Trust and digital privacy: willingness to disclose personal information to banking chatbot services," Journal of Financial Services Marketing, Palgrave Macmillan, vol. 28(2), pages 337-357, June.
    6. Baabdullah, Abdullah M. & Alalwan, Ali Abdallah & Algharabat, Raed S. & Metri, Bhimaraya & Rana, Nripendra P., 2022. "Virtual agents and flow experience: An empirical examination of AI-powered chatbots," Technological Forecasting and Social Change, Elsevier, vol. 181(C).

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