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Exploring the Antecedents of Artificial Intelligence Products’ Usage. The Case of Business Students

Author

Listed:
  • Rodney Duffett

    (Cape Peninsula University of Technology, Cape Town, South Africa)

  • Rodica Milena Zaharia

    (Bucharest University of Economic Studies, Bucharest, Romania)

  • Tudor Edu

    (Romanian-American University, Bucharest, Romania)

  • Raluca Constantinescu

    (Bucharest University of Economic Studies, Bucharest, Romania)

  • Costel Negricea

    (Romanian-American University, Bucharest, Romania)

Abstract

This study aims to investigate to what extent facilitating conditions (those means that users consider necessary to use for a certain technology) and other predictors (perceived risk and lack of trust in technology, gender, education, income, technology proficiency and equipment used to access the Internet) influence the use of Artificial Intelligence Products (AIP) in general and for education. Using the Unified Theory of Acceptance and Use of Technology (UTAUT), the data collected, through an online questionnaire from a sample of 450 Romanian business students, were examined using principal component analysis (PCA) and logistic regression. Facilitating conditions indicated a direct effect (positive) on the dependent variables, and the combination between perceived risk and perceived lack of trust in technology displayed an opposite effect (negative) on the dependent variables. Female students showed a greater tendency to use AIPs in general and for education. Undergraduate students were more inclined to use AIPs in general. Students not using smartwatches or personal computers are inclined to use AIPs more in general and for education. This study advances the theory by exploring the actual use of AIPs for educational purposes, developing the UTAUT model by isolating facilitating conditions and using descriptive variables as predictors. At the same time, the present research contributes to enriching the empirical evidence related to UTAUT on the acceptance and use of technology in Romania. The results of the research allow for the formulation of practical recommendations for universities as current and potential providers of AIPs in order to make the educational process more efficient.

Suggested Citation

  • Rodney Duffett & Rodica Milena Zaharia & Tudor Edu & Raluca Constantinescu & Costel Negricea, 2024. "Exploring the Antecedents of Artificial Intelligence Products’ Usage. The Case of Business Students," The AMFITEATRU ECONOMIC journal, Academy of Economic Studies - Bucharest, Romania, vol. 26(65), pages 106-106, February.
    • Handle: RePEc:aes:amfeco:v:26:y:2024:i:65:p:106
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    References listed on IDEAS

    as
    1. Robinson, Stephen Cory, 2020. "Trust, transparency, and openness: How inclusion of cultural values shapes Nordic national public policy strategies for artificial intelligence (AI)," Technology in Society, Elsevier, vol. 63(C).
    2. Scott Thiebes & Sebastian Lins & Ali Sunyaev, 2021. "Trustworthy artificial intelligence," Electronic Markets, Springer;IIM University of St. Gallen, vol. 31(2), pages 447-464, June.
    3. Du, Shuili & Xie, Chunyan, 2021. "Paradoxes of artificial intelligence in consumer markets: Ethical challenges and opportunities," Journal of Business Research, Elsevier, vol. 129(C), pages 961-974.
    4. Alina Iorga Pisica & Tudor Edu & Rodica Milena Zaharia & Razvan Zaharia, 2023. "Implementing Artificial Intelligence in Higher Education: Pros and Cons from the Perspectives of Academics," Societies, MDPI, vol. 13(5), pages 1-13, May.
    5. Bernd Schmitt, 2019. "From Atoms to Bits and Back: A Research Curation on Digital Technology and Agenda for Future Research," Journal of Consumer Research, Journal of Consumer Research Inc., vol. 46(4), pages 825-832.
    6. Gansser, Oliver Alexander & Reich, Christina Stefanie, 2021. "A new acceptance model for artificial intelligence with extensions to UTAUT2: An empirical study in three segments of application," Technology in Society, Elsevier, vol. 65(C).
    Full references (including those not matched with items on IDEAS)

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    More about this item

    Keywords

    Artificial Intelligence (AI); Artificial Intelligence Product (AIP); business students; Unified Theory of Acceptance and Use of Technology (UTAUT); principal component analysis (PCA); logistic regression; Romania.;
    All these keywords.

    JEL classification:

    • I23 - Health, Education, and Welfare - - Education - - - Higher Education; Research Institutions
    • M31 - Business Administration and Business Economics; Marketing; Accounting; Personnel Economics - - Marketing and Advertising - - - Marketing
    • C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation
    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods

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