Determinants of Chatbot Brand Trust in the Adoption of Generative Artificial Intelligence in Higher Education
Bibliographic Data
| ID | 22041807 |
|---|---|
| Authors | Oluwanife Segun Falebita (0000-0002-8287-4005, University of Zululand, corresponding author), Joshua Abah Abah (0000-0001-5485-9396, University of Zululand), Akorede Ayoola Asanre (0000-0003-2787-2346, University of Zululand), Taiwo Oluwadayo Abiodun (0000-0003-2614-2229, Tai Solarin University of Education), Musa Adekunle Ayanwale (0000-0001-7640-9898, University of Johannesburg), Olubunmi Kayode Ayanwoye (0000-0001-7196-6302, Federal University Oye Ekiti) |
| Year | 2025 |
| Volume | 15 |
| Issue | 10 |
| Pages | 1389 |
| Publication date | 2025-10-17 |
| Peer Reviewed | Yes |
| Open Access | Yes |
| Type | ARTICLE |
| Venue | Education Sciences (JOURNAL) |
| Journal identifiers | ISSN: 2227-7102 • E-ISSN: 2227-7102 |
| Publisher | MDPI AG (PUBLISHER • IT) |
| DOI | 10.3390/educsci15101389 |
| OpenAlex | W4415279341 |
| Language | EN |
| Citations received | 1 |
| References cited | 60 |
The use of generative artificial intelligence (GenAI) chatbots in brands is growing exponentially, and higher education institutions are not unaware of how such tools effectively shape the attitudes and behavioral intentions of students. These chatbots are able to synthesize an enormous amount of data input and can create contextually aware, human-like conversational content that is not limited to simple scripted responses. This study examines the factors that determine chatbot brand trust in the adoption of GenAI in higher education. By extending the Technology Acceptance Model (TAM) with the construct of brand trust, the study introduces a novel contribution to the literature, offering fresh insights into how trust in GenAI chatbots is developed within the academic context. Using the convenience sampling technique, a sample of 609 students from public universities in North Central and Southwestern Nigeria was selected. The collected data were analyzed via partial least squares structural equation modelling. The results indicated that attitudes toward chatbots determine behavioral intentions and GenAI chatbot brand trust. Surprisingly, behavioral intentions do not affect GenAI chatbot brand trust. Similarly, the perceived ease of use of chatbots does not determine behavioral intention or attitudes toward GenAI chatbot adoption but rather determines perceived usefulness. Additionally, the perceived usefulness of chatbots affects behavioral intention and attitudes toward GenAI chatbot adoption. Moreover, social influence affects behavioral intention, perceived ease of use, perceived usefulness and attitudes toward GenAI chatbot adoption. The implications of the findings for higher education institutions are that homegrown GenAI chatbots that align with the principles of the institution should be developed, creating an environment that promotes a positive attitude toward these technologies. Specifically, the study recommends that policymakers and university administrators establish clear institutional guidelines for the design, deployment, and ethical use of homegrown GenAI chatbots, ensuring alignment with educational goals and safeguarding student trust
Chatbot · Higher education · Institution · Structural equation modeling · Technology Acceptance Model · Usability · Diverse Topics in Contemporary Research · Impact of AI and Big Data on Business and Society · Technology Adoption and User Behaviour
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| Unique citing works | 1 |
|---|---|
| Citations per year | 1 |
| Citation span | 2026 - 2026 (1) |
| Citation velocity | current |
| Highly cited | No |
| Citation types | Neutral: 1 |