Previous studies employing the theoretical frameworks and contribution of this research into the domain
| Authors | Antecedent | Outcomes | Mediator/moderator | Theory | Country | Key findings |
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| 1. Priya and Sharma (2023) |
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| The findings demonstrated that all AI and socio-psychological factors, except for the link between Perceived Anthropomorphism and Hedonic Attitude, significantly impact user attitudes toward Intelligent Virtual Assistants. Both Hedonic Attitude and Utilitarian Attitude positively influence IVA acceptance; however, the Utilitarian Attitude is confirmed as the dominant factor determining usage in the financial services context. This prioritization of functional benefits over pleasure aligns with the core principles of TAM (usefulness). The study also found that the Need for Human Interaction acts as a positive moderator, strengthening the perceived usefulness derived from both anthropomorphism and intelligence. This strong emphasis on functionality suggests a foundation for future research to explore potential barriers, such as financial anxiety, which could create a “Knowledge-Behavior Gap” where knowing a technology is useful (Utilitarian Attitude) does not guarantee its full acceptance (Usage) |
| 2. Ma and Lei (2024) |
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| The study supported all proposed hypotheses, affirming TAM's effectiveness in the educational context. Perceived Usefulness (PU) was confirmed as the single most significant direct factor driving Behavioral Intention (BI), suggesting that teachers prioritize the functional benefits (utility) of AI. Furthermore, Artificial Intelligence Literacy (AIL) had the strongest indirect effect on acceptance. This dominance of knowledge-based factors (PU and AIL) establishes a foundation for future research to investigate how external obstacles, such as institutional disparities or policy issues, might prevent this high knowledge/utility perception from translating reliably into actual usage behavior (the Knowledge-Behavior Gap) |
| 3. Chocarro et al. (2021) |
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| Perceived Usefulness (PU) and Perceived Ease of Use (PEU) significantly increase teachers' intention to use educational chatbots. Surprisingly, social language use (including emoticons) was found to have a significant negative influence on usage intention, indicating a preference for formal communication in educational settings. Proactiveness, teacher Age, and Digital Skills did not significantly predict acceptance. The confirmed dominance of functional benefits (PU, a core TAM construct) in this professional context establishes the groundwork for future research to investigate the Knowledge-Behavior Gap, analyzing why this high awareness of utility (knowledge) might fail to result in widespread adoption if other external barriers, such as policy or institutional characteristics, are present | |
| 4. Stibe and Dinh (2024) |
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| The primary hypothesis path was strongly supported, confirming that Knowledge – Acceptance - Intention – Behavior is the dominant route for AI adoption, although weaker “shortcut” paths were also observed. The effect of Education level was confirmed to positively strengthen the link between Knowledge and Behavior, and Age was found to strengthen the link from Acceptance to Intention. The overall success of the sequential KBG model, which challenges the assumption that knowledge automatically translates into action, directly enables future research to integrate this gap premise with classical models like TAM, specifically by exploring how external factors block the perceived utility (knowledge) from translating into actual behavior |
| 5. Zhang et al. (2025c) |
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| Subjective norm was found to influence user attitudes toward Generative AI (GenAI) consistently in both countries, and Attitude, Subjective norm, and Perceived behavioral control were critical predictors of Usage intention across both groups. However, significant cultural differences emerged: Perceived usefulness and Perceived risk were the most crucial predictors for users in China, reflecting a focus on collective utility and caution, while Perceived ease of use and Openness to experience were more influential for users in the USA, reflecting a preference for individual autonomy and usability. This strong emphasis on Perceived usefulness (a core TAM construct based on cognitive knowledge of benefits) in one culture, juxtaposed with high Perceived risk acting as a negative barrier (also highly significant in China), sets the stage for future research exploring how strong knowledge of utility might still be blocked from translating into behavior by cultural risk aversion or other external factors not fully captured by the core model |
| 6. Abdelrahman et al. (2025) |
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| All hypothesized relationships in the integrated model were strongly supported. The study confirmed that Organizational Culture positively impacts employee perceptions of Perceived usefulness and Perceived ease of use, as well as directly increasing Knowledge Management Systems usage. Consistent with TAM, both Perceived usefulness and Perceived ease of use significantly drive KMSs usage, which, in turn, facilitates Knowledge Sharing, subsequently leading to enhanced Organizational Effectiveness. The success of this model in confirming that the cognitive benefit (Perceived usefulness, a core TAM construct) is enhanced by Organizational Culture lays the groundwork for future research to investigate the Knowledge-Behavior Gap by exploring how organizational friction or deep-seated cultural resistance to sharing (behavioral barriers) might still constrain the achievement of Organizational Effectiveness, despite employees acknowledging the utility of the system |
| 7. Ajili Ben Youssef et al. (2025) |
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| All seven factors derived from the TOE framework, spanning technological, organizational, and environmental contexts, were found to significantly influence GenAI adoption. Organizational readiness (OR) emerged as the most influential driver, confirming that internal capacity is paramount, while Complexity (CPL) presented a significant negative barrier to adoption. The strong positive confirmation of factors based on knowledge of utility, such as Relative advantage and Compatibility, reinforces the core idea of TAM (Perceived Usefulness). This strong emphasis on organizational knowledge and utility, set against the significant barrier of complexity, provides a foundation for future research to explore how the functional knowledge of GenAI benefits might be undermined by implementation challenges and the complexity of the regulatory environment | |
| 8. Kelly and Palaniappan (2023) |
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| The study supported nearly all hypotheses, indicating that Perceived usefulness, Perceived ease of use, Perceived risk, Perceived cost, and Social influence all significantly impact Attitude toward using mobile money banking, which then impacts Actual use of mobile banking. Notably, Perceived usefulness was found to have a significant positive impact on Actual use, while the relationship between Perceived trust and Attitude was not supported in the model. Furthermore, the study concluded that users' Attitude toward using mobile money significantly impacts Actual use. The dominance of Perceived usefulness (a core TAM construct based on cognitive knowledge of utility) confirms its role as a key factor in continuous usage. This reliance on known utility, coupled with the unexpected finding that a key psychological factor like Perceived trust failed to positively influence attitude, suggests a foundation for future research exploring the Knowledge-Behavior Gap by investigating whether strong knowledge of utility is sufficient to overcome potential behavioral or systemic barriers, such as a lack of trust or external risks, that might otherwise inhibit long-term adoption and continuous usage |
| 9. Lim and Zhang (2022) |
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| The integrative model successfully predicted the adoption behavior of users. Consistent with TAM, Perceived usefulness and Perceived ease of use positively influenced Attitudes toward AI-powered news, which subsequently drove Engagement and Adoption. The most substantial finding was the powerful role of Perceived contingency, which exhibited the strongest total influence on Adoption through both direct and indirect paths, emphasizing the importance of adaptive interactivity in AI-driven technologies. Furthermore, Attitudes and Engagement acted as full mediators for Perceived ease of use on Adoption, but only partial mediators for Perceived usefulness |
| Current study |
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| The study revealed divergent results between the two countries regarding specific adoption factors. Information diagnosticity was positively associated with the assessment's perceived utility in Vietnam, but the results showed the opposite in China. Furthermore, social influence was significantly linked to the intention to adopt AI-powered financial management in China, yet it had no significance associated with the Vietnamese old generation's intention. Key foundational variables such as AI self-efficacy and AI literacy were generally found to be positively linked to user perceptions (like perceived ease of use and perceived utility) and acceptance in both countries |
| Authors | Antecedent | Outcomes | Mediator/moderator | Theory | Country | Key findings |
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| 1. | Perceived Anthropomorphism Perceived Intelligence Perceived Animacy Technological Self-efficacy Social Presence | Usage of Intelligent Virtual Assistants (Chatbot) of Fintech services | Hedonic Attitude Utilitarian Attitude Need for Human Interaction (NFHI) | Technology Adoption Models (TAM 1, TAM 2) Theory of Reasoned Action Theory of Planned Behavior Dual-Process Theory CASA (Computers Are Social Actors) paradigm | India | The findings demonstrated that all AI and socio-psychological factors, except for the link between Perceived Anthropomorphism and Hedonic Attitude, significantly impact user attitudes toward Intelligent Virtual Assistants. Both Hedonic Attitude and Utilitarian Attitude positively influence IVA acceptance; however, the Utilitarian Attitude is confirmed as the dominant factor determining usage in the financial services context. This prioritization of functional benefits over pleasure aligns with the core principles of TAM (usefulness). The study also found that the Need for Human Interaction acts as a positive moderator, strengthening the perceived usefulness derived from both anthropomorphism and intelligence. This strong emphasis on functionality suggests a foundation for future research to explore potential barriers, such as financial anxiety, which could create a “Knowledge-Behavior Gap” where knowing a technology is useful (Utilitarian Attitude) does not guarantee its full acceptance (Usage) |
| 2. | Artificial Intelligence Literacy (AIL) Subjective Norms (SN) | Behavioral Intention | Output Quality (OQ) Perceived Usefulness (PU) Perceived Ease of Use (PEU) | Technology Acceptance Model (TAM) | China | The study supported all proposed hypotheses, affirming TAM's effectiveness in the educational context. Perceived Usefulness (PU) was confirmed as the single most significant direct factor driving Behavioral Intention (BI), suggesting that teachers prioritize the functional benefits (utility) of AI. Furthermore, Artificial Intelligence Literacy (AIL) had the strongest indirect effect on acceptance. This dominance of knowledge-based factors (PU and AIL) establishes a foundation for future research to investigate how external obstacles, such as institutional disparities or policy issues, might prevent this high knowledge/utility perception from translating reliably into actual usage behavior (the Knowledge-Behavior Gap) |
| 3. | Perceived Usefulness (PU) Perceived Ease of Use (PEU) Social Language Proactiveness Teacher's digital skills Teacher's age | Chatbot Intention of Use | Technology Acceptance Model (TAM) | Spain | Perceived Usefulness (PU) and Perceived Ease of Use (PEU) significantly increase teachers' intention to use educational chatbots. Surprisingly, social language use (including emoticons) was found to have a significant negative influence on usage intention, indicating a preference for formal communication in educational settings. Proactiveness, teacher Age, and Digital Skills did not significantly predict acceptance. The confirmed dominance of functional benefits (PU, a core TAM construct) in this professional context establishes the groundwork for future research to investigate the Knowledge-Behavior Gap, analyzing why this high awareness of utility (knowledge) might fail to result in widespread adoption if other external barriers, such as policy or institutional characteristics, are present | |
| 4. | Knowledge | Behavior | Acceptance Intention | Technology Acceptance Model (TAM) Theory of Reasoned Action (TRA) The Unified Theory of Acceptance and Use of Technology (UTAUT) | Global | The primary hypothesis path was strongly supported, confirming that Knowledge – Acceptance - Intention – Behavior is the dominant route for AI adoption, although weaker “shortcut” paths were also observed. The effect of Education level was confirmed to positively strengthen the link between Knowledge and Behavior, and Age was found to strengthen the link from Acceptance to Intention. The overall success of the sequential KBG model, which challenges the assumption that knowledge automatically translates into action, directly enables future research to integrate this gap premise with classical models like TAM, specifically by exploring how external factors block the perceived utility (knowledge) from translating into actual behavior |
| 5. | Perceived ease of use (PEU) | Usage intention (UI) | Perceived usefulness (PU) Attitude toward GenAI (ATT) Subjective norm (SN) Perceived behavioral control (PBC) Perceived risk (PR) AI literacy (AIL) Cultural value differences | Technology Acceptance Model Theory of Planned Behavior | China USA | Subjective norm was found to influence user attitudes toward Generative AI (GenAI) consistently in both countries, and Attitude, Subjective norm, and Perceived behavioral control were critical predictors of Usage intention across both groups. However, significant cultural differences emerged: Perceived usefulness and Perceived risk were the most crucial predictors for users in China, reflecting a focus on collective utility and caution, while Perceived ease of use and Openness to experience were more influential for users in the USA, reflecting a preference for individual autonomy and usability. This strong emphasis on Perceived usefulness (a core TAM construct based on cognitive knowledge of benefits) in one culture, juxtaposed with high Perceived risk acting as a negative barrier (also highly significant in China), sets the stage for future research exploring how strong knowledge of utility might still be blocked from translating into behavior by cultural risk aversion or other external factors not fully captured by the core model |
| 6. | Organizational Culture | Organizational Effectiveness | Perceived usefulness (PU) Perceived ease of use (PEU) Knowledge Management Systems usage Knowledge Sharing | Technology Acceptance Model (TAM) | Europe Middle East (EME) | All hypothesized relationships in the integrated model were strongly supported. The study confirmed that Organizational Culture positively impacts employee perceptions of Perceived usefulness and Perceived ease of use, as well as directly increasing Knowledge Management Systems usage. Consistent with TAM, both Perceived usefulness and Perceived ease of use significantly drive KMSs usage, which, in turn, facilitates Knowledge Sharing, subsequently leading to enhanced Organizational Effectiveness. The success of this model in confirming that the cognitive benefit (Perceived usefulness, a core TAM construct) is enhanced by Organizational Culture lays the groundwork for future research to investigate the Knowledge-Behavior Gap by exploring how organizational friction or deep-seated cultural resistance to sharing (behavioral barriers) might still constrain the achievement of Organizational Effectiveness, despite employees acknowledging the utility of the system |
| 7. | Relative advantage (RA) Compatibility (CPT) Complexity (CPL) Organizational readiness (OR) Firm size (FS) Competitive pressure (CP) Government support (GS) | Generative AI adoption (GAIA) | Technology – Organization - Environment (TOE) Innovation Diffusion Theory (IDT) Technology Acceptance Model (TAM) | Vietnam | All seven factors derived from the TOE framework, spanning technological, organizational, and environmental contexts, were found to significantly influence GenAI adoption. Organizational readiness (OR) emerged as the most influential driver, confirming that internal capacity is paramount, while Complexity (CPL) presented a significant negative barrier to adoption. The strong positive confirmation of factors based on knowledge of utility, such as Relative advantage and Compatibility, reinforces the core idea of TAM (Perceived Usefulness). This strong emphasis on organizational knowledge and utility, set against the significant barrier of complexity, provides a foundation for future research to explore how the functional knowledge of GenAI benefits might be undermined by implementation challenges and the complexity of the regulatory environment | |
| 8. | Perceived ease of use Perceived usefulness Perceived trust Perceived cost Perceived risk Social influence | Actual use of mobile banking | Attitude toward using mobile money banking | Technology Acceptance Model (TAM) Theory of Reason Action (TRA) | Ghana | The study supported nearly all hypotheses, indicating that Perceived usefulness, Perceived ease of use, Perceived risk, Perceived cost, and Social influence all significantly impact Attitude toward using mobile money banking, which then impacts Actual use of mobile banking. Notably, Perceived usefulness was found to have a significant positive impact on Actual use, while the relationship between Perceived trust and Attitude was not supported in the model. Furthermore, the study concluded that users' Attitude toward using mobile money significantly impacts Actual use. The dominance of Perceived usefulness (a core TAM construct based on cognitive knowledge of utility) confirms its role as a key factor in continuous usage. This reliance on known utility, coupled with the unexpected finding that a key psychological factor like Perceived trust failed to positively influence attitude, suggests a foundation for future research exploring the Knowledge-Behavior Gap by investigating whether strong knowledge of utility is sufficient to overcome potential behavioral or systemic barriers, such as a lack of trust or external risks, that might otherwise inhibit long-term adoption and continuous usage |
| 9. | Perceived usefulness (PU) Perceived ease of use (PEOU) Perceived contingency (CONT) | Adoption of AI-powered news (ADOPT) | Attitudes toward AI-powered news (ATTI) Engagement with AI-powered news (ENGA) | Technology Acceptance Model (TAM) The Perceived Contingency Model | USA | The integrative model successfully predicted the adoption behavior of users. Consistent with TAM, Perceived usefulness and Perceived ease of use positively influenced Attitudes toward AI-powered news, which subsequently drove Engagement and Adoption. The most substantial finding was the powerful role of Perceived contingency, which exhibited the strongest total influence on Adoption through both direct and indirect paths, emphasizing the importance of adaptive interactivity in AI-driven technologies. Furthermore, Attitudes and Engagement acted as full mediators for Perceived ease of use on Adoption, but only partial mediators for Perceived usefulness |
AI Self-Efficacy Perceived Accountability Social Influence Information Diagnosticity Information Quality Information Understandability | Intention | AI Literacy Assessment Perceived Utility Perceived Ease of Use Acceptance Perceived Privacy Control Personal Innovativeness Brand Reputation | Technology Acceptance Model (TAM) KBG model | Vietnam China | The study revealed divergent results between the two countries regarding specific adoption factors. Information diagnosticity was positively associated with the assessment's perceived utility in Vietnam, but the results showed the opposite in China. Furthermore, social influence was significantly linked to the intention to adopt AI-powered financial management in China, yet it had no significance associated with the Vietnamese old generation's intention. Key foundational variables such as AI self-efficacy and AI literacy were generally found to be positively linked to user perceptions (like perceived ease of use and perceived utility) and acceptance in both countries |
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