The technology acceptance model and adopter type analysis in the context of artificial intelligence DOI Creative Commons
Fabio Ibrahim, Johann‐Christoph Münscher, Monika Daseking

et al.

Frontiers in Artificial Intelligence, Journal Year: 2025, Volume and Issue: 7

Published: Jan. 16, 2025

Artificial Intelligence (AI) is a transformative technology impacting various sectors of society and the economy. Understanding factors influencing AI adoption critical for both research practice. This study focuses on two key objectives: (1) validating an extended version Technology Acceptance Model (TAM) in context by integrating Big Five personality traits mindset, (2) conducting exploratory k-prototype analysis to classify adopters based demographics, AI-related attitudes, usage patterns. A sample N = 1,007 individuals (60% female; M 30.92; SD 8.63 years) was collected. Psychometric data were obtained using validated scales TAM constructs, traits, mindset. Regression used validate TAM, clustering algorithm applied participants into adopter categories. The psychometric confirmed validity TAM. Perceived usefulness strongest predictor attitudes towards (β 0.34, p < 0.001), followed mindset scale growth 0.28, 0.001). Additionally, openness positively associated with perceived ease use 0.15, revealed four distinct clusters, consistent diffusion innovations model: early (n 218), majority 331), late 293), laggards 165). findings highlight importance shaping toward adoption. results provide nuanced understanding types, aligning established innovation theories. Implications deployment strategies, policy-making, future directions are discussed.

Language: Английский

The impact of adopting AI educational technologies on projected course satisfaction in university students DOI Creative Commons
Paul Rodway, Astrid Schepman

Computers and Education Artificial Intelligence, Journal Year: 2023, Volume and Issue: 5, P. 100150 - 100150

Published: Jan. 1, 2023

Artificial Intelligence (AI) applications for education are being developed at an increasing pace. It seems reasonable to assume that these would enhance student experiences and course satisfaction, therefore educational institutions should invest in technologies their offer. However, this be tested empirically. In the current study a gender-balanced sample of 302 UK students rated completed General Attitudes towards AI Scale (GAAIS), comfortableness with applications, satisfaction if were adopted. Although were, on average, moderately comfortable dropped response hypothetical adoption. assigned summative grades or offered wellbeing support gave rise highest levels discomfort. Students more career support, formative administrative support. Positive Negative attitudes predicted difference, mediation via applications. We recommend Higher Education Institutions exercise caution before making major investments

Language: Английский

Citations

67
Self-determination and attitudes toward artificial intelligence: Cross-national and longitudinal perspectives DOI Creative Commons
J. Bergdahl, Rita Latikka, Magdalena Celuch

et al.

Telematics and Informatics, Journal Year: 2023, Volume and Issue: 82, P. 102013 - 102013

Published: June 29, 2023

Artificial intelligence (AI) is becoming increasingly important in all domains of life. Therefore, it crucial to understand individuals' attitudes towards AI. This article investigated toward AI through two studies that are based on the self-determination theory and basic psychological needs (autonomy, competence, relatedness). Study 1 used cross-sectional samples adult populations aged 18–75 Finland (N = 1,541), France 1,561), Germany 1,529), Ireland 1,112), Italy 1,530), Poland 1,533). 2 was a longitudinal two-wave sample adults 18–80 from 828). Based robust regression analyses, found were associated with higher positivity lower negativity across Europe. According results, hybrid multilevel models, autonomy relatedness increased decreased over time. The results provide evidence role Self-determination an factor acceptance considering rapid development adoption solutions.

Language: Английский

Citations

49
Exploring the artificial intelligence anxiety and machine learning attitudes of teacher candidates DOI
Sinan Hopcan, Gamze Türkmen, Elif Polat

et al.

Education and Information Technologies, Journal Year: 2023, Volume and Issue: 29(6), P. 7281 - 7301

Published: Aug. 12, 2023

Language: Английский

Citations

49
Perceptions and Acceptance of Artificial Intelligence: A Multi-Dimensional Study DOI Creative Commons
Michael Gerlich

Social Sciences, Journal Year: 2023, Volume and Issue: 12(9), P. 502 - 502

Published: Sept. 7, 2023

In this comprehensive study, insights from 1389 scholars across the US, UK, Germany, and Switzerland shed light on multifaceted perceptions of artificial intelligence (AI). AI’s burgeoning integration into everyday life promises enhanced efficiency innovation. The Trustworthy AI principles by European Commission, emphasising data safeguarding, security, judicious governance, serve as linchpin for widespread acceptance. A correlation emerged between societal interpretations impact elements like trustworthiness, associated risks, usage/acceptance. Those discerning threats often view its prospective outcomes pessimistically, while proponents recognise transformative potential. These inclinations resonate with trust perceived singularity. Consequently, factors such trust, application breadth, vulnerabilities shape public consensus, depicting humanity’s boon or bane. study also accentuates public’s divergent views evolution, underlining malleability opinions amidst polarising narratives.

Language: Английский

Citations

42
Comprehension, apprehension, and acceptance: Understanding the influence of literacy and anxiety on acceptance of artificial Intelligence DOI
Gianluca Schiavo, Stefano Businaro, Massimo Zancanaro

et al.

Technology in Society, Journal Year: 2024, Volume and Issue: 77, P. 102537 - 102537

Published: March 29, 2024

Language: Английский

Citations

42
Does AI-Driven Technostress Promote or Hinder Employees’ Artificial Intelligence Adoption Intention? A Moderated Mediation Model of Affective Reactions and Technical Self-Efficacy DOI Creative Commons
Po‐Chien Chang, Wenhui Zhang, Qihai Cai

et al.

Psychology Research and Behavior Management, Journal Year: 2024, Volume and Issue: Volume 17, P. 413 - 427

Published: Feb. 1, 2024

Purpose: The increasing integration of Artificial Intelligence (AI) within enterprises is generates significant technostress among employees, potentially influencing their intention to adopt AI. However, existing research on the psychological effects this phenomenon remains inconclusive. Drawing Affective Events Theory (AET) and Challenge–Hindrance Stressor Framework (CHSF), current study aims explore “black box” between challenge hindrance technology stressors employees’ AI, as well boundary conditions mediation relationship. Methods: employs a quantitative approach utilizes three-wave data. Data were collected through snowball sampling technique structured questionnaire survey. sample comprises employees from 11 distinct organizations located in Guangdong Province, China. We received 301 valid questionnaires, representing an overall response rate 75%. theoretical model was tested confirmatory factor analysis regression analyses using Mplus Process macro for SPSS. Results: results indicate that positive affect mediates relationship AI adoption intention, whereas anxiety negative intention. Furthermore, reveal technical self-efficacy moderates affective reactions indirect anxiety, respectively. Conclusion: Overall, our suggests AI-driven positively impact cultivation affect, while impede by triggering anxiety. Additionally, emerges crucial moderator shaping these relationships. This has potential make meaningful contribution literature deepening holistic understanding influential mechanisms involved. affirms applicability relevance Challenge-Hindrance (CHSF). In practical terms, provides actionable insights effectively manage Keywords: stressors,

Language: Английский

Citations

29
Investigating the Social Sustainability of Immersive Virtual Technologies in Higher Educational Institutions: Students’ Perceptions toward Metaverse Technology DOI Open Access
Abeer F. Alkhwaldi

Sustainability, Journal Year: 2024, Volume and Issue: 16(2), P. 934 - 934

Published: Jan. 22, 2024

The Metaverse technology (MVTECH) is an immersive virtual sphere where people interact with each other via avatars. MVTECH promised to provide a number of potentials for various sectors including higher education. Despite the fact that promotes social interaction between (e.g., university students), there lack knowledge on what affects users’ perceptions regarding its sustainability in HEIs, specifically developing nations. Therefore, this research paper aims determine variables affect learners’ toward (SS) educational institutions (HEIs) Jordan. A study model was formulated by integrating core factors “unified theory acceptance and use technology” (UTAUT) (“performance expectancy, PE; effort EE; influence, SI; facilitating conditions, FC”) “perceived curiosity” (PC) “extraversion” (EXT) factors. Both PC EXT were included as context-related may possibly contribute enhancing applicability UTAUT wide range information technologies settings. Data collected from 422 students enrolled Jordanian universities based online survey. analysis “structural equation modeling” (SEM) found students’ significantly influenced PE, FC, EXT. Furthermore, construct affected EE construct. However, SI revealed have no significant impact SS. Drawing these results, makes theoretical advances clarifies practical implications those involved development, design, decision-making processes support HEIs.

Language: Английский

Citations

27
Artificial intelligence innovation of tourism businesses: From satisfied tourists to continued service usage intention DOI
Edward C.S. Ku, Chun-Der Chen

International Journal of Information Management, Journal Year: 2024, Volume and Issue: 76, P. 102757 - 102757

Published: Jan. 25, 2024

Language: Английский

Citations

26
ChatGPT vs. neurologists: a cross-sectional study investigating preference, satisfaction ratings and perceived empathy in responses among people living with multiple sclerosis DOI Creative Commons
Elisabetta Maida, Marcello Moccia, Raffaele Palladino

et al.

Journal of Neurology, Journal Year: 2024, Volume and Issue: 271(7), P. 4057 - 4066

Published: April 3, 2024

Abstract Background ChatGPT is an open-source natural language processing software that replies to users’ queries. We conducted a cross-sectional study assess people living with Multiple Sclerosis’ (PwMS) preferences, satisfaction, and empathy toward two alternate responses four frequently-asked questions, one authored by group of neurologists, the other ChatGPT. Methods An online form was sent through digital communication platforms. PwMS were blind author each response asked express their preference for questions. The overall satisfaction assessed using Likert scale (1–5); Consultation Relational Empathy employed perceived empathy. Results included 1133 (age, 45.26 ± 11.50 years; females, 68.49%). ChatGPT’s showed significantly higher scores (Coeff = 1.38; 95% CI 0.65, 2.11; p > z < 0.01), when compared neurologists’ responses. No association found between ChatGPT’ mean 0.03; − 0.01, 0.07; 0.157). College graduate, high school education responder, had lower likelihood prefer (IRR 0.87; 0.79, 0.95; 0.01). Conclusions ChatGPT-authored provided than neurologists. Although AI holds potential, physicians should prepare interact increasingly digitized patients guide them on responsible use. Future development consider tailoring AIs’ individual characteristics. Within progressive digitalization population, could emerge as helpful support in healthcare management rather alternative.

Language: Английский

Citations

23
Could AI Ethical Anxiety, Perceived Ethical Risks and Ethical Awareness About AI Influence University Students’ Use of Generative AI Products? An Ethical Perspective DOI
Wenjuan Zhu, Lei Huang,

Xinni Zhou

et al.

International Journal of Human-Computer Interaction, Journal Year: 2024, Volume and Issue: unknown, P. 1 - 23

Published: March 8, 2024

The study aims to explore the factors that influence university students' behavioral intention (BI) and use behavior (UB) of generative AI products from an ethical perspective. Referring decision-making theory, research model extends UTAUT2 with three influencing factors: awareness (EA), perceived risks (PER), anxiety (AIEA). A sample 226 students was analysed using Partial Least Squares Structural Equation Modelling technique (PLS-SEM). results further validate effectiveness UTAUT2. Furthermore, performance expectancy, hedonistic motivation, price value, social all positively BI products, except for effort expectancy. Facilitating conditions habit show no significant impact on BI, but they can determine UB. extended perspective play roles as well. AIEA PER are not key determinants BI. However, directly inhibit From mediation analysis, although do have a direct UB, it inhibits UB indirectly through AIEA. Ethical Nevertheless, also increase PER. These findings help better accept ethically products.

Language: Английский

Citations

21