Relevant bibliographies by topics / AI adoption intention model

Contents

  1. Journal articles
  2. Dissertations / Theses
  3. Book chapters
  4. Conference papers
  5. Reports

Academic literature on the topic 'AI adoption intention model'

Author: Grafiati
Published: 5 June 2025
Last updated: 25 June 2025

Create a spot-on reference in APA, MLA, Chicago, Harvard, and other styles

Select a source type:

Consult the lists of relevant articles, books, theses, conference reports, and other scholarly sources on the topic 'AI adoption intention model.'

Next to every source in the list of references, there is an 'Add to bibliography' button. Press on it, and we will generate automatically the bibliographic reference to the chosen work in the citation style you need: APA, MLA, Harvard, Chicago, Vancouver, etc.

You can also download the full text of the academic publication as pdf and read online its abstract whenever available in the metadata.

Journal articles on the topic "AI adoption intention model"

1

Chuang, Li-Min, and Sheng-Hsuan Huang. "AI-Supported Healthcare Technology Resistance and Behavioral Intention: A Serial Mediation Empirical Study on the JD-R Model and Employee Engagement." Systems 13, no. 4 (2025): 268. https://doi.org/10.3390/systems13040268.

Full text
Abstract:
This study combines innovation resistance theory, the stimulus–organism–response (SOR) framework, and the job demands–resources model to facilitate an in-depth exploration of the barriers faced by healthcare professionals and the psychological responses they exhibit when adopting AI-supported healthcare technologies. We conducted a questionnaire survey and obtained 296 valid responses from healthcare professionals to examine the relationship between resistance to AI-supported healthcare technologies and AI adoption behavioral intentions. Using the SOR framework as a basis, this study validated a serial mediation model with moderating effects, demonstrating that resistance to AI-supported healthcare technologies influenced AI adoption behavioral intentions through job resource, job demand, and levels of employee engagement. Further, this study sought to validate the relationship between age-moderated job resource and job demand in employees exhibiting resistance to AI-supported healthcare technologies and their associated AI adoption behavioral intentions. The results indicated that job resources, job demands, and employee engagement serially mediated the relationship between resistance to AI-supported healthcare technologies and AI adoption behavioral intentions. Additionally, age only exhibited significant moderating effects on the relationship between job demands in resistance to AI-supported healthcare technologies and AI adoption behavioral intentions. The findings of this study can aid in promoting the adoption of AI-supported healthcare technologies by healthcare professionals, generating new insights and broadening the scope and vision of existing literature.
APA, Harvard, Vancouver, ISO, and other styles
2

Kim, Youngsoo, Victor Blazquez, and Taeyeon Oh. "Determinants of Generative AI System Adoption and Usage Behavior in Korean Companies: Applying the UTAUT Model." Behavioral Sciences 14, no. 11 (2024): 1035. http://dx.doi.org/10.3390/bs14111035.

Full text
Abstract:
This study addresses the academic gap in the adoption of generative AI systems by investigating the factors influencing technology acceptance and usage behavior in Korean firms. Although recent advancements in AI are accelerating digital transformation and innovation, empirical research on the adoption of these systems remains scarce. To fill this gap, this study applies the Unified Theory of Acceptance and Use of Technology (UTAUT) model, surveying 300 employees from both large and small enterprises in South Korea. The findings reveal that effort expectancy and social influence significantly influence employees’ behavioral intention to use generative AI systems. Specifically, effort expectancy plays a critical role in the early stages of adoption, while social influence, including support from supervisors and peers, strongly drives the adoption process. In contrast, performance expectancy and facilitating conditions show no significant impact. The study also highlights the differential effects of age and work experience on behavioral intention and usage behavior. For older employees, social support is a key factor in technology acceptance, whereas employees with more experience exhibit a more positive attitude toward adopting new technologies. Conversely, facilitating conditions are more critical for younger employees. This study contributes to the understanding of the interaction between various factors in AI technology adoption and offers strategic insights for the successful implementation of AI systems in Korean companies.
APA, Harvard, Vancouver, ISO, and other styles
3

Fang, Wang, Meng Na, and Syed Shah Alam. "Usage Intention of AI Among Academic Librarians in China: Extension of UTAUT Model." Sustainability 17, no. 7 (2025): 2833. https://doi.org/10.3390/su17072833.

Full text
Abstract:
This study explores how academic librarians adopt artificial intelligence (AI) technologies, using the Unified Theory of Acceptance and Use of Technology (UTAUT) as its main framework, expanded with elements from Personal Innovativeness in IT (PIIT) and the Technology Readiness Index (TRI). A quantitative approach was applied, gathering data from 340 academic librarians and analyzing them using PLS-SEM. The results indicate that facilitating conditions (β = 0.345, p < 0.001) and effort expectancy (β = 0.123, p = 0.034) significantly influence behavioral intention, while performance expectancy (β = 0.091, p = 0.085) and top management support (β = 0.000, p = 0.997) show limited direct effects. These findings challenge some traditional assumptions of the UTAUT model. Additionally, attitudes were found to mediate the relationship between effort expectancy and social influence on behavioral intentions, while individual readiness and personal innovativeness moderate these relationships (β = −0.069, p = 0.003), highlighting the importance of individual traits. The model demonstrated strong predictive power, with R2 values of 0.677 for behavioral intention and 0.574 for actual behavior, along with Q2 predict values exceeding 0.56. By incorporating PIIT and TRI, this study broadens existing models of technology adoption, offering deeper insights into how organizational factors, personal traits, and readiness interact to influence AI adoption. Practical recommendations include introducing adaptive training programs, personalized support systems, and AI-driven infrastructure enhancements to encourage effective AI integration. Future research should consider longitudinal studies to examine how readiness and innovativeness evolve over time, explore cross-cultural differences, and refine strategies to ensure sustainable AI adoption in diverse academic settings.
APA, Harvard, Vancouver, ISO, and other styles
4

Patel, Anil. "A Study on Factors Affecting Adoption of AI Tools on Consumers While Shopping Online." International Scientific Journal of Engineering and Management 04, no. 06 (2025): 1–9. https://doi.org/10.55041/isjem04340.

Full text
Abstract:
Abstract: This research investigates the factors influencing the adoption of AI tools, particularly chatbots, by consumers during online shopping. By integrating the Technology Acceptance Model (TAM) and Behavioral Reasoning Theory (BRT), the study explores how perceptions like ease of use, usefulness, trust, discomfort, and optimism affect consumer attitudes and intentions. Data collected from 182 respondents was analyzed using SmartPLS. The results show that attitude, perceived usefulness, and perceived ease of use significantly influence consumer intention to adopt AI chatbots. Innovation, optimism, and complexity also affect perceptions and attitudes. This research contributes theoretical insights and practical strategies for enhancing AI adoption in digital retail. Keywords: AI Chatbots, Consumer Behavior, E-Commerce, TAM, BRT, Perceived Usefulness, Perceived Ease of Use, Digital Adoption
APA, Harvard, Vancouver, ISO, and other styles
5

Nguyen, Thi Hai Duong, Xuan Tiep Nguyen, Tran Ha Trang Le, and Quynh Anh Bui. "Determinants influencing the adoption of artificial intelligence technology in non-life insurers." Corporate Governance and Organizational Behavior Review 8, no. 1 (2024): 205–12. http://dx.doi.org/10.22495/cgobrv8i1p17.

Full text
Abstract:
Although artificial intelligence (AI) technology has been widely used in the insurance industry at a global scale, studies examining the adoption of AI technology in emerging markets are few and far between. This paper fills this gap by using Cronbach’s alpha, exploratory factor analysis, confirmatory factor analysis, and structural equation model (SEM) to discover significant factors affecting their behavioral intentions to adopt AI technology in Vietnam, a developing country. Data is collected from nearly 470 employees in Vietnamese non-life insurance firms. Empirical findings show that the most important determinant influencing the adoption of AI technology in Vietnamese non-life insurers is attitudes toward adoption. Attitudes toward adoption are positively related to the perceived ease of use and perceived usefulness, consistent with Gupta et al. (2022). Although perceived risk has a negative influence on the behavioral intention to adopt AI technology, it is not a serious issue for insurance companies.
APA, Harvard, Vancouver, ISO, and other styles
6

Chatterjee, Sheshadri, Bang Nguyen, Soumya Kanti Ghosh, Kalyan Kumar Bhattacharjee, and Sumana Chaudhuri. "Adoption of artificial intelligence integrated CRM system: an empirical study of Indian organizations." Bottom Line 33, no. 4 (2020): 359–75. http://dx.doi.org/10.1108/bl-08-2020-0057.

Full text
Abstract:
Purpose The purpose of this study is to explore the behavioral intention of the employees to adopt artificial intelligence (AI) integrated customer relationship management (CRM) system in Indian organizations. Design/methodology/approach To identify the factors impacting the behavioral intention of the employees to adopt AI integrated CRM system in Indian organizations helps of literature review and theories have been taken. Thereafter, some hypotheses have been formulated followed by the development of a theoretical model conceptually. The model has been tested statistically for validation using a survey by considering 308 usable respondents. Findings The results of this study show that perceived usefulness and perceived ease of use directly impact the behavioral intention of the employees to adopt an AI integrated CRM system in organizations. Also, these two exogenous factors impact the behavioral intention of the employees to adopt an AI integrated CRM system mediating through two intermediate variables such as utilitarian attitude (UTA) and hedonic attitude (HEA). The proposed model has achieved predictive power of 67%. Research limitations/implications By the help of the technology acceptance model and motivational theory, the predictors of behavioral intention to adopt AI integrated CRM systems in organizations were identified. The effectiveness of the model was strengthened by the consideration of two employee-centric attitudinal attributes such as UTA and HEA, which is claimed to have provided contributions to the extant literature. The proposed theoretical model claims a special theoretical contribution as no extant literature considered the effects of leadership support as a moderator for the adoption of an AI integrated CRM system in Indian organizations. Practical implications The model implies that the employees using AI integrated CRM system in organizations must be made aware of the usefulness of the system and the employees must not face any complexity to use the system. For this, the managers of the concerned organizations must create a conducive atmosphere congenial for the employees to use the AI integrated CRM system in the organizations. Originality/value Studies covering exploration of the adoption of AI integrated CRM systems in Indian organizations are found to be in a rudimentary stage and in that respect, this study claims to have possessed its uniqueness.
APA, Harvard, Vancouver, ISO, and other styles
7

Gyesi, Kwesi, Vivian Amponsah, and Samuel Ankamah. "Forecasting Ghanaian Medical Library Users’ Artificial Intelligence (AI) Technology’s Acceptance and Use." Biblios Journal of Librarianship and Information Science, no. 88 (April 11, 2025): e004. https://doi.org/10.5195/biblios.2025.1211.

Full text
Abstract:
Objective. This study investigated the behavioural intentions of medical students in an academic library regarding the use of AI-assisted technologies for research and learning. Method. Employing a survey research design and a quantitative approach, the study sampled 302 respondents using Krejcie and Morgan’s published table. Statistical analyses were conducted using the Statistical Package for Social Sciences (SPSS) version 26, with linear and multiple linear regressions utilised to establish relationships between variables. Results. The results of the study indicate that perceived usefulness, perceived ease of use, and self-efficacy within the extended Technology Acceptance Model (TAM) significantly influence the behavioural intention to utilise AI in an academic library in Ghana. Additionally, the results suggest that perceived usefulness plays a more significant role in influencing behavioural intention compared to perceived ease of use. Furthermore, the study reveals a direct relationship between behavioural intention and use behaviour within TAM. Conclusion. This study underscores the critical factors within the extended Technology Acceptance Model that drive the adoption of AI in academic libraries in Ghana. The results highlight the paramount importance of perceived usefulness in shaping behavioural intention, surpassing the impact of perceived ease of use. Moreover, the direct link between behavioural intention and actual use behaviour reaffirms the model’s applicability in predicting technology adoption. These insights provide a valuable foundation for developing strategies to enhance AI integration in academic libraries, ultimately improving their operational efficiency and service delivery.
APA, Harvard, Vancouver, ISO, and other styles
8

Apostoaie, Constantin-Marius, Teodora Roman, Alexandru Maxim, and Dumitru-Tudor Jijie. "Determinants of AI adoption intention in SMEs. Romanian case study." Journal of Business Economics and Management 26, no. 1 (2025): 277–96. https://doi.org/10.3846/jbem.2025.23650.

Full text
Abstract:
The paper investigates the drivers and barriers that encourage or hinder the adoption of artificial intelligence (AI) technologies within Romanian SMEs. By using the Technology-Organisation-Environment (TOE) framework, we examined the role of several factors from each TOE dimension in predicting the AI adoption behaviour. The factors were constructed through factor analysis followed by the estimation of a linear regression model. Partial least squares structural equation modelling was then used in order to further explore the relationships and to check the robustness of the linear regression model. Our findings highlight the significant role played by leadership, organizational readiness, as well as the “push-and-pull” effect of competitors and customers in encouraging SMEs to adopt AI technologies. However, in the case of Romania, specific challenges related to a lack of digital skills among employees, a limited understanding of the relative advantage that digitalisation can offer, as well as a lack of marketing efforts from the side of vendors make it difficult for SMEs to consider the implementation of AI technologies. This exploratory study seeks to understand the underlying trends of the phenomenon and serves as a stepping stone for vendors, managers, as well as researchers to better understand the market for AI tools and solutions among Romanian SMEs.
APA, Harvard, Vancouver, ISO, and other styles
9

Lakulu, Muhammad Modi, Ayad Shihan Izkair, Mohd Fadhil Abdul Muttalib, and Nur Azlan Zainuddin. "Understanding AI and Mobile Learning Adoption in Malaysian Universities: A UTAUT-Based Model." International Journal of Interactive Mobile Technologies (iJIM) 19, no. 11 (2025): 80–111. https://doi.org/10.3991/ijim.v19i11.52977.

Full text
Abstract:
This study explores the key determinants influencing the intention to adopt artificial intelligence (AI) applications and mobile learning in Higher Education Institutions (HEIs) in Malaysia. As AI technologies and mobile learning increasingly transform the higher education landscape, it is crucial to understand the specific factors driving their adoption. The research identifies five critical determinants—social influence (SI), effort expectancy (EE), hedonic motivations (HM), performance expectancy (PE), and consumer trust (TR)—that significantly impact the intention to use AI-powered mobile learning solutions. Through a survey of 263 undergraduate and postgraduate students from Malaysian universities, the study develops an adapted model to assess these adoption factors, contributing unique insights into the integration of AI and mobile learning within the Malaysian higher education context. This model provides actionable recommendations for university administrators, educators, and mobile learning developers, offering practical guidance on promoting the adoption of these technologies to enhance student engagement and learning outcomes. By focusing on real-world application, this study not only bridges theoretical research with practical implementation but also offers valuable lessons for similar educational contexts globally, particularly in emerging markets.
APA, Harvard, Vancouver, ISO, and other styles
10

Jang, Eun-Gyo, and Jin-Myong Lee. "Continuous Use Intention of Fashion AI Recommendation Service Applying Value-based Adoption Model." Journal of Consumer Studies 35, no. 1 (2024): 149–71. http://dx.doi.org/10.35736/jcs.35.1.7.

Full text
APA, Harvard, Vancouver, ISO, and other styles
More sources

Dissertations / Theses on the topic "AI adoption intention model"

1

Pajany, Peroumal. "AI Transformative Influence: Extending the TRAM to Management Student's AI’s Machine Learning Adoption." Franklin University / OhioLINK, 2021. http://rave.ohiolink.edu/etdc/view?acc_num=frank1623093426530669.

Full text
APA, Harvard, Vancouver, ISO, and other styles
2

Vikström, Fredrik. "How does Organizational Culture Impact Intention to use Customer Relationship Management Amongst Employees?" Thesis, Luleå tekniska universitet, Institutionen för ekonomi, teknik och samhälle, 2016. http://urn.kb.se/resolve?urn=urn:nbn:se:ltu:diva-60033.

Full text
Abstract:
Purpose: The aim of this thesis is to elaborate on if organisational culture has an impact on the intention to use a CRM system. Methodology: The data was collected by use of an online questionnaire, the questions used were created based on the literature review andmeasured according to a 5 point Likert-scale Conclusion: Organisational culture has no meaningful impact on intention touse CRM. This since each of the culture types produced results which were outside acceptable perimeters. Out of the three aspects of the technology acceptance model,attitude has the biggest impact on intention to use CRM. PEOU and PU were not within acceptable perimeters. Neither PU nor PEOU had a statistical significant impact on attitude, leaving attitude as a sole positive contributor to intentionto use CRM. K
APA, Harvard, Vancouver, ISO, and other styles
3

Forslund, Lia, and Mentzer Sofia von. "Sjukvårdskris och svalt mottagande av AI, hur går det ihop? : En fallstudie i vilka faktorer som har störst påverkan på införandet av artificiell intelligens." Thesis, Uppsala universitet, Institutionen för informatik och media, 2020. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-414559.

Full text
Abstract:
Det svenska sjukvårdssystemet är konstant under hög press och situationen benämns ofta i media som en sjukvårdskris. Radiologin är en av de medicinska discipliner som drabbats av en kontinuerligt ökande arbetsbelastning och personalbrist. Detta sätter sjukvården i en situation att konstant tvingas väga effektivitet mot kvalitet. Trots höga förväntningar på att innovationer som Artificiell Intelligens (AI) ska kunna bistå behoven, används AI idag i en mycket begränsad utsträckning. Denna studie syftar till att utreda påverkande faktorer för införandet av AI inom radiologin. För att besvara arbetets forskningsfråga har HA Adoption-Decision Model, en modifierad version av det väletablerade Technology-Organization-Environment Framework (TOE), tillämpats. Ramverket innefattar tre kontexter; teknologisk, organisatorisk och extern kontext. Varje kontexts delaspekter, så kallade faktorer, följer under respektive kontext. Dessa tio faktorer utvärderades för att besvara studiens forskningsfråga om vilka faktorer som har störst påverkan på införande av AI inom radiologi. Genom att förena tidigare forskning med resultatet från sex intervjuer visade sig affärsvärde , strategisk lämplighet , ledningsstöd och reglering av datahantering ha störst påverkan. Avslutningsvis presenteras ett förslag om att introducera en elfte faktor, IT-mognad, till ramverket.
APA, Harvard, Vancouver, ISO, and other styles
4

Albadran, Norah Fahad Mrs. "Flipped Classroom Model Based Technology Acceptance and Adoption Among Faculty Members in Saudi Arabia Universities." University of Toledo / OhioLINK, 2020. http://rave.ohiolink.edu/etdc/view?acc_num=toledo1587078759013376.

Full text
APA, Harvard, Vancouver, ISO, and other styles
5

Wang, Xuyang. "Factors Influence Citizen Adoption for Government E-Tax Service." Thesis, Örebro universitet, Handelshögskolan vid Örebro Universitet, 2012. http://urn.kb.se/resolve?urn=urn:nbn:se:oru:diva-22959.

Full text
Abstract:
E-tax is an important function of e-government since it is highly related to the life of citizens (Wu & Chen, 2005). So in this paper I have discussed the factors influence the citizen adoption of government e-tax service. I have used the decomposed TPB model as my research model. This model integrated two important theories – TAM model and TPB model. The taxpayers were divided into adopters who have used the e-tax service and non-adopter who has used the conventional method to pay their tax. And the effect of these factors for adopters and non-adopters are different. Therefore, understand the factors’ effect can help governments formulate the corresponding measures to promote more citizens to use the e-tax service and lead to better planning and implementation of e-tax service.
APA, Harvard, Vancouver, ISO, and other styles
6

Radif, Mustafa. "A learning management system adoption framework for higher education : the case of Iraq." Thesis, Cranfield University, 2016. http://dspace.lib.cranfield.ac.uk/handle/1826/11191.

Full text
Abstract:
This study focuses on the implementation of Learning Management System (LMS) in the higher education sector in Iraq. Its aim is to develop a policy adoption framework for LMS implementation by scientifically investigating LMS adoption using a model that combines the principles of the Technology Acceptance Model (TAM) and Technology-Organisation-Environment (TOE) framework. The research methodology comprises of seven stages that adopts the interpretive paradigm and a mixed-methods research design. A case study design is used to investigate LMS integration in the University of Al-Qadisiyah. A TAM-TOE questionnaire is developed for the academic staff of the University of Al-Qadisiyah, in which the perceived usefulness and perceived ease of use of LMS are analysed in the case organisation. The technological, organisational, and environmental aspects of LMS implementation are also examined. The survey received valid responses from 283 academic staff. In-depth semi-structured interviews of 8 academics, administrative staff and IT personnel contributed to the qualitative data. The survey respondents are selected using stratified sampling whilst purposive sampling is used to select the interview participants. The questionnaire data was analysed using correlation analysis, whilst thematic analysis is used for the interview data. The study identifies the barriers to LMS implementation as: Lack of or limited teachers’ training, lack of commitment to constructivist pedagogy, lack of experience to use the new technology, lack of technical support, and lack of appropriate educational software. These results feed into the policy framework design. The contribution to research knowledge includes the creation of a new adoption model derived from TAM and TOE to examine the LMS implementation barriers in a war recovering economy like Iraq. This approach the integration of academic users’ acceptance with macro-level factors like government support. The results lease to the development of the LMS policy framework to guide policy makers to prioritise their limited LMS investments. The novelty of the work is the bringing together the considerations of the individual users and the socio-economic context.
APA, Harvard, Vancouver, ISO, and other styles
7

Kowalczyk, Nina K. "The Impact Of Voluntariness, Gender, And Age On Subjective Norm And Intention To Use Digital Imaging Technology In A Healthcare Environment:Testing A Theoretical Model." The Ohio State University, 2008. http://rave.ohiolink.edu/etdc/view?acc_num=osu1226605857.

Full text
APA, Harvard, Vancouver, ISO, and other styles
8

Zhang, Yusha, and Klavdija Zalar. "The Application of the Extended Technology Acceptance Model in Different Cultural Contexts to Understand Mobile Payment Adoption : A comparative study between China and Sweden." Thesis, Linnéuniversitetet, Institutionen för informatik (IK), 2020. http://urn.kb.se/resolve?urn=urn:nbn:se:lnu:diva-96961.

Full text
Abstract:
Rapid technological progress has transformed our daily activities. One of these is how we pay for goods. Mobile payment is a payment option with great potential, but it is still struggling to become part of individuals' daily life. Previous research shows that adoption and acceptance of mobile payment vary widely between different countries. It is important to understand the determinants of mobile payment adoption, as cultural differences between countries may be one of the primary reasons for the different degrees of user mobile payment adoption. The purpose of this study is to investigate the factors, which influence user adoption of mobile payment in one Asian country, China, and one European country, Sweden. In addition, the aim of the study is to explore the difference in mobile payment adoption from the cultural point of view at an individual level. In this study, two research questions are proposed: what influences user intention to adopt mobile payment in the context of China and Sweden, and how does an individual culture influence user adoption of mobile payment in the context of China and Sweden. The research was conducted with a combination of an extended UTAUT (Unified Theory of Acceptance and Use of Technology) model with the added concept of Perceived Information security and Hofstede's cultural theory. Altogether, it was studied how these concepts influence Behavioural intention.  Based on the literature review of mobile payment adoption by users and Hofstede's culture theory, this study uses qualitative research to interpret the phenomenon on a deeper level with the intention of explaining it. Through observation, interviews, and questionnaires, several conclusions were drawn. The analysis of the results showed that the proposed research model applies to China and Sweden. Performance Expectancy, Effort Expectancy, and Social Influence have influenced the user mobile payment adoption in both studied countries, and Perceived Information Security has a strong influence on users in Sweden. The results also show that Power Distance, Collectivism, and Masculinity have a strong moderating effect on the behavioural intention of users in China, while Collectivism and Femininity have a strong moderating effect on the behavioural intention of users in Sweden. On this basis, it is suggested that cultural factors be incorporated into the research model of technology acceptance, and further research should be conducted in different countries to provide different perspectives.
APA, Harvard, Vancouver, ISO, and other styles
9

Shabani, Maryam. "A Model of Crucial Factors Influencing on the Innovation Resistance for Purchasing Innovative Passenger Vehicles in Automotive Industry of Iran." Doctoral thesis, Universitat Internacional de Catalunya, 2020. http://hdl.handle.net/10803/670677.

Full text
Abstract:
Purpose: The goal of this thesis is to render a model of influencing factors on Innovation resistance for purchasing innovative passenger vehicles in Auto industry of Iran. Design/Methodology/Approach: The innovative passenger vehicles that are produced by 4 car manufacturing companies of Iran are selected. Data is collected in two phases, at the first step which is qualitative phase, 13 questionnaires are distributed among panel of experts who are managers and top experts of SAIPA car manufacturing company (Appendix 1). Then in the second phase which is quantitative, the questionnaire which is prepared based on the results of first phase, are distributed among 265 customers of Kerman Khodro Co., Modiran Khodro Co. and Iran Khodro Co. that have resisted to purchase innovative vehicle of SAIPA (Appendix 2). The resistance factors are detected and grouped through Exploratory Factor Analysis techniques, and the Structural Equation Modeling (SEM), which is a very general statistical modeling technique that is normally used in the behavioral sciences. It can be viewed as a combination of factor analysis and regression or path analysis, so by SEM method will provide the aforementioned impacts of these resistance factors on resistance purchasing behavior. Findings: The results of qualitative phase show that Trialability, Co-dependence, Visibility, Realization, Relative advantage and Value factors are the most influential factors on innovation resistance which are clustered in Functional barriers. On the other hand, Economic Risk, Functional Risk, Usage, Image, Previous Innovation Experience and Usefulness are the most influential factors on Innovation Resistance, which are categorized in Psychological barriers. Additionally, the Demographic barriers extracted as influential factors on innovation resistance analyzed are: Age, Income and Education. The new factor of "After Sales Services" is recommended by panel of experts from Delphi model, in order to add to influential factors on Innovation Resistance. Thereafter, the above-mentioned factors have a crucial and prominent role in reducing the resistance of consumers in order to purchase innovative passenger vehicles. In the second phase which is quantitative step of this research, based on the results of first step the questionnaire has been prepared and are distributed among 265 ordinary customers of three Iranian car manufacturing companies. The abovementioned factors resulting of the first step of this research are used in order to assess its impact on Intention to buy, and the mediation role of Active Innovation Resistance between Barriers and Intention to buy. A research model, in which these constructs are included, is proposed and analyzed through Structural Equation Modeling (SEM). Results show that “Active innovation resistance” is playing the role of a complementary mediation. Therefore, the impact of “Functional barriers” on “Intention to buy” is mediated by “Active innovation resistance”. In the same way, “Active innovation resistance” also mediates between “Psychological barriers” and “Intention to buy”. Research Implications: A new fresh model analyzing the mediator role of Active Innovation Resistance shed light to conceptualize the way Barriers (both Functional and Psychological) impacts on customer behavior, in the specific setting of innovative automotive industry in Iran. Practical Implications: The propagation of innovation in automotive industry is challenging and imposing huge investment to manufacturer, so they should pay attention to real barriers for resisting to purchase their innovative vehicles. Moreover, customers, who are playing the main role for their success, might adjust its intention to purchase these innovative cars, and foster the Iranian society to be interested in innovation of car manufactures.
APA, Harvard, Vancouver, ISO, and other styles
10

CHEN, MENG-YANG, and 陳孟揚. "Adoption Intention in Smart Space：An Elaboration Likelihood Model." Thesis, 2017. http://ndltd.ncl.edu.tw/handle/n2ttdz.

Full text
Abstract:
碩士<br>逢甲大學<br>企業管理學系<br>105<br>Due to progression of modern medication and technology, the average life span is extending, pursuing high-quality, healthy and long life growing to an old age is more desirable than ever. Then the aged society related issues have presented serious challenges to public policy as the elderly population in Taiwan increases rapidly. Many developed countries have used "Aging in Place" as the guiding principle for devising elderly care policy. In addition, accompany with the progress of ICT(Information Communication and Technology ,ICT), the ICT integrated for aging in place has been discussing broadly ,and smart space had also become the application of ICT equipment to support the elderly. However, previous research has focused on technology oriented and product development rather than user decision process. Therefore, the purpose of this study is to explore the factors that affect the decision-making in the process of adopting smart space in the face of personal, environment and technology. This study based on Elaboration-Likelihood Model(ELM) to compared two alternative influence processes, the central(Technology Readiness) and peripheral(Social Influence) routes, in motivating Smart Space acceptance. Further, this study examined how these influence process were moderated by users’ ICT user experience.This study collected 310 questionnaire from May 31,2017 to July 30,2017 by paper and internet, and analyze by Smart PLS 2.0 and SPSS. With the result of this study, central route supported that the positive attitude will promote the smart space adoption, but the peripheral route had no effect on smart space adoption. The moderation of ICT user experience had effect toward central and peripheral route. This research makes a comprehensive view which is based on the personal, technology and, environment. It provides a structure as the basis for the study that explores smart space adoption from user experience and decision process. Intellectual structure, a systematic way to search literature that provides an objective and efficient way to explore the literature. In terms of practice, to improve adoption of smart space can be emphasized in the user experience and technology readiness, and in the social influence must first consider the user's understanding of product attributes. The research topic is innovative and still at the stage of development. In this study, it is limited by regional, cultural and time, but it can provide a complete and effective contribution to the academic and practical aspects. In the future, we can refer to this study’s theoretical framework, methods for more profound discussion.
APA, Harvard, Vancouver, ISO, and other styles
More sources

Book chapters on the topic "AI adoption intention model"

1

Zhu, Yiwei, and Shiwei Sun. "Exploring Patients’ AI Adoption Intention in the Context of Healthcare." In Communications in Computer and Information Science. Springer Singapore, 2021. http://dx.doi.org/10.1007/978-981-16-3631-8_4.

Full text
APA, Harvard, Vancouver, ISO, and other styles
2

Gong, Zixuan, and Yanxia Cheng. "Information Adoption Intention of Tagged Online Reviews Based on Information Adoption Model." In Lecture Notes in Electrical Engineering. Springer Singapore, 2022. http://dx.doi.org/10.1007/978-981-16-4258-6_142.

Full text
APA, Harvard, Vancouver, ISO, and other styles
3

Sadriwala, Maruf Fatima, and Manish Dadhich. "Marketing Innovation, Subjective Norms, Behavioral Control and Intention to Adoption of Artificial Intelligence." In The AI Revolution: Driving Business Innovation and Research. Springer Nature Switzerland, 2024. http://dx.doi.org/10.1007/978-3-031-54383-8_21.

Full text
APA, Harvard, Vancouver, ISO, and other styles
4

Kumar, Nishant, Mitushi Singh, Kamal Upreti, and Divya Mohan. "Blockchain Adoption Intention in Higher Education: Role of Trust, Perceived Security and Privacy in Technology Adoption Model." In Proceedings of International Conference on Emerging Technologies and Intelligent Systems. Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-82616-1_27.

Full text
APA, Harvard, Vancouver, ISO, and other styles
5

Denni-Fiberesima, Damiebi. "Navigating the Generative AI-Enabled Enterprise Architecture Landscape: Critical Success Factors for AI Adoption and Strategic Integration." In Navigating the Technological Tide: The Evolution and Challenges of Business Model Innovation. Springer Nature Switzerland, 2024. http://dx.doi.org/10.1007/978-3-031-67434-1_20.

Full text
APA, Harvard, Vancouver, ISO, and other styles
6

Kumar, Nishant, Mitushi Singh, Kamal Upreti, and Divya Mohan. "Correction to: Blockchain Adoption Intention in Higher Education: Role of Trust, Perceived Security and Privacy in Technology Adoption Model." In Proceedings of International Conference on Emerging Technologies and Intelligent Systems. Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-82616-1_58.

Full text
APA, Harvard, Vancouver, ISO, and other styles
7

Petschnig, Martin, and Patrick Spieth. "How to Push Consumers’ Intention to Adopt Alternative Fuel Vehicles – An Integrative Adoption Model." In Marketing Dynamism & Sustainability: Things Change, Things Stay the Same… Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-10912-1_103.

Full text
APA, Harvard, Vancouver, ISO, and other styles
8

Worek, Maija, and Päivi Aaltonen. "AI Adoption Challenges in Family-Owned Firms: A Case Study." In Technology, Work and Globalization. Springer Nature Switzerland, 2025. https://doi.org/10.1007/978-3-031-74779-3_9.

Full text
Abstract:
Abstract AI transformation is reshaping organizations and societies, pushing firms to embrace new technologies. In the presence of abundant technology, personnel, and personnel management becomes increasingly crucial in creating a competitive edge. Family firms, making up a significant portion of businesses worldwide, serve as an example of industrial firms with existing leveraged emphasis on softer values, yet face significant challenges in AI adoption. Various models used to understand digital transformation, such as the Technology-Organization-Environment model and the Technology Acceptance Model, may not adequately explain the complexities involved in AI adoption, particularly regarding familial factors like trust and collaboration. Family firms are often slow in adopting technology due to concentrated ownership, risk aversion, and a focus on non-financial goals. This study explores the specific challenges family-owned businesses experience in AI adoption and responses to these challenges. By examining five family-owned firms, the research aims to contribute to the understanding of technology adoption by identifying barriers and forming categories that can inform future studies on family firms and AI technology.
APA, Harvard, Vancouver, ISO, and other styles
9

Srivastava, Karnika, Manoj Kumar, Rinki Verma, Shreyanshu Singh, and Pratibha Maurya. "Analyzing the Drivers of Adoption in Higher Education E-Learning." In Advances in Web Technologies and Engineering. IGI Global, 2025. https://doi.org/10.4018/979-8-3693-2973-3.ch003.

Full text
Abstract:
Learners face problems while using traditional e-learning systems but AI introduces an innovative stage of advancement in technology that gives revolution in e-learning process. Study investigates factors that influence learner behavioral intention to use AI and actual usage in higher education. The study proposed UTAUT and IS model with additional external variables like perceive risk, work engagement and self-efficacy of learner. Cross-sectional study was used to measure research models based on several theories related to AI that brings cutting-edge technologies that enhance e-learning. Data was analysed using SEM technique. Research model and hypothesis testing was done by AMOS. Study investigate performance expectancy, effort expectancy, facilitating condition, system quality, service quality information quality, perceived risk, work engagement; self-efficacy had significantly influenced behavioral intention and actual use of AI. Finding gives practical references to stakeholders for adoption and acceptance of AI within e-learning process in higher education in NCR.
APA, Harvard, Vancouver, ISO, and other styles
10

Fares, Omar H., Queenie Zhu, Seung Hwan (Mark) Lee, and Joseph Aversa. "Consumers' Drivers of Generative Pre-Trained Transformer (GPT) Conversational Bot Adoption." In Revolutionizing the Service Industry Wth OpenAI Models. IGI Global, 2024. http://dx.doi.org/10.4018/979-8-3693-1239-1.ch005.

Full text
Abstract:
This chapter examines the relationship between society and artificial intelligence (AI), emphasizing the factors driving consumer adoption of AI conversational bots. The authors examine how societal norms, past experiences, and trust in technology influence the acceptance and usage of generative-pre trained transformer (GPT) bots. They provide a theoretical framework, integrating key concepts from social influence and technology acceptance theory, to understand the complex dynamics of GPT bot adoption. Conducting a survey, they analyze data from 412 participants in North America to test various hypotheses. The findings broadly support the proposed model, highlighting the significant roles of social norms, word of mouth, and trust in shaping consumer behaviour towards AI conversational bots. However, an intriguing exception is found in the lack of a direct relationship between behavioural intention and actual technology usage, pointing to the need for further investigation into the factors that bridge the gap between the intention to use and the actual use of AI technologies in everyday contexts.
APA, Harvard, Vancouver, ISO, and other styles

Conference papers on the topic "AI adoption intention model"

1

Handoko, Bambang Leo, Shaqira Aufaanashwa, Arta Moro Sundjaja, and Evelyn Hendriana. "Behavioral Intention Model for Cryptocurrency Investment Platform Adoption." In 2024 International Conference on ICT for Smart Society (ICISS). IEEE, 2024. http://dx.doi.org/10.1109/iciss62896.2024.10751599.

Full text
APA, Harvard, Vancouver, ISO, and other styles
2

Rani, Nisha, TILAK SETHI, and PARDEEP GUPTA. "Impact of Occupation of Banking Customers on Artificial Intelligence-driven Financial Assistant Adoption Factors and Behavioural Intention." In 2025 First Global Conference on AI Research and Emerging Developments. Ganitara Research Foundation, 2025. https://doi.org/10.63169/gcared2025.p26.

Full text
APA, Harvard, Vancouver, ISO, and other styles
3

Kiros, Atakilti Brhanu, Ayodeji Olalekan Salau, Satvik Vats, Keshav Kaushik, Ting Tin Tin, and Crescent Onyebuchi Omeje. "Cloud-based Machine Learning Adoption Model for Higher Education Institutions." In 2024 International Conference on Artificial Intelligence and Emerging Technology (Global AI Summit). IEEE, 2024. https://doi.org/10.1109/globalaisummit62156.2024.10947842.

Full text
APA, Harvard, Vancouver, ISO, and other styles
4

Patel, Anamika, Y. Maheshwaran, and P. Santhya. "Easing Adoption of Model Based System Engineering With Application of Generative AI." In 2024 IEEE Space, Aerospace and Defence Conference (SPACE). IEEE, 2024. http://dx.doi.org/10.1109/space63117.2024.10667868.

Full text
APA, Harvard, Vancouver, ISO, and other styles
5

Madibo, Carol Thato, Rene Van Eck, and Fhatuwani Vivian Mapande. "Readiness for Adoption Model of AI-based chatbots in Academic Institutions: A Review." In 2024 4th International Multidisciplinary Information Technology and Engineering Conference (IMITEC). IEEE, 2024. https://doi.org/10.1109/imitec60221.2024.10850987.

Full text
APA, Harvard, Vancouver, ISO, and other styles
6

Verma, Anuj, Meenakshi Verma, and Anuradha Goswami. "Adoption of AI in CRM in the Retail Sector. A perspective from Technology Acceptance Model." In 2024 8th International Conference on Computing, Communication, Control and Automation (ICCUBEA). IEEE, 2024. https://doi.org/10.1109/iccubea61740.2024.10775068.

Full text
APA, Harvard, Vancouver, ISO, and other styles
7

Hernandez, Alexander A., Victor James C. Escolano, Muhammad Syukur, Ace Lagman, Roland A. Calderon, and Rosanna T. Adao. "Predicting the Factors to Artificial Intelligence in Peer-to-Peer Energy Sharing Service Adoption Intention: A Structural Equation Model Assessment." In 2024 9th International Conference on Business and Industrial Research (ICBIR). IEEE, 2024. https://doi.org/10.1109/icbir61386.2024.10875879.

Full text
APA, Harvard, Vancouver, ISO, and other styles
8

Gil, Heungbae, Seong-In Kang, JeongHwan Jang, and Min Joon Kong. "Digital Twin for Maintenance and Disaster Management of the Cable- stayed Bridge." In IABSE Symposium, Tokyo 2025: Environmentally Friendly Technologies and Structures: Focusing on Sustainable Approaches. International Association for Bridge and Structural Engineering (IABSE), 2025. https://doi.org/10.2749/tokyo.2025.0930.

Full text
Abstract:
&lt;p&gt;Digitalization and adoption of a digital twin in the transport sector are considered to be a little bit slower than in other industries. However, as the use of BIM (Building Information Modeling) in infrastructure projects has rapidly increased, the concept of digital twin is beginning to be accepted for infrastructure management. To enhance maintenance and disaster management in the road sector through digital transformation, a pilot project was launched in 2023 to construct a digital twin of the Seohae Bridge, a cable-supported bridge. The Bridge consists of a cable-stayed bridge and two different types of pre-stressed concrete box girder bridges. The digital twin for the Seohae Bridge is constructed by integrating the following components: a BIM-based 3D digital model, UAV- based defect inspection data and real-time sensor data, scenario-based structural events simulation analysis, real-time bridge safety assessment, and AI algorithm-based sensor data monitoring.&lt;/p&gt;
APA, Harvard, Vancouver, ISO, and other styles
9

Tasić, Aleksandra, Jelena Ćulibrk, Nenad Medić, Bojana Jokanović, and Predrag Vidicki. "FACTORS THAT INFLUENCE ADOPTION OF AI IN ORGANIZATIONS." In 19th International Scientific Conference on Industrial Systems. Faculty of Technical Sciences, 2023. http://dx.doi.org/10.24867/is-2023-t1.1-8_05041.

Full text
Abstract:
In the last few years, the rapid development of Artificial Intelligence (AI) has created the conditions for its increasing use in various organizations, in order to achieve the well-known goals of increasing productivity, efficiency, effectiveness and more rational use of resources. However, most companies have difficulties in implementing artificial intelligence and realizing the benefits it brings. Most of the researchers in this field, in order to examine in more detail which factors influence the adoption of new technologies in the organization and what their mutual relationship is, uses previously well-developed models such as TAM (Technology acceptance Model), UTAUT (The Unified Theory of Acceptance and Use of Technology) and TOE (TechnologyOrganization-Environment). Through a more detailed review of the literature, this paper provides a framework overview of the factors. The article highlights the insufficient focus of previous studies on the factors related to the intention of employees to use artificial intelligence in everyday business tasks, that is, it proposes a framework for further research in this area with special attention to the intention of employees to use AI. Our results can help scholars and practitioners to include those factors in further theory development.
APA, Harvard, Vancouver, ISO, and other styles
10

Dilshan, A., J. Wijayanayake, D. Asanka, and C. Karunarathna. "Adoption success of using Generative AI apps for the ECommerce Platforms in Sri Lanka." In Proceedings of the 3rd International Conference on Sustainable & Digital Business. SLIIT Business School, 2024. https://doi.org/10.54389/burh1886.

Full text
Abstract:
The digital landscape has witnessed the widespread influence of e-commerce, with the Information Technology industry embracing generative AI applications. This research aims to investigate the adoption success of existing e-commerce platforms in Sri Lanka in incorporating generative AI technologies. A systematic literature review using the PRISMA framework identified how generative AI is used in various industries, its Future Directions, Ethical Concerns, Security, and Privacy Considerations, and the most widely used and accepted models for understanding technology adoption. The Technology Acceptance Model (TAM) and the Unified Theory of Acceptance and Use of Technology (UTAUT) are the two most widely used in past research for the acceptance of technology. These two models and past literature were used to develop a conceptual framework. The variables in this research model were measured through questionnaires with five-point Likert scales and close-ended questions completed by the Software Engineering and Software development process-related employees in Sri Lanka. Data cleaning and demographic data analysis were conducted using IBM SPSS 21, and preliminary data analysis was performed using PLS-SEM (SmartPLS 4). The study found that generative AI apps are productive, effective, and capable of retaining users with a positive intention to use them in Ecommerce. High implementation costs negatively impact, and Low training and maintenance costs positively affect the intention of users to adopt generative AI apps. The factors such as innovativeness, perceived benefits, and level of attitudes, positively impact the overall adoption success. These findings are expected to guide Sri Lankan e-commerce platforms, aiding them in enhancing the successful adoption and seamless integration of generative AI apps. By aligning with the wisdom of TAM and its associated models, our research contributes to understanding the adoption success of Sri Lankan e-commerce platforms to embrace generative AI technologies. Keywords: Adoption Success, Acceptance of Technology, E-Commerce, Generative AI Apps, Technology Acceptance Model
APA, Harvard, Vancouver, ISO, and other styles

Reports on the topic "AI adoption intention model"

1

Pasupuleti, Murali Krishna. Securing AI-driven Infrastructure: Advanced Cybersecurity Frameworks for Cloud and Edge Computing Environments. National Education Services, 2025. https://doi.org/10.62311/nesx/rrv225.

Full text
Abstract:
Abstract: The rapid adoption of artificial intelligence (AI) in cloud and edge computing environments has transformed industries by enabling large-scale automation, real-time analytics, and intelligent decision-making. However, the increasing reliance on AI-powered infrastructures introduces significant cybersecurity challenges, including adversarial attacks, data privacy risks, and vulnerabilities in AI model supply chains. This research explores advanced cybersecurity frameworks tailored to protect AI-driven cloud and edge computing environments. It investigates AI-specific security threats, such as adversarial machine learning, model poisoning, and API exploitation, while analyzing AI-powered cybersecurity techniques for threat detection, anomaly prediction, and zero-trust security. The study also examines the role of cryptographic solutions, including homomorphic encryption, federated learning security, and post-quantum cryptography, in safeguarding AI models and data integrity. By integrating AI with cutting-edge cybersecurity strategies, this research aims to enhance resilience, compliance, and trust in AI-driven infrastructures. Future advancements in AI security, blockchain-based authentication, and quantum-enhanced cryptographic solutions will be critical in securing next-generation AI applications in cloud and edge environments. Keywords: AI security, adversarial machine learning, cloud computing security, edge computing security, zero-trust AI, homomorphic encryption, federated learning security, post-quantum cryptography, blockchain for AI security, AI-driven threat detection, model poisoning attacks, anomaly prediction, cyber resilience, decentralized AI security, secure multi-party computation (SMPC).
APA, Harvard, Vancouver, ISO, and other styles
2

Hermansen, Anna, and Cailean Osborne. The Economic and Workforce Impacts of Open Source AI: Insights from Industry, Academia, and Open Source Research Publications. The Linux Foundation, 2025. https://doi.org/10.70828/itvq4899.

Full text
Abstract:
In a literature review commissioned by Meta, LF Research found that open source AI (OSAI) is widely adopted, cost effective, highly performing, and leads to faster and higher-quality development of tools and models. The study included a comprehensive analysis of academic and industry literature as well as empirical data from previous LF Research surveys to determine existing evidence of the economic and workforce impacts of OSAI. The study assessed these impacts in four areas: Adoption rates: a significant majority (89%) of organizations are using some form of open source in their AI stack and almost two-thirds (63%) of companies are using an open model Economic benefits: OSAI is considered a cost-effective choice as compared to proprietary solutions while increasing productivity and accelerating collaborative innovation Workforce impacts: AI has nuanced impacts on the workforce and is poised to be more of a complement for jobs than a tool to replace jobs Sector-specific insights: AI has unique impacts on healthcare, agriculture, construction, manufacturing, and energy
APA, Harvard, Vancouver, ISO, and other styles
3

Pasupuleti, Murali Krishna. Quantum Intelligence: Machine Learning Algorithms for Secure Quantum Networks. National Education Services, 2025. https://doi.org/10.62311/nesx/rr925.

Full text
Abstract:
Abstract: As quantum computing and quantum communication technologies advance, securing quantum networks against emerging cyber threats has become a critical challenge. Traditional cryptographic methods are vulnerable to quantum attacks, necessitating the development of AI-driven security solutions. This research explores the integration of machine learning (ML) algorithms with quantum cryptographic frameworks to enhance Quantum Key Distribution (QKD), post-quantum cryptography (PQC), and real-time threat detection. AI-powered quantum security mechanisms, including neural network-based quantum error correction (QEC), deep learning-driven anomaly detection, and reinforcement learning for adaptive encryption, provide a self-learning security model for quantum communication systems. The study also examines quantum blockchain integration, AI-optimized quantum network traffic management, and secure quantum biometric authentication as emerging trends in AI-enhanced quantum cybersecurity. Additionally, it evaluates industry adoption, policy considerations, and global quantum security initiatives across China, the US, the EU, and India. By addressing scalability, automation, and real-time quantum security monitoring, this research provides a roadmap for leveraging AI in next-generation secure quantum networks to enable fault-tolerant, self-healing cybersecurity frameworks. Keywords: Quantum intelligence, machine learning, secure quantum networks, AI-driven quantum cryptography, quantum key distribution, post-quantum cryptography, neural network-based quantum error correction, deep learning anomaly detection, reinforcement learning in quantum security, AI-driven quantum authentication, quantum blockchain security, quantum biometric authentication, quantum-enhanced AI cybersecurity, real-time quantum security monitoring, AI-optimized quantum routing, scalable quantum encryption, quantum cybersecurity policy, AI-powered post-quantum security, self-healing quantum networks, AI-driven quantum forensics.
APA, Harvard, Vancouver, ISO, and other styles
You might also be interested in the extended bibliographies on the topic 'AI adoption intention model' for particular source types:
Journal articles Dissertations / Theses
We offer discounts on all premium plans for authors whose works are included in thematic literature selections. Contact us to get a unique promo code!

To the bibliography