Technology Acceptance Theory Research Articles

Examination of Cyber-Physical System Applications in Manufacturing Enterprises with the Unified Technology Acceptance and Utilization Theory

In this study, the perception, acceptance and usage status of Cyber Physical Systems (CPSs) which seem likely to become a more dominant tool in the industrial sector in the coming years, in manufacturing industry enterprises, and the advantages it provides to small and medium-sized enterprises (SMEs) in the manufacturing sector are examined in line with the requirements of the sector. In this regard, the study will offer comprehensive insights to researchers, scientists, and decision-makers within industrial sectors, as well as institutions and organizations tasked with making strategic decisions. In addition, as with any new technology, the importance of determining the attitudes of staff and managers, who are the users of the technology, towards CPS was evaluated with an acceptance model developed by considering industrial conditions. By applying a questionnaire with open-ended questions including the opinions of SMEs, it is aimed to examine the factors in the Unified Technology Acceptance and Utilization Theory (UTAUT) model whose effects on usage are advocated. analysis demonstrate that the major hesitations of the enterprises are concentrated on the high costs of the technology, the lack of human resource competence to use the systems and the lack of solution partners in case of possible failures, but they still have positive opinion about the use. The study's findings shed light on the factors influencing the feasibility of CPS technology in the industrial sector. These results can serve as a guide for conceptualization, policy support, planning, and the development of new management strategies that will be essential in this field in the forthcoming years.

Knowledge sharing leads to engagement during Covid-19 for online gamers

Online games have emerged as a breath of fresh air in the lives of the current digital generation amidst the backdrop of COVID-19 and subsequent global lockdowns. Within Internet communities, online gamers actively engage in knowledge sharing, exchanging insights and updates on their experiences. This study introduces a model designed for Massive Multiplayer Online Gamers of Travian, focusing on intrinsic factors such as perceived usefulness, perceived ease of use, and the flow state, supported by the Technology Acceptance Model. Amidst the COVID-19 pandemic, with lockdowns and quarantine as moderators, this study uses partial least squares structural equation modeling (PLS-SEM) methodology, encompassing 496 gamers, to elucidate the impact of technology acceptance and flow theory on intrinsic motivational factors that drive online gamers' knowledge-sharing activities, underpinning the social protection theory. This pioneering research explores the implications of COVID-19 restrictions on gamers' behavioral patterns, contributing significantly to the existing literature by providing a deeper psychological understanding of the less-explored realm of diverse online gamers' activities during the pandemic.

An integrated bibliometric analysis and systematic review modelling students’ technostress in higher education

ABSTRACT Technology integration in higher education has been widely recognised for its multifarious benefits. Nevertheless, arising from various factors, the prevalence of technostress poses a substantial impediment to learning effectiveness. In response, this study employs visualisation analysis and systematic review techniques to formulate a comprehensive model that encompasses variables related to technostress. Based on a systematic selection from 1,861 publications, 83 publications were included to model predictors and outcomes of higher-education students’ technostress. Our findings reveal that the COVID-19 pandemic has spurred growing academic interest in technostress, owing to concerns about the stressful and anxious nature of remote learning. Existing research on this topic predominantly relies on technology acceptance models and theories, with ongoing expansions incorporating variables from multiple research domains. In particular, external factors assume pivotal roles as predictors of technostress, along with subdimensions related to technostress. The impact of technostress can be observed in various aspects, such as learning experiences and performance outcomes. The findings of this study provide valuable insights for future research endeavours, facilitating further exploration and informing technology-enhanced teaching practice.

VERIFYING THE DETERMINANTS OF BLOCKCHAIN ADOPTION INTENTION: A META-ANALYSIS ON SUPPLY CHAIN STUDIES

Numerous significant variables for the adoption of Blockchain technology in supply chains have been identified empirically. These variables, which influence adoption behavior in a variety of contexts, are discussed theoretically using technology acceptance theories and various other theories and methodological approaches. Given that research have been undertaken in many contexts, it is necessary to validate the previously proposed relationships between factors that facilitate blockchain adoption and the intention to utilize blockchain technology. Therefore, the purpose of this study is to investigate and validate the critical variables that stand out in related studies by using meta-analysis. 38 studies published in SSCI and SCI-E-indexed journals were used after searching WoS, Scopus, and Google Scholar databases and employing various filtering criteria. In addition to the variables considered in the most widely accepted technological, environmental, and organizational classifications, the research results disclose newly emerging or relatively less interesting variables. While the study's empirical findings have managerial implications, this study also provides suggestions for future research agendas.

OPTIMIZING PROJECT TIMELINES: THE IMPACT OF E-PROCUREMENT IN ACCELERATING PUBLIC SECTOR PROJECTS IN NIGERIA

Purpose: E-procurement is recognized globally as a tool for enhancing efficiency and transparency, with major intergovernmental bodies advocating its adoption. This study investigates the impact of electronic procurement (e-procurement) on project completion times in the Nigerian public sector. The research focuses on e-tendering, e-invoicing, and e-sourcing, hypothesizing their effects on project completion times. Theoretical Framework: The study employs a conceptual framework highlighting the interplay between e-procurement practices and government policies. Theoretical frameworks, including Innovation Diffusion Theory and Technology Acceptance Theory guided the study. Design/Methodology/Approach: The study adopted a descriptive survey research design to collect primary data from 361 procurement staff from four agencies in Abuja using a structured questionnaire. Data collected were analysed using descriptive statistics and multiple regression analysis. Findings: The results indicate a positive relationship between e-procurement practices and project completion times, with e-invoicing having the most significant impact. However, the introduction of government e-procurement policies as a variable diminishes the individual effects of e-tendering, e-invoicing, and e-sourcing. Research, Practical & Social Implications: The study established a positive relationship between electronic procurement practices and project completion times, with higher implementation levels resulting in shorter project durations. However, organizations should evaluate their impact, balance oversight and efficiency. Originality/Value: By focusing specifically on the Nigerian public sector, testing clearly defined e-procurement elements, collecting robust primary data, and generating new context-specific evidence, this study makes an original, timely and valuable contribution to knowledge on the impact of e-procurement adoption.

Factors affecting the social acceptance of agricultural and solar energy systems: The case of new cities in Egypt

Can the building sector become productive and, in parallel, help create livable spaces? Agricultural and solar energy systems can contribute to the building sector’s transformation; however, research on these systems has mostly focused on technological development and achieved gains, while overlooking a key driver of success, which is social acceptance. Only recently has the discussion on social acceptance of the systems gained momentum revealing that their adoption, especially in residential sectors, is bound to end users. Therefore, using a quantitative, survey-based, case study approach, we investigated what influences the social acceptance of end users, i.e., the residents of residential buildings in Egyptian new cities. Based on UTAUT – a Technology Acceptance theory – seven underlying factors were tackled using a statistical contingency analysis (SPSS, n = 274) to test their association with (a) social acceptance of agricultural and solar energy systems and (b) the sociocultural background of the residents. Results revealed that social acceptance of the systems was associated with factors like the expected effort for implementation, concerns and anxieties about the systems, external supporting conditions, and social influences – while surprisingly, it was not associated with the expected performance of the systems, their perceived costs, and the need for financial support. Most studied factors showed associations with the sociocultural aspects, except for the expected effort and perceived cost of solar systems and financial facilitations of both systems, which proved to be completely independent of the sociocultural background of the residents. The conducted analysis and concluded insights about the underlying factors behind social acceptance have not been previously covered in detail for the two systems in comparison, especially for the case of new Egyptian residences. The study findings can support relevant stakeholders such as policymakers, suppliers, engineers, etc. in triggering the social acceptance of the systems in Egypt and contexts of similar settings.

An Empirical Evaluation of a Generative Artificial Intelligence Technology Adoption Model from Entrepreneurs’ Perspectives

Technologies, such as Chat Generative Pre-Trained Transformer (ChatGPT), are prime examples of Generative Artificial Intelligence (AI), which is a constantly evolving area. SMEs, particularly startups, can obtain a competitive edge, innovate their business models, gain business value, and undergo a digital transformation by implementing these technologies. Continuous but gradual experimentation with these technologies is the foundation for their adoption. The experience that comes from trying new technologies can help entrepreneurs adopt new technologies more strategically and experiment more with them. The urgent need for an in-depth investigation is highlighted by the paucity of previous research on ChatGPT uptake in the startup context, particularly from an entrepreneurial perspective. The objective of this research study is to empirically validate the Generative AI technology adoption model to establish the direction and strength of the correlations among the adoption factors from the perspectives of the entrepreneurs. The data are collected from 482 entrepreneurs who exhibit great diversity in their genders, the countries in which their startups are located, the industries their startups serve, their age, their educational levels, their work experience as entrepreneurs, and the length of time the startups have been on the market. Collected data are analyzed using the Partial Least Squares Structural Equation Modeling (PLS-SEM) technique, which results in a statistical examination of the relationships between the adoption model’s factors. The results indicate that social influence, domain experience, technology familiarity, system quality, training and support, interaction convenience, and anthropomorphism are the factors that impact the pre-perception and perception phase of adoption. These factors motivate entrepreneurs to experiment more with the technology, thereby building perceptions of its usefulness, perceived ease of use, and perceived enjoyment, three factors that in turn affect emotions toward the technology and, finally, switching intentions. Control variables like age, gender, and educational attainment have no appreciable effect on switching intentions to alternatives of the Generative AI technology. Rather, the experience factor of running businesses shows itself to be a crucial one. The results have practical implications for entrepreneurs and other innovation ecosystem actors, including, for instance, technology providers, libraries, and policymakers. This research study enriches the Generative AI technology acceptance theory and extends the existing literature by introducing new adoption variables and stages specific to entrepreneurship.

Exploring the behavioral stage transition of traveler's adoption of carsharing: An integrated choice and latent variable model

This study investigates the process of stage transition in traveler's adoption of carsharing. The carsharing adoption behaviors are classified into five stages using the transtheoretical model: precontemplation (PC), contemplation (C), preparation (PA), action (A), and maintenance (M). In Beijing, a comprehensive survey combining stated preference and revealed preference methods is conducted to collect data on travelers' adoption attitudes and related attributes, such as socioeconomic characteristics, travel features, and carsharing usage environments. Specifically, ten latent attitudinal variables are derived from the technology acceptance model and theory of planned behavior. An integrated choice and latent variable model is developed to examine the impact of these explanatory factors on the transition processes between the five adoption stages. The findings reveal that the effects of explanatory factors on stage transitions in carsharing adoption behaviors differ across stages. Factors such as education level, income, having children, car ownership, familiarity with carsharing, personal condition, and social pressures play a crucial role in the early stages of understanding before carsharing adoption, namely the PC-C and C-PA stage transitions. Conversely, in the later stages (PA-A and A-M), travelers show a greater emphasis on carsharing infrastructure, including station reachability, vehicle availability, and perception toward rental stations and shared vehicles. Additionally, factors related to travel habits and expectations are influential throughout all stages of the carsharing adoption process. Lastly, three categories of measures, namely soft, neutral, and hard measures, are derived from the results to guide policymakers and carsharing operators in formulating strategies for the operation and management of carsharing systems.

Factors influencing students’ intention to use learning management system at Saudi Universities: A structural equation modeling approach

BACKGROUND: To encourage students’ behavioural intentions (BI) to use Learning Management System (LMS) in Saudi Arabia, policymakers, particularly the ministry of higher education, should persuade potential users that LMS is useful, simple to use, and that others have high expectations for its use in the near future. OBJECTIVE: This study aims to identify factors influencing students’ BI towards accepting the LMS in Saudi Arabia. METHODS: An online questionnaire was used to collect 212 student responses from Saudi Arabia’s University of Hail. The integrated model was tested using Structural Equation Modeling (SEM). RESULTS: The results of analysis using Structural Equation Modeling (SEM) revealed that factors influencing students’ attitudes towards accepting the LMS and, thus, their BI towards the use of the LMS in Saudi Arabia, were their perceived behavioural control (PBC) and perceived usefulness (PUS). On the contrary, attitudes toward behaviour (ATB), subjective norms (SN), and perceived ease of use (PEU) have no influence on students’ BI. CONCLUSIONS: The findings of this study contribute to our understanding of the predictor variables Technology Acceptance Modell (TAM) and Theory of Plan Behaviour (TPB) on students’ BI to use LMS in Saudi Arabian universities.

Strategy Formulation to Increase User Intention to Use Electric Ride Hailing Service in Indonesia

The emergence of electric ride-hailing services as a form of contribution from applicators in response to the government's transformation movement towards massive and equitable use of electric vehicles (EVs) by 2030 has captured the attention of the public in Indonesia. However, this new business model still needs to be reviewed to gain more awareness so that more users can use the service. Research on user perceptions of the technology is needed to develop electric ride-hailing services. Analysis of factors related to the user adoption process of electric online transportation services will be carried out using an integrated model of the Technology Acceptance Model (TAM) and Theory of Planned Behavior (TPB). Data processing and analysis will be carried out using the Structural Equation Modeling (SEM) method. The results showed that usefulness has a significant effect on Attitude Towards Use and Attitude Towards Use has a significant effect on Intention to Use so that applicators are expected to be able to implement strategies in increasing user perceptions of the value of usefulness in increasing the intention to use this service.

Profiling of OTT Viewers and their Perception Mapping using Advanced Technological Models

Purpose – The study explores the significant attributes that inspire customers to select OTT platforms and to measure the positions of OTT platforms in the mind of an individual via a perceptual map. Design/methodology/approach –To develop a perceptual map to measure the attribute-based motivation regulations with regards to OTT platforms. With combination of theoretical frameworks such as Technology Acceptance Model (TAM); Diffusion of Innovation Theory (DIT); Uses and Gratifications Theory (UGT) and Unified Technology Acceptance and Use Theory (UTAUT) used to develop as scale. Furthermore, this study used mixed method approach. Findings – Four attributes/ regulations were proposed: ease of use, social influence etc. Research limitations/implications – The study utilises a theoretical framework to create a structured framework for motivating young people based on OTT attributes. Practical implications – Study directs OTT marketers in strategically positioning the channel based on specific qualities. Originality/value – This work in the OTT channels utilized the combination of TAM, UGT, DIT and UTAUT framework.

Employee Acceptance of Human Resource Management Information System: Integrated UTAUT and TTF Model in a Selected Public Firm in Sri Lanka

Aim: In the modern digital world, many companies are moving towards technology-based applications to perform human resource administration work. Employees nowadays are capable of accessing a web-based Human Resource Management Information System (HRMIS) to obtain critical data from recognized techniques such as System Applications and Products (SAP), PeopleSoft, Bann and Lawson. This study aims to investigating the factors affecting the adopting intention of HRMIS in a selected public firm in Sri Lanka.
 Design: Acknowledging the vital concepts on accepting or resisting technology, six components (performance expectancy, effort expectancy, social influence, facilitating conditions, task characteristics, and technology characteristics) from the Unified Theory of Acceptance and Use of Technology (UTAUT) model and the Task Technology Fit (TTF) model were contextualized to investigate the drivers influencing HRMIS adoption intentions in a selected public firm in Sri Lanka. Target population was identified as the Executives, Supervisors/Technical Officers, Clerical and Allied employees of the chosen public company in Sri Lanka. A structured online questionnaire, including 30 items, was used to collect data.
 Findings: Multiple regression analysis results revealed that the factors of Performance Expectation, Task Characteristics, and Technology Characteristics have a positive influence on users’ adoption intention to HRMIS. Effort Expectancy, Social Influence, and Facilitating Conditions had negative influence.
 Implications: The outcomes highlight the necessity of combining TTF components with technology acceptance theories when evaluating the factors influencing acceptance of HRMIS or other information systems. The study's findings will aid management in making the required organizational changes to encourage employees to use the HRMIS application.

Factors affecting medical students’ intention to use Rain Classroom: a cross-sectional survey

BackgroundRain Classroom was one of the most popular online learning platforms in Chinese higher education during the pandemic. However, there is little research on user intention under the guidance of technology acceptance and unified theory (UTAUT).ObjectiveThis research aims to determine factors influencing students' behavioural intention to use Rain Classroom.MethodsIn this cross-sectional and correlational investigation, 1138 medical students from five medical universities in Guangxi Province, China, made up the sample. This study added self-efficacy (SE), motivation (MO), stress (ST), and anxiety (AN) to the UTAUT framework. This study modified the framework by excluding actual usage variables and focusing only on intention determinants. SPSS-26 and AMOS-26 were used to analyze the data. The structural equation modelling technique was chosen to confirm the hypotheses.ResultsExcept for facilitating conditions (FC), all proposed factors, including performance expectancy (PE), effort expectancy (EE), social influence (SI), self-efficacy (SE), motivation (MO), anxiety (AN), and stress (ST), had a significant effect on students' behavioural intentions to use Rain Classroom.ConclusionsThe research revealed that the proposed model, which was based on the UTAUT, is excellent at identifying the variables that influence students' behavioural intentions in the Rain Classroom. Higher education institutions can plan and implement productive classrooms.

The Effect of Augmented Reality Acceptance on E-Commerce on Cosmetic Purchase Decisions Using Combination TPB and TAM

The fact that the sales of cosmetic products in Indonesia are increasing causes competition between brands to be unavoidable. One of the strategies the company prepared is to expand its marketing reach with e-commerce. But when selling cosmetic products by online new problem arises, scilicet the absence of a tester causes a lack of information about the product and how the technology is accepted. A lack of understanding about the product will affect consumer buying interest. Shopee answers this problem by providing a markerless augmented reality-based beauty cam feature. Based on this description, this study will analyze the effect of acceptance of the use of augmented reality on product purchase decisions using a combination of the Technology Acceptance Model and Theory of Planned Behavior. Data in his study was collected by distributing online questionnaires to Shopee users who have used this feature. The results of this study indicate that behavioral control variables do not affect a person's behavioral intention to use the beauty cam feature or the intention to buy cosmetic products. In addition to these correlations, all proposed correlations have a significant effect. The results of this study can stimulate future research and become a consideration for feature developers and business owners in other fields.

Understanding the role and impact of Generative Artificial Intelligence (AI) hallucination within consumers’ tourism decision-making processes

ABSTRACT ChatGPT, which launched only a year ago, is the fastest-growing website in the world today. When generative AI software such as ChatGPT generates ideas for people, they often generate false ideas. This occurrence has been called ‘AI Hallucination’. It can include generating false text output that is extremely believable to completely gibberish. This source of potential misinformation has significant potential implications for the travel and tourism industry. Using survey responses from 900 consumers, this empirical study contributes to theorizing and examination of how consumers’ awareness of AI Hallucination potential combines with existing concepts from the Technology Acceptance Model (TAM) and Theory of Planned Behaviour (TPB) when it comes to the decision to use generative AI platforms such as ChatGPT for tourism planning. This research also examines if the consumers are actually able to discern AI Hallucination and why they select to use AI technologies over other tourism information sources, such as aggregated peer review websites like TripAdvisor, government tourism websites, or social media influencers. The results indicate that many consumers chose error-filled AI tourism itineraries over other options because they trust the AI to be more impartial and customized than the other sources.

Teleworking antecedents: an exploration into availability bias as an impediment

Telework technologies have been known since the 1970s, yet their adoption levels remained low until Covid-19-related lockdowns and curfews. The known rational and non-rational technology acceptance theory and biases cannot fully explain this effect. One of the possible answers to fill this gap could be availability bias which has probably also affected the lag in adopting other technologies. To examine this phenomenon, we conducted a qualitative study with 22 interviews with individuals from different organizational backgrounds and telework adoption levels. Following a combination of inductive and deductive coding, we identified three key aspects of availability bias: intention, cognitive visibility, and cognitive transfer. The findings also allowed us to delineate this bias further from other biases, e.g., the status quo bias, and classical technology acceptance models, e.g., UTAUT. Thereby, this study examines a bias so far only very limitedly researched in the information systems and extends technology acceptance and cognitive bias literature. The findings should also enable practitioners to question their way of working and technology use more thoroughly.

Bite-Sized Learning on TikTok: Exploring the Platform’s Educational Value within the Framework of TAM (Technology Acceptance Theory)

Bite-Sized Learning on TikTok: Exploring the Platform’s Educational Value within the Framework of TAM (Technology Acceptance Theory)

Understanding digital marketing adoption by start-up companies in India: through an integrated technology acceptance model and theory of planned behaviour framework

Understanding digital marketing adoption by start-up companies in India: through an integrated technology acceptance model and theory of planned behaviour framework

Fintech Adoption: A Study of Users in the Guangdong-Macao In-Depth Cooperation Zone in Hengqin (China)

Intended as an economic and development hub, the Hengqin Cooperation Zone aims to foster collaboration and integration between mainland China, Hong Kong, and Macao, serving as a platform for economic development and innovation among the three regions. The zone's development has increased demand for financial services, often offered through fintech. There is, however, a lack of interoperability between the fintech services currently used in Macao and Hengqin. This may hinder Macao users' adoption of the technology. Thus, our research objective is to identify the factors determining Macao residents' adoption of fintech services in the area and provide insights for service providers, developers, and policymakers. A framework based on the Technology Acceptance Model (TAM) and Theory of Planned Behavior (TPB) was used for this purpose. The responses of 103 Macao residents provided evidence that ease of use significantly and positively impacts the usefulness of the technology. This in turn influences attitudes towards fintech usage. Subjective norms and perceived behavioral control positively impact fintech adoption intentions. The fintech industry and the governments of Macao and Hengqin can work on improving technology's ease of use and usefulness. They can also promote them to Macao users, and provide the resources required for better access to fintech in the zone.

Transformative impact : Online learning evolution in higher education Post-Covid-19 pandemic

The COVID-19 outbreak led to a significant change in India’s educational landscape, resulting in the widespread adoption of e-learning technologies in the classroom. To evaluate the success of this transition, a study was conducted utilizing the Unified Theory of Technology Acceptance and Use (UTAUT) framework. The objective of the research was to evaluate the usefulness of e-learning in higher education institutions. The study involved conducting a cross-sectional survey through a structured questionnaire to test the hypotheses through empirical evidence. The statistical findings, based on a sample of 313 participants from several educational institutions, show that factors such as faculty influence, quality of services, performance expectancy and facilitating conditions significantly influence students’ behavioral intentions. The expectation of effort, however, had no impact on the students’ intentions. Additionally, the students’ behavioral intentions positively impact their usage behavior