Predicting university students’ behavioral intention toward electronic train ticketing system using Technology Acceptance Model

Purpose – The purpose of this study is to propose a refined technology acceptance model (TAM) to examine the relationship between factors that affect travelers' use of hotel self-service kiosks. Design/methodology/approach – The target population of the study is domestic travelers whose e-mail addresses are in a publicly available database. The measures in this study were developed based on a thorough review of the previous literature. A self-administered questionnaire was developed and distributed through online, and a structural equation modeling (SEM) analysis was conducted by LISREL 8.0 to test the proposed extended technology acceptance model (TAM). Findings – Results suggested that all external variables (i.e. perceived usefulness, perceived ease of use, compatibility, and perceived risks) have significant direct effects on travelers' attitude toward using hotel self-service kiosks. However, perceived usefulness and perceived ease of use did not have significant effects on travelers' satisfaction. Specifically, compatibility was the most important factor that influences travelers' attitude toward using hotel self-service kiosks, followed by perceived ease of use. Further, perceived risks have a significant influence on travelers' satisfaction, followed by compatibility. Research limitations/implications – This paper provides guidance which will be useful to hotel managers and marketers seeking to improve travelers' acceptance of hotel self-service kiosks when utilizing these in their service delivery as well as to manage travelers' satisfaction of their experience with hotel self-service kiosks. Originality/value – The new refined model of factors affecting travelers' use of hotel self-service kiosks comprises three new factors, including compatibility, perceived risks, and satisfaction.

This study endeavors to explore the factors affecting the behavioral intention toward using smartphone by university students in Bangladesh. In this study, “Technology Acceptance Model” (TAM) and “Theory of reasoned action” (TRA) have been integrated to examine the factors that influence attitude as well as an intention toward using smartphone. Factors used in the basic “Technology Acceptance Model” (TAM) include “Perceived Ease of Use” and “Perceived Usefulness”. “Subjective Norm”, deriving from “Theory of Reasoned Action” (TRA), is integrated with the theoretical framework. In this study, a survey is conducted on 428 students of 10 different universities in Bangladesh. Based on a theoretical framework of the study, a questionnaire is adopted from TAM using a seven point Likert’s scale. Statistical techniques such as multicollinearity test, reliability test, construct and discriminant validity, path analysis, and hypothesis testing are used to analyze the primary data. Findings reveal that “Perceived Ease of Use”, “Perceived Usefulness” along with “Subjective Norm” have significant influence on “Attitude toward using smartphone” that directly impact “Behavioral Intention”. IIUC Business Review, Vol.-11, Issue-1, Dec. 2022, pp. 35-51

Moodle is widely used in higher education institutions in this digital age. With the growing popularity of Moodle use in education, this study aimed to research on the factors that influence student users’ intentions to adopt Moodle for learning purposes in Macau. A total of 564 students from nine departments at the University of Macau responded to a survey in which ten constructs from a framework that integrated the Diffusion of Innovation Theory and Technology Acceptance Model, were measured. The results of this study showed that the research model had a good fit. Two variables—usefulness and ease of use—had significantly influenced Macau students’ attitudes towards Moodle use. Other variables such as usefulness, attitude, and perceived behavioral control were found to be important determinants of students’ behavioral intentions. Furthermore, usefulness was significantly associated with ease of use, output quality, trialability, as well as subjective norm. Students’ perceptions on the ease of use was significantly influenced by technology complexity and trialability. On the whole, the proposed research model had explained 66% of the variance of Macau university students’ behavioral intentions to use Moodle. This study contributed to deepening our understanding of technology acceptance theories by contextualizing the current study within the Macau higher education.

The present study examines university students’ acceptance of e-learning according to the Technology Acceptance Model (TAM). We also investigate the influence of external factors, including self-efficacy with digital media, self-regulated learning, prior experience, and affinity for technology, to extend the model with valid individual factors. Structural equation modeling with maximum-likelihood estimation served to evaluate the proposed research model, which included online questionnaire data from N = 225 undergraduates studying various subjects in 53 universities. The results indicate that the TAM is replicable regarding e-learning for German-speaking university students. Additionally, we found self-regulated learning and affinity for technology to be significantly positively related to the two main components of the TAM, perceived ease of use and perceived usefulness, implying their importance in technology acceptance. However, self-efficacy with digital media and prior experience showed no significant impact on university students’ technology acceptance. We also found a significant positive relationship between attitudes toward e-learning and behavioral intention, showing that university students with positive attitudes are more willing to use it in the future. Therefore, higher education should consider students’ individual prerequisites for e-learning and support students during the use of e-learning environments, to promote the development of positive experiences and attitudes toward e-learning.

As China's population continues to age rapidly, smart elderly care has become a crucial strategy for addressing this societal challenge. Smart home systems have the potential to significantly enhance the quality of life, safety, and autonomy of the elderly. However, the adoption rate of these systems in this demographic remains relatively low, requiring an exploration of the key factors influencing the behavioral intention to use such systems. This study developed a comprehensive model based on the Technology Acceptance Model and the Unified Theory of Acceptance and Use of Technology. Through empirical analysis using partial least squares structural equation modeling, this study systematically examined the pathways through which various factors affected the behavioral intentions of the elderly. The findings revealed that perceived usefulness, facilitating conditions, compatibility, and perceived cost had significant direct effects on behavioral intention. Additionally, social influence, perceived trust, facilitating conditions, and compatibility indirectly influenced behavioral intention through perceived usefulness and perceived ease of use. Although perceived trust did not directly affect behavioral intention, it exerted an indirect influence through perceived usefulness. This comprehensive model provides theoretical insights into the behavioral intentions of the elderly toward smart home systems and offers practical guidance for developers, designers, and policymakers in the development, design, and promotion of these systems.

This paper examines the social, organisational and individual factors that may affect students' acceptance of e‐learning systems in higher education in a cross‐cultural context. A questionnaire was developed based on an extended technology acceptance model ( TAM ). A total sample of 1173 university students from two private universities in L ebanon and one university in E ngland participated in this study. After performing the satisfactory reliability and validity checks, the hypothesised model was estimated using structural equation modeling. The findings of this study revealed that perceived usefulness ( PU ), perceived ease of use ( PEOU ), social norms ( SN s), perceived quality of work life ( QWL ), computer self‐efficacy ( SE ) and facilitating conditions ( FC ) are significant determinants of behavioural intentions (BIs) and usage of e‐learning system for the L ebanese and B ritish students. QWL , the newly added variable, was found the most important construct in explaining the causal process in the model for both samples. Differences were found between L ebanese and B ritish students with regard to PEOU , SN , QWL , FC , SE and actual usage; however, no differences were detected in terms of PU and BI . Overall, the proposed model achieves acceptable fit and explains for 69% of the B ritish sample and 57% of the L ebanese sample of its variance which is higher than that of the original TAM . Our findings suggest that individual, social and organisational factors are important to consider in explaining students' BI and usage of e‐learning environments.

<p>The mobile industry in recent years has been growing at a speedy pace where the use of cell phone is no longer limited to conventional usage like the voice communication, but has enriched the customer experiences with mobile internet services and other value added services. Along with the growing mobile industry, technology behind it is also changing accordingly. However, the user acceptance of technology depends on various factors that lead to either user acceptance or rejection. This study thus aims to identify the major determining factors that influence the user to use the 3G mobile internet and examines the interrelation among the determinants along with effect of the demographic variable limited to Kathmandu Valley users. The conceptual framework of this study is based on the extended version of Davis (1989)’s technology acceptance model using variables social influence, price perception, perceived usefulness, perceived ease of use, attitude to use and behavior intention. The primary survey is conducted using a set of questionnaire, which produced 180 valid responses from the mobile users in Kathmandu Valley. The reliability of the data from questionnaire is verified with factor analysis and Cronbach’s alpha. The result shows that social influence has significant influence on perceived ease of use while it has no significant influence on perceived usefulness. Price perception, on the other hand, influences the perceived usefulness. Similarly, perceived usefulness and perceived ease of use influence the attitude of use, which finally influences the behavioral intention. Along with this, social influence is also found to be the extended factors that can influence the attitude of the users, which in turn affects the behavioral intention. Demographic variables, however in this study, have shown no significant influence on the behavioral intentions. On the whole, the usage of 3G mobile internet service is not seen to be satisfying from the study. The major reasons as surveyed from the users themselves for this lower utilization seems to be higher data costs, presence of cheaper alternatives for internet like Wi-Fi internet, quick drainage of battery and slow mobile internet service provided by the mobile service providers. Thus, for mobile service providers, internet service providers are their direct competitors for 3G mobile internet services. This paper enhances understanding of user acceptance of 3G mobile internet services.</p><p>Journal of Business and Social Sciences Research, Vol. 1, No. 2, pp. 135-152</p>

Dyslexia research in China is crucial because of limited awareness, lack of tools, and insufficient support. These issues seriously hinder students' academic success. To address this gap, this study examines how history-related short videos on social media platforms influence the learning behavior of students with dyslexia. This study introduces dyslexia as a moderating variable within the Technology Acceptance Model (TAM) framework for the first time, addressing a significant gap in understanding how learning differences influence technology adoption in educational contexts. History poses special challenges for learners with dyslexia because it requires extensive reading and complex texts. Short videos may offer a more accessible and engaging alternative. A cross-sectional study was conducted among 400 university students in Hebei province, China using a self-administered questionnaire. Several scales were used in the survey: Quality of Content (CQ), Perceived Ease of Use (PEOU), Perceived Usefulness (PU), Behavioral Intention (BI), Dyslexia Scale, and Learning Behavior (LB). Descriptive statistics and structural equation modeling (SEM) analyses were performed. A P value of <0.05 was considered significant. The results show positive correlations among key variables. Content quality was positively correlated with perceived usefulness (r=0.369), perceived ease of use (r=0.329), and behavioral intention (r=0.203), all p<0.01. Ease of use is also associated with usefulness (r=0.323), and usefulness with intention (r=0.249). Learning intention further predicts behavior (r=0.359). However, the direct link between ease of use and behavioral intention is not significant (p=0.17). Dyslexia significantly moderates the relationship between PEOU and PU (p<0.001). However, it does not significantly affect the relationships between (1) PEOU and BI or (2) PU and BI, though these effects approach marginal significance. Students with dyslexia show different levels of learning intention depending on content quality, ease of use, and usefulness. Dyslexia significantly moderates some of these relationships. The findings suggest that history-related short videos can be effective educational tools, especially when they emphasize usability and usefulness.

A better understanding of how advancement in science and technology affect students’ learning behavior in an academic setting can help all educators in higher education. With the advancement of science and technology, the new-generation information technology represented by “Cloud Computing, Big Data, Internet of Things, Mobile Network, and Artificial Intelligence” has been profoundly changing the form of education, accelerating the transformation from Teaching 1.0 to Learning 2.0. To investigate the factors influencing university students using a new-generation information technology in intelligent foreign language learning, this study proposed a research model based on Technology Acceptance Model. The sample data were collected from a survey of 237 students at a university. The analysis of structural equation modeling indicated that perceived usefulness, perceived ease of use, construction of foreign language intelligence classroom, and computer self-efficacy all have a positive impact on learners’ behavioral intention. These findings suggest that more emphasis should be laid on students’ learning characteristics, advantages of a new generation of technology, as well as teachers’ intelligent literacy, to further promote the deep integration of the new-generation information technology and intelligent foreign language learning, improving the learning effectiveness ultimately and effectively.

This study investigates how digital literacy moderates the relationships among intrinsic motivation, Technology Acceptance Model (TAM) perceptions, and mobile gaming adoption among African university students, addressing whether technology acceptance pathways operate uniformly across users with varying technological backgrounds. Combining TAM with Self-Determination Theory, the research conceptualized digital literacy as a fundamental moderator shaping how competency, relatedness, and autonomy influence perceived usefulness, perceived ease of use, behavioral intention, and actual usage. Using a quantitative cross-sectional design, data were collected from 310 Nigerian university students and analyzed through multi-group structural equation modeling. Participants were classified into high (34.8%), moderate (45.2%), and low (20.0%) digital literacy groups based on technology experience profiles across seven platforms. The findings reveal substantial literacy-contingent variation in adoption pathways. Competency effects on perceived ease of use were markedly stronger among low-literacy users, while autonomy significantly predicted perceived usefulness only among digitally experienced users. Perceived ease of use consistently dominated the formation of behavioral intention across all literacy levels. However, actual usage remained constrained by infrastructure and economic barriers, irrespective of user expertise. These findings challenge foundational assumptions within TAM and Self-Determination Theory about the universal applicability of adoption processes, demonstrating instead that motivational hierarchies are conditional on users’ digital proficiency. Hence, the results foreground the need for literacy-sensitive theoretical models and adaptive technology designs that align competency scaffolding, autonomy features, and social integration with users’ digital capacities and proficiency level. Policy interventions that address structural constraints are also necessary to translate adoption intentions into sustained usage within African higher education settings.

The rapid advancements in artificial intelligence (AI) have significantly transformed various domains, including education, by introducing innovative tools that reshape teaching and learning processes. This research investigates the perceptions and attitudes of students towards the use of AI tools in their academic activities, focusing on constructs such as perceived usefulness, the perceived ease of use, security and privacy concerns, and both positive and negative attitudes towards AI. On the basis of Technology Acceptance Model (TAM) and the General Attitudes towards Artificial Intelligence Scale (GAAIS), this research seeks to identify the factors influencing students’ behavioral intentions and actual adoption of AI tools in educational settings. A structured survey was administered to students at Multimedia University, Malaysia, capturing their experiences and opinions on widely used AI tools such as ChatGPT, Quillbot, Grammarly, and Perplexity. Hypothesis testing was used to evaluate the statistical significance of relationships between the constructs and behavioral intention and actual use of the AI tools. The findings reveal a high level of engagement with AI tools among University students, primarily driven by their perceived benefits in enhancing academic performance, improving efficiency, and facilitating personalized learning experiences. The findings also uncover significant concerns related to data security, privacy, and the potential over-reliance on AI tools, which may hinder the development of critical thinking and problem-solving skills.

Based on a Technology Acceptance Model, this study investigates and increases the understanding of how perceived technological attributes (perceived technological implicitness and compatibility) and internal beliefs (perceived usefulness and perceived ease of use) will influence the behavioral intention of accepting licensing in new technology. This study adopts the Structural Equation Modeling approach. Based on the 244 correspondents from Taiwan's four high technology industries, 63% of the variance of licensees' behavioral intention can be accounted for by perceived usefulness, perceived technological implicitness, and compatibility in one theoretical mediate model. However, the evidence from Taiwan's 95 biotechnology companies indicates that 64% of the variance of behavioral intention can be explained by an alternative theoretical mediate and moderate model that consists of perceived technological compatibility, perceived usefulness and perceived ease of use.

This study aims to examine the effect of perceived usefulness, perceived ease of use, and behavioral intention to actually use accounting software. Therefore, the variables of this study consist of 4 (four) independent variables, they are perceived usefulness and perceived ease of use, intervening variable is behavioral intention and dependent variable is actual system use. The population of this study is the owner of the MSMEs food and beverages in Mataram city. Samples were taken using the solvin formula. Data obtained by distributing questionnaires to 50 respondents. Questionnaires are returned and can be used as many is 46 questionnaries. Data were analyzed using Partial Least Square (PLS) with SmartPLS 3.0 software. The results indicate that perceived usefulness and perceived ease of use doesn't affect significantly to the actual system use, instead of perceived usefulness and perceived ease of use has a significant effect on the behavioral intention. Behavioral intention has a significant effect on the actual system use, perceived usefulness has a significant effect on the actual system use through behavioral intention, perceived ease of use doesn't affect significantly to the actual system use through behavioral intention.

The purpose of this study was to test the relationship of influence of ease of use and perceived usefulness on motivation, collaboration, and behavioral intention in university students in times of Covid-19. The methodology used for the study corresponds to a non-experimental investigation, a questionnaire was applied to a convenience sample of 530 university students (n=19; α=0.944 ω=0.946), using Factor Exploratory and Confirmatory Analysis as tests of validity and reliability, through the Modeling of Structural Equations of Partial Least Squares PLS-SEM. The results have shown that there is a positive effect of causality of perceived ease of use on student collaboration, student motivation and perceived usefulness; in the same way, there exists a causal relationship between the perceived usefulness and the student's collaboration, the intention of the behavior and the student's motivation. Contrarily, there would not be an influence relationship between perceived ease of use on behavioral intention in university students in a context of Covid-19.

The integration of generative artificial intelligence (GenAI) into the educational landscape of China is advancing at a pace marked by unprecedented speed, which requires researchers to re-examine the psychological mechanisms underlying students' technology adoption. Despite the established role of Perceived Usefulness (PU) as a core cognitive driver, the interplay between this factor and the emerging emotional barrier of Artificial Intelligence Anxiety (AIA) has not been sufficiently examined. This study theoretically bridges the Technology Acceptance Model (TAM) and the emotional cognitive perspective. Through a questionnaire survey of 192 Chinese university students, the impact of PU, AIA and their interaction on the intention of learning behavior using GenAI was systematically tested. Hierarchical regression analysis shows that PU emerged as a robust predictor of Behavioral Intention (BI) ( = 0.697, p &lt; .01); however, AIA exerted no significant direct or interactive (with PU) effect on intention. Further exploratory analysis shows that even if AIA is deconstructed into three sub-dimensions of learning anxiety, sociotechnical blindness anxiety and AI configuration anxiety, its predictive effect on BI is still not significant, and the dominant role of PU remains robust ( = 0.720, p &lt; .001). The research results show that under the present learning context, the adoption decision-making of university students shows the phenomenon of "intention-emotion decoupling", that is, it is mainly driven by the rational evaluation of the value of the tool, and different types of AIA do not substantially intervene in the process of intention formation.