The Influence of Technology Acceptance on E-Commerce Behavior of Sociolla Users is Mediated by Behavioral Intentions (UTAUT 2 Testing Study)

Using the frameworks of the Theory of Use and Gratification (UGT) and the Unified Theory of Acceptance and Use of Technology (UTAUT2), this study explores the factors that influence individual behavior and behavioral goals in the adoption of digital banking. Partial Least Square-Structural Equation Modeling (PLS-SEM) is used in the analysis of research data using the program SmartPLS 3.2.9 professional. There are 432 people in the research sample that filled out questionnaires. The results show that behavioral intentions are strongly influenced by the integration of UGT-UTAUT2 by 60.3%. Performance and effort expectations are influenced by cognitive needs, effort expectations are influenced by affective needs, and social influence is impacted by social needs. Behavioral intentions for the use of digital banking are shaped by a combination of factors such as price value, hedonic motivation, habits, facilitating conditions, and effort expectations. The relationship between behavioral intentions, affective and cognitive needs is mediated by effort expectations. In the context of using digital banking, habits and behavioral intentions are important factors that influence behavior; in contrast, cognitive needs, affective needs, performance expectations, and social influence have no direct effect on behavioral intentions.

This study examines the factors influencing pre-service teachers’ behavioral intention to use AI-enabled educational tools during their practicum, using the Unified Theory of Acceptance and Use of Technology 2 (UTAUT2) as the theoretical framework. The model includes the core UTAUT2 constructs such as performance expectancy, effort expectancy, hedonic motivation, social influence, facilitating conditions, price value, and habit. It also incorporates additional predictors including computer self-efficacy, computer anxiety, and computer playfulness. Data were collected from 563 pre-service teachers using a structured questionnaire and analyzed using Partial Least Squares Structural Equation Modeling (PLS-SEM). The results indicate that performance expectancy and hedonic motivation are the strongest predictors of behavioral intention. Computer self-efficacy, computer anxiety, and computer playfulness significantly influenced effort expectancy, although effort expectancy did not directly predict behavioral intention. Performance expectancy was significantly predicted by extrinsic motivation, job fit, relative advantage, and outcome expectations. Constructs such as social influence and facilitating conditions showed limited or inverse effects. These findings suggest that internal motivational, cognitive, and emotional factors are more influential than external or institutional factors in shaping the adoption of AI-enabled tools. The study highlights the importance of promoting personal relevance, confidence, and enjoyment in teacher preparation programs to encourage technology integration.

The purpose of the study is to find out Information Technology challenges facing by practicing auditors using measurement variables used in the Unified Theory of Acceptance and Use of Technology (UTAUT) model. This research study has adopted the sequential mixed method research in which the exploratory qualitative study is conducted with the qualified practicing auditors across Kerala to identify various Enterprise Resource Planning (ERP) software using in their audit firms. The results of this exploratory study are then empirically tested with the 321 respondents from qualified practicing-auditor accountants in Kerala using Structural Equation Modelling-Partial Least Squares (SEM-PLS). The findings reveal that there is a significant and positive relationship between variables used in the UTAUT model with practicing auditors. Thus, the results suggest that all the four constructs from UTAUT (performance expectancy, effort expectancy, social influence, and facilitating conditions) seem to be predominantly significant factors influencing practicing auditors.

The unified theory of acceptance and use of technology 2 (UTAUT2) is applied and extended to explore the adoption and use of mobile shopping apps in India. This study adds impulsiveness construct to the original model. The data gathered from 328 respondents were evaluated using the partial least square structural equation modelling (PLS-SEM) method. All construct (i.e., performance expectancy, effort expectancy, facilitating conditions, hedonic motivation, habit and impulsiveness), except for social influence and price value were found to significantly relate to behavioural intention to use mobile shopping applications. Behavioural intention, habit and impulsiveness were found to significantly influence use behaviour of mobile shopping apps, except for facilitating conditions. Moreover, significant mediating influences were reported in the study. The findings of the study provide valuable insights and suggestions for mobile marketers and developers of shopping apps to enable their increased adoption and use. Further, the mediating roles of performance expectancy, effort expectancy and habit have been explored in the model.

This thesis evaluates the acceptance of the E-counseling system at the University of Jambi using the Unified Theory of Acceptance and Use of Technology 3 (UTAUT 3) model. This research is based on the problem of mental health levels in students supported by data from WHO and the Ministry of Health. The University of Jambi provides online counseling services to help students solve their problems, but from the pre-research it was found that the level of knowledge and use of E-counseling is still very low. This study aims to implement the UTAUT 3 model which is used to identify factors that influence the acceptance of E-counseling at the University of Jambi. This study took a sample of 100 respondents from all active undergraduate students at the University of Jambi. The analysis technique used in this study is PLS-SEM (Partial Last Structural Equation Modeling) which uses the SmartPLS 4 application in its data calculation. The results obtained from the data calculation show that there are 4 hypotheses that have a significant influence, namely Habit on Use Behavior, Personal Innovativeness on Behavioral Intention, Hedonic Motivation on Behavioral Intention, and Facilitating Conditions on Use Behavior and 8 other hypotheses that do not have a significant influence, namely Performance Expectancy on Behavioral Intention, Effort Expectancy on Behavioral Intention, Social Influence on Behavioral Intention, Facilitating Condition on Behavioral Intention, Price Value on Behavioral Intention, Habit on Behavioral Intention, Personal Innovativeness on Use Behavior and Behavioral Intention on Use Behavior.

Purpose: This study used the UTAUT2 (Unified Theory of Acceptance and Use of Technology 2) paradigm to investigate the factors influencing teachers' adoption of Digital Learning Resources (DLR). In addition to examining variations by gender, frequency of technology use, and academic field, this study assesses the influence of Performance Expectancy (PE), Effort Expectancy (EE), Social Influence (SI), Facilitating Conditions (FC), Hedonic Motivation (HM), Price Value (PV), and Habit (HB) on behavioural intention (BI) and use behaviour (UB). Design/methodology/approach: Data were gathered from 502 teachers in nine taluks in Dakshina Kannada, India using a quantitative study approach and stratified random sampling. Google Forms and offline surveys were used to collect data, and structural equation modelling (SEM) was used for analysis. Group differences were also investigated using one-way analysis of variance (ANOVA) and independent sample t-tests. Findings: The findings showed that teachers’ BIs were highly influenced by PV, HM, SI, PE, and EE. Use behaviour is greatly influenced by behavioural aims and facilitating circumstances. FC did not affect BI, and HB had no discernible impact on BI or UB. Gender-based BI did not differ significantly according to the group analysis; however, the frequency of technology use and field of study did differ significantly. Practical implications: This study highlights the need for customised training, improved digital infrastructure, and targeted professional development to enhance the integration of digital tools in education. Originality/value: This study provides empirical insights into digital adoption patterns among teachers and offers valuable guidance to policymakers and teachers aiming to enhance technology-driven learning environments. Type of the paper: Original Article

This paper examines the impacts of AI-powered assistive technologies (AIATs) on the academic success of higher education university students with visual impairments. As digital learning contexts become progressively more prevalent in higher education institutions, it is critical to understand how these technologies foster the academic success of university students with blindness or low vision. Based on the Unified Theory of Acceptance and Use of Technology (UTAUT) model, the study conducted a quantitative research approach and collected data from 390 visually impaired students who were enrolled in different universities across Saudi Arabia (SA). Employing Partial Least Squares Structural Equation Modeling (PLS-SEM), the paper tested the influences of four UTAUT dimensions—Performance Expectancy (PE), Effort Expectancy (EE), Social Influence (SI), and Facilitating Conditions (FC)—on Academic Performance (AP), while also evaluating the mediating role of Behavioral Intention (BI). The results revealed a significant positive relationship between the implementation of AI-based assistive tools and students’ academic success. Particularly, BI emerged as a key mediator in these intersections. The results indicated that PE (β = 0.137, R2 = 0.745), SI (β = 0.070, R2 = 0.745), and BI (β = 0.792, R2 = 0.745) significantly affected AP. In contrast, EE (β = −0.041, R2 = 0.745) and FC (β = −0.004, R2 = 0.745) did not have a significant effect on AP. Concerning predictors of BI, PE (β = 0.412, R2 = 0.317), SI (β = 0.462, R2 = 0.317), and EE (β = 0.139, R2 = 0.317) were all positively associated with BI. However, FC had a significant negative association with BI (β = −0.194, R2 = 0.317). Additionally, the analysis revealed that EE, SI, and PE can all indirectly enhance Academic Performance by influencing BI. The findings provide practical insights for higher education policymakers, higher education administrators, and AI designers, emphasizing the need to improve the accessibility and usability of sustainable and long-term assistive technologies to better accommodate learners with visual impairments in higher education contexts.

The rapid expansion of online ride-hailing services has transformed urban mobility; however, sustaining user engagement remains a major challenge due to the interplay of psychological and technical factors. Despite widespread adoption, the determinants influencing users’ continued use of such applications remain inconsistent and not fully understood. Therefore, this study examines the effects of Customer Satisfaction (CS), Social Influence (SI), and Facilitating Conditions (FC) on Use Behavior (UB) of online transportation applications, with Behavioral Intention (BI) as a mediating variable. The research was conducted in Surabaya with 150 active users of online ride-hailing services, and data were analyzed using Structural Equation Modeling–Partial Least Squares (SEM-PLS). The findings indicate that FC significantly affects both BI and UB, while CS and SI have significant positive effects on BI but not directly on UB. Moreover, BI is identified as the strongest predictor of UB and acts as a significant mediator in the relationships CS → BI → UB, SI → BI → UB, and FC → BI → UB. These results highlight the central role of intention in linking psychological and technical factors to actual use behavior. The study suggests that service providers enhance customer satisfaction, utilize social influence, and strengthen facilitating conditions to sustain user engagement.

The unified theory of acceptance and use of technology 2 (UTAUT2) is applied and extended to explore the adoption and use of mobile shopping apps in India. This study adds impulsiveness construct to the original model. The data gathered from 328 respondents were evaluated using the partial least square structural equation modelling (PLS-SEM) method. All construct (i.e., performance expectancy, effort expectancy, facilitating conditions, hedonic motivation, habit and impulsiveness), except for social influence and price value were found to significantly relate to behavioural intention to use mobile shopping applications. Behavioural intention, habit and impulsiveness were found to significantly influence use behaviour of mobile shopping apps, except for facilitating conditions. Moreover, significant mediating influences were reported in the study. The findings of the study provide valuable insights and suggestions for mobile marketers and developers of shopping apps to enable their increased adoption and use. Further, the mediating roles of performance expectancy, effort expectancy and habit have been explored in the model.

Despite the increasing use of generative artificial intelligence (GenAI) tools among students, limited research has examined the underlying mechanisms guiding their adoption in English as a Foreign Language (EFL) education. Drawing on the unified theory of acceptance and use of technology 2 (UTAUT2) and self-determination theory (SDT), this study examines the factors shaping Indonesian EFL students’ intention and actual use of GenAI for English learning. Using a cross-sectional survey design, data were collected using an online questionnaire from 462 EFL students at three private universities in Indonesia and analyzed with the partial least squares structural equation modeling (PLS-SEM) using SmartPLS 4. The results indicated that performance expectancy, effort expectancy, social influence, facilitating conditions, hedonic motivation, habit, autonomy, and relatedness significantly impacted EFL students’ intention to adopt GenAI for English learning. While competence did not significantly influence behavioral intention, both the SDT components (autonomy, competence, and relatedness) and behavioral intention were predictors of actual usage. The integrated framework explained a high proportion of variance (R² = 83.1% for behavioral intention; R² = 77.1% for actual use). These insights advance understanding of the technological and motivational determinants of GenAI adoption in EFL education and offer evidence-based direction for designing effective, equitable, and ethically responsible AI-supported English learning practices.

This study aims to analyze the effect of product quality, promotion, brand image, and celebrity endorsers on purchasing decisions using the Structural Equation Modeling-Partial Least Squares (SEM-PLS) approach. The population of this study were consumers who had purchased Garnier products, with a sample of 144 respondents selected using purposive sampling techniques. Primary data were collected through questionnaires and analyzed using the SEM-PLS method with SmartPLS software. The analysis results show that: 1) Product quality has a positive and significant effect on purchasing decisions. 2) Promotion does not have a significant effect on purchasing decisions. 3) Brand image has a positive and significant effect on purchasing decisions. 4) Celebrity endorsers have a positive and significant effect on purchasing decisions. These findings indicate that product quality, brand image, and celebrity endorsers are the main factors influencing purchasing decisions, while promotion does not have a significant impact. The results of this study can be a guide for companies in designing more effective marketing strategies that are by consumer preferences. Penelitian ini bertujuan untuk menganalisis pengaruh kualitas produk, promosi, brand image, dan celebrity endorser terhadap keputusan pembelian menggunakan pendekatan Structural Equation Modeling-Partial Least Squares (SEM-PLS). Populasi penelitian ini adalah konsumen yang telah membeli produk Garnier, dengan sampel sebanyak 144 responden yang dipilih menggunakan teknik purposive sampling. Data primer dikumpulkan melalui kuesioner dan dianalisis menggunakan metode SEM-PLS dengan software SmartPLS. Hasil analisis menunjukkan bahwa: 1) Kualitas produk berpengaruh positif dan signifikan terhadap keputusan pembelian. 2) Promosi tidak berpengaruh signifikan terhadap keputusan pembelian. 3) Brand image berpengaruh positif dan signifikan terhadap keputusan pembelian. 4) Celebrity endorser berpengaruh positif dan signifikan terhadap keputusan pembelian. Temuan ini menunjukkan bahwa kualitas produk, brand image, dan celebrity endorser menjadi faktor utama dalam mempengaruhi keputusan pembelian, sedangkan promosi tidak memiliki dampak yang signifikan. Hasil penelitian ini dapat menjadi panduan bagi perusahaan dalam merancang strategi pemasaran yang lebih efektif dan sesuai dengan preferensi konsumen.

This study aims to analyze behavioral intention and use behavior in using fintech investment management through the Unified Theory of Acceptance and Use of Technology 2 (UTAUT 2) model, namely performance expectancy, effort expectancy, social influences, facilitating conditions, hedonic motivation, price values and habits. This study used quantitative approach. The population in this study were all Generation Z in Bali which determine using convenience sampling method. The data analysis technique in this research is multiple regression using Smart-pls software. The results of the analysis provide evidence that performance expectancy, social influences, facilitating conditions, hedonic motivation and habits had positive effect on behavioral intention in using fintech investment management. In addition, behavioral intention had a positive effect on the use behavior of using fintech investment management.

PurposeAlthough wearable health-monitoring technology (WHMT) has become a stimulus for public health, women’s acceptance rate of this technology appears to be low. Thus, this study intends to investigate the factors affecting women’s adoption of WHMT.Design/methodology/approachThe unified theory of acceptance and use of technology–2 model has been used in this study as a research framework that has been extended to include lifestyle and attitude. The proposed extended framework is validated using primary data (n = 314) collected from female respondents using a structured questionnaire; the partial least square-based structural equation modeling technique is subsequently used to test the proposed hypothesis.FindingsThe results show that effort expectancy, social influence, price value, habit, attitude and lifestyle have significant positive effects on women’s behavioral intention to use WHMT and accelerate actual usage behavior. Notably, effort expectancy and habit exhibit the largest impact on behavioral intention. However, performance expectancy, facilitating conditions and hedonic motivation are not significantly associated with behavioral intentions.Practical implicationsThe findings of this study are important for healthcare practitioners and service providers to comprehensively understand the factors that affect women’s behavioral intentions in line with their actual usage behavior. This insight will help policymakers design viable strategies regarding WHMT to promote its sustainable usage in least developed countries.Originality/valueThis study contributes novelty by using an extended model that links women’s attitudes and lifestyles to their adoption of WHMT. This study also fills the gaps in the existing literature on women’s behavioral intentions in the context of WHMT by showing novel associations in the domain of WHMT uptake.

Purpose: This study explores online hotel booking intentions among Bangladeshi tourists. The Unified Theory of Acceptance and Use of Technology 2 (UTAUT2), the most widely used and cited IT adoption model, was employed in this investigation as the theoretical framework for analyzing customers' online hotel booking intentions. In the UTAUT2 paradigm, this work introduces three new concepts called service affordability, online reviews, and website trust. Methods: The study targeted individuals in Bangladesh with prior experience in online hotel booking. Data were gathered from 400 participants via a self-administered online questionnaire in Google Forms, using convenience sampling, and responses were analyzed using partial least squares structural equation modeling (PLS-SEM). Results: According to the findings, performance expectancy, social influence, habit, price value, service affordability, and website trust are the most critical determinants of behavioral intention to book hotels online. In contrast, online reviews, effort expectancy, facilitating conditions, and hedonic motivation do not affect customers' intention to book hotels online. Implications: This study provides practical insights for legislators, marketers, and hospitality managers to improve users' trust, perceived affordability, and overall acceptance of online hotel booking platforms. The findings facilitate the formulation of more user-centric digital strategies in the hospitality sector by identifying key variables related to booking intention and usage. Originality: This study represents a pioneering effort in Bangladesh by extending the UTAUT2 model to examine online hotel booking behavior. It introduces additional constructs, such as service affordability, online reviews, and website trust, thereby offering a more comprehensive framework for understanding technology adoption in emerging digital tourism markets.

This study aims to examine the key factors influencing passengers’ adoption of electronic ticketing (e-ticketing) systems in public transportation in an emerging economy. To achieve this objective, the Unified Theory of Acceptance and Use of Technology 2 (UTAUT2) framework is extended by incorporating three additional variables: return and exchange, technological anxiety, and perceived risk to capture contextual and psychological influences more comprehensively. Partial Least Squares Structural Equation Modeling (PLS-SEM) was employed to analyze data from 392 participants. The findings reveal that performance expectancy, effort expectancy, social influence, hedonic motivation, habit, facilitating conditions, price value, return and exchange, and perceived risk have significant effects on passengers’ behavioral intention to adopt e-ticketing. In contrast, technological anxiety does not exhibit a considerable influence. These results underscore the importance of incorporating extended UTAUT2 variables to gain a more comprehensive understanding of adoption behavior. It provides actionable insights for transport operators, policymakers, and platform developers seeking to enhance user engagement and facilitate digital transformation in public transport services.