Understanding consumers' intentions to purchase smart clothing using PLS-SEM and fsQCA.

Purpose: This study explores the impact of augmented reality (AR) technology on purchase intention in Indonesia. By integrating the AR experience framework with an extended Technology Acceptance Model (TAM), the research examines how five dimensions of the AR experience—sensory experience (SE), emotional experience (EE), thinking experience (TE), action experience (AE), and related experience (RE)—affect perceived ease of use (PEOU) and perceived usefulness (PU), which subsequently influence purchase intention (PI), with attitudinal ambivalence (AA) as a mediating factor.Method: A quantitative, cross-sectional survey was conducted with 300 Indonesian respondents, aged 18 to 60, who were recent users of the AR Sephora Virtual Artist. Data were collected through an online questionnaire and analyzed using Partial Least Squares Structural Equation Modeling (PLS-SEM).Result: Findings reveal that the dimensions of the AR experience positively impact PEOU and PU, which subsequently negatively influence AA. PU also directly fosters positive PI, while PEOU does not. Importantly, AA negatively affects PI, underscoring its critical role in consumer decision-making.Practical Implications for Economic Growth and Development: This research offers valuable insights for retailers to optimize AR implementation, thereby enhancing consumer engagement and driving purchase intention. Improving AR usability and effectiveness can reduce consumer uncertainty, strengthen market adoption, and advance digital commerce in the beauty industry.Originality/Value: This study uniquely integrates AA into existing AR adoption models and combines the AR experience framework with an extended TAM, providing novel theoretical contributions to AR in retail and insights into consumer behavior.

The aim of this research is to suggest a unified model that integrates the task fit technology (TTF) model, technology acceptance model (TAM), IoT concerns, and social incentive to examine behavioural intentions to use the Internet of Things (IoT) applications in the healthcare context. A sample of 257 respondents in Jordan who are potential users of IoT participated in this research. Structural equation modelling (SEM) applied via AMOS 25.0 package is carried out to examine the study hypotheses. The findings illustrate that the theoretical model which integrated the TTF model for utility/advantage and TAM for the technology acceptance offers a better comprehensive insight of users’ behaviour relevant to the study setting: (1) perceived usefulness (PU) and attitude (ATT) are significant to the behavioural intentions to use IoT; (2) PU has a critical mediation impact on the relationship between: perceived ease of use (PEoU), the TTF construct, security and privacy (SP), and social influences (SI) and behavioural intentions; (3) PEoU, TTF, and SI are revealed to play critical roles to predict behavioural intentions; (4) ITF, TTF, and SP affect the PEoU; (5) unexpectedly, PEoU and SI have no significant impact on ATT, and ITF and SP do not influence PU. The findings have theoretical and practical implications for IoT researchers, developers, and policymakers.KeywordsIoT acceptanceHealthcareJordanTAMTTFIoT concernsSocial influenceBehavioural intention

In higher education, PLS-SEM supports the study of multidimensional relationships, such as technology acceptance behavior and educational innovation effectiveness. PLS-SEM is a powerful analytical tool used to test complex theoretical models, especially in cases where data are limited or non-normally distributed. TAM provides a theoretical foundation for usefulness and ease of use, while IRT emphasizes psychological and functional barriers to innovation. Data were collected from 420 lecturers at Vietnamese higher education institutions on the acceptance of using artificial intelligence (AI) in higher education to test the integrated model of TAM and IRT. The results show that perceived usefulness (PU) and perceived ease of use (PEU) positively affect attitudes and intentions to adopt AI. In contrast, IRT barriers such as complexity of use, value, risk, and tradition have adverse effects, limiting lecturers’ application of AI in teaching. The research results contribute to the expansion of PLS-SEM applications in higher education and provide recommendations for managers to promote the acceptance of AI technology and reduce barriers to innovation in this field.

This study investigates the key determinants influencing the adoption of Artificial Intelligence (AI) by Small and Medium Enterprises (SMEs) in the e-commerce sector and examines its impact on marketing performance. The research integrates the Technology–Organization–Environment (TOE) framework and the Technology Acceptance Model (TAM) to explain the relationships among technological readiness, organizational support, environmental pressure, perceived usefulness (PU), perceived ease of use (PEOU), and AI adoption level. A quantitative approach employing Partial Least Squares–Structural Equation Modeling (PLS-SEM) was conducted on 155 e-commerce SMEs operating in Jakarta, Indonesia. Empirical results reveal that technology, organization, and environment significantly affect perceived usefulness, which in turn strongly drives AI adoption. Perceived usefulness is identified as the most powerful determinant of adoption, whereas perceived ease of use exerts an indirect influence via usefulness perception. Furthermore, AI adoption has a positive and significant effect on marketing performance, particularly in enhancing digital campaign effectiveness, product innovation, and customer loyalty. The findings emphasize that internal readiness and external competitive pressures jointly foster AI-driven digital transformation within SMEs. The study provides both theoretical validation of the TOE–TAM integration and practical guidance for policymakers and business owners to design effective, ethical, and sustainable AI adoption strategies.

Purpose This study examines the influence of disciplinary differences and applied practices between architecture and engineering on students’ cognitive and affective responses to online education systems by employing the Technology Acceptance Model (TAM). Design/methodology/approach A questionnaire addressing the aimed TAM constructs is conducted with 483 architecture and engineering students. Partial least square structural equation modeling (PLS-SEM) is used to test the direct and indirect relationships between students’ attitudes towards using (ATU), perceived usefulness (PU), perceived ease of use (PEOU) and system quality (SQ) based on disciplines’ diverse learning methods and approaches. Findings This research shows that online education systems’ quality (SQ) influences students’ attitudes toward using (ATU) directly and indirectly. The strongest relationship is observed between system quality (SQ) and perceived ease of use (PEOU), proving that online education adoption is strongly linked to the environment’s quality where applied practices are conducted. Architecture students’ attitude is significantly shaped by the system’s visual and interactional attributes parallel to constructivist and experiential learning. Oriented towards multidimensional problem-solving, engineering students’ attitude is mainly influenced by their efficiency and productivity. Originality/value This research contributes to the knowledge of technology acceptance in online education by exploring students’ attitudes and the less-examined differences between architecture and engineering disciplines. Emphasizing the impact of system quality on online education concerning applied practices, the study also underlines the possible shortcomings of the generalization of approaches. The findings offer insights into tailoring online education more inclusively and effectively by considering discipline-specific applied learning methods.

PurposeThis study aims to propose guidelines for the joint use of partial least squares structural equation modeling (PLS-SEM) and fuzzy-set qualitative comparative analysis (fsQCA) to combine symmetric and asymmetric perspectives in model evaluation, in the hospitality and tourism field.Design/methodology/approachThis study discusses PLS-SEM as a symmetric approach and fsQCA as an asymmetric approach to analyze structural and configurational models. It presents guidelines to conduct an fsQCA based on latent construct scores drawn from PLS-SEM, to assess how configurations of exogenous constructs produce a specific outcome in an endogenous construct.FindingsThis research highlights the advantages of combining PLS-SEM and fsQCA to analyze the causal effects of antecedents (i.e., exogenous constructs) on outcomes (i.e., endogenous constructs). The construct scores extracted from the PLS-SEM analysis of a nomological network of constructs provide accurate input for performing fsQCA to identify the sufficient configurations required to predict the outcome(s). Complementing the assessment of the model’s explanatory and predictive power, the fsQCA generates more fine-grained insights into variable relationships, thereby offering the means to reach better managerial conclusions.Originality/valueThe application of PLS-SEM and fsQCA as separate prediction-oriented methods has increased notably in recent years. However, in the absence of clear guidelines, studies applied the methods inconsistently, giving researchers little direction on how to best apply PLS-SEM and fsQCA in tandem. To address this concern, this study provides guidelines for the joint use of PLS-SEM and fsQCA.

This study examines the intention to adopt digital banking in Saudi Arabia by integrating the Technology Acceptance Model (TAM) and the Theory of Planned Behavior (TPB). It includes Perceived Web Security (PWS) and Age as moderators, addressing trust and security perceptions across user segments in emerging markets. Data were collected from 353 digital banking users in Saudi Arabia using a cross-sectional quantitative design. The model was tested via Partial Least Squares Structural Equation Modeling (PLS-SEM), assessing measurement validity, path significance, moderation, and mediation effects. Predictive accuracy was evaluated with in-sample (R²) and out-of-sample (Q², PLS-Predict) indicators. The results confirmed the significance of core TAM variables—Perceived Ease of Use (PEU), Perceived Usefulness (PU), and Attitude Toward Use (ATU)—on Behavioral Intention (BI). Attitude was a strong predictor of BI, but Subjective Norms (SN) and Perceived Behavioral Control (PBC) were not significant. PWS moderated the ATU–BI relationship, enhancing intention under high security perception, but Age's dual-moderation effect was unsupported. Sequential mediation analysis validated that PEU and PU influence BI indirectly via ATU. This study enhances digital adoption research through a validated dual-level moderation model combining security perception and age. It refines TAM-TPB integration and offers practical insights for creating secure, user-centered digital banking systems tailored to specific cultures.

This study examines how Generation Z's desire to utilize the myBCA mobile application is affected by perceived utility (PU) and perceived ease of use (PEOU) using trust as a mediating variable. To precisely capture behavioral patterns in digital financial services, the study model expands about the Model of Technology Acceptance. Partial Least Squares Structural Equation Modeling (PLS-SEM) was used to examine data from 70 respondents using a quantitative cross-sectional survey approach. The structural model showed high fit and strong predictive performance (Q square Intention to Use: 0.593). The results indicate that PU significantly and positively influences both Trust and Intention to Use. Conversely, PEOU significantly influences Trust, but doesn't directly impact the intention to use. The mediation analysis reveals that Trust fully mediates the PEOU-Intention to Use relationship, while partially mediating the relationship between PU and Intention to Use. These findings firmly suggest that Trust is a central psychological driver, transforming the perception of ease into actual adoption intention and substantially strengthening the impact of usefulness. The outcomes provide deep practical insights for financial institutions, highlighting the strategic importance of consistently strengthening user trust to enhance loyalty and adoption rates in the quickly changing digital banking market.

This study investigates the factors influencing the acceptance of e-training among faculty staff at Sebha University using the extended Technology Acceptance Model (TAM2). A total of 74 responses were collected via Google Forms concerning subjective norm, image, job relevance, output quality, result demonstrability, perceived ease of use (PEOU), perceived usefulness (PU), experience, voluntariness, and intention to use. Measurement and structural models were evaluated using Partial Least Squares Structural Equation Modelling (PLS-SEM) with SmartPLS 4. Reliability, internal consistency, and validity were confirmed, with Cronbach’s α ranging from 0.776 to 0.929 and AVE values from 0.688 to 0.876, indicating convergent validity. PEOU was found to predict PU, and both PEOU and PU predicted intention to use, albeit with weaker support than the model suggested (β = 0.441, p < 0.001; β = 0.284, p = 0.046; β = 0.314, p = 0.033). No significant effects were identified for subjective norm, image, job relevance, output quality, or result demonstrability. Moderation analysis revealed that experience and voluntariness had no effect on the impact of subjective norm on PU or behavioural intention (all p > 0.05; all f² < 0.01). The model accounted for 66.5% of the variance in PU and 56.6% in intention, highlighting the importance of perceived ease of use and usefulness in the adoption of e-training.

The COVID-19 pandemic has caused constraints on education that takes place face-to-face; thus, the learning process has been conducted online. With this emergence, an application-based learning tool called a Learning Management System (LMS) was created to cater to the requirements of distant students. Therefore, this study explores how SPACE-LMS is used in the Teacher Professional Education Program (TPEP) and how it interacts with the Technology Acceptance Model (TAM) and self-efficacy. This study collected data from TPEP participants in the province of West Sumatra-Indonesia from the 2022 cohort, and 245 individuals actively participated. As the quantitative method, Partial Least Square-Structural Equation Modeling (PLS-SEM) analysis with SmartPLS software was used to test and predict the conceptual model. The empirical findings demonstrate that the readiness of adopting SPACE influences perceived ease of use (PEU) and perceived usefulness (PU). Self-efficacy (SE) influences PEU and intention to use (ITU); PEU influences PU; PEU influences attitudes toward users (ATT); and PU influences ATT. Interestingly, PU had no impact on the ITU. The desire of TPEP students to use the SPACE-LMS is also influenced by their sense of self-efficacy. Thus, this study has both theoretical and practical implications.

Purpose This study examines digital hoarding behavior (DHB) among short video platform (SVP) users to reduce unnecessary accumulation, enhance information management efficiency and support SVP sustainability. Design/methodology/approach Guided by the cognition–affect–conation (C-A-C) framework, we analyzed 402 valid responses using partial least squares structural equation modeling (PLS-SEM) and fuzzy-set qualitative comparative analysis (fsQCA). Findings PLS-SEM results show that perceived usefulness (PU), subjective norm (SN) and information overload (IO) significantly increase fear of missing out (FoMO), while PU, time pressure (TP) and SN enhance emotional attachment (EA). Both FoMO and EA promote DHB. fsQCA further reveals three distinct pathways leading to DHB, highlighting multifactorial interactions and configurational patterns. Practical implications This study provides actionable strategies for SVP managers, including optimizing recommendation algorithms, enhancing users’ digital information literacy and implementing intelligent content management tools. Additionally, campaigns and tailored interventions addressing offline and online behavioral differences can promote healthy digital habits, improve information management and reduce unnecessary DHB. Originality/value This study is the first to apply the C-A-C framework to DHB in SVPs, which feature high interactivity and large-scale user engagement. By integrating PLS-SEM and fsQCA, it systematically uncovers the cognitive and emotional mechanisms of DHB, emphasizing its multidimensional nature. The findings contribute to the theoretical understanding of user behavior in high-speed information environments and offer practical insights for fostering SVP sustainability.

Research in international business and management (IM) is highly complex, contextual, and spans various subfields and related theoretical lenses. These characteristics pose research challenges that require utilizing sophisticated research designs and methodologies. This paper and our focused issue on ‘The use of partial least squares structural equation modeling (PLS-SEM) and complementary methods in IM research’ further clarify whether and how researchers using PLS-SEM can address (some of) the challenges in IM research. We explain how researchers can benefit from the (advanced) capabilities that PLS-SEM offers; either as a stand-alone method or in triangulation efforts that leverage complementary approaches. In addition, we review the IM literature for PLS-SEM applications and evaluate whether and how researchers are already using these approaches. We identify some room for improvement when it comes to the application of both more advanced PLS-SEM capabilities and the triangulation of PLS-SEM with qualitative data analyses, and techniques such as fuzzy set qualitative comparative analyses and necessary condition analyses. For better guidance, we refer to PLS-SEM application examples in which the methodological advances are used.

PurposeThis article aims to study the determinants of e-learning acceptability by university students based on their experiences with distance learning during the coronavirus disease 2019 (COVID-19) pandemic.Design/methodology/approachA questionnaire was used to collect data from 448 students enrolled in a Moroccan business school's fourth and fifth years. The technology acceptance model (TAM) was the primary framework used for this analysis, into which variables from the expectation confirmation model were injected, namely facilitating conditions, social influence, expectation confirmation and satisfaction. The proposed conceptual model was tested and evaluated using the partial least squares structural equation modeling (PLS-SEM) technique. Then the authors have offered an in-depth analysis by employing the importance-performance map analysis (IPMA) approach.FindingsThe investigation suggested that the proposed measurement scale effectively assesses the factors impacting students' decision to continue using e-learning in the future. This study’s results show that e-learning acceptance depends significantly on the students' satisfaction, perceived ease of use (PEU) and perceived usefulness (PU). In contrast, the facilitating conditions are not a valid measurement scale to determine students' attitudes toward e-learning.Originality/valueThis is one of the first studies in the Moroccan context to evaluate e-learning acceptability by management students after COVID-19 using a unique research model.

<p><em><em>This study investigates the determinants of online Zakat payment adoption in Indonesia by extending the Technology Acceptance Model (TAM) through the integration of Trust. It examines the effects of Perceived Usefulness (PU), Perceived Ease of Use (PEoU), and Trust on Attitude, as well as the influence of Attitude on Behavioral Intention. A quantitative approach using Partial Least Squares-Structural Equation Modeling (PLS-SEM) was employed, based on survey responses from 350 participants. The empirical findings show that all hypothesized relationships are significant (p < 0.05). Trust (t = 7.060), PU (t = 4.802), and PEoU (t = 4.222) each have significant positive effects on Attitude, while Attitude strongly influences Behavioral Intention (t = 7.546). The extended model demonstrates moderate predictive relevance for Attitude (R² = 51.9%). Among the antecedents, Trust has the largest effect size (f² = 0.174), indicating its central role in shaping attitudes toward online Zakat payment. These results validate the extension of TAM with Trust in the context of Islamic fintech adoption in Indonesia. The findings highlight the importance of security and transparency, suggesting that Zakat Management Organizations (ZMOs) should strengthen data protection systems and provide transparent reporting to foster positive user attitudes and enhance adoption intentions.</em></em></p>

This study aims to examine the effect of perceived usefulness (PU), perceived ease of use (PEU), trust (TR), subjective norm (SN), and attitude (AT) on customer's Intention to Adopt Internet Banking (IAIB) at Islamic banks and conventional banks before and during the Covid-19 pandemic in Indonesia. The research model is based on the Theory of Planned Behavior (TPB) and the Technology Acceptance Model (TAM). This study involves 213 respondents for Islamic banks and 410 respondents for conventional banks from 25 provinces in Indonesia. Data was analyzed using partial least square (PLS) regression with the Structural Equation Model (SEM) method. The result of data analysis confirms several hypotheses taken from the literature. The results before the Covid-19 pandemic showed that AT and SN influence IAIB in Islamic banks. Whereas in conventional banks, AT, PU, SN, and TR influence IAIB. While during the Covid-19 pandemic, it shows that the AT, PU, IB, SN, and customer TR influence IAIB in Islamic banks and conventional banks. From the analysis, it was found that the PEU variable did not have a significant effect on the intention of customers of Islamic banks and conventional banks to use Internet banking.