Digital innovation in education: a study of e-procurement technology acceptance models

Purpose With the pandemic reshaping healthcare delivery, telemedicine has emerged as a vital solution for overcoming access barriers, particularly in resource-constrained settings. Hence, this study explores the key drivers behind the sustained use of telemedicine services in low-income countries during the post-pandemic period. Design/methodology/approach Using a quantitative research approach and purposive sampling technique, 273 valid responses were gathered from participants in Bangladesh. A comparative analysis utilizing partial least squares structural equation modeling (PLS-SEM) and fuzzy-set qualitative comparative analysis (fsQCA) were conducted to ensure greater accuracy. Findings The PLS-SEM analysis revealed that expectation confirmation and perceived ease of use positively influence satisfaction. Similarly, perceived usefulness and perceived ease of use directly impact Attitude toward telemedicine services. However, perceived usefulness and perceived security were not significantly associated with satisfaction and attitude toward telemedicine services, respectively. The findings highlight that user satisfaction drives continuance use intention for telemedicine services, but only when it also cultivates a positive attitude toward telemedicine services. While the PLS-SEM findings indicate that perceived usefulness has no significant relationship with satisfaction and perceived security is not significantly associated with attitude toward telemedicine services, the fsQCA results offer a different perspective. fsQCA reveals that perceived usefulness retains a significant association with satisfaction and that perceived security, regardless of whether its effect is high or low, is equally effective in contributing to the intention for continuous telemedicine use. These findings underscore fsQCA’s ability to provide deeper insights into the complex causal relationships among the antecedents. Practical implications The findings provide valuable insights for hospitals, doctors and telemedicine providers on retaining existing users. Additionally, governments can leverage this information to address healthcare disparities between urban and rural areas. The study also identifies strategies to reduce costs and improve the efficiency of healthcare services. Originality/value This study advances telemedicine research by employing the extended technology continuance theory (ETCT) alongside a hybrid analytical approach that integrates PLS-SEM and fsQCA. It highlights that telemedicine organizations can boost patient confidence and encourage continued use by enhancing satisfaction and cultivating a positive user attitude. The innovative use of ETCT and the combined methodologies provide a comprehensive analysis, offering actionable strategies to retain telemedicine users in low-income countries during the post-pandemic period.

Aim/Purpose: This research aims to test the continued use of an AI platform through an extended Expectation Confirmation Model (ECM). Background: The paper addresses the issues of user trust and satisfaction in the context of an AI platform in education by employing the ECM to analyze how system quality, information quality, and user satisfaction influence continued use intentions among respondents from various educational institutions in Indonesia. Methodology: We utilized partial least squares structural equation modeling (PLS-SEM) to analyze data from 390 respondents. The analysis followed a two-step approach, focusing on measurement and structural models. The scales for system quality, information quality, confirmation, satisfaction, and continued use intention were adapted from established measures to fit the context of sustainable AI use. Contribution: The study identifies key factors such as system quality, information quality, satisfaction, and trust that influence continued use intentions. The findings show that satisfaction predicts trust more significantly than the reverse, suggesting that enhancing user satisfaction is key to fostering trust and encouraging ongoing engagement with an AI platform. Findings: Demographic analysis revealed a diverse sample, supporting the generalizability of our results. User satisfaction is identified as a stronger predictor of trust than vice versa, indicating that satisfied users are more likely to trust the AI platform, which is essential for continued use. Both system quality and information quality positively influence user satisfaction, which in turn leads to greater intentions to continue using the platform. Trust serves as a significant mediator between confirmation and continued use intention. Although confirmation itself does not directly impact satisfaction, it influences satisfaction through trust, ultimately affecting users’ intentions to continue engaging with the platform. Recommendations for Practitioners: Practitioners and policymakers should prioritize strategies that enhance user satisfaction with the AI platform, as this has been shown to significantly influence trust and intentions for continued use. Such strategies may include improving system usability, providing responsive customer support, and ensuring the relevance of AI outputs. Recommendation for Researchers: Future studies should investigate additional factors influencing user behavior with the AI platform, such as perceived ease of use, user demographics, and contextual variables in specific educational settings. Impact on Society: The findings of this paper have broader implications for integrating AI platforms across sectors, especially in education. By highlighting the importance of user satisfaction and trust, the research underscores the need for ethical AI development that prioritizes user experience. This can lead to more effective AI applications that enhance learning outcomes, promote equitable access to technology, and foster a more informed public discourse about AI’s role in society. Future Research: Future research should investigate the role of user experience by examining how various elements, such as interface design and personalization, influence satisfaction and trust in AI platforms. Additionally, understanding cultural influences is crucial, as it can reveal how cultural differences affect user perceptions and acceptance of AI platforms, particularly in diverse educational contexts. Lastly, evaluating the long-term effects of AI integration in education is essential, as this can provide insights into its impact on student engagement, learning outcomes, and overall satisfaction with educational technologies.

The adoption of multi-channel strategies by retailers, encompassing both online and offline modalities, has fundamentally transformed consumer shopping behaviors, resulting in a significant increase in mobile shopping. Nonetheless, the long-term success of mobile shopping apps is heavily dependent on consumers’ continuous use. Regrettably, the existing studies on this area remain vague and require further exploration. This study aims to close this gap by examining Malaysian consumers’ continuance intention and continuance use of mobile shopping through the lens of ISSM in the context of mobile shopping apps. We utilised a quantitative approach and successfully collected 369 responses from Klang Valley, using purposive sampling techniques. The predictive hypotheses developed were validated using Partial Least Square – Structural Equation Modelling (PLS-SEM) and were further supplemented with Necessary Condition Analysis (NCA) to determine must-have factors based on necessary logic. The PLS-SEM results confirmed the association between continuance intention and continuance use. The findings reveal that service quality and system quality are associated with satisfaction, but not information quality. Additionally, service quality, system quality, and information quality, together with satisfaction, trust and incentive have a positive significant influence on Malaysians’ mobile shopping app continuance intention. However, the NCA results indicate that system quality is the sole must-have factor that contributes to satisfaction. Meanwhile, service quality, system quality, information quality, satisfaction, trust, and incentive are the must-have predictors for mobile shopping app continuance intention. The study sheds light on previously unexplored aspects namely continuance intention and continuance use, within the framework of the ISSM in the context of mobile shopping. By doing so, it offers more refined and actionable insights to improve consumer experience and foster sustained engagement with mobile shopping apps. Simultaneously, it contributes to the advancement of knowledge regarding the foundational constructs and their interconnectedness, thereby enhancing theoretical development in this domain.

Gamification within eHealth services can increase eHealth adoption. However, little is known about factors affecting adoption of gamified eHealth among older adults. In this study, we sought to explain the (continued) use of a gamified eHealth service among older adults (55+). Participants used a gamified eHealth service, focusing on falls prevention, for 4weeks and completed a post-test questionnaire based on the Technology Acceptance Model. We used Partial Least Squares Structural Equation Modeling to analyse our data. Seventy-two older adults participated with a mean age of 65.1years (SD = 7.0). Our results show that first, perceived ease of use affected use of the service (use duration: β = 0.303, R2 = 0.130, and use frequency: β = 0.304, R2 = 0.107). Second, perceived usefulness affected the intention to continue using the service (β = 0.754, R2 = 0.640). Third, use of the service did not predict the intention to continue using it. Furthermore, enjoyment affected perceived usefulness (β = 0.783, R2 = 0.563) and aesthetics affected perceived ease of use (β = 0.634, R2 = 0.652). This study refutes the expected relation between use and intention to continue use a gamified eHealth service. Additionally, we learned that using theoretical approaches focusing on technology acceptance, are not suitable for explaining (continued) use of gamified eHealth services.

The acceptance of Educational Data Mining (EDM) technology is on the rise due to, its ability to extract new knowledge from large amounts of students' data. This knowledge is important for educational stakeholders, such as policy makers, educators, and students themselves to enhance efficiency and achievements. However, previous studies on EDM have focused more on technical aspects, such as evaluating methods and techniques, while ignoring the end-users' acceptance of the technology. Realising its importance, this study has analysed the determinants that could influence the acceptance of EDM technology, particularly among undergraduate students since they are the most affected by the technology. For this reason, 11 hypotheses have been formulated based on determinants of technology readiness index (TRI) and technology acceptance model 3 (TAM3), which could render an in-depth insight regarding EDM acceptance. A survey was conducted on 211 undergraduate students from six public universities in Malaysia for a period of 6 months (May to October 2014) using questionnaires as the instrument to collect data to test the hypothesised relationships. The partial least squares structural equation modeling (PLS-SEM) approach was used to analyse the proposed acceptance model, which was run using SmartPLS, version 3 software. The findings have revealed that `relevance for analysing', `self-efficacy', `facilitating conditions', `perceived usefulness', `perceived ease of use', `optimism' and `discomfort' have influenced the acceptance of EDM technology among undergraduate students.

Aim/Purpose: This study investigated a model of mobile esports acceptance among urban citizens based on an extended Technology Acceptance Model (TAM). Background: Currently, esports are increasingly popular and in demand by the public. Supported by the widespread development of mobile devices, it has become an interactive market trend to play games in a new model, mobile esports. Methodology: This study collected data from 400 respondents and analyzed it using partial least squares-structural equation modeling (PLS-SEM). Contribution: This study addresses two research gaps. The first gap is limited esports information systems studies, particularly in mobile esports acceptance studies. The second gap is limited exploration of external variables in online gaming acceptance studies. Thus, this study proposed a TAM extended model by integrating the TAM native variables with other external variables such as visual appeal, enjoyment, social interaction, and competition to explore mobile esports acceptance by urban citizens. Findings: Nine hypotheses were accepted, and four were rejected. The visual appeal did not affect the acceptance. Meanwhile, social interaction and enjoyment significantly affected both perceived ease of use and usefulness. However, perceived ease of use surprisingly had an insignificant effect on attitude toward using mobile esports. Moreover, competition significantly affected the acceptance, particularly on perceived usefulness. Recommendations for Practitioners: Fresh and innovative features, such as new game items or themes, should be frequently introduced to enhance players’ continued enjoyment. Moreover, mobile esports providers should offer a solid platform to excite players’ interactions to increase the likelihood that users feel content. On the other hand, the national sports ministry/agency or responsible authorities should organize many esports competitions, big or small, to search for new talents. Recommendation for Researchers: Visual appeal in this study did not influence the perceived ease of use or usefulness. However, it could affect enjoyment. Thus, it would be worth revisiting the relationship between visual appeal and enjoyment. At the same time, perceived ease of use is a strong driver for the continued use of most online games, but not in this study. It could indicate significant differences between mobile esports and typical online games, one of which is the different purposes. Users might play online games for recreational intention, but players would use mobile esports to compete, win, or even get monetary rewards. Therefore, although users might find mobile esports challenging and hard to use, they tend to keep playing it. Thus, monetary rewards could be considered a determinant of the continuation of use. Impact on Society: Nowadays, users are being paid for playing games. It also would be an excel-lent job if they become professional esports athletes. This study investigated factors that could affect the continued use of mobile esports. Like other jobs, playing games professionally in the long term could make the players tedious and tired. Therefore, responsible parties, like mobile esports providers or governments, could use the recommendations of this study to promote positive behavior among the players. They will not feel like working and still con-sider playing mobile esports a hobby if they happily do the job. In the long run, the players could also make a nation’s society proud if they can be a champion in prestigious competitions. Future Research: A larger sample size will be needed to generalize the results, such as for a nation. It is also preferable if the sample is randomized systematically. Future works should also investigate whether the same results are acquired in other mobile esports. Furthermore, to extend our knowledge and deepen our understanding of the variables that influence mobile esports adoption, the subsequent research could look at other mobile esports acceptability based on characteristics of system functionality and moderator effects. Finally, longitudinal data-collecting approaches are suggested for future studies since behavior can change over time.

To face Industrial Revolution 4.0, company start to invest Information Technology (IT) system to improve effectiveness and efficiency in decision making and business processes. One of the technology investments chosen by a lot of companies is using the Enterprise Resources Planning (ERP) system. However, the ERP implementation has a 60-90% failure risk (Ahmad, 2014) and user technology readiness is the main key for the success of ERP implementation (Sun, 2011). To make strategies that fit the needs of food service company, this research was evaluating the Technology Readiness Index (TRI) of the workers and researching the relation between technology readiness and the acceptance of ERP technology named NetSuite in Company X. To evaluating the TRI, the researcher used the updated Technology Readiness Index method developed by Parasuraman in (2014). To research the correlation between technology readiness and the technology acceptance model, the researcher uses Technology Readiness and Acceptance Model (TRAM) and processed by Partial Least Square- Structural Equation Modelling (PLS-SEM). The result is Company X has a High Readiness Technology and the variable that affects the behavior intention of using NetSuite is perceived ease of use, the variable affected the perceived ease of use are optimism, innovativeness, and discomfort. The strategy plan designed by the result of the research and validated using Importance-Performance Analysis (IPA).

Purpose This study aims to extend the Technology Acceptance Model 2 (TAM2) by incorporating hedonic motivation and service quality and exploring their collective impact on users’ continuance intention in the context of e-grocery. The purpose is to provide a comprehensive understanding of the factors influencing e-grocery technology acceptance. Design/methodology/approach The empirical analysis follows a cross-sectional design, using data collected in Italy from January to March 2023. The survey, utilizing the convenience sampling method, focuses on users who have made online grocery purchases in the previous six months. Data analysis employs partial least squares structural equation modelling (PLS-SEM), which enables causal-predictive model assessment. Findings The research reveals significant relationships among hedonic motivation, service quality, perceived ease of use, perceived usefulness and continuance intention. Hedonic motivation positively impacts perceived usefulness but not perceived ease of use. Service quality significantly influences both perceived ease of use and perceived usefulness. Additionally, perceived ease of use positively influences perceived usefulness and continuance intention, while perceived usefulness significantly impacts continuance intention. Research limitations/implications The cross-sectional design could limit the study’s ability to capture the evolution of users’ continuance intention over time. Cultural influences on users’ perceptions could be explored further to develop context-specific strategies. Practical implications The findings emphasize the importance of hedonic motivation, service quality, ease of use and perceived usefulness in shaping users’ intentions to continue using online grocery services. Practitioners are encouraged to focus on enhancing hedonic elements for increased user loyalty and invest in service quality, particularly in customer care and checkout processes, to improve user perception and ease of use. Originality/value This study contributes to the existing literature by integrating hedonic motivation and service quality into TAM2, offering a novel perspective on their combined impact on technology acceptance. The inclusion of these factors enhances the model’s applicability in understanding user behaviour in the adoption of technology, specifically in the e-grocery sector.

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.

The objective of the study is to clarify the influence of digital capabilities on innovation capability, considering the direct and indirect impacts of digital leadership and digital culture in small and medium enterprises (SMEs) in Vietnam. The study used a mixed research method including qualitative with in-depth interviews and quantitative with Partial Least Squares Structural Equation Model (PLS-SEM) to analyze 271 responses. Research results show that digital capabilities have a positive impact on SMEs’ innovation capability. Digital leadership and digital culture also, directly and indirectly, affect firms’ digital capabilities and innovation capabilities. From there, the study confirms the theoretical contributions as well as proposes suggestions for SMEs to develop digital capabilities, and as a result, to develop innovation capabilities.

Context. The technology acceptance model (TAM) is a theoretical framework that consists of perceived usefulness (PUS), perceived ease of use (PEU), attitude toward using (ATT), behavioral intention to use (USI), and actual system use. Here, actual system use is posed by the smartphone use in higher education (SHE) described such as student self-management (MNG), student learning results (LRS), student achievements perceptions (SFB), student cost-benefits perceptions (VCB), and student expectations (EXP) that help to understand and explain how students’ acceptance and adoption of smartphone technology could be better achieved. Nowadays, after the COVID-19 pandemic, student motivation (MTV) and student quality perceptions (SQY) are two factors that reinforce the TAM model. Problem. The research confronts challenges from the dynamic and rapidly changing technology and education environments. The post-COVID-19 era introduces uncertainties, potentially affecting the TAM-SHE model's long-term sustainability. The fluidity of student preferences and technological advancements obstruct the establishment of a universally applicable framework for smartphone acceptance in education. This raises concerns about the model's adaptability and generalizability across diverse educational settings, emphasizing the careful consideration of evolving factors. Therefore, the following research question is proposed: What is the TAM for SHE empirical framework as an innovative tool? Purpose. The research aims to explore students' acceptance of smartphone technology in education using the technology acceptance model (TAM), focusing on perceived usefulness, ease of use, attitude, intention, and actual system use within smartphone use in higher education (SHE) in the context of post-COVID-19 era, the study considers student motivation (MTV) and student quality perceptions (SQY) as crucial factors enhancing the TAM-SHE framework. Methodology. We determined the following steps: Step 1. A qualitative study based on the Delphi Panel-Focus Group and Analytic Hierarchy Process (AHP) to determine the questionnaire TAM-SHE among three specialists: 1 information technology expert, 1 information technology professor, and 1 university student related to TAM for SHE and questioned about the items and factors related to the preliminary questionnaire design. Step 2. A literature review to explain the items and factors for the questionnaire (ex-ante) proposal involved in the design will be applied to more than 523 Mexican university students in the second semester of 2023. Step 3. Once all the data in the questionnaires had been collected were probed regarding the Cronbach Alpha reliability. A quantitative study on confirmatory factor analysis based on partial least square structural equation modeling (PLS-SEM) with SMART PLS (4.0.9.8) was used to probe convergent, discriminant, and nomological validity for the final conceptual TAM-SHE framework. Theoretical and practical findings. We propose a robust empirical TAM-SHE framework able to explain and predict how their factors enhance smartphone use in higher education. Transdisciplinary and sustainable innovation originality. The utilization of smartphones in higher education contributes to sustainable development by reducing educational disparities between students from different socioeconomic backgrounds. Additionally, mobile learning aligns with the Sustainable Development Goals (SDGs), particularly SDG4, by advancing sustainable quality higher education. Furthermore, it facilitates worldwide access to education, promoting a more inclusive and equitable learning environment Conclusions and limitations. For the post-COVID pandemic era, more studies are necessary to verify the new student motivations (MTV), student quality perceptions (SQY), and the actual system use factors to facilitate mobile technology in use for higher education through the technology acceptance model (TAM).

The objective of this study was to examine the determinants that impact the inclination of Generation Z individuals to use QR Pay in the context of Vietnam following the COVID-19 pandemic. In order to gather the necessary data, this study conducted a survey among a sample of 415 individuals who were customers of the relevant service or product. The survey was conducted using the Google Forms platform from September 2022 to January 2023, employing a convenience sampling approach. This paper constructed a research model utilizing the technology acceptance model (TAM) and unified theory of acceptance and use of technology (UTAUT) frameworks. Then, it analyzed the data using partial least squares structural equation modeling (PLS-SEM). Principal findings indicate that attitude, COVID-19 impact, personal innovativeness, perceived compatibility, perceived ease of use, perceived usefulness, and social influence are significant determinants of Vietnamese Gen Z’s intention to adopt QR Pay. This study provides valuable insights into the factors affecting Gen Z customers’ behavior toward technology adoption in Vietnam under the shadow of the COVID-19 pandemic. The findings can benefit business managers and policymakers, as they can better understand the factors that influence customers’ technology adoption and develop effective strategies to enhance customers’ acceptance of technology. AcknowledgmentThe author wishes to convey heartfelt gratitude to all consumers who took the time to complete the survey. Furthermore, heartfelt gratitude is extended to all parties involved, as well as the Ho Chi Minh City University of Banking, for their incredible support and help, which contributed considerably to the completion of this study.

The accelerating growth of virtual reality (VR) technology and evolving customer needs make multifarious challenges and opportunities for service industries. Based on the Technology Acceptance Model (TAM) and Theory of Affection Responses, we explored the key drivers of customer loyalty in virtual reality-enabled services through a large-scaled survey data collected from VR users in four major cities of Pakistan. The study employs the partial least squares structural equation modeling (PLS-SEM). We verified that the authenticity of the VR experience and TAM dimensions (ease of use, usefulness of VR) are the key drivers of customer loyalty béhavioral in VR-enabled services. Furthermore, results revealed that Affective responses (i.e., enjoyment, emotional involvement, and flow state) significantly mediated the relationships between the drivers and customer loyalty (continued use, recommendation, and willingness to pay premium). Implications for researchers and VR practitioners were also provided.

The majority of previous research on new technology acceptance has been conducted with single-step Structural Equation Modeling (SEM) based methods. The primary purpose of the study is to enhance the new technology acceptance based research with the Artificial Neural Network (ANN) method to enable more precise and in-depth research results as compared to the single-step SEM method. This study measures the relation between technology readiness dimension (optimism, innovativeness, discomfort, insecurity) and the technology acceptance (perceived ease of use and perceived usefulness) – and the intention to use cryptocurrency, such as bitcoin. The contribution of this study include the use of a multi-analytical approach by combining Partial Least Squares- Structural Equation Modeling (PLS-SEM) and Artificial Neural Network (ANN) analysis. First, PLS-SEM was applied to assess which factor has significant influence toward intention to use cryptocurrency. Second, an ANN was employed to rank the relative influence of the significant predictor variables attained from the PLS-SEM. The findings of the two-step PLS-SEM and ANN approach confirm that the use of ANN further verifies the results obtained by the PLS-SEM analysis. Also, ANN is capable of modelling complex linear and non-linear relationships with high predictive accuracy compared to SEM methods. Also, an Importance-Performance Map Analysis (IPMA) of the PLS-SEM results provides a more specific understanding of each factor’s importance-performance.

Green financial technology (fintech) focuses on achieving sustainable development goals. The Ant Forest application is a typical example that reflects the characteristics of green fintech, serving as a focal point for investigation in this study. Environmental concerns and green trust are important factors in promoting the user acceptance and adoption of green services. As green fintech has green and technological features, however, the joint effects among environmental concerns and green trust and the technology adoption perspective on users’ sustainable use of green fintech (i.e., Ant Forest) remain unknown. To address this research gap, the expectation-confirmation model (ECM) is applied in this paper by integrating environmental concerns and green trust to construct a research model to investigate users’ continuous willingness to use green fintech. We employed a survey research method by collecting 653 responses to examine the model. A partial least squares structural equation modeling (PLS-SEM) approach was adopted for statistical examination. The results show that environmental concerns can improve green trust and that green trust can improve user satisfaction through confirmation and perceived usefulness, thus enhancing users’ willingness to continuously use green fintech. This paper provides theoretical contributions by extending two green antecedents (i.e., environmental concerns and green trust) to the ECM to further understand user decisions to continuously use green fintech. The findings also hold significant practical implications for green fintech vendors, especially in terms of designing fintech solutions and collaborating with environmental agencies to promote continuous public use of green fintech.