Factors influencing pneumatic precision corn planter adoption in the Philippines: An empirical study using the Technology Acceptance Model (TAM) and Partial Least Squares Structural Equation Modeling (PLS-SEM)

This study examines the factors influencing seniors’ adoption of virtual reality (VR) cognitive training games by integrating the Theory of Planned Behavior (TPB) and the Technology Acceptance Model (TAM). Beyond the traditional constructs of these models, the research incorporates perceived enjoyment (PE), personal innovativeness (PI), and computer anxiety (CAX) to address seniors’ cognitive health needs and explore VR-based non-pharmacological interventions. Using Partial Least Squares Structural Equation Modeling (PLS-SEM), the study analyzed direct and indirect effects on adoption within a questionnaire-based framework. The research was conducted at community care centers in Taoyuan City, Taiwan, with 150 seniors aged 65–80. Participants engaged in a 20-min session with Nintendo Switch VR games and subsequently completed a questionnaire assessing their experiences. Results revealed that perceived ease of use (PEOU), PE, and subjective norms (SN) significantly shaped attitudes toward VR adoption, which strongly influenced behavioral intention (BI). BI emerged as a robust predictor of actual usage behavior (AUB), while CAX negatively impacted BI, highlighting the need to address emotional barriers. This study underscores the importance of designing intuitive, engaging, and accessible VR cognitive training games tailored for seniors. It also highlights the pivotal role of family and caregivers in fostering adoption, alongside the necessity of providing social and emotional support. These findings contribute to the theoretical understanding of VR-based games adoption in older adults and offer practical guidance for developers and healthcare providers aiming to create effective interventions for cognitive health.

The rapid pace of urbanization has intensified competition among businesses, prompting the adoption of innovative strategies to enhance sales performance and customer engagement. PT Inspirasi Bisnis Nusantara, under the HAUS! brand, introduced “Huling,” a hyperlocal distribution service utilizing electric bikes (e-bikes) equipped with integrated storage boxes to improve delivery efficiency and environmental sustainability. This study aims to evaluate customer acceptance of the Huling service by applying the Technology Acceptance Model (TAM). The model incorporates five core variables: Perceived Ease of Use (PEOU), Perceived Usefulness (PU), Attitude Towards Usage (ATU), Behavioral Intention (BI), and Actual Usage (AU). A quantitative research approach was employed, collecting data from 258 respondents through structured questionnaires. The data were analyzed using the Partial Least Squares Structural Equation Modeling (PLS-SEM) method to assess the relationships among the TAM variables. The findings reveal that PEOU has a significant positive effect on both PU and ATU, indicating that ease of use not only improves perceptions of usefulness but also fosters favorable attitudes toward adoption. PU significantly influences ATU and BI, suggesting that perceived benefits drive both positive attitudes and intentions to use the service. Furthermore, BI has a direct and significant effect on AU, confirming that stronger behavioral intentions translate into actual utilization. The analysis highlights the strongest impact along the pathway PEOU → ATU → BI → AU, underscoring the critical role of user-friendly design and positive attitudes in driving customer adoption. This research contributes to the literature by demonstrating the applicability of TAM in the hyperlocal distribution sector, offering practical implications for service providers seeking to enhance user acceptance through improved usability and perceived value. The findings suggest that optimizing ease of use and communicating tangible benefits can significantly increase customer engagement and sustained usage of innovative delivery services.

Effect of strategic imperative on technology adoption in academic libraries in Pakistan: A TAM & PLS-SEM analysis.

The increasing complexity of audit engagements, particularly with large clients, and growing competition within the auditing field necessitate the adoption of advanced technologies such as Big Data Analytics (BDA). However, little is known about the factors influencing auditors’ behavioral intention (BI) to adopt BDA tools. This study aims to investigate how audit client size and competition affect auditors' intention to adopt BDA in auditing processes, using the Technology Acceptance Model (TAM) as the theoretical framework. A census survey was conducted among 94 auditors from Big Four accounting firms in Palestine, achieving an 86% response rate. Data were analyzed using Partial Least Squares Structural Equation Modeling (PLS-SEM). The results indicate that audit client size positively influences both perceived usefulness (PU) (β = 0.366, p < 0.001) and perceived ease of use (PEU) (β = 0.490, p < 0.000) of BDA tools. Similarly, competition positively affects PU (β = 0.512, p < 0.000) and PEU (β = 0.333, p < 0.001). Furthermore, PU significantly predicts auditors’ BI to adopt BDA (β = 0.532, p < 0.000), while PEU does not. BI, in turn, positively influences the actual use of BDA tools (β = 0.481, p < 0.001). These findings spotlight the importance of leveraging client size and competitive pressures to enhance PU and PEU, thereby fostering the adoption of BDA technologies. By adopting these tools, auditing firms can improve efficiency, enhance fraud detection, and provide more comprehensive assurances, ultimately achieving a competitive edge in the market.

This study examines the influence of the Technology Acceptance Model (TAM), focusing on Perceived Ease of Use (PEOU) and Perceived Usefulness (PU), on users’ Behavioral Intention (BI) to adopt and continue using M-Din, a Sharia-based mobile banking application at Bank Muamalat in West Java. Employing a quantitative survey of 100 active M-Din users, data were analyzed using Partial Least Squares Structural Equation Modeling (PLS-SEM). The results show that PEOU significantly affects PU, and both PEOU and PU significantly influence BI; additionally, PU partially mediates the effect of PEOU on BI. This research contributes to the digital banking literature by reaffirming TAM constructs within an Islamic finance context and offers practical recommendations for optimizing Sharia-compliant mobile banking strategies. Implications for enhancing user interface design and promoting key features to boost adoption are discussed.

Digital transformation plays a vital role in enhancing the competitiveness of Micro, Small, and Medium Enterprises (MSMEs) in developing regions. A case in point is Rumahekraf in West Papua Province, which faces infrastructure challenges such as limited internet access, inadequate technological devices, and insufficient digital training for MSME actors. In addition to infrastructure challenges, external factors such as economic conditions, local culture, and the digital divide also influence the adoption rate of this platform. This study aims to investigate the factors that drive and hinder its adoption. By combining the Technology Acceptance Model (TAM), Technology Readiness Index (TRI), and Performance Importance Map Analysis (IPMA). Particularly, this study examines the role of optimism, innovativeness, discomfort, and insecurity in shaping behavioral intention (BI) that might lead to usage behavior (UB). With a total of 157 respondents, and analyzed using Partial Least Squares Structural Equation Modeling (PLS-SEM), the results showed that perceived ease of use (PEOU) and perceived usefulness (PU) have a significant effect on BI (R2=56.3%), while BI influenced UB (R2=58%). Optimism affects PEOU but not PU, this can be explained by the nature of optimism, which tends to reinforce confidence in one's ability to master technology rather than directly evaluating the platform's perceived benefits. While Innovativeness positively affects both. The findings emphasize that in areas with limited infrastructure, such as West Papua, prioritizing easy-to-use design and useful features is key to effective platform adoption. This research provides insights for policymakers and developers to improve strategies in promoting digital platform adoption among MSMEs.

This study examines the determinants of corporate tax compliance in Thailand, partic-ularly in the context of increasing digitalization. While prior studies have separately addressed technology acceptance and behavioral intention, few have integrated these domains to explain voluntary tax compliance. This research employs a hybrid model that combines the Technology Acceptance Model (TAM), the Theory of Planned Be-havior (TPB), and taxpayer responsibility theory. Using data from 500 corporate ac-countants, we employed Partial Least Squares Structural Equation Modeling (PLS-SEM), Necessary Condition Analysis (NCA), and Importance–Performance Map Analysis (IPMA) to analyze the data. The results demonstrate that perceived ease of use, subjec-tive norms, and perceived behavioral control significantly influence tax intention, which in turn affects compliance behavior. Furthermore, attitudes toward technology and perceived usefulness indirectly support compliance, while taxpayer responsibility ex-hibits a strong direct effect. These findings contribute to the theoretical understanding of compliance behavior and offer practical insights for enhancing technology-enabled tax systems in emerging markets. This study examines the determinants of corporate tax compliance in Thailand, partic-ularly in the context of increasing digitalization. While prior studies have separately addressed technology acceptance and behavioral intention, few have integrated these domains to explain voluntary tax compliance. This research employs a hybrid model that combines the Technology Acceptance Model (TAM), the Theory of Planned Be-havior (TPB), and taxpayer responsibility theory. Using data from 500 corporate ac-countants, we employed Partial Least Squares Structural Equation Modeling (PLS-SEM), Necessary Condition Analysis (NCA), and Importance–Performance Map Analysis (IPMA) to analyze the data. The results demonstrate that perceived ease of use, subjec-tive norms, and perceived behavioral control significantly influence tax intention, which in turn affects compliance behavior. Furthermore, attitudes toward technology and perceived usefulness indirectly support compliance, while taxpayer responsibility ex-hibits a strong direct effect. These findings contribute to the theoretical understanding of compliance behavior and offer practical insights for enhancing technology-enabled tax systems in emerging markets.

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 examines the factors influencing the behavioral intention and usage behavior of e-bikes in Metro Manila and the National Capital Region (NCR) using constructs from the Diffusion of Innovation (DOI) theory, the Technology Acceptance Model (TAM), and external variables such as government policies, infrastructure, social influence, and public awareness. A cross-sectional survey of 340 respondents was analyzed using Partial Least Squares Structural Equation Modeling (PLS-SEM) to explore the relationships among these constructs. The results indicate that perceived usefulness (PU), perceived ease of use (PEOU), social influence, and public awareness significantly affect behavioral intention, which strongly predicts e-bike usage behavior. Infrastructure also positively impacts ease of use, while trialability enhances perceived usefulness. However, the relationships between government policies and perceived usefulness, as well as between trialability and ease of use, were insignificant, reflecting contextual limitations in the Philippine setting. The findings highlight the importance of behavioral intention as a primary driver of e-bike adoption. To address barriers, practical recommendations include expanding bike lanes, implementing e-bike sharing systems, strengthening government incentives, and launching public awareness campaigns that highlight the benefits of e-bikes, such as cost savings and environmental sustainability. This study also contributes to theory by integrating DOI and TAM frameworks, offering a comprehensive understanding of e-bike adoption in developing urban settings. These insights provide actionable strategies for policymakers, manufacturers, and stakeholders to promote sustainable transportation in the Philippines and similar contexts.

TThe practice of real estate agents and the extent to which Information and Communication Technology (ICT) is applied in Malaysia appears to be more specialised and diverse with the exploration of technology and innovation. Due to the increasing interest in using more innovative marketing and negotiation techniques, this study focuses on real estate agents' acceptance as well as the intention to use ICT in Malaysia according to the extended Technology Acceptance Model (TAM). In this study, a sample including 400 real estate agency practitioners was surveyed and analysed using Partial Least Squares-Structural Equation Modelling (PLS-SEM). The findings show that Perceived Usefulness (PU), Perceived Ease of Use (PEOU), as well as Trust (TRU) affect Behavioural Intention (BI). On the other hand, PU is affected by PEOU as well as Service Quality (SERQ). Meanwhile, PEOU is affected by Perceived Enjoyment (ENJ) as well as Innovativeness (INNO). These results indicate that ICT acceptance among real estate agents can be improved by providing them with high-quality service, fostering perceived enjoyment, building trust, and establishing innovative ICT solutions tailored to real estate agents' needs.

The utilization of information technology and the internet in the industry is generally done through the implementation of Enterprise Resource Planning (ERP) systems to manage business processes. The success of ERP system implementation requires efforts to support and prevent failure risks. One of the risk factors for failure is the User Interface (UI) design of the ERP system. Good UI design that meets user needs needs to be considered. This research utilizes the Design Thinking (DT) method to create a good UI design and the Technology Acceptance Model (TAM) method to measure the acceptance of UI design in the manufacturing module of PT Allure Alluminio. The DT method was chosen as the UI design method for the ERP system because it is considered more creative in generating product concepts compared to other standard methods and TAM was chosen as one of the best methods for explaining technology acceptance and is a popular and commonly used approach. The UI design process is carried out in 6 phases of DT under the guidance of the Person in Charge (PIC), and the acceptance of UI design is measured after system implementation. Acceptance measurement is conducted using TAM with navigation and UI design variables as external variables, which are taken from previous research, and it tests the variables of Perceived Usefulness (PU), Perceived Ease of Use (PEOU), and Behavioral Intention to Use (BITU) among 50 users of the ERP system in the manufacturing module at PT Allure Alluminio through a Google Form questionnaire. The collected data is analyzed using Partial Least Squares Structural Equation Modeling (PLS-SEM) in SmartPLS 3.2.9. The research results indicate that the DT method is effective for UI design as it involves users. The analysis shows that the use of ERP systems is influenced by perceived usefulness and ease of use, but not influenced by UI design. Navigation and UI design provide ease of use.

Computerised Maintenance Management System (CMMS) is a widely recognised software in Facilities Management (FM) that provides numerous advantages to facility managers by enhancing productivity at work. The objective of this research is to provide insight and assess the factors influencing the acceptance of CMMS among facility managers in Malaysia. As a result, an improved comprehension of CMMS technology acceptance can be formed, as well as a better understanding of other FM technology adoption. Multiple factors influence CMMS acceptance, and this study used a quantitative technique to verify the hypothesis, using the Technology Acceptance Model (TAM) in conjunction with a Partial Least Square-Structural Equation Model (PLS-SEM). In addition, 125 facility managers completed an online survey that was utilised to collect primary data. The quantitative and structural models were analysed using PLS-SEM. Based on the study's findings, perceived usefulness (PU) and perceived ease of use (PEOU) have a favourable impact on behavioural intention (BI), which influences actual usage (AU) of CMMS. The research aims to improve awareness of the degree of acceptance of CMMS among facility managers and to contribute to FM organisations' better understanding of future technology adoptions.

This study explores the key features, operational mechanisms, and functional advantages of a multifunctional alarm system, emphasizing its security applications and its integration into skills training for Electrical Installation and Maintenance (EIM). Grounded on the Technology Acceptance Model (TAM), the study seeks to optimize the system by integrating advanced technologies to enhance security, reliability, and user-friendliness. It further aims to evaluate the adoption level of the system by assessing user acceptance, market viability, and potential implementation challenges among teacher-trainers—graduates of Industrial Technology and allied courses—teaching TVL-E subjects in junior and senior high schools in the Division of Iligan City. A descriptive-correlational research design utilizing mixed methods was employed. Quantitative data were collected using a validated five-point Likert scale survey and analyzed using descriptive statistics and Partial Least Squares Structural Equation Modeling (PLS-SEM) to evaluate the relationships among perceived Usefulness (PU), perceived ease of use (PEU), Attitude towards use, behavioral intent to use (BIU), and actual system usage. Thirty (30) purposively selected respondents participated in the survey. Qualitative data from open-ended questions were thematically analyzed to determine patterns of opinion regarding the system’s application in skills training. The results revealed high agreement levels across all constructs: level of expertise (M = 3.92), perceived Usefulness (M = 4.553), perceived ease of use (M = 4.040), attitude towards use (M = 4.392), behavioral intent to use (M = 4.350), and actual system use (M = 4.077). All six hypothesized relationships in the structural model were statistically significant (p < 0.05), with the strongest path observed between behavioral intent to use and actual system usage (β = 0.782, t = 9.811, p = 0.000). Thematic analysis revealed three key themes: “Learning Experience and Development,” “Seminars and Workshops,” and “Simulation and Identification of Alarms,” confirming the system’s relevance in realistic learning environments. Validation by experts from academia, industry, and TESDA further affirmed the system’s instructional applicability. In conclusion, the study affirms the effectiveness and educational value of the multifunctional alarm system as a training device in EIM. Recommendations include the development of modular kits, integration of smart technologies, improved connectivity features, enhanced portability, and clear maintenance protocols to increase accessibility, usability, and long-term adoption.

This study investigates the predictors influencing continued usage intention of Online Food Delivery Services (OFDS) among Malaysian university students. Grounded in the Technology Acceptance Model (TAM), the research explores the effects of perceived usefulness (PU), perceived ease of use (PEOU), variety of food choices (VFC), and electronic word of mouth (e-WOM) on behavioral intentions. Data were collected from 150 students through an online survey and analyzed using Partial Least Squares Structural Equation Modeling (PLS-SEM). The results reveal that PU, PEOU, and e-WOM significantly influence continued usage intention, whereas VFC does not show a statistically significant impact. These findings offer theoretical and practical implications for service providers aiming to retain younger digital consumers in a competitive food delivery market. The study highlights the importance of system usability and social influence in fostering long-term engagement with OFDS platforms.

IntroductionTechnological change is a mega trend that drives sustainable development in the agrifood sector globally. The introduction of BanQu, a blockchain-enabled platform, aimed to address challenges like lack of transparency, side-selling, and unfair pricing in Uganda's barley value chain, but its acceptance has been slow. While blockchain adoption has thrived in developed countries and large supply chains, empirical evidence on its uptake among smallholder farmers in Sub-Saharan Africa, especially Uganda, remains limited. This study investigates determinants of smallholder barley farmers' intentions to accept blockchain technology (BCT) in Uganda.MethodsThe study utilized the second extension of the Technology Acceptance Model (TAM2), customized to fit Uganda's context. Quantitative data were gathered from 245 farmers in Bukwo and Kween, the two leading barley-producing districts in eastern Uganda. The data were analyzed using Partial Least Squares Structural Equation Modeling (PLS-SEM).Results and discussionThe study showed that perceived usefulness (PU) significantly influenced behavioral intention (BI) and shaped perceived ease of use (PEU). Subjective norms (SUN) and voluntariness (BV) enhanced PU, while perceived behavioral control (PBC) improved PEU. Notably, BCT relevance (BR) directly influenced BI, bypassing PU. These findings provide fresh insights into rural technology adoption, highlighting PU's influence on PEU and BV's role in shaping PU. The study recommends emphasizing BCT benefits such as reducing transaction costs, leveraging social networks, and addressing resource gaps to boost acceptance. This study advances understanding of BCT adoption among smallholder farmers in emerging economies like Uganda.