Technology Acceptance Model Framework Research Articles

Students’s Attitudes Toward the Use of CANVAS in the EFL Virtual Learning Environment

This study examines students’ attitudes toward the Learning Management System (hereafter LMS) CANVAS in the Virtual Learning Environment (henceforth VLE). This study used mixed methods in nature, which used a survey to collect data on the attitudes of 118 EFL students who enrolled in the Technology Enhanced Language Learning (hereafter TELL) course. Researchers gathered data through a questionnaire and semi-structured interviews to assess students’ attitudes using the Technology Acceptance Model (TAM). The survey results were analyzed using descriptive statistics to investigate the quantitative data, while thematic analysis was used to study the qualitative data obtained from interviews. The survey results were analyzed using descriptive statistics to investigate the quantitative data, while thematic analysis was used to study the qualitative data obtained from interviews. Based on the research findings, the TAM framework identifies two main categories: Perceived Usefulness and Perceived Ease of Use. The Perceive Usefulness category comprises four categories: CANVAS Engagement Time, CANVAS Enhances Interaction, Learning Efficacy, and Effective Communication, CANVAS Enhances Language Learning, and CANVAS Boosting Students’ Confidence and Motivation in a Fun Way. In addition, the Perceive Ease of Use category comprises three categories: CANVAS Usability in Mobile Learning Environments, CANVAS User-Friendly Design, and CANVAS Seamless Navigation and Accessibility.

Life After COVID-19: Artificial Intelligence in Hotels; In-depth Literature Review

Purpose: This study aims to systematically review the impact of artificial intelligence (AI) on the hotel industry post-COVID-19, focusing on articles published between 2019 and 2024. Grounded in the Technology Acceptance Model (TAM), the research examines the relevance and application of AI within the industry, particularly in response to the challenges posed by the pandemic. Study design/methodology/approach: The study adopts an interpretive paradigm and employs thematic analysis to synthesise findings from various academic journals. Keywords such as ‘hotels,’ ‘tourism industry,’ ‘COVID-19,’ and ‘artificial intelligence’ are used to identify relevant literature. The methodology involves a detailed literature review and analysis to explore how AI technologies enhance operational efficiencies, service quality, and cost reductions in the hotel industry. Findings: The findings reveal that AI has become critical in adapting hotel operations to new market realities post-COVID-19. AI technologies offer innovative solutions that align with changing consumer expectations and industry standards, contributing to improved customer experiences and operational efficiency. Integrating AI into hotel management and customer service platforms is essential for the recovery and future growth of the hospitality sector. Originality/value: This study contributes to the existing literature by providing insights into the impact of AI on the hotel industry post-COVID-19. It highlights the importance of AI technologies in improving hotel customer experiences, operational efficiency, and profitability. The application of the TAM framework underscores the significance of perceived usefulness and ease of use in driving the acceptance and sustained use of AI in the hotel industry. The study recommends ongoing investment in AI technologies and adaptation to technological advancements to meet evolving customer needs and industry demands.

Supporting parents with acutely ill children: Environment scan and user evaluation of mobile applications (the SuPa kids project)

BackgroundChildren are one of the biggest users of emergency departments in the UK, sometimes utilising services when experiencing acute illnesses that can be managed at home. mHealth can be an efficacious way for parents/guardians to manage acute illnesses. It has also become a ubiquitous resource to promote public health interests within a resource constrained health system. However, to be effective, co-design is necessary with concepts such as usefulness, ease of use, trustworthiness and security underpinning the utility of mHealth interventions for acute childhood illness. ObjectiveThe objective of this study was to conduct an environmental scan of mHealth apps for parental assessment and management of acute childhood illnesses in 0- to 5-year-olds, review the content and functionality of each identified app against the list of desired attributes identified in previous research and synthesise publicly available reviews from end users to demonstrate the quality of current apps in the marketplace and identify areas for improvement. MethodApp characteristics were mapped to an a priori defined list of desirable attributes. End user reviews were mapped to a modified Technology Acceptance Model framework that included overarching themes of: Perceived Usefulness (PU), Perceived Ease of Use (PEU), Perceived Trustworthiness (PT) and Perceived Security (PS) using reflexive thematic analysis. ResultsOverall, 15 apps were included in the analysis (Table 2). Fourteen of the 15 apps were available on both the iOS and Android platforms. ‘Baby Illness, Prevention, Cure’ was only available on the Android store. All apps were free to download and did not restrict access to information or features via in-app purchases. Baby and child first aid (British Red Cross) was the earliest app to be released (2014). This app was updated annually, with the most recent update being 2022. The most recent apps to be released (2018) were ‘AskFirst’ (formerly Ask NHS), ‘Essex Child Health’ and ‘The Lullaby Trust Baby Check’, updated in 2022, 2020 and 2019, respectively. No individual app met all the desirable attributes highlighted by parents in previous research. Both ‘Healthier Together’, and ‘The Lullaby Trust Baby Check’ included all but one desirable attributes (video), as did the ‘’CATCH (Common Approach to Children’s Health), which did not utilise a traffic light system. Apps that were locality specific were not rated by users (Berkshire Child Health, Cheshire Child Health, Child Health Guide Newham, Child Health HMR, Oldham Child Illness and Walsall Healthy Child). All other apps were rated from 2/5 to 5/5 stars. When considering localities, the ‘CATCH’ app was only supported in Halton, Cheshire, Knowsley, Liverpool, St Helens and Vale Royal. Further investigation evidenced no correlation between inclusion of the desirable attributes and app rating. ConclusionOverall, this research has highlighted several aspects of best practise when developing mHealth apps for the management of acute childhood illnesses, for increasing PU, PEU, PT and PS; and also, places importance on co-design.

Tourists’ behavioural intentions to use ChatGPT for tour route planning: an extended TAM model including rational and emotional factors

ABSTRACT This study incorporates perceived coolness and perceived enjoyment as emotional factors into Technology Acceptance Model (TAM), which traditionally focuses on rational factors, to comprehensively understand how tourists develop usage intentions of ChatGPT for tour route planning. Structural equation modeling was utilized to analyse 491 online questionnaires. Findings support that perceived information quality is an antecedent factor of perceived ease of use and perceived usefulness. Consequently, perceived ease of use and perceived usefulness significantly influence tourists’ attitudes towards using ChatGPT for tour route planning, while perceived usefulness directly influences tourists’ behavioural intentions regarding ChatGPT usage. Moreover, perceived coolness directly affects tourists’ attitudes towards ChatGPT usage and indirectly affects their behavioural intentions through perceived enjoyment and attitudes. The primary contribution of this research lies in the integration of perceived coolness and perceived enjoyment into the traditional TAM, thus establishing a new rational-emotional extended TAM framework. This advancement provides a more comprehensive understanding of tourists’ adoption of generative AI tools such as ChatGPT for tour route planning.

PATTERNS OF UTILIZING AI–ASSISTED TOOLS AMONG EFL STUDENTS: NEED SURVEYS FOR ASSESSMENT MODEL DEVELOPMENT

This study explores patterns of AI-tool utilization among Indonesian EFL students, as preliminary data for assessment-model development. Using a convenience sampling technique, this study involved 208 university students of various year levels. A questionnaire was developed based on technology acceptance model (TAM) frameworks to collect data through Google Form, covering aspects of knowledge and use of AI tools in completing tasks, frequency of AI use and friendliness levels, reasons for using AI tools, ease of using AI tools, and desire to use AI tools. The results reveal that the participants had basic knowledge of AI but a significant number of participants admitted not knowing AI tools, suggesting the need for more education and awareness about AI. Grammarly and Google Translate were the most familiar and frequently used applications. Our findings also reveal strong relationships between perceived ease of use (PEoU) and perceived usefulness (PU) and between PU and technology acceptance (TA), implying how TAM frameworks may predict willingness to use technology-assisted or AI applications and the actual utilization. As most research participants were teacher candidates, it becomes clear that integrating AI-assisted learning content and activities appears essential as their experiences in their teacher education may influence the way they teach in the future.

Factors Affecting the Participating Intention in Online Voter Contact: A Case Study of Long An Province

The aim of this study is to investigate the factors influencing online voter contact intention in Long An province, based on merging the TAM (Technology Acceptance Model) and TPB (Theory of Planned Behavior) frameworks. Analysis conducted using PLS-SEM with a sample size of 201 participants reveals that perceived usefulness is the most significant predictor of participants’ attitudes. The constructs of TPB, including attitude, subjective norms, and perceived behavior control, exhibit positive and statistically significant effects on the intention to participate in online voter contact. The findings of this study have several implications for agencies involved in promoting policies related to online voter contact.

A Conceptual Development of Digital Trade Adoption among Manufacturing Companies in China: A Technology Acceptance Model Approach

The proliferation of digital technologies has brought about transformative changes in various sectors, including manufacturing. In the context of China, a prominent manufacturing hub, the adoption of digital trade practices has emerged as a critical determinant of competitiveness and sustainability for manufacturing companies. This paper proposes a conceptual framework for understanding the factors influencing the adoption of digital trade among manufacturing firms in China, employing the Technology Acceptance Model (TAM) as a theoretical lens. Drawing upon extant literature and empirical insights, this conceptual paper identifies key constructs within the TAM framework, such as perceived usefulness, perceived ease of use, attitude toward digital trade, and behavioral intention, and adapts them to the specific context of digital trade adoption in the Chinese manufacturing sector. It explores how factors such as organizational readiness, technological infrastructure, government policies, and cultural factors influence the perceived usefulness and ease of use of digital trade platforms among manufacturing companies in China. Moreover, this paper extends the traditional TAM model by incorporating additional constructs such as trust in technology, perceived risk, and organizational innovativeness, which are deemed essential in understanding the complexities of digital trade adoption in a rapidly evolving technological landscape. It underscores the significance of trust-building mechanisms, risk mitigation strategies, and organizational culture in facilitating the successful implementation of digital trade initiatives within manufacturing enterprises in China. The proposed conceptual framework contributes to both theoretical and practical understandings of digital trade adoption by elucidating the interplay between technological factors, organizational dynamics, and contextual influences within the Chinese manufacturing context. By offering insights into the determinants of digital trade adoption and the mechanisms for enhancing acceptance and utilization of digital trade platforms, this paper aims to inform policymakers, industry practitioners, and scholars engaged in the promotion and facilitation of digital transformation within the manufacturing sector in China and beyond.

Profiling of OTT Viewers and their Perception Mapping using Advanced Technological Models

Purpose – The study explores the significant attributes that inspire customers to select OTT platforms and to measure the positions of OTT platforms in the mind of an individual via a perceptual map. Design/methodology/approach –To develop a perceptual map to measure the attribute-based motivation regulations with regards to OTT platforms. With combination of theoretical frameworks such as Technology Acceptance Model (TAM); Diffusion of Innovation Theory (DIT); Uses and Gratifications Theory (UGT) and Unified Technology Acceptance and Use Theory (UTAUT) used to develop as scale. Furthermore, this study used mixed method approach. Findings – Four attributes/ regulations were proposed: ease of use, social influence etc. Research limitations/implications – The study utilises a theoretical framework to create a structured framework for motivating young people based on OTT attributes. Practical implications – Study directs OTT marketers in strategically positioning the channel based on specific qualities. Originality/value – This work in the OTT channels utilized the combination of TAM, UGT, DIT and UTAUT framework.

The factors influencing teacher education students’ willingness to adopt artificial intelligence technology for information-based teaching

ABSTRACT This study, rooted in the Technology Acceptance Model (TAM), investigates the multifaceted factors that influence teacher education students in Information-Based Teaching to embrace artificial intelligence technologies. To enrich the TAM framework, we have incorporated elements such as Artificial Intelligence Literacy (AIL), Subjective Norms (SN), and Output Quality (OQ), with the aim of examining their respective effects on the willingness of teacher education students to adopt AI technologies. To substantiate this theoretical framework, we conducted empirical research involving teacher education students from various Chinese universities. Our findings affirm the robustness of the TAM in explaining the inclination of teacher education students, engaged in the actual teaching process within a digitized educational environment, to adopt AI technologies. Through this model, our study underscores the pivotal role of Artificial Intelligence Literacy (AIL) in influencing educators’ acceptance of AI technologies, establishing a foundational cornerstone for subsequent explorations within the theoretical landscape of the TAM. In this study, we identify Perceived Usefulness (PU) and Artificial Intelligence Literacy (AIL) as the primary factors affecting Behavioral Intention (BI) to use AI technologies. Consequently, to foster broader adoption of AI technologies by educators, it is essential to emphasize their tangible benefits and superiority in teaching, with the goal of promoting the extended utilization of AI in digitalized instruction.

Exploring the influence of ChatGPT on tourism behavior using the technology acceptance model

Purpose The present study’s aims are twofold: 1) to contribute to theory development by accounting for both personality and trust in the conceptualization of technology acceptance using the technology acceptance model (TAM) as the theoretical framework; and 2) to explore the influence of ChatGPT-integrated chatbots on tourism behavior. Design/methodology/approach The target population for this study was travelers who previously used technology (website/ app) to plan their holiday abroad. An online survey questionnaire created with Google Forms was distributed via a panel company (iPanel). A screening question was included to filter out respondents who have not previously used technological means to plan their holiday abroad. A panel company (iPanel) was hired to collect data from a convenience sample of 305 Israeli tourists who met the above criterion between August 22 and 27, 2023, and were at least 18. Findings A significant and positive relationship was observed between trust in ChaptGPT and perceived usefulness. Furthermore, a significant and positive association was observed between perceived ease of use and intentions to use ChatGPT-integrated chatbots to plan future holidays. Post hoc analyses suggest that perceived ease of use mediates the relationship between extraversion and trust, trust mediates the relationship between perceived ease of use and perceived usefulness and age moderates the relationship between perceived ease of use and behavioral intentions. Research limitations/implications Data was collected from a convenience sample of Israeli travelers. Hence, generalizations to other countries, nationalities and cultures should be treated carefully; the study is cross-sectional and thus represents respondents’ beliefs and behavioral intentions at a particular time; and the study is based on one of several theoretical frameworks that can be used to conceptualize behaviors associated with using AI by tourists. Practical implications The findings of the present study point to the importance of accounting for tourists’ personal factors, such as personality and age, in developing AI products in the tourism industry. chief executive officers and relevant shareholders would benefit from conducting market research to obtain insights into the factors that may enhance or hamper tourists’ adoption of AI-based technology for planning their holidays abroad. Originality/value Previous work falls short of accounting for personality traits and trust in a single model using the TAM framework. To the best of the authors’ knowledge, this is the first study empirically investigating tourism behavior related to ChatGPT based chatbots as a tool to plan future holidays abroad. Furthermore, the possible role of age as a moderating variable was overlooked in past research.

From Old to New Technologies: Exploring the Role and Impact of Value Resonance

In the research of technology switch, theories such as Push-Pull-Mooring (PPM), Behavioral Reasoning (BRT), Innovation Resistance (IRT), and Status Quo Bias (SQB) have been employed to extend the Technology Acceptance Model (TAM), focusing on how old technology factors such as inertia as barriers to embracing new technological innovations. However, our research contends that the impact of these old technology factors on the technology switch is not unequivocal, as they may either hinder or facilitate the transition, depending on whether the new technology retains valued features of the old technology. To delve into this complexity, we introduce the concept of value resonance between old and new technologies. Utilizing Nintendo Switch for empirical analysis, two quantitative studies were conducted. Out of 630 distributed questionnaires, 553 valid responses were collected, yielding an 87.7% response rate. The first study used multi-groups analysis within TAM to differentiate between the technology acceptance group (TAG) and the technology switch group (TSG), contributing to the development of the Technology Switch Model (TSM). The second study applied Covariance-Based Structural Equation Modeling (CB-SEM) to examine value resonance’s mediating role in the TSM. The empirical results revealed discernible differences between TAG and TSG within the TAM framework, providing a robust theoretical basis for the TSM. Furthermore, the result indicated that factors associated with old technology could enhance users’ switching intentions through the mediating mechanism of value resonance. These findings aim to provide a more nuanced understanding of technology switch, highlighting that the dynamics between old and new technologies are more complex and variable than previously assumed.

Evaluation and significance of a digital assistant for patient history-taking and physical examination in telemedicine

Introduction Assisted history-taking systems can be used in provider-to-provider teleconsultations to task-shift the collection of evidence-based medical history and physical exam information to a frontline health worker. We developed such a task-shifting digital assistant, called ‘Ayu’, for nurses in rural India to collect clinical information from a patient and share it with a remote doctor to arrive at an accurate diagnosis and triage decision. Materials & Methods We evaluated the ability of the task-shifting digital assistant to collect a comprehensive patient history by using 190 standardized patient case studies and evaluating the information recall of the assistant by a skilled clinician. Following this, we tested the ability of nurses to use the system by training and evaluating the system’s accuracy when used by 19 nurses in rural Gujarat, India. We also measured the diagnostic and triage accuracy based on the generated history note. Finally, we evaluated the system’s acceptability by using the Technology Acceptance Model framework. Results Ayu could capture 65% of patient history information and 42% of physical exam information from patient case studies. When used by nurses, the mean accuracy of the generated clinical note was 7.71 ± 2.42. Using the information collected by a nurse using Ayu, a primary care physician could arrive at the correct diagnosis in 74% of cases, and correct triage decision in 88% of cases. Overall, we saw a high acceptability from nurses to use the system. Conclusions Ayu can capture an acceptable proportion of clinical information and can aid in collecting an evidence-based medical history by task-shifting some of the early investigational steps. Further development of Ayu to increase its information retrieval ability and ease of use by health workers is needed.

Harnessing digital issue in adopting metaverse technology in higher education institutions: Evidence from the United Arab Emirates

This study delves into the intricate landscape of metaverse technology adoption within higher education institutions in the UAE, investigating the multifaceted interplay of accessibility, technology adaptability, and policies and regulations. Using a cross-sectional research design, data was meticulously collected through a multistage sampling approach, combining probability and non-probability methods. A pretested questionnaire underwent rigorous evaluation, ensuring unbiased item formulation and adherence to best practices. The investigation challenges and extends the Technology Acceptance Model (TAM) by revealing unexpected findings. The absence of a significant relationship between accessibility and metaverse adoption prompts a call for an expanded TAM framework. Surprisingly, a negative correlation between technology adaptability and adoption is highlighted, emphasizing the need for a cautious assimilation approach. Moreover, the research underscores the influential role of policies and regulations in metaverse adoption, advocating for a comprehensive TAM framework that encompasses regulatory dynamics. Findings offer practical implications for stakeholders, policymakers, and institutions, emphasizing diverse adoption facets beyond accessibility. The study contributes to the discourse on metaverse adoption and advances theoretical frameworks for technology integration within educational contexts. The methodology's meticulous design underscores the study's rigor, ensuring the robustness of the insights gleaned from the investigation.

MALL as a Language Learning Tool for Saudi EFL University Learners: An Empirical Study With Reference to TAM

Veteran US technology writer and publisher Fred Davis defined the Technology Acceptance Model (TAM) as characterized by perceived usefulness and usefulness by users. However, these attitudes are largely determined by external variables such as age, gender, and social set up. This study aims to apply an extended conceptual framework of TAM to examine the adoption of MALL by English-major students, encompassing variables such as perceived enjoyment, instructor support, and MALL interactivity as exogenous factors. A questionnaire was administered to 392 English-major students at King Saud University, employing a cross-sectional research design. Using AMOS version 26.0, results from confirmatory factor analysis (CFA) supported the convergent and discriminant validity of the study constructs. The structural model results demonstrated a statistically significant impact of external variables – perceived enjoyment, MALL interactivity, and instructor support – on students' perceptions of MALL usefulness and ease of use. As a result, students' perceived usefulness and ease of use significantly influenced their intention to adopt MALL for language learning. The model accounted for 62% of the variance in MALL tools adoption among Saudi English major students. In conclusion, the extended TAM framework effectively explains the adoption of MALL by Saudi English major students.

The Impact of Harnessing Total Quality Management Studies on the Performance of Smart Applications: A study in Public and Private Sectors in the UAE

This study explores the complex environment of smart applications technology in the UAE's public and private sectors, looking into the complex interactions between technological adaptability and accessibility as well as the effects of Total Quality Management (TQM) studies presented by policies and regulations. Data was collected by a multistage sampling strategy, mixing probability and non-probability methods, using a cross-sectional research design. To ensure impartial item creation and adherence to best practices, a pretested questionnaire underwent extensive examination. Through the revelation of unexpected results, the research tests and expands upon the Technology Acceptance Model (TAM). There is a request for an enlarged TAM framework because there is no substantial correlation found between accessibility and the performance of smart applications. A negative link is resulted, unexpectedly, between technology adaptation and TQM adoption, underscoring the necessity of a cautious integration strategy. The report also emphasizes how important TQM policies and regulations are to the functioning of smart applications, supporting the need for a thorough TAM framework that takes in regulatory dynamics into consideration. Practical implications for stakeholders, quality policymakers, and institutions are presented by the findings, which highlight several adoption aspects beyond accessibility. This research adds a contribution on smart application performance and develops theoretical models for integrating technology in organizational settings. The rigorous design of the methodology highlights the integrity of the study and guarantees the validity of the insights obtained from the investigation.

Why Do People Use Telemedicine Apps in the Post-COVID-19 Era? Expanded TAM with E-Health Literacy and Social Influence

This study delves into the determinants influencing individuals’ intentions to adopt telemedicine apps during the COVID-19 pandemic. The study aims to offer a comprehensive framework for understanding behavioral intentions by leveraging the Technology Acceptance Model (TAM), supplemented by e-health literacy and social influence variables. The study analyzes survey data from 364 adults using partial least squares structural equation modeling (PLS-SEM) to empirically examine the internal relationships within the model. Results indicated that e-health literacy, attitude, and social influence significantly impacted the intention to use telemedicine apps. Notably, e-health literacy positively influenced both perceived usefulness and ease of use, expanding beyond mere usage intention. The study underscored the substantial role of social influence in predicting the intention to use telemedicine apps, challenging the traditional oversight of social influence in the TAM framework. The findings will help researchers, practitioners, and governments understand how social influence and e-health literacy influence the adoption of telehealth apps and promote the use of telehealth apps through enhancing social influence and e-health literacy.

Assessing the Factors Influencing the Adoption of Digital Signatures Among Government Employees in Tanzania

This study aimed at assessing the factors influencing the adoption of digital signatures among government employees in Tanzania. The study was guided by the technology acceptance model (TAM) with an additional of facilitating condition, a construct that was borrowed from the Unified Theory of Acceptance and Use of Technology (UTAUT). The quantitative research design was used by employing a purposive sampling technique to effectively identify cases that would use limited research resources. The study involved sample of 256 respondents drawn from selected government organizations. Findings indicated that the results are consistent with the original TAM framework and the additional factor – facilitating conditions fit well into the model. The results were discussed and recommendations as well as future research directions were suggested.

Predicting attitude, use, and future intentions with translation websites through the TAM framework: a multicultural study among Saudi and South Korean language learners

Machine translation (MT) practice and activity development in education are possible when students with diverse backgrounds contribute to helping define how MT can best be used for language learning. This study employed a questionnaire based on an adapted version of the technology acceptance model (TAM) to gain perspective on the perceptions, attitudes, and use of MT tools like Google Translate among Saudi and Korean university students learning English as a foreign language (EFL). A total of 470 students were recruited from Saudi Arabia and South Korea to complete a questionnaire measuring scales on perceived ease of use, perceived usefulness, attitude, actual use, and intended future use of MT websites. Structural equation modeling analyzed the relationships among the TAM variables. Results found that Saudi and Korean students both reported high levels on the TAM variables, indicating that translation tools were easy to use and useful for studying language. Lower L2 proficiency correlated with greater perceived usefulness and a more positive attitude. Students frequently use MT tools when learning English and plan to continue using them in the future. The model explained 71% of actual use and 42% of behavioral intention to use MT for language learning. Furthermore, Saudi students reported a slightly easier time using MT tools for language learning, while Korean students planned to use MT more often. Other findings, along with practical applications, are presented in this paper.

The influence of information privacy concerns and perceived electricity usage habits on the usage intention of advanced metering infrastructure

According to the increase in electricity consumption in residential buildings, advanced metering infrastructures (AMIs) have been widely installed in residential buildings. AMIs help households to monitor and reduce their electricity consumption. Although the usefulness of AMIs has been validated, there still exist several barriers to their widespread use. This study considers household’s information privacy concerns (IPCs) and perceived electricity usage habits (PEUHs) as barriers to AMI penetration. AMI data on electricity usage may reveal extensive information about households, such as indoor behaviors and appliance types. This information may cause households to be concerned about invasion of privacy, and such concerns may affect AMI usage intentions. In terms of PEUHs, electric power companies argue that households with undesirable electricity usage habits, such as large amount of electricity usage with unpredictable usage patterns, are prospective AMI customers. This study develops IPCs and PEUHs scales and conducts a path analysis based on the framework of technology acceptance model to validate the influence of IPCs and PEUHs on AMI usage intention. The identified effects of IPCs and PEUHs on AMI usage intention are expected to provide practical information for understanding how IPCs and PEUHs influence AMI usage intention from the perspective of households.

Exploring the Consumer Acceptance of Nano Clothing Using a PLS-SEM Analysis

We use an extended framework of the technology acceptance model (TAM) to identify the most significant drivers behind the intention to buy clothes produced with nano fabrics (nano clothing). Based on survey data, we estimate an integrated model that explains this intention as being driven by attitudes, perceived usefulness, and perceived ease of use. The influences of social innovativeness, relative advantage, compatibility, and ecologic concern on perceived usefulness are tested using perceived ease of use as a mediator. We employ a partial least squares path model in WarpPLS 7.0., a predictive technique that informs policies. The results show positive effects for all the studied relationships, with effect sizes underscoring perceived usefulness, attitude, and compatibility as the most suitable targets for practical interventions. Our study expands the TAM framework into the field of nano fashion consumption, shedding light on the potential drivers of the adoption process. Explorations of the topic hold the potential to make a substantial contribution to the promotion of sustainable fashion practices.