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Purpose: The emergence of artificial intelligence technologies, like ChatGPT, has taken the world by storm, particularly in the education sector. This study aims to adopt the unified theory of acceptance and use of technology to explore how effort expectancy (EEC) and performance expectancy (PEE) individually, jointly, congruently and incongruently affect higher education students' intentions and actual uses of ChatGPT for their learning. Design/methodology/approach: An advanced methodology--polynomial regression with response surface analysis--and a sample of 1,461 higher education students recruited in Vietnam through three-phase stratified random sampling approach were adopted to test developed hypotheses. Findings: Both EEC and PEE were found to have a direct positive impact on the likelihood of higher education students' intention to use ChatGPT, which in turn promotes them actually use this tool for learning purposes. Conversely, a large incongruence between EEC and PEE will lower the level of intentions and actual uses of ChatGPT for learning. However, when there is a growing incongruence between EEC and PEE, either in a positive or negative direction, the likelihood of students' intentions to use ChatGPT for learning decreases. Practical implications: Some practical implications are subsequently recommended to obtain advantages and address potential threats arising from the implementation of this novel technology in the education context. Originality/value: This study shed the new light on the educational setting by testing how higher education students' intentions to use ChatGPT and subsequent actual uses of ChatGPT are synthesized from the balance between high EEC and PEE.

The human and social dimensions of knowledge transfer are essential to understand applied solutions for improving climate, land sustainability, and food production. The lack of knowledge and dissemination mechanisms of precision agriculture (PA) among agricultural Extension professionals hinder widespread PA adoption initiatives. Three theories were adapted to examine the comprehensive structural relationships between the factors affecting intentions to promote PA technologies. We surveyed 255 Extension agents and specialists from three U. S. states' agricultural Extension systems with an instrument using six constructs measured as multi-item scales and demographic items. Data were analysed using SPSS 28.0 for descriptive and inferential statistics. The results indicated that Extension professionals were somewhat knowledgeable about PA but had low self-efficacy in promoting PA. In addition, a significant positive relationship existed between behavioural intention and performance expectancy, social influence, self-efficacy, effort expectancy, and facilitating conditions. Multiple regression results indicated that performance expectancy, social influence, and facilitating conditions significantly predicted behavioural intention to promote PA. The results underscore the importance of enhancing Extension professionals' performance expectancy, social influence, and access to facilitating conditions to foster PA technology adoption. By addressing these key factors, stakeholders can develop strategic initiatives that not only improve PA knowledge transfer but also contribute to the broader goals of sustainable agricultural practices and the achievement of multiple Sustainable Development Goals. We recommend that future research can further evaluate and validate the key factors that have been identified as contributing to the dissemination of PA, thereby improving land sustainability and food security. [ABSTRACT FROM AUTHOR]

Technostress can be seen as a relevant factor that may affect student satisfaction and student performance. However, a lack of research has been carried out to analyse the simultaneous effect of the four technostress dimensions, namely techno-overload, techno-complexity, techno-insecurity, and techno-uncertainty on student satisfaction and performance expectancy. Performance expectancy is appropriate to use as an endogenous construct since this research was carried out during open and distance learning (ODL) implementation and before the final examination. Hence, this study aims to investigate the association between the four technostress dimensions towards student satisfaction. This research also seeks to examine the relationship between student satisfaction and performance expectancy among undergraduates. A total of 500 self-administered questionnaires were distributed but 458 valid questionnaires were found. All of the respondents were at the diploma level from UiTM Pahang Branch Campus. An online survey questionnaire was used since all respondents were in their hometowns due to the Malaysian government's Movement Control Order (MCO). In this study, SEMAMOS was conducted to evaluate the measurement model and to test the hypotheses. This study found that techno-complexity displays a more significant contribution to student satisfaction and performance expectancy than techno-uncertainty. However, the results explicitly imply that the influence of techno-overload and techno-insecurity on students' satisfaction and performance expectancy is not significant.

• This study provides a new perspective on the interplay between the benefit and cost perceptions of ICT use to support clinical learning methods in nursing education, complementing two well-known models of technology acceptance: Unified Theory of Acceptance and Use of Technology and Technology Acceptance Model. • Nursing students' performance expectancy is positively associated with the intention to adopt ICT and social media, while effort expectancy positively moderates this relationship. • We recommend nursing education and training prioritize communicating the benefits of ICTs and social media over ease of use to improve the effectiveness and efficiency of nursing education and training while lowering costs. The integration of information and communication technologies (ICT) in clinical learning is crucial for evidence-based nursing and student-centered learning. The study examines whether effort expectancy moderates the relationship between performance expectancy and ICT usage intention among Moroccan nursing students. The Bayesian Mindsponge Framework analytics, combining the reasoning strengths of Mindsponge Theory and inference advantages of Bayesian analysis, was employed on a dataset of 702 students. We found that students' performance expectancy is positively associated with the intention to adopt ICT and social media, while effort expectancy positively moderates this relationship. Moreover, the model with effort expectancy as the moderator was discovered to have a significantly larger weight than the model with effort expectancy as the direct predictor, validating the information-processing reasoning of the Mindsponge Theory. These findings add theoretical novelty to the existing literature on the Technology Acceptance Model and the Unified Theory of Acceptance and Use of Technology. Practically, they provide insights for communication priorities regarding ICTs to improve the effectiveness and efficiency of nursing education and training while lowering costs. [ABSTRACT FROM AUTHOR]

Purpose: This study aimed to explore the technostress effects on the students' expectancy in their academic performance. Three main factors were used as predictors, namely techno-complexity (TC), techno-insecurity (TIS) and techno-overload (TO), to measure the students' performance expectancy via the mediating effects of student satisfaction (SS). Design/methodology/approach: A total of 234 survey-based online questionnaires were filled by students from Universiti Teknologi Mara (UiTM). Based on the data, the hypothetical model was tested statistically using the Partial Least Square--Structural Equation Modelling (PLS-SEM), specifically the Smart Partial Least Square (SmartPLS) version 3.3.2. Findings: The results indicated that SS mediated the relationship between TC, TIS and performance expectancy. Nevertheless, the two predictors (TC and TIS) negatively affected SS, whereas SS positively affected the performance expectancy. The findings further revealed that reducing TC and TIS could increase SS and their expectancy to achieve better academic performance. Practical implications: This study proposed that higher learning institutions provide an innovative and user-friendly platform for the online learning environment. Consequently, this improvement could increase SS with the online learning experience and motivate them to expect better academic achievement. Originality/value: This study also contributed to the existing literature by building and testing a technostress model and articulating the inter-relations between SS and performance expectancy.

GoPay is a leader amongst mobile wallet service providers, however the position is threatened by the coming of new players in the market. This research aims to investigate the influence of performance expectancy and the perception of security towards continuance usage intention and satisfaction’s role as the mediator on GoPay users in Banda Aceh. It is conducted by distributed online questionnaires to GoPay users which result in 90 respondents. Partial Least Square-Structural Equation Model (PLS-SEM) was used for data analysis. This study found that performance expectancy and satisfaction affect users’ intention to continue using GoPay. However, no direct influence is found in the relationship between perceived security and users’ willingness to continue using GoPay. This study also found that satisfaction can act as the mediator in the relationship between performance expectancy, perceived security, and intention to continue.

Over the past few decades, there has been a significant advancement in the development of mobile commerce. This study examines the effect of performance expectancy, effort expectancy, and perceived trust on the acceptance of mobile commerce through intention. Convenience sampling was employed whereby 400 survey questionnaires were distributed to consumers residing in Malaysia's Klang Valley area who possess smartphones and engage in mobile commerce transactions. The study's hypotheses were determined using a two-phase structural equation modeling procedure. The results indicated that perceived trust, performance expectancy, and effort expectancy significantly impact the intention to utilize mobile commerce. Moreover, the adoption of mobile commerce is significantly impacted by the purpose of utilizing mobile commerce, as well as the enabling circumstances. The results also showed that perceived trust indirectly affected the acceptance of mobile commerce through intention. However, these insights benefit mobile commerce providers and enterprises seeking to improve the acceptance of mobile commerce transactions in Malaysia. These discoveries will be advantageous for academicians, researchers, marketers, and other stakeholders in the sector.

Study designQuantitative survey study is the study design.ObjectivesThe study aims to develop a model for the factors that drive or impede the use of an artificial intelligence clinical decision support system (CDSS) called PROPOSE, which supports shared decision-making on the choice of treatment of ordinary spinal disorders.MethodsA total of 62 spine surgeons were asked to complete a questionnaire regarding their behavioral intention to use the CDSS after being introduced to PROPOSE. The model behind the questionnaire was the Unified Theory of Acceptance and Use of Technology. Data were analyzed using partial least squares structural equation modeling.ResultsThe degree of ease of use associated with the new technology (effort expectancy/usability) and the degree to which an individual believes that using a new technology will help them attain gains in job performance (performance expectancy) were the most important factors. Social influence and trust in the CDSS were other factors in the path model. r2 for the model was 0.63, indicating that almost two-thirds of the variance in the model was explained. The only significant effect in the multigroup analyses of path differences between two subgroups was for PROPOSE use and social influence (p = 0.01).ConclusionShared decision-making is essential to meet patient expectations in spine surgery. A trustworthy CDSS with ease of use and satisfactory predictive ability promoted by the leadership will stand the best chance of acceptance and bridging the communication gap between the surgeon and the patient.

BackgroundChatGPT (OpenAI) is a powerful tool for a wide range of tasks, from entertainment and creativity to health care queries. There are potential risks and benefits associated with this technology. In the discourse concerning the deployment of ChatGPT and similar large language models, it is sensible to recommend their use primarily for tasks a human user can execute accurately. As we transition into the subsequent phase of ChatGPT deployment, establishing realistic performance expectations and understanding users’ perceptions of risk associated with its use are crucial in determining the successful integration of this artificial intelligence (AI) technology. ObjectiveThe aim of the study is to explore how perceived workload, satisfaction, performance expectancy, and risk-benefit perception influence users’ trust in ChatGPT. MethodsA semistructured, web-based survey was conducted with 607 adults in the United States who actively use ChatGPT. The survey questions were adapted from constructs used in various models and theories such as the technology acceptance model, the theory of planned behavior, the unified theory of acceptance and use of technology, and research on trust and security in digital environments. To test our hypotheses and structural model, we used the partial least squares structural equation modeling method, a widely used approach for multivariate analysis. ResultsA total of 607 people responded to our survey. A significant portion of the participants held at least a high school diploma (n=204, 33.6%), and the majority had a bachelor’s degree (n=262, 43.1%). The primary motivations for participants to use ChatGPT were for acquiring information (n=219, 36.1%), amusement (n=203, 33.4%), and addressing problems (n=135, 22.2%). Some participants used it for health-related inquiries (n=44, 7.2%), while a few others (n=6, 1%) used it for miscellaneous activities such as brainstorming, grammar verification, and blog content creation. Our model explained 64.6% of the variance in trust. Our analysis indicated a significant relationship between (1) workload and satisfaction, (2) trust and satisfaction, (3) performance expectations and trust, and (4) risk-benefit perception and trust. ConclusionsThe findings underscore the importance of ensuring user-friendly design and functionality in AI-based applications to reduce workload and enhance user satisfaction, thereby increasing user trust. Future research should further explore the relationship between risk-benefit perception and trust in the context of AI chatbots.

Purpose: This study aimed to investigate the role of effort expectancy, social influences, and facilitating conditions in the intention to use information and communication technology with the mediating role of performance expectancy among graduate students of Tabriz University of Medical Sciences.Methodology: The present study is a descriptive-survey correlational study based on the structural equation model in terms of applied purpose and in terms of data collection. The statistical population of the study is all graduate students of Tabriz University of Medical Sciences with a number of 1500 people. The statistical sample of this research is 306 people who have been selected by the stratified random sampling method. The data collection tool is a translation and synthesis of a standard questionnaire based on the use of technology modified by the researcher. The validity of the questionnaire was confirmed based on content validity, face validity, and construct validity (confirmatory factor analysis, CFA) and its reliability coefficient was obtained based on Cronbach's alpha coefficient which is equal to 0.86. The collected data were analyzed using descriptive statistics (frequency, mean, standard deviation, and Pearson correlation coefficient) and inferential statistics (path analysis of structural equation model) by SPSS and LISREL software.Finding: The results showed that the variables of effort expectancy, social influences, and facilitator conditions with mediating role of performance expectancy have a positive and significant causal effect on the intention to use information and communication technology of Tabriz University of Medical Sciences students with mediating role of performance expectation (p

Medicine is a discipline based on and nurtured by scientific research and technological development. The use of health services supported by information technology is increasing worldwide, and Latin America is no exception. Factors such as needing more specialists in peripheral cities, large geographic areas, and socio-cultural aspects limit the possibility of receiving timely and quality medical care services. Information Technology (IT) for health purposes, such as e-health, is a cost-effective solution for equitable access to quality healthcare services and optimization of the rising associated costs. As an e-health service, telemedicine facilitates and mediates distance communication between the patient and medical staff. Even though Latin America is at the beginning of the development of telemedicine, it would have a relevant impact, given the geographic and socioeconomic conditions of the population in this part of the world. Drawing on the extended Unified Theory of Acceptance and Use of Technology (UTAUT2) theory, we developed a theoretical model to identify the latent factors influencing the public acceptance of telemedicine and examined their interrelationships. A survey questionnaire was designed and administered to 391 residents in Antofagasta, a mine region of Chile. After that, structural equation modeling was employed to analyze the survey data. The results reveal that the UTAUT2 factors' performance expectancy, social influence, and price value significantly impact the intention to use (R2 = 0.693). Additionally, the model presented a good fit. This study enriches the existing theoretical research on the acceptance of telemedicine services and offers insights into understanding and managing technology in the Chilean health sector.

This study aims to analyze the socio-economic dimensions and performance expected by customers in using Kredit Adil Cooperative application fintech, Sakti.link. This research was carried out at the Kredit Adil Cooperative in Dlingo, Bantul, the only cooperative that has used fintech and serves areas spread across Bantul. Data was collected by survey method on 200 respondents with purposive sampling technique. The data analysis technique used Structural Equation Modeling (SEM) PLS. The results show that the socio-economic effect that affect customers using fintech in cooperatives are income, occupation, the distance (space) of the customer's domicile with financial institutions, and education (education). The variable of performance expectancy that affect the use of fintech include cost efficiency, residual income, ability to disburse loans/liquidity (ability to disburse loans), time efficiency (time efficiency), and environmentally friendly (paperless). The use of fintech is seen based on transaction traffic, the number of users, and changes in the structure of outstanding loans and bad loans.

Background: ChatGPT (OpenAI) is a powerful tool for a wide range of tasks, from entertainment and creativity to health care queries. There are potential risks and benefits associated with this technology. In the discourse concerning the deployment of ChatGPT and similar large language models, it is sensible to recommend their use primarily for tasks a human user can execute accurately. As we transition into the subsequent phase of ChatGPT deployment, establishing realistic performance expectations and understanding users' perceptions of risk associated with its use are crucial in determining the successful integration of this artificial intelligence (AI) technology., Objective: The aim of the study is to explore how perceived workload, satisfaction, performance expectancy, and risk-benefit perception influence users' trust in ChatGPT., Methods: A semistructured, web-based survey was conducted with 607 adults in the United States who actively use ChatGPT. The survey questions were adapted from constructs used in various models and theories such as the technology acceptance model, the theory of planned behavior, the unified theory of acceptance and use of technology, and research on trust and security in digital environments. To test our hypotheses and structural model, we used the partial least squares structural equation modeling method, a widely used approach for multivariate analysis., Results: A total of 607 people responded to our survey. A significant portion of the participants held at least a high school diploma (n=204, 33.6%), and the majority had a bachelor's degree (n=262, 43.1%). The primary motivations for participants to use ChatGPT were for acquiring information (n=219, 36.1%), amusement (n=203, 33.4%), and addressing problems (n=135, 22.2%). Some participants used it for health-related inquiries (n=44, 7.2%), while a few others (n=6, 1%) used it for miscellaneous activities such as brainstorming, grammar verification, and blog content creation. Our model explained 64.6% of the variance in trust. Our analysis indicated a significant relationship between (1) workload and satisfaction, (2) trust and satisfaction, (3) performance expectations and trust, and (4) risk-benefit perception and trust., Conclusions: The findings underscore the importance of ensuring user-friendly design and functionality in AI-based applications to reduce workload and enhance user satisfaction, thereby increasing user trust. Future research should further explore the relationship between risk-benefit perception and trust in the context of AI chatbots., (©Avishek Choudhury, Hamid Shamszare. Originally published in JMIR Human Factors (https://humanfactors.jmir.org), 27.05.2024.)

Social media are platforms through which people of the different networks create, share and exchange information, ideas and also market products such as books in a virtual community. They are instruments for communication that do not just pass information but interact with customers. Since many benefits are derivable from the use of social media for marketing, it becomes imperative to investigate how book marketers use social media to achieve the objectives of their organisations. This study adopted a descriptive research design of correlational type. The population of the study was 212 marketing and sales staff of selected publishing firms. The total enumeration sampling technique was used to collect data from the respondents. A questionnaire was the instrument used for data collection and data collected were analysed through the use of descriptive statistics such as frequency distribution, percentages, mean and standard deviation. The hypothesis was tested at a 0.05 level of significance. The results showed the performance expectancy of staff of publishing firms in the use of social media for marketing to be high. There was also a significant relationship between performance expectancy and use of social media by the staff of publishing firms (Perceived usefulness r=0.150, p<0.05, relative advantage r= 0.226, p<0.05 and outcome expectation r= 0.343, p<0.05). The study concluded that publishing firms should intensify efforts towards ensuring the proper and effective use of social media as well as providing ICT tools for effective marketing of published books. [ABSTRACT FROM AUTHOR]

The purpose of this study is to examine the effect of performance expectancy on the interest in implementing a regional financial management information system (SIPKD). This research is based on the results of a test of 80 respondents using information systems of regional financial managers who work in the government of Padang City Hall. This study uses a research respondent that is distributed directly and uses a simple linear regression technique to test the research data with the help of SPSS 25. This study uses an independent variable performance expectancy and one dependent variable, namely: interest in implementing regional financial management information systems. The results of the study show that partially, performance expectancy has a significant effect on the interest in implementing the regional financial management information system

Aim/Purpose: This study examines the influence of Performance Expectancy (PE), Effort Expectancy (EE), and Facilitating Conditions (FC) on the use of smart phones for mobile learning by postgraduate students in University of Ibadan, Nigeria. Background: Due to the low level of mobile learning adoption by students in Nigeria, three base constructs of the Unified Theory of Acceptance and Use of Technology (UTAUT) model were used as factors to determine smart phone use for mobile learning by the postgraduate students in the University of Ibadan. Methodology: The study adopted a descriptive survey research design of the correlational type, the two-stage random sampling technique was used to select a sample size of 217 respondents, and a questionnaire was used to collect data. Descriptive statistics (frequency counts, percentages, mean, and standard deviation), test of norm, and inferential statistics (correlation and regression analysis) were used to analyze the data collected. Contribution: The study empirically validated the UTAUT model as a model useful in predicting smart phone use for mobile learning by postgraduate students in developing countries. Findings: The study revealed that a significant number of postgraduate students used their smart phones for mobile learning on a weekly basis. Findings also revealed a moderate level of Performance Expectancy (x-bar=16.97), Effort Expectancy (x-bar=12.57) and Facilitating Conditions (x-bar=15.39) towards the use of smart phones for mobile learning. Results showed a significant positive relationship between all the independent variables and use of smart phones for mobile learning (PE, r=0.527; EE, r=0.724; and FCs, r=0.514). Out of the independent variables, PE was the strongest predictor of smart phone use for mobile learning (beta=0.189). Recommendations for Practitioners: Librarians in the university library should organize periodic workshops for postgraduate students in order to expose them to the various ways of using their smart phones to access electronic databases. Recommendations for Researchers: There is a need for extensive studies on the factors influencing mobile technologies adoption and use in learning in developing countries. Impact on Society: Nowadays, mobile learning is increasingly being adopted over conventional learning systems due to its numerous benefits. Thus, this study provides an insight into the issues influencing the use of smart phones for mobile learning by postgraduate students from developing countries. Future research: This study utilized the base constructs of the UTAUT model to determine smart phone use for mobile learning by postgraduate students in a Nigerian university. Subsequent research should focus on other theories to ascertain factors influencing Information Technology adoption and usage by students in developing countries.

Global environment is now changing drastically, and a revolutionary change has been observed in consumer buying behavior, radically shifting from physically environment to mobile commerce. Regardless of the previous researches that has executed by researches over the last two decades on the adoption behavior of mobile commerce in a field of marketing and IT, further empirical investigation is required to explore the individual characteristic such as personal innovativeness that stimulate the consumers to adopt the mobile commerce services. Primarily this research is conducted to understand the relationships among performance expectancy, effort expectancy, personal innovativeness and behavioral intentions in a Pakistani consumer market and how individual variable dubbed personal innovativeness mediates the relationship among performance expectancy, effort expectancy, personal innovativeness and behavioral intentions using framework of unified theory of acceptance and use of technology (UTAUT). The study has conducted a questionnaire-based survey of 320 users of mobile commerce in total. Structural equation modeling (SEM) technique is used through AMOS version 23. Results show that the performance expectancy and effort expectancy are significantly influence the behavioral intentions to adopt mobile commerce with significant effect of mediator and the results for this study could be fruitful for telecommunication, mobile commerce companies and marketers in formulating strategies to attract potential consumers effectively and efficiently. The present study enriches and adds value to limited literature on performance expectancy, effort expectancy, personal innovativeness and behavioral intentions. In addition, personal innovativeness has not been inspected earlier as a mediating variable.

Purpose: Drawing on the Theory of Planned Behavior, this study aims to explore the role of individual digital competencies, encompassing information and data literacy, communication and collaboration, safety and security, and problem-solving, in shaping cognitive determinants and influencing digital entrepreneurial intentions as well as investigates the moderating effect of performance expectancy of AI solutions on the relationship between digital competencies, cognitive determinants, and digital entrepreneurial intention. Design/methodology/approach: Using a sample of 1326 MBA students in Vietnam with a stratified sampling approach, the second-order PLS-SEM is used to test the formulated hypotheses rigorously. Findings: The study reveals that individual digital competencies, sculpted by information and data literacy, communication and collaboration, safety and security, and problem-solving, significantly impact cognitive determinants (attitude towards digital entrepreneurship, subjective norms, and perceived behavioral control), influencing digital entrepreneurial intentions. Performance expectancy of AI solutions also plays a crucial moderating role, enhancing the relationship between digital competencies and digital entrepreneurial intention. Research limitations/implications: Some practical implications have been recommended for policymakers, educators, and entrepreneurs. Originality/value: This research provides original empirical findings, validating the impact of a varied array of digital competencies on entrepreneurial mindsets/cognition and intentions. The introduction of performance expectancy of AI solutions as a moderator introduces a nuanced dimension to comprehending the interaction between technological skills and entrepreneurial intentions. [ABSTRACT FROM AUTHOR]