Effort Expectancy Research Articles

The Readiness of Private Higher Education Institutions in Indonesia to Adopt Blockchain in Accounting Information Systems

This study aims to evaluate the readiness of Private Higher Education Institutions (HEI) in Indonesia to adopt blockchain technology. Using the Unified Theory of Acceptance and Use of Technology (UTAUT) model, this research explores the factors influencing the acceptance of blockchain technology, including Relative Advantage, Accounting Information Quality, Trust, Performance Expectancy, Effort Expectancy, and Intention to Use. Blockchain, as a decentralized, transparent, and secure technology, has the potential to enhance the accounting systems in Private HEIs. However, the adoption of this technology in the education sector remains at an early stage. This study uses a quantitative approach, with surveys distributed through questionnaires to financial department heads in accredited Private HEI across Indonesia. The findings show that Relative Advantage and Accounting Information Quality have a significant positive impact on Performance Expectancy, while Trust strongly influences Effort Expectancy. Performance Expectancy and Effort Expectancy contribute to the Intention to Use blockchain in Private HEI. This study contributes to the literature on blockchain adoption, particularly in the context of higher education, by emphasizing the potential of this technology to create more efficient, transparent, and secure accounting systems in Private HEI. These findings aim to provide practical guidance for higher education institutions and stakeholders in preparing for successful blockchain implementation.

E-commerce applications: A study of customers’ behavioral intentions and behaviors of using these applications towards online shopping

This study uses the UTAUT2 (Unified theory of acceptance and use of technology) model as well as adding other factors such as Platform Usability, User Autonomy to determine the behavioral intention and behavior of online shoppers using e-commerce applications (ECAs) in Vietnam. Using the analysis results from structural equation modeling, it was shown that Social Influence, Use Proficiency, Hedonic Motivation, User Skill, Effort Expectancy positively affect Behavioral Intention. At the same time, Behavioral Intention is negatively affected by Performance Expectancy. Behavioral Intention and Facilitating Conditions are two factors that positively affect Use Behavior. Besides, User Autonomy negatively affects Use Behavior. The research results are an important basis for ECAs providers, managers and stakeholders to apply in assessing the behavioral intentions and behaviors of online shopping customers using ECAs in Vietnam to promote the use of ECAs in online shopping.

Drivers of Chatbot Adoption among K–12 Teachers in Saudi Arabia

The aim of the current study was to identify the factors influencing teachers’ acceptance of using chatbots in education. To achieve this, we employed the descriptive method, applying the conceptual framework of the unified theory of acceptance and use of technology (UTAUT2) to a sample of 406 teachers from the Eastern Province in Saudi Arabia. By applying structural equation modelling (SEM), the research results revealed that the most influential factors of chatbot acceptance among Saudi teachers were artificial intelligence literacy, followed by hedonic motivation, and then social influence. Meanwhile, performance expectancy, effort expectancy, and facilitating conditions were not significant indicators of teachers’ acceptance of using chatbots in education. In light of these findings, we recommend the following actions: focusing on artificial intelligence literacy for teachers, holding specialised workshops on chatbot applications in education, enhancing teachers’ motivation to use chatbots, and forming professional communities for teachers to exchange experiences and knowledge.

Factors influencing the acceptance and use of a South African data-free job search application

Background: Despite the rise of digital job search tools, many South Africans remain excluded due to connectivity and financial barriers. The digital divide, particularly among youth and low-income groups, limits access to job opportunities, exacerbated by data costs and limited digital skills.Objectives: This study investigates the factors influencing the acceptance and use of a data-free job search application, focusing on challenges related to connectivity, data costs, and digital skills.Method: A qualitative approach is employed, analysing Google Play Store reviews through thematic analysis. The Unified Theory of Acceptance and Use of Technology (UTAUT) framework is applied to explore the influence of performance expectancy, effort expectancy, social influence, and facilitating conditions on user adoption.Results: Performance expectancy, effort expectancy, and facilitating conditions are key drivers of application usage. Positive user experiences with these factors enhance engagement, while negative perceptions of usability and technical issues limit consistent use.Conclusion: Addressing connectivity and usability issues is essential to improving the acceptance and use of data-free job search applications in South Africa. Enhancing performance expectancy, effort expectancy, social influence, and facilitating conditions can significantly increase user engagement.Contribution: The study offers practical insights for developers and policymakers to enhance the accessibility and usability of data-free job search tools, promoting more equitable access to job opportunities for disadvantaged groups.

Decoding Millenial Preferences for M-Health App Features: Strategic Insights for Marketers

Utilizing user satisfaction as a mediating variable, this study attempts to investigate how the Unified Theory of Acceptance and Use of Technology (UTAUT) model affects millennial generation preferences for utilizing mobile health applications (m-health) and what it means for marketing tactics. Four primary UTAUT constructs—performance expectancy, effort expectancy, social influence, and facilitating conditions—are incorporated into this study methodology. For this study, 200 members of the millennial generation participated in a survey. Path analysis techniques were employed in the data analysis to examine the correlation between the variables in the study model. The analysis's conclusions demonstrate that, both directly and through the mediation of user satisfaction, the UTAUT variable significantly influences users' preferences for utilizing m-health applications. This research also highlights the significance of user happiness in influencing preferences. Marketers can utilize this information to inform the development of more successful marketing plans aimed at encouraging the millennial age to adopt mhealth apps. The results have practical significance for marketers creating more engaging and relevant marketing campaigns, as well as for m-health app developers and healthcare providers creating tactics that boost millennials' happiness and user uptake.

MODEL PERILAKU PENGGUNA APLIKASI QRIS DAN HUBUNGANNYA TERHADAP IMPULSIVE BUYING

This type of research is quantitative research that assesses the QRIS user behavior model and its relationship with Impulsive Buying. Research was conducted on people who use QRIS in carrying out online and offline transactions. This research uses the UTAUT approach. This research also supports IKU 1 Polytechnic LP3I Jakarta, namely the work readiness of graduates because of. In this study there are 4 independent variables (X) and 2 dependent variables (Y), namely, performance expectancy (X1), effort expectancy (X2), social influence (X3), facilitating conditions (X4), behavioral intention (Y1), Impulsive Buying (Y2) Respondents in this study were LP3I Jakarta polytechnic students who belonged to generation Z with a birth year range of 2002-2006 who used QRIS as many as 100 people. For more accurate results, respondents taken were those who had used QRIS >5x. The results of hypothesis testing in this research prove that performance expectancy has a significant positive effect on user behavior intention. This means that performance expectancy influences behavioral intention that the use of QRIS digital payments is very fast and efficient. Hypothesis testing in this research proves that effort expectancy has a significant positive effect on user behavior intention. This means that effort expectancy influences behavior intention so that those using QRIS digital payments can learn and become more skilled in using the new information system

PENGARUH SELF EFFICACY, PERFORMANCE EXPECTANCY, EFFORT EXPECTANCY, DAN SOCIAL INFLUENCE TERHADAP NIAT PENGGUNAAN E-WALLET PADA UMKM KECAMATAN GEMOLONG

The purpose of this study is to analyze self-efficacy, performance expectancy, effort expectancy and social influence on the behavioural intention of MSME players in Gemolong Subdistrict to adopt e-wallet. This study uses quantitative research methods, more than 200 questionnaires were distributed to MSME players in Gemolong Subdistrict and 170 were responded obtained to assess the reliability and validity of the instrument. This study uses Partial Least Square Technique using SMARTPLS app. This study found that self-efficacy has a significant influence into e-wallet behaviour intention, the performance expectancy variable found has a significant influence into behaviour intention of e-wallet, the effort expectancy variable wasn’t have significant influence into behavioural intention of e-wallet, and social influence variable found that have a significant influence on behavioural intention of e-wallet.

Nurses' acceptance of nursing information systems: Amulti-center cross-sectional study in China.

In China, nursing information systems (NIS) implementation can face numerous barriers to acceptance, including the attitudes of potential users. However, few studies have evaluated this acceptance. The aim of this study was to explain the acceptance of NIS utilizing a survey based on unified theory of acceptance and use of technology. A multi-center cross-sectional study utilizing an online survey was conducted. SPSS AMOS was used to conduct a structural equation modelling analysis. This research followed the STROBE Checklist. A total of 3973 Nurses participated in the study between January 2023 and March 2023. The acceptance of NIS among nurses was overall moderate to high. The proposed model has been rigorously tested and validated using empirical data, ensuring its credibility and dependability. Performance expectancy (PE), social influence (SI), and attitude significantly and positively affected intentions to use NIS. Effort expectancy (EE) did not show any significant effects in the sample. Facilitating conditions (FCs) was found to have a negative relationship with the intention to use NIS. There was a statistically significant difference BI between the different age groups, working years, and computer training experience. The model demonstrates a good fit with the observed data. This study identified PE, SI, and attitude as facilitators of nurses' intentions to use NIS. The findings about EE indicates that the ease of using NIS does not seem to be a concern among nurses. Moreover, high FC might be perceived as indicative of a complex system or extensive usage, that can lead to increased workload and reduced behavioural intention (BI). The significant differences in BI among various demographic groups highlight the need for more studies understanding the preferences and barriers faced by different, levels of experience and training backgrounds. No patient or public contribution.

Understanding Data-Driven Analytic Decision Making on Air Quality Monitoring an Empirical Study

Air quality monitoring is increasingly relying on data-driven analytic decision-making tools to provide accurate and timely information, forming the background of this study. The objective is to understand the factors influencing the adoption and usage behavior of these tools using the Unified Theory of Acceptance and Use of Technology (UTAUT2) model. The method involves incorporating UTAUT2 constructs Performance Expectancy (PE), Effort Expectancy (EE), Social Influence (SI), Facilitating Conditions (FC), Price Value (PV), Hedonic Motivation (HM), and Habit (H), alongside external variables such as Considered Risk (CR) and Considered Trust (CT). Data from 287 respondents were analyzed to assess their impact on Behavior Intention (BI) and Usage Behavior (UB). The results demonstrate that both trust and risk considerations significantly affect user behavior, underscoring the need to address these factors to enhance the adoption of air quality monitoring systems. In conclusion, this research provides valuable insights for developers and policymakers on improving the implementation and acceptance of data-driven technologies in environmental monitoring, thereby contributing to more effective air quality management.

Determining factors in the adoption of fintech of sharia in Indonesia: analysis of the effect of utaut2, Es-qual, and religiosity

This research examines the antecedents of actional desires towards using Islamic financial application among Indonesian customers. The objectives of the study empirically tested the expanded unified theory of acceptance and use of application (UTAUT2), ES-QUAL and religiosity as independent variables to explain the adoption of Islamic financial application in Indonesia. The method was quantitative. The 200 data are analyzed using the Partial least squares (PLS). The research results show that Effort Expectancy (EE), Social Influence (SI), Hedonic Motivation (HM), Esqual (ESQ), and Religiosity (RE) have a positive effect on Desire to Use Islamic Financial Application (IB). Furthermore, the Desire to Use Islamic Financial Application (IB) positively affects the Use Action of Islamic Financial Application (UB). In addition, only gender (GE) can weaken the influence of hedonic motivation and habit on the Desire to Use Islamic financial application. The influence actional desires to use Islamic financial application because of the lack of research in this domain in Indonesia, especially considering the context of religiosity and combining the concepts of UTAUT2 and ESQUAL. This research contributes to the service quality literature by identifying E-SQ and confirming its effectiveness in FinTech adoption. This can also enhance to the development of understanding financial concepts.

Beyond credit cards: A TEP perspective on buy-now-pay-later adoption

ABSTRACT As the utilization of modern fintech credit products, such as Buy-Now-Pay-Later (BNPL), continues to grow, there is a growing need to enhance our understanding of their adoption. This study aims to uncover the determinants of BNPL adoption by identifying factors from technological, economical, and psychological (TEP) perspectives. This research examines consumer adoption of BNPL by drawing upon the Unified Theory of Acceptance and Use of Technology (UTAUT) and Self-Determination Theory (SDT). A cross-sectional research design was utilized in this study, and data from 226 participants were analyzed using Partial Least Square-Structural Equation Modeling (PLS-SEM). Further, the study used importance-performance map analysis (IPMA) to identify the importance and performance of each independent variable against the intention to adopt BNPL. The findings support the hypotheses that technological factors, performance expectancy, and effort expectancy significantly influence the intention to adopt BNPL. Moreover, the economic factor, the flexibility of payment, is positively associated with forming a positive attitude toward BNPL adoption. Further, psychological factors, perceived competence, and perceived relatedness positively influence perceived usefulness, which, in turn, positively affects the intention to adopt BNPL. The study offers valuable strategic insights for BNPL service providers to formulate impactful go-to-market strategies for broadening their customer reach.

Incidental learning in EFL learners’ vocabulary accumulation: the lens of dual process theory

PurposeDrawing on dual process theory as the overarching framework, this study investigates how different types of incidental vocabulary learning yield different performance, repetition, and continuance intention outcomes and uncovers the underlying mechanism.Design/methodology/approachWe identify four popular types of incidental learning: traditional, a murder mystery game, noneducational live streaming, and VTuber. We propose that the underlying mechanism is the mediating role of perceived novelty as heuristic processing, and effort and performance expectancy as systematic processing. We conduct a between-subject experiment with four groups for the four types of incidental learning. From a total of 220 subjects, 55 valid responses were collected from each group. Analysis of variance and a partial least squares structural equation model are employed to examine the differences and mechanism.FindingsThe results show that noneducational live streaming performs significantly best for all three outcomes. The mechanism test demonstrates that perceived novelty and performance expectancy play significantly positive mediating roles, whereas effort expectancy has a null mediating effect.Originality/valueThe research provides both theoretical and practical implications.

Investigating the factors affecting the intention to adopt smart electricity meters in Indian households

Smart electric meters play a pivotal role in making energy systems decarbonized and automating the energy system. Smart electric meters denote huge business opportunities for both public and private companies. Utility players can manage the electricity demand more efficiently whereas customers can monitor and control the electricity bill through the adoption of smart electric meters. The study examines the factors affecting the adoption intention of smart electric meters in Indian households. This study draws a roadmap that how utility providers and customers can improve the smart electric meters adoption. The study has five independent variables (performance expectancy, effort expectancy, social influence, environmentalism, and hedonic motivation) and one dependent variable (adoption intention). The sample size for the study is four hundred and sixty-two respondents from Delhi and the National Capital Region (NCR). The data was analysed using structural equation modelling (SEM). The results of this study have confirmed that performance expectancy, environmentalism, and social influence have a significant impact on the intention of adopting smart electric meters. Therefore, utility providers can improve their strategies to attract more customers to adopt smart electric meters by focusing more on the performance of smart electric meters and by making them environmentally friendly. This research offers meaningful insights to both customers and utility providers to make energy systems decarbonized and control energy consumption.

Impact of Digital Storytelling on Improving Brand Image Among Consumers

Prior literature has shown that brands can use digital storytelling (DST) to reduce uncertainty among consumers and thus increase sales. As such, it is important to understand the elements of storytelling and its role in marketing a product. Extant studies have not explored the elements of DST in terms of the technological convenience of the consumer. This study, therefore, examines the mediating impact of DST elements through factors such as perceived efficiency, social interaction, effort expectancy, and facilitating conditions. The Unified Theory of Acceptance and Use of Technology (UTAUT) model was employed as a theoretical base for the study. A sample of 305 respondents who had made an online purchase were shown a digital story of a known brand. The results indicate that the elements of storytelling significantly impact the factors of the UTAUT model. Further, these factors mediate the relationship between DST and two dependent variables (behavioral intention and perceived brand image).

Exploring factors affecting E-Commerce Adoption of SMEs in Sri Lanka

This paper seeks to investigate the factors that impact the adoption of E-commerce by small and medium-sized enterprises (SMEs) in Sri Lanka. Explores the impact of various determinants, including performance expectancy, effort expectancy, social influence, facilitating conditions, perceived risk, and adoption intention on the adoption of e-commerce in Sri Lankan SMEs. The study is based on SMEs in the country. The study encompasses Small and Medium Enterprises (SMEs) from four provinces across the country, spanning ten different industries. A sample of 252 Small and Medium Enterprises (SMEs) across 10 industrial sectors in 4 regions was selected using a simple random sampling technique.The results indicated that Performance Expectancy, Effort Expectancy, Facilitating Conditions, and Perceived Risk as major influences on the adoption of e-commerce significantly influenced the adoption of e-commerce by SMEs in Sri Lanka. However, it was observed that comparatively reduced influence of Social Influence on E-commerce adoption among SMEs.

Determinants of Behavioral Intention Toward Telemedicine Services in Indonesia Post-Pandemic COVID-19

The COVID-19 pandemic has significantly disrupted daily life & accelerated the adoption of digital technologies across various sectors, including healthcare. In Indonesia, this shift has prompted the rapid development and implementation of Telemedicine services by both start-ups and established healthcare institutions. This study aims to identify the factors that influence customer intention to use Telemedicine services in the post-pandemic period, using the Unified Theory of Acceptance and Use of Technology (UTAUT2) model. The research focuses on five key variables: Price Value, Effort Expectancy, Geographical Location, Performance Expectancy, and Social Influence. Data collected from 507 respondents across Indonesia through an online questionnaire reveals that user satisfaction is critical for further use of Telemedicine services. The findings indicate that improvements in the affordability, user-friendliness, accessibility, effectiveness, and social endorsement of Telemedicine services significantly enhance user satisfaction. The study provides practical recommendations for Telemedicine providers to improve these factors, thereby increasing customer retention and adoption rates. This research contributes to the understanding and offers insights for optimizing Telemedicine services in Indonesia in the evolving post-pandemic behaviors

Examining the dynamics of mobile banking app. Adoption during the COVID-19 pandemic: A digital shift in the crisis

Mobile banking applications (apps) have become crucial in maintaining financial services accessibility during the COVID-19 pandemic. This study leverages the Unified Theory of Acceptance and Use of Technology (UTAUT) to examine Malaysian millennials' behavioral intentions toward mobile banking app adoption, aiming to aid banks in developing targeted strategies to expand their user base. Data collection was conducted from October 2020 to February 2021 during the peak of the COVID-19 pandemic. A survey was administered to 270 respondents using convenience and snowball sampling methods. The Sequential Least Square method was used for the analysis. Our findings reveal that performance expectancy, effort expectancy, trust, and personal innovativeness significantly influence mobile banking app adoption intentions, whereas social influence and facilitating conditions do not. Demographic factors also modulate these relationships to varying degrees. These insights contribute to theoretical discussions on technology adoption and offer practical guidance for banks looking to enhance their digital service offerings in a post-pandemic landscape. This study underscores the shifts in consumer behavior triggered by the pandemic and highlights the ongoing potential for digital banking growth in Malaysia.

Examining Farmers’ Usage Behavior on Agricultural E-Markets: Integrating UTUAT2 and Swift Guanxi Factors

The agricultural sector recognizes the potential of electronic marketplaces (e-markets) in enhancing efficiency, market access, and pricing over traditional markets. Despite this acknowledgment, farmers’ adoption of these platforms in developing countries remains limited. This study examines the determinants of farmers’ usage behavior on agricultural e-market platforms by integrating the UTUAT2 and swift guanxi factors. The study employed a self-administered questionnaire to gather data from 330 farmers in India who had exposure to agricultural e-markets and utilized PLS-SEM to analyze the data collected through purposive sampling. The study found that UTAUT2 and swift guanxi factors significantly influence farmers’ intentions to adopt agricultural e-markets, with the exception of effort expectancy. The outcomes of the multigroup analyses indicate that both educational qualifications and crop type significantly influence farmers’ usage behavior. This study contributes to practical applications and academic literature by integrating the UTAUT2 framework and swift guanxi concepts in the context of the agricultural e-market. Notably, while all dimensions prove significant, the negative impact of effort expectancy on usage intention stands out, a departure from previous e-commerce studies. This study enriches the technology adoption literature by uncovering the pivotal factors shaping farmers’ adoption of e-market platforms in agriculture.

Intention to use personal health record system and its predictors among chronic patients enrolled at public hospitals in Bahir Dar city, northwest Ethiopia: using modified UTAUT2 model.

Chronic diseases are the leading causes of death in the world. In sub-Saharan Africa, it leads to more mortality than almost every other region in the world. Currently, digital health technology like personal health records plays a crucial role in managing patients with chronic diseases. In low-resource countries like Ethiopia, it is uncertain how many chronic patients intend to use PHRs and the accompanying circumstances. Hence, the aim of this study was to assess chronic patients' intention to use PHRs and its predictors enrolled in public health hospitals in Bahir Dar city, northwest Ethiopia. An institutional-based cross-sectional study was conducted among 924 respondents from April 5 to May 9, 2023, in Bahir-Dar city public hospitals. A stratified sampling technique followed by a systematic sampling technique was applied to select the study participants. An interviewer-administrated questionnaire was conducted using Kobo Collect. A UTAUT2 model was applied to develop theoretical frameworks. SPSS version 25 software was used to estimate the descriptive statistics, and the structural equation model analysis was used to evaluate model constructs using AMOS version 21 software. In this study, a total of 908 study subjects participated. The proportion of chronic patients' intention to use PHR was 46.7% [95.0% CI (43.4-50.1)]. According to the findings, performance expectancy (β = 0.259, p-value <0.001), effort expectancy (β = 0.214, p-value <0.001), social influence (β = 0.174, p-value <0.001), and facilitating condition (β = 0.114, p-value <0.01) had a significant effect on the intention to use PHRs. Generally, the overall intention to use PHR was low. Our finding illustrates that the effects of performance expectancy, effort expectancy, social influence, and facilitating conditions had a positive effect on patients' intentions to use PHRs. The effect of effort expectancy on the intention to use a PHR was positively moderated by age. Since the findings of this study would help policymakers and programmers to future academics interested in this area and insight to future research workers. Therefore, implementers should focus on improving patient capacity, motivating users, and raising awareness regarding PHR.

How to avoid sinking in swamp: exploring the intentions of digitally disadvantaged groups to use a new public infrastructure that combines physical and virtual spaces

With advances in digital technology, physical and virtual spaces have gradually merged. For digitally disadvantaged groups, this transformation is both convenient and potentially supportive. Previous research on public infrastructure has been limited to improvements in physical facilities, and few researchers have investigated the use of mixed physical and virtual spaces. In this study, we focused on integrated virtual and physical spaces and investigated the factors affecting digitally disadvantaged groups’ intentions to use this new infrastructure. Building on a unified theory of the acceptance and use of technology, we focused on social interaction anxiety, identified the characteristics of digitally disadvantaged groups, and constructed a research model to examine intentions to use the new infrastructure. We obtained 337 valid data from the questionnaire and analysed them using partial least squares structural equation modelling. The results showed positive relationships between performance expectancy, perceived institutional support, perceived marketplace influence, effort expectancy, and facilitating conditions. The influence of psychological reactance was significantly negative. Finally, social interaction anxiety had a regulatory effect on performance expectancy, psychological reactance, perceived marketplace influence, and effort expectancy. Its effects on perceived institutional support and facilitating conditions were not significant. The results support the creation of inclusive smart cities by ensuring that the new public infrastructure is suitable for digitally disadvantaged groups. Meanwhile, this study presents new theoretical concepts of new public infrastructures, mixed physical and virtual spaces, which provides a forward-looking approach to studying digitally disadvantaged groups in this field and paves the way for subsequent scholars to explore the field in theory and literature.