Search results

This research aims to explore factors influencing accountants' usage of enterprise resource planning (ERP) at a global development agency. The paper tests a model, which hypothesised that attitudes, performance expectancy, effort expectancy, social influence and self-efficacy would have significant and positive effects on behavioural intention to use, and facilitating conditions and behavioural intention would have significant and positive effects on frequency of use (actual usage).

The study utilised a quantitative approach through an online survey of 104 respondents from the different countries that the organisation operates within.

Using multiple regression analysis, the findings showed that attitudes towards use, performance expectancy, self-efficacy and effort expectancy were significant predictors of behavioural intention to use the ERP system. Behavioural intentions and facilitating conditions significantly and positively influenced actual ERP usage. Social influence was found to be non-significant.

The study used a small sample drawn from a single organization.

The paper tests a model of usage of ERP and identifies those factors that are likely to influence ERP usage in a global development agency.

The paper supplements the existing literature on ERP usage in global organizations.

Consumers interacting with smart wearable devices is on the rise in the current health-AI market, which offers a great opportunity for companies to execute interactive marketing. However, this opportunity is mainly reliant on consumers' use of smart wearable devices. This paper aims to develop a model considering health and privacy factors to elucidate consumers' use of smart wearable devices for unleashing their full potential in interactive marketing.

The authors collected 250 samples via an online survey to validate the smart wearable devices usage model that elucidates factors that stimulate consumer usage, including privacy concerns, health consciousness and consumer innovativeness. The authors used structural equation modeling and multi-group analysis to test the hypotheses.

Privacy concerns of consumers have a negative effect on smart wearable devices usage, while health consciousness positively impacts consumers' usage of smart wearable devices. Consumer innovativeness indirectly affects smart wearable devices usage via effort expectancy. Experienced consumers are less sensitive to the performance expectancy but more affected by effort expectancy regarding smart wearable devices.

The present study contributes to the literature stream of health-AI usage by unraveling the impacts of privacy concerns and health consciousness and examining the moderating role of prior experience. The findings suggest marketers in the health-AI industry should endeavor to build transparent and sound privacy protection mechanisms and promote smart wearable devices by fostering health awareness of potential consumers.

Banks and financial services providers are increasingly delivering their services via electronic banking, also known as e-banking. Yet even though this type of delivery is now common, the degree of personalization in the services provided via this channel exhibit considerable variation. The purpose of this paper is to examine the impact of service personalization on consumer reaction to the e-banking service. Based on research of information and communication technology (ICT) service innovation and the Unified Theory of Acceptance and Use of Technology (UTAUT) model, this study further examines one contingent factor, compatibility with previous experience with e-banking. This study focuses on the interactions effect of personalization and technology compatibility on customer e-banking service usage.

A survey was conducted to investigate the impacts of personalization on e-banking usage decision process and the interactions between personalization and compatibility with past e-banking experience. Quota sampling was applied and different type of customers were approached in 30 branches of the commercial bank. Data were collected from a sample of 181 banking customers in a metropolitan region in southern China.

The results indicated that personalization leads to increased performance expectancy and decreased effort expectancy, which in turn lead to increasing intention to continue to use e-banking services. In addition, compatibility with previous e-banking experience and personalization produces an interaction effect on both performance expectancy and effort expectancy.

The theoretical contribution of this study is to demonstrate how the contingent factor of compatibility moderates the impact of personalization, thus extending the UTAUT model in the area of e-banking service adoption. Implications are twofold: personalization influences evaluations of both utility and ease of use, and the effect is magnified when compatibility with prior e-banking experience is factored into the model. This is an important extension and future research should examine whether the same relationship holds in other industries using new technologies to deliver services. The UTAUT model, after extension by including the moderating impact of compatibility, works well in demonstrating the impact of various factors on the adoption of a new technological delivery system for a service.

This study has two significant implications for managerial practices. First, the study sheds lights on the segmentation of e-banking customers. Modern marketers know that the best way to engage with consumers is through personal messaging strategies and should make great efforts to identify customers before trying to reach them. In the e-banking realm, consumer banking preferences keep changing. With a clear understanding of the different consumer banker segments, financial institutions can identify which channels appeal to them. For example, some users are more likely than average to use e-banking. Second, this study helps e-banking service provider design different personalized e-banking service for different customers.

This study sheds light on social value of personalization, particularly among those new to a delivery platform.

This study provides evidence demonstrating that personalization increases customer perceptions of performance expectancy and decreases effort expectancy, and that the effect is most profound for customers with limited level of perceived compatibility with past experience with e-banking. This paper extended the UTAUT model and research on ICT service innovation by providing more insights on the impacts of e-banking service personalization and the contingency impact of user’s background in e-banking context.

Satisfaction and experience are essential ingredients for successful customer retention. This study aims to verify the moderating effect of experience on two types of relationships: the relationship of certain antecedents with satisfaction, and the relationship of satisfaction with intention to repurchase.

This paper applies structural equation modelling (SEM) and multi-group analysis to examine the moderating role of experience in a conceptual model estimating the intention to repurchase. Responses from 393 people were used to examine the differences between high- and low-experienced users of online shopping.

The research shows that experience has moderating effects on the relationships between performance expectancy and satisfaction and satisfaction and intention to repurchase. This study empirically demonstrates that prior customer experience strengthens the relationship between performance expectancy and satisfaction, while it weakens the relationship of satisfaction with intention to repurchase.

Practitioners should differentiate the way they treat their customers based on their level of experience. Specifically, the empirical research demonstrates that the expected performance of the online shopping experience (performance expectancy) affects satisfaction only on high-experienced customers. Instead, the effort needed to use online shopping (effort expectancy) and the user's belief in own abilities to use online shopping (self-efficacy) influence satisfaction only on low-experienced customers. The effect of trust and satisfaction is significant on online shopping behaviour on both high- and low-experienced customers.

This paper investigates how different levels of experience affect customers' satisfaction and online shopping behaviour. It is proved that experience moderates the effect of performance expectancy on satisfaction and the effect of satisfaction on intention to repurchase. It also demonstrates that certain effects (effort expectancy and performance expectancy) are valid for only one of the two examined groups, while only one effect (trust) is valid for both (high- and low-experienced).

The study investigates the consumer’s attitude to using artificial intelligence (AI) devices in hospitality service settings considering social influence, hedonic motivation, anthropomorphism, effort expectancy, performance expectancy and emotions.

This study employed a quantitative methodology to collect data from Bangladeshi consumers who utilized AI-enabled technologies in the hospitality sector. A total of 343 data were collected using a purposive sampling method. The SmartPLS 4.0 software was used to determine the constructs' internal consistency, reliability and validity. This study also applied the partial least squares structural equation modeling (PLS-SEM) to test the research model and hypotheses.

The finding shows that consumer attitude toward AI is influenced by social influence, hedonic motivation, anthropomorphism, performance and effort expectancy and emotions. Specifically, hedonic motivation, social influence and anthropomorphism affect performance and effort expectations, affecting consumer emotion. Moreover, emotions ultimately influenced the perceptions of hotel customers' willingness to use AI devices.

This study provides a practical understanding of issues when adopting more stringent AI-enabled devices in the hospitality sector. Managers, practitioners and decision-makers will get helpful information discussed in this article.

This study investigates the perceptions of guests' attitudes toward the use of AI devices in hospitality services. This study emphasizes the cultural context of the hospitality industry in Bangladesh, but its findings may be reflected in other areas and regions.

The service industry is facing the huge impact of digital transformation, in which artificial intelligence (AI) plays one of the most important roles. This study aims to expand the understanding of the AI acceptance framework and confirm whether consumers’ digital skills have a moderating effect on the research model.

Hypotheses were tested using a data set of 1,641 individuals. Partial least squares structural equation modeling and multi-group analysis were used to estimate the model.

The results indicate that antecedent factors influence consumers’ willingness to use AI devices in services. The two groups of different digitally savvy respondents differ because the influence of anthropomorphism, social influence and hedonic motivation on respondents’ perceived efforts to use AI devices in service delivery depends on respondents’ digital skills.

The novel contribution of this study is reflected in a comprehensive model that explains the moderating effect of individual digital skills on willingness to use AI devices. The attitudes of experienced and digitally skilled consumers are valuable and highlight some important theoretical, practical implications and future lines of research.

The adoption of the Internet of Things (IoT) as a new technology is gaining traction in many business organizations in developing countries. The purpose of this study is to assess the effect of IoT on the organizational performance of Tanzanian banks.

For data collection, this study used a quantitative approach with a questionnaire. A total of 342 respondents were considered, with an 82.16% response rate. AMOS software was used to analyze data using structural equation modeling (SEM) as the primary technique.

The results revealed that the majority of the hypotheses tested in this study have a significant effect on organizational performance, as indicated by their p-value of 0.05. However, there is no statistically significant effect of performance expectancy on organizational performance by lowering IoT operation costs. Furthermore, the availability of IoT has no discernible effect on organizational performance by improving service quality.

The findings of this study inform policymakers to reformulate information and communication technologies policy to clearly spell out the adoption and implementation of the IoT as a new technological innovation for providing services not only in the banking sector but also in other service delivery organizations. In particular, the policy should have a clear vision of implementing an appealing, conducive and positive, meaningful service delivery environment, as well as achieving appropriate, successful, effective and sustainable organizational performance

As a result, this paper contributes to a better understanding of the factors (including performance expectancy, effort expectancy and accessibility) of IoT on organizational performance by influencing operational costs, service delivery speed and service quality. These factors were not adequately addressed in previous related studies, and they have a significant influence on organizational performance levels in Tanzanian banks.

This study aims to examine the factors affecting behavioural intention to use E-learning during the COVID-19 pandemic. The study applies the unified theory of acceptance and use of technology 2 (UTAUT2) to identify the factors that predict intention to use E-learning. Also, the study examines the effect of personal innovativeness in information technology and perceived financial cost on intention to use E-learning.

The study adopted a cross-sectional quantitative study design involving 617 university students. The data was collected through an online survey due to the COVID-19 restrictions. The proposed hypotheses were analysed using partial least squares structural equation modelling.

The study found that personal innovativeness in information technology, perceived financial cost, performance expectancy, hedonic motivation and social influence have a significant effect on the intention to use E-learning. Contrary to expectation, habits, effort expectancy and facilitating conditions did not predict intention to use E-learning.

The study was conducted on university students and did not include other school-going students and working professionals. Also, the study sample was not drawn from many universities. The study used a quantitative approach. The use of a mixed-methods approach could provide deeper insights into the factors affecting the intention to use E-learning in developing countries.

The practical implications inform policymakers and educational institutions on how E-learning adoption can be enhanced. In this context, social influence, performance expectancy, hedonic motivation, personal innovativeness and perceived financial cost are identified as predictors of intention to use E-learning. This study has implications for the development of E-learning systems and the promotion of the use of E-learning in the context of developing countries.

The study is amongst the few studies from a developing economy to use the UTAUT2 model to examine students’ intention to use E-learning. The study proposes the inclusion of personal innovativeness in information technology and perceived financial cost as factors predicting intention to use E-learning. Again, the study adopts importance-performance matrix analysis to provide decisional areas where management may improve for successful E-learning acceptance and use.

The purpose of this paper is to examine the impact of key antecedents of unified theory of acceptance and use of technology model 2 on behavioral intention to accept and use mobile payment systems in National Capital Region, India.

A sample of 267 mobile payment system users in National Capital Region was obtained through an online survey. A partial least squares method was used to find out whether key antecedents of UTAUT2 predict behavioral intention to accept mobile payment systems which further predicts use behavior toward mobile payment systems.

The research substantiates that performance expectancy, effort expectancy, habit and facilitating conditions significantly predict behavioral intention, which in turn significantly predict use behavior to use mobile payment systems. Both social influence and hedonic motivation were weak predictors of behavioral intention.

The research substantiates that performance expectancy, effort expectancy, habit and facilitating conditions significantly predict behavioral intention, which in turn significantly predict use behavior to use mobile payment systems. Both social influence and hedonic motivation were weak predictors of behavioral intention.

The research substantiates that performance expectancy, effort expectancy, habit and facilitating conditions significantly predict behavioral intention, which in turn significantly predict use behavior to use mobile payment systems. Both social influence and hedonic motivation were weak predictors of behavioral intention.

This study attempts to gain insight into what factors influence individual behavior towards the adoption of telemedicine application during coronavirus disease 2019 (COVID-19) pandemic. The research model incorporates two well-known theories namely the extended unified theory of acceptance and use of technology (UTAUT2) and DeLone and McLean information success model to examine individual behavior towards the adoption of telemedicine application.

The research design of this study is based on quantitative research approach. During research survey, 350 valid responses were received from Pakistani citizens and examined to understand citizen's behavior towards the adoption of telemedicine applications. The research model was empirically tested with the latest statistical approach namely variance-based structural equation modeling (VB-SEM).

The results of the structural equation modeling have revealed that altogether performance expectancy, social influence, effort expectancy, facilitating condition, habit, hedonic motivation, price values, information quality, system quality and service quality explained 77.9% variance in determining user behavior towards adoption of telemedicine application. The predictive relevance of the research model was found substantial in measuring user behavior to adopt telemedicine applications. The research framework is further extended with moderating role of perceived severity between the relationship of user intention and actual usage behavior. Results confirmed that the positive relationship between intention to adopt telemedicine health application and usage behavior will be stronger when perceived severity is higher.

Theoretically, this study integrates extended UTAUT2 and DeLone and McLean information success model and contributes to e-health literature. Practically, this research suggests that by improving user performance expectancy and effort expectancy, managers and healthcare professionals can boost user confidence towards the adoption of telemedicine applications.

This study is unique as it integrates the extended UTAUT2 with DeLone and McLean information success model and perceived severity to investigate user behavior towards adoption of telemedicine application during COVID-19 pandemic. Additionally, the integration of theories contributes to information system literature in the context of the adoption of telemedicine applications.