• The Journal of Industrial Distribution & Business
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• v.13 no.11
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• pp.1-10
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• 2022

Purpose: This study measures the influence of facilitating conditions on employees' attitudes towards the adoption of big data analytics by selected medical aid organizations in Durban. In the health care sector, there are various sources of big data such as patients' medical records, medical examination results, and pharmacy prescriptions. Several organizations take the benefits of big data to improve their performance and productivity. Research design, data, and methodology: A survey research strategy was conducted on some selected medical aid organizations. A non-probability sampling and the purposive sampling technique were adopted in this study. The collected data was analysed using version 23 of Statistical Package for Social Science (SPSS) Results: the results show that the "facilitating conditions" have a positive influence on employees' attitudes in the adoption of big data analytics Conclusions: The findings of this study provide empirical and scientific contributions of the facilitating conditions issues regarding employee attitudes toward big data analytics adoption. The findings of this study will add to the body of knowledge in this field and raise awareness, which will spur further research, particularly in developing countries.

• Journal of Korean Society for Quality Management
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• v.50 no.1
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• pp.43-61
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• 2022

Purpose: The purpose of this study was verifying factors that affect to intention to use AI financial services and finding a way of building an user oriented AI ecology. Methods: This study used the UTAUT (Unified Theory of Acceptance and Use of Technology) model with independent variables such as performance expectancy, effort expectancy, social influence, facilitating conditions, trust, personal innovativeness and AI understanding as moderating variable. The data was collected through online & offline survey with questionnaire from 330 financial customers. Results: As a result, the analysis suggested that the performance expectancy, social influence, facilitating conditions, personal innovativeness are statistically significant to the intention to use AI. It was also found that AI knowledge of users differently influence the intention to use through the moderating effect on the facilitating conditions. Conclusion: Performance expectancy, social influence, facilitating conditions, personal innovativeness have positive causation to the intention to use in AI financial service. On the facilitating conditions, unlike other variables, it was found that the user's intention to use was different by the level of AI understanding. It means that customers could have the strong intention to use AI even though they don't have enough pieces of knowledge on the factors. Customers seem to be of recognition that the technology has certain benefits for themselves. The facilitating factors are significantly affected by AI understanding and differently effect on the intention to use AI.

• The Journal of Asian Finance, Economics and Business
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• v.7 no.10
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• pp.481-489
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• 2020

The study examines the role of facilitating conditions and user habits in the use of technology in Online Learning Platform (OLP) in Indonesia. The adoption of online learning, persistence, and learning results in online platforms is essential for ensuring that education technology is implemented and gets as much value as possible. People who use technology and systems will embrace new technologies even more. This quantitative study is based on a survey of 254 respondents, who were active users of the technology, and considers the facilitating conditions and user habits variables. Two research hypotheses were tested using the Partial Least Square-Structural Equation Modeling method. Cronbach's Alpha, path coefficient, AVE, R-square, T-test were applied. The results showed that the factors significantly influence the Online Learning Platform technology behavioral intention. This impact is primarily associated with the availability of the resources required to use OLP technology. The availability of these resources includes supporting infrastructures such as widespread Internet access, easy access to mobile devices, and file sizes that affect access speed. The findings of this study suggest that it is necessary to introduce and increase the availability of resources for using OLP technology, and familiarize people with the technology features.

• Journal of Korea Trade
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• v.25 no.7
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• pp.56-74
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• 2021

Purpose - This study aims to identify consumer tendencies in Korea and Vietnam, focusing on the online platform called cross-border, to derive revenue generation measures and use them for strategies to advance into ASEAN. Design/methodology - The questionnaire collected 420 copies from December 1 to December 31, 2020, of which 408 were used for statistical processing. The structural equation model (SEM) and moderating effect analysis with Amos was used to test hypothesis in this research. Findings - The hypotheses were set as factors that positively influence the intention to use e-commerce, such as effort expectancy, social influence, facilitating conditions and variety seeking showed statistically significant results. Among them, the social influence factor had the greatest influence, followed by facilitating condition. The sample was divided into countries, Korea and Vietnam, and these changes and differences in influence were confirmed through moderating effect analysis. Originality/value - The moderating effect on both countries (Korea and Vietnam) was found to have a moderating effect on the intention to use. For Korean consumers, significant results were found in the effort expectancy, social influence, facilitating conditions, and variety seeking, but for Vietnamese consumers, there were significant effects on the social influence and facilitating conditions, but the effort expectancy and variety seeking had no significant effect.

• The Journal of Asian Finance, Economics and Business
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• v.7 no.12
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• pp.711-720
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• 2020

This research aims to analyze the factors affecting the acceptance of social commerce, including performance expectancy, effort expectancy, social support, facilitating conditions, hedonic motivation, habitability, price saving orientation, and privacy concerns using the Unified Theory of Acceptance and Use of Technology (UTAUT2). UTAUT2 has been examined and modified in various contexts. The research model studies the acceptance and use of technology in the context of customers. This study adopts a quantitative method using the partial least squares regression (PLS) approach involving 244 respondents. The respondents are users of social commerce in Indonesia. The result of this research indicates that social influence, facilitating conditions, hedonic motivation, habit, price value orientation, and privacy concerns have a significant effect on behavioral intention. On the other hand, performance expectancy and effort expectancy does not affect behavioral intention. Furthermore, price value has a significant effect on social commerce user behavior. Lastly, facilitating conditions and habits does not affect social commerce user behavior. This research contributes to the development of theory by examining an additional variable, which is privacy concern. This study is significant since social media and social commerce have grown exponentially nowadays. Implications of the results for the development of the theory (UTAUT2) and practice are discussed in the article.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.8
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• pp.4162-4179
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• 2017

The main purpose of this research is to investigate relationships between the significant control factors on acceptance intention to User Experience (UX) sports smart wearable devices by applying Technology Readiness (TR) and Unified Theory of Technology (UTAUT). Research survey targeted on users of golf smart devices in Seoul. A total 534 questionnaires were collected and used for testing hypotheses. Methods to analyze the data included frequency analysis, reliability analysis, confirmatory factor analysis, correlation analysis, and structural equation modeling in accordance with the purpose of the study by using SPSS and AMOS. The results are as follows; First, positive TR had a significantly positive effect on social influence, effort expectancy, facilitating conditions, perceived enjoyment, performance expectancy. Second, negative TR had a significant negative effect on performance expectancy, social influence, facilitating conditions, perceived enjoyment. Third, TR had a no significantly effect on behavioral intention. Fourth, performance expectancy, perceived enjoyment and facilitating conditions had a significantly positive effect on behavioral intention. Fifth, behavioral intention had a significantly positive effect on use behavior. Thus it became crucial to identify the difference in acceptance intention models per each products are as follows. Positive TR of golf-related mobile application users has a positive effect on both technology acceptance belief and acceptance intention, whereas negative TR has no statistically significant effect on technology acceptance belief nor acceptance intention.

• Journal of Information Technology Services
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• v.12 no.2
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• pp.131-152
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• 2013

Many studies have reported that software piracy is prevalent in today's society. As software is more closely integrated with across industries, software piracy would put more burdens on national economy. In spite of software anti-piracy efforts, the phenomenon has been getting worse. It is necessary to change the focus of current deterrence strategies. For better understanding of unethical behavioral intention, a research model of potential determinants for the software piracy is developed and empirically tested. The results from the study show that the planned behavior model variables-attitude, subjective norms, and perceived behavioral control-have impact on intention to commit software piracy. In addition to the variables, past behavior, perceived benefits and risk were found to be significant predictors of attitude toward software piracy. However, neither attitude nor intention was influenced by facilitating conditions. Moreover, the effect of past piracy behavior on attitude was strongly mediated by perceived benefits. Implications for research and practice are discussed.

• Journal of Information Technology Applications and Management
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• v.29 no.5
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• pp.13-25
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• 2022

The purpose of this study is to explore the factors that influence the purchase of AI speakers in China. We integrate the Unified Theory of Acceptance and Use of Technology (UTAUT) and Task-technology fit (TTF) model into one model and put forward assumptions. According to the characteristics of AI speakers, we selected 6 independent variables, such as Performance Expectation, Effort Expectation, Social Influence, Facilitating Conditions, Task and Technology-characteristics. The final impact on purchase behavior is evaluated through Task-technology fit and purchase intention. After counting 478 samples, through SPSS22.0 and AMOS analysis, hypotheses have been proved by strong experimental data, except facilitating conditions. These results also imply that improving the technical level of AI speakers and enhancing consumers' purchasing intention are the central line of marketing. Based on this, we put forward several suggestions to marketers, including strengthening the research and development of AI speaker technology, and building a circle of friends of AI speakers.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.39 no.3
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• pp.192-203
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• 2016

Uganda is a country blessed with the biggest number of mountain Gorillas in the whole world. These animals contribute at least 12% in revenue generation to the Tourism sector through tracking by both local and foreign tourists who pay for the tracking permits. However, Gorilla tracking is also a big challenge even in the presence of highly skilled and well-trained game rangers. Development and implementation of a secure Computer and Mobile based Gorilla Tracking (GT) system that uses GIS and GPS technologies would be the most ideal technology to use. Therefore, this study aimed to find out the critical factors that would affect the Behavioral Intention of the would-be users to successfully decide to use such GIS/GPS-GT system. We used the existing UTAUT model to integrate six factors such as Performance Expectancy, Effort Expectancy, Employee Peer Influence, Facilitating Conditions, Behavioral Intention and System Use. However, Infrastructure Availability and Non-Technical Facilitating Conditions were added to reflect Ugandan ICT context. This amended UTAUT model was used to carry out the survey. The questionnaire was emailed to 220 government employees in the fields of ICT, Tour and Travel, Environmental Groups officials and Farmers who garden near the game reserves. A total of 133 were obtained fully completed, whereas 127 were deemed usable thus yielding a response rate of 58%. The analysis results show that except for non-technical facilitating conditions, effort expectancy, peer influence, performance expectancy and infrastructure availability positively affects behavioral Intention to use GIS/GPS-GT. This indicates that people in Uganda don't bother about regulations and rules in regard to using information system. As long as the system does what they want it to, anything else does not matter. As an employee in an organization is told to use a system by their supervisor, they have no objection to otherwise they risk losing their job. This implies that, supervisors have a great responsibility in the process of developing, implementing and using the system in Uganda.

• Journal of Information Technology Applications and Management
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• v.27 no.1
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• pp.75-95
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• 2020

Smart Factory is the decisive factor of the Fourth Industrial Revolution and is a key field for national competitiveness. Until now, most smart factory research has focused on policy and technology. In order to spread more technology, it is necessary to study what factors influence the adoption of smart factory technology in the enterprise. Nevertheless, little research has been done. In this study, based on the UTAUT (Unified Theory of Acceptance and Use of Technology), which has been proved through many years of research, I have studied the factors that influence the acceptance of smart factory technology. As a result of research, performance expectancy, social influence, and facilitating conditions of UTAUT model had a positive(+) effect on behavior intention. Their relationship of influence was in the order of performance expectancy (β = .459)> facilitating conditions (β = .212)> social influence (β = .210). However, it was found that the effort expectancy did not affect the behavior intention, and the impact of the newly perceived risk on the behavior intention to use was not confirmed. The main reason is that the acceptance of smart factory technology is not a matter of personal interest but a matter of organizational choice. Trust, on the other hand, was found to be partially mediated between performance expectancy, facilitating conditions, social influence and behavior intention. For many years, many researchers have validated the UTAUT, which has been validated through various empirical studies. It is academically meaningful to begin the study of factors affecting the acceptance of smart factory technology in terms of the UTAUT. In practice, it is necessary to provide SME employees with more information related to the introduction of smart factories, to provide advanced services related to the establishment of smart factories, and to establish a standardized model for each industry.