• Asia pacific journal of information systems
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• v.22 no.4
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• pp.7-29
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• 2012

Smartphone and its applications (i.e. apps) are increasingly penetrating consumer markets. According to a recent report from Korea Communications Commission, nearly 50% of mobile subscribers in South Korea are smartphone users that accounts for over 25 million people. In particular, the importance of smartphone has risen as a geospatially-aware device that provides various location-based services (LBS) equipped with GPS capability. The popular LBS include map and navigation, traffic and transportation updates, shopping and coupon services, and location-sensitive social network services. Overall, the emerging location-based smartphone apps (LBA) offer significant value by providing greater connectivity, personalization, and information and entertainment in a location-specific context. Conversely, the rapid growth of LBA and their benefits have been accompanied by concerns over the collection and dissemination of individual users' personal information through ongoing tracking of their location, identity, preferences, and social behaviors. The majority of LBA users tend to agree and consent to the LBA provider's terms and privacy policy on use of location data to get the immediate services. This tendency further increases the potential risks of unprotected exposure of personal information and serious invasion and breaches of individual privacy. To address the complex issues surrounding LBA particularly from the user's behavioral perspective, this study applied the privacy calculus model (PCM) to explore the factors that influence the adoption of LBA. According to PCM, consumers are engaged in a dynamic adjustment process in which privacy risks are weighted against benefits of information disclosure. Consistent with the principal notion of PCM, we investigated how individual users make a risk-benefit assessment under which personalized service and locatability act as benefit-side factors and information privacy risks act as a risk-side factor accompanying LBA adoption. In addition, we consider the moderating role of trust on the service providers in the prohibiting effects of privacy risks on user intention to adopt LBA. Further we include perceived ease of use and usefulness as additional constructs to examine whether the technology acceptance model (TAM) can be applied in the context of LBA adoption. The research model with ten (10) hypotheses was tested using data gathered from 98 respondents through a quasi-experimental survey method. During the survey, each participant was asked to navigate the website where the experimental simulation of a LBA allows the participant to purchase time-and-location sensitive discounted tickets for nearby stores. Structural equations modeling using partial least square validated the instrument and the proposed model. The results showed that six (6) out of ten (10) hypotheses were supported. On the subject of the core PCM, H2 (locatability ${\rightarrow}$ intention to use LBA) and H3 (privacy risks ${\rightarrow}$ intention to use LBA) were supported, while H1 (personalization ${\rightarrow}$ intention to use LBA) was not supported. Further, we could not any interaction effects (personalization X privacy risks, H4 & locatability X privacy risks, H5) on the intention to use LBA. In terms of privacy risks and trust, as mentioned above we found the significant negative influence from privacy risks on intention to use (H3), but positive influence from trust, which supported H6 (trust ${\rightarrow}$ intention to use LBA). The moderating effect of trust on the negative relationship between privacy risks and intention to use LBA was tested and confirmed by supporting H7 (privacy risks X trust ${\rightarrow}$ intention to use LBA). The two hypotheses regarding to the TAM, including H8 (perceived ease of use ${\rightarrow}$ perceived usefulness) and H9 (perceived ease of use ${\rightarrow}$ intention to use LBA) were supported; however, H10 (perceived effectiveness ${\rightarrow}$ intention to use LBA) was not supported. Results of this study offer the following key findings and implications. First the application of PCM was found to be a good analysis framework in the context of LBA adoption. Many of the hypotheses in the model were confirmed and the high value of $R^2$ (i.,e., 51%) indicated a good fit of the model. In particular, locatability and privacy risks are found to be the appropriate PCM-based antecedent variables. Second, the existence of moderating effect of trust on service provider suggests that the same marginal change in the level of privacy risks may differentially influence the intention to use LBA. That is, while the privacy risks increasingly become important social issues and will negatively influence the intention to use LBA, it is critical for LBA providers to build consumer trust and confidence to successfully mitigate this negative impact. Lastly, we could not find sufficient evidence that the intention to use LBA is influenced by perceived usefulness, which has been very well supported in most previous TAM research. This may suggest that more future research should examine the validity of applying TAM and further extend or modify it in the context of LBA or other similar smartphone apps.

• Informatization Policy
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• v.25 no.2
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• pp.20-45
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• 2018

This study aims to find the factors of Internet overdependence in adults, through the decision tree analysis model, which is a data mining method using National Information Society Agency's raw data from the survey on Internet overdependence in 2016. As a result of the decision tree analysis, a total 16 nodes of Internet overdependence risk groups were identified. The main predicated variables were the amount of time spent per smart media usage in weekdays; amount of time spent per smart media usage in weekends; experiences of purchasing cash items; percentage of using smart media for leisure; negative personality; percentage of using smart media for information search and utilization; and awareness on good functions of the Internet, all of which in order had greater impact on the risk groups. Users in the highest risk node spent the smart media for more than 5 minutes per use and less than 5~10 minutes in weekdays, had experiences of cash item purchase, and had lower level of awareness on the good functions of the Internet. The analysis led to the following recommendations: First, even a short-time use has higher chances of causing Internet overdependence, and therefore, guidelines need to be developed based on research on the usage behavior rather than the usage time. Second, self-regulation is required because factors that affect overindulgence in games, such as the cash items, increase Internet overdependence. Third, using the Internet for leisure causes higher risk of overdependence and therefore, other means of leisure should be recommended.

• Korean Journal of Community Nutrition
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• v.24 no.2
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• pp.106-116
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• 2019

Objectives: This study examined the status of children's favorite foods intake and the relationship with the policy environment based on the Special Act on Safety Control of Children's Dietary Life for suggesting a supportive policy strategy. Methods: The subjects were 4th grade students (n=1,638) in elementary school from 45 schools collected from seven areas (Seoul, Daegu, Daejeon, Gyeonggi, Chungnam, Jeonbuk, and Gyeongnam). The children participated in a self-administered questionnaire survey in class under the supervision of the teacher. The questionnaire consisted of items, such as social demographic characteristics, frequency of intake of the children's favorite foods, and policy cognition. A t-test and ANOVA were applied to explore the relationship between the frequency of children's favorite foods intake and policy cognition. The survey was implemented from August 2016 to September 2016. Results: For the boys, the frequency of 'high-calorie low nutrient foods intake' (HCLN) was significantly higher than that of the girls (p<0.01). For the children who received information on their favorite foods from the internet, the frequency of HCLN was higher than the other sources (p<0.01). The time of TV viewing and computer usage, and smartphone usage was associated with a higher frequency of HCLN, and a lower healthy favorite food intake (all p<0.001). The intake frequency of healthy favorite foods indicated a positive correlation with the policy cognition, including policy perception, usefulness, necessity and buying intention, and educational experience. Conclusions: This study showed a correlation with the frequency of children's favorite foods intake and policy. In particular, the frequency of children's healthy favorite foods intake indicated a meaningful relationship with the policy than the frequency of HCLN. This study also found that the consumption of children's healthy favorite foods was positively correlated with the educational experience. To develop a supportive policy for a good dietary environment for children, there is a need to focus on how to collaborate with multiple levels of influences, such as the national level, school level, and family.

• The Journal of Society for e-Business Studies
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• v.21 no.4
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• pp.29-40
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• 2016

Voice User Interface (VUI) is the most familiar and comfortable interface to human. Recently, with the development of cloud and AI technologies VUI has been applied to various products. The aim of this study was to identify the problems of the current VUI and to find the direction of future study by investigating the utilization status and user perception of the VUI of smartphones. A survey was conducted with 163 college students using Google Forms. The results showed that the level of recognition of VUI is high but the rate of usage is very low, and many users feel uncomfortable about the voice recognition rate, reaction speed and operation method. Most of the survey participants tried VUI out of curiosity, but only a small portion of them found it useful to continue to use it. Many participants disliked talking to machines and also did not want others to listen. The study results will guide future research efforts for improving the utilization of VUI.

• Annals of Occupational and Environmental Medicine
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• v.35
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• pp.50.1-50.11
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• 2023

Background: The rise in telecommuting or non-face-to-face work owing to the coronavirus disease 2019 pandemic has fueled conversations regarding the "right to disconnect." Although evidence suggests that receiving work-related communications through telecommunication devices outside of work hours may lead to various symptoms and illnesses, limited research has been undertaken on these symptoms. This study therefore aims to investigate the correlation between receiving work communications through telecommunication devices after work hours and the occurrence of work-related headaches and eyestrain in full-time, non-shift white-collar workers. Methods: This study used data from the 6th Korean Working Conditions Survey. The frequency of using telecommunication devices for work purposes outside of working hours was divided into five categories: "Every day," "Several times a week," "Several times a month," "Rarely," and "Never." Work-related headaches and eyestrain were categorized based on a "yes" or "no" response to the survey questions. Descriptive statistics, χ² tests, and multiple logistic regression analyses were performed using SPSS 27.0. Results: After adjusting for sex, age, income level, education, occupation, workplace size, work hours, and sleep disorders, the odds ratio (OR) of work-related headaches and eyestrain based on frequency of telecommunication device usage were as follows: "rarely" (OR: 1.292; 95% confidence interval [CI]: 1.111-1.503), "several times a month" (OR: 1.551; 95% CI: 1.249-1.926), "several times a week" (OR: 1.474; 95% CI: 1.217-1.784), and "every day" (OR: 1.548; 95% CI: 1.321-1.813). Conclusions: Employees who use telecommunication devices for work after regular hours are more susceptible to experiencing work-related headaches and eyestrain compared to those who do not. However, there is a dearth of research examining the physical and mental health impacts of using telecommunication devices for after-hours work. Furthermore, the existing preventative measures in Korea are insufficient. Consequently, it is imperative to develop effective measures and conduct additional research to address this issue.

• International Journal of Computer Science & Network Security
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• v.24 no.4
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• pp.163-169
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• 2024

India is a developing nation and has come with comprehensive way in modernizing its reducing poverty, economy and rising living standards for an outsized fragment of its residents. The STEM (Science, Technology, Engineering, and Mathematics) education plays an important role in it. STEM is an educational curriculum that emphasis on the subjects of "science, technology, engineering, and mathematics". In traditional education scenario, these subjects are taught independently, but according to the educational philosophy of STEM that teaches these subjects together in project-based lessons. STEM helps the students in his holistic development. Youth unemployment is the biggest concern due to lack of adequate skills. There is a huge skill gap behind jobless engineers and the question arises how we can prepare engineers for a better tomorrow? Now a day's Industry 4.0 is a new fourth industrial revolution which is an intelligent networking of machines and processes for industry through ICT. It is based upon the usage of cyber-physical systems and Internet of Things (IoT). Industrial revolution does not influence only production but also educational system as well. IoT in academics is a new revolution to the Internet technology, which introduced "Smartness" in the entire IT infrastructure. To improve socio-economic status of the India students must equipped with 21st century digital skills and Universities, colleges must provide individual learning kits to their students which can help them in enhancing their productivity and learning outcomes. The major goal of this paper is to present a low cost, effective learning mechanism for STEM implementation using Raspberry Pi 3+ model (Single board computer) and Node Red open source visual programming tool which is developed by IBM for wiring hardware devices together. These tools are broadly used to provide hands on experience on IoT fundamentals during teaching and learning. This paper elaborates the appropriateness and the practicality of these concepts via an example by implementing a user interface (UI) and Dashboard in Node-RED where dashboard palette is used for demonstration with switch, slider, gauge and Raspberry pi palette is used to connect with GPIO pins present on Raspberry pi board. An LED light is connected with a GPIO pin as an output pin. In this experiment, it is shown that the Node-Red dashboard is accessing on Raspberry pi and via Smartphone as well. In the final step results are shown in an elaborate manner. Conversely, inadequate Programming skills in students are the biggest challenge because without good programming skills there would be no pioneers in engineering, robotics and other areas. Coding plays an important role to increase the level of knowledge on a wide scale and to encourage the interest of students in coding. Today Python language which is Open source and most demanding languages in the industry in order to know data science and algorithms, understanding computer science would not be possible without science, technology, engineering and math. In this paper a small experiment is also done with an LED light via writing source code in python. These tiny experiments are really helpful to encourage the students and give play way to learn these advance technologies. The cost estimation is presented in tabular form for per learning kit provided to the students for Hands on experiments. Some Popular In addition, some Open source tools for experimenting with IoT Technology are described. Students can enrich their knowledge by doing lots of experiments with these freely available software's and this low cost hardware in labs or learning kits provided to them.