• 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 Intelligence and Information Systems
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• v.12 no.4
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• pp.1-14
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• 2006

This study proposed a customer preference estimation model for production recommendation and a method to enhance the performance of product recommendation using the estimated customer preference information. That is, we suggested customer preference estimation model to estimate exactly customer's product preference with his behavior. This model shows the relationship of customer's behaviors with his preferences. The proposed estimation model is optimized by learning the relative weights of customer's behavior variables to have an effect on his preference and enables to estimate exactly his preference. To validate our proposed models, we collected virtual book store data and then made a comparative analysis of our proposed models and a benchmark model in terms of performance results of collaborative filtering for product recommendation. The benchmark model means a prior preference weighting model. The results of our empirical analysis showed that our proposed model performed better results than the benchmark model.

• The Journal of Information Systems
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• v.21 no.4
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• pp.1-29
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• 2012

The purpose of this study was to find about personal information security of internet and social networks by focusing on end users. User competence and subjective criterion, which are the antecedents, are affecting security behaviors For these security behaviors, the study examined the relationship between security behavior intention on internet use and security behavior intention about social network that is actively achieved in many fields. Behaviors of internet and social network were classified into an action of executing security and an action of using a security technology. In addition, this study investigated a theory about motivational factors of personal intention on a certain behavior based on theory of reasoned action in order to achieve the purpose of this study. A survey was conducted on 224 general individual users through online and offline, and the collected data was analyzed with SPSS 12.0 and SmartPLS 2.0 to verify demographic characteristics of respondents, exploratory factor analysis, and suitability of a study model. Interesting results were shown that security behavior intention of social network is not significant in all security behavior execution, which is security performance behavior, and security technology use. Internet security behavior is significant to security technology use but it does not have an effect on behavior execution.

• Journal of Korean Academy of Nursing
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• v.43 no.3
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• pp.399-408
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• 2013

Purpose: The study was done to construct and test a structural model to explain primipara breastfeeding behavior. Methods: The participants were 213 primiparas on postpartum wards. Data were analyzed using the PASW 18.0 and AMOS 19.0 programs. Results: Fitness statistics for the hypothetical model were appropriate ($x^2$=38.50, p=.070, GFI=.96, RMSEA=.05, AGFI=.93, NFI=.95, TLI=.97, CFI=.98, PNFI=.57, $x^2/df$=1.43). Breastfeeding behaviors were directly influenced by intention to breastfeed, perceived effectiveness of breastfeeding, and the amount of supplementary feeding. The amount of supplementary feeding had the largest direct impact on breastfeeding behavior. The largest total effect on breastfeeding behavior was intention to breastfeed. The environment of the maternity hospital indirectly influenced breastfeeding behavior. These factors explained 18.9% of variance in the primipara breastfeeding behavior. Conclusion: The results of the study indicate that in order to promote primipara breastfeeding the amount of supplementary feeding immediately after the birth should be limited and an environment that encourages exclusive breastfeeding in the hospital should be provided. The results also suggest it is necessary to provide nursing interventions that increase the intention to breastfeed and the perceived effectiveness of breastfeeding.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.3
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• pp.1481-1501
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• 2019

In opportunistic network, the behavior of a node is autonomous and has social attributes such as selfishness.If a node wants to forward information to another node, it is bound to be limited by the node's own resources such as cache, power, and energy.Therefore, in the process of communication, some nodes do not help to forward information of other nodes because of their selfish behavior. This will lead to the inability to complete cooperation, greatly reduce the success rate of message transmission, increase network delay, and affect the overall network performance. This article proposes a hybrid incentive mechanism (Mim) based on the Reputation mechanism and the Credit mechanism.The selfishness model, energy model (The energy in the article exists in the form of electricity) and transaction model constitute our Mim mechanism. The Mim classifies the selfishness of nodes and constantly pay attention to changes in node energy, and manage the wealth of both sides of the node by introducing the Central Money Management Center. By calculating the selfishness of the node, the currency trading model is used to differentiate pricing of the node's services. Simulation results show that by using the Mim, the information delivery rate in the network and the fairness of node transactions are improved. At the same time, it also greatly increases the average life of the network.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.10 no.2
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• pp.66-76
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• 2011

The Sightseeing ITS is defined as a system that gives tourists and inhabitants the information concerned with road network conditions, parking, sightseeing spots, and travel time in the relevant area. When focusing on tourists' excursion behaviors in sightseeing areas, however, it is sometimes found that they feel much annoyed with insufficient information about the area. While they also have a variety of needs to get information and make a decision about their excursions, it becomes one of important subjects to understand the actual circumstances of their information usage and to identify the causal relationship between their excursion patterns and the obtained information. This paper aims to investigate basic issues toward development of Sightseeing ITS and to modify an analytical model of tourist's excursion behavior considering information usage at Fuji five lakes Area, which is a representative sightseeing place in Japan. The relationship was analyzed using a structural equation model: information usage at the scheduling stage has an impact on tourists' individual cognition of the sightseeing area, tourists' individual cognition affects information usage at the excursion stage, and information usage at the excursion stage affects behavior during excursions. It is found that tourists' decision making behaviors on their excursion tend to depend on the information usage. This implies essential results to construct effective and customer oriented ITS.

• The Journal of Information Systems
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• v.26 no.1
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• pp.143-169
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• 2017

Purpose With the increase of the elderly population, the growth of its information system related market is increasing. However, empirical studies for the usage of elderly people's smartphones are still limited. This study aims to investigate the factors that affect the seniors' smartphone usage behaviors. Design/Methodology/Approach First, a preliminary study was conducted with targeting seniors who have visited Gwangju Senior Technology Center(GSTC) in order to understand the factors that affect the intention of utilizing smartphones. Next, based on the preliminary study results and literature reviews including the UTAUT model, performance expectancy, effort expectancy and social influence were considered for the major factors affecting the usage of elderly people's smartphones. Also, the moderate effects of personal innovativeness and usage function were discussed. A questionnaire survey of 181 seniors visiting GSTC was analyzed to empirically test the research model. Findings By the empirical tests, the performance expectancy and the effort expectancy of the seniors had significant impacts on their smartphone usage behavior. While the moderating effect of personal innovativeness was not significant, the moderating effect of the usage function was significant in the relationship between performance expectancy and the smartphone usage behavior. The results of this study are expected to provide guidelines to excavate the technical development and the niche market targeting the elderly people.

• The Journal of Korean Association of Computer Education
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• v.17 no.2
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• pp.11-19
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• 2014

Presently the instructional model for internet ethics education is modeled after the integrated morality. The model is based on the assumption that ethical awareness will lead to ethical activities which is based on the theory that cognition is correlated to the behavioral domains. But the side effects of the information society in the cyber space increased even when the education for the awareness of ethics in the cyber space has been taught more aggressively than before. In this study, the relation of the cognition for information ethics and the ethical behavior in the cyber space was analyzed in order to find out the implications for the effective internet ethics education model. The tools used are the 'DIT (Defining Issues Test)' to measure the behavioral ability in the physical world, the Information Ethics Judgment to measure the behavioral ability in the cyber space, and the self diagnostic tool of 'Internet ethics awareness' to measure the level of cognitive knowledge for internet ethics. The correlation of three measures was analyzed. The results were college students' levels of ethics from three tools from are considerably low. Moral judgement and information ethics judgement were not correlated which means that the behavior in the physical world was not necessarily correlated to the behavior in the cyber space. The three measurements were not statistically significantly correlated. Therefore the cognitive awareness for the information ethics were not necessarily correlated to the ethical behavior in the cyber space. Ethical cognition and the moral behavior need to be taught with equal emphasis as they do not have strong correlation.

• Journal of Digital Policy
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• v.1 no.1
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• pp.15-20
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• 2022

Recently, the healthcare field is trying to develop a model that can improve service quality by reflecting the requirements of various industrial fields. In this paper, we propose an Internet of Behavior (IoB) environment model that can process users' healthcare information in real time in a 5G environment to improve healthcare services. The purpose of the proposed model is to analyze the user's healthcare information through deep learning and then check the health status in real time. In this case, the biometric information of the user is transmitted through communication equipment attached to the portable medical equipment, and user authentication is performed through information previously input to the attached IoB device. The difference from the existing IoT healthcare service is that it analyzes the user's habits and behavior patterns and converts them into digital data, and it can induce user-specific behaviors to improve the user's healthcare service based on the collected data.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.26 no.6
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• pp.1619-1637
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• 2016

With wide distribution of smart phones and development of mobile network, social network service (SNS) is displaying remarkable growth rates. Users build new social relations by sharing their interests, which brings surging growth to the SNS based on the combination between the strength of expanding the place for communication and distribution of smart phones featured with easy portability. This study is designed to understand impact factors of SNS on users in Korea and to conduct empirical research on casual relationship between the factors above and the factors affecting personal information behavior through the privacy protection and self-efficacy. In order to accomplish the objective above, the study presented a research model applied with key variables of the Health Belief Model (HBM) predicting behaviors capable of recognizing and preventing individual diseases in the field of health communication. To perform empirical verification on the research model of this study, a survey was conducted upon college students at N university located in Chungcheongnam-do and K university in rural area, who have experiences using the SNS. Through this survey, a total of 186 samples were collected, and path analysis was performed in order to analyze the relationship between the factors. Based on the findings from the survey, first, variables Perceived probability, Perceived severity, Perceived impairment of the HBM, key factors of personal information protection behavior on the SNS, were found to exhibit negative relationship with self-efficacy, and Perceived probability, Perceived benefit, Perceived impairment were found to exhibit negative relationship with privacy protection. But the above, Perceived severity showed positive relationship with privacy protection, and Perceived benefit and self-efficacy also displayed positive relationship. Second, although self-efficacy, a parameter, showed positive relationship with privacy protection, it demonstrated negative relationship with personal information protection behavior. Lastly, privacy protection exhibited positive relationship with personal information protection behavior. By presenting theoretical model reflected with characteristics of prevention based on these findings above unlike previous studies on personal information protection using technologies threatening personal information, this study is to provide theoretical and operational foundation capable of offering explanations how to predict personal information protection behavior on the SNS in the future.