• Journal of the Korean Society of Food Culture
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• v.22 no.1
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• pp.43-57
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• 2007

This study was designed to identify the actual state of ready-to-eat street-foods usage in a college-town in northern part of seoul. For the empirical study, data was collected from customers who had eaten street-foods and a survey was conducted from 16 to 30, May 2006. The results showed that many respondents had irregular eating habits. More than 60% of them responded they usually skipped breakfast and the reason was no time. It was shown that they have had Frequent snacks and unbalanced diet. The results of survey are as follows ; 1. The major time for street-foods usage: p.m 3-5 (28.77%). 2. The frequency of street-foods usage: 1-2 times/week (43.85%). 3. The street-foods usage days of the week: weekday (52.79%). 4. The mean cost for the onetime purchase of street-foods usage: 1000-3000won (71.79%). 5. The monthly cost for the purchase of street-foods usage: below 50000won (81.84%). 6. The reason for street-foods usage: mainly convenience (60.61%). 7. The reason for minding street-foods : mainly insanitary (40.50)%. 8. Factors considered when choosing street-foods: tastes of the foods (65.08%). Also, it was shown that over 50% of respondents have considered the street-foods as the worth of meal replacement, and taken effective factor on eating habits for influx of new culture. It was indicated that problems of street-foods usage was the unbalanced nutrition for 81.8% of respondents and suggestions for improving the street-foods were sanitary controls for products for 63.4% of respondents.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.4
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• pp.1489-1503
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• 2018

Spectrum reuse has attracted much concern of researchers and scientists, however, the dynamic spectrum access is challenging, since an individual secondary user usually just has limited sensing abilities. One key insight is that spectrum usage forecasting among secondary users, this inspiration enables users to obtain more informed spectrum opportunities. Therefore, spectrum usage forecasting is vital to cognitive radio networks (CRNs). With this insight, a spectrum usage forecasting model for the occurrence of primary users prediction is derived in this paper. The proposed model is based on auto regressive enhanced primary user emergence reasoning (AR-PUER), which combines linear prediction and primary user emergence reasoning. Historical samples are selected to train the spectrum usage forecasting model in order to capture the current distinction pattern of primary users. The proposed scheme does not require the knowledge of signal or of noise power. To verify the performance of proposed spectrum usage forecasting model, we apply it to the data during the past two months, and then compare it with some other sensing techniques. The simulation results demonstrate that the spectrum usage forecasting model is effective and generates the most accurate prediction of primary users occasion in several cases.

• 한국경영정보학회:학술대회논문집
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• 2007.06a
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• pp.885-890
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• 2007

This study is to investigate factors that affect usage change in mobile data service (MDS). In the first, an exploratory study based on 378 survey responses was conducted to learn about important decision factors of MDS usage. It revealed discrepancy between the influencing forces of usage increase and those of usage decrease. Based on the findings from the exploratory study and the two-factor theory, we postulated information quality as the motivator and system quality as the de-motivator (or hygiene) of MDS. Then, a confirmative study was undertaken on their respective role in encouraging and discouraging the usage of mobile data service. A research model was proposed and subsequent hypotheses were empirically tested with partial least square (PLS) based on 478 responses from the users of mobile data service. It was learned that information quality (as a motivator) was positively associated with usage increase in mobile data service, but system quality (as a de-motivator) was not. Also, system quality was negatively associated with usage decrease, but information quality was not. Lastly, their association strength was partially moderated by the type of motivation for using MDS.

• Journal of the Korean Operations Research and Management Science Society
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• v.38 no.1
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• pp.183-199
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• 2013

This study investigates customers' different behavior in accumulating and redeeming points and focuses on the moderating effect of usage level. We measure the hedonic accumulation and redemption ratio and usage level using loyalty program transaction data and link them to the survey data of loyalty and satisfaction. By doing so, we examine the effects of hedonic accumulation and redemption ratio on a consumer's loyalty intention and his or her satisfaction and the moderating effect of usage level. The result shows that there is a significant positive effect of hedonic accumulation and redemption ratio on customer loyalty and the mediating role of satisfaction on customer loyalty in both stages. And accumulation and redemption most importantly, we find an interaction effect of usage level on outlet type in point redemption stage while no effect in accumulation stage. That is if customers accumulate and redeem points at a hedonic outlets in both stages, it will give him a feeling of satisfaction and finally it will enhance the loyalty toward the focal loyalty program. And light buyers' loyalty increase more than those of heavy buyers when they redeem points in hedonic outlet. Our findings will help marketing managers of loyalty program to apply the effective segmentation strategy to the reward program which affects the customer's satisfaction and loyalty.

• Journal of Korean Library and Information Science Society
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• v.45 no.2
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• pp.5-27
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• 2014

This study aims to investigate the relationship between university library usage and educational achievement of academic library users. To proceed with this study, academic library usage data were collected from S university undergraduate students. Academic achievement was measured using the students' grade point average(GPA). T-test and analysis of variance were used to compare differences of means between library usage and academic achievement with the background variables. Hierarchical regression analyses were conducted to determine the association between library usage and academic achievement. As a result, a positive correlation was found between academic achievement and the use of library resources and services according to gender, year and academic subject. In addition, academic library usage had a positive significant influence on academic achievement. Students who used more library resources and facilities ultimately get better grades.

• The Journal of Industrial Distribution & Business
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• v.7 no.3
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• pp.13-18
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• 2016

Purpose - Usage of E-services is critical for businesses to maximize work efficiency and gain competitive advantage. The aim of the study is to explore how awareness of technology and e-services usage in an emerging economy in Pakistan. The studies aimed to explore as to what extent these factors can potentially motivate transport employees towards e-services; who are generally not aware about technology and hence also not confident in using it also. Research design, data, and methodology - Employees from the three transport subsidiary units from a large private company in Pakistan were sampled for the study. Through using self-administered technique, the questionnaires were distributed during the month of April, 2016 to 189 employees. A total of 150 responses were taken further for analysis where the study found a positive link between awareness of technology and e-services usage. Results - This study found positive relationship between intention to use and e-service usage among the employees of three subsidiary units. The paper has reported 30 percent variance explained by the predicting variables in relation with e-services usage. Conclusions - Employees could be motivated to use e-services and latest technology through enhancing their awareness about their respective importance and viability. Accordingly, organizations can foster employees' intentions to use to enhance e-service usage.

• Knowledge Management Research
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• v.9 no.3
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• pp.21-42
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• 2008

As many companies have recognized the importance of Knowledge Management(KM), they have invested lots of their resources in developing and deploying Knowledge Management Systems(KMS) to organize and share knowledge. When they implemented KMS in their organizations, most of them had high expectations about KMS at tile beginning. However, as time passed, its usage was rapidly declined. There have been many attempts to increase its usage. Many research works have tried to find solutions from users and organizations viewpoints, instead of the actual usage data itself. In order to assess the usage level of KMS, they have normally utilized user's attitudes toward KMS by assuming that user attitudes have strong relationship with actual uses of KMS. The purpose of this study is to assess tile impacts of user, organizational, and job characteristics on the satisfaction and the usage levels of KMS. Unlike other studies, this study is to explore impact factors which affect the usage level of KMS in organizations by using actual KMS log data as well as user's attitudes.

• Journal of Computing Science and Engineering
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• v.5 no.4
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• pp.338-345
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• 2011

Nowadays mobile devices are used for various applications such as making voice/video calls, browsing the Internet, listening to music etc. The average battery consumption of each of these activities and the length of time a user spends on each one determines the battery lifetime of a mobile device. Previous methods have provided predictions of battery lifetime using a static battery consumption rate that does not consider user characteristics. This paper proposes an approach to predict a mobile device's available battery lifetime based on usage patterns. Because every user has a different pattern of voice calls, data communication, and video call usage, we can use such usage patterns for personalized prediction of battery lifetime. Firstly, we define one or more states that affect battery consumption. Then, we record time-series log data related to battery consumption and the use time of each state. We calculate the average battery consumption rate for each state and determine the usage pattern based on the time-series data. Finally, we predict the available battery time based on the average battery consumption rate for each state and the usage pattern. We also present the experimental trials used to validate our approach in the real world.

• Journal of the Korean Operations Research and Management Science Society
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• v.37 no.4
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• pp.225-238
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• 2012

The purpose of this study is to examine the factors influencing usage intention of u-Healthcare with voluntariness in long-term care hospitals. This model tests various theoretical research hypotheses relating to u-Healthcare, UTAUT theory and voluntariness. The proposed model is analyzed to target long-term care hospitals. Questionnaires have been collected during two months of 2010 and total 142 has been considered to be valid. Smart PLS (partial least square) 2.0 and SPSS 15.0 have been utilized for deriving the study results. The results of hypothesis testing are as follows. First, performance expectance, effort expectancy and social influence positively influence usage intention. Second, facilitation not influence usage intention. Still due to lack of technical infrastructure to promote conditions of use u-Healthcare in long-care hospitals for u-Healthcare system also considered to be not significantly affected. Finally, performance expectance to usage intention for low voluntariness group is significantly larger than those for high voluntariness group. In addition, social influence to usage intention for high voluntarines group is significantly larger than those for low voluntariness group.

• Journal of Navigation and Port Research
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• v.30 no.8 s.114
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• pp.669-674
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• 2006

The purpose of this study is to examine the effects of the factors on the usage level of e-business in the shipping companies. In order to do empirical analysis, firstly, this study carried out reliability analysis and factor analysis. Secondly, this study examined the effects of the factors on the usage level of e-business in the shipping companies by multiple regression analysis. In conclusion, the analysis result revealed that 5 factors effect on the service business usage's level and 4 factors effect on the real transaction usage's level of e-business.