• 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.

• Fashion & Textile Research Journal
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• v.25 no.3
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• pp.291-303
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• 2023

The purpose of this study is to investigate the impact of technical acceptance factors of Chinese MZ generation consumers' use of online fashion platforms on behavioral intentions and usage behavior, and to determine whether satisfaction plays an additional role in the relationship between behavioral intentions and usage behavior. The research results can be summarized as follows. First, among the technology acceptance factors that influence Generation MZ consumers when they use online fashion platforms, it was found that performance expectancy, effort expectancy, facilitating conditions, hedonic motivation, price value, habit, and content quality significantly influence the behavioral intention to use online fashion platforms. Second, the facilitating conditions and the platform usage intention of Chinese Generation MZ consumers directly and significantly influence the usage behavior on online fashion platforms. In contrast, it was confirmed that habit does not significantly influence actual usage behavior. Third, this study confirmed the moderating effect of satisfaction on the relationship between behavioral intention and usage behavior on online fashion platforms. This research, which proposes a research model explaining the usage intention and behavior of online fashion platforms based on UTAUT2, integrating not only the organizational aspect but also the consumer aspect to empirically verify the usage intention and the final usage behavior from the general consumer's perspective, has academic significance.

• Health Policy and Management
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• v.33 no.3
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• pp.295-310
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• 2023

Background: The long-term care (LTC) group has higher rates of chronic disease and disability registration compared to the general older people population. There is a need to provide integrated medical services and care for LTC group. Consequently, this study aimed to identify medical usage patterns based on the ratings of LTC and the characteristics of benefits usage in the LTC group. Methods: This study employed the National Health Insurance Service Database to analyze the effects of demographic and LTC-related characteristics on medical usage from 2015 to 2019 using a repeated measures analysis. A longitudinal logit model was applied to binary data, while a linear mixed model was utilized for continuous data. Results: In the case of LTC ratings, a positive correlation was observed with overall medical usage. In terms of LTC benefit usage characteristics, a higher overall level of medical usage was found in the group using home care benefits. Detailed analysis by medical institution classification revealed a maintained correlation between care ratings and the volume of medical usage. However, medical usage by classification varied based on the characteristics of LTC benefit usage. Conclusion: This study identified a complex interaction between LTC characteristics and medical usage. Predicting the requisite medical services based on the LTC rating presented a challenge. Consequently, it becomes essential for the LTC group to continuously monitor medical and care needs, even after admission into the LTC system. To facilitate this, it is crucial to devise an LTC rating system that accurately reflects medical needs and to broaden the implementation of integrated medical-care policies.

• Korean Management Science Review
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• v.34 no.3
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• pp.43-60
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• 2017

This study empirically examined the differences in degrees of product or process innovations according to the activation forms of all knowledge management (KM) processes (i.e., socialization, internalization, externalization, and combination), which are influenced by the usage patterns of management control systems (MCS)(i.e., interactive and diagnostic usage patterns). We empirically investigated and identified the links among usage patterns of MCS, the activation forms of KM processes, and the kinds of innovation promoted. Under high competitive conditions, it was found that the interactive usage of MCS is relatively more preferred and enhanced. However, when environmental uncertainty is high, it was shown that the diagnostic use of MCS is more emphasized. Thus, it is evident that the use patterns of MCS are determined by environmental conditions. From the results of this study, it was suggested that under high interactive use of MCS, the activation of socialization and internalization is more enhanced than the facilitation of externalization. It was also observed that when both interactive and diagnostic usage of MCS are high, KM processes are more activated and strengthened. The results indicated that under high activation of KM processes, product innovation as well as process innovation are more frequently occurred. Finally, the results of this study suggested that according to the levels of innovation openness, major innovations are more frequently occurred and promoted than minor innovations.

• Korean Journal of Computational Design and Engineering
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• v.18 no.1
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• pp.36-48
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• 2013

In general, the product is used under several circumstances including environmental and usage conditions. According to the circumstances, the product has various performance degradation processes. In order to optimize the lifecycle of product usage, it is important to observe the degradation process and make suitable decisions on product operations. However, there are not much research works in evaluating the degree of product degradation based on product usage data. Recently, due to emerging ICT (Information and Communication Technology) technologies, it becomes possible to get the product usage data. Based on the gathered data, it is possible to analyze the degree of product degradation. The analysis of product usage data can improve product use and product design with advanced decisions. To this end, this study addresses one approach based on FMEA/FMECA method, called PDMCA (Performance, Degradation Modes and Criticality Analysis) for evaluating product degradation status and making suitable decisions.

• Journal of Korean Society for Quality Management
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• v.46 no.4
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• pp.797-820
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• 2018

Purpose: It is to seek for an appropriate cost rate analysis methodology of credit card value propositions in Korea. For this issue, it is claimed that methodologies based on probability distribution is more suitable than methodologies based on data-mining. The analysis model constructed for the cost rate estimation is called VCPM model. Methods: The model includes two major variables denoted as S and P. S is monthly credit card usage amount. P stands for the proportion of usage amount at special merchants over the whole monthly usage amount. The distributions assumed for P are positively skewed distributions such as exponential, gamma and lognormal. The major inputs to the model are also derived from S and P, which are E(S) and the aggregate proportion of usage amount at special merchants over the total monthly usage amount. Results: When the credit card's value proposition is general discount, the VCPM model fits well and generates reasonable cost rate(denoted as R). However, it seems that the model does not work well for other types of credit cards. Conclusion: The VCPM model is reliable for calculating cost rate for credit cards with positively skewed distribution of P, which are general discount card. However, another model should be built for cards with other types of distributions of P.

• Journal of Environmental Science International
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• v.31 no.8
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• pp.707-713
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• 2022

This study aimed to comprehensively analyze the usage characteristics of children's parks according to location in Gangneung-si. Weekday and weekend, gender, time of stay, and usage behavior according to age group were analyzed and a video analysis of unmanned camera data for park management was conducted. On the average, the use of children's parks during spring and autumn was more than twice that during summer, and the use rate of children's parks located in old central districts by elderly people was relatively higher than the use rate of those located in housing development district. Overall, the usage ratio (24.6%) by elderly people was high, and their usage ratio (31.3%) in the morning period from dawn was significantly high. Among the usage behaviors, the rate at which dogs walk was analyzed to be somewhat high. As the usage ratio by elderly people is high with diverse usage behavior, it is necessary to provide complex functions to children's parks in the future.

• 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.