• Journal of Preventive Medicine and Public Health
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• v.31 no.3 s.62
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• pp.564-578
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• 1998

Most extended care facilities have admitted both the healthy and unhealthy elderly, among which members' average caring demand vary. The Aged Welfare Law, however, currently provides no reasonable basis on the staffing policy for extended care facilities. It just reflects the admitted number of the elderly rather than differences in members' average caring demand among facilities. This study is designed to estimate the need for caring staff on the basis of the correlation between the individual health status measured by various tools including Activities of Daily Living and caring demand by actual service time for each one. The sample included all of the admitted elderly(187 persons) in 4 extended care facilities, two in Seoul and the other two in Kangwon-Do over the survey period October 5 through October 20, 1996. The survey process consisted of 3 stages. (1) The current staffing information was collected through self-completed written questionnaires left for head of official in each facility. (2) Six graduate students at School of Public Health interviewed all residents to collect information on their health status and sociodemographics. The response rate for the interview was relatively high(85%). (3) Information on direct and indirect caring time consumed for each residents came from self-completed written questionnaires given to nurses and helpers in each target facilities. Analysis of the data was made using Pearson's correlation and multiple regression technique through SAS program. Based on this procedure, the following was found. 1. No facility meet the staffing standard in the Aged Welfare Law completely. 2. It is actual service time that is most correlated with ADL(Activities of daily living). 3. When all of the elderly are divided by four groups based on the level of ADL, the mean values of needed caring time in each group are 15, 21, 36 and 88 minutes respectively. 4. There is no significant difference among facilities in distribution of elderly person by group. 5. No facility meets the estimated number of nurses and helpers which reflects health status of the admitted elderly. Therefore, it is required that severity of the admitted elderly be considered in establishing staffing standard for extended care facility.

• 한국벤처창업학회:학술대회논문집
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• 2006.04a
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• pp.45-75
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• 2006

How much influence does a business plan have on a corporate performance? Whilst previous studies and literatures all assert a strong correlation between the two, very few have actually conducted practical analyses to support that. This study takes an empirical approach in its analysis of Korea' s small and medium-sized enterprises (SME) with the view to finding an answer to the question. A business plan' s components, which have to date been suggested only in theory and in concept, have been selected through the study of literatures and preliminary examination. The selected components were then narrowed down into five factors of productivity, implementation, operational direction, product/service and customer accessibility by applying factor analysis. With which items to measure corporate performance is also an important question as results differ depending on which measurement items were used. For the purpose of this study, corporate performance was classified into effectiveness, adaptability and efficiency to measure how greatly each is influenced by the components of a business plan. Results show that effectiveness and adaptability have a positive (+) influence on corporate performance. The regression model seems to explain effectiveness particularly well. However, different directions of influences were showed in explain power of the research model were not high. And it can be interpreted that implementation of the plan is as important as the establishment of it. Thus a good corporate performance is to be had only under an excellent plan and following an excellent implementation. In most of the companies surveyed, business plans were established regularly led by the intense involvement of the CEO. Such plans were then used in internal operations, such as guiding operational direction and measuring corporate performance. Unlike general expectations, relatively few companies used them in financing from external sources such as banks or venture capitals. These findings are different from previous studies conducted in this field. Also, as market uncertainty was pointed out as the biggest obstacle to business planning. a manager must pay more attention to acquiring external information and knowledge so as to minimize it.

• The Journal of Society for e-Business Studies
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• v.25 no.4
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• pp.33-60
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• 2020

Along with the rapid advance in internet technologies, ubiquitous mobile device usage has enabled consumers to access real-time information and increased interaction with others through various social media. Consumers can now get information more easily when making purchase decisions, and these changes are affecting the brand landscape. In a digitally connected world, brand image is not communicated to the consumers one-sidedly. Rather, with consumers' growing influence, it is a result of co-creation where consumers have an active role in building brand image. This explains a reality where people no longer purchase products just because they know the brand or because it is a famous brand. However, there has been little discussion on the matter, and many practitioners still rely on the traditional measures of brand indicators. The goal of this research is to present the limitations of traditional definition and measurement of brand and brand image, and propose a more direct and adequate measure that reflects the nature of a connected world. Inspired by the proverb, "A man is known by the company he keeps," the proposed measurement offers insight to the position of brand (or brand image) through co-purchased product networks. This paper suggests a framework of network analysis that clusters brands of cosmetics by the frequency of other products purchased together. This is done by analyzing product networks of a brand extracted from actual purchase data on Amazon.com. This is a more direct approach, compared to past measures where consumers' intention or cognitive aspects are examined through survey. The practical implication is that our research attempts to close the gap between brand indicators and actual purchase behavior. From a theoretical standpoint, this paper extends the traditional conceptualization of brand image to a network perspective that reflects the nature of a digitally connected society.

• Journal of the Korean Institute of Landscape Architecture
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• v.47 no.5
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• pp.78-90
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• 2019

The purpose of this study is to explore the direction of developing policies for parks and green spaces for inclusive urban planning and regeneration. By reviewing the status, budget, and laws pertaining to urban parks in Korea, as well as assessing the inclusivity of urban parks, this study revealed the problems and limitations in Korea as follows. First, the urban park system, which takes into account indicators such as park area per capita and green space ratio, is focused only on quantitative expansion. Second, the distribution of urban parks is unequal; hence, the higher the number of vulnerable residents, the lower the quality of urban parks and green spaces. Moreover, this study focused on the UK central government, along with the five local governments, including London, Edinburgh, Cardiff, Belfast, and Liverpool. Through an analysis of the contexts and contents establishing UK park and green space policies that can reduce socioeconomic inequalities while at the same time increase inclusiveness. This study discovered the following. The government's awareness of the necessity of tackling socioeconomic inequalities to make an inclusive society, the change in the urban regeneration policies from physical redevelopment to neighborhood renewal, and the survey and research on the correlation of parks and green spaces, inequality, health, and well-being provided the background for policy establishment. As a result, the creation of an inclusive society has been reflected in the stated goals of the UK's national plan and the strategies for park and green space supply and qualitative improvement. Deprived areas and vulnerable groups have been included in many local governments' park and green space policies. Also, tools for analyzing deficiencies in parks and methods for examining the qualitative evaluation of parks were developed. Besides, for the sustainability of each project, various funding programs have been set up, such as raising funds and fund-matching schemes. Different ways of supporting partnerships have been arranged, such as the establishment of collaborative bodies for government organizations, allowing for the participation of private organizations. The study results suggested five policy schemes, including conducting research on inequality and inclusiveness for parks and green spaces, developing strategies for improving the quality of park services, identifying tools for analyzing policy areas, developing park project models for urban regeneration, and building partnerships and establishing support systems.

• Journal of the Korean Institute of Landscape Architecture
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• v.50 no.4
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• pp.63-76
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• 2022

This study was conducted to compare the perceptions of the park use status, importance, and satisfaction of users in the first implemented and completed Uijeongbu Jikdong Neighborhood Park among the private park special projects carried out as a countermeasure for long-term non-execution of urban parks. To this end, in the initiated project, apartment residents and non-residents were classified according to the promotion plan, and a questionnaire research on importance and satisfaction was conducted to analyze the park use status and IPA(importance-performance analysis). First, as a result of the analysis of the current situation in terms of locational characteristics that occur during the promotion of special projects for private parks, unlike the mountainous areas, the targeted site was close to flat land, indicating that users' satisfaction with the landscape was high. Second, the access of the apartment residents in the initiated project site was easy. Thus, the use rate of residents was relatively higher than that of the non-residents. Third, differences in perception by item were identified through the analysis of IPA and the establishment of strategies. In quadrant I, among the facilities and services, installing restrooms was the priority for residents, and parking facilities and rest facilities were the priority than installing restrooms for non-residents. In quadrant II, overall scores for residents and non-residents were similar, but the distance to the park was in quadrant III due to the low level of satisfaction among non-residents. In this study, the difference in perception between residents and non-residents may cause problems in access and facilities in managing the park in the future. Therefore, it would be necessary to find a way to improve it by establishing a management strategy that takes into account the difference in the perception of residents after construction. In addition, through the results of this study, it was judged that the purpose of park development, the selection of types of parks, and the selection of plans and management indicators for each kind would be significant in the promotion of initiated projects in the planning of park development.

• Journal of Intelligence and Information Systems
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• v.25 no.3
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• pp.117-140
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• 2019

As the aging phenomenon accelerates and various social problems related to the elderly of the vulnerable are raised, the need for effective elderly care solutions to protect the health and safety of the elderly generation is growing. Recently, more and more people are using Smart Toys equipped with ICT technology for care for elderly. In particular, log data collected through smart toys is highly valuable to be used as a quantitative and objective indicator in areas such as policy-making and service planning. However, research related to smart toys is limited, such as the development of smart toys and the validation of smart toy effectiveness. In other words, there is a dearth of research to derive insights based on log data collected through smart toys and to use them for decision making. This study will analyze log data collected from smart toy and derive effective insights to improve the quality of life for elderly users. Specifically, the user profiling-based analysis and elicitation of a change in quality of life mechanism based on behavior were performed. First, in the user profiling analysis, two important dimensions of classifying the type of elderly group from five factors of elderly user's living management were derived: 'Routine Activities' and 'Work-out Activities'. Based on the dimensions derived, a hierarchical cluster analysis and K-Means clustering were performed to classify the entire elderly user into three groups. Through a profiling analysis, the demographic characteristics of each group of elderlies and the behavior of using smart toy were identified. Second, stepwise regression was performed in eliciting the mechanism of change in quality of life. The effects of interaction, content usage, and indoor activity have been identified on the improvement of depression and lifestyle for the elderly. In addition, it identified the role of user performance evaluation and satisfaction with smart toy as a parameter that mediated the relationship between usage behavior and quality of life change. Specific mechanisms are as follows. First, the interaction between smart toy and elderly was found to have an effect of improving the depression by mediating attitudes to smart toy. The 'Satisfaction toward Smart Toy,' a variable that affects the improvement of the elderly's depression, changes how users evaluate smart toy performance. At this time, it has been identified that it is the interaction with smart toy that has a positive effect on smart toy These results can be interpreted as an elderly with a desire to meet emotional stability interact actively with smart toy, and a positive assessment of smart toy, greatly appreciating the effectiveness of smart toy. Second, the content usage has been confirmed to have a direct effect on improving lifestyle without going through other variables. Elderly who use a lot of the content provided by smart toy have improved their lifestyle. However, this effect has occurred regardless of the attitude the user has toward smart toy. Third, log data show that a high degree of indoor activity improves both the lifestyle and depression of the elderly. The more indoor activity, the better the lifestyle of the elderly, and these effects occur regardless of the user's attitude toward smart toy. In addition, elderly with a high degree of indoor activity are satisfied with smart toys, which cause improvement in the elderly's depression. However, it can be interpreted that elderly who prefer outdoor activities than indoor activities, or those who are less active due to health problems, are hard to satisfied with smart toys, and are not able to get the effects of improving depression. In summary, based on the activities of the elderly, three groups of elderly were identified and the important characteristics of each type were identified. In addition, this study sought to identify the mechanism by which the behavior of the elderly on smart toy affects the lives of the actual elderly, and to derive user needs and insights.

• Journal of Intelligence and Information Systems
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• v.27 no.3
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• pp.57-73
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• 2021

Maintenance and prevention of failure through anomaly detection of ICT infrastructure is becoming important. System monitoring data is multidimensional time series data. When we deal with multidimensional time series data, we have difficulty in considering both characteristics of multidimensional data and characteristics of time series data. When dealing with multidimensional data, correlation between variables should be considered. Existing methods such as probability and linear base, distance base, etc. are degraded due to limitations called the curse of dimensions. In addition, time series data is preprocessed by applying sliding window technique and time series decomposition for self-correlation analysis. These techniques are the cause of increasing the dimension of data, so it is necessary to supplement them. The anomaly detection field is an old research field, and statistical methods and regression analysis were used in the early days. Currently, there are active studies to apply machine learning and artificial neural network technology to this field. Statistically based methods are difficult to apply when data is non-homogeneous, and do not detect local outliers well. The regression analysis method compares the predictive value and the actual value after learning the regression formula based on the parametric statistics and it detects abnormality. Anomaly detection using regression analysis has the disadvantage that the performance is lowered when the model is not solid and the noise or outliers of the data are included. There is a restriction that learning data with noise or outliers should be used. The autoencoder using artificial neural networks is learned to output as similar as possible to input data. It has many advantages compared to existing probability and linear model, cluster analysis, and map learning. It can be applied to data that does not satisfy probability distribution or linear assumption. In addition, it is possible to learn non-mapping without label data for teaching. However, there is a limitation of local outlier identification of multidimensional data in anomaly detection, and there is a problem that the dimension of data is greatly increased due to the characteristics of time series data. In this study, we propose a CMAE (Conditional Multimodal Autoencoder) that enhances the performance of anomaly detection by considering local outliers and time series characteristics. First, we applied Multimodal Autoencoder (MAE) to improve the limitations of local outlier identification of multidimensional data. Multimodals are commonly used to learn different types of inputs, such as voice and image. The different modal shares the bottleneck effect of Autoencoder and it learns correlation. In addition, CAE (Conditional Autoencoder) was used to learn the characteristics of time series data effectively without increasing the dimension of data. In general, conditional input mainly uses category variables, but in this study, time was used as a condition to learn periodicity. The CMAE model proposed in this paper was verified by comparing with the Unimodal Autoencoder (UAE) and Multi-modal Autoencoder (MAE). The restoration performance of Autoencoder for 41 variables was confirmed in the proposed model and the comparison model. The restoration performance is different by variables, and the restoration is normally well operated because the loss value is small for Memory, Disk, and Network modals in all three Autoencoder models. The process modal did not show a significant difference in all three models, and the CPU modal showed excellent performance in CMAE. ROC curve was prepared for the evaluation of anomaly detection performance in the proposed model and the comparison model, and AUC, accuracy, precision, recall, and F1-score were compared. In all indicators, the performance was shown in the order of CMAE, MAE, and AE. Especially, the reproduction rate was 0.9828 for CMAE, which can be confirmed to detect almost most of the abnormalities. The accuracy of the model was also improved and 87.12%, and the F1-score was 0.8883, which is considered to be suitable for anomaly detection. In practical aspect, the proposed model has an additional advantage in addition to performance improvement. The use of techniques such as time series decomposition and sliding windows has the disadvantage of managing unnecessary procedures; and their dimensional increase can cause a decrease in the computational speed in inference.The proposed model has characteristics that are easy to apply to practical tasks such as inference speed and model management.

• Journal of Intelligence and Information Systems
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• v.25 no.4
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• pp.1-33
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• 2019

The small and medium sized enterprises (hereinafter SMEs) are already at a competitive disadvantaged when compared to large companies with more abundant resources. Manufacturing SMEs not only need a lot of information needed for new product development for sustainable growth and survival, but also seek networking to overcome the limitations of resources, but they are faced with limitations due to their size limitations. In a new era in which connectivity increases the complexity and uncertainty of the business environment, SMEs are increasingly urged to find information and solve networking problems. In order to solve these problems, the government funded research institutes plays an important role and duty to solve the information asymmetry problem of SMEs. The purpose of this study is to identify the differentiating characteristics of SMEs that utilize the public information support infrastructure provided by SMEs to enhance the innovation capacity of SMEs, and how they contribute to corporate performance. We argue that we need an infrastructure for providing information support to SMEs as part of this effort to strengthen of the role of government funded institutions; in this study, we specifically identify the target of such a policy and furthermore empirically demonstrate the effects of such policy-based efforts. Our goal is to help establish the strategies for building the information supporting infrastructure. To achieve this purpose, we first classified the characteristics of SMEs that have been found to utilize the information supporting infrastructure provided by government funded institutions. This allows us to verify whether selection bias appears in the analyzed group, which helps us clarify the interpretative limits of our study results. Next, we performed mediator and moderator effect analysis for multiple variables to analyze the process through which the use of information supporting infrastructure led to an improvement in external networking capabilities and resulted in enhancing product competitiveness. This analysis helps identify the key factors we should focus on when offering indirect support to SMEs through the information supporting infrastructure, which in turn helps us more efficiently manage research related to SME supporting policies implemented by government funded institutions. The results of this study showed the following. First, SMEs that used the information supporting infrastructure were found to have a significant difference in size in comparison to domestic R&D SMEs, but on the other hand, there was no significant difference in the cluster analysis that considered various variables. Based on these findings, we confirmed that SMEs that use the information supporting infrastructure are superior in size, and had a relatively higher distribution of companies that transact to a greater degree with large companies, when compared to the SMEs composing the general group of SMEs. Also, we found that companies that already receive support from the information infrastructure have a high concentration of companies that need collaboration with government funded institution. Secondly, among the SMEs that use the information supporting infrastructure, we found that increasing external networking capabilities contributed to enhancing product competitiveness, and while this was no the effect of direct assistance, we also found that indirect contributions were made by increasing the open marketing capabilities: in other words, this was the result of an indirect-only mediator effect. Also, the number of times the company received additional support in this process through mentoring related to information utilization was found to have a mediated moderator effect on improving external networking capabilities and in turn strengthening product competitiveness. The results of this study provide several insights that will help establish policies. KISTI's information support infrastructure may lead to the conclusion that marketing is already well underway, but it intentionally supports groups that enable to achieve good performance. As a result, the government should provide clear priorities whether to support the companies in the underdevelopment or to aid better performance. Through our research, we have identified how public information infrastructure contributes to product competitiveness. Here, we can draw some policy implications. First, the public information support infrastructure should have the capability to enhance the ability to interact with or to find the expert that provides required information. Second, if the utilization of public information support (online) infrastructure is effective, it is not necessary to continuously provide informational mentoring, which is a parallel offline support. Rather, offline support such as mentoring should be used as an appropriate device for abnormal symptom monitoring. Third, it is required that SMEs should improve their ability to utilize, because the effect of enhancing networking capacity through public information support infrastructure and enhancing product competitiveness through such infrastructure appears in most types of companies rather than in specific SMEs.