• Journal of the Korean Institute of Landscape Architecture
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• v.50 no.5
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• pp.40-53
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• 2022

This study carried out to provide the methodology and basic status material of using Korean national statistics needed to find the actual state of the landscape architecture industry. The landscape architecture industry was classified into 'Design', 'Construction Management', 'construction', 'Maintenance & Management', 'Materials', 'Research', 'Education', and 'Administration' areas. In each field, business types were systemized and associated in accordance with Korean standard industrial classification and legislations pertinent to construction. Among them, the business types directly defined in the construction related legislations under the Ministry of Land, Infrastructure and Transport were focused on, and the establishment, association, integration, distribution, duplication, and omission of national statistics were analyzed. As a result, the business types of statistical analysis were selected. In order for commonality of statistical items and minimized error of interpretation, semantic analysis was conducted. Finally, the number of registered business types, the number of workers, and sales were selected. Based on them, the analysis framework applicable to fundamental analysis and evaluation of the actual state of the industry was proposed. Actual national statical data were applied for analysis and evaluation. In 2019, the number of registered business types related to the landscape architecture industry was 12,160, the number of workers by business type was 106,296, and the sales by business type were 8,308.5 billion KRW. The number of registered business types and the number of workers had been on the rise from 2017, whereas the sales had been on the decrease. It is required to come up with a plan for industrial development. This study was conducted with the national statistics established by multiple public institutions, so that there are limitations in securing consistency and reliability. Therefore, it is necessary to establish systematic and consistent national statistics in accordance with 「Landscaping Promotion Act」. In the future, it will planned to research application and development plans of national statistics according to subjects including park and green.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.28 no.5B
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• pp.595-601
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• 2008

The purpose of this study is to investigate the trends and patterns of various kind of water uses in a household by metering in Korea. Water use components are classified by toilet, washbowl, bathing, laundry, kitchen, miscellaneous. Flow meters are installed in 140 household selected by sampling in all around Korea. The data are gathered by web-based data collection system from the year 2002 to 2006, considering pre-investigated data such as occupation, revenue, family members, housing types, age, floor area, water saving devices, education, miscellaneous. Reliable data are selected by upper fence method for each observed water use component and statistical characteristics are estimated for each residential type to determine liter per capita per day. Estimated domestic per capita day show an indoor water use with the range from 150 lpcd to 169 lpcd for each housing type as the order of high rise apartment, multi-house, and single house. As the order of consuming amount among water use components, it is investigated that toilet (38.5 lpcd) is the first, and the second is laundry water (30.8 lpcd), the third is kitchen (28.4 lpcd), the fourth is bathtub (24.7 lpcd), the next is washbowl (15.4 lpcd). The results are compared with water uses in U.K. and U.S. As life style has been changed into western style, pattern of water use in Korea is tend to be similar with the U.S. water use pattern. Compared with the surveying results by Bradley, on 1985. Thirty liter of total use increased with the advancement of economic level, and a little change of water use pattern can be found. Especially, toilet water take almost half part of total water use and laundry water shows lowest as 11% in surveying at the year of 1985. But, this study shows that 39 liter, 28% of toilet water, has been decreased by the spread of saving devices and campaign. It is supposed that the spread large sized laundry machine make by-hand laundry has been decreased and water use increased. Unit water amount of each end-use in household can be applied to design factor for water and wastewater facilities, and it play a role as information in establishing water demand forecasting and conservation policy.

• Journal of Nutrition and Health
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• v.50 no.2
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• pp.171-179
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• 2017

Purpose: We conducted comparative analysis of dietary behavior and food and nutrient intakes of Korean elderly in urban and rural areas using the 2014 Korea National Health and Nutrition Examination Survey (KNHANES). Methods: This study was conducted on 1,239 participants (urban elderly: 867, rural elderly: 372) aged 65 years and over who participated in the health examination and nutrition survey in the 6th 2014 KNHANES. Dietary behaviors, including skipping meals, eating out frequencies, and food and nutrient intakes were analyzed using 24-hour recall data. Analysis of complex sample design data through SPSS 19.0 was used for the analysis. Results: The rate of skipping dinner was higher in urban (6.5%) than in rural elderly (3.6%) (p < 0.05), and the frequency of eating out per week of urban elderly (1.73) was higher than that of rural elderly (1.35) (p < 0.001). The rural elderly consumed a greater amount of grain compared to urban elderly, whereas consumption of water, seaweed food, and dairy products was lower in rural than in urban areas (p < 0.05). The rural elderly consumed significantly less highly unsaturated fatty acids, n-6 fatty acids, phosphorus, iron, vitamin A, carotene, niacin, and vitamin C in comparison with elderly in urban areas. Comparison of the percentages of Dietary Reference Intakes for Koreans (KDRIs) between the two groups showed that intakes of vitamin A and vitamin C were significantly lower in the rural elderly than in urban elderly. Conclusion: The elderly in rural areas showed unbalanced food and nutrient intakes compared to the elderly in urban areas. Therefore, customized nutrition education according to residential areas should be developed and provided to rural elderly to improve their health and nutritional status.

• Asia pacific journal of information systems
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• v.24 no.4
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• pp.443-472
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• 2014

To survive in the global competitive environment, enterprise should be able to solve various problems and find the optimal solution effectively. The big-data is being perceived as a tool for solving enterprise problems effectively and improve competitiveness with its' various problem solving and advanced predictive capabilities. Due to its remarkable performance, the implementation of big data systems has been increased through many enterprises around the world. Currently the big-data is called the 'crude oil' of the 21st century and is expected to provide competitive superiority. The reason why the big data is in the limelight is because while the conventional IT technology has been falling behind much in its possibility level, the big data has gone beyond the technological possibility and has the advantage of being utilized to create new values such as business optimization and new business creation through analysis of big data. Since the big data has been introduced too hastily without considering the strategic value deduction and achievement obtained through the big data, however, there are difficulties in the strategic value deduction and data utilization that can be gained through big data. According to the survey result of 1,800 IT professionals from 18 countries world wide, the percentage of the corporation where the big data is being utilized well was only 28%, and many of them responded that they are having difficulties in strategic value deduction and operation through big data. The strategic value should be deducted and environment phases like corporate internal and external related regulations and systems should be considered in order to introduce big data, but these factors were not well being reflected. The cause of the failure turned out to be that the big data was introduced by way of the IT trend and surrounding environment, but it was introduced hastily in the situation where the introduction condition was not well arranged. The strategic value which can be obtained through big data should be clearly comprehended and systematic environment analysis is very important about applicability in order to introduce successful big data, but since the corporations are considering only partial achievements and technological phases that can be obtained through big data, the successful introduction is not being made. Previous study shows that most of big data researches are focused on big data concept, cases, and practical suggestions without empirical study. The purpose of this study is provide the theoretically and practically useful implementation framework and strategies of big data systems with conducting comprehensive literature review, finding influencing factors for successful big data systems implementation, and analysing empirical models. To do this, the elements which can affect the introduction intention of big data were deducted by reviewing the information system's successful factors, strategic value perception factors, considering factors for the information system introduction environment and big data related literature in order to comprehend the effect factors when the corporations introduce big data and structured questionnaire was developed. After that, the questionnaire and the statistical analysis were performed with the people in charge of the big data inside the corporations as objects. According to the statistical analysis, it was shown that the strategic value perception factor and the inside-industry environmental factors affected positively the introduction intention of big data. The theoretical, practical and political implications deducted from the study result is as follows. The frist theoretical implication is that this study has proposed theoretically effect factors which affect the introduction intention of big data by reviewing the strategic value perception and environmental factors and big data related precedent studies and proposed the variables and measurement items which were analyzed empirically and verified. This study has meaning in that it has measured the influence of each variable on the introduction intention by verifying the relationship between the independent variables and the dependent variables through structural equation model. Second, this study has defined the independent variable(strategic value perception, environment), dependent variable(introduction intention) and regulatory variable(type of business and corporate size) about big data introduction intention and has arranged theoretical base in studying big data related field empirically afterwards by developing measurement items which has obtained credibility and validity. Third, by verifying the strategic value perception factors and the significance about environmental factors proposed in the conventional precedent studies, this study will be able to give aid to the afterwards empirical study about effect factors on big data introduction. The operational implications are as follows. First, this study has arranged the empirical study base about big data field by investigating the cause and effect relationship about the influence of the strategic value perception factor and environmental factor on the introduction intention and proposing the measurement items which has obtained the justice, credibility and validity etc. Second, this study has proposed the study result that the strategic value perception factor affects positively the big data introduction intention and it has meaning in that the importance of the strategic value perception has been presented. Third, the study has proposed that the corporation which introduces big data should consider the big data introduction through precise analysis about industry's internal environment. Fourth, this study has proposed the point that the size and type of business of the corresponding corporation should be considered in introducing the big data by presenting the difference of the effect factors of big data introduction depending on the size and type of business of the corporation. The political implications are as follows. First, variety of utilization of big data is needed. The strategic value that big data has can be accessed in various ways in the product, service field, productivity field, decision making field etc and can be utilized in all the business fields based on that, but the parts that main domestic corporations are considering are limited to some parts of the products and service fields. Accordingly, in introducing big data, reviewing the phase about utilization in detail and design the big data system in a form which can maximize the utilization rate will be necessary. Second, the study is proposing the burden of the cost of the system introduction, difficulty in utilization in the system and lack of credibility in the supply corporations etc in the big data introduction phase by corporations. Since the world IT corporations are predominating the big data market, the big data introduction of domestic corporations can not but to be dependent on the foreign corporations. When considering that fact, that our country does not have global IT corporations even though it is world powerful IT country, the big data can be thought to be the chance to rear world level corporations. Accordingly, the government shall need to rear star corporations through active political support. Third, the corporations' internal and external professional manpower for the big data introduction and operation lacks. Big data is a system where how valuable data can be deducted utilizing data is more important than the system construction itself. For this, talent who are equipped with academic knowledge and experience in various fields like IT, statistics, strategy and management etc and manpower training should be implemented through systematic education for these talents. This study has arranged theoretical base for empirical studies about big data related fields by comprehending the main variables which affect the big data introduction intention and verifying them and is expected to be able to propose useful guidelines for the corporations and policy developers who are considering big data implementationby analyzing empirically that theoretical base.