Big data refers to the data that cannot be processes with conventional contemporary data technologies. As smart devices and social network services produces vast amount of data, big data attracts much attention from researchers. There are strong demands form governments and industries for bib data as it can create new values by drawing business insights from data. Since various new technologies to process big data introduced, academic communities also show much interest to the big data domain. A notable advance related to the big data technology has been in various fields. Big data technology makes it possible to access, collect, and save individual's personal data. These technologies enable the analysis of huge amounts of data with lower cost and less time, which is impossible to achieve with traditional methods. It even detects personal information that people do not want to open. Therefore, people using information technology such as the Internet or online services have some level of privacy concerns, and such feelings can hinder continued use of information systems. For example, SNS offers various benefits, but users are sometimes highly exposed to privacy intrusions because they write too much personal information on it. Even though users post their personal information on the Internet by themselves, the data sometimes is not under control of the users. Once the private data is posed on the Internet, it can be transferred to anywhere by a few clicks, and can be abused to create fake identity. In this way, privacy intrusion happens. This study aims to investigate how perceived personal information overload in SNS affects user's risk perception and information privacy concerns. Also, it examines the relationship between the concerns and user resistance behavior. A survey approach and structural equation modeling method are employed for data collection and analysis. This study contributes meaningful insights for academic researchers and policy makers who are planning to develop guidelines for privacy protection. The study shows that information overload on the social network services can bring the significant increase of users' perceived level of privacy risks. In turn, the perceived privacy risks leads to the increased level of privacy concerns. IF privacy concerns increase, it can affect users to from a negative or resistant attitude toward system use. The resistance attitude may lead users to discontinue the use of social network services. Furthermore, information overload is mediated by perceived risks to affect privacy concerns rather than has direct influence on perceived risk. It implies that resistance to the system use can be diminished by reducing perceived risks of users. Given that users' resistant behavior become salient when they have high privacy concerns, the measures to alleviate users' privacy concerns should be conceived. This study makes academic contribution of integrating traditional information overload theory and user resistance theory to investigate perceived privacy concerns in current IS contexts. There is little big data research which examined the technology with empirical and behavioral approach, as the research topic has just emerged. It also makes practical contributions. Information overload connects to the increased level of perceived privacy risks, and discontinued use of the information system. To keep users from departing the system, organizations should develop a system in which private data is controlled and managed with ease. This study suggests that actions to lower the level of perceived risks and privacy concerns should be taken for information systems continuance.
Korean Journal of Construction Engineering and Management
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v.20
no.4
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pp.22-33
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2019
The government has steadily revised and developed laws and systems for activating remodeling of apartments in response to the problems of aged apartments. However, despite such efforts, remodeling has yet to be activated. For many reasons, this study noted that there were no tools for reasonable profitability judgements and decision making in the preliminary stages of the remodeling project. Thus, the feasibility evaluation model was developed. Generally, the profitability judgements are made after the conceptual design. However, decisions to drive remodeling projects are made at the preliminary stage. So a feasibility evaluation model is required at the preliminary stage. Accordingly, In this study, a feasibility evaluation model was developed for determining preliminary stage profitability. Construction costs, business expenses, financial expenses, and generally sales revenue were calculated using the initial available information and remodeling variables derived through the existing cases. Through this process, we developed an algorithm that can give an overview of the return on investment. In addition, the preliminary stage feasibility evaluation model developed was applied to three cases to verify the applicability of the model. Although applied in three cases, the difference between the model's forecast and actual case values is less than 5%, which is considered highly applicable. If cases are expanded in the future, it will be a useful tool that can be used in actual work. The feasibility evaluation model developed in this study will support decision making by union members, and if the model is applied in different regions, it will be expected to help local governments to understand the size of possible remodeling projects.
Hyeong Ju Seok;Chang Hun Lee;Choul-Hee Hwang;Young Ryun Kim;Daesun Kim;Moon Suk Lee
Journal of the Korean Society of Marine Environment & Safety
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v.29
no.7
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pp.802-811
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2023
Marine spatial planning (MSP) is a crucial element for rational allocation and sustainable use of marine areas. Particularly, Fishing Activity Protected Areas constitute essential zones accounting for 45.6% designated for sustainable fishing activities. However, the current assessment of these zones does not adequately consider future demands and potential values, necessitating appropriate evaluation methods and predictive tools for long-term planning. In this study, we selected key fish species (Scomber japonicus, Trichiurus lepturus, Engraulis japonicus, and Larimichthys polyactis) within the Fishing Activity Protected Area to predict their distribution and compare it with the current designated zones for evaluating the ability of the prediction tool. Employing the Intergovernmental Panel on Climate Change (IPCC) 6th Assessment Report scenarios (SSP1-2.6 and SSP5-8.5), we used species distribution models (such as MaxEnt) to assess the movement and distribution changes of these species owing to future variations. The results indicated a 30-50% increase in the distribution area of S. japonicus, T. lepturus, and L. polyactis, whereas the distribution area of E. japonicus decreased by approximately 6-11%. Based on these results, a species richness map for the four key species was created. Within the marine spatial planning boundaries, the overlap between areas rated "high" in species richness and the Fishing Activity Protected Area was approximately 15%, increasing to 21% under the RCP 2.6 scenario and 34% under the RCP 8.5 scenario. These findings can serve as scientific evidence for future evaluations of use zones or changes in reserve areas. The current and predicted distributions of species owing to climate change can address the limitations of current use zone evaluations and contribute to the development of plans for sustainable and beneficial use of marine resources.
Journal of Korea Society of Industrial Information Systems
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v.23
no.5
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pp.119-134
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2018
Today, many firms face the environment of high uncertainty and severe competition due to the rapid technology development and the diverse needs of customers. In the business environment, one of the most important ways to gain sustainable competitive advantage and future growth engine is related to NPD (New Product Development), which is a very important issue for practice and academia. Thus, this study intends to provide new values to practitioners and researchers related to NPD by analyzing current research trends and future trends in NPD field. For this, we bibliometrically analyzed keyword networks which consist of keywords that were already published in the eminent journals from Scopus database to generate insights that have not been captured in the previous reviews on the topic. As a result, we could understand the extant research streams in NPD field, and suggest the changes of specific research topics based on the connected relationships among keywords over the time. In addition, we also foresaw the general future research trends in NPD field based on the keywords according to preferential attachment processes. Through this study, it was confirmed that NPD keyword network is a small world network that follows the distribution of power law and the growth of network is formed by link formation by keyword preferential attachment. In addition, through component analysis and centrality analysis, keywords such as Innovation, New product innovation, Risk management, Concurrent engineering, Research and development, and Product life cycle management are highly centralized in NPD keyword network. On the other hand, as a result of examining the change of preferential attachment of keywords over the time, we suggested the required new research direction including i) NPD collaboration with suppliers, ii) NPD considering market uncertainty, iii) NPD considering convergence with the other academic areas like technology management and knowledge management, iv) NPD from SME(Small and medium enterprises) perspective. The results of this study can be used to determine the research trends of NPD and the new research themes for interdisciplinary studies with other disciplines.
Journal of the Korean Institute of Landscape Architecture
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v.43
no.3
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pp.77-91
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2015
This study aims to suggest adequate soil management through the analysis of physicochemical properties of soil in the planting grounds of Incheon International Airport, which was constructed on a massive land reclamation site. Study areas were 5 sites at the international business complex, the passenger terminal, the airport support complex, the free trade zone, and the access road. Soil profile analysis showed that 9 plots out of the 27 plots were hardpan and heterospere within 80cm from the soil surface. The earth laid on the ground was categorized as gravel based soil(4 plots), dredged soil from the sea bottom and mixed reclamation materials(2 plots), clay with poor permeability(3 plots) and waste construction material(1 plot). Average soil hardness was $11.5kg/cm^2$ and soil textures were sandy soil, sandy loam and loamy sand. Average soil pH was 6.7 and average organic matter content was 0.7%. Electrical conductivity was 0.0dS/m and exchangeable cation concentrations were $Ca^{2+}$ 3.4cmol/kg, $Mg^{2+}$ 1.5cmol/kg, $K^+$ 0.3cmol/kg and $Na^+$ 1.0cmol/kg. Average cation exchange capacity was 11.0cmol/kg. Although average figures in Solum mostly meet the landscape design criteria, properties of each soil layer showed various values sometimes over the limit. Base saturations were $Ca^{2+}$ 29.9%, $Mg^{2+}$ 13.3% and $K^+$ 3.7% for lower soil, $Ca^{2+}$ 33.3%, $Mg^{2+}$ 17.0% and $K^+$ 2.7% for mid-soil and $Ca^{2+}$ 32.6%, $Mg^{2+}$ 12.2% and $K^+$ 1.9% for upper soil. Exchangeable sodium percentages were 16.4% for lower soil, 7.5% for mid-soil and 4.7% upper soil. Sodium adsorption rates were 0.8 for lower soil, 0.3 for mid-soil and 0.2 for upper soil. Factors affecting to the vegetation growth were heterogeneity and poorness of solum, disturbance of dredged soils, high soil hardness including hardpan in the subsurface soil layer and shallow effective soil depth, high soil acidity, imbalance of base contents, low organic matter content and low available phosphate levels in the soil.
Mobile games have taken 80% of the market sales in smart device application industry that is highly regarded as one of the fast growing pool of cultural content after the distribution of smart devices. One of the most successful mobile games after the smart device's appearance is . created by Gung-ho Online entertainment under Softbank Japan, has gained the sales revenue of one trillion dollars after its release in 2012, just after one year of its exposure to the market. The game also has been the top rank by Worldwide Mobile Game Revenues for 2years achieving 40 million downloads worldwide in 2015. However, there is no place for a Korean game in world mobile game sales ranks yet. Even though the mobile game industry has been expanding every year, Korean games are losing its places in the market. Therefore, the analysis of a successful game such as is vital for diagnosing Korea's game content and its lack of direction. This study utilizes K. Masanao's Matrix for Creating Profit System for analyzing 's factors for its success. First, the game has incorporated puzzle and RPG contents for creating a new genre, which led various age groups to play the game. Second, the developers have applied 'limited time' in-game festivals and collaborations between the game and famous contents such as God Festival and Character Draw system to increase the profit revenue. Third, the company communicated with on and off line players to seek their needs for developing the game's better development. Consequently, the three success factors of deduced from this study not only reflect the related researches and academic values, but also contribute for the search in finding better ways to developing game contents for Korean mobile game industry.
The government's implementation of customer-friendly financial policies, such as lowering commission fees for credit card merchants and lowering the maximum interest rate, put the specialized credit finance companies in a crisis of lowering profitability. In this unfavorable situation, the efficiency study of specialized credit finance companies is meaningful. Accordingly, this study measured the efficiency of 34 specialized credit finance companies through Data Envelopment Analysis (DEA) and meta-frontier analysis. For meta-frontier analysis, specialized credit finance companies were divided into two groups (card companies and non-card companies) by industry or three groups (AA0 and above, AA-, and A+ or below) by credit rating. The results of the analysis will provide general insight into the efficiency of specialized credit finance companies. The results of this study are as follows. First, the average meta-efficiency of card companies was analyzed higher than that of non-card companies. Second, 80% of non-card's decision-making units (DMUs) were inefficient by pure technology rather than by scale. Third, decision-making units (DMUs), which account for 62.5% of the credit card company group and 80% of the 'AA-' credit rating group, are in non-economic areas of scale. Fourth, there was no statistically significant difference in meta-efficiency values (TE and PTE) by industry (card companies, non-card companies) and credit rating (AA0 or higher, AA-, A+ or lower). The contribution of this study will provide strategic initiatives for establishing management strategies to improve inefficiency by measuring the efficiency level of companies under an unfriendly business environment for specialized credit finance companies.
The purpose of this study is to verify empirically the causal relationship between service quality, ease of use, customer satisfaction, and repurchase intention of mobile shopping mall. And this study is to investigate the ease of use and customer satisfaction mediating effect of between service quality and repurchase intention. Therefore, 323 university students in Jeonnam area were surveyed and the structural equation model was derived based on previous research. Service quality of mobile shopping mall make a significant effect on using easiness, purchasing satisfaction and repurchase intention. However, among service quality of mobile shopping mall, service scape like mobile interface and site design made a positive effect on purchasing satisfaction, but did not any effect on repurchase intention. In other words, service quality factors that make positive effects on customer's pleasant using and repurchase intention make a positive effect on repurchase intention when providing and using the service customer wants faithfully rather than external part of the site and mutually influencing attitude or behavior well. The implications suggested by this study are as follows. First, service quality of mobile shopping mall makes a significant effect on repurchase intention, so it's necessary to improve CS service system so as to treat customers' inquiries or inconveniences actively during mobile shopping and return and refund of defective products quickly and conveniently. And, in addition to the finally used factors in analysis process, benefits using customers' grade by number of purchases, such as various events, coupons, reserve, etc. and active contents marketing strategies providing more various pleasures and values of shopping are necessary. Second, satisfaction of mobile shopping mall makes a positive effect on repurchase intention, so visiting of site and repurchasing of product are continuously done as customers' satisfaction on shopping mall is increasing. Therefore, shopping mall site requires differentiation of contents, exact plan and practice of service, marketing, etc. so that customers can feel more satisfaction. This study is significant as it systematically analyzed concepts of components that service quality of mobile shopping mall makes an effect on using easiness, purchasing satisfaction, and repurchase intention, verified the relations, systematized it by theoretical structure, and widened the understanding of effects making an effect on repurchase intention.
Journal of Korean Home Economics Education Association
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v.35
no.1
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pp.1-14
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2023
The objective of the study was to examine the associations of dietary carbohydrate and fat intake with the prevalence of metabolic syndrome in Korean women. A cross-sectional study was employed based on data from the Korea National Health and Nutrition Examination (2007-2016). A total of 22,850 women aged 19 to 69 years were studied after excluding responses from pregnant or lactating women and those with missing metabolic values. Dietary intake data were collected with a 24-hour recall method. Dietary carbohydrate and fat intakes were divided into quintiles. After controlling for confounding variables, a multivariable logistic regression and general linear model were used. The findings indicated that HDL cholesterol levels were lower (p for trend<0.01), while triglyceride levels (p for trend=0.04), waist circumference (p for trend<0.01), and systolic blood pressure (p for trend<0.01) were higher among participants in the highest quintile of carbohydrate intake compared to those in the lowest quintile. Participants in the highest quintile of fat intake had lower waist circumference (p for trend=0.02), triglyceride level (p for trend<0.01), and systolic blood pressure (p for trend<0.01), while higher HDL cholesterol level (p for trend<0.01) compared to those in the lowest fat intake quintile. Metabolic syndrome was more likely to be present in the highest quintile of carbohydrates intake than in the lowest quintile (5th quintile vs. 1st quintile, OR: 1.32; 95% CI: 1.11 to 1.57). However, metabolic syndrome was less likely to be present in the highest quintile of fat intake than in the lowest quintile (5th quintile vs. 1st quintile, OR: 0.73; 95% CI: 0.61 to 0.86). This study revealed that high dietary carbohydrate intake and low dietary fat intake were associated with metabolic syndrome in Korean women.
In this research, a methodology was developed for constructing an appropriate rainfall image database for estimating rainfall intensity based on CCTV video. The database was constructed in the Large-Scale Climate Environment Chamber of the Korea Conformity Laboratories, which can control variables with high irregularity and variability in real environments. 1,728 scenarios were designed under five different experimental conditions. 36 scenarios and a total of 97,200 frames were selected. Rain streaks were extracted using the k-nearest neighbor algorithm by calculating the difference between each image and the background. To prevent overfitting, data with pixel values greater than set threshold, compared to the average pixel value for each image, were selected. The area with maximum pixel variability was determined by shifting with every 10 pixels and set as a representative area (180×180) for the original image. After re-transforming to 120×120 size as an input data for convolutional neural networks model, image augmentation was progressed under unified shooting conditions. 92% of the data showed within the 10% absolute range of PBIAS. It is clear that the final results in this study have the potential to enhance the accuracy and efficacy of existing real-world CCTV systems with transfer learning.
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