• Land and Housing Review
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• v.15 no.3
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• pp.97-111
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• 2024

Greenhouse gas emissions and environmental pollution persist globally, leading to an increase in extreme weather events, such as floods and droughts. Previous studies have investigated various factors for energy consumption, such as household, residential, economic, and social characteristics. However, the body of research examining energy-saving behavior and perceptions remains limited and underexplored. In particular, significant differences in energy conservation perceptions can be observed among individual household members, even within the same household. To this end, this study explores how household energy consumption is associated with various factors, including household characteristics, housing characteristics, energy-saving behaviors, and seasonal factors. We utilize survey data from the Household Energy Panel, spanning a 24-month period from January 2018 to December 2019, comprising a sample of 5,897 households across 17 cities and provinces nationwide. The findings of this study are expected to offer an empirical evidence for household energy-saving policies.

• Journal of Cardiovascular Imaging
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• v.30 no.2
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• pp.99-108
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• 2022

BACKGROUND: Adding pulsation to the Fontan circulation might change the fate of patients palliated by this procedure. Our aim was to compare the pulsatility index (PI) of the pulmonary artery (PA) between the various modifications of Fontan palliation. METHODS: Doppler-derived PI was measured in PA branches of a cohort of 28 patients palliated by 6 modifications of Fontan procedure. A group of normal individuals was included for comparison. RESULTS: Atriopulmonary connection (APC) group had the highest PA branches PI and statistically was close to the PI of the normal individuals (right pulmonary artery [RPA] PI of 1.58 vs. 1.63; p = 0.99 and left pulmonary artery [LPA] PI of 1.54 vs. 1.68; p = 0.46, respectively). The lowest PA branches PI was seen in the group of extracardiac total cavopulmonary connection (RPA PI of 0.62 and LPA PI of 0.65). Other 4 modifications including the extracardiac conduit with oversewn pulmonary valve, extracardiac conduit with preserved adjusted antegrade flow, extracardiac conduit from inferior vena cava onto the rudimentary right ventricle and lateral tunnel had a mean "RPA and LPA" PI of "1.19 and 1.17", "1.16 and 1.11", "1.13 and 1.11", "0.82 and 0.84", respectively. The modified Dunnett's post hoc test has shown a significant statistical decline in PI of all modifications compared to the normal individuals except for the APC group. CONCLUSIONS: Fontan palliated patients in different groups of surgical modification showed a spectrum of Doppler-derived PI with the highest amounts belong to the groups of pulsatile Fontan.

• Journal of agricultural medicine and community health
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• v.37 no.1
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• pp.36-51
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• 2012

Objectives: This study was conducted to implement Health Plus Happiness Plus projects in Gyeongsangnam-Do and assess the policy implications of initiatives to address regional health inequalities. Methods: Health Plus Happiness Plus projects were started as strategies to address regional health inequalities in Gyeongsangnam-Do. The principles of these projects are taken from the Health Action Zones initiatives in England: participation, partnership, resource concentration in project areas. The time period for these projects is from 2010 to 2017, and the total budget is 5.6 billion won. In 2010, a 6.8 hundred million won total budget was invested in 17 project areas. Such investments fell into four broad categories: establishment of the means and local framework; survey development to analyze the health determinants; development of an education and training center; and establishment of a technical support center. Results: Education and training programs for practitioners and coordinators were provided, and project teams and project promotion committees were established in project areas. Health survey result briefing meetings were held, and 17 health committees were established in project areas. Conclusions: Health Plus Happiness Plus projects have some problems in relation to participation and partnerships, however, if these principled projects are performed continuously, they will contribute to a reduction of standardized mortality rate and regional health inequalities in Gyeongsangnam-Do and the improvement of residents' well-being in project areas.

• Journal of Internet Computing and Services
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• v.22 no.1
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• pp.109-135
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• 2021

his study classified the development process of artificial intelligence (AI) speakers through analysis of the news text of artificial intelligence (AI) speakers shown in traditional news reports, and identified the characteristics of each product by period. The theoretical background used in the analysis are news frames and topic frames. As analysis methods, topic modeling and semantic network analysis using the LDA method were used. The research method was a content analysis method. From 2014 to 2019, 2710 news related to AI speakers were first collected, and secondly, topic frames were analyzed using Nodexl algorithm. The result of this study is that, first, the trend of topic frames by AI speaker provider type was different according to the characteristics of the four operators (communication service provider, online platform, OS provider, and IT device manufacturer). Specifically, online platform operators (Google, Naver, Amazon, Kakao) appeared as a frame that uses AI speakers as'search or input devices'. On the other hand, telecommunications operators (SKT, KT) showed prominent frames for IPTV, which is the parent company's flagship business, and 'auxiliary device' of the telecommunication business. Furthermore, the frame of "personalization of products and voice service" was remarkable for OS operators (MS, Apple), and the frame for IT device manufacturers (Samsung) was "Internet of Things (IoT) Integrated Intelligence System". The econd, result id that the trend of the topic frame by AI speaker development period (by year) showed a tendency to develop around AI technology in the first phase (2014-2016), and in the second phase (2017-2018), the social relationship between AI technology and users It was related to interaction, and in the third phase (2019), there was a trend of shifting from AI technology-centered to user-centered. As a result of QAP analysis, it was found that news frames by business operator and development period in AI speaker development are socially constituted by determinants of media discourse. The implication of this study was that the evolution of AI speakers was found by the characteristics of the parent company and the process of co-evolution due to interactions between users by business operator and development period. The implications of this study are that the results of this study are important indicators for predicting the future prospects of AI speakers and presenting directions accordingly.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.18 no.5
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• pp.77-90
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• 2023

This study aims to investigate the potential of alternative credit assessment through Social Networking Sites (SNS) as a complementary tool to conventional loan review processes. It seeks to discern the impact of SNS usage characteristics and loan product attributes on credit loan repayment. To achieve this objective, we conducted a binomial logistic regression analysis examining the influence of SNS usage patterns, loan characteristics, and personal attributes on credit loan conditions, utilizing data from Company A's credit loan program, which integrates SNS data into its actual loan review processes. Our findings reveal several noteworthy insights. Firstly, with respect to profile photos that reflect users' personalities and individual characteristics, individuals who choose to upload photos directly connected to their personal lives, such as images of themselves, their private circles (e.g., family and friends), and photos depicting social activities like hobbies, which tend to be favored by individuals with extroverted tendencies, as well as character and humor-themed photos, which are typically favored by individuals with conscientious traits, demonstrate a higher propensity for diligently repaying credit loans. Conversely, the utilization of photos like landscapes or images concealing one's identity did not exhibit a statistically significant causal relationship with loan repayment. Furthermore, a positive correlation was observed between the extent of SNS usage and the likelihood of loan repayment. However, the level of SNS interaction did not exert a significant effect on the probability of loan repayment. This observation may be attributed to the passive nature of the interaction variable, which primarily involves expressing sympathy for other users' comments rather than generating original content. The study also unveiled the statistical significance of loan duration and the number of loans, representing key characteristics of loan portfolios, in influencing credit loan repayment. This underscores the importance of considering loan duration and the quantity of loans as crucial determinants in the design of microcredit products. Among the personal characteristic variables examined, only gender emerged as a significant factor. This implies that the loan program scrutinized in this analysis does not exhibit substantial discrimination based on age and credit scores, as its customer base predominantly consists of individuals in their twenties and thirties with low credit scores, who encounter challenges in securing loans from traditional financial institutions. This research stands out from prior studies by empirically exploring the relationship between SNS usage and credit loan repayment while incorporating variables not typically addressed in existing credit rating research, such as profile pictures. It underscores the significance of harnessing subjective, unstructured information from SNS for loan screening, offering the potential to mitigate the financial disadvantages faced by borrowers with low credit scores or those ensnared in short-term liquidity constraints due to limited credit history a group often referred to as "thin filers." By utilizing such information, these individuals can potentially reduce their credit costs, whereas they are supposed to accrue a more substantial financial history through credit transactions under conventional credit assessment system.

• Land and Housing Review
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• v.15 no.1
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• pp.1-22
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• 2024

This research explores the household and housing characteristics of young renters aged between 19 and 34 living independently in rental housing of non-Seoul Metropolitan Area (non-SMA) and to determine the factors of their housing affordability and residential environment qualities in two districts of non-SMA - metropolises and non-metropolises. Using the 2020 Korean Housing Survey (KHS), this study identified 1,191 unmarried young renters, and most were single adults in mid-twenties who were salaried workers with a bachelor's degree or higher. Also, many lived in single-room occupancy of non-APT housing for less than 2 years and rarely relied on social services. The findings showed that the distinction of local housing market between metropolises and non-metropolises forced the former to spend more housing expense (tenancy deposit and rental fees) than the latter. With regard to housing affordability indices (Schwabe index, housing expense ratio and rent to income ratio), most were housing cost-burdened and nearly one quarter were severely rent-burdened. The regression analysis indicated that housing affordability in both districts was positively affected by income increase and social services, and housing satisfaction in non-metropolises was added to its determinants. Further, residential environment qualities were largely divided into two groups of livelihood and urban infrastructure, and the two factors influenced residential assessment in both districts. Since young renters interdependently living had suffered with housing affordability, both income growth and housing assistance are critically required to enable them not just to reduce the burden but to ensure livability.

• Health Policy and Management
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• v.34 no.3
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• pp.261-270
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• 2024

Background: Various researchers are calculating the health adjusted life expectancy (HALE) at the regional level in South Korea using several methods, most studies merely enumerate the differences in healthy life expectancy based on social characteristics. This study aims to analyze the association between various sociodemographic factors and HALE at the regional level. Methods: To calculate HALE, we utilized the various data sources, including National Health Insurance claims data, and applied the Sullivan's method. We conducted multiple linear regression with regional socioeconomic variables from Korean Statistical Information Service. For the multiple linear regression analysis, we designed three regression models. Model 1 comprised solely socioeconomic variables, model 2 involved both socioeconomic variables and individual health behaviors, and model 3 integrated model 2 with healthcare utilization. Results: The analysis shows that an increase in financial independence (p<0.05), population density (p<0.1), and the number of doctors (p<0.05) associated with an increase in HALE, whereas an increase in the number of beds (p<0.01) was associated with a decrease in HALE. In case of the obesity rate, in model 2 (p<0.1) and model 3 (p<0.05), there was a negative association between HALE and obesity rate. Conclusion: Amidst various variables, it was observed that increased financial independence in specific regions had association with an increase in HALE, highlighting the need for stronger local governance in South Korea. Additionally, the inverse association between hospital beds and HALE suggests several implications, such as the appropriate deployment of healthcare resources. To gain a deeper understanding of the relationship between hospital beds and HALE, further analysis distinguishing different types of hospital beds across healthcare institutions seems necessary.

• Journal of Preventive Medicine and Public Health
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• v.11 no.1
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• pp.123-127
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• 1978

The major objective of this research is to identify those hospital characteristics that best explain cost variation among hospitals and to formulate linear models that can predict hospital costs. Specific emphasis is placed on hospital output, that is, the identification of diagnosis related patient groups (DRGs) which are medically meaningful and demonstrate similar patterns of hospital resource consumption. A casemix index is developed based on the DRGs identified. Considering the common problems encountered in previous hospital cost research, the following study requirements are estab-lished for fulfilling the objectives of this research: 1. Selection of hospitals that exercise similar medical and fiscal practices. 2. Identification of an appropriate data collection mechanism in which demographic and medical characteristics of individual patients as well as accurate and comparable cost information can be derived. 3. Development of a patient classification system in which all the patients treated in hospitals are able to be split into mutually exclusive categories with consistent and stable patterns of resource consumption. 4. Development of a cost finding mechanism through which patient groups' costs can be made comparable across hospitals. A data set of Medicare patients prepared by the Social Security Administration was selected for the study analysis. The data set contained 27,229 record abstracts of Medicare patients discharged from all but one short-term general hospital in Connecticut during the period from January 1, 1971, to December 31, 1972. Each record abstract contained demographic and diagnostic information, as well as charges for specific medical services received. The 'AUT-OGRP System' was used to generate 198 DRGs in which the entire range of Medicare patients were split into mutually exclusive categories, each of which shows a consistent and stable pattern of resource consumption. The 'Departmental Method' was used to generate cost information for the groups of Medicare patients that would be comparable across hospitals. To fulfill the study objectives, an extensive analysis was conducted in the following areas: 1. Analysis of DRGs: in which the level of resource use of each DRG was determined, the length of stay or death rate of each DRG in relation to resource use was characterized, and underlying patterns of the relationships among DRG costs were explained. 2. Exploration of resource use profiles of hospitals; in which the magnitude of differences in the resource uses or death rates incurred in the treatment of Medicare patients among the study hospitals was explored. 3. Casemix analysis; in which four types of casemix-related indices were generated, and the significance of these indices in the explanation of hospital costs was examined. 4. Formulation of linear models to predict hospital costs of Medicare patients; in which nine independent variables (i. e., casemix index, hospital size, complexity of service, teaching activity, location, casemix-adjusted death. rate index, occupancy rate, and casemix-adjusted length of stay index) were used for determining factors in hospital costs. Results from the study analysis indicated that: 1. The system of 198 DRGs for Medicare patient classification was demonstrated not only as a strong tool for determining the pattern of hospital resource utilization of Medicare patients, but also for categorizing patients by their severity of illness. 2. The wei틴fed mean total case cost (TOTC) of the study hospitals for Medicare patients during the study years was $11,27.02 with a standard deviation of $117.20. The hospital with the highest average TOTC ($1538.15) was 2.08 times more expensive than the hospital with the lowest average TOTC ($743.45). The weighted mean per diem total cost (DTOC) of the study hospitals for Medicare patients during the sutdy years was $107.98 with a standard deviation of $15.18. The hospital with the highest average DTOC ($147.23) was 1.87 times more expensive than the hospital with the lowest average DTOC ($78.49). 3. The linear models for each of the six types of hospital costs were formulated using the casemix index and the eight other hospital variables as the determinants. These models explained variance to the extent of 68.7 percent of total case cost (TOTC), 63.5 percent of room and board cost (RMC), 66.2 percent of total ancillary service cost (TANC), 66.3 percent of per diem total cost (DTOC), 56.9 percent of per diem room and board cost (DRMC), and 65.5 percent of per diem ancillary service cost (DTANC). The casemix index alone explained approximately one half of interhospital cost variation: 59.1 percent for TOTC and 44.3 percent for DTOC. Thsee results demonstrate that the casemix index is the most importand determinant of interhospital cost variation Future research and policy implications in regard to the results of this study is envisioned in the following three areas: 1. Utilization of casemix related indices in the Medicare data systems. 2. Refinement of data for hospital cost evaluation. 3. Development of a system for reimbursement and cost control in hospitals.

• Management & Information Systems Review
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• v.37 no.1
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• pp.139-154
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• 2018

R programming is free and open source system associated with a rich and ever-growing set of libraries of functions developed and submitted by independent end-users. It is recognized as a popular tool for handling big data sets and analyzing them. Reflecting these characteristics, R has been gaining popularity from data analysts. However, the antecedents of R technology acceptance has not been studied yet. In this study we identify and investigates cognitive factors contributing to build user acceptance toward R in education environment. We extend the existing technology acceptance model by incorporating social norms and software capability. It was found that the factors of subjective norm, perceived usefulness, ease of use affect positively on the intention of acceptance R programming. In addition, perceived usefulness is related to subjective norms, perceived ease of use, and software capability. The main difference of this research from the previous ones is that the target system is not a stand-alone. In addition, the system is not static in the sense that the system is not a final version. Instead, R system is evolving and open source system. We applied the Technology Acceptance Model (TAM) to the target system which is a platform where diverse applications such as statistical, big data analyses, and visual rendering can be performed. The model presented in this work can be useful for both colleges that plan to invest in new statistical software and for companies that need to pursue future installations of new technologies. In addition, we identified a modified version of the TAM model which is extended by the constructs such as subjective norm and software capability to the original TAM model. However one of the weak aspects that might inhibit the reliability and validity of the model is that small number of sample size.

• Journal of Intelligence and Information Systems
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• v.22 no.4
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• pp.157-176
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• 2016

For a long time, mobile phone had a sole function of communication. Recently however, abrupt innovations in technology allowed extension of the sphere in mobile phone activities. Development of technology enabled realization of almost computer-like environment even on a very small device. Such advancement yielded several forms of new high-tech devices such as smartphone and tablet PC, which quickly proliferated. Simultaneously with the diffusion of the mobile devices, mobile applications for those devices also prospered and soon became deeply penetrated in consumers' daily lives. Numerous mobile applications have been released in app stores yielding trillions of cumulative downloads. However, a big majority of the applications are disregarded from consumers. Even after the applications are purchased, they do not survive long in consumers' mobile devices and are soon abandoned. Nevertheless, it is imperative for both app developers and app-store operators to understand consumer behaviors and to develop marketing strategies aiming to make sustainable business by first increasing sales of mobile applications and by also designing surviving strategy for applications. Therefore, this research analyzes consumers' mobile application usage behavior in a frame of substitution/supplementary of application categories and several explanatory variables. Considering that consumers of mobile devices use multiple apps simultaneously, this research adopts multivariate probit models to explain mobile application usage behavior and to derive correlation between categories of applications for observing substitution/supplementary of application use. The research adopts several explanatory variables including sociodemographic data, user experiences of purchased applications that reflect future purchasing behavior of paid applications as well as consumer attitudes toward marketing efforts, variables representing consumer attitudes toward rating of the app and those representing consumer attitudes toward app-store promotion efforts (i.e., top developer badge and editor's choice badge). Results of this study can be explained in hedonic and utilitarian framework. Consumers who use hedonic applications, such as those of game and entertainment-related, are of young age with low education level. However, consumers who are old and have received higher education level prefer utilitarian application category such as life, information etc. There are disputable arguments over whether the users of SNS are hedonic or utilitarian. In our results, consumers who are younger and those with higher education level prefer using SNS category applications, which is in a middle of utilitarian and hedonic results. Also, applications that are directly related to tangible assets, such as banking, stock and mobile shopping, are only negatively related to experience of purchasing of paid app, meaning that consumers who put weights on tangible assets do not prefer buying paid application. Regarding categories, most correlations among categories are significantly positive. This is because someone who spend more time on mobile devices tends to use more applications. Game and entertainment category shows significant and positive correlation; however, there exists significantly negative correlation between game and information, as well as game and e-commerce categories of applications. Meanwhile, categories of game and SNS as well as game and finance have shown no significant correlations. This result clearly shows that mobile application usage behavior is quite clearly distinguishable - that the purpose of using mobile devices are polarized into utilitarian and hedonic purpose. This research proves several arguments that can only be explained by second-hand real data, not by survey data, and offers behavioral explanations of mobile application usage in consumers' perspectives. This research also shows substitution/supplementary patterns of consumer application usage, which then explain consumers' mobile application usage behaviors. However, this research has limitations in some points. Classification of categories itself is disputable, for classification is diverged among several studies. Therefore, there is a possibility of change in results depending on the classification. Lastly, although the data are collected in an individual application level, we reduce its observation into an individual level. Further research will be done to resolve these limitations.