• Journal of Digital Convergence
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• v.19 no.8
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• pp.151-160
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• 2021

This study aims to analyze the determinants of culture and art consumption of one person households using 「2019 National Art and Culture Activity Survey」. Based on previous research, cultural and economic capital, health perception, and residence were selected as independent variables, and 1,755 single household data on cultural attendance, art education, and demographics were extracted to analyze the relationships. Zero-inflated negative binomial model was employed as cultural attendance variable includes many zeros. It was found that education has a significant impact on cultural attendance possibility and frequency. However, art education in childhood, income, health perception, and residence were found to have selective effects, and unique characteristics of single households influences the findings. This study contributes to developing relevant research by focusing on the single households and provides implications to boost cultural consumption. Finally, directions for future research, such as considering psychographic variables, were suggested.

• Journal of Digital Convergence
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• v.20 no.3
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• pp.283-295
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• 2022

The number of citations in a patent is one of the indicators of the qualitative value of a patent. In this study, negative binomial regression model analysis was performed focusing on 47,354 US patents of 14 global top automotive makers in order to examine the major factors affecting the number of patent citations. As a result of the review, it was found that, elapsed years since filing, the number of patent claims, the number of claim letters, the number of inventors, the number of patent family countries, and the number of patent families, as well as IPC diversity, had a positive and significant effect on the number of citations. The results of this study are expected to provide a basic basis for considering the IPC diversity index together in analyzing and evaluating future patents and establishing strategies for creating excellent patents.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.34 no.2
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• pp.583-595
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• 2014

Currently, Korean transportation policies are aiming for increase of safety and environment-friendly and efficient operation, by avoiding construction and expansion of roads, and upgrading road alignments and facilities. This is revealed by that there have been 22 road expansion projects (30%) and 50 road improvement projects (70%) under the 3rd Five-Year Plan for National Highways ('11~'15), while there were 53 road expansion projects (71%) and 22 road improvement projects (29%) under the 2nd Five-Year Plan for National Highways. For more effective road improvement projects, there is a need of choosing projects after an objective and scientific safety assessment of each road, and assessing safety improvement depending on projects. This study is intended to develop a model for this road safety analysis and assessment. The major objective of this study is creating a road safety analysis and assessment model appropriate for Korean society, based on the HSM (Highway Safety Manual) of the U.S. In order to build up data for model development, the sections thought to have identical geometrical structure factors in 5 lines, Cheonbuk province, were divided as homogeneous sections, and representative values of geometric structures, facilities, traffic volume, climate conditions and land usage were collected from the 1,452 sections divided. In order to build up data for model development, the sections thought to have identical geometrical structure factors in 5 lines, Cheonbuk province, were divided as homogeneous sections, and representative values of geometric structures, facilities, traffic volume, climate conditions and land usage were collected from the 1,452 sections divided. The collected data was processed correlation analysis of each road element was implemented to see which factor had a big effect on traffic accidents. On the basis of these results, then, an accident model was established as a negative binomial regression model.Using the developed model, an Crash Modification Factor (CMF) which determines accident frequency changes depending on safety performance function (SPF) predicting the number of accident occurrence through traffic volume and road section expansion, road geometric structure and traffic properties, was extracted.

• Korean journal of applied entomology
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• v.24 no.1 s.62
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• pp.29-33
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• 1985

Every plant in $990m^2$ onion field was inspected for damages by the onion maggot. Maps were constructed every ten days to show which plants were infested and which were not from April 11 to May 21, 1984. The maps were sectioned into squares one of which contains 80 onion plants and the counts of damaged onions in each square were fitted to poisson and negative binomial distribution and tested by chi-square. We argue that the satisfactory fitness of the expected negative binomial $[P(x^2)>0.05]$ provided a useful description of the spatial distribution patterns of the damaged onions. Edge effect was tested by the differences of damage ratio and variance/mean ratio (${\sigma}^2/m$) between edge and center part. The result showed that the damage ratioes and variances of all the periods, ${\sigma}^2/m$ values after May 1 were greater in edge part than in center part. Again, the maps were sectioned into four blocks and the squares (sample units) were sectioned into quadrants. By application of the variance component technique, it was suggested that $2{\sim}8$ sample units for 5% sampling error and $1{\sim}2$ sample units for 10% error should be sampled randomly to estimate the damage ratio when $2{\sim}3$ quadrants were inspected.

• Journal of Korean Society of Transportation
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• v.30 no.2
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• pp.101-116
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• 2012

Accident prediction models have been utilized to predict accident possibilities in existing or projected freeways and to evaluate programs or policies for improving safety. In this study, a traffic accident prediction model for freeways was developed for the above purposes. When selecting variables for the model, the highest priority was on the ease of both collecting data and applying them into the model. The dependent variable was set as the number of total accidents and the number of accidents including casualties in the unit of IC(or JCT). As a result, two models were developed; the overall accident model and the casualty-related accident model. The error structure adjusted to each model was the negative binomial distribution and the Poisson distribution, respectively. Among the two models, a more appropriate model was selected by statistical estimation. Major nine national freeways were selected and five-year dada of 2003~2007 were utilized. Explanatory variables should take on either a predictable value such as traffic volumes or a fixed value with respect to geometric conditions. As a result of the Maximum Likelihood estimation, significant variables of the overall accident model were found to be the link length between ICs(or JCTs), the daily volumes(AADT), and the ratio of bus volume to the number of curved segments between ICs(or JCTs). For the casualty-related accident model, the link length between ICs(or JCTs), the daily volumes(AADT), and the ratio of bus volumes had a significant impact on the accident. The likelihood ratio test was conducted to verify the spatial and temporal transferability for estimated parameters of each model. It was found that the overall accident model could be transferred only to the road with four or more than six lanes. On the other hand, the casualty-related accident model was transferrable to every road and every time period. In conclusion, the model developed in this study was able to be extended to various applications to establish future plans and evaluate policies.

• Land and Housing Review
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• v.13 no.4
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• pp.55-71
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• 2022

Recently, the domestic department store industry is growing into a complex shopping cultural space, which is advanced and differentiated by changes in consumption patterns. In addition, competition is intensifying across 70 places operated by five large companies. This study investigates the determinants of the visits to department stores using the big data concept's automatic vehicle access system (pos) and proposes how to strengthen the competitiveness of the department store industry. We use a negative binomial regression test to predict the frequency of visits to 67 branches, except for three branches whose annual sales were incomplete due to the new opening in 2021. The results show that the demand for visiting department stores is positively associated with airport, terminal, and train stations, land areas, parking lots, VIP lounge numbers, luxury store ratio, F&B store numbers, non-commercial areas, and hotels. We suggest four strategies to enhance the competitiveness of domestic department stores. First, department store consumers have a high preference for luxury brands. Therefore, department stores need to form their own overseas buyer teams to discover and attract new luxury brands and attract customers who have a high demand for luxury brands. In addition, to attract consumers with high purchasing power and loyalty, it is necessary to provide more differentiated products and services for VIP customers than before. Second, it is desirable to focus on transportation hub areas such as train stations, airports, and terminals in Gyeonggi and Incheon. Third, department stores should attract tenants who can satisfy customers, given that key tenants are an important component of advanced shopping centers for department stores. Finally, the department store, a top-end shopping center, should be developed as a space with differentiated shopping, culture, dining out, and leisure services, such as "The Hyundai", which opened in 2021, to ensure future growth potential.

• Korean Journal of Poultry Science
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• v.50 no.1
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• pp.41-50
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• 2023

Over the last decade, avian influenza (AI) has been considered an emerging disease that would become the next pandemic, particularly in countries like South Korea, with continuous animal outbreaks. In this situation, risk assessment is highly needed to prevent and prepare for human infection with AI. Thus, we developed the risk assessment matrix for a high-risk area of human infection with AI in South Korea based on the notion that risk is the multiplication of hazards with vulnerability. This matrix consisted of highly pathogenic avian influenza (HPAI) in poultry farms and the number of poultry-associated production facilities assumed as hazards of avian influenza and vulnerability, respectively. The average number of HPAI in poultry farms at the 229-municipal level as the hazard axis of the matrix was predicted using a negative binomial regression with nationwide outbreaks data from 2003 to 2018. The two components of the matrix were classified into five groups using the K-means clustering algorithm and multiplied, consequently producing the area-specific risk level of human infection. As a result, Naju-si, Jeongeup-si, and Namwon-si were categorized as high-risk areas for human infection with AI. These findings would contribute to designing the policies for human infection to minimize socio-economic damages.

• Korean Journal of Social Welfare
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• v.67 no.3
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• pp.253-280
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• 2015

This study reconsiders the concept of publicness by raising a question about the problems which the recent marketization of social services in South Korea. The existing perspective on publicness, however, is insufficient to account for the entire Long-term care market because only public organizations have publicness. Accordingly, this study presents 'integrated publicness', particularly 'dimensional publicness' and 'normative publicness'. A disproportional stratified sampling procedure was used to consider ownership. A merged dataset combining surveys from 248 Long-term Care facilities and on-line resources was used and analyzed by multiple regression, negative binomial regression and multiple imputation analysis. The analysis results suggest as follows. First, ownership publicness appeared more effective in the overall. Second, the regulations on the government funding did not show effective, and the regulation on evaluation system showed the effect. Third, professionalization of normative publicness showed a negative effect on service structure and showed a positive effect on service process. Lastly, user of free services whose public accountability was identified to be effective on service structure and outcome. These findings suggest that not only existing ownership but also dimensional publicness and normative publicness showed an effect on service quality. In this respect, this is important as the performance produced by empirical models of integrated publicness, in this situation that the outcome of marketization is insignificant.

• Journal of Digital Convergence
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• v.9 no.6
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• pp.173-186
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• 2011

In this study, the influence of the CEOs' characteristics on the technology innovation performances of IT venture companies was analyzed. The relation between business performance and the characteristics of CEOs has been dealt with in earlier studies, but most paid attention to financial perspective, and few of these focused on the influence of managers on technology innovation. On the other hand, most of the studies related to the role of managers in technology innovation mainly focused on R&D investment and research infrastructure but did not delve on the characteristics of them in an in-depth way. In this study, the characteristics of CEOs and their technology innovation performances were empirically analyzed based on the results of a recently conducted survey on the IT venture companies. In the analytical aspect, a negative binominal model was applied to solve the over-dispersion problem that often appears in the count variable analysis. As a result, it was found that major, work type, and work experience, among managers' characteristics, have significant influences on managers' technology innovation performances, along with the company's innovation capacity, technological competitiveness, market competition, and support from the government.

• Review of Culture and Economy
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• v.19 no.2
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• pp.29-50
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• 2016

This paper is to apply an individual travel cost method(TCM) to estimate demand functions for cultural services enjoyed by visiting 3 branches of the National Museum of Modern and Contemporary Art located in the Seoul Metropolitan area. This paper extends the standard TCM by incorporating opportunity costs of leisure time and two different data generating process - 398 respondents from an on-site survey and 600 respondents from a general household survey. Negative binomial models reflecting the non-negative integer nature of visiting frequency with over-dispersed variance were best fitted for demand functions, in which residents of Seoul metropolitan area surveyed from on the site exhibited higher visitation demand for the national art museum. Price elasticity and income elasticity differed by respondents' residency. Price elasticity of long distance visitors (-0.21) was more inelastic from those of Seoul residents (-0.34 ~ -0.5). Moreover, regional residents outside of Seoul area seemed to consider that services from the national art museum is a normal good with income elasticity of 0.5, whereas the Seoul residents seemed to perceive it to be an inferior good with income elasticity of -0.05.