• The Journal of Society for e-Business Studies
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• v.27 no.2
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• pp.153-173
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• 2022

This study analyzes yelp's online restaurant reviews written in 2019 and explores the factors influencing the decision of the usefulness for online reviews in the restaurant consumption decision process. Specifically, factors expected to affect review usefulness are classified according to the Elaboration Likelihood model. Also, it is assumed that the price range of the restaurant would have a moderating role. For the analysis, datasets provided by yelp.com in February 2020 are used. Among the datasets, online reviews of businesses located in Nevada in the US and belonging to the Food and Restaurant categories are targeted. As a result of the negative binomial regression analysis, it is confirmed that the central cues including review depth and readability and the peripheral cues including review consistency, reviewer popularity, and reviewer exposure positively affect the review usefulness. It is also confirmed that the influences of antecedents that affect the review restaurant prices moderate the effect of the central and peripheral cues on the review usefulness. It also provides implications for the need for price-differentiated review management strategies by review platforms and restaurant businesses.

• The Journal of Information Systems
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• v.26 no.1
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• pp.1-19
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• 2017

Purpose This study examines the roles of individual- and country-level social capital in entrepreneurial activities from the context of crowdfunding. Design/methodology/approach Two primary sources were used for data collection. From Kickstarter, the largest U.S.-based crowdfunding platform, this study obtained 15,716 crowdfunding projects and individual-level social capital. For country-level social capital, the social capital index from the 2016 Legatum Prosperity Index was utilized. By matching individual- and country-level social capital for each crowdfunding project, this research estimates the role of social capital in entrepreneurial activities at the individual and country level using the Poisson regression and the negative binomial regression. Findings Individual-level social capital measured by the number of Facebook friends, the number of other crowdfunding projects that a crowdfunding project founder invested in, and the word count of the description of a crowdfunding project are positively associated with the number of crowdfunding projects created by founders. The country-level social capital measured by aggregated social capital index is also positively associated with the number of crowdfunding projects created by founders. Both individual- and country-level social capital have a positive impact on entrepreneurial activities in terms of the creation of new crowdfunding projects.

• Journal of Korean Society of Transportation
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• v.25 no.1 s.94
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• pp.23-35
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• 2007

Freeway diverging areas are very vulnerable to traffic accidents due to abrupt vehicle speed changes and geometric changes. Therefore, in designing diverging areas, much attention should be Paid to safety The Present design criteria about freeway diverging areas regulate transition sections for lane changes, deceleration lanes, transition corves for direction changes. and other similar items. However, the design criteria were often violated in implementation because of ambiguities in the criteria. This study aims at clarifying and improving the present design criteria for freeway diverging areas. For this, field survey data and traffic accident data for diverging areas were analyzed.

• Knowledge Management Research
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• v.21 no.3
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• pp.67-87
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• 2020

Maintaining active users who repeatedly share high-quality knowledge is critical for the success of online Q&A sites. This study suggests two paths that lead to active users' continuous knowledge sharing: 1) elaborated decision process, represented by continuance intention, and 2) automated cognitive process, represented by past behavior. The direct and moderating effects of continuance intention and past behavior were verified by analyzing subjective intention data and objective behavior data of 333 active users of Naver Knowledge-iN. Using Cox proportional hazards regression and negative binomial regression, the influences of continuance intention and past behavior on two types of continuous knowledge sharing were examined. The results showed that only past behavior was significantly influential on knowledge sharing continuance and as to the frequency of knowledge sharing, both continuance intention and past behavior's influences were significant. It was also confirmed that past behavior negatively moderates continuance intention's effect on the frequency of knowledge sharing. In order to maintain active users' continuous knowledge sharing, it is important to habituate knowledge sharing through repetitive knowledge sharing behavior. And in order to increase the frequency of knowledge sharing, in addition to the habituation, appropriate benefits that can increase the continuance intention should be provided.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.20 no.9
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• pp.56-65
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• 2019

This study empirically analyzes the effect of weather on pedestrian volume in an urban space. We used data from the 2009 Seoul Flow Population Survey and constructed a model with the pedestrian volume as a dependent variable and the weather and physical environment as independent variables. We constructed 28 models and compared the results to determine the effects of weather on pedestrian volume by season, land use, and time zone. A negative binomial regression model was used because the dependent variable did not have a normal distribution. The results show that weather affects the volume of walking. Rain reduced walking volume in most models, and snow and thunderstorms reduced the volume in a small number of models. The effects of the weather depended on the season and land use, and the effects of environmental factors depended on the season. The results have various policy implications. First, it is necessary to provide semi-outdoor urban spaces that can cope with snow or rain. Second, it is necessary to have different policies to encourage walking for each season.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.21 no.2
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• pp.565-577
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• 2020

This study empirically examined how a firm size affects the determinants of innovative activities using the data of the Korean Innovation Survey (KIS) 2016. With data from 2,003 firms in the manufacturing sector, we performed logistic regression analysis and zero-inflated negative binomial regression analysis. R&D expenditure and patent applications were used as proxies for innovative activity. The independent variables included the firm's characteristics variables such as the firm's age, tech-level industry, RDemp (R&D employee ratio), venture, export, and industrial characteristics variables such as networking, appropriability, and spillovers. The empirical findings are that there are some differences in firms' innovative activity determinants among the firms' size groups. Next, strategic appropriability has negative impacts on small firms' R&D expenditure and medium-firms' patents. Networking is an important determinant of innovative activity for all firms, except for large firms. Furthermore, in deciding R&D activities, small and medium-sized firms were significantly influenced by industrial characteristics as compared to that of large firms. Our findings suggest some R&D promotion policies. Policies fostering firms' technological interaction would allow firms to take advantage of technological spillovers and thus raise the probability of investing in R&D.

• 한국노년학
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• v.38 no.4
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• pp.837-851
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• 2018

This study aimed to investigate the relationship between frailty and health care utilization in a cross-sectional design of a population-based sample of community-dwelling older adults. We used the data of 516 participants who dwell in Daejon, aged between 65 and 84 years old. Using K-frailty index, frailty status were measured and categorized as three groups: robust, prefrail, and frail. Logistic regression analysis was used to examine if frailty affects emergency department(ED) visit or hospitalization. In addition, negative binomial regression was used to examine the association between outpatient visits and frailty. Our results showed that the frail elderly increased the ED visit and the number of outpatient visit significantly after controlling for demographic characteristics, socioeconomic status, the number of chronic diseases, and self-rated health status. Considering that frailty is an important independent factor affecting health care utilization, more attention is required to prevent the frailty in our health care system.

• Health Policy and Management
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• v.34 no.1
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• pp.68-77
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• 2024

Background: Depressive disorders can be categorized into daily depression and clinical depression. The experience of depressive disorder can increase health care utilization due to decreased treatment compliance and somatization. On the other hand, the clinical depression group may also experience social prejudice associated with the illness, which can limit their access to health care utilization. In terms of the significance of health care utilization as a factor in individual and social issues, this study aims to compare the health care utilization of the clinical depression group with that of the non-depressed group and the daily depression group. Methods: The analysis utilized the inverse probability of treatment weighting based on the generalized propensity score. Results: As a result of the analysis, clinical depression and daily depression were higher among women, low-income groups, individuals with low education levels, and so forth. The clinical depression group was also higher among individuals who were not economically active, did not have private health insurance, or had multiple chronic diseases. The number of outpatient department visits in the depression group was significantly higher than in the non-depressed group. In addition, the number of outpatient department visits for the clinical depression group was significantly higher than that for the daily depression group. Outpatient medical expenses were higher in the depression group than in the non-depressed group, and there was no significant difference between the clinical depression group and the daily depression group. Conclusion: Health care utilization was higher in the depression group than the non-depressed group, it was also higher in the clinical depression group than the daily depression group.

• Journal of Korean Society of Transportation
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• v.32 no.4
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• pp.369-379
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• 2014

The Statistical regression model has been used to construct crash prediction models, despite its limitations in assuming data distribution and functional form. In response to the limitations associated with the statistical regression models, a few studies based on non-parametric methods such as neural networks have been proposed to develop crash prediction models. However, these models have a major limitation in that they work as black boxes, and therefore cannot be directly used to identify the relationships between crash frequency and crash factors. A genetic programming model can find a solution to a problem without any specified assumptions and remove the black box effect. Hence, this paper investigates the application of the genetic programming technique to develope the crash prediction model. The data collected from the Gyeongbu expressway during the past three years (2010-2012), were separated into straight and curve sections. The random forest technique was applied to select the important variables that affect crash occurrence. The genetic programming model was developed based on the variables that were selected by the random forest. To test the goodness of fit of the genetic programming model, the RMSE of each model was compared to that of the negative binomial regression model. The test results indicate that the goodness of fit of the genetic programming models is superior to that of the negative binomial models.

• Journal of Digital Convergence
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• v.13 no.1
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• pp.383-396
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• 2015

This study aims to identify factors related to rescreening the private health screening center. Data from private health screening center with seven district centers were analyzed. The number of subjects was 70,250 from 2008 through 2015. Socio-demographic characteristics, morbidity, history, physical measurement, laboratory test, and health behavior factors were analyzed the association with health rescreening using chi-square test and negative binominal regression. 19.2% of subjects were recheck their health status on each year from 2008 to 2012. The socio-demographic characteristics related to reuse private health screening center were male, 30-40 aged, Daegu, Gwangju, Jeonnam and Gyeongnam region residents. And overweight and pre-hypertension were also factors association with number of using the private health screening program. People who control their health risk factors such as alcohol intake, smoking and mental health and execute physical exercise tend to use health screening program regularly. Our finding suggest that customer relationship management can execute and private health screening center enable their strategic plan based on data-evidence.