• Journal of the Korea Convergence Society
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• v.6 no.6
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• pp.221-229
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• 2015

This study aims to identify and analyze the main factors that determine the properties and buying behavior in the premium bottled select and analyze the degree of impact on the relevant variables are premium water demand. When applied to the truncated negative binomial model to derive the study results: The results of estimating the variables that affect the demand for premium mineral water are as follows. Premium bottled water demand of this group my purchases with a choice between buying behavior variables are significantly higher than the relative population. To also do a good ingredient water, it appeared to be on a statistically significant positive effect on the demand for the more groups you purchase a premium bottled water for the purpose of receiving special feeling, just buy purpose is called to drinking water does not significantly affect to be analyzed. Among demographic characteristics it showed that demand for premium bottled water purchases are significantly higher in women than in men, professional / clerical job, such as the military, college graduates were more consumer research as significant in comparison to the relative population. Taste and package design factors of premium bottled mineral water among the select attribute factors are having a significant positive impact on the purchasing demand, local conditions and cost factors have been estimated to be insignificant.

• The Journal of the Korea Contents Association
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• v.19 no.12
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• pp.84-92
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• 2019

The deterioration of the urban heat environment due to climate change and the occurrence of heat-related diseases have emerged as one of the major social problems. This has led to more research on climate change, including heat waves, but it is mainly focused on climate factors. However, the urban heat island phenomenon accelerates the summer heat wave, and the increasing trend of heat-related patients in urban areas suggests the impact of the city's environment. Thus, this study analyzed the effects of physical and social characteristics of urban areas on heat-related patients in Seoul and Gyeonggi-do. The analysis showed that the ratio of the total area of residential, commercial and industrial facilities, the main source of heat energy locality, among the land use statuses, was not statistically significant, but the road area and the green area were found to have a positive and negative The population density and the percentage of people aged 65 or older, the percentage of people living alone and the proportion of people receiving basic living were all shown to be significant, with only the ratio of elderly living alone and the ratio of population density having negative effects. The results of the study can be used to develop urban policy alternatives related to local warming patients.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.14 no.1
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• pp.85-93
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• 2015

Previous studies have estimated crash prediction models with the fixed effect model which assumes the fixed value of coefficients without considering characteristics of each intersections. However the fixed effect model would estimate under estimation of the standard error resulted in over estimation of t-value. In order to overcome these shortcomings, the random effect model can be used with considering heterogeneity of AADT, geometric information and unobserved factors. In this study, data collections from 89 intersections in Daejeon and estimates of crash prediction models were conducted using the random and fixed effect negative binomial regression model for comparison and analysis of two models. As a result of model estimates, AADT, speed limits, number of lanes, exclusive right turn pockets and front traffic signal were found to be significant. For comparing statistical significance of two models, the random effect model could be better statistical significance with -1537.802 of log-likelihood at convergence comparing with -1691.327 for the fixed effect model. Also likelihood ration value was computed as 0.279 for the random effect model and 0.207 for the fixed effect model. This mean that the random effect model can be improved for statistical significance of models comparing with the fixed effect model.

• Journal of the Korean Regional Science Association
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• v.38 no.1
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• pp.3-20
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• 2022

The purpose of this study is to exploratory analyze the transition pattern of establishments and workers in new growth industries in the metropolitan area from 2010 to 2019 and to identify regional factors affecting the inflow and outflow of new growth industry start-ups. As for the analysis, the original data of the Census on Establishments were used, and spatial data at the sigungu level were constructed based on the inflow and outflow data of the number of new growth industry businesses and workers. For the analysis, the degree centrality of connection to outflow inflow by region was calculated, and an empirical analysis was conducted on regional-level factors affecting the inflow and outflow of new growth industries by applying a negative binomial regression model. According to the results, the new growth industry manufacturing sector was actively relocated in southern Gyeonggi Province, and the new growth industry service sector in Gangnam and Guro-Geumcheon-gu, and the impact of regional-level factors on the inflow and outflow of new growth industry start-ups varies depending on the industry. This study presented implications for regional industrial policies to improve the competitiveness of the local economy by attracting new industries by identifying spatial transition patterns for new growth industries and conducting empirical analysis to identify influencing factors.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.22 no.3
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• pp.1-19
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• 2023

Bikes have recently emerged as an alternative to carbon neutrality. To understand the demand for public bikes, we endeavored to estimate travel frequency of public bike by considering the intermediate stops. Using the GPS trajectory data of 'Ttareungyi', a public bike service in Seoul, we identified a stay point and estimated travel frequency reflecting population, land use, and physical characteristics. Application of map matching and a stay point detection algorithm revealed that stay point appeared in about 12.1% of the total trips. Compared to a trip without stay point, the trip with stay point has a longer average travel distance and travel time and a higher occurrence rate during off-peak hours. According to visualization analysis, the stay points are mainly found in parks, leisure facilities, and business facilities. To consider the stay point, the unit of analysis was set as a hexagonal grid rather than the existing rental station base. Travel frequency considering the stay point were analyzed using the Zero-Inflated Negative Binomial (ZINB) model. Results of our analysis revealed that the travel frequency were higher in bike infrastructure where the safety of bike users was secured, such as 'Bikepath' and 'Bike and pedestrian path'. Also, public bikes play a role as first & last mile means of access to public transportation. The measure of travel frequency was also observed to increase in life and employment centers. Considering the results of this analysis, securing safety facilities and space for users should be given priority when planning any additional expansion of bike infrastructure. Moreover, there is a necessity to establish a plan to supply bike infrastructure facilities linked to public transportation, especially the subway.

• Information Systems Review
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• v.22 no.2
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• pp.43-52
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• 2020

The mobile game industry has become the one of the fastest growing industries with its astonishing market size. Despite its industrial importance, a few studies empirically considered actual purchasing behavior in mobile games rather than the intention to purchase. Therefore, this paper investigates the key drivers of in-app purchase by analyzing the game-log dataset provided from a mobile game company in Korea. Specifically, the effects of goal-directed, habitual and social-interacted playing behavior are analyzed on in-app purchase. Furthermore, the recursive relationship with playing and purchasing behaviorsis also considered. The result shows that all suggested factors have positive impacts on in-app purchase in the current period. In addition, the effect of previous habitual playing has a positive impact, but the effect of social-interacted playing and in-app purchase in the previous period have negative impacts on in-app purchase of the current period. These findings can improve our understanding of the impact of game playing on in-app purchase in mobile games, and provide meaningful insights for researchers and practitioners.

• Journal of the Korean Institute of Landscape Architecture
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• v.52 no.1
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• pp.87-100
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• 2024

This study aimed to investigate the impact of the quality of the street environment in residential areas on the mental health of urban residents, considering the frequency of street use. Using a zero-inflated negative binomial regression model, the study analyzed the influence of walking frequency and the street environment on depressive symptoms of urban residents. The research focused on Seoul, South Korea, in 2017, with depressive symptoms as the dependent variable and street environment variables, walking variables, and individual characteristics as independent variables. Additionally, the study explores the interaction effect of street greenery and walking frequency to analyze the synergistic impacts of walking in green spaces on mental health. The findings indicate that a higher ratio of street green areas is associated with fewer depressive symptoms. Increased walking frequency is linked to a reduction in depressive symptoms or a weaker manifestation of such symptoms. The interaction effect confirms that more frequent walking in green spaces is associated with weaker depressive symptoms. Lower ratios of visual complexity are correlated with reduced depressive symptoms. This study contributes to addressing urban residents' mental health issues at the community level by emphasizing the importance of the street green environment in residential areas.

• Journal of the Korean Regional Science Association
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• v.31 no.3
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• pp.39-54
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• 2015

To assess an economic value of Cheonggyecheon river restoration project, an in-depth exit survey data was collected to apply travel cost method in this study. Poisson model, Negative Binomial, Zero-truncated Poisson, and Zero-truncated Negative Binomial model were executed due to the nature of count data. Empirical results showed that regressors were statistically significant and corresponded to general consumer theory. Since our survey data showed over-dispersion, Zero-truncated Negative Binomial was selected as an optimal one to analyze travel demand of Cheonggyecheon by model goodness of fit test among those aforementioned empirical models. Estimating an economic value of Cheonggyecheon river restoration project, which is known as an ecological river restoration project, we used annual visit of individual traveler and an optimal model. Suffice to say that the annual economic value of Cheonggyecheon river restoration project was estimated as 193.4 billion won in 2013.

• Journal of Intelligence and Information Systems
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• v.22 no.1
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• pp.43-61
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• 2016

Customer reviews help potential customers make purchasing decisions. However, the prevalence of reviews on websites push the customer to sift through them and change the focus from a mere search to identifying which of the available reviews are valuable and useful for the purchasing decision at hand. To identify useful reviews, websites have developed different mechanisms to give customers options when evaluating existing reviews. Websites allow users to rate the usefulness of a customer review as helpful or not. Amazon.com uses a ratio-type helpfulness, while Yelp.com uses a count-type usefulness index. This usefulness index provides helpful reviews to future potential purchasers. This study investigated the effects of sentiment and readability on useful votes for customer reviews. Similar studies on the relationship between sentiment and readability have focused on the ratio-type usefulness index utilized by websites such as Amazon.com. In this study, Yelp.com's count-type usefulness index for restaurant reviews was used to investigate the relationship between sentiment/readability and usefulness votes. Yelp.com's online customer reviews for stores in the beverage and food categories were used for the analysis. In total, 170,294 reviews containing information on a store's reputation and popularity were used. The control variables were the review length, store reputation, and popularity; the independent variables were the sentiment and readability, while the dependent variable was the number of helpful votes. The review rating is the moderating variable for the review sentiment and readability. The length is the number of characters in a review. The popularity is the number of reviews for a store, and the reputation is the general average rating of all reviews for a store. The readability of a review was calculated with the Coleman-Liau index. The sentiment is a positivity score for the review as calculated by SentiWordNet. The review rating is a preference score selected from 1 to 5 (stars) by the review author. The dependent variable (i.e., usefulness votes) used in this study is a count variable. Therefore, the Poisson regression model, which is commonly used to account for the discrete and nonnegative nature of count data, was applied in the analyses. The increase in helpful votes was assumed to follow a Poisson distribution. Because the Poisson model assumes an equal mean and variance and the data were over-dispersed, a negative binomial distribution model that allows for over-dispersion of the count variable was used for the estimation. Zero-inflated negative binomial regression was used to model count variables with excessive zeros and over-dispersed count outcome variables. With this model, the excess zeros were assumed to be generated through a separate process from the count values and therefore should be modeled as independently as possible. The results showed that positive sentiment had a negative effect on gaining useful votes for positive reviews but no significant effect on negative reviews. Poor readability had a negative effect on gaining useful votes and was not moderated by the review star ratings. These findings yield considerable managerial implications. The results are helpful for online websites when analyzing their review guidelines and identifying useful reviews for their business. Based on this study, positive reviews are not necessarily helpful; therefore, restaurants should consider which type of positive review is helpful for their business. Second, this study is beneficial for businesses and website designers in creating review mechanisms to know which type of reviews to highlight on their websites and which type of reviews can be beneficial to the business. Moreover, this study highlights the review systems employed by websites to allow their customers to post rating reviews.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.13 no.6
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• pp.54-63
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• 2014

Traffic accident frequency and severity level in Korea are known to be very serious. Especially the number of pedestrian fatalities was much worse and 1.6 time higher than the OECD average. According to the National Police Agency, the flash signals are reported to have many safety benefits as well as travel time reduction, which is opposed to the foreign studies. With this background of expanding the flash signal, this research aims to investigate the overall impact of the flash signal operation on safety, investigating and comparing the accident occurrence on the flash signal and the full signal intersections. For doing this accident prediction models for both flash and full signal intersections were estimated using independent variables (geometric features and traffic volume) and 3-year (2011-2013) accident data collected in Seoul. Considering the rare and random nature of accident occurrence and overdispersion (variance > mean) of the data, the negative binomial regression model was applied. As a result, installing wider crosswalk and increasing the number of pedestrian push buttons seemed to increase the safety of the flash signal intersections. In addition, the result showed that the average accident occurrence at the flash signal intersections was higher than at the full signal-operated intersections, 9% higher with everything else the same.