• 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.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2023.11a
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• pp.120-121
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• 2023

Recently, there has been a continuous imbalance between the demand and supply in the shipping industry. Consequently, shipping companies are implementing blank sailing to adjust the supply of vessels and achieve a balance between demand and supply. Blank sailing can create negative ripple effects by delaying cargo transportation, so this study uses Poisson regression analysis,

• The Korean Journal of Applied Statistics
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• v.24 no.3
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• pp.485-494
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• 2011

When the observations can take only the non-negative integer values, it is called the count data such as the numbers of car accidents, earthquakes, or insurance coverage. In general, the Poisson regression model has been used to model these count data; however, this model has a weakness in that it is restricted by the equality of the mean and the variance. On the other hand, the count data often tend to be too dispersed to allow the use of the Poisson model in practice because the variance of data is significantly larger than its mean due to heterogeneity within groups. When overdispersion is not taken into account, it is expected that the resulting parameter estimates or standard errors will be inefficient. Since coverage is the main issue for insurance, some accidents may not be covered by insurance, and the number covered by insurance may be zero. This paper considers the zero-inflated model for the count data including many zeros. The performance of this model has been investigated by using of real data with overdispersion and many zeros. The results indicate that the Zero-Inflated Negative Binomial Regression Model performs the best for model evaluation.

• 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.

• Journal of Korean Society of Transportation
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• v.30 no.4
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• pp.95-106
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• 2012

Driver's capability of identifying the change in freeway alignments and environments is one of important factors associated with traffic safety on freeways. In particular, driver's visibility and recognition capability are highly dependent on the altitude of the sun by sunset, sunrise, and nighttime. The purpose of this study is to identify the characteristics of geometric conditions affecting crash occurrences at sunset, sunrise, and nighttime. Poisson and negative binomial regressions were adopted to predict freeway crash frequency in this study. Freeway crash data during 2007~2010 were used for developing the crash frequency models. A set of variables representing the characteristics of geometric conditions were identified as significant ones affecting crash occurrences. The results of this study would be useful in deriving effective countermeasures for preventing traffic crashes that mainly occur at sunset, sunrise, and nighttime on freeways.

• Journal of Korean Public Health Nursing
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• v.29 no.3
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• pp.488-502
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• 2015

Purpose: This study was conducted to determine the neighborhood environmental factors associated with physical activity among adults living in rural communities. Methods: A cross-sectional descriptive survey was conducted with a convenience sample of 201 adults living in three Ri in Y-city, Gyeonggi-do. Data were collected from face-to-face interview by trained interviewers and were analyzed using a zero-inflated negative binominal regression model. Results: Participants reported engaged in moderate or vigorous physical activity was 76.1%; 10.5% of participants reported that they met moderate physical activity recommendations and 14.5% of participants reported that they met vigorous physical activity recommendations. Zero-inflated negative binominal regression analysis showed association of increasing days of physical activity with social cohesion (${\beta}=.130$, p=.005), social network (${\beta}=-.096$, p=.003), and safety for crime (${\beta}=-.151$, p=.036), and no days of physical activity was associated with no attainment of education and marginally associated with increasing BMI. Conclusion: Neighborhood environmental factors including social cohesion, social network, and crime for safety were significantly associated with physical activity of rural adults. Community health nurses should expand an approach for individual behavior change to incorporate rural adults' specific neighborhood environmental factors into physical activity interventions.

• Journal of Korea Planning Association
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• v.53 no.7
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• pp.49-66
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• 2018

The purpose of this study is to analyze neighborhood environmental factors affecting bicycle accidents and accidental severity in Seoul, Korea. The use of bicycles has increased rapidly as daily transportation means in recent years. As a result, bicycle accidents are also steadily increasing. Using Traffic Accident Analysis System (TAAS) data from 2015 to 2017, this study uses negative binomial regression analysis to identify neighborhood environmental factors affecting bicycle accidents and accidential severity. The main results are as follows. First, bicycle accidents are more likely to occur in commercial and mixed land use areas where pedestrians, bicycle and vehicles are moving together. Second, bicycle accidents are positively associated with road structures such as four-way intersection. In contrast, three-way intersection is negatively associated with serious bicycle accidents. The density of speed hump or street tree is negatively associated with bicycle accidents and accidential severity. This finding indicates the effect of speed limit or street trees on bicycle safety. Fourth, bicycle infrastructures are also important factors affecting bicycle accidents and accidential severity. Bicycle-exclusive roads or bicycle-pedestrian mixed roads are positively associated with bicycle accidents and accidential severity. Finally, this study suggests policy implications to improve bicycle safety.

• Journal of the Korean Data Analysis Society
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• v.20 no.6
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• pp.2829-2840
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• 2018

The random variable with an arbitrary value or more is called semi-continuous variable or zero-inflated one in case that its boundary value is more frequently observed than expected. This means the boundary value is likely to be practically observed more than it should be theoretically under certain probability distribution. When the distribution considered is continuous, the variable is defined as semi-continuous and when one of discrete distribution is assumed for the variable, we regard it as zero-inflated. In this study, we introduce the two-part model, which consists of one part for modelling the binary response and the other part for modelling the variable greater than the boundary value. Especially, the zero-inflated regression models are explained by using Poisson distribution and negative binomial distribution. In real data analysis, we employ the zero-inflated regression models to estimate the number of days under extreme heat-wave circumstances during the last 10 years in South Korea. Based on the estimation results, we create prediction maps for the estimated number of days under heat-wave advisory and heat-wave warning by using the universal kriging, which is one of the spatial prediction methods.

• 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.