• 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.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.28 no.2
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• pp.146-151
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• 2005

Some distributions have been used for diagnosing the lead time demand distribution in inventory system. In this paper, we describe the negative binomial distribution as a suitable demand distribution for a specific retail inventory management application. We here assume that customer order sizes are described by the Poisson distribution with the random parameter following a gamma distribution. This implies in turn that the negative binomial distribution is obtained by mixing the mean of the Poisson distribution with a gamma distribution. The purpose of this paper is to give an interpretation of the negative binomial demand process by considering the sources of variability in the unknown Poisson parameter. Such variability comes from the unknown demand rate and the unknown lead time interval.

• 도로교통
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• s.94
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• pp.51-64
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• 2003

본 연구는 사고요인과 사고모형의 문헌고찰을 통해 고속도로를 주행하는 버스와 화물차의 사고모형을 개발하고 그 적용방안에 대해 고찰하고자 수행되었다. 고속도로 사고 중 대형차로 인한 차량당 사고율은 승용차보다 월등히 높아 사고의 심각성을 나타내고 있으며, 따라서 이에 대한 별도의 검토가 필요한 시점에 와 있다. 특히 본 연구에 활용된 자료는 비집계된 사상자수로 구간자료를 집합화함으로써 발생하는 문제점을 해소할 수 있다. 모형의 분석기법으로 국내의 경우, 대부분 단순회귀식으로 사고모형을 개발, 적용하여 왔으나 사고수와 사상자수의 특성상 이산적 확률변수로 해석하여 포아송분포와 음이항분포로 적용하는 것이 바람직하다. 따라서 본 연구에서는 버스와 화물차의 사고유형별로 적합한 사고 모형을 개발하여 이로 인한 인사사고 요인에 대한 영향을 분석하고 그 적용방안을 제시하였다. 이러한 연구는 도로설계, 운영, 교통법규, 교통행정 등의 분야에서 거시적인 정책적 방향성을 제시하리라 판단된다. 특히 본 연구는 고속도로 운영주체인 한국도로공사의 고속도로사고조서를 바탕으로 사고유형별 사고모형을 개발, 적용한 것으로 고속도로의 안정성 향상을 위한 제반 정책 수립에 기초자료로 활용될 것으로 기대된다.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.28 no.4
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• pp.79-84
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• 2005

Some distributions have been used for diagnosing the lead time demand distribution in inventory system. In this paper, we describe the negative binomial distribution as a suitable demand distribution for a specific retail inventory management application. We here assume that customer order sizes are described by the Poisson distribution with the random parameter following a gamma distribution. This implies in turn that the negative binomial distribution is obtained by mixing the mean of the Poisson distribution with a gamma distribution. The purpose of this paper is to give an interpretation of the negative binomial demand process by considering the sources of variability in the unknown Poisson parameter. Such variability comes from the unknown demand rate and the unknown lead time interval.

• Journal of Korean Society of Transportation
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• v.26 no.3
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• pp.169-178
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• 2008

Level of Service (LOS) is one of ways to evaluate operational conditions. It is very important factor in evaluation especially for the facility of highways. However, some studies proved that ${\upsilon}/c$ ratio and accident rate is appeared like a second function which has a U-form. It means there is a gap between LOS and safety of highway facilities. Therefore, this study presents a method for evaluation of a signalized intersection which is considered both smooth traffic operation (delay) and traffic safety (accident). Firstly, as a result of our research, accident rates and EPDO are decreased when it has a big delay. In that reason, it is necessary to make a new Level of Service included traffic safety. Secondly, this study has developed a negative binominal regression model which is based on the relation between accident patterns and stream. Thirdly, standards of LOS are presented which is originated from calculation between annual delay costs and annual accident cost at each intersection. Lastly, worksheet form is presented as an expression to an estimation step of a signalized intersection with traffic accident prediction model and new LOS.

• 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.

• 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.

• Journal of Korean Society of Transportation
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• v.32 no.2
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• pp.170-178
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• 2014

Until now, several research on the relationship of traffic crash occurrences and geometric had been conducted and revealed that projects of road alignment, geometric improvement and hazardous segment selection reduced the number of accidents and accident severities. However, such variables did not consider the non-homogeneous characteristics of roadway segments due to the difficulty of data collection, which results in under-estimation of the standard error affecting the overall modeling goodness-of-fit. This study highlights the importance of non-homogeneity by looking at the effect of the non-homogeneous geometric variables through the modeling process. The model delivers meaningful results when using some geometric variables without relevant geometrics' variables.

• The Journal of the Korea Contents Association
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• v.17 no.4
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• pp.444-460
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• 2017

The duration of volunteering can be analyzed in terms of commitment and attachment. Previous studies have investigated the duration of volunteering predominantly from the perspective of commitment. Alternatively, this study focuses on the concept of attachment and investigates the characteristics of those who volunteer habitually over their whole life, regardless of the regularity and the intensity of the volunteer work. In so doing, the study attempts to identify factors associated with the attachment to volunteering. Data came from a sample of 8,415 participants, ages over twenty who responded to all the surveys of the Korea Welfare Panel Study, from Wave 1 to 10. Zero-inflated negative bionomial regression model was employed to analyze the total number of volunteering in the past ten years. Findings show that people with high attachment to volunteering were those with religion, less education, and a strong sense of reciprocity. Based on the findings, we provide the practical implications for the improved operation and management of volunteer organizations.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.8 no.2
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• pp.118-127
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• 2009

This study tries to develop model in order to assess personal factors of senior traffic accidents that are widely recognized as one of the social problems. For the current practice. it gathers data (Simulation & Questionnaire Survey) of KOTSA and conducts Poisson and Negative Binomial Regression Analysis to develop traffic accident severity model. The results show that elderly drivers' accidents are mainly affected by attentiveness selection, velocity prediction ability and attentiveness distribution ability in a positive(+) way. Second, non-senior drivers' accidents are also positively(+) influenced by attentiveness selection, velocity prediction, distance perception, attentiveness distribution ability and attentiveness diversion ability. Therefore, influencing factors of senior and non-senior drivers to vehicle accidents are different. This eventually poses a indication that preliminary education for car accident prevention should be implemented based up[n the distinction between senior drivers and non-senior drivers.