• Journal of the Korean Data and Information Science Society
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• v.26 no.2
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• pp.387-397
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• 2015

In this paper, the determinants of the number of job changes in the SMEs (small and medium enterprises) youth-intern project is analysed, utilizing SMEs youth-intern DB and employment insurance DB. Since the number of job changes are count data which take integer values other than negative values, general linear regression analysis becomes inappropriate. Therefore, four models such as Poisson regression model, zero inflated Poisson regression model, negative binomial regression model and zero inflated negative binomial regression model are tried to fit count data. A zero inflated negative binomial regression model is selected to be the best model. Major results are the followings. First, the number of job changes is shown to be significantly smaller in the treatment group than in the control group. Second, the number of job changes turns out to be significantly smaller in the young-age group than in the old-age group. Third, it is also shown that the number of job changes of man is significantly greater than that of woman. Lastly, the number of job changes in the bigger firm is shown to be significantly less than that of the smaller firm.

• Journal of Navigation and Port Research
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• v.48 no.1
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• pp.62-77
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• 2024

In the maritime shipping industry, imbalance between supply and demand has persistently increased, leading to the utilization of blank sailings by major shipping companies worldwide as a key means of flexibly adjusting vessel capacity in response to shipping market conditions. Traditionally, blank sailings have been frequently implemented around the Chinese New Year period. However, due to unique circumstances such as the global pandemic starting in 2020 and trade tensions between the United States and China, shipping companies have recently conducted larger-scale blank sailings compared to the past. As blank sailings directly impact freight transport delays, they can have negative repercussions from perspectives of both businesses and consumers. Therefore, this study employed Poisson regression models and negative binomial regression models to analyze the influence of maritime freight rate determinants on shipping companies' decisions regarding blank sailings, aiming to proactively address potential consequences. Results of the analysis indicated that, in Poisson regression analysis for 2M, significant variables included global container shipping volume, container vessel capacity, container ship scrapping volume, container ship newbuilding index, and OECD inflation. In negative binomial regression analysis, ocean alliance showed significance with global container shipping volume and container ship order volume, the alliance with container ship capacity and interest rates, non-alliance with international oil prices, global supply chain pressure index, container ship capacity, OECD inflation, and total alliance with container ship capacity and interest rates.

• The Korean Journal of Applied Statistics
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• v.9 no.1
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• pp.111-124
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• 1996

In this paper, we consider the first-order integer valued autoregressive(INAR(1)) model where correlation structure is similar to that of the continuous valued AR(1) process. Several methods for estimating the parameters of the INAR(1) process with negative binomial marginal are discussed. We derive asymptotic distributions of these estimators. The results of a simulation study for these estimators methods show that the estimator which we present in this paper is better than the estimator which Klimko and Nelson(1978) presented. As an application we considered the estimator of M/M/1 queue length.

• International Journal of Highway Engineering
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• v.11 no.2
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• pp.151-158
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• 2009

This study deals with the rear-end collisions in the rural aiea. The objectives of this study are 1) to analyze the characteristics of rear-end accidents of signalized intersections, and 2) to develop the accident models for Cheongju-Cheongwon. In pursing the above, this study gives the particular attentions to comparing the characters of urban and rural area. In this study, the dependent variables are the number of accidents and value of EPDO(equivalent property damage only), and independent variables are the traffic volumes and geometric elements. The main results analyzed are the followings. First, the statistical analyses show that the Poisson accident model using the number of accident as a dependant variable are statistically significant and the negative binomial accident model using the value of EPDO are statistically significant. Second, the independent variables of Poisson model are analyzed to be the ratio of high-occupancy vehicles, total traffic volume and the sum of exit/entry, and those of negative binomial regression are the main road width, total traffic volume and the ratio of high-occupancy vehicles. Finally, the specific independent variables to the rural area are the main road width, the ratio of high occupancy vehicle, and the sum exit/entry.

• Journal of Korea Technology Innovation Society
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• v.17 no.3
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• pp.449-466
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• 2014

There have been various researches on the relationship between a company's R&D investment and the outcome from innovation. However, these studies failed to effectively analyze the decision-making process followed by companies in relation to knowledge production. Especially, in analyzing the patent of companies, the Poisson model has been commonly used, but its limitations have been pointed out. In recent years, many studies have adopted negative binomial models, but they still pose limitations in analyzing the selection process. This paper proposed a hurdle negative binomial model to effectively reflect the company's decision embedded within patent information and conduct an empirical analysis on a survey of businesses' activities. In particular, the study analyzed the selection process of companies in determining the number of patents. As a result of estimation, the presence of over-dispersion was identified. In addition, the Wald-test confirmed that setting up of hurdles was valid, and there was a difference between the results of hurdle models and those of general negative binomial settings.

• Journal of Korean Society of Transportation
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• v.26 no.4
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• pp.29-40
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• 2008

Although a good understanding of the relationship between highway traffic accidents and highway geometric features is fundamental in highway design and safety, the relationship is not well understood quantitatively. The overall goal of this paper is to formulate a reliable statistical model fitting to historical highway accident data. The model can be used to estimate the effect of road design elements on safety for the practical purposes of highway design applications. En route to achieving this goal, a number of specific research objectives were accomplished: investigate the major design elements affecting highway safety; review the existing modeling approaches in order to assess the relationship between safety and highway design features; and formulate a statistical model fitting to the accident data in order to estimate the interchange ramp junction accident frequency of rural highways.

• The Korean Journal of Applied Statistics
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• v.23 no.3
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• pp.585-594
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• 2010

This study, investigates the effects of dispersion parameters between two response variables in zero-truncated bivariate generalized Poisson distributions. A Monte Carlo study shows that the zero-truncated bivariate Poisson and negative binomial models fit poorly wherein the zero-truncated bivariate count data has heterogeneous dispersion parameters on dependent variables. In addition, we derive the score test for testing the equality of the dispersion parameters and compare its efficiency with the likelihood ratio test.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.33 no.6
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• pp.2437-2445
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• 2013

The objective of this study is finding the relationship between interstate highway accident frequencies and geometrics using Random Parameter Negative Binomial model. Even though it is impossible to take account of the same design criteria to the all segments or corridors on the road in reality, previous research estimated the fixed value of coefficients without considering each segment's characteristic. The drawback of the traditional negative binomial is not to explain the integrated variations in terms of time and the distinct characters specific segment has. This results in under-estimation of the standard error which inflates the t-value and finally, affects the modeling estimation. Therefore, this study tries to find the relationship of accident frequencies with the heterogeneous geometrics using 9-years and 7-interstate highway data in Washington State area. 16-types of geometrics are used to derive the model which is compared with the traditional negative binomial Model to understand which Model is more suitable. In addition, by calculating marginal effect and elasticity, heterogeneous variables' effect to the accidents are estimated. Hopefully, this study will help to estiblish the future policy of geometrics.

• The Korean Journal of Applied Statistics
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• v.6 no.1
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• pp.41-52
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• 1993

In this paper we study numerical behavior of the adjustments for the variances of the pearson and deviance type dispersion statistics in two overdispersed mixture models; negative binomial and beta-binomial distribution. They are important families of an extended quasi-likelihood model which is very useful for the joint modelling of mean and dispersion. Comparisons are done for two types of dispersion statistics for various mean and dispersion parameters by simulation studies.

• Journal of the Korean Regional Science Association
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• v.31 no.4
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• pp.107-128
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• 2015

Technology innovation is a competitive weapon of sustainable economic growth at the urban and regional level and the growth of firms. In this study, we empirically investigate the effects of collaborative R&D activity on product innovative outputs and process innovative outputs in manufacturing firms in Korea. We analyze the links between collaborative R&D activity and two types of innovative outputs using an alternative negative binomial regression model. The major finding is that collaborative R&D activity has significant positive effects on both product and process innovation. The results also identify a positive link between all types of innovative outputs and other R&D activities including internal R&D activity, patent activity, external technology and capital goods acquisitions. To induce corporate growth that enhances the productivity of individual firms and produces prolonged economic growth, policy makers should place greater emphasis on creating effective arrangements to promote establishing collaborative R&D strategies for manufacturing firms.