• Journal of Korean Society for Quality Management
• /
• v.26 no.4
• /
• pp.111-123
• /
• 1998

We consider the problem of modeling count data where the observation period is determined by the life time of the system under study. We assume random effects or a frailty model to allow for a possible association between the death times and the counts. We assume that, given a random effect or a frailty, the death times follow a Weibull distribution with a hazard rate. For the counts, given a frailty, a Poisson process is assumed with the intensity depending on time. A gamma distribution is assumed for the frailty model. Maximum likelihood estimators of the model parameters are obtained. A model for the time to death and the number of failures system received is constructed and consequences of the model are examined.

• The Journal of Fisheries Business Administration
• /
• v.47 no.2
• /
• pp.33-41
• /
• 2016

The purpose of this study is to estimate the economic value of boat fishing experience marine tourism activity in Jeju Island's Chagwido. The economic value is estimated as consumer surplus using count data models including the truncated Poisson model and the truncated negative binominal distribution model. This study collects the effective 504 questionnaires from boat fishing experience tourists in Jeju Island's Chagwido. The truncated negative binominal distribution model was statistically more suitable and valid than other models. The truncated negative binominal distribution model was applied to estimate consumer surplus as economic value from boat fishing experience tourism activity in Jeju Island's Chagwido. A consumer surplus value per trip was estimated as about 209,900 won. The annual economic value from boat fishing experience tourism activity was estimated as 273,700 won in Jeju Island's Chagwido. Consequently, boat fishing experience marine tourism activity has a very large economic value in Jeju Island.

• Asia-Pacific Journal of Business
• /
• v.15 no.2
• /
• pp.23-40
• /
• 2024

Purpose - The purpose of this study is to examine the relation between accruals quality and managers' choice on the type of voluntary disclosure. Design/methodology/approach - Samples of this study are 8,248 firm-year observations listed in Korea Stock Exchange. Poisson regression analysis was hired in order to analyze the association between disclosure frequency and accruals quality because the dependent variables are count data. Findings - First, this study finds that managers' use of non-earnings-related type of voluntary disclosure is negatively related to accruals quality while their use of earnings-related disclosure is positively related to accruals quality. Second, discretionary accruals quality as well as innate accruals quality is significantly associated with disclosure frequency. Research implications or Originality - This study extends the line of research by incorporating the content of voluntary disclosure, earnings- and non-earnings-related information. The results of this study suggest that accruals quality may play a role in the choice of disclosure manner when investigating managers' voluntary disclosure.

• Journal of the Korean Data and Information Science Society
• /
• v.9 no.2
• /
• pp.311-322
• /
• 1998

In this paper the problem of modeling count data where the observation period is determined by the survival time of the individual under study is considered. We assume marginal frailty model in the counts. We assume that the death times follow a Weibull distribution with a rate that depends on some covariates. For the counts, given a frailty, a Poisson process is assumed with the intensity depending on time and the covariates. A gamma model is assumed for the frailty. Maximum likelihood estimators of the model parameters are obtained. The model is applied to data set of patients with breast cancer who received a bone marrow transplant. A model for the time to death and the number of supportive transfusions a patient received is constructed and consequences of the model are examined.

• The Journal of Economics, Marketing and Management
• /
• v.9 no.2
• /
• pp.33-43
• /
• 2021

Purpose: This study aims to verify sellers' economic incentives for voluntarily disclosing negative information in online markets and provide practical guidelines to online sellers in terms of whether, when, and how sharing low quality to buyers increase sales. Research design, data and methodology: Our model examines the number of bidders in Internet auctions to measure potential demand and uses count data analysis following previous studies that have also analyzed the number of bidders in auctions. After checking over-dispersion and zero-inflation in our data, we have run a Poisson regression to analyze the effect of sharing negative information on sales. Results: This study presents a counterintuitive result that low-quality sellers can increase their demand by fully disclosing negative information in an online market, if appropriate risk-reducing methods are employed. Our finding thus shows that there exists economic incentive for online sellers to voluntarily disclose negative information about their products, and that the context of transactions may affect this incentive structure as the incentive varies across product categories. Conclusions: As the positive impact of disclosing negative information has rarely been studied so far, this paper contributes to the literature by providing a unique empirical analysis on the impact of sellers' honesty on sales. By verifying economic incentives of disclosing low quality with actual online sales data, this study suggests practical implications on information disclosure strategy to many online sellers dealing with negative information.

• Communications for Statistical Applications and Methods
• /
• v.17 no.3
• /
• pp.413-421
• /
• 2010

In this study, we considered bivariate conditional auto-regressive model taking into account spatial association as well as correlation between the two dependent variables, which are the counts of murder and burglary. We conducted likelihood ratio test for checking over-dispersion issues prior to applying spatial poisson models. For the real application, we used the annual counts of violent crimes at 25 districts of Seoul in 2007. The statistical results are visually illustrated by geographical information system.

• Management & Information Systems Review
• /
• v.33 no.2
• /
• pp.301-315
• /
• 2014

The purpose of this study is to estimate the economic value of the Kumjung Mountain, using a Individual Travel Cost Model(ITCM). This paper compares Poisson and negative binomial count data models to measure the tourism demands. Interviewers were instructed to interview only individuals. So the sample was taken in 700. A dependent variable that is defined on the non-negative integers and subject to sampling truncation is the result of a truncated count data process. The results suggest that the truncated negative binomial model is improved overdispersion problem and more preferred than the other models in the study. This study emphasizes in particular 'travel cost' that is not only monetary cost but also including opportunity cost of 'travel time'. According to the truncated negative binomial model, estimates the Consumer Surplus(CS) values per trip of about 60,669 Korean won and the total economic value was estimated to be 252,383 Korean won.

• Journal of the Korean Society of Safety
• /
• v.32 no.6
• /
• pp.131-136
• /
• 2017

This study deals with the small-size roundabout accidents. The purpose of this study is to analyze the characteristics of small-size roundabout accidents from developing various types of accident models, and to discuss the improvement countermeasures by vehicle type. The geometric characteristics of 36 roundabouts are surveyed, and the traffic accident data from 2008 to 2014 are collected and classified as those of car, truck and motor cycle. In this study, dependent variable is the number of accident and independent variables are such 15 variables as geometry and traffic volume. The main results are as follows. First, the null hypotheses that the size of roundabout and type of vehicle are not related to traffic accident are rejected. Second, 8 count data models which are all statistically significant are developed. Third, the number of circulatory roadway lane and sidewalk are selected as common variables of roundabout size. Finally, the number of entry and circulatory roadway lane are selected as common variables of vehicle type.

• Journal of Korean Society of Transportation
• /
• v.29 no.5
• /
• pp.7-17
• /
• 2011

Traffic problems caused by drunk drivers have been steadily raised from the past. Even though the previous researches have focused on the development of countermeasures for preventing drunk driving, the number of drivers violating the DUI (Driving-Under-Influence) regulation is still increasing. Many studies seek countermeasures for preventing drunk driving by comparing the differences between general and drunk drivers. However, few researches have investigated focusing only on the characteristics of drunk drivers. It is well known that characteristics of general drivers are different from those of drunk drivers, and also habitual drunk drivers have different characteristics from non-habitual drunk drivers. Motivated by this fact, only the drivers who have violated DUI regulation are considered in the analysis. This study primarily aims to provide alternative solutions for reducing habitual drunk drivers who are highly inclined to do drunk driving repeatedly. For the analysis, various types of variables potentially effecting drunk driving behavior were investigated, and then truncated count data models were developed to analyze the effects of the variables selected on drunk driving. The results showed that 1) a truncated negative binomial model is better fitted to the data; and 2) five variables including experiential learning, the lack of self-control, self-reflection, the fear of crackdown, and the level of dependence on vehicles were found to be statistically significant.

• The Korean Journal of Applied Statistics
• /
• v.34 no.3
• /
• pp.375-388
• /
• 2021

This paper aims to help prevent the spread of COVID-19 by analyzing confirmed cases of COVID-19 in Daejeon. A high volume of visitors, downtown areas, and psychological fatigue with prolonged social distancing were considered as risk factors associated with the spread of COVID-19. We considered the weekly confirmed cases in each administrative district as a response variable. Explanatory variables were the number of passengers getting off at a bus station in each administrative district and the elapsed time since the Korean government had imposed distancing in daily life. We employed a mixed-effects zero-inflated Poisson regression model because the number of cases was repeatedly measured with excess zero-count data. We conducted k-means clustering to identify three groups of administrative districts having different characteristics in terms of the number of bars, the population size, and the distance to the closest college. Considering that the number of confirmed cases might vary depending on districts' characteristics, the clustering information was incorporated as a categorical explanatory variable. We found that Covid-19 was more prevalent as population size increased and a district is downtown. As the number of passengers getting off at a downtown district increased, the confirmed cases significantly increased.