• Management & Information Systems Review
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• v.37 no.4
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• pp.75-92
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• 2018

The Purpose of this study was to verify that the corporate social contribution activity(eco-friendly product production, donation activity, volunteer activity, fair trade had a positive influence on the corporate credibility, the intention of price premium and the persistent purchase intention. And also this study examined the differences of corporate credibility and price premium according to consumer's gender. To accomplish the purpose of this paper, I performed literature review which relates to corporate social contribution activity, the corporate credibility, the price premium and the persistent purchase intention, and also performed empirical research. I produced questionnaire which investigates the relation between the factors which influence corporate social contribution activity, the corporate credibility, the price premium and the persistent purchase intention. SPSS 21.0 and Lisrel 8.7 were used to analyze the collected data and to identify the influence relationships. The findings of this paper are as follows: First, the corporate social contribution activity(eco-friendly product production, fair trade) did significant effect on the corporate credibility and the price premium. Second, the intention to pay premium price had affected the intention of persistent purchasing but corporate credibility had affected the intention of persistent purchasing through the intention to pay premium price. Third, the difference in preception of men and woman about the corporate social contribution activity. Among the corporate social contribution activity, women's perception of the relationship between volunteer activity and fair trade on corporate reliability was higher than that of men. Fourth, among the corporate social contribution activity, women's perception of the relationship between volunteer activity and donation activity on the intention of price premium was higher than that of men.

• Communications for Statistical Applications and Methods
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• v.9 no.2
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• pp.381-388
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• 2002

It has been pointed out that the classical credibility model used in Korea since the beginning of 1990's lacks in objectiveness. Recently, in order to improve objectiveness, the empirical Bayes credibility model utilizing general exposure units like the number of claims and premium has been employed, but that model itself is not quite applicable in the country like Korea whose annual and classified empirical data are not well accumulated and even varied severely. In this article, we propose a new and better model, Based on the new model, we estimate both credibility and loss ratio of each class for fire insurance plans by Korean insurance companies. As a conclusion, we empirically make sure analysis that the number of claims is a more reasonable exposure unit than premium.

• Communications for Statistical Applications and Methods
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• v.17 no.5
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• pp.713-724
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• 2010

Calculating or estimating the proper insurance premium is very important decision making process for both the policyholder and the insurance company. The credibility theory is one of the most important theories in actuarial science to get the proper premium. In this research, we introduce the rule of relative exposure volume, the square root rule and the B$\ddot{u}$hlmann credibility, and estimate the new premiums based on these methods. By real data analysis, the accuracy of these credibility methods are compared.

• The Korean Journal of Applied Statistics
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• v.26 no.2
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• pp.321-333
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• 2013

Credibility theory is one of important theories in actuarial science to produce proper insurance premium. In this paper, new partial credibilities are proposed and introduced with widely accepted credibility theories such as rule of relative exposure volume, square root rule, B$\ddot{u}$hlmann credibility and B$\ddot{u}$hlmann-Straub credibility. Also, with credibilities estimated by current and newly suggested, the performance of the accuracy for estimating the risk is compared through real data analysis and we show that the newly suggested methods are improving the performance by reducing the error.

• The Korean Journal of Applied Statistics
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• v.24 no.2
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• pp.279-292
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• 2011

Credibility theory is one of the most important theories of actuarial science to calculate the proper insurance premium. In this paper, the rule of relative exposure volume, the square root rule, the B$\"{u}$hlmann credibility and B$\"{u}$hlmann-Straub credibility with the basic concept of credibility have been introduced, Also, we estimate new premiums based on these methods for real data. As a result, the rule of relative exposure volume provides the highest accuracy.

• Journal of the Korean Data and Information Science Society
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• v.16 no.4
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• pp.1147-1157
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• 2005

Bonus-Malus system is generally constructed based on claim frequency and Bayesian credibility model is used to represent claim frequency distribution. However, there is a problem with traditionally used credibility model for the purpose of constructing bonus-malus system. In traditional Bonus-Malus system adopted credibility model, individual estimates of premium rates for insureds are determined based solely on the total number of claim frequency without considering when those claims occurred. In this paper, a new model which is a modification of structural time series model applicable to counting time series data are suggested. Based on the suggested model relatively higher premium rates are charged to insured with more claim records.

• The Korean Journal of Applied Statistics
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• v.27 no.1
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• pp.71-87
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• 2014

The Bayes premium or the net premium in the credibility theory does not reflect the underlying tail risk. In this study we examine how the tail risk measures can be utilized in determining the risk premium. First, we show that the risk measures can not only provide the proper risk loading, but also allow the insurer to avoid the wrong decision made with the Bayesian premium alone. Second, it is illustrated that the rank of the tail thickness among different conditional loss distributions does not preserve for the corresponding predictive distributions, even if they share the identical prior variable. The implication of this result is that the risk loading for a contract should be based on the risk measure of the predictive loss distribution not the conditional one.

• Culinary science and hospitality research
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• v.22 no.8
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• pp.122-134
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• 2016

This study was conducted to examine what effect was produced on brand attitude and purchase intention by consumer attitude towards the visual merchandising of premium supermarket made using self-reported survey method during 1 Jun 2016 to 14 Jun 2016 as perceived by consumers who have experience in purchasing a product in premium supermarket located in Seoul. Result findings are follow. First there was significant influence between consumer perception and brand attitude (${\beta}=0.157$, p<.001) for harmony, ${\beta}=0.111$ (p<.01) for attractiveness, ${\beta}=0.639$ (p<.001) for suitability, and ${\beta}=0.146$ (p<.001) for trend), but credibility didn't have any effect on brand attitude. Second, according to the results of making a regression analysis in order to analyze an effect that brand attitude had on purchase intention, the brand attitude had a significantly positive (+) effect on purchase intention (${\beta}=0.818$, p<.001). Third, the influence on purchase intention by consumer attitude towards the visual merchandising of premium supermarket was verified (${\beta}=0.181$, p<.001) for attractiveness, ${\beta}=0.520$ (p<.001) for suitability, ${\beta}=0.325$ (p<.001) for trend), and the harmony and credibility didn't have any effect on purchase intention in current study.

• Journal of the Korean Data and Information Science Society
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• v.21 no.6
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• pp.1181-1190
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• 2010

When an insurer develops an insurance product, it is very critical to determine reasonable premiums, which is directly related to insurer's profits. There are three methods to determine premiums. Frist, the insurer utilizes premiums paid to the similar cases to the current one. Second, the insurer calculates premiums based on policyholder's past records. The last method is to combine the first with the second one. Based on the three methods, there are two major theories determining premiums, Limited Fluctuation Credibility Theory not based on statistical models and Greatest Accuracy Credibility Theory based on statistical models. There are well-known methods derived from Greatest Accuracy Credibility Theory, such as, Buhlmann model and Buhlmann-Straub model. In this paper, we extend the Buhlmann-Straub model to accommodate the fact that variability grows according to the number of data in practice and suggest a new non-parametric method to estimate the premiums. The suggested estimation method is also applied to the data gained from simulation and compared with the existing estimation method.

• Journal of the Korean Data and Information Science Society
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• v.24 no.4
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• pp.689-699
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• 2013

This paper studies the partial credibility application method by assuming the empirical prior or noninformative prior informations in auto insurnace business where intensive rating segmentation is expanded because of premium competition. Expanding of rating factor segmetation brings the increase of pricing cells, as a result, the number of cells for partial credibility application will increase correspondingly. This study is trying to suggest more accurate estimation method by considering the Bayesian framework. By using empirically well-known or noninformative information, inducing the proper posterior distribution and applying the Bayes estimate which is minimizing the error loss into the credibility method, we will show the advantage of Bayesian inference by comparison with current approaches. The comparison is implemented with square root rule which is a widely accepted method in insurance business. The convergence level towarding to the true risk will be compared among various approaches. This study introduces the alternative way of redcuing the error to the auto insurance business fields in need of various methods because of more segmentations.