• The Journal of Asian Finance, Economics and Business
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• v.9 no.1
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• pp.325-332
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• 2022

The aim of this research is to use a conceptual model to experimentally evaluate the mediating impact of government financial and training support on structural social capital and non-financial performance of family farms. Questionnaires were used to collect data from family farms in Guangxi, China, from August 25^th to September 8^th, 2021. There were 759 valid responses, accounting for 94.99 percent of the total number of respondents. The scales' reliability and validity, and the research's mediating effects and hypotheses, are tested using SPSS 22.0 and AMOS 26.0. The findings suggest that the impact of government financial assistance on family farms' non-financial performance cannot be substantiated. The intermediary chain connection of financial and training support, on the other hand, has a significant mediating effect between structural social capital and family farm non-financial performance. Direct financial assistance could be thought to encourage family farms to rely too much on funding, making them less competitive in market competition, innovation, and long-term operations. According to the conclusions of the study, government assistance to family farms could take a variety of forms, including providing diversified skills training programs in farming practices, managerial skills, and other areas.

• Journal of The Korean Astronomical Society
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• v.52 no.4
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• pp.133-144
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• 2019

We develop forecast models of daily probabilities of major flares (M- and X-class) based on empirical relationships between photospheric magnetic parameters and daily flaring rates from May 2010 to April 2018. In this study, we consider ten magnetic parameters characterizing size, distribution, and non-potentiality of vector magnetic fields from Solar Dynamics Observatory (SDO)/Helioseismic and Magnetic Imager (HMI) and Geostationary Operational Environmental Satellites (GOES) X-ray flare data. The magnetic parameters are classified into three types: the total unsigned parameters, the total signed parameters, and the mean parameters. We divide the data into two sets chronologically: 70% for training and 30% for testing. The empirical relationships between the parameters and flaring rates are used to predict flare occurrence probabilities for a given magnetic parameter value. Major results of this study are as follows. First, major flare occurrence rates are well correlated with ten parameters having correlation coefficients above 0.85. Second, logarithmic values of flaring rates are well approximated by linear equations. Third, using total unsigned and signed parameters achieved better performance for predicting flares than the mean parameters in terms of verification measures of probabilistic and converted binary forecasts. We conclude that the total quantity of non-potentiality of magnetic fields is crucial for flare forecasting among the magnetic parameters considered in this study. When this model is applied for operational use, it can be used using the data of 21:00 TAI with a slight underestimation of 2-6.3%.

• Korean Journal of Veterinary Research
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• v.47 no.2
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• pp.259-263
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• 2007

The choice of input distribution in quantitative risk assessments modeling is of great importance to get unbiased overall estimates, although it is difficult to characterize them in situations where data available are too sparse or small. The present study is particularly concerned with accommodation of uncertainties commonly encountered in the practice of modeling. The authors applied parametric and non-parametric bootstrap simulation methods which consist of re-sampling with replacement, in together with the classical Student-t statistics based on the normal distribution. The implications of these methods were demonstrated through an empirical analysis of trade volume from the amount of chicken and pork meat imported to Korea during the period of 1998-2005. The results of bootstrap method were comparable to the classical techniques, indicating that bootstrap can be an alternative approach in a specific context of trade volume. We also illustrated on what extent the bias corrected and accelerated non-parametric bootstrap method produces different estimate of interest, as compared by non-parametric bootstrap method.

• Korean Management Science Review
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• v.31 no.3
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• pp.41-59
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• 2014

The marketing literature suggests that personal relationships between customers and service providers influence consumers' evaluation of goods and services. In this paper, we investigate the effects of service providers' conversation types (non-physical communication) on customers' evaluation and satisfaction in conversation with service providers. The empirical results show that the non-physical communication affect consumers' satisfaction in communication with service providers. This implies that the non-physical communication could be considered as a strategic tool when corporations need to differentiate their services from competitors to gain an advantage in competition.

• Asia pacific journal of information systems
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• v.29 no.4
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• pp.644-672
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• 2019

Negative consequences incurred from employees' non-work-related computing (NWRC) have been one of the security-related issues in information intensive organizations. While most studies have focused on the factors that motivate employees to engage in NWRC, this study examines the mediating effect of moral beliefs on the relationship between sanctions and NWRC using a moral beliefs-based model. The research model posits that the formal (i.e., punishment severity and detection certainty) and informal sanctions (subjective norms and descriptive norms) enhance employees' moral beliefs against NWRC intention. From a cross-sectional scenario-based survey involving 176 employees working at banks in Mongolia, our results indicate that moral beliefs fully mediate the relationship between detection certainty/subjective norms and NWRC intention and act as a partial mediator in the relationship between descriptive norms and NWRC. The findings from this study present empirical evidence that both informal and formal sanctions could be an effective deterrent for NWRC intention through employees' moral beliefs.

• Journal of the Korean Operations Research and Management Science Society
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• v.31 no.3
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• pp.97-105
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• 2006

Brand Pricing is the most important issue for the brand manager in the dynamic market. in the typical dynamic pricing model, a linear function has been used based on the assumption that the non-Price Influences and the price influences were independent. However, to incorporate the characteristics of the dynamic market, it is natural to consider the multiplicative relationship. We are going to try the multiplicative linkage between the non-price Influences and the price influences and suggest a new dynamic pricing model with e multiplicative functional form. An empirical study of 19 brands in the Korean cigarette market shows the feasibility of the suggested model.

• Journal of the Korean Operations Research and Management Science Society
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• v.33 no.2
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• pp.1-16
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• 2008

The purpose of this paper is to propose a new binary classification method for predicting corporate failure based on genetic algorithm, and to validate its prediction power through empirical analysis. Establishing virtual companies representing bankrupt companies and non-bankrupt ones respectively, the proposed method measures the similarity between the virtual companies and the subject for prediction, and classifies the subject into either bankrupt or non-bankrupt one. The values of the classification variables of the virtual companies and the weights of the variables are determined by the proper model to maximize the hit ratio of training data set using genetic algorithm. In order to test the validity of the proposed method, we compare its prediction accuracy with ones of other existing methods such as multi-discriminant analysis, logistic regression, decision tree, and artificial neural network, and it is shown that the binary classification method we propose in this paper can serve as a premising alternative to the existing methods for bankruptcy prediction.

• Journal of the Korean Operations Research and Management Science Society
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• v.34 no.4
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• pp.15-26
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• 2009

Bass diffusion model have played a central role in studying the diffusion of the new products since 1969, the year of publication of Bass model. Almost 750 publications based on the Bass diffusion model have explored extensions and applications. Extension models can be divided into two types. One is the model containing marketing-mix variables and the other is the model containing additional parameters. This paper presents another extension model of the latter type. Our model allows the time varying coefficients of innovation and imitation. Two pieces approximation of time varying coefficients is introduced and it's parameters are estimated based on NLS(Non-Linear Mean Square) method. Empirical studies are performed and the results show that our model is superior to the basic Bass model and the NUI(Non-Uniform Influence) model which is the well-known extension of the Bass model. The model developed in this paper is, also, transformed into the Bass model with the ready potential adopters in order to enhance the descriptive power.

• Journal of the Korean Operations Research and Management Science Society
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• v.27 no.3
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• pp.1-19
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• 2002

Recently, increasing attention has been paid to building a successful software process in Information System(IS) implementation. This study establishes software process model as a key predictor of organizational performance. We propose a theoretical framework for capability maturity model derived from the Software Engineering Institute(SEI). This paper identify the process-related variables, financial performance and non-financial performance from the relevant literature and clarify the concept of software process by distinguishing between its component and determinants. We then examine the impact of software process on organizational performance. Hypotheses on software process were tested for 36 enterprises including 118 organizational units. Results indicate that software process capability may serve as a key predictor of organizational performance. Software process maturity found to be positively influenced on the financial and non-financial performance, while investment of information technology as a mediating variable not significantly affected to the performance.

• Journal of Korean Society for Quality Management
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• v.30 no.1
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• pp.22-46
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• 2002

Recently, increasing attention has been paid to building the software quality and software productivity due to ongoing software crisis. To overcome such problem, one of the many alternatives is to use the capability maturity model (CMM) suggested by the Software Engineering Institute(SEI), focusing on the improvement of software progress. This research is proposed the theoretical framework for CMM based on the previous studies, and review the status of software process on the software development organization. We then examine the impact of the software process capability on the organizational performance including financial measures and non-financial measures. Hypotheses on software process capability were tested 144 organizational units. The 62.5% of foreign companies are distribute to the second and third level, the Korean firms in this study are indicated the first level. Result indicate that maturity of software process may be served the key predictor of organizational performance, in particular the positive relationship between the software process and non-financial performance index such as customer service, IT Infrastructure, marketing, supplier and purchaser, production and operation.