In this paper, we develop theoretical game models to determine the level of government subsidies for banks to provide policy loans to Innovative SMEs(small and medium sized enterprises) through banks, which otherwise would not finance them for the sake of their own profitability. For this, we compare net cash flows of each bank using different strategies against high risk innovative SMEs. A bank can decide whether to provide them loans or not In each period. Following Kim(2003)'s Infinite horizon model on the soft budget constraint, we introduce a situation in which banks compete against each other for higher net long-term payoffs from their loans to innovative SMEs and non-innovative SMEs. From the models, we show that competition among banks in general leads to a tighter decision against innovative SMEs, as a Nash equilibrium. It is not because the government bank is simply loose in providing loans, but because competition among commercial banks for fewer riskier borrowers results in tighter loan decisions against innovative SMEs. Thus, the competitive market for policy loans to innovative SMEs fails to reach the socially optimal level of loans for innovative SMMs. Commercial banks in the competitive market may require additional supports from the government to make up for the differences in their payoffs to support innovative SMEs, possibly much riskier due to moral hazards and poor discounted cash flows. The monopolistic government bank might also request such supports from the government to fund otherwise unqualified SMEs. We calculate an optimal level of governmental support for banks to guarantee funding such high-risk innovative SMEs over periods without deviating from their optimal Nash equilibrium policies.

Today the u-government services are becoming more personalized and intelligent. For the successful implementation of personalization, individual user's privacy concerns must be respected and taken care of. Based on the empirical survey results, this research summarizes the reluctance to the government's use of private information using six categories. We measure user's psychological distance toward e-government using the four levels, adopting the suggestions by the Proxemics. Since a positive correlation is Identified between people's psychological Intimacy toward e-government and their tolerance to the use of private Information, the amount and/or types of private information should be sequentially used in personalization systems. Initially allowing the least intolerable private information such as occupation information, the personalization system should additionally use the next tolerable Information such as health information or service request/interest information, as user's psychological distance toward government services becomes shorter.

The recent economic crisis not only reduces the profit of department stores but also incurs the significance losses caused by the increasing late-payment rate of credit cards. Under this pressure, the scope of credit prediction needs to be broadened from the simple prediction of whether this customer has a good credit or not to the accurate prediction of how much profit can be gained from this customer. This study classifies the delinquent customers of credit card in a Korean department store into homogeneous clusters. Using this information, this study analyzes the repayment patterns for each cluster and develops the credit prediction system to manage the delinquent customers. The model presented by this study uses Kohonen network, which is one of artificial neural networks of data mining technique, to cluster the credit delinquent customers into clusters. Cox proportional hazard model is also used, which is one of survival analysis used in medical statistics, to analyze the repayment patterns of the delinquent customers in each cluster. The presented model estimates the repayment period of delinquent customers for each cluster and introduces the influencing variables on the repayment pattern prediction. Although there are some differences among clusters, the variables about the purchasing frequency in a month and the average number of installment repayment are the most predictive variables for the repayment pattern. The accuracy of the presented system leaches 97.5%.

Price discounts presupposing churn-in are important tools of competition in many industries such as mobile telecommunication services and newspaper. In this case, consumers can get discount only through changing the provider. For analyzing this kind of competitions, we should consider the incentive of utilizing iterative switching. Hence, in this paper, we consider multi-stage equilibrium and can find that equilibria are different from one stage discount. In particular, when consumers' decisions are for maximizing multi-stage utility, discounts can bring about churn-out as well as churn-in and firms lose the incentive of discounts.

Total profit level Increases if a company increase the cost for achieving R&D related goals of equipment productivity enhancement, production cost saving, or for achieving equipment scale target, sales volume goal. But how much money should be invested to achieve a certain level of profit? We formulated the model to set the optimal goal levels to minimize the investment cost under the constraint that certain level of total profit should be guaranteed. This model derived from a case of P steel company. We found that this should be considered in relation with the production sales planning (known as optimal product mix problem) to guarantee the profit. We suggested a nonlinear programming model, 3 valiant form of the p+roduct mix problem. We can find the optimal Investment level for the R&D related goals or sales volume goal, equipment scale target for the P steel company using the model.

"How does advertising affect sales?" is the fundamental issue of modern advertising research. There is an interesting issue for estimating carryover effects of advertising on sales, and the aggregated data biases exist in the duration of advertising effect. This research suggests an extended model of Koyck Model which is employed for micro-data (Koyck 1954) to estimate aggregated advertising data, and empirically shows the aggregated data bias. Our developed model with the aggregated level of actual advertising data is more appropriate than the basic Koyck model for micro-data. The result figures out that it is important to consider the disaggregated data level in the analysis of dynamic effects of adverting such as carryover effects.

This paper considers two-sided assembly line balancing with preemptive multiple goals. In the problem, three goals are taken into account in the following priority order : minimizing the number of mated-stations, achieving the goal level of workload smoothness, and maximizing the work relatedness. An evolutionary algorithm is used to solve the multiple goal problems. A new structure is presented in the algorithm, which is helpful to searching the solution satisfying the goals in the order of the priority. The proper evolutionary components such as encoding and decoding method, evaluation scheme, and genetic operators, which are specific to the problem being solved, are designed in order to improve the algorithm's performance. The computational results show that the proposed algorithm is premising in the solution quality.