• The Journal of the Korea Contents Association
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• v.11 no.3
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• pp.418-427
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• 2011

The purpose of this study is to investigate demand-determinant factors based on the number of visits and substitutive relations inter-restaurants, which are four major domestic family restaurants. Findings indicate that the factors of demand-determinant for visiting are affected by demographic characteristics, brand images of family restaurants, and the rate of the number of visits. In addition, this study used partial co-relation analysis to determine the substitutive relations of competitive restaurants. Considering these results, this study suggests how family restaurants' marketing strategy could be differentiated by discriminating the determinant factors which affect the number of visits. Also, this study makes it possible to arrange the opportunity to strengthen restaurants' competitiveness by examining competitive relations to the inter-restaurants.

• The Journal of Society for e-Business Studies
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• v.17 no.2
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• pp.63-72
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• 2012

The Korean telecommunications market has been expanding swiftly, these days, to be saturated. In this environment, the upcoming mobile telecommunication market, where 4G service was introduced this year, is becoming more substitutive and competitive. Thus, the demand forecasting of 4G service is very difficult, while it is critical to market success. This paper adopts a multi-generation diffusion model to capture the diffusion and substitution patterns for two successive generation of technological services, i.e., 3G and 4G mobile telecommunications services. The three parameters, i.e., the coefficient of innovation, the coefficient of imitation, and the coefficient of market potential, used in the multi-generation diffusion model based on Norton and Bass[11] are obtained by inference from similar substitutive relations between older and newer telecommunication services to 3G and 4G services. The simulation results show that the Bass type multi-generation model can be successfully applied to the demand forecasting of newly introduced 4G mobile telecommunication service.

• Journal of Korea Technology Innovation Society
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• v.10 no.1
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• pp.1-21
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• 2007

Among numerous policy influencers' and researchers' advices and policy suggestions, there is little opposition to the proposition that technology is essential to the economic development. The role of technology has never been more emphasized than today in Korea as in any other countries. The effects of the government's innovation policy on corporate R&D activities and more broadly the economic welfare of a whole nation are widely recognized with intuitional and empirical evidence. That is, various R&D incentives reduce the marginal cost of a firm's R&D efforts, inducing as much increase of its R&D investment to result in a better chance to acquire target technology. This paper examines the impact of R&D incentives on the technological outcomes by analyzing individual firms' investment behaviors subject to the government's R&D incentive policies. An econometric model of technological outcomes is estimated on a project level with cross-sectional data. "Probit model" is employed for estimations. Special attention was given to the effectiveness of R&D programs by estimating policy impact by types of investment. The data were collected from 928 different R&D projects completed between 1987 and 1993. With the single equation approach, we were able to find that the structure of investment is a far more significant factor in technological outcomes than the total amount of investment. The analysis also shows that the two types of firms' matching investment, in-kind and cash, do not bear a complementary, but a substitutive relations to each other. It also reconfirms the proposition that R&D incentives increase firm's financial investment. Despite many supportive studies emphasizing the cooperation between innovation performers, it is also found that the larger the number of institutions involved in a project, the less likely it leads to a technological success, And meeting the proposed deadlines without postponing is estimated to be a good barometer to predict the outcome of an R&D project. Also the probabilities of success for major variables are represented for policy implications, after calculating marginal effects.