• Journal of the Korea Academia-Industrial cooperation Society
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• v.20 no.4
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• pp.232-241
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• 2019

This study examines one of the conventional and controversial issues in modern finance. Specifically, this study identifies financial determinants of corporate R&D intensity for firms belonging to Korean Chaebols. Empirical estimation procedures are applied to derive more robust results of each hypothesis test. Static panel data, Tobit regression and stepwise regression models are employed to obtain significant financial factors of R&D expenditures, while logit, probit and complementary log-log regression models are used to detect financial differences between Chaebol firms and their counterparts not classified as Chaebols. Study results found the level of R&D intensity in the prior fiscal year, market-value based leverage ratio and firm size empirically showed their significance to account for corporate R&D intensity in the first hypothesis test, whereas the majority of explanatory variables had important power on a relative basis. Assuming that the current circumstances in the domestic capital market may necessitate gradual changes of Korean Chaebols in terms of their socio-economic function, the results of this study are expected to contribute to identifying financial antecedents that can be beneficial to attain optimal level of corporate R&D expenditures for Chaebol firms on a virtuous cycle.

• Journal of Korean Society of Transportation
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• v.23 no.2
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• pp.117-130
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• 2005

In both deteministic user Optimal Traffic Assignment Model (UOTAM) and stochastic UOTAM, travel time, which is a major ccriterion for traffic loading over transportation network, is defined by the sum of link travel time and turn delay at intersections. In this assignment method, drivers actual route perception processes and choice behaviors, which can become main explanatory factors, are not sufficiently considered: therefore may result in biased traffic loading. Even though there have been some efforts in Stochastic UOTAM for reflecting drivers' route perception cost by assuming cumulative distribution function of link travel time, it has not been fundamental fruitions, but some trials based on the unreasonable assumptions of Probit model of truncated travel time distribution function and Logit model of independency of inter-link congestion. The critical reason why deterministic UOTAM have not been able to reflect route perception cost is that the route perception cost has each different value according to each origin, destination, and path connection the origin and destination. Therefore in order to find the optimum route between OD pair, route enumeration problem that all routes connecting an OD pair must be compared is encountered, and it is the critical reason causing computational failure because uncountable number of path may be enumerated as the scale of transportation network become bigger. The purpose of this study is to propose a method to enable UOTAM to reflect route perception cost without route enumeration between an O-D pair. For this purpose, this study defines a link as a least definition of path. Thus since each link can be treated as a path, in two links searching process of the link label based optimum path algorithm, the route enumeration between OD pair can be reduced the scale of finding optimum path to all links. The computational burden of this method is no more than link label based optimum path algorithm. Each different perception cost is embedded as a quantitative value generated by comparing the sub-path from the origin to the searching link and the searched link.

• Environmental and Resource Economics Review
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• v.20 no.1
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• pp.119-153
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• 2011

This study reviews various aspects of model formulating processes of dichotomous choice responses of the contingent valuation method (CVM), which has been increasingly used in the preliminary feasibility test of Korea public investment projects. The theoretical review emphasizes the consistency between WTP estimation process and WTP measurement process. The empirical analysis suggests that two common parametric models for dichotmous choice responses (RUM and RWTP) and two commonly used probability distributions of random components (probit and logit) resulted in all most the same empirical WTP distributions, as long as the WTP functions are specified to be a linear function of the bid amounts. However, the efficiency gain of DB response compared to SB response were supported on the ground that the two CV responses are derived from the same WTP distribution. Moreover for the exponential WTP function which guarantees the non-negative WTP measures, sample mean WTP were quite different from median WTP if the scale parameter of WTP function turned out to be large.

• Journal of Digital Convergence
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• v.19 no.6
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• pp.143-162
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• 2021

Research on consumers' perception and willingness to purchase Battery Electric Vehicles (BEVs) is necessary to simulate BEVs' deployment in South Korea because South Korea's BEVs market is still in the early stage. This paper derives a theoretical framework for consumer segmentation based on consumers' willingness to purchase before and after BEV usage experience. In particular, this study empirically evaluates consumers' willingness to purchase and concerns using the survey data from BEVs users in either Seoul or the Jeju region. The empirical results from logit models show that experienced consumers' concerns about the heater and air conditioning (HAC) in BEVs decreased the consumers' willingness to buy, while greater daily driving distances increased the consumers' willingness to buy. In addition, the empirical findings from ordered probit models show that experienced consumers' concerns about the short driving distance, the availability of maintenance service (i.e., A/S service) during unexpected events, and the difficulties of driving BEVs up-hill increased the degree of concern about HAC. This paper will provide insights related to consumer segmentation, R&D, marketing strategies, and policy design for policymakers and firms.

• Journal of Intelligence and Information Systems
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• v.9 no.1
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• pp.227-249
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• 2003

Prediction of corporate failure using past financial data is a well-documented topic. Early studies of bankruptcy prediction used statistical techniques such as multiple discriminant analysis, logit and probit. Recently, however, numerous studies have demonstrated that artificial intelligence such as neural networks can be an alternative methodology for classification problems to which traditional statistical methods have long been applied. In building neural network model, the selection of independent and dependent variables should be approached with great care and should be treated as model construction process. Irrespective of the efficiency of a teaming procedure in terms of convergence, generalization and stability, the ultimate performance of the estimator will depend on the relevance of the selected input variables and the quality of the data used. Approaches developed in statistical methods such as correlation analysis and stepwise selection method are often very useful. These methods, however, may not be the optimal ones for the development of neural network model. In this paper, we propose a genetic algorithms approach to find an optimal or near optimal input variables fur neural network modeling. The proposed approach is demonstrated by applications to bankruptcy prediction modeling. Our experimental results show that this approach increases overall classification accuracy rate significantly.

• Journal of Korean Society of Transportation
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• v.20 no.4
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• pp.27-38
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• 2002

VTIS(Value-added Traffic Information System), among the sub-systems of ATIS, is an Advanced Traffic System which innovates efficiency and safety. And this system, having marketability and publicness, is very important. Moreover, This system offers definite traffic information according to the demand of specified users. And it is expected to produce additional spread effects because of high participation rate of private sector. However, the VTIS service media are varied and there are varied optimal Prices and payment methods according to each medium. Because of that, there needs the study on these problems or optimal criteria. But because existing studies were devoted to estimate the optimal route, the study toward the optimal price which was considered part of user and service use demand do not exist. Accordingly, we surveyed under imaginary alternative pricing scenarios and forecasted the use demand of VTIS by using Binary Logit model. Also, for the users who answered that they would use VTIS service in survey, we classified their use's behaviors as four categories and estimated the use ratio to each category by using Ordered Probit model. Last, using sensitivity analysis for results form above, we derived the optimal price that is 2800won in monthly. 145won in payment per call. Then, VTIS service use rate is respectively 65%, 75%.

• Korean Journal of Social Welfare
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• v.35
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• pp.85-105
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• 1998

This article examined the trend of 125 empirical researches which were published in Jr. of Korean Social Welfare from the first issue to no. 33. in terms of theoretical and methodological orientations. The content analysis was employed for the purpose of the study. Since 1979, the number of empirical researches was in the trend of increasing. The findings from this research were as follows. 1) Among 166 authors, 96.4% were majored in social welfare. Also 6.0% were practitioners and the rest of them were in the position of professors or researchers. The outcome of lack of interdisciplinary co-work and researcher-practitioner co-work led the article to conclude that the nature of applied social science of social welfare was not so actively pursued in Korea. 2) It was almost impossible to find researches which studied same theme or employed same analytical framework. This meant that the work of re-verifying and proving the contray could not be done although it was essential for theory-building. In other words, the disciplinary of social welfare was far behind in the process of theory-building. 3) The methodology upon which most of researches were relied was quantitative methodology(92.8%). The article concluded 'paradigm shift' was not begun in the disciplinary of social welfare yet. 4) The study concluded that the particularity of empirical researches of social welfare in Korea was descriptive-configurative study. Whereas 65.5% of 125 empirical studies were descriptive-configurative, 25% were hypothesis - model test and only 6% causal analysis. 5) The most applied statistic models through the period from 1979 to 1997 were descriptive statistics such as frequency, chi square test, Pearson's r. More advanced statistics such as logit regression, probit regression, path analysis, covariance structure analysis were shown since 1990.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.22 no.2
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• pp.248-258
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• 2021

The study analyzed the financial determinants of corporate R&D intensity that require more attention from academics and practitioners in the Korean capital market. Domestic small and medium enterprises (SMEs) may face with developing substitutes by making more R&D investments in scale and scope, given the unprecedented economic conditions such as the limitation of importing core components and materials from other nation(s). KOSDAQ-listed SMEs were selected as sample data, whose R&D expenditures may be less than those of large firms during the post-global financial turmoil period (2010~2018). Static panel data model was applied, along with Tobit and stepwise regression models, for examining the validity of results. Logit, probit, and complementary log-log regressions were also employed for a relative analysis. R&D expenditures in the prior year, the interaction effect between the previous R&D intensity and high-tech sector, firm size, and growth rate were significant to determine R&D intensity. Moreover, a majority of explanatory variables were found to change between the years 2011 and 2018, while time-lagged effects between the R&D intensity and growth rate exist. Results of the study are expected to be used for future research to detect optimal levels of R&D expenditures for the value maximization of SMEs.