• 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 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.

• Journal of Korean Society of Transportation
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• v.21 no.4
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• pp.113-132
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• 2003

Using nonradial data envelopment analysis(DEA) under assumptions of strong disposability and variable returns scale, this paper annually estimates productive. technical and allocative efficiencies of three publicly-owned rail transit properties which are different in terms of organizational type: Seoul Subway Corporation(SSC, local public corporation), the Seoul Metropolitan Electrified Railways sector (SMESRS) of Korea National Railroad(the national railway operator controlled by the Ministry of Construction and Transportation(MOCT)), and Busan Urban Transit Authority (BUTA, the national authority controlled by MOCT). Using the estimation results of Tobit regression analysis. the paper next computes their true productive, true technical and true allocative efficiencies, which reflect only the impacts of internal factors such as production activity by removing the impacts of external factors such as an organizational type and a track utilization rate. And the paper also computes an organizational efficiency and annually gross efficiencies for each property. The paper then conceptualized that the property produces a single output(car-kilometers) using four inputs(labor, electricity, car & maintenance and track) and uses unbalanced panel data consisted of annual observations on SSC, SMESRS and BUTA. The results obtained from DEA show that, on an average, SSC is the most efficient property on the productive and allocative sides, while SMESRS is the most technically-efficient one. On the other hand. BUTA is the most efficient one on the truly-productive and allocative sides, while SMESRS on the truly-technical side. Another important result is that the differences in true efficiency estimates among the three properties are considerably smaller than those in efficiency estimates. Besides. the most cost-efficient organizational type appears to be a local public corporation represented by SSC, which is also the most grossly-efficient property. These results suggest that a measure to sort out the impacts of external factors on the efficiency of rail transit properties is required to assess fairly it, and that a measure to restructure (establish) an existing(a new) rail transit property into a local public corporation(or authority) is required to improve its cost efficiency.