• Journal of Technology Innovation
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• v.22 no.1
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• pp.1-22
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• 2014

R&D investment also has a gestation period similar to other investments in economics. The gestation period originates from time lag effect of input and output. Thus it is necessary to consider time lag effects when analyzing the relationship between firms' R&D investment and R&D performance. The main objective of this research is to estimate the length of time lag effect of R&D investment. The Almon distribution lag model was applied to estimate the time lag effect. The firm level panel dataset was established from 2002 to 2009. The net value of R&D investment and the number of patent applications were used to measure R&D input and output, respectively. This method found the estimated time lag to be 1~2 years across all datasets. The same analyses were applied to chemical, metal, electronic, exact science, and machinery industries' data. And we found there were differences among sectors in regard to the time lag effect.

• Asia Pacific Journal of Business Review
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• v.6 no.2
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• pp.61-76
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• 2022

Based on the concept of advertising expenditure, manufacturing firm performance, and enterprise life cycle, this research conducts the listed Chinese manufacturing listed in 2016-2018 as the research sampling and divides these listed companies into three periods: growth, maturity, and decline. Next, this paper conducts empirical research from three aspects: advertising expenditure or investment and manufacturing firm performance, lag effect of advertising expenditure, and outcome effect and lag effect of advertising investment. It is found that in different stages of manufacturing enterprises, different advertising expenditures will have different impacts on the performance of manufacturing enterprises. In the growth stage, the advertising investment of manufacturing enterprises will significantly affect the performance results of the current period, and there will be the long-term lag effect. In contrast, the mature stage of enterprises' advertising investment has a shorter period of lag effect, while in the recession stage, the mature stage of manufacturing enterprises' advertising investment will have a shorter period of lag effect. The empirical results are not significant. This study provides a reference for manufacturing enterprises in different stages in the decision-making of advertising investment.

• Journal of Korean Institute of Industrial Engineers
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• v.33 no.2
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• pp.221-226
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• 2007

This paper suggests a valuation framework of investment project using the concept of real options. We show the valuation process of real assets using the risk-neutral pricing. Especially, we focus on the investment lag. Real assets have investment lag in general. The decision time and the payment time are not identical. So the investment lag should be considered when valuing real assets for reality. We provide the valuation process for real assets, including R&D project. The results of this paper can be used for the real assets valuation and strategic decision analysis.

• Knowledge Management Research
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• v.20 no.1
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• pp.27-43
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• 2019

This paper examines spillover effects of R&D investment in the ICT industry to other industries by analyzing panel data composed of 6 manufacturing industries for the period of 1983~2011. Major findings are as follows; (1) The increase of R&D investment in ICT industry has a significantly positive relationship with the increase in the value-added of the remaining 5 industries with 3~10 year lags, depending on the source of R&D funds and R&D stage. (2) More specifically, public R&D shows the spillover effects during 3~7-year lag periods, whereas private R&D started to exert spillover effects from 9-year lag. The result implies that the public R&D appropriately targets projects with more spillover effects. (3) Basic research, applied research, and development showed the spillover effects for the period of 9~10, 7~10, and 10-year lag, respectively. (4) The R&D investment in 5 other industries such as machinery, chemicals, and materials does not have positive spillover effects to the remaining industries. Few studies have been done to analyze the R&D spillover effects to other industries, with certain limitations. This study contributes to the existing literature by analyzing the spillover effects of the different R&D funds and R&D stages, and by considering various time-lag effects.

• Journal of Information Technology Applications and Management
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• v.16 no.4
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• pp.205-222
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• 2009

Considering time-lag in the performance evaluation of information system (IS) investment is important because its effect reveals after certain period of time passed. Particularly it is more in the systems of e-government informatization projects which the amount of investment and the scale of business are huge. Many methods to solve this issue have been proposed such as system dynamics methods, simulations, structural equations etc. However, it is still difficult and unsolved problem because collecting practical data for time-lag analysis is very hard. In this paper, we analyze IS time-lag effect through factor analysis using the accumulated practical operational DB data. For the performance evaluation of the G4C system, the representative e-government web portal, we selected eleven factors reflecting time passing in G4C DB data. With these factors this paper conduct time-lag analysis in four view points. First, we conducted 'Stabilizing of G4C system' and got a result that IS is needed about three years for the stabilization. Second, we conducted 'Utilization of G4C system' and got a result that the utilization reaches appropriate level after in three years later after the introduction of G4C system. Third, we conducted 'Cost reduction effect' and got a result that cost reduction is stable in the third year after the introduction of G4C system. Lastly, we conducted 'System maturity effect' and got a result that the system reaches to the quality level that users expect after third to fourth years. According to the results of this research, we found that performance of IS improv continuously not immediately, and it needs three or four years of time-lag.

• Proceedings of the Korea Technology Innovation Society Conference
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• 2000.11a
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• pp.346-356
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• 2000

This paper aims to analyse the relationship between R＆D investment and economic growth in Korea. The analysis result shows 38 percent of average economic growth rate(7.1%) of Korea between 1976 and 1998 was achieved by the growth of Total Factor Productivity (TFP), and the R&D investment during the period contributed in achieving the economic growth rate by as much as 9.86 percent. In the process of the estimate, the rate of return of the R&D investment from both government and private was calculated as 47 percent. The relationship between private R&D investment, government R&D investment and the GDP was also investigated, and it was estimated that the private sector invested 2.0 percent of the GDP in R&D during the period, and was found that 1 won of government R&D investment induced 0.202 won of private sector's R&D investment. However, the time-lag effect, which is naturally believed to exist between the R&D investment and the economic growth, could not be analysed in a mathematical form, because of the lack of the data to establish this relationship. However, this paper believe that the time-lag effect in this relationship was included implicitly by using the data of 23 years.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.35 no.1
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• pp.87-92
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• 2012

This study examines the relationship between R&D investment and subsequent outputs of the research activity. Usually, there is some time difference between the production of research outputs, such as academic papers and application or registration of patents, and the investment of R&D expenditure. The time lag for producing this kind of research outputs should be considered to evaluate the performance of research activity exactly. The purpose of this study is to identify time lag effect between the times of input and output of a R&D activity and to derive the degree of time lag using the data set of a long term R&D program supported by Korean government. A modified Almon model is suggested to identify the time lag effect between input and output of research activities performed by this program. Time-series cross-section data from 16 research centers between 2001 and 2009 are used to find time lag effect.

• The Journal of Asian Finance, Economics and Business
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• v.7 no.8
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• pp.69-76
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• 2020

The study examines lagged economic effects of research and development (R&D) investment on the market value of manufacturing firms listed on the Shanghai Stock Exchange or the Shenzhen Stock Exchange in China. This study applies panel data analysis methods to address the following issues: 1) There might be an adjustment lag in the impact of R&D investment on corporate market value, and 2) Unobserved firm effects must be taken into account. The balanced panel data includes a total of 1,462 observations with 34 cross-sections of manufacturing firms listed on Chinese stock markets and with 27 time-specific quarterly periods from 2007 to 2017. The results indicate that the R&D investment of Chinese manufacturing firms tends to yield favorable market value of the firm with some adjustments to time. The results show that R&D investment exhibits a strong positive impact on their market value of manufacturing firms in Chinese stock markets. Moreover, R&D investment has a positive time-lag effect on the market value of the firm. Interestingly, the R&D investment of Chinese manufacturing firms generate a relatively constant positive effect on their market value, supporting the notion that the corresponding returns of R&D investment for such firms yield lagged but added market values.

• Proceedings of the Technology Innovation Conference
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• 2001.06a
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• pp.145-156
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• 2001

This paper investigates the effect of imported technology on the economic growth of Korea. To this end, the relationship between input technology and economic growth are suggested in the numerical form and analysed empirically. The rates of return of technology investments, which are divided into the domestic R&D investment and the investment on imported technology, are estimated. Based on the result of this analysis, the rate of return of the input technology, which includes the domestic R&D investment and the investment on imported technology, are estimated as 31.4%, and this input technology is calculated as to contribute 8.9% on the economic growth rate of Korea. And the domestic R&D investment is fumed out to have bigger rate of return than the investment on imported technology during the surveyed period. However, the rates of return of detailed R&D investments, which can be divided into the investments on commercial R&D and basic science, were not calculated in this paper, because of the lack of data on this in this paper. As well, the time-lag effect, which is naturally believed to exist between the R&D investment and the economic growth, could not be analysed wit:1 the same reason. Thus when analysing the relationship between them, this paper tried to minimize the time-lag effect by using the long-term data of twenty-three years.

• The Journal of Asian Finance, Economics and Business
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• v.8 no.3
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• pp.119-126
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• 2021

This study is to examine the foreign direct investment (FDI) response to real effective exchange rate volatility in Vietnam by using the vector autoregression model. The research data are quarterly frequency data in the period from 2004:Q1 to 2019:Q2. The data on real effective exchange rate were collected from the statistics of Bruegel (Europe) and FDI data were collected from the International Financial Statistics. The quantitative study was conducted with two steps: (1) measuring exchange rate volatility by the GARCH(1,1) method; and (2) examining the impact of exchange rate volatility on FDI in the context of the global financial crisis. The estimation results show that FDI responded significantly to real exchange rate volatility with the lag of 3 periods at the 5% significance level. The FDI response increased after the exchange rate volatility with the lag of 3 periods, and the impact extended to the lag of 6 periods, and then gradually stabilized. The research findings indicate that FDI in Vietnam responds positively and significantly to exchange rate volatility with the lag of 3 periods. Simultaneously, the negative impact of the global financial crisis in 2008 with the lag of 2 periods leads to a slight decrease in FDI inflows into Vietnam.