• The Journal of Information Systems
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• v.22 no.3
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• pp.43-58
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• 2013

This work investigates factors that may affect the choice of real options by ERP project managers. Financial theory suggest that these factors include risk-free interest rate, time to maturity, volatility of net present value, and options exercise price. Other than these factors, we are interested in the exogenous risks related to external uncertainties about technological cost, user learning and consulting, and so forth and we argue these risks should have a significant impact upon the volatility of net present value. To validate these factors empirically, we collected survey questionnaires from ERP project managers in Korea. We find that perceived exogenous risks with regard to ERP projects influence volatility and additionally find that ERP project managers prefer contract options of the project when the volatility of the project is expected to be high. We expect that this work will not only validate theoretical propositions but help project managers consider ERP options strategically based on these factors.

• Journal of Korea Technology Innovation Society
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• v.22 no.3
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• pp.307-339
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• 2019

This study investigates factors that affect the transformation of multiplex tie into one specific type of relationship - competitive relationship. In particular, this study argues that the lower technological distance or gap of technological competency, the higher the chances are for the multiplex tie to become a competitive tie. In addition, technological characteristics of the firms are also found to affect the multiplex tie's transformation into the competitive tie. To study this phenomena, this study uses both quantitative analysis and case study method. This study is an exploratory attempt to find factors relevant to change multiplex ties into competition, contributing to the literature of multiplex ties by identifying technological variables that affect the transformation of such ties. This study also contributes to practices by providing the guidance on what strategies firms should implement in complex situations such as multiplex ties.

• Proceedings of the Korean Vacuum Society Conference
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• 2014.02a
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• pp.364.2-364.2
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• 2014

Magnesium oxide (MgO) thin films have attracted great scientific and technological interest in recent decades. Because of its distinguished properties such as a wide band gap (7.2 eV), a low dielectric constant (9.8), a low refractive index, an excellent chemical, and thermal stability (melting point=$2900^{\circ}C$), it is widely used as inorganic material in diverse areas such as fire resistant construction materials, optical materials, protective layers in plasma display panels, buffer layers of multilayer electronic/photonic devices, and perovskite ferroelectric thin films. Precursor used in the ALD requires volatility, stability, and low deposition temperature. Precursors using a heteroleptic ligands with different reactivity have advantage of selective reaction of the heteroleptic ligands on substrate during ALD process. In this study, we have synethesized new heteroleptic magnesium precursors ${\beta}$-diketonate and aminoalkoxide which have been widely used for the development of precursor because of the excellent volatility, chelating effects by increasing the coordination number of the metal, and advantages to synthesize a single precursor. A newly-synthesized Mg(II) precursor was adopted for growing MgO thin films using ALD.

• 한국경영정보학회:학술대회논문집
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• 2008.06a
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• pp.957-962
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• 2008

We propose a model for the line expansion problem in the AMOLED (Active Matrix Organic Light Emitting Diodes) industry, which now faces market uncertainty: for example, changing customer needs, technological development path, etc. We focus on the optimal investment time and size of the AMOLED production lines. In particular, employed here is the ROV (Real Options Valuation) model to show how to capture the value of line expansion and to determine the optimal investment time. The ROV framework provides a systematic procedure to quantify an expected outcome of a flexible decision which is not possible in the frame of the traditional NPV (Net Present Value) approach. Furthermore, we also use Monte Carlo simulation to measure the uncertainty associated with the line expansion decision; Monte Carlo simulation estimates the volatility of a decision alternative. Lastly, we present a scenario planning to be conducted for what-if analysis of the ROV model.

• Korean Journal of Construction Engineering and Management
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• v.18 no.4
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• pp.27-35
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• 2017

Based on Income-approach, this study develops the evaluation model which reflects construction industry's traits. Using Income approach, we derive future income's present value and evaluates the technological value by contribution to future income. As there exist more random variables in construction technology than in standardized manufactured products, we cannot help relying on not only quantitative estimation method but also qualitative evaluation by technology and market experts when we estimates construction technology value. Also, conservative estimation is needed for discount rate and cash-flow estimation, because of high uncertainty in sales and profits in construction industry. In empirical analysis, we applied economic periods of duration and cash-flow based on the standard guideline, and analyzed discount rate and technology factor based on characteristics of construction industry. The discount rate is estimated to 15% because of risk-premium increase by conservative evaluation. Technology factor is estimated to 46.7%, because technological intensity is estimated to 72% by technological superiority. Such implications can be inferred. Firstly, we need to build a database to diversify categories for division of sectors by activity or industrial classification which is now categorized only by two sectors in standard guideline. Secondly, the roles of experts who participate in technology evaluation are important because of volatility of construction technology.

• Journal of Internet Computing and Services
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• v.15 no.6
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• pp.15-26
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• 2014

This study focus on a economic value of the Big Data technologies by real options model using big data technology company's stock price to determine the price of the economic value of incremental assessed value. For estimating stochastic process of company's stock price by big data technology to extract the incremental shares, Generalized Moments Method (GMM) are used. Option value for Black-Scholes partial differential equation was derived, in which finite difference numerical methods to obtain the Big Data technology was introduced to estimate the economic value. As a result, a option value of big data technology investment is 38.5 billion under assumption which investment cost is 50 million won and time value is a about 1 million, respectively. Thus, introduction of big data technology to create a substantial effect on corporate profits, is valuable and there are an effects on the additional time value. Sensitivity analysis of lower underlying asset value appear decreased options value and the lower investment cost showed increased options value. A volatility are not sensitive on the option value due to the big data technological characteristics which are low stock volatility and introduction periods.

• Journal of Energy Engineering
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• v.28 no.3
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• pp.42-54
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• 2019

The solar and wind power is spreading as a means to $CO_2$ reduction, but it has the characteristics of the volatility depending on the weather changes. This article aims to estimate the additional integration costs in Korea electric system in response to such volatility of increasing solar and wind power generation, using Korea electric power trading analyzer(KEPTA). The analysis utilizes the statistics of "8th Basic Plan for Long-term Electricity Supply and Demand" and "Renewable Energy Plan 3020". As the results, integration costs will be estimated 13.94Won/kWh~32.55Won/kWh, consisting of 8.94Won/kWh as back-up costs, 1.03Won/kWh~4.45Won/kWh as balancing costs, and 3.97Won/kWh~19.16Won/kWh as grid-costs. These results suggest that when the integration costs are secured, Korea electric system will be expected in the stable situation. This article leaves the further studies with taking the technological development of solar and wind power generation, the introduction of energy storage system, and wholesale price of electricity into consideration.

• Korea Trade Review
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• v.43 no.4
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• pp.155-175
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• 2018

This study estimates the technical efficiency and total factor productivity(TFP) of and analyzes the relationship between TFP and exports for Korean manufacturing companies from 2000 to 2016. Specially, TFP is decomposed into Technical Change(TC), Technical Efficiency Change (TEC), and Sale Effect(SE), and compared between large and small enterprises. First, in the case of technical efficiency, the Korean economy has been very vulnerable to external shocks, such as the sharp decline following the 2008 financial crisis. The efficiency of the electronics, automobile, and machinery sectors is low and needs to be improved. In addition, the technological efficiency of large enterprises is higher than that of SMEs in most manufacturing sub-sectors except for non-ferrous metals. In the case of TFP, most changes are due to TC, and the effective combination of labor, capital and the effect of scale have little effect, suggesting that improvement of internal structure is urgent. In addition, volatility due to the impact of the financial crisis in 2008 was much larger in SMEs than in large companies, so external economic impacts are more greater for SMEs than large enterprises. The relationship between TFP decomposition factors and exports shows that TC has a positive effect only on exports of SMEs. Therefore, in order to increase exports, in the case of SMEs, R&D support to promote technological development is needed. In the case of large companies, it is necessary to establish differentiated strategies for each export market, competitor company, and item to link efficiency and scale effect of exports.

• Korea Trade Review
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• v.43 no.3
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• pp.1-26
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• 2018

This study estimates the technical efficiency and total factor productivity(TFP) of and analyzes the relationship between TFP and exports for Korean manufacturing companies from 2000 to 2016. Specially, TFP is decomposed into Technical Change(TC), Technical Efficiency Change (TEC), and Sale Effect(SE), and compared between large and small enterprises. First, in the case of technical efficiency, the Korean economy has been very vulnerable to external shocks, such as the sharp decline following the 2008 financial crisis. The efficiency of the electronics, automobile, and machinery sectors is low and needs to be improved. In addition, the technological efficiency of large enterprises is higher than that of SMEs in most manufacturing sub-sectors except for non-ferrous metals. In the case of TFP, most changes are due to TC, and the effective combination of labor, capital and the effect of scale have little effect, suggesting that improvement of internal structure is urgent. In addition, volatility due to the impact of the financial crisis in 2008 was much larger in SMEs than in large companies, so external economic impacts are more greater for SMEs than large enterprises. The relationship between TFP decomposition factors and exports shows that TC has a positive effect only on exports of SMEs. Therefore, in order to increase exports, in the case of SMEs, R&D support to promote technological development is needed. In the case of large companies, it is necessary to establish differentiated strategies for each export market, competitor company, and item to link efficiency and scale effect of exports.

• Journal of Korean Elementary Science Education
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• v.43 no.1
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• pp.81-94
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• 2024

This study explores and conducts an in-depth comparison of the epistemic characteristics in different data types utilized in the science inquiries of preservice teachers regarding noise as a risk in everyday life. Focusing on primary and secondary data in the context of science inquiries about noise, we examined how these data types differ in science inquires in terms of inquiry design, data collection, and analyses. The findings reveal that sensor-based primary data enable direct measurement and observation of key phenomena. Conversely, secondary data rely on predetermined measurement methods within a public data system. These differences require different epistemic considerations during the inquiry process. Based on these findings, we discuss the educational implications concerning teaching approaches for science inquiries, teacher education for inquiry teaching, and the development of risk response competencies in preparation for the VUCA (Volatility, Uncertainty, Complexity, and Ambiguity) era.