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Yoonmo Koo
Graduate School of Engineering Practice & Technology Management, Economics, and Policy Program, Seoul National University, Gwanakro 1, Gwanak-Gu, Seoul 08826, South Korea

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Journal article
Published: 20 February 2021 in Transportation Research Part D: Transport and Environment
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Quantifying environmental benefits from battery electric vehicles (BEVs) requires an understanding of the long-term substitutional relationships among different vehicle technologies. This study analyzes how BEV promotion can contribute to reductions in particulate matter (PM) emissions in Korea and investigates effective long-term policy options. Using a choice model, this study simulates consumers’ vehicle replacement behavior under various policy scenarios from 2018 to 2025. The results show that BEV promotion alone has limited effectiveness at reducing PM emissions because BEV purchases were predominantly made by gasoline vehicle owners while diesel vehicles are the key source of emissions. This finding is significant because investment in BEV promotion in Korea specifies PM emissions reductions as their core objective and legal basis. Investigation of additional policy options suggests that the combination of direct regulations on diesel vehicles and a targeted rebate to promote substitution between diesel vehicles and BEVs can reduce PM emissions by ~13%.

ACS Style

Hyunhong Choi; Yoonmo Koo. Effectiveness of battery electric vehicle promotion on particulate matter emissions reduction. Transportation Research Part D: Transport and Environment 2021, 93, 102758 .

AMA Style

Hyunhong Choi, Yoonmo Koo. Effectiveness of battery electric vehicle promotion on particulate matter emissions reduction. Transportation Research Part D: Transport and Environment. 2021; 93 ():102758.

Chicago/Turabian Style

Hyunhong Choi; Yoonmo Koo. 2021. "Effectiveness of battery electric vehicle promotion on particulate matter emissions reduction." Transportation Research Part D: Transport and Environment 93, no. : 102758.

Journal article
Published: 27 August 2020 in Energy
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Improving efficiency is an important option for reducing manufacturing sector emissions. More efficient technologies reduce energy use and emissions. However, efficiency improvements can induce unexpected effects known as rebound effects. Although previous studies have analyzed these effects, these studies fail to precisely evaluate the rebound effects due to improvements in technology efficiency. Bottom-up models are appropriate for analyzing efficiency improvements at the technology level, but they face limitations in exploring output changes because they usually assume that demand is given. In contrast, top-down models are appropriate for observing output changes in an efficiency-improving sector and in the rest of the economy, but they face limitations in explicitly describing technological changes. This study therefore constructs a hybrid model to overcome the limitations of both types of models and evaluates the impacts of climate policy in Korea’s manufacturing sector when rebound effects are considered. The expected emissions reduction due to new technology adoption in the manufacturing sector is 23.8 million tons CO2eq without rebound effects, but when rebound effects are included, the actual emission reduction (12.7 million tons CO2eq) is about 50% of the expected amount.

ACS Style

Hwarang Lee; Sung Won Kang; Yoonmo Koo. A hybrid energy system model to evaluate the impact of climate policy on the manufacturing sector: Adoption of energy-efficient technologies and rebound effects. Energy 2020, 212, 118718 .

AMA Style

Hwarang Lee, Sung Won Kang, Yoonmo Koo. A hybrid energy system model to evaluate the impact of climate policy on the manufacturing sector: Adoption of energy-efficient technologies and rebound effects. Energy. 2020; 212 ():118718.

Chicago/Turabian Style

Hwarang Lee; Sung Won Kang; Yoonmo Koo. 2020. "A hybrid energy system model to evaluate the impact of climate policy on the manufacturing sector: Adoption of energy-efficient technologies and rebound effects." Energy 212, no. : 118718.

Journal article
Published: 18 August 2020 in Energies
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This research attempts to evaluate the impact of renewable electricity generation mix on economic growth and CO2 emissions in Iran from 1980 to 2016. In this regard, by using EViews 10, the Structural Vector Autoregressive model (SVAR) is estimated by imposing the Blanchard and Quah long-run restrictions. The yearly data on real Gross Domestic Production (GDP), the share of electricity generation from renewable sources, and carbon dioxide emissions (CO2) caused by liquid, solid, and gaseous fuels were used. The positive impact of one standard deviation shock of increasing the share of renewable electricity on economic growth was confirmed by using Impulse Response Function (IRF). Contrary to the expectation, the share of renewable electricity in the energy mix is not at a desirable level to lower CO2 emissions, which partly could be explained by the dominant role of fossil fuel in Iran (as an energy-driven country). Moreover, the findings of Variance Decomposition (VD) verified the low share of electricity generated by renewable energy in explaining forecast error variations in economic growth and CO2 emissions. It indicates that in this stage of development, increasing the share of renewable electricity could not be considered as an appropriate strategy to control environmental issues. Therefore, initiating and implementing environmental policies could be considered as the most proper policies to lower CO2 emissions and to achieve the goal of sustainable development.

ACS Style

Bahareh Oryani; Yoonmo Koo; Shahabaldin Rezania. Structural Vector Autoregressive Approach to Evaluate the Impact of Electricity Generation Mix on Economic Growth and CO2 Emissions in Iran. Energies 2020, 13, 4268 .

AMA Style

Bahareh Oryani, Yoonmo Koo, Shahabaldin Rezania. Structural Vector Autoregressive Approach to Evaluate the Impact of Electricity Generation Mix on Economic Growth and CO2 Emissions in Iran. Energies. 2020; 13 (16):4268.

Chicago/Turabian Style

Bahareh Oryani; Yoonmo Koo; Shahabaldin Rezania. 2020. "Structural Vector Autoregressive Approach to Evaluate the Impact of Electricity Generation Mix on Economic Growth and CO2 Emissions in Iran." Energies 13, no. 16: 4268.

Journal article
Published: 27 June 2020 in Energy Policy
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While renewable energy is an eco-friendly source of electricity, it can be difficult to garner local acceptance when securing sites for renewable energy projects. Local acceptance is an important factor in determining the success of these projects. To elicit local acceptance, governments can consider profit-sharing, in which project developers pay a subsidy to the locals to compensate for the inconvenience of a renewable energy facility. The purpose of this study is to analyze local acceptance levels for photovoltaic and wind power projects in Korea and to evaluate the impact of profit-sharing on the profitability of such projects. Contingent valuation is used to estimate willingness to accept for a baseline renewable energy project. A choice experiment is conducted to estimate a marginal willingness to accept for project attributes. These are combined to simulate the total willingness to accept needed to gain local acceptance. Total willingness to accept for baseline photovoltaic and wind power projects are, respectively, USD 13,815 and USD 27,587 per household for 5 years. Internal rate of return is employed to assess the profitability of such projects. This rate without profit-sharing ranges from 4.49% to 9.50%. Meanwhile, the rate with profit-sharing ranges from −1.67% to 7.64%.

ACS Style

Kyung Jae Kim; Hwarang Lee; Yoonmo Koo. Research on local acceptance cost of renewable energy in South Korea: A case study of photovoltaic and wind power projects. Energy Policy 2020, 144, 111684 .

AMA Style

Kyung Jae Kim, Hwarang Lee, Yoonmo Koo. Research on local acceptance cost of renewable energy in South Korea: A case study of photovoltaic and wind power projects. Energy Policy. 2020; 144 ():111684.

Chicago/Turabian Style

Kyung Jae Kim; Hwarang Lee; Yoonmo Koo. 2020. "Research on local acceptance cost of renewable energy in South Korea: A case study of photovoltaic and wind power projects." Energy Policy 144, no. : 111684.

Journal article
Published: 12 February 2020 in Technological Forecasting and Social Change
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Along with the rapid evolution of mobile communication services, popularization of smartphones, and increase in traffic service usage, data traffic has also grown rapidly. Anticipating massive data traffic growth owing to the launch of the fifth-generation (5 G) mobile communication service in 2019, this study analyzes and forecasts: 1) the number of 5 G users using a logistic model, 2) consumer preference for 5 G services using a mixed logit model, and 3) 5 G data traffic increase using sensitivity analysis. The results indicate that data traffic would rapidly increase for 5 G services: the number of 5 G users is estimated to be 1.560 million by 2019, which will increase to 3.475 million by 2020 and 37.340 million by the end of 2025. Data traffic growth is predicted to reach 46 PB by the end of 2019, 129 PB by 2020, and 342 PB by 2021, after which it is projected to rapidly rise to 1,343 PB by 2022 and to 6,340 PB by 2025. The findings of this study provide a reference point for annual investment and marketing strategies of communication companies.

ACS Style

Hyungsup Shin; Jiyeon Jung; Yoonmo Koo. Forecasting the video data traffic of 5 G services in south korea. Technological Forecasting and Social Change 2020, 153, 119948 .

AMA Style

Hyungsup Shin, Jiyeon Jung, Yoonmo Koo. Forecasting the video data traffic of 5 G services in south korea. Technological Forecasting and Social Change. 2020; 153 ():119948.

Chicago/Turabian Style

Hyungsup Shin; Jiyeon Jung; Yoonmo Koo. 2020. "Forecasting the video data traffic of 5 G services in south korea." Technological Forecasting and Social Change 153, no. : 119948.

Journal article
Published: 13 May 2019 in Energies
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The building sector is considered to be important for Korean energy issues as it accounts for approximately 20% of Korea’s final energy consumption. As one of Korea’s passive strategies in its emission reduction plan is reducing energy consumption through improvements in energy efficiency because the energy loss mostly occurs from window sets, this study aims to examine the preferences and role of the energy efficiency level of window sets in South Korea. Given that the lifespan of a building exceeds 20 years, a building’s energy efficiency significantly impacts accumulated energy savings. However, window sets affect not only energy efficiency, but also the interior appearance of the building; therefore, it is important to understand consumer preferences and to examine their effect on building energy reduction accordingly. Using a mixed logit model, this study analyzes window set preferences and energy savings. As a result, this study determines that consumers consider the energy efficiency level to be the second most important factor in determining window preference, following the cost of the window. In addition, this study found that the marginal willingness to pay for efficiency level 2 window sets compared to level 3 window sets is USD 1256. For level 1 window sets, this figure increases to USD 3140. Further, a scenario analysis is conducted to analyze the government incentive program’s effectiveness in encouraging consumers to purchasing higher energy efficiency more efficient products, and thus in promoting the eco-friendly consumption of in households. Taking into consideration of households’ willingness to pay and cost saving amount for using energy efficient window sets, the optimal value of government incentives of is found to be approximately USD 700 is found to be optimal.

ACS Style

Kwan Byum Maeng; Jiyeon Jung; Yoonmo Koo. Quantitative Analysis of Consumer Preferences of Windows Set in South Korea: The Role of Energy Efficiency Levels. Energies 2019, 12, 1816 .

AMA Style

Kwan Byum Maeng, Jiyeon Jung, Yoonmo Koo. Quantitative Analysis of Consumer Preferences of Windows Set in South Korea: The Role of Energy Efficiency Levels. Energies. 2019; 12 (9):1816.

Chicago/Turabian Style

Kwan Byum Maeng; Jiyeon Jung; Yoonmo Koo. 2019. "Quantitative Analysis of Consumer Preferences of Windows Set in South Korea: The Role of Energy Efficiency Levels." Energies 12, no. 9: 1816.

Research article
Published: 23 April 2019 in Climate Policy
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Most countries implementing an emissions trading system (ETS), such as EU member states, California in the US, or South Korea, are generally targeting large sized companies, which consume energy above a specific threshold. However, previous studies using computable general equilibrium (CGE) models have analyzed climate policies without considering company size. This may have led to inaccurate results because the impacts of climate policy would differ depending on the coverage of regulated companies. Accordingly, this study examines the environmental and economic impacts of greenhouse gas emission reduction policies, assuming policy results vary by firm size, as covered by the Korean emission trading system. To this end, a CGE model with a separate social accounting matrix based on company size is used to compare three scenarios that reflect different types of carbon pricing methods. The results show that greenhouse gases will be reduced to a lower extent and utility will decrease more if mitigation policies are only imposed to large companies.

ACS Style

Yoonmo Koo; Yoonha Lee; Yong-Gun Kim. The differentiated impact of emissions trading system based on company size. Climate Policy 2019, 19, 923 -936.

AMA Style

Yoonmo Koo, Yoonha Lee, Yong-Gun Kim. The differentiated impact of emissions trading system based on company size. Climate Policy. 2019; 19 (7):923-936.

Chicago/Turabian Style

Yoonmo Koo; Yoonha Lee; Yong-Gun Kim. 2019. "The differentiated impact of emissions trading system based on company size." Climate Policy 19, no. 7: 923-936.

Journal article
Published: 04 February 2019 in Energy
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The bottom-up model of the industrial energy system has hitherto been analyzed using linear programming. However, it has limitations in describing practical technology selection and reproducing base-year technology selection. Positive mathematical programming, which provides an interior solution without any subjective constraints, can be considered as an alternative method that overcomes the limitations of linear programming when constructing a bottom-up model of the industry sector. The purpose of this study is to apply positive mathematical programming and identify the plausibility of using it in a forward-looking optimization model of the industry sector. A bottom-up model based on positive mathematical programming has the advantages of avoiding impractical technology selection in the industry sector, describing more flexible reactions to external changes, and calibrating base-year technology selection without subjective constraints. Although optimal solutions and simulation responses are dependent on parameter identification, the dependence of positive mathematical programming on the identification method can be lower than that of linear programming on the subjective constraints.

ACS Style

Hwarang Lee; Jiyong Eom; Cheolhung Cho; Yoonmo Koo. A bottom-up model of industrial energy system with positive mathematical programming. Energy 2019, 173, 679 -690.

AMA Style

Hwarang Lee, Jiyong Eom, Cheolhung Cho, Yoonmo Koo. A bottom-up model of industrial energy system with positive mathematical programming. Energy. 2019; 173 ():679-690.

Chicago/Turabian Style

Hwarang Lee; Jiyong Eom; Cheolhung Cho; Yoonmo Koo. 2019. "A bottom-up model of industrial energy system with positive mathematical programming." Energy 173, no. : 679-690.

Journal article
Published: 10 September 2018 in Sustainability
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In this study, we analyzed the effects of electricity market reform on investment in generation facilities. We used the data of 27 OECD member countries and considered ownership structure, horizontal and vertical unbundling, change of transaction method, and government regulation as explanatory variables for market reform. We used four regression models, in which we examined the effects of market reform on the capacity of generation facilities, supply reserve ratio, total investment, and base-load share, respectively. For each panel regression model, we performed a Hausman test to identify the model between random effect and fixed effect. Based on the estimation results, we found that electricity market reform has a negative effect on generation facilities in most countries. Both privatization and regulation have negative impacts on the generation facility and base-load share. On the other hand, the level of liberalization of transactions have positive effects on the generation facility, supply reserve ratio, and base-load share. The empirical analysis also showed that horizontal unbundling does not have a meaningful effect on investment, but vertical unbundling contributes to increasing the supply reserve ratio.

ACS Style

Juyong Lee; Youngsang Cho; Yoonmo Koo; Chansoo Park. Effects of Market Reform on Facility Investment in Electric Power Industry: Panel Data Analysis of 27 Countries. Sustainability 2018, 10, 3235 .

AMA Style

Juyong Lee, Youngsang Cho, Yoonmo Koo, Chansoo Park. Effects of Market Reform on Facility Investment in Electric Power Industry: Panel Data Analysis of 27 Countries. Sustainability. 2018; 10 (9):3235.

Chicago/Turabian Style

Juyong Lee; Youngsang Cho; Yoonmo Koo; Chansoo Park. 2018. "Effects of Market Reform on Facility Investment in Electric Power Industry: Panel Data Analysis of 27 Countries." Sustainability 10, no. 9: 3235.

Journal article
Published: 19 July 2018 in Telematics and Informatics
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A B2B transaction is a transaction between organizations. However, the ripple effects of a B2B transaction can reach the members of the organization and generate additional economic impact. Enterprise LTE (Long term evolution) is a newly introduced B2B service in the South Korean telecommunications market. While it provides secure and fast telecommunications services to businesses, it can also affect the employees’ utility in the business, since the service provider can provide a variety of additional services to employees who use the same telecommunications provider for their mobile devices. In this study, we empirically analyze how B2B and Enterprise LTE services affect consumer churn-in in the telecommunications market. We estimate consumer benefit based on the additional services provided after the introduction of the B2B service using conjoint analysis. We also estimate consumer switching cost for changing one’s mobile telecommunications service provider using contingent valuation method. By comparing these values, we analyze the switching probability of employees when B2B services are introduced at their workplace. The results show that in order to maximize revenue, considering the revenue gained from new subscribers and from fees for providing additional services, lowering service fees for additional services and maximizing market share are advisable.

ACS Style

Hyunsong Lee; Hyunhong Choi; Yoonmo Koo. Lowering customer’s switching cost using B2B services for telecommunication companies. Telematics and Informatics 2018, 35, 2054 -2066.

AMA Style

Hyunsong Lee, Hyunhong Choi, Yoonmo Koo. Lowering customer’s switching cost using B2B services for telecommunication companies. Telematics and Informatics. 2018; 35 (7):2054-2066.

Chicago/Turabian Style

Hyunsong Lee; Hyunhong Choi; Yoonmo Koo. 2018. "Lowering customer’s switching cost using B2B services for telecommunication companies." Telematics and Informatics 35, no. 7: 2054-2066.

Journal article
Published: 05 April 2018 in Ecological Economics
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Because the social benefit generated from a public facility varies according to its accessibility, population density of location, local income level, local taste, and the existence of similar nearby facilities, the value of facilities can vary depending on their location. Therefore, determining the ideal location is an important problem. This study provides a new direction for solving this problem by combining the contingent valuation (CV) method and nested partitions (NP) algorithm using siting of public arboretums as an example. First, consumers' willingness to pay for environmental facilities considering household characteristics and distance to both newly built and existing facilities are estimated using the CV method. In this process, consumers are divided into two groups (active and passive users), assuming they have different willingness to pay for the facilities. Then, using the results of the CV, the NP algorithm, a simulation-based discrete optimization technique, is constructed to efficiently identify optimal locations that maximize social benefit considering regional characteristics. The results of the proposed algorithm exceeded the performance of the benchmark case, and this study's findings can be used to aid decisions about complicated multiple facility locations. Moreover, visualized results are provided, which can be useful for local and central decision makers.

ACS Style

Hyunhong Choi; Yoonmo Koo. Using Contingent Valuation and Numerical Methods to Determine Optimal Locations for Environmental Facilities: Public Arboretums in South Korea. Ecological Economics 2018, 149, 184 -201.

AMA Style

Hyunhong Choi, Yoonmo Koo. Using Contingent Valuation and Numerical Methods to Determine Optimal Locations for Environmental Facilities: Public Arboretums in South Korea. Ecological Economics. 2018; 149 ():184-201.

Chicago/Turabian Style

Hyunhong Choi; Yoonmo Koo. 2018. "Using Contingent Valuation and Numerical Methods to Determine Optimal Locations for Environmental Facilities: Public Arboretums in South Korea." Ecological Economics 149, no. : 184-201.

Journal article
Published: 17 February 2018 in Sustainability
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This study examines the environmental impacts of roundtrip car sharing services by investigating transportation behavior. Car sharing should contribute to reduced greenhouse gas GHG emissions; however, such schemes include both positive and negative environmental effects, including: (1) reduced CO2e (carbon dioxide equivalent) from substituting private vehicle use for more fuel-efficient car sharing vehicles, (2) increased CO2e as car-less individuals switch from public transit to car sharing vehicles and (3) reduced CO2e due to fewer vehicles. This study examines the impacts of this modal shift on greenhouse gas (GHG) emissions using three types of models: a mixed logit model to analyze car sharing service preferences; a binary logit model to analyze whether individuals are willing to forgo vehicle ownership or planned purchases to use car sharing services; and a linear regression to determine how much private vehicle or public transportation use would be replaced by car sharing and the resulting effects on mobility. Total emissions from the current car sharing market equal 1,025,589.36 t CO2e/year. However, an increase in electric vehicle (EV) charging stations to 50% of the number of gasoline-fuel stations would increase the probability of electric car sharing vehicle use, thereby reducing emissions by 655,773 t CO2e. This study shows that forgoing vehicle purchases does not offset the increased GHG emissions caused by the shift from public transportation or private vehicle use to car sharing.

ACS Style

Jiyeon Jung; Yoonmo Koo. Analyzing the Effects of Car Sharing Services on the Reduction of Greenhouse Gas (GHG) Emissions. Sustainability 2018, 10, 539 .

AMA Style

Jiyeon Jung, Yoonmo Koo. Analyzing the Effects of Car Sharing Services on the Reduction of Greenhouse Gas (GHG) Emissions. Sustainability. 2018; 10 (2):539.

Chicago/Turabian Style

Jiyeon Jung; Yoonmo Koo. 2018. "Analyzing the Effects of Car Sharing Services on the Reduction of Greenhouse Gas (GHG) Emissions." Sustainability 10, no. 2: 539.

Book chapter
Published: 24 September 2013 in Springer Texts in Business and Economics
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In the mid-twentieth century, Fisher (1939) and Clark (1940) classified industry into primary, secondary, and tertiary production, which served as the basis of the International Standard Industrial Classification. However, some have criticized Fisher and Clark’s classification as too simple to account for the heterogeneity in tertiary production (i.e., the service industry). By using EU KLEMS and Organisation of Economic Co-operation and Development data, we suggest a new industrial classification based on value-creation behavior that helps explain economic development. In the new paradigm, industry is divided into value-creation sectors composed of base and extended value as well as transferred value industries comprised of production support service, private service, and public service components. The new industrial classification can inform an efficient industrial policy designed to accelerate economic growth.

ACS Style

Tai-Yoo Kim; Yoonmo Koo; Dong Ook Choi; Yeonbae Kim. The Necessity of a New Industrial Classification Based on Value-Creation Behavior. Springer Texts in Business and Economics 2013, 293 -308.

AMA Style

Tai-Yoo Kim, Yoonmo Koo, Dong Ook Choi, Yeonbae Kim. The Necessity of a New Industrial Classification Based on Value-Creation Behavior. Springer Texts in Business and Economics. 2013; ():293-308.

Chicago/Turabian Style

Tai-Yoo Kim; Yoonmo Koo; Dong Ook Choi; Yeonbae Kim. 2013. "The Necessity of a New Industrial Classification Based on Value-Creation Behavior." Springer Texts in Business and Economics , no. : 293-308.