38 research outputs found

    A Study on the Variability of EV Adoption in Modern Cities: Key Influencing Factors

    Get PDF
    ํ•™์œ„๋…ผ๋ฌธ(๋ฐ•์‚ฌ) -- ์„œ์šธ๋Œ€ํ•™๊ต๋Œ€ํ•™์› : ๊ณต๊ณผ๋Œ€ํ•™ ๊ฑด์„คํ™˜๊ฒฝ๊ณตํ•™๋ถ€, 2022.2. ์ •์ฐฝ๋ฌด.๋ณธ ์—ฐ๊ตฌ๋Š” ์ „๊ธฐ์ฐจ์˜ ๋ณด๊ธ‰ ์–‘์ƒ์— ๋”ฐ๋ฅธ ์ „๊ธฐ์ฐจ ๋ณด๊ธ‰ ๋ฐ ํ™•์‚ฐ์— ์˜ํ–ฅ์„ ์ฃผ๋Š” ์งยท๊ฐ„์ ‘์  ์š”์†Œ๋“ค๊ณผ ์š”์†Œ ๊ฐ„ ์ƒ๊ด€๊ด€๊ณ„ ๋ถ„์„์„ ํ†ตํ•ด ์ „๊ธฐ์ฐจ ๋ณด๊ธ‰ ๋ณ€๋™์„ฑ์„ ๊ทœ๋ช…ํ•˜๊ณ  ์žˆ์œผ๋ฉฐ ํ˜„๋Œ€๋„์‹œ ์‚ฌํšŒ ๊ด€์ ์—์„œ์˜ ์ „๊ธฐ์ฐจ ๋ณด๊ธ‰์„ ์ฆ๋Œ€ํ•˜๊ธฐ ์œ„ํ•œ ๋„์‹œ ์‚ฌํšŒ์˜ ์ •์ฑ…์ , ์‚ฌํšŒ์  ์˜์‚ฌ๊ฒฐ์ •์˜ ๋ฐฉํ–ฅ์„ฑ ์ œ์‹œํ•˜๊ณ  ์žˆ๋‹ค. ์ „๊ธฐ์ฐจ ๋ณด๊ธ‰ ๋ฐ ํ™•์‚ฐ๊ณผ ๊ด€๋ จ๋œ ๊ธฐ์กด ์—ฐ๊ตฌ๋“ค์€ ๋Œ€๋ถ€๋ถ„ ์ „๊ธฐ์ฐจ๋ฅผ ์ œํ’ˆ ๊ด€์ ์—์„œ ๊ตฌ๋งค๋ฅผ ์ด‰์ง„ ๋˜๋Š” ์žฅ๋ คํ•˜๊ธฐ ์œ„ํ•œ ์š”์ธ ๋ถ„์„๊ณผ ์ „๊ธฐ์ฐจ ๊ตฌ๋งค๋ฅผ ์ €ํ•ดํ•˜๋Š” ์š”์ธ ๋ถ„์„์— ์ค‘์ ์„ ๋‘์—ˆ๋‹ค. ๋˜ํ•œ, ๋ณด์กฐ๊ธˆ ์ •์ฑ…์˜ ํƒ€๋‹น์„ฑ, ์ถฉ์ „๊ธฐ๋ฐ˜์‹œ์„ค ์ ‘๊ทผ์„ฑ ๋“ฑ๊ณผ ๊ฐ™์€ ์ •์ฑ…์˜ ํšจ๊ณผ ๋ถ„์„์— ๋Œ€ํ•œ ๊ด‘๋ฒ”์œ„ํ•œ ๋…ผ์˜๋ฅผ ํ•˜๋ฉฐ ์ „๊ธฐ์ฐจ ๋ณด๊ธ‰์„ ์ฆ๊ฐ€์‹œํ‚ค๊ธฐ ์œ„ํ•œ ์ผ๋ฐ˜ํ™”๋œ ํ•ต์‹ฌ ์š”์ธ ์‹๋ณ„์„ ์‹œ๋„ํ•˜์˜€์œผ๋‚˜ ์ „๊ธฐ์ฐจ ๋ณด๊ธ‰ ์ดˆ๊ธฐ ์ƒํƒœ์—์„œ์˜ ์ „๊ธฐ์ฐจ ๊ตฌ๋งค์š”์ธ, ์ „๊ธฐ์ฐจ ๋ณด๊ธ‰ ์ €ํ•ด ๋˜๋Š” ์žฅ๋ ค ์š”์ธ ๋ฐ ๊ธฐํƒ€ ์ „๊ธฐ์ฐจ ๋ณด๊ธ‰ ์˜ํ–ฅ์š”์ธ๊ณผ ๊ด€๋ จ๋œ ์š”์ธ ๊ทœ๋ช…์— ๊ทธ์นœ ๋ฐ” ์žˆ๋‹ค. ๋”ฐ๋ผ์„œ ๊ฐœ๋ณ„๊ตญ๊ฐ€๋‚˜ ๋„์‹œ์˜ ์‚ฌํšŒยท๊ฒฝ์ œ์  ์„ฑ์ˆ™๋„ ์š”์ธ๊ณผ ๊ธฐ์ˆ ์  ์š”์ธ์— ์ „๊ธฐ์ฐจ ๋ณด๊ธ‰์— ์–ด๋–ค ์˜ํ–ฅ์„ ๋ฏธ์น˜๋ฉฐ, ๊ทธ์— ๋”ฐ๋ฅธ ์ •์ฑ…์  ์‹œ์‚ฌ์  ๋„์ถœ์—๋Š” ํ•œ๊ณ„๊ฐ€ ์žˆ์—ˆ๋‹ค. ๋ณธ ๋…ผ๋ฌธ์€ ๊ธฐ์กด ์—ฐ๊ตฌ์˜ ํ•œ๊ณ„๋ฅผ ๊ทน๋ณตํ•˜๊ธฐ ์œ„ํ•ด ์ „๊ธฐ์ฐจ ๋ณด๊ธ‰ ์ˆ˜์ค€๊ณผ ๊ฐœ๋ณ„๊ตญ๊ฐ€์˜ ์‚ฌํšŒ๊ฒฝ์ œ์  ์—ฌ๊ฑด์— ๋”ฐ๋ผ ์ „๊ธฐ์ฐจ ๋ณด๊ธ‰ ์žฅ๋ ค๋ฅผ ์œ„ํ•œ ์ž์›ํˆฌ์ž… ํšจ๊ณผ๊ฐ€ ๋‹ฌ๋ผ์งˆ ์ˆ˜ ์žˆ๋‹ค๋Š” ์ „์ œํ•˜์—์„œ ์ถœ๋ฐœํ•œ๋‹ค. ์ด๋ฅผ ์œ„ํ•ด, 18๊ฐœ ๊ตญ๊ฐ€๋ฅผ ๋Œ€์ƒ์œผ๋กœ 2010๋…„๋ถ€ํ„ฐ 2019๊นŒ์ง€ ์•ฝ 10๋…„๊ฐ„์˜ ๋ฐ์ดํ„ฐ๋ฅผ ๋ฐ”ํƒ•์œผ๋กœ ํŒจ๋„๋ฐ์ดํ„ฐ๋ฅผ ๊ตฌ์„ฑํ•˜๊ณ  ๊ตญ๊ฐ€๋ณ„ ์ „๊ธฐ์ฐจ ๋ณด๊ธ‰๋ฅ  ๋ณ€๋™๊ณผ ์‚ฌํšŒยท๊ฒฝ์ œ์  ์ •์ฑ…์š”์ธ๊ณผ ๊ธฐ์ˆ  ์ •์ฑ…์  ์š”์ธ ๊ฐ„์˜ ์ƒ๊ด€๊ด€๊ณ„๋ฅผ ์ด์šฉํ•˜์—ฌ ํŠน์ • ์‹œ์ , ํŠน์ • ๊ตญ๊ฐ€์˜ ์ „๊ธฐ์ฐจ ๋ณด๊ธ‰๋ฅ  ์–‘์ƒ์„ ๋Œ€๋ณ€ํ•  ์ˆ˜ ์žˆ๋Š” ๋ณ€์ด ๊ณ„์ˆ˜๋ฅผ ์กฐ์ž‘์ ์œผ๋กœ ์ •์˜ํ•˜์˜€๋‹ค. ์ด๋ฅผ ์ดˆ๊ธฐ, ์ถ”๊ฒฉ, ์„ฑ์ˆ™ ์ƒํƒœ์˜ 3๋‹จ๊ณ„๋กœ ๋ถ„๋ฅ˜ํ•˜์—ฌ ๊ทธ๋ฃน๋ณ„ ๋ณด๊ธ‰ ํŠน์„ฑ์„ ์„ค๋ช…ํ•˜๊ณ  ๊ทธ๋ฃน ๊ฐ„ ๋ณด๊ธ‰๋ฅ  ์„ฑ์žฅ์„ ์ด‰์ง„ํ•˜๋Š” ์š”์ธ์„ ๊ทœ๋ช…ํ•˜์˜€๋‹ค. ์ด๋ฅผ ํ†ตํ•ด, ๊ฐ ๊ตญ๊ฐ€์˜ ์ „๊ธฐ์ฐจ ๋ณด๊ธ‰์ƒํƒœ ๊ตฌ๊ฐ„(์ดˆ๊ธฐ, ์ถ”๊ฒฉ, ์„ฑ์žฅ)๋ณ„๋กœ ์ „๊ธฐ์ฐจ ๋ณด๊ธ‰์— ์˜ํ–ฅ์„ ์ฃผ๋Š” ์š”์ธ์˜ ์˜ํ–ฅ๋„ ๋ณ€ํ™” ๋ฐ ์š”์ธ์„ ๊ณ ๋ คํ•œ ์ •์ฑ…์ , ์‚ฌํšŒ์  ์ ์šฉ ๋ฐ ์ˆ˜์šฉ ๋ฐฉํ–ฅ์„ ์ œ์‹œํ•˜๋ฉฐ ์ „๊ธฐ์ฐจ, ์‚ฌ์šฉ์ž, ๋ฌผ๋ฆฌ์  ๊ณต๊ฐ„, ๋ผ์ดํ”„ ์Šคํƒ€์ผ ๋“ฑ๊ณผ ๊ฐ™์€ ์ „๊ธฐ์ฐจ๊ฐ€ ์šดํ–‰๋˜๋Š” ์ „์ฒด ์‚ฌ์ดํด ๊ด€์ ์—์„œ์˜ ์ „๊ธฐ์ฐจ ๋ณด๊ธ‰์ƒํƒœ ๋ฐ ์ž์›ํˆฌ์ž… ๋ฐฉ์•ˆ์— ๋Œ€ํ•œ ์ •์ฑ…์  ์‹œ์‚ฌ์ ์„ ์ œ์‹œํ•˜์˜€๋‹ค.This study researches the variability of electric vehicle (EV) adoption through regression analysis among direct and indirect factors influencing the adoption and diffusion of EVs. It also suggests the direction of urban policy and social decision-making to increase the adoption of EVs in modern urban society. Most of the existing studies that address the adoption and diffusion of EVs focused on factor analysis to encourage the adoption of EVs from a product perspective and factor analysis that hinders the purchase of EVs. Moreover, the existing studies extensively discussed the analysis of the effectiveness of policies such as the validity of subsidy policies and access to charging infrastructure and attempted to identify generalized key factors to increase the adoption of EVs. However, they have only identified factors related to purchase factors, obstacles or incentives, and other factors influencing the adoption of EVs in the initial state of electric vehicle supply. Therefore, there were limitations to formulating policies in accordance with socio-economic maturity factors and technical factors of individual countries or cities that affect the adoption of EVs and in deriving implication policies accordingly. In order to overcome the limitations of existing research, this paper starts with the assumption that the variable effect of resource input for promoting EV distribution depends on the current level of adoption and the socio-economic conditions of individual countries. To deep dive into the matter, panel data was constructed based on data from 2010 to 2019 for 18 countries. A coefficient of variation representing the pattern of EV adoption in a specific country was manipulated using the correlation between socio-economic policy factors and technical policy factors. By using the correlation between changes in EV adoption by countries, social and economic policy factors, and technological policy factors, a coefficient of variation that can represent the level of EV adoption in a specific country at a specific point in time is operationally defined. The 18 countries were divided into three stages: initial, pursuit, and maturity, explaining the distribution characteristics of each group, and identifying factors that promote the growth of the penetration rate between groups. Through this, changes in the influence of factors affecting the adoption for each country's EV supply status (initial, pursuit, growth) were revealed, and policy and social application, and acceptance directions were presented in consideration of the change factors. In addition, policy implications are presented on the adoption status of EVs and resource input methods from the perspective of the entire EV operating cycles, such as the number of EVs, users, physical space, and lifestyle.๋ชฉ ์ฐจ ์ œ 1 ์žฅ ์„œ๋ก  1 ์ œ 1 ์ ˆ ์—ฐ๊ตฌ์˜ ๋ฐฐ๊ฒฝ ๋ฐ ๋ชฉ์  1 ์ œ 2 ์ ˆ ์—ฐ๊ตฌ ๋‚ด์šฉ 9 1. ์—ฐ๊ตฌ ๋ฐฉ๋ฒ• 9 2. ๋…ผ๋ฌธ ๊ตฌ์„ฑ 10 ์ œ 2 ์žฅ ์„ ํ–‰์—ฐ๊ตฌ ๊ณ ์ฐฐ 12 ์ œ 1 ์ ˆ ์ „๊ธฐ์ฐจ ๋„์ž… ๋ฐฐ๊ฒฝ ๋ฐ ๊ตญ๋‚ด์™ธ ํ˜„ํ™ฉ 12 ์ œ 2 ์ ˆ ์ „๊ธฐ์ฐจ ๋ณด๊ธ‰ ๋ฐ ํ™•์‚ฐ ๊ด€๋ จ ์„ ํ–‰์—ฐ๊ตฌ 16 1. ์ƒˆ๋กœ์šด ์ œํ’ˆ ๊ด€์ ์—์„œ์˜ ์„ ํ–‰์—ฐ๊ตฌ 16 2. ์‚ฌํšŒ๊ฒฝ์ œ์  ์˜ํ–ฅ์š”์ธ ๊ด€์ ์—์„œ์˜ ์„ ํ–‰์—ฐ๊ตฌ 18 3. ๋„์‹œํ™” ๊ด€์ ์—์„œ์˜ ์„ ํ–‰์—ฐ๊ตฌ 21 4. ๊ธฐ์ˆ ์  ์˜ํ–ฅ์š”์ธ ๊ด€์ ์—์„œ์˜ ์„ ํ–‰์—ฐ๊ตฌ 23 ์ œ 3 ์žฅ ์—ฐ๊ตฌ ๊ฐ€์„ค ๋ฐ ์ฐจ๋ณ„์„ฑ 26 ์ œ 1 ์ ˆ ๊ธฐ์กด ์—ฐ๊ตฌ์˜ ํ•œ๊ณ„์„ฑ ๋ฐ ์—ฐ๊ตฌ ์ฐจ๋ณ„์„ฑ 26 ์ œ 2 ์ ˆ ๊ฐ€์„ค ์ˆ˜๋ฆฝ ๋ฐ ๊ฐœ๋… ์ •์˜ 28 ์ œ 3 ์ ˆ ์—ฐ๊ตฌ ๋ฒ”์œ„ ๋ฐ ๋Œ€์ƒ ์ •์˜ 33 ์ œ 4 ์žฅ ์—ฐ๊ตฌ ๋ถ„์„ ๊ฒฐ๊ณผ 41 ์ œ 1 ์ ˆ ๊ธ€๋กœ๋ฒŒ ์ „๊ธฐ์ž๋™์ฐจ ๋ถ„์„ 41 ์ œ 2 ์ ˆ ์ „๊ธฐ์ฐจ ๋ณด๊ธ‰๊ณผ ์ถฉ์ „๋ฐฉ์‹์— ๋Œ€ํ•œ ์—ฐ๊ด€์„ฑ 44 ์ œ 3 ์ ˆ ์ „๊ธฐ์ฐจ ๋ณด๊ธ‰๊ณผ ์†Œ๋“์— ๋Œ€ํ•œ ์—ฐ๊ด€์„ฑ 49 ์ œ 4 ์ ˆ ์ „๊ธฐ์ฐจ ๋ณด๊ธ‰๊ณผ ๋„์‹œํ™”์— ๋Œ€ํ•œ ์—ฐ๊ด€์„ฑ 54 ์ œ 5 ์ ˆ ์ „๊ธฐ์ฐจ ๋ณด๊ธ‰์— ๋Œ€ํ•œ ์ข…ํ•ฉ๋ถ„์„ ๊ฒฐ๊ณผ 58 ์ œ 5 ์žฅ ๊ฒฐ๋ก  ๋ฐ ๊ณ ์ฐฐ 68 ์ œ 1 ์ ˆ ๊ฒฐ๋ก  68 ์ œ 2 ์ ˆ ํ–ฅํ›„ ์—ฐ๊ตฌ ๋ฐฉํ–ฅ ๋ฐ ํ•œ๊ณ„์  72 ์ฐธ๊ณ ๋ฌธํ—Œ 74 ๋ถ€๋ก 89 Abstract 92 ๊ฐ์‚ฌ์˜ ๊ธ€ 95๋ฐ•

    (A) Study on Solid Phase Epitaxy and Selective Etching for Elevated Source/Drain Formation

    No full text
    Maste

    Wide loading rates ์„ ์ธ๊ฐ€ํ•  ์ˆ˜ ์žˆ๋Š” ๋‹ค๊ธฐ๋Šฅ ์œ ์ „์˜๋™ force spectroscopy์˜ ๊ธฐ์ˆ ๊ฐœ๋ฐœ

    No full text
    Dept. of Biomedical Engineering/์„์‚ฌThe simultaneous investigation of a large number of events with different types of intermolecular interactions, from non-equilibrium high-force pulling assay to quasi-equilibrium unbinding events inside the same environment, is very important issues for fully understanding intermolecular bond rupture mechanism. Here, we describe a novel dielectrophoretic force spectroscopy technique that utilizes micro-sized beads as multifunctional probes for parallel measurement of intermolecular forces with an extremely wide force rate (10-4pN/s-104pN/s) inside a microfluidic device. In our experiments, various forces, which broadly form the basis of all molecular interactions in order to establish that our approach can be used for wide range of applications, were measured across a range of force loading rates by multifunctional probes with various diameters with about 600 events per mm2, simultaneously and under the same environment. Furthermore, the individual bond rupture forces, parameters for the characterization of entire energy landscapes, and the effective stiffness of the force spectroscopy were determined using the measured results. This method of determining intermolecular forces could be very useful for the precise and simultaneous examination of various molecular interactions as it can be easily and cost-effectively implemented within a micro-fluidic device for a range of applications including immunoassays, molecular mechanics, chemical and biological screening, and mechanobiology.ope

    ์ง์ ‘ ์•Œ์ฝ”์˜ฌ ์—ฐ๋ฃŒ ์ „์ง€์˜ ์ „๊ทน ๋ฐ˜์‘์„ ์œ„ํ•œ ํ‘œ๋ฉด ๊ฐœ์งˆ ๊ธˆ ๋‚˜๋…ธ์ž…์ž

    No full text
    Thesis(doctor`s)--์„œ์šธ๋Œ€ํ•™๊ต ๋Œ€ํ•™์› :ํ™”ํ•™์ƒ๋ฌผ๊ณตํ•™๋ถ€,2007.Docto

    Correlation between perceptual evaluation(GRBAS and CAPE-V) and acoustic evaluation(MDVP) in women with vocal nodules

    No full text
    ์–ธ์–ด๋ณ‘๋ฆฌํ•™ ํ˜‘๋™๊ณผ์ •/์„์‚ฌ๋ณธ ์—ฐ๊ตฌ์˜ ๋ชฉ์ ์€ ์—ฌ์„ฑ ์„ฑ๋Œ€๊ฒฐ์ ˆ ํ™˜์ž๋ฅผ ๋Œ€์ƒ์œผ๋กœ GRBAS์™€ CAPE-V์˜ ์ธก์ •์น˜๋ฅผ ๊ฐ๊ฐ MDVP์™€ ์ƒ๊ด€๊ด€๊ณ„๋ฅผ ๋น„๊ตํ•˜์—ฌ GRBAS์™€ CAPE-V๊ฐ€ ์ฒญ์ง€๊ฐ์  ํ‰๊ฐ€๋„๊ตฌ๋กœ์„œ ๊ฐ€์ง€๋Š” ์ž„์ƒ์ ์ธ ํŠน์„ฑ์„ ์‚ดํŽด๋ณด๋Š”๋ฐ ์žˆ๋‹ค. ๋ณธ ์—ฐ๊ตฌ์—์„œ๋Š” ์–ธ์–ด์น˜๋ฃŒ์‚ฌ์™€ ๋Œ€ํ•™์›์ƒ(์ดํ•˜ ํ•™์ƒ)์ด 39๋ช…์— ํ•ด๋‹นํ•˜๋Š” ํ™˜์ž๊ตฐ์˜ ์Œ์„ฑ์„ GRBAS์™€ CAPE-V๋กœ ๊ฐ๊ฐ ์ฒญ์ง€๊ฐ์  ํ‰๊ฐ€๋ฅผ ์ง„ํ–‰ํ•˜์˜€๋‹ค. ์–ธ์–ด์น˜๋ฃŒ์‚ฌ์™€ ํ•™์ƒ์˜ ํ‰๊ฐ€ ๊ฒฐ๊ณผ๋ฅผ ๋น„๊ตํ•จ์œผ๋กœ์จ GRBAS์™€ CAPE-V๊ฐ€ ํ‰๊ฐ€๊ฒฝํ—˜์— ๋”ฐ๋ฅธ ์‹ ๋ขฐ๋„์˜ ์ฐจ์ด๋„ ์‚ดํŽด๋ณด๊ณ ์ž ํ•˜์˜€๋‹ค. ์—ฐ๊ตฌ ๊ฒฐ๊ณผ, GRBAS, CAPE-V์˜ ์‹ ๋ขฐ๋„๋Š” ๋ชจ๋‘ ์‹ ๋ขฐํ•  ๋งŒํ•œ ์ˆ˜์ค€์ด์—ˆ์ง€๋งŒ CAPE-V๊ฐ€ MDVP์™€์˜ ์ƒ๊ด€๊ด€๊ณ„์—์„œ ์œ ์˜ํ•œ ํ•ญ๋ชฉ์ด ๋” ๋งŽ์•˜๊ณ  ์ƒ๊ด€๊ณ„์ˆ˜๋„ ๋” ๋‹ค์–‘ํ•˜๊ฒŒ ๋‚˜ํƒ€๋‚ฌ๋‹ค. ๊ทธ๋ฆฌ๊ณ  CAPE-V๋Š” ์ƒ๋Œ€์ ์œผ๋กœ GRBAS๋ณด๋‹ค ํ‰๊ฐ€ ๊ฒฝํ—˜์— ๋”ฐ๋ผ ์‹ ๋ขฐ๋„์— ์˜ํ–ฅ์„ ๋ฐ›์•˜๋‹ค. ๊ฒฐ๋ก ์ ์œผ๋กœ CAPE-V๋Š” GRBAS๋ณด๋‹ค ํ™˜์ž์˜ ์Œ์„ฑ์„ ์„ธ๋ฐ€ํ•˜๊ฒŒ ํ‰๊ฐ€ํ•  ์ˆ˜ ์žˆ์—ˆ๊ณ  ๋‹ค๊ฐ์ ์œผ๋กœ ํ‰๊ฐ€ํ•  ์ˆ˜ ์žˆ์—ˆ์œผ๋‚˜ ์ฒญ์ง€๊ฐ์  ํ‰๊ฐ€๊ฒฝํ—˜์— ๋”ฐ๋ผ ๊ฒฐ๊ณผ์— ์˜ํ–ฅ์„ ๋” ๋งŽ์ด ๋ฐ›์•˜๋‹ค. ๋”ฐ๋ผ์„œ ์ดˆ๋ณด์Œ์„ฑ์น˜๋ฃŒ์‚ฌ๊ฐ€ ์ฒญ์ง€๊ฐ์  ํ‰๊ฐ€๋ฅผ ์ง„ํ–‰ํ•  ๋•Œ ์‹ ๋ขฐ๋„ ๋†’์€ ๊ฒฐ๊ณผ๋ฅผ ์–ป๊ธฐ ์œ„ํ•ด์„œ๋Š” CAPE-V๋ณด๋‹ค GRBAS๋ฅผ ์‚ฌ์šฉํ•˜๋Š” ๊ฒƒ์ด ๋ฐ”๋žŒ์งํ•˜๋ฉฐ ํ‰๊ฐ€๊ฒฝํ—˜์ด ๋งŽ์€ ํ‰๊ฐ€์ž๋ผ ํ• ์ง€๋ผ๋„ CAPE-V์— ๋Œ€ํ•œ ์ˆ™๋ จ๋„์— ๋”ฐ๋ผ ๊ฒฐ๊ณผ๊ฐ€ ๋‹ฌ๋ผ์งˆ ์ˆ˜ ์žˆ์œผ๋ฏ€๋กœ GRBAS์™€ CAPE-V๋ฅผ ํ•จ๊ป˜ ์‚ฌ์šฉํ•˜๋Š” ๊ฒƒ์ด ์ด์ƒ์ ์ธ ์ฒญ์ง€๊ฐ์  ํ‰๊ฐ€๊ฐ€ ๋  ๊ฒƒ์ด๋‹ค.ope

    Real Options Valuation ๊ธฐ๋ฒ•์„ ์ด์šฉํ•œ ํœด๋Œ€ ์ธํ„ฐ๋„ท ์‚ฌ์—…์˜ ๊ฒฝ์ œ์„ฑ ํ‰๊ฐ€์— ๊ด€ํ•œ ์—ฐ๊ตฌ

    No full text
    ํ•™์œ„๋…ผ๋ฌธ(์„์‚ฌ)--์„œ์šธ๋Œ€ํ•™๊ต ๋Œ€ํ•™์› :์‚ฐ์—…๊ณตํ•™๊ณผ,2006.Maste

    A Study on the Variability of EV Adoption in Modern Cities: Key Influencing Factors

    Get PDF
    ๋ณธ ์—ฐ๊ตฌ๋Š” ์ „๊ธฐ์ฐจ์˜ ๋ณด๊ธ‰ ์–‘์ƒ์— ๋”ฐ๋ฅธ ์ „๊ธฐ์ฐจ ๋ณด๊ธ‰ ๋ฐ ํ™•์‚ฐ์— ์˜ํ–ฅ์„ ์ฃผ๋Š” ์งยท๊ฐ„์ ‘์  ์š”์†Œ๋“ค๊ณผ ์š”์†Œ ๊ฐ„ ์ƒ๊ด€๊ด€๊ณ„ ๋ถ„์„์„ ํ†ตํ•ด ์ „๊ธฐ์ฐจ ๋ณด๊ธ‰ ๋ณ€๋™์„ฑ์„ ๊ทœ๋ช…ํ•˜๊ณ  ์žˆ์œผ๋ฉฐ ํ˜„๋Œ€๋„์‹œ ์‚ฌํšŒ ๊ด€์ ์—์„œ์˜ ์ „๊ธฐ์ฐจ ๋ณด๊ธ‰์„ ์ฆ๋Œ€ํ•˜๊ธฐ ์œ„ํ•œ ๋„์‹œ ์‚ฌํšŒ์˜ ์ •์ฑ…์ , ์‚ฌํšŒ์  ์˜์‚ฌ๊ฒฐ์ •์˜ ๋ฐฉํ–ฅ์„ฑ ์ œ์‹œํ•˜๊ณ  ์žˆ๋‹ค. ์ „๊ธฐ์ฐจ ๋ณด๊ธ‰ ๋ฐ ํ™•์‚ฐ๊ณผ ๊ด€๋ จ๋œ ๊ธฐ์กด ์—ฐ๊ตฌ๋“ค์€ ๋Œ€๋ถ€๋ถ„ ์ „๊ธฐ์ฐจ๋ฅผ ์ œํ’ˆ ๊ด€์ ์—์„œ ๊ตฌ๋งค๋ฅผ ์ด‰์ง„ ๋˜๋Š” ์žฅ๋ คํ•˜๊ธฐ ์œ„ํ•œ ์š”์ธ ๋ถ„์„๊ณผ ์ „๊ธฐ์ฐจ ๊ตฌ๋งค๋ฅผ ์ €ํ•ดํ•˜๋Š” ์š”์ธ ๋ถ„์„์— ์ค‘์ ์„ ๋‘์—ˆ๋‹ค. ๋˜ํ•œ, ๋ณด์กฐ๊ธˆ ์ •์ฑ…์˜ ํƒ€๋‹น์„ฑ, ์ถฉ์ „๊ธฐ๋ฐ˜์‹œ์„ค ์ ‘๊ทผ์„ฑ ๋“ฑ๊ณผ ๊ฐ™์€ ์ •์ฑ…์˜ ํšจ๊ณผ ๋ถ„์„์— ๋Œ€ํ•œ ๊ด‘๋ฒ”์œ„ํ•œ ๋…ผ์˜๋ฅผ ํ•˜๋ฉฐ ์ „๊ธฐ์ฐจ ๋ณด๊ธ‰์„ ์ฆ๊ฐ€์‹œํ‚ค๊ธฐ ์œ„ํ•œ ์ผ๋ฐ˜ํ™”๋œ ํ•ต์‹ฌ ์š”์ธ ์‹๋ณ„์„ ์‹œ๋„ํ•˜์˜€์œผ๋‚˜ ์ „๊ธฐ์ฐจ ๋ณด๊ธ‰ ์ดˆ๊ธฐ ์ƒํƒœ์—์„œ์˜ ์ „๊ธฐ์ฐจ ๊ตฌ๋งค์š”์ธ, ์ „๊ธฐ์ฐจ ๋ณด๊ธ‰ ์ €ํ•ด ๋˜๋Š” ์žฅ๋ ค ์š”์ธ ๋ฐ ๊ธฐํƒ€ ์ „๊ธฐ์ฐจ ๋ณด๊ธ‰ ์˜ํ–ฅ์š”์ธ๊ณผ ๊ด€๋ จ๋œ ์š”์ธ ๊ทœ๋ช…์— ๊ทธ์นœ ๋ฐ” ์žˆ๋‹ค. ๋”ฐ๋ผ์„œ ๊ฐœ๋ณ„๊ตญ๊ฐ€๋‚˜ ๋„์‹œ์˜ ์‚ฌํšŒยท๊ฒฝ์ œ์  ์„ฑ์ˆ™๋„ ์š”์ธ๊ณผ ๊ธฐ์ˆ ์  ์š”์ธ์— ์ „๊ธฐ์ฐจ ๋ณด๊ธ‰์— ์–ด๋–ค ์˜ํ–ฅ์„ ๋ฏธ์น˜๋ฉฐ, ๊ทธ์— ๋”ฐ๋ฅธ ์ •์ฑ…์  ์‹œ์‚ฌ์  ๋„์ถœ์—๋Š” ํ•œ๊ณ„๊ฐ€ ์žˆ์—ˆ๋‹ค. ๋ณธ ๋…ผ๋ฌธ์€ ๊ธฐ์กด ์—ฐ๊ตฌ์˜ ํ•œ๊ณ„๋ฅผ ๊ทน๋ณตํ•˜๊ธฐ ์œ„ํ•ด ์ „๊ธฐ์ฐจ ๋ณด๊ธ‰ ์ˆ˜์ค€๊ณผ ๊ฐœ๋ณ„๊ตญ๊ฐ€์˜ ์‚ฌํšŒ๊ฒฝ์ œ์  ์—ฌ๊ฑด์— ๋”ฐ๋ผ ์ „๊ธฐ์ฐจ ๋ณด๊ธ‰ ์žฅ๋ ค๋ฅผ ์œ„ํ•œ ์ž์›ํˆฌ์ž… ํšจ๊ณผ๊ฐ€ ๋‹ฌ๋ผ์งˆ ์ˆ˜ ์žˆ๋‹ค๋Š” ์ „์ œํ•˜์—์„œ ์ถœ๋ฐœํ•œ๋‹ค. ์ด๋ฅผ ์œ„ํ•ด, 18๊ฐœ ๊ตญ๊ฐ€๋ฅผ ๋Œ€์ƒ์œผ๋กœ 2010๋…„๋ถ€ํ„ฐ 2019๊นŒ์ง€ ์•ฝ 10๋…„๊ฐ„์˜ ๋ฐ์ดํ„ฐ๋ฅผ ๋ฐ”ํƒ•์œผ๋กœ ํŒจ๋„๋ฐ์ดํ„ฐ๋ฅผ ๊ตฌ์„ฑํ•˜๊ณ  ๊ตญ๊ฐ€๋ณ„ ์ „๊ธฐ์ฐจ ๋ณด๊ธ‰๋ฅ  ๋ณ€๋™๊ณผ ์‚ฌํšŒยท๊ฒฝ์ œ์  ์ •์ฑ…์š”์ธ๊ณผ ๊ธฐ์ˆ  ์ •์ฑ…์  ์š”์ธ ๊ฐ„์˜ ์ƒ๊ด€๊ด€๊ณ„๋ฅผ ์ด์šฉํ•˜์—ฌ ํŠน์ • ์‹œ์ , ํŠน์ • ๊ตญ๊ฐ€์˜ ์ „๊ธฐ์ฐจ ๋ณด๊ธ‰๋ฅ  ์–‘์ƒ์„ ๋Œ€๋ณ€ํ•  ์ˆ˜ ์žˆ๋Š” ๋ณ€์ด ๊ณ„์ˆ˜๋ฅผ ์กฐ์ž‘์ ์œผ๋กœ ์ •์˜ํ•˜์˜€๋‹ค. ์ด๋ฅผ ์ดˆ๊ธฐ, ์ถ”๊ฒฉ, ์„ฑ์ˆ™ ์ƒํƒœ์˜ 3๋‹จ๊ณ„๋กœ ๋ถ„๋ฅ˜ํ•˜์—ฌ ๊ทธ๋ฃน๋ณ„ ๋ณด๊ธ‰ ํŠน์„ฑ์„ ์„ค๋ช…ํ•˜๊ณ  ๊ทธ๋ฃน ๊ฐ„ ๋ณด๊ธ‰๋ฅ  ์„ฑ์žฅ์„ ์ด‰์ง„ํ•˜๋Š” ์š”์ธ์„ ๊ทœ๋ช…ํ•˜์˜€๋‹ค. ์ด๋ฅผ ํ†ตํ•ด, ๊ฐ ๊ตญ๊ฐ€์˜ ์ „๊ธฐ์ฐจ ๋ณด๊ธ‰์ƒํƒœ ๊ตฌ๊ฐ„(์ดˆ๊ธฐ, ์ถ”๊ฒฉ, ์„ฑ์žฅ)๋ณ„๋กœ ์ „๊ธฐ์ฐจ ๋ณด๊ธ‰์— ์˜ํ–ฅ์„ ์ฃผ๋Š” ์š”์ธ์˜ ์˜ํ–ฅ๋„ ๋ณ€ํ™” ๋ฐ ์š”์ธ์„ ๊ณ ๋ คํ•œ ์ •์ฑ…์ , ์‚ฌํšŒ์  ์ ์šฉ ๋ฐ ์ˆ˜์šฉ ๋ฐฉํ–ฅ์„ ์ œ์‹œํ•˜๋ฉฐ ์ „๊ธฐ์ฐจ, ์‚ฌ์šฉ์ž, ๋ฌผ๋ฆฌ์  ๊ณต๊ฐ„, ๋ผ์ดํ”„ ์Šคํƒ€์ผ ๋“ฑ๊ณผ ๊ฐ™์€ ์ „๊ธฐ์ฐจ๊ฐ€ ์šดํ–‰๋˜๋Š” ์ „์ฒด ์‚ฌ์ดํด ๊ด€์ ์—์„œ์˜ ์ „๊ธฐ์ฐจ ๋ณด๊ธ‰์ƒํƒœ ๋ฐ ์ž์›ํˆฌ์ž… ๋ฐฉ์•ˆ์— ๋Œ€ํ•œ ์ •์ฑ…์  ์‹œ์‚ฌ์ ์„ ์ œ์‹œํ•˜์˜€๋‹ค.This study researches the variability of electric vehicle (EV) adoption through regression analysis among direct and indirect factors influencing the adoption and diffusion of EVs. It also suggests the direction of urban policy and social decision-making to increase the adoption of EVs in modern urban society. Most of the existing studies that address the adoption and diffusion of EVs focused on factor analysis to encourage the adoption of EVs from a product perspective and factor analysis that hinders the purchase of EVs. Moreover, the existing studies extensively discussed the analysis of the effectiveness of policies such as the validity of subsidy policies and access to charging infrastructure and attempted to identify generalized key factors to increase the adoption of EVs. However, they have only identified factors related to purchase factors, obstacles or incentives, and other factors influencing the adoption of EVs in the initial state of electric vehicle supply. Therefore, there were limitations to formulating policies in accordance with socio-economic maturity factors and technical factors of individual countries or cities that affect the adoption of EVs and in deriving implication policies accordingly. In order to overcome the limitations of existing research, this paper starts with the assumption that the variable effect of resource input for promoting EV distribution depends on the current level of adoption and the socio-economic conditions of individual countries. To deep dive into the matter, panel data was constructed based on data from 2010 to 2019 for 18 countries. A coefficient of variation representing the pattern of EV adoption in a specific country was manipulated using the correlation between socio-economic policy factors and technical policy factors. By using the correlation between changes in EV adoption by countries, social and economic policy factors, and technological policy factors, a coefficient of variation that can represent the level of EV adoption in a specific country at a specific point in time is operationally defined. The 18 countries were divided into three stages: initial, pursuit, and maturity, explaining the distribution characteristics of each group, and identifying factors that promote the growth of the penetration rate between groups. Through this, changes in the influence of factors affecting the adoption for each country's EV supply status (initial, pursuit, growth) were revealed, and policy and social application, and acceptance directions were presented in consideration of the change factors. In addition, policy implications are presented on the adoption status of EVs and resource input methods from the perspective of the entire EV operating cycles, such as the number of EVs, users, physical space, and lifestyle.๋ชฉ ์ฐจ ์ œ 1 ์žฅ ์„œ๋ก  1 ์ œ 1 ์ ˆ ์—ฐ๊ตฌ์˜ ๋ฐฐ๊ฒฝ ๋ฐ ๋ชฉ์  1 ์ œ 2 ์ ˆ ์—ฐ๊ตฌ ๋‚ด์šฉ 9 1. ์—ฐ๊ตฌ ๋ฐฉ๋ฒ• 9 2. ๋…ผ๋ฌธ ๊ตฌ์„ฑ 10 ์ œ 2 ์žฅ ์„ ํ–‰์—ฐ๊ตฌ ๊ณ ์ฐฐ 12 ์ œ 1 ์ ˆ ์ „๊ธฐ์ฐจ ๋„์ž… ๋ฐฐ๊ฒฝ ๋ฐ ๊ตญ๋‚ด์™ธ ํ˜„ํ™ฉ 12 ์ œ 2 ์ ˆ ์ „๊ธฐ์ฐจ ๋ณด๊ธ‰ ๋ฐ ํ™•์‚ฐ ๊ด€๋ จ ์„ ํ–‰์—ฐ๊ตฌ 16 1. ์ƒˆ๋กœ์šด ์ œํ’ˆ ๊ด€์ ์—์„œ์˜ ์„ ํ–‰์—ฐ๊ตฌ 16 2. ์‚ฌํšŒ๊ฒฝ์ œ์  ์˜ํ–ฅ์š”์ธ ๊ด€์ ์—์„œ์˜ ์„ ํ–‰์—ฐ๊ตฌ 18 3. ๋„์‹œํ™” ๊ด€์ ์—์„œ์˜ ์„ ํ–‰์—ฐ๊ตฌ 21 4. ๊ธฐ์ˆ ์  ์˜ํ–ฅ์š”์ธ ๊ด€์ ์—์„œ์˜ ์„ ํ–‰์—ฐ๊ตฌ 23 ์ œ 3 ์žฅ ์—ฐ๊ตฌ ๊ฐ€์„ค ๋ฐ ์ฐจ๋ณ„์„ฑ 26 ์ œ 1 ์ ˆ ๊ธฐ์กด ์—ฐ๊ตฌ์˜ ํ•œ๊ณ„์„ฑ ๋ฐ ์—ฐ๊ตฌ ์ฐจ๋ณ„์„ฑ 26 ์ œ 2 ์ ˆ ๊ฐ€์„ค ์ˆ˜๋ฆฝ ๋ฐ ๊ฐœ๋… ์ •์˜ 28 ์ œ 3 ์ ˆ ์—ฐ๊ตฌ ๋ฒ”์œ„ ๋ฐ ๋Œ€์ƒ ์ •์˜ 33 ์ œ 4 ์žฅ ์—ฐ๊ตฌ ๋ถ„์„ ๊ฒฐ๊ณผ 41 ์ œ 1 ์ ˆ ๊ธ€๋กœ๋ฒŒ ์ „๊ธฐ์ž๋™์ฐจ ๋ถ„์„ 41 ์ œ 2 ์ ˆ ์ „๊ธฐ์ฐจ ๋ณด๊ธ‰๊ณผ ์ถฉ์ „๋ฐฉ์‹์— ๋Œ€ํ•œ ์—ฐ๊ด€์„ฑ 44 ์ œ 3 ์ ˆ ์ „๊ธฐ์ฐจ ๋ณด๊ธ‰๊ณผ ์†Œ๋“์— ๋Œ€ํ•œ ์—ฐ๊ด€์„ฑ 49 ์ œ 4 ์ ˆ ์ „๊ธฐ์ฐจ ๋ณด๊ธ‰๊ณผ ๋„์‹œํ™”์— ๋Œ€ํ•œ ์—ฐ๊ด€์„ฑ 54 ์ œ 5 ์ ˆ ์ „๊ธฐ์ฐจ ๋ณด๊ธ‰์— ๋Œ€ํ•œ ์ข…ํ•ฉ๋ถ„์„ ๊ฒฐ๊ณผ 58 ์ œ 5 ์žฅ ๊ฒฐ๋ก  ๋ฐ ๊ณ ์ฐฐ 68 ์ œ 1 ์ ˆ ๊ฒฐ๋ก  68 ์ œ 2 ์ ˆ ํ–ฅํ›„ ์—ฐ๊ตฌ ๋ฐฉํ–ฅ ๋ฐ ํ•œ๊ณ„์  72 ์ฐธ๊ณ ๋ฌธํ—Œ 74 ๋ถ€๋ก 89 Abstract 92 ๊ฐ์‚ฌ์˜ ๊ธ€ 95๋ฐ•
    corecore