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    Development of the Integrated Optimization Model of

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    ํ•™์œ„๋…ผ๋ฌธ (๋ฐ•์‚ฌ)-- ์„œ์šธ๋Œ€ํ•™๊ต ๋Œ€ํ•™์› ๊ณต๊ณผ๋Œ€ํ•™ ์—๋„ˆ์ง€์‹œ์Šคํ…œ๊ณตํ•™๋ถ€, 2017. 8. ๊ฐ•์ฃผ๋ช….์šฐ๋ฆฌ๋‚˜๋ผ์˜ ํ’๋ ฅ๋ฐœ์ „์€ ์ •๋ถ€์™€ ์ง€์ž์ฒด์˜ ๋†’์€ ๊ด€์‹ฌ์—๋„ ๋ถˆ๊ตฌํ•˜๊ณ  ๋น„๊ณผํ•™์ ์ธ ์ž…์ง€์„ ์ •๊ณผ ํ’๋ ฅ์ž์›์˜ ์ฒด๊ณ„์ ์ธ ํ™œ์šฉํ™” ๊ณ„ํš์˜ ๋ฏธ๋น„๋กœ ์ž„๊ธฐ์‘๋ณ€์‹ ์†Œ๊ทœ๋ชจ ํ’๋ ฅ๋‹จ์ง€์กฐ์„ฑ ๋ฐ ์‹ค์ฆ๋‹จ๊ณ„์— ๋จธ๋ฌผ๋Ÿฌ ์žˆ๋‹ค. ์ด ์—ฐ๊ตฌ๋Š” ๊ตญ๋‚ด ํ’๋ ฅ์˜ ์ž์›ํ™”์— ์˜ํ–ฅ์„ ๋ฏธ์น˜๋Š” ์ธ์ž์ธ ๋ฐ”๋žŒ์˜ ๋ฒกํ„ฐ์  ํŠน์„ฑ, ๊ณ„ํ†ต์—ฐ๊ณ„, ์ง€๋ฆฌ์  ํŠน์„ฑ ๋ฐ ๊ฒฝ์ œ์„ฑ์œผ๋กœ ํŠน์„ฑํ™”ํ•˜์—ฌ ๊ฐ ์ธ์ž๋“ค์„ ์ธ๊ณต์‹ ๊ฒฝ๋ง ๊ธฐ๋ฒ•์— ๋ณ‘ํ•ฉํ•˜๋Š” ๋ชจ๋ธ์„ ๊ฐœ๋ฐœํ•˜์˜€๋‹ค. ์ธ๊ณต์‹ ๊ฒฝ๋ง ํ•™์Šต์„ ํ†ตํ•ด ํ’๋ ฅ์ž์›์ด ์šฐ์ˆ˜ํ•œ ์ง€์—ญ์„ ์„ ๋ณ„ํ•˜์—ฌ ์ž์›๋ถ„ํฌ๋„๋ฅผ ์ œ์‹œํ•˜์˜€๋‹ค. ๋ถ„ํฌ๋„์—์„œ ํ™•์ธํ•œ ํ’๋ ฅ๋ฐœ์ „ ์œ ๋ง์œ„์น˜์— ๋”ฐ๋ผ ์ตœ๋Œ€์˜ ๊ฒฝ์ œ์„ฑ์„ ํ™•๋ณดํ•˜๊ธฐ ์œ„ํ•œ ๋‹จ์ง€๊ทœ๋ชจ, ๊ณ„ํ†ต์—ฐ๊ณ„ ๋ฐฉ์•ˆ, ํ’๋ ฅํ„ฐ๋นˆ์˜ ์ข…๋ฅ˜๋ฅผ ์ตœ์ ํ™”ํ•˜๋Š” ํ†ตํ•ฉ์‹œ์Šคํ…œ์„ ๊ตฌ์ถ•ํ•˜์˜€๋‹ค. ํ†ตํ•ฉ์‹œ์Šคํ…œ์€ ํ’๋ ฅ์‚ฌ์—… ์ตœ์ ํ™” ์ธ์ž๋“ค๊ฐ„์˜ ๋ฏผ๊ฐ๋„๋ถ„์„์„ ํ†ตํ•ด ๊ฐ์ข… ์ฃผ์š”์ธ์ž๋ฅผ ์ •๋Ÿ‰ํ™”ํ•˜๊ณ  ๊ฒฝ์ œ์„ฑ ๋ถ„์„ ํ”„๋กœ๊ทธ๋žจ๊ณผ ์—ฐ๋™ํ•  ์ˆ˜ ์žˆ๋„๋ก ๊ตฌ์„ฑํ•˜์˜€๋‹ค. ํ†ตํ•ฉ ์ตœ์ ํ™”์‹œ์Šคํ…œ์˜ ๊ฒ€์ฆ์€ ํ˜„์žฌ ํƒ€๋‹น์„ฑํ‰๊ฐ€ ํ›„ ํ’๋ ฅ๋‹จ์ง€๊ฐ€ ๊ฑด์„ค ์ค‘์ธ ์ „๋‚จ ์‹ ์•ˆ๊ตฐ 100MW๊ธ‰ ์œก์ƒํ’๋ ฅ์„ ๋Œ€์ƒ์œผ๋กœ ์ˆ˜ํ–‰ํ•˜์˜€๋‹ค. ํ†ตํ•ฉ ์‹œ์Šคํ…œ์˜ ์ตœ์ ์„ค๊ณ„์•ˆ์€ ๊ฒ€์ฆ ๋Œ€์ƒ์˜ ๋‹จ์ง€๊ทœ๋ชจ, ๊ณ„ํ†ต์—ฐ๊ณ„ ๋ฐฉ์•ˆ์„ ๋™์ผํ•˜๊ฒŒ ์ œ์‹œํ•˜์˜€์„ ๋ฟ๋งŒ ์•„๋‹ˆ๋ผ ๊ธฐ๋Œ€ ๋‚ด๋ถ€์ˆ˜์ต์œจ๊ณผ ์ˆœํ˜„๊ฐ€๋Š” ์•ฝ 4%์ด๋‚ด์˜ ์˜ค์ฐจ๋ฅผ ๋ณด์ž„์œผ๋กœ์จ ํ˜„์žฅ ์ ์šฉ์„ฑ์„ ๊ฒ€์ฆํ•˜์˜€๋‹ค. ์‚ฌ์—…์ดˆ๊ธฐ ๋‹จ๊ณ„์ธ 40MW๊ธ‰ ์œก์ƒํ’๋ ฅ(์ „๋‚จ ์ž์šด๋„)๊ณผ 100MW๊ธ‰ ํ•ด์ƒํ’๋ ฅ(์ œ์ฃผ ํ•œ๊ฒฝ๋ฉด)์„ ๋Œ€์ƒ์œผ๋กœ ์ตœ์ ํ™” ์„ค๊ณ„๋ฅผ ์ˆ˜ํ–‰ํ•˜์˜€๋‹ค. ์ „๋‚จ ์ž์šด๋„๋Š” 100MW๊ธ‰์œผ๋กœ ํ’๋ ฅ๋‹จ์ง€๋ฅผ ํ™•๋Œ€ํ•œ๋‹ค๋ฉด 40MW๊ธ‰ ๊ธฐ์กด ๊ณ„ํš๋ณด๋‹ค 1.5%๊ฐ€๋Ÿ‰ ๋‚ด๋ถ€ ์ˆ˜์ต์œจ์ด ํ–ฅ์ƒ๋  ์ˆ˜ ์žˆ์„ ๊ฒƒ์œผ๋กœ ๋ถ„์„๋˜์—ˆ๋‹ค. ์ œ์ฃผ ํ•œ๊ฒฝ๋ฉด ํ•ด์ƒํ’๋ ฅ์˜ ๊ฒฝ์šฐ, ๋‹จ์ง€๊ทœ๋ชจ๋Š” ์ ์ •ํ•˜์ง€๋งŒ ํ’๋ ฅํ„ฐ๋นˆ์˜ ์ข…๋ฅ˜์™€ ์„ค์น˜๊ฐœ์ˆ˜๋ฅผ ๊ฐœ์„ ํ•จ์œผ๋กœ์จ ๊ฒฝ์ œ์„ฑ์„ ํ–ฅ์ƒ์‹œํ‚ฌ ์ˆ˜ ์žˆ์—ˆ๋‹ค. ๊ฐœ๋ฐœํ•œ ํ’๋ ฅ๋ฐœ์ „ ํ†ตํ•ฉ ์ตœ์ ํ™”์‹œ์Šคํ…œ์„ ์ด์šฉํ•˜์—ฌ ์†Œ๊ทœ๋ชจ(100MW๊ธ‰), ๋Œ€๊ทœ๋ชจ(400MW๊ธ‰) ํ’๋ ฅ๋‹จ์ง€์— ์ ํ•ฉํ•œ ์ง€์—ญ์„ ์„ ๋ณ„ํ•˜๊ณ  ์ตœ์  ์„ค๊ณ„๋ฅผ ์‹ค์‹œํ•˜์˜€๋‹ค. ์†Œ๊ทœ๋ชจ ํ’๋ ฅ๋‹จ์ง€๋Š” ์ „๋‚จ ํ•ด์ƒ๊ณผ ์ œ์ฃผ ์œก์ƒ์ด ๊ฐ€์žฅ ์œ ๋งํ•˜๊ณ  ๊ฐ๊ฐ 13.5%์™€ 16.1%์˜ ๋†’์€ ๋‚ด๋ถ€์ˆ˜์ต์œจ์„ ๊ธฐ๋Œ€ํ•  ์ˆ˜ ์žˆ๋‹ค. ๋Œ€๊ทœ๋ชจ ํ’๋ ฅ๋‹จ์ง€๋Š” ์ „๋‚จ ํ•ด์ƒ์—์„œ 12.2%์˜ ๋‚ด๋ถ€์ˆ˜์ต์œจ์„ ํ™•๋ณดํ•  ์ˆ˜ ์žˆ์„ ๊ฒƒ์œผ๋กœ ํ‰๊ฐ€๋˜์—ˆ๋‹ค. ์ด ์—ฐ๊ตฌ์—์„œ ๊ฐœ๋ฐœํ•œ ์ธ๊ณต์‹ ๊ฒฝ๋ง ๊ธฐ๋ฐ˜์˜ ํ†ตํ•ฉ ์‹œ์Šคํ…œ์€ ํŠน์ • ์ง€์—ญ์—์„œ ๊ฐ€์žฅ ํšจ์œจ์ ์ธ ์ตœ์ ํ™” ํ’๋ ฅ์‚ฌ์—… ๋ชจ๋ธ์„ ์ œ์‹œํ•  ๋ฟ๋งŒ ์•„๋‹ˆ๋ผ, ํ˜„์žฌ ์šด์˜ ์ค‘์ด๊ฑฐ๋‚˜ ๊ณ„ํš ์ค‘์ธ ํ’๋ ฅ์‚ฌ์—…์˜ ๊ฐœ์„ ์ ์„ ์ œ์‹œํ•˜๊ณ  ํ–ฅํ›„ ์šฐ๋ฆฌ๋‚˜๋ผ ํ’๋ ฅ์ž์›์„ ์ฒด๊ณ„ํ™”ํ•˜๋Š” ์ฃผ์š”ํ•œ ๋„๊ตฌ๋กœ ํ™œ์šฉํ•  ์ˆ˜ ์žˆ๋‹ค.๋ชฉ ์ฐจ ์ดˆ ๋กโ€ฆโ€ฆโ€ฆโ€ฆโ€ฆโ€ฆโ€ฆโ€ฆโ€ฆโ€ฆโ€ฆโ€ฆโ€ฆโ€ฆโ€ฆโ€ฆโ€ฆโ€ฆโ€ฆโ€ฆโ€ฆโ€ฆโ€ฆโ€ฆโ€ฆโ€ฆโ€ฆโ…  List of Tables..โ€ฆโ€ฆโ€ฆโ€ฆโ€ฆโ€ฆโ€ฆโ€ฆโ€ฆโ€ฆโ€ฆโ€ฆโ€ฆโ€ฆโ€ฆโ€ฆโ€ฆโ€ฆโ€ฆโ€ฆโ€ฆโ€ฆโ€ฆโ…ฃ List of Figures.โ€ฆโ€ฆโ€ฆโ€ฆโ€ฆโ€ฆโ€ฆโ€ฆโ€ฆโ€ฆโ€ฆโ€ฆโ€ฆโ€ฆโ€ฆโ€ฆโ€ฆโ€ฆโ€ฆโ€ฆโ€ฆโ€ฆโ€ฆโ€ฆโ…ฅ 1. ์„œ๋ก โ€ฆโ€ฆโ€ฆโ€ฆโ€ฆโ€ฆโ€ฆโ€ฆโ€ฆโ€ฆโ€ฆโ€ฆโ€ฆโ€ฆโ€ฆโ€ฆโ€ฆโ€ฆโ€ฆโ€ฆโ€ฆโ€ฆโ€ฆโ€ฆโ€ฆโ€ฆโ€ฆโ€ฆโ€ฆ1 2. ์ด๋ก ์  ๋ฐฐ๊ฒฝโ€ฆโ€ฆโ€ฆโ€ฆโ€ฆโ€ฆโ€ฆโ€ฆโ€ฆโ€ฆโ€ฆโ€ฆโ€ฆโ€ฆโ€ฆโ€ฆโ€ฆโ€ฆโ€ฆโ€ฆโ€ฆโ€ฆโ€ฆโ€ฆโ€ฆโ€ฆโ€ฆ9 2.1 ์ƒ์šฉ์†Œํ”„ํŠธ์›จ์–ด WAsP์„ ํ†ตํ•œ ํ’๋ ฅ๋ฐœ์ „ ๋ชจ๋ธ๋งโ€ฆโ€ฆโ€ฆโ€ฆโ€ฆโ€ฆ9 2.2 ์ธ๊ณต์‹ ๊ฒฝ๋ง(ANN)โ€ฆโ€ฆโ€ฆโ€ฆโ€ฆโ€ฆโ€ฆโ€ฆโ€ฆโ€ฆโ€ฆโ€ฆโ€ฆโ€ฆโ€ฆโ€ฆโ€ฆโ€ฆโ€ฆโ€ฆโ€ฆโ€ฆโ€ฆ16 2.3 ํ’๋ ฅ๋ฐœ์ „์‚ฌ์—… ๊ฒฝ์ œ์„ฑ ๋ถ„์„โ€ฆโ€ฆโ€ฆโ€ฆโ€ฆโ€ฆโ€ฆโ€ฆโ€ฆโ€ฆโ€ฆโ€ฆโ€ฆโ€ฆโ€ฆโ€ฆโ€ฆโ€ฆ19 3. ์—ฐ๊ตฌ ๋ฐฉ๋ฒ•โ€ฆโ€ฆโ€ฆโ€ฆโ€ฆโ€ฆโ€ฆโ€ฆโ€ฆโ€ฆโ€ฆโ€ฆโ€ฆโ€ฆโ€ฆโ€ฆโ€ฆโ€ฆโ€ฆโ€ฆโ€ฆโ€ฆโ€ฆโ€ฆโ€ฆโ€ฆโ€ฆ23 3.1 ์ž๋ฃŒ ์ˆ˜์ง‘ ๋ฐ ํ†ตํ•ฉโ€ฆโ€ฆโ€ฆโ€ฆโ€ฆโ€ฆโ€ฆโ€ฆโ€ฆโ€ฆโ€ฆโ€ฆโ€ฆโ€ฆโ€ฆโ€ฆโ€ฆโ€ฆโ€ฆโ€ฆโ€ฆโ€ฆ.23 3.2 ์ตœ์  ํ’๋ ฅ๋ฐœ์ „์‚ฌ์—… ์„ ์ •โ€ฆโ€ฆโ€ฆโ€ฆโ€ฆโ€ฆโ€ฆโ€ฆโ€ฆโ€ฆโ€ฆโ€ฆโ€ฆโ€ฆโ€ฆโ€ฆโ€ฆโ€ฆโ€ฆ33 3.3 ์ธ๊ณต์‹ ๊ฒฝ๋ง์„ ํ™œ์šฉํ•œ ํ’๋ ฅ๋ฐœ์ „ ์œ ๋ง์ง€์—ญ ์„ ๋ณ„โ€ฆโ€ฆโ€ฆโ€ฆโ€ฆโ€ฆ38 3.4 ๊ฐœ๋ฐœ๋œ ํ’๋ ฅ๋ฐœ์ „์‚ฌ์—… ์ตœ์ ํ™” ์‹œ์Šคํ…œโ€ฆโ€ฆโ€ฆโ€ฆโ€ฆโ€ฆโ€ฆโ€ฆโ€ฆโ€ฆโ€ฆโ€ฆ49 4. ์‚ฌ๋ก€๋ถ„์„ ๋ฐ ์ตœ์ ํ™”โ€ฆโ€ฆโ€ฆโ€ฆโ€ฆโ€ฆโ€ฆโ€ฆโ€ฆโ€ฆโ€ฆโ€ฆโ€ฆโ€ฆโ€ฆโ€ฆโ€ฆโ€ฆโ€ฆโ€ฆโ€ฆโ€ฆ58 4.1 ์‚ฌ๋ก€๋ถ„์„โ€ฆโ€ฆโ€ฆโ€ฆโ€ฆโ€ฆโ€ฆโ€ฆโ€ฆโ€ฆโ€ฆโ€ฆโ€ฆโ€ฆโ€ฆโ€ฆโ€ฆโ€ฆโ€ฆโ€ฆโ€ฆโ€ฆโ€ฆโ€ฆโ€ฆโ€ฆโ€ฆโ€ฆโ€ฆ58 4.2 ํ’๋ ฅ๋ฐœ์ „ ํ†ตํ•ฉ์ตœ์ ํ™”โ€ฆโ€ฆโ€ฆโ€ฆโ€ฆโ€ฆโ€ฆโ€ฆโ€ฆโ€ฆโ€ฆโ€ฆโ€ฆโ€ฆโ€ฆโ€ฆโ€ฆโ€ฆโ€ฆโ€ฆโ€ฆ90 5. ๊ฒฐ๋ก โ€ฆโ€ฆโ€ฆโ€ฆโ€ฆโ€ฆโ€ฆโ€ฆโ€ฆโ€ฆโ€ฆโ€ฆโ€ฆโ€ฆโ€ฆโ€ฆโ€ฆโ€ฆโ€ฆโ€ฆโ€ฆโ€ฆโ€ฆโ€ฆโ€ฆโ€ฆโ€ฆโ€ฆโ€ฆโ€ฆ98 ๋ถ€๋ก A. ์ธ๊ณต์‹ ๊ฒฝ๋ง ๊ธฐ๋ฐ˜ ํ”„๋ก์‹œ ๋ชจ๋ธ ๋ถ„์„.โ€ฆ.โ€ฆโ€ฆ.โ€ฆโ€ฆโ€ฆโ€ฆโ€ฆโ€ฆโ€ฆโ€ฆโ€ฆ105 ๋ถ€๋ก B. ๊ฐœ๋ฐœ๋œ ์‹œ์Šคํ…œ๊ณผ ๊ธฐ์กด ์‚ฌ์—…์„ฑ๋ถ„์„ ๊ฒฐ๊ณผ ์˜ค์ฐจ ๋ถ„์„โ€ฆโ€ฆโ€ฆโ€ฆ109 Abstractโ€ฆโ€ฆโ€ฆโ€ฆโ€ฆโ€ฆโ€ฆโ€ฆโ€ฆโ€ฆโ€ฆ..โ€ฆโ€ฆโ€ฆโ€ฆโ€ฆโ€ฆโ€ฆโ€ฆโ€ฆ.โ€ฆโ€ฆโ€ฆ.โ€ฆโ€ฆโ€ฆโ€ฆโ€ฆโ€ฆโ€ฆโ€ฆโ€ฆ113Docto

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    ๋…ธํŠธ : KRIHS FOCUS: ๊ตญํ† ์—ฐ๊ตฌ์› ์†Œ

    ์ˆ˜์—ด๋ฐ˜์‘์„ ํ†ตํ•œ ํƒ„์†Œ ์‹œํŠธ ํ•ฉ์„ฑ

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    ํ•™์œ„๋…ผ๋ฌธ (์„์‚ฌ)-- ์„œ์šธ๋Œ€ํ•™๊ต ๋Œ€ํ•™์› : ๊ธฐ๊ณ„ํ•ญ๊ณต๊ณตํ•™๋ถ€, 2016. 8. ๊น€์šฉํ˜‘.์‚ฐํ™” ๊ทธ๋ž˜ํ•€(Graphene oxide)์€ ํƒ„์†Œ ์›์ž๊ฐ€ ์„œ๋กœ ๊ณต์œ ๊ฒฐํ•ฉ์„ ํ•œ ์ƒํƒœ๋กœ ์œก๊ฐํ˜•์˜ ๊ฒฉ์ž ๊ตฌ์กฐ๋ฅผ ์ด๋ฃจ๊ณ  ์›์ž ํ•œ ์ธต์˜ ์–‡์€ ๋‘๊ป˜๋ฅผ ๊ฐ€์ง„ 2์ฐจ์› ๋ฌผ์งˆ์ด๋ฉฐ, ํ‘œ๋ฉด์— ๋‹ค์–‘ํ•œ ์‚ฐ์†Œ ๊ธฐ๋Šฅ๊ธฐ๋ฅผ ๊ฐ€์ง„ ํ™”ํ•™์  ๊ตฌ์กฐ๋ฅผ ๊ฐ€์ง„๋‹ค. ์ด๋Ÿฐ ํŠน์ง•์— ๊ธฐ์ธํ•˜์—ฌ ์‚ฐํ™” ๊ทธ๋ž˜ํ•€์€ ๋†’์€ ๋น„ ํ‘œ๋ฉด์ , ์ˆ˜์šฉ์•ก์—์„œ ์•ˆ์ •์ ์ธ ๋ถ„์‚ฐ ์ƒํƒœ ์œ ์ง€, ํ™”ํ•™์  ๋ฐ˜์‘ ์œ ๋„ ๋ฐ ๊ธฐ๋Šฅํ™”๊ฐ€ ๊ฐ€๋Šฅํ•˜์—ฌ ๋‹ค์–‘ํ•œ ํ˜•ํƒœ๋ฅผ ๊ฐ€์ง„ ์‚ฐํ™” ๊ทธ๋ž˜ํ•€ ๊ฑฐ์‹œ์  ๊ตฌ์กฐ์ฒด๊ฐ€ ์ œ์ž‘๋  ์ˆ˜ ์žˆ๋‹ค. ๋˜ํ•œ ์ถ”๊ฐ€์ ์ธ ํ™˜์› ๊ณผ์ •์„ ํ†ตํ•ด ๊ทธ๋ž˜ํ•€๊ณผ ์œ ์‚ฌํ•œ ์—ด, ์ „๊ธฐ์  ํŠน์„ฑ์„ ํšŒ๋ณต์‹œํ‚ฌ ์ˆ˜ ์žˆ์–ด ํˆฌ๋ช… ์ „๊ทน[8], ํžˆํ„ฐ[9], ์—๋„ˆ์ง€ ์ €์žฅ์žฅ์น˜์˜ ์ „๊ทน[10], ์ˆ˜์ฒ˜๋ฆฌ ๋ถ„๋ฆฌ๋ง‰[11], ๋ณตํ•ฉ์†Œ์žฌ[12] ๋“ฑ ๋‹ค์–‘ํ•œ ์‘์šฉ๋ถ„์•ผ์— ์ ์šฉ๋  ์ˆ˜ ์žˆ๋‹ค. ์ง€๊ธˆ๊นŒ์ง€ ๋ณด๊ณ ๋œ ์‚ฐํ™” ๊ทธ๋ž˜ํ•€์˜ ์ œ์ž‘ ๊ณต์ •์€ ํ‘์—ฐ(Graphite)์„ ๊ฐ•๋ ฅํ•œ ์‚ฐํ™”์ œ๋กœ ์‚ฐํ™” ์‹œ์ผœ ์ธต๊ฐ„ ๊ฐ„๊ฒฉ์„ ์ฆ๊ฐ€ ์‹œํ‚จ ํ›„ ์šฉ์•ก ์ƒ์—์„œ์˜ ์ค‘ํ™” ๊ณผ์ •๊ณผ ๋ถ„๋ฆฌ ๊ณผ์ •์„ ์ด์šฉํ•œ๋‹ค. [1,2,3,4,5,6,7] ๋”ฐ๋ผ์„œ ๊ณต์ •์˜ ํŠน์„ฑ์ƒ ์žฅ ์‹œ๊ฐ„์˜ ์‚ฐํ™” ๊ณต์ •์ด ํ•„์š”ํ•˜๊ณ , ์œ ๋…๊ฐ€์Šค, ์ค‘๊ธˆ์† ๋ฐ ์‚ฐ ํ์ˆ˜ ๋ฐฐ์ถœ์€ ํ”ผํ•  ์ˆ˜ ์—†๋Š” ๋ฌธ์ œ๋กœ ์ง€์ ๋˜๊ณ  ์žˆ์œผ๋ฉฐ ์ด๋Š” ์‚ฐํ™” ๊ทธ๋ž˜ํ•€ ์ œ์ž‘์˜ ๊ฒฝ์ œ์„ฑ๊ณผ ์ƒ์‚ฐ ํšจ์œจ์„ฑ์„ ๊ฐ์†Œ์‹œํ‚ค๋Š” ์š”์ธ์ด๋ผ ํ•  ์ˆ˜ ์žˆ๋‹ค. ๋ณธ ๋…ผ๋ฌธ์—์„œ๋Š” ์‚ฐํ™” ๊ทธ๋ž˜ํ•€๊ณผ ์œ ์‚ฌํ•œ ๊ธฐํ•˜ํ•™์ , ํ™”ํ•™์  ํŠน์ง•์„ ๊ฐ€์ง€๋Š” ํƒ„์†Œ ์‹œํŠธ(Carbon sheet)๋ฅผ ๊ฐ’์‹ผ ์žฌ๋ฃŒ๋ฅผ ์ด์šฉํ•ด ๋‹จ ์‹œ๊ฐ„์— ํ•ฉ์„ฑํ•˜๋Š” ์นœ ํ™˜๊ฒฝ์  ๊ณต์ • ๋ฐฉ๋ฒ•์„ ์ œ์‹œํ•œ๋‹ค. ํƒ„์†Œ ์‹œํŠธ๋ฅผ ์ œ์ž‘ํ•˜๊ธฐ ์œ„ํ•œ ๋นŒ๋”ฉ ๋ธ”๋ก์œผ๋กœ ํ”ผ๋กœ๊ฐˆ๋กค(1,2,3-Trihydroxybenzene), ํฌ๋„๋‹น(Glucose), ์—ฌ๋ถ„์˜ ๋ฌผ ๋งŒ์„ ์ด์šฉํ•˜์˜€์œผ๋ฉฐ ๊ณ ์˜จ ๊ณ ์••์˜ ์ˆ˜์—ด๋ฒ• ๊ณต์ •์„ ํ†ตํ•ด ๋‹จ ์‹œ๊ฐ„์— ํ”ผ๋กœ๊ฐˆ๋กค๊ณผ ํฌ๋„๋‹น์˜ ํ™”ํ•™์  ๊ฒฐํ•ฉ์„ ์œ ๋„ํ•˜๋Š” ์ƒํ–ฅ์‹ ์ ‘๊ทผ๋ฒ•(Bottom-up approach)์„ ์ด์šฉํ•˜์—ฌ ํƒ„์†Œ ์‹œํŠธ๋ฅผ ์ œ์ž‘ํ•˜์˜€๋‹ค. ์ฃผ์‚ฌ์ „์žํ˜„๋ฏธ๊ฒฝ(Scanning Electron Microscopy, SEM)๊ณผ ํˆฌ๊ณผ์ „์žํ˜„๋ฏธ๊ฒฝ(Transmission Electron Microscopy, TEM), ์›์ž๊ฐ„๋ ฅํ˜„๋ฏธ๊ฒฝ(Atomic Force Microscope, AFM)์„ ์ด์šฉํ•˜์—ฌ 2์ฐจ์› ํƒ„์†Œ ์‹œํŠธ์˜ ๊ธฐํ•˜ํ•™์  ๊ตฌ์กฐ๋ฅผ ํ™•์ธํ•˜์˜€๊ณ , ํ“จ๋ฆฌ์— ๋ณ€ํ™˜ ์ ์™ธ์„  ๋ถ„๊ด‘๊ณ„(Fourier-Transform Infrared Spectroscopy, FT-IR)๊ณผ ๊ด‘์ „์ž ๋ถ„๊ด‘๊ณ„(X-ray Photoelectron Spectroscopy, XPS)๋ฅผ ์ด์šฉํ•˜์—ฌ ์‚ฐํ™” ๊ทธ๋ž˜ํ•€๊ณผ ์œ ์‚ฌํ•œ ํžˆ๋“œ๋ก์‹ค๊ธฐ, ์—ํญ์‹œ๊ธฐ, ์นด๋ฅด๋ณด๋‹๊ธฐ, ์นด๋ฅด๋ณต์‹ค๊ธฐ์˜ ํ™”ํ•™์  ๊ตฌ์กฐ๋ฅผ ํ™•์ธํ•˜์˜€๋‹ค. ๋ณธ ์—ฐ๊ตฌ์—์„œ ์ œ์ž‘๋œ ํƒ„์†Œ ์‹œํŠธ๋ฅผ ์ด์šฉํ•˜์—ฌ ์—ด ์ „์ง€(Thermocell)์˜ ์ „๊ทน์„ ์ œ์ž‘ํ•˜์—ฌ ๋‹จ์œ„ ์งˆ๋Ÿ‰ ๋‹น ์ตœ๋Œ€ ์ถœ๋ ฅ ์„ฑ๋Šฅ์„ ์ธก์ •ํ•˜๊ณ  ๊ทธ๋ž˜ํ•€ ์ „๊ทน๊ณผ ์„ฑ๋Šฅ์„ ๋น„๊ตํ•˜์˜€๋‹ค. ์˜จ๋„ ์ฐจ ๋ถ€์‹ ์ „์ง€(Thermogalvanic cell) ํ˜น์€ ์—ด-์ „๊ธฐํ™”ํ•™ ์ „์ง€(Thermo-electrochemical cell)๋กœ ์•Œ๋ ค์ง„ ์—ด ์ „์ง€๋Š” ๋‘ ์ „๊ทน ์‚ฌ์ด์˜ ์˜จ๋„ ์ฐจ์— ๊ธฐ์ธํ•ด ๋ฐœ์ƒํ•˜๋Š” ์ „ํ•ด์งˆ์˜ ์‚ฐํ™” ํ™˜์› ๋ฐ˜์‘์„ ์ด์šฉํ•˜์—ฌ ์ „๋ ฅ์„ ์ƒ์‚ฐํ•˜๋ฏ€๋กœ ๋ฐœ์ „์†Œ ํ˜น์€ ์‚ฐ์—… ์‹œ์„ค์—์„œ ๋ฐœ์ƒํ•˜๋Š” ํ์—ด๋กœ๋ถ€ํ„ฐ ์ „๊ธฐ ์—๋„ˆ์ง€๋ฅผ ์ˆ˜์ง‘ํ•  ์ˆ˜ ์žˆ๋‹ค. ์ˆ˜์—ด๋ฒ•(Hydrothermal process)์— ๊ธฐ๋ฐ˜ํ•˜์—ฌ ์ œ์ž‘๋œ ํƒ„์†Œ ์‹œํŠธ์˜ ์ƒ์‚ฐ ๋‹จ๊ฐ€๋Š” 216.8์›/g์œผ๋กœ ์‚ฐํ™” ๊ทธ๋ž˜ํ•€(150,000์›/g~300,000์›/g)์— ๋น„ํ•ด ์•ฝ 700๋ฐฐ ์ €๋ ดํ•˜๋ฉฐ ํ•„์š”ํ•œ ๋ฌผ์˜ ์–‘์€ 2.3L/kg์œผ๋กœ ์‚ฐํ™” ๊ทธ๋ž˜ํ•€ ์ œ์ž‘ ์‹œ ํ•„์š”ํ•œ ์–‘(160L/kg~460L/kg)๋ณด๋‹ค ์•ฝ 80๋ฐฐ ์ ์€ ์ˆ˜์น˜์ด๋‹ค. ํƒ„์†Œ ์‹œํŠธ ํ•ฉ์„ฑ ๊ณต์ • ์‹œ๊ฐ„์€ 4์‹œ๊ฐ„์— ๋ถˆ๊ณผํ•˜๋ฉฐ ํ•ฉ์„ฑ ๊ณผ์ • ์‹œ ์œ ๋…๊ฐ€์Šค, ์ค‘๊ธˆ์†, ์‚ฐ ํ์ˆ˜ ๋ฐฐ์ถœ ์—†์ด ํ™˜๊ฒฝ ์นœํ™”์ ์ธ ๋ฐฉ๋ฒ•์œผ๋กœ ํƒ„์†Œ ์‹œํŠธ๋ฅผ ์ œ์ž‘ํ•  ์ˆ˜ ์žˆ์œผ๋ฉฐ, ์—ด ์ „์ง€ ์‘์šฉ์—์„œ ๊ทธ๋ž˜ํ•€๊ณผ ์œ ์‚ฌํ•œ ์„ฑ๋Šฅ์„ ํ™•์ธํ•˜์˜€๋‹ค.1. ์„œ๋ก  1 1.1 ๊ทธ๋ž˜ํ•€(Graphene) 1 1.2 ์—ฐ๊ตฌ๋ชฉํ‘œ 4 2. ์‹คํ—˜ 6 2.1 ์ˆ˜์—ด๋ฒ•(Hydrothermal process) 6 2.2 ํƒ„์†Œ ์‹œํŠธ ํ•ฉ์„ฑ์„ ์œ„ํ•œ ์ตœ์ ํ™” ๊ณต์ • 8 2.2.1 ์šฉ์งˆ์˜ ๋†๋„ 8 2.2.2 ๊ณต์ • ์‹œ๊ฐ„ 9 2.2.3 ํƒ„์†Œ ์‹œํŠธ ํ•ฉ์„ฑ ๋ฉ”์ปค๋‹ˆ์ฆ˜ 12 2.2.4 ์šฉ์งˆ์˜ ๋น„์œจ 14 2.2.5 ๊ธฐํ•˜ํ•™์  ๊ตฌ์กฐ 22 2.2.6 ํ™”ํ•™์  ๊ตฌ์กฐ 23 3. ์—ด ์ „์ง€(Thermocell) 25 3.1 ์—ด ์ „์ง€ ์›๋ฆฌ 25 3.2 ์—ด ์ „์ง€ ์ œ์ž‘ ๋ฐ ์ธก์ • 27 3.3 ์—ด ์ „์ง€ ์ธก์ • ๊ฒฐ๊ณผ 31 4. ๊ฒฐ๋ก  35 ์ฐธ๊ณ  ๋ฌธํ—Œ 37 Abstract 39Maste

    ๊ณ„์ธต์  ์ •๋ถ€์‹ ๋ขฐ๋ฅผ ์ค‘์‹ฌ์œผ๋กœ

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    ํ•™์œ„๋…ผ๋ฌธ(๋ฐ•์‚ฌ)--์„œ์šธ๋Œ€ํ•™๊ต ๋Œ€ํ•™์› :ํ–‰์ •๋Œ€ํ•™์› ํ–‰์ •ํ•™๊ณผ(์ •์ฑ…ํ•™์ „๊ณต),2019. 8. ๊น€์ˆœ์€.Trust, as excellent social capital, plays a significant role in reducing costs in social communication and promoting harmonious social development. The issue of public trust in government sounds like a platitude, but nevertheless it is a thought-provoking problem. In the microscopic view, the trust in the government relates to the smooth operation of the government policy; in the macroscopic view, it concerns the legitimacy of a regime. Hence, the issue of public trust in government has been the center of attention in different historical eras. Compared with China, most of the other countries level of public trust in government is not high. In terms of the inter-governmental relationship, Chinese public trust in government has demonstrated a distinctive trait. According to Li Lianjiang, in China there is a high level of trust in the national government but a low level of trust in the local government, which is referred to as a hierarchical government trust structure. Contrarily, most of the capitalist countries, including South Korea, have a reversed government trust structure. To be more specific, a high level of trust is demonstrated in the local government, while a low level of trust in the national government. Many scholars attribute a low level of government trust to high public exceptions brought by economic growth, while other scholars argue that it is the paradox of distance caused by devolution that leads to the reverse-hierarchical government trust in the western countries. Chinese scholars believe that it is the Chinese political system, the cultural tradition, and government performance that affect Chinese hierarchical government trust. Among all the countries in the world, South Korea is the unique country which shares the most similar cultural tradition with China. Moreover, the state-dominant economic development model of South Korea is the same as that of China. According to the research literature and social survey in South Korea, until the early 1980s, South Korean citizens have demonstrated more trust in and were more concerned with the national rather than the local government affairs. The change took place after the democracy movement in 1987 and the decentralization in 1994. Over the past decade, the South Koreans overall trust in the government is not high. Also, like most western capitalist countries, South Korea is featured by a reverse-hierarchical government trust structure. The current study aims to compare differences in the public government trust of South Korea and China which have a similar cultural background but different economic development levels and political systems. In particular, on the basis of the natural experiment, the comparison between South Korean and Chinese government trust will be conducted in terms of the consistency, difference as well as simultaneous changes of China and South Korea. The research frame is based on the hypothesis that human beings are the combination of rationality and sensibility. Furthermore, two questions have been raised in the current study. Firstly, why are citizens trust in national government and local government inconsistent? Moreover, if the trust is closely related to culture and government performance, how is South Korean citizens trust in their national and local government? With the data collected from the 4th Asian Barometer Survey, from the perspective of cultural theory and institutional theory, independent variables, namely, traditional Asian value, diffused support, such as the support to the regime, and special support, for example the transparency and the economic performance, and the control variables, such as the social capital, media use habits, etc., have been analyzed by a classic regression model. And a ANCOVA method is also applied to compare the differences of the regression model slopes between South Korean and Chinese national and local government trust. The research results indicate that cultural influence on both national and local government trust is waning gradually. As for the cultural factors, the consciousness of obedience to authority does not bear any relation to national and local government trust in China and South Korea, and groupism is only related to the national government trust. As for the institutional factors, in South Korea, community consciousness(part of the diffused support) is irrelated with both national and local government trust. Whereas, it is related to the Chinese national but not local government trust. In terms of special support, South Korean governments responsiveness and anti-corruption performance have been proved to be related with both national and local government trust. On the other hand, it has been found that the responsiveness, transparency, anti-corruption performance and economic performance all demonstrate a positive statistic correlation to both national and local government trust in China. Finally, it is found in the paper that the sources of Chinese national government trust are richer than that of Chinese local government, which means the public trust in Chinese national government, especially the national government can get more support from cultural factors, diffused support and special support, while the trust in the local government is relatively weaker. This situation is owing to the integration of the CPC Party and government and the national governmental control over the local government. In South Korea, on the other hand, due to the slight influence of the cultural factor, diffused support, and the citizens high expectation, there is no statistically significant correlation between government trust and government performance. South Koreas government trust structure presents a trend of separatism caused by social and economic development and political institutional reform.๋ณธ ์—ฐ๊ตฌ๋Š” ์ •๋ถ€์‹ ๋ขฐ ํ˜•ํƒœ ์ค‘ ๊ณ„์ธต์  ์ •๋ถ€์‹ ๋ขฐ๋ฅผ ์ ์šฉํ•˜์—ฌ ํ•œ๊ตญ๊ณผ ์ค‘๊ตญ์˜ ์ •๋ถ€์‹ ๋ขฐ ์˜ํ–ฅ ์š”์†Œ๋ฅผ ๋น„๊ต ๋ถ„์„ํ•˜์˜€๋‹ค. ๊ณ„์ธต์  ์ •๋ถ€์‹ ๋ขฐ๋Š” ํ•œ ์‚ฌ๋žŒ์ด ๋‹ค๋ฅธ ๊ณ„์ธต์˜ ์ •๋ถ€์— ๋Œ€ํ•ด ๋‹ค๋ฅธ ์‹ ๋ขฐ ํƒœ๋„๋ฅผ ๋ณด์—ฌ์ฃผ๋Š” ๊ฒƒ์„ ์˜๋ฏธํ•œ๋‹ค. ํ•œ๊ตญ์—์„œ๋Š” ๊ณ„์ธต์  ์ •๋ถ€์‹ ๋ขฐ ํ˜„์ƒ์ด ๋šœ๋ ทํ•˜๊ฒŒ ๋‚˜ํƒ€๋‚˜์ง€ ์•Š์•„์„œ ์ด์— ๊ด€ํ•œ ์—ฐ๊ตฌ๊ฐ€ ๋ถ€์กฑํ•˜์ง€๋งŒ, ์ค‘๊ตญ์—์„œ ์ด๋Ÿฐ ํ˜„์ƒ์ด ์˜ค๋ž˜์ „๋ถ€ํ„ฐ ๋šœ๋ ทํ•˜๊ฒŒ ์กด์žฌํ•ด ์™”๊ธฐ ๋•Œ๋ฌธ์— ๊ณ„์ธต์  ์ •๋ถ€์‹ ๋ขฐ์˜ ์˜๋ฏธ๊ฐ€ ์ž˜ ๋ฐํ˜€์กŒ๋‹ค. ํ˜„์žฌ ํ•œ๊ตญ์€ ์ค‘์•™์ •๋ถ€์— ๋Œ€ํ•œ ์‹ ๋ขฐ๊ฐ€ ๋‚ฎ๊ณ , ์ง€๋ฐฉ์ •๋ถ€์— ๋Œ€ํ•œ ์‹ ๋ขฐ๋Š” ๋†’์€ ์—ญ๊ณ„์ธต์  ์ •๋ถ€์‹ ๋ขฐ ํ˜•ํƒœ๋ฅผ ๊ฐ€์ง€๋ฉฐ, ์ค‘๊ตญ์€ ์ด์™€ ๋ฐ˜๋Œ€๋กœ, ์ค‘์•™์ •๋ถ€์— ๋Œ€ํ•œ ์‹ ๋ขฐ๋Š” ๋†’๊ณ , ์ง€๋ฐฉ์ •๋ถ€์— ๋Œ€ํ•œ ์‹ ๋ขฐ๊ฐ€ ๋‚ฎ์€ ์ •๋ถ€์‹ ๋ขฐ ํ˜•ํƒœ๋ฅผ ๊ฐ–๊ณ  ์žˆ๋‹ค. ์ •๋ถ€์‹ ๋ขฐ์˜ ์˜ํ–ฅ ์š”์†Œ๋Š” ์ผ๋ฐ˜์ ์œผ๋กœ ๋ฌธํ™”๋ก ์  ์ธก๋ฉด ๋ฐ ์ œ๋„ยท์„ฑ๊ณผ๋ก ์  ์ธก๋ฉด์œผ๋กœ ๋‚˜๋ˆ„์–ด์„œ ์ ‘๊ทผํ•œ๋‹ค. ๋ฌธํ™”๋ก ์  ์ธก๋ฉด์—์„œ ๋ณผ ๋•Œ, ์ •๋ถ€์— ๋Œ€ํ•œ ์‹ ๋ขฐ๋Š” ์‚ฌํšŒ๋ฌธํ™” ์†์— ์žˆ๋Š” ์ผ๋ฐ˜์‹ ๋ขฐ์˜ ํ™•์‚ฐ์œผ๋กœ ์ธ์‹๋œ๋‹ค. ๋”ฐ๋ผ์„œ ์‹ ๋ขฐ๋Š” ๊ฐ์„ฑ์„ ๊ธฐ๋ฐ˜์œผ๋กœ ๋ฐœ์ƒํ•œ ๊ฐ์ •์ ์ธ ํ–‰๋™์œผ๋กœ ๋ณผ ์ˆ˜ ์žˆ๋‹ค. ๋ฐ˜๋Œ€๋กœ ์ œ๋„ยท์„ฑ๊ณผ ์ธก๋ฉด์—์„œ ๋ณด๋ฉด, ์ •๋ถ€์— ๋Œ€ํ•œ ์‹ ๋ขฐ๋Š” ํ˜„์‹ค ์„ฑ๊ณผ์— ๊ทผ๊ฑฐํ•œ ์ด์„ฑ์ ์ธ ํŒ๋‹จ์œผ๋กœ ๋ณผ ์ˆ˜ ์žˆ๋‹ค. ์ฆ‰ ๊ตญ๋ฏผ์€ ์ •๋ถ€ ๋˜๋Š” ์ •๋ถ€์˜ ์ œ๋„๊ฐ€ ์ด๋ฃจ์–ด๋‚ธ ์„ฑ๊ณผ์— ๊ทผ๊ฑฐ๋ฅผ ๋‘๊ณ  ์ •๋ถ€์— ๋Œ€ํ•œ ์ง€์ง€ ์—ฌ๋ถ€๋ฅผ ํŒ๋‹จํ•œ๋‹ค. ์ด๋Ÿฐ ๋‘ ๊ฐ€์ง€ ์ ‘๊ทผ๋ฒ• ์•„๋ž˜, ํ•œ ๋‚˜๋ผ์˜ ๋ฌธํ™”์  ๋ฐฐ๊ฒฝ ๋ฐ ์ •๋ถ€์˜ ์„ฑ๊ณผ๋Š” ์ •๋ถ€์‹ ๋ขฐ์— ๋Œ€ํ•œ ์—ฐ๊ตฌ ์ค‘์—์„œ ๋ฐ˜๋“œ์‹œ ๊ณ ๋ คํ•ด์•ผ ํ•  ๋ถ€๋ถ„์ด ๋œ๋‹ค. ๋น„๊ต์˜ ๊ด€์ ์—์„œ ์ถœ๋ฐœํ•˜๋ฉด, ๋น„๊ต ๋Œ€์ƒ์˜ ์ผ์น˜์„ฑ, ์ฐจ์ด์„ฑ, ๊ณต๋™๋ณ€ํ™”์„ฑ์„ ๊ณ ๋ คํ•ด์•ผ ํ•œ๋‹ค. ํ•œ๊ตญ๊ณผ ์ค‘๊ตญ์€ ์ผ๋ฐ˜์ ์œผ๋กœ ์ „ํ†ต์ ์ธ ๋™์•„์‹œ์•„ ์œ ๊ต ๊ตญ๊ฐ€๋กœ ๋ถ„๋ฅ˜๋˜์–ด ๊ทธ๋“ค์˜ ๋ฌธํ™”์  ๋ฐฐ๊ฒฝ์ด ๋งค์šฐ ์œ ์‚ฌํ•˜๋‹ค๊ณ  ์ธ์‹๋œ๋‹ค. ๋˜ํ•œ, ํ•œ๊ตญ๊ณผ ์ค‘๊ตญ์€ ๋น„์Šทํ•œ ๊ฒฝ์ œ๋ฐœ์ „ ๋…ธ์„ ์ธ ์ค‘์•™์ง‘๊ถŒ์ฃผ์˜์  ๊ฒฝ์ œ๋ฐœ์ „ ๋ชจ๋ธ์„ ์ฑ„ํƒํ–ˆ๋‹ค. ์ด๋Ÿฐ ์ผ์น˜์„ฑ์—๋„ ๋ถˆ๊ตฌํ•˜๊ณ  ์–‘๊ตญ์€ ์ œ๋„ยท์„ฑ๊ณผ์  ์š”์†Œ์—์„œ ์ฐจ์ด์ ์„ ๋ณด์ธ๋‹ค. ์–‘๊ตญ์˜ ์ •๋ถ€์‹ ๋ขฐ ํ˜•ํƒœ์˜ ์ฐจ์ด๊ฐ€ ์ด๋Ÿฌํ•œ ์ œ๋„ยท์„ฑ๊ณผ์  ์š”์†Œ์™€ ์—ฐ๊ด€์„ฑ์ด ์žˆ๋Š”์ง€๊ฐ€ ๋ณธ ๋…ผ๋ฌธ์˜ ์—ฐ๊ตฌ์ฃผ์ œ์ด๋‹ค. ์ฆ‰, ๋ฌธํ™”์  ๋ฐฐ๊ฒฝ์ด ์œ ์‚ฌํ•˜๊ณ , ์ œ๋„์™€ ์„ฑ๊ณผ๊ฐ€ ์„œ๋กœ ๋‹ค๋ฅธ ๋‘ ๊ตญ๊ฐ€์—์„œ ์ค‘์•™๊ณผ ์ง€๋ฐฉ์ •๋ถ€ ์‚ฌ์ด์— ์‹ ๋ขฐ ์ฐจ์ด๊ฐ€ ๋ฐœ์ƒํ•˜๋Š” ์˜ํ–ฅ ์š”์†Œ๊ฐ€ ๋ฌด์—‡์ด๊ณ , ๊ทธ ๊ฐ€๋Šฅํ•œ ์›์ธ์ด ๋ฌด์—‡์ธ์ง€์— ๋Œ€ํ•ด์„œ ์—ฐ๊ตฌํ•ด ๋ณด๋ ค๊ณ  ํ•œ๋‹ค. ์ด์— ๋”ฐ๋ผ ๋ณธ ๋…ผ๋ฌธ์—์„œ๋Š” ๊ฐ™์€ ๊ฐœ์ฒด์ž„์—๋„ ๋ถˆ๊ตฌํ•˜๊ณ  ์ค‘์•™๊ณผ ์ง€๋ฐฉ์ •๋ถ€์—๊ฒŒ ์„œ๋กœ ๋‹ค๋ฅธ ์‹ ๋ขฐ ํƒœ๋„๋ฅผ ๋ณด์—ฌ์ฃผ๋Š” ๊ฐœ์ธ์„ ๊ฐ์„ฑ ๋ฐ ์ด์„ฑ์ด ๊ณต์กดํ•˜๋Š” ๊ฒฐํ•ฉ์ฒด๋กœ ๋ณด๊ณ , ๊ฐ์„ฑ์ , ์ฆ‰ ๋ฌธํ™”์  ์š”์†Œ ๊ทธ๋ฆฌ๊ณ  ์ด์„ฑ์ , ์ฆ‰ ์ •๋ถ€ ์‹ค์ ์— ๋Œ€ํ•œ ์ธ์‹์ด ์ค‘์•™ ๋ฐ ์ง€๋ฐฉ์ •๋ถ€์‹ ๋ขฐ์™€ ์–ด๋–ค ๊ด€๊ณ„๊ฐ€ ์žˆ๋Š”์ง€๋ฅผ ์‚ดํŽด๋ณด์•˜๋‹ค. ๋ถ„ ๋…ผ๋ฌธ์—์„œ๋Š” ๋ฌธํ™”์  ์š”์†Œ๋ฅผ ๊ถŒ์œ„๋ณต์ข…, ์ง‘๋‹จ์˜์‹์œผ๋กœ ๊ตฌ์„ฑ๋œ ๋‹จ์ผ์ฐจ์›์œผ๋กœ, ๊ทธ๋ฆฌ๊ณ  ์ œ๋„ยท์„ฑ๊ณผ์  ์š”์†Œ๋Š” ๊ณต๋™์ฒด์˜์‹, ๋ ˆ์ง์ง€์ง€๋กœ ๊ตฌ์„ฑ๋œ ํฌ๊ด„์  ์ง€์ง€ ๋ฐ ์ •๋ถ€์˜ ์ ˆ์ฐจ์  ์š”์†Œ(์ •๋ถ€ ํˆฌ๋ช…์„ฑ, ์ •๋ถ€ ๋Œ€์‘์„ฑ), ์ •๋ถ€์˜ ๊ธฐ๋Šฅ์  ์š”์†Œ(์ •๋ถ€ ๊ฒฝ์ œ์„ฑ๊ณผ, ๋ถ€ํŒจํ‡ด์น˜)๋กœ ๊ตฌ์„ฑ๋œ ํŠน์ •์  ์ง€์ง€์˜ 2๊ฐœ ์ฐจ์›์œผ๋กœ ๋‚˜๋ˆ„์–ด์„œ ํ•œ๊ตญ๊ณผ ์ค‘๊ตญ์˜ ์ค‘์•™๊ณผ ์ง€๋ฐฉ์ •๋ถ€์— ๋™์ผํ•œ ๋…๋ฆฝ๋ณ€์ˆ˜๋ฅผ ์ ์šฉํ•˜์—ฌ ๋‹ค์ค‘ํšŒ๊ท€๋ถ„์„ ๋ฐฉ๋ฒ•์œผ๋กœ ๋ถ„์„ํ•˜์˜€๋‹ค. ๊ฒฐ๋ก ์ ์œผ๋กœ, ํ•œ๊ตญ๊ณผ ์ค‘๊ตญ์€ ๊ฒฝ์ œ๋ฐœ์ „์— ๋”ฐ๋ผ ๋ฌธํ™”์  ์š”์†Œ์™€ ์ •๋ถ€์‹ ๋ขฐ์˜ ์ƒ๊ด€๊ด€๊ณ„๊ฐ€ ์ ์ฐจ ์•ฝํ™”ํ•˜๋Š” ํ˜„์ƒ์ด ๋‚˜ํƒ€๋‚ฌ๋‹ค. ํ•œ๊ตญ์˜ ์ค‘์•™์ •๋ถ€์™€ ์ง€๋ฐฉ์ •๋ถ€์— ๋Œ€ํ•œ ๋ฌธํ™”์  ์‹ ๋ขฐ ์˜ํ–ฅ ์š”์†Œ๋ฅผ ์‚ดํŽด๋ณด๋ฉด, ๊ถŒ์œ„๋ณต์ข… ์˜์‹์ด ์ค‘์•™๊ณผ ์ง€๋ฐฉ์ •๋ถ€ ์ˆ˜์ค€์—์„œ ํ†ต๊ณ„์ ์œผ๋กœ ๋ฌด์˜๋ฏธํ•˜๊ฒŒ ๋‚˜์˜ค๊ณ , ์ง‘๋‹จ์˜์‹์ด ์ค‘์•™์ •๋ถ€ ์ˆ˜์ค€์—์„œ๋งŒ ํ†ต๊ณ„์ ์œผ๋กœ ์œ ์˜๋ฏธํ•˜๊ฒŒ ๋‚˜์™”๋‹ค. ํ•œํŽธ, ํฌ๊ด„์  ์ง€์ง€ ์ธก๋ฉด์—์„œ ๋ณด๋ฉด, ๋ ˆ์ง์— ๋Œ€ํ•œ ์ง€์ง€๋Š” ์ค‘์•™๊ณผ ์ง€๋ฐฉ์ •๋ถ€์—์„œ ํ†ต๊ณ„์ ์œผ๋กœ ์œ ์˜๋ฏธํ•˜๊ฒŒ ๋‚˜์˜ค์ง€๋งŒ, ๊ณต๋™์ฒด ์˜์‹์ด ์ „๋ถ€ ๋ฌด์˜๋ฏธํ•˜๊ฒŒ ๋‚˜์™”๋‹ค. ๋˜ํ•œ, ํŠน์ •์  ์ง€์ง€ ์ธก๋ฉด์—์„œ ๋ณด๋ฉด, ์ค‘์•™์ •๋ถ€ ์ˆ˜์ค€์—์„œ ์ ˆ์ฐจ์  ์„ฑ๊ณผ์ธ ๋Œ€์‘์„ฑ๊ณผ ๊ธฐ๋Šฅ์  ์„ฑ๊ณผ์ธ ๋ถ€ํŒจํ‡ด์น˜๋Š” ํ†ต๊ณ„์ ์œผ๋กœ ์œ ์˜๋ฏธํ•˜๊ฒŒ ๋‚˜์˜ค์ง€๋งŒ, ์ง€๋ฐฉ์ •๋ถ€ ์ˆ˜์ค€์—์„œ ๋ณผ ๋•Œ ์ ˆ์ฐจ์  ์„ฑ๊ณผ์ธ ๋Œ€์‘์„ฑ๊ณผ ๊ธฐ๋Šฅ์  ์„ฑ๊ณผ์ธ ๊ฒฝ์ œ์„ฑ๊ณผ๋Š” ํ†ต๊ณ„์ ์œผ๋กœ ์œ ์˜๋ฏธํ•˜๊ฒŒ ๋‚˜ํƒ€๋‚ฌ๋‹ค. ์ค‘๊ตญ์˜ ๊ฒฝ์šฐ, ๋ฌธํ™”์  ์ธก๋ฉด์—์„œ ๋ณด๋ฉด, ๊ถŒ์œ„๋ณต์ข… ์˜์‹์ด ์ค‘์•™๊ณผ ์ง€๋ฐฉ์ •๋ถ€ ์ˆ˜์ค€์—์„œ ํ†ต๊ณ„์ ์œผ๋กœ ์œ ์˜๋ฏธํ•˜๊ฒŒ ๋‚˜ํƒ€๋‚˜์ง€ ๋ชปํ•˜๋ฉฐ, ์ง‘๋‹จ์˜์‹์ด ์ค‘์•™์ •๋ถ€์™€ ์ง€๋ฐฉ์ •๋ถ€ ์ˆ˜์ค€์—์„œ ๋‹ค ํ†ต๊ณ„์ ์œผ๋กœ ์œ ์˜๋ฏธํ•˜๊ฒŒ ๋‚˜์˜ค์ง€๋งŒ, ์ง€๋ฐฉ์ •๋ถ€์˜ ํšŒ๊ท€๊ณ„์ˆ˜๋Š” ๋งˆ์ด๋„ˆ์Šค ๋ถ€ํ˜ธ๋ฅผ ๊ฐ€์ง„๋‹ค. ์ฆ‰, ์ง‘๋‹จ์ฃผ์˜ ์˜์‹์ด ๊ฐ•ํ• ์ˆ˜๋ก, ์ค‘๊ตญ ์ง€๋ฐฉ์ •๋ถ€์— ๋Œ€ํ•œ ์‹ ๋ขฐ๊ฐ€ ์˜คํžˆ๋ ค ์ค„์–ด๋“œ๋Š” ํ˜„์ƒ์ด ๋‚˜ํƒ€๋‚œ๋‹ค๋Š” ๊ฒƒ์ด๋‹ค. ํ•œํŽธ, ํฌ๊ด„์  ์ง€์ง€ ์ธก๋ฉด์—์„œ ๋ณด๋ฉด, ๋ ˆ์ง์— ๋Œ€ํ•œ ์ง€์ง€๋Š” ์ค‘์•™๊ณผ ์ง€๋ฐฉ์ •๋ถ€์—์„œ ํ†ต๊ณ„์ ์œผ๋กœ ์œ ์˜๋ฏธํ•˜๊ฒŒ ๋‚˜ํƒ€๋‚˜์ง€๋งŒ ๊ณต๋™์ฒด ์˜์‹์€ ์ค‘์•™์ •๋ถ€ ์ˆ˜์ค€์—์„œ๋งŒ ์œ ์˜๋ฏธํ•˜๊ฒŒ ๋‚˜์˜ค๊ณ , ์ง€๋ฐฉ์ •๋ถ€ ์ˆ˜์ค€์—์„œ๋Š” ์œ ์˜๋ฏธํ•˜๊ฒŒ ๋‚˜ํƒ€๋‚˜์ง€ ๋ชปํ–ˆ๋‹ค. ๊ทธ๋ฆฌ๊ณ  ํŠน์ •์  ์ง€์ง€ ์ธก๋ฉด์„ ์‚ดํŽด๋ณด๋ฉด, ์ค‘์•™์ •๋ถ€์™€ ์ง€๋ฐฉ์ •๋ถ€๋Š” ์ ˆ์ฐจ์  ์„ฑ๊ณผ ๋ฐ ๊ธฐ๋Šฅ์  ์„ฑ๊ณผ ๋ฉด์—์„œ ๋ชจ๋‘ ์œ ์˜๋ฏธํ•œ ํšŒ๊ท€๊ฒฐ๊ณผ๊ฐ€ ๋‚˜ํƒ€๋‚ฌ๋‹ค. ์ข…ํ•ฉ์ ์œผ๋กœ ๋น„๊ตํ•˜๋ฉด, ํ•œ๊ตญ๊ณผ ์ค‘๊ตญ์˜ ์ •๋ถ€์‹ ๋ขฐ ์˜ํ–ฅ ์š”์†Œ์— ์žˆ์–ด์„œ ๋ฌธํ™”์  ์š”์†Œ ์ธก๋ฉด์—์„œ๋Š” ๋‘ ๊ตญ๊ฐ€๋Š” ์ฐจ์ด๊ฐ€ ์—†๋‹ค๋Š” ๊ฒฐ๊ณผ๊ฐ€ ๋„์ถœ๋˜์—ˆ๊ณ , ์ œ๋„ยท์„ฑ๊ณผ์  ์š”์†Œ ์ธก๋ฉด์—์„œ๋Š” ์ค‘๊ตญ์˜ ํฌ๊ด„์  ์ง€์ง€ ๋ฐ ํŠน์ •์  ์ง€์ง€๊ฐ€ ํ•œ๊ตญ๋ณด๋‹ค ๋” ๊ฐ•๋ ฅํ•˜๋‹ค๋Š” ๊ฒฐ๊ณผ๊ฐ€ ๋„์ถœ๋˜์—ˆ๋‹ค. ์ฆ‰, ์ค‘๊ตญ๊ณผ ๋น„๊ตํ–ˆ์„ ๋•Œ, ํ•œ๊ตญ ์ค‘์•™์ •๋ถ€ ์ˆ˜์ค€์—์„œ๋Š” ์‹ ๋ขฐ์˜ ์›์ธ์ธ ํฌ๊ด„์  ์ง€์ง€์˜ ์ˆ˜์ค€์ด ๋‚ฎ๋‹ค. ๊ทธ๋ฆฌ๊ณ  ํ•œ๊ตญ์˜ ์ค‘์•™๊ณผ ์ง€๋ฐฉ์ •๋ถ€ ์ˆ˜์ค€์—์„œ๋Š” ํŠน์ •์  ์ง€์ง€๋„ ๋ถ€์กฑํ•˜๋‹ค. ์ด๋Ÿฐ ์ฐจ์ด๋Š” ํ•œ๊ตญ์ด ๋ฏผ์ฃผ์ฃผ์˜ ์ฒด์ œ์™€ ์ง€๋ฐฉ๋ถ„๊ถŒ ์ œ๋„๋ฅผ ์ฑ„ํƒํ•˜์˜€๊ณ  ์ค‘๊ตญ์ด ๊ณต์‚ฐ์ฃผ์˜ ์ฒด์ œ์™€ ๋‹น์ •์ผ์ฒด ์ •๋ถ€ ๊ตฌ์กฐ๋ฅผ ์ฑ„ํƒํ•œ ์  ๋ฐ ์–‘๊ตญ์˜ ๊ฒฝ์ œ๋ฐœ์ „ ์ˆ˜์ค€์˜ ์ฐจ์ด์— ๋”ฐ๋ฅธ ์–‘๊ตญ ๊ตญ๋ฏผ์˜ ๊ฐ€์น˜๊ด€์˜ ์ฐจ์ด์™€ ๊ด€๊ณ„๊ฐ€ ์žˆ๋Š” ๊ฒƒ์œผ๋กœ ๋ณด์ธ๋‹ค.์ œ1์žฅ ์„œ๋ก  1 ์ œ1์ ˆ ๋ฌธ์ œ์˜ ์ œ๊ธฐ ๋ฐ ์—ฐ๊ตฌ๋ชฉ์  1 ์ œ2์ ˆ ์—ฐ๊ตฌ์˜ ๋ฒ”์œ„ ๋ฐ ๋ฐฉ๋ฒ• 8 ์ œ2์žฅ ์ด๋ก ์  ๋…ผ์˜ 10 ์ œ1์ ˆ ์ •๋ถ€์‹ ๋ขฐ์— ๊ด€ํ•œ ์ด๋ก  10 1. ์‹ ๋ขฐ ๋ฐ ์ •๋ถ€์‹ ๋ขฐ 10 2. ๊ณ„์ธต์  ์ •๋ถ€์‹ ๋ขฐ 35 ์ œ2์ ˆ ์ •๋ถ€์‹ ๋ขฐ์˜ ์˜ํ–ฅ์š”์†Œ 46 1. ๋ฌธํ™”์  ์š”์†Œ 47 2. ์ œ๋„์„ฑ๊ณผ์  ์š”์†Œ 63 ์ œ3์žฅ ์—ฐ๊ตฌ์„ค๊ณ„ 84 ์ œ1์ ˆ ์—ฐ๊ตฌ๊ฐ€์„ค ๋ฐ ๋ถ„์„๋ชจํ˜• 84 1. ์—ฐ๊ตฌ์˜ ๊ฐ€์„ค 84 2. ์—ฐ๊ตฌ์˜ ๋ถ„์„ํ‹€ 88 3. ๋ถ„์„ ๋ชจํ˜• ๋ฐ ๋ฐฉ๋ฒ• 88 ์ œ2์ ˆ ๋ณ€์ˆ˜์˜ ์„ ์ • ๋ฐ ์ธก์ • 91 1. ์ข…์†๋ณ€์ˆ˜์˜ ์ธก์ • 94 2. ๋…๋ฆฝ๋ณ€์ˆ˜์˜ ์ธก์ • 95 ์ œ4์žฅ ๋ถ„์„ ๊ฒฐ๊ณผ 111 ์ œ1์ ˆ ๊ธฐ์ˆ ํ†ต๊ณ„๋ถ„์„ 111 1. ๋ณ€์ˆ˜์˜ ๊ธฐ์ˆ ํ†ต๊ณ„๋ถ„์„ 111 2. ๋ณ€์ˆ˜ ๊ฐ„์˜ ์ƒ๊ด€๊ด€๊ณ„ 114 ์ œ2์ ˆ ์—ฐ๊ตฌ๊ฒฐ๊ณผ์˜ ๋ถ„์„ 118 1. ๋ถ„์„ ๊ฒฐ๊ณผ 118 2. ๊ฐ€์„ค์— ๋Œ€ํ•œ ๊ฒ€์ฆ 121 ์ œ3์ ˆ ํ•œ์ค‘ ๋น„๊ต๋ถ„์„ 162 1. ํ•œ๊ตญ๊ณผ ์ค‘๊ตญ ์ •๋ถ€์˜ ๊ตฌ์กฐ ๋ฐ ๊ธฐ๋Šฅ 162 2. ํ•œ์ค‘ ๊ฑด๊ตญ ์ดํ›„์˜ ์ •๋ถ€์‹ ๋ขฐ 181 3. ํ•œ๊ตญ๊ณผ ์ค‘๊ตญ์˜ ์ผ์น˜์„ฑ, ์ฐจ์ด์  ๋ฐ ๋™์‹œ๋ณ€ํ™”์„ฑ 195 ์ œ5์žฅ ๊ฒฐ๋ก  ๋ฐ ํ•จ์˜ 210 ์ œ1์ ˆ ์—ฐ๊ตฌ๊ฒฐ๊ณผ์˜ ์š”์•ฝ 210 ์ œ2์ ˆ ์—ฐ๊ตฌ์˜ ํ•จ์˜ 212 1. ์ด๋ก ์  ํ•จ์˜ 212 2. ์ •์ฑ…์  ํ•จ์˜ 215 ์ œ3์ ˆ ์—ฐ๊ตฌ์˜ ํ•œ๊ณ„์  219 ์ฐธ๊ณ ๋ฌธํ—Œ 221 Abstract 255 ๋ถ€๋ก1 261Docto

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    ํ•™์œ„๋…ผ๋ฌธ(์„์‚ฌ) -- ์„œ์šธ๋Œ€ํ•™๊ต๋Œ€ํ•™์› : ํ–‰์ •๋Œ€ํ•™์› ๊ณต๊ธฐ์—…์ •์ฑ…ํ•™๊ณผ, 2021.8. ์ž„๋„๋นˆ.With the inauguration of the current administration, the "hydrogen economy" is one of the biggest energy policy paradigm change keywords, and the expansion and dissemination of hydrogen cars is a representative implementation task of this policy. However, there was no review of the impact of expanding the charging infrastructure of hydrogen cars and providing subsidies that required huge budgeting, and it was also necessary to study how the unique attributes of hydrogen cars also affected them. Therefore, through this study, we would like to examine the direction of the government's policy on the expansion of hydrogen vehicles. The purpose of this study was to analyze the effect of four external properties (economic, functional, service, and value) of hydrogen vehicles derived from several prior research analyses on the purchase intention of hydrogen vehicles. In addition, the study sought to verify the impact of the government's charging infrastructure expansion and purchase subsidy policies on the purchase intention of hydrogen cars and how these policies have a controlling effect on the relationship between the external nature of hydrogen cars and the purchase intention. For this study, data were collected and analyzed both online and offline surveys of hydrogen vehicle users. Statistical analysis methods conducted frequency analysis to identify demographic characteristics, and factor analysis and reliability analysis were conducted to ensure the validity of the survey composition items to verify the suitability of the study model. In addition, multiple regression analyses were conducted to determine how the external properties of hydrogen cars and government's policies directly affect the purchasing intentions of hydrogen cars during the hypothesis verification phase, and in particular, hierarchical regression analysis was conducted to verify the regulatory effect of government's policies. The results of this study can be summarized as follows: First, The hypothesis was mostly supported that the external properties of hydrogen cars would have a positive (+) effect on the intention to purchase. Specifically, it was analyzed that the purchase intention was greatly influenced by the order of economy, functionality, and value of hydrogen cars. Given that the service sector is considered the most unsatisfactory factor for users of hydrogen vehicles, it was confirmed that it has no direct influence on the intention to purchase them. In addition, both, the expansion of charging infrastructure and the purchase subsidy policy under the government's expansion policy of hydrogen vehicles have a significant positive impact on the purchase intention of hydrogen cars. In particular, the degree of expansion of charging infrastructure has been shown to control the impact of economic feasibility on purchase intentions among external properties of hydrogen cars. The analysis of the adjustment effect through the interaction term between hydrogen charging station distances and economic variables shows that groups close to hydrogen charging station distances have a lower economic impact on their purchasing intentions than those not. The implications of this study are as follows: First, like other eco-friendly cars, policy aid to economic areas such as subsidies and various tax benefits are effective in revitalizing the supply of hydrogen cars at the initial stage of supply. Second, it should be noted that the government's policy to expand its charging infrastructure is a top priority, given the inherent nature of hydrogen cars that are rapidly spreading to compensate for the shortcomings of electric cars, the same eco-friendly car. Third, the government can consider harmonious implementation of the two policies for the supply of hydrogen vehicles. In other words, the central government should focus more on expanding the charging infrastructure led by local governments, which have been passive in distributing hydrogen cars. In areas where charging infrastructure is relatively well-equipped, the policy of expanding purchase subsidies should be focused to ensure stable supply of hydrogen cars. In addition, sufficient economic feasibility should be secured for the operation of hydrogen charging stations to induce synergy in the direction of expansion of charging infrastructure led by the private sector.ํ˜„ ์ •๋ถ€๊ฐ€ ์ถœ๋ฒ”ํ•˜๋ฉด์„œ ๊ฐ€์žฅ ํฐ ์—๋„ˆ์ง€ ์ •์ฑ… ํŒจ๋Ÿฌ๋‹ค์ž„ ๋ณ€ํ™”์˜ ํ‚ค์›Œ๋“œ ์ค‘์— ํ•˜๋‚˜๊ฐ€ โ€˜์ˆ˜์†Œ๊ฒฝ์ œโ€™ ๋กœ ์ˆ˜์†Œ์ฐจ ํ™•๋Œ€ ๋ณด๊ธ‰์€ ์ด ์ •์ฑ…์˜ ๋Œ€ํ‘œ์ ์ธ ์‹คํ–‰๊ณผ์ œ์ด๋‹ค. ๊ทธ๋Ÿฌ๋‚˜, ๋ง‰๋Œ€ํ•œ ์˜ˆ์‚ฐ ํˆฌ์ž…์ด ํ•„์š”ํ•œ ์ˆ˜์†Œ์ฐจ ์ถฉ์ „ ์ธํ”„๋ผ ํ™•์ถฉ๊ณผ ๋ณด์กฐ๊ธˆ ์ง€๊ธ‰์ด ์ •์ฑ… ํšจ๊ณผ๋กœ ์ด๋ค„์ง€๋Š”์ง€์— ๋Œ€ํ•œ ์˜ํ–ฅ ๊ฒ€ํ† ๊ฐ€ ์ „๋ฌดํ•˜์˜€๊ณ , ์ˆ˜์†Œ์ฐจ์˜ ๊ณ ์œ ํ•œ ์†์„ฑ๋“ค์ด ๋˜ํ•œ ์–ด๋– ํ•œ ์˜ํ–ฅ์„ ๋ฏธ์น˜๋Š”์ง€์— ๋Œ€ํ•ด์„œ๋„ ์—ฐ๊ตฌํ•  ํ•„์š”๊ฐ€ ์žˆ์—ˆ๋‹ค. ๋”ฐ๋ผ์„œ, ๋ณธ ์—ฐ๊ตฌ๋ฅผ ํ†ตํ•ด ์ •๋ถ€์˜ ์ˆ˜์†Œ์ฐจ ํ™•๋Œ€ ๋ณด๊ธ‰ ์ •์ฑ…์— ๋Œ€ํ•œ ๋ฐฉํ–ฅ์„ฑ์„ ์‚ดํŽด๋ณด๊ณ ์ž ํ•œ๋‹ค. ๋ณธ ์—ฐ๊ตฌ๋Š” ์—ฌ๋Ÿฌ ์„ ํ–‰์—ฐ๊ตฌ ๋ถ„์„์„ ํ†ตํ•ด ๋„์ถœ๋œ ์ˆ˜์†Œ์ฐจ์˜ 4๊ฐ€์ง€ ์™ธ์  ์†์„ฑ(๊ฒฝ์ œ์„ฑ, ๊ธฐ๋Šฅ์„ฑ, ์„œ๋น„์Šค, ๊ฐ€์น˜์„ฑ)์ด ์ˆ˜์†Œ์ฐจ์˜ ๊ตฌ๋งค ์˜๋„์— ๊ธฐ๋ณธ์ ์œผ๋กœ ๋ฏธ์น˜๋Š” ์˜ํ–ฅ์„ ๋ถ„์„ํ•˜๊ณ ์ž ํ•˜์˜€๋‹ค. ๋˜ํ•œ, ์ •๋ถ€์—์„œ ์ˆ˜์†Œ์ฐจ ๋ณด๊ธ‰์„ ์œ„ํ•ด ํ•ต์‹ฌ์ ์œผ๋กœ ์ถ”์ง„ํ•˜๊ณ  ์žˆ๋Š” ์ถฉ์ „์ธํ”„๋ผ ํ™•์ถฉ๊ณผ ๊ตฌ๋งค ๋ณด์กฐ๊ธˆ ์ •์ฑ…์ด ์ˆ˜์†Œ์ฐจ์˜ ๊ตฌ๋งค ์˜๋„์— ๋ฏธ์น˜๋Š” ์˜ํ–ฅ๊ณผ ์ด๋Ÿฐ ์ •๋ถ€์˜ ์ •์ฑ…๋“ค์ด ์ˆ˜์†Œ์ฐจ์˜ ์™ธ์  ์†์„ฑ๊ณผ ๊ตฌ๋งค ์˜๋„๊ฐ„์˜ ๊ด€๊ณ„์— ์–ด๋– ํ•œ ์กฐ์ ˆํšจ๊ณผ๋ฅผ ๊ฐ€์ง€๋Š”์ง€๋ฅผ ๊ฒ€์ฆํ•˜๊ณ ์ž ํ•˜์˜€๋‹ค. ๋ณธ ์—ฐ๊ตฌ๋ฅผ ์œ„ํ•ด ์ˆ˜์†Œ์ฐจ ์ด์šฉ์ž๋ฅผ ๋Œ€์ƒ์œผ๋กœ ์˜จ๋ผ์ธ ๋ฐ ์˜คํ”„๋ผ์ธ ์„ค๋ฌธ์กฐ์‚ฌ๋ฅผ ๋ณ‘ํ–‰ํ•˜์—ฌ ๋ฐ์ดํ„ฐ๋ฅผ ์ˆ˜์ง‘ํ•˜๊ณ  ๋ถ„์„ํ•˜์˜€๋‹ค. ํ†ต๊ณ„์  ๋ถ„์„๋ฐฉ๋ฒ•์œผ๋กœ๋Š” ์ธ๊ตฌํ†ต๊ณ„ํ•™์  ํŠน์„ฑ ํŒŒ์•…์„ ์œ„ํ•ด ๋นˆ๋„๋ถ„์„์„ ์‹œํ–‰ํ•˜์˜€๊ณ , ์„ค๋ฌธ ๊ตฌ์„ฑํ•ญ๋ชฉ์˜ ํƒ€๋‹น์„ฑ ํ™•๋ณด๋ฅผ ์œ„ํ•ด ์š”์ธ๋ถ„์„ ๋ฐ ์‹ ๋ขฐ๋„๋ถ„์„์„ ์‹ค์‹œํ•˜์—ฌ, ์—ฐ๊ตฌ๋ชจํ˜•์„ ์ ํ•ฉ์„ฑ์„ ๊ฒ€์ฆํ•˜์˜€๋‹ค. ๋˜ํ•œ, ๊ฐ€์„ค ๊ฒ€์ฆ ๋‹จ๊ณ„์—์„œ ์ˆ˜์†Œ์ฐจ์˜ ์™ธ์  ์†์„ฑ๊ณผ ์ •๋ถ€์˜ ์ •์ฑ…์ด ์ˆ˜์†Œ์ฐจ์˜ ๊ตฌ๋งค ์˜๋„์— ์–ด๋– ํ•œ ์ง์ ‘์ ์ธ ์˜ํ–ฅ์„ ๋ฏธ์น˜๋Š” ์ง€ ํ™•์ธํ•˜๊ธฐ ์œ„ํ•ด ๋‹ค์ค‘ํšŒ๊ท€๋ถ„์„์„ ํ•˜์˜€๊ณ , ํŠนํžˆ, ์ •๋ถ€์˜ ์ •์ฑ…์˜ ์กฐ์ ˆํšจ๊ณผ์— ๋Œ€ํ•œ ๊ฐ€์„ค๊ฒ€์ฆ์„ ์œ„ํ•ด ์œ„๊ณ„์  ํšŒ๊ท€๋ถ„์„์„ ์‹œํ–‰ํ•˜์˜€๋‹ค. ๋ณธ ์—ฐ๊ตฌ์˜ ๊ฒฐ๊ณผ๋Š” ๋‹ค์Œ๊ณผ ๊ฐ™์ด ์š”์•ฝํ•  ์ˆ˜ ์žˆ๋‹ค. ๋จผ์ €, ์ˆ˜์†Œ์ฐจ์˜ ์™ธ์  ์†์„ฑ์ด ๊ตฌ๋งค ์˜๋„์— ์ •(+)์˜ ์˜ํ–ฅ์„ ๋ฏธ์น  ๊ฑฐ๋ผ๋Š” ๊ฐ€์„ค์€ ๋Œ€๋ถ€๋ถ„ ์ง€์ง€๋˜์—ˆ๋‹ค. ๊ตฌ์ฒด์ ์œผ๋กœ ์ˆ˜์†Œ์ฐจ์˜ ๊ฒฝ์ œ์„ฑ, ๊ธฐ๋Šฅ์„ฑ, ๊ฐ€์น˜์„ฑ ์ˆœ์„œ๋Œ€๋กœ ๊ตฌ๋งค ์˜๋„์— ํฐ ์˜ํ–ฅ์„ ๋ฏธ์น˜๋Š” ๊ฒƒ์œผ๋กœ ๋ถ„์„๋˜์—ˆ๋‹ค. ์„œ๋น„์Šค ๋ถ€๋ถ„์€ ์ˆ˜์†Œ์ฐจ ์ด์šฉ์ž๋“ค์ด ๊ฐ€์žฅ ๋ถˆ๋งŒ์กฑ์Šค๋Ÿฝ๊ฒŒ ์ƒ๊ฐ๋˜๊ณ  ์žˆ๋Š” ์š”์†Œ์ธ ๊ฒƒ์„ ๊ฐ์•ˆํ•  ๋•Œ, ๊ตฌ๋งค ์˜๋„์™€ ์ง์ ‘์ ์ธ ์˜ํ–ฅ๋ ฅ์ด ์—†์Œ์„ ํ™•์ธํ•˜์˜€๋‹ค. ๋˜ํ•œ, ์ •๋ถ€์˜ ์ˆ˜์†Œ์ฐจ ํ™•๋Œ€ ์ •์ฑ…์ธ ์ถฉ์ „์ธํ”„๋ผ ํ™•์ถฉ๊ณผ ๊ตฌ๋งค ๋ณด์กฐ๊ธˆ ์ •์ฑ…์€ ๋ชจ๋‘ ์ˆ˜์†Œ์ฐจ์˜ ๊ตฌ๋งค ์˜๋„์— ์ƒ๋‹นํ•œ ์ •(+)์˜ ์˜ํ–ฅ์„ ๋ฏธ์น˜๋Š” ๊ฒƒ์œผ๋กœ ๋‚˜ํƒ€๋‚ฌ๋‹ค. ํŠนํžˆ, ์ถฉ์ „์ธํ”„๋ผ ํ™•์ถฉ์˜ ์ •๋„๊ฐ€ ์ˆ˜์†Œ์ฐจ์˜ ์™ธ์  ์†์„ฑ ์ค‘ ๊ฒฝ์ œ์„ฑ์ด ๊ตฌ๋งค ์˜๋„์— ๋ฏธ์น˜๋Š” ์˜ํ–ฅ๋ ฅ์„ ์กฐ์ ˆํ•˜๋Š” ๊ฒƒ์œผ๋กœ ๋‚˜ํƒ€๋‚ฌ๋‹ค. ์ˆ˜์†Œ์ถฉ์ „์†Œ ๊ฑฐ๋ฆฌ์™€ ๊ฒฝ์ œ์„ฑ ๋ณ€์ˆ˜์˜ ์ƒํ˜ธ์ž‘์šฉํ•ญ์„ ํ†ตํ•ด ์กฐ์ ˆํšจ๊ณผ๋ฅผ ๋ถ„์„ํ•ด๋ณธ ๊ฒฐ๊ณผ, ๋Œ€๋ฆฝ์กฐ์ ˆํšจ๊ณผ๋ฅผ ๊ฐ€์ง€๋Š” ๊ฒƒ์œผ๋กœ ๋‚˜ํƒ€๋‚ฌ๋Š”๋ฐ, ์ด๊ฒƒ์€ ์ˆ˜์†Œ์ถฉ์ „์†Œ ๊ฑฐ๋ฆฌ๊ฐ€ ๊ฐ€๊นŒ์šด ์ง‘๋‹จ์€ ๊ทธ๋ ‡์ง€ ์•Š์€ ์ง‘๋‹จ์— ๋น„ํ•ด ์ˆ˜์†Œ์ฐจ์˜ ๊ฒฝ์ œ์„ฑ์ด ๊ตฌ๋งค ์˜๋„์— ๋ฏธ์น˜๋Š” ๊ธ์ •์ ์ธ ์˜ํ–ฅ๋ ฅ์˜ ํฌ๊ธฐ๊ฐ€ ๋‚ฎ๋‹ค๋Š” ๊ฒƒ์„ ํ™•์ธํ•  ์ˆ˜ ์žˆ์—ˆ๋‹ค. ๋ณธ ์—ฐ๊ตฌ์˜ ๊ฒฐ๊ณผ๋กœ๋ถ€ํ„ฐ ์–ป์„ ์ˆ˜ ์žˆ๋Š” ์‹œ์‚ฌ์ ์€ ๋‹ค์Œ๊ณผ ๊ฐ™๋‹ค. ์ฒซ์งธ, ๋‹ค๋ฅธ ์นœํ™˜๊ฒฝ์ฐจ์™€ ๋งˆ์ฐฌ๊ฐ€์ง€๋กœ ์ˆ˜์†Œ์ฐจ๋„ ์ดˆ๊ธฐ ๋ณด๊ธ‰ ๋‹จ๊ณ„ ์‹œ์ ์—๋Š” ํ™œ์„ฑํ™”๋ฅผ ์œ„ํ•ด์„œ ๋ณด์กฐ๊ธˆ ๋ฐ ๊ฐ์ข… ์„ธ์ œ ํ˜œํƒ ๋“ฑ ๊ฒฝ์ œ์ ์ธ ๋ถ€๋ถ„์— ๋Œ€ํ•œ ์ •์ฑ…์ ์ธ ๋ณด์กฐ ์ˆ˜๋‹จ์ด ํšจ๊ณผ์ ์œผ๋กœ ์ž‘์šฉํ•œ๋‹ค๋Š” ์‚ฌ์‹ค์ด๋‹ค. ๋‘˜์งธ, ๊ฐ™์€ ์นœํ™˜๊ฒฝ์ฐจ์ธ ์ „๊ธฐ์ฐจ์˜ ๋‹จ์ ์„ ๋ณด์™„ํ•˜๊ธฐ ์œ„ํ•ด ๊ธ‰์†ํ•˜๊ฒŒ ํ™•์‚ฐ์„ ์ถ”์ง„ํ•˜๊ณ  ์žˆ๋Š” ์ˆ˜์†Œ์ฐจ์˜ ํƒœ์ƒ์ ์ธ ํŠน์„ฑ์„ ๊ฐ์•ˆํ•  ๋•Œ, ์ถฉ์ „ ์ธํ”„๋ผ์˜ ํ™•์ถฉ์„ ์œ„ํ•œ ์ •๋ถ€์˜ ์ •์ฑ…์€ ์ˆ˜์†Œ์ฐจ์˜ ๊ตฌ๋งค ์˜๋„๋ฅผ ๋†’์ด๊ธฐ ์œ„ํ•œ ์ตœ์šฐ์„  ์ •์ฑ…์ž„์„ ์ฃผ์ง€ํ•ด์•ผ ํ•œ๋‹ค. ์…‹์งธ, ์ •๋ถ€์˜ ์ˆ˜์†Œ์ฐจ ๋ณด๊ธ‰์„ ์œ„ํ•œ ๋‘๊ฐ€์ง€ ์ •์ฑ…์˜ ์กฐํ™”๋กœ์šด ์‹œํ–‰ ๋ฐฉ์•ˆ์„ ๊ณ ๋ฏผํ•ด ๋ณผ ์ˆ˜ ์žˆ๋‹ค. ์ฆ‰, ๊ทธ๊ฐ„ ์ˆ˜์†Œ์ฐจ ๋ณด๊ธ‰์— ์†Œ๊ทน์ ์ธ ์ง€์ž์ฒด๋ฅผ ์ค‘์‹ฌ์œผ๋กœ ์ถฉ์ „ ์ธํ”„๋ผ ์‹ ๊ทœ ํ™•์ถฉ์— ์ค‘์•™์ •๋ถ€ ์ฃผ๋„๋กœ ๋” ์ง‘์ค‘ํ•˜๊ณ , ์ƒ๋Œ€์ ์œผ๋กœ ์ถฉ์ „ ์ธํ”„๋ผ๊ฐ€ ์ž˜ ๊ฐ–์ถฐ์ง„ ์ง€์—ญ์—๋Š” ๊ตฌ๋งค ๋ณด์กฐ๊ธˆ ํ™•๋Œ€ ์ •์ฑ…์œผ๋กœ ์ง‘์ค‘ํ•ด ์•ˆ์ •์ ์ธ ์ˆ˜์†Œ์ฐจ ๋ณด๊ธ‰์— ๋‚˜์„œ๊ณ , ์•„์šธ๋Ÿฌ ์ˆ˜์†Œ์ถฉ์ „์†Œ ์šด์˜์— ์ถฉ๋ถ„ํ•œ ๊ฒฝ์ œ์„ฑ์ด ํ™•๋ณด๋˜๋„๋ก ํ•˜์—ฌ, ๋ฏผ๊ฐ„์—์„œ ์ฃผ๋„ํ•˜๋Š” ์ถฉ์ „ ์ธํ”„๋ผ ํ™•์ถฉ ๋ฐฉํ–ฅ์˜ ์‹œ๋„ˆ์ง€๋ฅผ ์ค„ ์ˆ˜ ์žˆ๋„๋ก ์œ ๋„ํ•ด์•ผ ํ•  ๊ฒƒ์ด๋‹ค.์ œ 1 ์žฅ ์„œ ๋ก  1 ์ œ 1 ์ ˆ ์—ฐ๊ตฌ๋ฐฐ๊ฒฝ ๋ฐ ๋ชฉ์  1 ์ œ 2 ์ ˆ ์—ฐ๊ตฌ๋ฒ”์œ„ ๋ฐ ๊ตฌ์„ฑ 5 ์ œ 2 ์žฅ ์ด๋ก ์  ๋ฐฐ๊ฒฝ ๋ฐ ์„ ํ–‰์—ฐ๊ตฌ ๊ฒ€ํ†  6 ์ œ 1 ์ ˆ ์ด๋ก ์  ๋ฐฐ๊ฒฝ 6 1. ์ˆ˜์†Œ๊ฒฝ์ œ 6 2. ์ˆ˜์†Œ๊ฒฝ์ œ ํ™œ์„ฑํ™” ๋กœ๋“œ๋งต 7 3. ์ˆ˜์†Œ์ฐจ(์ˆ˜์†Œ์—ฐ๋ฃŒ์ „์ง€์ž๋™์ฐจ) 8 4. ์ˆ˜์†Œ์ถฉ์ „์†Œ 9 ์ œ 2 ์ ˆ ์„ ํ–‰์—ฐ๊ตฌ ๊ฒ€ํ†  13 1. ์‹œ์žฅ๊ณผ ์ •๋ถ€์˜ ์—ญํ•  ๊ด€๋ จ ์—ฐ๊ตฌ 13 2. ์ •๋ถ€์˜ ์ˆ˜์†Œ์ฐจ ๋ณด๊ธ‰ ์ •์ฑ… ์—ฐ๊ตฌ 14 3. ์ˆ˜์†Œ์ฐจ์˜ ์™ธ์  ์†์„ฑ 16 4. ์ˆ˜์†Œ์ฐจ์˜ ๊ตฌ๋งค ์˜๋„ 20 ์ œ 3 ์žฅ ์—ฐ๊ตฌ์„ค๊ณ„ ๋ฐ ๋ถ„์„๋ฐฉ๋ฒ• 23 ์ œ 1 ์ ˆ ๋ถ„์„์˜ ํ‹€ ๋ฐ ๊ฐ€์„ค ์„ค์ • 23 1. ์—ฐ๊ตฌ๋ถ„์„์˜ ํ‹€ 23 2. ์—ฐ๊ตฌ๊ฐ€์„ค ์„ค์ • 24 ์ œ 2 ์ ˆ ๋ณ€์ˆ˜์˜ ์กฐ์ž‘์  ์ •์˜ 27 1. ์ข…์†๋ณ€์ˆ˜ : ๊ตฌ๋งค ์˜๋„ 27 2. ๋…๋ฆฝ๋ณ€์ˆ˜ : ์ˆ˜์†Œ์ฐจ์˜ ์™ธ์  ์†์„ฑ 27 3. ์กฐ์ ˆ๋ณ€์ˆ˜ : ์ •๋ถ€์˜ ์ •์ฑ… 28 4. ํ†ต์ œ๋ณ€์ˆ˜ 29 ์ œ 3 ์ ˆ ์ž๋ฃŒ์˜ ์ˆ˜์ง‘ ๋ฐ ๋ถ„์„๋ฐฉ๋ฒ• 31 1. ์ž๋ฃŒ์˜ ์ˆ˜์ง‘ ๋ฐฉ๋ฒ• 31 2. ์„ค๋ฌธ์ง€ ๊ตฌ์„ฑ 32 3. ๋ถ„์„๋Œ€์ƒ์˜ ์„ ์ • 33 4. ์ž๋ฃŒ๋ถ„์„ ๋ฐฉ๋ฒ• 34 ์ œ 4 ์ ˆ ์ธก์ •๋„๊ตฌ์˜ ํƒ€๋‹น์„ฑ ๋ถ„์„ 35 1. ์ข…์†๋ณ€์ˆ˜์˜ ์š”์ธ๋ถ„์„ 36 2. ๋…๋ฆฝ๋ณ€์ˆ˜์˜ ์š”์ธ๋ถ„์„ 36 3. ์—ฐ๊ตฌ๋ชจํ˜• ์ˆ˜์ • 38 ์ œ 4 ์žฅ ์—ฐ๊ตฌ ๋ถ„์„ ๋ฐ ๊ฒฐ๊ณผ 41 ์ œ 1 ์ ˆ ๊ธฐ์ˆ ํ†ต๊ณ„ ๋ถ„์„ 41 1. ์ข…์†๋ณ€์ˆ˜ 41 2. ๋…๋ฆฝ๋ณ€์ˆ˜ 43 3. ์กฐ์ ˆ๋ณ€์ˆ˜ 48 ์ œ 2 ์ ˆ ์‹ ๋ขฐ๋„ ๋ถ„์„ 50 ์ œ 3 ์ ˆ ์ƒ๊ด€ ๋ถ„์„ 52 ์ œ 4 ์ ˆ ํšŒ๊ท€๋ถ„์„ ๋ฐ ๊ฐ€์„ค์˜ ๊ฒ€์ฆ 54 1. 1๋‹จ๊ณ„ ๋ชจํ˜•๋ถ„์„ : ๊ฐ€์„ค1์˜ ๊ฒ€์ฆ 55 2. 2๋‹จ๊ณ„ ๋ชจํ˜•๋ถ„์„œ : ๊ฐ€์„ค2์˜ ๊ฒ€์ฆ 57 3. 3๋‹จ๊ณ„ ๋ชจํ˜•๋ถ„์„ : ๊ฐ€์„ค3, 4์˜ ๊ฒ€์ฆ 59 4. ๊ฐ€์„ค ๊ฒ€์ฆ ๊ฒฐ๊ณผ 66 ์ œ 5 ์žฅ ๊ฒฐ๋ก  67 ์ œ 1 ์ ˆ ์—ฐ๊ตฌ๊ฒฐ๊ณผ์˜ ์š”์•ฝ 67 ์ œ 2 ์ ˆ ์—ฐ๊ตฌ์˜ ์˜์˜ ๋ฐ ์‹œ์‚ฌ์  71 ์ œ 3 ์ ˆ ์—ฐ๊ตฌ์˜ ํ•œ๊ณ„ ๋ฐ ํ–ฅํ›„ ์—ฐ๊ตฌ ๊ณผ์ œ 74 ์ฐธ๊ณ ๋ฌธํ—Œ 76 ๋ถ€๋ก(์„ค๋ฌธ์ง€) 79 Abstract 83์„

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    ํ•™์œ„๋…ผ๋ฌธ (์„์‚ฌ) -- ์„œ์šธ๋Œ€ํ•™๊ต ๋Œ€ํ•™์› : ํ–‰์ •๋Œ€ํ•™์› ๊ณต๊ธฐ์—…์ •์ฑ…ํ•™๊ณผ, 2020. 8. ๊ตฌ๋ฏผ๊ต.๋ณธ ์—ฐ๊ตฌ์˜ ๋ชฉ์ ์€ ์˜ˆ๋น„ํƒ€๋‹น์„ฑ์กฐ์‚ฌ ์ œ๋„ ๊ฐœํŽธ๋ฐฉ์•ˆ(๊ธฐํš์žฌ์ •๋ถ€ ๋“ฑ, 2019. 4.) ์ค‘ ์ˆ˜๋„๊ถŒ/๋น„์ˆ˜๋„๊ถŒ ํ‰๊ฐ€ํ•ญ๋ชฉ ๋น„์ค‘ ์ด์›ํ™”์˜ ํšจ๊ณผ๋ฅผ ๋ถ„์„ํ•˜์—ฌ ์ •์ฑ…์ง‘ํ–‰์˜ ํšจ์šฉ์„ฑ์„ ๋ฏธ๋ฆฌ ์˜ˆ์ธกํ•˜๊ณ , ์•ž์œผ๋กœ์˜ ์‹œํ–‰ ๊ณผ์ •์—์„œ ๋ณด์™„ํ•ด์•ผ ํ•  ์‚ฌํ•ญ๋“ค์— ๋Œ€ํ•˜์—ฌ ๊ฒ€ํ† ํ•˜๋Š” ๊ฒƒ์ด๋‹ค. ์˜ˆ๋น„ํƒ€๋‹น์„ฑ์กฐ์‚ฌ ์ œ๋„ ๋„์ž… ์ดํ›„ 20๋…„์ด ๊ฒฝ๊ณผํ•˜๋ฉด์„œ ๊ทธ๊ฐ„์˜ ๋ณ€ํ™”๋œ ๊ฒฝ์ œโ€ค์‚ฌํšŒ์  ์—ฌ๊ฑด์„ ์ œ๋„์— ๋ฐ˜์˜ํ•ด์•ผ ํ•  ํ•„์š”์„ฑ์ด ์ œ๊ธฐ๋จ์— ๋”ฐ๋ผ ์ •๋ถ€๋Š” ๊ตญ๊ฐ€๊ท ํ˜•๋ฐœ์ „๊ณผ ๋‹ค์–‘ํ•œ ์‚ฌํšŒ์  ๊ฐ€์น˜์— ๋Œ€ํ•œ ์‹คํ˜„ ์š”๊ตฌ๊ฐ€ ์ฆ๋Œ€ํ•˜๊ณ  ์žˆ๋‹ค๊ณ  ํŒ๋‹จํ•˜๊ณ  ์žˆ๋‹ค. ์ด์— ์ •๋ถ€๋Š” ์ข…ํ•ฉํ‰๊ฐ€ ๋น„์ค‘์„ ๊ฐœํŽธํ•˜์—ฌ ์ˆ˜๋„๊ถŒ/๋น„์ˆ˜๋„๊ถŒ์˜ ํ‰๊ฐ€๋ฅผ ์ด์›ํ™”ํ•˜๊ณ  ์ด๋ฅผ ํ†ตํ•˜์—ฌ ์ง€๋ฐฉ์˜ ๋‚™ํ›„์ง€์—ญ์„ ๋ฐฐ๋ คํ•˜๊ณ ์ž ํ•˜์˜€๋‹ค. ๊ทธ๋Ÿฌ๋‚˜ ์ •๋ถ€์—์„œ ์–˜๊ธฐํ•˜๋Š” ๋น„์ˆ˜๋„๊ถŒ์ด ๊ผญ ๋‚™ํ›„์ง€์—ญ์€ ์•„๋‹ ๊ฒƒ์ด๋ผ๋Š” ์˜๋ฌธ์ด ์žˆ๋Š” ๋งŒํผ, ๊ด€๋ จ ๊ฐœํŽธ๋ฐฉ์•ˆ์˜ ์ˆ˜๋„๊ถŒ/๋น„์ˆ˜๋„๊ถŒ์˜ ์ด์›ํ™”์™€ ํ•จ๊ป˜ ๋ฒ•์  ๊ฐœ๋…์— ๊ทผ๊ฑฐํ•œ ๋‚™ํ›„์ง€์—ญ/๋น„๋‚™ํ›„์ง€์—ญ์˜ ๊ตฌ๋ถ„์„ ํ†ตํ•˜์—ฌ ์ •๋ถ€ ์ •์ฑ…์˜ ๋ชฉํ‘œ ์‹คํ˜„ ๊ฐ€๋Šฅ์„ฑ์„ ๊ฒ€ํ† ํ•ด๋ณด์•˜๋‹ค. ์ด๋ฅผ ์œ„ํ•˜์—ฌ 2009๋…„ 1์›”๋ถ€ํ„ฐ 2019๋…„ 7์›”๊นŒ์ง€ ๋ฐœ๊ฐ„๋œ ์˜ˆ๋น„ํƒ€๋‹น์„ฑ์กฐ์‚ฌ๋ณด๊ณ ์„œ๋ฅผ ์ˆ˜์ง‘ํ•˜์—ฌ ์ด 377๊ฐœ ํ‘œ๋ณธ ์‚ฌ์—…์— ๋Œ€ํ•œ ๋ถ„์„์„ ์‹œํ–‰ํ•˜์˜€๋‹ค. ๋จผ์ €, ์ œ๋„ ๊ฐœํŽธ ์ „์˜ AHP ์ข…ํ•ฉํ‰์  ๋ฐ ๊ฒฝ์ œ์„ฑ ์‹œํ–‰ํ‰์ ์„ ์ˆ˜๋„๊ถŒ/๋น„์ˆ˜๋„๊ถŒ์œผ๋กœ ๊ตฌ๋ถ„ํ•˜์—ฌ ๋น„๊ตํ•œ ๊ฒฐ๊ณผ, ์–‘ ๊ถŒ์—ญ ๊ฐ„์— ์˜ˆ๋น„ํƒ€๋‹น์„ฑ์กฐ์‚ฌ AHP ์ข…ํ•ฉํ‰์ ์€ ํ†ต๊ณ„์ ์œผ๋กœ ์œ ์˜ํ•œ ์ฐจ์ด๊ฐ€ ์—†์—ˆ์œผ๋ฉฐ, ๊ฒฝ์ œ์„ฑ ์‹œํ–‰ํ‰์ ์€ ์ˆ˜๋„๊ถŒ ์‚ฌ์—…์ด ๋น„์ˆ˜๋„๊ถŒ ์‚ฌ์—…์— ๋น„ํ•˜์—ฌ 17.5% ๋†’์•˜๋‹ค. ์ด๋ฅผ ๋‚™ํ›„์ง€์—ญ/๋น„๋‚™ํ›„์ง€์—ญ์œผ๋กœ ๋‹ค์‹œ ๊ตฌ๋ถ„ํ•˜์—ฌ ๋น„๊ตํ•œ ๊ฒฐ๊ณผ, ์–‘ ๊ถŒ์—ญ ๊ฐ„์— ์˜ˆ๋น„ํƒ€๋‹น์„ฑ์กฐ์‚ฌ AHP ์ข…ํ•ฉํ‰์ ์€ ํ†ต๊ณ„์ ์œผ๋กœ ์œ ์˜ํ•œ ์ฐจ์ด๊ฐ€ ์—†์—ˆ์œผ๋ฉฐ, ๊ฒฝ์ œ์„ฑ ์‹œํ–‰ํ‰์ ์€ ๋น„๋‚™ํ›„์ง€์—ญ ์‚ฌ์—…์ด ๋‚™ํ›„์ง€์—ญ ์‚ฌ์—…์— ๋น„ํ•˜์—ฌ 55.2% ๋†’์•˜๋‹ค. ์ƒ๋Œ€์ ์œผ๋กœ ์†Œ์™ธ๋œ ์ง€์—ญ์ด๋ผ ํ•  ์ˆ˜ ์žˆ๋Š” ๋น„์ˆ˜๋„๊ถŒ์ด๋‚˜ ๋‚™ํ›„์ง€์—ญ์ด ์ˆ˜๋„๊ถŒ์ด๋‚˜ ๋น„๋‚™ํ›„์ง€์—ญ์— ๋น„ํ•˜์—ฌ ์˜ˆ๋น„ํƒ€๋‹น์„ฑ์กฐ์‚ฌ์— ๋”ฐ๋ฅธ AHP ์ข…ํ•ฉํ‰์ ์ด ๊ฒฐ์ฝ” ๋‚ฎ์€ ์ˆ˜์ค€์ด ์•„๋‹ˆ๋ผ๋Š” ๊ฒƒ์„ ์•Œ ์ˆ˜ ์žˆ์—ˆ๋‹ค. ๋˜ํ•œ, ๊ฒฝ์ œ์„ฑ ์‹œํ–‰ํ‰์ ์€ ๋น„์ˆ˜๋„๊ถŒ ์ง€์—ญ ๋ณด๋‹ค๋Š” ๋‚™ํ›„์ง€์—ญ์ด ์ƒ๋Œ€์ ์œผ๋กœ ๋” ๋‚ฎ์€ ํ‰์ ์„ ๊ธฐ๋กํ•˜๊ณ  ์žˆ์Œ์„ ์•Œ ์ˆ˜ ์žˆ์—ˆ๋‹ค. ์˜ˆ๋น„ํƒ€๋‹น์„ฑ์กฐ์‚ฌ ์ œ๋„ ๊ฐœํŽธ์˜ ํšจ๊ณผ๋ฅผ ๊ฒ€์ฆํ•˜๊ธฐ ์œ„ํ•˜์—ฌ ๊ธฐ์กด์˜ ์‚ฌ์—…๋“ค์„ ์ˆ˜๋„๊ถŒ๊ณผ ๋น„์ˆ˜๋„๊ถŒ, ๋‚™ํ›„์ง€์—ญ๊ณผ ๋น„๋‚™ํ›„์ง€์—ญ์˜ ์‚ฌ์—…์œผ๋กœ ์žฌ๋ถ„๋ฅ˜ํ•˜์—ฌ ์‹œ๋ฎฌ๋ ˆ์ด์…˜์„ ์‹œํ–‰ํ•˜์˜€๋‹ค. ๊ธฐ์กด์˜ ์˜ˆ๋น„ํƒ€๋‹น์„ฑ์กฐ์‚ฌ๋ณด๊ณ ์„œ๋ฅผ ํ†ตํ•˜์—ฌ ๊ฐ ์‚ฌ์—…์˜ ํ‰๊ฐ€ํ•ญ๋ชฉ๋ณ„ ํ‰์ ๊ณผ ๊ฐ€์ค‘์น˜๋ฅผ ์‚ฐ์ถœํ•˜์˜€๊ณ , ์ด๋ฅผ ๊ฐœํŽธ๋œ ์ œ๋„์— ์ ์šฉํ•˜์—ฌ ์ƒˆ๋กœ์šด ๊ฐ€์ค‘์น˜ ๋ถ€์—ฌ ํ›„, ๆ–ฐ AHP ์ข…ํ•ฉํ‰์ ์„ ์‚ฐ์ •ํ•˜์˜€๋‹ค. ์˜ˆ๋น„ํƒ€๋‹น์„ฑ์กฐ์‚ฌ ์ œ๋„ ๊ฐœํŽธ ์ „โ€คํ›„์˜ AHP ์ข…ํ•ฉํ‰์ ์„ ๋น„๊ตํ•œ ๊ฒฐ๊ณผ, ๋น„์ˆ˜๋„๊ถŒ ์‚ฌ์—…์˜ AHP ์ข…ํ•ฉํ‰์ ์€ ์ œ๋„ ๊ฐœํŽธ ์ „ ๋Œ€๋น„ 4.8% ์ƒ์Šนํ•˜์˜€์œผ๋ฉฐ ์ด๋Š” ํ†ต๊ณ„์ ์œผ๋กœ๋„ ์œ ์˜ํ•œ ๊ฒฐ๊ณผ์˜€๋‹ค. ๋น„์ˆ˜๋„๊ถŒ ๋‚ด ๋‚™ํ›„์ง€์—ญ๊ณผ ๋น„๋‚™ํ›„์ง€์—ญ์„ ๊ตฌ๋ถ„ํ•˜์—ฌ ๋น„๊ตํ•ด๋ณด๋ฉด, ๋‚™ํ›„์ง€์—ญ์€ ์ œ๋„ ๊ฐœํŽธ ์ „ ๋Œ€๋น„ 7.4%, ๋น„๋‚™ํ›„์ง€์—ญ์€ 1.6% ์ƒ์Šนํ•˜์˜€์œผ๋ฉฐ ๋ชจ๋‘ ํ†ต๊ณ„์ ์œผ๋กœ๋„ ์œ ์˜ํ•œ ๊ฒฐ๊ณผ์˜€๋‹ค. ๊ฒฐ๊ตญ, ๊ฒฝ์ œ์„ฑ ํ‰๊ฐ€์˜ ๋น„์ค‘ ์กฐ์ •์€ ๋น„์ˆ˜๋„๊ถŒ๊ณผ ๋‚™ํ›„์ง€์—ญ์— ๋ชจ๋‘ ์œ ๋ฆฌํ•˜๊ฒŒ ์ž‘์šฉํ•  ๊ฒƒ์œผ๋กœ ํŒ๋‹จ๋œ๋‹ค. AHP ์ข…ํ•ฉํ‰์ ์˜ ๋ณ€๋™์— ๋”ฐ๋ฅธ ์˜ˆ๋น„ํƒ€๋‹น์„ฑ์กฐ์‚ฌ ํ†ต๊ณผ์œจ์€ ๋น„์ˆ˜๋„๊ถŒ, ํŠนํžˆ ๋‚™ํ›„์ง€์—ญ์—์„œ ๊ธ‰๊ฒฉํžˆ ์ƒ์Šนํ•˜๋Š” ๊ฒƒ์œผ๋กœ ๋‚˜ํƒ€๋‚ฌ๋‹ค. ์ •๋ถ€์—์„œ ์˜ˆ๋น„ํƒ€๋‹น์„ฑ์กฐ์‚ฌ ํ‰๊ฐ€ํ•ญ๋ชฉ์˜ ์ˆ˜๋„๊ถŒ/๋น„์ˆ˜๋„๊ถŒ ์ด์›ํ™”๋ฅผ ์ถ”์ง„ํ•˜๋Š” ๋ชฉ์ ์€ ๋‚™ํ›„์ง€์—ญ์— ๋Œ€ํ•œ ๋ฐฐ๋ ค์ด๋‹ค. ๋ณธ ์—ฐ๊ตฌ์˜ ๊ฒฐ๊ณผ์—์„œ ๋‚˜ํƒ€๋‚ฌ๋“ฏ์ด ํ™•์‹คํ•˜๊ณ  ์ •ํ™•ํ•œ ๋ชฉ์ ์˜ ๋‹ฌ์„ฑ์„ ์œ„ํ•ด์„œ๋Š” ์ˆ˜๋„๊ถŒ/๋น„์ˆ˜๋„๊ถŒ์˜ ๊ตฌ๋ถ„๋ณด๋‹ค๋Š” ๋‚™ํ›„์ง€์—ญ/๋น„๋‚™ํ›„์ง€์—ญ์˜ ๊ถŒ์—ญ ๊ตฌ๋ถ„์ด ์ •์ฑ… ๋ชฉํ‘œ๋ฅผ ๋‹ฌ์„ฑํ•˜๋Š” ๋ฐ์— ๋ณด๋‹ค ํšจ๊ณผ์ ์œผ๋กœ ๊ธฐ์—ฌํ•  ์ˆ˜ ์žˆ์„ ๊ฒƒ์ด๋‹ค.The purpose of this study is to predict the effectiveness of the policy implementation in advance by analyzing the effects of the dualization of the proportion of assessment items in metropolitan/non-metropolitan areas in the plan to reform the preliminary feasibility study system, and to review matters that need to be supplemented in the future implementation process. As 20 years have passed since the introduction of the preliminary feasibility study system, there is a need to reflect the changed economic and social conditions in the system. As a result, the government judges that calls for balanced national development and realization of various social values are increasing. In response, the government intended to dualize the evaluation of metropolitan and non-metropolitan areas by reorganizing the proportion of comprehensive assessment, thereby considering underdeveloped areas in the provinces. However, there is a question that the non-metropolitan area, which the government says, is not necessarily an underdeveloped area. Thus, along with the above-mentioned reform measures, we reviewed the feasibility of realizing the goals of government policies through the classification of underdeveloped/non-underdeveloped areas based on legal concepts. For this purpose, a total of 377 sample projects were analyzed by collecting preliminary feasibility study reports published from January 2009 to July 2019. First of all, I compared AHP's overall score and economic feasibility evaluation score before the system reform by dividing it into metropolitan and non-metropolitan areas. As a result, there was no statistically significant difference in the preliminary feasibility study AHP overall score between the two regions, and the economic feasibility evaluation score was 17.5% higher than that of non-metropolitan area. As a result of comparing them again by dividing them into underdeveloped/non-underdeveloped areas, the preliminary feasibility study AHP overall scores between the two regions showed no statistically significant difference, and the economic feasibility evaluation score was 55.2% higher than that of underdeveloped area. I could see that AHP's overall score based on preliminary feasibility studies in non-metropolitan areas or underdeveloped areas, which are relatively marginalized areas, was never lower than that of metropolitan areas or non-underdeveloped areas. Also, I could see that the economic evaluation score of underdeveloped areas was relatively lower than that of non-metropolitan areas. As another task, the simulation was conducted by reclassifying existing projects into those of metropolitan/non-metropolitan area, and underdeveloped/non-underdeveloped area, to verify the effectiveness of the preliminary feasibility study system reform. The scores and weights for each project were calculated through the existing preliminary feasibility study reports. In addition, the existing weights were applied to the revised system to give new weights to calculate the new AHP overall score. Based on the above process, we compared the AHP overall scores before and after the reorganization of the preliminary feasibility study system. The overall AHP score for non-metropolitan projects rose 4.8% compared to the period before the system was reorganized, which was also a statistically significant. Comparing underdeveloped and non-underdeveloped in non-metropolitan areas, the overall AHP score for projects in underdeveloped areas rose 7.4% compared to before the system was reformed, while that for non-underdeveloped areas rose 1.6%. And they were all statistically significant results. After all, the adjustment of the weight of economic assessment is expected to benefit both non-metropolitan areas and underdeveloped areas. The passing rate of preliminary feasibility studies due to changes in AHP overall scores has been shown to rise sharply in non-metropolitan areas, especially in underdeveloped areas. The purpose of the government's push for the dualization of preliminary feasibility study assessment items between metropolitan and non-metropolitan areas is to provide consideration for underdeveloped areas. As shown in the results of this study, in order to achieve a clear and accurate purpose, the division of areas in underdeveloped/non-underdeveloped areas could contribute more effectively to achieving policy goals than in the metropolitan/non-metropolitan areas.์ œ 1 ์žฅ ์„œ๋ก  1 ์ œ 1 ์ ˆ ์—ฐ๊ตฌ์˜ ๋ฐฐ๊ฒฝ ๋ฐ ๋ชฉ์  1 ์ œ 2 ์ ˆ ์—ฐ๊ตฌ์˜ ๋ฒ”์œ„ ๋ฐ ๋ฐฉ๋ฒ• 5 ์ œ 2 ์žฅ ์ด๋ก ์  ๋ฐฐ๊ฒฝ ๋ฐ ์„ ํ–‰์—ฐ๊ตฌ ๋ถ„์„ 10 ์ œ 1 ์ ˆ ์˜ˆ๋น„ํƒ€๋‹น์„ฑ์กฐ์‚ฌ์™€ ๋‚™ํ›„์ง€์—ญ ๊ด€๋ จ ์ด๋ก ์  ๋ฐฐ๊ฒฝ 10 1. ์˜ˆ๋น„ํƒ€๋‹น์„ฑ์กฐ์‚ฌ 10 2. ๋‚™ํ›„์ง€์—ญ 19 ์ œ 2 ์ ˆ ์„ ํ–‰์—ฐ๊ตฌ ๊ฒ€ํ†  26 ์ œ 3 ์ ˆ ์š”์•ฝ ๋ฐ ์—ฐ๊ตฌ์˜ ์ฐจ๋ณ„์„ฑ 28 ์ œ 3 ์žฅ ์—ฐ๊ตฌ๋ฐฉ๋ฒ• 29 ์ œ 1 ์ ˆ ์—ฐ๊ตฌ์˜ ๋ถ„์„ํ‹€ 29 1. ์—ฐ๊ตฌ๋ชจํ˜•์˜ ์„ค์ • 29 2. ์—ฐ๊ตฌ ๊ฐ€์„ค 35 ์ œ 2 ์ ˆ ์ž๋ฃŒ์ˆ˜์ง‘ ๋ฐ ๋ถ„์„๋ฐฉ๋ฒ• 36 ์ œ 4 ์žฅ ๋ถ„์„๊ฒฐ๊ณผ 37 ์ œ 1 ์ ˆ ๊ธฐ์ˆ ํ†ต๊ณ„ ๋ฐ ๋นˆ๋„ ๋ถ„์„ 37 1. ๊ธฐ์ˆ ํ†ต๊ณ„ ๋ถ„์„ 37 2. ๋นˆ๋„ ๋ถ„์„ 40 ์ œ 2 ์ ˆ ๊ฒฝ์ œ์„ฑ ํ‰๊ฐ€์˜ ์˜ํ–ฅ๋ ฅ ๋ถ„์„ 43 1. ์—ฐ๋„๋ณ„ ํ‰๊ท  B/C๋น„์œจ ๋ถ„์„ 43 2. B/C๋น„์œจ๊ณผ ์˜ˆ๋น„ํƒ€๋‹น์„ฑ์กฐ์‚ฌ ํ†ต๊ณผ์œจ ๋ถ„์„ 46 ์ œ 3 ์ ˆ ์ˆ˜๋„๊ถŒ ๊ตฌ๋ถ„๊ณผ ๋‚™ํ›„์ง€์—ญ ๊ตฌ๋ถ„์˜ ๋™์งˆ์„ฑ ๋ถ„์„ 48 1. ์ˆ˜๋„๊ถŒ/๋น„์ˆ˜๋„๊ถŒ ๊ตฌ๋ถ„์— ๋”ฐ๋ฅธ ์‚ฌ์—… ๋ถ„์„ 48 2. ๋‚™ํ›„์ง€์—ญ/๋น„๋‚™ํ›„์ง€์—ญ ๊ตฌ๋ถ„์— ๋”ฐ๋ฅธ ์‚ฌ์—… ๋ถ„์„ 50 3. ์ˆ˜๋„๊ถŒ-๋น„๋‚™ํ›„์ง€์—ญ(๋˜๋Š” ๋น„์ˆ˜๋„๊ถŒ-๋‚™ํ›„์ง€์—ญ) ๊ฐ„ ๋™์งˆ์„ฑ ๋ถ„์„ 52 ์ œ 4 ์ ˆ ํ‰๊ฐ€ํ•ญ๋ชฉ ๋น„์ค‘ ์ด์›ํ™”์˜ ํšจ๊ณผ ๋ถ„์„ 53 1. ๆ–ฐ์ œ๋„ ๊ฐœํŽธ์‹œ ํ‰๊ฐ€ํ•ญ๋ชฉ๋ณ„ ๊ฐ€์ค‘์น˜ ์˜ˆ์ธก 53 2. ๆ–ฐ์ œ๋„ ๊ฐœํŽธ์‹œ AHP ์ข…ํ•ฉํ‰์  ๋ฐ ํ†ต๊ณผ๋น„์œจ ์˜ˆ์ธก 55 ์ œ 5 ์žฅ ๊ฒฐ๋ก  56 ์ œ 1 ์ ˆ ๋ถ„์„๊ฒฐ๊ณผ์— ๋Œ€ํ•œ ๊ณ ์ฐฐ 56 ์ œ 2 ์ ˆ ์˜ˆ๋น„ํƒ€๋‹น์„ฑ์กฐ์‚ฌ ์ œ๋„ ๊ฐœํŽธ๋ฐฉ์•ˆ์— ๋Œ€ํ•œ ๊ณ ์ฐฐ 59 1. ์ˆ˜๋„๊ถŒ/๋น„์ˆ˜๋„๊ถŒ ํ‰๊ฐ€ ์ด์›ํ™” 59 2. ์ข…ํ•ฉํ‰๊ฐ€ ์ฃผ์ฒด์˜ ๋ณ€๊ฒฝ 60 ์ œ 3 ์ ˆ ์—ฐ๊ตฌ์˜ ํ•œ๊ณ„ ๋ฐ ํ–ฅํ›„ ๊ณผ์ œ 62 ์ฐธ๊ณ ๋ฌธํ—Œ 63Maste

    ํ•ด์™ธ์œ ์ „๊ฐœ๋ฐœ์‚ฌ์—… ์ง„์ถœ -ํ•œ๊ตญ์„์œ ๊ณต์‚ฌ์˜ ๋‚˜์ด์ง€๋ฆฌ์•„์‹ฌํ•ด ๊ด‘๊ตฌํ™•๋ณด ์‚ฌ๋ก€๋ถ„์„-

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    ํ•œ๊ตญ์„์œ ๊ณต์‚ฌ๋Š” 1978๋…„ ํ•œ๊ตญ์„์œ ๊ฐœ๋ฐœ๊ณต์‚ฌ๋ฒ•์˜ ๊ณตํฌํ›„ 1979๋…„์— ์„ค๋ฆฝ๋œ ์ด๋ž˜, 21์„ธ๊ธฐ ๊ตญ๊ฐ€์—๋„ˆ ์ง€ ์ž๋ฆฝ์„ ์„ ๋„ํ•˜๋Š” ์„ธ๊ณ„์  ๊ตญ์˜ ์„์œ ํšŒ์‚ฌ๋ผ๋Š” ๋น„์ „์„ ๋‹ฌ์„ฑํ•˜๊ธฐ ์œ„ํ•ด ์„์œ ๊ฐœ๋ฐœ์‚ฌ์—… ํ™œ์„ฑํ™”, ์ž์ฃผ ๊ณต๊ธ‰๊ฐ€๋Šฅ๋ฌผ๋Ÿ‰์˜ ํ™•๋Œ€, ํ˜์‹ ์„ ํ†ตํ•œ ์‚ฌ์—…์ถ”์ง„์—ญ๋Ÿ‰์˜ ๊ฐ•ํ™”, ์‚ฌ์—…์„ฑ๊ณต์œจ ํ–ฅ์ƒ์— ์—ญ๋Ÿ‰์„ ์ง‘์ค‘ํ•˜๊ณ  ์žˆ๋‹ค. ๊ณต์‚ฌ๋ฐœ์กฑ ์ดํ›„ 1982๋…„์— ํ•œ๊ตญ์„์œ ์‹œ์ถ”(์ฃผ)๋ฅผ ์„ค๋ฆฝํ•˜๊ณ , 1986๋…„์— ํ•œ๊ตญ์†ก์œ ๊ด€(์ฃผ)์„ ์„ค๋ฆฝ, 1987 ๋…„์—๋Š” ๊ตญ๋‚ด ๋Œ€๋ฅ™๋ถ•์—์„œ ์ตœ์ดˆ๋กœ ๊ฐ€์Šค๋ฅผ ๋ฐœ๊ฒฌํ•˜์˜€์œผ๋ฉฐ 1992๋…„์—๋Š” ๋ฒ ํŠธ๋‚จ์‚ฌ๋ฌด์†Œ๋ฅผ ๊ฐœ์†Œํ•˜์˜€๋‹ค. 1996๋…„์— ์˜๊ตญํ˜„์ง€๋ฒ•์ธ์ธ KCCL์„ ์„ค๋ฆฝํ•˜์˜€๊ณ , 1997๋…„์—๋Š” ํŽ˜๋ฃจ์‚ฌ๋ฌด์†Œ ๋ฐ ์ธ๋„๋„ค์‹œ์•„ ํ˜„์ง€๋ฒ• ์ธ KSL์„ ์„ค๋ฆฝํ•˜์˜€๋‹ค. 1999๋…„์— ํšŒ์‚ฌ๋ช…์นญ์„ ํ•œ๊ตญ์„์œ ๊ณต์‚ฌ๋กœ ๋ณ€๊ฒฝํ•˜์˜€์œผ๋ฉฐ 2000๋…„๋ถ€ํ„ฐ ํ•ด์™ธ๊ด‘๊ตฌ ๊ถŒ ํ™•๋ณด๋ฅผ ์œ„ํ•œ ์‚ฌ์—…์„ ์ถ”์ง„ํ•œ ๊ฒฐ๊ณผ 2000~2001๋…„์— ๋ฐฐํŠธ๋‚จ 15-1 ๊ด‘๊ตฌ๋ฅผ ๊ฐœ๋ฐœํ•˜๊ณ  2002๋…„์—๋Š” ๋™ ํ•ด ๊ฐ€์Šค์ƒ์‚ฐ์‹œ์„ค์„ ๊ตฌ์ถ•ํ•˜์˜€์œผ๋ฉฐ 2005๋…„์— ์นด์žํ์Šคํƒ„ ์‚ฌ๋ฌด์†Œ๋ฅผ ๊ฐœ์†Œํ•˜๋Š” ๋“ฑ ํ™œ๋ฐœํ•œ ๊ตญ๋‚ด์™ธ ํ™œ๋™ ์„ ํ•˜๊ณ  ์žˆ๋‹ค. ๋˜ํ•œ ํ•œ๊ตญ์„์œ ๊ณต์‚ฌ๋Š” ๊ตญ๋‚ด์„์œ ์ˆ˜๊ธ‰์˜ ์•ˆ์ •์„ ๋ณด์žฅํ•˜๊ธฐ ์œ„ํ•ด ์ž์ฃผ๊ฐœ๋ฐœ์›์œ  10% ํ™•๋ณด๋ฅผ ๋ชฉํ‘œ๋กœ ํ•ด์™ธ์œ ์ „๊ฐœ๋ฐœ์— ์ ๊ทน์ ์œผ๋กœ ์ฐธ์—ฌํ•˜๊ณ  ์žˆ๋Š”๋ฐ ์ตœ๊ทผ ๊ฐ€์‹œ์  ์„ฑ๊ณผ๋ฅผ ๊ฑฐ๋‘” ์‹ ๊ทœ์‚ฌ์—…์œผ๋กœ๋Š” ์นด์žํ์Šค ํƒ„(์ž ๋นŒ, ADA ๊ด‘๊ตฌ), ๋Ÿฌ์‹œ์•„(์„œ์บ„์ฐจ์นด ์‚ฌ์—…), ์˜ˆ๋ฉ˜(16 ๊ด‘๊ตฌ, 70 ๊ด‘๊ตฌ), ํ˜ธ์ฃผ(Vic P49 ๊ด‘๊ตฌ), ๋‚˜์ด์ง€ ๋ฆฌ์•„(OPL 321, OPL 323 ๊ด‘๊ตฌ)๋“ฑ์ง€์˜ ํƒ์‚ฌ๊ด‘๊ตฌ ์ง„์ถœ์ด ์žˆ๋‹ค. ํŠนํžˆ ์ค‘๋™์‚ฐ์œ ๊ตญ์ธ ์˜ˆ๋ฉ˜์—์„œ ๋‹จ๋… ์šด์˜๊ถŒ์ž ์‚ฌ์—…์„ ํ™•๋ณดํ•จ์œผ๋กœ์จ ๊ณต์‚ฌ์˜ ์šฐ์ˆ˜ํ•œ ์„์œ ๊ฐœ๋ฐœ ๊ธฐ์ˆ ๋ ฅ์„ ์ž…์ฆํ•˜์˜€์œผ๋ฉฐ ์ตœ๊ทผ์— ์ง„ํ–‰์ค‘์ธ ๋‚˜์ด์ง€๋ฆฌ์•„ ์‚ฌ์—…์€ ๊ตญ๋‚ด๊ธฐ์—…์˜ ๋ฐœ์ „์‚ฌ์—… ์ฐธ์—ฌ์™€ ์—ฐ๊ณ„ํ•˜์—ฌ ํš๋“ํ•œ ํƒ์‚ฌ๊ด‘๊ตฌ๋กœ์„œ ํ•œ๊ตญ์ „๋ ฅ๊ณต์‚ฌ, ํฌ์Šค์ฝ” ๊ฑด์„ค๊ณผ์˜ ๋™๋ฐ˜ ์ง„์ถœ์„ ๋ชจ์ƒ‰ํ•˜๊ณ  ์žˆ๋‹ค

    Cost Structure of the Korean Urban Bus Transit Industry: An Application of the Fourier Flexible Functional Form

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    ํ•™์œ„๋…ผ๋ฌธ (๋ฐ•์‚ฌ)-- ์„œ์šธ๋Œ€ํ•™๊ต ํ™˜๊ฒฝ๋Œ€ํ•™์› : ํ™˜๊ฒฝ๊ณ„ํšํ•™๊ณผ, 2014. 2. ๊น€์„ฑ์ˆ˜.๋ณธ ์—ฐ๊ตฌ์—์„œ๋Š” ์„œ์šธ์‹œ๋ฅผ ํฌํ•จํ•œ 7๊ฐœ ๋Œ€๋„์‹œ์˜ 159๊ฐœ ์‹œ๋‚ด๋ฒ„์Šค์—…์ฒด์— ๋Œ€ํ•œ 2008๋…„ ๊ธฐ์ค€ ํšก๋‹จ๋ฉด ์ž๋ฃŒ๋ฅผ ์ด์šฉํ•˜์—ฌ ์‹œ๋‚ด๋ฒ„์Šค์šด์†ก์—…์˜ ๋น„์šฉ๊ตฌ์กฐ์™€ ์ค€๊ณต์˜์ œ์˜ ์˜ํ–ฅ์„ ๋ถ„์„ํ•˜๊ณ , ๋ถ„์„ ๊ฒฐ๊ณผ๋กœ๋ถ€ํ„ฐ ๋น„์šฉ ์ธก๋ฉด์—์„œ ๊ตฌ์กฐ๊ฐœํŽธ๋ฐฉ์•ˆ์˜ ๊ฒฝ์ œ์  ํƒ€๋‹น์„ฑ์„ ๊ฒ€์ฆํ•˜์˜€๋‹ค. ๋ณธ ์—ฐ๊ตฌ๋Š” ์‹œ๋‚ด๋ฒ„์Šค์—…์ฒด๋ฅผ ๋…ธ๋™, ์—ฐ๋ฃŒ, ์ •๋น„, ์ž๋ณธ ์š”์†Œ๋ฅผ ํˆฌ์ž…ํ•˜์—ฌ ์ผ๋ฐ˜๋ฒ„์Šค-km, ์ขŒ์„๋ฒ„์Šค-km๋ฅผ ์ƒ์‚ฐํ•˜๋Š” ๋‹ค์ˆ˜์‚ฐ์ถœ๋ฌผ ๊ธฐ์—…ํ˜•ํƒœ๋กœ ์ƒ์ •ํ•˜์˜€๋‹ค. ๋‹ค์Œ์œผ๋กœ ๋ฐ˜๋ณต๊ฒฐํ•ฉ์ผ๋ฐ˜ํ™”์ตœ์†Œ์ž์Šน๋ฒ•(ITSUR)์„ ์ด์šฉํ•ด ์ถ”์ •๋œ ํ‘ธ๋ฆฌ์— ์ด๋น„์šฉํ•จ์ˆ˜๋กœ๋ถ€ํ„ฐ ์ผ๋ฐ˜๋ฒ„์Šค์™€ ์ขŒ์„๋ฒ„์Šค ๊ฐ„ ๋น„์šฉ๋ณด์™„์„ฑ ๋ฐ ๊ทœ๋ชจ์˜ ๊ฒฝ์ œ์„ฑ ๊ทธ๋ฆฌ๊ณ  ์ตœ์†Œํšจ์œจ๊ทœ๋ชจ๋ฅผ ์‚ฐ์ถœ๋Ÿ‰ ๊ตฌ์„ฑ๋น„์œจ์— ๋”ฐ๋ผ ์ถ”์ •ํ•˜์˜€๋‹ค. ๋”๋ถˆ์–ด ์ค€๊ณต์˜์ œ์˜ ์‹œํ–‰ ์—ฌ๋ถ€์— ๋Œ€ํ•œ ๋”๋ฏธ๋ณ€์ˆ˜์™€ ์š”์†Œ๊ฐ€๊ฒฉ์˜ ๊ต์ฐจํ•ญ์„ ํ†ตํ•ด ์ค€๊ณต์˜์ œ๊ฐ€ ์ด๋น„์šฉ์„ ์ฆ๊ฐ€์‹œํ‚ค๋Š” ์ •๋„์™€ ์š”์†Œ๊ฐ€๊ฒฉ์— ๋ฏธ์น˜๋Š” ์˜ํ–ฅ์˜ ์ •๋„๋ฅผ ๋ถ„์„ํ•˜์˜€๋‹ค. ๋ณธ ์—ฐ๊ตฌ์˜ ๋ถ„์„๊ฒฐ๊ณผ๋Š” ๋‹ค์Œ๊ณผ ๊ฐ™๋‹ค. ์ฒซ์งธ, ๊ตญ๋‚ด ์‹œ๋‚ด๋ฒ„์Šค์šด์†ก์—…์˜ ๋น„์šฉ๊ตฌ์กฐ๋ฅผ ๋ณด๋‹ค ์ž˜ ๋ฐ˜์˜ํ•˜๋Š” ํ•จ์ˆ˜ํ˜•ํƒœ๋Š” ์ดˆ์›”๋Œ€์ˆ˜ ํ•จ์ˆ˜ํ˜•ํƒœ๊ฐ€ ์•„๋‹ˆ๋ผ ํ‘ธ๋ฆฌ์— ํ•จ์ˆ˜ํ˜•ํƒœ์ธ ๊ฒƒ์œผ๋กœ ๋‚˜ํƒ€๋‚ฌ๋‹ค. ์ด๋Š” ์ขŒ์„๋ฒ„์Šค-km์˜ ๋ถ„ํฌ ํŠน์„ฑ์ด ํ‰๊ท ์ ์—์„œ ๊ทผ์‚ฌํ•˜๋Š” ์ดˆ์›”๋Œ€์ˆ˜ ํ•จ์ˆ˜ํ˜•ํƒœ๋ณด๋‹ค ์ „์—ญ์  ๊ทผ์‚ฌ๊ฐ€ ๊ฐ€๋Šฅํ•œ ํ‘ธ๋ฆฌ์— ํ•จ์ˆ˜ํ˜•ํƒœ์— ๋” ์ ํ•ฉํ•˜๊ธฐ ๋•Œ๋ฌธ์œผ๋กœ, ์ถ”์ •๊ฒฐ๊ณผ ์—ญ์‹œ ์‚ผ๊ฐํ•จ์ˆ˜ํ•ญ๋“ค์ด ๋Œ€๋ถ€๋ถ„ ์œ ์˜ํ•˜๊ฒŒ ๋‚˜ํƒ€๋‚ฌ๊ณ , ์ดˆ์›”๋Œ€์ˆ˜ ํ•จ์ˆ˜ํ˜•ํƒœ๋ณด๋‹ค ํ‘ธ๋ฆฌ์— ํ•จ์ˆ˜ํ˜•ํƒœ์˜ ์˜ˆ์ธก์˜ค์ฐจ์œจ์ด ์ „์ฒด ๋ฒ”์œ„์—์„œ ๋” ๋‚ฎ์€ ๊ฒƒ์œผ๋กœ ๋‚˜ํƒ€๋‚ฌ๋‹ค. ๋‘˜์งธ, ์‹œ๋‚ด๋ฒ„์Šค์—…์ฒด๋Š” ๋Œ€์ฒด๋กœ ์š”์†Œ๊ฐ€๊ฒฉ์˜ ๋ณ€ํ™”์— ๋น„ํƒ„๋ ฅ์ ์ธ ๊ฒƒ์œผ๋กœ ๋‚˜ํƒ€๋‚ฌ์ง€๋งŒ, ์ •๋น„์š”์†Œ์˜ ์ž๊ธฐ๊ฐ€๊ฒฉํƒ„๋ ฅ์„ฑ๊ณผ ๋…ธ๋™์š”์†Œ์™€์˜ ๊ต์ฐจํƒ„๋ ฅ์„ฑ์€ ์ƒ๋Œ€์ ์œผ๋กœ ๋†’๊ฒŒ ๋‚˜ํƒ€๋‚˜ ์šดํ–‰๋น„์šฉ์„ ์ค„์ด๊ธฐ ์œ„ํ•ด ๋น„๊ต์  ํƒ„๋ ฅ์ ์ธ ์ •๋น„๋น„์šฉ์„ ์ค„์ด๋ฉด ๊ฐ€์žฅ ํฐ ๋น„์šฉ์š”์†Œ์ธ ๋…ธ๋™๋น„์šฉ์„ ์ฆ๊ฐ€์‹œํ‚ฌ ์ˆ˜ ์žˆ์Œ์„ ๊ณ ๋ คํ•˜์—ฌ ์ ์ • ์ˆ˜์ค€์˜ ์ •๋น„๋Š” ์œ ์ง€ํ•ด์•ผ ํ•จ์„ ์•Œ ์ˆ˜ ์žˆ์—ˆ๋‹ค. ์ž๋ณธ์š”์†Œ์˜ ์ž๊ธฐ๊ฐ€๊ฒฉํƒ„๋ ฅ์„ฑ์€ ์ค€๊ณต์˜์ œ ์‹œํ–‰ ์ดํ›„ ๋น„ํšจ์œจ์ ์ธ ์š”์†Œ ํˆฌ์ž…์ด ์ด๋ฃจ์–ด์ง€๋Š” ๊ฒƒ์œผ๋กœ ๋‚˜ํƒ€๋‚ฌ์œผ๋ฏ€๋กœ ์ฐจ๋Ÿ‰์„ ๊ฐ์ถ•ํ•˜๊ธฐ ์œ„ํ•ด์„œ๋Š” ๋Œ€๋‹น ํ‘œ์ค€์šด์†ก์›๊ฐ€์— ์˜ํ•ด ์žฌ์ •์ง€์›์ด ์ด๋ฃจ์–ด์ง€๋Š” ํ˜„์žฌ์˜ ๋ฐฉ์‹์„ ๊ฐœ์„ ํ•  ํ•„์š”๊ฐ€ ์žˆ๋‹ค๊ณ  ํŒ๋‹จ๋œ๋‹ค. ํ•œํŽธ ๋…ธ๋™๊ณผ ์ž๋ณธ, ์—ฐ๋ฃŒ์™€ ์ž๋ณธ์€ ๋ณด์™„๊ด€๊ณ„๋กœ ๋‚˜ํƒ€๋‚ฌ๊ณ , ๋…ธ๋™๊ณผ ์ •๋น„, ์ •๋น„์™€ ์ž๋ณธ์€ ๋Œ€์ฒด๊ด€๊ณ„๋กœ ๋‚˜ํƒ€๋‚ฌ๋‹ค. ์…‹์งธ, ๊ทœ๋ชจ์˜ ๊ฒฝ์ œ์„ฑ๊ณผ ๋น„์šฉ๋ณด์™„์„ฑ์€ ์‚ฐ์ถœ๋Ÿ‰ ๊ตฌ์„ฑ๋น„์œจ๊ณผ ์‚ฐ์ถœ๋Ÿ‰ ๊ทœ๋ชจ์— ๋”ฐ๋ผ ๊ฒฐ์ •๋œ๋‹ค. ๊ตญ๋‚ด ์‹œ๋‚ด๋ฒ„์Šค์šด์†ก์—…์€ ์‚ฐ์ถœ๋ฌผ๋ณ„๋กœ๋Š” ๊ทœ๋ชจ์˜ ๊ฒฝ์ œ๊ฐ€ ์กด์žฌํ•˜์ง€๋งŒ ์ผ๋ฐ˜๋ฒ„์Šค์™€ ์ขŒ์„๋ฒ„์Šค ๊ฐ„ ๋ฒ”์œ„์˜ ๋ถˆ๊ฒฝ์ œ๋กœ ์ธํ•ด ์ „๋ฐ˜์ ์ธ ๊ทœ๋ชจ์˜ ๊ฒฝ์ œ๋Š” ํ•œ์ •์ ์œผ๋กœ ์กด์žฌํ•˜๋Š” ๊ฒƒ์œผ๋กœ ๋ถ„์„๋˜์—ˆ๋‹ค. ๋”ฐ๋ผ์„œ ์ผ๋ฐ˜๋ฒ„์Šค์™€ ์ขŒ์„๋ฒ„์Šค๋Š” ๊ฐ๊ฐ ์ „๋ฌธํ™”ํ•˜์—ฌ ์šดํ–‰ํ•˜๊ณ , ์—…์ฒด ๊ทœ๋ชจ๋Š” ๋„์‹œ๋ณ„๋กœ ์ฐจ์ด๋Š” ์žˆ์ง€๋งŒ ์•ฝ 300~500๋Œ€๋กœ ๋Œ€ํ˜•ํ™”ํ•˜๋Š” ๊ฒƒ์ด ๋น„์šฉ ์ธก๋ฉด์—์„œ ๋” ํšจ์œจ์ ์ธ ๊ฒƒ์œผ๋กœ ๋‚˜ํƒ€๋‚ฌ๋‹ค. ๊ทธ๋Ÿฌ๋‚˜ ์‚ฌํšŒ์  ๊ด€์ ์—์„œ ์ผ๋ฐ˜๋ฒ„์Šค์™€ ์ขŒ์„๋ฒ„์Šค์˜ ๊ฒฐํ•ฉ์šดํ–‰์ด ๋ฐ˜๋“œ์‹œ ๋‚˜์œ ์„ ํƒ์ด๋ผ๊ณ  ํ•  ์ˆ˜๋Š” ์—†๋‹ค. ์ผ๋ถ€์ด๊ธฐ๋Š” ํ•˜์ง€๋งŒ ๋ฒ”์œ„์˜ ๊ฒฝ์ œ๊ฐ€ ์กด์žฌํ•  ๊ฐ€๋Šฅ์„ฑ์„ ํ™•์ธํ•˜์˜€๊ณ , ์ขŒ์„๋ฒ„์Šค์˜ ๋ถ„๋ฆฌ ๋Œ€์‹ ์— ์œ ์ธ๊ทœ์ œ๋ฅผ ํ†ตํ•ด ๋น„์šฉ ์ธก๋ฉด์˜ ํšจ์œจ์„ฑ์„ ๊ฐœ์„ ํ•  ์ˆ˜๋„ ์žˆ๊ธฐ ๋•Œ๋ฌธ์ด๋‹ค. ๋Œ€ํ˜•ํ™”์— ๋”ฐ๋ฅธ ๊ฒฝ์ œ์  ํšจ๊ณผ๋Š” ์„œ์šธ์‹œ์˜ ๊ฒฝ์šฐ ์‹œ๋‚ด๋ฒ„์Šค์—…์ฒด์˜ ํ‰๊ท ๊ทœ๋ชจ๊ฐ€ ์•ฝ 122๋Œ€์ธ๋ฐ, ์ด๋ฅผ ์•ฝ 300๋Œ€๋กœ ๋Œ€ํ˜•ํ™”ํ•˜๋ฉด ํ˜„์žฌ 60๊ฐœ์˜ ์—…์ฒด๋Š” ์•ฝ 23๊ฐœ์˜ ์—…์ฒด๋กœ ์ค„์–ด๋“ค๋ฉฐ ์šด์†ก์›๊ฐ€๋Š” ์•ฝ 6.34%๊ฐ€ ์ค„์–ด๋“ค๊ฒŒ ๋˜๊ณ , 500๋Œ€๋กœ ๋Œ€ํ˜•ํ™”ํ•  ๊ฒฝ์šฐ์—๋Š” ์—…์ฒด์ˆ˜๋Š” ์•ฝ 14๊ฐœ๊ฐ€ ๋˜๋ฉฐ ์šด์†ก์›๊ฐ€๋Š” 10.72% ๊ฐ์†Œํ•˜๋Š” ๊ฒƒ์œผ๋กœ ๋‚˜ํƒ€๋‚ฌ๋‹ค. ๊ทธ๋Ÿฌ๋‚˜ ๊ตญ๋‚ด ์‹œ๋‚ด๋ฒ„์Šค์—…์ฒด๋“ค ์ค‘์—์„œ ๊ฐ€์žฅ ๊ทœ๋ชจ๊ฐ€ ํฐ ์—…์ฒด๊ฐ€ 302๋Œ€์˜ ์ฐจ๋Ÿ‰์„ ๋ณด์œ ํ•˜๊ณ  ์žˆ๊ณ , 200๋Œ€ ์ด์ƒ ๋ณด์œ ์—…์ฒด๋„ 6๊ฐœ ์—…์ฒด์— ๋ถˆ๊ณผํ•˜๋ฏ€๋กœ 300๋Œ€ ์ด์ƒ์˜ ๊ทœ๋ชจ๋กœ ๋Œ€ํ˜•ํ™”ํ•  ๋•Œ ์‹ค์ œ ๋น„์šฉ์ ˆ๊ฐํšจ๊ณผ๊ฐ€ ๋‚˜ํƒ€๋‚  ์ง€๋Š” ํ™•์‹คํ•˜๋‹ค๊ณ  ํ•  ์ˆ˜๋Š” ์—†๋‹ค. ์ด๋Š” ๋„์‹œ๋ณ„๋กœ ์ฐจ๊ณ ์ง€์˜ ์œ„์น˜, ๋…ธ์„ ์˜ ๊ธธ์ด ๋ฐ ์„œ๋น„์Šค ๋ฉด์  ๋“ฑ์— ๋”ฐ๋ผ ์ง€๋‚˜์นœ ๋ฒ„์Šค์—…์ฒด์˜ ๋Œ€ํ˜•ํ™”๋Š” ๋ถˆํ•„์š”ํ•œ ์šดํ–‰์„ ์ฆ๊ฐ€์‹œํ‚ฌ ์ˆ˜ ์žˆ์œผ๋ฉฐ, ์—…์ฒด ๊ฐ„ ๊ฒฝ์Ÿ์€ ์šด์˜ํšจ์œจ์„ฑ์„ ๋†’์ด๋Š” ๋ฐ ํ•„์š”ํ•˜๊ธฐ ๋•Œ๋ฌธ์ด๋‹ค. ๋„ท์งธ, ์ค€๊ณต์˜์ œ๋Š” ์‹œ๋‚ด๋ฒ„์Šค์—…์ฒด์˜ ์ด๋น„์šฉ๊ณผ ์šด์ „๊ธฐ์‚ฌ์˜ ์ž„๊ธˆ์„ ์ƒ์Šน์‹œํ‚ค๊ณ , ์šดํ–‰์ ์ž๋ถ„์„ ์ „์•ก ๋ณด์ƒ๋ฐ›๊ธฐ ๋•Œ๋ฌธ์— ์ˆ˜์ต์„ฑ์ด ๋‚ฎ์€ ๊ด‘์—ญ๋ฒ„์Šค์˜ ๊ฐ์ถ•, ๊ฒฝ์ œ์ ์ธ CNG์ฐจ๋Ÿ‰์œผ๋กœ์˜ ๊ต์ฒด ๋“ฑ์— ๋น„ํ˜‘์กฐ์ ์ธ ๊ฒƒ์œผ๋กœ ๋‚˜ํƒ€๋‚ฌ๋‹ค. ์ค€๊ณต์˜์ œ ์‹œํ–‰์‹œ ์ด๋น„์šฉ์€ ๋ฏธ์‹œํ–‰์‹œ์— ๋น„ํ•ด ์•ฝ 16.4%๊ฐ€ ์ฆ๊ฐ€ํ•˜๊ณ , ๋…ธ๋™๊ฐ€๊ฒฉ์„ ์ƒ์Šน์‹œํ‚จ๋‹ค. ์—ฐ๋ฃŒ์™€ ์ž๋ณธ๊ฐ€๊ฒฉ์—๋„ ์ค€๊ณต์˜์ œ๊ฐ€ ์˜ํ–ฅ์„ ์ฃผ๋Š” ๊ฒƒ์ฒ˜๋Ÿผ ๋‚˜ํƒ€๋‚ฌ์œผ๋‚˜, ์ด๋Š” ์ค€๊ณต์˜์ œ๋ฅผ ์‹œํ–‰ํ•˜๋Š” ๋„์‹œ์˜ ์ขŒ์„๋ฒ„์Šค ๋น„์ค‘์ด ๋” ๋†’๊ธฐ ๋•Œ๋ฌธ์œผ๋กœ ์ค€๊ณต์˜์ œ์™€ ์ง์ ‘ ๊ด€๋ จ์ด ์žˆ๋Š” ๊ฒƒ์€ ์•„๋‹ˆ๋‹ค. ๋งˆ์ง€๋ง‰์œผ๋กœ, ํ˜„์žฌ ์žฌ์ •์ง€์›์˜ ๊ธฐ์ค€์ด ๋˜๋Š” ํ‘œ์ค€์šด์†ก์›๊ฐ€์˜ ์ˆ˜์ • ๋ฐ ๋ณด์™„์ด ์ฃผ์š” ์Ÿ์ ์ด ๋˜๊ณ  ์žˆ์ง€๋งŒ ์‹ค์ œ๋กœ ํ‘œ์ค€์šด์†ก์›๊ฐ€์˜ ์ฃผ์š” ๋น„์šฉํ•ญ๋ชฉ์ธ ์šด์ „๊ธฐ์‚ฌ ์ธ๊ฑด๋น„์™€ ์—ฐ๋ฃŒ๋น„๊ฐ€ ์‹ค๋น„์ง€๊ธ‰๋˜๋Š” ์ƒํ™ฉ์—์„œ ๋‚˜๋จธ์ง€ ๋น„์šฉํ•ญ๋ชฉ์˜ ์กฐ์ •๋งŒ์œผ๋กœ๋Š” ์žฌ์ •์ง€์›๊ธˆ์•ก์„ ํฌ๊ฒŒ ๋‚ฎ์ถ”๋Š” ๊ฒƒ์ด ๊ฑฐ์˜ ๋ถˆ๊ฐ€๋Šฅํ•˜๋‹ค. ์ฆ‰ ๊ตญ๋‚ด ์ค€๊ณต์˜์ œ ์žฌ์ •์ง€์›๋ฐฉ์‹์ด ์‹ค์งˆ์ ์œผ๋กœ๋Š” ๊ฐ€์žฅ ๋น„ํšจ์œจ์ ์ธ ๋ฐฉ์‹์œผ๋กœ ์•Œ๋ ค์ง„ cost-plus contracts ๋ฐฉ์‹์ด๊ธฐ ๋•Œ๋ฌธ์— ์žฅ๊ธฐ์ ์œผ๋กœ ์žฌ์ •์ง€์›๋ฐฉ์‹์„ ๊ฐœ์„ ํ•  ํ•„์š”๊ฐ€ ์žˆ๊ณ , ๋‹จ๊ธฐ์ ์œผ๋กœ๋Š” ๋ชฉํ‘œ์›๊ฐ€๋ฅผ ๋„์ž…ํ•˜๊ณ  ์„ฑ๊ณผ์ด์œค์„ ํ™•๋Œ€ํ•  ํ•„์š”๊ฐ€ ์žˆ๋‹ค. ๋ณธ ์—ฐ๊ตฌ์˜ ํ•œ๊ณ„์™€ ํ–ฅํ›„ ์—ฐ๊ตฌ๋ฐฉํ–ฅ์€ ๋‹ค์Œ๊ณผ ๊ฐ™๋‹ค. ์ฒซ์งธ, ๋ณธ ์—ฐ๊ตฌ๊ฒฐ๊ณผ๋Š” ์‹œ๋‚ด๋ฒ„์Šค์—…์ฒด๊ฐ€ ์ขŒ์„๋ฒ„์Šค๋ฅผ ์ผ๋ฐ˜๋ฒ„์Šค์™€ ํ•จ๊ป˜ ์šดํ–‰ํ•˜๋Š” ๊ฒƒ์€ ๋น„์šฉ ์ธก๋ฉด์—์„œ ํšจ์œจ์ ์ด์ง€ ๋ชปํ•˜๋ฏ€๋กœ ์ขŒ์„๋ฒ„์Šค๋ฅผ ๋ถ„๋ฆฌํ•˜๋„๋ก ์ œ์•ˆํ•˜์˜€์„ ๋ฟ ์ขŒ์„๋ฒ„์Šค์˜ ์šดํ–‰๋ฐฉ์‹์— ๋Œ€ํ•ด์„œ๋Š” ๋ถ„์„ํ•˜์ง€ ์•Š์•˜๋‹ค. ์ด๋Š” ํ–ฅํ›„ ์‹œ์™ธ๋ฒ„์Šค์—…์ฒด์™€ ๊ณ ์†๋ฒ„์Šค์—…์ฒด๋ฅผ ํฌํ•œํ•˜๋Š” ์ž๋ฃŒ๋ฅผ ๊ตฌ์ถ•ํ•˜์—ฌ ๋ฒ„์Šค์„œ๋น„์Šค๋ณ„ ๊ฒฐํ•ฉ์ƒ์‚ฐ์— ๋”ฐ๋ฅธ ๋ฒ”์œ„์˜ ๊ฒฝ์ œ์„ฑ ๋ถ„์„์„ ํ†ตํ•ด ํŒ๋‹จํ•  ์ˆ˜ ์žˆ์„ ๊ฒƒ์ด๋‹ค. ๋‘˜์งธ, ๋‹ค์ˆ˜์‚ฐ์ถœ๋ฌผ์‚ฐ์—…์˜ ํŠน์„ฑ์„ ๋ฐ˜์˜ํ•˜๊ธฐ ์œ„ํ•ด์„œ๋Š” ์‚ฐ์ถœ๋Ÿ‰ ์ง‘๊ณ„๋ณ€์ˆ˜์™€ ํ•จ๊ป˜ ์งˆ์  ์†์„ฑ๋ณ€์ˆ˜๋ฅผ ์„ ํƒํ•˜์—ฌ ๋น„์šฉํ•จ์ˆ˜์— ์ง์ ‘ ํฌํ•จ์‹œํ‚ฌ ํ•„์š”๊ฐ€ ์žˆ๋‹ค. ๊ทธ๋Ÿฌ๋‚˜ ์ž๋ฃŒ์˜ ํ•œ๊ณ„ ๋•Œ๋ฌธ์— ์ถ”์ •๋œ ๋น„์šฉํ•จ์ˆ˜์— ์†์„ฑ๋ณ€์ˆ˜, ์˜ˆ๋ฅผ ๋“ค๋ฉด ๋„คํŠธ์›Œํฌ ๊ธธ์ด๋‚˜ ํ‰๊ท ์†๋„, ์šดํ–‰ํšŸ์ˆ˜, peak/base ratio ๋“ฑ์„ ํฌํ•จ์‹œํ‚ฌ ์ˆ˜ ์—†์—ˆ๋‹ค. ์…‹์งธ, ๋ณธ ์—ฐ๊ตฌ์—์„œ ์ œ์•ˆํ•œ ๋Œ€ํ˜•ํ™” ๋ฐฉ์•ˆ์€ ์‹œ๋‚ด๋ฒ„์Šค์—…์ฒด๋งŒ์„ ๋Œ€์ƒ์œผ๋กœ ํ•  ๋ฟ์ด๊ณ , ์–ด๋–ค ๋ฐฉ์‹์œผ๋กœ ๋Œ€ํ˜•ํ™”ํ•˜๋Š” ๊ฒƒ์ด ์ข‹์„ ์ง€์— ๋Œ€ํ•ด์„œ๋Š” ์ œ์‹œํ•˜์ง€ ์•Š์•˜๋‹ค. ์ฆ‰ ๋งˆ์„๋ฒ„์Šค, ์‹œ์™ธ๋ฒ„์Šค, ๊ณ ์†๋ฒ„์Šค๋“ค์€ ์ž๋ฃŒ์— ํฌํ•จ๋˜์ง€ ์•Š์•˜๊ณ , ๋Œ€ํ˜•ํ™”์˜ ๋ฐฉ์‹๋„ ๋™์ผ ๋Œ€ํ‘œ์ž์— ์˜ํ•ด ๋ฒ„์Šค์šด์†ก๊ทธ๋ฃน์œผ๋กœ ์šด์˜ํ•˜๋Š” ๋ฐฉ์•ˆ๊ณผ ์™„์ „ํ•œ ํ†ตํํ•ฉ์„ ํ•˜๋Š” ๋ฐฉ์•ˆ ๋“ฑ ์—ฌ๋Ÿฌ ๋ฐฉ์‹์ด ์žˆ์„ ์ˆ˜ ์žˆ๊ฒ ์œผ๋‚˜ ์ด์— ๋Œ€ํ•ด์„œ๋Š” ์ œ์‹œํ•˜์ง€ ์•Š์•˜๋‹ค. ๋˜ํ•œ ์‹ค์ œ ์‹œ๋‚ด๋ฒ„์Šค์—…์ฒด์˜ ์ธํ—ˆ๊ฐ€ ๋ฌธ์ œ ๋“ฑ ์ •์ฑ…์ , ์ œ๋„์  ๊ตฌ์กฐ๋Š” ๋น„์šฉํ•จ์ˆ˜์— ๋ฐ˜์˜ํ•  ์ˆ˜ ์—†์—ˆ์œผ๋ฏ€๋กœ ๋ณธ ์—ฐ๊ตฌ์˜ ๊ฒฐ๊ณผ๋Š” ๋‹จ์ง€ ๋น„์šฉ ์ธก๋ฉด์—์„œ ๋Œ€ํ˜•ํ™”์˜ ํšจ๊ณผ๋ฅผ ๋ถ„์„ํ•œ ๊ฒƒ์ด๋‹ค. ๋งˆ์ง€๋ง‰์œผ๋กœ ๊ตญ๋‚ด ์‹œ๋‚ด๋ฒ„์Šค์šด์†ก์—…์˜ ๋ฌธ์ œ๋Š” ์—…์ฒด์˜ ์˜์„ธ์„ฑ์ด ์ฃผ์š” ์›์ธ์ด ์•„๋‹ˆ๋ฏ€๋กœ ๋Œ€ํ˜•ํ™” ๋ฐฉ์•ˆ์œผ๋กœ ๋‹น๋ฉดํ•œ ๋ฌธ์ œ๊ฐ€ ๋ชจ๋‘ ํ•ด๊ฒฐ๋  ์ˆ˜๋Š” ์—†๋‹ค. ๋‹ค๋งŒ ๊ตญ๋‚ด ๋Œ€๋„์‹œ์˜ ์‹œ๋‚ด๋ฒ„์Šค์šด์†ก์—…์˜ ๋น„์šฉ๊ตฌ์กฐ ๋ถ„์„๊ฒฐ๊ณผ ๋„์‹œ๋ณ„๋กœ ์ฐจ์ด๋Š” ์žˆ์ง€๋งŒ ๋Œ€์ฒด๋กœ 300๋Œ€~500๋Œ€ ์‚ฌ์ด์—์„œ ๋น„์šฉ ํšจ์œจ์ ์ด๋ฏ€๋กœ ๋„์‹œ๋ณ„ ํ˜„ํ™ฉ์— ๋งž๊ฒŒ ๋Œ€ํ˜•ํ™”ํ•˜๋Š” ๊ฒƒ์ด ๋น„์šฉ ์ธก๋ฉด์—์„œ ์ ์ ˆํ•˜๋‹ค๋Š” ๊ฒƒ์ด๋‹ค. ๋Ÿฐ๋˜์‹œ์˜ ๊ฒฝ์šฐ์—๋„ ์—…์ฒด๋ณ„ ํ‰๊ท  ๊ทœ๋ชจ๋Š” ์•ฝ 430๋Œ€์ด์ง€๋งŒ ์—…์ฒด๋ณ„ ๋ฒ„์Šค๋Œ€์ˆ˜์˜ ๋ถ„ํฌ๊ฐ€ 63๋Œ€~885๋Œ€๊นŒ์ง€ ๋‹ค์–‘ํ•˜๊ณ , ํŠนํžˆ ํ•˜๋‚˜์˜ ๋Œ€ํ˜• ๋ฒ„์Šค๊ทธ๋ฃน์ด ๋ณต์ˆ˜์˜ ๋ฒ„์Šค์—…์ฒด๋ฅผ ํฌ๊ด„ํ•˜์—ฌ ์šด์˜ํ•˜๋Š” ํ˜•ํƒœ๊ฐ€ ๋งŽ์•˜์œผ๋ฉฐ, ๋Ÿฐ๋˜์‹œ ๋ฟ ์•„๋‹ˆ๋ผ ๋‹ค๋ฅธ ๋„์‹œ์—์„œ๋„ ๋ฒ„์Šค๋ฅผ ์šดํ–‰ํ•˜๋Š” ๋“ฑ ๋ฒ„์Šค์—…์ฒด์˜ ๊ฒฝ์˜๊ตฌ์กฐ๊ฐ€ ๋‹ค์–‘ํ•˜๋ฏ€๋กœ ์ด๋ฅผ ์ฐธ๊ณ ํ•  ํ•„์š”๊ฐ€ ์žˆ๋‹ค.โ… . ์„œ๋ก  1 1. ์—ฐ๊ตฌ์˜ ๋ฐฐ๊ฒฝ๊ณผ ๋ชฉ์  1 2. ์—ฐ๊ตฌ์˜ ๋ฒ”์œ„์™€ ๋ฐฉ๋ฒ• 4 3. ์—ฐ๊ตฌ์˜ ์˜์˜์™€ ๊ตฌ์„ฑ 6 โ…ก. ํ•จ์ˆ˜ํ˜•ํƒœ์˜ ์„ ์ • ๋ฐ ์„ ํ–‰์—ฐ๊ตฌ์˜ ๊ณ ์ฐฐ 9 1. ํ•จ์ˆ˜ํ˜•ํƒœ์˜ ์„ ์ • 9 1) ์ดˆ์›”๋Œ€์ˆ˜ ํ•จ์ˆ˜ํ˜•ํƒœ 9 2) ์ผ๋ฐ˜์ดˆ์›”๋Œ€์ˆ˜ ํ•จ์ˆ˜ํ˜•ํƒœ 14 3) Minflex Laurents ํ•จ์ˆ˜ํ˜•ํƒœ 16 4) ํ‘ธ๋ฆฌ์— ํ•จ์ˆ˜ํ˜•ํƒœ 17 2. ๊ด€๋ จ ์„ ํ–‰์—ฐ๊ตฌ์˜ ๊ณ ์ฐฐ 25 1) ๊ด€๋ จ ์„ ํ–‰์—ฐ๊ตฌ์˜ ์„ ์ • 25 2) ๋ฒ„์Šค์šด์†ก์—…์˜ ๊ทœ๋ชจ ๋ฐ ๋ฒ”์œ„์˜ ๊ฒฝ์ œ์„ฑ์— ๊ด€ํ•œ ๊ตญ์™ธ ์„ ํ–‰์—ฐ๊ตฌ 28 3) ๋ฒ„์Šค์šด์†ก์—…์˜ ๊ทœ๋ชจ ๋ฐ ๋ฒ”์œ„์˜ ๊ฒฝ์ œ์„ฑ์— ๊ด€ํ•œ ๊ตญ๋‚ด ์„ ํ–‰์—ฐ๊ตฌ 40 4) ํ‘ธ๋ฆฌ์— ๋น„์šฉํ•จ์ˆ˜๋ฅผ ๊ตํ†ต๋ถ€๋ฌธ์— ์ ์šฉํ•œ ์„ ํ–‰์—ฐ๊ตฌ 42 5) ์„ ํ–‰์—ฐ๊ตฌ์˜ ์‹œ์‚ฌ์  43 โ…ข. ์—ฐ๊ตฌ ๋ฐฉ๋ฒ•๋ก ์˜ ์ •๋ฆฝ 46 1. ์ด๋น„์šฉํ•จ์ˆ˜๋ชจํ˜•์˜ ์„ค์ • 46 1) ์ข…์†๋ณ€์ˆ˜ 46 2) ๋…๋ฆฝ๋ณ€์ˆ˜ 47 3) ํ‘ธ๋ฆฌ์— ์ด๋น„์šฉํ•จ์ˆ˜๋ชจํ˜• 52 2. ๋น„์šฉ๊ตฌ์กฐ์˜ ๋ถ„์„๋ฐฉ๋ฒ• 57 1) ์ƒ์‚ฐ์š”์†Œ์˜ ํŽธ๋Œ€์ฒดํƒ„๋ ฅ์„ฑ๊ณผ ์š”์†Œ์ˆ˜์š”์˜ ๊ฐ€๊ฒฉํƒ„๋ ฅ์„ฑ 57 2) ๋ฒ”์œ„์˜ ๊ฒฝ์ œ์„ฑ ๋ฐ ๋น„์šฉ๋ณด์™„์„ฑ 60 3) ๋ฐฉ์‚ฌํ˜• ๊ทœ๋ชจ์˜ ๊ฒฝ์ œ์„ฑ 63 4) ํ‰๊ท ๋น„์šฉ๊ณผ ํ•œ๊ณ„๋น„์šฉ 66 3. ์ค€๊ณต์˜์ œ ํšจ๊ณผ์˜ ๋ถ„์„๋ฐฉ๋ฒ• 67 โ…ฃ. ์ž๋ฃŒ์™€ ์ถ”์ •๋ฐฉ๋ฒ• 69 1. ์‹œ๋‚ด๋ฒ„์Šค์šด์†ก์—…์ฒด ์ž๋ฃŒ์˜ ๊ตฌ์ถ• 69 1) ์ด๋น„์šฉ 72 2) ์š”์†Œ๊ฐ€๊ฒฉ 73 3) ๋„์‹œ ๋”๋ฏธ๋ณ€์ˆ˜ 78 2. ์ž๋ฃŒ์˜ ๊ธฐ์ˆ ์  ๋ถ„์„ 81 1) ์ด๋น„์šฉ๊ณผ ์š”์†Œ์ ์œ ์œจ 82 2) ์‚ฐ์ถœ๋ฌผ์˜ ๋ถ„ํฌ ํŠน์„ฑ 88 3) ์ƒ์‚ฐ์š”์†Œ์˜ ํˆฌ์ž…๋Ÿ‰๊ณผ ์š”์†Œ๊ฐ€๊ฒฉ 91 4) ์‚ฐ์ถœ๋Ÿ‰ ๊ตฌ์„ฑ๋น„์œจ(p1)๊ณผ ์ฐจ๋Ÿ‰๋Œ€์ˆ˜ 99 5) CNG ์ฐจ๋Ÿ‰๋น„์œจ 106 6) ๋ถ€๋ถ„์ƒ์‚ฐ์„ฑ 107 7) ์šด์†ก์ˆ˜์ž… ๋ฐ ์›๊ฐ€๋ณด์ƒ์œจ 110 8) ๋™์ผ ๋Œ€ํ‘œ์ž ์†Œ์œ ์˜ ๋ณต์ˆ˜ ๋ฒ„์Šค์—…์ฒด 114 3. ์ถ”์ •๋ฐฉ๋ฒ• 118 โ…ค. ์‹œ๋‚ด๋ฒ„์Šค์šด์†ก์—…์˜ ๋น„์šฉ๊ตฌ์กฐ ๋ถ„์„๊ฒฐ๊ณผ 120 1. ์ด๋น„์šฉํ•จ์ˆ˜๋ชจํ˜•์˜ ์ถ”์ •๊ฒฐ๊ณผ 120 2. ๋ชจํ˜•์˜ ์ •ํ•ฉ์„ฑ ๊ฒ€ํ†  125 1) ์ด๋ถ„์‚ฐ์„ฑ 125 2) ์ •๊ทœ์„ฑ ์กฐ๊ฑด์˜ ๋งŒ์กฑ๋„ 126 3) ์˜ˆ์ธก์˜ค์ฐจ์œจ 130 3. ๋น„์šฉ๊ตฌ์กฐ์˜ ๋ถ„์„๊ฒฐ๊ณผ 135 1) ์ƒ์‚ฐ์š”์†Œ์˜ ํŽธ๋Œ€์ฒดํƒ„๋ ฅ์„ฑ๊ณผ ์š”์†Œ์ˆ˜์š”์˜ ๊ฐ€๊ฒฉํƒ„๋ ฅ์„ฑ 135 2) ๊ทœ๋ชจ์˜ ๊ฒฝ์ œ์„ฑ 147 3) ์‹œ๋‚ด์ผ๋ฐ˜๋ฒ„์Šค์™€ ์ขŒ์„๋ฒ„์Šค ๊ฐ„ ๋ฒ”์œ„์˜ ๊ฒฝ์ œ์„ฑ 161 4) ํ‰๊ท ๋น„์šฉ ๋ฐ ์ตœ์†Œํšจ์œจ๊ทœ๋ชจ 170 5) ์‹œ๋‚ด๋ฒ„์Šค ์šดํ–‰๋น„์šฉ์— ๋Œ€ํ•œ ์ค€๊ณต์˜์ œ์˜ ์˜ํ–ฅ 177 4. ์‹œ๋‚ด๋ฒ„์Šค์šด์†ก์—…์˜ ๊ตฌ์กฐ๊ฐœํŽธ๋ฐฉ์•ˆ 184 1) ์ขŒ์„๋ฒ„์Šค ๋ถ€๋ฌธ์˜ ๋ถ„๋ฆฌ๋ฅผ ํ†ตํ•œ ์šด์†ก์›๊ฐ€ ์ ˆ๊ฐ๋ฐฉ์•ˆ(์„œ์šธ์‹œ ๋Œ€์ƒ) 184 2) ๋Œ€ํ˜•ํ™”๋ฅผ ํ†ตํ•œ ์šด์†ก์›๊ฐ€ ์ ˆ๊ฐ๋ฐฉ์•ˆ(์„œ์šธ์‹œ ๋Œ€์ƒ) 187 3) ๊ตฌ์กฐ๊ฐœํŽธ๋ฐฉ์•ˆ์˜ ์‹คํ˜„์„ ์œ„ํ•œ ์žฌ์ •์ง€์›๋ฐฉ๋ฒ• 191 โ…ฅ. ๊ฒฐ๋ก  196 1. ์—ฐ๊ตฌ๊ฒฐ๊ณผ์˜ ์š”์•ฝ๊ณผ ์ •์ฑ…์  ์‹œ์‚ฌ์  196 1) ์—ฐ๊ตฌ๊ฒฐ๊ณผ์˜ ์š”์•ฝ 196 2) ์ •์ฑ…์  ์‹œ์‚ฌ์  198 2. ๋…ผ๋ฌธ์˜ ํ•œ๊ณ„ ๋ฐ ํ–ฅํ›„ ์—ฐ๊ตฌ๋ฐฉํ–ฅ 202Docto
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