27 research outputs found

    ๋™๊ธฐ ์œ ํ•œ ์ƒํƒœ ๊ธฐ๊ณ„์—์„œ ์‚ฌ์ดํด ๋ณ„ ์ „๋ ฅ ์†Œ๋ชจ์˜ ์ •ํ™•ํ•œ ์ธก์ •

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    ํ•™์œ„๋…ผ๋ฌธ(์„์‚ฌ)--์„œ์šธ๋Œ€ํ•™๊ต ๋Œ€ํ•™์› :์ปดํ“จํ„ฐ๊ณตํ•™๊ณผ,2000.Maste

    Policy dilemma of Bilateral Investment Treaties: A Case Study of Recent Indian Government Policies

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    ๊ฐœ๋„๊ตญ๋“ค์€ ์™ธ๊ตญ์ธ์ง์ ‘ํˆฌ์ž์˜ ์œ ์น˜๋ฅผ ๋ชฉ์ ์œผ๋กœ ๊ฒฝ์Ÿ์ ์œผ๋กœ ์–‘์ž๊ฐ„ ํˆฌ์žํ˜‘์ •์„ ์ฒด๊ฒฐํ•ด์™”๋‹ค. ์™ธ๊ตญ์ธ ํˆฌ์ž์œ ์น˜ ์ธก๋ฉด์—์„œ ๊ธฐ๋Œ€ํ•œ ๋งŒํผ์˜ ๊ธ์ •์  ํšจ๊ณผ๋Š” ๋“œ๋Ÿฌ๋‚˜์ง€ ์•Š๊ณ  ์žˆ์ง€๋งŒ, ์—ฌ์ „ํžˆ ํˆฌ์žํ˜‘์ •์€ ์™ธ๊ตญ์ธ ํˆฌ์ž์ž๋“ค์ด ํ•„์š”๋กœ ํ•˜๋Š” ํˆฌ์ž๋ณดํ˜ธ์— ๊ด€ํ•œ ๋ฒ•์  ์•ˆ์ „์„ฑ์„ ์ œ๊ณตํ•˜๋Š” ์œ ์šฉํ•œ ์ˆ˜๋‹จ์ด ๋˜๊ณ  ์žˆ๋‹ค. ๊ทธ๋Ÿฌ๋‚˜ ํ˜„์ง€๊ตญ ์ •๋ถ€๊ฐ€ ์™ธ๊ตญ์ธํˆฌ์ž์ž์— ์˜ํ•ด ๊ตญ์ œ์ค‘์žฌ์— ํ”ผ์†Œ๋˜๋Š” ํˆฌ์ž์ž ๋Œ€ ์ •๋ถ€ ๊ฐ„ ๋ถ„์Ÿ์ด ๊ธ‰์†ํžˆ ์ฆ๊ฐ€ํ•˜๋ฉด์„œ, ํˆฌ์žํ˜‘์ •์˜ ์ž ์žฌ์  ๋น„์šฉ์— ๋Œ€ํ•œ ๊ฐœ๋„๊ตญ ์ •๋ถ€์˜ ์ธ์‹์ด ์ œ๊ณ ๋˜๊ณ  ์žˆ๋‹ค. ์ด์— ๋”ฐ๋ผ ์™ธ๊ตญ์ธ ํˆฌ์ž์œ ์น˜์˜ ์ฆ๋Œ€์™€ ํˆฌ์ž๋ถ„์Ÿ์˜ ์ž ์žฌ์  ์œ„ํ—˜์˜ ์ถ•์†Œ๋ผ๋Š” ๋ชฉํ‘œ ์‚ฌ์ด์—์„œ ํˆฌ์žํ˜‘์ •์˜ ๋ฐฉํ–ฅ์— ๊ด€ํ•œ ๊ฐœ๋„๊ตญ ์ •๋ถ€์˜ ์ •์ฑ…์  ๊ณ ๋ฏผ์ด ๋“œ๋Ÿฌ๋‚˜๊ณ  ์žˆ๋‹ค. ๋ณธ ๋…ผ๋ฌธ์—์„œ๋Š” ์ด๋Ÿฌํ•œ ๊ณ ๋ฏผ์ด ์ •์ฑ…์  ๋”œ๋ ˆ๋งˆ์˜ ๋ชจ์Šต์œผ๋กœ ๋‚˜ํƒ€๋‚˜๊ณ  ์žˆ๋Š” ์ตœ๊ทผ ์ธ๋„ ์ •๋ถ€์˜ ์‚ฌ๋ก€์— ๋Œ€ํ•ด ๊ณ ์ฐฐํ•˜๊ณ  ์žˆ๋‹ค. ์™ธ๊ตญ์ธํˆฌ์ž์ž์— ์˜ํ•ด ํ”ผ์†Œ๋˜๋Š” ๋‹ค์ˆ˜์˜ ์‚ฌ๋ก€๋“ค์ด ๋Œ€๋‘๋˜๋ฉด์„œ ์ด์— ๋Œ€ํ•œ ๋Œ€์‘์œผ๋กœ ์ธ๋„์ •๋ถ€๋Š” ๊ธฐ์กด์— ์ฒด๊ฒฐํ•œ ์–‘์ž๊ฐ„ ํˆฌ์žํ˜‘์ •๋“ค์— ๋Œ€ํ•œ ๊ฐœ์ •ํ˜‘์ƒ์„ ์ถ”์ง„ํ•˜๊ธฐ๋กœ ํ•˜๊ณ  ํ˜‘์ƒ ์‹œ ์ธ๋„์ •๋ถ€์˜ ์ž…์žฅ์ด ๋  ์ธ๋„์˜ ๊ฐœ์ • ํˆฌ์žํ˜‘์ •๋ชจ๋ธ์„ ๋ฐœํ‘œํ•˜์˜€๋‹ค. ์ด ๋ชจ๋ธ์€ ์™ธ๊ตญ์ธ ํˆฌ์ž์ž์— ๋Œ€ํ•œ๋ณดํ˜ธ์ˆ˜์ค€์„ ํฌ๊ฒŒ ํ›„ํ‡ด์‹œํ‚จ ๋‚ด์šฉ์œผ๋กœ์„œ, ํˆฌ์ž์œ ์น˜ ์ˆ˜๋‹จ์œผ๋กœ์„œ์˜ ํˆฌ์žํ˜‘์ •์˜ ์œ ์šฉ์„ฑ์„ ํ›ผ์†ํ•˜๋”๋ผ๋„ ์ธ๋„์ •๋ถ€์˜ ํ”ผ์†Œ ์œ„ํ—˜์„ ์ถ•์†Œํ•˜๋Š”๋ฐ ์ดˆ์ ์„ ๋งž์ถ”๊ณ  ์žˆ๋‹ค. ์ด์™€ ๋Œ€์กฐ์ ์œผ๋กœ, ์ตœ๊ทผ ์ธ๋„์˜ ๋ชจ๋”” ์ •๋ถ€๋Š” ์ธ๋„๊ฒฝ์ œ์˜ ์žฌ๋„์•ฝ์„ ๋ชฉํ‘œ๋กœ ์™ธ๊ตญ์ธ์ง์ ‘ํˆฌ์ž ์œ ์น˜์ •์ฑ…์— ๋ฐฉ์ ์„ ๋‘๊ณ , ์ด์˜ ์ผํ™˜์œผ๋กœ ๋ฏธ๊ตญ๊ณผ์˜ ์–‘์ž๊ฐ„ ํˆฌ์žํ˜‘์ •์„ ์ ๊ทน ์ถ”์ง„ํ•˜๊ณ  ์žˆ๋‹ค. ๋ฌธ์ œ๋Š” ์ธ๋„์˜ ๊ฐœ์ • ํˆฌ์žํ˜‘์ • ๋ชจ๋ธ๊ณผ ๋ฏธ๊ตญ์˜ ํˆฌ์žํ˜‘์ • ๋ชจ๋ธ ๊ฐ„์— ์ฃผ์š” ๋‚ด์šฉ์—์„œ ํฐ ๊ดด๋ฆฌ๊ฐ€ ์กด์žฌํ•œ๋‹ค๋Š” ์ ์— ์žˆ๋‹ค. ๋ฏธ๊ตญ์ด ์ธ๋„์˜ ๊ฐœ์ •ํˆฌ์žํ˜‘์ •๋ชจ๋ธ์˜ ๋‚ด์šฉ์„ ์ƒ๋‹นํžˆ ์ˆ˜์šฉํ•˜๋Š” ์„ ์—์„œ ๋‚ฎ์€ ์ˆ˜์ค€์˜ ํˆฌ์žํ˜‘์ •์„ ๋ฐ›์•„๋“ค์ผ ๊ฐ€๋Šฅ์„ฑ์€ ํฌ๋ฐ•ํ•˜๋‹ค. ๋ฐ˜๋ฉด ์ธ๋„์ •๋ถ€๊ฐ€ ๋ฏธ๊ตญ์˜ ์š”๊ตฌ๋ฅผ ์ˆ˜์šฉํ•˜์—ฌ ๋†’์€ ์ˆ˜์ค€์˜ ํˆฌ์žํ˜‘์ •์„ ์ฒด๊ฒฐํ•˜๋Š” ๊ฒฝ์šฐ, ํ–ฅํ›„ ๋‹ค๋ฅธ ์„ ์ง„๊ตญ๋“ค๊ณผ์˜ ํˆฌ์žํ˜‘์ • ๊ฐœ์ •ํ˜‘์ƒ ๊ณผ์ •์—์„œ๋„ ์ธ๋„์ •๋ถ€๋Š” ์ž๊ตญ์˜ ๊ฐœ์ • ํˆฌ์žํ˜‘์ • ๋ชจ๋ธ์„ ์ฃผ์žฅํ•˜๊ธฐ์— ์–ด๋ ค์šด ์ž…์žฅ์— ๋†“์ผ ์ˆ˜๋ฐ–์— ์—†๋‹ค. ์™ธ๊ตญ์ธํˆฌ์ž์œ ์น˜๋ฅผ ๋ชฉํ‘œ๋กœ ํ•œ ๋ฏธ๊ตญ๊ณผ์˜ ์–‘์ž๊ฐ„ํˆฌ์žํ˜‘์ • ์ฒด๊ฒฐ, ํˆฌ์ž๋ถ„์Ÿ์˜ ํšŒํ”ผ๋ฅผ ๋ชฉํ‘œ๋กœ ํ•œ ๊ฐœ์ • ํˆฌ์žํ˜‘์ •๋ชจ๋ธ์€ ์ธ๋„์ •๋ถ€๊ฐ€ ๋™์‹œ์— ์ถ”๊ตฌํ•˜๊ธฐ ์–ด๋ ค์šด ๊ณผ์ œ์ด๋‹ค.Developing countries have competitively signed bilateral investment treaties (BITs) in order to attract more foreign direct investment. Though the benefits of participation in BITs for developing countries are now perceived less apparent than expected, BITs are still useful tools to afford legal security needed by foreign investors. On the other hand, developing countries become increasingly aware of the potential costs of BITs with the rapid growth in the number of investor-state dispute settlement cases. Governments in many developing countries are now facing a challenge in their BIT policies to find a proper balance between the two objectives of promoting inward foreign investment and mitigating potential risk being claimed by foreign investors. This paper studies the case of the Indian government which is facing a policy dilemma of BITs. As a reaction to a number of arbitration claims brought by foreign investors, the Indian government drafted a new model BIT text which will serve as a template for Indias future BIT renegotiations. The new model reflects a significantly regressive attitudes towards foreign investment protection. It may help Indian government avoid arbitration claims, but curtails the usefulness to foreign investors. In contrast, the Indian government is eager to pursue a bilateral investment treaty with the United States. The Indian government led by PM Modi puts emphasis on foreign direct investment to revive the economy and undertakes a number of initiatives, including the restart of stalled negotiations on BIT with the US, to restore foreign investor confidence. The India governments dilemma is that there Is a vast divergence between its new model BIT and the US model BIT on fundamental issues. The US is not expected to cede considerable ground to conclude a low-standard BIT with India. If India agrees to US demands for a high-standard BIT, then its new model BIT will lose ground as an acceptable proposal in the future negotiations with other capital exporting countries

    ๊ฐ€๊ฒฉ๋น„๊ต์‡ผํ•‘์„ ์œ„ํ•œ ์•„์ดํ…œ์ง‘ํ•ฉ ์ƒ์„ฑ ๊ธฐ๋ฒ•

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    ํ•™์œ„๋…ผ๋ฌธ (๋ฐ•์‚ฌ)-- ์„œ์šธ๋Œ€ํ•™๊ต ๋Œ€ํ•™์› : ์‚ฐ์—…๊ณตํ•™๊ณผ, 2012. 8. ๋ฐ•์ข…ํ—Œ.๊ฐ€๊ฒฉ๋น„๊ต ์‡ผํ•‘์„œ๋น„์Šค(price comparison shopping service)๋Š” ๊ฐ ์•„์ดํ…œ ํƒ€์ž…(item type)์— ๋Œ€ํ•œ ์•„์ดํ…œ ์ง‘ํ•ฉ(itemset)์„ ์ œ๊ณตํ•˜๋Š” ์‡ผํ•‘ ๋„๊ตฌ๋กœ ํ™œ์šฉ๋˜๊ณ  ์žˆ๋‹ค. ์ด๋•Œ ์•„์ดํ…œ ์ง‘ํ•ฉ์€ ๋™์ผํ•œ ์•„์ดํ…œ ํƒ€์ž…์— ํ•ด๋‹น๋˜๋Š” ์•„์ดํ…œ๋“ค์˜ ์ง‘ํ•ฉ์œผ๋กœ ์ •์˜๋œ๋‹ค. ๋”ฐ๋ผ์„œ, ์†Œ๋น„์ž๋“ค์€ ๊ฐ€๊ฒฉ๋น„๊ต ์‡ผํ•‘์„œ๋น„์Šค๋ฅผ ์ด์šฉํ•˜์—ฌ ๊ฐœ๋ณ„ ์‡ผํ•‘๋ชฐ์— ๋ฐฉ๋ฌธํ•˜์ง€ ์•Š๊ณ ๋„ ๋‹ค์–‘ํ•œ ๊ตฌ๋งค ๋Œ€์•ˆ์„ ๊ฐ€๊ฒฉ ์ธก๋ฉด์—์„œ ๋น„๊ตํ•  ์ˆ˜ ์žˆ๊ฒŒ ๋˜์–ด ์•„์ดํ…œ์„ ์ฐพ๋Š” ๋น„์šฉ์„ ์ ˆ๊ฐํ•  ์ˆ˜ ์žˆ๋‹ค. ์ด์ฒ˜๋Ÿผ ๊ฐ€๊ฒฉ๋น„๊ต ์‡ผํ•‘์„œ๋น„์Šค๋Š” ์†Œ๋น„์ž์—๊ฒŒ ๋…ํŠนํ•œ ๊ฐ€์น˜๋ฅผ ์ œ๊ณตํ•จ์—๋„ ๋ถˆ๊ตฌํ•˜๊ณ , ์„œ๋น„์Šค ์šด์˜์— ๋งŽ์€ ์‹œ๊ฐ„๊ณผ ๋น„์šฉ์ด ์†Œ๋ชจ๋˜๊ธฐ ๋•Œ๋ฌธ์— ์„œ๋น„์Šค ํšจ์œจ๊ฐœ์„ ์„ ์œ„ํ•œ ์—ฐ๊ตฌ๊ฐ€ ํ•„์š”ํ•˜๋‹ค. ์ด ๋…ผ๋ฌธ์€ ํฌ๊ฒŒ ๋„ค ๋ถ€๋ถ„์œผ๋กœ ๊ตฌ์„ฑ๋˜์–ด ์žˆ์œผ๋ฉฐ, ๊ฐ ๋ถ€๋ถ„์€ ๊ฐ€๊ฒฉ๋น„๊ต ์‡ผํ•‘์„œ๋น„์Šค์—์„œ ๋ฐœ์ƒํ•˜๋Š” ๊ฐ ๋ฌธ์ œ์— ๋Œ€ํ•œ ํ•ด๊ฒฐ๋ฐฉ์•ˆ์„ ์ œ์‹œํ•œ๋‹ค. ๋…ผ์˜๋˜๋Š” ๋ฌธ์ œ๋“ค์€ ์•„์ดํ…œ ์ง‘ํ•ฉ์˜ ์ƒ์„ฑ๊ธฐ๋ฒ•์ด ๋Œ€์šฉ๋Ÿ‰์˜ ์•„์ดํ…œ์„ ์ฒ˜๋ฆฌํ•ด์•ผ ํ•œ๋‹ค๋Š” ์ ๊ณผ ์•„์ดํ…œ ์ง‘ํ•ฉ ์ƒ์„ฑ๋ฐฉ๋ฒ•์€ ์„œ๋น„์Šค์˜ ์ˆ˜์ต๊ณผ ์งˆ์— ์ง์ ‘์ ์œผ๋กœ ์˜ํ–ฅ์„ ๋ฏธ์นœ๋‹ค๋Š” ์ ์— ์ฐฉ์•ˆํ•˜๊ณ  ์žˆ๋‹ค. ๊ตฌ์ฒด์ ์œผ๋กœ, ๋ณธ ๋…ผ๋ฌธ์—์„œ ์–ธ๊ธ‰๋˜๋Š” ๋„ค ๊ฐ€์ง€ ๋ฌธ์ œ๋“ค๊ณผ ์ด์˜ ํ•ด๊ฒฐ์„ ์œ„ํ•ด ์ œ์•ˆ๋˜๋Š” ๊ธฐ๋ฒ•๋“ค์€ ๋‹ค์Œ๊ณผ ๊ฐ™๋‹ค. ์ฒซ์งธ, ํšจ์œจ์ ์ธ ์•„์ดํ…œ ์ง‘ํ•ฉ์ƒ์„ฑ(itemset construction)์„ ์œ„ํ•œ ์•„์ดํ…œ ๋žญํ‚น(item ranking)๊ธฐ๋ฒ•์ด ์ œ์•ˆ๋œ๋‹ค. ์•„์ดํ…œ ์ง‘ํ•ฉ ์ƒ์„ฑ์ž‘์—…์€ ์ž‘์—…์ž์˜ ์ˆ˜์ž‘์—…์„ ๋™๋ฐ˜ํ•˜๊ฒŒ ๋˜๋Š”๋ฐ, ์ด๋•Œ ๊ฐ ์•„์ดํ…œ ์ง‘ํ•ฉ์— ๋Œ€ํ•ด ์‹ ๊ทœ ์•„์ดํ…œ์„ ๋žญํ‚น ํ•˜๋Š” ๊ฒƒ์€ ์ž‘์—…์ž๋“ค์˜ ์ž‘์—…๋Ÿ‰์„ ์ค„์ด๋Š”๋ฐ ๋งค์šฐ ์ค‘์š”ํ•˜๋‹ค. ์ œ์•ˆ๋œ ์•„์ดํ…œ ๋žญํ‚น๊ธฐ๋ฒ•์€ ๊ฐ ์•„์ดํ…œ ์ง‘ํ•ฉ์— ์†ํ•ด ์žˆ๋Š” ์•„์ดํ…œ๋“ค์˜ ์„ค๋ช…(item description)๊ณผ ๊ฐ€๊ฒฉ(item price)์„ ์ด์šฉํ•˜์—ฌ ํ•ด๋‹น ์•„์ดํ…œ ์ง‘ํ•ฉ์— ๋Œ€ํ•œ ์‹ ๊ทœ ์•„์ดํ…œ๋“ค์˜ ๋žญํ‚น์„ ๋ชฉ์ ์œผ๋กœ ํ•œ๋‹ค. ๊ธฐ์กด์˜ ๋‹จ์–ด ๊ฐ€์ค‘์น˜(term weighting) ๊ธฐ๋ฒ•์„ ๊ธฐ๋ฐ˜์œผ๋กœ, ๋ณธ ์—ฐ๊ตฌ์—์„œ๋Š” ๋‹จ์–ด์˜ ์ •๋ณด์„ฑ(term informativeness)๊ณผ ์—ฐ๊ด€์„ฑ(term cohesiveness)์„ ๊ณ ๋ คํ•œ ๋‹จ์–ด ๊ฐ€์ค‘์น˜๋ฅผ ์—ฐ๊ตฌํ•˜์˜€๊ณ , ๊ฐ€๊ฒฉ์„ ๋ฐ”ํƒ•์œผ๋กœ ํŠน์ • ์•„์ดํ…œ์ง‘ํ•ฉ์— ๋Œ€ํ•ด ์•„์ดํ…œ๋“ค์˜ ๊ฐ€์ค‘์น˜(item weighting)๋ฅผ ์‚ฐ์ •ํ•˜์˜€๋‹ค. ์ œ์•ˆ๋œ ๊ธฐ๋ฒ•์€ ๊ธฐ์กด ๊ธฐ๋ฒ•๋“ค ๋Œ€๋น„ ๊ฐœ์„ ๋œ ์•„์ดํ…œ ๋žญํ‚น์„ฑ๋Šฅ์„ ๋ณด์˜€์œผ๋ฉฐ, ์ œ์•ˆ๋œ ๊ธฐ๋ฒ•์„ ํ†ตํ•ด ๊ฐ€๊ฒฉ๋น„๊ต ์‡ผํ•‘์„œ๋น„์Šค์—์„œ ์ž‘์—…์ž๋“ค์˜ ์ž‘์—…๋Ÿ‰๊ณผ ์•„์ดํ…œ ์ง‘ํ•ฉ์˜ ์˜ค๋ฅ˜๋ฅผ ์ค„์ผ ์ˆ˜ ์žˆ์„ ๊ฒƒ์œผ๋กœ ํŒ๋‹จ๋œ๋‹ค. ๋‘˜์งธ, ๊ฐ€๊ฒฉ๋น„๊ต ์‡ผํ•‘์„œ๋น„์Šค์˜ ์šด์˜๋น„์šฉ(operational cost) ์ตœ์†Œํ™”๋ฅผ ์œ„ํ•œ ๊ธฐ๋ฒ•์„ ๊ฐœ๋ฐœํ•˜์˜€๋‹ค. ์šด์˜๋น„์šฉ ์ตœ์†Œํ™”๋ฅผ ์œ„ํ•œ ๊ธฐ๋ฒ•์—์„œ๋Š” ์•„์ดํ…œ์ง‘ํ•ฉ ์ƒ์„ฑ์‹œ์˜ ์ฃผ์–ด์ง„ ๊ฐ ๋น„์šฉ ํŒŒ๋ผ๋ฉ”ํ„ฐ(cost parameter)๋“ค์„ ๋ฐ”ํƒ•์œผ๋กœ ์˜ค๋ฅ˜(processing error)์™€ ์‹œ๊ฐ„(processing time)์˜ ๊ท ํ˜•(trade-off)์„ ๊ณ ๋ คํ•จ์œผ๋กœ์จ ๊ฐ€์žฅ ์šด์˜๋น„์šฉ์„ ์ตœ์†Œํ™”ํ•  ์ˆ˜ ์žˆ๋Š” ์•„์ดํ…œ ๋ถ„๋ฅ˜๊ธฐ(item classifier)๋ฅผ ์„ ํƒํ•˜๋Š” ๋ฐฉ๋ฒ•์„ ์ œ์•ˆํ•œ๋‹ค. ๋‹ค์–‘ํ•œ ๋น„์šฉ ํŒŒ๋ผ๋ฉ”ํ„ฐ๋“ค์˜ ๊ฐ’๋“ค์— ๋Œ€ํ•ด ๋ชจ์˜ ์‹คํ—˜์„ ์ˆ˜ํ–‰ํ•ด ํ•ด๋ณธ ๊ฒฐ๊ณผ, ์ œ์•ˆ๋œ ๊ธฐ๋ฒ•์€ ๊ฐ€๊ฒฉ๋น„๊ต ์‡ผํ•‘์„œ๋น„์Šค์˜ ์šด์˜๋น„์šฉ์„ ํฌ๊ฒŒ ์ ˆ๊ฐํ•  ์ˆ˜ ์žˆ๋Š” ๊ฒƒ์œผ๋กœ ๋‚˜ํƒ€๋‚ฌ๋‹ค. ๋‹ค์Œ์œผ๋กœ, ์†Œ๋น„์ž์˜ ์•„์ดํ…œ ์ง‘ํ•ฉ๊ณผ ๋žญํฌ ๋ณ„์˜ ์•„์ดํ…œ ํด๋ฆญ ํšŸ์ˆ˜(click-through)๋ฅผ ์ด์šฉํ•˜์—ฌ ๊ฐ€๊ฒฉ๋น„๊ต ์‡ผํ•‘์„œ๋น„์Šค์˜ ์ˆ˜์ต(revenue)์„ ๊ทน๋Œ€ํ™”ํ•˜๋Š” ๊ธฐ๋ฒ•์ด ์ œ์•ˆ๋˜์—ˆ๋‹ค. ๊ฐœ๋ฐœ๋œ ๊ธฐ๋ฒ•์€ ๊ฐ ์•„์ดํ…œ์ด ํŠน์ • ์•„์ดํ…œ ์ง‘ํ•ฉ์—์„œ์˜ ๋žญํฌ(rank)์™€ ์†Œ์†(membership)๋ณ€ํ™”๋ฅผ ๋™์‹œ์— ๊ณ ๋ คํ•˜์—ฌ, ์•„์ดํ…œ๋“ค์„ ๋ณด๋‹ค ๋งŽ์€ ํด๋ฆญ์„ ์œ ๋ฐœํ•  ์ˆ˜ ์žˆ๋Š” ์•„์ดํ…œ ์ง‘ํ•ฉ์œผ๋กœ ์†Œ์†์„ ์žฌ์ •์˜(membership re-assignment)ํ•œ๋‹ค. ์‹คํ—˜๊ฒฐ๊ณผ ์ œ์•ˆ๋œ ๊ธฐ๋ฒ•์€ ๊ธฐ์กด์˜ ๊ธฐ๋ฒ•๋“ค์— ๋น„ํ•ด ์†Œ๋น„์ž๋“ค์˜ ํด๋ฆญ ํšŸ์ˆ˜๋ฅผ ํฌ๊ฒŒ ํ–ฅ์ƒ ์‹œํ‚ฌ ์ˆ˜ ์žˆ๋Š” ์•„์ดํ…œ์ง‘ํ•ฉ ์ƒ์„ฑ์— ์ ํ•ฉํ•œ ๊ฒƒ์œผ๋กœ ํŒ๋‹จ๋œ๋‹ค. ๋งˆ์ง€๋ง‰์œผ๋กœ, ๊ฐ€๊ฒฉ์‚ฌ๊ธฐ(pricing fraud)๋ฅผ ์ž๋™์œผ๋กœ ์‹๋ณ„ํ•˜๊ธฐ ์œ„ํ•œ ๋ชจ๋ธ์ด ์ œ์•ˆ๋œ๋‹ค. ๊ฐ€๊ฒฉ๋น„๊ต ์‡ผํ•‘์„œ๋น„์Šค์—์„œ์˜ ๊ฐ€๊ฒฉ์‚ฌ๊ธฐ๋Š” ์„œ๋น„์Šค์˜ ์งˆ์„ ์ €ํ•˜์‹œํ‚ฌ ๋ฟ๋งŒ ์•„๋‹ˆ๋ผ ์ด๋“ค์„ ์ •์ •ํ•˜๊ธฐ ์œ„ํ•œ ์ž‘์—…์œผ๋กœ ์ธํ•ด ์„œ๋น„์Šค ์šด์˜๋น„์šฉ์„ ํฌ๊ฒŒ ์ฆ๊ฐ€์‹œํ‚ค๋Š” ๋ฌธ์ œ๋ฅผ ์•ผ๊ธฐํ•œ๋‹ค. ๊ธฐ์กด์˜ ์—ฐ๊ตฌ๋Š” ๋Œ€๋ถ€๋ถ„์˜ ํ™˜๊ฒฝ์—์„œ๋Š” ์–ป๊ธฐ ์–ด๋ ค์šด ์ถ”๊ฐ€์ ์ธ ์ •๋ณด๋ฅผ ์ด์šฉํ•˜์—ฌ ๊ฐ€๊ฒฉ์‚ฌ๊ธฐ๋ฅผ ์‹๋ณ„ํ•˜๋Š”๋ฐ ๋ชฉ์ ์„ ๋‘๊ณ  ์žˆ๊ธฐ ๋•Œ๋ฌธ์—, ๋‹ค์–‘ํ•œ ์‹ค์ œ ์„œ๋น„์Šค์—์„œ์˜ ์ ์šฉ์€ ์ œํ•œ์ ์ด๋ผ ํ•  ์ˆ˜ ์žˆ๋‹ค. ๋”ฐ๋ผ์„œ, ๋ณธ ์—ฐ๊ตฌ์—์„œ๋Š” ์ถ”๊ฐ€์ ์ธ ์ •๋ณด๋‚˜ ์‹œ์Šคํ…œ ์—†์ด๋„ ๊ฐ ์•„์ดํ…œ์˜ ๊ฐ€๊ฒฉ์‚ฌ๊ธฐ๋ฅผ ์‹๋ณ„ํ•  ์ˆ˜ ์žˆ๋Š” ๋น„์ง€๋„ ํ•™์Šต(unsupervised learning) ๊ธฐ๋ฐ˜์˜ ๋ชจ๋ธ์„ ๊ฐœ๋ฐœํ•˜์˜€๋‹ค. ์ œ์•ˆ๋œ ๋ณธ ๊ธฐ๋ฒ•์€ ๊ฐ€๊ฒฉ์‚ฌ๊ธฐ ์•„์ดํ…œ์„ ์‹๋ณ„ํ•˜๋Š”๋ฐ ๊ธฐ์กด ๊ธฐ๋ฒ•๋“ค ๋Œ€๋น„ ์•ž์„  ์„ฑ๋Šฅ์„ ๋ณด์˜€๋‹ค. ๋ณธ ๋…ผ๋ฌธ์˜ ๊ธฐ์—ฌ์™€ ์‘์šฉ๋ฐฉ์•ˆ์€ ๋‹ค์Œ๊ณผ ๊ฐ™์€ ์„ธ ๊ฐ€์ง€๋กœ ์š”์•ฝ๋  ์ˆ˜ ์žˆ๋‹ค. ์ฒซ์งธ, ๋ณธ ๋…ผ๋ฌธ์€ ๊ฐ€๊ฒฉ๋น„๊ต ์‡ผํ•‘์„œ๋น„์Šค์—์„œ ํ•ต์‹ฌ์ ์ธ ๋ฌธ์ œ๋“ค์„ ๋ชจ๋‘ ํ•ด๊ฒฐํ•˜๊ธฐ ์œ„ํ•œ ํ†ตํ•ฉ๋œ ์•„์ดํ…œ์ง‘ํ•ฉ ์ƒ์„ฑ๊ธฐ๋ฒ•๋“ค์„ ์ œ์‹œํ•˜์˜€๊ณ , ์ž‘์—…์ž์˜ ์ž‘์—…๋Ÿ‰์„ ์ค„์ด๊ณ  ์„œ๋น„์Šค์˜ ์งˆ์„ ๋†’์ด๋Š”๋ฐ ์ค‘์š”ํ•œ ์—ญํ• ์„ ์ˆ˜ํ–‰ํ•˜๊ฒŒ ๋  ๊ฒƒ์œผ๋กœ ํŒ๋‹จ๋œ๋‹ค. ๋‘˜์งธ, ์ œ์‹œ๋œ ๊ธฐ๋ฒ•๋“ค์€ ๊ธฐ์กด์˜ ์˜ค๋ฅ˜ ์ตœ์†Œํ™”(error minimizing classification), ์•„์ดํ…œ ๋ฒˆ๋“ค๋ง(item bundling), ํด๋ฆญ ๋ถ„์„(click-through analysis) ๋ฐ ์‚ฌ๊ธฐ์‹๋ณ„(fraud detection) ๋“ฑ์˜ ์ „์ž์ƒ๊ฑฐ๋ž˜(e-Commerce) ๊ด€๋ จ ์—ฐ๊ตฌ๋“ค ์ ‘๋ชฉํ•˜๊ณ  ํ™•์žฅํ•˜์—ฌ ๊ฐ€๊ฒฉ๋น„๊ต ์‡ผํ•‘์„œ๋น„์Šค์— ์ ํ•ฉํ•œ ํ†ตํ•ฉ๋œ ๋ฐฉ๋ฒ•์„ ์ œ์‹œํ•˜์˜€๋‹ค. ๋‚˜์•„๊ฐ€์„œ, ๋ณธ ์—ฐ๊ตฌ๋Š” ์‹ค์ œ ๊ฐ€๊ฒฉ๋น„๊ต ์‡ผํ•‘์„œ๋น„์Šค์˜ ๋ฐ์ดํ„ฐ๋ฅผ ๋ฐ”ํƒ•์œผ๋กœ ์—ฐ๊ตฌ ๋ฐ ์‹คํ—˜๋˜์–ด ์ด๋ก ์ ๋ฟ๋งŒ ์•„๋‹ˆ๋ผ ์‹ค์šฉ์ ์œผ๋กœ๋„ ์˜๋ฏธ ์žˆ๋Š” ๊ฒƒ์œผ๋กœ ๊ฒ€์ฆ๋˜์—ˆ๋‹ค. ๋ณธ ๋…ผ๋ฌธ์—์„œ ์ œ์‹œ๋œ ๊ธฐ๋ฒ•๋“ค์€ ์‹ค์ œ ํ™˜๊ฒฝ์˜ ๋ฐ์ดํ„ฐ๋ฅผ ์ด์šฉํ•˜์—ฌ ์ถฉ๋ถ„ํžˆ ์„ฑ๋Šฅ์„ ๊ฒ€์ฆํ•˜์˜€๊ธฐ ๋•Œ๋ฌธ์—, ์ œ์‹œ๋œ ๊ธฐ๋ฒ•๋“ค์€ ๋‹ค์–‘ํ•œ ํ˜•ํƒœ์˜ ๊ฐ€๊ฒฉ๋น„๊ต ์‡ผํ•‘์„œ๋น„์Šค์— ํ™œ์šฉ๋  ์ˆ˜ ์žˆ์„ ๊ฒƒ์œผ๋กœ ํŒ๋‹จ๋˜๋ฉฐ,์˜จ๋ผ์ธ ์‡ผํ•‘๋ชฐ์ด๋‚˜ ์˜จ๋ผ์ธ ๊ฒฝ๋งค ๋“ฑ์˜ ์ „์ž์ƒ๊ฑฐ๋ž˜ ์‘์šฉ์„œ๋น„์Šค์—๋„ ์ ์šฉ๋  ์ˆ˜ ์žˆ์„ ๊ฒƒ์œผ๋กœ ์ƒ๊ฐ๋œ๋‹ค. ๋˜ํ•œ, ๋ณธ ์—ฐ๊ตฌ์—์„œ ๊ฐœ๋ฐœ๋œ ์•Œ๊ณ ๋ฆฌ์ฆ˜๊ณผ ํ™•๋ฅ ๋ชจ๋ธ๋“ค์€ ๋‹ค์–‘ํ•œ ์‘์šฉ๋ถ„์•ผ์—์„œ์˜ ๊ณ ๊ธ‰์ฃผ์ œ๋ฅผ ๋‹ค๋ฃจ๊ธฐ ์œ„ํ•œ ์‹œ์ž‘์ ์œผ๋กœ๋„ ํ™œ์šฉ๋  ์ˆ˜ ์žˆ์„ ๊ฒƒ์œผ๋กœ ๊ธฐ๋Œ€๋œ๋‹ค.In online shopping, price comparison shopping services (PCSSs) play an important role in enhancing shopping experience of customers by providing itemsets, which are sets of price-sorted items for an item type. Since the items in an itemset are from a single item type, customers are not only able to compare various purchase alternatives for an item type but also to reduce item search costs by eliminating the need of visiting individual shopping malls. The dissertation aims to address four problems in PCSS, which are to be solved to improve service efficiency and effectiveness in terms of quality and cost, by proposing four methods. Specifically, the developed methods in this dissertation are as the following. First, an item ranking method for itemset construction tasks is proposed. Since itemset construction tasks often involve human intensive labor, a method that can reduce the workload is of great importance in PCSSs. The proposed item ranking method is designed to rank items against an itemset based on terms and prices. The item ranking performances were able to be improved by utilizing the proposed item ranking method compared to those obtained by using alternatives, implying the manual workloads to construct itemsets in PCSSs can be sucessfully reduced. Second, an itemset construction method designed to minimize the operational costs and maximize the revenue of a PCSS is suggested. The first one is to minimize the operational costs of PCSSs by considering the trade-off between itemset construction errors and processing time based on two cost parameters. Through simulating the operational cost of a PCSS by adjusting the cost parameters, it has been shown that the operational costs of PCSSs can be significantly reduced by utilizing the proposed method. Next, a method which aims to maximize the revenue of PCSSs through maximizing the number of click-throughs of customers is developed. Specifially, a mathmatical programming and heuristic algorithm are proposed, which address item membership updates according to rank updates. The proposed revenue maximizing method showed improved results in terms of the expected number of click-throughs compared to the existing methods that consider only textual features of items. Finally, unsupervised learning based models to automatically detect pricing frauds are suggested. Pricing frauds in PCSSs not only reduce service quality but also incur costs to handle them. Nevertheless, the previous research focuses on detecting fraud patterns based on additional information which are costly and limited to obtain in many services. To cope with the limitations, this dissertation applies unsupervised approach to detect pricing frauds without additional information and proprietary systems, and the developed pricing detection model calculates the fraud probability for each item by estimating its fraud state. The experiment results imply that the proposed pricing fraud detection model can further improve the pricing fraud detection performances compared to the previous outlier detection method. The contribution and utility of this dissertation are summarized into three points. Firstly, the dissertation proposes an integrated approach to cover the important issues of PCSSs which are essential to reduce human intensive tasks and improve service quality. Second, the previous work related to e-Commerce, which are error minimizing itemset construction methods, item bundling methods, click-through analysis, and fraud detection methods, are successfully extended and developed in this dissertation for PCSSs. Lastly, this doctoral dissertation attempts to propose an integrated approach for itemset construction which are not only theoretical but also practical to directly cope with the essential issues to construct itemsets for PCSSs in the real-world settings. Since the proposed methods have been sufficiently tested on the real-world datasets of a PCSS, it is expected that the underlying ideas of this dissertation can be employed in various applications of e-Commerce including not only PCSSs but also online shopping malls or internet auction services. Moreover, the proposed methods can be a good starting point to design models that address advanced issues in various domains.1 Introduction 1 1.1 Background and motivation 1 1.2 Objectives 6 1.3 Scope and framework 10 1.4 Thesis outline 12 2 Research Background 13 2.1 Price comparison shopping services (PCSSs) 13 2.2 Itemset construction 17 2.3 Pricing fraud detection 24 3 Itemset Construction methods 30 3.1 Item ranking method 30 3.1.1 Term and item weighting method 31 3.1.2 Item ranking function 37 3.1.3 Experiments 38 3.1.4 Discussions 46 3.2 Cost-conscious method 47 3.2.1 Term selection 50 3.2.2 Cost-conscious classifier selection 54 3.2.3 Experiments 57 3.2.4 Discussions 68 3.3 Revenue maximizing method 70 3.3.1 Revenue maximizing problem 72 3.3.2 Research framework 75 3.3.3 Membership update methods 81 3.3.4 Experiments 91 3.3.5 Discussions 100 4 Pricing Fraud Detection 106 4.1 Research background and objectives 106 4.2 Proposed pricing fraud detection models 109 4.2.1 Pricing fraud detection model (PDM) 109 4.2.2 Pricing fraud detection model with known number of clusters (PDMC) 116 4.3 Parameter estimation 122 4.3.1 EM algorithm for PDM 122 4.3.2 EM algorithm for PDMC 125 4.4 Experiments 129 4.4.1 Dataset 129 4.4.2 Evaluation criteria 131 4.4.3 Outlier detection method 132 4.4.4 Computational issues 132 4.4.5 Experiment results 134 4.5 Discussions 144 5 Conclusions 148 5.1 Summary and contrubutions 148 5.2 Limitations and future research 150 A Glossary 171 B Experiment results 175 B.1 Experiment results for operational cost minimization 175 B.1.1 Macro-F1 values of candidate classifiers according to the number of selected terms 175 B.1.2 Error ratios of candidate classifiers 175 B.1.3 Processing times of candidate classifiers 176 B.1.4 Ratio of monthly operational cost (SVM) 176 B.1.5 Ratio of monthly operational cost (PART) 177 B.2 Experiment results for pricing fraud detection 178 B.2.1 Macro-F1 values when N = 600 178 B.2.2 NMI values when N = 600 178 Abstract (In Korean) 180Docto

    ์ค‘ํ™˜์ž์‹ค์—์„œ ์งˆ๋ณ‘ ํ˜ธ์ „์œผ๋กœ ํ‡ด์›ํ•œ ํ™˜์ž์˜ ์žฅ๊ธฐ์  ์˜ˆํ›„

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    Unjust Enrichment in Civil Enforcement - that is Procedurally Due but Substantively Unfair

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    ํ•™์œ„๋…ผ๋ฌธ(์„์‚ฌ) -- ์„œ์šธ๋Œ€ํ•™๊ต๋Œ€ํ•™์› : ๋ฒ•๊ณผ๋Œ€ํ•™ ๋ฒ•ํ•™๊ณผ, 2023. 2. ์ด๊ณ„์ •.๋ณธ ๋…ผ๋ฌธ์—์„œ๋Š” ๋ฏผ์‚ฌ์ง‘ํ–‰์ ˆ์ฐจ์—์„œ ๋ฐœ์ƒํ•  ์ˆ˜ ์žˆ๋Š” ๋ถ€๋‹น์ด๋“๋ฐ˜ํ™˜์ฒญ๊ตฌ๊ถŒ์˜ ์„ฑ๋ฆฝ ๋ฌธ์ œ๋ฅผ ์—ฐ๊ตฌํ•˜์˜€๋‹ค. ์—ฐ๊ตฌ์˜ ๋ชฉ์ ์€ ์ง‘ํ–‰์ฑ„๊ถŒ์ž์˜ ์‹ค์ฒด์  ๊ถŒ๋ฆฌ์‹คํ˜„์„ ์ตœ๋Œ€ํ•œ ๋ณดํ˜ธํ•˜๋ฉด์„œ ์ง‘ํ–‰์ ˆ์ฐจ๋น„์šฉ์„ ์ตœ์†Œํ™”ํ•˜๋Š” ๋ฐฉ๋ฒ•์„ ์ฐพ๋Š” ๊ฒƒ์ด๊ณ , ๊ทธ ๋ฐฉ๋ฒ•๋ก ์œผ๋กœ ํ•„์ž๊ฐ€ ์ƒ๊ฐํ•˜๋Š” ๋ฏผ์‚ฌ์ง‘ํ–‰์ ˆ์ฐจ์—์„œ ๋ถ€๋‹น์ด๋“ ๋ฌธ์ œ๋ฅผ ๋ฐ”๋ผ๋ณผ ๋•Œ ํ•„์š”ํ•œ ์„ธ ๊ฐ€์ง€ ๊ด€์ ์„ ์ œ์‹œํ•˜๊ณ , ์ง‘ํ–‰์ ˆ์ฐจ์—์„œ ๋ถ€๋‹น์ด๋“์ด ๋ฌธ์ œ๋˜๋Š” ์„ธ ๊ฐ€์ง€ ์ฃผ์š” ์œ ํ˜•์„ ๊ตฌ๋ถ„ํ•œ ํ›„ ๊ฐ ์œ ํ˜•์—์„œ ๋ถ€๋‹น์ด๋“ ๋ฐœ์ƒํ˜•ํƒœ์˜ ํŠน์ˆ˜์„ฑ๊ณผ ๋ฌธ์ œ์ ์„ ๊ฒ€ํ† ํ•˜์—ฌ ๊ทธ์— ๋Œ€ํ•œ ๊ฐœ์„ ๋ฐฉํ–ฅ์„ ๋ฒ•๋ฆฌ์  ์ธก๋ฉด๊ณผ ๋ฒ•์ •์ฑ…์  ์ธก๋ฉด์—์„œ ๊ณ ์ฐฐ(่€ƒๅฏŸ)ํ•˜์˜€๋‹ค. ๋จผ์ €, ๋ฏผ์‚ฌ์ง‘ํ–‰์—์„œ ๋ถ€๋‹น์ด๋“ ๋ฌธ์ œ๋ฅผ ๊ฒ€ํ† ํ•  ๋•Œ ํ•„์š”ํ•œ ๊ด€์ ์œผ๋กœ ๋‹ค์Œ ์„ธ ๊ฐ€์ง€๋ฅผ ์ œ์•ˆํ•˜์˜€๋‹ค. ์ฒซ์งธ๋Š” ์‹ค์ฒด๋ฒ•๊ณผ ์ ˆ์ฐจ๋ฒ•์˜ ์ฃผ์ข…(ไธปๅพž)๊ด€๊ณ„๋ฅผ ์›์น™์œผ๋กœ ํ•˜๋˜ ์ด๋ฅผ ์ ˆ๋Œ€์‹œํ•˜๋Š” ํ˜•์‹๋ก ์„ ๊ฒฝ๊ณ„ํ•˜๊ณ  ๋ฒ•์ •์ฑ…์  ๋ชฉ์ ์— ๋”ฐ๋ผ ๋”์šฑ ์œ ์—ฐํ•œ ์ ‘๊ทผ์ด ํ•„์š”ํ•˜๋‹ค๋Š” ๊ด€์ ์ด๋‹ค. ๋‘˜์งธ๋Š” ๋ฏผ๋ฒ•์ƒ ๋ฐฐํƒ€์  ๋ฌผ๊ถŒ๊ณผ ์ƒ๋Œ€์  ์ฑ„๊ถŒ์˜ ๊ตฌ๋ถ„ ๋ชฉ์ ์„ ์ง‘ํ–‰์ ˆ์ฐจ ๋‚ด์—์„œ๋„ ๊ทธ๋Œ€๋กœ ์œ ์ง€ํ•จ์ด ๋ฒ•๋ฆฌ์ ยท๋ฒ•๊ฒฝ์ œ์ ์œผ๋กœ ํƒ€๋‹นํ•˜๋‹ค๋Š” ๊ด€์ ์ด๋‹ค. ์…‹์งธ๋Š” ์šฐ๋ฆฌ ๋ฏผ์‚ฌ์ง‘ํ–‰์ ˆ์ฐจ๊ฐ€ ์ฑ„๊ถŒ์ž-์ฑ„๋ฌด์ž ์–‘์ž(๏ฅธ่€…)์‚ฌ์ด์˜ ๊ฐœ๋ณ„์ง‘ํ–‰์  ์„ฑ๊ฒฉ๊ณผ ํ•จ๊ป˜ ๋‹ค์ˆ˜์˜ ์ ˆ์ฐจ์ฐธ์—ฌ์ž๊ฐ€ ๊ด€์—ฌํ•˜๋Š” ๋‹จ์ฒด๋ฒ•์  ์„ฑ๊ฒฉ์„ ๊ฐ€์ง€๊ณ  ์žˆ์–ด, ๊ฐœ๋ณ„์ง‘ํ–‰์  ์„ฑ๊ฒฉ์—์„œ๋Š” ์ง‘ํ–‰์ฑ„๊ถŒ์ž์˜ ์‹ค์ฒด์  ๊ถŒ๋ฆฌ์‹คํ˜„์ด ์šฐ์„ ์ด์ง€๋งŒ ๋‹จ์ฒด๋ฒ•์  ์„ฑ๊ฒฉ์—์„œ๋Š” ์ ˆ์ฐจ๊ด€์—ฌ์ž์˜ ์ ˆ์ฐจ์•ˆ์ •์„ฑ ์š”์ฒญ์„ ๋ฌด์‹œํ•  ์ˆ˜ ์—†๋‹ค๋Š” ๊ด€์ ์ด๋‹ค. ๋‹ค์Œ์œผ๋กœ, ๋ฏผ์‚ฌ์ง‘ํ–‰์ ˆ์ฐจ์—์„œ ๋ถ€๋‹น์ด๋“์ด ๋ฌธ์ œ๋˜๋Š” ์œ ํ˜•์„ ์„ธ ๊ฐ€์ง€๋กœ ๊ตฌ๋ถ„ํ•˜์˜€๋‹ค. ์ฒซ ๋ฒˆ์งธ ์œ ํ˜•์€ ํ•˜์ž ์žˆ๋Š” ์ง‘ํ–‰์ฑ„๊ถŒ์— ๋”ฐ๋ฅธ ๊ฐ•์ œ์ง‘ํ–‰์˜ ๊ฒฝ์šฐ์ด๋‹ค. ์ง‘ํ–‰์ฑ„๊ถŒ์ž๊ฐ€ ์ ˆ์ฐจ๋ฒ•์ƒ ์ ๋ฒ•ํ•˜๊ฒŒ ์ง„ํ–‰๋œ ์ง‘ํ–‰์— ์˜ํ•œ ์ฑ„๊ถŒ๋งŒ์กฑ์„ ์–ป๋Š”๋‹ค ํ•˜๋”๋ผ๋„ ๊ทธ๊ฒƒ์ด ์‹ค์ฒด๋ฒ•์ƒ ์ด๋“๋ณด์œ ์˜ ์ •๋‹นํ•œ ๊ถŒ์›์ด ์—†๋Š” ๊ฒฝ์šฐ์—๋Š” ๋ถ€๋‹น์ด๋“์œผ๋กœ ๋ฐ˜ํ™˜ํ•˜์—ฌ์•ผ ํ•œ๋‹ค. ์ด ๊ฒฝ์šฐ ํŒ๊ฒฐ์˜ ๋ชจ์ˆœ๋ฐฉ์ง€๋ผ๋Š” ์†Œ์†ก๋ฒ•์  ๋ชฉ์ ์„ ์œ„ํ•˜์—ฌ ๊ธฐํŒ๋ ฅ์˜ ์‹œ์  ๋ฒ”์œ„์— ์†ํ•˜๋Š” ์‹ค์ฒด์  ์‚ฌ์‹ค์— ๋Œ€ํ•˜์—ฌ๋Š” ๊ธฐํŒ๋ ฅ์ด ์ž‘์šฉํ•˜์—ฌ ํ›„์†Œ์—์„œ ๋ถ€๋‹น์ด๋“ ๋ฐ˜ํ™˜์ฒญ๊ตฌ๊ฐ€ ์ œ์•ฝ๋  ์ˆ˜ ์žˆ๋‹ค. ๋‘ ๋ฒˆ์งธ ์œ ํ˜•์€ ์ œ3์ž์˜ ์žฌ์‚ฐ์— ๋Œ€ํ•œ ๊ฐ•์ œ์ง‘ํ–‰์˜ ๊ฒฝ์šฐ์ด๋‹ค. ์„ ์˜์ทจ๋“์ด๋‚˜ ์ œ3์ž ๋ณดํ˜ธ๊ทœ์ •์— ์˜ํ•˜์—ฌ ๋งค์ˆ˜์ธ์ด ์ง‘ํ–‰๋ชฉ์ ๋ฌผ์˜ ์†Œ์œ ๊ถŒ์„ ์ทจ๋“ํ•  ์ˆ˜ ์žˆ๋Š” ์˜ˆ์™ธ์ ์ธ ๊ฒฝ์šฐ๋ฅผ ์ œ์™ธํ•œ๋‹ค๋ฉด, ์ œ3์ž์˜ ์žฌ์‚ฐ์— ๋Œ€ํ•œ ๊ฐ•์ œ์ง‘ํ–‰์˜ ๊ฒฝ์šฐ๋Š” ์›์น™์ƒ ๋งค์ˆ˜์ธ์ด ์†Œ์œ ๊ถŒ์„ ์ทจ๋“ํ•  ์ˆ˜ ์—†์Œ์ด ํŒ๋ก€์™€ ํ†ต์„ค์˜ ํƒœ๋„์ด๋‹ค. ์ด๋Š” ์ œ3์ž์˜ ์‹ค์ฒด๋ฒ•์ƒ ๊ถŒ๋ฆฌ๋ฅผ ๋ณดํ˜ธํ•˜๊ธฐ ์œ„ํ•˜์—ฌ ์‹ค์ฒด๋ฒ•์˜ ์ ˆ์ฐจ๋ฒ•์— ๋Œ€ํ•œ ์šฐ์œ„(ๅ„ชไฝ)๊ด€๊ณ„์™€ ๋ถ€๋™์‚ฐ๋“ฑ๊ธฐ์˜ ๊ณต์‹ ๋ ฅ์ด ์—†์Œ์„ ๊ทผ๊ฑฐ๋กœ ์ ˆ์ฐจ๋ฒ•์ƒ ์ ๋ฒ•ยท์œ ํšจํ•˜๊ฒŒ ์ง„ํ–‰๋œ ๊ฐ•์ œ์ง‘ํ–‰์˜ ๊ฒฐ๊ณผ๋ฅผ ๋ฌด์‹œํ•˜๋Š” ๊ฒƒ์ด ํƒ€๋‹นํ•˜๋‹ค๋Š” ํŒ๋‹จ์— ๊ทผ๊ฑฐํ•œ๋‹ค. ํ•˜์ง€๋งŒ ์ด๋กœ ์ธํ•˜์—ฌ ๋ถ€๋™์‚ฐ ๋“ฑ๊ธฐ์™€ ๋ฒ•์›์˜ ๊ฒฝ๋งค์ ˆ์ฐจ๋ฅผ ์‹ ๋ขฐํ•œ ๋งค์ˆ˜์ธ์€ ์‹ฌ๊ฐํ•œ ๋ฒ•์  ๋ถˆ์•ˆ์— ์ฒ˜ํ•˜๊ฒŒ ๋˜๋Š” ๋ฌธ์ œ์ ์ด ์žˆ์–ด ๊ทธ ๊ถŒ๋ฆฌ๊ตฌ์ œ์ˆ˜๋‹จ์œผ๋กœ์„œ ๋ฏผ๋ฒ• ์ œ578์กฐ ๋‹ด๋ณด์ฑ…์ž„์˜ ์ ์šฉ์—ฌ๋ถ€๊ฐ€ ๋…ผ์˜๋œ๋‹ค. ์„ธ ๋ฒˆ์งธ ์œ ํ˜•์€ ๋ฐฐ๋‹น์˜ค๋ฅ˜(๋ถ€๋‹น๋ฐฐ๋‹น)์˜ ๊ฒฝ์šฐ์ด๋‹ค. ๋ฐฐ๋‹น์š”๊ตฌ๋กœ ๋ฐฐ๋‹น์— ์ฐธ๊ฐ€ํ•œ ์ผ๋ฐ˜์ฑ„๊ถŒ์ž๊ฐ€ ๋ฐฐ๋‹น๊ธฐ์ผ์— ๋ฐฐ๋‹น์ด์˜๋ฅผ ํ•ดํƒœํ•œ ๊ฒฝ์šฐ์—๋„ ๋ฐฐ๋‹น์ข…๋ฃŒ ํ›„ ๋ถ€๋‹น์ด๋“ ๋ฐ˜ํ™˜์„ ํ†ตํ•˜์—ฌ ๊ทธ ๋ฐฐ๋‹น์•ก ์†์‹ค๋ถ„์„ ๋ฐ˜ํ™˜๋ฐ›์„ ์ˆ˜ ์žˆ๋„๋ก ํ—ˆ์šฉํ•˜๋Š” ๊ฒƒ์ด ํŒ๋ก€์™€ ํ†ต์„ค์˜ ํƒœ๋„์ด๋‹ค. ํŒ๋ก€๋Š” ๊ทธ ๊ทผ๊ฑฐ๋กœ ์ด๋ฅธ๋ฐ” ์‹ค์ฒด์  ๋ฐฐ๋‹น์ˆ˜๋ น๊ถŒ ์ด๋ก ์„ ์ค„๊ณง ์„ค์‹œํ•ด์™”๋‹ค. ๊ทธ๋Ÿฌ๋‚˜ ํ•„์ž๋Š” ๋ฐฐ๋‹น์ข…๋ฃŒ ํ›„ ๋ถ€๋‹น์ด๋“๋ฐ˜ํ™˜์ฒญ๊ตฌ๋ฅผ ๋ถ€์ •ํ•จ์ด ํƒ€๋‹นํ•˜๋‹ค๋Š” ์ž…์žฅ์—์„œ ํŒ๋ก€์˜ ์‹ค์ฒด์  ๋ฐฐ๋‹น์ˆ˜๋ น๊ถŒ ์ด๋ก ์„ ๋น„ํŒ์ ์œผ๋กœ ๊ฒ€ํ† ํ•˜์˜€๋‹ค. ์นจํ•ด๋ถ€๋‹น์ด๋“์˜ ๋ฒ•๋ฆฌ์— ์˜ํ•˜๋”๋ผ๋„ ๋ฏผ์‚ฌ์ง‘ํ–‰๋ฒ• ์ œ155์กฐ์˜ ์‹ค๊ถŒ๊ทœ์ •์ด ์žˆ์–ด ๋ฒ•๋ฆฌ์ ์œผ๋กœ ๋ถ€๋‹น์ด๋“ ๋ถ€์ •์„ค์„ ์ทจํ•˜๋Š” ๊ฒƒ์ด ๊ฐ€๋Šฅํ•˜๊ณ , ์ด์ตํ˜•๋Ÿ‰ ๊ด€์ ์—์„œ๋„ ํŒ๋ก€์˜ ๋ถ€๋‹น์ด๋“ ๊ธ์ •์„ค์€ ๊ณผ๋„ํ•œ ์ ˆ์ฐจ๋ถˆ์•ˆ์„ ์ดˆ๋ž˜ํ•˜๋Š” ๋งŒํผ ๊ทธ ์‹ค์ฒด์  ๊ถŒ๋ฆฌ๋ณด์žฅ์˜ ์‹คํšจ์„ฑ์ด ํฌ์ง€ ์•Š๋‹ค๊ณ  ํŒ๋‹จํ•˜์˜€๋‹ค. ๋งˆ์ง€๋ง‰์œผ๋กœ ๋ฐฐ๋‹น์˜ ์ˆœํ™˜๊ด€๊ณ„๋ผ๋Š” ์šฐ๋ฆฌ ๋ฏผ์‚ฌ์ง‘ํ–‰๋ฒ•์ œ์˜ ํŠน์ˆ˜ํ•œ ์™œ๊ณกํ˜„์ƒ์„ ๊ณ ๋ คํ•  ๋•Œ ๋ฐฐ๋‹น์˜ค๋ฅ˜ ์‚ฌ์•ˆ์—์„œ๋Š” ๋ถ€๋‹น์ด๋“๋ฐ˜ํ™˜์ฒญ๊ตฌ ๋ถ€์ •์„ค์„ ์ทจํ•˜๋Š” ๊ฒƒ์ด ๋ฒ•์ตํ˜•๋Ÿ‰์˜ ๊ฒฐ๊ณผ ์ตœ์„ ์ด๋ผ๋Š” ๊ฒฐ๋ก ์— ๋„๋‹ฌํ•˜์˜€๋‹ค. ๋ฏผ์‚ฌ์ง‘ํ–‰๋ฒ•์ œ๋ฅผ ๋…ผ์˜ํ•˜๋Š” ์ตœ์ข… ๋ชฉ์ ์€, ์ง‘ํ–‰๋ฒ•์›์˜ ์‚ฌ๋ฒ•ํ–‰์ •๋ ฅ๊ณผ ์ง‘ํ–‰์ฐธ์—ฌ์ž๋“ค์˜ ์ ˆ์ฐจ๋น„์šฉ์ด๋ผ๋Š” ๋ฌดํ˜•์˜ ํ•œ์ •๋œ ์ž์‚ฐ์„ ์‚ฌ์šฉํ•˜์—ฌ ๊ตญ๋ฏผ์˜ ์‹ค์ฒด๋ฒ•์ƒ ์žฌ์‚ฐ๊ถŒ ์‹คํ˜„์„ ๊ทน๋Œ€ํ™”ํ•˜๋Š” ๋ฐฉํ–ฅ์œผ๋กœ ๋ฏผ์‚ฌ์ง‘ํ–‰์ œ๋„๋ฅผ ๊ตฌํ˜„ํ•ด ๋‚˜๊ฐ€๋Š” ๊ฒƒ์ด๋ผ๊ณ  ์ƒ๊ฐํ•œ๋‹ค. ๋ฏผ์‚ฌ์ง‘ํ–‰์ ˆ์ฐจ์—์„œ ๋ฐœ์ƒํ•˜๋Š” ๋ถ€๋‹น์ด๋“์— ๋Œ€ํ•œ ๊ธฐ์กด์˜ ๋…ผ์˜์—์„œ๋Š” ์ฑ„๊ถŒ์ž-์ฑ„๋ฌด์ž ์–‘์ž์‚ฌ์ด์—์„œ์˜ ์‹ค์ฒด์  ๊ถŒ๋ฆฌ์‹คํ˜„๋งŒ์„ ์ฃผ๋œ ๋ชฉ์ ์œผ๋กœ ํ•˜์˜€๊ณ , ์ด๋ฅผ ์œ„ํ•˜์—ฌ ์‹ค์ฒด๋ฒ•๊ณผ ์ ˆ์ฐจ๋ฒ•์˜ ์ฃผ์ข…(ไธปๅพž)๊ด€๊ณ„๋ผ๋Š” ๋ฒ•๋ฆฌ์  ํ˜•์‹๋ก ์„ ์ ˆ๋Œ€์‹œํ•˜์˜€๋‹ค. ๊ทธ๋Ÿฌ๋‚˜ ์ฑ„๊ถŒ์žํ‰๋“ฑ์ฃผ์˜๋ผ๋Š” ๋‹จ์ฒด๋ฒ•์  ์ง‘ํ–‰๋ฒ•์ œ๋ฅผ ํƒํ•œ ์šฐ๋ฆฌ ๋ฏผ์‚ฌ์ง‘ํ–‰๋ฒ•์˜ ๊ตฌ์กฐ์  ํŠน์ง•๊ณผ ํ•จ๊ป˜ ์šฐ๋ฆฌ์˜ ๊ฒฝ๋งค์ œ๋„ ๋ฐœ์ „๊ณผ ์‚ฌํšŒ์  ์—ฌ๊ฑด์˜ ๋ณ€ํ™”๋ฅผ ๊ธฐ๋ฐ˜์œผ๋กœ ํ•˜์—ฌ ์ด์ œ๋Š” ์ง‘ํ–‰์ ˆ์ฐจ์ƒ ์†Œ๋ชจ๋˜๋Š” ์ ˆ์ฐจ๋น„์šฉ์˜ ๋ฌธ์ œ, ์ฆ‰ ๋ฒ•์  ์•ˆ์ •์„ฑ์˜ ์š”์ฒญ์„ ๋ฌต๊ณผํ•˜์ง€ ์•Š๋Š” ๋ฐฉํ–ฅ์œผ๋กœ ๋ฒ•ํ•ด์„์„ ์‹œ๋„ํ•  ํ•„์š”๊ฐ€ ์žˆ๋‹ค. ์‹ค์ฒด์  ๊ถŒ๋ฆฌ๋ณดํ˜ธ์— ์ถฉ์‹คํ•˜๋ฉด์„œ๋„ ๊ทธ๋กœ ์ธํ•˜์—ฌ ํฌ์ƒ๋˜๋Š” ๋ฒ•์ ์•ˆ์ •์„ฑ์˜ ์š”์ฒญ์„ ์ตœ์†Œํ™”ํ•˜๋Š” ๋ฐฉํ–ฅ์œผ๋กœ ๋ณด๋‹ค ์œ ์—ฐํ•œ ๋ฏผ์‚ฌ์ง‘ํ–‰์ œ๋„์˜ ์šด์šฉ์ด ํ•„์š”ํ•œ ์‹œ์ ์ด๋‹ค.It is clear that the role of procedural law is the realization of substantive right. In previous discussions, the superiority between procedural law and substantive law was main issue. As it is clear that the role of procedural law is the realization of substantive right, the superiority of substantive law over procedural law can be a starting point for approaching many issues. However, there is a limit to reaching a conclusion only with this superiority relationship between these two laws. In the end, I insist that this problem can be solved only by legal policy decision-making of the court considering procedural transaction costs from the law-economical perspective of a collective procedure. Then, is it possible for a creditor(an applicant for distribution) who did not raise objection to his or her substantively wrongful dividends awarded by the auction court on the distribution date in the civil enforcement distribution procedure to have still a claim for return of wrongful gain(unjust enrichment) after the confirmation of his or her dividends on the grounds that there was substantial unfairness on the confirmed distribution schedule? In accordance with the previous general theory and precedents, this kind of unjust enrichment caused by other persons infringement is similar with tort. Therefore, the requirements of unjust enrichment of this kind are satisfied only when the creditor who had an exclusive right for his or her original dividends such as a holder of the collective security(keun-mortgage) or a mortgage received dividends less than what the auction court should have awarded to him or her during the auction proceedings. However, the creditor who merely acquired a right to demand claims without any exclusive rights in the substantive law and submitted claim statements asking for dividends in auction procedural law can not satisfy the requirement of unjust enrichment in this case. Even in civil enforcement procedure, it shall not be permitted to acknowledge that an creditor without any exclusive rights can be regarded as the exclusive right holder acquiring a kind of mortgage. Because it is against the principle of law to specify the real right (jus in rem) which prohibits the creation of new systems. Although it is reasonable to treat exclusive security right holders and general creditors separately according to the legal principles on the unjust enrichment, our Civil Enforcement Code and legal systems are in a special situation where it is impossible to follow such dichotomy. The main cause of this situation is the enactment of various special laws which were made without systematic consideration of the order of the substantive rights. Due to this chaos, the circulatory relationship of dividends' occurred in the distribution procedure and violates the essential contents of a mortgage, the exclusive right. Therefore, the dichotomy could no longer be used as a standard for civil enforcement distribution procedure. As a result, we face an alternative situation in which we have to choose between the affirmative theory and the negative one regarding the right to claim for return of wrongful gain(unjust enrichment). Even though both of them do not perfectly conform to the legal principles on the unjust enrichment in the substantive law. Thus, this situation can be solved only by legal policy decision-making of the court considering procedural transaction costs from the law-economical perspective of a collective procedure.์ œ1์žฅ ์„œ๋ก  1 ์ œ2์žฅ ๋ฏผ์‚ฌ์ง‘ํ–‰๊ณผ ๋ถ€๋‹น์ด๋“ 5 ์ œ1์ ˆ ๋…ผ์˜์— ํ•„์š”ํ•œ ์„ธ ๊ฐ€์ง€ ๊ด€์  5 1. ์‹ค์ฒด๋ฒ•๊ณผ ์ ˆ์ฐจ๋ฒ•์˜ ์ฃผ์ข…(ไธปๅพž)๊ด€๊ณ„ 5 2. ์‹ค์ฒด๋ฒ•์ƒ ๋ฌผ๊ถŒ๊ณผ ์ฑ„๊ถŒ์˜ ๊ตฌ๋ถ„ 6 3. ์ ˆ์ฐจ๋ฒ•์ƒ ๊ฐœ๋ณ„์ง‘ํ–‰์  ์„ฑ๊ฒฉ๊ณผ ์ฑ„๊ถŒ์ž๊ณต๋™์ฒด์  ์„ฑ๊ฒฉ์˜ ๊ตฌ๋ถ„ 9 ์ œ2์ ˆ ๋ฏผ์‚ฌ์ง‘ํ–‰์ ˆ์ฐจ์—์„œ ๋ถ€๋‹น์ด๋“์ด ๋ฌธ์ œ๋˜๋Š” ์„ธ ๊ฐ€์ง€ ์œ ํ˜• 10 1. ํ•˜์ž ์žˆ๋Š” ์ง‘ํ–‰์ฑ„๊ถŒ์— ๋”ฐ๋ฅธ ๊ฐ•์ œ์ง‘ํ–‰ 11 2. ์ œ3์ž์˜ ์žฌ์‚ฐ์— ๋Œ€ํ•œ ๊ฐ•์ œ์ง‘ํ–‰ 11 3. ๋ฐฐ๋‹น์˜ค๋ฅ˜(๋ถ€๋‹น๋ฐฐ๋‹น) 12 ์ œ3์žฅ ํ•˜์ž ์žˆ๋Š” ์ง‘ํ–‰์ฑ„๊ถŒ์— ๋”ฐ๋ฅธ ๊ฐ•์ œ์ง‘ํ–‰ 14 ์ œ1์ ˆ ๊ฐœ์š” 14 ์ œ2์ ˆ ์ง‘ํ–‰๊ถŒ์› ์„ฑ๋ฆฝ ๋‹น์‹œ๋ถ€ํ„ฐ ์‹ค์ฒด์  ํ•˜์ž๊ฐ€ ์žˆ์—ˆ๋˜ ๊ฒฝ์šฐ 15 1. ์ง‘ํ–‰๊ถŒ์›์— ๊ธฐํŒ๋ ฅ์ด ์žˆ๋Š” ๊ฒฝ์šฐ 15 2. ์ง‘ํ–‰๊ถŒ์›์— ๊ธฐํŒ๋ ฅ์ด ์—†๋Š” ๊ฒฝ์šฐ 17 ์ œ3์ ˆ ์ง‘ํ–‰๊ถŒ์› ์„ฑ๋ฆฝ ํ›„ ์‹ค์ฒด์  ํ•˜์ž๊ฐ€ ์ƒ๊ธด ๊ฒฝ์šฐ 18 ์ œ4์ ˆ ์ง‘ํ–‰์ข…๋ฃŒ ํ›„ ์ง‘ํ–‰๊ถŒ์›์˜ ํšจ๋ ฅ์— ๋ณ€๋™์ด ์žˆ๋Š” ๊ฒฝ์šฐ 18 1. ๊ฐ€์ง‘ํ–‰์„ ๊ณ ๊ฐ€ ์‹คํšจ๋œ ๊ฒฝ์šฐ 19 2. ์žฌ์‹ฌ์œผ๋กœ ์ง‘ํ–‰๊ถŒ์›์ด ํ๊ธฐ๋œ ๊ฒฝ์šฐ 23 ์ œ5์ ˆ ์ง‘ํ–‰๊ถŒ์›์ด ์œ„์กฐ๋œ ๊ฒฝ์šฐ ๋˜๋Š” ๋‹ด๋ณด๊ถŒ์ด ๋ฌดํšจ์ธ ๊ฒฝ์šฐ 24 1. ๊ฐœ์š” 24 2. ์ง‘ํ–‰๊ถŒ์›์ด ์œ„์กฐ๋œ ๊ฒฝ์šฐ 25 3. ๋‹ด๋ณด๊ถŒ์ด ๋ฌดํšจ์ธ ๊ฒฝ์šฐ 25 ๊ฐ€. ๋‹ด๋ณด๊ถŒ์ด ๊ฒฝ๋งค๊ฐœ์‹œ๊ฒฐ์ • ์ „ ์ด๋ฏธ ๋ฌดํšจ์ธ ๊ฒฝ์šฐ 25 ๋‚˜. ๋‹ด๋ณด๊ถŒ์ด ๊ฒฝ๋งค๊ฐœ์‹œ๊ฒฐ์ • ํ›„ ๋ฌดํšจ๊ฐ€ ๋œ ๊ฒฝ์šฐ 34 ์ œ6์ ˆ ์†Œ๊ฒฐ 34 ์ œ4์žฅ ์ œ3์ž์˜ ์žฌ์‚ฐ์— ๋Œ€ํ•œ ๊ฐ•์ œ์ง‘ํ–‰ 36 ์ œ1์ ˆ ๊ฐœ์š” 36 ์ œ2์ ˆ ๋งค์ˆ˜์ธ์ด ๊ฒฝ๋งค๋ชฉ์ ๋ฌผ์„ ์ ๋ฒ•ํ•˜๊ฒŒ ์ทจ๋“ํ•˜์ง€ ๋ชปํ•˜๋Š” ๊ฒฝ์šฐ 36 1. ๋งค์ˆ˜์ธ์˜ ์†Œ์œ ๊ถŒ ์ทจ๋“ ๋ถˆ๋Šฅ 37 2. ์ œ3์ž ์ด์˜์˜ ์†Œ ๋ถˆํ–‰์‚ฌ์™€ ์‹ค๊ถŒํšจ ๋…ผ์˜ 37 3. ๋งค์ˆ˜์ธ ๋ณดํ˜ธ๋ฅผ ์œ„ํ•œ ํ•˜์ž๋‹ด๋ณด์ฑ…์ž„ ๋…ผ์˜ 39 ์ œ3์ ˆ ๋งค์ˆ˜์ธ์ด ๊ฒฝ๋งค๋ชฉ์ ๋ฌผ์„ ์ ๋ฒ•ํ•˜๊ฒŒ ์ทจ๋“ํ•˜๋Š” ๊ฒฝ์šฐ 44 ์ œ4์ ˆ ์†Œ๊ฒฐ 45 ์ œ5์žฅ ๋ฐฐ๋‹น์˜ค๋ฅ˜ 47 ์ œ1์ ˆ ๊ฐœ์š” 47 ์ œ2์ ˆ ๋…ผ์˜์˜ ์ „์ œ 47 1. ๋ถ€๋‹น์ด๋“ ์ผ๋ฐ˜๋ก  47 2. ๋ฐฐ๋‹น์š”๊ตฌ, ๋ฐฐ๋‹น์ด์˜ ์œ ๋ฌด์— ๋”ฐ๋ฅธ ๋ถ€๋‹น์ด๋“ ๊ด€๊ณ„ 48 ๊ฐ€. ๋ฐฐ๋‹น์š”๊ตฌ์˜ ์˜์˜ 48 ๋‚˜. ๋ฐฐ๋‹น์š”๊ตฌ๋ฅผ ํ•˜์ง€ ์•Š์€ ๊ฒฝ์šฐ ๋ถ€๋‹น์ด๋“ ์„ฑ๋ฆฝ์—ฌ๋ถ€ 49 ๋‹ค. ๋ฐฐ๋‹น์š”๊ตฌ๋ฅผ ํ•œ ๊ฒฝ์šฐ ๋ถ€๋‹น์ด๋“ ์„ฑ๋ฆฝ์—ฌ๋ถ€ 50 3. ๋ฐฐ๋‹น์˜ค๋ฅ˜์™€ ๋ถ€๋‹น์ด๋“๋ฐ˜ํ™˜์ฒญ๊ตฌ๊ถŒ 50 ๊ฐ€. ํ•™์„ค 51 ๋‚˜. ํŒ๋ก€ 53 ๋‹ค. ๊ฒ€ํ†  54 ์ œ3์ ˆ ํŒ๋ก€์˜ '์‹ค์ฒด์  ๋ฐฐ๋‹น์ˆ˜๋ น๊ถŒ' ์ด๋ก  56 1. ๊ฐœ๋…๊ณผ ์—ฐํ˜ 56 2. ์นจํ•ด๋ถ€๋‹น์ด๋“ ๊ด€์ ์—์„œ ๋น„ํŒ์  ๊ฒ€ํ†  57 3. ์ด์ตํ˜•๋Ÿ‰ ๊ด€์ ์—์„œ ๋น„ํŒ์  ๊ฒ€ํ†  59 ๊ฐ€. ํ›„์ˆœ์œ„ ๋‹ด๋ณด๊ถŒ์ž์ธ ์›๊ณ ๊ฐ€ ์„ ์ˆœ์œ„ ๋ฌด๊ถŒ๋ฆฌ์ž์ธ ํ”ผ๊ณ ๋ฅผ ์ƒ๋Œ€๋กœ ์ฒญ๊ตฌํ•˜๋Š” ๊ฒฝ์šฐ(์˜์—ญโ… -โ‘ ) 65 ๋‚˜. ์„ ์ˆœ์œ„ ๋‹ด๋ณด๊ถŒ์ž์ธ ์›๊ณ ๊ฐ€ ํ›„์ˆœ์œ„ ์œ ๊ถŒ๋ฆฌ์ž์ธ ํ”ผ๊ณ ๋ฅผ ์ƒ๋Œ€๋กœ ์ฒญ๊ตฌํ•˜๋Š” ๊ฒฝ์šฐ(์˜์—ญโ… -โ‘ก) 67 ๋‹ค. ์ผ๋ฐ˜์ฑ„๊ถŒ์ž์ธ ์›๊ณ ๊ฐ€ ์„ ์ˆœ์œ„ ๋ฌด๊ถŒ๋ฆฌ์ž์ธ ํ”ผ๊ณ ๋ฅผ ์ƒ๋Œ€๋กœ ์ฒญ๊ตฌํ•˜๋Š” ๊ฒฝ์šฐ(์˜์—ญโ…ก-โ‘ a) 68 ๋ผ. ์ผ๋ฐ˜์ฑ„๊ถŒ์ž์ธ ์›๊ณ ๊ฐ€ ๋™์ˆœ์œ„ ๋ฌด๊ถŒ๋ฆฌ์ž์ธ ํ”ผ๊ณ ๋ฅผ ์ƒ๋Œ€๋กœ ์ฒญ๊ตฌํ•˜๋Š” ๊ฒฝ์šฐ(์˜์—ญโ…ก-โ‘ b) 69 ๋งˆ. ์ผ๋ฐ˜์ฑ„๊ถŒ์ž์ธ ์›๊ณ ๊ฐ€ ๋™์ˆœ์œ„ ์œ ๊ถŒ๋ฆฌ์ž์ธ ํ”ผ๊ณ ๋ฅผ ์ƒ๋Œ€๋กœ ์ฒญ๊ตฌํ•˜๋Š” ๊ฒฝ์šฐ(์˜์—ญโ…ก-โ‘ก) 69 ๋ฐ”. ๋ฒ•์ตํ˜•๋Ÿ‰ ๊ฒฐ๊ณผ : ๋ถ€๋‹น์ด๋“๋ฐ˜ํ™˜์ฒญ๊ตฌ ๋ถ€์ •์„ค์ด ํƒ€๋‹น 70 4. ๋ฐฐ๋‹น์˜ ์ˆœํ™˜๊ด€๊ณ„๋ฅผ ๊ณ ๋ คํ•œ ์ ˆ์ฐจ๋น„์šฉ ๊ด€์ ์—์„œ ๋น„ํŒ์  ๊ฒ€ํ†  70 ์ œ4์ ˆ ๋ฏผ์‚ฌ์ง‘ํ–‰๋ฒ• ์ œ155์กฐ์˜ ํ•ด์„๋ก  75 ์ œ5์ ˆ ์†Œ๊ฒฐ 77 ์ œ6์žฅ ๊ฒฐ๋ก  78 ์ฐธ๊ณ ๋ฌธํ—Œ 81 Abstract 87 ํ‘œ๋ชฉ์ฐจ [ํ‘œ] ๋ฐฐ๋‹น์˜ค๋ฅ˜ ์œ ํ˜•์— ๋”ฐ๋ฅธ ๋ฒ•์ตํ˜•๋Ÿ‰ ๊ฒ€ํ†  62 [ํ‘œ] ๊ฐ๊ตญ์˜ ๋ฏผ์‚ฌ์ง‘ํ–‰๋ฐฐ๋‹น ๊ตฌ์กฐ 72์„

    ๋งˆ์ดํฌ๋กœ ์ง„๋™์ˆ˜์ •์ €์šธ ๋ฐ ์ดˆ๊ณ ์†์นด๋ฉ”๋ผ๋ฅผ ์ด์šฉํ•œ ์ดˆ์†Œ์ˆ˜์„ฑ ํ‘œ๋ฉด ์œ„ ํด๋ฆฌ์Šคํ‹ฐ๋ Œ ๋ถ„์‚ฐ์ž…์ž ์•ก์ ์˜ ์ถฉ๊ฒฉ๊ฑฐ๋™ ๋ถ„์„

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    MasterWe investigated the impact dynamics of droplets containing various sizes and concentrations of polystyrene microparticles (PSM) on superhydrophobic surfaces using a high-speed camera and a quartz crystal microresonator (QCM). Gold nanoflake structures were synthesized on QCM surfaces and treated with perfluorooctane ethylthiol molecules to obtain superhydrophobic characteristics. Upon the collision onto the superhydrophobic surface, the droplet spread, retracted, and bounced off the surface due to its nonwetting characteristics. Within the experimental range of PSM size and PSM concentration, the high-speed camera detected only negligible changes in the impact dynamics; however, abnormally large changes in the resonance frequency were observed with the QCM when the concentration or sizes of the PSM exceeded a certain threshold. The abnormal change in frequency was attributed to the formation of a shear-induced PSM structure.๋ณธ ๋…ผ๋ฌธ์—์„œ๋Š” ์ดˆ์†Œ์ˆ˜์„ฑ ํ‘œ๋ฉด ์œ„์— ํด๋ฆฌ์Šคํ‹ฐ๋ Œ ์ฝœ๋กœ์ด๋“œ ์•ก์ ์„ ์ถฉ๋Œ ์‹œ์ผฐ์„ ๋•Œ ์ดˆ๊ณ ์† ์นด๋ฉ”๋ผ์™€ QCM์žฅ๋น„๋ฅผ ์ด์šฉ ํ•จ์œผ๋กœ์จ, ์ถฉ๋Œ ์‹œ ์•ก์ ์˜ ๊ฑฐ๋™ ๋ฐ ๊ณ„๋ฉด๊ณผ ์ฝœ๋กœ์ด๋“œ ์‚ฌ์ด์˜ ๊ด€๊ณ„๋ฅผ ๋ถ„์„ํ•˜๊ณ ์ž ํ•˜์˜€๋‹ค. QCMํ‘œ๋ฉด ์œ„์— ๋ฐ˜๋ณต์ ์ธ ๊ธˆ ํ™˜์› ๋ฐฉ์‹์— ์˜ํ•œ ๊ธˆ ๋‚˜๋…ธํ”Œ๋ ˆ์ดํฌ ๊ตฌ์กฐ๋ฅผ ํ˜•์„ฑ์‹œ์ผฐ๊ณ  ์ดํ›„, ํ‘œ๋ฉด๊ฐœ์งˆ์„ ํ†ตํ•ด ์ฝœ๋กœ์ด๋“œ ์•ก์ ์ด ์ˆ˜์‹ญ ๋ฒˆ ์ถฉ๋Œ์—๋„ ์ดˆ์†Œ์ˆ˜์„ฑ ํŠน์„ฑ์„ ์žƒ์ง€ ์•Š๋Š” ํ‘œ๋ฉด์„ ์ œ์ž‘ํ•˜์˜€๋‹ค. ๋จผ์ € ์ดˆ๊ณ ์† ์นด๋ฉ”๋ผ๋ฅผ ํ†ตํ•œ ์•ก์ ์˜ ์ถฉ๊ฒฉ๊ฑฐ๋™ ๋ถ„์„ ๊ฒฐ๊ณผ๋Š” ๋‹ค์Œ๊ณผ ๊ฐ™์•˜๋‹ค. ์•ก์ ์ด ํ‘œ๋ฉด๊ณผ ์ถฉ๋Œํ•˜๋Š” ์‹œ์ ๋ถ€ํ„ฐ ์ตœ๋Œ€ ํผ์กŒ์„ ๋•Œ ๋„๋‹ฌํ•˜๋Š” ์‹œ๊ฐ„๋ณด๋‹ค ์ตœ๋Œ€ ํผ์กŒ์„ ๋•Œ๋ฅผ ์‹œ์ ์œผ๋กœ ๋‹ค์‹œ ํŠ•๊ฒจ์ ธ ๋‚˜๊ฐ€๋Š” ์‹œ๊ฐ„์ด ๋” ์˜ค๋ž˜ ๊ฑธ๋ ธ์Œ์„ ํ™•์ธํ•  ์ˆ˜ ์žˆ์—ˆ๋‹ค. ์ด๋ฅผ ํ™•์ธํ•˜๊ธฐ ์œ„ํ•ด ๋‹ค์–‘ํ•œ ๋†๋„๋ฅผ ๊ฐ€์ง€๋Š” ์•ก์ ์— ๋Œ€ํ•ด์„œ ์‹คํ—˜ํ•œ ๊ฒฐ๊ณผ ๋†๋„๊ฐ€ ๋†’์„์ˆ˜๋ก ๋˜๋Œ์•„ ์˜ค๋Š” ์‹œ๊ฐ„์ด ๋” ์˜ค๋ž˜ ๊ฑธ๋ ธ์Œ์„ ํ™•์ธ ํ•  ์ˆ˜ ์žˆ์—ˆ๊ณ , ์ตœ์ข…์ ์œผ๋กœ ์•ก์  ๋‚ด๋ถ€์˜ ์ž…์ž์™€ ํ‘œ๋ฉด๊ณผ์˜ ๋งˆ์ฐฐ ํ˜น์€ ์ ๋„์— ์˜ํ•ด ์œ„์™€ ๊ฐ™์€ ํ˜„์ƒ์ด ๋ฐœ์ƒ๋จ์„ ์•Œ ์ˆ˜ ์žˆ์—ˆ๋‹ค. QCM์„ ํ†ตํ•œ ์•ก์ ์˜ ์ถฉ๊ฒฉ ๊ฑฐ๋™ ๋ถ„์„์€ ์ž…์ž์™€ ๊ณ„๋ฉด์‚ฌ์ด์— ๋ฐœ์ƒ๋˜๋Š” ํ˜„์ƒ์— ๋Œ€ํ•ด์„œ ๊ด€์ฐฐ ํ•  ์ˆ˜ ์žˆ์—ˆ๊ณ  ์ด๋Š” ์ดˆ๊ณ ์† ์นด๋ฉ”๋ผ๋ฅผ ํ†ตํ•ด์„œ๋Š” ์–ป์„ ์ˆ˜ ์—†๋Š” ์ •๋ณด์˜€๋‹ค. QCM์œ„์— ์ฝœ๋กœ์ด๋“œ ์•ก์ ์ด ์ถฉ๋Œํ•  ๋•Œ, ํŠน์ • ์ดํ•˜์˜ ๋†๋„ ๋ฐ ์ž…์ž ์‚ฌ์ด์ฆˆ์— ๋Œ€ํ•ด์„œ ์ˆ˜ Hz์˜ ์ง„๋™์ˆ˜์˜ ๋ณ€ํ™”๋Ÿ‰์„ ๋ณด์ด๋Š” ๋ฐ˜๋ฉด, ํŠน์ • ์ด์ƒ์˜ ๋†๋„ ๋ฐ ์ž…์ž ์‚ฌ์ด์ฆˆ๊ฐ€ ์ถฉ๋Œ ๋˜์—ˆ์„ ๊ฒฝ์šฐ ์ˆ˜ MHz์˜ ์ง„๋™์ˆ˜์˜ ๋ณ€ํ™”๋Ÿ‰์„ ๋ณด์˜€๋‹ค. ์ด๋Š” ํŠน์ • ์กฐ๊ฑด์—์„œ ์ฝœ๋กœ์ด๋“œ ์•ก์  ๋‚ด๋ถ€์˜ ์ž…์ž๋“ค์ด ์ถฉ๋Œ์‹œ์ ๋ถ€ํ„ฐ ์ตœ๋Œ€๋กœ ํผ์ง€๋Š” ๊ทธ ๊ธฐ๊ฐ„๋™์•ˆ, ํ‘œ๋ฉด์œ„์— ๋นฝ๋นฝํ•˜๊ฒŒ ๋ญ‰์ณ์ง„ ํ›„์— ์ธต์œผ๋กœ ํ˜•์„ฑ๋˜์–ด QCMํ‘œ๋ฉด์œ„์— ์ƒˆ๋กœ์šด ๊ณ ์ฒด์ธต์ด ํ˜•์„ฑ๋˜์–ด ํฐ ๊ณต๋ช…์ง„๋™์ˆ˜์˜ ๋ณ€ํ™”๋Ÿ‰์ด ๊ด€์ฐฐ ๋˜์—ˆ๋‹ค๊ณ  ์ถ”์ธกํ•˜์˜€๋‹ค. ์ž…์ž์˜ ๋†๋„๊ฐ€ ๋‚ฎ์„ ๊ฒฝ์šฐ์—๋Š” ์ž…์ž๊ฐ„์˜ ๋นฝ๋นฝํ•œ ์ธต์ด ํ˜•์„ฑ๋˜์ง€ ์•Š๊ณ , ๋˜ํ•œ ์ž…์ž์˜ ํฌ๊ธฐ๊ฐ€ ์ปค์งˆ์ˆ˜๋ก ๋‹จ์œ„ ์งˆ๋Ÿ‰๋‹น ์ฐจ์ง€ํ•˜๋Š” ์ž…์ž์˜ ๊ฐœ์ˆ˜๊ฐ€ ์ ์ฐจ ์ค„์–ด๋“ค๊ธฐ ๋•Œ๋ฌธ์— ๋งˆ์ฐฌ๊ฐ€์ง€๋กœ ํ‘œ๋ฉด์œ„์— ๋นฝ๋นฝํ•œ ์ธต์ด ํ˜•์„ฑ๋˜์ง€ ์•Š์•˜๋‹ค. ์ด๋Š” ๋น„๊ต๊ตฐ์ธ DI water ์™€ ๋™์ผํ•˜๊ฒŒ ์ˆ˜ Hz์˜ ๊ณต๋ช…์ง„๋™์ˆ˜์˜ ๋ณ€ํ™”๋Ÿ‰์ด ๊ด€์ฐฐ๋˜์—ˆ๊ณ  ์œ„์˜ ๊ฐ€์„ค์„ ๋’ท๋ฐ›์นจ ํ•˜์˜€๋‹ค. ์ด๋Ÿฌํ•œ ๊ฒฐ๊ณผ๋ฅผ ๋ฐ”ํƒ•์œผ๋กœ ๊ธฐ์กด์— ์ดˆ์†Œ์ˆ˜์„ฑ ํ‘œ๋ฉด ์œ„ ์ฝœ๋กœ์ด๋“œ ์•ก์ ์˜ ์ถฉ๊ฒฉ ๊ฑฐ๋™์—์„œ ๊ณ„๋ฉด๊ณผ ์ž…์ž๊ฐ„์˜ ์‚ฌ์ด์—์„œ ๋ฒŒ์–ด์ง€๋Š” ํ˜„์ƒ์— ๋Œ€ํ•ด์„œ ์ฒ˜์Œ์œผ๋กœ ๊ด€์ฐฐ ํ•˜์˜€๊ณ , ์ด๋Š” ์ดˆ๊ณ ์† ์นด๋ฉ”๋ผ๋ฅผ ํ†ตํ•ด ์–ป์ง€ ๋ชปํ•˜๋Š” ์ •๋ณด๋“ค ์ด๋ฏ€๋กœ, QCM์ด ์ƒˆ๋กœ์šด ์ถฉ๊ฒฉ๊ฑฐ๋™ ๋ถ„์„ ์žฅ๋น„๋กœ์จ ํ˜น์€ ์ดˆ๊ณ ์† ์นด๋ฉ”๋ผ์™€ ํ•จ๊ป˜ ์ƒํ˜ธ ๋ณด์™„์ ์ธ ๋„๊ตฌ๋กœ ์ด์šฉ ๋  ์ˆ˜ ์žˆ์Œ์„ ๋ณด์˜€๋‹ค
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