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    ๋‹ค์–‘์„ฑ๊ด€๋ฆฌ๊ฐ€ ๊ณต๊ธฐ์—…์˜ ์„ฑ๊ณผ์— ๋ฏธ์น˜๋Š” ์˜ํ–ฅ์— ๊ด€ํ•œ ์—ฐ๊ตฌ

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    ํ•™์œ„๋…ผ๋ฌธ (์„์‚ฌ)-- ์„œ์šธ๋Œ€ํ•™๊ต ํ–‰์ •๋Œ€ํ•™์› : ํ–‰์ •๋Œ€ํ•™์› ํ–‰์ •ํ•™๊ณผ ํ–‰์ •ํ•™ ์ „๊ณต, 2016. 2. ์ด์ˆ˜์˜.๋ณธ ์—ฐ๊ตฌ๋Š” ๋‹ค์–‘์„ฑ์ด ์ฆ๋Œ€ํ•˜๊ณ  ์žˆ๋Š” ํ˜„์‹ค์—์„œ ๋‹ค์–‘์„ฑ๊ด€๋ฆฌ๊ฐ€ ๋‹ค์–‘์„ฑ์˜ ๊ธ์ •์ ์ธ ํšจ๊ณผ๋ฅผ ๊ทน๋Œ€ํ™”ํ•˜์—ฌ ์กฐ์ง์„ฑ๊ณผ๋ฅผ ๋†’์ผ ์ˆ˜ ์žˆ๋‹ค๋Š” ๊ฒƒ์„ ์‹ค์ฆ์ ์œผ๋กœ ์ฆ๋ช…ํ•œ๋‹ค. ๊ธฐ์กด์˜ ๊ฒฝํ—˜์  ์—ฐ๊ตฌ๋“ค์€ ๋‹ค์–‘์„ฑ๊ด€๋ฆฌ์— ๊ด€ํ•œ ์ฒด๊ณ„-๊ตฌ์กฐ์  ๊ด€์ ์˜ ์—ฐ๊ตฌ๋“ค์ด ๋Œ€๋‹ค์ˆ˜๋ฅผ ์ฐจ์ง€ํ•˜๊ณ  ์žˆ์œผ๋ฉฐ, ์ „๋žต์  ๊ด€์ ์— ๋Œ€ํ•œ ๋…ผ์˜๊ฐ€ ์ƒ๋Œ€์ ์œผ๋กœ ๋ถ€์กฑํ–ˆ๋‹ค๋Š” ํ•œ๊ณ„๊ฐ€ ์žˆ์—ˆ๋‹ค. ์ด๋Ÿฌํ•œ ์—ฐ๊ตฌ ๊ฒฝํ–ฅ์€ ๋‹ค์–‘์„ฑ์€ ์กฐ์ง์— ๋ถ€์ •์ ์ธ ์˜ํ–ฅ์„ ๋ฏธ์นœ๋‹ค๋Š” ์ ์„ ์ „์ œํ•˜๊ณ  ์žˆ์œผ๋ฉฐ, ๊ฒฐ๊ตญ ๋‹ค์–‘์„ฑ๊ณผ ๋‹ค์–‘์„ฑ๊ด€๋ฆฌ์— ๋Œ€ํ•œ ํ•œ์ •์ ์ธ ์ธก๋ฉด๋งŒ์„ ์ธ์‹ํ•˜๊ณ  ์žˆ๋‹ค๋Š” ํ•œ๊ณ„๊ฐ€ ์žˆ์—ˆ๋‹ค. ๋ณธ ์—ฐ๊ตฌ๋Š” ์ด๋Ÿฌํ•œ ๋ฌธ์ œ๋ฅผ ํ•ด๊ฒฐํ•˜๊ธฐ ์œ„ํ•ด, ๋‹ค์–‘์„ฑ๊ด€๋ฆฌ์— ๋Œ€ํ•œ ์ดˆ๊ธฐ ์—ฐ๊ตฌ์ธ Thomas(1990), Cox & Blake(1991)์˜ ์ฃผ์žฅ์— ๋”ฐ๋ผ ๋‹ค์–‘์„ฑ๊ด€๋ฆฌ๊ฐ€ ์กฐ์ง ์™ธ๋ถ€์˜ ์ž์›์„ ์œ ์ž…ํ•˜์—ฌ ์กฐ์ง์„ฑ๊ณผ๋ฅผ ๋†’์ผ ์ˆ˜ ์žˆ๋‹ค๋Š” ๊ฒƒ์„ ๋ถ„์„ํ•˜๊ณ ์ž ํ•˜์˜€๋‹ค. ์ด๋Ÿฌํ•œ ์ฃผ์žฅ์— ๊ฒฝํ—˜์  ๊ทผ๊ฑฐ๋ฅผ ์ œ์‹œํ•˜๊ธฐ ์œ„ํ•˜์—ฌ ์šฐ๋ฆฌ๋‚˜๋ผ์˜ 30๊ฐœ ๊ณต๊ธฐ์—…์˜ 5๋…„๊ฐ„์˜ ์ž๋ฃŒ๋ฅผ ์ด์šฉํ•˜์—ฌ ํŒจ๋„๋ถ„์„์„ ์‹ค์‹œํ•˜์˜€๋‹ค. ๊ตฌ์ฒด์ ์œผ๋กœ๋Š” ์„ฑ๋ณ„ ๋‹ค์–‘์„ฑ์„ ์ค‘์‹ฌ์œผ๋กœ, Pitts(2006)๊ฐ€ ์ œ์‹œํ•œ ๋‹ค์–‘์„ฑ๊ด€๋ฆฌ ๋ถ„์„ํ‹€์— ๋”ฐ๋ผ ์ฑ„์šฉ, ์‚ฌ๋ณด, ์œ ์—ฐ๊ทผ๋ฌด์ œ๊ฐ€ ์กฐ์ง์„ฑ๊ณผ์— ๋‹ค์–‘์„ฑ์„ ๋งค๊ฐœํ•˜์—ฌ ์˜ํ–ฅ์„ ๋ฏธ์น˜๋Š”์ง€๋ฅผ ํ™•์ธํ•˜์˜€๋‹ค. ์ข…์†๋ณ€์ˆ˜๋กœ๋Š” ์ด์ž์‚ฐ์ด์ต๋ฅ , ๋งค์ถœ์ˆ˜์ต๋ฅ , ์ง์›์ƒ์‚ฐ์„ฑ์„ ์„ ์ •ํ•˜์˜€๊ณ , ๋งค๊ฐœ๋ณ€์ˆ˜๋Š” Blau index๋ฅผ ์ด์šฉํ•˜์—ฌ ๋‹ค์–‘์„ฑ ์ง€ํ‘œ๋ฅผ ํ™œ์šฉํ•˜์˜€๋‹ค. ๋ถ„์„ ๊ฒฐ๊ณผ, ๋‹ค์–‘์„ฑ๊ด€๋ฆฌ ์ค‘ ์‚ฌ๋ณด๋ฅผ ์ œ์™ธํ•œ ์ฑ„์šฉ๊ณผ ์œ ์—ฐ๊ทผ๋ฌด์ œ๋„๋งŒ์ด ์กฐ์ง์„ฑ๊ณผ์— ๋Œ€ํ•ด ๋‹ค์–‘์„ฑ์„ ๋งค๊ฐœํ•˜๋Š” ๊ด€๊ณ„๋ฅผ ๋ณด์ด๊ณ  ์žˆ์—ˆ๋‹ค. ์ฒซ ์งธ, ์‹ ๊ทœ์ฑ„์šฉ์ธ์› ์ค‘ ์—ฌ์„ฑ์˜ ๋น„์œจ์ด ๋†’์•„์งˆ์ˆ˜๋ก ์กฐ์ง์˜ ๋‹ค์–‘์„ฑ์ด ๋†’์•„์ง€๊ณ , ๋‹ค์–‘์„ฑ์ด ์กฐ์ง์„ฑ๊ณผ๋ฅผ ๋†’์˜€๋‹ค. ํŠนํžˆ ํ•ด๋‹น ๊ด€๊ณ„๋Š” ์™„์ „๋งค๊ฐœ๊ด€๊ณ„๋ฅผ ๋ณด์ด๊ณ  ์žˆ์—ˆ๋Š”๋ฐ, ์ด๋Š” ์ ๊ทน์ ์กฐ์น˜์— ๋Œ€ํ•œ ์ƒ๋ฐ˜๋˜๋Š” ์ฃผ์žฅ์— ๋Œ€ํ•œ ํ•ด์„์„ ์ œ์‹œํ•  ์ˆ˜ ์žˆ์„ ๊ฒƒ์œผ๋กœ ๋ณด์ธ๋‹ค. ์ ๊ทน์ ์กฐ์น˜๋กœ ๋ณผ ์ˆ˜ ์žˆ๋Š” ์—ฌ์„ฑ ์ฑ„์šฉ์€ ์—ญ์ฐจ๋ณ„์„ ์ดˆ๋ž˜ํ•˜๊ณ  ์—ฌ์„ฑ์˜ ์„ฑ๊ณผ๋ฅผ ํ•œ์ •์ ์œผ๋กœ ์ธ์‹ํ•˜๊ฒŒ ๋งŒ๋“œ๋Š” ๋“ฑ์˜ ๋ถ€์ •์  ํšจ๊ณผ๊ฐ€ ์žˆ๋‹ค๊ณ  ๋ณด๊ณ ํ•œ ์—ฐ๊ตฌ๊ฐ€ ์žˆ๋Š” ๋ฐ˜๋ฉด, ์กฐ์ง์„ฑ๊ณผ๋ฅผ ๋†’์ธ๋‹ค๊ณ  ํ•˜๋Š” ๋…ผ์Ÿ์ ์ธ ๊ฒฐ๊ณผ๊ฐ€ ์žˆ์—ˆ๋‹ค. ๋ณธ ์—ฐ๊ตฌ ๊ฒฐ๊ณผ๋Š” ์ฑ„์šฉ ๊ทธ ์ž์ฒด๊ฐ€ ์กฐ์ง์„ฑ๊ณผ๋ฅผ ๋†’์ด๋Š” ๊ฒƒ์ด ์•„๋‹ˆ๋ผ, ์ฑ„์šฉ์ด ์กฐ์ง๊ตฌ์„ฑ์„ ๋‹ค์–‘ํ•˜๊ฒŒ ํ•˜๊ณ , ๋†’์•„์ง„ ๋‹ค์–‘์„ฑ์œผ๋กœ ์ธํ•œ ์ฐฝ์˜์„ฑ์ด๋‚˜ ์œ ์—ฐ์„ฑ ๋“ฑ์˜ ํšจ๊ณผ๊ฐ€ ์กฐ์ง์„ฑ๊ณผ์— ๊ธ์ •์ ์ธ ์˜ํ–ฅ์„ ๋ฏธ์น  ์ˆ˜ ์žˆ๋‹ค๋Š” ๊ฐ€๋Šฅ์„ฑ์„ ์ œ์‹œํ•œ๋‹ค. ๋‘˜์งธ๋กœ, ๋ณธ ์—ฐ๊ตฌ๊ฐ€ ์„ ์ •ํ•œ ์ผ๊ณฑ ๊ฐ€์ง€ ํ˜•ํƒœ์˜ ์œ ์—ฐ๊ทผ๋ฌด์ œ๋Š” ๊ฒฝ์Ÿ์  ๋งค๊ฐœ, ๋ถ€๋ถ„ ๋งค๊ฐœ, ์™„์ „ ๋งค๊ฐœ ๋“ฑ ๋‹ค์–‘ํ•œ ๋งค๊ฐœ๊ด€๊ณ„๋ฅผ ๋ณด์ด๊ณ  ์žˆ์—ˆ๋‹ค. ๊ทธ ์ค‘ ๊ณตํ†ต์ ์ธ ๊ฒฐ๊ณผ๋Š” ๊ทผ๋ฌด์˜ ์‹œ๊ฐ„๊ณผ ๊ณต๊ฐ„์„ ๋ชจ๋‘ ๋ฐ”๊พธ๋Š” ๊ฒฝ์„ฑ์˜ ์ œ๋„๋ณด๋‹ค, ๋Œ€์ฒด๋กœ ์ „ํ†ต์ ์ธ ๊ทผ๋ฌดํ˜•ํƒœ๋ฅผ ์œ ์ง€ํ•˜๋ฉด์„œ ์ถœํ‡ด๊ทผ ์‹œ๊ฐ„์˜ ๋ณ€ํ™”๋งŒ์„ ํ—ˆ์šฉํ•˜๋Š” ํ˜•ํƒœ์ธ ์—ฐ์„ฑ์˜ ์ œ๋„๊ฐ€ ์กฐ์ง์„ฑ๊ณผ์— ๋งค๊ฐœํšจ๊ณผ๋ฅผ ๋ณด์ด๋ฉฐ ๊ธ์ •์ ์ธ ์˜ํ–ฅ์„ ๋ฏธ์น˜๊ณ  ์žˆ์—ˆ๋‹ค. ํŠนํžˆ ์—ฐ์„ฑ์˜ ์œ ์—ฐ๊ทผ๋ฌด์ œ ์ค‘ ์‹œ๊ฐ„์ œ๊ทผ๋ฌด ์ œ๋„(์ „์ผ์ œ ๊ทผ๋ฌด ์ง์›์ด ์‹ ์ฒญ์„ ํ†ตํ•ด ์ฃผ 40์‹œ๊ฐ„ ์ดํ•˜๋ฅผ ๊ทผ๋ฌดํ•  ์ˆ˜ ์žˆ๊ฒŒ ์ „ํ™˜ํ•˜๋Š” ์ œ๋„)๋Š” ์กฐ์ง์„ฑ๊ณผ์— ์ง์ ‘์ ์œผ๋กœ๋Š” ๋ถ€์ •์ ์ธ ์˜ํ–ฅ์„ ๋ฏธ์น˜์ง€๋งŒ, ํ•ด๋‹น ์ œ๋„๊ฐ€ ๋‹ค์–‘์„ฑ์„ ๋†’์ด๋ฉฐ, ๋†’์•„์ง„ ๋‹ค์–‘์„ฑ์ด ์กฐ์ง์„ฑ๊ณผ์— ๊ธ์ •์ ์ธ ์˜ํ–ฅ์„ ๋ฏธ์น˜๋Š” ๋ฐ˜๋Œ€๋˜๋Š” ์˜ํ–ฅ์„ ๋ฏธ์น˜๊ณ  ์žˆ์—ˆ๋‹ค. ์ด์™€ ๋‹ฌ๋ฆฌ ์œ ์—ฐ๊ทผ๋ฌด์ œ๋„์— ๋Œ€ํ•œ ๋ถ€์ •์ ์ธ ํšจ๊ณผ๋„ ์žˆ์—ˆ๋‹ค. ์ผ๊ณฑ ๊ฐ€์ง€ ์œ ์—ฐ๊ทผ๋ฌด์ œ๋„ ์ค‘ ์žฌํƒ๊ทผ๋ฌด์ œ๋„๋Š” ์˜คํžˆ๋ ค ๋‹ค์–‘์„ฑ์„ ๋‚ฎ์ถ”๋Š” ๊ฒƒ์œผ๋กœ ๋‚˜ํƒ€๋‚ฌ๋‹ค. ๊ตฌ์ฒด์ ์œผ๋กœ๋Š” ์กฐ์ง ๋‚ด ์—ฌ์„ฑ์˜ ๋น„์œจ์„ ์ค„์ด๊ณ  ์žˆ์—ˆ๋Š”๋ฐ, ๋ณธ ์—ฐ๊ตฌ์—์„œ๋Š” ์ด๋Ÿฌํ•œ ๊ฒฐ๊ณผ๊ฐ€ ์žฌํƒ๊ทผ๋ฌด์ œ๋„์˜ ๊ทผ๋ณธ์ ์ธ ์†์„ฑ์œผ๋กœ ์ธํ•œ ๊ฐ€๋Šฅ์„ฑ๊ณผ(Lee & Hong, 2011), ์œ ๋ฆฌ์ ˆ๋ฒฝ(glass cliff) ํ˜„์ƒ(Sabharwal, 2015)์œผ๋กœ ํ•ด์„ํ•˜์˜€์œผ๋‚˜ ์—ฌ์ „ํžˆ ํ•œ๊ณ„๊ฐ€ ์žˆ์—ˆ๋‹ค. ์ด์— ๋Œ€ํ•œ ํ•ด์„์—๋Š” ๋”์šฑ ์‹ฌ๋„ ๊นŠ์€ ์—ฐ๊ตฌ๊ฐ€ ํ•„์š”ํ•  ๊ฒƒ์œผ๋กœ ๋ณด์ธ๋‹ค. ๋ณธ ์—ฐ๊ตฌ๊ฒฐ๊ณผ๋Š” ๋‹ค์–‘์„ฑ๊ด€๋ฆฌ์— ์ƒˆ๋กœ์šด ๊ด€์ ์„ ์ œ์‹œํ•œ๋‹ค๋Š” ์ ์—์„œ ์˜์˜๊ฐ€ ์žˆ๋‹ค. ์ด์ „์— ํ•œ์ •์ ์ธ ๊ด€์ ์—์„œ๋งŒ ์ดํ•ด๋˜์–ด ์˜ค๋˜ ๋‹ค์–‘์„ฑ๊ด€๋ฆฌ๋Š” ๊ทธ ๊ฐ€์น˜๊ฐ€ ๊ณผ์†Œํ‰๊ฐ€๋˜๊ณ  ์žˆ์—ˆ๋Š”๋ฐ, ๋‹ค์–‘์„ฑ๊ด€๋ฆฌ๊ฐ€ ๊ทธ ์ž์ฒด๋กœ ์ „๋žต์ด ๋  ์ˆ˜ ์žˆ๋‹ค๋Š” ๊ด€์ ์—์„œ ๋‹ค์–‘์„ฑ๊ด€๋ฆฌ์— ๋Œ€ํ•œ ์ธ์‹์„ ์žฌ๊ณ ํ•  ์ˆ˜ ์žˆ์œผ๋ฉฐ, ๊ถ๊ทน์ ์œผ๋กœ ํ˜„์žฅ์—์„œ ๋‹ค์–‘์„ฑ๊ด€๋ฆฌ์˜ ํ™œ์šฉ์„ ๋†’์ผ ์ˆ˜ ์žˆ์„ ๊ฒƒ์ด๋ผ๊ณ  ๊ธฐ๋Œ€๋œ๋‹ค. ๋˜ ๋‚จ๋…€ ๋ชจ๋‘์—๊ฒŒ ๋ถ€์ •์ ์œผ๋กœ ์ธ์‹๋˜๊ณ  ์žˆ๋Š” ์ ๊ทน์ ์กฐ์น˜์—์„œ ๋ฒ—์–ด๋‚˜, ๋” ์œ ์—ฐํ•œ ๋ฐฉ์‹์œผ๋กœ ์กฐ์ง ๊ด€๋ฆฌ๋ฅผ ํ•  ํ•„์š”์„ฑ์— ๋Œ€ํ•ด ์ œ๊ธฐํ•œ๋‹ค๋Š” ์˜์˜๊ฐ€ ์žˆ๋‹ค. ๋งˆ์ง€๋ง‰์œผ๋กœ ๋™์งˆ์„ฑ์„ ์ง€ํ–ฅํ•˜๋Š” ์šฐ๋ฆฌ๋‚˜๋ผ์˜ ๋ฌธํ™”๊ฐ€ ๋‹ค์–‘์„ฑ์ด ๋†’์•„์ง€๊ณ  ์žˆ๋Š” ํ˜„์‹ค์—์„œ ํ•œ๊ณ„์— ๋ถ€๋”ชํžˆ๊ณ  ์žˆ๋Š”๋ฐ, ์ด๋Ÿฌํ•œ ๋ฌธํ™”์˜ ํ•œ๊ณ„๋ฅผ ์ธ์‹ํ•˜๊ณ  ๋ณ€ํ™”์‹œํ‚ฌ ์ˆ˜ ์žˆ๋Š” ๊ธฐํšŒ๊ฐ€ ๋  ์ˆ˜ ์žˆ๋‹ค๊ณ  ์ƒ๊ฐํ•œ๋‹ค. ๊ทธ๋Ÿผ์—๋„ ๋ณธ ์—ฐ๊ตฌ๋Š” ์—ฌ๋Ÿฌ ํ•œ๊ณ„๊ฐ€ ์žˆ๋‹ค. ์ฒซ ์งธ๋Š” ์‚ฌ๋ณด์— ๊ด€ํ•œ ๊ฒฐ๊ณผ๋ฅผ ์ •ํ™•ํžˆ ํ•ด์„ํ•˜์ง€ ๋ชปํ–ˆ๋‹ค๋Š” ๊ฒƒ์ด๋‹ค. ์‚ฌ๋ณด๊ฐ€ ์กฐ์ง์„ฑ๊ณผ ์ค‘ ์ด์ž์‚ฐ์ด์ต๋ฅ ๊ณผ ๋งค์ถœ์ˆ˜์ต๋ฅ ์— ๊ฐ๊ฐ ๋‹ค๋ฅธ ๋ถ€ํ˜ธ๋กœ ์˜ํ–ฅ์„ ๋ฏธ์น˜๊ณ  ์žˆ๋Š”๋ฐ, ์ด์— ๋Œ€ํ•œ ํ•ด์„์ด ๋ถ€์กฑํ•˜์˜€๋‹ค. ๋‘˜์งธ๋Š” ์ „์ˆ ํ•œ ๋ฐ”์™€ ๊ฐ™์ด ์žฌํƒ๊ทผ๋ฌด์ œ์˜ ํšจ๊ณผ์— ๋Œ€ํ•œ ํ•ด์„๋„ ๊ฐ€๋Šฅ์„ฑ๋งŒ์„ ์ œ์‹œํ•˜๊ณ  ์žˆ๋‹ค๋Š” ๊ฒƒ์ด๋‹ค. ์…‹์งธ๋Š” ๊ณ ๊ฐ์ด๋‚˜ ์ฃผ๋ฌด๋ถ€์ฒ˜์˜ ์š”๊ตฌ ๋“ฑ์„ ํ†ต์ œํ•˜์ง€ ๋ชปํ–ˆ๋‹ค๋Š” ์ , ๋งˆ์ง€๋ง‰์œผ๋กœ๋Š” ๋‹ค์–‘์„ฑ์˜ ์—ฌ๋Ÿฌ ๊ฐœ๋… ์ค‘ ์„ฑ๋ณ„ ๋‹ค์–‘์„ฑ์—๋งŒ ์ฃผ๋ชฉํ–ˆ๋‹ค๋Š” ์ ์ด๋‹ค. ์ด๋Ÿฌํ•œ ๋ฌธ์ œ๋ฅผ ํ•ด๊ฒฐํ•˜๊ธฐ ์œ„ํ•œ ํ›„์† ์—ฐ๊ตฌ๊ฐ€ ์ด๋ฃจ์–ด์ง„๋‹ค๋ฉด, ๋‹ค์–‘์„ฑ๊ด€๋ฆฌ์— ๋Œ€ํ•œ ํ•™๋ฌธ์  ๋ฐœ์ „์ด ์ด๋ฃจ์–ด์งˆ ์ˆ˜ ์žˆ์œผ๋ฆฌ๋ผ๊ณ  ์ƒ๊ฐํ•œ๋‹ค.์ œ 1์žฅ ์„œ๋ก  1 ์ œ 1์ ˆ ์—ฐ๊ตฌ ๋ชฉ์  ๋ฐ ํ•„์š”์„ฑ 1 ์ œ 2์ ˆ ์—ฐ๊ตฌ๋ฒ”์œ„ ๋ฐ ์—ฐ๊ตฌ๋ฐฉ๋ฒ• 3 ์ œ 2์žฅ ๋‹ค์–‘์„ฑ๊ณผ ๋‹ค์–‘์„ฑ๊ด€๋ฆฌ์— ๊ด€ํ•œ ์ด๋ก ์  ๊ฒ€ํ†  4 ์ œ 1์ ˆ ๋‹ค์–‘์„ฑ(diversity)์˜ ์˜์˜ ๋ฐ ๋‹ค์–‘์„ฑ์— ๊ด€ํ•œ ์„ ํ–‰์—ฐ๊ตฌ 4 1. ๋‹ค์–‘์„ฑ์˜ ์ •์˜ 4 2. ๋‹ค์–‘์„ฑ์˜ ๊ธฐ๋Œ€ํšจ๊ณผ 7 ์ œ 2์ ˆ ๋‹ค์–‘์„ฑ๊ด€๋ฆฌ(diversity management)์˜ ์˜์˜ ๋ฐ ๋‹ค์–‘์„ฑ๊ด€๋ฆฌ์— ๊ด€ํ•œ ์„ ํ–‰์—ฐ๊ตฌ 11 1. ๋‹ค์–‘์„ฑ๊ด€๋ฆฌ์˜ ์ •์˜ 11 2. ๋‹ค์–‘์„ฑ๊ด€๋ฆฌ์™€ ์ ๊ทน์ ์กฐ์น˜(affirmative action)์™€์˜ ์ฐจ์ด์  14 3. ๋‹ค์–‘์„ฑ๊ด€๋ฆฌ์˜ ๊ธฐ๋Œ€ํšจ๊ณผ 19 4. ์กฐ์ง๊ณผ ํ™˜๊ฒฝ์˜ ๊ด€๊ณ„๋ฅผ ์ค‘์‹ฌ์œผ๋กœ ๋ณธ ๋‹ค์–‘์„ฑ๊ด€๋ฆฌ 22 ์ œ 3์ ˆ ๋‹ค์–‘์„ฑ๊ด€๋ฆฌ์— ๊ด€ํ•œ ์ œ๋„์˜ ์—ญ์‚ฌ ๋ฐ ์šฐ๋ฆฌ๋‚˜๋ผ ๊ณต๊ณต๊ธฐ๊ด€์˜ ๋‹ค์–‘์„ฑ๊ด€๋ฆฌ ํ˜„ํ™ฉ 27 1. ์ฑ„์šฉ ๋ถ€๋ฌธ 27 2. ๋ฌธํ™”์  ์ธ์‹์˜ ์ œ๊ณ  ๋ถ€๋ฌธ ์‚ฌ๋ณด 29 3. ์‹ค์šฉ์ ์ธ ํ”„๋กœ๊ทธ๋žจ(pragmatic program) ๋ถ€๋ฌธ ์œ ์—ฐ๊ทผ๋ฌด์ œ 31 ์ œ 3์žฅ ์กฐ์ง์„ฑ๊ณผ์— ๊ด€ํ•œ ์ด๋ก ์  ๊ฒ€ํ†  35 ์ œ 1์ ˆ ์กฐ์ง์„ฑ๊ณผ์˜ ์ •์˜ 35 ์ œ 2์ ˆ ์กฐ์ง์„ฑ๊ณผ ๊ฐœ๋…์˜ ๊ณต๊ณต๋ถ€๋ฌธ์—์˜ ์ ์šฉ 36 ์ œ 4์žฅ ์—ฐ๊ตฌ ๋ถ„์„ํ‹€ ๋ฐ ๊ฐ€์„ค 38 ์ œ 1์ ˆ ์—ฐ๊ตฌ๋ชจํ˜• ๋„์ถœ 38 1. ์ „๋žต์  ๊ด€์ ์œผ๋กœ์„œ์˜ ๋‹ค์–‘์„ฑ๊ด€๋ฆฌ 38 2. ๋‹ค์–‘์„ฑ๊ด€๋ฆฌ์˜ ๋ถ„๋ฅ˜ 40 ์ œ 2์ ˆ ๋‹ค์–‘์„ฑ๊ด€๋ฆฌ์˜ ์ฒด๊ณ„-๊ตฌ์กฐ์  ๊ด€์ ์— ๊ด€ํ•œ ์„ ํ–‰์—ฐ๊ตฌ 43 ์ œ 3์ ˆ ๋‹ค์–‘์„ฑ๊ด€๋ฆฌ์˜ ์ „๋žต์  ์„ ํƒ ๊ด€์ ์— ๊ด€ํ•œ ์„ ํ–‰์—ฐ๊ตฌ 45 1. ๋‹ค์–‘์„ฑ๊ด€๋ฆฌ๊ฐ€ ๋‹ค์–‘์„ฑ์— ๋ฏธ์น˜๋Š” ์˜ํ–ฅ 46 2. ๋‹ค์–‘์„ฑ์ด ์กฐ์ง์„ฑ๊ณผ์— ๋ฏธ์น˜๋Š” ์˜ํ–ฅ 49 ์ œ 5์žฅ ์—ฐ๊ตฌ ์„ค๊ณ„ ๋ฐ ๋ฐ์ดํ„ฐ ์ˆ˜์ง‘ 51 ์ œ 1์ ˆ ์—ฐ๊ตฌ๋ฌธ์ œ ๋ฐ ๊ฐ€์„ค ์„ค์ • 51 ์ œ 2์ ˆ ์—ฐ๊ตฌ ๋Œ€์ƒ ์„ ์ • 53 ์ œ 3์ ˆ ๋ณ€์ˆ˜ ์„ ์ • 54 1. ์ข…์†๋ณ€์ˆ˜ 54 2. ๋…๋ฆฝ๋ณ€์ˆ˜ 56 3. ๋งค๊ฐœ๋ณ€์ˆ˜ 58 4. ํ†ต์ œ๋ณ€์ˆ˜ 58 ์ œ 6์žฅ ๋ถ„์„ ๊ฒฐ๊ณผ 60 ์ œ 1์ ˆ ๊ธฐ์ดˆํ†ต๊ณ„ ๋ถ„์„ ๊ฒฐ๊ณผ 60 ์ œ 2์ ˆ ๋ถ„์„ ๊ฒฐ๊ณผ 64 1. ๋งค๊ฐœํšจ๊ณผ์˜ ๋ถ„์„ ๊ณผ์ • 64 2. ๋‹ค์–‘์„ฑ๊ด€๋ฆฌ๊ฐ€ ๋‹ค์–‘์„ฑ์— ๋ฏธ์น˜๋Š” ์˜ํ–ฅ(path a) 66 3. ๋‹ค์–‘์„ฑ์ด ์กฐ์ง์„ฑ๊ณผ์— ๋ฏธ์น˜๋Š” ์˜ํ–ฅ(path b) 70 4. ๋‹ค์–‘์„ฑ๊ด€๋ฆฌ์™€ ์กฐ์ง์„ฑ๊ณผ(path c and c') 72 5. ๋งค๊ฐœํšจ๊ณผ ๊ฒ€์ฆ 80 6. ๊ฐ€์„ค ์ฑ„ํƒ ์—ฌ๋ถ€ 81 ์ œ 7์žฅ ๊ฒฐ๋ก  ๋ฐ ์‹œ์‚ฌ์  82 ์ œ 1์ ˆ ์—ฐ๊ตฌ์˜ ํ•จ์˜ ๋ฐ ์‹œ์‚ฌ์  82 ์ œ 2์ ˆ ์—ฐ๊ตฌ์˜ ํ•œ๊ณ„ 85 ์ฐธ๊ณ ๋ฌธํ—Œ 87 Abstract 96Maste

    ํ‘œ๋ฉด์  ๋‹ค์–‘์„ฑ์—์„œ ์‹ฌ์ธต์  ๋‹ค์–‘์„ฑ์œผ๋กœ์˜ ํ™•์žฅ

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    ํ•™์œ„๋…ผ๋ฌธ(๋ฐ•์‚ฌ)--์„œ์šธ๋Œ€ํ•™๊ต ๋Œ€ํ•™์› :ํ–‰์ •๋Œ€ํ•™์› ํ–‰์ •ํ•™๊ณผ(ํ–‰์ •ํ•™์ „๊ณต),2020. 2. ์ด์ˆ˜์˜.This research identifies the impacts of diversity on organizational performance on the presumption that previous research cannot fully explain the actual relationships between groups. Previous research mainly posits that the relationship is formed by similarity based on surface-level diversity, such as gender, race, and ethnicity. However, in reality, individuals do not develop relationships only at the surface level: they usually have positive relations with dissimilar others, hostile relations with similar others, or their relations are not static. Previous research on diversity has not explained these phenomena, therefore it cannot provide practical suggestions on the impacts of diversity and diversity management. The two limitations of previous studies are as follows. First, previous studies in Public Administration have narrowly understood diversity in line with affirmative action, which is implemented to improve equity and organizational legitimacy. Second, studies on diversity rarely attempt to understand the relationships between groups from a structural view, while they borrow the concept of group inequality from sociology. For example, members consider power in the relationship between others, and a new relationship occurs in the process of social mobility. This research conducts three empirical analyses to resolve the aforementioned problems. First, the analysis conceptualizes deep-level diversity and identifies its impact on organizational performance. This study selects the board of directors as the research subject, and their position, tenure, and occupation as independent variables. The dependent variable is monitoring management, which is discussed as one of the major performance indicators of the board in agency theory: I track the boards decision based on board minutes, and consider that the higher the rate of revision and rejection, rather than approval of each agenda, the higher the degree of monitoring. According to Feasible Generalized Least Squares(FGLS) analysis of three-year panel data of state-owned companies in Korea, the positive impact of surface-level diversity (gender diversity) is reinforced after adding the deep-level diversity in the model. This result allows us to assume that the conflicting gender effect in the previous research is because of omitted deep-level diversity. Tenure diversity and occupation diversity are also found to increase the level of monitoring. These results support the idea that diverse values and expertise improve organizational performance following an information/decision-making perspective. In this chapter, I recognize that deep-level diversity is an important factor in identifying the actual behavior of members, and gender diversity is more beneficial than previously thought. Second analysis identifies has found whether diversity is positive even when considered a discriminatory, distributed power. Unlike the previous assumption that diverse members offer diverse opinions and values, the individual is likely to choose compliance and support rather than resistance to the person with more power (mainly his/her superordinate). I investigate the impacts of congruence of gender, educational attainment, occupation, region of origin, and affiliated universities between ministers and vice-ministers on organizational performance in relational demography. According to the Generalized Method of Moment(GMM) analyses of ten-year panel data of central government, I found that while the congruence of affiliated universities (mainly the congruence of Seoul National University) is negative with regard to organizational performance, gender (mainly the congruence of male), occupation (mainly the congruence of bureaucrat), and the region of origin (mainly the congruence of Seoul) are positive. These results suppose that male subordinates do not prefer female superordinate following the role congruity theory, that bureaucrats have a higher level of understanding of governmental organizations, and that the region of origin has a role to play in positive social capital. These results, in turn, show that diverse members are not always positive on organizational performance: Trust brought about between similar members is sometimes more efficient, and institutional intervention such as affirmative action can be limited to breaking the firmly ordered system of super- and subordination. The final analysis identifies the impacts of members changed relationships in social mobility on organizational performance. I chose two independent variables: Employment status diversity, which is the transition policy from nonstandard workers to standard workers in vertical social mobility, and work status diversity, which is the change to part-time work in horizontal social mobility. According to the Generalized Method of Moment(GMM) analyses of five-year panel data of state-owned companies, work status diversity was found to be statistically significant while employment status diversity was not. I assume that the impact of employment status diversity is traded off between the nonstandard workers improved motivation to work and the standard workers discontent. Work status diversity is positive on organizational performance as the positive effect of work-life balance from the part-time work is reinforced by social information processing. These findings imply that social mobility causes a positive or negative change not only to the changed individual but also to the overall organization, and this provides a more practical managerial suggestion regarding the reality of diverse work contracts. This research contributes to the discussion of multidimensional diversity embedded in structural factors. Given these findings, it is expected that the delicate, or sometimes even lack of relational relationships between members is more understandable. This study also suggests that diversity is not positive in itself, but is significant for organizational openness, and that the reform of the conventional system should be more beneficial than the introduction of a new diversity management method.๋ณธ ์—ฐ๊ตฌ๋Š” ํ–‰์ •ํ•™์—์„œ์˜ ๋‹ค์–‘์„ฑ ๋…ผ์˜๊ฐ€ ํ˜„์‹ค์˜ ์ง‘๋‹จ ๊ด€๊ณ„๋ฅผ ๋ชจ๋‘ ์„ค๋ช…ํ•ด์ฃผ์ง€ ๋ชปํ•œ๋‹ค๋Š” ๋ฌธ์ œ์˜์‹ ํ•˜์—, ๋‹ค์–‘์„ฑ๊ณผ ์กฐ์ง์„ฑ๊ณผ์˜ ๊ด€๊ณ„๋ฅผ ๋ฐํžˆ๋Š” ์—ฐ๊ตฌ๋ฅผ ์‹œํ–‰ํ•˜์˜€๋‹ค. ์„ ํ–‰์—ฐ๊ตฌ๋“ค์€ ์ฃผ๋กœ ์„ฑ๋ณ„, ์ธ์ข…, ๋ฏผ์กฑ์„ฑ๊ณผ ๊ฐ™์€ ํ‘œ๋ฉด์  ์š”์ธ๋“ค์— ์˜ํ•ด ์ง‘๋‹จ์ด ํ˜•์„ฑ๋˜๊ณ , ์œ ์‚ฌ์„ฑ์„ ํ† ๋Œ€๋กœ ์„ ํ˜ธ๋„๋ฅผ ๊ฒฐ์ •ํ•ด ๊ด€๊ณ„๊ฐ€ ํ˜•์„ฑ๋œ๋‹ค๊ณ  ๋ณด์•˜๋‹ค. ๊ทธ๋ ‡์ง€๋งŒ ํ˜„์‹ค์—์„œ ๊ฐœ์ธ๋“ค์€ ๋‹จ์ˆœํžˆ ์™ธ์ ์ธ ์š”์ธ์— ์˜ํ•ด์„œ๋งŒ ๊ด€๊ณ„๋ฅผ ๊ฒฐ์ •ํ•˜์ง€ ์•Š์œผ๋ฉฐ, ์ž์‹ ๊ณผ ์™ธ์ ์œผ๋กœ ์œ ์‚ฌํ•˜์ง€ ์•Š์€ ํƒ€์ธ๊ณผ ์šฐํ˜ธ์ ์ธ ๊ด€๊ณ„๋ฅผ ๋งบ๊ณ  ์žˆ๋Š” ๊ฒฝ์šฐ๋„ ์žˆ๊ณ , ์œ ์‚ฌํ•œ ํƒ€์ธ๊ณผ ๋ถ€์ •์ ์ธ ๊ด€๊ณ„๋ฅผ ๋งบ๋Š” ๊ฒฝ์šฐ๋„ ๋งŽ์œผ๋ฉฐ ๊ด€๊ณ„๊ฐ€ ํ•ญ์ƒ ๊ณ ์ •์ ์ธ ๊ฒƒ๋„ ์•„๋‹ˆ๋‹ค. ๊ธฐ์กด์˜ ๋‹ค์–‘์„ฑ ๋…ผ์˜๋“ค์€ ์ด๋Ÿฌํ•œ ํ˜„์ƒ๋“ค์„ ์„ค๋ช…ํ•˜์ง€ ๋ชปํ•˜๊ณ  ์žˆ์—ˆ์œผ๋ฉฐ, ๊ทธ๋ ‡๊ธฐ ๋•Œ๋ฌธ์— ๋‹ค์–‘์„ฑ์˜ ํšจ๊ณผ์™€ ๊ด€๋ฆฌ๋ฐฉ์‹์— ๋Œ€ํ•ด ์‹ค์ฒœ์  ์ œ์–ธ์„ ์ œ๊ณตํ•˜์ง€ ๋ชปํ–ˆ๋‹ค. ๊ตฌ์ฒด์ ์œผ๋กœ ๋ณธ ์—ฐ๊ตฌ๊ฐ€ ์ธ์‹ํ•œ ์„ ํ–‰์—ฐ๊ตฌ์˜ ํ•œ๊ณ„๋Š” ๋‹ค์Œ๊ณผ ๊ฐ™๋‹ค. ์ฒซ์งธ, ํ–‰์ •ํ•™์€ ํ˜•ํ‰์„ฑ ๊ฐ•ํ™”์™€ ์กฐ์ง ์ •๋‹น์„ฑ ํ™•๋ณด๋ฅผ ์œ„ํ•ด ์ ๊ทน์  ์กฐ์น˜์˜ ์—ฐ์žฅ์„ ์—์„œ ๋‹ค์–‘์„ฑ์„ ํ˜‘์†Œํ•œ ๊ฐœ๋…์œผ๋กœ ์ดํ•ดํ•˜๊ณ  ์žˆ๋‹ค. ๋‘˜์งธ, ๋‹ค์–‘์„ฑ ๋…ผ์˜๋“ค์€ ์‚ฌํšŒํ•™์—์„œ์˜ ์ง‘๋‹จ ๊ฐ„ ๋ถˆํ‰๋“ฑ์ด๋ผ๋Š” ๋ฌธ์ œ์˜์‹์„ ์ฐจ์šฉํ•œ ๊ฒƒ์— ๋น„ํ•ด ๊ตฌ์„ฑ์›๋“ค์˜ ๊ด€๊ณ„๋ฅผ ๊ตฌ์กฐ์  ๊ด€์ ์—์„œ ์ดํ•ดํ•˜๋ ค๋Š” ์‹œ๋„๋Š” ์ ์—ˆ๋‹ค. ์˜ˆ๋ฅผ ๋“ค์–ด ๊ตฌ์„ฑ์›์ด ๋‹จ์ˆœํžˆ ์œ ์‚ฌ์„ฑ์ด ์•„๋‹ˆ๋ผ ๊ถŒ๋ ฅ ๊ด€๊ณ„๋ฅผ ๊ณ ๋ คํ•ด ๊ด€๊ณ„๋ฅผ ๊ฒฐ์ •ํ•  ์ˆ˜ ์žˆ๋‹ค๋Š” ์ , ๊ด€๊ณ„๊ฐ€ ๊ณ ์ •์ ์ธ ๊ฒƒ์ด ์•„๋‹ˆ๋ผ ์‚ฌํšŒ ์ด๋™์ด ๋ฐœ์ƒํ•  ๋•Œ ์ƒˆ๋กœ์šด ๊ด€๊ณ„๊ฐ€ ํ˜•์„ฑ๋  ์ˆ˜ ์žˆ๋‹ค๋Š” ์ ์ด ๊ฐ„๊ณผ๋˜์—ˆ๋‹ค. ์ด๋Ÿฌํ•œ ๋ฌธ์ œ๋ฅผ ํ† ๋Œ€๋กœ, ๋ณธ ์—ฐ๊ตฌ๋Š” ์„ธ ๊ฐ€์ง€ ์‹ค์ฆ๋ถ„์„์„ ์‹œํ–‰ํ•˜์˜€๋‹ค. ์ฒซ ๋ฒˆ์งธ ์‹ค์ฆ๋ถ„์„์€ ์‹ฌ์ธต์  ๋‹ค์–‘์„ฑ์„ ๊ฐœ๋…ํ™”ํ•˜๊ณ  ํšจ๊ณผ๋ฅผ ํ™•์ธํ•˜๋Š” ๊ฒƒ์ด๋‹ค. ์ด๋ฅผ ์œ„ํ•ด ๋ณธ ์—ฐ๊ตฌ๋Š” ๊ณต๊ณต๊ธฐ๊ด€ ์ด์‚ฌํšŒ๋ฅผ ์—ฐ๊ตฌ ๋Œ€์ƒ์œผ๋กœ, ์ด์‚ฌ์ง„์˜ ์ง์œ„์™€ ์žฌ์ž„๊ธฐ๊ฐ„, ๊ฒฝ๋ ฅ์„ ๋‹ค์–‘์„ฑ ๋ณ€์ˆ˜๋กœ ์„ ์ •ํ•˜์˜€๋‹ค. ์ข…์†๋ณ€์ˆ˜๋Š” ๋Œ€๋ฆฌ์ธ ์ด๋ก  ๊ด€์ ์—์„œ ์ด์‚ฌํšŒ์˜ ์ฃผ์š” ์„ฑ๊ณผ ์ค‘ ํ•˜๋‚˜๋กœ ๋…ผ์˜๋˜๋Š” ๊ฒฝ์˜์ง„์— ๋Œ€ํ•œ ํ†ต์ œ์ˆ˜์ค€์„ ์„ ์ •ํ•˜์˜€๋‹ค. ์ด๋Š” ๊ณต๊ณต๊ธฐ๊ด€ ์ด์‚ฌํšŒ ํšŒ์˜๋ก์— ๊ณต๊ฐœ๋œ ์˜๊ฒฐ ์•ˆ๊ฑด ๊ฒฐ๊ณผ๋ฅผ ํ† ๋Œ€๋กœ, ์ „์ฒด ์˜๊ฒฐ ์ˆ˜ ๋Œ€๋น„ ์ˆ˜์ • ์˜๊ฒฐ๊ณผ ๋ถ€๊ฒฐ์˜ ๋น„์œจ๋กœ ๊ตฌํ•˜์˜€๋‹ค. 3๋…„๊ฐ„์˜ ์ž๋ฃŒ๋ฅผ ํ™œ์šฉํ•œ Feasible Generalized Least Squares(FGLS) ๋ถ„์„ ๊ฒฐ๊ณผ, ์‹ฌ์ธต์  ๋‹ค์–‘์„ฑ์„ ์ถ”๊ฐ€ํ•œ ํ›„ ํ‘œ๋ฉด์  ๋‹ค์–‘์„ฑ(์„ฑ๋ณ„ ๋‹ค์–‘์„ฑ)์˜ ๊ธ์ •์  ํšจ๊ณผ๋Š” ์˜คํžˆ๋ ค ๋” ๊ฐ•ํ™”๋˜๋Š” ๊ฒƒ์œผ๋กœ ํ™•์ธ๋˜์—ˆ๋‹ค. ์ด๋Š” ๊ทธ๊ฐ„ ์„ฑ๋ณ„ ํšจ๊ณผ๋กœ ๋…ผ์˜๋˜์—ˆ๋˜ ๊ฒƒ์ด ์‹ค์ œ๋กœ๋Š” ๊ฒฝ๋ ฅ์ด๋‚˜ ์ง์œ„ ๋“ฑ์— ์˜ํ•œ ํšจ๊ณผ์ผ ์ˆ˜ ์žˆ๋‹ค๋Š” ์ถ”์ธก์„ ๊ฐ€๋Šฅํ•˜๊ฒŒ ํ•œ๋‹ค. ์‹ฌ์ธต์  ๋‹ค์–‘์„ฑ ์ค‘ ์žฌ์ž„๊ธฐ๊ฐ„ ๋‹ค์–‘์„ฑ๊ณผ ๊ฒฝ๋ ฅ ๋‹ค์–‘์„ฑ์€ ๊ฒฝ์˜์ง„์— ๋Œ€ํ•œ ํ†ต์ œ์ˆ˜์ค€์„ ์ฆ๊ฐ€์‹œํ‚ค๋Š” ์š”์ธ์œผ๋กœ ํ™•์ธ๋˜์—ˆ๋‹ค. ์ด๋Ÿฌํ•œ ๊ฒฐ๊ณผ๋“ค์€ ์ •๋ณด/์˜์‚ฌ๊ฒฐ์ • ๊ด€์ ์ด ์ฃผ์žฅํ•˜๋Š” ๊ฒƒ์ฒ˜๋Ÿผ ๋‹ค์–‘ํ•œ ๊ฐ€์น˜๊ด€๊ณผ ์ „๋ฌธ์„ฑ์ด ์กฐ์ง์„ฑ๊ณผ๋ฅผ ์ฆ๊ฐ€์‹œํ‚ฌ ์ˆ˜ ์žˆ์Œ์„ ๋ณด์—ฌ์ค€๋‹ค. ์ด๋Ÿฌํ•œ ๋…ผ์˜๋ฅผ ํ†ตํ•ด ์‹ฌ์ธต์  ๋‹ค์–‘์„ฑ์€ ์‹ค์ œ ๊ตฌ์„ฑ์›์˜ ํ–‰ํƒœ๋ฅผ ํ™•์ธํ•˜๊ธฐ ์œ„ํ•ด ์ค‘์š”ํ•œ ์š”์ธ์ด๋ผ๋Š” ์ , ๋˜ํ•œ ์„ฑ๋ณ„ ๋‹ค์–‘์„ฑ์˜ ํšจ๊ณผ๋Š” ์•Œ๋ ค์ ธ ์žˆ๋Š” ๊ฒƒ๋ณด๋‹ค ๋” ๊ธ์ •์ ์ด๋ผ๋Š” ์  ๋“ฑ์„ ํ™•์ธํ•˜์˜€๋‹ค. ๋‘ ๋ฒˆ์งธ ์‹ค์ฆ๋ถ„์„์—์„œ๋Š” ์ฐจ๋ณ„์ ์œผ๋กœ ๋ฐฐ๋ถ„๋œ ๊ถŒ์œ„๋ฅผ ๊ณ ๋ คํ•˜์˜€์„ ๋•Œ์—๋„ ๋‹ค์–‘์„ฑ์€ ๊ธ์ •์ ์ธ๊ฐ€๋ฅผ ํ™•์ธํ•˜์˜€๋‹ค. ๋‹ค์–‘ํ•œ ๊ตฌ์„ฑ์›์ด ๋‹ค์–‘ํ•œ ๊ฒฌํ•ด๋ฅผ ๊ฐ€์ ธ์˜จ๋‹ค๋Š” ๊ธฐ์กด์˜ ๊ฐ€์ •๊ณผ ๋‹ฌ๋ฆฌ, ๊ฐœ์ธ์€ ์ž์‹ ๋ณด๋‹ค ๋” ๋งŽ์€ ๊ถŒํ•œ๊ณผ ์ž์›์„ ๊ฐ€์ง„ ์ด(์ฃผ๋กœ ์ƒ์‚ฌ)์—๊ฒŒ ์ €ํ•ญ๋ณด๋‹ค๋Š” ์ˆœ์‘๊ณผ ์ง€์›์„ ํƒํ•  ๊ฐ€๋Šฅ์„ฑ์ด ์žˆ๋‹ค. ์ด๋ฅผ ์œ„ํ•ด ๋ณธ ์—ฐ๊ตฌ๋Š” ๊ตฌ์„ฑ์› ๊ฐ„ ์ด์งˆ์„ฑ(relational demography)์„ ํ™•์ธํ•˜๊ธฐ ์œ„ํ•ด ์žฅยท์ฐจ๊ด€์˜ ์„ฑ๋ณ„, ํ•™๋ ฅ, ๊ฒฝ๋ ฅ, ์ถœ์‹  ์ง€์—ญ๊ณผ ์ถœ์‹  ํ•™๊ต(์ถœ์‹  ๋Œ€ํ•™๊ต)์˜ ์ผ์น˜ ์—ฌ๋ถ€๊ฐ€ ์žฌ์ •์„ฑ๊ณผ๋ชฉํ‘œ๊ด€๋ฆฌ์ œ๋„์˜ ๋ชฉํ‘œ๋‹ฌ์„ฑ์œจ, ์ •๋ถ€์—…๋ฌดํ‰๊ฐ€๊ฒฐ๊ณผ์— ๋ฏธ์น˜๋Š” ์˜ํ–ฅ์„ ํ™•์ธํ•˜์˜€๋‹ค. 10๋…„๊ฐ„์˜ ์ž๋ฃŒ๋ฅผ ํ† ๋Œ€๋กœ Generalized Method of Moment(GMM) ๋ถ„์„์„ ์‹œํ–‰ํ•œ ๊ฒฐ๊ณผ, ์žฅยท์ฐจ๊ด€์˜ ์ถœ์‹  ํ•™๊ต ์ผ์น˜(์ฃผ๋กœ ์„œ์šธ๋Œ€ ์ผ์น˜)๋Š” ๋ถ€์ •์ ์ด์—ˆ์œผ๋‚˜ ์„ฑ๋ณ„(์ฃผ๋กœ ๋‚จ์„ฑ ์ผ์น˜), ๊ฒฝ๋ ฅ(์ฃผ๋กœ ๊ด€๋ฃŒ ์ผ์น˜), ์ถœ์‹  ์ง€์—ญ(์ฃผ๋กœ ์„œ์šธ์ถœ์‹  ์ผ์น˜)์€ ์ผ์น˜ํ•  ๋•Œ ์˜คํžˆ๋ ค ์กฐ์ง์„ฑ๊ณผ์— ๊ธ์ •์ ์ธ ์˜ํ–ฅ์„ ๋ฏธ์น˜๋Š” ๊ฒƒ์œผ๋กœ ํ™•์ธ๋˜์—ˆ๋‹ค. ์ด๋Š” ์—ญํ• ์ผ์น˜์ด๋ก ์— ๋”ฐ๋ผ ์—ฌ์„ฑ ์ƒ์‚ฌ(์—ฌ์„ฑ ์žฅ๊ด€)๋ฅผ ์„ ํ˜ธํ•˜์ง€ ์•Š๋Š” ๊ฒฝํ–ฅ, ๊ด€๋ฃŒ ์ถœ์‹ ์ด ์กฐ์ง์— ๋Œ€ํ•œ ์ดํ•ด๋„๊ฐ€ ์ƒ๋Œ€์ ์œผ๋กœ ๋†’์€ ์ , ์ถœ์‹  ์ง€์—ญ์ด ์‚ฌํšŒ์ž๋ณธ์˜ ๊ธ์ •์  ํšจ๊ณผ๋ฅผ ๋ฐœํœ˜ํ•˜๋Š” ์  ๋“ฑ์œผ๋กœ ์ถ”์ธกํ•  ์ˆ˜ ์žˆ๋‹ค. ์ด๋Ÿฌํ•œ ๊ฒฐ๊ณผ๋Š” ๋‹ค์–‘ํ•œ ๊ตฌ์„ฑ์›์ด ๋ฐ˜๋“œ์‹œ ๊ธ์ •์ ์ธ ๊ฒƒ์€ ์•„๋‹ˆ๋ผ๋Š” ์ ์„ ๋ณด์—ฌ์ค€๋‹ค. ์ฆ‰ ๋™์งˆ์ ์ธ ๊ตฌ์„ฑ์› ๊ฐ„ ๋ฐœํœ˜๋˜๋Š” ์‹ ๋ขฐ ๊ธฐ๋ฐ˜์˜ ์šด์˜์ด ํšจ์œจ์ ์ผ ์ˆ˜ ์žˆ์œผ๋ฉฐ, ์ ๊ทน์  ์กฐ์น˜์™€ ๊ฐ™์€ ์ œ๋„์  ๋ณด์™„๋„ ์กฐ์ง์˜ ์ˆ˜์ง์  ๊ตฌ์กฐ๋ผ๋Š” ๊ณต๊ณ ํ•œ ์ฒด์ œ๋ฅผ ๊นจ๊ธฐ์— ์ œํ•œ์ ์ผ ์ˆ˜ ์žˆ๋‹ค. ์„ธ ๋ฒˆ์งธ ์‹ค์ฆ๋ถ„์„์—์„œ ๋ณธ ์—ฐ๊ตฌ๋Š” ์‚ฌํšŒ์ด๋™ ๊ณผ์ •์—์„œ ๋‚˜ํƒ€๋‚˜๋Š” ๊ด€๊ณ„์˜ ๋ณ€ํ™”๊ฐ€ ์กฐ์ง์„ฑ๊ณผ์— ๋ฏธ์น˜๋Š” ํšจ๊ณผ๋ฅผ ํ™•์ธํ•˜์˜€๋‹ค. ๋ณธ ์—ฐ๊ตฌ๋Š” ์ง€์œ„์˜ ๊ณ ํ•˜๋ฅผ ๋ณ€ํ™”์‹œํ‚ค๋Š” ์ˆ˜์ง์  ์‚ฌํšŒ์ด๋™์œผ๋กœ์„œ ๋น„์ •๊ทœ์ง์˜ ์ •๊ทœ์ง ์ „ํ™˜ ์ •์ฑ…(๊ณ ์šฉํ˜•ํƒœ ๋‹ค์–‘์„ฑ)์„, ์ˆ˜ํ‰์  ์‚ฌํšŒ์ด๋™์œผ๋กœ์„œ ์‹œ๊ฐ„์ œ๊ทผ๋กœ์ œ๋„ ์ •์ฑ…(๊ทผ๋ฌดํ˜•ํƒœ ๋‹ค์–‘์„ฑ)์„ ๋…๋ฆฝ๋ณ€์ˆ˜๋กœ ์„ ์ •ํ•˜์˜€๋‹ค. ์กฐ์ง์„ฑ๊ณผ๋Š” ๊ณต๊ณต๊ธฐ๊ด€ ๊ฒฝ์˜ํ‰๊ฐ€์ œ๋„์˜ ์ฃผ์š”์‚ฌ์—… ํ‰๊ฐ€ ์˜์—ญ์˜ ๋“์  ๋น„์œจ๋กœ ์ •ํ•˜์˜€๋‹ค. 5๋…„๊ฐ„์˜ ์ž๋ฃŒ๋ฅผ ํ™œ์šฉํ•œ GMM ๋ถ„์„ ๊ฒฐ๊ณผ, ๊ณ ์šฉํ˜•ํƒœ ๋‹ค์–‘์„ฑ์€ ํ†ต๊ณ„์ ์œผ๋กœ ์œ ์˜ํ•˜์ง€ ์•Š์•˜์ง€๋งŒ ๊ทผ๋ฌดํ˜•ํƒœ ๋‹ค์–‘์„ฑ์€ ์กฐ์ง์„ฑ๊ณผ์— ๊ธ์ •์ ์ธ ์˜ํ–ฅ์„ ๋ฏธ์น˜๋Š” ๊ฒƒ์œผ๋กœ ํ™•์ธ๋˜์—ˆ๋‹ค. ๊ณ ์šฉํ˜•ํƒœ ๋‹ค์–‘์„ฑ์˜ ํšจ๊ณผ๋Š” ์ „ํ™˜๋œ ๋น„์ •๊ทœ์ง์˜ ๊ทผ๋กœ์˜์š• ๊ณ ์ทจ๋ผ๋Š” ๊ธ์ •์  ํšจ๊ณผ์™€ ๊ธฐ์กด ์ •๊ทœ์ง์˜ ๋ถˆ๋งŒ์ด๋ผ๋Š” ๋ถ€์ •์  ํšจ๊ณผ๊ฐ€ ์ƒ์‡„๋˜์—ˆ์„ ๊ฐ€๋Šฅ์„ฑ์ด ์žˆ๋‹ค. ๊ทผ๋ฌดํ˜•ํƒœ ๋‹ค์–‘์„ฑ์€ ์‹œ๊ฐ„์ œ ๊ทผ๋กœ๋ฅผ ํ†ตํ•œ ์ผ-๊ฐ€์ • ์–‘๋ฆฝ์˜ ๊ธ์ •์  ํšจ๊ณผ์™€ ๋‹ค๋ฅธ ๊ทผ๋กœ์ž๋“ค์˜ ์‹œ๊ฐ„์ œ๊ทผ๋กœ์— ๋Œ€ํ•œ ๊ธฐ๋Œ€๊ฐ€ ๋”ํ•ด์ ธ ์กฐ์ง์„ฑ๊ณผ์— ๊ธ์ •์ ์ธ ํšจ๊ณผ๋ฅผ ๋ฐœํœ˜ํ–ˆ์„ ๊ฒƒ์ด๋ผ๊ณ  ๋ณด์•˜๋‹ค. ์ด ๊ฒฐ๊ณผ๋Š” ๊ถ๊ทน์ ์œผ๋กœ ์‚ฌํšŒ์ด๋™์€ ์ด๋™ํ•˜๋Š” ๊ฐœ์ธ๋ฟ ์•„๋‹ˆ๋ผ ์ง‘๋‹จ์˜ ๊ด€๊ณ„๋ฅผ ๊ธ์ •์ , ํ˜น์€ ๋ถ€์ •์ ์œผ๋กœ ๋ณ€ํ™”์‹œํ‚จ๋‹ค๋Š” ์ ์„ ๋ณด์—ฌ์ฃผ๋ฉฐ ์กฐ์ง๊ณผ ๊ฐœ์ธ์˜ ๊ทผ๋กœ ๊ณ„์•ฝ์ด ๋‹ค์–‘ํ™”๋˜๋Š” ํ˜„์‹ค์—์„œ ๋”์šฑ ๋…ผ์˜์˜ ์˜์˜๊ฐ€ ์žˆ๋‹ค๊ณ  ํŒ๋‹จ๋œ๋‹ค. ๋ณธ ์—ฐ๊ตฌ๋Š” ๋‹ค์ฐจ์›์ ์ธ ๋‹ค์–‘์„ฑ๊ณผ ๊ตฌ์กฐ์  ์š”์ธ์— ๋ฐฐํƒœ๋œ ๋‹ค์–‘์„ฑ์„ ๋…ผ์˜ํ–ˆ๋‹ค๋Š” ์˜์˜๊ฐ€ ์žˆ๋‹ค. ์ด๋ฅผ ํ†ตํ•ด ๋ณต์žก ๋ฏธ๋ฌ˜ํ•˜๊ณ  ๋•Œ๋กœ๋Š” ๋น„ํ•ฉ๋ฆฌ์ ์ธ ๊ตฌ์„ฑ์› ๊ฐ„ ๊ด€๊ณ„๋ฅผ ์ดํ•ดํ•  ์ˆ˜ ์žˆ์„ ๊ฒƒ์œผ๋กœ ๊ธฐ๋Œ€๋œ๋‹ค. ์ด์— ๋”ฐ๋ผ ๋‹ค์–‘์„ฑ์ด ๊ทธ ์ž์ฒด๋กœ ๊ธ์ •์ ์ธ ๊ฒƒ์€ ์•„๋‹ˆ์ง€๋งŒ ์กฐ์ง์˜ ๊ฐœ๋ฐฉ์„ฑ์— ๋Œ€ํ•œ ์˜์˜๊ฐ€ ์žˆ์Œ์„ ๋…ผ์˜ํ•˜์˜€๊ณ , ์ƒˆ๋กœ์šด ๋‹ค์–‘์„ฑ๊ด€๋ฆฌ์ œ๋„์˜ ๋„์ž…๋ณด๋‹ค ๊ธฐ์กด ์ฒด๊ณ„์˜ ๊ฐœ์„ ์ด ์šฐ์„ ๋˜์–ด์•ผ ํ•จ์„ ์ œ์•ˆํ•˜์˜€๋‹ค.์ œ1์žฅ ์„œ๋ก  1 ์ œ1์ ˆ ์—ฐ๊ตฌ ๋ฐฐ๊ฒฝ ๋ฐ ํ•„์š”์„ฑ 1 ์ œ2์ ˆ ์—ฐ๊ตฌ ๋ชฉ์  3 ์ œ3์ ˆ ์—ฐ๊ตฌ์˜ ๋ฒ”์œ„ ๋ฐ ์—ฐ๊ตฌ ๋Œ€์ƒ 4 ์ œ4์ ˆ ์—ฐ๊ตฌ ๋ฐฉ๋ฒ• ๋ฐ ์ž๋ฃŒ ์ˆ˜์ง‘ 5 ์ œ2์žฅ ์ด๋ก ์  ๋…ผ์˜ 7 ์ œ1์ ˆ ๋‹ค์–‘์„ฑ์— ๊ด€ํ•œ ๋…ผ์˜ 7 1. ๋‹ค์–‘์„ฑ์˜ ์ •์˜ 7 2. ๋‹ค์–‘์„ฑ์˜ ์œ ํ˜• 10 3. ํ–‰์ •ํ•™์—์„œ์˜ ๋‹ค์–‘์„ฑ ๋…ผ์˜์˜ ๋ฐœ์ „ 19 4. ๋‹ค์–‘์„ฑ์˜ ์ธก์ • 27 ์ œ2์ ˆ ๋‹ค์–‘์„ฑ๊ณผ ์กฐ์ง์„ฑ๊ณผ์— ๊ด€ํ•œ ๋…ผ์˜ 30 1. ์กฐ์ง์„ฑ๊ณผ์— ๊ด€ํ•œ ๋…ผ์˜ 30 2. ๋‹ค์–‘์„ฑ์ด ์กฐ์ง์„ฑ๊ณผ์— ๋ฏธ์น˜๋Š” ํšจ๊ณผ 33 3. ๋‹ค์–‘์„ฑ๊ณผ ์กฐ์ง์„ฑ๊ณผ์˜ ๋…ผ์˜์˜ ํ•„์š”์„ฑ ๋ฐ ํ•œ๊ณ„ 37 4. ๋ณธ ์—ฐ๊ตฌ์˜ ๋ถ„์„ํ‹€ 38 ์ œ3์žฅ ๋‹ค์–‘์„ฑ๊ณผ ์กฐ์ง์„ฑ๊ณผ: ์‹ฌ์ธต์  ๋‹ค์–‘์„ฑ ๋…ผ์˜์˜ ํ™•์žฅ 41 ์ œ1์ ˆ ์—ฐ๊ตฌ ๋ชฉ์ ๊ณผ ์—ฐ๊ตฌ ๋ฐฉ๋ฒ• 41 1. ์—ฐ๊ตฌ ๋ชฉ์  41 2. ์—ฐ๊ตฌ ๋ฐฉ๋ฒ• 42 ์ œ2์ ˆ ๊ณต๊ณต๊ธฐ๊ด€ ์ด์‚ฌํšŒ์— ๊ด€ํ•œ ๋…ผ์˜ 43 1. ๊ณต๊ณต๊ธฐ๊ด€ ์ด์‚ฌํšŒ์˜ ์ •์˜ 43 2. ๊ณต๊ณต๊ธฐ๊ด€ ์ด์‚ฌํšŒ ๋…ผ์˜์˜ ํ•„์š”์„ฑ 43 3. ๊ณต๊ณต๊ธฐ๊ด€ ์ด์‚ฌํšŒ์— ๊ด€ํ•œ ์„ ํ–‰์—ฐ๊ตฌ์˜ ํ•œ๊ณ„ ๋ฐ ๋ณธ ์—ฐ๊ตฌ์˜ ์˜์˜ 44 ์ œ3์ ˆ ๋‹ค์–‘์„ฑ๊ณผ ์ด์‚ฌํšŒ์˜ ์„ฑ๊ณผ 45 1. ์„ฑ๋ณ„ ๋‹ค์–‘์„ฑ์— ๊ด€ํ•œ ๋…ผ์˜ 46 2. ์ง์œ„ ๋‹ค์–‘์„ฑ์— ๊ด€ํ•œ ๋…ผ์˜ 48 3. ์žฌ์ž„๊ธฐ๊ฐ„ ๋‹ค์–‘์„ฑ์— ๊ด€ํ•œ ๋…ผ์˜ 49 4. ๊ฒฝ๋ ฅ ๋‹ค์–‘์„ฑ์— ๊ด€ํ•œ ๋…ผ์˜ 52 ์ œ4์ ˆ ์ด์‚ฌํšŒ์˜ ์„ฑ๊ณผ: ๊ฒฝ์˜์ง„์— ๋Œ€ํ•œ ํ†ต์ œ 54 1. ์ด์‚ฌํšŒ์˜ ํ†ต์ œ ๊ธฐ๋Šฅ์— ๊ด€ํ•œ ๋…ผ์˜์˜ ํ•„์š”์„ฑ 54 2. ๋Œ€๋ฆฌ์ธ ์ด๋ก  55 3. ์ž์›์˜์กด์ด๋ก  56 ์ œ5์ ˆ ์—ฐ๊ตฌ ์„ค๊ณ„ 57 1. ์—ฐ๊ตฌ ๋Œ€์ƒ ๋ฐ ์—ฐ๊ตฌ ๋ฐฉ๋ฒ• 57 2. ๋ณ€์ˆ˜์˜ ์ธก์ • 60 ์ œ6์ ˆ ๋ถ„์„ ๊ฒฐ๊ณผ 69 1. ๊ธฐ์ดˆํ†ต๊ณ„๋ถ„์„ ๊ฒฐ๊ณผ 69 2. ์ƒ๊ด€๊ด€๊ณ„๋ถ„์„ ๊ฒฐ๊ณผ 76 3. ํŒจ๋„๋ถ„์„ ๊ฒฐ๊ณผ 79 ์ œ7์ ˆ ์†Œ๊ฒฐ 83 ์ œ4์žฅ ๋‹ค์–‘์„ฑ๊ณผ ์กฐ์ง์„ฑ๊ณผ: ์ฐจ๋ณ„์  ๊ถŒ์œ„์˜ ๋ฐฐ๋ถ„๊ณผ ๋‹ค์–‘์„ฑ 86 ์ œ1์ ˆ ์—ฐ๊ตฌ ๋ชฉ์ ๊ณผ ์—ฐ๊ตฌ ๋ฐฉ๋ฒ• 86 1. ์ œ๋„์™€ ๋‹ค์–‘์„ฑ ๋…ผ์˜์˜ ํ•„์š”์„ฑ 86 2. ์—ฐ๊ตฌ ๋ฐฉ๋ฒ•: ๊ตฌ์„ฑ์› ๊ฐ„ ์ด์งˆ์„ฑ(relational demography) 87 ์ œ2์ ˆ ๊ตฌ์„ฑ์› ๊ฐ„ ์ด์งˆ์„ฑ๊ณผ ์‹ฌ์ธต์  ๋‹ค์–‘์„ฑ 88 1. ์ฐจ๋ณ„์  ๊ถŒ์œ„๋ฅผ ๋ณด์œ ํ•œ ํ–‰์œ„์ž๋“ค์— ๊ด€ํ•œ ๊ด€์‹ฌ 88 2. ๊ตฌ์„ฑ์› ๊ฐ„ ์ด์งˆ์„ฑ: ์Œ(dyad) ๋ถ„์„์ˆ˜์ค€์˜ ์„ ํ–‰์—ฐ๊ตฌ์™€ ํ•œ๊ณ„ 89 ์ œ3์ ˆ ์žฅยท์ฐจ๊ด€์˜ ๋‹ค์–‘์„ฑ์— ๊ด€ํ•œ ๋…ผ์˜์˜ ํ•„์š”์„ฑ 91 1. ์žฅยท์ฐจ๊ด€์˜ ์—ญํ• ๊ณผ ์˜์˜ 91 2. ์žฅยท์ฐจ๊ด€์˜ ์‹ฌ์ธต์  ๋‹ค์–‘์„ฑ ์—ฐ๊ตฌ์˜ ํ•„์š”์„ฑ๊ณผ ์„ ํ–‰์—ฐ๊ตฌ์˜ ํ•œ๊ณ„ 92 ์ œ4์ ˆ ํ‘œ๋ฉด์ ยท์‹ฌ์ธต์  ๋‹ค์–‘์„ฑ๊ณผ ์ •๋ถ€์„ฑ๊ณผ 93 1. ์„ฑ๋ณ„ ๋‹ค์–‘์„ฑ์— ๊ด€ํ•œ ๋…ผ์˜ 94 2. ํ•™๋ ฅ ๋‹ค์–‘์„ฑ์— ๊ด€ํ•œ ๋…ผ์˜ 96 3. ๊ฒฝ๋ ฅ ๋‹ค์–‘์„ฑ์— ๊ด€ํ•œ ๋…ผ์˜ 98 4. ์—ฐ๊ณ (็ทฃๆ•…) ๋‹ค์–‘์„ฑ์— ๊ด€ํ•œ ๋…ผ์˜ 100 ์ œ5์ ˆ ์ •๋ถ€์„ฑ๊ณผ์— ๊ด€ํ•œ ๋…ผ์˜ 105 ์ œ6์ ˆ ์—ฐ๊ตฌ ์„ค๊ณ„ 106 1. ์—ฐ๊ตฌ๋Œ€์ƒ ๋ฐ ์—ฐ๊ตฌ ๋ฐฉ๋ฒ• 106 2. ๋ณ€์ˆ˜์˜ ์ธก์ • 110 ์ œ7์ ˆ ๋ถ„์„ ๊ฒฐ๊ณผ 117 1. ๊ธฐ์ดˆํ†ต๊ณ„๋ถ„์„ ๊ฒฐ๊ณผ 117 2. ์ƒ๊ด€๊ด€๊ณ„๋ถ„์„ ๊ฒฐ๊ณผ 125 3. ํŒจ๋„๋ถ„์„ ๊ฒฐ๊ณผ 129 ์ œ8์ ˆ ์†Œ๊ฒฐ 137 ์ œ5์žฅ ๋‹ค์–‘์„ฑ๊ณผ ์กฐ์ง์„ฑ๊ณผ: ์‚ฌํšŒ ์ด๋™์˜ ํšจ๊ณผ์— ๊ด€ํ•œ ๋…ผ์˜ 140 ์ œ1์ ˆ ์—ฐ๊ตฌ ๋ชฉ์  140 1. ์‚ฌํšŒ ์ด๋™ ๋…ผ์˜์˜ ํ•„์š”์„ฑ 140 2. ์—ฐ๊ตฌ ๋ฐฉ๋ฒ• 141 ์ œ2์ ˆ ๊ณต๊ณต๊ธฐ๊ด€์˜ ์‚ฌํšŒ ์ด๋™ ๋…ผ์˜์˜ ์ ์ ˆ์„ฑ 142 ์ œ3์ ˆ ์—ญํ•  ๋ณ€๋™์— ๊ด€ํ•œ ๋…ผ์˜ 143 1. ์—ญํ• ์˜ ์ •์˜ 143 2. ์—ญํ•  ๋ณ€๋™์— ๋”ฐ๋ฅธ ์ง„์ž… ์ถฉ๊ฒฉ 144 3. ๋‹ค์–‘์„ฑ ๊ด€์ ์—์„œ์˜ ์—ญํ•  ๋ณ€๋™๊ณผ ์กฐ์ง์„ฑ๊ณผ ๋…ผ์˜ ํ•„์š”์„ฑ 145 ์ œ4์ ˆ ํ‘œ๋ฉด์  ๋‹ค์–‘์„ฑ๊ณผ ๊ณต๊ณต๊ธฐ๊ด€ ์„ฑ๊ณผ 146 ์ œ5์ ˆ ๊ณ ์šฉํ˜•ํƒœ ๋‹ค์–‘์„ฑ๊ณผ ๊ณต๊ณต๊ธฐ๊ด€ ์„ฑ๊ณผ 148 1. ๋น„์ •๊ทœ์ง์— ๊ด€ํ•œ ๋…ผ์˜ 148 2. ๋น„์ •๊ทœ์ง์˜ ์ •๊ทœ์ง ์ „ํ™˜ ์ด์Šˆ 152 3. ๊ณ ์šฉํ˜•ํƒœ ๋‹ค์–‘์„ฑ์— ๊ด€ํ•œ ๋…ผ์˜ 154 ์ œ6์ ˆ ๊ทผ๋ฌดํ˜•ํƒœ ๋‹ค์–‘์„ฑ๊ณผ ๊ณต๊ณต๊ธฐ๊ด€ ์„ฑ๊ณผ 156 1. ๊ฐ€์กฑ์นœํ™”์ •์ฑ…์— ๊ด€ํ•œ ๋…ผ์˜ 156 2. ๊ณต๊ณต๊ธฐ๊ด€์˜ ๊ฐ€์กฑ์นœํ™”์ •์ฑ… 160 3. ๊ทผ๋ฌดํ˜•ํƒœ ๋‹ค์–‘์„ฑ์— ๊ด€ํ•œ ๋…ผ์˜ 162 ์ œ7์ ˆ ๊ณต๊ณต๊ธฐ๊ด€์˜ ์กฐ์ง์„ฑ๊ณผ์— ๊ด€ํ•œ ๋…ผ์˜ 164 1. ๊ณต๊ณต๊ธฐ๊ด€ ๊ฒฝ์˜ํ‰๊ฐ€์ œ๋„ 164 2. ๊ณต๊ณต๊ธฐ๊ด€ ๊ฒฝ์˜ํ‰๊ฐ€์ œ๋„์— ๊ด€ํ•œ ์„ ํ–‰์—ฐ๊ตฌ 166 ์ œ8์ ˆ ์—ฐ๊ตฌ ์„ค๊ณ„ 166 1. ์—ฐ๊ตฌ ๋Œ€์ƒ ๋ฐ ์—ฐ๊ตฌ ๋ฐฉ๋ฒ• 166 2. ๋ณ€์ˆ˜์˜ ์ธก์ • 167 ์ œ9์ ˆ ๋ถ„์„ ๊ฒฐ๊ณผ 171 1. ๊ธฐ์ดˆํ†ต๊ณ„๋ถ„์„ ๊ฒฐ๊ณผ 171 2. ์ƒ๊ด€๊ด€๊ณ„๋ถ„์„ ๊ฒฐ๊ณผ 177 3. ํŒจ๋„๋ถ„์„ ๊ฒฐ๊ณผ 180 ์ œ10์ ˆ ์†Œ๊ฒฐ 185 ์ œ6์žฅ ๊ฒฐ๋ก  186Docto

    The Effects of Pay for Performance on Innovation Activities in Public Organizations: A Study of the Effects on Different Employee Ranks

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    ๋ณธ ์—ฐ๊ตฌ๋Š” ๊ณต๊ณต๋ถ€๋ฌธ์—์„œ์˜ ์„ฑ๊ณผ๊ธ‰์ด ํ˜์‹ ํ™œ๋™์— ๋ฏธ์น˜๋Š” ํšจ๊ณผ์— ๊ด€ํ•ด ์‹ค์ฆ๋ถ„์„์„ ์‹œ๋„ํ•œ๋‹ค. ๊ณต ๊ณต๋ถ€๋ฌธ์—์„œ์˜ ์„ฑ๊ณผ๊ธ‰์€ ์™ธ๋ถ€์˜ ์••๋ ฅ์— ์˜ํ•œ ํ–‰์ •์  ํ˜์‹ ์œผ๋กœ ๋ณผ ์ˆ˜ ์žˆ๋Š”๋ฐ, ๋ณธ ์—ฐ๊ตฌ๋Š” ์ด๋Ÿฌํ•œ ํ˜์‹ ์ด ๋ฐ˜๋“œ์‹œ ๊ตฌ์„ฑ์›์˜ ํ˜์‹ ํ™œ๋™์— ๊ธ์ •์ ์ธ ์˜ํ–ฅ์„ ๋ฏธ์น˜๋Š” ๊ฒƒ์€ ์•„๋‹ˆ๋ผ๋Š” ๊ด€์ ์—์„œ ๋…ผ์˜ํ•˜์˜€๋‹ค. ์ฒซ์งธ, ๋ณธ ์—ฐ๊ตฌ๋Š” ๋™๊ธฐ๊ตฌ์ถ•์ด๋ก ์˜ ๊ด€์ ์—์„œ, ๋‚ด์žฌ์  ๋ณด์ƒ์— ๋Œ€ํ•œ ์š•๊ตฌ๊ฐ€ ๊ฐ•ํ•œ ๊ณต๊ณต๋ถ€๋ฌธ ์ข…์‚ฌ์ž๋“ค ์—๊ฒŒ ์™ธ์žฌ์  ๋ณด์ƒ์ธ ์„ฑ๊ณผ๊ธ‰์ด ํ˜์‹ ํ™œ๋™์— ๋ถ€์ •์ ์ธ ์˜ํ–ฅ์„ ๋ฏธ์น˜๋Š”๊ฐ€์— ๋Œ€ํ•ด ํ™•์ธํ•˜์˜€๋‹ค. ๋‘˜์งธ, ๋ณธ ์—ฐ๊ตฌ๋Š” ์ž๊ธฐ๊ฒฐ์ •์ด๋ก ์˜ ๊ด€์ ์—์„œ, ์ง๊ธ‰์— ๋”ฐ๋ผ ์กฐ์ง ๋‚ด ์—…๋ฌด์ž์›๊ณผ ์žฌ๋Ÿ‰๊ถŒ ๋“ฑ์„ ๋‹ค๋ฅด๊ฒŒ ์†Œ์œ  ํ•˜๊ณ  ์žˆ๋Š” ๊ฐ ์ง๊ธ‰๋ณ„ ๊ตฌ์„ฑ์›๋“ค์—๊ฒŒ์„œ ์™ธ์žฌ์  ๋ณด์ƒ์˜ ๋‚ด์žฌํ™” ์ˆ˜์ค€์—์„œ ์ฐจ์ด๊ฐ€ ๋ฐœ์ƒํ•จ์— ๋”ฐ๋ผ ์„ฑ๊ณผ๊ธ‰์˜ ํšจ๊ณผ๊ฐ€ ์ฐจ๋ณ„์ ์ผ ๊ฒƒ์ด๋ผ๊ณ  ๊ฐ€์ •ํ•˜๊ณ  ์‹ค์ฆ๋ถ„์„์„ ์‹œํ–‰ํ•˜์˜€๋‹ค. ์‚ฌ์—…์ฒดํŒจ๋„์ž๋ฃŒ๋ฅผ ํ™œ์šฉํ•ด ํŒจ๋„๋ถ„์„์„ ์‹œํ–‰ํ•œ ๊ฒฐ๊ณผ, ์„ฑ๊ณผ๊ธ‰์€ ๊ตฌ์„ฑ์›์˜ ๋…ธ๋™์ƒ์‚ฐ์„ฑ์— ๋ถ€์ •์ ์ธ ์˜ํ–ฅ์„ ๋ฏธ์น˜๋ฉฐ, ํŠนํžˆ ์ค‘ํ•˜์œ„์ง๊ธ‰์„ ๋Œ€์ƒ์œผ๋กœ ์‹œํ–‰ํ•˜๋Š” ์„ฑ๊ณผ๊ธ‰์ด ์ œํ’ˆํ˜์‹ ์— ๋ถ€์ •์ ์ธ ์˜ํ–ฅ์„ ๋ฏธ์นœ๋‹ค๋Š” ๊ฒƒ์„ ํ™•์ธํ•˜์˜€๋‹ค. ๋ณธ ์—ฐ ๊ตฌ๋Š” ์ด๋Ÿฌํ•œ ๊ฒฐ๊ณผ๋ฅผ ํ†ตํ•ด ๊ณต๊ณต๋ถ€๋ฌธ์˜ ์„ฑ๊ณผ์ง€ํ–ฅ์  ๊ด€๋ฆฌ๋ฐฉ์‹์˜ ๋„์ž…์€ ๊ตฌ์„ฑ์›์˜ ์š•๊ตฌ์— ๋Œ€ํ•œ ๊ณ ๋ ค ๊ฐ€ ํ•„์š”ํ•  ๊ฒƒ์ด๋ฉฐ, ๋˜ํ•œ ์—…๋ฌดํ™˜๊ฒฝ์— ๋Œ€ํ•œ ๊ณ ๋ ค๊ฐ€ ํ•„์š”ํ•  ๊ฒƒ์ด๋ผ๊ณ  ํŒ๋‹จํ•˜์˜€๋‹ค.This research examines the effect of pay for performance on the innovation activities in public organizations. Pay for performance was implemented based on external demand for reform of the public sector. That this administrative innovation does not stimulate the innovation activities of employees is discussed. First, approaching pay for performance from the perspective of motivation crowding theory assessed whether or not the extrinsic rewards of pay for performance hinder innovation activities by public sector employees with intrinsic motivation. Second, employees would have different internalized extrinsic rewards in accordance with rank based on the self-determination theory literature since resources or discretion held by employees differ by position. Therefore it was hypothesized that there would be a distinction in the effectiveness of pay for performance on innovation activities by rank. The results of an empirical analysis using the Workplace Panel Survey indicate that pay for performance has a negative effect on innovation, especially on the activities of lower-level employees. This evidence suggests the distinct work environment and needs of public sector employees should be considered when adopting performance-oriented management systems in public organizations

    An Analysis of the Effects of a Performance-Oriented Personnel System on Organizational Commitment: A Test of System and Experience as Referents of Equity

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    ๋ณธ ์—ฐ๊ตฌ๋Š” ํ˜•ํ‰์ด๋ก ์˜ ์ƒˆ๋กœ์šด ๋‘ ๊ฐ€์ง€ ์ค€๊ฑฐ๋ฅผ ์ค‘์‹ฌ์œผ๋กœ ์„ฑ๊ณผ์ง€ํ–ฅ์  ๋ณด์ƒ๋ฐฉ์‹์— ๊ด€ํ•œ ๊ตฌ์„ฑ์›์˜ ์กฐ์ง๋ชฐ์ž…์— ๊ด€ํ•ด ๋…ผ์˜ํ•˜์˜€๋‹ค. ๊ธฐ์กด์˜ ์„ฑ๊ณผ์ง€ํ–ฅ์  ๋ณด์ƒ๋ฐฉ์‹์— ๊ด€ํ•ด ๋…ผ์˜ํ•œ ์—ฐ๊ตฌ๋“ค์€ ์„ฑ๊ณผ๊ธ‰์ œ๋„ ๋ฅผ ์ค‘์‹ฌ์œผ๋กœ ๋…ผ์˜ํ•˜์˜€๋‹ค๋Š” ํ•œ๊ณ„๊ฐ€ ์žˆ๋‹ค. ์ด๋Ÿฌํ•œ ํ•œ๊ณ„๋ฅผ ์ธ์‹ํ•˜์—ฌ, ๋ณธ ์—ฐ๊ตฌ๋Š” ์„ฑ๊ณผ์ง€ํ–ฅ์  ๋ณด์ƒ๋ฐฉ ์‹์„ ๋ณด์ƒ๊ณผ ์ œ์žฌ๋กœ ๋‚˜๋ˆ„์–ด, ๋‘ ๊ฐ€์ง€ ์ œ๋„๋ฅผ ์ค‘์‹ฌ์œผ๋กœ ๋…ผ์˜ํ•˜์˜€๋‹ค. ๋˜ํ•œ ๋ณธ ์—ฐ๊ตฌ๋Š” ๊ฐœ์ธ์˜ ํ˜•ํ‰์„ฑ ์ธ์‹์— ๋Œ€ํ•œ ๋‘ ๊ฐ€์ง€ ์ค€๊ฑฐ๊ฐ€ ์„ฑ๊ณผ์ง€ํ–ฅ์  ๋ณด์ƒ๋ฐฉ์‹๊ณผ ์กฐ์ง๋ชฐ์ž…๊ณผ์˜ ์˜ํ–ฅ์„ ๋ณ€ํ™”์‹œํ‚ค๋Š”์ง€์— ๋Œ€ํ•ด ๋…ผ์˜ํ•˜๊ณ ์ž ํ•˜์˜€๋‹ค. Goodman(1974)์€ ๊ฐœ์ธ์ด ํ˜•ํ‰์„ฑ์„ ํƒ€์ธ๊ณผ์˜ ๋น„๊ต ๋ฟ ์•„๋‹ˆ๋ผ ์Šค์Šค๋กœ๋„ ์ œ ๋„์— ๋Œ€ํ•œ ๊ธฐ๋Œ€, ๊ณผ๊ฑฐ์˜ ๊ฒฝํ—˜ ๋“ฑ์„ ํ† ๋Œ€๋กœ ํ˜•ํ‰์„ฑ์„ ์ธ์‹ํ•œ๋‹ค๋Š” ๊ฒƒ์„ ์ฃผ์žฅํ•˜์˜€๋Š”๋ฐ, ๋ณธ ์—ฐ๊ตฌ๋Š” ์ด๋Ÿฌํ•œ ๋‘ ๊ฐ€์ง€ ์ค€๊ฑฐ๋ฅผ ๊ฐ๊ฐ ์ž…์ง์‹œ๊ธฐ(์„ฑ๊ณผ์ง€ํ–ฅ์  ๋ณด์ƒ์ œ๋„์˜ ๋„์ž… ์ด์ „/์ดํ›„)์™€ ๋ฏผ๊ฐ„์กฐ์ง ๊ฒฝ๋ ฅ์œผ๋กœ ์กฐ์ž‘ํ™”ํ•˜์—ฌ ๊ทธ ์˜ํ–ฅ์„ ํ™•์ธํ•˜๊ณ ์ž ํ•˜์˜€๋‹ค. ๋ถ„์„ ๊ฒฐ๊ณผ, ๋‘ ๊ฐ€์ง€ ์„ฑ๊ณผ์ง€ํ–ฅ์  ๋ณด์ƒ๋ฐฉ์‹์€ ์กฐ์ง๋ชฐ ์ž…์— ๊ธ์ •์ ์ธ ์˜ํ–ฅ์„ ๋ฏธ์น˜๋Š” ๊ฒƒ์œผ๋กœ ํ™•์ธ๋˜์—ˆ๋‹ค. ์ด ๋•Œ ์„ฑ๊ณผ์ง€ํ–ฅ์  ๋ณด์ƒ๋ฐฉ์‹์˜ ๋„์ž… ์ด์ „์— ์ž…์งํ•œ ๊ณต๋ฌด์›์˜ ๊ฒฝ์šฐ ์„ฑ๊ณผ๊ธ‰์ด ์กฐ์ง๋ชฐ์ž…์— ๋ฏธ์น˜๋Š” ์˜ํ–ฅ์ด ์•ฝํ™”๋˜๋Š” ๊ฒƒ์œผ๋กœ ํ™•์ธ๋˜์—ˆ๊ณ , ๋ฏผ๊ฐ„์กฐ์ง ๊ฒฝ๋ ฅ์ด ์žˆ๋Š” ๊ฒฝ์šฐ ์ €์„ฑ๊ณผ์ž ์ œ์žฌ ์ œ๋„์˜ ์˜ํ–ฅ์„ ๊ฐ•ํ™”์‹œํ‚ค๋Š” ๊ฒƒ์œผ๋กœ ํ™•์ธ๋˜์—ˆ๋‹ค. ๋ณธ ์—ฐ๊ตฌ๋Š” ๊ฐœ์ธ ์˜ ํ˜•ํ‰์„ฑ ์ธ์‹์ด ๋‹ค์ฐจ์›์ ์œผ๋กœ ๊ฒฐ์ •๋œ๋‹ค๋Š” ๊ฒƒ์„ ๋ณด์—ฌ์ฃผ๋ฉฐ, ์ด์— ๋”ฐ๋ผ ์ œ๋„์˜ ๋„์ž…๊ณผ ๊ตฌ์„ฑ์›์˜ ์„ค๋“์„ ์œ„ํ•ด ์ด๋Ÿฌํ•œ ์š”์ธ์ด ์ดํ•ด๋˜์–ด์•ผ ํ•  ๊ฒƒ์œผ๋กœ ํŒ๋‹จ๋œ๋‹ค.This paper empirically tests Goodmans (1974) two referents of equity theory in performance-oriented personnel systems in government. To complement previous research only focused on performance-related pay, this paper divides system in two: performance-related pay and punishment of poor performers. This paper also adopts Goodmans referents of system and experience to show overlooked standards of personal equity awareness. System in this paper identifies differences between system expectations and the actual system are measured through the year of employment, and experience represents a comparison with the past job measured as work experience in a private organization. The results show that the two performance-oriented personnel systems increase organizational commitment, that performance-related pays effect is weakened when an employee joined an organization before the system was introduced, and that the punishment effect is strengthened when an employee has work experience in a private organization. The results suggest that there is a multidimensional perceptual structure of system equity, and it should be understood for the introduction of systems and persuading employees

    An Analysis of the Effects of Macro Socioeconomic Factors on Public Happiness: A Study of Local Government in Korea

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    ๋ณธ ์—ฐ๊ตฌ๋Š” ๊ฑฐ์‹œ์  ์‚ฌํšŒ๊ฒฝ์ œ์š”์ธ์ด ๊ตญ๋ฏผ์˜ ํ–‰๋ณต์— ๋ฏธ์น˜๋Š” ์˜ํ–ฅ์„ ํ™•์ธํ•˜๊ณ ์ž ํ•˜์˜€๋‹ค. ์ด๋Ÿฌํ•œ ์˜ํ–ฅ์„ ํ™•์ธํ•˜๊ธฐ ์œ„ํ•ด ๊ฐœ๋ณ„ ์‚ฌํšŒ๊ฒฝ์ œ์š”์ธ์ด ๊ฐœ์ธ์˜ ์ข…ํ•ฉ์ ์ธ ํ–‰๋ณต์ˆ˜์ค€์— ์˜ํ–ฅ์„ ์ค€๋‹ค๋Š” ์ƒํ–ฅํ™•์‚ฐ์ด๋ก (bottom-up spillover theory)์˜ ์ฃผ์žฅ์„ ์ ์šฉํ•˜์˜€๋‹ค. ๋˜ํ•œ, ๋ณธ ์—ฐ๊ตฌ๋Š” ๊ธฐ์กด ์—ฐ๊ตฌ์™€ ์ฐจ๋ณ„ํ™”ํ•˜์—ฌ ๊ธฐ์ดˆ์ž์น˜๋‹จ์ฒด๋ฅผ ๋ถ„์„๋‹จ์œ„๋กœ ์„ ์ •ํ•˜์˜€๋‹ค. ๋…๋ฆฝ๋ณ€์ˆ˜๋กœ๋Š” ์ •๋ถ€ ์ฒญ๋ ด๋„, ์ค‘์•™ ๊ด‘์—ญ ๊ธฐ์ดˆ์ •๋ถ€ ์‹ ๋ขฐ๋„, ๊ณต๊ณต์„œ๋น„์Šค ๋งŒ์กฑ๋„, ๊ทธ๋ฆฌ๊ณ  ๊ฑฐ์‹œ๊ฒฝ์ œ์ ๋ณ€์ˆ˜๋ฅผ, ์ข…์†๋ณ€์ˆ˜๋กœ๋Š” ์ง€์—ญ์ฃผ๋ฏผํ–‰๋ณต ์ˆ˜์ค€์„ ์„ ์ •ํ•˜์—ฌ ํ•ด๋‹น ์š”์ธ๋“ค์ด ๊ตญ๋ฏผ์˜ ํ–‰๋ณต์— ๋ฏธ์น˜๋Š” ์˜ํ–ฅ์„ ํšŒ๊ท€๋ถ„์„ ๋ฐฉ๋ฒ•์„ ํ†ตํ•ด ํ™•์ธํ•˜์˜€๋‹ค. ์—ฐ๊ตฌ๊ฒฐ๊ณผ, ์ƒํ™œํ™˜๊ฒฝ์„œ๋น„์Šค, ๊ต์œก/๋ฌธํ™” ๋“ฑ ์„œ๋น„์Šค, ์†Œ๋ฐฉ์•ˆ์ „ ์„œ๋น„์Šค, ๊ทธ๋ฆฌ๊ณ  ์žฌ์ •์ž์ฃผ๋„๊ฐ€ ๊ตญ๋ฏผ์˜ ํ–‰ ๋ณต์— ํ†ต๊ณ„์ ์œผ๋กœ ์œ ์˜๋ฏธํ•œ ๊ธ์ •์  ์˜ํ–ฅ์„ ๋ฏธ์น˜๋Š” ๊ฒƒ์œผ๋กœ ๋‚˜ํƒ€๋‚ฌ๋‹ค. ์ด๋Ÿฌํ•œ ์—ฐ๊ตฌ๊ฒฐ๊ณผ๋Š” ๊ตญ๋ฏผ ํ–‰๋ณต์„ ์œ„ํ•ด ์ •๋ถ€๊ฐ€ ์‹ ๊ฒฝ์จ์•ผ ํ•  ๋ถ€๋ถ„์— ๋Œ€ํ•œ ์‹œ์‚ฌ์ ์„ ์ œ์‹œํ•˜๋ฉฐ, ํ–ฅํ›„ ๊ธฐ์ดˆ์ž์น˜๋‹จ์ฒด์˜ ์—ญํ• ์— ๋Œ€ํ•œ ๋ฐฉํ–ฅ์„ฑ์„ ์ œ์‹œํ•œ๋‹ค๋Š” ๋ฐ์— ๊ทธ ์˜์˜๊ฐ€ ์žˆ๋‹ค๊ณ  ํ•  ๊ฒƒ์ด๋‹ค

    The Trade-off Effects in the Parental Leave: How does the Work-Family Balance of Organizational Members Change?

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