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遺��옄�뱾�쓽 珥덇꺽李� �룆�꽌踰� |
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| 저자 | 媛�誘몄삤移� 留덉궗�븘�궎 |
| 출판사 | �뙟�븻�뙆而ㅼ뒪 |
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�썝�쑀 媛�寃⑹뿉 �슱怨� �썐�뒗 �꽭怨� 寃쎌젣 |
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| 2005�뀈 �쑀媛�媛� 移섏넖湲� �떆�옉�븳 �씠�썑 OPEC怨� �윭�떆�븘�뒗 �쑀濡�媛� �뾾�뿀�뜕 �쁽湲� �옍移섏뿉 利먭굅�슫 鍮꾨챸�쓣 吏덈���떎. �븯吏�留� �쑀媛�媛� 諛곕윺 �떦 147 �떖�윭濡� �젙�젏�뿉 �떖�븳 �씠�썑, 媛�寃⑹씠 怨ㅻ몢諛뺤쭏移섍퀬 �엳�떎. �썝�쑀媛��쓽 �긽�듅怨� �븯�씫, �씠 �쁽�긽�씠 �썝�쑀 �닚�닔�엯援��뿉寃뚮뒗 �뼱�뼡 �쓽誘몄씪源�? 諛섎��濡� 二쇱슂 �궛�쑀援��뿉寃뚮뒗? �옣湲곗쟻�씤 愿��젏�뿉�꽌 �씠 沅곴툑利앹쓣 ����뼱蹂댁옄.
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Getting to Neutral |
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| 저자 | Trevor Moawad |
| 출판사 | HarperOne |
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Prediction Machines |
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| 저자 | Ajay Agrawal �쇅 |
| 출판사 | Harvard Business Review Press |
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Tapping into the For |
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| If we view the world萸� population as a pyramid ?with the richest people at the top, and poorest people at the broad base ?it may surprise you to realize that some of the best business opportunities await those who target the bottom of the pyramid. |
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[115]권 
