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    기업 입지 유형이 기업생산성에 미치는 영향에 관한 연구 : 제주지역을 중심으로 = A Study for the Effect of a Corporate Productivity Influenced by the Business Location : focusing on the Jeju

    한글로보기

    https://www.riss.kr/link?id=T13191121

    • 저자
    • 발행사항

      제주 : 제주대학교 대학원, 2012

    • 학위논문사항

      학위논문(석사) -- 제주대학교 대학원 , 경제학과 , 2012. 8

    • 발행연도

      2012

    • 작성언어

      한국어

    • 발행국(도시)

      제주특별자치도

    • 형태사항

      vii , 81 p. ; 26 cm

    • 일반주기명

      지도교수: 정수연

    • 소장기관
      • 제주대학교 중앙도서관 소장기관정보
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    다국어 초록 (Multilingual Abstract) kakao i 다국어 번역

    The study is to differentiate the location types of IT & BT companies in Jeju agglomeration and non-concentrated areas to analyze and compare its productivity to add on the explanation of the external effect on industrial agglomeration.
    In addition, to find the main factor that effects productivity improvement to establish an efficient local policy for corporate productivity improvement, industry vitalization and for the development of Jeju.
    The analyzed targets for this study are 78 individual IT & BT corporate within Jeju in 2009 that fits the condition that it does not have missing data on any variables etc.
    Out of 78 corporate it is differentiated by 34 agglomeration corporate and 44 non-concentrated areas corporate where companies that are located within Jeju Science Park and Jeju Techno Park are agglomeration corporate and the rest are non-concentrated areas corporate.
    As for the study method, by the Cobb-Douglas production function, the production function was estimated by setting up dummy variables that presents labor, capital and corporate location types that was the foundation to estimate the total factor productivity by corporate location type.
    And the main factors that affect the decision of total factor productivity such as corporate age, corporate size, whether there is study development spending, whether it is relevant to IT industry etc were selected for explanatory variables to analyze the decision main factor.
    StataSE 10.0 program was used for these multiple regression analysis and correlation analysis etc quantitative analysis.
    From the result of the estimated production function, it was possible to anticipate that when the number of employees or tangible fixed assets increases the corporate sales will increase.
    And by having similar industry companies to locate within the same area there is a sales increase effect.
    By subdividing all the variables with the estimated production function and comparing total factor productivity by selecting the comparable targets for agglomeration and non-concentrated areas corporate, concentrated areas showed a higher total factor productivity.
    In the end, it was analyzed that the IT & BT companies in Jeju during 2009 that were located in agglomeration has a higher productivity.
    As a results of analyzing the main factors that decide the total factor productivity, small in size and old corporate are predict to have a more efficient productivity.
    In this study, cross-section data was used as building time series data was inadequate and in analyzing the main factors for results, there weren’t many variables to use as the variables that are expected to effect corporate productivity were not used, there were limited individual corporate data.
    In the future, on setting up the model, to analyze the total factor productivity that reflect the size of economy and overcome the study limit after building the time series data through the same study we will leave it as an assignment to gain stronger credibility.
    번역하기

    The study is to differentiate the location types of IT & BT companies in Jeju agglomeration and non-concentrated areas to analyze and compare its productivity to add on the explanation of the external effect on industrial agglomeration. In addition, ...

    The study is to differentiate the location types of IT & BT companies in Jeju agglomeration and non-concentrated areas to analyze and compare its productivity to add on the explanation of the external effect on industrial agglomeration.
    In addition, to find the main factor that effects productivity improvement to establish an efficient local policy for corporate productivity improvement, industry vitalization and for the development of Jeju.
    The analyzed targets for this study are 78 individual IT & BT corporate within Jeju in 2009 that fits the condition that it does not have missing data on any variables etc.
    Out of 78 corporate it is differentiated by 34 agglomeration corporate and 44 non-concentrated areas corporate where companies that are located within Jeju Science Park and Jeju Techno Park are agglomeration corporate and the rest are non-concentrated areas corporate.
    As for the study method, by the Cobb-Douglas production function, the production function was estimated by setting up dummy variables that presents labor, capital and corporate location types that was the foundation to estimate the total factor productivity by corporate location type.
    And the main factors that affect the decision of total factor productivity such as corporate age, corporate size, whether there is study development spending, whether it is relevant to IT industry etc were selected for explanatory variables to analyze the decision main factor.
    StataSE 10.0 program was used for these multiple regression analysis and correlation analysis etc quantitative analysis.
    From the result of the estimated production function, it was possible to anticipate that when the number of employees or tangible fixed assets increases the corporate sales will increase.
    And by having similar industry companies to locate within the same area there is a sales increase effect.
    By subdividing all the variables with the estimated production function and comparing total factor productivity by selecting the comparable targets for agglomeration and non-concentrated areas corporate, concentrated areas showed a higher total factor productivity.
    In the end, it was analyzed that the IT & BT companies in Jeju during 2009 that were located in agglomeration has a higher productivity.
    As a results of analyzing the main factors that decide the total factor productivity, small in size and old corporate are predict to have a more efficient productivity.
    In this study, cross-section data was used as building time series data was inadequate and in analyzing the main factors for results, there weren’t many variables to use as the variables that are expected to effect corporate productivity were not used, there were limited individual corporate data.
    In the future, on setting up the model, to analyze the total factor productivity that reflect the size of economy and overcome the study limit after building the time series data through the same study we will leave it as an assignment to gain stronger credibility.

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    목차 (Table of Contents)

    • Ⅰ. 서 론 1
    • 1. 연구의 배경 및 목적 1
    • 2. 연구의 범위 및 방법 3
    • Ⅱ. 이론적 배경 및 선행연구 검토 4
    • Ⅰ. 서 론 1
    • 1. 연구의 배경 및 목적 1
    • 2. 연구의 범위 및 방법 3
    • Ⅱ. 이론적 배경 및 선행연구 검토 4
    • 1. 이론적 배경 4
    • 1) 산업집적 4
    • 2) 기업입지 6
    • 3) 지식기반산업 특징 11
    • 4) 지식기반산업 입지 특징 12
    • 2. 선행연구 검토 15
    • 1) 산업집적경제의 요인에 관련된 선행연구 검토 15
    • Ⅲ. 산업단지 현황 및 특성 20
    • 1. 산업단지 개요 20
    • 1) 산업단지의 정의 및 유형 20
    • 2) 산업입지 및 산업단지의 경향 변화 21
    • 2. 전국 산업단지 현황 22
    • 1) 현황 22
    • 2) 추이 22
    • 3. 전국 산업단지의 운용 성과 26
    • 1) 산업단지 원단위 변화 추이 26
    • 2) 산업단지 생산성 분석 29
    • 4. 제주첨단과학기술단지 현황 및 특성 32
    • 1) 입주기업 수 및 업종 33
    • 2) 면적 34
    • 3) 기업규모(직원수) 36
    • 4) 기업나이 38
    • 5) 기업 이전경로 및 이전형태 39
    • 6) 소결 45
    • Ⅳ. 분석모형 및 분석자료 46
    • 1. 총요소생산성의 개념 46
    • 1) 단일요소생산성 46
    • 2) 총요소생산성 47
    • 2. 총요소생산성의 측정방법 48
    • 3. 본 연구의 분석모형 및 변수 설정 51
    • 1) 변수 선정 51
    • 2) 분석모형 설정 52
    • 3) 분석 대상 및 변수 자료 선정 53
    • Ⅴ. 기업 입지에 따른 총요소생산성 분석 55
    • 1. 기초통계량 55
    • 1) 기초통계량 55
    • 2) 상관관계 분석 58
    • 2. 총요소생산성 추정 62
    • 1) 생산함수 추정 결과 62
    • 2) 총요소생산성 추정 결과 64
    • 3) 총요소생산성 결정 요인 분석 67
    • Ⅵ. 결 론 72
    • 1. 분석결과 및 요약 72
    • 2. 연구의 한계 및 향후 과제 73
    • 참 고 문 헌 75
    • ABSTRACT 79
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