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製造企業에서의 生産性 向上을 위한 統計的 技法의 適用方案에 관한 硏究
Study on the application methods of statistical techniques to improve the productivity of manufacturing firms
제조기업에서의 생산성 향상을 위한 통계적 기법의 적용방안에 관한 연구

  • 간행물
    기업경영연구 바로가기
  • 권호(발행년)
    제3권 제1호(제4집) (1996.05) 바로가기
  • 페이지
    pp.47-78
  • 저자
    黃末東
  • 언어
    한국어(KOR)
  • URL
    https://www.earticle.net/Article/A295981

원문정보

초록

영어
This paper reviews several techinques and theorems which can be served as a foundation for achieving managerial goals, aiming at productive, reasinable, efficient and scientific activity of firms and deciding the managerial plans such as the production plan, personnel plan, purchase plan and financial plan of firms. Thoes techniques and theorems deals with multivariate solution techniques, the degree of belongs of fuzzy set, quantitative theorem of fuzzy events, Ⅰ, Ⅱ, Ⅲ, and Ⅳ. Especially, regression equation, auto regression and auto correlation of multivariate solution techniques can play critical roles in making decisions and forecast of production, purchase, demand and supply of firms. Without precise forecast of their production and sale, firms fail to achieve their managrial goals since they could lose profit opportunities. This paper suggests various techniques which can make a contribution to the solution of these probles. In particular, new quantitative theorems of fuzzy enents, Ⅰ, Ⅱ, Ⅲ, Ⅳ are discussed consistently. It should be stressed in those theorems that dealing events should have a clear set and a reasonable degree of belongs. There are no clear critria for classifying firms into information industry and th non-manufacturing industry. In analyzing information industry and venture business, we whould consider the level of creteria for classifying firms into information industry and venture business. Especially, if the degree of belongings has value, 1 or 0, the techniques with which this paper deals are not the extension of the quantitative theorems of fuzzy enents as mians of the previous quantitative theorems.

목차

I. 序論
 II. 要因分析과 正選相關分析의 諸理論
  1. 要因分析의 槪念
  2. 要因分析의 類型과 妥當性 및 信賴性의 檢證
  3. 要因分析의 假定과 適用可能性의 檢證
  4. 正準相關分析의 諸理論
  5. 正準 相關分析 技法의 目的과 節次
  6. 正準相關分析의 妥當性 檢證과 限界点
 III. 多變量 共通分散分析과 多童線型判l別 分析
  1. 多變量 共通分散分析의 槪念
  2. 多變量 分散分析의 假定과 妥當性 檢證
  3. 多量 模型判別分析의 妥當性 檢證과 對凝方案
 IV. 數量化 理論에 의한 最適데이터 解釋의 事例硏究
  1. 數量化 理論에 I 類-質的데이터에 의한 回歸分析의 事例
  2. 數量化 理論에 II 類-質的데이터에 의한 判別分析의 事例
  3. 數量化 理論에 III 類-質的데이터에 의한 正準相關의 事例
 V. 結論
 참고문헌
 Abstract

저자

  • 黃末東 [ 황말동 | 慶南大學校 經商大學 經營學科 敎授 ]

참고문헌

자료제공 : 네이버학술정보

    간행물 정보

    • 간행물
      기업경영연구 [Korean Corporation Management Review]
    • 간기
      격월간
    • pISSN
      1229-957X
    • 수록기간
      1994~2026
    • 등재여부
      KCI 등재
    • 십진분류
      KDC 325 DDC 658