메뉴 건너뛰기
.. 내서재 .. 알림
소속 기관/학교 인증
인증하면 논문, 학술자료 등을  무료로 열람할 수 있어요.
한국대학교, 누리자동차, 시립도서관 등 나의 기관을 확인해보세요
(국내 대학 90% 이상 구독 중)
로그인 회원가입 고객센터 ENG
주제분류

추천
검색
질문

논문 기본 정보

자료유형
학술저널
저자정보
Kiyoshi Nagata (Daito Bunka University) Masashi Umezawa (Daito Bunka University) Michio Amagasa (Daito Bunka University) Fuyume Sai (Tokyo University of Science)
저널정보
대한산업공학회 Industrial Engineering & Management Systems Industrial Engineering & Management Systems 제7권 제3호
발행연도
2008.12
수록면
245 - 256 (12page)

이용수

표지
📌
연구주제
📖
연구배경
🔬
연구방법
🏆
연구결과
AI에게 요청하기
추천
검색
질문

초록· 키워드

오류제보하기
In order to cope with the ill-defined problem of human behavior being immanent uncertainty, several methodologies have been studied in game theoretic, social psychological and political science frameworks. As methods to arrange system elements systematically and draw out the consenting structural model concretively, ISM, FSM and DEMATEL based on graph theory etc. have been proposed. In this paper, we propose a modified structural modeling method to recognize the nature of problem. We introduce the statistical method to adjust the establishment levels in group decision situation. From this, it will become possible to obtain effectively and smoothly the structural model of group members in comparison with the traditional methods. Further we propose a procedure for achieving the consenting structural model of group members based on the structural modeling method. By applying the method to recognize the nature of ill-defined problems, it will be possible to solve the given problem effectively and rationally. In order to inspect the effectiveness of the method, we conduct a practical problem as an empirical study: “Behavior analysis of passengers for the Joban line of East Japan Railway Company after new railway service of Tsukuba Express opened”.

목차

Abstract
1. INTRODUCTION
2. GROUP DECISION MAKING BASED ON STRUCTURAL MODELING METHOD
3. BEHAVIOR ANALYSIS OF PASSENGERS FOR EAST JAPAN RAILWAY COMPANY
4. CONCLUSION AND REMARKS
ACKNOWLEDGMENT
REFERENCES

참고문헌 (0)

참고문헌 신청

함께 읽어보면 좋을 논문

논문 유사도에 따라 DBpia 가 추천하는 논문입니다. 함께 보면 좋을 연관 논문을 확인해보세요!

이 논문의 저자 정보

이 논문과 함께 이용한 논문

최근 본 자료

전체보기

댓글(0)

0

UCI(KEPA) : I410-ECN-0101-2013-530-002615083