Grey Relational Analysis and Analytic Hierarchy process for Health Evaluation Center

碩士 === 靜宜大學 === 管理碩士在職專班 === 95 === The main purposes of health examinations are to discover diseases and their relative cures in early stages. However, regular health examinations have not been taken seriously by people due to lack of time, or various other reasons. Some diseases cause human bodies...

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Bibliographic Details
Main Authors: Wen-chun Sung, 宋文君
Other Authors: Chen-Fong Wu
Format: Others
Language:zh-TW
Published: 2007
Online Access:http://ndltd.ncl.edu.tw/handle/72352057244200077314
Description
Summary:碩士 === 靜宜大學 === 管理碩士在職專班 === 95 === The main purposes of health examinations are to discover diseases and their relative cures in early stages. However, regular health examinations have not been taken seriously by people due to lack of time, or various other reasons. Some diseases cause human bodies to deteriorate over a very short period of time. For instance, some types of cancer may take from just six to twelve months between the first symptoms and the last phases. Thus, regular health examinations are of vital importance for true understanding and control of personal health conditions. Health examinations have been part of preventive medicine of which the purposes are to prevent and detect, and by which early determination of a certain disease is necessary for appropriate treatments. Therefore, health examinations have been considered effective and medically correct, as well as educationally positive. The theme of the present research is based on health examination users selecting examinations centers and Grey Relational Analysis as well as Analytic Hierarchy Process as research tools. Through questionnaire, the opinion and willingness of purchase of health center users are determined, which are then followed by Grey Relational Analysis for filtering and finally Analytic Hierarchy Process for ordering. The study is intended for a sales reference and strategy. Finally, we apply Grey-Hierarchy Selection System to save data analysis time and lessen human resource waste.