The Application of AHP Method on Exploring the Potential Use of Japan’s Nursing Care Robots in Taiwan

碩士 === 淡江大學 === 亞洲研究所碩士班 === 103 === Japan has already been a super-aging society where one out of four persons are 65 aged and over. In facing the rapid aging of society, the application of technology on supporting such a society is indispensible. In order to enhance the labor productivity and effi...

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Bibliographic Details
Main Authors: Kuei-Lan Tsai, 蔡桂蘭
Other Authors: 蔡錫勲
Format: Others
Language:zh-TW
Published: 2015
Online Access:http://ndltd.ncl.edu.tw/handle/4zz75r
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Summary:碩士 === 淡江大學 === 亞洲研究所碩士班 === 103 === Japan has already been a super-aging society where one out of four persons are 65 aged and over. In facing the rapid aging of society, the application of technology on supporting such a society is indispensible. In order to enhance the labor productivity and efficiency at the caring places, reduce the nursing care expenses and caregiver’s burden, and solve the shortage of nursing care workers, Japan government has started a project for the Development and Introduction of Robotic Devices for Nursing Care. Though the increase in elderly is more rapid in Taiwan, the development of nursing care robots for elderly in Taiwan is still in the earlier stage. Hence, this thesis attempts to explore the potential use of Japan’s nursing care robots in Taiwan for the aging problem. The Analytic Hierarchy Process (AHP) method is used to evaluate the weighting scores and identify the priority of the factors affecting the nursing care robots’ potential use in Taiwan. Based on the results, it is suggested that the first three priority factors significantly influencing the development of nursing care robots for elderly in Taiwan are “international safety certification”, “establishment of product safety standard” and “setup of risk assessment”. They are followed by “guaranteed operational safety”, “maintenance cost”, “provision of caring information and training” and “product sale price”. The factors “government subsidy”, “industry-academic-government corporation” and “tax preference” are the last three standing having least influence among the seventeen factors.