Browsing by Author "Chang, I-Chiu"

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Do Patients' Privacy Concerns Influence Their Intention toward Medical Image Exchange Consent in Taiwan?
(2020-03-01)
Tseng, Hsiao-Ting
;
Hung, Won-Fu
;
Hwang, Hsin-Ginn
;
Chang, I-Chiu
;
資訊管理與財務金融系註：原資管所+財金所
The primary purpose of this study was to examine patients' concerns surrounding information privacy and their intention toward medical image exchange consent. Patients' concerns about information privacy in terms of collection, unauthorized access, errors and secondary use all have significant relationships with patients' intention toward medical image exchange consent in Taiwan. Trust is the foundation for both parties. In this study, we aimed to determine the moderating effect of trust in order to examine patients' intention toward medical image exchange consent under the influence of their information privacy concerns. Three hundred and fifty patients responded to the survey, which yielded a 92.3% response rate. The results of data analysis revealed that patients' information privacy concerns had no significant relationship with patients' intention toward medical image exchange consent. After considering the moderating effect of trust, patients' information privacy concerns do have a significant relationship with patients' intention toward medical image exchange consent, however, the R-square was only 4.5%. Based on this research result, we modified the research framework in order to examine patients' information privacy concerns in terms of collection/non-collection. The R-square of the modified framework was 18.6%, and both collection and non-collection had significant relationships with patients' intention toward medical image exchange consent. Finally, the implications, limitations and future research have been discussed.
Factors influencing Chinese tourists\' intentions to use the Taiwan Medical Travel App
(2016-05-01)
Chang, I-Chiu
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Chou, Pei-Chin
;
Yeh, Ralph Keng-Jung
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Tseng, Hsiao-Ting
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資訊管理與財務金融系註：原資管所+財金所
Global economic progress has resulted in the rapid development of transportation, finance, and tourism. Consequently, medical tourism has emerged as a new and booming market. Hospitals in Taiwan have excellent medical quality and highly-ranked information technology. The geographical, cultural, and linguistic proximity between Taiwan and Mainland China further enhances the appeal of medical tourism in Taiwan as an option for patients from China. Thus, the Taiwanese government has actively modified and improved various aspects of its tourism infrastructure, such as visa regulations, marketing policies, and technologies, to attract medical tourists. One important technology marketing method in its arsenal is the Taiwan Medical Travel App (TMT App), which can be downloaded to mobile devices. The TMT App focuses on promoting Taiwan\'s medical tourism. Nevertheless, the effectiveness of the TMT App and the usage intention of Chinese patients have not been evaluated. This study proposes a research model based on a literature review to explore the factors that influence Chinese patients\' intention to use the TMT App. The research model is then validated using questionnaires and statistical analyses. The results can be used as a reference to enhance customers\' intention to use the TMT App and to improve this and other similar Apps. (C) 2015 Elsevier Ltd. All rights reserved.
IoT-Based Image Recognition System for Smart Home-Delivered Meal Services
(2017-07-01)
Tseng, Hsiao-Ting
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Hwang, Hsin-Ginn
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Hsu, Wei-Yen
;
Chou, Pei-Chin
;
Chang, I-Chiu
Population ageing is an important global issue. The Taiwanese government has used various Internet of Things (IoT) applications in the 10-year long-term care program 2.0. It is expected that the efficiency and effectiveness of long-term care services will be improved through IoT support. Home-delivered meal services for the elderly are important for home-based long-term care services. To ensure that the right meals are delivered to the right recipient at the right time, the runners need to take a picture of the meal recipient when the meal is delivered. This study uses the IoT-based image recognition system to design an integrated service to improve the management of image recognition. The core technology of this IoT-based image recognition system is statistical histogram-based k-means clustering for image segmentation. However, this method is time-consuming. Therefore, we proposed using the statistical histogram to obtain a probability density function of pixels of a figure and segmenting these with weighting for the same intensity. This aims to increase the computational performance and achieve the same results as k-means clustering. We combined histogram and k-means clustering in order to overcome the high computational cost for k-means clustering. The results indicate that the proposed method is significantly faster than k-means clustering by more than 10 times.