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題名 電子化醫療服務採用：兩階段分析
E-health Service Adoption: A Two-phase Analysis作者 林顯宗
Lin, Hsien-Tsung貢獻者 張欣綠
Chang, Hsin-Lu
林顯宗
Lin, Hsien-Tsung關鍵詞 E-health
Service concept
Elaboration likelihood model
Symbolic adoption
Use adoption日期 2020 上傳時間 3-八月-2020 17:35:36 (UTC+8) 摘要 E-health has been comprehensively discussed over the past few years. Although e-health’s potential to improve quality of care has been well-discussed in past literature, the usage of e-health is still low. Therefore, we aim to examine the items that can persuade people to try e-health services and those items that can persuade people to sustain the use of e-health. We integrate the service concept, elaboration likelihood model (ELM) and symbolic adoption model to examine users’ attitude changes across different adoption phases. Moreover, individual differences, including user involvement and expertise source, are considered moderators in this paper. Our survey respondents include two types of users: potential and experienced users. In our study, we quantify the influence of e-health items and the relationship between these items and the adoption process, distinguish which items can arouse users’ interest the most, and rationalize resource allocation when hospitals provide new e-health services. 參考文獻 Almeida, J. P., Van Sinderen, M., Pires, L. F., & Quartel, D. (2003). A systematic approach to platform-independent design based on the service concept. 7th IEEE International Enterprise Distributed Object Computing Conference, 112–123.Anderson, S., Pearo, L. K., & Widener, S. K. (2008). Drivers of service satisfaction: Linking customer satisfaction to the service concept and customer characteristics. Journal of Service Research, 10(4), 365–381.Angst, C. M., & Agarwal, R. (2009). Adoption of electronic health records in the presence of privacy concerns: The elaboration likelihood model and individual persuasion. MIS Quarterly, 33(2), 339–370.Angst, C. M., Block, E. S., D’Arcy, J., & Kelley, K. (2017). When do it security investments matter? Accounting for the influence of institutional factors in the context of healthcare data breaches. MIS Quarterly, 41(3), 893–916.Bansal, G., Zahedi, F. M., & Gefen, D. (2015). The role of privacy assurance mechanisms in building trust and the moderating role of privacy concern. European Journal of Information Systems, 24(6), 624–644.Bhattacherjee, A., & Sanford, C. (2006). Influence processes for information technology acceptance: An elaboration likelihood model. MIS Quarterly, 30(4), 805–825.Bigelow, B., & Arndt, M. (2005). Transformational change in health care: changing the question. Hospital Topics, 83(2), 19–26.Bitner, M. J., & Obermiller, C. (1985). The elaboration likelihood model: Limitations and extensions in marketing. Advances in Consumer Research, 12(1), 420–425.Bohlen, J. M., & Beal, G. M. (1957). The Diffusion Process. Special Report, Agriculture Extension Service, 18, 56–77.Box, G. E. P. (1949). A General Distribution Theory for a Class of Likelihood Criteria. Biometrika, 36(3–4), 317–346.Burton-Jones, A., & Volkoff, O. (2017). How can we develop contextualized theories of effective use? A demonstration in the context of community-care electronic health records. Information Systems Research, 28(3), 468–489.Büyüköztürk, Ş., & Çokluk-Bökeoǧlu, Ö. (2008). Discriminant function analysis: Concept and application. Eurasian Journal of Educational Research, 33, 73–92.Chaiken, S., & Maheswaran, D. (1994). Heuristic processing can bias systematic processing: Effects of source credibility, argument ambiguity, and task importance on attitude judgment. Journal of Personality and Social Psychology, 66(3), 460-473.Chang, H. L., Shaw, M. J., Lai, F., Ko, W. J., Ho, Y. L., Chen, H. S., & Shu, C. C. (2010). U-Health: An example of a high-quality individualized healthcare service. Personalized Medicine, 7(6), 677–687.Chang, H. L., Szu, W. W., & Tu, Y. J. (2017). 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國立政治大學
資訊管理學系
107356009資料來源 http://thesis.lib.nccu.edu.tw/record/#G0107356009 資料類型 thesis dc.contributor.advisor 張欣綠 zh_TW dc.contributor.advisor Chang, Hsin-Lu en_US dc.contributor.author (作者) 林顯宗 zh_TW dc.contributor.author (作者) Lin, Hsien-Tsung en_US dc.creator (作者) 林顯宗 zh_TW dc.creator (作者) Lin, Hsien-Tsung en_US dc.date (日期) 2020 en_US dc.date.accessioned 3-八月-2020 17:35:36 (UTC+8) - dc.date.available 3-八月-2020 17:35:36 (UTC+8) - dc.date.issued (上傳時間) 3-八月-2020 17:35:36 (UTC+8) - dc.identifier (其他 識別碼) G0107356009 en_US dc.identifier.uri (URI) http://nccur.lib.nccu.edu.tw/handle/140.119/130977 - dc.description (描述) 碩士 zh_TW dc.description (描述) 國立政治大學 zh_TW dc.description (描述) 資訊管理學系 zh_TW dc.description (描述) 107356009 zh_TW dc.description.abstract (摘要) E-health has been comprehensively discussed over the past few years. Although e-health’s potential to improve quality of care has been well-discussed in past literature, the usage of e-health is still low. Therefore, we aim to examine the items that can persuade people to try e-health services and those items that can persuade people to sustain the use of e-health. We integrate the service concept, elaboration likelihood model (ELM) and symbolic adoption model to examine users’ attitude changes across different adoption phases. Moreover, individual differences, including user involvement and expertise source, are considered moderators in this paper. Our survey respondents include two types of users: potential and experienced users. In our study, we quantify the influence of e-health items and the relationship between these items and the adoption process, distinguish which items can arouse users’ interest the most, and rationalize resource allocation when hospitals provide new e-health services. en_US dc.description.tableofcontents CHAPTER ONE: INTRODUCTION 1CHAPTER TWO: CONCEPTUAL BACKGROUND 32.1. Service concept 32.2. Symbolic adoption 52.3. Elaboration likelihood model 7CHAPTER THREE: RESEARCH FRAMEWORK 113.1. The Central and Peripheral Cues of the ELM 113.2. Symbolic Adoption in the Concept of the ELM 123.3. Use Adoption in the Concept of the ELM 133.4. The moderator of the ELM 14CHAPTER FOUR: RESEARCH METHODOLOGY 174.1 Service introduction 174.2 Data Collection 224.3 Instrument 234.4 Instrument Validation 24CHAPTER FIVE: DATA ANALYSIS AND RESULT 295.1 Mean Value Analysis 295.2 Discriminant function analysis 31CHAPTER SIX: DISCUSSION 46CHAPTER SEVEN: CONCLUSION 497.1 Summary 497.2 Contributions 507.3 Limitations 50REFERENCE 52APPENDIX A. QUESTIONNAIRE OF PROSPECTIVE CUSTOMERS (ENGLISH VERSION) 59APPENDIX B. QUESTIONNAIRE OF THE FEEDBACK OF CASE (ENGLISH VERSION) 62APPENDIX C. QUESTIONNAIRE OF PROSPECTIVE CUSTOMERS (CHINESE VERSION) 65APPENDIX D. QUESTIONNAIRE OF THE FEEDBACK OF CASE (CHINESE VERSION) 68 zh_TW dc.format.extent 5134796 bytes - dc.format.mimetype application/pdf - dc.source.uri (資料來源) http://thesis.lib.nccu.edu.tw/record/#G0107356009 en_US dc.subject (關鍵詞) E-health en_US dc.subject (關鍵詞) Service concept en_US dc.subject (關鍵詞) Elaboration likelihood model en_US dc.subject (關鍵詞) Symbolic adoption en_US dc.subject (關鍵詞) Use adoption en_US dc.title (題名) 電子化醫療服務採用：兩階段分析 zh_TW dc.title (題名) E-health Service Adoption: A Two-phase Analysis en_US dc.type (資料類型) thesis en_US dc.relation.reference (參考文獻) Almeida, J. P., Van Sinderen, M., Pires, L. F., & Quartel, D. (2003). A systematic approach to platform-independent design based on the service concept. 7th IEEE International Enterprise Distributed Object Computing Conference, 112–123.Anderson, S., Pearo, L. K., & Widener, S. K. (2008). Drivers of service satisfaction: Linking customer satisfaction to the service concept and customer characteristics. Journal of Service Research, 10(4), 365–381.Angst, C. M., & Agarwal, R. (2009). Adoption of electronic health records in the presence of privacy concerns: The elaboration likelihood model and individual persuasion. MIS Quarterly, 33(2), 339–370.Angst, C. M., Block, E. S., D’Arcy, J., & Kelley, K. (2017). When do it security investments matter? Accounting for the influence of institutional factors in the context of healthcare data breaches. MIS Quarterly, 41(3), 893–916.Bansal, G., Zahedi, F. M., & Gefen, D. (2015). The role of privacy assurance mechanisms in building trust and the moderating role of privacy concern. European Journal of Information Systems, 24(6), 624–644.Bhattacherjee, A., & Sanford, C. (2006). Influence processes for information technology acceptance: An elaboration likelihood model. MIS Quarterly, 30(4), 805–825.Bigelow, B., & Arndt, M. (2005). Transformational change in health care: changing the question. Hospital Topics, 83(2), 19–26.Bitner, M. J., & Obermiller, C. (1985). The elaboration likelihood model: Limitations and extensions in marketing. Advances in Consumer Research, 12(1), 420–425.Bohlen, J. M., & Beal, G. M. (1957). The Diffusion Process. Special Report, Agriculture Extension Service, 18, 56–77.Box, G. E. P. (1949). A General Distribution Theory for a Class of Likelihood Criteria. Biometrika, 36(3–4), 317–346.Burton-Jones, A., & Volkoff, O. (2017). How can we develop contextualized theories of effective use? A demonstration in the context of community-care electronic health records. Information Systems Research, 28(3), 468–489.Büyüköztürk, Ş., & Çokluk-Bökeoǧlu, Ö. (2008). Discriminant function analysis: Concept and application. Eurasian Journal of Educational Research, 33, 73–92.Chaiken, S., & Maheswaran, D. (1994). Heuristic processing can bias systematic processing: Effects of source credibility, argument ambiguity, and task importance on attitude judgment. Journal of Personality and Social Psychology, 66(3), 460-473.Chang, H. L., Shaw, M. J., Lai, F., Ko, W. J., Ho, Y. L., Chen, H. S., & Shu, C. C. (2010). U-Health: An example of a high-quality individualized healthcare service. Personalized Medicine, 7(6), 677–687.Chang, H. L., Szu, W. W., & Tu, Y. J. (2017). Drivers of eHealth adoption: Linking eHealth adoption to service concept. International Conference on Electronic Business (ICEB), 85–92.Chen, S. H., Wen, P. C., & Yang, C. K. (2014). Business concepts of systemic service innovations in e-Healthcare. Technovation, 34(9), 513–524.Chen, Y., Yang, L., Zhang, M., & Yang, J. (2018). Central or peripheral? Cognition elaboration cues’ effect on users’ continuance intention of mobile health applications in the developing markets. International Journal of Medical Informatics, 116, 33–45.Cheung, M.-Y. C., Sia, C.-L., & Kuan, K. K. Y. (2012). Is This Review Believable? A Study of Factors Affecting the Credibility of Online Consumer Reviews from an ELM Perspective. Journal of the Association for Information Systems, 13(8), 618–635.Cho, S., Mathiassen, L., & Nilsson, A. (2008). Contextual dynamics during health information systems implementation: an event-based actor-network approach. European Journal of Information Systems, 17, 614–630.Corchado, J. M., Bajo, J., Paz, Y. de, & Tapia, D. I. (2008). Intelligent environment for monitoring Alzheimer patients, agent technology for health care. Decision Support Systems, 44(2), 382–396.Cortina, J. M. (1993). What Is Coefficient Alpha? An Examination of Theory and Applications. Journal of Applied Psychology, 78(1), 98–104.Dinev, T. (2014). Why would we care about privacy? European Journal of Information Systems, 23, 97–102.Dinoff, B. L., & Kowalski, R. M. (1999). Reducing aids risk behavior: The combined efficacy of protection motivation theory and the elaboration likelihood model. Journal of Social and Clinical Psychology, 18(2), 223–239.Dutta-Bergman, M. J. (2004). The impact of completeness and web use motivation on the credibility of e-health information. Journal of Communication, 54(2), 253–269.Edvardsson, B., Gustafsson, A., & Roos, I. (2005). Service portraits in service research: A critical review. International Journal of Service Industry Management, 16(1), 107–121.Edvardsson, B., & Olsson, J. (1996). Key concepts for new service development. Service Industries Journal, 16(2), 140–164.Farzandipour, M., Mohamadian, H., & Sohrabi, N. (2016). Intention of Continuing to use the Hospital Information System: Integrating the elaboration-likelihood, social influence and cognitive learning. Electronic Physician, 8(12), 3385–3394.Fields, D. M., & Greco, A. J. (1991). A Model Of The Adoption Process For Revolutionary Product Innovations. JOURNAL OF MANAGERIAL ISSUES, 3(4), 528–548.Friedman, J. H. (1989). Regularized discriminant analysis. Journal of the American Statistical Association, 84(405), 165–175.Fu, F., & Elliott, M. (2013). The moderating effect of perceived product innovativeness and product knowledge on new product adoption: An integrated model. Journal of Marketing Theory and Practice, 21(3), 257–272.Fynes, B., & Lally, A. M. (2008). Innovation in Services: From Service Concepts to Service Experiences. 329–333.Goh, J. M., Gao, G. G., & Agarwal, R. (2016). The creation of social value: Can an online health community reduce rural-urban health disparities? MIS Quarterly, 40(1), 247–263.Goldstein, S. M., Johnston, R., Duffy, J., & Raod, J. (2002). The service concept: the missing link in service design research? Journal of Operations Management, 20(2), 121–134.Grossbart, S. L., Mittelstaedt, R. A., & DeVere, S. P. (1976). Customer Stimulation Needs and Innovative Shopping Behavior: the Case of Recycled Urban Places. ACR North American Advances.Hair, J. F., Black, W. C., Babin, B. J., & Anderson, R. E. (2010). 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