博碩士論文 107421033 詳細資訊




以作者查詢圖書館館藏 以作者查詢臺灣博碩士 以作者查詢全國書目 勘誤回報 、線上人數:52 、訪客IP:3.15.3.154
姓名 許珈儀(HSU,CHIA-YI)  查詢紙本館藏   畢業系所 企業管理學系
論文名稱 自助服務系統使用意圖之研究 - 整合科技準備度、自我決定論與現狀偏好理論
(Intention to Use Self-Service Technologies – The Integration of Technology Readiness, Self-Determination Theory and Status Quo Bias Theory)
相關論文
★ 二氧化鈦技術生命週期之研究★ 整體後勤業參與同步工程於產品開發績效關係之研究—以中科院為例
★ 筆記型電腦之IFA/PIFA天線技術生命週期分析★ 國籍航空公司經營績效分析-以資料包絡分析方法分析
★ 從專利分析看3D IC技術與市場發展★ 影響企業導入電子發票系統成效之因素探討
★ 影響企業導入數位學習成功因素之探討-以個案公司為例★ 產品生命週期管理系統導入成功要素之探討--以S科技公司為例--
★ 組織創新能力影響因素研究★ 製 造 業 閒 置 資 產 轉 售 平 台 製造業閒置資產轉售平台-以廣達電腦股份有限公司為例
★ 供應商先行者優勢探討-以宸鴻科技為例★ 團隊領導者創新特質與開放式創新專案關係之研究
★ 從商業生態系統談樞紐者策略-以Apple 與Nokia 為例★ 個人電腦的競爭與發展策略-以台灣電子產業為例
★ 應用兩階段資料包絡分析法評估高級職業學校之經營績效★ ERP導入的促進因素:使用者觀點
檔案 [Endnote RIS 格式]    [Bibtex 格式]    [相關文章]   [文章引用]   [完整記錄]   [館藏目錄]   至系統瀏覽論文 ( 永不開放)
摘要(中) 近年來隨著網路科技的進步與消費行為的改變,各種業態不斷推陳出新,自助服務科技 (Self-Service Technologies, SSTs)提供零售服務所衍生出的資訊服務和產品,似乎改變了消費者的生活型態,但是否為大眾普遍接受,成了值得關注的議題。有別於過去討論使用者對自助服務系統使用意圖之研究,本研究將科技準備度同時從接受面和抑制面觀察對新技術的使用意圖,並且整合自我決定論及現狀偏好理論延展準備度之能力與意願 (Willingness)層面,最後加入情境因素進一步觀察自助和人助關係,以釐清服務接觸影響使用者對科技接受之使用意圖。 本研究採用問卷調查法,共計回收有效問卷 514份,以線性結構方程式進行研究假說之分析。本研究經由實證分析結果發現,自主性與慣性存在中介效果,代表消費者的科技準備取決於消費者的意願,才能促進自助服務系統的使用。勝任感與轉換成本不具有中介效果,此外,轉換成本與使用意圖呈現正相關,表示現代人相信自己的能力能夠完成目標,不會因為轉換成本存在就不去使用自助服務系統,樂於接受新科技的挑戰。另一方面,人際互動具有顯著的調節效果,代表服務人員之推薦引導的使用示範效果,能夠促進消費者的使用意圖。本研究的研究結果能夠提供學術與企業對於未來人機配置的參考方向與建議。
摘要(英) In recent years, because of the advancement of technology and changes in consumer behavior, Self-Service Technologies (SSTs) provides information and products derived from retail services to consumers. It has become a topic worthy of our attention. As far as we know, previous studies have focused on how to enable user’s intention to use self-service technologies. This study is based on Technology Readiness to understand customers’ intention from the drivers and inhibitors, and integrating Self-Determination Theory and Status Quo Bias Theory to extend factor of ability and willingness. Additionally, we use situational factor to clarify the factor service encounter influencing the intention to use.
The research model was tested with data collected from 514 potential users, and using structural equation modeling (SEM) to validate the causal relationship between variables. The results of this study were summarized as follows. Autonomy and inertia have mediating effect. It means that the acceptance of self-service technology depends on customers’ willingness. Competence and switching cost do not exist mediating effect. Moreover, switching cost has the positive effect on intention to use. It means that people believe that their ability to achieve their goals, they are willing to accept the challenges of new technology not because of existing of switching cost. Besides, need for human interaction has the significant moderating effect. We conclude that demonstration effect of staff’s guidance could increase intention to use. The results of this study could provide a reference on academic and practical aspects.
關鍵字(中) ★ 自助服務系統
★ 科技準備度
★ 自我決定論
★ 現狀偏好理論
★ 人際互動
關鍵字(英) ★ Self-Service Technologies
★ Technology Readiness
★ Self-Determination Theory
★ Status Quo Bias Theory
★ Need for Human Interaction
論文目次 摘要 I
Abstract II
誌謝 III
圖目錄 VI
表目錄 VI
第一章 緒論 1
1.1研究背景與動機 1
1.2研究目的 4
1.3研究流程 5
第二章 文獻探討 6
2.1自助服務系統 6
2.2 科技準備度 7
2.2.1科技準備度之定義 7
2.2.2科技準備度之相關研究 8
2.3自我決定論 10
2.3.1自我決定論之定義 10
2.3.2自我決定論相關研究 11
2.4現狀偏好理論 12
2.4.1現狀偏好理論之定義 12
2.4.2現狀偏好理論之相關研究 14
2.5人際互動 15
第三章 研究方法 18
3.1研究架構與假說推論 18
3.2操作性定義與問卷設計 25
3.3研究對象與資料蒐集 30
3.4統計方法分析 30
3.4.1樣本資料分析 30
3.4.2 信度檢定 31
3.4.3 效度檢定 31
3.4.4 假設驗證 32
第四章 資料分析與研究討論 36
4-1 樣本基本資料分析 36
4-2 研究構面敘述性統計分析 40
4-3測量模型之信效度分析 42
4-3-1信度分析 42
4-3-2效度分析 43
4-4 結構模型路徑分析 47
4-4-1研究模型與模型配適度檢定 47
4-4-2路徑分析與實證討論 48
第五章 結論與建議 59
5.1結論 59
5.2研究意涵 60
5.2.1學術意涵 60
5.2.2實務建議 61
5.3研究現制與建議 62
參考文獻 64
附錄問卷 73
參考文獻 Amabile, T. M. (1993). What does a theory of creativity require?. Psychological Inquiry, 4(3), 179-181.
Anderson, J. C., & Gerbing, D. W. (1988). Structural equation modeling in practice: A review and recommended two-step approach. Psychological bulletin, 103(3), 411.
Aslanzadeh, M., & Keating, B. W. (2014). Inter-channel effects in multichannel travel services: Moderating role of social presence and need for human interaction. Cornell Hospitality Quarterly, 55(3), 265-276.
Bagozzi, R. P., & Yi, Y. (1988). On the evaluation of structural equation models. Journal of the Academy of Marketing Science, 16(1), 74-94.
Bandura, A. (1986). The explanatory and predictive scope of self-efficacy theory. Journal of Social and Clinical Psychology, 4(3), 359-373.
Biologics, B. (2018). Sales of Recombinant Therapeutic Antibodies & Proteins; Research and Markets Report.
Bisignani,G.(2011). Annual Report 2011 International Air Transport Association. International Air Transport Association.
Bolyard, E. A., Deitchman, S., Pearson, M. L., Shapiro, C. N., Tablan, O. C., & Williams, W. W. (1998). Guideline for infection control in health care personnel, 1998.
Browne, M. W., Cudeck, R., Bollen, K. A., & Long, J. S. (1993). Testing structural equation models.
Chen, K. C., & Jang, S. J. (2010). Motivation in online learning: Testing a model of self-determination theory. Computers in Human Behavior, 26(4), 741-752.
Chen, M. F., & Lin, N. P. (2018). Incorporation of health consciousness into the technology readiness and acceptance model to predict app download and usage intentions. Internet Research.
Chen, Q., Hu, J., Zhang, W., Evans, R., & Ma, X. (2020). Employee use of public social media: theories, constructs and conceptual frameworks. Behaviour & Information Technology, 1-25.
Chen, S. C., Chen, H. H., & Chen, M. F. (2009). Determinants of satisfaction and continuance intention towards self‐service technologies. Industrial Management & Data Systems.
Chen, S. C., Jong, D., & Lai, M. T. (2014). Assessing the relationship between technology readiness and continuance intention in an E-appointment system: relationship quality as a mediator. Journal of medical systems, 38(9), 76.
Chen, S. C., Liu, M. L., & Lin, C. P. (2013). Integrating technology readiness into the expectation–confirmation model: An empirical study of mobile services. Cyberpsychology, Behavior, and Social Networking, 16(8), 604-612.
Chen, Y., Yu, J., Yang, S., & Wei, J. (2018). Consumer’s intention to use self-service parcel delivery service in online retailing. Internet Research.
Chung, N., Han, H., & Joun, Y. (2015). Tourists’ intention to visit a destination: The role of augmented reality (AR) application for a heritage site. Computers in Human Behavior, 50, 588-599.
Claudy, M. C., Garcia, R., & O’Driscoll, A. (2015). Consumer resistance to innovation—a behavioral reasoning perspective. Journal of the Academy of Marketing Science, 43(4), 528-544.
Colby, C. L., & Parasuraman, A. (2001). Techno-Ready Marketing: How and Why Customers Adopt Technology. Simon and Schuster.
Curran, J. M., & Meuter, M. L. (2005). Self‐service technology adoption: comparing three technologies. Journal of services marketing.
Dabholkar, P. A. (1996). Consumer evaluations of new technology-based self-service options: an investigation of alternative models of service quality. International Journal of research in Marketing, 13(1), 29-51.
Dabholkar, P. A., Bobbitt, L. M., & Lee, E. J. (2003). Understanding consumer motivation and behavior related to self‐scanning in retailing. International Journal of Service Industry Management.
De Naeghel, J., Van Keer, H., Vansteenkiste, M., Haerens, L., & Aelterman, N. (2016). Promoting elementary school students′ autonomous reading motivation: Effects of a teacher professional development workshop. The Journal of Educational Research, 109(3), 232-252.
Deci, E. L., & Ryan, R. M. (2000). The" what" and" why" of goal pursuits: Human needs and the self-determination of behavior. Psychological inquiry, 11(4), 227-268.
Deci, E. L., & Ryan, R. M. (2002). Overview of self-determination theory: An organismic dialectical perspective. Handbook of self-determination research, 3-33.
Demircioglu, M. A. (2018). Examining the effects of social media use on job satisfaction in the Australian public service: Testing self-determination theory. Public Performance & Management Review, 41(2), 300-327.
Evans, K. R., Gremler, D. D., Schlacter, J. L., & Wolfe, W. G. (1995). The impact of salesperson socialization on organizational commitment, satisfaction, and performance in a professional service organization. Journal of Professional Services Marketing, 11(2), 139-156.
Feng, W., Tu, R., Lu, T., & Zhou, Z. (2019). Understanding forced adoption of self-service technology: the impacts of users’ psychological reactance. Behaviour & Information Technology, 38(8), 820-832.
Fornell, C., & Larcker, D. F. (1981). Structural equation models with unobservable variables and measurement error: Algebra and statistics. Journal of Marketing Research, 18(3), 382-388.
Garn, A. C., Matthews, M. S., & Jolly, J. L. (2010). Parental influences on the academic motivation of gifted students: A self-determination theory perspective. Gifted Child Quarterly, 54(4), 263-272.
Gong, X., Zhang, K. Z., Chen, C., Cheung, C. M., & Lee, M. K. (2020). Transition from web to mobile payment services: The triple effects of status quo inertia. International Journal of Information Management, 50, 310-324.
Guay, F., Senécal, C., Gauthier, L., & Fernet, C. (2003). Predicting career indecision: A self-determination theory perspective. Journal of counseling psychology, 50(2), 165.
Guilford, J. P. (1966). Intelligence: 1965 model. American Psychologist, 21(1), 20.
Hagger, M. S., Chatzisarantis, N. L., & Biddle, S. J. (2002). The influence of autonomous and controlling motives on physical activity intentions within the Theory of Planned Behaviour. British journal of health psychology, 7(3), 283-297.
Hajli, M. N. (2014). A study of the impact of social media on consumers. International Journal of Market Research, 56(3), 387-404.
Hanafizadeh, P., Behboudi, M., Koshksaray, A. A., & Tabar, M. J. S. (2014). Mobile-banking adoption by Iranian bank clients. Telematics and Informatics, 31(1), 62-78.
Hartnett, M. K. (2015). Influences that undermine learners’ perceptions of autonomy, competence and relatedness in an online context. Australasian Journal of Educational Technology, 31(1).
Hemdi, M. A., Rahman, S. A. S., Hanafiah, M. H., & Adanan, A. (2016, October). Airport self-service check-in: The influence of technology readiness on customer satisfaction. In Proceedings of the 3rd International Hospitality and Tourism Conference & 2nd International Seminar on Tourism, Bandung, Indonesia (pp. 10-12).
Hersey, P., & Blanchard, K. H. (1969). Life cycle theory of leadership. Training & Development Journal.
Ho, S. H., Yang, Z. K., Nagarajan, D., Chang, J. S., & Ren, N. Q. (2017). High-efficiency removal of lead from wastewater by biochar derived from anaerobic digestion sludge. Bioresource technology, 246, 142-149.
Hsieh, P. J., & Lin, W. S. (2018). Explaining resistance to system usage in the PharmaCloud: A view of the dual-factor model. Information & Management, 55(1), 51-63..
Hu, L. T., & Bentler, P. M. (1999). Cutoff criteria for fit indexes in covariance structure analysis: Conventional criteria versus new alternatives. Structural equation modeling: a multidisciplinary journal, 6(1), 1-55.
Jia, H., Wang, Y., Ge, L., Shi, G., & Yao, S. (2012). Asymmetric effects of regulatory focus on expected desirability and feasibility of embracing self‐service technologies. Psychology & Marketing, 29(4), 209-225.
Jong-Hyeon, K. I. M., & Park, J. W. (2019). The Effect of Airport Self-Service Characteristics on Passengers’ Technology Acceptance and Behavioral Intention.,17(5), 29-37.
Kang, M., & Gretzel, U. (2012). Perceptions of museum podcast tours: Effects of consumer innovativeness, Internet familiarity and podcasting affinity on performance expectancies. Tourism Management Perspectives, 4, 155-163.
Kang, M., & Gretzel, U. (2012). Perceptions of museum podcast tours: Effects of consumer innovativeness, Internet familiarity and podcasting affinity on performance expectancies. Tourism Management Perspectives, 4, 155-163.
Kaushik, A. K., & Rahman, Z. (2017). An empirical investigation of tourist’s choice of service delivery options. International Journal of Contemporary Hospitality Management.
Kaushik, A. K., Agrawal, A. K., & Rahman, Z. (2015). Tourist behaviour towards self-service hotel technology adoption: Trust and subjective norm as key antecedents. Tourism Management Perspectives, 16, 278-289.
Keller, E. F. (1979). Cognitive repression in contemporary physics. American Journal of Physics, 47(8), 718-721.
Khedhaouria, A., Thurik, R., Gurau, C., & Van Heck, E. (2016). Customers′ continuance intention regarding mobile service providers: A status quo bias perspective. Journal of Global Information Management (JGIM), 24(4), 1-21.
Kim, H. W., & Kankanhalli, A. (2009). Investigating user resistance to information systems implementation: A status quo bias perspective. MIS quarterly, 567-582.
Kim, J., & Gupta, P. (2012). Emotional expressions in online user reviews: How they influence consumers′ product evaluations. Journal of Business Research, 65(7), 985-992.
Kuo, K. M., Liu, C. F., & Ma, C. C. (2013). An investigation of the effect of nurses’ technology readiness on the acceptance of mobile electronic medical record systems. BMC medical informatics and decision making, 13(1), 88.
Kwon, H. S., & Chidambaram, L. (2000, January). A test of the technology acceptance model: The case of cellular telephone adoption. In Proceedings of the 33rd Annual Hawaii International Conference on System Sciences (pp. 7-pp). IEEE.
Lai, H. M., Hsiao, Y. L., & Hsieh, P. J. (2018). The role of motivation, ability, and opportunity in university teachers’ continuance use intention for flipped teaching. Computers & Education, 124, 37-50.
Lee, H. J., & Lyu, J. (2016). Personal values as determinants of intentions to use self-service technology in retailing. Computers in Human Behavior, 60, 322-332.
Lending, D., & Straub, D. W. (1997). Impacts of an Integrated Information Center on faculty end‐users: A qualitative assessment. Journal of the American Society for Information Science, 48(5), 466-471.
Li, M., & Huang, S. (2019). Understanding customers’ continuance intentions toward in-lobby self-service technologies. Frontiers in psychology, 10.
Li, Y., & Wang, X. (2017). Online social networking sites continuance intention: A model comparison approach. Journal of Computer Information Systems, 57(2), 160-168.
Li, Y., Wang, X., Lin, X., & Hajli, M. (2018). Seeking and sharing health information on social media: A net valence model and cross-cultural comparison. Technological Forecasting and Social Change, 126, 28-40.
Liang, B., & Scammon, D. L. (2013). Incidence of online health information search: a useful proxy for public health risk perception. Journal of Medical Internet Research, 15(6), e114.
Liaw, S. S., & Huang, H. M. (2011, May). A study of investigating learners attitudes toward e-learning. In 5th International Conference on Distance Learning and Education (Vol. 12, pp. 28-32).
Liaw, S. S., Huang, H. M., & Chen, G. D. (2007). Surveying instructor and learner attitudes toward e-learning. Computers & Education, 49(4), 1066-1080.
Liébana-Cabanillas, F., Sánchez-Fernández, J., & Muñoz-Leiva, F. (2014). Antecedents of the adoption of the new mobile payment systems: The moderating effect of age. Computers in Human Behavior, 35, 464-478.
Liljander, V., Gillberg, F., Gummerus, J., & Van Riel, A. (2006). Technology readiness and the evaluation and adoption of self-service technologies. Journal of Retailing and Consumer Services, 13(3), 177-191.
Lu, J., Wang, L., & Hayes, L. A. (2012). How do technology readiness, platform functionality and trust influence C2C user satisfaction. Journal of Electronic Commerce Research, 13(1), 50-69.
Mahmud, I., Ramayah, T., & Kurnia, S. (2017). To use or not to use: Modelling end user grumbling as user resistance in pre-implementation stage of enterprise resource planning system. Information Systems, 69, 164-179.
Marhefka, S. L., Turner, D., & Lockhart, E. (2019). Understanding Women′s Willingness to Use e-Health for HIV-Related Services: A Novel Application of the Technology Readiness and Acceptance Model to a Highly Stigmatized Medical Condition. Telemedicine and e-Health, 25(6), 511-518.
Massey, A. P., Khatri, V., & Montoya‐Weiss, M. M. (2007). Usability of online services: The role of technology readiness and context. Decision Sciences, 38(2), 277-308.
McNamara, G., & Bromiley, P. (1997). Decision making in an organizational setting: Cognitive and organizational influences on risk assessment in commercial lending. Academy of Management Journal, 40(5), 1063-1088.
Menard, P., Bott, G. J., & Crossler, R. E. (2017). User motivations in protecting information security: Protection motivation theory versus self-determination theory. Journal of Management Information Systems, 34(4), 1203-1230.
Meuter, M. L., Ostrom, A. L., Bitner, M. J., & Roundtree, R. (2003). The influence of technology anxiety on consumer use and experiences with self-service technologies. Journal of Business Research, 56(11), 899-906.
Mick, D. G., & Fournier, S. (1998). Paradoxes of technology: Consumer cognizance, emotions, and coping strategies. Journal of Consumer research, 25(2), 123-143.
Midgley, D. F., & Dowling, G. R. (1978). Innovativeness: The concept and its measurement. Journal of consumer research, 4(4), 229-242.
Morris, R. P. (2015). U.S. Patent No. 8,983,264. Washington, DC: U.S. Patent and Trademark Office.
Mudassir, M. M., & Rahim, A. U. (2012). Effect of Trustworthiness of Internet Merchants on Consumer Trust in Online Shopping with the Moderating Effect of Perceived Risk. Global Journal of Management And Business Research, 12(19).
Mulaik, S. A., James, L. R., Van Alstine, J., Bennett, N., Lind, S., & Stilwell, C. D. (1989). Evaluation of goodness-of-fit indices for structural equation models. Psychological bulletin, 105(3), 430.
Nikou, S. A., & Economides, A. A. (2017). Mobile-Based Assessment: Integrating acceptance and motivational factors into a combined model of Self-Determination Theory and Technology Acceptance. Computers in Human Behavior, 68, 83-95.
Ntoumanis, N. (2001). A self‐determination approach to the understanding of motivation in physical education. British journal of educational psychology, 71(2), 225-242.
Oh, J. C., & Yoon, S. J. (2014). Predicting the use of online information services based on a modified UTAUT model. Behaviour & Information Technology, 33(7), 716-729.
Oh, J. C., & Yoon, S. J. (2014). Theory‐based approach to factors affecting ethical consumption. International Journal of Consumer Studies, 38(3), 278-288.
P. A. Dabholkar, D. I. Thorpe, and J. O. Rentz, "A measure of service quality for retail stores: scale development and validation," Journal of the Academy of Marketing Science, vol. 24, no. 1, p. 3, 1996.
Parasuraman, A. (2000). Technology Readiness Index (TRI) a multiple-item scale to measure readiness to embrace new technologies. Journal of service research, 2(4), 307-320.
Parasuraman, A., & Colby, C. L. (2015). An updated and streamlined technology readiness index: TRI 2.0. Journal of service research, 18(1), 59-74.
Plouffe, C. R., Hulland, J. S., & Vandenbosch, M. (2001). Richness versus parsimony in modeling technology adoption decisions—understanding merchant adoption of a smart card-based payment system. Information Systems Research, 12(2), 208-222.
Polites, G. L., & Karahanna, E. (2012). Shackled to the status quo: The inhibiting effects of incumbent system habit, switching costs, and inertia on new system acceptance. MIS quarterly, 21-42.
Pradhan, M. K., Oh, J., & Lee, H. (2018). Understanding travelers’ behavior for sustainable smart tourism: A technology readiness perspective. Sustainability, 10(11), 4259.
Reinders, M. J., Dabholkar, P. A., & Frambach, R. T. (2008). Consequences of forcing consumers to use technology-based self-service. Journal of Service Research, 11(2), 107-123.
Roca, J. C., & Gagné, M. (2008). Understanding e-learning continuance intention in the workplace: A self-determination theory perspective. Computers in Human Behavior, 24(4), 1585-1604.
Rosenthal, S. B., Twomey, C. R., Hartnett, A. T., Wu, H. S., & Couzin, I. D. (2015). Revealing the hidden networks of interaction in mobile animal groups allows prediction of complex behavioral contagion. Proceedings of the National Academy of Sciences, 112(15), 4690-4695.
Ryan, R. M., & Deci, E. L. (2000). Self-determination theory and the facilitation of intrinsic motivation, social development, and well-being. American Psychologist, 55(1), 68.
Samuelson, W., & Zeckhauser, R. (1988). Status quo bias in decision making. Journal of risk and uncertainty, 1(1), 7-59.
Seth, N., Deshmukh, S. G., & Vrat, P. (2005). Service quality models: a review. International journal of quality & reliability management.
Sharma, S. K. (2019). Integrating cognitive antecedents into TAM to explain mobile banking behavioral intention: A SEM-neural network modeling. Information Systems Frontiers, 21(4), 815-827.
Sheldon, K. M., Elliot, A. J., Kim, Y., & Kasser, T. (2001). What is satisfying about satisfying events? Testing 10 candidate psychological needs. Journal of Personality and Social Psychology, 80(2), 325.
Siegrist, M. (2000). The influence of trust and perceptions of risks and benefits on the acceptance of gene technology. Risk analysis, 20(2), 195-204.
Sørebø, Ø., Halvari, H., Gulli, V. F., & Kristiansen, R. (2009). The role of self-determination theory in explaining teachers’ motivation to continue to use e-learning technology. Computers & Education, 53(4), 1177-1187.
Standage, M., Duda, J. L., & Ntoumanis, N. (2006). Students′ motivational processes and their relationship to teacher ratings in school physical education: A self-determination theory approach. Research quarterly for exercise and sport, 77(1), 100-110.
Suh, A., Wagner, C., & Liu, L. (2018). Enhancing user engagement through gamification. Journal of Computer Information Systems, 58(3), 204-213.
Teo, T. (2009). A case for using structural equation modelling (SEM) in educational technology research. British Journal of educational technology, 41(5), E89-E91.
Teo, T., Lee, C. B., Chai, C. S., & Choy, D. (2009). Modelling pre-service teachers’ perceived usefulness of an ICT-based student-centred learning (SCL) curriculum: A Singapore study. Asia Pacific Education Review, 10(4), 535-545.
Tsai, J. M., Cheng, M. J., Tsai, H. H., Hung, S. W., & Chen, Y. L. (2019). Acceptance and resistance of telehealth: The perspective of dual-factor concepts in technology adoption. International Journal of Information Management, 49, 34-44.
Tsikriktsis, N. (2004). A technology readiness-based taxonomy of customers: A replication and extension. Journal of Service Research, 7(1), 42-52.
Van de Belt, T. H., Engelen, L. J., Verhoef, L. M., van der Weide, M. J., Schoonhoven, L., & Kool, R. B. (2015). Using patient experiences on Dutch social media to supervise health care services: exploratory study. Journal of medical Internet research, 17(1), e7.
Vatanasombut, B., Igbaria, M., Stylianou, A. C., & Rodgers, W. (2008). Information systems continuance intention of web-based applications customers: The case of online banking. Information & Management, 45(7), 419-428.
Venkatesh, V., & Davis, F. D. (2000). A theoretical extension of the technology acceptance model: Four longitudinal field studies. Management Science, 46(2), 186-204.
Venkatesh, V., Morris, M. G., Davis, G. B., & Davis, F. D. (2003). User acceptance of information technology: Toward a unified view. MIS quarterly, 425-478.
Walczuch, R., Lemmink, J., & Streukens, S. (2007). The effect of service employees’ technology readiness on technology acceptance. Information & Management, 44(2), 206-215.
Wang, C., Harris, J., & Patterson, P. G. (2012). Customer choice of self‐service technology: the roles of situational influences and past experience. Journal of Service Management.
Wang, Y., So, K. K. F., & Sparks, B. A. (2017). Technology readiness and customer satisfaction with travel technologies: A cross-country investigation. Journal of Travel Research, 56(5), 563-577.
White, A., Breazeale, M., & Collier, J. E. (2012). The effects of perceived fairness on customer responses to retailer SST push policies. Journal of Retailing, 88(2), 250-261.
World Economic Forum. (2018). The future of jobs report 2018. Geneva: World Economic Forum.
Yi, Y. (2003). The Realization of Knowledge Sharing and Knowledge Innovation in an Enterprise [J]. Information Science, 10, 1108-1109.
Zeithaml, V. A., & Gilly, M. C. (1987). Characteristics affecting the acceptance of retailing technologies: A comparison of elderly and nonelderly consumers. Journal of retailing.
Zhang, X., Guo, X., Wu, Y., Lai, K. H., & Vogel, D. (2017). Exploring the inhibitors of online health service use intention: a status quo bias perspective. Information & Management, 54(8), 987-997.
Zhang, X., Han, X., Dang, Y., Meng, F., Guo, X., & Lin, J. (2017). User acceptance of mobile health services from users’ perspectives: The role of self-efficacy and response-efficacy in technology acceptance. Informatics for Health and Social Care, 42(2), 194-206.
Zhao, L., Lu, Y., Wang, B., & Huang, W. (2011). What makes them happy and curious online? An empirical study on high school students’ Internet use from a self-determination theory perspective. Computers & Education, 56(2), 346-356.
Zhou, M. (2016). Chinese university students′ acceptance of MOOCs: A self-determination perspective. Computers & Education, 92, 194-203.
指導教授 洪秀婉(Hung, SHIU-WAN) 審核日期 2020-11-27
推文 facebook   plurk   twitter   funp   google   live   udn   HD   myshare   reddit   netvibes   friend   youpush   delicious   baidu   
網路書籤 Google bookmarks   del.icio.us   hemidemi   myshare   

若有論文相關問題,請聯絡國立中央大學圖書館推廣服務組 TEL:(03)422-7151轉57407,或E-mail聯絡  - 隱私權政策聲明