博碩士論文 105451024 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:37 、訪客IP:3.144.96.159
姓名 陳思彤(Ssu-Tung Chen)  查詢紙本館藏   畢業系所 企業管理學系在職專班
論文名稱 探討銀行員工抗拒轉換企業系統因素之研究:以性別與科技失調為調節變數
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) 資訊技術快速發展的今日,隨著人們消費型態改變,金融交易模式也跟著調整,由早期人們習慣到銀行臨櫃交易,至今多數金融消費者已透過網路銀行或行動裝置操作。金融消費模式的改變,銀行所採用的作業系統勢必得更新,方能跟上金融市場的快速變化的步伐,而人員對於新系統導入的大幅度異動普遍容易產生不安情緒。本研究將從現狀偏好(使用者習慣性)的角度探討銀行員抗拒企業系統導入之因素,以結構方程式進行資料分析,探討銀行員的心理承諾及理性決策制定下,對認知失誤產生的影響,並以性別及科技失調為調節變數,了解在新系統採用過程中抗拒行為的產生原因,針對臺灣地區曾經經歷實施新舊系統轉換,並於該時期在職在任的銀行從業人員為研究對象進行問卷調查,共取得有效問卷 211 份,結果顯示心理承諾及理性決策制定二者皆會對認知失誤造成影響,導致使用者抗拒行為產生,心理承諾亦可不透過中介變數而直接產生使用者抗拒行為,並將性別及科技失調做為調整變數,對使用者理性決策制定及認知失誤產生部分影響,最後,本研究將根據分析結果對未來欲導入新系統之企業或研究提出建議。
摘要(英) Today, with the rapid development of information technology, as people′s consumption patterns change, the financial transaction model has also been adjusted. From the early days people used to bank transactions, most financial consumers have operated through online banking or mobile devices. The change in the mode of financial consumption, the operating system adopted by the bank is bound to be updated, in order to keep up with the rapid changes in the financial market, and the large changes in the introduction of new systems are generally prone to anxiety. This study will explore the factors that bankers resist the introduction of enterprise systems from the perspective of current status preferences (user habits), analyze the data with structural equations, and explore the impact of bankers′ psychological commitments and rational decision-making on cognitive errors. Using gender and science and technology disorders as adjustment variables to understand the reasons for the resistance behavior in the process of adopting the new system, the questionnaire survey was conducted for bank practitioners who had experienced the transformation of the old and new systems in Taiwan during the period. A total of 211 valid questionnaires were obtained. The results showed that both psychological commitment and rational decision-making have an impact on cognitive errors, resulting in users resisting behaviors, and psychological commitments can directly generate user resistance behaviors without mediating variables. Gender and technology disorders act as adjustment variables, which have a partial impact on users′ rational decision-making and cognitive errors. Finally, this study will make recommendations based on the analysis results for companies or research that will introduce new systems in the future.
關鍵字(中) ★ 使用者抗拒
★ 新作業系統
★ 性別
★ 科技失調
關鍵字(英) ★ User resistance
★ New system
★ Gender
★ Technology dissonance
論文目次 摘 要 I
Abstract II
誌 謝 III
目 錄 IV
圖目錄 VI
表目錄 VII
第一章 緒論 1
第一節 研究背景與動機 1
第二節 研究目的 4
第三節 研究流程 5
第二章 文獻探討 6
第一節 現狀偏好理論 6
第二節 認知失調理論 9
第三節 性別差異 11
第三章 研究架構與研究設計 13
第一節 研究架構 13
第二節 研究假設 14
第三節 變數之操作型定義及問項 22
第四節 研究對象及資料來源 27
第五節 資料分析方法 28
一、 敘述性統計分析 28
二、 信度檢驗 28
三、 效度檢驗 29
四、 假設檢驗 30
第四章 實證統計分析與結果 32
第一節 敘述性統計 32
一、 樣本資料敘述統計 32
二、 研究變數敘述統計 35
第二節 模型信效度分析 37
一、 信度分析 37
二、 效度分析 38
第三節 結構模型路徑分析 41
一、 模型配適度檢定 41
二、 模型分析結果 42
三、 調節變數分析 44
第五章 結論與建議 49
第一節 研究討論 49
第二節 研究意涵 53
第三節 研究限制及未來研究建議 56
參考文獻 57
一、 中文資料 57
二、 英文資料 59
附錄:問卷 70
參考文獻 參考文獻
一、 中文資料
王承平、陳立民(2010),休旅車廣告裡性別空間之形塑與再現。文化研究月報。第107卷,頁30-51。
王歆(2012),消費者特性、資訊豐富度與購買意願關聯之研究-以智慧型手機為例,國立中正大學企業管理研究所碩士論文。
余曉清(2002)。科學教育的性別差異。第一次全國科學教育會議公聽會提案資料。教育部、行政院國家科學委員會。頁144-148。
李清修(2005)。國內銀行發展新一代核心系統影響因素探討。中央大學資訊管理研究所碩士論文。
胡宗鳳、江文鉅(2017)。以整合科技接受模式探討閱聽者下載新聞類行動應用程式之意願。管理資訊計算,第6卷第1期,頁125-134。
徐仁輝(1995)。新制度經濟學與公共行政。世新學報。第5卷,頁273-288。
張巧真、陳筠惠(2014)。應用延伸型整合科技接受模式探討線上購買意願- 以雙媒介之觀點。電子商務研究,第12卷第2期,頁143-168。
張春興(1992)。心理學。臺北:東華。
張馨尹(2014)。繼任CEO來源對企業變革的影響之研究:以高階管理團隊為干擾因子。國立高雄應用科技大學企業管理系論文。
葉翠玉、周雨青、鄭淑利、孫慧芳(2016)。軍校生心理健康與適應狀態於性別因素之探討。源遠護理。第10卷第1期,頁34-44。
劉仲矩、詹孟慈(2013)。餐廳美學重要性之研究。行銷評論。第10卷第3期,頁271-292。
蔡淑玲、瞿海源(1988)。性別與成就抱負:以台大學生為例。中國社會學刊。第2卷第2期,頁135-201。

謝小岑(1992)。性別與教育機會-以兩所北市國中為例。國家科學委員會研究彙刊:人文及社會科學。第2卷第2期,頁179-201。
王燕超、白璧珍、劉奕霆(2014)。以整合型科技接受模式探討擴增實境資訊站導入西門町商圈推廣之研究。中華印刷科技年報。
王素彎、王曉茹(2017)。從轉換成本看科技產品在競爭法的適用。經濟前瞻。2017年9月。
陳瑞甫、陳勁宇、姜凱傑、陳雅文(2015)。由現狀偏誤觀點探討影響醫師跨院電子病歷交換系統使用的關鍵因素。103年度科技部補助專題研究計劃成果報告,嘉藥學校財團法人嘉南藥理大學資訊管理系,計畫編號103-2410-H-041-002-。
孫彬訓(2018),華銀、一銀等今年導入行庫新潮流建數位迎賓系統。工商時報,2018年9月24日。https://www.chinatimes.com/newspapers/
20180924000237-260205
金融監督管理委員會(2017)。106年* 銀行及信用合作社受僱員工性別分析表
https://www.fsc.gov.tw/ch/index.jsp

中央銀行全球資訊網各縣市金融機構分布情形
https://www.cbc.gov.tw/lp.asp?CtNode=886&CtUnit=490&BaseDSD=7&mp=1
勞動部勞動統計查詢網
https://statfy.mol.gov.tw/index01.aspx
 二、 英文資料
Ajzen, I. (1991). The theory of planned behavior. Organizational Behavior and Human Decision Processes, 50(2), 179-211.RAI Revista de Administração e Inovação,13(3), 221-230.
Alshamaila, Y., S. Papagiannidis, & F Li (2013). Cloud computing adoption by SMEs in the north east of England: A multi-perspective framework. Journal of Enterprise Information Management, 26,250-275.
Aronson, E. (1968) Dissonance theory: Progress and problems. In R. P. Abelson, E. Aronson, W. J. McGuire, T. M. Newcomb, M. J. Rosenberg, & P. H. Tannenbaum (Ed.), Theories of Cognitive Consistency: A Sourcebook, Chicago: Rand McNally.
Aronson, E. (1999) Dissonance, hypocrisy, and the self-concept. In E. Harmon-Jones & J. Mills (Ed.), Cognitive dissonance: Progress on a Pivotal Theory in Social Psychology. Washington, DC: American Psychological Association.
Avey, J. B., Luthans, F., & Jensen, S. (2009). Psychological capital: A positive resource for combating stress and turnover. Human Resource Management, 48(5), 677-693.
Avey, J. B., Wernsing, T. S., & Luthans, F. (2008). Can positive employees help positive organizational change? Impact of psychological capital and emotions on relevant attitudes and behaviors. The Journal of Applied behavioral Science, 44(1), 48-70.
Bagozzi, R. P., & Yi, Y., (1988). On the Evaluation of Structural Equation Models. Journal of the Academy of Marketing Science. 16(1), 74-94.
Bentler, P. M. (1990). Comparative fit indexes in structural models. Psychological Bulletin, 107: 238–246.
Berigel, M., Kokoc, M., & Karal, H. (2012). Exploring university students’ level of online learning acceptance. Eurasian Journal of Educational Research, (49a), 275-288
Berk, L. E. (1997). Child development. Boston: Allyn & Bacon.
Biken SK. & Pollard D. (1993) Gender and education. Chicago:National Society for the Study of Education.
Bradley, B., & Russell, G. (1997). Computer experience, school support & computer anxieties. Educational Psychology , 17 (3), 267-295.
Brosnan, M. J. (1998). The impact of computer anxiety and self-efficacy upon performance. Journal of Computer Assisted Learning, 14, 223-234.
Buerk, D. (1985). The Voices of Women Marking Meaning in Mathematics. Journal of Education, 167(3), 59.
Busch, T. (1995). Gender differences in self-efficacy & attitudes toward computers. Journal of Educational Computing Research , 12(2), 147-158.
Choi, G., & Chung, H. (2013). Applying the technology acceptance model to social networking sites (SNS): Impact of subjective norm and social capital on the acceptance of SNS. International Journal of Human-Computer Interaction, 29(10), 619-628.
Clarke, V. A. (1990). Sex differences in computing participation: concerns, extent, reasons and strategies. Australian Journal of Education, 34(1), 52-66.
Colley, A. (2003). Gender differences in adolescents’ perceptions of the best and worst aspects of computing at school. Computers in Human Behavior, 19, 673-682.
Colley, M., Gale, T., & Harris, A. (1994). Effects of gender role identity and experience on computer attitude components. Journal of Educational Computing Research, 10(2), 129-137.
Cross, R.W., & Huberty, T. J. (1993). Factor analysis of the State-Trait Anxiety Inventory for children with a sample of seventh- and eighth-grade students. Journal of Psychoeducational Assessment, 11,232-241.
Daughtry, D., & Paulk, D. L. (2006). Gender differences in depression-related coping patterns. Counseling and Clinical Psychology Journal, 3(2), 47-59.
Davis, F. D. (1989). Perceived usefulness, perceived ease of use and user acceptance of information technology. MIS Quarterly, 14, 319-340.
Dickson, G. W. & J. Wetherbe (1985). The Management of Information Systems, Macgraw-Hill.
DiMaggio, P. J., & Powell W. W. (1983). The Iron Cage Revisited: Institutional Isomorphism and Collective Rationality in Organizational Fields. American Sociological Review, 48(2), 147-160.
Doll, R., Peto, R., Wheatley, K., Gary, R., & Sutherland, I. (1994). Mortality in relation to smoking: 40 years’ observations on male British doctors. BMJ;309 :901.
Egan, L. C., Santos, L. R., & Bloom, P. (2007). The origins of cognitive dissonance. Evidence from children and monkeys. Psychological Science, 18, 978-983.
Eisenberger, R., Fasolo, P., & Davis-LaMastro (1990). Perceived organization support and employee diligence, commitment, and innovation. Journal of Applied Psychology,75,51-59.
Elliot, A. J., & Devine, P. G. (1994). On the motivational nature of cognitive dissonance: Dissonance as psychological discomfort. Journal of Personality and Social Psychology, 67, 382-394.
Ert, E., & Erev, I. (2013). On the descriptive value of loss aversion in decisions under risk: Six clarifications. Judgment and Decision Making, 8(3), 214-235.
Eysenck, M. W., Derakshan, N., Santos, R., & Calvo, M. G. (2007). Anxiety and cognitive performance: Attentional control theory. Emotion, 7(2), 336-353.
Fan, T. S., & Li, Y. C. (2005). Gender issues and computers: college computer science education in Taiwan. Computers & Education, 44(3), 285-300.
Fan, Y. W., Chen, C. D., WU, C. C., & Fang, Y. H. (2015). The effect of status quo bias on cloud system adoption. Journal of Computer Information Systems, 55(3), 55-64.
Feeney, J. R., McCarthy, J. M., & Goffin, R., (2015). “Applicant Anxiety: Examining the Sex‐Linked Anxiety Coping Theory in Job Interview Contexts.” International Journal of Selection and Assessment, 23(3), 295-305.
Ferris, J. & Tang, S. (1993). The new institutionalism and public administration: An overview. Journal of Public Administration: Research and Theory, 3(1), 4-10.
Festinger, L. (1957) A Theory of Cognitive Dissonance. Stanford : Stanford University Press.
Fornell, Clase, & David F. Larcker (1981). “Evaluating Structural Equation Models with Unobservable Variables and Measurement Error.” Journal of Marketing Research.18(February):39-50.
Frey, P. A., Richard, J. P., Ho, H. T., R. S., Sammons, R. D., & Sheu, K. F. (1982) Stereochemistry of selected phosphotransferases and nucleotidyl transferases. Methods Enzymol, 87, 213-235.
Gail, W. S. (2005). Handbook of Psychiatric Nursing 6th edition. St. Louis: Mosby.
Gardner, D. G., Dukes, R. L, & Discenza, R. (1994). Computer use, self-confidence, and attitudes: A causal analysis. Computers in human behavior, 9(4), 427-440.
Gatignon, H., & Robertson, T. S. (1985). A propositional inventory for new diffusion research. Journal of consumer research,849-867.
Ghoshal, S. & Barlette, C. (1990). The multinational corporation as an interorganizational network. Academy of Management Review, 15(4), 603-625.
Goldstein, N. J. (2009). Harnessing social pressure, Harvard Business Review, 43-47.
Gordon W.C., & Rebecca, S. L. (2008). Testing mediationand suppression effectsof latent variables bootstrapping with structural equation models. OrganizationalResearch Methods, 11(2), 296-325.
Griskevicius, V., Cialdini, R. B., & Goldstein, N. J. (2008). Applying (and resisting) peer influence, Sloan Management Review, 49(2), 84-88.
Guilford, J. P. (1965). "Fundamental statistics in psychology and education. " New York: McGraw-Hill.
Gupchup, G. V., Borrego, M. E., & Konduri, N. (2004). The impact of student life stress on health related quality of life among doctor of pharmacy students. College Student Journal, 38(2), 292-301.
Gutek, B. A., Searle, S., & Klepa, L. (1991). Relational versus gender role explanations for work-family conflict. Journal of Applied Psychology, 76(4), 560-568.
Heide Jan B. & George John, (1988). ”The Role of Dependence Balancing in Safeguarding Transaction-Specific Assets in Conventional.
Herold, D. M., Fedor, D. B., & Caldwell, S. D.(2007). Beyond change management: A multilevel investigation of contextual and personal influences on employees’ commitment to change. Journal of Applied Psychology, 92(4), 942-951.
Hirschheim, R., & Newman, M. (1988). Information systems and user resistance: theory and practice. The Computer Journal, 31(5), 398-408.
Hsieh, P. J. (2015). Healthcare professionals’ use of health clouds: Integrating technology acceptance and status quo bias perspectives. International journal of medical informatics, 84(7), 512-523.
Hu, L. & Bentler, P. M. in press. Fit indices in covariance structure modeling: Sensitivity to underparameterized model misspecification. Psychological Methods,
Igbaria, M., Zinatelli, N., Cragg, P. & Cavaye, A. (1997). Personal computing Igbaria, M., Zinatelli, N., Cragg, P. & Cavaye, A. (1997). Personal computing acceptance factors in small firms: a structural equation model. MIS Quarterly, 279-305.
Jackson, B.B. (1985). Build Customer Relationships that Last, Harvard Business Review, 63(11), 120-128.
Jermias, J. (2001) Cognitive dissonance and resistance to change: The influence of commitment confirmation and feedback on judgment usefulness of accounting systems. Accounting, Organizations and Society, 26(2), 141-160.
Jiang, J. J., Muhanna, W. A., & Klein, G. (2000). User resistance and strategies for promoting acceptance across system types. Information & Management, 37(1), 25-36.
Jones, M. A., Mothersbaugh, D. L. & Beatty, S. E. (2002). "Why customers stay: measuring the underlying dimensions of services switching costs and managing their differential strategic outcomes." Journal of Business Research, 55(6), 441-450.
Kahneman, D., & Tversky, A. (1990). Prospect theory: An analysis of decision under risk. Econometrica, 47(2), 140e170.
Kay, R. H. (1993). An exploration of theoretical and practical foundation for assessing attitudes towards computers: The computer attitude measure (CAM). Comp utersin Human Behavior, 9, 371-386.
Kendall, K. E. (1997). The significance of information systems research on emerging technologies: Seven information technologies that promise to improve managerial effectivencess. Decision Sciences, 28(4), 775-792.
Kim, B., & Min, J. (2015). The distinct roles of dedication-based and constraint-based mechanisms in social networking sites. Internet Research, 25(1).
Kim, H. W. (2011). The effects of switching costs on user resistance to enterprise systems implementation. Engineering Management, IEEE Transactions on, 58(3), 471-482.
Kim, H. W., & Kankanhalli, A. (2009). Investigating user resistance to information systems implementation: a status quo bias perspective. Mis Quarterly, 567-582.
Kim, S. H., & Srinivasan, V. (2009). A conjoint-hazard model of the timing of buyers′ upgrading to improved versions of high-technology products. The Journal of Product Innovation Management, 26(3), 278.
Kroll, E., & Ziegler, M.,(2016). “Discrimination due to Ethnicity and Gender: How Susceptible are Video-based Job Interviews?” International Journal of Selection and Assessment, 24(2), 161-171.
Laukkanen, T., & Pasanen, M. (2008). Mobile banking innovators and early adopters: How they differ from other online users & quest. Journal of Financial Services Marketing,13(2), 86-94.
Lazarus, R. S. (1991). Emotion and adaptation. Oxford University Press.21(4), 609-637.
Lee, J., Lee, J. & Feick, L. (2001). The Impact of Switching Costs on the Customer Satisfaction-loyalty Link: Mobile Phone Service in France, Journal of Services Marketing, 15(1), 35-48.
Li, J., Liu M., Liu, X. (2016). Why do employees resist knowledge management systems? An empirical study from the status quo bias and inertia perspectives. Computers in Human Behavior, 65, 189-e200.
Lian, J. W., D. C. Yen, & Y. T. Wang (2014). An exploratory study to understand the critical factors affecting the decision to adopt cloud computing in Taiwan hospital. International Journal of Information Management, 34,.28-36.
Liang, H., Saraf, N., Hu, Q., & Xue, Y.(2007) “Assimilation of Enterprise Systems: The Effect of Institutional Pressures and the Mediating Role of Top Management," MIS Quarterly ,31(1), 59-87.
Lu, J., & Xie, X. (2014). To change or not to change: A matter of decision maker’s role. Organizational Behavior and Human Decision Processes, 124(1), 47-55.
Mangleburg, T. F., Donkey, P. M., & Bristol, T. (2004). Shopping with friends & teens′ susceptibility to peer influence. Journal of Retailing, 80(2), 101.
Marcus, G. E., Neuman, W. R., & Michael MK (2000). Affective Intelligence and Political Judgment. The University of Chicago Press Chicago and London.
Markus, M. L. (1983). Power, politics, and MIS implementation. Communications of the ACM, 26(6), 430-444.
Massey, A. P., Montoya-Weiss, M. M., & Brown, S. A. 2001. "Reaping the Benefits of Innovative IT: The Long and Winding Road," IEEE Transactions on Engineering Management, 48(3), 348-357.
Mcneil, D. W., Turk C. L., & Ries, B. I. (1994). Anxiety and Fear. Human Behavior, 14 (1), 151-163.
Measor, Lynda, & Sikes (1993). Pat Gender and Schools. New York: Cassell.
Meyers-Levy, J., & Zhu, R., (2010). “Gender Differences in the Meanings Consumers Infer from Music and Other Aesthetic Stimuli” Journal of Consumer Psychology, 20(4), 495–507.
Michael, Steven C. (2007). Transaction Cost Entrepreneurship. Journal of Business Venturing, 22, 3: 412-426.
Mikkelsen, A., Øgaard, T., Lindøe, P. H., & Olsen, O. E. (2002). Job characteristics and computer anxiety in the production industry. Computers in Human Behavior, 18, 223-239.
North, D. (1990). Institutions, institutional change and economic performance. Now York: Cambridge University Press.
Nunnally, J. C. 1978. Psychometric theory, New York: McGraw‐Hill.
O’Neill, M. A., & Palmer, A. (2004). Importance-performance analysis: a useful tool for directing continuous quality improvement in higher education. Quality Assurance in Education, 12(1), 39-52.
Ostrom, E. (1990) Governing the commons: The evolution of institutions for collective action: Cambridge University Press.
Polites G. L., & Karahanna E.(2012). Schackled to the Status Quo: The inhibiting effects of incumbent system habit, switching costs, and inertia on new system acceptance. MIS Quarterly, 36(1), 21-42.
Porter, M. E. & Strategy, C. (1980). Techniques for analyzing industries and competitors. Cambridge: Havard Business School.
Redondo, I., & Charron, J. P. (2013). The payment dilemma in movie and music downloads: An explanation through cognitive dissonance theory. Computers in Human Behavior, 29, 2037-2046.
Sacks, C. H., Bellisimo, Y., & Mergendoller, J. (1993). Attitudes toward computers and computer use: The issue of gender. Journal of Research on Coputing in Education, 26(2), 256-269.
Samuelson, W. & Zeckhauser, R. (1988). "Status quo bias in decision making." Journal of risk and uncertainty, 1(1), 7-59.
Saules, K. K., Pomerleau, C. S., Snedecor, S. M., Mehringer, A. M., Shadle, M. B., Sax, L. J., … & Gilmartin, S. K. (2002). A longitudinal investigation of emotional health among first-year college students: Comparisons of women and men. Paper presented at the Annual Meeting of the Association for the Study of Higher Education, Sacramento, California, USA.
Scher, S. J., & Osterman, N. (2002). Procrastination, conscientiousness, anxiety, and goals: Exploring the measurement and correlates of procrastination among school-aged children. Psychology in the Schools, 39, 385-398.
Schmalensee, R. (1982). Antitrust and the New Industrial Economics. The American Economic Review, 72(2), 24-28.
Sharifi, S. S., & Esfidani, M. R. (2014). The impacts of relationship marketing on cognitive dissonance, satisfaction, and loyalty: The mediating role of trust and cognitive dissonance. International Journal of Retial and Distribution Management, 42(6), 553-575.
Shneiderman, B. (1997). Designing the user interface: Strategies for effective human-computer interaction. Reading, MA: Addison-Wesley.
Sigmon, S. T., Pells, J. J., Boulard, N. E., Whitcomb-Smith, S., Edenfield, T. M., Hermann, B. A., ... & Elizabeth, K. (2005). Gender differences in self-reports of depression: The response bias hypothesis revisited. Sex Roles, 53(5), 401-411.
Simon, H. A. (1956). Dynamic Programming Under Uncertainty with a Quadratic Criterion Function. Econometrica, 24(1), 74-81.
Smith, M. J., Conway, F. T., & Karsh, B. T. (1999). Occupational stress in human computer interaction. Industrial Health, 37, 157-173.
Spielberger, C. D. (1966). Theory and research on anxiety. In C. D. Spielberger (Ed.), Anxiety and behavior. New York: Academic Press.
Steele, C. M. (1988). The psychology of self-affirmation: Sustaining the integrity of the self. In L. Berkowitz (Ed.), Advances in experimental social psychology. San Diego, CA: Academic Press.
Sun, J. C. Y., Yu, S. J., Lin, S. S. J., & Tseng, S. S. (2016). The mediating effect of anti-phishing self- efficacy between college students’ internet self-efficacy and anti-phishing behavior and gender difference. Computers in Human Behavior, 59, 249-257.
Sweeney, J. C., & Soutar, G. S. (2001). Consumer perceived value: The development of a multiple item scale. Journal of Retailing, 77(2), 203-220.
Tanford, S., & Montgomery, R. (2014). The effects of social influence and cognitive dissonance on travel purchase decisions. Journal of Travel Research, 54(5).
Teo, T. (2010). A path analysis of pre-service teachers’ attitudes to computer use: Applying and extending the technology acceptance model in an educational context. Interactive Learning Environments, 18(1), 65-79.
Thorkildsen, T. A., & Nicholls, J. G. (1998). Fifth graders’ achievement orientations and beliefs: Individual and classroom differences. Journal of Educational Psychology, 90(2), 179-201.
Venkatesh, V., Morris, M. G., Davis, G. B., & Davis, F. D. (2003). User acceptance of information technology: Toward an unified view. MIS Quarterly, 27(3), 425-478.
Wang, Y.M., Wang, Y.S. & Yang, Y.F. (2010), “Understanding the determinants of RFID adoption in the manufacturing industry”, Technological Forecasting & Social Change, Vol. 77 No. 5, 803-815.
Williamson, E. O. (1985). The economic institutions of capitalism. New York, NY: The Free Press.
Wu, C.-C. (2012). Status quo bias in information system adoption:a meta-analytic review. Online Information Review, Vol. 40(7), 998-1017.
Zhu, K., Kraemer, K. L., & Dedrick, J. (2004). Information technology payoff in e-business environments: An international perspective on value creation of e-business in the financial services industry. Journal of management information systems,21(1),17-54.
Zhuhadar, L., Marklin, S., Thrasher, E., & Lytras, M. D. (2016). Is there a gender difference in interacting with intelligent tutoring system? Can Bayesian Knowledge Tracing and Learning Curve Analysis Models answer this question? Computers in Human Behavior, 61, 198-204.
指導教授 洪秀婉(Shiu-Wan Hung) 審核日期 2019-7-17
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