Suchergebnisse - "淡江大學資訊管理學系"
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Schlagwörter: 隱私計算理論, 個人化服務, 感知資訊關聯, 資訊敏感度, 調節焦點, Information privacy, Personalized services, Privacy calculus, Relevance theory, Regulatory focus theory
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Relation: 一、 中文文獻：\n[1] 何自然，冉永平（2000)。《關聯性：溝通與認知》導讀。外語教學與研究出版社。取自https://doi.org/10.1191/026765800673158592\n[2] 賴立芸（2019）。資訊隱私悖論因素探討。國立政治大學資訊管理學系碩士論文，台北市。取自https://hdl.handle.net/11296/uzx2qt\n[3] 林承穎（2017）。從調節焦點和隱私計算探討社群網站使用者隱私揭露之研究。淡江大學資訊管理學系碩士班碩士論文，新北市。取自https://hdl.handle.net/11296/xaf922\n[4] 趙庭瑋（2009）。調節焦點對尋求多樣化之影響。國立臺灣大學商學研究所碩士論文，台北市。取自http://ntur.lib.ntu.edu.tw//handle/246246/184558\n[5] 馬慶玲（2010）。調節焦點影響廣告效果之研究。國立政治大學心理學研究所碩士論文，台北市。 取自https://hdl.handle.net/11296/uemup5\n\n二、 英文文獻：\n[1] Anderson, C. L., &Agarwal, R. (2011). The digitization of healthcare: Boundary risks, emotion, and consumer willingness to disclose personal health information. In Information Systems Research (Vol. 22, Issue 3, pp. 469–490). https://doi.org/10.1287/isre.1100.0335\n[2] Bansal, G., Zahedi, F. M., &Gefen, D. (2010). The impact of personal dispositions on information sensitivity, privacy concern and trust in disclosing health information online. Decision Support Systems, 49(2), 138–150. https://doi.org/10.1016/j.dss.2010.01.010\n[3] Basyuk, D., Prymak, T., &Pohuda, N. (2018). The role of informational technologies in creating a personalized customer experience: a case study of tourism branch in Ukraine. Centre for European Studies (CES) Working Papers, 10(3),406–422. http://search.ebscohost.com/login.aspx?direct=true&db=asx&AN=133272521&lang=de&site=eds-live\n[4] Brown, J. O., Broderick, A. J., &Lee, N. (2007). Online Communities : Conceptualizing the Online Social Network. Journal of Interactive Marketing, 21(3), 2–20. https://doi.org/10.1002/dir\n[5] Celsi, R. L., &Olson, J. C. (1988). The Role of Involvement in Attention and Comprehension Processes. Journal of Consumer Research, 15(2), 210. https://doi.org/10.1086/209158\n[6] Chellappa, R. K., &Raymond G. Sin. (2005). Personalization versus Privacy: An Empirical Examination of the Online Consumer’s Dilemma. Information Technology and Management, 6(2–3), 181–202. https://doi.org/10.3138/cras.42.1.7\n[7] Chellappa, R. K., &Shivendu, S. (2007). An economic model of privacy: A property rights approach to regulatory choices for online personalization. Journal of Management Information Systems, 24(3), 193–225. https://doi.org/10.2753/MIS0742-1222240307\n[8] Craciun, G. (2018). Choice defaults and social consensus effects on online information sharing: The moderating role of regulatory focus. Computers in Human Behavior, 88(June), 89–102. https://doi.org/10.1016/j.chb.2018.06.019\n[9] Culnan, M. J., Armstrong, P. K., Science, S. O., Feb, N. J., Culnan, M. J., &Armstrong, P. K. (1999). Information Privacy Concerns , Procedural Fairness , and Impersonal Trust : An Empirical Investigation. 10(1), 104–115.\n[10] Culnan, M. J., &Bies, R. J. (2003). Consumer privacy: Balancing economic and justice considerations. Journal of Social Issues, 59(2), 323–342. https://doi.org/10.1111/1540-4560.00067\n[11] Dienlin, T., &Metzger, M. J. (2016). An Extended Privacy Calculus Model for SNSs: Analyzing Self-Disclosure and Self-Withdrawal in a Representative U.S. Sample. Journal of Computer-Mediated Communication, 21(5), 368–383. https://doi.org/10.1111/jcc4.12163\n[12] Dinev, T., &Hart, P. (2006). An extended privacy calculus model for e-commerce transactions. Information Systems Research, 17(1), 61–80. https://doi.org/10.1287/isre.1060.0080\n[13] Dinev, T., Xu, H., Smith, J. H., &Hart, P. (2013). Information privacy and correlates: An empirical attempt to bridge and distinguish privacyrelated concepts. European Journal of Information Systems, 22(3), 295–316. https://doi.org/10.1057/ejis.2012.23\n[14] Gauzente, C. (2004). Web Merchants’ Privacy and Security Statements : How Reassuring Are They for Consumers ? a Two-Sided Approach. Journal of Electronic Commerce Research, 5(3), 181–198.\n[15] Gerber, N., Gerber, P., &Volkamer, M. (2018). Explaining the privacy paradox: A systematic review of literature investigating privacy attitude and behavior. Computers and Security, 77, 226–261. https://doi.org/10.1016/j.cose.2018.04.002\n[16] Gupta, Ashish; Patel, Vimla L.; Greenes, R. A. (2016). Advances in Healthcare Informatics an Analytics. https://doi.org/10.1007/978-3-319-23294-2\n[17] Higgins, E. T. (1998). Promotion and Prevention: Regulatory Focus as A Motivational Principle. Advances in Experimental Social Psychology, 30(C), 1–46. https://doi.org/10.1016/S0065-2601(08)60381-0\n[18] Hsiao, C. H., Tsai, C. F., &Hsu, Y. H. (2012). The influences of self-construal and regulatory focus on impulsive buying behavior. NTU Management Review, 23(1), 119–150. https://doi.org/10.6226/NTURM2012.AUG.M5\n[19] Jung, A. R. (2017). The influence of perceived ad relevance on social media advertising: An empirical examination of a mediating role of privacy concern. Computers in Human Behavior, 70, 303–309. https://doi.org/10.1016/j.chb.2017.01.008\n[20] Kehr, F., Kowatsch, T., Wentzel, D., &Fleisch, E. (2015). Blissfully ignorant: The effects of general privacy concerns, general institutional trust, and affect in the privacy calculus. Information Systems Journal, 25(6), 607–635. https://doi.org/10.1111/isj.12062\n[21] Krasnova, H., Spiekermann, S., Koroleva, K., &Hildebrand, T. (2010). Online Social Networks: Why We Disclose Author Version. Journal of Information Technology, 25(2), 109–125.\n[22] Krishnan, M. S., &Awad, N. F. (2006). The Personalization Privacy Paradox : An Empirical Evaluation of Information Transparency and the Willingness to be Profiled Online for Personalization. 30(1), 13–28.\n[23] Laufer, R. S., &Wolfe, M. (1977). Privacy as a concept and a social issue: A multidimensional developmental theory. Journal of Social Issues, 33(3), 22–42.\n[24] Li, H., &Sarathy, R. (2007). Understanding online information disclosure as a privacy calculus adjusted by exchange fairness. In ICIS 2007 Proceedings - Twenty Eighth International Conference on Information Systems.\n[25] Li, H., Sarathy, R., &Xu, H. (2010). Understanding situational online information disclosure as a privacy calculus. Journal of Computer Information Systems, 51(1), 62–71. https://doi.org/10.1080/08874417.2010.11645450\n[26] Li, H., Sarathy, R., &Xu, H. (2011). The role of affect and cognition on online consumers’ decision to disclose personal information to unfamiliar online vendors. Decision Support Systems, 51(3), 434–445. https://doi.org/10.1016/j.dss.2011.01.017\n[27] Li, Y. (2012). Theories in online information privacy research: A critical review and an integrated framework. Decision Support Systems, 54(1), 471–481. https://doi.org/10.1016/j.dss.2012.06.010\n[28] Liberman, N., Idson, L. C., Camacho, C. J., &Higgins, E. T. (1999). Promotion and prevention choices between stability and change. Journal of Personality and Social Psychology, 77(6), 1135–1145. https://doi.org/10.1037/0022-3514.77.6.1135\n[29] Liu, X. (2013). How Are People Enticed to Disclose Personal Information Despite Privacy Concerns in Social Network Sites? The Calculus Between Benefit and Cost. Journal of the American Society for Information Science and Technology, 64(July), 1852–1863. https://doi.org/10.1002/asi\n[30] Lockwood, P., Jordan, C. H., &Kunda, Z. (2002). Motivation by positive or negative role models: Regulatory focus determines who will best inspire us. Journal of Personality and Social Psychology, 83(4), 854–864. https://doi.org/10.1037/0022-3514.83.4.854\n[31] Malhotra, N. K., Kim, S. S., &Agarwal, J. (2004). Internet users’ information privacy concerns (IUIPC): The construct, the scale, and a causal model. Information Systems Research, 15(4), 336–355. https://doi.org/10.1287/isre.1040.0032\n[32] Milne, G. R. (1997). Consumer participation in mailing lists: A field experiment. Journal of Public Policy and Marketing, 16(2), 298–309. https://doi.org/10.1177/074391569701600210\n[33] Milne, G. R., &Gordon, M. E. (1993). Direct Mail Privacy-Efficiency Trade-offs within an Implied Social Contract Framework. Journal of Public Policy & Marketing, 12(2), 206–215. https://doi.org/10.1177/074391569101200206\n[34] Milne, G. R., Pettinico, G., Hajjat, F. M., &Markos, E. (2017). Information Sensitivity Typology: Mapping the Degree and Type of Risk Consumers Perceive in Personal Data Sharing. Journal of Consumer Affairs, 51(1), 133–161. https://doi.org/10.1111/joca.12111\n[35] Mingwei Hsu, Kharlamov, A., &Glenn Parry. (2019). Managing personalization-privacy paradox of digital services: A systematic literature review. Data for Policy.\n[36] Norberg, P. A., Horne, D. R., &Horne, D. A. (2007). The privacy paradox: Personal information disclosure intentions versus behaviors. Journal of Consumer Affairs, 41(1), 100–126. https://doi.org/10.1111/j.1745-6606.2006.00070.x\n[37] Nowak, G. J., &Phelps, J. (1992). Understanding privacy concerns.An assessment of consumers’ information-related knowledge and beliefs. Journal of Direct Marketing, 6(4), 28–39. https://doi.org/10.1002/dir.4000060407\n[38] Odel, L. I. M., Ersuasion, I. N. P., &Angst, B. C. M. (2009). Adoption of electronic health records in the presence of privacy concerns: the elaboration likelihood model and individual persuasion.pdf. Management Information Systems Quarterly, 33(2), 339–370.\n[39] Pavlou, P. A., &Stewart, D. W. (2000). Measuring the Effects and Effectiveness of Interactive Advertising. Journal of Interactive Advertising, 1(1), 61–77. https://doi.org/10.1080/15252019.2000.10722044\n[40] Pham, M. T., &Avnet, T. (2004). Ideals and Oughts and the Reliance on Affect versus Substance in Persuasion. Journal of Consumer Research, 30(4), 503–518. https://doi.org/10.1086/380285\n[41] Phelps, J., Nowak, G., &Ferrell, E. (2000). Privacy concerns and consumer willingness to provide personal information. Journal of Public Policy and Marketing, 19(1), 27–41. https://doi.org/10.1509/jppm.19.1.27.16941\n[42] Pötzsch, S. (2009). Privacy awareness: A means to solve the privacy paradox? IFIP Advances in Information and Communication Technology, 298(216483), 226–236. https://doi.org/10.1007/978-3-642-03315-5_17\n[43] Rohm, A. J., &Milne, G. R. (2004). Just what the doctor ordered. The role of information sensitivity and trust in reducing medical information privacy concern. Journal of Business Research, 57(9), 1000–1011. https://doi.org/10.1016/S0148-2963(02)00345-4\n[44] Sassenberg, K., Landkammer, F., &Jacoby, J. (2014). The influence of regulatory focus and group vs. individual goals on the evaluation bias in the context of group decision making. Journal of Experimental Social Psychology, 54, 153–164. https://doi.org/10.1016/j.jesp.2014.05.009\n[45] Schoenbachler, D. D., &Gordon, G. L. (2002). Trust and customer willingness to provide information in database-driven relationship marketing. Journal of Interactive Marketing, 16(3), 2–16. https://doi.org/10.1002/dir.10033\n[46] Sharma, S., &Crossler, R. E. (2014). Disclosing too much? Situational factors affecting information disclosure in social commerce environment. Electronic Commerce Research and Applications, 13(5), 305–319. https://doi.org/10.1016/j.elerap.2014.06.007\n[47] Sheehan, K. B., &Hoy, M. G. (2000). Dimensions of Privacy Concern Among Online Consumers. Journal of Public Policy & Marketing, 19(1), 62–73.\n[48] Sheng, H., Nah, F. F. H., &Siau, K. (2008). An experimental study on ubiquitous commerce adoption: Impact of personalization and privacy concerns. Journal of the Association for Information Systems, 9(6), 344–376.\n[49] Siegrist, M., Cvetkovich, G., &Roth, C. (2000). Salient value similarity, social trust, and risk/benefit perception. Risk Analysis, 20(3), 353–362. https://doi.org/10.1111/0272-4332.203034\n[50] Sitkin, S. B., &Pablo, A. L. (1992). Reconceptualizing the Determinants of Risk Behavior Author ( s ): Sim B . Sitkin and Amy L . Pablo Source : The Academy of Management Review , Vol . 17 , No . 1 ( Jan ., 1992 ), pp . 9-38 Published by : Academy of Management Stable URL : http://www.jstor. Academy of Management, 17(1), 9–38.\n[51] Sperber, D., &Wilson, D. (1986). Relevance: Communication and Cognition. In Cambridge, MA: Harvard University Press. (Vol. 142). https://doi.org/10.1111/j.1468-0017.1989.tb00246.x\n[52] Spiekermann, S., Grossklags, J., &Berendt, B. (2001). E-privacy in 2nd generation E-commerce: Privacy preferences versus actual behavior. Proceedings of the ACM Conference on Electronic Commerce, 38–47.\n[53] Stone, D. L. (1981). The effects of the valence of outcomes for providing data and the perceived relevance of the data requested on privacy-related behaviors, beliefs, and attitudes.\n[54] Sutanto, J., Palme, E., Tan, C.-H., &Phang, C. W. (2013). Addressing the personalization-privacy paradox: an empirical assessment from a field experiment on smartphone users. MIS Quarter, 37(4), 1141–1164.\n[55] Wang, T., Duong, T. D., &Chen, C. C. (2016). Intention to disclose personal information via mobile applications: A privacy calculus perspective. International Journal of Information Management, 36(4), 531–542. https://doi.org/10.1016/j.ijinfomgt.2016.03.003\n[56] Xu, H., Luo, X., Carroll, J. M., &Rosson, M. B. (2011). The personalization privacy paradox: An exploratory study of decision making process for location-aware marketing. Decision Support Systems, 51(1), 42–52. https://doi.org/10.1016/j.dss.2010.11.017\n[57] Xu, H., Teo, H. H., Tan, B. C. Y., &Agarwal, R. (2009). The role of push-pull technology in privacy calculus: The case of location-based services. Journal of Management Information Systems, 26(3), 135–174. https://doi.org/10.2753/MIS0742-1222260305\n[58] Zhang, B., &Xu, H. (2016). Privacy nudges for mobile applications: Effects on the creepiness emotion and privacy attitudes. Proceedings of the ACM Conference on Computer Supported Cooperative Work, CSCW, 27, 1676–1690. https://doi.org/10.1145/2818048.2820073\n[59] Zhang, E. M. (2010). Beauty as a tool: The effect of model attractiveness, product relevance, and elaboration likelihood on advertising effectiveness. Psychology & Marketing, 30(6), 461–469. https://doi.org/10.1002/mar\n[60] Zhou, T. (2011). The impact of privacy concern on user adoption of location-based services. In Industrial Management and Data Systems (Vol. 111, Issue 2, pp. 212–226). https://doi.org/10.1108/02635571111115146\n[61] Zhu, Y. Q., &Chang, J. H. (2016). The key role of relevance in personalized advertisement: Examining its impact on perceptions of privacy invasion, self-awareness, and continuous use intentions. Computers in Human Behavior, 65, 442–447. https://doi.org/10.1016/j.chb.2016.08.048\n[62] Zimmer, J. C., Arsal, R. E., Al-Marzouq, M., &Grover, V. (2010). Investigating online information disclosure: Effects of information relevance, trust and risk. Information and Management, 47(2), 115–123. https://doi.org/10.1016/j.im.2009.12.003; G0107356029; https://nccur.lib.nccu.edu.tw//handle/140.119/131499; https://nccur.lib.nccu.edu.tw/bitstream/140.119/131499/1/602901.pdf
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Schlagwörter: Bibliometrics, Opinion Mining, Scientific measurement, Sentiment analysis, Social Network Analysis, 社會網路分析, 科學計量, 書目計量學, 情感分析, 意見探勘
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Relation: Acedo, F. J., Barroso, C., Casanueva, C., & Galan, J. L. (2006). Co‐authorship in management and organizational studies: An empirical and network analysis. Journal of Management Studies, 43(5), 957-983. Alavi, M., & Leidner, D. E. (2001). Review: Knowledge management and knowledge management systems: Conceptual foundations and research issues. Mis Quarterly, 107-136. Bastian, M., Heymann, S., & Jacomy, M. (2009). Gephi: an open source software for exploring and manipulating networks. ICWSM, 8, 361-362. Batres-Estrada, B. (2015). Deep learning for multivariate financial time series. Borgman, C. L. (1990). Scholarly communication and bibliometrics. Brass, D., Labianca, G., Mehra, A., Halgin, D., & Borgatti, S. P. (2014). Contemporary perspectives on organizational social networks: Emerald Group Publishing. Cole, A. L., & Knowles, J. G. (2008). Arts-informed research. Handbook of the arts in qualitative research, 55-70. Culnan, M. J. (1986). The intellectual development of management information systems, 1972–1982: A co-citation analysis. Management science, 32(2), 156-172. Culnan, M. J. (1987). Mapping the intellectual structure of MIS, 1980-1985: a co-citation analysis. Mis Quarterly, 341-353. Dunbar, R. I. (2009). The social brain hypothesis and its implications for social evolution. Annals of human biology, 36(5), 562-572. Garfield, E. (1972). Citation analysis as a tool in journal evaluation. Gross, P., & Gross, E. (1927). College libraries and chemical education. Hood, W., & Wilson, C. (2001). The literature of bibliometrics, scientometrics, and informetrics. Scientometrics, 52(2), 291-314. Huberman, B. A., Romero, D. M., & Wu, F. (2008). Social networks that matter: Twitter under the microscope. Ibarra, H. (1993). Network centrality, power, and innovation involvement: Determinants of technical and administrative roles. Academy of Management journal, 36(3), 471-501. Jarneving, B. (2005). A comparison of two bibliometric methods for mapping of the research front. Scientometrics, 65(2), 245-263. Latour, B. (2005). Reassembling the social: An introduction to actor-network-theory: Oxford university press. Montoyo, A., MartiNez-Barco, P., & Balahur, A. (2012). Subjectivity and sentiment analysis: An overview of the current state of the area and envisaged developments: Elsevier. Nerur, S. P., Rasheed, A. A., & Natarajan, V. (2008). The intellectual structure of the strategic management field: An author co‐citation analysis. Strategic Management Journal, 29(3), 319-336. Piryani, R., Madhavi, D., & Singh, V. (2017). Analytical mapping of opinion mining and sentiment analysis research during 2000–2015. Information Processing & Management, 53(1), 122-150. Pritchar.A. (1969). STATISTICAL BIBLIOGRAPHY OR BIBLIOMETRICS. Journal of Documentation, 25(4), 348-&. Ravi, K., & Ravi, V. (2015). A survey on opinion mining and sentiment analysis: Tasks, approaches and applications. Knowledge-Based Systems, 89, 14-46. doi:10.1016/j.knosys.2015.06.015 Rubin, R. E. (1998). Foundations of Library and Information Science: ERIC. Scott, J. (2011). Social network analysis: developments, advances, and prospects. Social network analysis and mining, 1(1), 21-26. Walker, G., Kogut, B., & Shan, W. (1997). Social capital, structural holes and the formation of an industry network. Organization science, 8(2), 109-125. Wasserman, S., & Faust, K. (1994). Social network analysis: Methods and applications (Vol. 8): Cambridge university press. Wellman, B., & Berkowitz, S. D. (1988). Social structures: A network approach (Vol. 2): CUP Archive. White, H. D., & Griffith, B. C. (1981). Author cocitation: A literature measure of intellectual structure. Journal of the Association for Information Science and Technology, 32(3), 163-171.; https://tkuir.lib.tku.edu.tw/dspace/handle/987654321/114498; https://tkuir.lib.tku.edu.tw/dspace/bitstream/987654321/114498/1/index.html
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Schlagwörter: 計劃行為理論, 知識分享, 虛擬社群, 沈浸, 共同依附, 線上遊戲, Theory of planned behavior, knowledge sharing, Virtual Community, immersion, Codependency, Online Game
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Relation: 1. Ajzen I. (1991). The theory of planned behavior. Organizational Behavior & Human Decision Process, 50, 179-211. 2. Ajzen, I. (1985). From intentions to actions: A theory of planned behavior Springer. 3. Ajzen, I., & Fishbein, M. (1980). Understanding attitudes and predicting social behaviour. 4. Algesheimer, R., Dholakia, U. M., & Herrmann, A. (2005). The social influence of brand community: Evidence from european car clubs. Journal of Marketing, 69(3), 19-34. 5. Armstrong, A. G. and J. Hagel. (1996). The real value of on-line communities. Harvard Business Review, 74(3), 134-140. 6. Autenshlyus, Y. b. (2008). Codependence and post-traumatic stress disorders. International Journal of Psychophysiology, 69, 276-316. 7. Bagozzi, R. P., Gopinath, M., & Nyer, P. U. (1999). The role of emotions in marketing. Journal of the Academy of Marketing Science, 27(2), 184-206. 8. Cermak, T. L. (1991). Co-addiction as a disease. Psychiatric Annals, 21(5), 266-272. 9. Chan, C. M. L., Bhandar, M., Oh, L., & Chan, H. (2004). Recognition and participation in a virtual community. Paper presented at the System Sciences, 2004. Proceedings of the 37th Annual Hawaii International Conference On, 10 pp. 10. Chin, W. W. (1998). The partial least squares approach to structural equation modeling. Modern Methods for Business Research, 295(2), 295-336. 11. Choi D , J Kim. (2004). Why people continue to play online games: In search of critical design factors to increase customer loyalty to online contents. CYBERPSYCHOLOGY & BEHAVIOR, 7(1), 11-24. 12. Crawford, C. (2003). In Williams R. (Ed.), Chris crawford on game design [動畫基礎技法. (龍溪出版社)] Indianapolis: New Riders. 13. Csikszentmihalyi, M. (1975). Play and intrinsic rewards. Journal of Humanistic Psychology, 14. Csikszentmihalyi, M., & LeFevre, J. (1989). Optimal experience in work and leisure. Journal of Personality and Social Psychology, 56(5), 815. 15. Curtis P. (1992). Mudding: Social phenomena in text-based virtual realities. Directions and Implications of Advanced Computing, 16. Darr, E. D., & Kurtzberg, T. R. (2000). An investigation of partner similarity dimensions on knowledge transfer. Organizational Behavior and Human Decision Processes, 82(1), 28-44. 17. Davenport, T. H., & Prusak, L. (1998). Working knowledge: How organizations manage what they know Harvard Business Press. 18. Dubinsky, A. J., & Loken, B. (1989). Analyzing ethical decision making in marketing. Journal of Business Research, 19(2), 83-107. 19. Fishbein M, A. I. (1975). Belief, attitude, intention, and behavior: An introduction to theory and research, reading Addison-Wesley. 20. Fornell, C., & Larcker, D. F. (1981). Evaluating structural equation models with unobservable variables and measurement error. Journal of Marketing Research, , 39-50. 21. Gupta, A. K., & Govindarajan, V. (2000). Knowledge flows within multinational corporations. Strategic Management Journal, 21(4), 473-496. 22. Ha, I., Yoon, Y., & Choi, M. (2007). Determinants of adoption of mobile games under mobile broadband wireless access environment. Information & Management, 44(3), 276-286. 23. Hagel III, J., & Armstrong, A. G. (1997). Netgain, harvard business school press. Boston, MA, 24. Hagel, J., & Armstrong, A. (1997). Net gain: Expanding markets through virtual communities Harvard Business Press. 25. Hair Jr, J. F.,Hult, G. T. M.,Ringle,C., & Sarstedt, M. (2013). A primer on parital least squares structural equation modeling(PLS-SEM)SAGE publications. Incorporated, 26. Hair Jr, J. F., Hult, G. T. M., Ringle, C., & Sarstedt, M. (2016). A primer on partial least squares structural equation modeling (PLS-SEM) Sage Publications. 27. Hands, M., & Dear, G. (1994). Co‐dependency: A critical review. Drug and Alcohol Review, 13(4), 437-445. 28. Hatterer, L. (1994). Addictive process, encyclopedia of psychology. NY: John Wiley & Sons, 29. Hendriks, P. (1999). Why share knowledge?the influence of ICT on motivation for knowledge sharing. Knowledge and Process Management, 6(2), 91-100. 30. Hoffman L. D. , Novak P. T. (1996). Marketing in hypermedia computer-mediated environments conceptual foundations. Journal of Marketing, 60(7), 50-68. 31. Hughes-Hammer, C,Martstolf,D.S. & Zeller, R.A. (1998). Development and testing of the codependency assessment tool. Archives of Psychiatric Nursing, 12(5), 264-272. 32. Johnson, D. and J. Wiles. (2003). Effective affective user interface design in games. Ergonomics, 46(13-14), 1332-1345. doi:doi:10.1080/00140130310001610865 33. Kassem, N. O., Lee, J. W., Modeste, N. N., & Johnston, P. K. (2003). Understanding soft drink consumption among female adolescents using the theory of planned behavior. Health Education Research, 18(3), 278-291. 34. Kim, K. H., Park, J. Y., Kim, D. Y., Moon, H. I., & Chun, H. C. (2002). E-lifestyle and motives to use online games. Irish Marketing Review, 15(2), 71. 35. Koh, J., Kim, Y., & Kim, Y. (2003). Sense of virtual community: A conceptual framework and empirical validation. International Journal of Electronic Commerce, 8(2), 75-94. 36. Lee, M. (2009). Understanding the behavioural intention to play online games: An extension of the theory of planned behaviour. Online Information Review, 33(5), 849-872. 37. McKnight, D. H., Choudhury, V., & Kacmar, C. (2002). The impact of initial consumer trust on intentions to transact with a web site: A trust building model. The Journal of Strategic Information Systems, 11(3), 297-323. 38. Nick, Y. (2006). Running head: MMORPG DEMOGRAPHICS, MOTIVATIONS, AND EXPERIENCES. Teleoperators and Virtual Environments, (15), 309-329. 39. Nonaka, I., & Takeuchi, H. (1997). The knowledge-creating company. The Economic Impact of Knowledge, , 183. 40. Nonaka, I., & Takeuchi, H. (1995). The knowledge creation company: How japanese companies create the dynamics of innovation. Oxford University Press.New York, USA, , 304. 41. Novak, T. P., Hoffman, D. L., & Duhachek, A. (2003). The influence of goal-directed and experiential activities on online flow experiences. Journal of Consumer Psychology, 13(1), 3-16. 42. Nunnally, J. C., & Bernstein, I. (1994). The assessment of reliability. Psychometric Theory, 3(1), 248-292. 43. P. Sweetser and P. Wyeth. (2005). GameFlow: A model for evaluating player enjoyment in games. ACM Computers in Entertainment, 3(3), 1-23. 44. Purser, R. E., & Pasmore, W. A. (1992). Organizing for learning. Research in Organizational Change and Development, 6(3), 7-114. 45. Rollings, A., & Adams, E. (2003). Andrew rollings and ernest adams on game design New Riders. 46. Rouse, R. (2001). In Plano (Ed.), Game design: Theory and practice Word ware. 47. Ruggles, R. (2009). Knowledge management tools Routledge. 48. Sherry, J. L. (2004). Flow and media enjoyment. Communication Theory, 14(4), 328-347. 49. Song, S., & Lee, J. (2007). RETRACTED: Key factors of heuristic evaluation for game design: Towards massively multi-player online role-playing game. International Journal of Human-Computer Studies, 65(8), 709-723. 50. Taylor, S., & Todd, P. (1995). Decomposition and crossover effects in the theory of planned behavior: A study of consumer adoption intentions. International Journal of Research in Marketing, 12(2), 137-155. 51. Thomas-Hunt, M. C., Ogden, T. Y., & Neale, M. A. (2003). Who''s really sharing? effects of social and expert status on knowledge exchange within groups. Management Science, 49(4), 464-477. 52. Urbach, N., & Ahlemann, F. (2010). Structural equation modeling in information systems research using partial least squares. JITTA: Journal of Information Technology Theory and Application, 11(2), 5. 53. Wang, Y., Wang, Y., Lin, H., & Tang, T. (2003). Determinants of user acceptance of internet banking: An empirical study. International Journal of Service Industry Management, 14(5), 501-519. 54. Wasko, M. M., & Faraj, S. (2000). “It is what one does”: Why people participate and help others in electronic communities of practice. The Journal of Strategic Information Systems, 9(2), 155-173. 55. Wasko, M. M., & Faraj, S. (2005). Why should I share? examining social capital and knowledge contribution in electronic networks of practice. MIS Quarterly, , 35-57. 56. Wellman, B. (1982). Studying personal communities. Social Structure and Network Analysis, , 61-80. 57. Yao, M. Z., & Flanagin, A. J. (2006). A self-awareness approach to computer-mediated communication. Computers in Human Behavior, 22(3), 518-544. doi:http://dx.doi.org.ezproxy.lib.tku.edu.tw/10.1016/j.chb.2004.10.008 58. 余泰魁 、鄭時宜 , (2005). 影響虛擬社群線上行為因素之研究. 國立金門技術學院學報, (1), 91-102. 59. 余泰魁 、鄭時宜. (2004). 虛擬社群線上聊天行為模式之研究. Electronic Commerce Studies, 2(2), 117-135. 60. 侯正裕. (2011). 「遷移到虛擬新世界」—以人口遷移理論探討MMORPG. 中山管理評論, 19(1), 141-172. 61. 劉上裕 、葉榮椿 、王子玲 、黃宏隆等 . (2011). 影響線上遊戲玩家使用行為相關因素之研究. 美和學報, 30(1), 147-172. 62. 劉月純. (2012). 臺灣遊戲產業發展與全球趨勢分析. 臺北: 財團法人資訊工業策進會產業情報研究所（MIC）. 63. 張世宗. (2006). 游藝學-傳統童玩與現代兒童. 歷史月刊, (224), 4-10. 64. 張意珮. (2002). 線上遊戲使用者轉換因素之研究 ,Available from AiritiLibrary. 65. 彭淑芸、饒培倫、楊錦洲等. (2004). 網路沉迷要素關連性模型之建構與分析. 師大學報: 人文與社會科學類, 49(2), 67-84. 66. 徐嘉靖,、許尚華. (2009). 探索多人線上角色扮演遊戲的遊戲社群社交互動性因素,碩士論文, 國立交通大學工業工程與管理系所 67. 朱文禎、陳哲賢. (2007 年春季). 探討虛擬社群之知識分享行為:以線上遊戲社群為例. 電子商務研究, 第五卷(第一期), 55-80. 68. 林倩如、王智弘,、林旻沛等. (2012). 網路成癮傾向兒童之短期動力取向團體心理治療方案. 中華團體心理治療, 18(4), 11-27. 69. 林東清. (2007), 知識管理 (再版), 台北市: 智勝文化. 70. 童國偉. (2011). 以同儕互動理論分析知識分享之影響因素. 嶺東科技大學資訊管理與應用研究所學位論文, , 1-39. 71. 羅家德. (1999). 虛擬社群版主特質對經營績效之影響-以CityFamily網路同學會為例, 學位論文, 國立中山大學 72. 翁漢騰 、張世宗 、張恬君等 . (2010). 單人動作遊戲之創作元素分析. [creative element analysis of single player action game]. 商業設計學報, (14), 83-96. 73. 莊丙農. (2008). 從沈浸理論探討免費線上遊戲玩家對購買電腦周邊產品行為意圖之研究 (碩士論文). 74. 莊智凱 、周長青 、李建邦等 . (2014). 探討Facebook涉入程度、人格特質與網際人關係對路成癮之影響. Journal of Data Analysis, 9(3), 165-186. 75. 葉建亨 、黃文楨. (2011). 整合社會資本與社會交換理論探討虛擬社群知識分享意願. 資訊管理學報, 18(3), 75-99. 76. 葉思義 、宋昀璐 . (2004). 數位遊戲設計：遊戲設計知識全領域. 台北: 碁峰資訊. 77. 謝佩玲. (2014). 影響線上遊戲玩家沈浸與價值共創因素之研究. [DOI:10.6510/JTLM.2(2).15] 觀光與休閒管理期刊, 2(2), 197-211. 78. 邱光輝 、紀東昀 . (2014). 共依附對虛擬社群成員繼續分享知識意圖之影響. 輔仁管理評論, 21(1), 1-32. 79. 郭冠樟 、葉乘豪 . (2012 年夏季). 以沉浸理論、網路外部性、計畫行為理論探討體感遊戲機購買意圖之研究. 電子商務研究, 10(2), 199-216. 80. 陳俐文. (2010). 結合棒球轉播及線上文字報導建構以事件為主之影片擷取系統 (碩士論文). Available from 國立雲林科技大學資訊工程研究所碩士班. 81. 陳怡安. (2003). 線上遊戲的魅力-以重度玩家為例 (碩士論文).南華大學 82. 陳秀菁 、吳麗娟 、林世華等. (2004). 大學生的共依附特質、人際親密能力與親密感之相關研究. 教育心理學報, 36(2), 145-164. 83. 陳美如 、王渝薇 、范錚強等 . (2016). 玩線上遊戲是計劃行為嗎? 從非計劃型的因素探討. 資訊管理學報, 23(2), 217-245. 84. 黃彥達. (2015). 數位時代論壇. New York: 85. 黃日鉦 、林承賢. (2013). 以計畫行為理論探討縮短數位落差之持續使用行為. International Journal, 5(1), 057-078.; https://tkuir.lib.tku.edu.tw/dspace/handle/987654321/114500; https://tkuir.lib.tku.edu.tw/dspace/bitstream/987654321/114500/1/index.html
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Schlagwörter: 80/20 法則, 銷售策略, 顧客關係管理, 80/20 rule, sales strategy, Customer Relationship Management
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Relation: 一、 中文文獻 [1] 李翠琴，2004，顧客關係管理之個案實證研究-以顧客利潤分析為例，國立中正大學會計與資訊科技研究所碩士論文。 [2] 吳春貴，2016，客戶消費行為與投資金額的關聯強度探討，國立中興大學高階經理系碩士論文。 [3] 吳松融，2002，在分析型的顧客關係管理模式下顧客區隔策略之研究，朝陽科技大學資訊管理系碩士論文。 [4] 林幸忞，2005，顧客屬性對顧客利潤影響之研究-以資訊通路個案公司為例，國立政治大學經營管理碩士學程會計組碩士論文。 [5] 洪莉萍，2013，客戶結構管理與經營績效之研究-以資訊通路U公司為例，碩士論文，國立政治大學經營管理系碩士論文。 [6] 徐茂練，2012，顧客關係管理（第四版），新北市：全華圖書。 [7] 張川裕，2002，關鍵客戶管理，國立台北大學企業管理學系碩士論文。 [8] 張良榮，2007，應用資料採礦技術協助制訂交叉銷售與垂直銷售策略-以某披薩業為例，逢甲大學工業工程與系統管理學研究所碩士論文。 [9] 胡政源，2013，顧客關係管理（第二版），新北市：新文京開發出版。 [10] 黃瓊華，2016，資訊通路商顧客服務策略之分析－以B公司為例，淡江大學國際企業學系碩士論文。 [11] 黃柏堯，2014，資訊系統整合商競爭策略之研究-以D公司為例，世新大學資訊管理學研究所碩士論文。 [12] 莊雅薰，2011，影響顧客利潤因素之實證研究-以定期航運產業為例，國立交通大學管理學院經營管理學程碩士論文。 [13] 賈光宇，1999，結合客戶特徵資料與消費模式探勘信用卡客戶及行銷策略之研究，私立銘傳大學資訊管理學系碩士論文。 [14] 劉文良，2013，顧客關係管理（第三版）-新時代的決勝關鍵，台北：碁峰資訊。 [15] 蔡承孝，2015，頂尖業務員的研究-探討台灣科技產業B2B 業務員個人因素對銷售行為的影響，國立清華大學科技管理研究所碩士論文。 [16] 謝曜聲，2006，資訊服務業之銷售管理策略，國立清華大學科技管理研究所碩士論文。 [17] 鄭翠琴，2003，資料探勘應用於顧客關係管理之研究-以零售業為例，國立台北大學資訊管理研究所碩士論文。 二、 英文文獻 [1] Fox, T. and Stead, S. 2001. “Customer Relationship Management: Delivering the Benefits,” White Paper, CRM（UK） Ltd. And SECOR Consulting Ltd., Stitling and Surrey, UK. [2] Kumar, V. 2010. “Customer relationship management.” John Wiley & Sons, Ltd. [3] Wayland, R. E., and Cole, P. M. 1997. “Customer connections: new strategies for growth.” Harvard Business Press. [4] Zeithaml, V. A., Rust, R. T., and Lemon, K. H. 2001. “The Customer Pyramid: creating and serving profitable customers,” California Management Review, 4; https://tkuir.lib.tku.edu.tw/dspace/handle/987654321/114504; https://tkuir.lib.tku.edu.tw/dspace/bitstream/987654321/114504/1/index.html
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Schlagwörter: 計劃行為理論, 知識分享, 虛擬社群, 沈浸, 共同依附, 線上遊戲, Theory of planned behavior, knowledge sharing, Virtual Community, immersion, Codependency, Online Game, info, socio
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Schlagwörter: 數位相框, 縮短時程, 專案管理, Digital Photo Frames, Shorter duration, Project Management
Dateibeschreibung: 144 bytes; text/html
Relation: 一、中文文獻 1. 沈翰祖，2011，《ISO_IEC 17025規範及認證實務介紹》，行政院農業委員會。 2. 劉晉奇，2001， 電腦繪圖與設計雜誌 (CADesigner雜誌), No.162, 26-34。 3. 維基百科，無日期，，檢索日期：2015年12月21日，取自https://zh.wikipedia.org/wiki/%E6%95%B0%E7%A0%81%E7%9B%B8%E6%A1%86。 4. 林清河，1995，，華泰書局。 5. MBA智庫百科，無日期，，檢索日期：2015年12月21日，取自http://wiki.mbalib.com/zh-tw/%E7%89%A9%E6%96%99%E7%AE%A1%E7%90%86。 6. 鄭竣安，2008，，私立義守大學電機工程學系。 7. 拾景源，2008，，國立清華大學工業工程與工程管理研究所碩士論文。 8. 鄭欣如，2004，，私立中原大學工業工程研究所碩士論文。 9. 簡婉蓉，2007，，私立明新科技大學工程管理研究所碩士論文。 10. 卓佳宏，2005，，國立中山大學資訊管理研究所碩士論文。 11. 社團法人中華專案管理學會編著，2010，專案管理基礎知識與應用實務，第三版。臺北縣：中華專案管理學會。 12. 張盛鴻，2003，，私立明新科技大學，檢索日期：2016年1月4日。 13. 李榮貴，2009，，國立交通大學工業工程系，檢索日期：2016年1月4日。 14. 社團法人中華專案管理學會編著，2011，專案管理基礎知識與應用實務，第四版。新北市：中華專案管理學會。 15. 黃淋玉，2011，，私立明新科技大學企業管理研究所碩士論文。 16. Kyle，2008，，科技產業資訊室，檢索日期：2016年1月16日，取自http://cdnet.stpi.narl.org.tw/techroom/market/eedisplay/2008/eedisplay_08_017.htm。 17. 許詩佩，2001，，國立中山大學資訊管理研究所碩士論文。 18. 吳景鑫，2012，，國立中山大學管理學院高階經營研究所碩士論文。 19. 楊國雄，2008，，國立清華大學工業工程與工程管理研究所碩士論文。 20. 歐陽正二，2007，，私立萬能科技大學碩士論文。 21. 楊凱翔，2010，，私立元智大學碩士論文。 22. 李金墩，1995，，中鋼技術訓練出版委員會, 第20卷第2期，頁57-70。 23. 高莉莉，2005，，私立中原大學企業管理學所碩士論文。 24. PMI國際專案管理學會臺灣分會(譯) (2009)。專案管理知識體指南(PMBOK® Guide)，第四版(原作者：PMI國際專案管理學會)。新北市：宏典文化出版(原著出版年：2008)。 二、 英文文獻 1. Practice Standard for Scheduling (August 2011), Second Edition, U.S.A., Project Management Institute (Corporate Author). 2. Nicholas John M. (2001), Project Management for Business and Technology, Ohio: Prentice Hall, Inc. 3. Stevenson, W. J. (2002), “Operations Management” 7th ed., McGraw-Hill. 4. Grey, S. (1995), Practical Risk Assessment for Project Management. 5. Goldratt, Eliyahu M., Critical Chain (1997), North-River Press. 6. Practice Standard for Project Risk Management, Original edition (July 1, 2009), USA, Project Management Institute (Corporate Author). 7. Construction Extension to the PMBOK Guide, Third Edition (2005), U.S.A., Project Management Institute (Corporate Author). 8. PMI (Project Management Institute) (2004), PMBOK: Project management body of knowledge, PMI Press, PA. 9. McGrath, M. E. (1996), “Setting the PACE in Product Development: A Guide to Product And Cycle-time Excellence”, Butterworth-Heinemann. 10. Boehm, B. W. (1981), Software Engineering Economics, Englewood Cliffs, NJ: Prentice Hall. 11. Boehm, B. W. (1981)”A Experiment in Small-Scale Application SoftwareEngineering”, IEEE Trans. Software Engineering. 12. Argos Press (2003), Project Management Glossary, Retrieved 3 November 2004 from . 13. Project Management Institute (2004), A Guide To The Project Management Body Of Knowledg (PMBOK guide) Third Edition. 14. Keil, M., Mann, J. and Rai, A. (Dec. 2000), Why Software Projects Escalate: An Empirical Analysis and Test of Four Theoretical Models, MIS Quarterly (24:4), pp. 631-664. 15. Deeprose, D. (2002).Project Management -Operation and Technology, 3th Ed, John Wiley & Sons, Inc. 16. Tate, K. & Martin, P.K. (1997). Project Management Memory JoggerTM: A Pocket Guide for Project Teams. Salem, NH: GOAL/QPC.; https://tkuir.lib.tku.edu.tw/dspace/handle/987654321/111141; https://tkuir.lib.tku.edu.tw/dspace/bitstream/987654321/111141/1/index.html
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Schlagwörter: 軟體專案, 系統整合, 關鍵要素評估表, 競標, software project, System integration, key factor assessment table, Bidding
Dateibeschreibung: 144 bytes; text/html
Relation: 參考文獻 一、 中文文獻 1. 葉文賢，2014，資訊專案競標前定價方法論改善之研究，淡江大學碩士論文。 2. 張順教，2014，賽局與策略管理個案分析，華泰文化。 3. 宋明哲，2012，風險管理新論：全方位與整合，五南圖書出版股份有限公司。 4. 行政院公共工程委員會，2011，政府採購法，華總一義字第100015641號令。 5. 游書郎，2007，專案競標成功因素之探討—以資訊系統整合業為例，高雄科大碩士論文。 6. 邱志聖，2006，策略行銷分析-架構與實務應用，智勝文化。 7. 黃瑞麟，2005，資訊系統整合業的競合關係之研究，成功大學高階管理碩士在職專班EMBA碩士論文。 8. Charles W. L. Hill & Gareth R. Jones，2004，策略管理，華泰文化。 9. David I. Cleland & Lewis R. Ireland，2004，專案管理策略精論，麥格羅希爾。 10. Adam M., Brandenburger, Barry J., Nalebuff，2004，競合策略，台灣培生教育。 11. 劉紋宏，2002，專案業務型態之競標策略探討，中山大學管理學院高階經營碩士學程專班碩士論文。 12. 史帝文.模里斯，葛瑞漢.威爾庫克，1999，與顧客發生關係，傳智國際文化。 13. Michael E. Poter，1998，競爭策略：產業環境及競爭者分析，天下文化出版。 14. Regis Mckenna，1997，關係行銷，長河出版社。 15. 漥田干貫，1996，價格戰略，書泉出版社。 二、 英文文獻 1. PMI. (2013). PMBOK Guide Edition: A guide to the project management body of knowledge. 2. Kerzner, Harold. R. (2013). Project Management: a Systems Approach to Planning, Scheduling, and Controlling. 3. Jefferies, M., Gameson, R., Rowlinson, S. (2002). Critical success factors of the BOOT procurement system. Engineering Construction & Architectural Management. 4. Feindt, S., Jeffcoate, J., Chappell, C. (2002). Identifying success factors for rapid growth in SME e-commerce. Small Business Economics. 5. Dobbins, J.H. (2001). Identifying and analyzing critical success factors. Program Management. 6. Morgan Robert M., Shelby D. (1994). The Commitment-Trust Theory of Relationship Marketing. Journal of Marketing. 7. Boseman F. (1986). Strategic Management: Text and Cases. New York.; https://tkuir.lib.tku.edu.tw/dspace/handle/987654321/105510; https://tkuir.lib.tku.edu.tw/dspace/bitstream/987654321/105510/1/index.html
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Consumer Software Piracy in Virtual Communities: An Integrative Model of Heroism and Social Exchange
Autoren: et al.
Weitere Verfasser: et al.
Schlagwörter: Knowledge sharing, Software piracy, Virtual community
Relation: Internet Research 25(2), p.317-334; https://tkuir.lib.tku.edu.tw/dspace/handle/987654321/99818; https://tkuir.lib.tku.edu.tw/dspace/bitstream/987654321/99818/1/index.html
Verfügbarkeit: https://tkuir.lib.tku.edu.tw/dspace/handle/987654321/99818
https://doi.org/10.1108/IntR-08-2013-0187
https://tkuir.lib.tku.edu.tw/dspace/bitstream/987654321/99818/1/index.html
https://tkuir.lib.tku.edu.tw/dspace/bitstream/987654321/99818/-1/Consumer software piracy in virtual communities An integrative model of heroism and social exchange.pdf -
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Consumer Software Piracy in Virtual Communities: An Integrative Model of Heroism and Social Exchange
Autoren: et al.
Weitere Verfasser: et al.
Schlagwörter: Knowledge sharing, Software piracy, Virtual community, manag, eco
Relation: http://tkuir.lib.tku.edu.tw:8080/dspace/bitstream/987654321/99818/-1/Consumer software piracy in virtual communities An integrative model of heroism and social exchange.pdf; http://tkuir.lib.tku.edu.tw:8080/dspace/handle/987654321/99818
Verfügbarkeit: http://tkuir.lib.tku.edu.tw:8080/dspace/bitstream/987654321/99818/-1/Consumer software piracy in virtual communities An integrative model of heroism and social exchange.pdf
http://tkuir.lib.tku.edu.tw:8080/dspace/handle/987654321/99818 -
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Autoren: et al.
Weitere Verfasser: et al.
Schlagwörter: 意見探勘, 意見單元, 影響力分析, Opinion Mining, Opinion unit, Influence analysis
Relation: 中文部分 [1] 石矛、方勇、曾祥平、王長輝，《IDM 模型分析及其影响力改进算法》， 成都信息工程学院学报，23(1)，69-72，2008。 [2] 朱嫣岚、闵锦、周雅倩、黄萱菁、吴立德，《基于 Hownet 的词汇语义倾向计算》，中文信息学报，20(1)，14-20，2012。 [3] 何韜、胡勇、吳越，《基于影响力形成的论坛意见领袖识别》，信息安全与通信保密，(6)，81-83，2012。 [4] 肖宇、許煒、夏霖，《一种基于情感倾向分析的网络团体意见领袖识别算法》， 计算机科学， 39(2)，34-37，2012。 [5] 李孟潔、張俊盛，《利用機器學習作法之中文意見分析》，碩士論文，國立清華大學資訊科學與工程研究所，2009。 [6] 孫瑛澤、陳建良、劉峻杰、劉昭麟、蘇豐文，〈中文短句之情緒分類〉，2010自然語言與語音處理研討會，頁184-198，暨南大學，2010。 [7] 陳柏翰、蕭瑞祥，《基於中文語法規則的意見單元抽取方法之研究》，碩士論文，淡江大學資訊管理研究所，2013。 [8] 陳維君、蕭瑞祥，《網路意見分析與傳統意見調之比較》，碩士論文，淡江大學資訊管理研究所，2013。 [9] 崔懷芝，〈量表信度的測量： kappa 統計量之簡介〉，網址：http://biostatistics.cmu.edu.tw/online/teaching_corner_011.pdf， 上網日期：2014年2月。 [10] 邱鴻達、梁婷，《意見探勘在中文電影評論之應用》，碩士論文，國立交通大學資訊工程研究所，2011。 [11] 黃婷穎、莊裕澤，《網路評價視覺化》，碩士論文，國立台灣大學資訊管理研究所，2011。 [12] 簡之文、蕭瑞祥，《部落格文章情感分析之研究》，碩士論文，淡江大學資訊管理研究所，2012。 [13] 楊盛帆、陸承志，《以整合式規則來做網路論壇上的3C 產品口碑分析》，碩士論文，元智大學資訊管理研究所，2009。 [14] 劉瀚之、王正豪，《微網誌訊息影響力分析及回應意見評價之研究》，碩士論文，國立台北科技大學資訊工程研究所，2012。 [15] 樊興華、趙靜、方濱興、李欲曉，《影响力扩散概率模型及其用于意见领袖发现研究》，计算机学报，36(2)，360-367，2013。 [16] 樊興華、吳昊，《意见领袖识别中的文本倾向性研究》，计算机应用研究，30(9)，2613-2615，2013。 英文部分 [17] Bodendorf, F., and Kaiser, C., "Detecting opinion leaders and trends in online social networks," Proceedings of the 2nd ACM workshop on Social web search and mining, pp. 65-68, 2009. [18] Ding, X., Liu, B., and Yu, P. S., "A holistic lexicon-based approach to opinion mining," Proceedings of the International Conference on Web Search and Web Data Mining, pp. 231-240. 2008. [19] Forman, C., Ghose, A., and Wiesenfeld, B., "Examining the relationship between reviews and sales: The role of reviewer identity disclosure in electronic markets," Information Systems Research, vol. 19, no 3, pp. 291-313, 2008. [20] Hu, M., and Liu, B., "Mining Opinion Features in Customer Reviews," Proceedings of the 19th National Conference on Artificial Intelligence, SanJose, California, United States, pp. 755-760, 2004. [21] Hu, M., and Liu, B., "Mining and Summarizing Customer Reviews," Proceedings of the 10th ACM International Conference on Knowledge Discovery and Data Mining, Seattle, Washington, United States, pp. 168-174, 2004. [22] Hu, N., Liu, L., and Zhang, J., "Do online reviews affect product sales? The role of reviewer characteristics and temporal effects," Information Technology and Management, vol. 9, no 3, pp. 201-214, 2008. [23] Kim, S. M., and Hovy, E., "Determining the sentiment of opinions," Proceedings of the COLING conference, pp. 1367-1374, 2004. [24] Liu, B., Hu, M., and Cheng, J., "Opinion Observer: Analyzing and Comparing Opinions on the Web, " Proceedings of the 14th international Conference on World Wide Web, Chiba, Japan, pp. 342-351, 2005. [25] Liu, B., "Sentiment Analysis and Subjectivity." in Handbook of Natural Language Processing, 2nd Ed. CRC Press, pp. 627-666, 2010. [26] Latané, B., "Psychology of social impact," American Psychologist, 36,pp. 343-356. 1981. [27] Nunamaker, J. R., Chen, J. F., and Purdin, T. D. M., "Systems Development in Information Systems Research," Journal of Management Information Systems, vol. 7, no. 3, pp. 89-106, 1990-1991. [28] Matsumura, N., Ohsawa, Y., and Ishizuka, M., "Influence diffusion model in text-based communication," Transactions of the Japanese Society for Artificial Intelligence, vol. 17, no. 3, pp. 259-267, 2002. [29] Turney, P. D., "Thumbs up or thumbs down?: semantic orientation applied to unsupervised classification of reviews," Proceedings of the 40th annual meeting on association for computational linguistics, pp. 417-424, 2002. [30] Wang, J. H., Fu, T., Lin, H. M., and Chen, H., "A framework for exploring gray web forums: analysis of forum-based communities in Taiwan," In Intelligence and Security Informatics, Springer Berlin Heidelberg pp. 498-503, 2006. [31] Wang, J. H., and Lee, C. C., "Unsupervised Opinion Phrase Extraction and Rating in Chinese Blog Posts," Proceedings of the 3rd IEEE International Conference on Social Computing (SocialCom), Boston, USA, pp.820-823, 2011. [32] Yang, C. C., Tang, X., and Thuraisingham, B. M., "An analysis of user influence ranking algorithms on Dark Web forums," In ACM SIGKDD Workshop on Intelligence and Security Informatics, pp. 10, 2010.; https://tkuir.lib.tku.edu.tw/dspace/handle/987654321/102368
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Autoren: et al.
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Schlagwörter: 意見探勘, 意見單元, 影響力分析, Opinion Mining, Opinion unit, Influence analysis, manag, envir
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Autoren: et al.
Weitere Verfasser: et al.
Schlagwörter: E-Mail Security Awareness, Information Security, Information Security Awareness, Knowledge Maps, Situational Awareness Theory
Relation: International Journal of Distance Education Technologies 9(4), pp.41-56; https://tkuir.lib.tku.edu.tw/dspace/handle/987654321/74818; https://tkuir.lib.tku.edu.tw/dspace/bitstream/987654321/74818/2/index.html
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Autoren: et al.
Weitere Verfasser: et al.
Schlagwörter: 自動摘要, TFIDF, 相似度, Hownet, 重複句排除, Automatic Summarization, Similarity Measure, Duplicate Sentences
Dateibeschreibung: 143 bytes; application/octet-stream
Relation: [1] CKIP Autotag 中央研究院詞庫小組，取自http://godel.iis.sinica.edu.tw/CKIP/ws，2003。 [2] 王永成、劉功申、劉傳漢、胡佩華、孫展，“論文本的自動摘要”，上海交通大學電腦科學技術系，2000。 [3] 李彬、劉挺、秦兵、李生，“基於語義依存的漢語句子相似度計算”，哈爾濱工業大學信息檢索研究室論文，2003。 [4] 徐銘忠，“植基於本體論之文件摘要系統之研究－以中文股市新聞為例”，東海大學資訊工程與科學系碩士論文，2004。 [5] 陳世偉，“植基於功能詞及知網架構之軟體搜尋系統”，淡江大學資訊管理學系碩士論文，2004。 [6] 陳光華，“網際網路服務的過去現在與未來”，國立成功大學圖書館館刊，6，1-7，2000。 [7] 曾元顯，“中文手機新聞簡訊自動摘要”，第十六屆自然語言與語音處理研討會，台北，頁177-189，2004年9月2-3日。 [8] 楊存一、邱立豐，“TFIDF與GBP方法於重要句子擷取績效評估”，雲林科技大學資訊管理學系碩士論文，2001。 [9] 董振東、董強，知網，取自http://keenage.com，1999。 [10] 劉政璋、葉鎮源，“以概念分群為基礎之新聞事件自動摘要”，交通大學資訊科學系碩士論文，2005。 [11] 劉群、李建素，“基於知網的詞彙語義相似度計算”，第三屆漢語詞彙語義研討會，2001。 [12] 謝文泰、陳文鋕、張履平，“以句子資訊量來產生文件摘要之模式”，第七屆人工智慧與應用研討會(TAAI2002)論文集，C4-7，台北，2002。 [13] Chen, F., Han, K. and Chen, G., "An Approach to Sentence-Selection-Based Text Summarization", IEEE Region 10 Conference on Computers, Communications, Control and PowerEngineering, (TENCON ''02) Volume1, Page(s):489-493, Oct. 2002. [14] Edmundson, H.P., "New methods in automatic abstracting extracting", Journal of the Association for Computing Machinery, 16(2):264-285, 1969. [15] Johns, K.S., "A Statistical Interpretation of Term Specificity and its Application in Retrieval", Journal of Documentation, 28(1): 11-20, March 1972. [16] Larocca-Neto, J., Freitas, A.A. and Kaestner, C.A. A., "Automatic Text Summarization using a Machine Learning Approach", In Proceedings of 16th Brazilian Symposium on Artificial Intelligence, 2002:205-215, 2002. [17] Luhn, H.P., "The Automatic Creation of Literature Abstracts", IBM Journal of Research and Development, 2(2):159-165, 1958. [18] Mani, I. and Bloedorn, E., "Machine Learning of Generic and User-focused Summarization", In Proceedings of Fifteenth National Conference on Artificial Intelligence, AAAI-98:821-826, 1998. [19] McDonald, D. and Chen, H.C., "Using Sentence-Selection Heuristics to Rank Text Segment in TXTRACTOR", Proceedings of the second ACM/IEEE-CS joint conference on Digital libraries Portland, Oregon, USA, Page(s): 28-35, 2002. [20] Ohsawa, Y., Benson, N. E. and Yachida, M., "KeyGraph: Automatic Indexing by Co-occurrence Graph based on Building Construction Metaphor", Proceedings of Advanced Digital Library Conference, 1998.; https://tkuir.lib.tku.edu.tw/dspace/handle/987654321/34098; https://tkuir.lib.tku.edu.tw/dspace/bitstream/987654321/34098/1/
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Autoren: et al.
Weitere Verfasser: et al.
Schlagwörter: 數位浮水印, 影像處理, 密碼學, 智慧財產權, Digital Watermarking, Image Processing, Cryptography, Intellectual Property Right
Relation: 第十三屆國際資訊管理學術研討會論文集(I)=Proceedings of the 13th International Conference on Information Management(I)，頁521-526; 第十三屆國際資訊管理學術研討會=The 13th International Conference on Information Management; https://tkuir.lib.tku.edu.tw/dspace/handle/987654321/68550; https://tkuir.lib.tku.edu.tw/dspace/bitstream/987654321/68550/1/index.html
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Schlagwörter: 數位浮水印, 影像處理, 密碼學, 智慧財產權, Digital Watermarking, Image Processing, Cryptography, Intellectual Property Right, droit, info
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Autoren: et al.
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Schlagwörter: 網路廣告, 廣告效果, 巨量資料, Google AdWords, DAGMAR, Internet advertising, Advertising Effectiveness, Big Data
Dateibeschreibung: 144 bytes; text/html
Relation: [1] 方世榮、駱少康譯 (2012)。「行銷管理學14 版」。Kotler, P., Keller, K.著。台北市：臺灣培生教育。 [2] 江義平、江岱衛 (2010)。「關鍵字廣告點擊行為探究」。Electronic Commerce Studies, 8(3), pp. 407-432. [3] 吳統雄 (2010)。「統雄-統計神掌 單因子變異數分析」。取得日： 2015-12-28 。 http://tx.liberal.ntu.edu.tw/~PurpleWoo/Methodology/Analy- TxStatisticsCanon-ANOVA.htm。 [4] 邱建偉 (2002)。「不同banner 廣告呈現方式之表現效果研究」， 國立中山大學企業管理學系研究所碩士論文。 [5] 邱皓政、林碧芳、許碧純、陳育瑜 (2012)。「統計學:原理與應用」 台北市：五南圖書。 [6] 阿里巴巴台灣(2016)。「阿里巴巴首次對外公佈b2b 電商市場報 告」。取得日：2016-03-12。 http://www.alibaba-tw.com/trade/637。 [7] 柳婷 (2005)。「廣告與行銷」。台北市：五南圖書。 [8] 徐達光 (2003)。「使用者心理學」。台北市：東華書局。 [9] 徐靜儀 (2002)。「廣告訴求對廣告效果影響之研究-以網頁廣告為 例」。東吳大學企業管理學系研究所碩士論文。 [10] 郭心語、蔡文淵 (2013)。「魔圖網路廣告投放技術」。華東師範大 學學報（自然科學版）。2013(3), pp. 84-92, 105. [11] 陳卉茹 (2009)。「影響置入性網路廣告效果之研究」。中原大學資 訊管理研究所碩士論文。 [12] 陳淼勝、李德治 (2010)。「統計學概論」。台北市：前程文化。 [13] 陳君厚（2014）。「Collaboration with Statistician? 矩陣視覺化於探 索式資料分析」。取得日： 2016-05-11 。 http://www.slideshare.net/tw_dsconf/collaboration-with-statistician [14] 彭金燕 (1999)。「代言人可信度對廣告效果與購買意願影響之研 究」。大葉大學事業經營研究所碩士論文。 [15] 曾光華 (2014)。「行銷管理: 理論解析與實務應用 第六版」。台 北市：前程文化。 [16] 黃盟祺、洪雅慧、周巧絃 (2012)。「關鍵字廣告效果之研究─搜尋 產品類型, 認知需求與知覺風險之影響」。傳播與管理研究 11 卷 2 期，39-77 頁 [17] 劉文良 (2012)。「電子商務與網路行銷」。台北市：碁峰資訊。 [18] 劉佩婷 (2012)。「關鍵字廣告不被點擊也能獲得品牌態度: 以重 複曝光效果討論」。中國文化大學國際貿易學系碩士論文。 [19] 鄭江宇、張佳榮 (2014)。掌握行銷新趨勢：你不可不知的網站流 量分析 Google analytics (初版 ed.). 新北市: 新頁圖書. [20] 蕭富峰、張佩娟、卓峰志 (2010)。「廣告學」。台北市：智勝文化。 [21] 顏志龍、鄭中平 (2016)。「給論文寫作者的統計指南：傻瓜也會 跑統計」。台北市：五南。 [22] 顏章原 (2013)。「中小企業之網路行銷最佳化模式-以關鍵字廣告 為例」。逢甲大學電子商務碩士在職專班碩士論文。 [23] 羅清俊 (2010)。「社會科學研究方法: 打開天窗說量化」。台北市： 威仕曼文化。 [24] 野口竜司、石井陽子、渥美英紀、村上知紀、松田昭穂、阪田裕 里子、高見俊介 (2011)。「Web マーケティング基礎講座」。東京 都：翔泳社。 [25] 陳亦苓譯（2015）。「統計學，最強的商業武器：實踐篇」。西內 啓著。台北市：精誠資訊。 [26] 財新網（2016）。「什麼是“探索性資料分析”」 。取得日： 2016-05-11。 http://m.opinion.caixin.com/m/2016-01- 06/100896563.html?utm_source=TouTiao&utm_medium=toutiaomx ml&utm_campaign=Hezuo [27] 經濟部商業司（2016）。「行政院第3482 次會議 電子商務發展 推動措施 」取得日：2016-05-11。 http://www.ey.gov.tw/Upload/RelFile/19/732700/28bd7da3-b125- 4633-a395-762a1281eb04.pdf [28] Arens, W. F., Weigold, M. F., & Arens, C. (2009). “Contemporary advertising,” Mcgraw-Hill, New York. [29] Bosworth, K., Gustafson, D. H., Hawkins, R. P., & BARN Research Group. (1994). “The BARN system: Use and impact of adolescent health promotion via computer,” Computers in Human Behavior, 10(4), pp. 467-482. [30] Braender, L. M., Kapp, C. M., & Yeras, J. (2009). “Using web technology to teach students about their digital world,” Journal of Information Systems Education, 20(2), pp. 145. [31] Briggs, R., & Hollis, N. (1997). “Advertising on the web: Is there response before click-through?” Journal of Advertising Research, 37(2), pp. 33-46. [32] Chatterjee, P., Hoffman, D. L., & Novak, T. P. (2003). “Modeling the clickstream: Implications for web-based advertising efforts,” Marketing Science, 22(4), pp. 520-541. [33] Colley, R. H. (1961). “Defining advertising goals: For measured advertising results The Association,” Association of National Advertisers, New York. [34] Conover, W. J., Johnson, M. E., & Johnson, M. M. (1981). “A comparative study of tests for homogeneity of variances, with applications to the outer continental shelf bidding data.,” Technometrics, 23(4), pp. 351-361. [35] Dahlen, M. (2001). “Banner advertisements through a new lens,” Journal of Advertising Research, 41(4), pp. 23-30. [36] Dutka, S. (1995). DAGMAR, defining advertising goals for measured advertising results NTC Business Books. [37] Hoffman, D. L., & Novak, T. P. (1996). “Marketing in hypermedia computer-mediated environments: Conceptual foundations,” The Journal of Marketing, 60(3), pp. 50-68. [38] Kotler, P. (2000). “Marketing management, analysis, planning, implementation, and control 10/e.,” Prentice Hall, New Jersey. [39] Lim, Y., Yap, C. Y. C., & Lau, T. (2010). “Response to internet advertising among malaysian young consumers,” Cross-Cultural Communication, 6(2), pp. 93-99. [40] McCoy, S., Everard, A., Polak, P., & Galletta, D. F. (2007). “The effects of online advertising,” Communications of the ACM, 50(3), pp. 84-88. [41] McHugh, M. L. (2008). “Standard error: Meaning and interpretation.” Biochemia Medica, 18(1), pp. 7-13. [42] Plaza, B. (2009). “Monitoring web traffic source effectiveness with google analytics: An experiment with time series,” Paper presented at the Aslib Proceedings, 61(5), pp. 474-482. [43] Strong, E. K. (1925). “The psychology of selling and advertising,” McGraw-Hill, New York. [44] Tukey, J. W. (1977). “Exploratory data analysis,” Addison-Wesley, Boston. [45] Wright J. S., Warner D. S., Winter W. L., & Zeigler S. K. (1977). “Advertising,” Mcgraw-Hill, New York. [46] Yoo, C. Y. (2009). “The effects of persuasion knowledge on clickthrough of keyword search ads: Moderating role of search task and perceived fairness,” Journalism & Mass Communication Quarterly, 86(2), pp. 401-418.; https://tkuir.lib.tku.edu.tw/dspace/handle/987654321/111177; https://tkuir.lib.tku.edu.tw/dspace/bitstream/987654321/111177/1/index.html
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Schlagwörter: 情感運算, 服務科學, 服務補救, 類神經網路, 決策樹, Affective computing, Service science, service recovery, artificial neural networks, Decision tree
Relation: 參考文獻 [1] 行政院，，網址：http://www.dgbas.gov.tw/public/data/dgbas03/bs4/nis93/ni.pdf [2] Abdel-Hamid, O., Mohamed, A. R., Jiang, H., & Penn, G. (2012). Applying convolutional neural networks concepts to hybrid NN-HMM model for speech recognition. In Acoustics, Speech and Signal Processing (ICASSP), 2012, March IEEE International Conference on (pp. 4277-4280). IEEE. [3] Abe, T. (2005). What is service science. FRI Research Report no. 246, Fujitsu Research Institute, [4] Alter, S. (2011). Making a science of service systems practical: Seeking usefulness and understandability while avoiding unnecessary assumptions and restrictions. In The Science of Service Systems (pp. 61-72). Springer US. [5] Alter, S. (2012). Challenges for service science. Journal of Information Technology Theory and Application, 13(2), 22-38. [6] Bachu, R., Kopparthi, S., Adapa, B., & Barkana, B. (2008). Separation of voiced and unvoiced using zero crossing rate and energy of the speech signal. American Society for Engineering Education (ASEE), Zone Conference Proceedings, 1-7. [7] Baranyi, P., & Csapo, A. (2012). Definition and synergies of cognitive infocommunications. Acta Polytechnica Hungarica, 9(1), 67-83. [8] Barile, S., & Polese, F. (2010). Smart service systems and viable service systems: Applying systems theory to service science. Service Science, 2(1-2), 21-40. [9] Bengio, Y., & Grandvalet, Y. (2003). No unbiased estimator of the variance of K-fold cross-validation. CIRANO. [10] Bitner, M. J., Booms, B. H., & Mohr, L. A. (1994). Critical service encounters: The employee''s viewpoint. The Journal of Marketing, 58(4), 95-106. [11] Bitner, M. J., Booms, B. H., & Tetreault, M. S. (1990). The service encounter: Diagnosing favorable and unfavorable incidents. Journal of Marketing, 54(1), 71-84. [12] Bratko, I., & Muggleton, S. (1995). Applications of inductive logic programming. Communications of the ACM, 38(11), 65-70. [13] Brooke, J. (1996). SUS-A quick and dirty usability scale. Usability Evaluation in Industry, 189, 194. [14] Burkhardt, F., Paeschke, A., Rolfes, M., Sendlmeier, W. F., & Weiss, B. (2005). A database of german emotional speech. Interspeech, Vol. 5, 1517-1520 [15] Busso, C., Deng, Z., Yildirim, S., Bulut, M., Lee, C. M., Kazemzadeh, A Narayanan, S. (2004). Analysis of emotion recognition using facial expressions, speech and multimodal information. Proceedings of the 6th International Conference on Multimodal Interfaces, 205-211. [16] Cambria, E., Livingstone, A., & Hussain, A. (2012). The hourglass of emotions. In Cognitive behavioural systems, Vol. 74(3), 144-157. Springer Berlin Heidelberg. [17] Chang, P., Wang, Y., & Tsai, C. (2005). Evolving neural network for printed circuit board sales forecasting. Expert Systems with Applications, 29(1), 83-92. [18] Chebat, J., & Slusarczyk, W. (2005). How emotions mediate the effects of perceived justice on loyalty in service recovery situations: An empirical study. Journal of Business Research, 58(5), 664-673. [19] Chung, B. G., & Hoffman, K. D. (1998). Critical incidents: Service failures that matter most. The Cornell Hotel and Restaurant Administration Quarterly, 39(3), 66-71. [20] Coiera, E. (2003). Interaction design theory. International Journal of Medical Informatics, 69(2), 205-222. [21] Coleman, T., Branch, M. A., & Grace, A. (1999). Optimization toolbox. For use with MATLAB.User’s Guide for MATLAB 5, Version 2, Relaese II, [22] Conlon, D. E., & Murray, N. M. (1996). Customer perceptions of corporate responses to product complaints: The role of explanations. Academy of Management Journal, 39(4), 1040-1056. [23] Demirkan, H., Kauffman, R. J., Vayghan, J. A., Fill, H., Karagiannis, D., & Maglio, P. P. (2009). Service-oriented technology and management: Perspectives on research and practice for the coming decade. Electronic Commerce Research and Applications, 7(4), 356-376. [24] DeWitt, T., Nguyen, D. T., & Marshall, R. (2008). Exploring customer loyalty following service recovery the mediating effects of trust and emotions. Journal of Service Research, 10(3), 269-281. [25] Douglas-Cowie, E., Campbell, N., Cowie, R., & Roach, P. (2003). Emotional speech: Towards a new generation of databases. Speech Communication, 40(1), 33-60. [26] Dube, L., & Menon, K. (2000). Multiple roles of consumption emotions in post-purchase satisfaction with extended service transactions. International Journal of Service Industry Management, 11(3), 287-304. [27] Fahlman, S. E. (1988). An empirical study of learning speed in back-propagation networks. [28] Ferrario, R., Guarino, N., Janiesch, C., Kiemes, T., Oberle, D., & Probst, F. (2011). Towards an ontological foundation of services science: The general service model. [29] Fragopanagos, N., & Taylor, J. G. (2005). Emotion recognition in human–computer interaction. Neural Networks, 18(4), 389-405. [30] Fredrickson, B. L. (2002). Positive emotions. Handbook of Positive Psychology, Vol. 3, 120-134. [31] Gharavian, D., Sheikhan, M., Nazerieh, A., & Garoucy, S. (2012). Speech emotion recognition using FCBF feature selection method and GA-optimized fuzzy ARTMAP neural network. Neural Computing and Applications, 21(8), 2115-2126. [32] Gronroos, C. (1988). Service quality: The six criteria of good perceived service quality. Review of Business, 9(3), 10-13 [33] Gronroos, C., & Gummerus, J. (2014). The service revolution and its marketing implications: service logic vs service-dominant logic. Managing Service Quality, 24(3), 206-229. [34] Gronroos, C., & Gummerus, J. (2014). The service revolution and its marketing implications: Service logic versus service-dominant logic. Managing Service Quality, 24(3), 1-1. [35] Guo, Z., Zhao, W., Lu, H., & Wang, J. (2012). Multi-step forecasting for wind speed using a modified EMD-based artificial neural network model. Renewable Energy, 37(1), 241-249. [36] Hall, M. A., & Holmes, G. (2003). Benchmarking attribute selection techniques for discrete class data mining. Knowledge and Data Engineering, IEEE Transactions on, 15(6), 1437-1447. [37] Han, J., Kamber, M., & Pei, J. (2006). Data mining: Concepts and techniques Morgan kaufmann. [38] Han, W., Chan, C., Choy, C., & Pun, K. (2006). An efficient MFCC extraction method in speech recognition. Circuits and Systems, 2006. ISCAS 2006. Proceedings. 2006 IEEE International Symposium on, 4, 145-148. [39] Hariharan, M., Saraswathy, J., Sindhu, R., Khairunizam, W., & Yaacob, S. (2012). Infant cry classification to identify asphyxia using time-frequency analysis and radial basis neural networks. Expert Systems with Applications, 39(10), 9515-9523. [40] Hart, C. W., Heskett, J. L., & Sasser, W. E.,Jr. (1990). The profitable art of service recovery. Harvard Business Review, 68(4), 148-156. [41] Hayes-Roth, B., Ball, G., Lisetti, C., Picard, R. W., & Stern, A. (1998). Panel on affect and emotion in the user interface. International Conference on Intelligent User Interfaces: Proceedings of the 3 Rd International Conference on Intelligent User Interfaces, 6(09), 91-94. [42] Hecht-Nielsen, R. (1989). Theory of the backpropagation neural network. Neural Networks, 1989. IJCNN., International Joint Conference on, 593-605. [43] Hess, R. L., Ganesan, S., & Klein, N. M. (2003). Service failure and recovery: The impact of relationship factors on customer satisfaction. Journal of the Academy of Marketing Science, 31(2), 127-145. [44] Hinton, G. E., Srivastava, N., Krizhevsky, A., Sutskever, I., & Salakhutdinov, R. R. (2012). Improving neural networks by preventing co-adaptation of feature detectors. arXiv preprint arXiv:1207.0580. [45] Hoffman, K. D., Kelley, S. W., & Rotalsky, H. M. (1995). Tracking service failures and employee recovery efforts. Journal of Services Marketing, 9(2), 49-61. [46] Holmlid, S. (2009). Interaction design and service design: Expanding a comparison of design disciplines. Nordes, (2), 157-164. [47] Holmlid, S., & Evenson, S. (2008). Bringing service design to service sciences, management and engineering. Service science, management and engineering education for the 21st century (pp. 341-345) Springer. [48] Huang, H. C. (2012). Using artificial neural networks to predict restaurant industry service recovery. International Journal of Advancements in Computing Technology, 4(10), 315-321. [49] Huang, K. Y. (2009). Challenges in human-computer interaction design for mobile devices. In Proceedings of the World Congress on Engineering and Computer Science, Vol. 1, 236-241. [50] IBM Research (2004). Services science: a new academic discipline? A 120-page report of a two-day summit entitled Architecture of On-Demand Business, May 17-18, 2004. [51] Inanoglu, Z., & Caneel, R. (2005). Emotive alert: HMM-based emotion detection in voicemail messages. Proceedings of the 10th International Conference on Intelligent User Interfaces, 251-253. [52] Ingale, A. B., & Chaudhari, D. S. (2012). Speech emotion recognition. International Journal of Soft Computing and Engineering (IJSCE) ISSN, 2231-2307. [53] Izgi, E., Oztopal, A., Yerli, B., Kaymak, M. K., & Şahin, A. D. (2012). Short–mid-term solar power prediction by using artificial neural networks. Solar Energy, 86(2), 725-733. [54] Jiang, N., Zhao, Z., & Ren, L. (2003). Design of structural modular neural networks with genetic algorithm. Advances in Engineering Software, 34(1), 17-24. [55] Junginger, S., & Sangiorgi, D. (2009). Service design and organizational change: Bridging the gap between rigour and relevance. 3rd IASDR Conference on Design Research, Seoul, Korea, [56] Jyh-Shing Roger Jang, "Audio Signal Processing and Recognition," (in Chinese) available at the links for on-line courses at the author''s homepage athttp://www.cs.nthu.edu.tw/~jang. [57] Kaliouby, R. e., Picard, R., & BARON‐COHEN, S. (2006). Affective computing and autism. Annals of the New York Academy of Sciences, 1093(1), 228-248. [58] Kelley, S. W., Hoffman, K. D., & Davis, M. A. (1994). A typology of retail failures and recoveries. Journal of retailing, 69(4), 429-452. [59] Kinnunen, T. (2002). Designing a speaker-discriminative adaptive filter bank for speaker recognition. In INTERSPEECH. [60] Kohavi, R. (1995). A study of cross-validation and bootstrap for accuracy estimation and model selection. Ijcai, 14(2), 1137-1145. [61] Kollias, S., & Karpouzis, K. (2005). Multimodal emotion recognition and expressivity analysis. Multimedia and Expo, 2005. ICME 2005. IEEE International Conference on, 779-783. [62] Komunda, M., & Osarenkhoe, A. (2012). Remedy or cure for service failure? Effects of service recovery on customer satisfaction and loyalty. Business Process Management Journal, 18(1), 82-103. [63] Koolagudi, S. G., & Rao, K. S. (2012). Emotion recognition from speech using source, system, and prosodic features. International Journal of Speech Technology, 15(2), 265-289. [64] Kort, B., Reilly, R., & Picard, R. W. (2001). An affective model of interplay between emotions and learning: Reengineering educational pedagogy-building a learning companion. Advanced Learning Technologies, 2001. Proceedings. IEEE International Conference on, 43-46. [65] Krothapalli, S. R., Yadav, J., Sarkar, S., Koolagudi, S. G., & Vuppala, A. K. (2012). Neural network based feature transformation for emotion independent speaker identification. International Journal of Speech Technology, 15(3), 335-349. [66] Lee, C. M., & Narayanan, S. S. (2005). Toward detecting emotions in spoken dialogs. Speech and Audio Processing, IEEE Transactions on, 13(2), 293-303. [67] Lee, T. (2004). Back-propagation neural network for long-term tidal predictions. Ocean Engineering, 31(2), 225-238. [68] Lek, S., & Guegan, J. (1999). Artificial neural networks as a tool in ecological modelling, an introduction. Ecological Modelling, 120(2), 65-73. [69] Leon, E., Clarke, G., Callaghan, V., & Sepulveda, F. (2004). Real-time detection of emotional changes for inhabited environments. Computers & Graphics, 28(5), 635-642. [70] Leon, E., Clarke, G., Callaghan, V., & Sepulveda, F. (2007). A user-independent real-time emotion recognition system for software agents in domestic environments. Engineering Applications of Artificial Intelligence, 20(3), 337-345. [71] Lewis, B. R., & Spyrakopoulos, S. (2001). Service failures and recovery in retail banking: The customers’ perspective. International Journal of Bank Marketing, 19(1), 37-48. [72] Li, Q., Zheng, J., Tsai, A., & Zhou, Q. (2002). Robust endpoint detection and energy normalization for real-time speech and speaker recognition. Speech and Audio Processing, IEEE Transactions on, 10(3), 146-157. [73] Li, W., Zhang, Y., & Fu, Y. (2007). Speech emotion recognition in e-learning system based on affective computing. Natural Computation, 2007. ICNC 2007. Third International Conference on, Vol. 5, 809-813. [74] Liao, W., Yang, D., & Hung, M. (2010). An intelligent recommendation model with a case study on u-tour taiwan of historical momuments and cultural heritage. Technologies and Applications of Artificial Intelligence (TAAI), 2010 International Conference on, 72-79. [75] Lisetti, C., Nasoz, F., LeRouge, C., Ozyer, O., & Alvarez, K. (2003). Developing multimodal intelligent affective interfaces for tele-home health care. International Journal of Human-Computer Studies, 59(1), 245-255. [76] Litman, D., & Forbes, K. (2003). Recognizing emotions from student speech in tutoring dialogues. Automatic Speech Recognition and Understanding, 2003. ASRU''03 2003. IEEE Workshop on, 25-30. [77] Logan, B. (2000). Mel frequency cepstral coefficients for music modeling. ISMIR. [78] Lusch, R. F. (2011). Reframing supply chain management: a service‐dominant logic perspective. Journal of Supply Chain Management, 47(1), 14-18. [79] Lusch, R. F., & Vargo, S. L. (2006). Service-dominant logic: Reactions, reflections and refinements. Marketing Theory, 6(3), 281-288. [80] Lusch, R. F., & Vargo, S. L. (2011). Service-dominant logic: A necessary step. European Journal of Marketing, 45(7/8), 1298-1309. [81] Lusch, R. F., Vargo, S. L., & Tanniru, M. (2010). Service, value networks and learning. Journal of the Academy of Marketing Science, 38(1), 19-31. [82] Madikeri, S. R., & Murthy, H. A. (2011). Mel filter bank energy-based slope feature and its application to speaker recognition. Communications (NCC), 2011 National Conference on, 1-4. [83] Maglio, P. P., Srinivasan, S., Kreulen, J. T., & Spohrer, J. (2006). Service systems, service scientists, SSME, and innovation. Communications of the ACM, 49(7), 81-85. [84] Mao, X., Zhang, B., & Luo, Y. (2007). Speech emotion recognition based on a hybrid of HMM/ANN. Proceedings of the 7th Conference on 7th WSEAS International Conference on Applied Informatics and Communications, 367-370. [85] Mattila, A. S. (1999). An examination of factors affecting service recovery in a restaurant setting. Journal of Hospitality & Tourism Research, 23(3), 284-298. [86] Miller, J. L., Craighead, C. W., & Karwan, K. R. (2000). Service recovery: A framework and empirical investigation. Journal of Operations Management, 18(4), 387-400. [87] Murty, K. S. R., & Yegnanarayana, B. (2006). Combining evidence from residual phase and MFCC features for speaker recognition. Signal Processing Letters, IEEE, 13(1), 52-55. [88] Ng, I., Maull, R., & Smith, L. (2011). Embedding the new discipline of service science. The science of service systems (pp. 13-35) Springer. [89] Ng, I., Parry, G., Smith, L., Maull, R., & Briscoe, G. (2012). Transitioning from a goods-dominant to a service-dominant logic: Visualising the value proposition of Rolls-Royce. Journal of Service Management, 23(3), 416-439. [90] Nicholson, J., Takahashi, K., & Nakatsu, R. (2000). Emotion recognition in speech using neural networks. Neural Computing & Applications, 9(4), 290-296. [91] Nilsson, M., & Ejnarsson, M. (2002). Speech recognition using hidden markov model. Department of Telecommunications and Speech Processing, Blekinge Institute of Technology. [92] Nwe, T. L., Foo, S. W., & De Silva, L. C. (2003). Speech emotion recognition using hidden markov models. Speech Communication, 41(4), 603-623. [93] Pahlavan, R., Omid, M., & Akram, A. (2012). Energy input–output analysis and application of artificial neural networks for predicting greenhouse basil production. Energy, 37(1), 171-176. [94] Petrushin, V. (1999). Emotion in speech: Recognition and application to call centers. Proceedings of Artificial Neural Networks in Engineering, pp. 7-10. [95] Picard, R. W. (1999). Affective computing for HCI. Proceedings of HCI International (the 8th International Conference on Human-Computer Interaction) on Human-Computer Interaction: Ergonomics and User Interfaces, Vol. 1. 829-833. [96] Picard, R. W. (2002). Affective medicine: Technology with emotional intelligence. Studies in Health Technology and Informatics, 80, 69-84. [97] Picard, R. W. (2003). Affective computing: Challenges. International Journal of Human-Computer Studies, 59(1), 55-64. [98] Picard, R. W. (1997) Affective computing. The MIT Press. [99] Portnoff, M. (1976). Implementation of the digital phase vocoder using the fast fourier transform.Acoustics, Speech and Signal Processing, IEEE Transactions on, 24(3), 243-248. [100] Quinlan, J. R. (1996). Improved use of continuous attributes in C4.5. [101] Quinlan, J. R. (1986). Induction of decision trees. Machine learning, 1(1), 81-106. [102] Quinlan, J. R. (1993). C4. 5: programs for machine learning, Vol. 1. [103] Rabiner, L. R., & Schafer, R. W. (1979). Digital processing of speech signals IET. [104] Ratanamahatana, C. a., & Gunopulos, D. (2003). Feature selection for the naive bayesian classifier using decision trees. Applied Artificial Intelligence, 17(5-6), 475-487. [105] Reed, R. (1993). Pruning algorithms-a survey. Neural Networks, IEEE Transactions on, 4(5), 740-747. [106] Ren, F., & Quan, C. (2012). Linguistic-based emotion analysis and recognition for measuring consumer satisfaction: an application of affective computing.Information Technology and Management, 13(4), 321-332. [107] Rong, J., Li, G., & Chen, Y. P. (2009). Acoustic feature selection for automatic emotion recognition from speech. Information Processing & Management, 45(3), 315-328. [108] Royse, C. F., Chung, F., Newman, S., Stygall, J., & Wilkinson, D. J. (2013). Predictors of patient satisfaction with anaesthesia and surgery care: a cohort study using the Postoperative Quality of Recovery Scale. European Journal of Anaesthesiology (EJA), 30(3), 106-110. [109] Rummelhart, D. E. (1986). Learning representations by back-propagating errors.Nature, 323(9), 533-536. [110] Russell, J. A. (2003). Core affect and the psychological construction of emotion. Psychological Review, 110(1), 145-172. [111] Sabharwal, N., Soch, H., & Kaur, H. (2010). Are we satisfied with incompetent services? A scale development approach for service recovery. Journal of Services Research, 10(1), 125-142. [112] Saco, R. M., & Goncalves, A. P. (2008). Service design: An appraisal. Design Management Review, 19(1), 10-19. [113] Saffer, D. (2005). The Role of Metaphor in Interaction Design. [114] Saffer, D. (2010). Designing for interaction: Creating smart applications and clever devices, New Riders Pub. [115] Shneiderman, B. (2000). The limits of speech recognition. Communications of the ACM, 43(9), 63-65 [116] Smith, A. K., & Bolton, R. N. (2002). The effect of customers'' emotional responses to service failures on their recovery effort evaluations and satisfaction judgments. Journal of the Academy of Marketing Science, 30(1), 5-23. [117] Spohrer, J., & Kwan, S. K. (2008). Service science, management, engineering, and design (SSMED): Outline & references. The Future of Services: Trends and Perspectives, Vol. 1,107-232. [118] Spohrer, J., Anderson, L., Pass, N., & Ager, T. (2008). Service science and service-dominant logic. Otago Forum, Vol. 2, 4-18. [119] Spreng, R. A., Harrell, G. D., & Mackoy, R. D. (1995). Service recovery: Impact on satisfaction and intentions. Journal of Services Marketing, 9(1), 15-23. [120] Tao, J., & Tan, T. (2005). Affective computing: A review. Affective computing and intelligent interaction, (pp. 981-995) Springer. [121] Tax, S. S., & Brown, S. W. (2012). Recovering and learning from service failure. Sloan Management. [122] Thomassey, S., & Fiordaliso, A. (2006). A hybrid sales forecasting system based on clustering and decision trees. Decision Support Systems, 42(1), 408-421. [123] Vargo, S. L., Maglio, P. P., & Akaka, M. A. (2008). On value and value co-creation: A service systems and service logic perspective. European Management Journal, 26(3), 145-152. [124] Vargo, Stephen L. and Robert F. Lusch (2006). Service-Dominant Logic: What it is, What it is not, What it might be. The Service-Dominant Logic of Marketing: Dialog, Debate, and Directions, 43-56. [125] Vergin, R., & O''Shaughnessy, D. (1995). Pre-emphasis and speech recognition. Electrical and Computer Engineering, Vol. 2, 1062-1065. [126] Vergin, R., O''Shaughnessy, D., & Gupta, V. (1996). Compensated mel frequency cepstrum coefficients. Acoustics, Speech, and Signal Processing, IEEE International Conference on, Vol. 1, 323-326. [127] Vesterinen, E. (2001). Affective computing. Digital Media Research Seminar, Helsinki, [128] Wang, C., Miao, Z., & Meng, X. (2008). Differential mfcc and vector quantization used for real-time speaker recognition system. Image and Signal Processing, Vol. 5, 319-323. [129] Wan-I, L., Chia-Chi, L., Cheng-Wu, C., & Chieh-Shan, C. (2012). An experimental design of service failure, recovery and speed analysis in cloud service. African Journal of Business Management, 6(8), 3059-3064. [130] Weiss, S., & Kulikowski, C. (1991). Computer systems that learn. [131] Weng, Z., Li, L., & Guo, D. (2010). Speaker recognition using weighted dynamic MFCC based on GMM. Anti-Counterfeiting Security and Identification in Communication (ASID), 2010 International Conference on, 285-288. [132] Wieland, H., Polese, F., Vargo, S. L., & Lusch, R. F. (2012). Toward a service (eco) systems perspective on value creation. International Journal of Service Science, Management, Engineering, and Technology (IJSSMET), 3(3), 12-25. [133] Wirtz, J., & Mattila, A. S. (2004). Consumer responses to compensation, speed of recovery and apology after a service failure. International Journal of Service Industry Management, 15(2), 150-166. [134] Wirtz, J., & McColl-Kennedy, J. R. (2010). Opportunistic customer claiming during service recovery. Journal of the Academy of Marketing Science, 38(5), 654-675. [135] Wu, X., Kumar, V., Quinlan, J. R., Ghosh, J., Yang, Q., Motoda, H., Philip, S. Y. (2008). Top 10 algorithms in data mining. Knowledge and Information Systems, 14(1), 1-37. [136] Yacoub, J., Takahashi, K., & Nakatsu, R. (2000). Emotion recognition in speech using neural networks. Neural Computing & Applications, 9(4), 290-296. [137] Yacoub, S. M., Simske, S. J., Lin, X., & Burns, J. (2003). Recognition of emotions in interactive voice response systems. Interspeech. [138] Yao, X. (1999). Evolving artificial neural networks. Proceedings of the IEEE, 87(9), 1423-1447. [139] Yu, F., Chang, E., Xu, Y., & Shum, H. (2001). Emotion detection from speech to enrich multimedia content. Proceedings of the Second IEEE Pacific Rim Conference on Multimedia: Advances in Multimedia Information Processing, Vol. 1, 550-557. [140] Zeithaml, V. A., Parasuraman, A., & Berry, L. L. (1985). Problems and strategies in services marketing. The Journal of Marketing, 49(2), 33-46. [141] Zemke, R., & Bell, C. (1990). Service recovery: Doing it right the second time. Training, 27(6), 42-48. [142] Zheng, F., Zhang, G., & Song, Z. (2001). Comparison of different implementations of MFCC. Journal of Computer Science and Technology, 16(6), 582-589. [143] Zhou, X., He, X., & Chen, B. (2002). Genetic algorithm based on new evaluation function and mutation model for training of BPNN. Tsinghua Science and Technology, 7(1), 28-31.; https://tkuir.lib.tku.edu.tw/dspace/handle/987654321/102392
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Schlagwörter: 多國企業, 本國企業, 集中化, 資訊科技管理, Multinational Companies, local Companies, centralization, information technology management
Relation: 一、 中文文獻 1. 中央銀行經濟研究處（2012）。中華民國金融統計月報。9月版。 2. 吳統雄（1984）。電話調查：理論與方法。台北市：聯經出版事業公司。 3. 邱皓政（2005）。量化研究法（二）：「統計原理與分析技術」。台北市：雙葉書廊。 4. 林彩梅（1994）。多國籍企業論。台北市：五南書局。 5. 李志宏（1994）。跨兩岸資訊系統─以資訊產業為例。國立中央大學資訊管理研究所碩士論文。 6. 李基永（1994）。影響在台多國籍企業資訊管理績效之研究。國立政治大學企業管理研究所碩士論文。 7. 李淑慧（2012年1月20日）。金管會：外銀的消費金融資料，不准跨境委外辦理。經濟日報。2012年1月20日，取自http://edn.udn.com/article/view.jsp?aid=474629&cid=47'' 8. 周文賢（2002）。多變量統計分析─SAS／STAT之應用。台北市：智勝文化。 9. 梁昇凱（1998）。跨國企業與本國企業資訊科技分散程度影響因素。國立中央大學資訊管理研究所碩士論文。 10. 劉文雄（1997）。企業競爭策略與資訊集中化程度關係之研究。國立中央大學資訊管理研究所碩士論文。 二、 英文文獻 11. Ahituv, N., Neumann, S., & Zviran, M. (1989). Factors Affecting the Policy for Distributing Computing Resources. MIS Quarterly, 13(4), 389-401. 12. Australia Prudential Regulation Authority. (2010). Prudential Practice Guide PPG 234 – Management of security risk in information and information technology. Canberra, APRA: Author. 13. Bartlett, C. A., & Ghoshal, S. (1989). Managing Across Border. Boston: Harvard Business School Press. 14. Blanpain, R. (1979). The OECD guildiness for multinational enterprise and labor relations 1976-1979. Deventer, Netherlands: Kluwer Academic Publisher. 15. Brown, C. V., & Magill, S. L. (1994). Alignment of the IS Function With the Enterprise:Toward a Model of Antecedents. MIS Quarterly, 18(4), 371-403. 16. Clark, T. D. (1992). Corporate Systems Management: An Overview and Research Perspective. Communication of the ACM, 35(2), 61-75. 17. Deans, P. C., Karwan, K. R., Goslar, M. D., Ricks, D. A., & Toyne, B. (1991). Identification of Key International Information Systems Issues in U.S.-Based Multinational Corporations. Journal of Management Information Systems, 7(4), 27-50. 18. DeVellis, R. F. (1998). Scale Development: Theory and Applications. NewBury Park, CA: Sage. 19. Dunning, J. H. (1973). Explining changing Patterns of International Production: In Support of the Eclectic Theory. Oxford Bulletin of Economics and Statistics, 41, 269-295. 20. George, J. F., & King, J. L. (1991). Examining the Computing and Centralization Debate. Communication of the ACM, 34(7), 63-72. 21. Martin, J. (1981). Computer networks and distributed processing, software, techniques, and architecture. Englewood Cliffs, Prentice-Hall. 22. Leifer, R. (1988). Matching Computer-Based Information Systems with Organizational Structures. MIS Quarterly, 12(1), 63-73. 23. Lilienthal, D. E. (1960). Management of the multinational corporations. New York:Mcgraw-Hill. 24. Moynihan, T. (1990). What Chief Executives and Senior Managers Want From Their IT Departments. MIS Quarterly, 14(1), 15-25. 25. Nunnally, J. C. (1978). Psychometric Theory. New York: Mcgraw-Hill. 26. Olson, M. H., & Chervany, N. L. (1980). The Relationship Between Organizational Characteristics and The Structure of The Informaiton Services Function. MIS Quarterly, 4(2), 57-68. 27. Palvia, P. C., Palvia, S., & Zigli. R. M. (1992). Global Information Technology Environment : Key MIS Issues in Advanced and Less-Developed Nations. Idea Group Publishing, 2-34. 28. Robinson, R. D. (1984). Internationalization of businesss: An introduction. Chicago:The Dryden Press. 29. Roche, E. M. (1992). Managing Information Technology in Multinational Corporations. New York:Macmillan. 30. Selig, G. J. (1982). A Framework for Multinational Information Systems Planning. Information and Management, 5, 95-115. 31. Tractinsky, N., & Jarvenpaa, S. L. (1995). Information Systems Design Decisions in a Global Versus Domestic Context. MIS Quarterly, 19(4), 507-534. 32. Vernon, R. (1971). Sovereignty at bay: The multinational spread of U.S. enterprise. New York: Basic Books. 33. Watson, R. T., & Brancheau, J. C. (1991). Key Issues in Information Systems Management:An International Perspective. Information & Management, 20, 213-223.; https://tkuir.lib.tku.edu.tw/dspace/handle/987654321/87737
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Schlagwörter: 顧客關係管理, CRM, Customer Relationship Management
Relation: [1] 陳冬漢，《台灣紡織產業企業資源規劃、供應鏈管理、客戶關係管理推行之研究》，碩士論文，國立成功大學高階管理碩士在職專班，2005。 [2] 黃奕瑛，《金融業導入顧客關係管理之關鍵成功因素探討》，碩士論文，台北大學企業管理研究所，2001。 [3] 賴冠宇，《顧客關係管理(CRM)系統的使用現況與影響因素之探索性研究》，碩士論文，國立中央大學資訊管理研究所，2006。 [4] 賴華璘，《CRM系統採用過程之使用者行為敘說分析-以某跨國企業為例》，碩士論文，國立中山大學管理學院國際經營管理碩士學程，2009。 [5] 謝佩倩，《製造業導入顧客關係管理系統(CRM)之評估與規劃》，碩士論文，國立台灣大學國際企業學研究所，2006。 [6] Alavi, M., & Leidner, D., “Knowledge Management Systems: Emerging Views and Practices Form the Field,” proceedings of the 32nd Hawaii International Conference on System Science, Maui, 1999. [7] Beath, C.M., “Supporting the Information Technology Champion,” MIS Quarterly, Vol.15, No.3, pp. 355-371, 1991. [8] Berson, A., Thearling, K., & Smith, S., “Building Data Mining Applications for CRM,” New York: McGraw-Hill, 2000. [9] Beynon-Davies, P., “Human Error and Information Systems Failure: The Case of the London Ambulance Computer-aided Despatch System Project,” Interacting with computers (ISSN: 0953-5438). 11(1), pp. 699-720, 1999. [10] Bhaskar, R., “A Customer Relationship Management System to Target Customers at Cisco,” Journal of Electronic Commerce in Organizations, 2(4), pp. 63-73, 2004. [11] Bhatia, A., “A Roadmap to Implementation of Customer Relationship Management (CRM),” 1999. from http://crm.ittoolbox.com/, accessed 2011/11/09. [12] Bostrom, R.P., & Heinen, J.S., “MIS Problems and Failures: A Socio-technical Perspective Part I: The Causes,” MIS Quarterly, Vol.1, No.3, pp. 17-32, 1977. [13] Brown, S. A., & Gulycz, M., “Performance Driven CRM,” Canda: PwC Consulting, 2002. [14] Brown, S. A., “Customer Relationship Management: A Strategic Imperative in the World of E-Business,” Toronto: John Wiley & Sons, 2000. [15] Campbell, B., “CRM How to: Close Encounters,” Retrieved September 7, 2004. from http://www.oracle.com/oramag/profit/02-aug/p32crm_close.html, accessed 2011/11/02. [16] Chen, J. S., & Ching, R. K. H., “An Empirical Study of the Relationship of IT Intensity and Organizational Absorptive Capability on CRM Performance,” Journal of Global Information Management, 12(1), pp. 1-17, 2004. [17] Croteau, A. M., & Li, P., “Critical Success Factors of CRM Technological Initiatives,” Canadian Journal of Administrative Sciences, 20(1), pp. 21-34, 2003. [18] Day, G. S., “Capabilities for Forging Customer Relationships,” Report No.00-118. Cambridge, MA: Marketing Science Institute, 2000. [19] Desai, C., Wright, G., & Fletcher, K., “Barriers to Successful Implementation of Database Marketing: A Cross-industry Study,” International Journal of Information Management, Vol.18, No.4, pp. 265-276, 1998. [20] Duncan, N. B., & Bogucki, N., “Capturing Flexibility of Information Technology Infrastructure: A Study of Resource Characteristics and Their Measure,” Journal of Management Information systems, 12(2), pp. 37-57, 1995. [21] Garter Group, “Industry Forecast and Growth Factors: Online Banking and Electronic Bill Payment,” Stamford. CT: Author, 2000. [22] Greenberg, P., “CRM at the Speed of Light,” Berkeley, CA: Osborne/McGraw-Hill, 2001. [23] Homburg, C., Workman, J. P., & Jensen, O., “Fundamental Changes in Marketing Organization: The Movement Toward a Customer-Focused Organizational Structure,” Journal of the Academy of Marketing Science, 28(4), pp. 459-478, 2000. [24] Iacovou, C. L., Benbasat, I., & Dexter, A. S., “Electronic Data Interchange and Small Organizations: Adoption and Impact of Technology,” MIS Quarterly, 19(4), pp. 465-486, 1995. [25] Jayachandran, S., Sharma, S., Kaufman, P., & Raman, P., “The Role of Relational Information Processes and Technology Use in Customer Relationship Management,” Journal of Marketing, 69, pp. 177-192, 2001. [26] Jutla, D., Craig, J., & Bodorik, P., “Enabling and Measuring Electronic Customer Relationship Management Readiness,” Proceedings of the 34th Hawaii International Conference on System Sciences, Maui, 2001. [27] Kalakota, R., & Robinson, M., “e-Business 2.0, Roadmap for Success,” Addison Wesley, 2001. [28] Kim, H.W., & Pan, S.L., “Towards a Process Model of Information Systems Implementation: The Case of Customer Relationship Management(CRM),” The Database for Advances in Information Systems - Winter 2006, Vol.37, No.1, 2006. [29] Klaus, D.W., “CRM Systems and Users: How Do They Fit?,” Presented at the CRM Connect Conference in Zurich, 2000. [30] Kracklauer, A., Passenheim, O., & Seifert, D., “Mutual Customer Approach: How Industry and Trade are Executing Collaborative Customer Relationship Management,” International Journal of Retail & Distribution Management, 29(12), pp. 515-519, 2001. [31] Langerak, F., & Verhoef, P. C., “Strategically Embedding CRM,” Business Strategy Review, 14(4), pp. 73-80, 2003. [32] Lyytinen, K., & Hirschheim, R., “Information Systems Failures - a Survey and Classification of the Empirical Literature,” Oxford University Press, Inc. New York, NY, USA, 1987. [33] Pan, S.L., & Lee, J.N., “Using e-CRM for a Unified View of the Customer,” Communications of ACM, Vol.6, No.1, pp. 95-99, 2003. [34] Peppard, J., “Customer Relationship Management (CRM) in Financial Services,” European Management Journal, 18(3), pp. 312-327, 2000. [35] Peppers, D., & Rogers, M., “The One to One Future: Building Relationships One Customer at a Time,” New York: Doubleday, 1993. [36] Rai, A., & Bajwa, D. S., “An Empirical Investigation into Factors Relating to the Adoption of Executive Information Systems: An Analysis of EIS for Collaboration and Decision Support,” Decision Sciences, 28(4), pp. 939-975, 1997. [37] Reinartz, W., Krafft, M., & Hoyer, W. D., “The Customer Relationship Management Process: Its Measurement and Impact on Performance,” Journal of Marketing Research, 1(41), pp. 293-305, 2004. [38] Rigby, D.K., Reichheld, F.F., & Schefter, P., “Avoid the Four Perils of CRM,” Harvard Business Review, Vol.80, No.2, pp. 101-109, 2002. [39] Roberts, M. L., Liu, R. R., & Hazard, K., “Strategy, Technology and Organisational Alignment : Key Components of CRM Success,” Database Marketing & Customer Strategy Management, 12(4), pp. 315-626, 2005. [40] Ross, J. W., Beath, C. M., & Goodhue, D. L., “Develop Long-Term Competitiveness through IT Assets,” Sloan Management Review, 38(1), pp. 31-43, 1996. [41] Ryals, L., & Knox, S., “Cross-functional Issues in the Implementation of Relationship Marketing through Customer Relationship Management,” European Management Journal, Vol.19, No.5, pp. 534-542, 2001. [42] Ryals, L., “Making Customers Pay: Measuring and Managing Customer Risk and Returns,” Journal of Strategic Marketing, 11, pp. 165-175, 2003. [43] Sauer, C., “Why Information Systems Fail: A Case Study Approach,” Information Systems Series. Henley-on-Thames, 1993. [44] Seybold, P. B., “The Customer Revolution: How to Thrive When Customersare in Control,” Random House, Inc, 2001. [45] Sheth, J. N., & Sisodia, R. S., “Marketing Productivity: Issues and Analysis,” Journal of Business Research, 55(5), pp. 349-362, 2002. [46] Spengler, B., & Fluss, D., “CRM Gains Ground as Dynamic e-Business Applications,” InfoWord, pp. 42, 1999. [47] Srivastava, R. K., Shervani, T. A., & Fahey, L., “Marketing, Business Processes, and Shareholder Value: An Organizationally Embedded View of Marketing Activities and the Discipline of Marketing,” Journal of Marketing, 63(4, Special Issue), pp. 168-179, 1999. [48] Stefanou, C., Sarmaniotis, C., & Stafyla, A., “CRM and Customer-Centric Knowledge Management: An Empirical Research,” Business Process Management Journal, 9(5), pp. 617-634, 2003. [49] Tan, X., Yen, D. C., & Fang, X., “Internet Integrated Customer Relationship Management,” Journal of Computer Information Systems, pp. 77-86, 2002. [50] Vance, D. M., “Information, Knowledge and Wisdom: The Epistemic Hierarchy and Computer-Based Information System,” Proceedings of the 1997 AIS America’s Conference, 1997. [51] Vandermerwe, S., “Achieving Deep Customer Focus,” MIT Sloan Management Review, 45(3), pp. 26-34, 2004. [52] Weill, P., Broadbent, M., & Butler, C., “Exploring How Firms View IT Infrastructure,” Working Paper No.4, The University of Melbourne, 1996.; https://tkuir.lib.tku.edu.tw/dspace/handle/987654321/87741
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Schlagwörter: 物件導向技術, 繪圖程式庫, Object-Oriented technique, Graphic Library, 3D, OpenGL, JOGL
Relation: [1] Donald Hearn and M. Pauline Baker, “Computer Graphics with OpenGL, Third Edition”, Prentice Hall , 2003. [2] OpenGL.org , OpenGL, http://www.opengl.org, 1997 [3] Richard S Wright, Jr and Michael Sweet, OpenGL SuperBible, Second Edition, Waite Group, 1999 [4] Dennis J Bouvier, Getting Started with the Java 3D API, Sun Microsystems, 2009 [5] Grady Booch, Robert A. Maksimchuk, Michael W. Engle, Bobbi J. Young, Ph.D., Jim Conallen, Kelli A. Houston, Object-Oriented Analysis and Design with Applications, Addison Wesley, 2007 [6] Dave Shreiner (Author), The Khronos OpenGL ARB Working Group, OpenGL Programming Guide: The Official Guide to Learning OpenGL, Versions 3.0 and 3.1 (7th Edition), Addison Wesley, 2007 [7] Jim X. Chen, Edward J. Wegman, Foundations of 3D Graphics Programming Using JOGL and Java3D (Second Edition), Springer, 2008 [8] James D. Foley, Andries van Dam, Steven K. Feiner, John F. Hughes, Computer Graphics: Principles and Practice in C (2nd Edition), Addison Wesley, 1997 [9] OpenGL Architecture Review Board, Dave Shreiner, OpenGL Reference Manual: The Official Reference Document to OpenGL, Version 1.4 (4th Edition), Addison Wesley, 2004 [10] Edward Angel, Interactive Computer Graphics: A Top-Down Approach using OpenGL (4th Edition), Addison Wesley, 2006 [11] 向賢偉, 《以OpenGL建構的3D導覽系統》, 碩士論文, 淡江大學資訊管理研究所, 2008 [12] 劉定衡,《全尺度宇宙儀》, 碩士論文, 淡江大學資訊管理研究所, 2009 [13] 張弘毅,《支援遠近效果的繪圖程式庫》, 碩士論文, 淡江大學資訊管理研究所, 2010 [14] JogAmp.org , Java OpenGL, http://jogamp.org/, 2011 [15] Oracle.com , Java SE Desktop Technologies, http://www.oracle.com/technetwork/java/javase/tech/index-jsp-138252.html, 2011; https://tkuir.lib.tku.edu.tw/dspace/handle/987654321/77419
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