臺灣博碩士論文加值系統

近年來線上博弈平台應用視訊串流技術產生了串流直播博弈遊戲，獲得線上博弈愛好者的使用與關注並在實際營運中獲得了成功印證。本研究以(Westaby, 2005)所發展之行為推理理論為基礎，並加入了知覺享樂性、便利性、認知安全性、知覺障礙等來探討使用者之實際行為的背後的影響因素。針對台灣地區線上博弈平台使用者調查，透過問卷的形式來蒐集資料。
本研究結果顯示，線上博弈平台使用者著重使用者體驗與感官娛樂性體驗，可隨時隨地的使用與操作便利性對於使用者有一定程度的吸引力。線上博弈平台對於安全性技術採用與所建立的安全性形象必需要有更多的著墨，並且對於企業社會責任的投入參與，多展現對社會的正向回饋，可望降低民眾對於線上博弈平台的知覺障礙門檻。

Recently, online casino combined media streaming technology to create live streaming gambling games, to attract online gambling lovers’ attention and acceptance. There is a positive correlation between online gambling players’ acceptance of live stream gambling games and the revenue of online casino game company. This research is based on the behavior reasoning theory by Westaby in 2005 and to reseach furthermore on the attitude and behavior of the online gambling game players by discussing the following topics: perceived enjoyment, convenience, perceived safety, and barriers. That is based on the questionnaires from online casino users in Taiwan as the empirical data.
The result of this research demonstrated that online gambling platform users tend to consider perceived enjoyment, and convenience of the games as the more attracting factors of all. The need for advance security technology adaption, and creating positive public image with enterprise social responsibility can potentially decrease general public''s negative perception toward online gambling platform in which may overcome the barriers.

目　次

目　次 III
表目錄 V
圖目錄 VI
第一章 緒論 1
第一節 研究背景與動機 1
第二節 研究目的 7
第二章 文獻探討 8
第一節 視訊串流的技術發展 8
第二節 線上博弈之技術應用 10
第三節 態度與意圖 13
第四節 行為推理理論 15
第五節 知覺享樂性 18
第六節 便利性 20
第七節 認知安全性 22
第八節 創新抵制與知覺障礙 24
第九節 線上博弈的相關研究 27
第三章 研究方法 31
第一節 研究架構 31
第二節 研究假說 32
第三節 操作型定義與衡量問項 35
第四節 資料蒐集 45
第五節 資料分析方法 46
第六節 問卷設計 49
第四章 資料分析與探討 51
第一節 問卷基本資訊與回收 51
第二節 敘述性統計分析 51
第三節 信度與效度分析 54
第四節 假說檢定 57
第五章 結論與建議 64
第一節 結論 64
第二節 研究限制 68
第三節 管理實務上的建議 69
參考文獻 72

表目錄

表3-1 信念與價值觀量表 37
表3-2 採用態度量表 38
表3-3 採用意圖量表 39
表3-4 知覺享樂性量表 40
表3-5 便利性量表 41
表3-6 認知安全性量表 42
表3-7 知覺障礙量表 43
表4-1 敘述性統計樣本分佈(性別、年齡區間、學歷、行業別) 53
表4-2 敘述性統計樣本分佈(使用線上博弈平台的經驗、使用線上博弈平台的載具) 54
表4-3 各構面題項因素負荷量分析表 55
表4-4 潛在構面之平均變異數萃取量(AVE)、組合信度(CR)和Cronbach’s α 56
表4-5 相關距陣與平均變異抽取量之平方根表 57
表4-6 模型路徑檢定表(Bootstrapping n = 2000) 59
表4-7 本研究假說檢定結果 60

圖目錄

圖1-1 2017Q1 akamai全球網路流量使用分析表 2
圖1-2 直播服務收看類型分析圖表 3
圖1-3 全球線上博弈市場分析 2009 to 2018 4
圖1-4 老子有錢網站視訊博弈遊戲示意圖 6
圖2-1 視訊串流服務基本架構 9
圖2-2 電子程序模擬賭桌遊戲示意圖 11
圖2-3 視訊串流技術應用於線上博弈之架構概念圖 12
圖2-4 視訊串流技術應用於線上博弈示意圖 13
圖2-5 行為推理理論結構模型圖 17
圖3-1 研究架構與假說示意圖 31
圖4-1 本研究之路徑關係圖 58

中文文獻
[1]資誠聯合會計師事務所(2017)。『2017 全球與臺灣娛樂暨媒體業展望報告：使用者體驗 引領全球娛樂暨媒體業未來』。參閱時間：20170729。參閱網址：https://www.pwc.tw/zh/news/press-release/press-20170607.html。
[2]創市際市場研究顧問(2017)。『創市際2017合作專題一：台灣直播市場「台灣網友直播看什麼？」調查』。參閱時間：20170902。參閱網址：http://www.ixresearch.com/news/news_07_06_17
[3]鄭志強、李文中(2000)。網路影音即時播放－技術公開。台北：實書堂。
[4]張基成, & 顏啟芳. (2012). 以擴充的科技接受模式探討行動英語學習之接受度. 電子商務學報, 14(1), 97-119.
[5]陳佳宏 (2014)，『以行為推理理論探討行動電話使用者對4G LTE之轉換』， 淡江大學資訊管理研究所學位論文(2014)
[6]廖珮瑧 ( 2015)，『以行為推理理論控討使用HCE手機信用卡之意願』，淡江大學資訊管理研究所學位論文( 2015)
[7]陳靜(2013)。『線上博弈遊戲消費行為研究』。銘傳大學傳播管理學系碩士班(2013)。
[8]古喜先 (2011)。『線上麻將遊戲玩家之行為與情緒探討』。世新大學資訊傳播研究所(2011)。
[9]楊雅鈞(2010)。『線上博弈網站服務品質、正向情緒與網站滿意度』東海大學管理碩士在職專班(2010)。
[10]王品勻(2010)。『線上博弈網站品質與資訊安全及隱私對網站滿意度與忠誠度之影響-享樂價值之中介角色』。東海大學管理碩士在職專班(2010)
[11]林娟娟, 林禹均, & 王舒民. (2010)。『網路消費者的知覺風險對其購買態度及意願之研究-以網路購物經驗與退貨經驗為調節變數』. Electronic Commerce Studies, 8(1), 37-70.

英文文獻
[1]Ajzen, I. (1985). From intentions to actions: A theory of planned behavior. In Action control (pp. 11-39). Springer Berlin Heidelberg.
[2]Akamai international co., Ltd.(2017). akamai’s [state of the internet] Q1 2017 report. Reference time: 20170305. Reference website: https://www.akamai.com/fr/fr/multimedia/documents/state-of-the-internet/q1-2017-state-of-the-internet-connectivity-report.pdf
[3]Ahn, T., Ryu, S., & Han, I. (2007). The impact of Web quality and playfulness on user acceptance of online retailing. Information & management, 44(3), 263-275.
[4]Atkinson, M., & Kydd, C. (1997). Individual characteristics associated with World Wide Web use: an empirical study of playfulness and motivation. ACM SIGMIS Database: the DATABASE for Advances in Information Systems, 28(2), 53-62.
[5]Barich, H., & Kotler, P. (1991). A framework for marketing image management. MIT Sloan Management Review, 32(2), 94.
[6]Bagozzi, R. P., Henderson, G., Dabholkar, P. A., & Iacobucci, D. (1996). Network analyses of hierarchical cognitive connections between concrete and abstract goals: An application to consumer recycling attitudes and behaviors.
[7]Berry, L. L., Seiders, K., & Grewal, D. (2002). Understanding service convenience. Journal of marketing, 66(3), 1-17.
[8]Bruner II, G. C., & Kumar, A. (2005). Explaining consumer acceptance of handheld Internet devices. Journal of business research, 58(5), 553-558.
[9]Brown, J. S., Collins, A., & Duguid, P. (1989). Situated cognition and the culture of learning. Educational researcher, 18(1), 32-42.
[10]Bollen, K. A., & Stine, R. A. (1992). Bootstrapping goodness-of-fit measures in structural equation models. Sociological Methods & Research, 21(2), 205-229.
[11]Chen, P., Lin, J. J., Lu, C. S., Ong, C. T., Hsieh, P. F., Yang, C. C., ... & Yu, H. Y. (2011). Carbamazepine-induced toxic effects and HLA-B* 1502 screening in Taiwan. New England Journal of Medicine, 364(12), 1126-1133.
[12]Claudy, M. C., & Peterson, M. (2014). Understanding the underutilization of urban bicycle commuting: A behavioral reasoning perspective. Journal of Public Policy & Marketing, 33(2), 173-187.
[13]Crosby, L. A., Evans, K. R., & Cowles, D. (1990). Relationship quality in services selling: an interpersonal influence perspective. The journal of marketing, 68-81.
[14]Cyr, D., Head, M., & Ivanov, A. (2006). Design aesthetics leading to m-loyalty in mobile commerce. Information & Management, 43(8), 950-963.
[15]Davis, F. D., Bagozzi, R. P., & Warshaw, P. R. (1992). Extrinsic and intrinsic motivation to use computers in the workplace. Journal of applied social psychology, 22(14), 1111-1132.
[16]Efron, B. (1979). Computers and the theory of statistics: thinking the unthinkable. SIAM review, 21(4), 460-480.
[17]Entrepreneur international co., Ltd.(2017). The History of Online Gambling (Infographic). Reference time: 20170421. Reference website: https://www.entrepreneur.com/article/288918
[18]Fishbein, M. (1963). An investigation of the relationships between beliefs about an object and the attitude toward that object. Human relations, 16(3), 233-239.
[19]Fishbein, M., & Ajzen, I. (1975). Belief, attitude, intention and behavior: An introduction to theory and research.
[20]Fornell, C., & Lacker, D. F. (1981). Evaluating structural equation modeling for travel behavior research. Transportation research part B, University of Michigan, 37, 1-25.
[21]Gainsbury, S., Wood, R., Russell, A., Hing, N., & Blaszczynski, A. (2012). A digital revolution: Comparison of demographic profiles, attitudes and gambling behavior of Internet and non-Internet gamblers. Computers in Human Behavior, 28(4), 1388-1398.
[22]Gainsbury, S. M., Suhonen, N., & Saastamoinen, J. (2014). Chasing losses in online poker and casino games: Characteristics and game play of Internet gamblers at risk of disordered gambling. Psychiatry research, 217(3), 220-225.
[23]Gainsbury, S. M., Russell, A., Hing, N., Wood, R., Lubman, D., & Blaszczynski, A. (2015). How the Internet is changing gambling: Findings from an Australian prevalence survey. Journal of Gambling Studies, 31(1), 1-15.
[24]Gehrt, K. C., & Yale, L. J. (1993). The dimensionality of the convenience phenomenon: A qualitative reexamination. Journal of Business and Psychology, 8(2), 163-180.
[25]Gefen, D., Straub, D., & Boudreau, M. C. (2000). Structural equation modeling and regression: Guidelines for research practice. Communications of the association for information systems, 4(1), 7.
[26]Griffith, D. A., Krampf, R. F., & Palmer, J. W. (2001). The role of interface in electronic commerce: Consumer involvement with print versus on-line catalogs. International Journal of Electronic Commerce, 5(4), 135-153.
[27]Hair, J. F., Black, W. C., Babin, B. J., Anderson, R. E., & Tatham, R. L. (1998). Multivariate data analysis (Vol. 5, No. 3, pp. 207-219). Upper Saddle River, NJ: Prentice hall.
[28]Hamari, J., Sjöklint, M., & Ukkonen, A. (2016). The sharing economy: Why people participate in collaborative consumption. Journal of the Association for Information Science and Technology, 67(9), 2047-2059.
[29]Hsu, F. C., Luo, J. Y., Yeh, K. W., Chen, T. K., Huang, T. W., Wu, P. M., ... & Wu, M. K. (2008). Superconductivity in the PbO-type structure α-FeSe. Proceedings of the National Academy of Sciences, 105(38), 14262-14264.
[30]Hovland, C. I., & Rosenberg, M. J. (Eds.). (1960). Attitude organization and change. Yale University Press.
[31]Hoque, A. Y., & Lohse, G. L. (1999). An information search cost perspective for designing interfaces for electronic commerce. Journal of marketing research, 387-394.
[32]Hossain, M. M., & Prybutok, V. R. (2008). Consumer acceptance of RFID technology: An exploratory study. IEEE transactions on engineering management, 55(2), 316-328.
[33]Hulland, J. (1999). Use of partial least squares (PLS) in strategic management research: A review of four recent studies. Strategic management journal, 195-204.
[34]James D. Westaby(2005). Behavioral reasoning theory: Identifying new linkages underlying intentions and behavior. Organizational Behavior and Human Decision Processes 98 (2005) 97–120
[35]Kim, H. W., Chan, H. C., & Gupta, S. (2007). Value-based adoption of mobile internet: an empirical investigation. Decision support systems, 43(1), 111-126.
[36]Kim, H. Y., Shim, Y. M., Lee, K. S., Han, J., Yi, C. A., & Kim, Y. K. (2007). Persistent pulmonary nodular ground-glass opacity at thin-section CT: histopathologic comparisons. Radiology, 245(1), 267-275.
[37]Kim, H. S., Wohl, M. J., Salmon, M. M., Gupta, R., & Derevensky, J. (2015). Do social casino gamers migrate to online gambling? An assessment of migration rate and potential predictors. Journal of Gambling Studies, 31(4), 1819-1831
[38]Khodawandi, D., Pousttchi, K., & Wiedemann, D. G. (2003). Akzeptanz mobiler Bezahlverfahren in Deutschland.
[39]Krech, D., Crutchfield, R. S., & Ballachey, E. L. (1962). Individual in society.
[40]Kotler, P., Saliba, S., & Wrenn, B. (1991). Marketing management: Analysis, planning, and control: Instructor''s Manual. Prentice-hall.
[41]Kuisma, T., Laukkanen, T., & Hiltunen, M. (2007). Mapping the reasons for resistance to Internet banking: A means-end approach. International Journal of Information Management, 27(2), 75-85.
[42]Kuisma, T., Laukkanen, T. and Hiltunen, M. (2007). “Mapping the reasons for resistance to internet banking: a eans-end approach”, Int J Inform Manage, 27(2), 75-85.
[43]Laukkanen, T., Sinkkonen, S., Kivijärvi, M., & Laukkanen, P. (2007). Innovation resistance among mature consumers. Journal of Consumer Marketing, 24(7), 419-427.
[44]Lee, M. K., & Turban, E. (2001). A trust model for consumer internet shopping. International Journal of electronic commerce, 6(1), 75-91.
[45]Loroz, P. S. (2004). Golden‐age gambling: Psychological benefits and self‐concept dynamics in aging consumers'' consumption experiences. Psychology & Marketing, 21(5), 323-349.
[46]Mallat, N., Rossi, M., Tuunainen, V.K. and Oorni, A. (2006). “The impact of use situation and mobility on the acceptance of mobile ticketing services”, Proceedings of the 39th Hawaii International Conference on System Science, USA. Marketing”, Journal of Consumer Marketing, 6(3), 13-19.
[47]McCormack, A., Shorter, G. W., & Griffiths, M. D. (2014). An empirical study of gender differences in online gambling. Journal of Gambling Studies, 30(1), 71-88
[48]Moon, J. W., & Kim, Y. G. (2001). Extending the TAM for a World-Wide-Web context. Information & management, 38(4), 217-230.
[49]O’Loughlin, I., & Blaszczynski, A. (2017). Comparative Effects of Differing Media Presented Advertisements on Male Youth Gambling Attitudes and Intentions. International Journal of Mental Health and Addiction, 1-15.
[50]Hayashi, F. (2008). Does Safety Matter? Consumer Payment Choice and Perceived Safety of Payment Methods. unpublished paper, June.
[51]Hayashi, F. (2012). Mobile payments: What''s in it for consumers? Economic Review-Federal Reserve Bank of Kansas City, 35.
[52]Pavlou, P. A., & Fygenson, M. (2006). Understanding and predicting electronic commerce adoption: An extension of the theory of planned behavior. MIS quarterly, 115-143.
[53]Petty, R. E., Cacioppo, J. T., & Goldman, R. (1981). Personal involvement as a determinant of argument-based persuasion. Journal of personality and social psychology, 41(5), 847.
[54]Papacharissi, Z., & Rubin, A. M. (2000). Predictors of Internet use. Journal of broadcasting & electronic media, 44(2), 175-196.
[55]Pitt, H., Thomas, S. L., Bestman, A., Daube, M., & Derevensky, J. (2017). Factors that influence children’s gambling attitudes and consumption intentions: lessons for gambling harm prevention research, policies and advocacy strategies. Harm reduction journal, 14(1), 11.
[56]Ram, S., & Sheth, J. N. (1989). Consumer resistance to innovations: the marketing problem and its solutions. Journal of Consumer Marketing, 6(2), 5-14.
[57]Ringe, C. M., Wende, S., & Will, A. (2005). Smart PLS 2.0 (M3).
[58]Rosenberg, M. J., & Hovland, C. I. (1966). Attitude organization and change: An analysis of consistency among attitude components.
[59]Royne, M. B., Marian, L. and Jennifer, M. (2011). The public health implications of consumers'' environmental concern and their willingness to pay for an eco-friendly product. Journal of Consumer Affairs, 45(2), 329-343.
[60]Steenbergh, T. A., Meyers, A. W., May, R. K., & Whelan, J. P. (2002). Development and validation of the Gamblers'' Beliefs Questionnaire. Psychology of addictive behaviors, 16(2), 143.
[61]Sheth, J. N. (1981). An integrative theory of patronage preference and behavior (pp. 9-28). College of Commerce and Business Administration, Bureau of Economic and Business Research, University of Illinois, Urbana-Champaign.
[62]Siau, K., Sheng, H., Nah, F., & Davis, S. (2004). A qualitative investigation on consumer trust in mobile commerce. International Journal of Electronic Business, 2(3), 283-300.
[63]Teo, T. S., Lim, V. K., & Lai, R. Y. (1999). Intrinsic and extrinsic motivation in Internet usage. Omega, 27(1), 25-37.
[64]To, P. L., Liao, C., & Lin, T. H. (2007). Shopping motivations on Internet: A study based on utilitarian and hedonic value. Technovation, 27(12), 774-787.
[65]Van der Heijden, H. (2004). User acceptance of hedonic information systems. MIS quarterly, 695-704.
[66]Von Neumann, J., & Morgenstern, O. (1945). Theory of games and economic behavior. Bull. Amer. Math. Soc, 51(7), 498-504.
[67]Vijayasarathy, L. R. (2004). Predicting consumer intentions to use on-line shopping: the case for an augmented technology acceptance model. Information & management, 41(6), 747-762.
[68]Wu, D., Hou, Y. T., Zhu, W., Zhang, Y. Q., & Peha, J. M. (2001). Streaming video over the Internet: approaches and directions. IEEE Transactions on circuits and systems for video technology, 11(3), 282-300
[69]Wold, S., Ruhe, A., Wold, H., & Dunn, III, W. J. (1984). The collinearity problem in linear regression. The partial least squares (PLS) approach to generalized inverses. SIAM Journal on Scientific and Statistical Computing, 5(3), 735-743.
[70]Yale, L., & Venkatesh, A. (1986). Toward the construct of convenience in consumer research. ACR North American Advances.
[71]Yang, Z., & Jun, M. (2002). Consumer perception of e-service quality: from internet purchaser and non-purchaser perspectives. Journal of Business strategies, 19(1), 19.
[72]Zhang, M., Zhao, L., Tang, Y., Luo, J. G., & Yang, S. Q. (2005, November). Large-scale live media streaming over peer-to-peer networks through global internet. In Proceedings of the ACM workshop on Advances in peer-to-peer multimedia streaming (pp. 21-28). ACM.