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題名 消費者採用即時通訊應用程式 之決策因素
The research of the key factors of adopting Mobile Instant Messenger
作者 馮千晏
貢獻者 黃思明<br>白佩玉
馮千晏
關鍵詞 即時通訊應用程式
科技接受模式
貼圖愉悅性
結構方程模式
LISREL
日期 2012
上傳時間 2-九月-2013 15:16:12 (UTC+8)
摘要 隨著智慧型手機逐漸取代功能型手機及3G手機網路普及，即時通訊應用程式(Mobile Instant Messenger，MIM)成為新的溝通管道，尤其在低成本且具即時性的特性下，越來越多人傾向使用即時通訊應用程式作為溝通的工具，從2013年跨年簡訊量減少三成的比例來看，未來即時通訊應用程式取代傳統簡訊是指日可待的，因此即時通訊應用程式的重要性也越來越高，但即時通訊應用程式之相關學術研究仍趨於少數，較多為即時通訊軟體(Instant Messenger)。
參照即時傳訊軟體以及現有的對於MIM的相關研究後，本研究採用科技採用模式(Technology Acceptance Model 3，TAM3) 理論探討知覺有用性、知覺易用性、系統愉悅性及貼圖愉悅性對使用者採用即時通訊應用程式之使用意向的影響，同時以LISREL統計軟體進行結構方程式的分析。
本研究中發現貼圖愉悅性對於知覺有用性、知覺易用性與系統愉悅性具顯著的正向影響，在過去文獻中未有人討論貼圖對於即時通訊軟體之影響，而本研究證實其為科技採用中的前導因素，將即時通訊應用程式的研究範圍更加多元化與完整性，作為後續研究的參考。
參考文獻 中文文獻
1. 丁鴻裕(2011)。消費者行動App使用現況分析。產業情報研究所(報告編號：CDOC20111228016)
2. 蘇文彬(2013)。即時通訊軟體流行影響，跨年簡訊銳減1至3成。2013年5月30日，取自iThome Online，網址：http://www.ithome.com.tw/
3. 蘇伯方(2004)，即時傳訊軟體採用模式之研究，國立中山大學傳播管理研究所碩士論文，2004。
4. 2012國人智慧型手機使用行為大調查(2013)，台灣數位匯流發展協會。

日文文獻
まつもとあつし, コグレマサト(2012)。LINE なぜ若者たちは無料通話&メールに飛びついたのか?。ISBN978-4-8399-4488-9

英文文獻
1. Ajzen, I. & Fishbein, M. (1980). Understanding attitudes and predicting social behavior. Englewood Cliffs, NJ: Prentice-Hall.
2. Ajzen, I. (1991). The Theory of Planned Behavior. Organizational Behavior and Human Decision Processes, 50(2), 179-211.
3. Ajzen, I. (1998). Attitudes, Personality and Behaviour. Chicago, IL: The Dorsey Press.
4. Bagozzi, R. P., and Yi, Y. (1998), On the Evaluation of Structural Equation Models, Journal of the Academy of Marketing Science, 16 (1), 76-94.
5. Browne, M.W., & Cudeck, R. (1993). Alternative ways of assessing model fit. In K. A. Bollen & J. S. Long (Eds.), Testing structural equation models (pp. 136–162). Newbury Park, CA: Sage
6. Cuieford, 1965. Fundamental Statistics in Psychology and Education. 4th ed., New York: McGraw-Hill.
7. Compeau, D. R., & Higgins, C. A. (1995a). Application of social cognitive theory to training for computer skills. Information Systems Research, 6, 118–143.
8. Davis, F. D., Bagozzi, R.P., & Warshaw, P. R.(1989). User acceptance of computer technology: A comparison of two theorical models. Management Science, 35(8), 982-1103
9. Jiang Guoyin, Deng Wenjuan.(2011), An empirical analysis of factors influencing the adoption of Mobile Instant Messaging in China. International Journal of Mobile Communications,9(6),2011. 563-583.
10. Grinter, R., & Palen, L. (2002). Instant messaging in teen life. In Proceedings ACM CSCW 2002 (pp. 21–30). New Orleans, LA: ACM Press.
11. Harrison, D. A., Mykytyn, P. P., & Riemenschneider, C. K. (1997). Executive decisions about adoption of information technology in small business: theory and empirical tests. Information Systems Research, 8(2), 171-195.
12. Harpreet Singh (2012). Top 10 social messaging apps, Retrieved May 25, 2013, from Hindustan Times. Web site: http://www.hindustantimes.com/Technology/technology-review-application/SecLid.aspx
13. Hartwick, J. and H. Barki, (1994), Explaining the Role of User Participation in Information System Use. Management Science, 40(4), 440-465.
14. Hu, L., & Bentler, P. M. (1999). Cutoff criteria for fit indexes in covariance structure analysis: Conventional criteria versus new alternatives. Structural Equation Modeling, 6, 1–55.
15. Jöreskog, K. G., & Sorbom, D. (2004). LISREL 8.7.Lincolnwood, IL: Scientific Software International, Inc.
16. Kelman, H. C.(1958). Compliance, identification and internalization: three processes of attitude change. Journal of Conflict Resolution, 2, 51-60.
17. Yeung Ken,(2013). WhatsApp processed a whopping (record) 18 billion messages on the last day of 2012, Retrieved February 20, 2013, from The Next Web. Web Site: http://thenextweb.com/
18. Kerlinger, F. N., & Lee, H. B. (2000). Foundations of behavioral research, 4th ed. Holt, NY: Harcourt College Publishers.
19. Laurence Goasduff. (2007). Gartner Predicts Instant Messaging Will Be De Facto Tool for Voice, Video and Text Chat by The End of 2011. Retrieved May 30, 2013, from Gartner. Web Site: http://www.gartner.com/
20. Lee, Y., Lee, J., Lee, Z. (2006). Social Influence on Technology Acceptance Behavior: Self-Identity Theory Perspective, Database for Advances in Information Systems,37(2/3), 60-75.
21. McDonald, R.P. and Ho, M.-H.R. (2002), Principles and Practice in Reporting Statistical Equation Analyses, Psychological Methods, 7 (1), 64-82.
22. Moor, G. C., & Benbasat, I. (1991). Development of an instrument to measure the perceptions of adopting an information technology innovation. Information Systems Research, 2, 192-222.
23. Nardi, B. A., Whittaker, S., & Bradner, E. (2000). Interaction and Outeraction: Instant Messaging in Action. Paper presented at the Computer Supported Cooperative Work, New Orleans, Louisiana, USA.
24. Neha Dharia(2012). Ovum estimates that operators lost $13.9bn in 2011 due to social messaging. Retrieved February 11, 2013, from Ovum. Web site: http://ovum.com/
25. Richard Glass, Suhong Li.(2010). Social influence and instant messaging adoption. Journal of Computer Information Systems,51(2). 24-30
26. Rogers, Everett M.(1983), Diffusion of Innovations: Third Ed. New York: Fee press.
27. Zhou Tao , Lu Yaobin.(2011, ). Examining mobile instant messaging user loyalty from the perspectives of network externalities and flow experience. Computers in Human Behavior, 27(2). 883-889.
28. Venkatesh, V. (2000). Determinants of perceived ease of use: Integrating perceived behavioral control, computer anxiety and enjoyment into the technology acceptance model. Information Systems Research, 11, 342–365.
29. Venlatesh, V., & Davis, F. D.(2000). A theoretical extension of the technology acceptance model: Four longitudinal studies. Management Science, 46(2), 186-204.
30. Venkatesh, V., Morris, M. G., Davis, G. B., & Davis, F. D. (2003). User acceptance of information technology: Toward a unified view. MIS Quarterly, 27, 425–478.
31. Venlatesh, V., & Hillol Bala. (2008). Technology Acceptance Model 3 and a Research Agenda on Interventions. Decision Sciences, 39(2), 273-315.
32. Wang, Y., Lin, H., Luanm, P.(2006). Predicting consumer intention to use mobile service. Information Systems Journal 16, 157-179.
33. Webster, J., & Martocchio, J. J. (1992). Microcomputer playfulness: Development of a measure with workplace implications. MIS Quarterly, 16, 201–226.
34. Wilkie, W.L (1994), Consumer Behavior, 3rd ed., New York: John Wiley and Sons Inc.
35. Liu Zhenhua, Min Qingfei (2011). A study of Mobile Instant Messaging adoption: within-culture variation. International Journal of Mobile Communications,9,3,2011. 280-297.
36. Deng, Z., Lu, Y., Wei, K. K., & Zhang, J. (2010). Understanding customer satisfaction and loyalty: An empirical study of mobile instant messages in China. International Journal of Information Management, 30(4), 289-300.
描述 碩士
國立政治大學
企業管理研究所
100355045
101
資料來源 http://thesis.lib.nccu.edu.tw/record/#G1003550451
資料類型 thesis
dc.contributor.advisor 黃思明<br>白佩玉zh_TW
dc.contributor.author (作者) 馮千晏zh_TW
dc.creator (作者) 馮千晏zh_TW
dc.date (日期) 2012en_US
dc.date.accessioned 2-九月-2013 15:16:12 (UTC+8)-
dc.date.available 2-九月-2013 15:16:12 (UTC+8)-
dc.date.issued (上傳時間) 2-九月-2013 15:16:12 (UTC+8)-
dc.identifier (其他 識別碼) G1003550451en_US
dc.identifier.uri (URI) http://nccur.lib.nccu.edu.tw/handle/140.119/59229-
dc.description (描述) 碩士zh_TW
dc.description (描述) 國立政治大學zh_TW
dc.description (描述) 企業管理研究所zh_TW
dc.description (描述) 100355045zh_TW
dc.description (描述) 101zh_TW
dc.description.abstract (摘要) 隨著智慧型手機逐漸取代功能型手機及3G手機網路普及，即時通訊應用程式(Mobile Instant Messenger，MIM)成為新的溝通管道，尤其在低成本且具即時性的特性下，越來越多人傾向使用即時通訊應用程式作為溝通的工具，從2013年跨年簡訊量減少三成的比例來看，未來即時通訊應用程式取代傳統簡訊是指日可待的，因此即時通訊應用程式的重要性也越來越高，但即時通訊應用程式之相關學術研究仍趨於少數，較多為即時通訊軟體(Instant Messenger)。
參照即時傳訊軟體以及現有的對於MIM的相關研究後，本研究採用科技採用模式(Technology Acceptance Model 3，TAM3) 理論探討知覺有用性、知覺易用性、系統愉悅性及貼圖愉悅性對使用者採用即時通訊應用程式之使用意向的影響，同時以LISREL統計軟體進行結構方程式的分析。
本研究中發現貼圖愉悅性對於知覺有用性、知覺易用性與系統愉悅性具顯著的正向影響，在過去文獻中未有人討論貼圖對於即時通訊軟體之影響，而本研究證實其為科技採用中的前導因素，將即時通訊應用程式的研究範圍更加多元化與完整性，作為後續研究的參考。		zh_TW
dc.description.tableofcontents 第一章 緒論 1
第一節、 研究背景 1
第二節、 研究動機與目的 1
第三節、 研究流程與架構 2
第二章 文獻探討 3
第一節、 即時通訊應用程式定義(Mobile Instant Messenger) 3
第二節、 使用行為之理論 11
第三節、 科技接受模式(Technology Acceptance Model) 14
第四節、 文獻整理小結 20
第三章 研究架構與方法 21
第一節、 研究架構 21
第二節、 變數定義與操作化 22
第三節、 研究假說 22
第四節、 問卷設計 24
第五節、 問卷發放與整理 29
第六節、 資料分析方法 29
第四章 資料分析與結果 30
第一節、 研究樣本特徵描述與分析 30
第二節、 因素分析與效度分析 38
第三節、 信度分析 40
第四節、 變項與各知覺構面之差異性分析 41
第五節、 相關性分析 56
第六節、 「即時通訊軟體採用行為模式之驗證」 57
第五章 結論與建議 65
第一節、 研究結論 65
第二節、 研究貢獻 65
第三節、 研究限制 66
第四節、 後續研究建議 67
參考文獻 68
附錄－問卷 72		zh_TW
dc.format.extent 1759243 bytes-
dc.format.mimetype application/pdf-
dc.language.iso en_US-
dc.source.uri (資料來源) http://thesis.lib.nccu.edu.tw/record/#G1003550451en_US
dc.subject (關鍵詞) 即時通訊應用程式zh_TW
dc.subject (關鍵詞) 科技接受模式zh_TW
dc.subject (關鍵詞) 貼圖愉悅性zh_TW
dc.subject (關鍵詞) 結構方程模式zh_TW
dc.subject (關鍵詞) LISRELzh_TW
dc.title (題名) 消費者採用即時通訊應用程式 之決策因素zh_TW
dc.title (題名) The research of the key factors of adopting Mobile Instant Messengeren_US
dc.type (資料類型) thesisen
dc.relation.reference (參考文獻) 中文文獻
1. 丁鴻裕(2011)。消費者行動App使用現況分析。產業情報研究所(報告編號：CDOC20111228016)
2. 蘇文彬(2013)。即時通訊軟體流行影響，跨年簡訊銳減1至3成。2013年5月30日，取自iThome Online，網址：http://www.ithome.com.tw/
3. 蘇伯方(2004)，即時傳訊軟體採用模式之研究，國立中山大學傳播管理研究所碩士論文，2004。
4. 2012國人智慧型手機使用行為大調查(2013)，台灣數位匯流發展協會。

日文文獻
まつもとあつし, コグレマサト(2012)。LINE なぜ若者たちは無料通話&メールに飛びついたのか?。ISBN978-4-8399-4488-9

英文文獻
1. Ajzen, I. & Fishbein, M. (1980). Understanding attitudes and predicting social behavior. Englewood Cliffs, NJ: Prentice-Hall.
2. Ajzen, I. (1991). The Theory of Planned Behavior. Organizational Behavior and Human Decision Processes, 50(2), 179-211.
3. Ajzen, I. (1998). Attitudes, Personality and Behaviour. Chicago, IL: The Dorsey Press.
4. Bagozzi, R. P., and Yi, Y. (1998), On the Evaluation of Structural Equation Models, Journal of the Academy of Marketing Science, 16 (1), 76-94.
5. Browne, M.W., & Cudeck, R. (1993). Alternative ways of assessing model fit. In K. A. Bollen & J. S. Long (Eds.), Testing structural equation models (pp. 136–162). Newbury Park, CA: Sage
6. Cuieford, 1965. Fundamental Statistics in Psychology and Education. 4th ed., New York: McGraw-Hill.
7. Compeau, D. R., & Higgins, C. A. (1995a). Application of social cognitive theory to training for computer skills. Information Systems Research, 6, 118–143.
8. Davis, F. D., Bagozzi, R.P., & Warshaw, P. R.(1989). User acceptance of computer technology: A comparison of two theorical models. Management Science, 35(8), 982-1103
9. Jiang Guoyin, Deng Wenjuan.(2011), An empirical analysis of factors influencing the adoption of Mobile Instant Messaging in China. International Journal of Mobile Communications,9(6),2011. 563-583.
10. Grinter, R., & Palen, L. (2002). Instant messaging in teen life. In Proceedings ACM CSCW 2002 (pp. 21–30). New Orleans, LA: ACM Press.
11. Harrison, D. A., Mykytyn, P. P., & Riemenschneider, C. K. (1997). Executive decisions about adoption of information technology in small business: theory and empirical tests. Information Systems Research, 8(2), 171-195.
12. Harpreet Singh (2012). Top 10 social messaging apps, Retrieved May 25, 2013, from Hindustan Times. Web site: http://www.hindustantimes.com/Technology/technology-review-application/SecLid.aspx
13. Hartwick, J. and H. Barki, (1994), Explaining the Role of User Participation in Information System Use. Management Science, 40(4), 440-465.
14. Hu, L., & Bentler, P. M. (1999). Cutoff criteria for fit indexes in covariance structure analysis: Conventional criteria versus new alternatives. Structural Equation Modeling, 6, 1–55.
15. Jöreskog, K. G., & Sorbom, D. (2004). LISREL 8.7.Lincolnwood, IL: Scientific Software International, Inc.
16. Kelman, H. C.(1958). Compliance, identification and internalization: three processes of attitude change. Journal of Conflict Resolution, 2, 51-60.
17. Yeung Ken,(2013). WhatsApp processed a whopping (record) 18 billion messages on the last day of 2012, Retrieved February 20, 2013, from The Next Web. Web Site: http://thenextweb.com/
18. Kerlinger, F. N., & Lee, H. B. (2000). Foundations of behavioral research, 4th ed. Holt, NY: Harcourt College Publishers.
19. Laurence Goasduff. (2007). Gartner Predicts Instant Messaging Will Be De Facto Tool for Voice, Video and Text Chat by The End of 2011. Retrieved May 30, 2013, from Gartner. Web Site: http://www.gartner.com/
20. Lee, Y., Lee, J., Lee, Z. (2006). Social Influence on Technology Acceptance Behavior: Self-Identity Theory Perspective, Database for Advances in Information Systems,37(2/3), 60-75.
21. McDonald, R.P. and Ho, M.-H.R. (2002), Principles and Practice in Reporting Statistical Equation Analyses, Psychological Methods, 7 (1), 64-82.
22. Moor, G. C., & Benbasat, I. (1991). Development of an instrument to measure the perceptions of adopting an information technology innovation. Information Systems Research, 2, 192-222.
23. Nardi, B. A., Whittaker, S., & Bradner, E. (2000). Interaction and Outeraction: Instant Messaging in Action. Paper presented at the Computer Supported Cooperative Work, New Orleans, Louisiana, USA.
24. Neha Dharia(2012). Ovum estimates that operators lost $13.9bn in 2011 due to social messaging. Retrieved February 11, 2013, from Ovum. Web site: http://ovum.com/
25. Richard Glass, Suhong Li.(2010). Social influence and instant messaging adoption. Journal of Computer Information Systems,51(2). 24-30
26. Rogers, Everett M.(1983), Diffusion of Innovations: Third Ed. New York: Fee press.
27. Zhou Tao , Lu Yaobin.(2011, ). Examining mobile instant messaging user loyalty from the perspectives of network externalities and flow experience. Computers in Human Behavior, 27(2). 883-889.
28. Venkatesh, V. (2000). Determinants of perceived ease of use: Integrating perceived behavioral control, computer anxiety and enjoyment into the technology acceptance model. Information Systems Research, 11, 342–365.
29. Venlatesh, V., & Davis, F. D.(2000). A theoretical extension of the technology acceptance model: Four longitudinal studies. Management Science, 46(2), 186-204.
30. Venkatesh, V., Morris, M. G., Davis, G. B., & Davis, F. D. (2003). User acceptance of information technology: Toward a unified view. MIS Quarterly, 27, 425–478.
31. Venlatesh, V., & Hillol Bala. (2008). Technology Acceptance Model 3 and a Research Agenda on Interventions. Decision Sciences, 39(2), 273-315.
32. Wang, Y., Lin, H., Luanm, P.(2006). Predicting consumer intention to use mobile service. Information Systems Journal 16, 157-179.
33. Webster, J., & Martocchio, J. J. (1992). Microcomputer playfulness: Development of a measure with workplace implications. MIS Quarterly, 16, 201–226.
34. Wilkie, W.L (1994), Consumer Behavior, 3rd ed., New York: John Wiley and Sons Inc.
35. Liu Zhenhua, Min Qingfei (2011). A study of Mobile Instant Messaging adoption: within-culture variation. International Journal of Mobile Communications,9,3,2011. 280-297.
36. Deng, Z., Lu, Y., Wei, K. K., & Zhang, J. (2010). Understanding customer satisfaction and loyalty: An empirical study of mobile instant messages in China. International Journal of Information Management, 30(4), 289-300.		zh_TW