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題名 行動裝置APP價值創新與擴散之研究─以LINE為例
A Research into the Value Creation and Diffusion of Mobile APPs on Cases of LINE
作者 黃詩貽
Huang, Szu Yi
貢獻者 姜國輝
Chiang, Kuo Huie
黃詩貽
Huang, Szu Yi
關鍵詞 創新擴散理論
思考可能性模式
延伸的科技接受度模型
個人涉入
應用程式內購買
innovation diffusion theory
elaboration likelihood model
extended technology acceptance model
Personal Involvement
in-App purchases
日期 2013
上傳時間 25-Aug-2014 15:16:06 (UTC+8)
摘要 自從Apple於2007年推出了第一隻iPhone,智慧型裝置的時代也來臨。HTC也從2008年開始陸續發表了數隻Android為系統的手機。iPhone與各廠牌Android系統手機的競爭炒熱了智慧型手機的市場。於2013年,智慧型手機的全球銷售量終於超過了一般功能性手機 (Feature Phone)。智慧型裝置的流行也帶動了行動應用程式(Mobile Apps)的發展。智慧型手機系統的兩大龍頭Google與Apple皆於2013年宣布其應用程式商店的應用程式數量已經超過五千萬,而且下載量也超過一百萬次。隨著應用程式產業的蓬勃發展,也出現了各式各樣的營利模式,其中應用內購買(In-App Purchasing)是最近比較流行的一種模式。
本研究試圖了解影響使用者購買應用程式內商品的變數,並以有多樣種類商品的LINE為研究案例。本研究的假設是建立於創新擴散理論(Innovation Diffusion Theory)、深思可能性模式(Elaboration Likelihood Model)以及延伸的科技接受度模型(Extended-TAM)。
本研究以問卷的方式調查使用者行為並收集了301個有效樣本,並以SmartPLS分析資料。研究結果發現:一、社會網絡對於使用者購買應用程式內商品的態度沒有直接關系;二、社會網絡影響使用者的感知趣味性以及個人涉入程度;三、使用者的感知趣味性以及個人涉入程度對於使用者購買應用程式內商品的態度有直接影響。
Since Apple introduced the first iPhone in 2007, the market share of smart devices is raging. HTC introduced several Android-based smart phones in 2008. The competition between iPhone and Android phones has heated up the market of smartphone. By 2013, worldwide sales of smartphones surpassed sales of feature phone. The prevailing state of smart devices has also stimulated the development of mobile application (Apps) industry. In year 2013, both Apple and Google announced that the number of Apps published in their stores has reached over 1 million Apps and the number of Apps downloaded has reached over 50 billion. Among all profit models of Apps, in-App purchasing is becoming the favorable one.
This study attempts to understand the causes that would influence users’ behavior when deciding to purchase products in Apps such as LINE. The model of the study is based on Innovation Diffusion Theory, Elaboration Likelihood Model (ELM) and the Extended Technology Acceptance Model (Extended-TAM).
In this study, data was collected from 301 valid respondents through both online questionnaires and paper copies. SmartPLS was employed as data analysis tools. Result revealed that: (1) Social network effects hardly have direct impact on the attitude toward in-App purchases; (2) Social network effects have impact on a user’s perceived playfulness and personal involvement; and (3) A user’s perceived playfulness and personal involvement have impact on the attitude toward in-App purchases.
參考文獻 [1] Afthanorhan, W. M. A. B. W. (2013). A Comparison Of Partial Least Square Structural Equation Modeling (PLS-SEM) and Covariance Based Structural Equation Modeling (CB-SEM) for Confirmatory Factor Analysis. International Journal Engineering and Science Innovative Technologies (IJESIT), 2(5), 8.
[2] App Annie and International Data Cooperation (2014). Mobile App Advertising and Monetization Trends 2012-2017: The Economics of Free. Retried from App Annie website: http://goo.gl/QPMgS3
[3] Bagozzi, R. P., & Yi, Y. (1988). On the evaluation structural equation models. Academic of Marketing Science, 16, 74-94
[4] Bagozzi, R. P., Davis, F. D., Warshaw, P. R. (1992), Development and test of a theory of technological learning and usage. Human Relations, 45(7), 660–686.
[5] Bhattacherjee, A., Hikmet, N. (2007). Physicians’ Resistance toward Healthcare Information Technology: A theoretical Model and Empirical Test. European Journal of Information Systems, 16 (6), 725-737.
[6] Booth-Butterfield, S., Welbourne, J. (2002). The Elaboration Likelihood Model: Its Impact on Persuasion Theory and Research. In J. P. Dillard & M. Pfau (eds.), the Persuasion Handbook: Developments in Theory and Practice. Thousand Oaks, CA: Sage, pp. 155-173
[7] Brancheau, J. C., Wetherbe, J. C. (1990). The Adoption of Spreadsheet Software: Testing Innovation Diffusion Theory in the Context of End-User Computing. Information Systems Research. 1(2), 115-143.
[8] Bruce, K. (2013). Use of mobile technology for monitoring and evaluation in international health and development programs [Abstract]. The University of North Carolina at Chapel Hill, California. Retrieved from ProQuest Dissertations & Theses.
[9] Chau, P.Y., Hu, P.J.H. (2001) Information Technology Acceptance by Individual Professionals: A Model Comparison Approach. Decision Sciences, 32(4), 699-719.
[10] Chiang, J. K., Hung, K.L. & Huang, S.Y. (2013, July). A Research into the Diffusion Effects of Free-Trial to Mobile Applications. Business Intelligence for Innovation, 國立政治大學商學院服務創新研究中心與資管系.
[11] Cooper, D. R., & Schindler, P. S. (2008). Business Research Methods 10th ed. New York, NY: McGraw-Hill
[12] Davis, F. D. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Quarterly, 13(3), 319–340.
[13] Flynn L.R., Goldsmith R.E. (1993). Application of the personal involvement inventory in marketing. Psychology & Marketing, 10(4), 357-366.
[14] Fornell, C., & Larcker, D. F. (1981). Evaluating structural equation models with unobservable variables and measurement error. Journal of Marketing Research, 18(3), 39-50.
[15] Forrest, C. (2014, March 21). Apple v. Google: The goliath deathmatch by the numbers in 2014. Tech Republic. Retrieved May 19, 2014, from http://www.techrepublic.com/article/apple-v-google-the-goliath-deathmatch-by-the-numbers-in-2014/
[16] Gartner Inc. (2014). Market Share Analysis: Mobile Phones, Worldwide, 4Q13 and 2013. Retrieved from Gartner website: https://www.gartner.com/doc/2665319
[17] Hair, J. F., Ringle, C. M., & Sarstedt, M. (2011). PLS-SEM: Indeed a silver bullet. The Journal of Marketing Theory and Practice, 19(2), 139-152.
[18] Heggestuen, J. (2013, December 19). Global Messaging App LINE Sees Explosive Revenue Growth from Stickers, Games, and Paid Accounts. Business Insider. Retrieved May 5, 2014, from http://www.businessinsider.com/line-is-not-just-about-sticker-revenue-2013-12
[19] Hong, K. (2014, February 6). Line shows the potential for chat apps as platforms, after chalking up $338m in revenue for 2013. The Next Web.com. Retrieved May 19, 2014, from http://thenextweb.com/apps/2014/02/06/line-shows-the-potential-for-chat-apps-as-platforms-after-chalking-up-338m-in-revenue-for-2013/
[20] Hsu, L.L. (2009). A Study on the Construction of a Diffusion of Innovation Model for Web-based Learning Communities. National Kaohsiung Normal University, Kaohsiung. Doctoral desertion retrieved from National Digital Library of Thesis and Dissertations in Taiwan.
[21] Hu, P.J., Chau, P.Y., Sheng, O.R.L., Tim, K.Y. (1999). Examining the Technology Acceptance of Telemedicine Technology. Journal of Management Information Systems, 16(2), 91-112.
[22] Huang, L. Y., & Hsieh, Y. J. (2011). “Predicting online game loyalty based on need gratification and experiential motives.” Internet Research, 21(5), 581-598.
[23] Ingraham, N. (2013, October 22). Apple Announces 1 Million Apps in the App Store, More Than 1 Billion Songs Played On iTunes Radio. The Verge. Retrieved March 8, 2014, from http://www.theverge.com/2013/10/22/4866302/apple-announces-1-million-apps-in-the-app-store
[24] Kim, D., Chang, H. (2007). Key Functional Characteristics in Designing and Operating Health Information Websites for User Satisfaction: An Application of the Extended Technology Acceptance Model. International Journal of Medical Informatics, 76 (11-12), 790-800.
[25] Klein, R. (2007). An Empirical Examination of Patient-physician Portal Acceptance. European Journal of Information Systems, 16(6), 751-760.
[26] Koetsier, J. (2014, March 27). Mobile app monetization: Freemium is king, but in-App ads are growing fast. VentureBeat. Retrieved June 19, 2014, from http://venturebeat.com/2014/03/27/mobile-app-monetization-freemium-is-king-but-in-App-ads-are-growing-fast/
[27] Moores, T.T. (2012). Towards and Integrated Model of IT Acceptance in Healthcare. Decision Support Systems, 53(3), 507-516.
[28] Petty R.E., Cacioppo, J.T. (1986). Involvement and Persuasion: Tradition versus Integration. Psychological Bulletin, 106 (3), 367-374.
[29] Petty R.E., Cacioppo, J.T., Strathman, A.J. (2005) To Think or Not to Think: Exploring Two Route to Persuation. In T.C. Brock and M. C. Green (eds.), Persuasion: Psychological Insights and Perspectives, 2nd. Thousand Oaks, CA: Sage, pp.81-116
[30] Richins M.L., Bloch P.H. (1986). After the New Wears off: The Temporal Context of Product Involvement. Journal of Consumer Research, 13 (2), 280-285.
[31] Rogers, E. M. (1983). Diffusion of innovations (3rd edition). New York: Free Press.
[32] Sun, Y.q., Wang, N., Gou, X.T., Peng, Z.Y. (2013). Understanding the Acceptance of Mobile Health Services: A comparison and Integration of Alternative Models. Journals of Electronic Commerce Research, 14(2), 183-200.
[33] Victor, H. (2013, July 24). Android`s Google Play beats App Store with over 1 million apps, now officially largest. Phonearena.com. Retrieved March 8, 2014 from http://www.phonearena.com/news/Androids-Google-Play-beats-App-Store-with-over-1-million-apps-now-officially-largest_id45680
[34] Webster J., Heian J.B., Michelman J.E., Computer training and computer anxiety in the educational process: an experimental analysis, in Proceedings of the Eleventh International Conference on Information Systems, 16-19 December 1990, Copenhagen, Denmark, pp. 171-182.
[35] Wu, J., & Liu, D. (2007). “The effects of trust and enjoyment on intention to play online games.” Journal of Electronic Commerce Research, 8(2), 128-140.
[36] Yu, C.S. (2012, August). A Novel VCC and Business Model for Designer Entrepreneurs. Global Business & International Management Conference, Portland.
[37] Zaichkowsky J.L. (1994). The Personal Involvement Inventory: Reduction, Revision, and Application to Advertising. Journal of Advertising, 23(4), 59-70
[38] 科技報橘 (2013年10月14日) App Store 有 76% 營收來自應用內購買,付費 App 大勢已去。2014年3月8日擷取自http://techorange.com/2013/10/14/in-App-purchase-is-the-trend/
[39] 唐錦超 (譯) (2006)。創新的擴散。台北市:遠流。(Rogers, E. M., 2003)
描述 碩士
國立政治大學
資訊管理研究所
101356011
102
資料來源 http://thesis.lib.nccu.edu.tw/record/#G0101356011
資料類型 thesis
dc.contributor.advisor 姜國輝zh_TW
dc.contributor.advisor Chiang, Kuo Huieen_US
dc.contributor.author (Authors) 黃詩貽zh_TW
dc.contributor.author (Authors) Huang, Szu Yien_US
dc.creator (作者) 黃詩貽zh_TW
dc.creator (作者) Huang, Szu Yien_US
dc.date (日期) 2013en_US
dc.date.accessioned 25-Aug-2014 15:16:06 (UTC+8)-
dc.date.available 25-Aug-2014 15:16:06 (UTC+8)-
dc.date.issued (上傳時間) 25-Aug-2014 15:16:06 (UTC+8)-
dc.identifier (Other Identifiers) G0101356011en_US
dc.identifier.uri (URI) http://nccur.lib.nccu.edu.tw/handle/140.119/69194-
dc.description (描述) 碩士zh_TW
dc.description (描述) 國立政治大學zh_TW
dc.description (描述) 資訊管理研究所zh_TW
dc.description (描述) 101356011zh_TW
dc.description (描述) 102zh_TW
dc.description.abstract (摘要) 自從Apple於2007年推出了第一隻iPhone,智慧型裝置的時代也來臨。HTC也從2008年開始陸續發表了數隻Android為系統的手機。iPhone與各廠牌Android系統手機的競爭炒熱了智慧型手機的市場。於2013年,智慧型手機的全球銷售量終於超過了一般功能性手機 (Feature Phone)。智慧型裝置的流行也帶動了行動應用程式(Mobile Apps)的發展。智慧型手機系統的兩大龍頭Google與Apple皆於2013年宣布其應用程式商店的應用程式數量已經超過五千萬,而且下載量也超過一百萬次。隨著應用程式產業的蓬勃發展,也出現了各式各樣的營利模式,其中應用內購買(In-App Purchasing)是最近比較流行的一種模式。
本研究試圖了解影響使用者購買應用程式內商品的變數,並以有多樣種類商品的LINE為研究案例。本研究的假設是建立於創新擴散理論(Innovation Diffusion Theory)、深思可能性模式(Elaboration Likelihood Model)以及延伸的科技接受度模型(Extended-TAM)。
本研究以問卷的方式調查使用者行為並收集了301個有效樣本,並以SmartPLS分析資料。研究結果發現:一、社會網絡對於使用者購買應用程式內商品的態度沒有直接關系;二、社會網絡影響使用者的感知趣味性以及個人涉入程度;三、使用者的感知趣味性以及個人涉入程度對於使用者購買應用程式內商品的態度有直接影響。
zh_TW
dc.description.abstract (摘要) Since Apple introduced the first iPhone in 2007, the market share of smart devices is raging. HTC introduced several Android-based smart phones in 2008. The competition between iPhone and Android phones has heated up the market of smartphone. By 2013, worldwide sales of smartphones surpassed sales of feature phone. The prevailing state of smart devices has also stimulated the development of mobile application (Apps) industry. In year 2013, both Apple and Google announced that the number of Apps published in their stores has reached over 1 million Apps and the number of Apps downloaded has reached over 50 billion. Among all profit models of Apps, in-App purchasing is becoming the favorable one.
This study attempts to understand the causes that would influence users’ behavior when deciding to purchase products in Apps such as LINE. The model of the study is based on Innovation Diffusion Theory, Elaboration Likelihood Model (ELM) and the Extended Technology Acceptance Model (Extended-TAM).
In this study, data was collected from 301 valid respondents through both online questionnaires and paper copies. SmartPLS was employed as data analysis tools. Result revealed that: (1) Social network effects hardly have direct impact on the attitude toward in-App purchases; (2) Social network effects have impact on a user’s perceived playfulness and personal involvement; and (3) A user’s perceived playfulness and personal involvement have impact on the attitude toward in-App purchases.
en_US
dc.description.tableofcontents List of Figure iii
List of Table iv
Chapter I. Introduction - 1 -
1.1. Research Background - 1 -
1.2. Research Motivation - 3 -
1.3. Research Objective - 5 -
1.4. Research Process - 7 -
Chapter II. Literature Review - 9 -
5.1 Diffusion of Innovation - 9 -
5.2 Extended Technology Acceptance Model (TAM) - 14 -
5.3 Elaborating Likelihood Model (ELM) - 15 -
5.4 Involvement - 18 -
5.5 Value Creation Cycle (VCC) - 19 -
Chapter III. Research Methodology - 21 -
3.1 Research Framework - 21 -
3.2 Hypothesis - 22 -
3.2.1 Social Network Effects and Perceived Playfulness - 22 -
3.2.2 Social Network Effects and Personal Involvement - 22 -
3.2.3 Perceived Playfulness and Attitude toward in-App Purchase - 23 -
3.2.4 Social Network Effects and Attitude toward in-App Purchase - 23 -
3.2.5 Personal Involvement and Attitude toward in-App Purchases - 23 -
3.2.6 Attitude toward in-Apps purchasing and Purchase Intention - 24 -
3.3 Variables and Operational Definitions - 24 -
3.3.1 Social Network Effects - 24 -
3.3.2 Perceived Playfulness - 26 -
3.3.3 Personal Involvement - 27 -
3.3.4 Attitude toward in-App Purchase - 29 -
3.3.5 Intention to perform in-App purchase - 30 -
3.4 Research Design - 31 -
3.4.1 Questionnaire Design - 31 -
3.4.2 Target Subjects - 31 -
3.4.3 Data Collection - 31 -
3.5 Data Analysis - 32 -
3.5.1 PLS-SEM - 32 -
3.5.2 Model Verification - 33 -
3.6 Pretest - 34 -
3.6.1 Demographic analysis for Pretest - 34 -
3.6.2 Measurement Assessment for Pretest - 36 -
Chapter IV. Result - 38 -
4.1 Demographic analysis - 39 -
4.2 Confirmatory Factor Analysis - 42 -
4.2.1 Reliability Test - 43 -
4.2.2 Validity Test - 43 -
4.3 Structural Model Assessment - 45 -
4.4 Hypothesis Testing - 47 -
Chapter V. Discussion - 48 -
5.1 Discussion - 48 -
5.1.1 Summary of Results - 48 -
5.1.2 Contribution and Key Insights - 49 -
5.2 Research Limitations - 50 -
5.3 Conclusion - 50 -
5.4 Future Research and Suggestions - 51 -
Reference - 52 -
Appendix I. Questionnaire of the Study - 57 -
zh_TW
dc.format.extent 2239872 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/#G0101356011en_US
dc.subject (關鍵詞) 創新擴散理論zh_TW
dc.subject (關鍵詞) 思考可能性模式zh_TW
dc.subject (關鍵詞) 延伸的科技接受度模型zh_TW
dc.subject (關鍵詞) 個人涉入zh_TW
dc.subject (關鍵詞) 應用程式內購買zh_TW
dc.subject (關鍵詞) innovation diffusion theoryen_US
dc.subject (關鍵詞) elaboration likelihood modelen_US
dc.subject (關鍵詞) extended technology acceptance modelen_US
dc.subject (關鍵詞) Personal Involvementen_US
dc.subject (關鍵詞) in-App purchasesen_US
dc.title (題名) 行動裝置APP價值創新與擴散之研究─以LINE為例zh_TW
dc.title (題名) A Research into the Value Creation and Diffusion of Mobile APPs on Cases of LINEen_US
dc.type (資料類型) thesisen
dc.relation.reference (參考文獻) [1] Afthanorhan, W. M. A. B. W. (2013). A Comparison Of Partial Least Square Structural Equation Modeling (PLS-SEM) and Covariance Based Structural Equation Modeling (CB-SEM) for Confirmatory Factor Analysis. International Journal Engineering and Science Innovative Technologies (IJESIT), 2(5), 8.
[2] App Annie and International Data Cooperation (2014). Mobile App Advertising and Monetization Trends 2012-2017: The Economics of Free. Retried from App Annie website: http://goo.gl/QPMgS3
[3] Bagozzi, R. P., & Yi, Y. (1988). On the evaluation structural equation models. Academic of Marketing Science, 16, 74-94
[4] Bagozzi, R. P., Davis, F. D., Warshaw, P. R. (1992), Development and test of a theory of technological learning and usage. Human Relations, 45(7), 660–686.
[5] Bhattacherjee, A., Hikmet, N. (2007). Physicians’ Resistance toward Healthcare Information Technology: A theoretical Model and Empirical Test. European Journal of Information Systems, 16 (6), 725-737.
[6] Booth-Butterfield, S., Welbourne, J. (2002). The Elaboration Likelihood Model: Its Impact on Persuasion Theory and Research. In J. P. Dillard & M. Pfau (eds.), the Persuasion Handbook: Developments in Theory and Practice. Thousand Oaks, CA: Sage, pp. 155-173
[7] Brancheau, J. C., Wetherbe, J. C. (1990). The Adoption of Spreadsheet Software: Testing Innovation Diffusion Theory in the Context of End-User Computing. Information Systems Research. 1(2), 115-143.
[8] Bruce, K. (2013). Use of mobile technology for monitoring and evaluation in international health and development programs [Abstract]. The University of North Carolina at Chapel Hill, California. Retrieved from ProQuest Dissertations & Theses.
[9] Chau, P.Y., Hu, P.J.H. (2001) Information Technology Acceptance by Individual Professionals: A Model Comparison Approach. Decision Sciences, 32(4), 699-719.
[10] Chiang, J. K., Hung, K.L. & Huang, S.Y. (2013, July). A Research into the Diffusion Effects of Free-Trial to Mobile Applications. Business Intelligence for Innovation, 國立政治大學商學院服務創新研究中心與資管系.
[11] Cooper, D. R., & Schindler, P. S. (2008). Business Research Methods 10th ed. New York, NY: McGraw-Hill
[12] Davis, F. D. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Quarterly, 13(3), 319–340.
[13] Flynn L.R., Goldsmith R.E. (1993). Application of the personal involvement inventory in marketing. Psychology & Marketing, 10(4), 357-366.
[14] Fornell, C., & Larcker, D. F. (1981). Evaluating structural equation models with unobservable variables and measurement error. Journal of Marketing Research, 18(3), 39-50.
[15] Forrest, C. (2014, March 21). Apple v. Google: The goliath deathmatch by the numbers in 2014. Tech Republic. Retrieved May 19, 2014, from http://www.techrepublic.com/article/apple-v-google-the-goliath-deathmatch-by-the-numbers-in-2014/
[16] Gartner Inc. (2014). Market Share Analysis: Mobile Phones, Worldwide, 4Q13 and 2013. Retrieved from Gartner website: https://www.gartner.com/doc/2665319
[17] Hair, J. F., Ringle, C. M., & Sarstedt, M. (2011). PLS-SEM: Indeed a silver bullet. The Journal of Marketing Theory and Practice, 19(2), 139-152.
[18] Heggestuen, J. (2013, December 19). Global Messaging App LINE Sees Explosive Revenue Growth from Stickers, Games, and Paid Accounts. Business Insider. Retrieved May 5, 2014, from http://www.businessinsider.com/line-is-not-just-about-sticker-revenue-2013-12
[19] Hong, K. (2014, February 6). Line shows the potential for chat apps as platforms, after chalking up $338m in revenue for 2013. The Next Web.com. Retrieved May 19, 2014, from http://thenextweb.com/apps/2014/02/06/line-shows-the-potential-for-chat-apps-as-platforms-after-chalking-up-338m-in-revenue-for-2013/
[20] Hsu, L.L. (2009). A Study on the Construction of a Diffusion of Innovation Model for Web-based Learning Communities. National Kaohsiung Normal University, Kaohsiung. Doctoral desertion retrieved from National Digital Library of Thesis and Dissertations in Taiwan.
[21] Hu, P.J., Chau, P.Y., Sheng, O.R.L., Tim, K.Y. (1999). Examining the Technology Acceptance of Telemedicine Technology. Journal of Management Information Systems, 16(2), 91-112.
[22] Huang, L. Y., & Hsieh, Y. J. (2011). “Predicting online game loyalty based on need gratification and experiential motives.” Internet Research, 21(5), 581-598.
[23] Ingraham, N. (2013, October 22). Apple Announces 1 Million Apps in the App Store, More Than 1 Billion Songs Played On iTunes Radio. The Verge. Retrieved March 8, 2014, from http://www.theverge.com/2013/10/22/4866302/apple-announces-1-million-apps-in-the-app-store
[24] Kim, D., Chang, H. (2007). Key Functional Characteristics in Designing and Operating Health Information Websites for User Satisfaction: An Application of the Extended Technology Acceptance Model. International Journal of Medical Informatics, 76 (11-12), 790-800.
[25] Klein, R. (2007). An Empirical Examination of Patient-physician Portal Acceptance. European Journal of Information Systems, 16(6), 751-760.
[26] Koetsier, J. (2014, March 27). Mobile app monetization: Freemium is king, but in-App ads are growing fast. VentureBeat. Retrieved June 19, 2014, from http://venturebeat.com/2014/03/27/mobile-app-monetization-freemium-is-king-but-in-App-ads-are-growing-fast/
[27] Moores, T.T. (2012). Towards and Integrated Model of IT Acceptance in Healthcare. Decision Support Systems, 53(3), 507-516.
[28] Petty R.E., Cacioppo, J.T. (1986). Involvement and Persuasion: Tradition versus Integration. Psychological Bulletin, 106 (3), 367-374.
[29] Petty R.E., Cacioppo, J.T., Strathman, A.J. (2005) To Think or Not to Think: Exploring Two Route to Persuation. In T.C. Brock and M. C. Green (eds.), Persuasion: Psychological Insights and Perspectives, 2nd. Thousand Oaks, CA: Sage, pp.81-116
[30] Richins M.L., Bloch P.H. (1986). After the New Wears off: The Temporal Context of Product Involvement. Journal of Consumer Research, 13 (2), 280-285.
[31] Rogers, E. M. (1983). Diffusion of innovations (3rd edition). New York: Free Press.
[32] Sun, Y.q., Wang, N., Gou, X.T., Peng, Z.Y. (2013). Understanding the Acceptance of Mobile Health Services: A comparison and Integration of Alternative Models. Journals of Electronic Commerce Research, 14(2), 183-200.
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