臺灣博碩士論文加值系統

論文摘要
隨著科技的快速發展，智慧型手機購物APP已儼然成為趨勢，現在民之生活重心也隨著擴展至流動場所，使用者利用智慧型手機所提供的行動資訊可在任何的時間、地點查詢的便利性，對傳統消費習慣的衝擊之大，也改變了過往傳統式的購物模式。透過行動APP的資訊提供更可讓消費者隨時隨地取得相關的購物資訊。因此，透過文獻彙整，試圖找出哪些因素會影響民眾使用智慧型手機購物APP之動機，並整提出研究模式，以探討使用者使用購物APP之主要因素為何。

本研究採用網路問卷調查及蒐集樣本，並連結於購物相關論壇、社群網站、PTT購物版。資料分析方法採結構化方程模式，並以SmartPLS2.0作為主要統計分析工具，驗證研究模式中個變數的因果關係。研究結果顯示，其中認知風險性和認知價格性不會直接影響使用意圖之外，智慧型手機購物APP之APP便利性、資訊豐富性、資訊品質、認知有用性、認知易用性、社會影響皆會影響使用意圖。

因此本研究探討使用智慧型手機購物APP之因素，能設計出讓民眾對智慧型手機購物APP，改變消費方式，提升最快的購物之效率。



關鍵字：APP便利性、資訊品質、資訊豐富性

Abstract
With the development of modern science and technology, using Shopping Apps on smart phone has become a general trend. People now focus our life on unsteady field instead of steady one.It is more convenient to use shopping apps on smart-phone people can look up the information they want at any time in any place. Using shopping apps on smart-phone make huge change to people's life. And it also changes the pattern of shopping habit on the past.People can get related shopping information from apps at any time they needed Thus, the result of our studies will show the key point to make people want to use the shopping apps. And reveal the model of research to discover other factors of using shopping apps.

This research is based on the data of questionnaire collecting from internet. And also public the questionnaire link on shopping forums and network soical media, The method of data analysis is based on the module equation. And use "SmartPLS2.0" as the major analysis tool to verify the realtion of variables, The result of research reveal the risk and price of acknowledge will not impact on the intention of using shopping apps directly, But the richness, quality of information and useful , easy to use of acknowledge and social influence will do,
Therefore, this research to investigate the key point of using shopping apps, to produce shopping apps that make people change the way in shopping and improve the affection.
Key words: App convenience、Information Quality、Information richness

目錄
目錄 i
表目錄 iii
圖目錄 iv
第一章 緒論 1
第一節 研究背景與動機 1
第二節 研究目的與問題 4
第三節 研究流程與論文架構 5
第二章 文獻探討 7
第一節 智慧型手機 7
第二節 科技接受模式 12
第三節 便利性 17
第四節 資訊豐富 19
第五節 資訊品質 20
第六節 認知風險 21
第七節 認知價格 22
第八節 社會影響 24
第三章 研究方法 26
第一節 研究架構 26
第二節 研究假設 28
第三節 變數之操作型定義 31
第四節 問卷設計 35
第五節 問卷調查與對象 39
第六節 資料分析方式 39
第四章 資料分析 43
第一節 樣本結構分析 43
第二節 信度與效度分析 45
第三節 研究假說之檢定 51
第五章 結論與建議 54
第一節 研究結論 54
第二節 研究貢獻 57
第三節 研究限制 58
第四節 未來研究方向 59
參考文獻 61
【中文部份】 61
【英文部份】 61
【網路資料部份】 66
附錄 研究問卷 67

參考文獻
【中文部份】
方世榮(民89)。購物環境、產品屬性、知覺風險與網路購物行為之研究，淡江大學國際貿學所碩士論文，未出版，新北市。
古佳禾(民104)。購物網站品質與購買意圖之比較研究:以行動版本與app版本為例，國立中央大學碩士論文，未出版，桃園市。
沈玉瑛(民89)。競爭策略與訂價策略配合對新產品績效影響之研究－以產品專利類型為分析，私立中原大學碩士論文，未出版，桃園市。
林欣欣(民103)。資訊品質與涉入程度對使用APP應用程式之行為意圖分析-以零售通路業為例，國立臺灣科技大學碩士論文，未出版，台北市。
許克銘(民104)。層級分析法於購物APP經營成功關鍵因素，國立虎尾科技大學碩士論文，未出版，雲林縣。
韓經綸(民83)。組織行為學理論。台北市：五南出版社。
【英文部份】
Agarwal, R., & Prasad, J. (1999). Are individual differences germane to the acceptance of new information technologies? Decision sciences, 30(2), 361-391.
Ahn, T., Ryu, S., & Han, I. (2005). The impact of the online and offline features on the user acceptance of Internet shopping malls. Electronic Commerce Research and Applications, 3(4), 405-420.
Ajzen, I. (1991). The theory of planned behavior. Organizational Behavior and Human Decision Processes, 50(2), 179-211.
Ajzen, I., & Fishbein, M. (1980). Understanding attitudes and predicting social behaviour.
Akaah, I. P., & Korgaonkar, P. K. (1988). A conjoint investigation of the relative importance of risk relievers in direct marketing. Journal of Advertising Research, 28(4), 38-44.
Andersson, P., & Heinonen, K. (2002). Acceptance of mobile services-insights from the Swedish market for mobile telephony.
Bauer, R. A. (1960). Consumer behavior as risk taking. Dynamic marketing for a changing world, 398.
Berry, L. L., Seiders, K., & Grewal, D. (2002). Understanding service convenience. Journal of marketing, 66(3), 1-17.
Bhattacherjee, A. (2000). Acceptance of e-commerce services: the case of electronic brokerages. Systems, Man and Cybernetics, Part A: Systems and Humans, IEEE Transactions on, 30(4), 411-420.
Biswas, A., & Blair, E. A. (1991). Contextual effects of reference prices in retail advertisements. The Journal of Marketing, 1-12.
Brown, L. G. (1990). Convenience in services marketing. Journal of Services Marketing, 4(1), 53-59.
Chin, W. W. (1998). The partial least squares approach to structural equation modeling. Modern methods for business research, 295(2), 295-336.
Cox, D. F., & Rich, S. U. (1964). Perceived risk and consumer decision-making: The case of telephone shopping. Journal of marketing research, 32-39.
Crespo, A. H., del Bosque, I. R., & de los Salmones Sanchez, M. G. (2009). The influence of perceived risk on Internet shopping behavior: a multidimensional perspective. Journal of Risk Research, 12(2), 259-277.
Daft, R. L., & Lengel, R. H. (1984). Information richness: A new approach to managerial behavior and organizational design. Research in Organizational Behavior.
Davis, F. D. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS quarterly, 319-340.
DeLone, W. H., & McLean, E. R. (2003). The DeLone and McLean model of information systems success: a ten-year update. Journal of management information systems, 19(4), 9-30.
Deutsch, M., & Gerard, H. B. (1955). A study of normative and informational social influences upon individual judgment. The journal of abnormal and social psychology, 51(3), 629.
Dick, A., Jain, A., & Richardson, P. (1995). Correlates of store brand proneness: some empirical observations. Journal of Product & Brand Management, 4(4), 15-22.
Dickinger, A. (2010). The trustworthiness of online channels for experience-and goal-directed search tasks. Journal of Travel Research.
Ducoffe, R. H. (1996). Advertising value and advertising on the web. Journal of advertising research, 36(5), 21-35.
Falk, R., & Miller, N. (1992). A primer for soft modeling University of Akron Press Akron: OH.
Fishbein, M., & Ajzen, I. (1975). Belief, attitude, intention and behavior: An introduction to theory and research.
Fornell, C. (1992). A national customer satisfaction barometer: The Swedish experience. the Journal of Marketing, 6-21.
Fornell, C., & Larcker, D. F. (1981). Evaluating structural equation models with unobservable variables and measurement error. Journal of marketing research, 39-50.
Gijsbrechts, E. (1993). Prices and pricing research in consumer marketing: Some recent developments. International Journal of Research in Marketing, 10(2), 115-151.
Greatorex, M., & Mitchell, V. W. (1994). Modelling consumer risk reduction preferences from perceived loss data. Journal of Economic Psychology, 15(4), 669-685.
Grewal, D., Monroe, K. B., & Krishnan, R. (1998). The effects of price-comparison advertising on buyers' perceptions of acquisition value, transaction value, and behavioral intentions. The Journal of Marketing, 46-59.
Gurn, R. M. (1995). Measuring information providers on the Internet. Computers in Libraries, 15(1), 42.
Hair, J., Black, W., Babin, B., & Anderson, R. (2010). Multirative data analysis: A global perspective: New Jersey: Pearson Prentice Hall.
Hsu, C.-L., & Lin, J. C.-C. (2008). Acceptance of blog usage: The roles of technology acceptance, social influence and knowledge sharing motivation. Information & management, 45(1), 65-74.
Hsu, C.-L., & Lu, H.-P. (2004). Why do people play on-line games? An extended TAM with social influences and flow experience. Information & Management, 41(7), 853-868.
Hur, Y., Ko, Y. J., & Claussen, C. L. (2012). Determinants of using sports web portals: An empirical examination of the sport website acceptance model. International Journal of Sports Marketing and Sponsorship, 13(3), 6-25.
Hurme, P. (2005). Mobile communication and work practices in knowledge-based organizations.
Jacoby, J., & Olson, J. C. (1977). nConsumer Response to Price: An Attitudinal, Information Processing Perspective, oin Moving Ahead with Attitude Research, Y. Wind and P. Greenberg, eds. Chicago: American Marketing Association, 73, 86.
Jiuan Tan, S. (1999). Strategies for reducing consumers' risk aversion in Internet shopping. Journal of Consumer Marketing, 16(2), 163-180.
Karahanna, E., Straub, D. W., & Chervany, N. L. (1999). Information technology adoption across time: a cross-sectional comparison of pre-adoption and post-adoption beliefs. MIS quarterly, 183-213.
Khalaf, S. (2013). Flurry five-year report: It’s an app world. The web just lives in It. The Flurry Blog, http://blog. flurry. com/bid/95723/Flurry-Five-Year-Report-It-s-an-App-World-The-Web-Just-Lives-in-It.
Kim, H.-W., Xu, Y., & Gupta, S. (2012). Which is more important in Internet shopping, perceived price or trust? Electronic Commerce Research and Applications, 11(3), 241-252.
Kukar-Kinney, M., & Close, A. G. (2010). The determinants of consumers’ online shopping cart abandonment. Journal of the Academy of Marketing Science, 38(2), 240-250.
Lee, I., Choi, B., Kim, J., & Hong, S.-J. (2007). Culture-technology fit: Effects of cultural characteristics on the post-adoption beliefs of mobile Internet users. International Journal of Electronic Commerce, 11(4), 11-51.
Lu, J., Yao, J. E., & Yu, C.-S. (2005). Personal innovativeness, social influences and adoption of wireless Internet services via mobile technology. The Journal of Strategic Information Systems, 14(3), 245-268.
McKinney, V., Yoon, K., & Zahedi, F. M. (2002). The measurement of web-customer satisfaction: An expectation and disconfirmation approach. Information systems research, 13(3), 296-315.
Melchor, M. Q., & Julián, C. P. (2008). The impact of the human element in the information systems quality for decision making and user satisfaction. Journal of Computer Information Systems, 48(2), 44-52.
Monroe, K. B. (1990). Useful Findings from Price Perception Research. Pricing: Making Profitable Decision, New York: McGraw-Hill.
Moon, J.-W., & Kim, Y.-G. (2001). Extending the TAM for a World-Wide-Web context. Information & management, 38(4), 217-230.
Negash, S., Ryan, T., & Igbaria, M. (2003). Quality and effectiveness in web-based customer support systems. Information & Management, 40(8), 757-768.
Obe, O., & Balogun, V. (2007). Practice, trends and challenges of mobile commerce in Nigeria. Information Technology Journal, 6(3), 448-456.
Oh, S., Lehto, X. Y., & Park, J. (2009). Travelers' intent to use mobile technologies as a function of effort and performance expectancy. Journal of Hospitality Marketing & Management, 18(8), 765-781.
Page, T. (2013). Use of Mobile Device Apps in Product Design. International Journal of Green Computing (IJGC), 4(1), 18-34.
Pai, F.-Y., & Huang, K.-I. (2011). Applying the Technology Acceptance Model to the introduction of healthcare information systems. Technological Forecasting and Social Change, 78(4), 650-660.
Pavlou, P. A. (2003). Consumer acceptance of electronic commerce: Integrating trust and risk with the technology acceptance model. International journal of electronic commerce, 7(3), 101-134.
Pavlou, P. A., & Fygenson, M. (2006). Understanding and predicting electronic commerce adoption: An extension of the theory of planned behavior. MIS quarterly, 115-143.
Petter, S., & McLean, E. R. (2009). A meta-analytic assessment of the DeLone and McLean IS success model: An examination of IS success at the individual level. Information & Management, 46(3), 159-166.
Shaw, R. S., Chen, C. C., Harris, A. L., & Huang, H.-J. (2009). The impact of information richness on information security awareness training effectiveness. Computers & Education, 52(1), 92-100.
Taylor, & Todd. (1995). Understanding information technology usage: A test of competing models. Information systems research, 6(2), 144-176.
Taylor, & Todd. (1995). Assessing IT usage: the role of prior experience. MIS Quarterly, 19(4), 561-570.
van Riel, A. C., & Pura, M. (2005). Linking perceived value and loyalty in location-based mobile services. Managing Service Quality: An International Journal, 15(6), 509-538.
Venkatesh, V., & Davis, F. D. (2000). A theoretical extension of the technology acceptance model: Four longitudinal field studies. Management science, 46(2), 186-204.
Venkatesh, V., Morris, M. G., Davis, G. B., & Davis, F. D. (2003). User acceptance of information technology: Toward a unified view. MIS quarterly, 425-478.
Wang, Y.-S., & Liao, Y.-W. (2007). The conceptualization and measurement of m-commerce user satisfaction. Computers in human behavior, 23(1), 381-398.
Wu, J.-H., & Wang, S.-C. (2005). What drives mobile commerce?: An empirical evaluation of the revised technology acceptance model. Information & management, 42(5), 719-729.
Yang, K., & Kim, H.-Y. (2012). Mobile shopping motivation: an application of multiple discriminant analysis. International Journal of Retail & Distribution Management, 40(10), 778-789.
Yoon, C., & Kim, S. (2007). Convenience and TAM in a ubiquitous computing environment: The case of wireless LAN. Electronic Commerce Research and Applications, 6(1), 102-112.
Yu, P., Li, H., & Gagnon, M.-P. (2009). Health IT acceptance factors in long-term care facilities: a cross-sectional survey. International journal of medical informatics, 78(4), 219-229.

【網路資料部份】
91mai(民104)。91mai就要買-行動購物商城應用程式。上網日期：104年05月15日，檢自https://play.google.com/store/apps/details?id=com.nineyi.mall&hl=zh_TW
App Store (民103)。應用程式類別。App Store。上網日期：103年10月1日，檢自https://itunes.apple.com/tw/genre/ios/id36?mt=8&l=zh
Chen Brian(民104年01月07日)。2014 年 App 使用量成長 76%，購物行動應用一路領先。上網日期：104年5月6日，檢自http://technews.tw/2015/01/07/app-usage-grew-76-in-2014-with-shopping-apps-leading-the-way/
Google Play (民103)。應用程式類別。Google Play。上網日期：103年10月1日，檢自：https://play.google.com/store/apps/category/TOOLS?hl=zh_TW
IT IS智網(民104年01月13日)。2015年行動購物、支付與音樂需求調查。上網日期：104年05月10日，檢自http://www2.itis.org.tw/service/newsTopic_show.aspx?tpc_no=1097
MIC產業情報研究所(民104年01月20日)。62.5%台灣網友有行動購物經驗。上網日期：104年5月6日，檢自http://mic.iii.org.tw/intelligence/pressroom/pop_pressfull.asp?sno=382&type1=2
陳亞柔(民104年03月29日)。行動革命、商業霸主。上網日期：104年05月10日，檢自http://ir.nctu.edu.tw/handle/11536/110360
陳品先(民100)。Google調查~39%智慧型手機用戶連在廁所都使用。上網日期：104年5月07日，檢自
http://www.meetclub.tw/article/view/id/18171
資策會FIND (民103年06月25日)。首創！資策會跨通路分析使用者行為評選2014年上半年臺灣風雲APP百強。上網日期:103年5月05日，檢自：http://www.find.org.tw/market_info.aspx?n_ID=7201
資策會FIND(民103年07月21日)。資策會FIND: 2014年上半年消費者行為調查出爐。上網日期：104年5月05日，檢自http://www.iii.org.tw/service/3_1_1_c.aspx?id=1367
蘇文彬(民104年01月)。資策會：國內超過6成網友有行動購物經驗。上網日期：104年05月15日，檢自：http://www.ithome.com.tw/news/93662