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題名 比較「智慧型手機主導之行動網路購物」與「電腦網路購物」兩者之相對屬性與重要性
Relative attribute importance of smartphone driven mobile commerce compared to computer based electronic commerce作者 柯思維
Servio Fernando Kloeth貢獻者 郭貞<br>郭貞
Kuo, Cheng<br>Kuo, Cheng
柯思維
Servio Fernando Kloeth關鍵詞 手機網路交易
電腦網路交易
通路價值
線上購物
科技接受模型
mobile commerce
electronic commerce
online shopping
technology acceptance model
channel value日期 2012 上傳時間 3-Jun-2013 18:03:34 (UTC+8) 摘要 現今智慧型手機之網路通路價值與電腦相比仍較低，也使得現今使用智慧型手機網路交易的比例仍低於使用電腦網路交易的比例。本研究採用付出為結構模型及恆等性分析，研究結果顯示，智慧型手機因其有用性及易用性較電腦低，因此使用者以手機網路交易的傾向也偏低。本研究以科技接受模型發現70%至80%的使用者都是因受社會及同儕影響，而較不傾向使用手機進行網路交易。一般認為，手機的便利性相對也使手機網路交易平台的風險提高。然而，研究結果顯示，以電腦從事網路交易的風險與手機網路交易的風險相當，便利性也幾無差異。因此本研究以社會影響為探討方向，認為其為影響現代人以手機從事網路交易的重要關鍵。
The net channel value of smartphone driven mobile-commerce measured against the alternative of computer based electronic-commerce is at this point in time still low. In an exploratory effort structural modeling and invariance analysis reveals mobile commerce is viewed with a less positive usability disposition in the light of usefulness and effortlessness. An adaptation of the Technology Acceptance model accounting for 70-80% of usage intention indicates social influences experienced from peers to engage the mobile platform is lower. Convenience and perceived risk are usually considered attributes relatively important for the m-commerce platform. However, the analysis reveals little difference of these attributes` salience compared with e-commerce, absolute scores for convenience are similar, and perceived risk seems to have marginal effects on usage in general. Social influences, experienced as lower for mobile commerce is a especially salient concept in determining usability disposition and ultimately intention to use mobile commerce, as is the salience of the usability disposition larger for mobile commerce than for electronic commerce.參考文獻 Abelson, R .P., & Levi, A. (1985). Decision making and decision theory, in the handbook of social psychology. NY: Knopf. 231-309.Ajzen, I., Fishbein, M., (1980). Understanding attitudes and predicting social behavior. Englewood Cliffs, NJ: Prentice-Hall.Ajzen, I. (1991). The theory of planned behavior. Organizational Behavior and Human Decision Processes, 50, 179–211.Anckar, B. (2002). Rationales for consumer adoption or rejection of e-commerce: Exploring the impact of product characteristics. Proceedings of the SSGRR 2002s International Conference.Anckar, B., & D’Incau, D. (2002). Value creation in mobile commerce: Findings from a consumer survey. The Journal of Information Technology Theory and Application, 4 (1), 43-64.Balasubraman, S., Peterson, R. A., & Jarvenpaa, S. L. (2002). Exploring the implications of m-commerce for markets and marketing. Journal of the Academy of Marketing Science, 30 (4), 348-361.Bandura, A. (1982). Self-efficacy mechanism in human agency. American Psychologist, 37 (2), 122-147.Beach, L. R., & Mitchell, T. R. (1978). A contingency model for the selection of decision strategies. Academy of Management Review, 3 (3), 439-449.Bentler, P. M. (1992). On the fit of models to covariances and methodology to the bulletin. Psychological Bulletin, 112, 400-404.Bhatnagar, A., Misra, S., & Rao, H. R. (2000). On risk, convenience, and internet shopping behavior, Communications of the ACM, 43 (11), 98–114.Bhattacherjee, A. (2000). Acceptance of e-commerce services: The case of electronic brokerages. IEEE Transactions on Systems, Man and Cybernetics 30 (4), 411–420.Bouwman, H., López-Nicolás, C., & Molina-Castillo, F. J. (2012). Consumer lifestyles: Alternative adoption patterns for advanced mobile services. International Journal of Mobile Communications, 10 (2), 169-189.Brown, L. G. (1989). The strategic and tactical implications of convenience in consumer product marketing. Journal of Consumer Marketing, 6, 13-19.Bruner, G. C. II., & Kumar, A. (2005). Explaining consumer acceptance of handheld Internet devices. Journal of Business Research, 58 (5), 553-558.Byrne, B. M., Shavelson, R. J., & Muthen, B. (1989). Testing for the equivalence of factor covariance and mean structures: The issue of partial measurement in variance. Psychological Bulletin, 105 (3), 456-466.Byrne, B. M. (2008). Testing for multigroup equivalence of a measuring instrument: A walk through the process. Psicothema, 20 (4), 872-882.Cavana, R. Y., Delanaye, B. L., & Sekaran, U. (2001). 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Please trust me: Trust antecedents that increase online consumer purchase intention. Journal of Internet Banking and Commerce, 16 (3). 描述 碩士
國立政治大學
國際傳播英語碩士學位學程(IMICS)
100461018
101資料來源 http://thesis.lib.nccu.edu.tw/record/#G0100461018 資料類型 thesis dc.contributor.advisor 郭貞<br>郭貞 zh_TW dc.contributor.advisor Kuo, Cheng<br>Kuo, Cheng en_US dc.contributor.author (Authors) 柯思維 zh_TW dc.contributor.author (Authors) Servio Fernando Kloeth en_US dc.creator (作者) 柯思維 zh_TW dc.creator (作者) Servio Fernando Kloeth en_US dc.date (日期) 2012 en_US dc.date.accessioned 3-Jun-2013 18:03:34 (UTC+8) - dc.date.available 3-Jun-2013 18:03:34 (UTC+8) - dc.date.issued (上傳時間) 3-Jun-2013 18:03:34 (UTC+8) - dc.identifier (Other Identifiers) G0100461018 en_US dc.identifier.uri (URI) http://nccur.lib.nccu.edu.tw/handle/140.119/58343 - dc.description (描述) 碩士 zh_TW dc.description (描述) 國立政治大學 zh_TW dc.description (描述) 國際傳播英語碩士學位學程(IMICS) zh_TW dc.description (描述) 100461018 zh_TW dc.description (描述) 101 zh_TW dc.description.abstract (摘要) 現今智慧型手機之網路通路價值與電腦相比仍較低，也使得現今使用智慧型手機網路交易的比例仍低於使用電腦網路交易的比例。本研究採用付出為結構模型及恆等性分析，研究結果顯示，智慧型手機因其有用性及易用性較電腦低，因此使用者以手機網路交易的傾向也偏低。本研究以科技接受模型發現70%至80%的使用者都是因受社會及同儕影響，而較不傾向使用手機進行網路交易。一般認為，手機的便利性相對也使手機網路交易平台的風險提高。然而，研究結果顯示，以電腦從事網路交易的風險與手機網路交易的風險相當，便利性也幾無差異。因此本研究以社會影響為探討方向，認為其為影響現代人以手機從事網路交易的重要關鍵。 zh_TW dc.description.abstract (摘要) The net channel value of smartphone driven mobile-commerce measured against the alternative of computer based electronic-commerce is at this point in time still low. In an exploratory effort structural modeling and invariance analysis reveals mobile commerce is viewed with a less positive usability disposition in the light of usefulness and effortlessness. An adaptation of the Technology Acceptance model accounting for 70-80% of usage intention indicates social influences experienced from peers to engage the mobile platform is lower. Convenience and perceived risk are usually considered attributes relatively important for the m-commerce platform. However, the analysis reveals little difference of these attributes` salience compared with e-commerce, absolute scores for convenience are similar, and perceived risk seems to have marginal effects on usage in general. Social influences, experienced as lower for mobile commerce is a especially salient concept in determining usability disposition and ultimately intention to use mobile commerce, as is the salience of the usability disposition larger for mobile commerce than for electronic commerce. en_US dc.description.tableofcontents TABLE OF CONTENTSRelative attribute importance of smartphone driven mobile commerce compared to computer based electronic commerce 1ELECTRONIC COMMERCE 1MOBILE COMMERCE 1RESEARCH GOAL 2THE CONTRIBUTION OF THIS PAPER 3Literature Review 4MODELS MEASURING ADOPTION AND USAGE OF TECHNOLOGY 4VARIABLES 10perceived usefulness. 10perceived ease of use. 11perceived convenience. 12perceived risk. 16social influences. 18Conceptual Model 21Research method 27DATA COLLECTION 27MEASUREMENT INSTRUMENT DEVELOPMENT 27likert scale. 29parcelling. 31DATA ANALYSIS 32Pilot 33DATA PREPARATION 34INDICATOR FIT 34DIRECT COMPARISON M-COMMERCE & E-COMMERCE 36STRUCTURAL EQUATION MODELS 37INVARIANCE MODEL 39PILOT CONCLUSION 41Data analysis 41DATA PREPARATION 42INDICATOR FIT 43DIRECT COMPARISON M-COMMERCE & E-COMMERCE 44STRUCTURAL EQUATION MODELS 44INVARIANCE MODEL 47PARTIAL LEAST SQUARES MODEL 54Discussion and results 54ATTITUDE TOWARDS PLATFORM & BEHAVIORAL INTENTION 54PERCEIVED RISK & BEHAVIORAL INTENTION 56SOCIAL INFLUENCES & BEHAVIORAL INTENTION 58SOCIAL INFLUENCES & ATTITUDE TOWARDS PLATFORM 59SOCIAL INFLUENCES & PERCEIVED RISK 60FINDINGS FOR RESEARCH QUESTION 60CONCLUDING REMARKS 62limitations. 63future research. 64References 65Appendix 72FULL SURVEY IN CHINESE 75FULL SURVEY QUESTIONS IN ENGLISH 78 zh_TW dc.format.extent 2952395 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/#G0100461018 en_US dc.subject (關鍵詞) 手機網路交易 zh_TW dc.subject (關鍵詞) 電腦網路交易 zh_TW dc.subject (關鍵詞) 通路價值 zh_TW dc.subject (關鍵詞) 線上購物 zh_TW dc.subject (關鍵詞) 科技接受模型 zh_TW dc.subject (關鍵詞) mobile commerce en_US dc.subject (關鍵詞) electronic commerce en_US dc.subject (關鍵詞) online shopping en_US dc.subject (關鍵詞) technology acceptance model en_US dc.subject (關鍵詞) channel value en_US dc.title (題名) 比較「智慧型手機主導之行動網路購物」與「電腦網路購物」兩者之相對屬性與重要性 zh_TW dc.title (題名) Relative attribute importance of smartphone driven mobile commerce compared to computer based electronic commerce en_US dc.type (資料類型) thesis en dc.relation.reference (參考文獻) Abelson, R .P., & Levi, A. (1985). Decision making and decision theory, in the handbook of social psychology. NY: Knopf. 231-309.Ajzen, I., Fishbein, M., (1980). Understanding attitudes and predicting social behavior. Englewood Cliffs, NJ: Prentice-Hall.Ajzen, I. (1991). The theory of planned behavior. Organizational Behavior and Human Decision Processes, 50, 179–211.Anckar, B. (2002). Rationales for consumer adoption or rejection of e-commerce: Exploring the impact of product characteristics. Proceedings of the SSGRR 2002s International Conference.Anckar, B., & D’Incau, D. (2002). Value creation in mobile commerce: Findings from a consumer survey. The Journal of Information Technology Theory and Application, 4 (1), 43-64.Balasubraman, S., Peterson, R. A., & Jarvenpaa, S. L. (2002). Exploring the implications of m-commerce for markets and marketing. Journal of the Academy of Marketing Science, 30 (4), 348-361.Bandura, A. (1982). Self-efficacy mechanism in human agency. American Psychologist, 37 (2), 122-147.Beach, L. R., & Mitchell, T. R. (1978). A contingency model for the selection of decision strategies. Academy of Management Review, 3 (3), 439-449.Bentler, P. M. (1992). On the fit of models to covariances and methodology to the bulletin. Psychological Bulletin, 112, 400-404.Bhatnagar, A., Misra, S., & Rao, H. R. (2000). On risk, convenience, and internet shopping behavior, Communications of the ACM, 43 (11), 98–114.Bhattacherjee, A. (2000). Acceptance of e-commerce services: The case of electronic brokerages. IEEE Transactions on Systems, Man and Cybernetics 30 (4), 411–420.Bouwman, H., López-Nicolás, C., & Molina-Castillo, F. J. (2012). Consumer lifestyles: Alternative adoption patterns for advanced mobile services. International Journal of Mobile Communications, 10 (2), 169-189.Brown, L. G. (1989). The strategic and tactical implications of convenience in consumer product marketing. Journal of Consumer Marketing, 6, 13-19.Bruner, G. C. 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