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題名 行動服務品質量表建構
Constructing the measurement scale of mobile service quality
作者 范雅筑
Fan, Ya Chu
貢獻者 管郁君<br>林勝為
Huang, Eugenia Y.<br>Lin, Sheng Wei
范雅筑
Fan, Ya Chu
關鍵詞 行動商務
行動服務
服務品質
量表建構
Mobile commerce
Mobile service
Service quality
Instrument development
日期 2011
上傳時間 30-Oct-2012 13:59:50 (UTC+8)
摘要 隨著網路科技、行動手持裝置的發展，多元的行動服務開始被廣泛開發及應用，為了能提供更好的行動服務，行動服務提供者必須了解使用者對行動服務的認知與想法。此研究希望透過不同行動服務類型的特性，定義行動服務品質(Mobile service quality; M-S-QUAL)之適用範圍，並根據Hinkin所建議之量表建構方法，發展出一份有效衡量行動服務品質之量表(M-S-QUAL)，以歸納法自既有的服務品質文獻發展初步的問項。由於行動服務提供有形商品與無形商品的交易與交換，因此，M-S-QUAL也同時包含有形與無形商品行動服務品質量表，初步的M-S-QUAL包含九構面：系統效率(efficiency)、履行性(Fulfillment)、系統可用性(System availability)、隱私性(Privacy)、反應性(Responsiveness)、補償性(Compensation)、聯絡性 (Contact)、內容(Content)、帳務議題(Billing)，而有形/ 無形商品行動服務品質量表分別以50/49題問項衡量。此份量表透過問卷調查法進行資料的蒐集，並透過探索性因素分析(Exploratory factor analysis; EFA)及驗證性因素分析(Confirmatory factor analysis; CFA)萃取出四構面、15題問項之有形商品行動服務品質量表與五構面、16題問項之無形商品行動服務品質量表，此研究亦針對M-S-QUAL量表進行信、效度檢驗並利用不同校標(感知價值與忠誠意圖)進行迴歸分析以建立校標關聯效度。研究結果顯示本研究所發展的行動服務品質量表具有良好的心理計量特質(psychometric properties)。
With the proliferation of wireless technologies, consumers are increasingly coming into contact with a diverse range of mobile services. Mobile service providers seeking to deliver a superior service must understand how consumers perceive mobile services. Many instruments such as SERVQUAL and E-S-QUAL have been used to measure service quality; however, no general mobile service quality evaluation measure currently exists. Given the many different types of mobile services available, our aim in this study was to ascertain the essential characteristics of mobile services by conceptualizing, constructing, refining and testing a multiple-item scale (M-S-QUAL) for measuring service quality in the mobile environment. According to Hinkin’s guide on the development of scales, items in the scale were generated by following a deductive approach based on a theoretical foundation. The mobile services examined in this study were divided into those for tangible and intangible product transactions. The results show that in intangible and tangible product shopping, M-S-QUAL includes five dimensions (contact, recovery, fulfillment, privacy, and efficiency) and four dimensions (contact, recovery, fulfillment, and efficiency), respectively. These two aspects of M-S-QUAL demonstrate good psychometric properties based on findings from a variety of exploratory factor analysis (EFA), confirmatory factor analysis (CFA), reliability and validity tests. The findings of this study may help mobile service providers assess the quality of their services and assist researchers in developing mobile service quality theories.
參考文獻 Akter, S., D’Ambra, J., & Ray, P. (2010). Service quality of mHealth platforms: Development and validation of a hierarchical model using PLS, Electronic Markets, 20, 209-227.
Bagozzi, R. P., & Yi, Y. (1988). On the evaluation of structural equation models. Journal of the Academy of Marketing Science, 16(1), 74–94.
Balasubramanian, 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.
Barclay, D., Higgins, C., & Thompson, R. (1995). The partial least squares approach to causal modeling: personal computer adoption and use as an illustration. Technology Studies, 2(2), 285–309.
Barnes, S. J. (2002). The mobile commerce value chain: Analysis and future developments. International Journal of Information Management, 22, 91–108.
Bentler, P. M. (1992). On the Fit of Models to Covariance and Methodology to the Bulletin. Psychological Bulletin, 112, 400-404.
Chae, M., Kim, J., Kim, H., & Ryu, H. (2002). Information quality for mobile internet services: A theoretical model with empirical validation. Electronic Markets, 12(1), 38–46.
Choi, C., Kim, C., Sung, N. & Park, Y. (2007, August). Evaluating the quality of service in mobile business based on fuzzy set theory. Paper presented at the Fourth International Conference on Fuzzy System and Knowledge Discovery, Haiku, China.
Chu, K. M., Yuan, J. C., & Chan, H.C. (2011). A study of mobile service’s adoption model: A prospect of cross services’ classification. Journal of E-business, 13 (3), 697-726.
Churchill G. A. (1979). A paradigm for developing better measures of marketing constructs. Journal of Marketing Research, 16 (1), 64–73.
Churchill, G. A. & Surprenant C. (1982). An investigation into the determinants of consumer satisfaction. Journal of Marketing Research, 19, 491-504.
Clarke, I. & Flaherty, T. B. (2003). Web-based B2B portals. Industrial Marketing Management, 32, 15-23.
Clarke, I. (2001). Emerging value propositions for m-commerce, Journal of Business Strategies, 18 (2), 133–148.
Coursaris, C., & Hassanein, K. (2002). Understanding m-commerce: A consumer-centric model. Quarterly Journal of Electronic Commerce, 3 (3), 247–271.
Cronbach, L. J. (1951). Coefficient and the internal structure of tests. Psychometrika, 16(13), 297–334.
Denga, Z., Lua, Y., Weib, K. K., & Zhanga, J. (2010). Understanding consumer satisfaction and loyalty: An empirical study of mobile instant messages in China. International Journal of Information Management, 30, 289–300.
European Commission. (1996). Strategic developments for the European publishing industry towards the year 2000－ Europe’s multimedia challenge. DG XIII/E. Brussels: European Commission.
Foreseeing Innovative New Digiservices (FIND) (2008). Innovative DigiTech-Enabled Applications & Service Institute (IDEA) of Institute for Information Industry
Fornell, C. & Larcker, D. F. (1981). Evaluating structural equation models with unobservable variables and measurement error. Journal of Marketing Research, 18(1), 39–50.
Gerbing, D. W. & Anderson, J. C. (1992). Monte Carlo evaluations of goodness of fit indices for structural equation models. Sociological Methods Research, 21, 132-160.
Gronroos, C. (1978). A service-oriented approach to marketing of services. European Journal of Marketing, 12 (8), 588-601.
Hair, J. F., Black, W. C., Babin, B. J. & Anderson, R. E. (2010). Multivariate data analysis. Pearson, NJ: Pearson Education Inc.
Harrison, D. A., McLaughlin, M.E. (1993). Cognitive Processes in Self-report Responses: Tests of Item Context Effects in Work Attitude Measures. Journal of Applied Psychology, 78, 129-140.
Harvey, R. J., Billings, R.S., & Nilan, K. J. (1985). Confirmatory Factor Analysis of The Job Diagnostic Survey: Good News and Bad News. Journal of Applied Psychology, 70, 461-468.
Hinkin, T. R. (1998). A brief tutorial on the development of measures for use in survey questionnaires. Organizational Research Methods, 1(1), 104-121.
Holeter, J. W. (1983). The analysis of covariance structures: Goodness-of-fit indices. Sociological Methods and Research, 11, 325-344.
Jöreskog, K. G. & Sörbom, D. (1992). LISREL: A Guide to the Program and Applications. 3rd ed. Chicago: Scientific Software International, Inc.
Kumar, A. & Lim, H. (2008). Age differences in mobile service perceptions: comparison of Generation Y and baby boomers, Journal of Services Marketing, 22 (7), 568–577.
Kuo, Y. F., Wub, C. M. & Deng, W. J. (2009). The relationships among service quality, perceived value, consumer satisfaction, and post-purchase intention in mobile value-added services, Computers in Human Behavior, 25, 887-896.
Kwon, O.B., & Sadeh, N. (2004). Applying case-based reasoning and multi-agent intelligent system to context-aware comparative shopping. Decision Support Systems, 37 (2), 199–213.
Lu, Y., Zhang, L. & Wang, B. (2009). A multidimensional and hierarchical model of mobile service quality. Electronic Commerce Research and Applications, 8, 228–240.
MacCallum R. C. & Hong, S. (1997). Power Analysis in Covariance Structure modeling using. Multivariate Behavioral Research, 32, 193-210.
Mackenzie, S. B., Posakoff, P. M., & Fetter, R. (1991), Organizational citizenship behavior and objective productivity as determinants of managerial evaluations os salespersons’ performance. Organizational Behavior and Human Decision Process, 50, 123-150.
Nunnally, J. C. (1978). Psychometric Theory, McGraw-Hill, New York.
Parasuraman, A., Berry, L. L., & Zeithaml, V. A. (1988). SERVQUAL: A multiple-item scale for measuring consumer perceptions of service. Quality Journal of Retailing, 64(1), 12-40.
Parasuraman, A., Berry, L. L., & Zeithaml, V. A. (1991). Refinement and reassessment of the SERVQUAL scale. Journal of Retailing, 64(1), 420-450.
Parasuraman, A., Zeithaml, V. A., & Berry, L. L. (1985). A conceptual model of service quality and its implications for future research. Journal of Marketing, 49, 41-50.
Parasuraman, A., Zeithaml, V. A., & Malhotra, A. (2005). E-S-QUAL. A multiple-item scale for assessing electronic service quality. Journal of Service Research, 7(3), 213-233.
Rao, B., & Minakakis, L. (2003). Evolution of mobile location-based services. Communications of the ACM, 46(12), 61–65.
Santouridis, I. & Trivellas, P. (2010). Investigating the impact of service quality and consumer satisfaction on consumer loyalty in mobile telephony in Greece, The TQM Journal, 22 (3), 330-343.
Sasser, W. E., Olsen, R. P., & Wyckoff, D. D. (1978). Management of service operations: Text and cases, Allyn & Bacon, Boston.
Steiger, J. H. (1990). Structural model evaluation and modification: An interval estimation approach. Multivariate Behavioral Resaerch, 25, 173-180.
Straub, D. W. (1989). Validating instruments in MIS research. MIS Quarterly, 13(2), 147–169.
Turela, O. & Serenko, A. (2006). Satisfaction with mobile services in canada: An empirical investigation. Telecommunications Policy, 30, 314-331.
Wang, Y. S. & Liao, Y. W. (2007). The conceptualization and measurement of m-commerce user satisfaction. Computers in Human Behavior, 23, 381-398.
Network resources
International Data Corporation (IDC) Worldwide Quarterly Mobile Phone Tracker, June 9, 2011. Retrived November 10, 2011, from http://www.idc.com/getdoc.jsp?containerId=prUS23297412
International Data Corporation (IDC), Press release IDC forecasts worldwide mobile applications revenues to experience more than 60% compound annual growth through 2014 (December 2010). Retrived November 30, 2011, from http://www.idc.com/about/viewpressrelease.jsp?containerId=prUS22617910§ionId=null&elementId=null&pageType=SYNOPSIS
Nielsen (June 2010), The State of Mobile Apps Retrived December 2, 2011, from http://blog.nielsen.com/nielsenwire/online_mobile/the-state-of-mobile-apps/
Statwiki, Confirmatory Factor Analysis (CFA), Retrived June 18, 2012, from http://statwiki.kolobkreations.com/wiki/Confirmatory_Factor_Analysis
Wiki, Confirmatory factor analysis, Retrived June 18, 2012, from http://en.wikipedia.org/wiki/Confirmatory_factor_analysis
描述 碩士
國立政治大學
資訊管理研究所
99356036
100
資料來源 http://thesis.lib.nccu.edu.tw/record/#G0099356036
資料類型 thesis
dc.contributor.advisor 管郁君<br>林勝為zh_TW
dc.contributor.advisor Huang, Eugenia Y.<br>Lin, Sheng Weien_US
dc.contributor.author (Authors) 范雅筑zh_TW
dc.contributor.author (Authors) Fan, Ya Chuen_US
dc.creator (作者) 范雅筑zh_TW
dc.creator (作者) Fan, Ya Chuen_US
dc.date (日期) 2011en_US
dc.date.accessioned 30-Oct-2012 13:59:50 (UTC+8)-
dc.date.available 30-Oct-2012 13:59:50 (UTC+8)-
dc.date.issued (上傳時間) 30-Oct-2012 13:59:50 (UTC+8)-
dc.identifier (Other Identifiers) G0099356036en_US
dc.identifier.uri (URI) http://nccur.lib.nccu.edu.tw/handle/140.119/54853-
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) 99356036zh_TW
dc.description (描述) 100zh_TW
dc.description.abstract (摘要) 隨著網路科技、行動手持裝置的發展，多元的行動服務開始被廣泛開發及應用，為了能提供更好的行動服務，行動服務提供者必須了解使用者對行動服務的認知與想法。此研究希望透過不同行動服務類型的特性，定義行動服務品質(Mobile service quality; M-S-QUAL)之適用範圍，並根據Hinkin所建議之量表建構方法，發展出一份有效衡量行動服務品質之量表(M-S-QUAL)，以歸納法自既有的服務品質文獻發展初步的問項。由於行動服務提供有形商品與無形商品的交易與交換，因此，M-S-QUAL也同時包含有形與無形商品行動服務品質量表，初步的M-S-QUAL包含九構面：系統效率(efficiency)、履行性(Fulfillment)、系統可用性(System availability)、隱私性(Privacy)、反應性(Responsiveness)、補償性(Compensation)、聯絡性 (Contact)、內容(Content)、帳務議題(Billing)，而有形/ 無形商品行動服務品質量表分別以50/49題問項衡量。此份量表透過問卷調查法進行資料的蒐集，並透過探索性因素分析(Exploratory factor analysis; EFA)及驗證性因素分析(Confirmatory factor analysis; CFA)萃取出四構面、15題問項之有形商品行動服務品質量表與五構面、16題問項之無形商品行動服務品質量表，此研究亦針對M-S-QUAL量表進行信、效度檢驗並利用不同校標(感知價值與忠誠意圖)進行迴歸分析以建立校標關聯效度。研究結果顯示本研究所發展的行動服務品質量表具有良好的心理計量特質(psychometric properties)。zh_TW
dc.description.abstract (摘要) With the proliferation of wireless technologies, consumers are increasingly coming into contact with a diverse range of mobile services. Mobile service providers seeking to deliver a superior service must understand how consumers perceive mobile services. Many instruments such as SERVQUAL and E-S-QUAL have been used to measure service quality; however, no general mobile service quality evaluation measure currently exists. Given the many different types of mobile services available, our aim in this study was to ascertain the essential characteristics of mobile services by conceptualizing, constructing, refining and testing a multiple-item scale (M-S-QUAL) for measuring service quality in the mobile environment. According to Hinkin’s guide on the development of scales, items in the scale were generated by following a deductive approach based on a theoretical foundation. The mobile services examined in this study were divided into those for tangible and intangible product transactions. The results show that in intangible and tangible product shopping, M-S-QUAL includes five dimensions (contact, recovery, fulfillment, privacy, and efficiency) and four dimensions (contact, recovery, fulfillment, and efficiency), respectively. These two aspects of M-S-QUAL demonstrate good psychometric properties based on findings from a variety of exploratory factor analysis (EFA), confirmatory factor analysis (CFA), reliability and validity tests. The findings of this study may help mobile service providers assess the quality of their services and assist researchers in developing mobile service quality theories.en_US
dc.description.tableofcontents Chapter 1 Introduction 1
Chapter 2 Literature review 4
2.1 Mobile commerce 4
2.1.1 From e-commerce to m-commerce 4
2.1.2 Scope of m-commerce applications 5
2.1.3 Products and services in mobile services 6
2.2 Service quality 7
2.2.1 Conceptualization of service quality 7
2.2.2 Electronic service quality 8
2.2.3 Mobile service quality 9
2.3 Scale development 11
Chapter 3 Research method 13
3.1 Questionnaire design 13
3.1.1 Modifying E-S-QUAL to mobile scenario 13
3.1.2 Developing a preliminary scale 14
3.1.3 Items simplification and content validity establishment 17
3.2 Data collection 18
3.2.1 Sampling and data collection 18
3.3 Statistical methods for data analysis 18
3.4 Pretesting and initial item reduction 20
Chapter 4 Data analysis and scale purification 21
4.1 Sampling data 21
4.2 Item analysis and reliability estimation 24
4.3 Identifying the factor structure of the M-S-QUAL construct 27
4.3.1 Exploratory factor analysis 28
4.3.2 Confirmatory factor analysis 30
4.4 Assessing reliability and validity 32
4.4.1 Reliability 33
4.4.2 Discriminant and convergent validity 33
4.4.3 Nomological validity 34
4.5 Data analysis result 35
Chapter 5 Discussions and conclusion 37
5.1 Practical implications 37
5.2 Conclusion and limitations 39
Appendix A 45
Appendix B 50		zh_TW
dc.language.iso en_US-
dc.source.uri (資料來源) http://thesis.lib.nccu.edu.tw/record/#G0099356036en_US
dc.subject (關鍵詞) 行動商務zh_TW
dc.subject (關鍵詞) 行動服務zh_TW
dc.subject (關鍵詞) 服務品質zh_TW
dc.subject (關鍵詞) 量表建構zh_TW
dc.subject (關鍵詞) Mobile commerceen_US
dc.subject (關鍵詞) Mobile serviceen_US
dc.subject (關鍵詞) Service qualityen_US
dc.subject (關鍵詞) Instrument developmenten_US
dc.title (題名) 行動服務品質量表建構zh_TW
dc.title (題名) Constructing the measurement scale of mobile service qualityen_US
dc.type (資料類型) thesisen
dc.relation.reference (參考文獻) Akter, S., D’Ambra, J., & Ray, P. (2010). Service quality of mHealth platforms: Development and validation of a hierarchical model using PLS, Electronic Markets, 20, 209-227.
Bagozzi, R. P., & Yi, Y. (1988). On the evaluation of structural equation models. Journal of the Academy of Marketing Science, 16(1), 74–94.
Balasubramanian, 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.
Barclay, D., Higgins, C., & Thompson, R. (1995). The partial least squares approach to causal modeling: personal computer adoption and use as an illustration. Technology Studies, 2(2), 285–309.
Barnes, S. J. (2002). The mobile commerce value chain: Analysis and future developments. International Journal of Information Management, 22, 91–108.
Bentler, P. M. (1992). On the Fit of Models to Covariance and Methodology to the Bulletin. Psychological Bulletin, 112, 400-404.
Chae, M., Kim, J., Kim, H., & Ryu, H. (2002). Information quality for mobile internet services: A theoretical model with empirical validation. Electronic Markets, 12(1), 38–46.
Choi, C., Kim, C., Sung, N. & Park, Y. (2007, August). Evaluating the quality of service in mobile business based on fuzzy set theory. Paper presented at the Fourth International Conference on Fuzzy System and Knowledge Discovery, Haiku, China.
Chu, K. M., Yuan, J. C., & Chan, H.C. (2011). A study of mobile service’s adoption model: A prospect of cross services’ classification. Journal of E-business, 13 (3), 697-726.
Churchill G. A. (1979). A paradigm for developing better measures of marketing constructs. Journal of Marketing Research, 16 (1), 64–73.
Churchill, G. A. & Surprenant C. (1982). An investigation into the determinants of consumer satisfaction. Journal of Marketing Research, 19, 491-504.
Clarke, I. & Flaherty, T. B. (2003). Web-based B2B portals. Industrial Marketing Management, 32, 15-23.
Clarke, I. (2001). Emerging value propositions for m-commerce, Journal of Business Strategies, 18 (2), 133–148.
Coursaris, C., & Hassanein, K. (2002). Understanding m-commerce: A consumer-centric model. Quarterly Journal of Electronic Commerce, 3 (3), 247–271.
Cronbach, L. J. (1951). Coefficient and the internal structure of tests. Psychometrika, 16(13), 297–334.
Denga, Z., Lua, Y., Weib, K. K., & Zhanga, J. (2010). Understanding consumer satisfaction and loyalty: An empirical study of mobile instant messages in China. International Journal of Information Management, 30, 289–300.
European Commission. (1996). Strategic developments for the European publishing industry towards the year 2000－ Europe’s multimedia challenge. DG XIII/E. Brussels: European Commission.
Foreseeing Innovative New Digiservices (FIND) (2008). Innovative DigiTech-Enabled Applications & Service Institute (IDEA) of Institute for Information Industry
Fornell, C. & Larcker, D. F. (1981). Evaluating structural equation models with unobservable variables and measurement error. Journal of Marketing Research, 18(1), 39–50.
Gerbing, D. W. & Anderson, J. C. (1992). Monte Carlo evaluations of goodness of fit indices for structural equation models. Sociological Methods Research, 21, 132-160.
Gronroos, C. (1978). A service-oriented approach to marketing of services. European Journal of Marketing, 12 (8), 588-601.
Hair, J. F., Black, W. C., Babin, B. J. & Anderson, R. E. (2010). Multivariate data analysis. Pearson, NJ: Pearson Education Inc.
Harrison, D. A., McLaughlin, M.E. (1993). Cognitive Processes in Self-report Responses: Tests of Item Context Effects in Work Attitude Measures. Journal of Applied Psychology, 78, 129-140.
Harvey, R. J., Billings, R.S., & Nilan, K. J. (1985). Confirmatory Factor Analysis of The Job Diagnostic Survey: Good News and Bad News. Journal of Applied Psychology, 70, 461-468.
Hinkin, T. R. (1998). A brief tutorial on the development of measures for use in survey questionnaires. Organizational Research Methods, 1(1), 104-121.
Holeter, J. W. (1983). The analysis of covariance structures: Goodness-of-fit indices. Sociological Methods and Research, 11, 325-344.
Jöreskog, K. G. & Sörbom, D. (1992). LISREL: A Guide to the Program and Applications. 3rd ed. Chicago: Scientific Software International, Inc.
Kumar, A. & Lim, H. (2008). Age differences in mobile service perceptions: comparison of Generation Y and baby boomers, Journal of Services Marketing, 22 (7), 568–577.
Kuo, Y. F., Wub, C. M. & Deng, W. J. (2009). The relationships among service quality, perceived value, consumer satisfaction, and post-purchase intention in mobile value-added services, Computers in Human Behavior, 25, 887-896.
Kwon, O.B., & Sadeh, N. (2004). Applying case-based reasoning and multi-agent intelligent system to context-aware comparative shopping. Decision Support Systems, 37 (2), 199–213.
Lu, Y., Zhang, L. & Wang, B. (2009). A multidimensional and hierarchical model of mobile service quality. Electronic Commerce Research and Applications, 8, 228–240.
MacCallum R. C. & Hong, S. (1997). Power Analysis in Covariance Structure modeling using. Multivariate Behavioral Research, 32, 193-210.
Mackenzie, S. B., Posakoff, P. M., & Fetter, R. (1991), Organizational citizenship behavior and objective productivity as determinants of managerial evaluations os salespersons’ performance. Organizational Behavior and Human Decision Process, 50, 123-150.
Nunnally, J. C. (1978). Psychometric Theory, McGraw-Hill, New York.
Parasuraman, A., Berry, L. L., & Zeithaml, V. A. (1988). SERVQUAL: A multiple-item scale for measuring consumer perceptions of service. Quality Journal of Retailing, 64(1), 12-40.
Parasuraman, A., Berry, L. L., & Zeithaml, V. A. (1991). Refinement and reassessment of the SERVQUAL scale. Journal of Retailing, 64(1), 420-450.
Parasuraman, A., Zeithaml, V. A., & Berry, L. L. (1985). A conceptual model of service quality and its implications for future research. Journal of Marketing, 49, 41-50.
Parasuraman, A., Zeithaml, V. A., & Malhotra, A. (2005). E-S-QUAL. A multiple-item scale for assessing electronic service quality. Journal of Service Research, 7(3), 213-233.
Rao, B., & Minakakis, L. (2003). Evolution of mobile location-based services. Communications of the ACM, 46(12), 61–65.
Santouridis, I. & Trivellas, P. (2010). Investigating the impact of service quality and consumer satisfaction on consumer loyalty in mobile telephony in Greece, The TQM Journal, 22 (3), 330-343.
Sasser, W. E., Olsen, R. P., & Wyckoff, D. D. (1978). Management of service operations: Text and cases, Allyn & Bacon, Boston.
Steiger, J. H. (1990). Structural model evaluation and modification: An interval estimation approach. Multivariate Behavioral Resaerch, 25, 173-180.
Straub, D. W. (1989). Validating instruments in MIS research. MIS Quarterly, 13(2), 147–169.
Turela, O. & Serenko, A. (2006). Satisfaction with mobile services in canada: An empirical investigation. Telecommunications Policy, 30, 314-331.
Wang, Y. S. & Liao, Y. W. (2007). The conceptualization and measurement of m-commerce user satisfaction. Computers in Human Behavior, 23, 381-398.
Network resources
International Data Corporation (IDC) Worldwide Quarterly Mobile Phone Tracker, June 9, 2011. Retrived November 10, 2011, from http://www.idc.com/getdoc.jsp?containerId=prUS23297412
International Data Corporation (IDC), Press release IDC forecasts worldwide mobile applications revenues to experience more than 60% compound annual growth through 2014 (December 2010). Retrived November 30, 2011, from http://www.idc.com/about/viewpressrelease.jsp?containerId=prUS22617910§ionId=null&elementId=null&pageType=SYNOPSIS
Nielsen (June 2010), The State of Mobile Apps Retrived December 2, 2011, from http://blog.nielsen.com/nielsenwire/online_mobile/the-state-of-mobile-apps/
Statwiki, Confirmatory Factor Analysis (CFA), Retrived June 18, 2012, from http://statwiki.kolobkreations.com/wiki/Confirmatory_Factor_Analysis
Wiki, Confirmatory factor analysis, Retrived June 18, 2012, from http://en.wikipedia.org/wiki/Confirmatory_factor_analysis		zh_TW