成功大學博碩士論文系統

簡易檢索 / 詳目顯示

回結果列表

研究生：	吳凰慈 Wu, Huang-Tzu
論文名稱：	影響網路購物再購買意願之因素探討 Understanding Online Consumers' Repurchase Intention: An Integration of Cognitive Absorption and Expectation-Confirmation Model
指導教授：	耿伯文 Kreng, Victor B.
學位類別：	碩士 Master
系所名稱：	管理學院 - 國際管理碩士在職進修專班(IMBA) International Master of Business Administration(IMBA)
論文出版年：	2006
畢業學年度：	94
語文別：	英文
論文頁數：	103
中文關鍵詞：	網路購物、再購買意願、B2C電子商務、認知全神貫注、期望確認理論、消費者行為
外文關鍵詞：	online consumer behavior, online shopping, B2C e-commerce, repurchase intention, expectation-confirmation theory, cognitive absorption
相關次數：	點閱：86 下載：1
分享至:	分享至facebook 分享至twitter

查詢本校圖書館目錄查詢臺灣博碩士論文知識加值系統勘誤回報

None

Expectation-Confirmation Theory (ECT) has been widely used to predict the contin-ued usage in the consumer behavior literature. This research examines the factors influ-encing online consumers’ intention to continue shopping in the context of B2C electronic commerce. Specifically, this study integrates Bhattacherjee’s Expectation-Confirmation Model (ECM) with cognitive absorption to investigate online consumers’ repurchase in-tention. Eight research hypotheses derived from the proposed model were empirically validated. The results suggest that online consumers’ repurchase intention is determined primarily by satisfaction, followed by perceived usefulness. Also, satisfaction is jointly determined by confirmation, perceived usefulness, and cognitive absorption.

With the addition of cognitive absorption, the extended ECM provides a better fit than the original model for predicting online consumers’ repurchase intention. Moreover, the research results indicate that cognitive absorption exerts a strong effect on satisfac-tion, whereas perceived usefulness exhibits a weak impact on consumers’ satisfaction. This finding implies that online consumers’ satisfaction may be more related to their in-trinsic motivations rather than the extrinsic motivations.

ACKNOWLEDGEMENTS.......... I
ABSTRACT..........II
TABLE OF CONTENTS..........III
LIST OF TABLES..........VII
LIST OF FIGURES..........IX

CHAPTER ONE  INTRODUCTION..........1
1.1 Research Background and Motivations..........1
1.2 Research Objectives..........4
1.3 Research Project..........5
1.4 Research Procedure..........5
1.5 The Structure of this Study..........6

CHAPTER TWO  LITERATURE REVIEW..........8
2.1 Theoretical Background..........8
2.1.1 Technology Acceptance Model..........8
2.1.2 Expectation-Confirmation Theory..........10
2.1.3 Expectation-Confirmation Model..........14
2.1.4 Cognitive Absorption..........16
2.1.5 Repurchase Intention..........19
2.2 Interrelationship among Research Constructs..........21
2.2.1 Interrelationship between Cognitive Absorption and Perceived Usefulness..........21
2.2.2 Interrelationship between Cognitive Absorption and Satisfaction..........22
2.2.3 Interrelationships among Cognitive Absorption, Perceived Usefulness, Confirmation, and Satisfaction.........23
2.2.4 Interrelationship between Perceived Usefulness and Satisfaction..........24
2.2.5 Interrelationship between Perceived Usefulness and Repurchase Intention..........26
2.2.6 Interrelationship between Satisfaction and Repurchase Intention..........26

CHAPTER THREE  RESEARCH DESIGN AND METHODOLOGY..........28
3.1 The Conceptual Model..........28
3.2 Construct Measurement..........29
3.2.1 Cognitive Absorption..........29
3.2.2 Perceived Usefulness..........30
3.2.3 Confirmation..........31
3.2.4 Satisfaction..........31
3.2.5 Repurchase Intention..........32
3.2.6 Information of Respondents..........32
3.3 Hypotheses to be Tested..........33
3.4 Questionnaire Design..........34
3.5 Pretest of the Survey Instrument..........35
3.6 Sample Plan..........37
3.7 Data Analysis Procedure..........37
3.7.1 Descriptive Statistic Analysis..........37
3.7.2 Reliability and Validity of the Measurement Variables..........37
3.7.3 Structural Equation Model..........38

CHAPTER FOUR  DESCRIPTIVE ANALYSIS AND RESULTS..........40
4.1 Introduction..........40
4.2 Descriptive Analysis..........40
4.2.1 Data Collection..........41
4.2.2 Characteristics of Respondents..........41
4.2.3 Measurement Results of Research Variables..........43
4.3 Reliability Tests..........45
4.3.1 Cognitive Absorption..........45
4.3.2 Perceived Usefulness..........47
4.3.3 Confirmation..........48
4.3.4 Satisfaction..........49
4.3.5 Repurchase Intention..........50
4.4 Confirmatory Factor Analysis (CFA)..........52
4.4.1 Scale Validation..........52
4.4.2 Convergent Validity..........53
4.4.3 Discriminant Validity..........61
4.5 Structural Equation Model (SEM)..........61
4.5.1 Interrelationships among Cognitive Absorption, Perceived Usefulness, and Confirmation..........62
4.5.2 Interrelationships among Key Constructs in Original ECM..........66
4.5.3 The Overall Model..........69
4.5.4 Model Comparison with Original ECM..........74
4.5.5 Results of Hypotheses Testing..........75

CHAPTER FIVE  CONCLUSIONS AND SUGGESTIONS..........81
5.1 Research Results..........81
5.1.1 Satisfaction: Main Driver of Repurchase Intention..........82
5.1.2 Perceived Usefulness: Secondary Driver of Repurchase Intention..........83
5.1.3 Strong Association between Cognitive Absorption and Satisfaction..........84
5.1.4 Weak Association between Perceived Usefulness and Satisfaction..........85
5.1.5 The Significant Impact of Confirmation on Cognitive Absorption, Perceived Usefulness, and Satisfaction....85
5.2 Research Contributions..........86
5.3 Limitations of this Research..........87

REFERENCES..........89
APPENDICES..........95
Appendix-1: Questionnaire Survey in English..........96
Appendix-2: Questionnaire Survey in Chinese..........100

LIST OF TABLES
Table 2-1  Summary of Prior Work on Internet Applications with ECT..........13
Table 2-2  Summary of Prior Work on Internet Applications with ECM..........15
Table 2-3  Summary of Prior Work on Cognitive Absorption..........19
Table 2-4  Operationalization of Constructs..........21
Table 3-1  Pretest Results of Reliability Tests on Research Variables..........36
Table 4-1  Demographic Profile of Respondents..........42
Table 4-2  Descriptive Analysis of Research Variables..........44
Table 4-3  Reliability Analysis of Cognitive Absorption..........46
Table 4-4  Correlation Matrix of Cognitive Absorption..........47
Table 4-5  Reliability Analysis of Perceived Usefulness..........48
Table 4-6  Correlation Matrix of Perceived Usefulness..........48
Table 4-7  Reliability Analysis of Confirmation..........49
Table 4-8  Correlation Matrix of Confirmation..........49
Table 4-9  Reliability Analysis of Satisfaction..........50
Table 4-10 Correlation Matrix of Satisfaction..........50
Table 4-11 Reliability Analysis of Repurchase Intention..........51
Table 4-12 Correlation Matrix of Repurchase Intention..........51
Table 4-13 Intercorrelations among Research Constructs..........52
Table 4-14 Goodness-of-fit Measures for Overall CFA Model..........53
Table 4-15 Confirmatory Factor Analysis of Cognitive Absorption..........56
Table 4-16 Confirmatory Factor Analysis of Perceived Usefulness..........57
Table 4-17 Confirmatory Factor Analysis of Confirmation..........58
Table 4-18 Confirmatory Factor Analysis of Satisfaction..........59
Table 4-19 Confirmatory Factor Analysis of Repurchase Intention..........60
Table 4-20 Correlations of Latent Variables and AVEs..........61
Table 4-21 Summary of SEM Analysis of Cognitive Absorption, Perceived Usefulness, and Confirmation..........66
Table 4-22 Summary of SEM Analysis of Key Constructs in Original ECM..........69
Table 4-23 Summary of SEM Analysis of Research Model..........73
Table 5-1  Summary of Hypotheses Testing..........82

LIST OF FIGURES
Figure 1-1. Growth of broadband Internet users in Taiwan	..........2
Figure 1-2. Conceptual framework of this study..........4
Figure 1-3. Flow chart of this research..........6
Figure 2-1. Technology acceptance model (TAM)..........9
Figure 2-2. Expectation-confirmation theory (ECT)..........10
Figure 2-3. Expectation-confirmation model (ECM)..........14
Figure 3-1. Conceptual model of this research..........28
Figure 4-1. SEM analysis of cognitive absorption, perceived usefulness, and confirmation..........64
Figure 4-2. SEM analysis of key constructs in original ECM 67
Figure 4-3. SEM analysis of research model..........70
                                    

ACNielsen Online Consumer Opinion Survey (2005). ACNielsen News. Available at http://tw.en.acnielsen.com/news/20051101.shtml. Accessed May 30, 2006.

Agarwal, R., & Karahanna, E. (2000). Time flies when you're having fun: Cognitive ab-sorption and beliefs about information technology usage. MIS Quarterly, 24(4), 665-694.

Ajzen, I. (1991). The theory of planned behavior. Organizational Behavior and Human Decision Processes, 50(2), 179-211.

Anderson, J. C., & Gerbing, D. W. (1988). Structural equation modeling in practice: A review and recommended two-step approach. Psychological Bulletin, 103(3), 411-423.

Arbuckle, J. L., & Wothke, W. (1999). Amos 4.0 user’s guide. IL: SmallWaters Corpora-tion.

Armstrong, J. S. (1967). Derivation of theory by means of factor analysis or Tom Swift and his electric factor analysis machine. The American Statistician, 21(5), 17–21.

Bagozzi, R. P., & Phillips, L. W. (1982). Representing and testing organizational theo-ries: A holistic construal. Administrative Science Quarterly, 27, 459-489.

Bagozzi, R. P., & Yi, Y. (1988). On the evaluation of structural equation models. Journal of the Academy of Marketing Science, 16(1), 74-94.

Bentler, P. M. (1990). Comparative fit indexes in structural models. Psychological Bulle-tin, 107(2), 238-246.

Bhattacherjee, A. (2001a). Understanding information systems continuance: An expecta-tion-confirmation model. MIS Quarterly, 25(3), 351-370.

Bhattacherjee, A. (2001b). An empirical analysis of the antecedents of electronic com-merce service continuance. Decision Support Systems, 32(2), 201-214.

Bhattacherjee, A., & Premkumar, G. (2004). Understanding changes in belief and attitude toward information technology usage: A theoretical model and longitudinal test. MIS Quarterly, 28(2), 229-254.

Bollen, K. A. (1989). Structural equations with latent variables. New York: Wiley.

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). New-bury Park, CA: Sage.

Campbell, D. T., & Fiske, D. W. (1959). Convergent and discriminant validation by the multitrait-multimethod matrix. Psychological Bulletin, 56(2), 81-105.

Chau, P. Y. K. (1996). An empirical assessment of a modified technology acceptance model. Journal of Management Information Systems, 13(2), 185-204.

Chen, L. D., Gillenson, M. L., & Sherrell, D. L. (2002). Enticing online consumers: An extended technology acceptance perspective. Information & Management, 39(8), 705-719.

Cheung, C. M. K., & Limayem, M. (2005). Drivers of university students’ continued use of advanced Internet-based learning technologies. In Proceedings of the 18th Bled eConference eIntegration in Action, Bled, Slovenia.

Cheung, C. M. K., Chan, G. W. W., & Limayem, M. (2005). A critical review of online consumer behavior: Empirical research. Journal of Electronic Commerce in Organi-zations, 3(4), 1-19.

Chiu, C. M., Hsu, M. H., & Sun, S. Y. (2005). Usability, quality, value and e-learning continuance decisions. Computers & Education, 45(4), 399-416.

Chung, I. K., & Lee, M. M. (2003). A study of influencing factors for repurchase inten-tion in Internet shopping malls, International Parallel and Distributed Processing Symposium.

Davis, F. D. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Quarterly, 13(3), 319-340.

Davis, F. D., Bagozzi, R. P., & Warshaw, P. R. (1989). User acceptance of computer technology: A comparison of two theoretical models. Management Science, 35(8), 982-1003.

Devaraj, S., Fan, M., & Kohli, R. (2002). Antecedents of b2C channel satisfaction and preference: Validation e-commerce metrics. Information Systems Research, 13(3), 316-333.

Find (2005). Internet in Taiwan. Available at http://www.find.org.tw/eng. Accessed June 5, 2006.

Fishbein, M., & Ajzen, I. (1975). Belief, attitude, intentions and behavior: An introduc-tion to theory and research. Reading, MA: Addison-Wesley.

Fornell, C., & Larcker, D. F. (1981). Evaluating structural equation models with unob-servable variables and measurement error, Journal of Marketing Research, 18 (Feb-ruary), 39-50.

Gefen, D., Straub, D., & Boudreau, M. C. (2000). Structural equation modeling and re-gression: Guidelines for research practice. Communications of AIS, 4(7), 1-78.

Hair, J. F., Anderson, R. E., Tatham, R. L., & Black, W. C. (1998). Multivariate data analysis (5th ed.). Upper Saddle River, NJ: Prentice Hall.

Hayashi, A., Chen, C., Ryan, T., & Wu, J. (2004). The role of social presence and moder-ating role of computer self efficacy in predicting the continuance usage of e-learning systems. Journal of Information Systems Education, 15(2), 139-154.

Hellier, P. K., Geursen, G. M., Carr, R. A., & Rickard, J. A. (2003). Customer repurchase intention: A general structural equation model. European Journal of Marketing, 37(11/12), 1762-1800.

Hong, S. J., Thong, J. Y. L., & Tam, K. Y. (2005). Understanding continued IT usage: An extension to the expectation-confirmation model in IT domain. In Proceedings of the Ninth Pacific Asia Conference on Information Systems, Bangkok, Thailand.

Hsu, M. H., & Chiu, C. M. (2004). Predicting electronic service continuance with a de-composed theory of planned behaviour. Behaviour & Information Technology, 23(5), 359-373.

Hsu, M. H., Chiu, C. M., & Ju, T. L. (2004). Determinants of continued use of the WWW: An integration of two theoretical models. Industrial Management + Data Systems, 104(8/9), 766-775.

Hsu, M. H., Yen, C. H., Chiu, C. M., & Chang, C. M. (2006). A longitudinal investiga-tion of continued online shopping behavior: An extension of the theory of planned behavior. International Journal of Human-Computer Studies, 64(9), 889-904.

Ifinedo, P. (2006). Acceptance and continuance intention of Web-based Learning Tech-nologies (WLT) use among university students in a Baltic country. Electronic Jour-nal of Information Systems in Developing Countries, 23(6), 1-20.

Joreskog, K., & Sorbom, D. (1994). Structural equation modeling with the SIMPLIS command language. Chicago: Scientific Software International.

Ju, T. L., & Hsu, M. H. (2004). Understanding Web site continuance from a composite view of expectancy disconfirmation theory and theory of planned behavior. In The 8th Pacific-Asia Conference on Information Systems, Shanghai, China.

Koppius, O., Speelman, W., & Stulp, O. (2005). Why are customers coming back to buy their airline tickets online? Theoretical explanations and empirical evidence. In Pro-ceedings of the 7th International Conference on Electronic Commerce, Xi'an, China.

Khalifa, M., & Liu, V. (2002). Satisfaction with Internet-based services. In Proceedings of the 35th Hawaii International Conference on System Sciences.

Khalifa, M., & Liu, V. (2005). Online consumer retention: Development of new habits. In Proceedings of the 38th Annual Hawaii International Conference on System Sci-ences.

Koufaris, M. (2002). Applying the technology acceptance model and flow theory to online consumer behavior. Information Systems Research, 13(2), 205-223.

LaTour, S. A., & Peat, N. C. (1979). Conceptual and methodological issues in consumer satisfaction research. Advances in Consumer Research, 6, 431-437.

Legris, P., Ingham, J., & Collerette, P. (2003). Why do people use information technol-ogy? A critical review of the technology acceptance model. Information & Manage-ment, 40(3), 191-204.

Leong, P., Ho, C., & Zhang, S. (2005). Understanding interactivity in online learning en-vironments: The role of social presence & cognitive absorption in student satisfac-tion. In Proceedings of World Conference on E-Learning in Corporate, Government, Healthcare, and Higher Education, Vancouver, Canada.

Lin, C. S., Wu, S., & Tsai, R. J. (2005). Integrating perceived playfulness into expecta-tion-confirmation model for Web portal context. Information & Management, 42(5), 683-693.

Mathieson, K. (1991). Predicting user intentions: Comparing the technology acceptance model with the theory of planned behavior. Information Systems Research, 2(3), 173-191.

McKinney, V., Yoon, K., & Zahedi, F. M. (2002). The measurement of Web-customer satisfaction: An expectation and disconfirmation approach. Information Systems Re-search, 13(3), 296-315.

Mueller, R. O. (1996). Basic principles of structural equation modeling: An introduction to LISREL and EQS. New York: Springer-Verlag.

Oliver, R. L. (1980). A cognitive model of the antecedents and consequences of satisfac-tion decisions. Journal of Marketing Research, 17(4), 460-469.

Oliver, R. L. (1981). Measurement and evaluation of satisfaction process in retail setting. Journal of Retailing, 57, 25-81.

Oliver, R. L., & DeSarbo, W. (1988). Response determinants in satisfaction judgments. Journal of Consumer Research, 14, 495-507.

Patterson, P. G., & Spreng, R. A. (1997). Modelling the relationship between perceived value, satisfaction and repurchase intentions in a business-to-business, services con-text: An empirical examination. International Journal of Service Industry Manage-ment, 8(5), 414-434.

Rai, A., Lang, S. S., & Welker, R. B. (2002). Assessing the validity of IS success models: An empirical test and theoretical analysis. Information Systems Research, 13(1), 50-69.

Roca, J. C., Chiu, C. M., & Martínez, F. J. (2006). Understanding e-learning continuance intention: An extension of the Technology Acceptance Model. International Journal of Human-Computer Studies, 64, 683-696.

Rosental, R., & Rosnow, R. L. (1991). Essentials of behavioral research: Methods and data analysis (2nd ed.). New York: McGraw-Hill.

Saadé, R., & Bahli, B. (2005). The impact of cognitive absorption on perceived useful-ness and perceived ease of use in on-line learning: An extension of the technology acceptance model. Information & Management, 42(2), 317-327.

Seddon, P. B. (1997). A respecification and extension of the DeLone and McLean model of IS success. Information Systems Research, 8(3), 240-253.

Shang, R. A., Chen, Y. C, & Shen, L. (2005). Extrinsic versus intrinsic motivations for consumers to shop on-line. Information & Management, 42(3), 401-413.

Shih, H. P. (2004). An empirical study on predicting user acceptance of e-shopping on the Web. Information & Management, 41(3), 351-368.

Siekpe, J. S. (2005). An examination of the multidimensionality of flow construct in a computer-mediated environment. Journal of Electronic Commerce Research, 6(1), 31-43.

Spreng, R. A., Mackenzie, S. B., & Olshavsky, R. W. (1996). A reexamination of the de-terminants of consumer satisfaction. Journal of Marketing, 60(3), 15-32.

Taiwan Network Information Center (2006). Internet Survey Results. Available at http://www.twnic.net.tw/download/200307/0308e.ppt. Accessed June 10, 2006.

Taylor, S., & Todd, P. A. (1995). Understanding information technology usage: A test of competing models. Information Systems Research,6(2), 144-176.

Tellegen, A., & Atkinson, G. (1974). Openness to absorbing and self-altering experiences ("absorption"), a trait related to hypnotic susceptibility. Journal of Abnormal Psy-chology, 83, 268-277.

Vallerand, R. J. (1997). Toward a hierarchical model of intrinsic and extrinsic motiva-tion. Advances in Experimental Social Psychology, 29, 271-360.

Venkatesh, V. (1999). Creation of favorable user perceptions: Exploring the role of in-trinsic motivation. MIS Quarterly, 23(2), 239-260.

Venkatesh, V. (2000). Determinants of perceived ease of use: Integrating control, intrin-sic motivation, and emotion into the technology acceptance model. Information Sys-tems Research, 11(4), 342-365.

Venkatesh, V., & Davis, F. D. (2000). A theoretical extension of the technology accep-tance model: Four longitudinal field studies. Management Science, 46(2), 186-204.

Wright, K. M., & Granger, M. J. (2001). Using the Web as a strategic resource: An ap-plied classroom exercise. In Proceedings of the 16th Annual Conference of the Inter-national Academy for Information Management.

Wu, J. (2006). An integrative model to predict the continuance use of electronic learning systems: Hints for teaching. International Journal on E-Learning, 5(2), 287-302.

Yam Web Frontier Foundation (2005). Internet Survey Results. Available at http://survey.yam.com/survey2005/chart/index.php. Accessed June 1, 2006.

Zhang, P., Li, N., & Sun, H. (2006). Affective quality and cognitive absorption: Extend-ing technology acceptance research. In Proceedings of the 39th Annual Hawaii In-ternational Conference on System Sciences.

校內：2008-08-29公開
校外：2012-08-29公開

簡易檢索 / 詳目顯示

相關論文