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E- TİCARETE İLİŞKİN TÜKETİCİLERİN RİSK ALGISININ TUTUM VE NİYETLER ÜZERİNE ETKİSİ: ORDİNAL YAPISAL EŞİTLİK MODELİ

Year 2010, Volume: 2 Issue: 2, 49 - 63, 31.07.2010

Veysel Yılmaz H. Eray Çelik M. Vedat Pazarlıoğlu

Abstract

Çalışmada, e-ticarete ilişkin tüketicilerin niyetlerini belirleyen faktörler arasındaki ilişkiler ordinal değişkenli yapısal eşitlik modellemesi kullanılarak açıklanmaya çalışılmıştır. Çalışmada e-anket kullanılarak elde edilen verilerin analizinde LISREL hazır yazılımı kullanılmıştır. Yapılan analiziler sonucunda araştırma modelinde yer alan bağımsız ve aracı değişkenlerin yeterli olduğu belirlenmiştir.

Keywords

E-ticaret Risk Yapısal Eşitlik Modellemesi Ordinal LISREL

References

  • ANTONY, S., LIN, Z., XU, B. (2006). Determinants of Escrow Service Adoption in Consumer-To-Consumer Online Auction Market: An Experimental Study, Decision Support Systems, 42(3), (s:1889–1900).
  • BHATNAGAR, A., MISRA, S., RAO, H. R. (2000). On Risk, Convenience, And Internet Shopping Behavior, Communications of the ACM, 43(11), (s:98-105).
  • BIDGOLI, H. (2002). Electronic Commerce: Principles and Practice. USA: Academic Press,
  • BOLLEN, K.A. (1989). Structural Equations with Latent Variables, Wiley, New York.
  • CORBITT, B.J., THANASANKIT, T., YI, H. (2003). Trust and E-Commerce: A Study of Consumer Perceptions, Electronic Commerce Research and Applications, 2(3), (s:203-215).
  • COUPER, M.P. (2000). Web Surveys: A Review of Issues and Approaches. Public Opinion Quarterly, 64(4), (s:464-494).
  • CRESPO, A. H., del BOSQUE, I. R. (2008). The Effect of Innovativeness On The Adoption of B2C E-Commerce: A Model Based On The Theory of Planned Behaviour, Computers in Human Behavior, 24(6), (s:2830-2847).
  • DAVIS, F.D. (1989). Perceived Usefulness, Perceived Ease of Use, and User Acceptance of Information Technology. MIS Quarterly, 13(3), (s:319-339).
  • 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), (s:982-1003).
  • FLORA, D.B., CURRAN, P.J. (2004). An Empirical Evaluation of Alternative Methods of Estimation For Confirmatory Factor Analysis With Ordinal Data, Psychological Methods, 9(4), (s:466-491).
  • JÖRESKOG, K.G. (1994). On The Estimation of Polychoric Correlations and Their Asymptotic Covariance Matrix, Psychometrica, 59, (s:381-389).
  • JÖRESKOG, K.G. (2005). Structural Equation Modeling with Ordinal Variables Using LISREL, Scientific Software International, Chicago.
  • JÖRESKOG, K.G., MOUSTAKI, I. (2001). Factor Analysis of Ordinal Variables: A Comparison of Three Approaches, Multivariate Behavioral Research, 36(3), (s:347-387).
  • JÖRESKOG, K.G., SÖRBOM, D. (1981). LISREL V: Analysis of Linear Structural Relationships By Maximum Likelihood and Least Squares Methods (Research Report 81−8), Uppsala, Sweden: University of Uppsala, Department of Statistics.
  • JÖRESKOG, K.G., SÖRBOM, D. (1993). LISREL 8 User’s Reference Guide; PRELIS 2 User’s Reference Guide, Scientific Software International, Chicago.
  • KALAKOTA, R., WHINSTON, A. B. (1997). Electronic Commerce, Massachusetts: Addison Wesley.
  • KELLER, C. (2005). Virtual Learning Environments: Three Implementation Perspectives. Learning, Media and Technology, 30(3). (s:299-311).
  • KIM, D.J., FERRIN, D.L., RAO, H.R. (2008). A Trust-Based Consumer Decision- Making Model in Electronic Commerce: The Role of Trust, Perceived Risk, and Their Antecedents, Decision Support System, 44, (s:544-564).
  • KIMERY, K.M., McCORD, M. (2002). Third-Party Assurances: Mapping The Road To Trust in E-Retailing, Journal of Information, Technology Theory and Application, 4(2), (s:63–81).
  • KLOPPING, I. M., McKINNEY, E. (2004). Information Technology. Learning, and Performance Journal, 24(1), (s:35-47).
  • KOLSAKER, A., LEE-KELLEY, L., CHOY, P.C. (2004). The Reluctant Hong Kong Consumer Web Use and Their Implications For E-Commerce, Journal of Consumer Studies, 28(3), (s:195-304).
  • LEE, S.Y.(2007). Structural Equation Modeling: A Bayesian Approach. WileyS.
  • LEGRIS, P., INGHAM, I., COLLERETTE, P. (2003). Why Do People Use Information Technology? A Critical Review Of The Technology Acceptance Model, Information Management, 40(3), (s:191-204).
  • LIAO, Z., CHEUNG, M. T. (2001). Internet-Based E-Shopping and Consumer Attitudes an Empirical Study. Information & Management, 38(5), (s:299-306).
  • LINGYUN, Q., DONG, L., (2008). Applying TAM in B2C E-Commerce Research: An Extended Model. Tsinghua Science & Technology, 13(3), (s:265-272).
  • McKNIGHT, D.H., CHOUDHURY, V., KACMAR, C. (2002). The Impact of Initial Consumer Trust on Intentions To Transact With A Website: A Trust Building Model, Journal of Strategic Information Systems, 11 (3–4), (s:297–323).
  • MIYAZAKİ, A.D., FERNANDEZ, A. (2000). Internet Privacy And Security: An Examination of Online Retailer Disclosures, Journal of Public Policy and Marketing, 19 (1), (s:54-61).
  • MOUSTAKI, I. (2000). A Latent Variable Model For Ordinal Variables, Applied Psychological Measurement, 24(3), (s:211-233).
  • MOUSTAKI, I., JÖRESKOG, K.G., MAVRIDIS, D. (2004). Factor Models For Ordinal Variables With Covariate Effects On The Manifest and Latent Variables: A Comparison Of LISREL and IRT Approaches, Structural Equation Modeling, 11(4), (s:487-513).
  • MUTHÉN, B.O. (1984). A General Structural Equation Model With Dichotomous, Ordered Categorical and Continuous Latent Variable Indicators. Psychometrika, 49, (s:115–132).
  • 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), (s:101-134).
  • RAYKOV, T., MARCOULIDES, G.A. (2006). A First Course In Structural Equation Modeling, Mahwah, NJ: Lawrence Erlbaum Associates.
  • SCHERMELLEH-ENGEL, K., MOOSBRUGGER, H., MÜLLER, H. (2003). Evaluating The Fit of Structural Equation Models: Test of Significance and Descriptive Goodness-Of-Fit Measures. Methods of Psychological Research - Online, 8(2), (s:23-74).
  • SHIH, PIN H. (2004). An Empirical Study On Predicting User Acceptance of E- Shopping On The Web, Information & Management, 41(3), (s:351-368).
  • SUH, B., HAN, I. (2002). Effect of Trust On Customer Acceptance of Internet Banking. Electronic Commerce Research and Applications, 1(3-4), (s:247-263).
  • TREESE, W.G., STEWART, L.C. (1998). Designing for Internet Commerce, Addison- Wesley, Longham, New York.
  • WANG, F., HEAD, M. (2007). How Can The Web Help Build Customer Relationships: An Empirical Study On E-Tailing, Information & Management, 44(2), (s:115- 129).
  • ZHOU, L., DAI, L., ZHANG, D. (2007). Online Shopping Acceptance Model – A Critical Survey Of Consumer Factors in Online Shopping, Journal of Electronic Commerce Research, 8(1), (s:41-62).

Year 2010, Volume: 2 Issue: 2, 49 - 63, 31.07.2010

Veysel Yılmaz H. Eray Çelik M. Vedat Pazarlıoğlu

Abstract

The relation between the factors, which determine the consumers’ intention about e-commerce, is tried to put forward by using Research Model via structural equation model with ordinal variable. By this aim LISREL packet program is used. At the end of the analysis, the independent and intermediary variables are found sufficient to explain the consumers’ intention about e-commerce.

Keywords

E-commerce Risk Structural Equation Model Ordinal LISREL

References

  • ANTONY, S., LIN, Z., XU, B. (2006). Determinants of Escrow Service Adoption in Consumer-To-Consumer Online Auction Market: An Experimental Study, Decision Support Systems, 42(3), (s:1889–1900).
  • BHATNAGAR, A., MISRA, S., RAO, H. R. (2000). On Risk, Convenience, And Internet Shopping Behavior, Communications of the ACM, 43(11), (s:98-105).
  • BIDGOLI, H. (2002). Electronic Commerce: Principles and Practice. USA: Academic Press,
  • BOLLEN, K.A. (1989). Structural Equations with Latent Variables, Wiley, New York.
  • CORBITT, B.J., THANASANKIT, T., YI, H. (2003). Trust and E-Commerce: A Study of Consumer Perceptions, Electronic Commerce Research and Applications, 2(3), (s:203-215).
  • COUPER, M.P. (2000). Web Surveys: A Review of Issues and Approaches. Public Opinion Quarterly, 64(4), (s:464-494).
  • CRESPO, A. H., del BOSQUE, I. R. (2008). The Effect of Innovativeness On The Adoption of B2C E-Commerce: A Model Based On The Theory of Planned Behaviour, Computers in Human Behavior, 24(6), (s:2830-2847).
  • DAVIS, F.D. (1989). Perceived Usefulness, Perceived Ease of Use, and User Acceptance of Information Technology. MIS Quarterly, 13(3), (s:319-339).
  • 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), (s:982-1003).
  • FLORA, D.B., CURRAN, P.J. (2004). An Empirical Evaluation of Alternative Methods of Estimation For Confirmatory Factor Analysis With Ordinal Data, Psychological Methods, 9(4), (s:466-491).
  • JÖRESKOG, K.G. (1994). On The Estimation of Polychoric Correlations and Their Asymptotic Covariance Matrix, Psychometrica, 59, (s:381-389).
  • JÖRESKOG, K.G. (2005). Structural Equation Modeling with Ordinal Variables Using LISREL, Scientific Software International, Chicago.
  • JÖRESKOG, K.G., MOUSTAKI, I. (2001). Factor Analysis of Ordinal Variables: A Comparison of Three Approaches, Multivariate Behavioral Research, 36(3), (s:347-387).
  • JÖRESKOG, K.G., SÖRBOM, D. (1981). LISREL V: Analysis of Linear Structural Relationships By Maximum Likelihood and Least Squares Methods (Research Report 81−8), Uppsala, Sweden: University of Uppsala, Department of Statistics.
  • JÖRESKOG, K.G., SÖRBOM, D. (1993). LISREL 8 User’s Reference Guide; PRELIS 2 User’s Reference Guide, Scientific Software International, Chicago.
  • KALAKOTA, R., WHINSTON, A. B. (1997). Electronic Commerce, Massachusetts: Addison Wesley.
  • KELLER, C. (2005). Virtual Learning Environments: Three Implementation Perspectives. Learning, Media and Technology, 30(3). (s:299-311).
  • KIM, D.J., FERRIN, D.L., RAO, H.R. (2008). A Trust-Based Consumer Decision- Making Model in Electronic Commerce: The Role of Trust, Perceived Risk, and Their Antecedents, Decision Support System, 44, (s:544-564).
  • KIMERY, K.M., McCORD, M. (2002). Third-Party Assurances: Mapping The Road To Trust in E-Retailing, Journal of Information, Technology Theory and Application, 4(2), (s:63–81).
  • KLOPPING, I. M., McKINNEY, E. (2004). Information Technology. Learning, and Performance Journal, 24(1), (s:35-47).
  • KOLSAKER, A., LEE-KELLEY, L., CHOY, P.C. (2004). The Reluctant Hong Kong Consumer Web Use and Their Implications For E-Commerce, Journal of Consumer Studies, 28(3), (s:195-304).
  • LEE, S.Y.(2007). Structural Equation Modeling: A Bayesian Approach. WileyS.
  • LEGRIS, P., INGHAM, I., COLLERETTE, P. (2003). Why Do People Use Information Technology? A Critical Review Of The Technology Acceptance Model, Information Management, 40(3), (s:191-204).
  • LIAO, Z., CHEUNG, M. T. (2001). Internet-Based E-Shopping and Consumer Attitudes an Empirical Study. Information & Management, 38(5), (s:299-306).
  • LINGYUN, Q., DONG, L., (2008). Applying TAM in B2C E-Commerce Research: An Extended Model. Tsinghua Science & Technology, 13(3), (s:265-272).
  • McKNIGHT, D.H., CHOUDHURY, V., KACMAR, C. (2002). The Impact of Initial Consumer Trust on Intentions To Transact With A Website: A Trust Building Model, Journal of Strategic Information Systems, 11 (3–4), (s:297–323).
  • MIYAZAKİ, A.D., FERNANDEZ, A. (2000). Internet Privacy And Security: An Examination of Online Retailer Disclosures, Journal of Public Policy and Marketing, 19 (1), (s:54-61).
  • MOUSTAKI, I. (2000). A Latent Variable Model For Ordinal Variables, Applied Psychological Measurement, 24(3), (s:211-233).
  • MOUSTAKI, I., JÖRESKOG, K.G., MAVRIDIS, D. (2004). Factor Models For Ordinal Variables With Covariate Effects On The Manifest and Latent Variables: A Comparison Of LISREL and IRT Approaches, Structural Equation Modeling, 11(4), (s:487-513).
  • MUTHÉN, B.O. (1984). A General Structural Equation Model With Dichotomous, Ordered Categorical and Continuous Latent Variable Indicators. Psychometrika, 49, (s:115–132).
  • 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), (s:101-134).
  • RAYKOV, T., MARCOULIDES, G.A. (2006). A First Course In Structural Equation Modeling, Mahwah, NJ: Lawrence Erlbaum Associates.
  • SCHERMELLEH-ENGEL, K., MOOSBRUGGER, H., MÜLLER, H. (2003). Evaluating The Fit of Structural Equation Models: Test of Significance and Descriptive Goodness-Of-Fit Measures. Methods of Psychological Research - Online, 8(2), (s:23-74).
  • SHIH, PIN H. (2004). An Empirical Study On Predicting User Acceptance of E- Shopping On The Web, Information & Management, 41(3), (s:351-368).
  • SUH, B., HAN, I. (2002). Effect of Trust On Customer Acceptance of Internet Banking. Electronic Commerce Research and Applications, 1(3-4), (s:247-263).
  • TREESE, W.G., STEWART, L.C. (1998). Designing for Internet Commerce, Addison- Wesley, Longham, New York.
  • WANG, F., HEAD, M. (2007). How Can The Web Help Build Customer Relationships: An Empirical Study On E-Tailing, Information & Management, 44(2), (s:115- 129).
  • ZHOU, L., DAI, L., ZHANG, D. (2007). Online Shopping Acceptance Model – A Critical Survey Of Consumer Factors in Online Shopping, Journal of Electronic Commerce Research, 8(1), (s:41-62).
There are 38 citations in total.

Details

Other ID JA44BA99PZ
Journal Section Review Article
Authors

Veysel Yılmaz

H. Eray Çelik

M. Vedat Pazarlıoğlu

Publication Date July 31, 2010
Published in Issue Year 2010Volume: 2 Issue: 2

Cite

APA Yılmaz, V., Çelik, H. E., & Pazarlıoğlu, M. V. (2010). E- TİCARETE İLİŞKİN TÜKETİCİLERİN RİSK ALGISININ TUTUM VE NİYETLER ÜZERİNE ETKİSİ: ORDİNAL YAPISAL EŞİTLİK MODELİ. Aksaray Üniversitesi İktisadi Ve İdari Bilimler Fakültesi Dergisi, 2(2), 49-63.
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