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İnternet Üzerinden Alışveriş Niyetini Etkileyen Faktörlerin Genişletilmiş Teknoloji Kabul Modeli Kullanarak İncelenmesi Ve Bir Model Önerisi (An Investigation And A Model Suggestion For Factors Affecting Online Shopping Intention Using Extended Technology

Year 2015, , 355 - 384, 12.01.2016
https://doi.org/10.18657/yecbu.76242

Abstract

İşletmeler için müşterilere ulaşmada internetin kullanımı giderek daha fazla cazip hale gelmektedir. TÜİK’in 2014 Ağustos’ta yayınladığı Hanehalkı Bilişim Teknolojileri Kullanım Araştırması sonuçlarına göre İnternet kullanan bireylerin internet üzerinden kişisel kullanım amacıyla mal veya hizmet siparişi verme ya da satın alma oranı %30,8 olmuştur. İnternet kanalıyla mal ve hizmet satan işletmelere, müşterilerin alışveriş niyetini etkileyen faktörler hakkında yol gösterici olmak giderek daha çok önem kazanmaktadır. Bu nedenle çalışma, internet üzerinden alışveriş yapan tüketicilerin niyetini etkileyen faktörler için, 1989 yılında Davis tarafından geliştirilen Teknoloji Kabul Modeli’nden (TKM) yola çıkmıştır. Bu araştırma, internet kullanan toplam 680 kişiden elde edilen verilerle, online alışveriş niyetini etkileyen faktörleri, Yapısal Eşitlik Modellemesi kullanarak incelemiştir. Algılanan kullanım kolaylığı, algılanan kullanışlılık, algılanan haz, tutum ve niyetin yanı sıra modelde algılanan bilgi kalitesi, algılanan sistem kalitesi, algılanan hizmet kalitesi, mağaza bilinirliği, güven ve öznel norm değişkenlerine de yer verilmiştir. Önerilen model, yeterli uyum iyiliği değerlerini vermiştir. Araştırmanın bulgularına göre öznel norm hariç olmak üzere modelde kullanılan tüm değişkenler arasındaki yol katsayıları anlamlıdır. Çalışmaya göre, öznel norm, tüketicilerin online alışveriş niyetini belirlemede rol oynamamaktadır.

The usage of internet while reaching to customers is getting more attractive day by day to firms. According to the TurkStat results of consumers information technology usage report that published in August 2014, individual internet users orders or buyings rate for their own usage was %30,8. It is getting more important today to help firms that are selling goods and services online, understand the buying intensions of internet consumers. Therefore, in order to understand those intensions, this study inspired from Technology Acceptance Model (TAM) which was developed by Davis in 1989. The data used in this research is gathered from a sample of 680 internet users and with the help of the relevant theory, the factors affecting online shopping intention are analyzed by structural equation modelling. In addition to perceived ease of use, perceived usefulness, perceived enjoyment, attitude and intention, information quality, perceived system quality, perceived service quality, store familiarity, trust and subjective norm variables are also used in the model. The proposed model submitted sufficient goodness of fit values. According to the findings of the research, it can be said that except of subjective norm, all other path coefficients between variables are significant. Subjective norm does not play any role in determining the consumers online shopping intention.

References

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Year 2015, , 355 - 384, 12.01.2016
https://doi.org/10.18657/yecbu.76242

Abstract

References

  • Ahn, T., Ryu, S., & Han, I. (2004). 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. http://doi.org/10.1016/j.elerap.2004.05.001
  • Ahn, T., Ryu, S., & Han, I. (2007). The Impact of Web Quality and Playfulness On User Acceptance of Online Retailing. Information & Management, 44(3), 263–275. http://doi.org/10.1016/j.im.2006.12.008
  • Ajzen, I. (1985). From Intention to Actions: A Theory of Planned Behavior, In: J. Kuhl, J. Bechmand (Eds.), Action Control: From Cognition to Behavior, Springer, New York.
  • Alan, M. A. (2002). Elektronik Ticaret ve İşletmeden Tüketiciye (B2C) Modeli Uygulaması. (Doktora Tezi, Cumhuriyet Üniversitesi, Sosyal Bilimler Enstitüsü).
  • -
  • Yönetim ve Ekonomi 22/2 (2015) 355-384
  • Atalar, G. (2012). Online Alışveriş Yönelimlerı̇ Ve Sanal Mağaza Atmosferı̇. (Yüksek Lisans Tezi, İstanbul Üniversitesi, Sosyal Bilimler Enstitüsü ,).
  • Barutçu, S. (2008). İnternet Tabanlı Tedarik Zinciri Yönetimi (Denizli Tekstil İşletmelerinin İnternet Tabanlı Tedarik Zinciri Yönetiminden Yararlanma Durumuna Yönelik Bir Araştırma).
  • Bhattacherjee, A. (2001). An Empirical Analysis of The Antecedents of Electronic Commerce Service Continuance. Decision Support Systems, 32(2), 201–214. http://doi.org/10.1016/S0167-9236(01)00111-7
  • Burton-Jones, A., & Hubona, G. S. (2006). The Mediation of External Variables In The Technology Acceptance Model. Information & Management, 43(6), 706–717. http://doi.org/10.1016/j.im.2006.03.007
  • Çakır, M. (2012). Development and Validation of B2c E-Commerce Adoption Model: An Empirical Investigation Using Structural Equation Modeling and Interpretative Phenomenological Analyses. (Doctor of Philosophy, The Graduate School of Informatics of The Middle East Technical University).
  • Çelik, H. E. (2009). Yapısal Eşitlik Modellemesi Ve Bir Uygulama: Genişletilmiş Online Alışveriş Kabul Modeli. (Doktora Tezi, Eskişehir Osmangazi Üniversitesi Fen Bilimleri Enstitüsü).
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  • Chiu, C.-M., Chang, C.-C., Cheng, H.-L., & Fang, Y.-H. (2009). Determinants of Customer Repurchase Intention In Online Shopping. Online Information Review, 33(4), 761–784. http://doi.org/10.1108/14684520910985710
  • Chiu, C.-M., Lin, H.-Y., Sun, S.-Y., & Hsu, M.-H. (2009). Understanding Customers’ Loyalty Intentions Towards Online Shopping: An Integration of Technology Acceptance Model and Fairness Theory. Behaviour & Information Technology, 28(4), 347–360. http://doi.org/10.1080/01449290801892492
  • Cho, S. E. (2010). Perceived Risks and Customer Needs of Geographical Accessibility In Electronic Commerce. Electronic Commerce Research and Applications, 9(6), 495-506.
  • Choi, G., & Chung, H. (2013). Applying the Technology Acceptance Model to Social Networking Sites (SNS): Impact of Subjective Norm and Social Capital on the Acceptance of SNS. International Journal of Human-Computer Interaction, 29(10), 619–628. http://doi.org/10.1080/10447318.2012.756333
  • Çokluk, Ö., Şekercioğlu, G. & Büyüköztürk, Ş. (2012). Sosyal Bilimler İçin Çok Değişkenli İstatistik SPSS ve LISREL Uygulamaları. Pegem Akademi Yayıncılık, Ankara.
  • Comegys, C., Hannula, M., & Váisánen, J. (2009). Effects of Consumer Trust and Risk On Online Purchase Decision-Making: A Comparison of Finnish and United States Students. International Journal of Management, 26(2), 295.
  • Cooper, M. R & Schindler, P. S. (1998). Business Research Methods Singapore: McGraw-Hill International Editions.
  • Crisostomo, E. A. (2007). Pacific Islanders and Internet Shopping: Perceived Usefulness, Internet Usage, Demographics, and Likelihood to Shop Online. (Texas Woman's University).
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Details

Primary Language English
Journal Section Articles
Authors

Cengiz Yılmaz This is me

Publication Date January 12, 2016
Published in Issue Year 2015

Cite

APA Yılmaz, C. (2016). İnternet Üzerinden Alışveriş Niyetini Etkileyen Faktörlerin Genişletilmiş Teknoloji Kabul Modeli Kullanarak İncelenmesi Ve Bir Model Önerisi (An Investigation And A Model Suggestion For Factors Affecting Online Shopping Intention Using Extended Technology. Journal of Management and Economics, 22(2), 355-384. https://doi.org/10.18657/yecbu.76242

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