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Website design quality and usage behavior: Unified Theory of Acceptance and Use of Technology

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  • Al-Qeisi, Kholoud
  • Dennis, Charles
  • Alamanos, Eleftherios
  • Jayawardhena, Chanaka

Abstract

Firms gain many benefits from well-designed websites. But which elements of website design quality really matter, and how do these elements influence usage behavior? With the Unified Theory of Acceptance and Use of Technology (UTAUT) as the theoretical foundation, this paper proposes that website design quality is a multi-dimensional construct with a higher-order structure that, when successfully incorporated into the UTAUT model, outperforms existing models. Results are based on a survey of 216 users of internet banking. Findings indicate that the technical, general content and appearance dimensions of a website are most important for users. These dimensions are significantly related to usage behavior directly and indirectly. A halo effect may influence overall evaluation of a website because the dimensions of website design quality are interrelated. The implication is that improvements to the appearance of a website should enhance the overall evaluation of the site, leading to greater usage intentions.

Suggested Citation

  • Al-Qeisi, Kholoud & Dennis, Charles & Alamanos, Eleftherios & Jayawardhena, Chanaka, 2014. "Website design quality and usage behavior: Unified Theory of Acceptance and Use of Technology," Journal of Business Research, Elsevier, vol. 67(11), pages 2282-2290.
    • Handle: RePEc:eee:jbrese:v:67:y:2014:i:11:p:2282-2290
    DOI: 10.1016/j.jbusres.2014.06.016
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    as
    1. Kim, Sang-Hoon & Park, Hyun Jung, 2011. "Effects of social influence on consumers' voluntary adoption of innovations prompted by others," Journal of Business Research, Elsevier, vol. 64(11), pages 1190-1194.
    2. Alsajjan, Bander & Dennis, Charles, 2010. "Internet banking acceptance model: Cross-market examination," Journal of Business Research, Elsevier, vol. 63(9-10), pages 957-963, September.
    3. Viswanath Venkatesh, 2000. "Determinants of Perceived Ease of Use: Integrating Control, Intrinsic Motivation, and Emotion into the Technology Acceptance Model," Information Systems Research, INFORMS, vol. 11(4), pages 342-365, December.
    4. Smith, Rachel & Deitz, George & Royne, Marla B. & Hansen, John D. & Grünhagen, Marko & Witte, Carl, 2013. "Cross-cultural examination of online shopping behavior: A comparison of Norway, Germany, and the United States," Journal of Business Research, Elsevier, vol. 66(3), pages 328-335.
    5. Ha, Sejin & Stoel, Leslie, 2009. "Consumer e-shopping acceptance: Antecedents in a technology acceptance model," Journal of Business Research, Elsevier, vol. 62(5), pages 565-571, May.
    6. Lee, Yong-Ki & Park, Jong-Hyun & Chung, Namho & Blakeney, Alisha, 2012. "A unified perspective on the factors influencing usage intention toward mobile financial services," Journal of Business Research, Elsevier, vol. 65(11), pages 1590-1599.
    7. Toufaily, Elissar & Ricard, Line & Perrien, Jean, 2013. "Customer loyalty to a commercial website: Descriptive meta-analysis of the empirical literature and proposal of an integrative model," Journal of Business Research, Elsevier, vol. 66(9), pages 1436-1447.
    8. Ajzen, Icek, 1991. "The theory of planned behavior," Organizational Behavior and Human Decision Processes, Elsevier, vol. 50(2), pages 179-211, December.
    9. Viswanath Venkatesh & Fred D. Davis, 2000. "A Theoretical Extension of the Technology Acceptance Model: Four Longitudinal Field Studies," Management Science, INFORMS, vol. 46(2), pages 186-204, February.
    10. Gounaris, Spiros & Koritos, Christos & Vassilikopoulou, Katerina, 2010. "Person-place congruency in the Internet Banking context," Journal of Business Research, Elsevier, vol. 63(9-10), pages 943-949, September.
    11. Richard D. Johnson & George M. Marakas, 2000. "Research Report: The Role of Behavioral Modeling in Computer Skills Acquisition: Toward Refinement of the Model," Information Systems Research, INFORMS, vol. 11(4), pages 402-417, December.
    12. Shirley Taylor & Peter A. Todd, 1995. "Understanding Information Technology Usage: A Test of Competing Models," Information Systems Research, INFORMS, vol. 6(2), pages 144-176, June.
    13. Thomas P. Novak & Donna L. Hoffman & Yiu-Fai Yung, 2000. "Measuring the Customer Experience in Online Environments: A Structural Modeling Approach," Marketing Science, INFORMS, vol. 19(1), pages 22-42, May.
    14. Choi, Hun & Kim, Youngchan & Kim, Jinwoo, 2011. "Driving factors of post adoption behavior in mobile data services," Journal of Business Research, Elsevier, vol. 64(11), pages 1212-1217.
    15. Fred D. Davis & Richard P. Bagozzi & Paul R. Warshaw, 1989. "User Acceptance of Computer Technology: A Comparison of Two Theoretical Models," Management Science, INFORMS, vol. 35(8), pages 982-1003, August.
    16. Gholamreza Torkzadeh & Gurpreet Dhillon, 2002. "Measuring Factors that Influence the Success of Internet Commerce," Information Systems Research, INFORMS, vol. 13(2), pages 187-204, June.
    17. Andrews, Lynda & Bianchi, Constanza, 2013. "Consumer internet purchasing behavior in Chile," Journal of Business Research, Elsevier, vol. 66(10), pages 1791-1799.
    18. Bauer, Hans H. & Falk, Tomas & Hammerschmidt, Maik, 2006. "eTransQual: A transaction process-based approach for capturing service quality in online shopping," Journal of Business Research, Elsevier, vol. 59(7), pages 866-875, July.
    19. Floh, Arne & Zauner, Alexander & Koller, Monika & Rusch, Thomas, 2014. "Customer segmentation using unobserved heterogeneity in the perceived-value–loyalty–intentions link," Journal of Business Research, Elsevier, vol. 67(5), pages 974-982.
    20. Dickinger, Astrid & Stangl, Brigitte, 2013. "Website performance and behavioral consequences: A formative measurement approach," Journal of Business Research, Elsevier, vol. 66(6), pages 771-777.
    21. Cortiñas, Mónica & Chocarro, Raquel & Villanueva, María Luisa, 2010. "Understanding multi-channel banking customers," Journal of Business Research, Elsevier, vol. 63(11), pages 1215-1221, November.
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