Using the S-o-r Model to Understand the Impact of Website Attributes on the Online Shopping Experience

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Using Mehrabian and Russell’s (1974) stimulus (S) - organism (O) - response (R) model, this study developed online shopping experience framework that explains consumer behavioral responses toward online and offline stores. The results of the examined hypothesized relationships in this study reveal website attributes that create positive affective and attitudinal states and behavioral responses toward the retailers and retailers’ websites. Among website attributes, interface design is the strongest predictor of all behavioral responses, while website attributes relating to shopping services and security/privacy affect long term behavioral responses, such as purchase intention and brand loyalty. This study is imperative to practitioners ... continued below

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Zimmerman, Jonelle August 2012.

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  • Zimmerman, Jonelle

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Using Mehrabian and Russell’s (1974) stimulus (S) - organism (O) - response (R) model, this study developed online shopping experience framework that explains consumer behavioral responses toward online and offline stores. The results of the examined hypothesized relationships in this study reveal website attributes that create positive affective and attitudinal states and behavioral responses toward the retailers and retailers’ websites. Among website attributes, interface design is the strongest predictor of all behavioral responses, while website attributes relating to shopping services and security/privacy affect long term behavioral responses, such as purchase intention and brand loyalty. This study is imperative to practitioners and researchers, as they will help further develop online store environments and online shopping experience.

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  • August 2012

Added to The UNT Digital Library

  • March 4, 2013, 2:02 p.m.

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  • Nov. 16, 2016, 3:47 p.m.

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Zimmerman, Jonelle. Using the S-o-r Model to Understand the Impact of Website Attributes on the Online Shopping Experience, thesis, August 2012; Denton, Texas. (digital.library.unt.edu/ark:/67531/metadc149694/: accessed October 18, 2018), University of North Texas Libraries, Digital Library, digital.library.unt.edu; .