Retail Technology Acceptance Model for online at offline (O@O): Comparing different generations of data analysis techniques

ABSTRACT

The purpose of this study is to examine consumers’ intentions to use retail technologies and to identify factors that affect their decision by extending the Technology Acceptance Model. This study employs Regression and Partial Least Squares Structural Equation Modeling to test the same construct in the proposed model, and the results were compared to find out similarities and differences. The result shows that depending on the consumers’ shopping orientation profile, they evaluated a technology differently. Also, depending on the types of technology, the factors that significantly affect consumers’ intentions to use are different. For an unfamiliar technology, consumers need to evaluate before confirming their intention to use (i.e. the mediating effect of evaluation between consumer’s profile and intention to use). Not all technologies require high usefulness for high intention to use, contrary to previous research. The PLS-SEM analysis was more appropriate than the regression for a newly developed model.

KEYWORDS:

• Offline shopping
• online shopping
• Partial Least Squares Structural Equation Modeling
• retail technology
• Technology Acceptance Model

Disclosure statement

No potential conflict of interest was reported by the author(s).

Correction Statement

This article has been republished with minor changes. These changes do not impact the academic content of the article.