The purpose of this paper is to advance product appeal and website appeal as focal psychological mechanisms that can be invoked by business-to-consumer e-commerce sites to mitigate problems of information asymmetry via signaling to bolster consumers’ purchase intention under the influence of trust.
Survey approach was employed to validate the research model.
Website appeal partially mediates the positive effect of product appeal on consumers’ purchase intention. Trust in e-commerce sites not only increases purchase intention directly, but it also reinforces the positive relationship between website appeal and purchase intention while attenuating the positive relationship between product appeal and purchase intention. Service content quality, search delivery quality, and enjoyment are confirmed as positive antecedents of website appeal whereas diagnosticity and justifiability are established as positive antecedents of product appeal.
This study not only delineates product and website appeal as complementary drivers of consumer purchase on e-commerce sites, but it also derives five signals that aid in bolstering both product and website appeal. Trust is revealed to exert a moderating influence on the impact of product and website appeal on purchase intention.
Practitioners should prioritize their resource allocation to enhance qualities most pertinent to product and website appeal. E-commerce sites should offer product-oriented functionalities to facilitate product diagnosticity and reassure consumers of their purchase decisions.
This study distinguishes between product and website appeal as well as between their respective antecedents. It also uncovers how trust can alter the effects of both website and product appeal on consumers’ purchase intention.
Liu, F., Xiao, B., Lim, E.T.K. and Tan, C.-W. (2017), "The art of appeal in electronic commerce: Understanding the impact of product and website quality on online purchases", Internet Research, Vol. 27 No. 4, pp. 752-771. https://doi.org/10.1108/IntR-09-2016-0280Download as .RIS
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