Abstract

PurposeConsumers often encounter issues of perceived ambiguity and performance risk when attempting to evaluate experience goods being offered online. Sellers try to alleviate this knowledge gap often seen in a medium of low naturalness by engaging in effective compensatory adaptation. This research theoretically looks into three primary aspects of compensatory adaption and their potential in securing communication of high-quality information between the online seller and consumer.Design/methodology/approachUtilizing survey data and structural equation modeling, this study tests the effectiveness of different aspects of compensatory adaption to alleviate the knowledge gap in a medium of low naturalness.FindingsDrawing on media naturalness theory and the tripartite model of attitude, this paper identifies three theoretical components that significantly affect the effectiveness of compensatory adaption. They are information retrieval capability from the cognitive/logical aspect, information richness from the affective/audiovisual aspect and interactivity from the behavioral aspect. The effectiveness of compensatory adaptation proves to have a positive impact on perceived information quality.Originality/valueTo the best of our knowledge, this is the first paper in the information systems literature to examine the compensatory adaptation tools for effective transfer of information. This study contributes to the academics by providing three handles to improve effectiveness of compensatory adaptation toward information quality. We focus on three compensatory adaptation tools in cognitive/logical, affective/audiovisual and behavioral aspects, and this compensation perspective leads to three practical factors that affect effective transfer of information between online sellers and consumers. The result of this study complements the nomological network of the enablers and impediments of e-commerce.

Full Text
Published version (Free)

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call