Effects of post-adoption beliefs on customers’ online product recommendation continuous usage: An extended expectation-confirmation model

This study aims to extend expectation-confirmation model (ECM) of IS continuance based on effort-accuracy model (EAM) for predicting and explaining continuous usage of online product recommendation (OPR) that has been ignored in prior literature. The proposed OPR continuance model, incorporating the...

Description complète

Enregistré dans:
Détails bibliographiques
Auteurs principaux: Muhammad Ashraf, Jamil Ahmad, Asad Afzal Hamyon, Muhammad Ramzan Sheikh, Wareesa Sharif
Format: article
Langue:EN
Publié: Taylor & Francis Group 2020
Sujets:
Accès en ligne:https://doaj.org/article/55f6be38a0754b1c8ec4060ae42839b4
Tags: Ajouter un tag
Pas de tags, Soyez le premier à ajouter un tag!
Description
Résumé:This study aims to extend expectation-confirmation model (ECM) of IS continuance based on effort-accuracy model (EAM) for predicting and explaining continuous usage of online product recommendation (OPR) that has been ignored in prior literature. The proposed OPR continuance model, incorporating the post-adoption beliefs of perceived usefulness, perceived decision quality and perceived decision effort, was empirically validated with data collected from an online survey of 626 existing users of the OPR. Results indicated a good explanatory power of the OPR continuance model (R2 = 62.1% of OPR continuance intention, R2 = 53% of satisfaction, R2 = 50.5% of perceived usefulness, and R2 = 9% of perceived decision effort, and R2 = 72.3% of perceived decision quality), with all major paths supported except one. We also analysed the data on the original ECM that reveals lower variances explained compared to the OPR continuance model (D6% in OPR continuance intention, D5.1% in customer satisfaction, and D3.2% in perceived usefulness). The salient effect of perceived decision quality signifies that the nature of the IS can be an important boundary condition in understanding the continuance behaviour. At a practical level, this study presents deeper insights into how to address users’ satisfaction and continued patronage.