Social learning approach in designing persuasive e-commerce recommender system model

• Main Authors: Che Lah, N. S., Che Hussin, A. R., Ab Rahim, N. Z., Busalim, A. H.
• Format: Article
• Language: English
• Published: Asian Research Publishing Network 2016
• Subjects: QA75 Electronic computers. Computer science
• Online Access: http://eprints.utm.my/id/eprint/72181/1/AbRazakCheHussin2016_SocialLearningApproachinDesigningPersuasive.pdf; http://eprints.utm.my/id/eprint/72181/; https://www.scopus.com/inward/record.uri?eid=2-s2.0-84984891050&partnerID=40&md5=91f9edb6e592d290ede7d46a059f0a27
• Institution: Universiti Teknologi Malaysia

Intention to purchase in existing online business practice is learned through observation of information display by online seller. The emergent growth of persuasive technologies currently holds a great potential in driving a positive influence towards consumer purchase behavior. But to date, there is still limited research on implementing persuasion concept into the recommender system context. Drawing upon the principle design of persuasive system, the main purpose of this study is to explore social learning advantages in creating persuasive features for E-Commerce recommender system. Based on Social Cognitive Theory, the influence of personal and environmental factors will be examined in measuring consumer purchase intention. In addition, dimensions of social learning environment are represented by observational learning theory and cognitive learning theory. From those reviews, this study assumed that social learning environment can be created based on attentiveness, retentiveness, motivational, knowledge awareness and interest evaluation cues of consumer learning factors. Furthermore, the persuasive environment of recommender system is assumed to have positive influence towards individual characteristics such as self-efficacy behavior, perceived task complexity and confused by over choice. Findings from those reviews have contributed to the development of a research model in visualizing social learning environment that can be used to develop a persuasive recommender system in E-Commerce and hence measures the impact towards consumer purchase intention.