Assessing the Moderating Effect of Consumer Product Knowledge and Online Shopping Experience on using Recommedation Agents for Customer Loyalty

• Main Authors: YOON, Victoria Y., HOSTLER, R. Eric, GUO, Zhiling, GUIMARAES, Tor
• Format: text
• Language: English
• Published: Institutional Knowledge at Singapore Management University 2013
• Subjects: Intelligent agents; Customer loyalty; Customer satisfaction with website; Customer value; Product knowledge; Online shopping experience; Computer Sciences; Management Information Systems
• Online Access: https://ink.library.smu.edu.sg/sis_research/1855; https://ink.library.smu.edu.sg/context/sis_research/article/2854/viewcontent/AssessingModeratingEffect_ConsumerProductKnowledge_CustomerLoyalty_afv.pdf
• Institution: Singapore Management University

Social media technologies have greatly facilitated the creation of many types of user-generated information, e.g., product rating information can be used to generate preference-based recommendation. As a decision support tool, a Recommendation Agent (RA) has been widely adopted by many e-commerce websites. The impact of RAs on online shopping has been extensively examined in the IS literature. However, from Marketing and Social Media perspectives, the widely adopted cognitive–affect–conative–action framework of customer loyalty has not been tested in the presence of RAs. Moreover, there has been little research assessing the impact of increasing consumer knowledge about specific product domains on customer satisfaction and loyalty. Based on these important constructs, this study proposes and empirically tests a parsimonious model assessing the moderating effect of consumer product knowledge and online shopping experience on using RA for customer loyalty. The results show that consumer product knowledge relationship between RA's recommendations negatively impacts the recommendation quality and customer satisfaction, however, consumer online shopping experience does not have a significant effect on the relationship between customer satisfaction and customer loyalty. The results make a significant contribution to a better understanding of the constructs in our research model and provide evidence useful for the management of websites using RAs for product recommendations.