Social Learning in Networks of Friends versus Strangers

• Published in: Marketing science (Providence, R.I.) Vol. 34; no. 4; pp. 573 - 589
• Main Authors: Zhang, Jurui, Liu, Yong, Chen, Yubo
• Format: Journal Article
• Language: English
• Published: Linthicum INFORMS 01.07.2015; Institute for Operations Research and the Management Sciences
• Subjects: Analysis; cascade; Consumers; Effectiveness studies; Judgement; Judgment; observational learning; Product choice; Product quality; Social aspects; social interaction; Social learning; Social media; Social networks; Special Section: Marketing Science in Emerging Markets; User groups; United States
• ISSN: 0732-2399; 1526-548X
• DOI: 10.1287/mksc.2015.0902

Networks and the embedded relationships are critical determinants of how people communicate and form beliefs. The explosion of social media has significantly increased the scope and impact of social learning among consumers. This paper studies observational learning in networks of friends versus strangers. A consumer decides whether to adopt a product after receiving a private signal about product quality and observing the actions of others. The preference for the product has greater heterogeneity in the stranger-network than in the friend-network. We show that when the network is small, observing friends’ actions helps the consumer make more accurate inferences about quality. As the network grows, however, the stranger-network becomes more effective. Underlying these results are two competing effects of network heterogeneity on social learning. These are the individual preference effect , which allows one to make a better quality judgment when the preference element of past actions is more certain, and the social conforming effect , wherein private signals are underused in quality judgment as people follow others’ actions. We find cascading is more likely to occur in the friend-network than in the stranger-network. For a high-quality firm, the stranger-network generates greater sales than the friend-network when the network size is sufficiently large or the private signal is sufficiently accurate. We also examine the existence of experts and firms using advertising to influence consumers. Finally, we show how networks that are highly homogeneous or heterogeneous could impede observational learning.