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dc.contributor.advisorChen, Yuboen_US
dc.contributor.advisorLiu, Yongen_US
dc.contributor.authorZhang, Jurui*
dc.creatorZhang, Juruien_US
dc.date.accessioned2012-06-11T22:42:44Z
dc.date.available2012-06-11T22:42:44Z
dc.date.issued2012
dc.identifier.urihttp://hdl.handle.net/10150/228497
dc.description.abstractNetworks and the relationships embedded in them are critical determinants of how people communicate, form beliefs, and behave. E-commerce platforms such as Amazon and eBay have made actions of "strangers" more observable to others. More recently, social media websites such as Facebook and Google Plus have created networks of "friends", and the actions of these friends have become more visible than ever before to consumers. This dissertation develops an analytical model to examine how social learning occurs in different types of networks. Specifically, I examine the pure-strategy perfect Bayesian equilibrium of observational learning in a friend-network vs. a stranger-network. In this model, each individual makes an adopt-or-reject decision about a product after receiving a private signal regarding the underlying quality of the product and observing past actions of other individuals in the network. Grounded on the homophily theory in sociology, the degree of network heterogeneity defines the key difference between a friend-network and a stranger-network. I show a threshold effect of network size regarding which network carries more valuable information: when the network size is small, a friend-network carries more valuable information than a stranger-network does. But when the network size gets larger, a stranger-network dominates a friend-network. This suggests two competing effects of network homogeneity on social learning: individual preference effects and social conforming effects. I also test key implications from theoretical results using experiments to demonstrate internal validity and enhance insights on social learning in networks. I found that experimental results are in line with predictions from the theoretical model.
dc.language.isoenen_US
dc.publisherThe University of Arizona.en_US
dc.rightsCopyright © is held by the author. Digital access to this material is made possible by the University Libraries, University of Arizona. Further transmission, reproduction or presentation (such as public display or performance) of protected items is prohibited except with permission of the author.en_US
dc.subjectSocial Learningen_US
dc.subjectSocial Networksen_US
dc.subjectManagementen_US
dc.subjectDiffusionen_US
dc.subjectInformation Cascadeen_US
dc.titleSocial Learning in a World of Friends Versus Connected Strangers: A Theoretical Model with Experimental Evidenceen_US
dc.typetexten_US
dc.typeElectronic Dissertationen_US
thesis.degree.grantorUniversity of Arizonaen_US
thesis.degree.leveldoctoralen_US
dc.contributor.committeememberGhosh, Mrinalen_US
dc.contributor.committeememberLusch, Roberten_US
dc.contributor.committeememberChen, Yuboen_US
dc.contributor.committeememberLiu, Yongen_US
dc.description.releaseRelease after 02-May-2014en_US
thesis.degree.disciplineGraduate Collegeen_US
thesis.degree.disciplineManagementen_US
thesis.degree.namePh.D.en_US
refterms.dateFOA2014-05-02T00:00:00Z
html.description.abstractNetworks and the relationships embedded in them are critical determinants of how people communicate, form beliefs, and behave. E-commerce platforms such as Amazon and eBay have made actions of "strangers" more observable to others. More recently, social media websites such as Facebook and Google Plus have created networks of "friends", and the actions of these friends have become more visible than ever before to consumers. This dissertation develops an analytical model to examine how social learning occurs in different types of networks. Specifically, I examine the pure-strategy perfect Bayesian equilibrium of observational learning in a friend-network vs. a stranger-network. In this model, each individual makes an adopt-or-reject decision about a product after receiving a private signal regarding the underlying quality of the product and observing past actions of other individuals in the network. Grounded on the homophily theory in sociology, the degree of network heterogeneity defines the key difference between a friend-network and a stranger-network. I show a threshold effect of network size regarding which network carries more valuable information: when the network size is small, a friend-network carries more valuable information than a stranger-network does. But when the network size gets larger, a stranger-network dominates a friend-network. This suggests two competing effects of network homogeneity on social learning: individual preference effects and social conforming effects. I also test key implications from theoretical results using experiments to demonstrate internal validity and enhance insights on social learning in networks. I found that experimental results are in line with predictions from the theoretical model.


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