Neighborhood Social Capital and Social Learning for Experience Attributes of Products

Loading...
Thumbnail Image
Penn collection
Marketing Papers
Degree type
Discipline
Subject
Bayesian learning
experience attributes
Poisson model
social capital
social learning
Advertising and Promotion Management
Behavioral Economics
Business
Cognitive Psychology
Marketing
Social Psychology
Funder
Grant number
License
Copyright date
Distributor
Related resources
Author
Lee, Jae Young
Bell, David R
Contributor
Abstract

Social learning can occur when information is transferred from existing customers to potential customers. It is especially important when the information that is conveyed pertains to experience attributes, i.e., attributes of products that cannot be fully verified prior to the first purchase. Experience attributes are prevalent and salient when consumers shop through catalogs, on home shopping networks, and over the Internet. Firms therefore employ creative and sometimes costly methods to help consumers resolve uncertainty; we argue that uncertainty can be partially resolved through social learning processes that occur naturally and emanate from local neighborhood characteristics. Using data from Bonobos, a leading U.S. online fashion retailer, we find not only that local social learning facilitates customer trial but also that the effect is economically important because about half of all trials were partially attributable to it. Merging data from the Social Capital Community Benchmark Survey, we find that neighborhood social capital, i.e., the propensity for neighbors to trust each other and communicate with each other, enhances the social learning process and makes it more efficient. Social capital does not operate on trials directly; rather, it improves the learning process and therefore indirectly drives sales when what is communicated is favorable.

Advisor
Date Range for Data Collection (Start Date)
Date Range for Data Collection (End Date)
Digital Object Identifier
Series name and number
Publication date
2013-01-01
Volume number
Issue number
Publisher
Publisher DOI
Journal Issue
Comments
Recommended citation
Collection