Abstract

As interest in online coupons from distributors like Groupon and Living Social have grown, eBay has proposed and built a marketplace. This marketplace is called eBay Local. It is a place where local merchants can post coupons that distributors can bid on the right to publish. Based on some initial data, we have built a model to t and predict the growth of this marketplace. The influence of salesmen and organic growth convert potential merchants into active members of the marketplace posting their goods and services. We have modeled the recruitment and retention of businesses within the marketplace, based on interactions with businesses and monetary incentives. Our model has a structure similar to epidemiological models. Parameters are estimated based on initial data sets provided by eBay and numerical results are obtained using a fourth-order Runge-Kutta method coded in MATLAB specifically for this thesis. By adjusting the model and the parameters within reasonable values, the system displayed an accurate representation of the marketplace. Using the model we have found realistic conditions under which the system is optimized, creating a stable population of active businesses inexpensively.

Publication Date

8-2013

Document Type

Thesis

Student Type

Graduate

Degree Name

Applied and Computational Mathematics (MS)

Department, Program, or Center

School of Mathematical Sciences (COS)

Advisor

David S. Ross

Advisor/Committee Member

Darren A. Narayan

Advisor/Committee Member

Matthew J. Ho man

Campus

RIT – Main Campus

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