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Category Archives: M

Geo-Spatial Modeling of Online Ad Distributions

By Mitchel Drake Gorecki

The purpose of this document is to demonstrate how spatial models can be integrated into purchasing decisions for real-time bidding on advertising exchanges to improve ad selection and performance. Historical data makes it very apparent that some neighborhoods are much more interested in some ads than others. Similarly, some neighborhoods are also much more interested in some online domains than others, meaning viewing habits across domains are not equal. Basic data analysis shows that neighborhoods behave in predictable ways that can be exploited using observed performance information. This paper demonstrates how it is possible to use spatially correlated information to better optimize advertising resources.

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Advisor: Charles Becker | JEL Codes: C3, C33, C53, M37 | Tagged: Ad Distribution, Advertising, Online, Real Time Bidding, Spatial

The Effects of Digital Media on Advertising Markets

By Bradford Lightcap and William Anthony Peek

This paper examines the viability of sustained advertising spending in an increasingly digital age. Beginning with print media and through the advent of television, the ad market has seen vast evolution in information consumption. The result has been a creative adaptability by advertisers to keep pace with said change. However, growth in ad spending has not significantly outpaced GDP growth, as documented in the Relative Constancy Hypothesis. RCH asserts that both ad spending and consumer expenditure as a percent of GDP remain steady over time. This paper focuses on whether the advertising claim holds up through the rise of the Internet. How this powerful medium may alter traditional advertising trends remains unclear. The answer could have implications for both advertisers and parties that rely on them

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Advisor: Connel Fullenkamp | JEL Codes: L82, M3, M37, O39 | Tagged: Digital Media, Relative Constancy Hypothesis

The Influence Effect of Critics’ Reviews on Foreign and Domestic Movies

By Jayoung Jeon and Luxuan Jiao

Critics and their reviews provide crucial information for consumers in many “experience goods” markets, and the movie market is one such market. Through their impact on the consumer’s film selection, critics’ reviews influence the first weekend box office performance (the influence effect). We hypothesize that the influence effect of critics’ reviews is different for foreign and domestic movies. Using the U.S. film industry as our empirical setting, we examine the effects of reviews on opening weekend revenues in the U.S. film industry. We find that, when the critics’ assessment of domestic movies is positive, people are discouraged from watching the movie. On the other hand, for foreign movies, the impact of positive reviews is found to be positive. We interpret this result as arising from the different target audiences for foreign and domestic movies. Further analysis of our data supports this hypothesis. We also find that people are more influenced to watch movies when they see multiple reviews than only a few of them. This positive impact of the number of critics’ reviews is greater for domestic than foreign movies, and greater for domestic art movies than domestic non-art movies.

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Advisor: James Roberts | JEL Codes: L82, M37 | Tagged: Art, Critics, Films, Foreign, Movies, Reviews

The Comprehensive Optimal Business Location Model

By Mitchel Gorecki

In order to ensure long run viability, a firm must understand the idea of optimal business location. In the designing of a strategy, it is important to not only evaluate the present market environment but to also account for possible future change. This paper will demonstrate the core ideas behind a comprehensive location model that will predict the optimal location for a business. The effectiveness of the model will be evaluated by using past data from Durham, North Carolina to predict current retail development. The model is determined to be successful by seeing if the trend recognized would be able to correctly identify the present location choices of firms. The model will be further used to predict the future development plans for businesses locating in the Durham area.

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Advisor: Charles Becker  |  JEL Codes: E3, M1, M2,

Measuring the Likelihood of Small Business Loan Default: Community Development Financial Institutions (CDFIs) and the use of Credit-Scoring to Minimize Default Risk1

By Andrea Coravos

Community development financial institutions (CDFIs) provide financial services to underserved markets and populations. Using small business loan portfolio data from a national CDFI, this paper identifies the specific borrower, lender, and loan characteristics and changes in economic conditions that increase the likelihood of default. These results lay the foundation for an in-house credit-scoring model, which could decrease the CDFI’s underwriting costs while maintaining their social mission. Credit-scoring models help CDFIs quantify their risk, which often allows them to extend more credit in the small business community.*

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Advisor: Charles Becker  |  JEL Codes:  K22, M1,

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