The Statistics in Marketing Section of the American Statistical Association is pleased to announce the winners of the 2017 Annual Doctoral Research Award. The winners are:
1. Daniel McCarthy from the University of Pennsylvania for his research titled “Customer-Based Corporate Valuation: Modeling with Limited, Aggregated, Missing Data.” There is growing interest in “customer-based corporate valuation,” that ties the value of a firm’s customers to overall valuation. In this research, the authors use a novel methodology based upon “indirect inference” to value firms by connecting common customer data summaries, which many firms disclose, with the parameters of latent variable models for customer behavior.
2. Andrey Simonov from the University of Chicago for his research titled “Demand for (Un)Biased News:
The Role of Government Control in Online News Markets.” In this research, the authors examine whether online news consumers (in Russia) prefer the political slant imposed by the government. Using a long panel of publication records data and overlapping browsing data, they measure the extent of government control in this market and estimate consumer preferences for sensitive news and ideological slant.
The award recognizes and supports outstanding statistics-based research applied to marketing problems. It includes a grant of USD 1,000.
This award is being given jointly with the Marketing Science Institute (MSI). The candidates considered for the award were those who submitted entries for the 2016-17 MSI Alden G. Clayton Dissertation Proposal Competition. MSI’s annual competition is intended to encourage doctoral work on topics of importance to the marketing community; 75 submissions from several continents were received this year. The proposals were reviewed by top academic experts.
Best,
------------------------------
Hui Lin
Data Scientist
DuPont Pioneer
------------------------------