Gorkem Turgut (G.T.) OZER​, MBA, MSc, PhD

Advisor, Assistant Professor of Business Analytics and Strategy
at the Robert H. Smith School of Business, University of Maryland

For most up to date information, please see linkedin.com/in/gtozer and rhsmith.umd.edu/directory/gorkem-turgut-ozer

Courses I have taught:
  • Data Mining and Predictive Analytics (Graduate -MSIS, MSBA): predict.gto.run
  • Data Mining and Predictive Analytics (Graduate -MBA version): data.gto.run
  • Big Data and Artificial Intelligence (Graduate -MBA, OMSBA): bigdata.gto.run
  • Managing Information Systems: Strategy, Software, and Data: 301.gto.run
Research projects I have worked on:
Strategy and societal/governance problems in and around digital platforms
  • Noisebnb: An empirical analysis of home sharing platforms (e.g., Airbnb, Vrbo/HomeAway) and noise complaints: Implications for policy and governance (with Anand Gopal and Brad Greenwood), Under review
  • Diff-in-diff and Bayesian analysis of 15 years of data on noise complaints following Airbnb’s entry into New York City.
  • Covid and chill: An empirical analysis of digital entertainment consumption (e.g., Spotify) (along with the use of cannabis in the states where it is legal) during the COVID-19 pandemic, Work in progress -Early stage
  • Analysis of Spotify streams (and potential complementarity/substitution with the use of cannabis) during COVID-19.
  • Digital multisided platforms and women's health: An empirical analysis of peer-to-peer lending platforms (e.g., LendingClub, Prosper) and abortion rates (with Brad Greenwood and Anand Gopal), Under review
  • Poisson QML diff-in-diff analysis on data from Lending Club, CDC, State Health Departments, and the U.S. Census.
  • Does social comparison tendency make the users social media platforms less altruistic? An experimental analysis of behavioral biases caused by “Instagram perfect” (with Gordon Gao and Yifei Wang), Work in progress
  • Experimental analysis of donations by supplementing an Amazon Turk study with a convolutional neural network.
  • On examining the performance implications of diversified vs. specialized variety on platforms for creative products in retail: An institutional logics perspective (with Sirkka Jarvenpaa and Anand Gopal), Under review
  • Clustering and panel analysis of 260K products on Ravelry, a marketplace like Etsy, for designers of clothing items.
  • Competitive (dis)advantage through learning in multisided platforms: Strategic implications of opening access to different platform sides (with Edward Anderson, Patrick Figge, and Jeffrey Martin), Under review
  • Agent-based computer simulation of platform strategies that leverage learning from competitors.
  • On Hold: Better going alone or with some company? An empirical analysis and comparison of rental revenues in Airbnb and HomeAway for individual and professionally-managed listings, Work in progress
  • Empirical analysis of 1.5 million vacation rentals in Los Angeles, CA to compare revenue models.
Digital transformation through big data and intelligent agents
  • Data centricity: Strategy that incorporates big data and artificial intelligence in its guiding policy and actions
  • Data strategy framework on value creation and capture through leveraging large datasets and emerging algorithms.
  • Resilience of sharing economy platforms to COVID-19: How do platform owners support third party complementors while navigating through the crisis? (with Sirkka Jarvenpaa), Work in progress
  • Text analysis of the announcements made by digital sharing economy platforms before and after COVID-19 hit.
  • When algorithms check on other algorithms: Anomaly detection in the age of “big data” (with Courtney Paulson), Work in progress -Early stage
  • Review of selected anomaly detection algorithms, performance tests, and the development of a typology.
  • On Hold: Use of deep learning algorithms for the detection and diagnosis of pulmonary nodules: A large-scale experimental analysis (with Kunpeng Zhang and Tony Lin, M.D.), Work in progress
  • Comparing the effectiveness of pulmonary nodule detection between a neural network, physician, their collaboration.
  • On Hold: Spillover effects of selected neighborhood incidents on the revenues and Yelp ratings of restaurants: A large-scale empirical analysis, Work in progress -Early stage
  • Creating a metric using 40 million records from 16 U.S. cities for the impact of incidents such as graffiti reports.
Other published work
  • Combining stock‐and‐flow, agent‐based, and social network methods to model team performance (with Edward Anderson and Kyle Lewis), Published in System Dynamics Review with doi.org/10.1002/sdr.1613
  • Comparing stock‐and‐flow models, agent‐based models, and social network analysis to argue for the advantages of a hybrid approach to the modeling of team science.
  • Behavioral biases in consumer decision making: Findings from a survey on financial behavior (with Adil Oran and Ozlem Yilmaz), Published in DEU Economics and Administrative Sciences Journal with ISSN:1303-0027
  • Survey and statistical analysis of the implications of behavioral biases for personal finance decisions.
Copyright © 2020 G.T. OZER. Some rights reserved.