Archived Guest Speakers Fall 2014

November 25, 2014 (Tuesday)

Managing Innovation: The Role of Collateral

Yifei Mao
Indiana University


November 21, 2014 (Friday)

Visualizing Travel Attitudes: The Role of Geographic Information Systems and Big Data

Greg Rybarczyk
Assistant Professor of Earth and Resource Science
University of Michigan - Flint

Greg Rybarczyk received his PhD from University of Wisconsin-Milwaukee in 2010, and has been at the University of Michigan-Flint, Department of Earth and Resource Science, since Fall 2010. He has used geographic information systems (GIS) for the past 11 years in the private, public, and government sectors and has worked on several transportation and community related projects. His research interests mainly cover the fields of transportation geography and GIS as they relate to spatial modeling and active living. Particular interests include bicycling/walking mode choice behavior, spatio-temporal modeling, bicycle crash analysis, agent based modeling, neighborhood planning, healthy food access, GIS education, and crime analysis.

This research presents an approach to the mapping and spatial analysis of commuter sentiment obtained from disaggregated social media data. Commuting stress is known to be a root of many problems, including cardiovascular problems such as increased heart rate, increased blood pressure, back problems, as well as certain types of cancer. Examining how travel stress (or enjoyment) varies through time and space may reveal previously unknown relationships to dynamic geographic and environmental factors such as: travel mode, weather, urban density, and urban context. The present study sets out to investigate these linkages using geographic information systems and exploratory spatial modeling. This analytical framework is of interest to transportation planners seeking to understand how to promote alternative travel modes using a unique dataset.


Business Model Shocks and Abnormal Accrual

Edward Owens, Emory University

Basic economics challenge the specification of discretionary accrual models. Since rent seeking firms pursue differentiated business strategies, firms in the same industry have heterogeneous accrual generating processes. Moreover, technological innovation, regulatory changes, and entry of new firms force existing firms to revise their extant business models. We present evidence that such business model shocks are widespread, propagate through multiple years of financial statements, reduce accrual models’ goodness of fit, and result in unrealistically large unsigned “abnormal” accruals. Further, there is a spillover effect among firms in the same industry in that one firm’s abnormal accrual is affected by business model shocks experienced by the other firms in the industry. We show that business model shocks not only add noise to abnormal accruals, but can also introduce biases into both unsigned and signed discretionary accruals. Our results suggest that removing observations with business model shocks leads to better specified accrual models, and reduces both Type I and Type II errors in tests of earnings management.

Read the Paper


November 19, 2014 (Wednesday)

MGMT 305
Chip Blaser, Director
Douglas County Community Foundation


November 03, 2014 (Monday)

Karl Geiger, Manager, Program Contacts, Raytheon Company

Mr. Karl Geiger graduated from KU Business School’s Undergraduate Program in 2006 and is now a manager at Raytheon responsible for the company’s global business in several important parts of the world. He will share his global business experiences at Raytheon and take questions from the audience.


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