Modeling Internet firm survival using Bayesian dynamic models with time-varying coefficients

Authors:
Sudipto Banerjee;Robert J. Kauffman;Bin Wang
Affiliations:
Division of Biostatistics, School of Public Health, University of Minnesota, United States;Information and Decision Sciences, and MIS Research Center, Carlson School of Management, University of Minnesota, United States;Computer Information Systems and Quantitative Methods, College of Business Administration, University of Texas - Pan American, United States
Venue:
Electronic Commerce Research and Applications
Year:
2007

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Abstract

We showcase a Bayesian dynamic analysis and apply it to a study on the impact of a set of industry, firm and e-commerce-related factors on Internet firm survival. Through the use of one age-based and another calendar time-based dynamic Bayesian model, we are able to examine how the impact of these factors changes over time. Our results are based on data from 115 publicly-traded Internet firms and suggest that Internet firm survival relates to different factors, such as the initial public offerings rate of Internet stocks in the market, financial capital and firm size at different stages in their lifetimes, whose influence may have changed over time.