Event history, spatial analysis and count data methods for empirical research in information systems

A large number of interesting business and technology problems in IS and e‐commerce research center around events and the associated variables that influence them. Researchers are often interested in studying the timing, patterns, and frequencies of events. Some of those events are related to the timing of strategic decisions such as new technology adoption, functionality upgrades to established software products, new outsourcing contracts, and the termination of failing IS projects. Still others are external events that have significant implications on the performance of firms, the structure of industries affected by IT, and the viability of various aspects of the economy. Event history methods, also known as survival analysis and duration analysis methods, spatial analysis, and count data analysis in the medical sciences, public health and biostatistics literature, offer rigorous methods for empirical analysis that can provide rich insights into research issues that arise in association with identifiable events. This article provides a current survey of these methods and in‐depth discussion of how researchers can apply them to study technology adoption problems and related issues in IS and e‐commerce. We offer a framework for mapping the methods to applicable problems, and discuss the relevant variants of the methods. We also illustrate the range of research questions that can be asked and answered through the use of the methods.