Event History, Spatial Analysis and Count Data Methods for Empirical Research in IS

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 ti...

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Main Authors: KAUFFMAN, Robert J., Techatassanasoontorn, A. A., WANG, B.
Format: text
Language:English
Published: Institutional Knowledge at Singapore Management University 2012
Subjects:
IT
Online Access:https://ink.library.smu.edu.sg/sis_research/2193
http://dx.doi.org/10.1007/s10799-011-0106-5
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Institution: Singapore Management University
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spelling sg-smu-ink.sis_research-31932014-04-02T10:22:16Z Event History, Spatial Analysis and Count Data Methods for Empirical Research in IS KAUFFMAN, Robert J. Techatassanasoontorn, A. A. WANG, B. 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. 2012-01-01T08:00:00Z text https://ink.library.smu.edu.sg/sis_research/2193 info:doi/10.1007/s10799-011-0106-5 http://dx.doi.org/10.1007/s10799-011-0106-5 Research Collection School Of Computing and Information Systems eng Institutional Knowledge at Singapore Management University Count data E-commerce Duration analysis Empirical research Event histories Hazard models IS research Information technology IT Research methods Statistics Spatial analysis Survival analysis Technology adoption Computer Sciences Numerical Analysis and Scientific Computing
institution Singapore Management University
building SMU Libraries
continent Asia
country Singapore
Singapore
content_provider SMU Libraries
collection InK@SMU
language English
topic Count data
E-commerce
Duration analysis
Empirical research
Event histories
Hazard models
IS research
Information technology
IT
Research methods
Statistics
Spatial analysis
Survival analysis
Technology adoption
Computer Sciences
Numerical Analysis and Scientific Computing
spellingShingle Count data
E-commerce
Duration analysis
Empirical research
Event histories
Hazard models
IS research
Information technology
IT
Research methods
Statistics
Spatial analysis
Survival analysis
Technology adoption
Computer Sciences
Numerical Analysis and Scientific Computing
KAUFFMAN, Robert J.
Techatassanasoontorn, A. A.
WANG, B.
Event History, Spatial Analysis and Count Data Methods for Empirical Research in IS
description 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.
format text
author KAUFFMAN, Robert J.
Techatassanasoontorn, A. A.
WANG, B.
author_facet KAUFFMAN, Robert J.
Techatassanasoontorn, A. A.
WANG, B.
author_sort KAUFFMAN, Robert J.
title Event History, Spatial Analysis and Count Data Methods for Empirical Research in IS
title_short Event History, Spatial Analysis and Count Data Methods for Empirical Research in IS
title_full Event History, Spatial Analysis and Count Data Methods for Empirical Research in IS
title_fullStr Event History, Spatial Analysis and Count Data Methods for Empirical Research in IS
title_full_unstemmed Event History, Spatial Analysis and Count Data Methods for Empirical Research in IS
title_sort event history, spatial analysis and count data methods for empirical research in is
publisher Institutional Knowledge at Singapore Management University
publishDate 2012
url https://ink.library.smu.edu.sg/sis_research/2193
http://dx.doi.org/10.1007/s10799-011-0106-5
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