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Using Data Mining Techniques for Information System Research Purposes – An Examplary Application in the Field of Business Intelligence and Corporate Performance Management Research

Authors:
Karin Hartl
Olaf Jacob

Keywords: Data Mining; Association Rule Discovery; Business Intelligence; Corporate Performance Management

Abstract:
Corporate Performance Management (CPM) is a management concept based on performance measures. These measures are supplied by Business Intelligence (BI), which transformed information technology in companies from data storage solutions towards decision support systems. It is believed that BI enhances CPM and that BI needs CPM for a purposeful commitment. To gain a detailed insight in the relationship between these two constructs a Data Mining approach is used. Data Mining is a data driven statistical approach for knowledge discovery. In comparison to commonly used Information System research approaches, like Structural Equation Modelling, in Data Mining no hypothesis have to be developed beforehand. Therefore, otherwise undiscovered patterns, information and hypothesis embedded in a given dataset can be discovered. As an example, Association Rule Discovery has been applied to a questionnaire based dataset investigating the relationship between BI and CPM. The results of the Data Mining approach show indeed more detailed information about the connection of BI and CPM than the usually applied research methods Exploratory Factor Analysis and Structural Equation Modelling.

Pages: 80 to 86

Copyright: Copyright (c) IARIA, 2016

Publication date: October 9, 2016

Published in: conference

ISSN: 2308-4464

ISBN: 978-1-61208-510-4

Location: Venice, Italy

Dates: from October 9, 2016 to October 13, 2016