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Business & Management - Business Information Systems | Advances in Research Methods for Information Systems Research - Data Mining, Data Envelopment

Advances in Research Methods for Information Systems Research

Data Mining, Data Envelopment Analysis, Value Focused Thinking

Osei-Bryson, Kweku-Muata, Ngwenyama, Ojelanki (Eds.)

2014, VII, 231 p. 52 illus., 30 illus. in color.

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  • Focuses on applying the non-traditional information systems research techniques of data mining, data envelopment analysis and value focused thinking
  • The methodologies covered can be used on their own or in a hybrid manner with many of the traditional research methods, with examples included in the book on how to apply hybrid approaches
  • Both editors are experienced researchers in the fields

Advances in social science research methodologies and data analytic methods are changing the way research in information systems is conducted. New developments in statistical software technologies for data mining (DM) such as regression splines or decision tree induction can be used to assist researchers in systematic post-positivist theory testing and development. Established management science techniques like data envelopment analysis (DEA), and value focused thinking (VFT) can be used in combination with traditional statistical analysis and data mining techniques to more effectively explore behavioral questions in information systems research. As adoption and use of these research methods expand, there is growing need for a resource book to assist doctoral students and advanced researchers in understanding their potential to contribute to a broad range of research problems.

Advances in Research Methods for Information Systems Research: Data Mining, Data Envelopment Analysis, Value Focused Thinking focuses on bridging and unifying these three different methodologies in order to bring them together in a unified volume for the information systems community. This book serves as a resource that provides overviews on each method, as well as applications on how they can be employed to address IS research problems. Its goal is to help researchers in their continuous efforts to set the pace for having an appropriate interplay between behavioral research and design science.

Content Level » Research

Keywords » Cluster Analysis - Data Envelopment Analysis - Data Mining - Information Systems - Multivariate Adaptive Regression Splines - Value Focused Thinking

Related subjects » Business Information Systems - Database Management & Information Retrieval - Information Systems and Applications

Table of contents 

Introduction.- Logical Foundations of Social Science Research.- Overview on Decision Tree Induction.- Using Decision Tree Induction for Theory Development.- A Hybrid Decision Tree-based Method for Exploring Cumulative Abnormal Returns.- An Ethnographic Decision Tree Modeling: An Exploration of Telecentre Usage in the Human Development Context.- Using Association Rules Mining to Facilitate Qualitative Data Analysis in Theory Building.- Overview on Multivariate Adaptive Regression Splines.- Reexamining the Impact of Information Technology Investment on Productivity Using Regression Tree and MARS.- Overview on Cluster Analysis.- Overview on Data Envelopment Analysis.- Exploring the ICT Utilization using Data Envelopment Analysis.- A DEA-centric Decision Support System for Monitoring Efficiency-Based Performance.- Overview on the Value Focused Thinking Methodology.- Using Value Focused Thinking to Develop Performance Criteria & Measures for Information Systems Projects.

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