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Main Data
Author: Stefanie Leimeister
Title: IT Outsourcing Governance Client Types and Their Management Strategies
Publisher: Gabler Verlag
ISBN/ISSN: 9783834963031
Edition: 1
Price: CHF 86.20
Publication date: 01/01/2010
Content
Category: Informatik, EDV Buch
Language: English
Technical Data
Pages: 368
Kopierschutz: DRM
Geräte: PC/MAC/eReader/Tablet
Formate: PDF
Table of contents
Stefanie Leimeister examines different types of IT outsourcing relationships and their characteristics depending on the outsourcing clients' underlying expectations. The author derives actionable advice for applicable strategies and an effective allocation of resources for an outsourcing venture.



Dr. Stefanie Leimeister completed her doctoral thesis under the supervision of Prof. Dr. Helmut Krcmar at the Chair of Information Systems at Technische Universität München (TUM) and currently works as a research division manager at fortiss - the TUM research institute for software intensive systems.
Table of contents
Foreword6
Acknowledgements7
Abstract8
Table of Contents10
List of Figures15
List of Tables19
List of Abbreviations22
1 Introduction24
1.1 Problem Statement and Motivation for this Research24
1.2 Research Objective and Research Questions26
1.3 Outline and Structure of the Thesis29
2 Epistemological Foundation and Research Methodology31
2.1 Philosophical Perspectives and Research Epistemology31
2.1.1 Positivist Research31
2.1.2 Interpretive Research33
2.1.3 Critical Research33
2.2 Research Design and Methods: Quantitative vs. Qualitative Research33
2.3 Summary of Epistemological Foundations of this Thesis35
3 Theoretical Background on Outsourcing36
3.1 Definition and Background of Information Systems Outsourcing36
3.1.1 Specific Characteristics of Information Systems Outsourcing37
3.1.2 IS Outsourcing Definitions39
3.2 Theoretical Foundation: Related Theories42
3.2.1 Transaction Cost Economics43
3.2.2 Exchange Theories: Social Exchange and Relational Exchange Theory45
3.2.2.1 Social Exchange Theory45
3.2.2.2 Relational Exchange Theory46
3.2.3 Psychological Contract Theory47
3.2.4 Expectation Confirmation Theory48
3.2.5 Theories of Power: Power-Political, Power Dependence, Power Conflict49
3.2.6 Summary of Theories for IS Outsourcing Relationships51
3.3 The Multi-Dimensionality of Outsourcing IS Functions52
3.3.1 Outsourcing Functions and the IT Service Lifecycle52
3.3.2 Forms of Outsourcing Arrangements54
3.4 Outsourcing Determinants and Expectations: Advantages and Disadvantages60
3.5 Prior Research on IS Outsourcing Relationships: State of the Art66
3.5.1 Evolution of IS Outsourcing Research towards a Relationship Focus66
3.5.2 The Relationship Perspective in IS Outsourcing67
3.5.3 Approaches for Classifying IS Outsourcing Relationships69
3.6 Constitutive Factors of an IS Outsourcing Relationship70
3.6.1 Strategic Intent and Contextual Factors70
3.6.2 Relationship Architecture71
3.6.3 Governance and Monitoring Mechanisms72
3.6.3.1 Formal Contractual Governance75
3.6.3.2 Informal Relational Governance76
3.6.3.3 The Interplay of Formal Contractual and Informal Relational Governance77
3.6.3.4 Governance via Management Processes78
3.6.3.5 Governance via Organizational Structures79
3.6.3.6 Governance via Experience and Risk-Reward Incentive Mechanisms80
3.6.4 Relational and Behavioral Interactions of the Outsourcing Parties82
3.6.5 Success of IS Outsourcing87
3.7 Shortcomings of the Current Research / Research Gap on Outsourcing Relationships and their Governance91
3.8 Framework for Classifying Outsourcing Relationships92
3.8.1 Methodological Approach to the Conceptualization of a Framework on Outsourcing Relationships93
3.8.2 Categories of the Framework94
3.8.3 Completeness vs. Parsimony of the Building Blocks94
3.8.4 Interdependencies among the Variables95
3.8.5 Conceptual Framework for Types in IS Outsourcing Relationships96
3.9 Summary of Outsourcing Foundations100
4 Theoretical and Methodological Foundations for Classifying Data102
4.1 Theoretical Foundations of Classification and Configuration102
4.1.1 Definition of Classification Terms: Classification, Configuration, Type102
4.1.2 Characteristics of Configurations or Types103
4.1.3 Typologies vs. Taxonomies104
4.2 Grouping Techniques107
4.2.1 Cluster Analysis107
4.2.1.1 Definition of Cluster Analysis107
4.2.1.2 General Procedure of Cluster Analysis108
4.2.1.3 Different Clustering Techniques and Algorithms109
4.2.1.4 Clustering Steps111
4.2.1.5 Strengths and Pitfalls of Cluster Analysis119
4.2.2 Discriminant Analysis120
4.2.3 Factor Analysis122
4.2.3.1 General Considerations and Distinctions in Factor Analysis: Exploratory vs. Confirmatory, R vs. Q Analysis122
4.2.3.2 Design and Process of a Factor Analysis123
4.3 Summary of the Methodological Foundations for Classifying Outsourcing Clients129
5 Empirical Evidence of Outsourcing Relationship Types131
5.1 Qualitative Pre-Study: First Evidence of Different IS Outsourcing Relationships133
5.1.1 Data Collection133
5.1.2 Results136
5.1.2.1 Strategic Intent, Expectations, and Context137
5.1.2.2 Relationship Architecture137
5.1.2.3 Governance and Monitoring137
5.1.2.4 Interaction138
5.1.3 Types of IS Outsourcing Relationships138
5.2 Research Design of the Quantitative Study142
5.3 Data Collection and Demographic Results144
5.4 Statistical Results: Data Analysis146
5.4.1 Diagnostic Pre-Analysis of Results: Missing Values and Distribution of Data146
5.4.1.1 Diagnostics: Analyzing the Extent and Impact of Missing Values147
5.4.1.2 Normal Distribution of the Data151
5.4.2 Factor Analysis: Customer Expectations towards IS Outsourcing152
5.4.2.1 Initial Factor Analysis with All Outsourcing Motives153
5.4.2.2 Final Improved Factor Solution155
5.4.2.3 Reliability Analysis of the Final Factor Solution160
5.4.2.4 Interpretation of Factors161
5.4.3 Cluster Analysis: Finding Configurations of Clients with Similar Outsourcing Expectations162
5.4.3.1 Selecting and Preparing the Input Variables for the Cluster Analysis163
5.4.3.2 Identifying Outliers in the Data Set163
5.4.3.3 Identifying the Number of Clusters and the Cluster Centroids164
5.4.3.4 Optimizing the Cluster Solution with k-Means166
5.4.3.5 Estimating and Validating the Cluster Solution with Discriminant Analysis167
5.5 Interpretation of Statistical Analysis: Configurations of Different Outsourcing Client Groups