E-Book, Englisch, 348 Seiten, eBook
E-Book, Englisch, 348 Seiten, eBook
Reihe: Ausgezeichnete Arbeiten zur Informationsqualität
ISBN: 978-3-8348-9634-6
Verlag: Vieweg & Teubner
Format: PDF
Kopierschutz: 1 - PDF Watermark
Dr. Saša Baškarada completed his doctoral thesis at the Strategic Information Management Laboratory at the University of South Australia.
Zielgruppe
Research
Autoren/Hrsg.
Weitere Infos & Material
1;Foreword;7
2;Preface;8
3;Contents;10
4;List of Figures;14
5;List of Tables;16
6;1 Introduction;18
6.1;1.1 Background to the Research;18
6.2;1.2 Research Problem and Research Questions;20
6.3;1.3 Justification for the Research;22
6.4;1.4 Aim of this Research;25
6.5;1.5 The Scope and Key Assumptions;25
6.6;1.6 Methodology;26
6.7;1.7 Findings;27
6.8;1.8 Outline of the Book;28
6.9;1.9 Conclusion;29
7;2 Literature Review;30
7.1;2.1 Introduction;30
7.2;2.2 Total Quality Management;31
7.2.1;2.2.1 Gurus;33
7.2.2;2.2.2 Critical Success Factors for TQM;40
7.2.3;2.2.3 Six Sigma;43
7.2.4;2.2.4 Summary;44
7.3;2.3 Quality Awards and Frameworks;44
7.3.1;2.3.1 The Deming Prize;45
7.3.2;2.3.2 Japan Quality Award;47
7.3.3;2.3.3 Singapore Quality Award;48
7.3.4;2.3.4 Malcolm Baldrige National Quality Award;49
7.3.5;2.3.5 Canadian Framework for Business Excellence;52
7.3.6;2.3.6 Australian Business Excellence Framework;53
7.3.7;2.3.7 European Foundation for Quality Management Excellence Model;55
7.3.8;2.3.8 Summary;55
7.4;2.4 Quality Standards and Best Practices;57
7.4.1;2.4.1 ISO 9000;57
7.4.2;2.4.2 ISO/IEC 15504;59
7.4.3;2.4.3 Capability Maturity Model;60
7.4.4;2.4.4 Capability Maturity Model Integration;62
7.4.5;2.4.5 Control Objectives for Information and Related Technology;63
7.4.6;2.4.6 Information Technology Infrastructure Library;68
7.4.7;2.4.7 ANSI/GEIA 859;70
7.4.8;2.4.8 The Level of Adoption;72
7.4.9;2.4.9 Summary;73
7.5;2.5 Data and Information Quality;73
7.5.1;2.5.1 From Data to Information;74
7.5.2;2.5.2 Definitions;75
7.5.3;2.5.3 Implications;78
7.5.4;2.5.4 Causes;80
7.5.5;2.5.5 The Product Analogy;81
7.5.6;2.5.6 Assessments;83
7.5.7;2.5.7 Management;85
7.5.8;2.5.8 Maturity Models;91
7.5.9;2.5.9 Summary;96
7.6;2.6 Engineering Asset Management;98
7.7;2.7 Conclusion;103
8;3 Research Methodology;104
8.1;3.1 Introduction;104
8.2;3.2 Philosophy of Science;105
8.2.1;3.2.1 Defining Science;105
8.2.2;3.2.2 Theories;106
8.2.3;3.2.3 Causality;107
8.2.4;3.2.4 Rationalism vs. Empiricism;108
8.2.5;3.2.5 Inductivism;111
8.2.6;3.2.6 Popper’s Falsificationism;112
8.2.7;3.2.7 Conventionalism;115
8.2.8;3.2.8 Scientific Research Programmes;115
8.2.9;3.2.9 Scientific Paradigms;116
8.3;3.3 Justification for the Qualitative Interpretive Research Approach;124
8.4;3.4 Research Design;126
8.4.1;3.4.1 Stage 1: Exploratory Phase;126
8.4.2;3.4.2 Stage 2: Theory Building Phase;132
8.4.3;3.4.3 Stage 3: Theory Testing and Enhancing Phase;139
8.5;3.5 Data Collection;141
8.5.1;3.5.1 Theoretical Sampling;141
8.5.2;3.5.2 Interviewing;141
8.6;3.6 Data Analysis;143
8.6.1;3.6.1 Constant Comparative Analysis;144
8.6.2;3.6.2 Hermeneutics;145
8.6.3;3.6.3 Pattern Matching;146
8.6.4;3.6.4 Explanation Building;146
8.6.5;3.6.5 Within-Case Analysis;147
8.6.6;3.6.6 Cross-Case Analysis;147
8.7;3.7 Criteria for Judging the Quality of Qualitative Interpretive Research;148
8.7.1;3.7.1 Construct Validity;150
8.7.2;3.7.2 Internal Validity;151
8.7.3;3.7.3 External Validity;151
8.7.4;3.7.4 Reliability;152
8.8;3.8 Ethical Considerations;153
8.9;3.9 Limitations;153
8.10;3.10 Conclusion;154
9;4 Analysis of Data;155
9.1;4.1 Introduction;155
9.2;4.2 Exploratory Stage;155
9.2.1;4.2.1 Profiles of the Exploratory Case Study Organisations;156
9.2.2;4.2.2 Candidate Maturity Indicators;157
9.3;4.3 Theory Building Stage;159
9.3.1;4.3.1 Constructing the Staged Capability Maturity Model;160
9.3.2;4.3.2 Constructing the IQM-CMM Diagnostic Tool;169
9.4;4.4 Theory Testing and Enhancing Stage;172
9.4.1;4.4.1 Assessment Method;173
9.4.2;4.4.2 Profiles of the Explanatory Case Study Organisations;178
9.4.3;4.4.3 Maturity Ratings of the Explanatory Case Study Organisations;179
9.4.4;4.4.4 Cross-Case Analysis;188
9.4.5;4.4.5 Theory Enhancements;235
9.4.6;4.4.6 Discussion;236
9.5;4.6 Conclusions;237
10;5 Conclusions;238
10.1;5.1 Introduction;238
10.2;5.2 Conclusions about the Research Questions and Hypotheses;239
10.3;5.3 Implications for Theory;246
10.4;5.4 Implications for Practice;247
10.5;5.5 Limitations;248
10.6;5.6 Future Research;249
10.7;5.7 Conclusion;250
11;References;251
12;Appendix;300
12.1;Glossary;300
12.2;Definitions;302
12.3;CobiT 4.0 Control Objectives Applicable to IQM;304
12.4;Definitions of IQ Dimensions;306
12.5;Candidate Maturity Indicators;310
12.6;Delphi Study Results;318
12.7;IQM-CMM Diagnostic Tool;320
Literature Review.- Research Methodology.- Analysis of Data.- Conclusions.
1 Introduction (p. 1)
"The beginning is the most important part of the work." —Plato, The Republic
This chapter lays out the foundation for the rest of the book by presenting a brief overview of the research background, the research problem, the research questions, the justifications for the research, and the aims of the research. The research methodology is briefly explained and delimitations of scope and key assumptions are discussed.
The chapter finally summarises the research findings and outlines the rest of the book. 1.1 Background to the Research Information and Communication Technologies (ICTs) have been evolving at a very fast rate in the relatively recent times. Such a rapid progress has made the production, collection, and storage of information very easy and inexpensive.
As a result, contemporary organisations are dealing with more information than ever before in history (Lyman & Varian 2003, McCue 2006, Nunno & Meehan 2007, Bell, Logan & Friedman 2008). However, these technological advances have among others led to a decrease in the quality of the available information. Information accuracy, completeness, timeliness, relevancy, and so on, have proven to be notoriously difficult to assess and manage.
Furthermore, even though quality assurance methodologies have played a crucial part in the software engineering and manufacturing industries for decades (Paulk et al. 1993, Mahoney & Thor 1994, CMMI 2002, ISO 2005b), Information Quality Management (IQM) is only practiced in a minority of contemporary organisations (TDWI 2006).
This is despite the fact that many such organisations clearly depend on quality information for every-day business operations, and even their very survival in today’s competitive business environments (Redman 1998). Quality management has been an integral component of software engineering and manufacturing industries for decades (Paulk et al. 1993, Mahoney & Thor 1994, CMMI 2002, ISO 2005b), and it has been described as being fundamental to organisational success and growth (Feigenbaum 1986, Zeithaml, Parasuraman & Berry 1990).
The Total Quality Management (TQM) movement started with the development of the statistical control charts by Walter Shewhart in 1925 (Shewhart 1925). Since then, many researchers, whom we now call “quality gurus”, including, Juran (1974), Crosby (1979), Deming (1982), and Ishikawa (1986) have contributed a great deal to quality management theories.
The Total Data Quality Management (TDQM) program at MIT has been instrumental in the adaptation of TQM theories to the field of information quality management (Wang & Strong 1996, Strong, Lee & Wang 1997b, Wang 1998) by drawing an analogy between the manufacture of tangible products and Information Products (IPs).
Crosby (1979) was the first to propose the idea of quality management maturity. His ideas have since been adopted by IBM (Radice et al. 1985) and SEI (Paulk et al. 1993, CMMI 2002) to software engineering, and by several other researchers (Chambless & Parker 1998, English 1999, Caballero, Gómez & Piattini 2004, Ryu, Park & Park 2006, Aiken et al. 2007) to information management and information quality management. This research further adapts Crosby’s ideas to the development of an Information Quality Management Capability Maturity Model – IQM-CMM.
IQM-CMM is developed inductively, as opposed to some deductively proposed models found in the literature, and, as such, it is grounded in empirical data gathered from a wide range of information quality experts and practitioners. As a result, the model does not represent a limited view of one researcher, but it aggregates a variety of different views.
1.2 Research Problem and Research Questions
It has been argued that to ask the right question is to be well on the way to finding the right answer (Brown et al. 1997), and that the formulation of a research problem is the first and most important step of the research process (Kumar 1999).
