1 INTRODUCTION.- 1.1 BACKGROUND.- 1.2 AIM AND OBJECTIVES OF THE RESEARCH.- 1.3 THESIS STRUCTURE.- 2 LITERATURE REVIEW.- 2.1 OVERVIEW.- 2.2 BUSINESS PROCESS MODELS.- 2.3 BUSINESS PROCESS UNDERSTANDING.- 2.4 BUSINESS RULES.- 2.5 BUSINESS PROCESS MODEL AND BUSINESS RULE INTEGRATION.- 2.6 INTEGRATION APPROACHES.- 2.7 CHAPTER SUMMARY.- 3 METHODOLOGY.- 3.1 RESEARCH METHOD OF STUDY 1 – EXPERIMENT.- 3.2 RESEARCH METHOD OF STUDY 2 – SYSTEMATIC LITERATURE REVIEW AND SURVEY.- 3.3 RESEARCH METHOD OF STUDY 3 – DESIGN SCIENCE.- 3.4 CHAPTER SUMMARY.- 4 RULE INTEGRATION AND MODEL UNDERSTANDING: A THEORETICAL UNDERPINNING.- 4.1 OVERVIEW.- 4.2 RELATED THEORIES.- 4.3 PROCESS MODELS AND RULES UNDERSTANDING.- 4.4 CHAPTER SUMMARY.- 5 THE EFFECT OF RULE LINKING ON BUSINESS PROCESS MODEL UNDERSTANDING.- 5.1 OVERVIEW.- 5.2 HYPOTHESES DEVELOPMENT.- 5.3 APPROACH.- 5.4 RESULT ANALYSIS.- 5.5 CHAPTER SUMMARY.- 6 IDENTIFICATION OF FACTORS AFFECTING BUSINESS PROCESS AND BUSINESS RULE INTEGRATION.- 6.1 OVERVIEW.- 6.2 APPROACH.- 6.3 BUSINESS RULE MODELLING FACTORS.- 6.4 EMPIRICAL VALIDATION OF FACTORS.- 6.5 BUSINESS RULE EMBEDDING GUIDELINES.- 6.6 CHAPTER SUMMARY.- 7 A BUSINESS RULE MODELLING DECISION FRAMEWORK.- 7.1 OVERVIEW.- 7.2 PROBLEM IDENTIFICATION AND DEFINITION OF OBJECTIVES.- 7.3 THE DESIGN AND DEVELOPMENT OF THE DECISION FRAMEWORK.- 7.4 THE DECISION FRAMEWORK DEMONSTRATION.- 7.5 THE DECISION FRAMEWORK EVALUATION.- 7.6 CHAPTER SUMMARY.- 8 CONCLUSION.- 8.1 OVERVIEW.- 8.2 SUMMARY OF CONTRIBUTIONS.- 8.3 RESEARCH LIMITATIONS AND FUTURE WORK.- REFERENCES.- APPENDIX A ONLINE SURVEY.- APPENDIX B EXPERIMENT MATERIALS.
This book combines multiple research methods, experiment, survey, and design science, as well as traditional measurements and neurophysiological techniques that can capture a variety of cognitive behaviors in human information processing, providing more solid and comprehended research findings. While the focus of the book is the modelling of process models and rules, the methods and techniques used in this book can also be adopted and applied to broader conceptual modelling research incorporating a variety of notations (e.g. UML, ER diagrams) or ontologies.
It is a revised version of the PhD dissertation written by the author at the School of Information Technology and Electrical Engineering of the University of Queensland, Australia. In 2018, the PhD dissertation won the “CAiSE PhD Award,” granted to outstanding PhD theses in the field of information systems engineering.