Using Secondary Notation to Influence the Model User's Attention

Recently cognitive principles have been discussed for Conceptual Modeling with the aim to increase domain understanding, model comprehension and modeling efficiency. In particular, the principle of Perceptual Discriminability, which discusses the visual differences of modeling constructs, reveals potential for model comprehension if human attention is influenced in a way that important modeling constructs are more easily detected, and can hence faster be processed. Yet, so far no conditions how the human gaze can be influenced have been defined and evaluated for Conceptual Modeling. This dissertation extends Perceptual Discriminability for conditions to attract human attention for those constructs that are important for model comprehension. Furthermore, these conditions are applied to constructs of two different modeling grammars in general as well as to elements of the process flow of Business Process Models. To evaluate the results a laboratory experiment of extended Perceptual Discriminability is described in which significant differences have been identified for process flow comprehension. For the demonstration of the potential of extended Perceptual Discriminability BPMN secondary notation is improved by emphasizing those constructs that are most important for model comprehension. Therefore, those constructs that are important for model comprehension have been identified within a content analysis and have been worked on according to the conditions of extended Perceptual Discriminability for those visual variables that are free for an application in secondary notation.:Preface ii Abstract iii Table of contents iv Table of Figures v List of Tables vi List of Abbreviations vii Part 1 - Summary Paper 1 1. Motivation 2 2. Research design 7 2.1 Research objectives 7 2.2 Scope 9 2.3 Research method 11 3. Structure of the dissertation 13 4. Contribution to theory and practice 17 5. Future Research Ideas 19 Part 2 - Publications 20 Publication 1 21 Publication 2 22 Publication 3 23 Publication 4 24 Publication 5 25 Publication 6 26 Literature 27 Part 3 - Appendix 3

Systemizing Colour for Conceptual Modeling

Colour is used in many conceptual models and is discussed intensively since MOODY has published his ‘Physics of Notation’. Yet, choosing the right colour for a construct is difficult but crucial. Using a colour for a certain construct which is not appropriate can lead to visual stress as well as too much or too little emphasis on that construct. The aim of this paper is to give a systematization of colour for conceptual modeling by reviewing theories of colour vision, colour harmony and visual attention. Based on this review we provide colour combinations for different conceptual modeling colour scenarios

USING SECONDARY NOTATION TO IMPROVE THE COGNITIVE EFFECTIVENESS OF BPMN-MODELS

Almost every implementation of a modeling grammar uses secondary notation to further specify a modeling grammar. Yet, secondary notation is usually applied in an unsystematic way, might contradict what is specified in primary notation and implements research results that should rather be implemented in primary notation. With this work we aim at showing how secondary notation can be used to implement recent research results that are not yet available in primary notation without contracting what is already specified in primary notation. We demonstrate a systematic update of recent research of extended Perceptual Discriminability for BPMN secondary notation and that way, show how research results can quickly be made available for practice without contradicting primary notation. We choose Perceptual Discriminability as it can be used to focus the model user’s attention on the most important constructs and can that way, improve model comprehension. For an update of BPMN secondary notation we first specify free BPMN variables and further show how these variables can be used to focus the model user’s attention on those constructs that most foster comprehension

A Survey-based Analysis of Principles to Evaluate Visual Notations of Process Modeling Languages

Process modeling languages such as BPMN or EPC provide a set of graphical constructs defining their visual notations. The visual notation is one comparison criteria in favor of a process modeling language. Usually, the first choice for the evaluation of visual notations are the principles of the Physics of Notation (PoN) theory. Their vague operationalization, however, gives room for contradictory recommendations how to improve visual notations. Therefore, the intention of this paper is to identify recent empirical studies to visual notations of process modeling languages, which might contribute to a better understanding of PoN principles. A comprehensive literature survey has been conducted showing a confirmation of the PoN principles and identifying refinements for their operationalization. We applied our findings to an evaluation of the visual notation of BPMN from 2012 and showed advancements. Our findings define the current guidelines for evaluating and improving visual notations of process modeling languages

How Novices and Experts Understand Hierarchies in Business Process Modeling

Conceptual models are essential for successful IT implementation, as they concisely represent the system\u27s component structures, behavior, and relationships. However, for conceptual models to fully realize their potential, they must be understood. To this end, hierarchy has been employed in business process modeling to enhance understanding of complex models. Prior research has proposed a two-component framework to explain the effects of hierarchy on understanding. Drawing on empirical data, this work extends this framework by investigating the influence of expertise on the understanding of hierarchical business process models. Our findings indicate that experts and novices benefit from hiding task-irrelevant information in subprocesses, with experts benefiting significantly more than novices. Additionally, experts profit more from recognizing familiar patterns in subprocesses than novices. Based on our results, we propose two principles for designing hierarchy and suggest future research avenues. Keywords: Business Process Modeling, Hierarchy, Expertise, Information Hiding

Design of Data-Driven Decision Support Systems for Business Process Standardization

Increasingly dynamic environments require organizations to engage in business process standardization (BPS) in response to environmental change. However, BPS depends on numerous contingency factors from different layers of the organization, such as strategy, business models (BMs), business processes (BPs) and application systems that need to be well-understood (“comprehended”) and taken into account by decision-makers for selecting appropriate standard BP designs that fit the organization. Besides, common approaches to BPS are non-data-driven and frequently do not exploit increasingly avail-able data in organizations. Therefore, this thesis addresses the following research ques-tion: “How to design data-driven decision support systems to increase the comprehen-sion of contingency factors on business process standardization?”. Theoretically grounded in organizational contingency theory (OCT), this thesis address-es the research question by conducting three design science research (DSR) projects to design data-driven decision support systems (DSSs) for SAP R/3 and S/4 HANA ERP systems that increase comprehension of BPS contingency factors. The thesis conducts the DSR projects at an industry partner within the context of a BPS and SAP S/4 HANA transformation program at a global manufacturing corporation. DSR project 1 designs a data-driven “Business Model Mining” system that automatical-ly “mines” BMs from data in application systems and represents results in an interactive “Business Model Canvas” (BMC) BI dashboard to comprehend BM-related BPS con-tingency factors. The project derives generic design requirements and a blueprint con-ceptualization for BMM systems and suggests an open, standardized reference data model for BMM. The project implements the software artifact “Business Model Miner” in Microsoft Azure / PowerBI and demonstrates technical feasibility by using data from an educational SAP S/4 HANA system, an open reference dataset, and three real-life SAP R/3 ERP systems. A field evaluation with 21 managers at the industry partner finds differences between tool results and BMCs created by managers and thus the po-tential for a complementary role of BMM tools to enrich the comprehension of BMs. A further controlled laboratory experiment with 142 students finds significant beneficial impacts on subjective and objective comprehension in terms of effectiveness, efficiency, and relative efficiency. Second, DSR project 2 designs a data-driven process mining DSS “KeyPro” to semi-automatically discover and prioritize the set of BPs occurring in an organization from log data to concentrate BPS initiatives on important BPs given limited organizational resources. The project derives objective and quantifiable BP importance metrics from BM and BPM literature and implements KeyPro for SAP R/3 ERP and S/4 HANA sys-tems in Microsoft SQL Server / Azure and interactive PowerBI dashboards. A field evaluation with 52 managers compares BPs detected manually by decision-makers against BPs discovered by KeyPro and reveals significant differences and a complemen-tary role of the artifact to deliver additional insights into the set of BPs in the organiza-tion. Finally, a controlled laboratory experiment with 30 students identifies the dash-boards with the lowest comprehension for further development. Third, OCT requires organizations to select a standard BP design that matches contin-gencies. Thus, DSR project 3 designs a process mining DSS to select a standard BP from a repository of different alternative designs based on the similarity of BPS contin-gency factors between the as-is process and the to-be standard processes. DSR project 3 thus derives four different process model variants for representing BPS contingency factors that vary according to determinant factors of process model comprehension (PMC) identified in PMC literature. A controlled laboratory evaluation with 150 stu-dents identifies significant differences in PMC. Based on laboratory findings, the DSS is implemented in the BPM platform “Apromore” to select standard BP reference mod-els from the SAP Best Practices Explorer for SAP S/4 HANA and applied for the pur-chase-to-pay and order-to-cash process of a manufacturing company