http://dl.gi.de/handle/20.500.12116/31947 2026-07-23T22:33:34Z http://dl.gi.de/handle/20.500.12116/31955 A Novel Business Process Prediction Model Using a Deep Learning Method Mehdiyev, Nijat; Evermann, Joerg; Fettke, Peter The ability to proactively monitor business processes is a main competitive differentiator for firms. Process execution logs generated by process aware information systems help to make process specific predictions for enabling a proactive situational awareness. The goal of the proposed approach is to predict the next process event from the completed activities of the running process instance, based on the execution log data from previously completed process instances. By predicting process events, companies can initiate timely interventions to address undesired deviations from the desired workflow. The paper proposes a multi-stage deep learning approach that formulates the next event prediction problem as a classification problem. Following a feature pre-processing stage with n-grams and feature hashing, a deep learning model consisting of an unsupervised pre-training component with stacked autoencoders and a supervised fine-tuning component is applied. Experiments on a variety of business process log datasets show that the multi-stage deep learning approach provides promising results. The study also compared the results to existing deep recurrent neural networks and conventional classification approaches. Furthermore, the paper addresses the identification of suitable hyperparameters for the proposed approach, and the handling of the imbalanced nature of business process event datasets. 2020-01-01T00:00:00Z http://dl.gi.de/handle/20.500.12116/31953 The Influence of Using Collapsed Sub-processes and Groups on the Understandability of Business Process Models Turetken, Oktay; Dikici, Ahmet; Vanderfeesten, Irene; Rompen, Tessa; Demirors, Onur Many factors influence the creation of business process models which are understandable for a target audience. Understandability of process models becomes more critical when size and complexity of the models increase. Using vertical modularization to decompose such models hierarchically into modules is considered to improve their understandability. To investigate this assumption, two experiments were conducted. The experiments involved 2 large-scale real-life business process models that were modeled using BPMN v2.0 (Business Process Model and Notation) in the form of collaboration diagrams. Each process was modeled in 3 modularity forms: fully-flattened, flattened where activities are clustered using BPMN groups, and modularized using separately viewed BPMN sub-processes. The objective was to investigate if and how different forms of modularity representation (used for vertical modularization) in BPMN collaboration diagrams influence the understandability of process models. In addition to the forms of modularity representation, the presentation medium (paper vs. computer) and model reader's level of business process modeling competency were investigated as factors that potentially influence model comprehension. 60 business practitioners from a large organization and 140 graduate students participated in our experiments. The results indicate that, when these three modularity representations are considered, it is best to present the model in a 'flattened' form (with or without the use of groups) and in the 'paper' format in order to optimally understand a BPMN model. The results also show that the model reader's business process modeling competency is an important factor of process model comprehension. 2020-01-01T00:00:00Z http://dl.gi.de/handle/20.500.12116/31954 A Project Portfolio Management Approach to Tackling the Exploration/Exploitation Trade-off Linhart, Alexander; Röglinger, Maximilian; Stelzl, Katharina Organizational ambidexterity (OA) is an essential capability for surviving in dynamic business environments that advocates the simultaneous engagement in exploration and exploitation. Over the last decades, knowledge on OA has substantially matured, covering insights into antecedents, outcomes, and moderators of OA. However, there is little prescriptive knowledge that offers guidance on how to put OA into practice and to tackle the trade-off between exploration and exploitation. To address this gap, the authors adopt the design science research paradigm and propose an economic decision model as artifact. The decision model assists organizations in selecting and scheduling exploration and exploitation projects to become ambidextrous in an economically reasonable manner. As for justificatory knowledge, the decision model draws from prescriptive knowledge on project portfolio management and value-based management, and from descriptive knowledge related to OA to structure the field of action. To evaluate the decision model, its design specification is discussed against theory-backed design objectives and with industry experts. The paper also instantiates the decision model as a software prototype and applies the prototype to a case based on real-world data. 2020-01-01T00:00:00Z http://dl.gi.de/handle/20.500.12116/31952 Developing Serious Games with Integrated Debriefing Grund, Christian Karl; Schelkle, Michael Serious games (SG) are recognized in several domains as a promising instructional approach. When it comes to the field of Information Systems, however, they are not yet broadly investigated. Especially in business intelligence and analytics, a literature review indicates the absence of SG for proper report design. Such games, however, seem beneficial since many business reports suffer from poor business information visualization (BIV). To address this issue, the scope of the study is twofold: first, the paper presents a SG that aims to foster learning about BIV. Second, it evaluates this SG in a laboratory experiment, comparing it to a more conventional instructional approach (i.e., presentation) and testing two different versions of the game: One version integrates debriefing into the game itself, whereas the other version uses classical post hoc debriefing. Results indicate that it is favorable to integrate debriefing into the game in terms of motivation and learning outcomes. In the vein of design science research, the authors thus intend to contribute a useful artifact as well as a novel design principle for this instructional approach: Integrating debriefing into SG. 2020-01-01T00:00:00Z