The recent Decision Model and Notation (DMN) establishes business decisions as first-class citizens of executable business processes. This research note has two objectives: first, to describe DMN's technical and theoretical foundations; second, to identify research directions for investigating DMN's potential benefits on a technological, individual and organizational level. To this end, we integrate perspectives from management science, cognitive theory and information systems research.

Business process models are an important means to design, analyze, implement, and control business processes. As with every type of conceptual model, a business process model has to meet certain syntactic, semantic, and pragmatic quality requirements to be of value. For many years, such quality aspects were investigated by centering on the properties of the model artifact itself. Only recently, the process of model creation is considered as a factor that influences the resulting model's quality. Our work contributes to this stream of research and presents an explorative analysis of the process of process modeling (PPM). We report on two large-scale modeling sessions involving 115 students. In these sessions, the act of model creation, i.e., the PPM, was automatically recorded. We conducted a cluster analysis on this data and identified three distinct styles of modeling. Further, we investigated how both task- and modeler-specific factors influence particular aspects of those modeling styles. Based thereupon, we propose a model that captures our insights. It lays the foundations for future research that may unveil how high-quality process models can be established through better modeling support and modeling instruction. (authors' abstract)

This thesis study proposes a method for organizations to perform business process modeling in a decentralized and concurrent manner. The Plural method is based on the idea that organizations&rsquo / processes can be modeled by individuals actually performing the processes. Instead of having a central and devoted group of people to understand, analyze, model and improve processes, individuals are held responsible to model and improve their own processes concurrently. These individual models are then integrated to form organization&rsquo / s process network. The method guides the application of this approach in organizations with the activities to be followed and the artifacts to be produced. To apply the method, the study also introduces a notation and a prototype toolset. A multiple-case study involving two cases is conducted in order to evaluate the applicability of the method for decentralized process modeling and validate the expected benefits.

This paper analyzes a proposed release controlmethodology, WIPLOAD Control (WIPLCtrl), using a transfer line case modeled by Markov process modeling methodology. The performance of WIPLCtrl is compared with that of CONWIP under 13 system configurations in terms of throughput, average inventory level, as well as average cycle time. As a supplement to the analytical model, a simulation model of the transfer line is used to observe the performance of the release control methodologies on the standard deviation of cycle time. From the analysis, we identify the system configurations in which the advantages of WIPLCtrl could be observed. / Singapore-MIT Alliance (SMA)

Reasoning about processes in applications such as manufacturing, web services, enterprise modeling, and planning requires the representation of composite processes with complicated flows of control. Previous research in process representation has used formalisms such as Event Systems, Petri nets, and the Unified Modeling Language activity diagrams. The computational hardness of temporal projection problems in Event Systems has been extensively examined in the literature, whereas Petri nets and UML activity diagrams are applied to describe more elaborate processes. This thesis takes a systematic look into the temporal reasoning problems in Event Systems and assigns accurate semantics to both Petri nets and, for the first time, to UML activity diagrams. We give an analysis of computational complexity in temporal projection problems by exploring the boundary between their tractable and intractable subproblems. Our results provide new insights into the prominent role the properties of partial ordering play, however we also show that partial ordering is not the sole source of the intractability as has been claimed in an earlier work by Nebel and B{\"a}ckstr{\"o}m. Two influential modeling languages, Petri nets and UML activity diagrams, are axiomatized as two Basic Action Theories of Situation Calculus. They are called, respectively, SCOPE (Situation Calculus Ontology of PEtri nets) and SCAD (Situation Calculus theory of Activity Diagrams). We provide a Prolog implementation of SCOPE and prove the correctness of this program for regressable queries. We use SCAD to axiomatize the structural and dynamic properties of UML activity diagrams and also provide the first set of computational results with regard to the reachability problems in activity diagrams. The correctness of each of these two axiomatizations is also demonstrated by proving that the theory is satisfiable, and the intended interpretation corresponds to a model of the theory.

Reasoning about processes in applications such as manufacturing, web services, enterprise modeling, and planning requires the representation of composite processes with complicated flows of control. Previous research in process representation has used formalisms such as Event Systems, Petri nets, and the Unified Modeling Language activity diagrams. The computational hardness of temporal projection problems in Event Systems has been extensively examined in the literature, whereas Petri nets and UML activity diagrams are applied to describe more elaborate processes. This thesis takes a systematic look into the temporal reasoning problems in Event Systems and assigns accurate semantics to both Petri nets and, for the first time, to UML activity diagrams. We give an analysis of computational complexity in temporal projection problems by exploring the boundary between their tractable and intractable subproblems. Our results provide new insights into the prominent role the properties of partial ordering play, however we also show that partial ordering is not the sole source of the intractability as has been claimed in an earlier work by Nebel and B{\"a}ckstr{\"o}m. Two influential modeling languages, Petri nets and UML activity diagrams, are axiomatized as two Basic Action Theories of Situation Calculus. They are called, respectively, SCOPE (Situation Calculus Ontology of PEtri nets) and SCAD (Situation Calculus theory of Activity Diagrams). We provide a Prolog implementation of SCOPE and prove the correctness of this program for regressable queries. We use SCAD to axiomatize the structural and dynamic properties of UML activity diagrams and also provide the first set of computational results with regard to the reachability problems in activity diagrams. The correctness of each of these two axiomatizations is also demonstrated by proving that the theory is satisfiable, and the intended interpretation corresponds to a model of the theory.

In order to make good decisions about the design of information systems, an essential skill is to understand process models of the business domain the system is intended to support. Yet, little knowledge to date has been established about the factors that affect how model users comprehend the content of process models. In this study, we use theories of semiotics and cognitive load to theorize how model and personal factors influence how model viewers comprehend the syntactical information of process models. We then report on a four-part series of experiments, in which we examined these factors. Our results show that additional semantical information impedes syntax comprehension, and that theoretical knowledge eases syntax comprehension. Modeling experience further contributes positively to comprehension efficiency, measured as the ratio of correct answers to the time taken to provide answers. We discuss implications for practice and research.

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Process modeling is an indispensable task in the discipline of Business Process Management. The process models created in this task help its readers in to acquiring a higher comprehension of a process, allowing for the discovery of opportunities for its improvement. However, the comprehension of a process model is not guaranteed, as process modeling is a complex task that depends on the proficiency of the process modeler to avoid the creation of badly designed constructs. Process modeling guidelines are an essential tool in this regard, though they are dispersed across the many studies of the literature and not all of them have empirical evidence validating their effects. In addition to this problem, it is still an open questions if a set of process modeling guidelines makes the process modeling task more challenging and how effective modelers are in using them. It is also unclear how receptive process analysts are to the modeling guidelines. This dissertation presents a systematic literature review we conducted to collect and analyze the modeling guidelines found in the literature. It investigated a total of 520 articles, extracting a total of 45 modeling guidelines spread across 4 different categories. These 45 guidelines were simplified into a set of 20 guidelines, based on their significance to create more comprehensible process models and their practicality. This dissertation also presents the findings of an empirical experiment performed by 13 subjects that compared the results of two process modeling tasks with and without the support of the 20 modeling guidelines presented by the review, in which it was possible to observe that the subjects recognize the usefulness of the guidelines, but find them difficult to understand and use.

Process and data are equally important for business process management. Process data is especially relevant in the context of automated business processes, process controlling, and representation of organizations' core assets. One can discover many process modeling languages, each having a specific set of data modeling capabilities and the level of data awareness. The level of data awareness and data modeling capabilities vary significantly from one language to another. This paper evaluates several process modeling languages with respect to the role of data. To find a common ground for comparison, we develop a framework, which systematically organizes process- and data-related aspects of the modeling languages elaborating on the data aspects. Once the framework is in place, we compare twelve process modeling languages against it. We generalize the results of the comparison and identify clusters of similar languages with respect to data awareness. / Prozesse und Daten sind gleichermaßen wichtig für das Geschäftsprozessmanagement. Prozessdaten sind dabei insbesondere im Kontext der Automatisierung von Geschäftsprozessen, dem Prozesscontrolling und der Repräsentation der Vermögensgegenstände von Organisationen relevant. Es existieren viele Prozessmodellierungssprachen, von denen jede die Darstellung von Daten durch eine fest spezifizierte Menge an Modellierungskonstrukten ermöglicht. Allerdings unterscheiden sich diese Darstellungenund damit der Grad der Datenmodellierung stark untereinander. Dieser Report evaluiert verschiedene Prozessmodellierungssprachen bezüglich der Unterstützung von Datenmodellierung. Als einheitliche Grundlage entwickeln wir ein Framework, welches prozess- und datenrelevante Aspekte systematisch organisiert. Die Kriterien legen dabei das Hauptaugenmerk auf die datenrelevanten Aspekte. Nach Einführung des Frameworks vergleichen wir zwölf Prozessmodellierungssprachen gegen dieses. Wir generalisieren die Erkenntnisse aus den Vergleichen und identifizieren Cluster bezüglich des Grades der Datenmodellierung, in welche die einzelnen Sprachen eingeordnet werden.