Constructing comparable business process models with domain specific languages - An empirical evaluation

The objective of this paper is to evaluate the semantic building block-based approach as a means for improving comparability in business process modelling. It is described whether and why the semantic building block-based approach reduces the variations in comparison to traditional modelling approaches. Our argumentation is grounded on the assumption that business process modelling projects in large organisations have to be conducted in a distributed manner. However, the goal of these projects is to integrate single models into a consistent process landscape. This allows the organisation to mine the processes for potential improvements. A lack of comparability could deteriorate the quality of the process landscape and the analysis performed on its basis. In a laboratory experiment the variations of distributed process modelling in the traditional and the building block-based approach have been compared. Results indicate that the semantic building block-based approach leads to considerably fewer variations between business process models and, thus, improves the comparability of them

A Performance Assessment System incorporating indirect indicators and semantics

Measuring performance is key to reengineering and optimization of business processes. Although many of them cannot easilybe measured due to their quantitative or non-deterministic nature, most performance measurement systems rely on the usageof numeric parameters (Key Performance Indicators, KPIs). So, performance problems stay invisible that could be assessedby other indirect indicators like goals, complexity, maturity, relations or dependencies. In this paper, a Four-Box-Model ispresented that also includes internal process views, descriptive approaches and semantics in addition to KPIs. It offers a broadrange of possibilities to better identify performance problems and hence, to increase process performance

Constructing comparable business process models with domain specific languages - An empirical evaluation

Establishing technologies has brought mixed socio-economic impacts across nations and regions. Researchers have studied the relationships between the establishment technologies and its impacts through identifying innovative processes, major actors, and available resources. However, the challenge to this literature is how less resourced countries have achieved greater prosperity than better resourced countries by establishing Information and Communication Technology (ICT). To understand and analyze this phenomenon, we propose a typology of the configuration of roles and actors in establishing ICT based on an innovation framework. The proposed typology can be used not only to explain different socio-economic impacts among countries or regions, but also to suggest a constructive way in establishing ICT through reconfiguring involved actors in the key roles

On the symbiosis between conceptual modeling and ontology engineering : recommendation-based conceptual modeling

Within an enterprise, different conceptual models, such as process, data, and goal models, are created by various stakeholders. These models are fundamentally based on similar underlying enterprise (domain) concepts, but they have a different focus, are represented using different modeling languages, take different viewpoints, utilize different terminology, and are used to develop different enterprise artefacts (such as documents, software, databases, etc.); therefore, they typically lack consistency and alignment. Another issue is that modelers have different vocabulary selections and different modeling styles. As a result, the enterprise can find itself accumulating a pile of models which cover similar aspects in different manners. Those models are not machine-readable and cannot be processed automatically. Enterprise-Specific Ontologies (ESOs) aim to solve this problem by serving as a reference during the conceptual model creation. Using such a shared semantic repository makes conceptual models semantically aligned and facilitates model integration. However, managing those ontologies is complicated; an enterprise is an evolving entity, and as it changes, the ESO might become outdated. During the years of research dedicated to this dissertation, the Recommendation-Based Conceptual Modeling and Ontology Evolution (CMOE+) framework was developed. This framework establishes a symbiotic relationship between the Ontology engineering and the Conceptual modeling fields. CMOE+ consists of two cycles: the Ontology Evolution cycle and the Conceptual Modeling cycle. The Ontology Evolution cycle is responsible for setting up the initial version of the ESO and updating it as the knowledge within the enterprise evolves. Additionally, this cycle encapsulates recommendation services to perform ontology look-up and to present the most relevant ESO concepts in support of the modeler. The Conceptual Modeling cycle is responsible for the creation of conceptual models in different modeling languages based on the ESO. This cycle is also concerned with the quality evaluation of the created models. CMOE+ was developed based on requirements identified as a result of a literature review and a case study. The development process follows the Design Science Research Methodology (DSRM). After the initial version of CMOE+ was put forward, our focus was narrowed towards the recommendation-based conceptual modeling part of CMOE+, and we continued to gradually improve the framework in iterations until it reached its current state. The Ontology Evolution Cycle is not fully addressed within the scope of this dissertation. In order to demonstrate the performance and usability of CMOE+, it was exemplified for process modeling using BPMN and goal modeling using i*. This thesis presents a detailed instantiation, and explains steps to be performed in order to instantiate CMOE+ for other modeling languages. In order to evaluate the process modeling instance of CMOE+, a CMOE+BPMN tool was implemented. This tool incorporates a BPMN modeler, facilitates storage and access of the ESO, and includes all algorithms functioning within CMOE+ for the BPMN modeling language (as some of the algorithms are language dependent). Next, CMOE+ was exemplified using the i* goal modeling language. Finally, we demonstrated the ability of CMOE+ to perform alignment between i* and BPMN models, in order to show that CMOE+ is indeed beneficial in achieving interoperability among models created in different modeling languages and covering distinct aspects of the enterprise