Refine
Year of publication
Document Type
- Part of Periodical (35)
- Bachelor Thesis (32)
- Diploma Thesis (27)
- Master's Thesis (27)
- Doctoral Thesis (13)
- Study Thesis (12)
- Book (1)
Keywords
- Internet of Things (4)
- Logistik (4)
- computer clusters (4)
- Datenaustausch (3)
- Datenschutz (3)
- E-Partizipation (3)
- Evaluation (3)
- Instant Messaging (3)
- parallel algorithms (3)
- Beschaffung (2)
Institute
- Institut für Wirtschafts- und Verwaltungsinformatik (147) (remove)
Predictive Process Monitoring is becoming more prevalent as an aid for organizations to support their operational processes. However, most software applications available today require extensive technical know-how by the operator and are therefore not suitable for most real-world scenarios. Therefore, this work presents a prototype implementation of a Predictive Process Monitoring dashboard in the form of a web application. The system is based on the PPM Camunda Plugin presented by Bartmann et al. (2021) and allows users to easily create metrics, visualizations to display these metrics, and dashboards in which visualizations can be arranged. A usability test is with test users of different computer skills is conducted to confirm the application’s user-friendliness.
Remote Working Study 2022
(2022)
The Remote Working Study 2022 is focused on the transition to work from home (WFH) triggered by the stay at home directives of 2020. These directives required employees to work in their private premises wherever possible to reduce the transmission of the coronavirus. The study, conducted by the Center for Enterprise Information Research (CEIR) at the University of Koblenz from December 2021 to January 2022, explores the transition to remote working.
The objective of the survey is to collect baseline information about organisations’ remote work experiences during and immediately following the COVID-19 lockdowns. The survey was completed by the key persons responsible for the implementation and/or management of the digital workplace in 19 German and Swiss organisations.
The data presented in this report was collected from member organisations of the IndustryConnect initiative. IndustryConnect is a university-industry research programme that is coordinated by researchers from the University of Koblenz. It focuses on research in the areas of the digital workplace and enterprise collaboration technologies, and facilitates the generation of new research insights and the exchange of experiences among user companies.
Advanced Auditing of Inconsistencies in Declarative Process Models using Clustering Algorithms
(2021)
To have a compliant business process of an organization, it is essential to ensure a onsistent process. The measure of checking if a process is consistent or not depends on the business rules of a process. If the process adheres to these business rules, then the process is compliant and efficient. For huge processes, this is quite a challenge. Having an inconsistency in a process can yield very quickly to a non-functional process, and that’s a severe problem for organizations. This thesis presents a novel auditing approach for handling inconsistencies from a post-execution perspective. The tool identifies the run-time inconsistencies and visualizes them in heatmaps. These plots aim to help modelers observe the most problematic constraints and help them make the right remodeling decisions. The modelers assisted with many variables can be set in the tool to see a different representation of heatmaps that help grasp all the perspectives of the problem. The heatmap sort and shows the run-time inconsistency patterns, so that modeler can decide which constraints are highly problematic and should address a re-model. The tool can be applied to real-life data sets in a reasonable run-time.
Enterprise collaboration platforms are increasingly gaining importance in organisations. Integrating groupware functionality and enterprise social software (ESS), they have substantially been transforming everyday work in organisations. While traditional collaboration systems have been studied in Computer Supported Cooperative Work (CSCW) for many years, the large-scale, infrastructural and heterogeneous nature of enterprise collaboration platforms remains uncharted. Enterprise collaboration platforms are embedded into organisations’ digital workplace and come with a high degree of complexity, ambiguity, and generativity. When introduced, they are empty shells with no pre-determined purposes of use. They afford interpretive flexibility, and thus are shaping and being shaped by and in their social context. Outcomes and benefits emerge and evolve over time in an open-ended process and as the digital platform is designed through use. In order to make the most of the platform and associated continuous digital transformation, organisations have to develop the necessary competencies and capabilities.
Extant literature on enterprise collaboration platforms has proliferated and provide valuable insights on diverse topics, such as implementation strategies, adoption hurdles, or collaboration use cases, however, they tend to disregard their evolvability and related multiple time frames and settings. Thus, this research aims to identify, investigate, and theorise the ways that enterprise collaboration platforms are changing over time and space and the ways that organisations build digital transformation capabilities. To address this research aim two different case study types are conducted: i) in-depth longitudinal qualitative case study, where case narratives and visualisations capturing hard-to-summarise complexities in the enterprise collaboration platform evolution are developed and ii) multiple-case studies to capture, investigate, and compare cross-case elements that contribute to the shaping of enterprise collaboration platforms in different medium-sized and large organisations from a range of industries. Empirical data is captured and investigated through a multi-method research design (incl. focus groups, surveys, in-depth interviews, literature reviews, qualitative content analysis, descriptive statistics) with shifting units of analysis. The findings reveal unique change routes with unanticipated outcomes and transformations, context-specific change strategies to deal with multiple challenges (e.g. GDPR, works council, developments in the technological field, competing systems, integration of blue-collar workers), co-existing platform uses, and various interacting actors from the immediate setting and broader context. The interpretation draws on information infrastructure (II) as a theoretical lens and related sociotechnical concepts and perspectives (incl. inscriptions, social worlds, biography of artefacts). Iteratively, a conceptual model of the building of digital transformation capabilities is developed, integrating the insights gained from the study of enterprise collaboration platform change and developed monitoring change tools (e.g. MoBeC framework). It assists researchers and practitioners in understanding the building of digital transformation capabilities from a theoretical and practical viewpoint and organisations implement the depicted knowledge in their unique digital transformation processes.
Enterprise Collaboration Systems (ECS) have become substantial for computer-mediated communication and collaboration among employees in organisations. As ECS combine features from social media and traditional groupware, a growing number of organisations implement ECS to facilitate collaboration among employees. Consequently, ECS form the core of the digital workplace. Thus, the activity logs of ECS are particularly valuable since they provide a unique opportunity for observing and analysing collaboration in the digital workplace.
Evidence from academia and practice demonstrates that there is no standardised approach for the analysis of ECS logs and that practitioners struggle with various barriers. Because current ECS analytics tools only provide basic features, academics and practitioners cannot leverage the full potential of the activity logs. As ECS activity logs are a valuable source for understanding collaboration in the digital workplace, new methods and metrics for their analysis are required. This dissertation develops Social Collaboration Analytics (SCA) as a method for measuring and analysing collaboration activities in ECS. To address the existing limitations in academia and practice and to contribute a method and structures for applying SCA in practice, this dissertation aims to answer two main research questions:
1. What are the current practices for measuring collaboration activities in Enterprise Collaboration Systems?
2. How can Social Collaboration Analytics be implemented in practice?
By answering the research questions, this dissertation seeks to (1) establish a broad thematic understanding of the research field of SCA and (2) to develop SCA as a structured method for analysing ac-tivity logs of ECS. As part of the first research question, this dissertation documents the status quo of SCA in the academic literature and practice. By answering the second research question, this dissertation contributes the SCA framework (SCAF), which guides the practical application of SCA. SCAF is the main contribution of this dissertation. The framework was developed based on findings from an analysis of 86 SCA studies, results from 6 focus groups and results from a survey among 27 ECS user companies. The phases of SCAF were derived from a comparison of established process models for data mining and business intelligence. The eight phases of the framework contain detailed descriptions, working steps, and guiding questions, which provide a step by step guide for the application of SCA in practice. Thus, academics and practitioners can benefit from using the framework.
The constant evaluation of the research outcomes in focus groups ensures both rigour and relevance. This dissertation employs a qualitative-dominant mixed-methods approach. As part of the university-industry collaboration initiative IndustryConnect, this research has access to more than 30 leading ECS user companies. Being built on a key case study and a series of advanced focus groups with representatives of user companies, this dissertation can draw from unique insights from practice as well as rich data with a longitudinal perspective.
The flexible integration of information from distributed and complex information systems poses a major challenge for organisations. The ontology-based information integration concept SoNBO (Social Network of Business Objects) developed and presented in this dissertation addresses these challenges. In an ontology-based concept, the data structure in the source systems (e.g. operational application systems) is described with the help of a schema (= ontology). The ontology and the data from the source systems can be used to create a (virtualised or materialised) knowledge graph, which is used for information access. The schema can be flexibly adapted to the changing needs of a company regarding their information integration. SoNBO differs from existing concepts known from the Semantic Web (OBDA = Ontology-based Data Access, EKG = Enterprise Knowledge Graph) both in the structure of the company-specific ontology (= Social Network of Concepts) as well as in the structure of the user-specific knowledge graph (= Social Network of Business Objects) and makes use of social principles (known from Enterprise Social Software). Following a Design Science Research approach, the SoNBO framework was developed and the findings documented in this dissertation. The framework provides guidance for the introduction of SoNBO in a company and the knowledge gained from the evaluation (in the company KOSMOS Verlag) is used to demonstrate its viability. The results (SoNBO concept and SoNBO framework) are based on the synthesis of the findings from a structured literature review and the investigation of the status quo of ontology-based information integration in practice: For the status quo in practice, the basic idea of SoNBO is demonstrated in an in-depth case study about the engineering office Vössing, which has been using a self-developed SoNBO application for a few years. The status quo in the academic literature is presented in the form of a structured literature analysis on ontology-based information integration approaches. This dissertation adds to theory in the field of ontology-based information integration approaches (e. g. by an evaluated artefact) and provides an evaluated artefact (the SoNBO Framework) for practice.
Within the field of Business Process Management, business rules are commonly used to model company decision logic and govern allowed company behavior. An exemplary business rule in the financial sector could be for example:
”A customer with a mental condition is not creditworthy”. Business rules are
usually created and maintained collaboratively and over time. In this setting,
modelling errors can occur frequently. A challenging problem in this context is
that of inconsistency, i.e., contradictory rules which cannot hold at the same
time. For instance, regarding the exemplary rule above, an inconsistency would
arise if a (second) modeller entered an additional rule: ”A customer with a mental condition is always creditworthy”, as the two rules cannot hold at the same
time. In this thesis, we investigate how to handle such inconsistencies in business
rule bases. In particular, we develop methods and techniques for the detection,
analysis and resolution of inconsistencies in business rule bases
The industry standard Decision Model and Notation (DMN) has enabled a new way for the formalization of business rules since 2015. Here, rules are modeled in so-called decision tables, which are defined by input columns and output columns. Furthermore, decisions are arranged in a graph-like structure (DRD level), which creates dependencies between them. With a given input, the decisions now can be requested by appropriate systems. Thereby, activated rules produce output for future use. However, modeling mistakes produces erroneous models, which can occur in the decision tables as well as at the DRD level. According to the Design Science Research Methodology, this thesis introduces an implementation of a verification prototype for the detection and resolution of these errors while the modeling phase. Therefore, presented basics provide the needed theoretical foundation for the development of the tool. This thesis further presents the architecture of the tool and the implemented verification capabilities. Finally, the created prototype is evaluated.
Regarding the rising amount of legal regulations, businesses should get the opportunity to use software to fulfill their Compliance Management with the usage of compliance pattern. These patterns are used to represent substantive and structural parts of the processes. This means companies can increase their efficiency and react to new regulations quickly to avoid possible violation which can lead to monetary losses or legal consequences. In the literature are many approaches that deal with compliance pattern but currently there does not exist any list with necessary compliance pattern that companies should face at (Delfmann and Hübers, 2015). The following bachelor thesis classifies 80 research contributions regarding their different approaches of compliance pattern. For that a systematic literature review was executed. As a result, the author developed a graphical classification context that provides an overview of connections between different compliance approaches. Furthermore, an appendix with 32 compliance patterns of the analyzed papers was developed that contains real-world patterns with the classification of the previous sections.
Unkontrolliert gewachsene Software-Architekturen zeichnen sich i.d.R. durch fehlende oder schlecht nachvollziehbare Strukturen aus. Hierfür können als Gründe beispielsweise mangelhafte Definitionen oder ein langsames Erodieren sein. Dies ist auch unter dem Begriff "Big Ball of Mud" bekannt. Langfristig erhöhen solche architekturellen Mängel nicht nur die Entwicklungskosten, sondern können letztendlich auch Veränderungen vollständig verhindern.
Die Software-Architektur benötigt somit eine kontinuierliche Weiterentwicklung, um solchen Effekten entgegen wirken zu können. Eine gute Software-Architektur unterstützt die Software-Entwicklung und erhöht die Produktivität. Auf der Ebene von Quellcode existieren bereits etablierte Vorgehensweisen zur kontrollierten Verbesserung der Qualität. Im Gegensatz hierzu existieren für Verbesserungen einer Software-Architektur jedoch keine allgemeingültigen Vorgehensweisen, welche unabhängig vom Anwendungsfall angewandt werden können. An diesem Punkt setzt die vorliegende Arbeit an.
Bisherige Arbeiten beschäftigen sich einerseits nur mit Teilpunkten des Problems. Anderseits existieren zwar bereits Vorgehensweisen zum Treffen von Architekturentscheidungen, jedoch agieren diese auf einer stark abstrakten Ebene ohne praktische Beispiele. Diese Arbeit stellt eine leichtgewichtige Vorgehensweise zum gezielten Verbessern einer Software-Architektur vor. Die Vorgehensweise basiert auf einem generischen Problemlösungsprozess. Auf dieser Basis ist ein Prozess zum Lösen von Problemen einer Software-Architektur entwickelt worden. Im Fokus der Arbeit stehen zur Eingrenzung des Umfanges architektonische Probleme aufgrund geforderter Variabilität sowie externer Abhängigkeiten.
Die wissenschaftliche Methodik, welcher der Arbeit zugrunde liegt, agiert im Rahmen der Design Science Research (DSR). Über mehrere Iterationen hinweg wurde eine Vorgehensweise entwickelt, welche sich an Softwareentwickler mit zwei bis drei Jahren Erfahrung und Kenntnissen über Grundlage der Softwareentwicklung und Software-Architektur richtet. Fünf Schritte inkl. Verweise auf aussagekräftige Literatur leiten Anwender anschließend durch den Prozess zur gezielten Verbesserung einer Software-Architektur.
