Refine
Document Type
- Journal article (1240)
- Conference proceeding (1035)
- Book chapter (381)
- Book (223)
- Doctoral Thesis (54)
- Working Paper (37)
- Anthology (32)
- Report (25)
- Patent / Standard / Guidelines (24)
- Issue of a journal (19)
Is part of the Bibliography
- yes (3079) (remove)
Institute
- ESB Business School (1103)
- Informatik (872)
- Technik (508)
- Life Sciences (343)
- Texoversum (219)
- Zentrale Einrichtungen (16)
Publisher
- Springer (346)
- IEEE (250)
- Elsevier (219)
- Hochschule Reutlingen (186)
- MDPI (98)
- Springer Gabler (79)
- Gesellschaft für Informatik (66)
- Universitätsbibliothek Tübingen (59)
- Wiley (54)
- ACM (40)
Context: Companies increasingly strive to adapt to market and ecosystem changes in real time. Gauging and understanding team performance in such changing environments present a major challenge.
Objective: This paper aims to understand how software developers experience the continuous adaptation of performance in a modern, highly volatile environment using Lean and Agile software development methodology. This understanding can be used as a basis for guiding formation and maintenance of high-performing teams, to inform performance improvement initiatives, and to improve working conditions for software developers.
Method: A qualitative multiple-case study using thematic interviews was conducted with 16 experienced practitioners in five organisations.
Results: We generated a grounded theory, Performance Alignment Work, showing how software developers experience performance. We found 33 major categories of performance factors and relationships between the factors. A cross-case comparison revealed similarities and differences between different kinds and different sizes of organisations.
Conclusions: Based on our study, software teams are engaged in a constant cycle of interpreting their own performance and negotiating its alignment with other stakeholders. While differences across organisational sizes exist, a common set of performance experiences is present despite differences in context variables. Enhancing performance experiences requires integration of soft factors, such as communication, team spirit, team identity, and values, into the overall development process. Our findings suggest a view of software development and software team performance that centres around behavioural and social sciences.
Das Provisioning Tool automaIT wurde prototypisch um die Möglichkeit eines Data Discovery erweitert, mit dem Ziel, nicht durch automaIT verwaltete Systeme anbinden und steuern zu können. Daten aus dem Data Discovery werden mittels dem Tool Facter gesammelt und können dynamisch in ausführbare Modelle von automaIT integriert und ausgewertet werden. Dadurch kann der Verlauf weiterer Provisionierungsschritte gesteuert werden, ohne dass es eines manuellen Eingriffs bedarf.
A sequence of transactions represents a complex and multi dimensional type of data. Feature construction can be used to reduce the data´s dimensionality to find behavioural patterns within such sequences. The patterns can be expressed using the blue prints of the constructed relevant features. These blue prints can then be used for real time classification on other sequences.
In a world with rapidly changing customer requirements and the increased role of technology, companies need more flexible systems to adapt their processes and react dynamically to changes. Adaptive Case Management (ACM) comes into consideration by providing a concept to adapt to changing business conditions. Within our research project we did a first foundational evaluation of the potential of ACM in supporting unpredictable sales processes. Based on a set of criteria we tested the concept of ACM with the open source tool Cognoscenti. The evaluation gave us the possibility to experience the concept of ACM. Hence we were able to provide a statement about the potential of ACM within the context of an unpredictable sales process, setting the path to further research and discussion of ACM in the area of sales processes.
The character of knowledge-intense processes is that participants decide the next process activities on base of the present information and their expert knowledge. The decisions of these knowledge workers are in general non-deterministic. It is not possible to model these processes in advance and to automate them using a process engine of a BPM system. Hence, in this context a process instance is called a case, because there is no predefined model that could be instantiated. Domain-specific or general case management systems are used to support the knowledge workers. These systems provide all case information and enable users to define the next activities, but they have no or only limited activity recommendation capabilities. In the following paper, we present a general concept for a self-learning system based on process mining that suggests the next best activity on quantitative and qualitative data for a given case. As a proof of concept, it was applied to the area of insurance claims settlement.
Business processes are important knowledge resources of a company. The knowledge contained in business processes impart procedures used to create products and services. However, modelling and application of business processes are affected by problems connected to knowledge transfer. This paper presents and implements a layered model to improve the knowledge transfer. Thus modelling and understanding of business process models is supported. An evaluation of the approach is presented and results and other areas of application are discussed.
EAM ist ein holistischer Ansatz, um komplexe IT- und Unternehmensstrukturen darzustellen. Dabei ist es von zentraler Bedeutung, diese Strukturen möglichst komplett und übersichtlich zu visualisieren. Ein Ansatz, dies zu erreichen, ist eine multiperspektivische Darstellung von mehreren Views in einem Architekturcockpit. Dabei können mehrere Views simultan betrachtet und analysiert werden. Dadurch ist es möglich, die Auswirkungen einer Analyse des Views eines Stakeholders simultan aus den Views anderer Stakeholder betrachten zu können, um eventuelle Wechselwirkungen zu erkennen und einen allgemeinen Überblick über die Unternehmensarchitektur zu behalten. In dieser Arbeit zeigen wir, von der Konzeption über die Umsetzung bis zu einem Anwendungsbeispiel, wie ein solches Architekturcockpit realisiert werden kann.
The digital transformation of our society changes the way we live, work, learn, communicate, and collaborate. This disruptive change interacts with all information processes and systems that are important business enablers for the digital transformation since years. The Internet of Things, social collaboration systems for adaptive case management, mobility systems and services for Big Data in cloud services environments are emerging to support intelligent user-centered and social community systems. They will shape future trends of business innovation and the next wave of information and communication technology. Biological metaphors of living and adaptable ecosystems provide the logical foundation for self-optimizing and resilient run-time environments for intelligent business services and related distributed information systems with service-oriented enterprise architectures. The present research investigates mechanisms for flexible adaptation and evolution of digital enterprise architectures in the context of integrated synergistic disciplines like distributed service-oriented architectures and information systems, EAM - Enterprise Architecture and Management, metamodeling, semantic echnologies, web services, cloud computing and Big Data technology. Our aim is to support flexibility and agile transformations for both business domains and related enterprise systems through adaptation and evolution of digital enterprise architectures. The present research paper investigates digital transformations of business and IT and integrates fundamental mappings between adaptable digital enterprise architectures and service-oriented information systems.
Decision-making in the field of Enterprise Architecture (EA) is a complex task. Many organizations establish a set of complex processes and hierarchical structures to enable strategy-driven development of their EA. This leads to slow and inefficient decision-making entailing bad time-to-market and discontented stakeholders. Collaborative EA delineates a lightweight approach to enable EA decisions but often neglects strategic alignment. In this paper, we present an approach to integrate the concept of collaborative EA and goal-driven decision-making through collaborative modeling of goal-oriented information demands based on ArchiMate’s motivation extension to reach a goal-oriented EA decision support in a collaborative EA environment.
Enterprise Architecture (EA) management is an activity that seeks to foster the alignment of business and IT, and pursues various goals further operationalizing this alignment. Key to effective EA management is a framework that defines the roles, activities, and viewpoints used for EA management in accordance to the concerns that the stakeholders aim to address. Consensus holds that such frameworks are organization-specific and hence they are designed in governance activities for EA management. As of today, top-down approaches for governance are used to derive organization-specific frameworks. These usually lack systematic mechanisms for improving the framework based on the feedback of the responsible stakeholders. We outline a bottom-up approach for EA management governance that systematically observes the behavior of the actors to learn user concerns and recommend appropriate viewpoints. With this approach, we complement traditional top-down governance activities.