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Auflistung nach Schlagwort "Decision support"

1 - 10 von 14
  • Zeitschriftenartikel
    Betriebliches Identitätsmanagement
    (Wirtschaftsinformatik: Vol. 51, No. 3, 2009) Royer, Denis; Meints, Martin
    Systeme für das betriebliche Identitätsmanagement (Enterprise Identity Management, EIdMS) stellen eine IT-basierte Infrastruktur dar, die in verschiedenen Geschäftsprozessen und zugehörigen Infrastrukturen integriert werden muss. Die Bewertung und Vorbereitung von Entscheidungen für eine Einführung eines EIdMS muss die Kosten, den Nutzen und die organisatorische Umgebung berücksichtigen. Eine Vielzahl von Methoden für die Beurteilung und die Entscheidungsunterstützung neuer IT im Allgemeinen, als auch für EIdMS, werden in der Literatur diskutiert. Allerdings basieren diese Methoden typischerweise auf einzelnen Dimensionen (z. B. finanziellen oder technologischen Aspekten). Dieser Beitrag schlägt ein multidimensionales Entscheidungsunterstützungsrahmenwerk auf Basis des Balanced-Scorecard-Konzepts vor. Der dargestellte Ansatz führt vier Perspektiven und eine zugehörige Menge initialer Entscheidungsparameter ein, um die Entscheidungsfindung zu unterstützen. Diese Perspektiven sind (a) finanzielle / monetäre Aspekte, (b) Geschäftsprozesse, (c) unterstützende Prozesse und (IKT-) Infrastruktur sowie (d) Informationssicherheit, Risiken und Compliance. Die Perspektiven und die anpassbare Menge der Entscheidungsparameter können auch als Grundlage für softwarebasierte Entscheidungsunterstützungsinstrumente dienen.AbstractEnterprise Identity Management Systems (EIdMS) are an IT-based infrastructure that needs to be integrated in various business processes and related infrastructures. Assessment and preparation of decisions for the introduction need to take the costs, benefits, and the organizational settings into consideration. A variety of methods for the evaluation and decision support of new IT (e. g. EIdMS) are discussed in the literature – however, these are typically based on single dimensions (e. g. financial or technology aspects). This paper proposes a multidimensional decision support framework, based on the Balanced Scorecard concept. The presented approach introduces four perspectives and a related set of initial decision parameters to support decision making. The perspectives are (a) financial/monetary, (b) business processes, (c) supporting processes and (ICT) infrastructure and (d) information security, risks and compliance. Perspectives and adaptable sets of decision parameters also may serve as foundation for software-based decision support instruments.
  • Konferenzbeitrag
    Continuous Innovation and Experimentation in Complex Problem Domains
    (Software Engineering und Software Management 2018, 2018) Klepper, Sebastian; Grimm, Christian; Bruegge, Bernd
    Continuous software engineering enables experimentation and empirical research in complex problem domains. Existing process models describe different approaches for exploration, innovation, and refinement. We propose a new approach based on problem solving techniques and focused on decision support to serve as the starting point for a unified process framework.
  • Zeitschriftenartikel
    Fair AI
    (Business & Information Systems Engineering: Vol. 62, No. 4, 2020) Feuerriegel, Stefan; Dolata, Mateusz; Schwabe, Gerhard
  • Konferenzbeitrag
    Impact of Hypothesis-Driven Development on Effectiveness, Quality, and Efficiency in Innovation Projects
    (Software Engineering und Software Management 2018, 2018) Klepper, Sebastian; Bruegge, Bernd
    We evaluate the impact of hypothesis-driven development in innovation projects dealing with complex problems, focusing on decision making processes instead of experimentation methods. Our findings show that this type of empirical research used for decision support can enhance effectiveness and quality without negatively impacting efficiency.
  • Zeitschriftenartikel
    An intelligent decision support system for readmission prediction in healthcare
    (it - Information Technology: Vol. 60, No. 4, 2018) Eigner, Isabella; Bodendorf, Freimut
    Readmission prediction in hospitals is a highly complex task involving multiple risk factors that can vary among different disease groups. We address this issue by implementing multiple cross-validated classification models within an intelligent CDSS to enhance patient discharge management. Depending on the diagnosis, the system selects and applies the appropriate model and visualises the prediction results. In addition, the cost and reimbursement development for each episode are determined. The architecture of the CDSS and the integration of the prediction models are presented in this paper.
  • Workshopbeitrag
    On the Convergence of Intelligent Decision Aids
    (Mensch und Computer 2021 - Workshopband, 2021) Loepp, Benedikt
    On the one hand, users’ decisionmaking in today’sweb is supported in numerous ways, with mechanisms ranging from manual search over automated recommendation to intelligent advisors. The focus on algorithmic accuracy, however, is questioned more and more. On the other hand, although the boundaries between the mechanisms are blurred increasingly, research on user-related aspects is still conducted separately in each area. In this position paper, we present a research agenda for providing a more holistic solution, in which users are supported with the right decision aid at the right time depending on personal characteristics and situational needs.
  • Textdokument
    Parametrizing Complex Co-Simulations to Support Decision Making in Mobility
    (INFORMATIK 2021, 2021) Stepien, Leonard; Köster, Frank
    The radical change in mobility calls for the simulative support of decision making for large-scale projects which asks for the simultaneous consideration of multiple stakeholders additionally. The major challenge in such simulation systems is nowadays the consistent and modifiable tool-independent parameterization to enable scenario analysis by systematic parameter variation and reach reliable support for those extensive decisions. Taking the example of public charging infrastructure, a holistic co-simulation framework is proposed, in which an approach for the central parameterization as well as the belonging scenario analysis tool take part. Necessary functionalities as well as the belonging interfaces are revealed. Proposing a loop of mainly getting and setting parameters automatically, a domain ontology is required to reach standardization of naming conventions. With this work, a research gap in the filled of co-simulation is addressed by proposing a framework which allows the central parametrization of such systems to enable decision support.
  • Zeitschriftenartikel
    Resource Planning in Disaster Response
    (Business & Information Systems Engineering: Vol. 57, No. 4, 2015) Schryen, Guido; Rauchecker, Gerhard; Comes, Tina
    Managing the response to natural, man-made, and technical disasters is becoming increasingly important in the light of climate change, globalization, urbanization, and growing conflicts. Sudden onset disasters are typically characterized by high stakes, time pressure, and uncertain, conflicting or lacking information. Since the planning and management of response is a complex task, decision makers of aid organizations can thus benefit from decision support methods and tools. A key task is the joint allocation of rescue units and the scheduling of incidents under different conditions of collaboration. The authors present an approach to support decision makers who coordinate response units by (a) suggesting mathematical formulations of decision models, (b) providing heuristic solution procedures, and (c) evaluating the heuristics against both current best practice behavior and optimal solutions. The computational experiments show that, for the generated problem instances, (1) current best practice behavior can be improved substantially by our heuristics, (2) the gap between heuristic and optimal solutions is very narrow for instances without collaboration, and (3) the described heuristics are capable of providing solutions for all generated instances in less than a second on a state-of-the-art PC.
  • Zeitschriftenartikel
    Robo-Advisory - Digitalization and Automation of Financial Advisory
    (Business & Information Systems Engineering: Vol. 60, No. 1, 2018) Jung, Dominik; Dorner, Verena; Glaser, Florian; Morana, Stefan
  • Zeitschriftenartikel
    Scheduling Flexible Demand in Cloud Computing Spot Markets
    (Business & Information Systems Engineering: Vol. 62, No. 1, 2020) Keller, Robert; H‰fner, Lukas; Sachs, Thomas; Fridgen, Gilbert
    The rapid standardization and specialization of cloud computing services have led to the development of cloud spot markets on which cloud service providers and customers can trade in near real-time. Frequent changes in demand and supply give rise to spot prices that vary throughout the day. Cloud customers often have temporal flexibility to execute their jobs before a specific deadline. In this paper, the authors apply real options analysis (ROA), which is an established valuation method designed to capture the flexibility of action under uncertainty. They adapt and compare multiple discrete-time approaches that enable cloud customers to quantify and exploit the monetary value of their short-term temporal flexibility. The paper contributes to the field by guaranteeing cloud job execution of variable-time requests in a single cloud spot market, whereas existing multi-market strategies may not fulfill requests when outbid. In a broad simulation of scenarios for the use of Amazon EC2 spot instances, the developed approaches exploit the existing savings potential up to 40 percent - a considerable extent. Moreover, the results demonstrate that ROA, which explicitly considers time-of-day-specific spot price patterns, outperforms traditional option pricing models and expectation optimization.