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- ZeitschriftenartikelDigital Nomads(Business & Information Systems Engineering: Vol. 62, No. 1, 2020) Richter, Shahper; Richter, Alexander
- ZeitschriftenartikelEfficient Model Points Selection in Insurance by Parallel Global Optimization Using Multi CPU and Multi GPU(Business & Information Systems Engineering: Vol. 62, No. 1, 2020) Ferreiro-Ferreiro, Ana Maria; GarcÌa-RodrÌguez, JosÈ Antonio; Souto, Luis A.; V·°zquez, CarlosIn the insurance sector, Asset Liability Management refers to the joint management of the assets and liabilities of a company. The liabilities mainly consist of the policies portfolios of the insurance company, which usually contain a large amount of policies. In the article, the authors mainly develop a highly efficient automatic generation of model points portfolios to represent much larger real policies portfolios. The obtained model points portfolio must retain the market risk properties of the initial portfolio. For this purpose, the authors propose a risk measure that incorporates the uncertain evolution of interest rates to the portfolios of life insurance policies, following Ferri (Optimal model points portfolio in life, 2019, arXiv:1808.00866 ). This problem can be formulated as a minimization problem that has to be solved using global numerical optimization algorithms. The cost functional measures an appropriate distance between the original and the model point portfolios. In order to solve this problem in a reasonable computing time, sequential implementations become prohibitive, so that the authors speed up the computations by developing a high performance computing framework that uses hybrid architectures, which consist of multi CPUs together with accelerators (multi GPUs). Thus, in graphic processor units (GPUs) the evaluation of the cost function is parallelized, which requires a Monte Carlo method. For the optimization problem, the authors compare a metaheuristic stochastic differential evolution algorithm with a multi path variant of hybrid global optimization Basin Hopping algorithms, which combines Simulated Annealing with gradient local searchers (Ferreiro et al. in Appl Math Comput 356:282-298, 2019a). Both global optimizers are parallelized in a multi CPU together with a multi GPU setting.
- ZeitschriftenartikelData Impact Analysis in Business Processes(Business & Information Systems Engineering: Vol. 62, No. 1, 2020) Tsoury, Arava; Soffer, Pnina; Reinhartz-Berger, IrisBusiness processes and their outcomes rely on data whose values are changed during process execution. When unexpected changes occur, e.g., due to last minute changes of circumstances, human errors, or corrections of detected errors in data values, this may have consequences for various parts of the process. This challenges the process participants to understand the full impact of the changes and decide on responses or corrective actions. To tackle this challenge, the paper suggests a semi-automated approach for data impact analysis. The approach entails a trans-formation of business process models to a relational database representation, to which querying is applied, in order to retrieve process elements that are related to a given data change. Specifically, the proposed method receives a data item (an attribute or an object) and information about the current state of process execution (in the form of a trace upon which an unexpected change has occurred). It analyzes the impact of the change in terms of activities, other data items, and gateways that are affected. When evaluating the usefulness of the approach through a case study, it was found that it has the potential to assist experienced process participants, especially when the consequences of the change are extensive, and its locus is in the middle of the process. The approach contributes both to practice with tool-supported guidance on how to handle unexpected data changes, and to research with a set of impact analysis primitives and queries.
- ZeitschriftenartikelDesigning Business Analytics Solutions(Business & Information Systems Engineering: Vol. 62, No. 1, 2020) Nalchigar, Soroosh; Yu, EricThe design and development of data analytics systems, as a new type of information systems, has proven to be complicated and challenging. Model based approaches from information systems engineering can potentially provide methods, techniques, and tools for facilitating and supporting such processes. The contribution of this paper is twofold. Firstly, it introduces a conceptual modeling framework for the design and development of advanced analytics systems. It illustrates the framework through a case and provides a sample methodological approach for using the framework. The paper demonstrates potential benefits of the framework for requirements elicitation, clarification, and design of analytical solutions. Secondly, the paper presents some observations and lessons learned from an application of the framework by an experienced practitioner not involved in the original development of the framework. The findings were then used to develop a set of guidelines for enhancing the understandability and effective usage of the framework.
- ZeitschriftenartikelScheduling Flexible Demand in Cloud Computing Spot Markets(Business & Information Systems Engineering: Vol. 62, No. 1, 2020) Keller, Robert; H‰fner, Lukas; Sachs, Thomas; Fridgen, GilbertThe 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.
- ZeitschriftenartikelHigh Performance Business Computing(Business & Information Systems Engineering: Vol. 62, No. 1, 2020) Schryen, Guido; Kliewer, Natalia; Fink, Andreas
- ZeitschriftenartikelInterview with Utz-Uwe Haus on"High Performance Computing in Economic Environments: Opportunities and Challenges"?(Business & Information Systems Engineering: Vol. 62, No. 1, 2020) Schryen, Guido; Kliewer, Natalia; Fink, Andreas