Within a consideration of cost effectiveness the evaluation of design science research artifacts is of major importance. In the past, a plenitude of approaches has been developed for this purpose -partly artifact-specific, partly artifact-neutral. Nonetheless, there is a lack of a comprehensive overview over existing methods as well as a systemization of those with regard to fundamental structuring criteria. The paper at hand surveys existing methods and introduces a framework that equally supports the designer and the user of artifact evaluation approaches. Subsequent to the embedding of the framework into the design science research process two exemplary application scenarios are described.
The quality of master data has become an issue of increasing prominence in companies. One reason for that is the growing number of regulatory and legal provisions companies need to comply with. Another reason is the growing importance of information systems supporting decision-making, requiring master data that is up-to-date, accurate and complete. While improving and maintaining master data quality is an organizational task that cannot be encountered by simply implementing a suitable software system, system support is mandatory in order to be able to meet challenges efficiently and make for good results. This paper describes the design process toward a functional reference model for master data quality management (MDQM). The model design process spanned several iterations comprising multiple design and evaluation cycles, including the model's application in a participative case study at consumer goods manufacturer Beiersdorf. Practitioners may use the reference model as an instrument for the analysis, design and implementation of a company's MDQM system landscape. Moreover, the reference model facilitates evaluation of software systems and supports company-internal and external communication. From a scientific perspective, the reference model is a design artifact; hence it represents a theory for designing information systems in the area of MDQM.
A number of business requirements (e.g. compliance with regulatory and legal provisions, diffusion of global standards, supply chain integration) are forcing consumer goods manufacturers to increase their efforts to provide product data (e.g. product identifiers, dimensions) at business-to-business interfaces timely and accurately.
Abstract-Service providers have to monitor the quality of offered services and to ensure the compliance of service levels provider and requester agreed on. Thereby, a service provider should notify a service requester about violations of service level agreements (SLAs). Furthermore, the provider should point to impacts on affected processes in which services are invoked. For that purpose, a model is needed to define dependencies between quality of processes and quality of invoked services. In order to measure quality of services and to estimate impacts on the quality of processes, we focus on measurable metrics related to functional elements of processes, services as well as components implementing services. Based on functional dependencies between processes and services of a service-oriented architecture (SOA), we define metric dependencies for monitoring the impact of quality of invoked services on quality of affected processes. In this paper we discuss how to derive metric dependency definitions from functional dependencies by applying dependency patterns, and how to map metric and metric dependency definitions to an appropriate monitoring architecture.
Um aktuellen Herausforderungen weltweiter Märkte begegnen zu können, brauchen Unternehmen ein einheitliches Verständnis ihrer Geschäftsobjekte. Einerseits sind regionale Spezifika zu unterstützen, um weltweit agieren und z.B. günstige Produktionsstandorte nutzen zu können. Andererseits sind einheitliche Datenstrukturen für unternehmensweite Analysen erforderlich, um z.B. globale Einkaufsstrategien umsetzen und vorteilhafte Einkaufskonditionen aushandeln zu können. Zusätzlich müssen Geschäftsobjekte neue Anforderungen seitens des Markts und regulierender Institutionen möglichst schnell abbilden-und das weltweit und konsistent. Ziel eines effektiven Managements von Geschäftsobjekt-Metadaten ist somit die Bereitstellung aktueller, detaillierter, flexibler und gleichzeitig unternehmensweit konsistenter Metadaten (z.B. technische und fachliche Spezifikationen, anwendungsspezifische Informationen zur korrekten Nutzung). Zur Unterstützung dieser Aufgabe stellt der Beitrag das Konzept eines fachlichen Metadatenkatalogs vor und diskutiert einen Wiki-basierten Prototyp, der gemeinsam mit dem Unternehmen Bayer CropScience realisiert wurde. Die Evaluation des Prototyps zeigt, dass sich insbesondere semantische Wikis gut zur Realisierung eines fachlichen Metadatenkatalogs eignen. Inhaltsübersicht 1 Metadaten zur Beschreibung von Geschäftsobjekten 2 Management fachlicher Metadaten mit Wikis 2.1 Wikis als Kollaborationsplattform in Unternehmen 2.2 Allgemeine Anforderungen an ein Business Data Dictionary 3 Ein Wiki als Business Data Dictionary bei Bayer CropScience 3.1 Fachliches Metadatenmanagement bei Bayer CropScience 3.2 Anforderungserhebung 3.3 Implementierung als semantisches Wiki 3.4 Evaluation und Szenariotests 4 Ergebnisse der Nutzung des Prototyps und weiterer Forschungsbedarf 5 Literatur
Daten sind die Grundlage der digitalen Wirtschaft, jedoch führen „Datensilos“ zu Herausforderungen in Bezug auf Datenpflege und -qualität. Ein innovativer Ansatz zur Lösung dieses Problems besteht darin, Prinzipien der Sharing Economy auf Daten zu übertragen. Das Beispiel der CDQ Data Sharing Community in diesem Artikel zeigt, wie Unternehmen ihre Geschäftspartnerdaten gemeinsam bewirtschaften und welche Nutzeffekte daraus entstehen.
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