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Cloud Computing is a topic that has gained momentum in the last years. Current studies show that an increasing number of companies is evaluating the promised advantages and considering making use of cloud services. In this paper we investigate the phenomenon of cloud computing and its importance for the operation of ERP systems. We argue that the phenomenon of cloud computing could lead to a decisive change in the way business software is deployed in companies. Our reference framework contains three levels (IaaS, PaaS, SaaS) and clarifies the meaning of public, private and hybrid clouds. The three levels of cloud computing and their impact on ERP systems operation are discussed. From the literature we identify areas for future research and propose a research agenda.
As Enterprise 2.0 (E2.0) initiatives are gradually moving out of the early experimentation phase it is time to focus greater attention on examining the structures, processes and operations surrounding E2.0 projects. In this paper we present the findings of an empirical study to investigate and understand the reasons for initiating E2.0 projects and the benefits being derived from them. Our study comprises seven in-depth case studies of E2.0 implementations. We develop a classification and means of visualising the scope of E2.0 initiatives and use these methods to analyse and compare projects.
Our findings indicate a wide range of motivations and combinations of technology in use and show a strong emphasis towards the content management functionality of E2.0 technologies.
Ziel dieser Forschungsarbeit ist die Auswahl und Evaluierung von Open-Source ERPSystemen auf effiziente Anwendbarkeit in Unternehmen zum Zwecke des Aufbaus eines "ERP-Future-Labs", in welchem mittelständische Handelsunternehmen das/die installierte(n) System(e) testen können. Den Projektabschluss bildet hierbei die Installation eines lauffähigen Systems, auf welchem die vom Auftraggeber vorgegebenen Geschäftsprozesse abgewickelt werden können. Ferner sollen die Auftraggeber auf dem System geschult, eine Dokumentation der Software (Installation/Bedienung) und des Projekts erstellt werden.
With the ongoing process of building business networks in today- economy, business to-business integration (B2B Integration) has become a strategic tool for utilizing and optimizing information exchange between business partners. Industry and academia have made remarkable progress in implementing and conceptualizing different kinds of electronic inter-company relationships in the last years. Nevertheless, academic findings generally focus exclusively on certain aspects of the research object, e.g. document standards, process integration or other descriptive criteria. Without arncommon framework these results stay unrelated and their mutual impact on each other remains largely unexplained. In this paper we explore motivational factors of B2B integration in practice. In a research project using a uniform taxonomy (eXperience methodology) we classified real-world B2B integration projects from a pool of over 400 case studies using a pre-developed framework for integration scenarios. The result of our partly exploratory research shows the influence of the role of a company in the supply chain and its motive to invest in a B2B solution.
Enterprise Collaboration Systems (ECS) sind essentielle Werkzeuge für die Unterstützung der digitalen Zusammenarbeit und ad hoc Projektarbeit in Unternehmen. Mit der zunehmenden Nutzung von ECS steigen auch die Bedeutung und der Bedarf an Analysen zur Schaffung eines verbesserten Verständnisses von digitaler Arbeit. Da Kollaboration sich regelmäßig über mehr als ein System erstreckt, stellt die Heterogenität der Daten verschiedener Systeme für Analysen eine Herausforderung dar, insbesondere weil plattformübergreifende Nutzungsmuster nicht ohne Weiteres nachverfolgbar und vergleichbar sind. Daher wurde die „Collaborative Actions on Documents Ontology“ (ColActDOnt) entwickelt, um Konzepte aus ECS (z. B. Events und Dokumente) einheitlich zu beschreiben. Basierend auf der ColActDOnt wurde ein Datastore implementiert, in welchem die Daten verschiedener Systeme in der Struktur der Ontologie gespeichert werden. Durch den ontologiebasierten Datastore stehen die Daten für Analysen in einheitlicher Form zur Verfügung. In die Datenebene wurden Daten aus dem ECS HCL Connections (CNX), welches somit das initiale Quellsystem darstellt, importiert. Mittels der ColActDOnt wurde außerdem eine abstrakte Ontologieebene mit den Elementen der Ontologie geschaffen. Die Elemente beider Ebenen sind über Beziehungen innerhalb einer Graphdatenbank miteinander und untereinander verknüpft.
Der ontologiebasierte Datenzugriff ermöglicht es dem Benutzer ohne Kenntnisse über die Datenstrukturen des Quellsystems, lediglich mit Domänenwissen über die ColActDOnt, Inhalte abzufragen.
Der Datastore ist als Graphdatenbank (Neo4j) implementiert und somit können Abfragen nativ als Graphenstrukturen visualisiert werden. Weiterhin kann der Prototyp an Business Intelligence Tools wie Microsoft PowerBI angebunden werden und bietet somit die Möglichkeit für tiefergehende Analysen. Die erste Version des Datastores stellt einen wichtigen Schritt in Richtung der Harmonisierung von Trace Data aus ECS dar. In Zukunft sollen weitere Kollaborationssysteme an den Datastore angeschlossen werden, um systemübergreifende Analysen von komplexen Kollaborationsplattformen zu ermöglichen.
The literature contains very few publications on the application of Process Mining methods for the analysis of event logs in Enterprise Collaboration Systems (ECS). This is not surprising because the analysis of digital support for collaborative work is extremely intricate due to various challenges relating to a lack of data access, poor data quality, unstructured processes and a lack of descriptive models. This article reports on the findings from an Action Design Research (ADR) project. The ADR team had access to a large instance of an operational ECS with more than 3000 users. The event log contains several million entries. Together with the platform’s operating team, intensive research was carried out over a period of six years on ways of analysing user activities on the platform. Several cycles were run to develop new methods and computational techniques to decipher the event logs and meaningfully describe the processes recorded in them. Thanks to the close collaboration between the researchers and the operators of the collaboration platform, it was possible to compare the real-world processes carried out in the platform with the processes discovered using a novel method for Social Process Mining (SPM). The result is a pattern analysis that discovers patterns in processes that have a high degree of correspondence with the real-world scenes of collaborative work. The research work has now reached a point where other software products are included (multi-system analysis) and a catalogue of collaborative work situations (scenes) has been developed to describe the process patterns that result from the Process Mining and graph-based analysis techniques.