Suchergebnisse

Dieser Sammelband stellt innovative Methoden, Konzepte und Werkzeuge zur Transformation klassischer Dienstleistungen zu sogenannten "Smart Services" vor. Durch Digitalisierung, Individualisierung und Kundenzentrierung entstehen flexible und zukunftsweisende Modelle, die branchenübergreifend als Schlüssel zu erfolgreichen Dienstleistungsinnovationen zu nutzen sind. Zahlreiche Beispiele verdeutlichen die Leistungsfähigkeit und die praktische Umsetzbarkeit der Smart Services als wesentliche Komponente neuer Geschäftsmodelle. Der Inhalt Digitale (R)evolution klassischer Dienstleistungen Service Engineering: Methoden und Werkzeuge Smart Services für die digitale Arbeit Mobility Servitization: Potenziale neuer Geschäftsmodelle. Die Zielgruppen Dozierende und Studierende der Betriebswirtschaftslehre, der Ingenieurwissenschaften und der Wirtschaftsinformatik, Entscheidungsträgerinnen und -träger aus Unternehmen mit Schwerpunkt Dienstleistungsmanagement. Die Herausgeber Univ.-Prof. Dr. Oliver Thomas ist Inhaber des Lehrstuhls für Informationsmanagement und Wirtschaftsinformatik an der Universität Osnabrück. Univ.-Prof. Dr. Markus Nüttgens ist Inhaber des Lehrstuhls für Wirtschaftsinformatik mit dem Schwerpunkt Betriebswirtschaftliche Standardsoftware und Informationsmanagement an der Universität Hamburg. Jun.-Prof. Dr. Michael Fellmann ist Inhaber des Lehrstuhls für Wirtschaftsinformatik, insbesondere Betriebliche Informationssysteme an der Universität Rostock.

In this thesis, we evaluate the complexity and understandability of compliance languages. First, to calculate the complexity, we apply established software metrics and interpret the results with respect to the languages' expressiveness. Second, to investigate the languages' understandability, we use a cognitive model of the human problem-solving process and analyze how efficiently users perform a compliance modeling task. Our results have theoretical and practical implications that give directions for the development of compliance languages, and rule-based languages in general.

In this thesis, we evaluate the complexity and understandability of compliance languages. First, to calculate the complexity, we apply established software metrics and interpret the results with respect to the languages' expressiveness. Second, to investigate the languages' understandability, we use a cognitive model of the human problem-solving process and analyze how efficiently users perform a compliance modeling task. Our results have theoretical and practical implications that give directions for the development of compliance languages, and rule-based languages in general.

Purpose
Patterns have proven to be useful for documenting general reusable solutions to a commonly occurring problem. In recent years, several different business process management (BPM)-related patterns have been published. Despite the large number of publications on this subject, there is no work that provides a comprehensive overview and categorization of the published business process model patterns. The purpose of this paper is to close this gap by providing a taxonomy of patterns as well as a classification of 89 research works.


Design/methodology/approach
The authors analyzed 280 research articles following a structured iterative procedure inspired by the method for taxonomy development from Nickerson et al. (2013). Using deductive and inductive reasoning processes embedded in concurrent as well as joint research activities, the authors created a taxonomy of patterns as well as a classification of 89 research works.


Findings
In general, the findings extend the current understanding of BPM patterns. The authors identify pattern categories that are highly populated with research works as well as categories that have received far less attention such as risk and security, the ecological perspective and process architecture. Further, the analysis shows that there is not yet an overarching pattern language for business process model patterns. The insights can be used as starting point for developing such a pattern language.


Originality/value
Up to now, no comprehensive pattern taxonomy and research classification exists. The taxonomy and classification are useful for searching pattern works which is also supported by an accompanying website complementing the work. In regard to future research and publications on patterns, the authors derive recommendations regarding the content and structure of pattern publications.

Effective self-management is crucial for a workforce with high levels of self-responsibility. Digital solutions enable highly scalable yet personalized support in everyday life. In particular, mobile devices and sensors enable new forms of individual tracking and personalized feedback. This dissertation investigates how technology can promote healthy and productive self-management. It explores the design space relevant for engineering occupational self-management assistance and showcases application areas. Especially, the support in managing personal energy as a key variable is demonstrated.

Effective self-management is crucial for a workforce with high levels of self-responsibility. Digital solutions enable highly scalable yet personalized support in everyday life. In particular, mobile devices and sensors enable new forms of individual tracking and personalized feedback. This dissertation investigates how technology can promote healthy and productive self-management. It explores the design space relevant for engineering occupational self-management assistance and showcases application areas. Especially, the support in managing personal energy as a key variable is demonstrated.

Advancing digitalization has shown the potential of so-called Quantified Vehicles for gathering valuable sensor data about the vehicle itself and its environment. Consequently, (vehicle) Data has become an important resource, which can pave the way to (Data-driven) Services. The (Data-driven Service) Ecosystem of actors that collaborate to ultimately generate services, has only shaped up in recent years. This cumulative dissertation summarizes the author's contributions and includes a synopsis as well as 14 peer-reviewed publications, which contribute to answer the three research questions.

Advancing digitalization has shown the potential of so-called Quantified Vehicles for gathering valuable sensor data about the vehicle itself and its environment. Consequently, (vehicle) Data has become an important resource, which can pave the way to (Data-driven) Services. The (Data-driven Service) Ecosystem of actors that collaborate to ultimately generate services, has only shaped up in recent years. This cumulative dissertation summarizes the author's contributions and includes a synopsis as well as 14 peer-reviewed publications, which contribute to answer the three research questions.