Classification is an essential approach in business model research. Empirical classifications, termed taxonomies, are widespread in and beyond Information Systems (IS) and enjoy high popularity as both stand-alone artifacts and the foundation for further application. In this article, we focus on the study of empirical business model taxonomies for two reasons. Firstly, as these taxonomies serve as a tool to store empirical data about business models, we investigate their coverage of different industries and technologies. Secondly, as they are emerging artifacts in IS research, we aim to strengthen rigor in their design by illustrating essential design dimensions and characteristics. In doing this, we contribute to research and practice by synthesizing the diffusion of business model taxonomies that helps to draw on the available body of empirical knowledge and providing artifact-specific guidance for building taxonomies in the context of business models.
The ever-growing amounts of data offer companies many opportunities to exploit them. Resulting datadriven services hold great potential for creating unique value for customers and the achievement of competitive advantages. Nevertheless, especially companies in the industrial environment struggle to implement successful data-driven service innovations. Surprisingly, there is a lack of scientific research addressing this issue. Thus, our research generates design principles for data-driven services to aid in their development. For this purpose, we present a qualitative interview study with experts in different lines of businesses among the industry sector, holding varying positions and roles in service systems. Through practical examples, we show which challenges exist in the development and use of datadriven services. On this basis, we derive design principles to help understanding data-driven services and to overcome difficulties identified in practice, notably, that allows practitioners to develop new services or redesign existing ones.
Forschungsbereiche der Datenökonomie Durch die rasant steigende Datenmenge ergeben sich viele Möglichkeiten, neue datengetriebene Geschäftsmodelle zu entwickeln. Die Datenökonomie gewinnt immer mehr an Bedeutung. Damit das ökonomische Potenzial ausgeschöpft werden kann, ist es elementar, dass genügend Fachkräfte verfügbar sind. Wichtige Forschungsbereiche der Datenökonomie sind die Bedeutung von Kooperationen und Wissen für die Entwicklung neuer Geschäftsmodelle, Daten und Algorithmen sowie das Branchencluster des Gesundheitswesens.
The ongoing shift to solution-oriented business models and growing digitalization lead to an increasing importance of services in manufacturing industry. Machine manufacturers in particular struggle to grasp the extent of transformational impact enabled or required by service developments. This is due to a narrow perspective on specific service characteristics, but not on the entire service process. Therefore, a service-dominant perspective is essential in the value creation of manufacturers, placing relevant service phases in the foreground. However, the process-related character of services is rarely considered in the literature. For this purpose, this study provides a taxonomy that classifies services based on phases. In addition to a systematic literature analysis, this study builds on practical insights by conducting eight expert interviews. The applicability and usefulness of the taxonomy is then demonstrated through exemplary application based on a case study, enabling practitioners to adopt a phase-oriented perspective on digital servitization.
In der Ko-Produktion industrieller Dienstleistungen verbergen sich enorme Potenziale. Es fehlt jedoch an einer einheitlichen Sprache, die eine effiziente und sichere Vernetzung von unterschiedlichen Unternehmen auf Netzwerkebene ermöglicht. Der Beitrag präsentiert den Lösungsansatz der Sealed Services. Unter Wahrung der Datensicherheit, -souveränität und -integrität können hierdurch kooperative Dienste über das Internet, vor allem durch kleine und mittlere Unternehmen, eigenständig entwickelt und umgesetzt werden.*)
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.