Realizing New Data-Driven Business Models by Launching Containers into the Cloud

Mathias Zink, Victor Naumann (), Andreas Harth () and Alexander Pflaum ()
Additional contact information
Mathias Zink: Fraunhofer Institute for Integrated Circuits
Victor Naumann: Fraunhofer Institute for Integrated Circuits
Andreas Harth: Friedrich-Alexander-University Erlangen-Nürnberg, Chair of Technical Information Systems
Alexander Pflaum: Otto-Friedrich-Universität Bamberg, Chair for Supply Chain Management

A chapter in Digital Business Models in Industrial Ecosystems, 2021, pp 155-170 from Springer

Abstract: Abstract Data-driven business models are modern ways for innovation in traditional environments. The vision of the Internet of Things (IoT), by making products smart and leveraging the data into services, is a modern paradigm of value creation. A representative case study evolved business models for industrial containers in the automotive industry into a cloud-based data-driven business model. This publication outlines the background for industrial containers and provides insights into the relevant technological architectures. Additionally, the data-driven business model and the expansion of the ecosystem are outlined. Thereby this publication enhances the necessary interdisciplinary understanding of business model research and information science.

Date: 2021
References: Add references at CitEc
Citations:

There are no downloads for this item, see the EconPapers FAQ for hints about obtaining it.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:spr:fuobcp:978-3-030-82003-9_10

Ordering information: This item can be ordered from
http://www.springer.com/9783030820039

DOI: 10.1007/978-3-030-82003-9_10

Access Statistics for this chapter

More chapters in Future of Business and Finance from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().