A digital business ecosystem maturity model for personal service firms

Authors: Ricardo Guerrero (Jacobs University Bremen gGmbH), Christoph Lattemann (Jacobs University Bremen gGmbH), Simon Michalke (Jacobs University Bremen gGmbH), Dominik Siemon (LUT University)

Handbook on Digital Business Ecosystems edited by Sabine Baumann, published in 2022, Edward Elgar Publishing Ltd
This is a draft chapter. The final version is available in Handbook on Digital Business Ecosystems edited by Sabine Baumann, published in 2022, Edward Elgar Publishing Ltd https://doi.org/10.4337/9781839107191.00026

Abstract: Personal services can be found in sectors such as education, retail, hospitality, and craftsmanship. As of today, personal service firms lack the know-how and experience on how to implement processes and practices to effectively build digital business ecosystems. This becomes an obstacle for these kinds of firms to overcome the challenges of todays digital age. Based on the guidelines of Design Science Research (DSR), we address this gap by proposing a maturity model, which offers specific guidance for this sector to be able to achieve the transition from analog to digital. The design of the model is grounded in a systematic literature review, semi-structured interviews, and a validation test involving company representatives from the field of personal services, business ecosystems, and digitalization. Results revealed a series of dimensions, capabilities, and maturity stages indicating an evolutionary path towards digital maturity for personal service firms. Thus, leading them to achieve a digital business ecosystem.

Submitted to arXiv on 02 Nov. 2022

Explore the paper tree

Click on the tree nodes to be redirected to a given paper and access their summaries and virtual assistant

Also access our AI generated Summaries, or ask questions about this paper to our AI assistant.

Beta

Look for similar papers (in beta version)

By clicking on the button above, our algorithm compares the title and abstract of this paper with all the papers of the same arXiv category that we have summarized, and finds the closest ones. You can rerun it from time to time: the results improve as our database grows.