Open this publication in new window or tab >>2023 (English)In: Reconfiguration of Business Models and Ecosystems: Decoupling and Resilience / [ed] Svetla T. Marinova; Marin A. Marinov, New York: Routledge, 2023, 1, p. 204-235Chapter in book (Refereed)
Abstract [en]
This chapter researches the reconfiguration of business models and ecosystems in relation to decoupling and resilience in the context of data-driven technologies via conducting a systematic literature review (SLR). New data-driven technologies have been largely introduced to different sectors. Digitalisation may lead to disruptive changes in any industry, including creating or entering new business models, lowering or changing entry barriers into markets and enabling the breakup of sectorial silos. Although the COVID-19 pandemic accelerated significantly the digitalisation of the healthcare sector, innovation adoption in the sector proceeds slower than in most other industries. This chapter reviews systematically the existing literature on this area and develops a research agenda aiming at answering the pre-set research question: To address the research question, an SLR methodology has been applied to provide insights, critical reflections, managerial implications and research road maps for future research. The chapter identifies the potential benefits of the use of data-driven technology in healthcare at organisational, institutional, ethical and macro-level dimensions. It discusses the adoption of digitalisation and healthcare management practices to enhance data-driven outcomes. Based on the conducted literature review and the bibliometric analysis of articles included in the chapter, an integrative conceptual framework for digital healthcare is suggested. © 2023 selection and editorial matter, Svetla T. Marinova and Marin A. Marinov; individual chapters, the contributors
Place, publisher, year, edition, pages
New York: Routledge, 2023 Edition: 1
National Category
Production Engineering, Human Work Science and Ergonomics
Identifiers
urn:nbn:se:hh:diva-50020 (URN)2-s2.0-85147936678 (Scopus ID)978-1-032-35402-6 (ISBN)978-1-003-32673-1 (ISBN)
2023-02-242023-02-242023-02-24Bibliographically approved