Data-driven business models and professional services firms: A strategic framework and transitionary pathways

, , , & (2019) Data-driven business models and professional services firms: A strategic framework and transitionary pathways. In Xu, Jennifer J., Zhu, Bin, Liu, Xiao, Shaw, Michael J., Zhang, Han, & Fan, Ming (Eds.) The Ecosystem of e-Business: Technologies, Stakeholders, and Connections: 17th Workshop on e-Business, WeB 2018, Revised Selected Papers (Lecture Notes in Business Information Processing, Volume 357). Springer, Switzerland, pp. 26-38.

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Description

Many organizations and industries are undergoing a significant transformation due to digital technologies. In our research, we study digital business model innovation in relation to Professional Services Firms (PSFs). In this conceptual paper, we contrast the traditional, human- centered, knowledge-intensive business model of PSFs with the new, computer-centered, data-driven business model that is developing due to the rise of big data, advanced data analytics and artificial intelligence. To better understand if, when and how data-driven business models may disrupt PSFs, we provide a strategic framework for identifying and analyzing the options for PSFs in relation to the nature and scope of their value proposition. We suggest sever-al possible transitionary pathways using digital technology for augmentation or automation and the need so scale across services and industries. As such this paper provides valuable insights to academics and practitioners into how PSFs might develop new business models given the nature of their service offerings and industry positions.

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ID Code: 131391
Item Type: Chapter in Book, Report or Conference volume (Conference contribution)
Series Name: Lecture Notes in Business Information Processing
ORCID iD:
Fielt, Erwinorcid.org/0000-0003-3923-4667
Desouza, Kevinorcid.org/0000-0002-4734-3081
Gable, Guyorcid.org/0000-0003-0828-1268
Measurements or Duration: 13 pages
Keywords: Business Models, Data, Data-Driven, Data-Driven Business Models, Digital, Digital Innovation, Digital Transformation, Knowledge, Knowledge-intensive, Knowledge-intensive business services, Professional services firms, Strategic Innovation
DOI: 10.1007/978-3-030-22784-5_3
ISBN: 978-3-030-22783-8
Pure ID: 33421629
Divisions: Past > QUT Faculties & Divisions > QUT Business School
Past > Institutes > Institute for Future Environments
Past > QUT Faculties & Divisions > Science & Engineering Faculty
Current > Schools > School of Management
Copyright Owner: 2019 Springer Nature Switzerland AG
Copyright Statement: This work is covered by copyright. Unless the document is being made available under a Creative Commons Licence, you must assume that re-use is limited to personal use and that permission from the copyright owner must be obtained for all other uses. If the document is available under a Creative Commons License (or other specified license) then refer to the Licence for details of permitted re-use. It is a condition of access that users recognise and abide by the legal requirements associated with these rights. If you believe that this work infringes copyright please provide details by email to qut.copyright@qut.edu.au
Deposited On: 15 Jul 2019 01:06
Last Modified: 02 Mar 2024 02:38