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Text analytics for co-creation in public sector organizations: a literature review-based research framework
Abstract
The public sector faces considerable challenges that stem from increasing external and internal demands, the need for diverse and complex services, and citizens’ lack of satisfaction and trust in public sector organisations (PSOs). An alternative to traditional public service delivery is the co-creation of public services. Data analytics has been fueled by the availability of immense amounts of data, including textual data, and techniques to analyze data, so it has immense potential to foster data-driven solutions for the public sector. In the paper, we systematically review the existing literature on the application of Text Analytics (TA) techniques on textual data that can support public service co-creation. In this review, we identify the TA techniques, the public services and the co-creation phase they support, as well as envisioned public values for the stakeholder groups. On the basis of the analysis, we develop a Research Framework that helps to structure the TA-enabled co-creation process in PSOs, increases awareness among public sector organizations and stakeholders on the significant potential of TA in creating value, and provides scholars with some avenues for further research.
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Authors (3)
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Aleksandra Revina magistr
- Brandenburg University of Applied Sciences, 14770 Brandenburg an der Havel, Germany
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Noella Edelmann PhD
- University for Continuing Education Krems, Krems an der Donau 3500, Austria
Cite as
Full text
- Publication version
- Accepted or Published Version
- DOI:
- Digital Object Identifier (open in new tab) 10.1007/s10462-025-11112-1
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Details
- Category:
- Articles
- Type:
- artykuły w czasopismach
- Published in:
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ARTIFICIAL INTELLIGENCE REVIEW
no. 58,
ISSN: 0269-2821 - Language:
- English
- Publication year:
- 2025
- Bibliographic description:
- Rizun N., Revina A., Edelmann N.: Text analytics for co-creation in public sector organizations: a literature review-based research framework// ARTIFICIAL INTELLIGENCE REVIEW -Vol. 58,iss. 4 (2025),
- DOI:
- Digital Object Identifier (open in new tab) 10.1007/s10462-025-11112-1
- Sources of funding:
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- Nie ma
- Verified by:
- Gdańsk University of Technology
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