Sengewald T, Posselt T, Riemer M (2024)
Publication Type: Conference contribution
Publication year: 2024
Publisher: Association for Computing Machinery
City/Town: New York, NY
Pages Range: 12
Conference Proceedings Title: SIGMIS-CPR '23: Proceedings of the 2023 Computers and People Research Conference
ISBN: 979-8-4007-0094-1
In the current efforts of many cities, towns, and regions to digitally transform into smart municipalities, there is a paradigm shift from mere resident participation to co-creation. In co-creation, residents and municipal staff form a unified workforce, working on digital innovations to improve the community's well-being and quality of life. However, the ability to use and access IT is not the same across all resident groups. This raises the question of how the design of digital open innovation platforms affects the power dynamics in collaboration between different resident groups. In this research-in-progress paper, we combine Work Systems Theory and Gaventa's "power cube" to form a theoretical framework that can be used to analyze the power dynamics between different resident groups. Our study aims to help researchers and practitioners design better digital open innovation platforms that can empower marginalized groups. A better balance of power can ensure that all members of the municipal community benefit and do not become further marginalized.
APA:
Sengewald, T., Posselt, T., & Riemer, M. (2024). Who's got the power?: Examining the impact of digital open innovation platforms on social power dynamics in smart municipalities. In SIGMIS-CPR '23: Proceedings of the 2023 Computers and People Research Conference (pp. 12). Pomona, CA, US: New York, NY: Association for Computing Machinery.
MLA:
Sengewald, Timon, Tim Posselt, and Manuel Riemer. "Who's got the power?: Examining the impact of digital open innovation platforms on social power dynamics in smart municipalities." Proceedings of the SIGMIS-CPR '23: 2023 Computers and People Research Conference, Pomona, CA New York, NY: Association for Computing Machinery, 2024. 12.
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