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How to Design User-Centered Decision Support Systems in Public Budgeting? Guidelines and a Web-Based Prototype With First Insights From a Mixed-Methods Study

Published: 15 September 2022 Publication History

Abstract

Due to increasing complexity and high political importance, public budgeting should be technically supported in the best way possible. In this paper, the use of a decision support prototype is explored to assist stakeholders in the context of public budgeting, to address the questions of what information is needed to facilitate decisions, and how to design and embed such a system. A user-centered approach was chosen, including a context analysis, qualitative interviews, and a shortened design sprint. From the insights gained, design implications as well as two hands-on application scenarios were derived. Based on this, a high-fidelity prototype was developed with modern web technologies. Afterwards, a summative evaluation was conducted in an interactive and cohesive online survey where participants could interact directly with the embedded prototype. The results show that the majority of participants expect such a system to have a positive impact on decision-making during budget preparations. Furthermore, most of the defined design requirements were fulfilled and the usability as well as the visual aesthetics of the prototype, were evaluated in a positive manner. The design implications provide a profound basis for further research and design iterations.

References

[1]
Bangor, A. 2009. Determining What Individual SUS Scores Mean: Adding an Adjective Rating Scale. J. Usability Studies. 4, 3 (May 2009), 114–123.
[2]
Bennett, N. and Lemoine, G.J. 2014. What a difference a word makes: Understanding threats to performance in a VUCA world. Business Horizons. 57, 3 (May 2014), 311–317.
[3]
Brooke, J. 1996. SUS: A “Quick and Dirty” Usability Scale. Usability Evaluation In Industry. P.W. Jordan, eds. Taylor & Francis.
[4]
Carter, S. and Nielsen, M. 2017. Using Artificial Intelligence to Augment Human Intelligence. Distill. 2, 12 (Dec. 2017), 10.23915/distill.00009. https://doi.org/10.23915/distill.00009.
[5]
Dhungel, A.-K. 2021. Too Bureaucratic to Flexibly Learn About AI? The Human-Centered Development of a MOOC on Artificial Intelligence in and for Public Administration. Mensch und Computer 2021 (Ingolstadt Germany, Sep. 2021), 563–567. DOI https://dx.doi.org/10.1145/3473856.3473998
[6]
Eid, M. 2017. Statistik und Forschungsmethoden: mit Online-Materialien. Beltz.
[7]
Fernandez-Cortez, V. 2020. Can Artificial Intelligence Help Optimize the Public Budgeting Process? Lessons about Smartness and Public Value from the Mexican Federal Government. 2020 Seventh International Conference on eDemocracy & eGovernment (ICEDEG) (Buenos Aires, Argentina, Apr. 2020), 312–315. https://doi.org/10.1109/ICEDEG48599.2020.9096745
[8]
Franke, T. 2019. A Personal Resource for Technology Interaction: Development and Validation of the Affinity for Technology Interaction (ATI) Scale. International Journal of Human–Computer Interaction. 35, 6 (Apr. 2019), 456–467.
[9]
Hebbar, A. 2017. Augmented intelligence: Enhancing human capabilities. 2017 Third International Conference on Research in Computational Intelligence and Communication Networks (ICRCICN) (Kolkata, Nov. 2017), 251–254. https://doi.org/10.1109/ICRCICN.2017.8234515
[10]
Herczeg, M. 2018. Software-Ergonomie: Theorien, Modelle und Kriterien für gebrauchstaugliche interaktive Computersysteme. De Gruyter Oldenbourg. https://doi.org/10.1515/9783110446869
[11]
Kirste, M. 2019. Augmented Intelligence – Wie Menschen mit KI zusammen arbeiten. Künstliche Intelligenz: Technologie | Anwendung | Gesellschaft. V. Wittpahl, ed. Springer Berlin Heidelberg. 58–71. https://doi.org/10.1007/978-3-662-58042-4_4
[12]
Knapp, J. 2018. Sprint: wie man in nur fünf Tagen neue Ideen testet und Probleme löst. REDLINE Verlag.
[13]
Kuckartz, U. 2018. Qualitative Inhaltsanalyse: Methoden, Praxis, Computerunterstützung. Beltz Juventa.
[14]
von Lucke, J. and Etscheid, J. 2020. Künstliche Intelligenz im öffentlichen Sektor. HMD Praxis der Wirtschaftsinformatik. 57, 1 (Feb. 2020), 60–76.
[15]
MAXQDA | Die #1 Software für Qualitative & Mixed-Methods-Forschung: 2022. https://www.maxqda.de/. Accessed: 2022-01-11.
[16]
Moshagen, M. and Thielsch, M.T. 2010. Facets of visual aesthetics. International Journal of Human-Computer Studies. 68, 10 (Oct. 2010), 689–709.
[17]
Papagiannis, F. 2020. An intelligent environmental plan for sustainable regionalisation policies: The case of Ukraine. Environmental Science & Policy. 108, (Jun. 2020), 77–84.
[18]
Rosson, M.B. and Carroll, J.M. 2002. Usability engineering: scenario-based development of human-computer interaction. Academic Press.
[19]
Schwarting, G. 2010. Der kommunale Haushalt: Haushaltssteuerung, Doppik, Finanzpolitik. E. Schmidt.
[20]
Valle-Cruz, D. 2022. From E-budgeting to smart budgeting: Exploring the potential of artificial intelligence in government decision-making for resource allocation. Government Information Quarterly. 39, 2 (Apr. 2022), 101644.
[21]
Valle-Cruz, D. 2020. Towards Smarter Public Budgeting? Understanding the Potential of Artificial Intelligence Techniques to Support Decision Making in Government. The 21st Annual International Conference on Digital Government Research (Seoul Republic of Korea, Jun. 2020), 232–242. https://doi.org/10.1145/3396956.3396995
[22]
Wessel, D. 2020. Affinity for technology interaction and fields of study: implications for human-centered design of applications for public administration. Proceedings of the Conference on Mensch und Computer (Magdeburg Germany, Sep. 2020), 383–386. https://doi.org/10.1145/3404983.3410020
[23]
Wirtz, B.W. 2021. Artificial Intelligence in the Public Sector - a Research Agenda. International Journal of Public Administration. (Aug. 2021), 1–26.
[24]
Wirtz, B.W. and Weyerer, J.C. 2019. Künstliche Intelligenz im öffentlichen Sektor: Anwendungen und Herausforderungen. Verwaltung & Management. 25, 1 (2019), 37–44.

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MuC '22: Proceedings of Mensch und Computer 2022
September 2022
624 pages
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Association for Computing Machinery

New York, NY, United States

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Published: 15 September 2022

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Author Tags

  1. Artificial Intelligence
  2. Decision Support System
  3. Knowledge Management
  4. Public Back Office
  5. Public Budget Preparation

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MuC '22
MuC '22: Mensch und Computer 2022
September 4 - 7, 2022
Darmstadt, Germany

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