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Cited by 64Scheduling and Timetabling SolutionsHealthcare Operations and Scheduling OptimizationSleep and Work-Related Fatigue

Fairness and Decision-making in Collaborative Shift Scheduling Systems

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Uhde, Alarith, Schlicker, Nadine, Wallach, Dieter P., Hassenzahl, Marc·2020·Proceedings of the 2020 CHI Conference on Human Factors in Computing Systems
DOI 10.1145/3313831.3376656
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Abstract

The strains associated with shift work decrease healthcare workers' well-being. However, shift schedules adapted to their individual needs can partially mitigate these problems. From a computing perspective, shift scheduling was so far mainly treated as an optimization problem with little attention given to the preferences, thoughts, and feelings of the healthcare workers involved. In the present study, we explore fairness as a central, human-oriented attribute of shift schedules as well as the scheduling process. Three in-depth qualitative interviews and a validating vignette study revealed that while on an abstract level healthcare workers agree on equality as the guiding norm for a fair schedule, specific scheduling conflicts should foremost be resolved by negotiating the importance of individual needs. We discuss elements of organizational fairness, including transparency and team spirit. Finally, we present a sketch for fair scheduling systems, summarizing key findings for designers in a readily usable way.

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  • Algorithmic scheduling is negatively associated with social support.

    “Social support (-)”

    From Algorithms as work designers: How algorithmic management influences the design of jobs (2022) · cites this paper as Uhde et al. (2020)

    In “Data souvereignity and transparency” (page unavailable), the paper says that algorithmic scheduling systems, if designed correctly, can facilitate pro-social behavior and may benefit team climate. It does not report a negative association with social support; its discussion points in the opposite direction. (LLM, conf=0.78)

    Checked by a reasoning model — may be wrong.

    Experimental — accuracy not yet measured

  • In complex schedule-making contexts such as healthcare, inability to intervene in automated scheduling decisions can alter social support by removing flexibility to exchange shifts or make friendly schedule arrangements.

    “Also, in complex schedule-making contexts such as healthcare, the inability to intervene in automated scheduling decisions can alter social support in taking away the flexibility for team members to exchange shifts or to make friendly schedule arrangements amongst them (Uhde et al., 2020).”

    From Algorithms as work designers: How algorithmic management influences the design of jobs (2022) · cites this paper as Uhde et al., 2020

    The Summary and Discussion advocates worker involvement over fully automated decisions, and the Interpersonal Justice and Cultivate a positive team spirit sections link cooperative relationships to shift swaps. But the paper does not say that inability to intervene removes the ability to exchange shifts or make informal arrangements; the Limitations section notes that workers adapt even presumably fixed schedules to their needs. No page numbers were available in our copy. (LLM, conf=0.82)

    Experimental — accuracy not yet measured

  • Instead of hampering social support between nurses, the easiness to use the system to swap shifts in order to accommodate coworkers triggered a positive team climate and a reduction of interpersonal conflicts, increasing social support.

    “Their findings indicate that, instead of hampering social support between nurses, the easiness to use the system to swap shifts in order to accommodate coworkers triggered a positive team climate and a reduction of interpersonal conflicts, increasing social support.”

    From Algorithms as work designers: How algorithmic management influences the design of jobs (2022) · cites this paper as Uhde et al., 2020

    In “Data souvereignity and transparency” (page not provided), the paper suggests that a scheduling system could facilitate pro-social behavior and may benefit team climate. It does not report that an easy-to-use system actually reduced interpersonal conflicts or increased social support. “Cultivate a positive team spirit” instead reports that existing respect and empathy increased willingness to swap shifts. (LLM, conf=0.88)

    Experimental — accuracy not yet measured

  • Uhde et al. (2020) provided evidence for the beneficial role of a collaborative automated scheduling system among nursing teams.

    “In the same vein, Uhde et al. (2020) provided evidence for the beneficial role of a collaborative automated scheduling system among nursing teams.”

    From Algorithms as work designers: How algorithmic management influences the design of jobs (2022) · cites this paper as Uhde et al., 2020

    The Summary and Discussion (page not available) reports that healthcare workers preferred mutual decision-making supported by an algorithm over decisions made by a fully autonomous algorithm. The Participants section identifies registered nurses in Study 1. But the Limitations section says the proposed system had not been implemented, so the paper does not demonstrate benefits from a deployed collaborative automated scheduling system among nursing teams. (LLM, conf=0.88)

    Experimental — accuracy not yet measured

  • Limitation of workers' voice in scheduling can occur through direct scheduling decisions or through scheduling nudging.

    “This can occur through direct scheduling decisions (Uhde, Schlicker, Wallach, & Hassenzahl, 2020), or through scheduling nudging, particularly common in gig work (Gal et al., 2020;Mateescu & Nguyen, 2019a).”

    From Algorithms as work designers: How algorithmic management influences the design of jobs (2022) · cites this paper as Uhde, Schlicker, Wallach, & Hassenzahl, 2020

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Cited by

Sorted by citations

Authors
Uhde, A., Schlicker, N., Wallach, D. P., & Hassenzahl, M.
Affiliations
  • University of Siegen (DE)
  • Ergosign GmbH, Saarbrücken, Germany
ORCID
Venue
Proceedings of the 2020 CHI Conference on Human Factors in Computing Systems
Publisher
ACM
Published
2020-04-21
Pages
1-13
DOI
10.1145/3313831.3376656
OpenAlex
W3003107055
Cited by
64
References
3
Citations by year
2026: 7 · 2025: 9 · 2024: 9 · 2023: 15 · 2022: 11 · 2021: 12 · 2020: 1
FWCI
13.24
Type
conference paper
Language
en
Open access
Licence
Locations
  • CHI Conference on Human Factors in Computing Systems (publishedVersion, cc-by)
  • arXiv (Cornell University) (submittedVersion)
  • arXiv (Cornell University)
Funders
  • European Social Fund (02L15A216)
  • Bundesministerium für Bildung und Forschung (02L15A216)
Topics
  • Social Sciences › Decision Sciences › Management Science and Operations Research › Scheduling and Timetabling Solutions
  • Health Sciences › Health Professions › Emergency Medical Services › Healthcare Operations and Scheduling Optimization
  • Social Sciences › Psychology › Experimental and Cognitive Psychology › Sleep and Work-Related Fatigue
Keywords
shift scheduling, healthcare workers, fairness, organizational justice, individual needs, decision-making, shift work, employee well-being, transparency, team spirit, scheduling conflicts

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