Norm Personalization at Scale: Preference-Concordant Work Systems to Reduce Autonomy Dissonance

Design and test a “preference-concordance” scheduling and policy system that maximizes the match between employee work-location preferences and team/organizational constraints, while meeting performance targets. The system produces a Preference-Concordance Index (PCI) for individuals and teams and dynamically adjusts norms and schedules to reduce autonomy dissonance. This approach flips the debate on remote vs. office work by focusing on governing for preference-concordance while preserving coordination. It builds on algorithmic management frameworks specifying inputs (preferences, task interdependence), processes (constraint optimization, fairness rules), and outputs (well-being, commitment, performance). Ethical safeguards prevent hidden inequities by culture, caregiving status, or geography. Insights from interdisciplinary primary care inform which roles benefit from rotation versus continuity. The model also handles multi-sovereign constraints and cultural diversity in international organizations. This research empirically tests whether norm personalization can reconcile autonomy, inclusion, and productivity, creating a new governance category for hybrid work beyond blanket mandates. It promises an evidence-based playbook for preference-aware organizational design and a scalable category in organizational sociology at the intersection of technology, ethics, and culture.

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