Paper Number
ECIS2026-2792
Paper Type
SP
Abstract
Representation Theory posits that information systems should faithfully represent real-world phenomena. However, many phenomena, especially in physical information systems, benefit from intentional deviations from faithfulness. While prior research has emphasized the positive impact of faithfulness, we lack theoretical guidance for designing non-faithful representations to become design assets that enhance rather than diminish usefulness. Drawing on the adequacy-for-purpose view, we propose a Task-fit Representation Theory that favors task-fit over world-fit by combining human physical intuitions with deliberately manipulated computational physics. In this view, usefulness peaks at an optimal faithfulness that selectively distorts perceived and real-world physics to align with task and context constraints, such as computational limitations, and human expectations. We articulate five propositions contrasting Task-fit Representation Theory with Representation Theory and outline empirical approaches for testing them.
Recommended Citation
Mazur, Philipp Gabriel and Schoder, Detlef, "Task-Fit Not World-Fit: Proposing A Task-Fit Representation Theory For Physical Information Systems" (2026). ECIS 2026 Proceedings. 37.
https://aisel.aisnet.org/ecis2026/cog_hbis/cog_hbis/37
Task-Fit Not World-Fit: Proposing A Task-Fit Representation Theory For Physical Information Systems
Representation Theory posits that information systems should faithfully represent real-world phenomena. However, many phenomena, especially in physical information systems, benefit from intentional deviations from faithfulness. While prior research has emphasized the positive impact of faithfulness, we lack theoretical guidance for designing non-faithful representations to become design assets that enhance rather than diminish usefulness. Drawing on the adequacy-for-purpose view, we propose a Task-fit Representation Theory that favors task-fit over world-fit by combining human physical intuitions with deliberately manipulated computational physics. In this view, usefulness peaks at an optimal faithfulness that selectively distorts perceived and real-world physics to align with task and context constraints, such as computational limitations, and human expectations. We articulate five propositions contrasting Task-fit Representation Theory with Representation Theory and outline empirical approaches for testing them.
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