Mismanaging diagnostic accuracy under congestion

Arbeitspapier

To study the effect of congestion on the fundamental trade-off between diagnostic accuracy and speed, we empirically test the predictions of a formal sequential testing model in a setting where the gathering of additional information can improve diagnostic accuracy, but may also take time and increase congestion as a result. The efficient management of such systems requires a careful balance of congestion-sensitive stopping rules. These include diagnoses made based on very little or no diagnostic information, and the stopping of diagnostic processes while waiting for information. We test these rules under controlled laboratory conditions, and link the observed biases to system dynamics and performance. Our data shows that decision makers (DMs) stop diagnostic processes too quickly at low congestion levels where information acquisition is relatively cheap. But they fail to stop quickly enough when increasing congestion requires the DM to diagnose without testing, or diagnose while waiting for test results. Essentially, DMs are insufficiently sensitive to congestion. As a result of these behavioral patterns, DMs manage the system with both lower-than-optimal diagnostic accuracy and higher-than-optimal congestion cost, underperforming on both sides of the accuracy/speed trade-off.

Angaben zum Objekt

• Sprache: Englisch

Verweise und Beziehungen

• Erschienen in: Series: ESMT Working Paper ; No. 22-01

Klassifikation und Themen

• Klassifikation: Management ; Market Structure, Pricing, and Design: Oligopoly and Other Forms of Market Imperfection ; Economics of Contract: Theory ; Vertical Restraints; Resale Price Maintenance; Quantity Discounts ; Antitrust Law
• Thema: Congestion ; Diagnostic accuracy ; Experiments ; Partially Observable Markov Decision Process ; Path-dependent Decision Making ; Undertesting ; Task Completion Bias

Beteiligte, Orts- und Zeitangaben

• Ereignis: Geistige Schöpfung
• (wer): Kremer, Mirko ; de Véricourt, Francis
• Ereignis: Veröffentlichung
• (wer): European School of Management and Technology (ESMT)
• (wo): Berlin
• (wann): 2022

Weitere Informationen

• Handle: http://hdl.handle.net/10419/251899
• URN: urn:nbn:de:101:1-2022033012520666013677
• Letzte Aktualisierung: 10.03.2025, 11:43 MEZ