 Task Architecture and Learning from Coarse PerformanceEkaterina Korotkova and Georgy Lukyanov No 26-1790, TSE Working Papers from Toulouse School of Economics (TSE) Abstract: Organizations often learn about competence only from project-level success or failure, even when a project contains several complementary tasks. We compare task architectures by the Blackwell order. An expert of unknown fixed competence can perform all tasks in one bundled project, one task in a project completed by an outside technology, or the same number of tasks across separate projects. Bundling dominates a single narrow assignment below an outside-reliability threshold and is otherwise incomparable with it. Holding the expert’s workload fixed strictly lowers this threshold but does not overturn the result: bundling still dominates when the outside technology is sufficiently unreliable, separate projects dominate only when that technology is perfect, and the experiments are otherwise incomparable. We derive the thresholds for any number of tasks and show that the fixed-workload threshold decreases to zero as task scope grows. Explicit posterior-variance formulas measure the cost of coarse aggregation for particular decisions. Finally, in the two-task case, occasional stage-level audits expand the bundling-dominance region according to an exact frontier. Keywords: task assignment; coarse information; competence; Blackwell order; auditing (search for similar items in EconPapers) Downloads: (external link) Related works: Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text Persistent link: https://EconPapers.repec.org/RePEc:tse:wpaper:132296 Access Statistics for this paper More papers in TSE Working Papers from Toulouse School of Economics (TSE) Contact information at EDIRC. |
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