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Screening Talent for Task Assignment: Absolute or Percentile Thresholds?
Author(s) -
BALAKRISHNAN RAMJI,
LIN HAIJIN,
SIVARAMAKRISHNAN KONDURU
Publication year - 2020
Publication title -
journal of accounting research
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 6.767
H-Index - 141
eISSN - 1475-679X
pISSN - 0021-8456
DOI - 10.1111/1475-679x.12327
Subject(s) - intuition , percentile , task (project management) , statistic , computer science , statistics , context (archaeology) , econometrics , social psychology , cognitive psychology , psychology , mathematics , economics , paleontology , management , biology , cognitive science
Matching talents to tasks is an important part of job design. Organizations routinely use performance thresholds to group agents by talent. We see thresholds defined both in terms of an individual's own performance (absolute value) and in terms of peer performance (percentile). Intuition suggests a preference for percentile thresholds because the resulting rank‐order statistic is sufficient to assess relative talent. Yet, in the context of a task assignment problem in which the objective is to match talent with task type (using two agents and two task types), we show that absolute thresholds can dominate percentile thresholds under either of two conditions. First, flexibility in task assignment tilts the balance toward absolute thresholds. Second, performance manipulation can adversely affect the inherent advantage of percentile thresholds because they motivate agents to invest relatively more in personally costly influence activities to cast their performance in a favorable light. We examine how these results hold up when there are countably large number of agents and discuss empirical implications.