多战场团队竞赛中的结果披露与时间细化
Outcome Disclosure and Temporal Refinement in Multi-Battle Team Contests
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中文总结 AI 辅助
针对多战场团队竞赛，研究结果披露与时间细化两种非货币工具对支出、产出的影响，明确不同成本结构下的最优设计，且机制可扩展至特定竞赛技术。
中文摘要 AI 辅助
团队竞赛设计者看重产出而非支出，非线性转换使得二者的区分至关重要。我们研究由成对全支付战场（参与者能力为私人信息）决定的多数规则竞赛中的两种非货币工具：披露已解决结果，以及将战场日程拆分为更精细的时段块。二者均不会改变战场的平均关键度，仅会在不同历史中重新分配该关键度。在嵌套信息结构下，这种重新分配使得每个参与者的均衡能力调整后支出弱更分散，且均值不变；在所有考虑的设计中，期望总支出不变。所得凸序比较对期望总产出进行排序：凸产出成本倾向于不披露和更粗糙的时间结构，凹成本倾向于完全披露和更精细的时间结构，线性成本则使两种比较无差异。该排序对有限支撑和平滑连续类型的能力分布均成立，机制可扩展至具有唯一均衡结果分布的零阶分量竞赛技术。无披露与完全披露界定了所有可允许的公共混淆。
英文摘要
A team-contest designer values output rather than expenditure; nonlinear conversion makes the distinction consequential. We study two non-pecuniary instruments in majority-rule contests decided by pairwise all-pay battles with private abilities: disclosing resolved outcomes and splitting the battle schedule into finer blocks. Neither changes a battle's average pivotality; each only redistributes it across histories. Under nested information structures, this redistribution makes equilibrium ability-scaled expenditure weakly more dispersed player by player without changing its mean; expected aggregate expenditure is invariant across all designs considered. The resulting convex-order comparison ranks expected total output: convex output costs favor no disclosure and coarser temporal structures, concave costs favor full disclosure and finer ones, and linear costs make both comparisons neutral. The rankings hold for finite-support and smooth continuous-type ability distributions. The mechanism extends to degree-zero component contest technologies with a unique equilibrium outcome distribution. No and full disclosure bound every admissible public garbling.
