科学,スタートアップ,セキュリティにおける失敗のダイナミクスを定量化

Yian Yin^1,2,3, Yang Wang^1,2,4, James A Evans^5,6

¹Center for Science of Science and Innovation, Northwestern University, Evanston, IL, USA.

Nature

|November 1, 2019

まとめ

失敗のダイナミクスを理解することは成功の鍵ですこの研究は繰り返された試行において明確なパターンを明らかにし停滞から進歩を区別し最終的な結果を予測するための早期のシグナルを提供します

科学分野:

複雑なシステム科学
イノベーション研究
行動ダイナミクス

背景:

人間の成功には多くの失敗が伴うが失敗のダイナミクスの根本的なメカニズムは十分に理解されていない
イノベーション,人間力学,学習に関する既存の研究は失敗のパターンを探求するための基盤を提供します.
複雑な動態を明らかにするために失敗を理解するための定量的なアプローチが必要です

研究の目的:

成功または停滞につながる明確な失敗ダイナミクスを予測するモデルを開発し,検証する.
成功への道にあるエージェントと最終的に失敗するエージェントを区別する早期のシグナルを特定します
様々な分野における失敗のダイナミクスの普遍性を調査する.

主な方法:

過去の努力を基に将来の成功をシミュレートする1パラメータ分析モデルを開発しました.
進行と停滞のダイナミクスを分離する相転換のモデルを分析した.
NIHの助成金申請,スタートアップの退出,テロ攻撃の被害者請求など 3つの分野から大規模な経験データを収集し分析しました.

主要な成果:

このモデルは,障害のダイナミクスの段階的移行を予測し,それらを進行 (漸進的精錬) または停滞 (分離探索) に分類します.
NIHの助成金やスタートアップやテロ攻撃の経験的なデータはモデルの予測を一貫して裏付けています
最終的な成功や失敗を予測する,明確な,検出可能な初期信号を特定した.

結論:

失敗のダイナミクスは予測可能なパターンを示し, 系統的な進歩と無目的の探索を分離する重要な値があります.
初期段階の試みは類似しているようですが根本的に異なる失敗のダイナミクスを明らかにします
この研究は失敗を理解するための定量的な枠組みを提供し様々な複雑な取り組みの結果を予測するための早期の指標を提供します

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