说服投资者:基于视频的研究

Allen Hu, Song Ma
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引用次数: 34

摘要

有说服力的沟通不仅通过内容发挥作用,而且通过传递方式发挥作用,例如面部表情、语调和措辞。本文考察了创业公司推介中交付的说服力。使用机器学习(ML)算法来处理全音高视频,我们量化了视觉、声音和语言维度的说服力。积极的(即充满激情,热情的)演讲能够提高融资的可能性。然而,在融资的条件下,高积极性的初创公司表现不佳。在评估单性别团队时,对女性的评价更偏重于交付,但在与男性在混合性别团队中合作时,她们被忽视了。通过实验,我们发现说服传递主要通过引导投资者形成不准确的信念而起作用。
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Persuading Investors: A Video-Based Study
Persuasive communication functions not only through content but also delivery, e.g., facial expression, tone of voice, and diction. This paper examines the persuasiveness of delivery in start-up pitches. Using machine learning (ML) algorithms to process full pitch videos, we quantify persuasion in visual, vocal, and verbal dimensions. Positive (i.e., passionate, warm) pitches increase funding probability. Yet conditional on funding, high-positivity startups underperform. Women are more heavily judged on delivery when evaluating single-gender teams, but they are neglected when co-pitching with men in mixed-gender teams. Using an experiment, we show persuasion delivery works mainly through leading investors to form inaccurate beliefs.
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