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- 2025
- Working Paper
Why Most Resist AI Companions
By: Julian De Freitas, Zeliha Oğuz-Uğuralp, Ahmet Kaan Uğuralp and Stefano Puntoni
AI companion applications—designed to serve as synthetic interaction partners—have recently
become capable enough to reduce loneliness, a growing public health concern. However,
behavioral research has yet to fully explain the barriers to adoption of such AI and... View Details
Keywords: Generative Ai; Chatbots; Artificial Intelligence; Algorithmic Aversion; Lonelines; Technology Adoption; AI and Machine Learning; Well-being; Emotions
De Freitas, Julian, Zeliha Oğuz-Uğuralp, Ahmet Kaan Uğuralp, and Stefano Puntoni. "Why Most Resist AI Companions." Harvard Business School Working Paper, No. 25-030, December 2024. (Revised May 2025.)
- 2008
- Working Paper
Platform Competition, Compatibility, and Social Efficiency
By: Ramon Casadesus-Masanell and Francisco Ruiz-Aliseda
Katz and Shapiro (1985) study systems compatibility in settings with one-sided plat- forms and direct network effects. We consider systems compatibility in settings with two-sided platforms and indirect network effects to develop an explanation why markets with... View Details
Casadesus-Masanell, Ramon, and Francisco Ruiz-Aliseda. "Platform Competition, Compatibility, and Social Efficiency." Harvard Business School Working Paper, No. 09-058, October 2008. (Revised November 2009.)