Reduced demand uncertainty and the sustainability of collusion: How AI could affect competition

• Published in: Information economics and policy 2021-03, Vol.54, p.100882, Article 100882
• Main Authors: O’Connor, Jason, Wilson, Nathan E.
• Format: Article
• Language: English
• Subjects: Ambiguity; Antitrust; Artificial Intelligence; Big Data; Collusion; Companies; Competitive intelligence; Consumers; Intelligence; Intuition; Price Discrimination; Sustainability; Technology; Transparency; Uncertainty; Welfare
• ISSN: 0167-6245; 1873-5975
• DOI: 10.1016/j.infoecopol.2020.100882

•An improved ability to predict demand may affect the nature of competition in oligopoly markets.•Greater transparency may enable coordination when previously not possible or improve it when already possible.•Greater transparency may also make coordination unsustainable where previously possible.•Transparency affects the payoffs to participating in and to defecting from a collusive strategy. We model how a technology that perfectly predicts one of two stochastic demand shocks alters the character and sustainability of collusion. Our results show that mechanisms that reduce firms’ uncertainty about the true level of demand have ambiguous welfare implications for consumers and firms alike. An exogenous improvement in firms’ ability to predict demand may make collusion possible where it was previously unsustainable or more profitable where it previously existed. However, an increase in transparency also may make collusion impracticable where it had been possible. The intuition for this ambiguity is that greater clarity about the true state of demand raises the payoffs both to colluding and to cheating. Our findings on the ambiguous welfare implications of reduced uncertainty contribute to the emerging literature on how algorithms, artificial intelligence (AI), and “big data” in market intelligence applications may affect competition.