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The use of autonomous machine learning-based pricing algorithms has grown in many markets in recent years, and many firms outsource their pricing algorithms to third party developers. Recent evidence highlights the potential for pricing algorithms to soften competition, but the role of third-party developers, and how the risks of these algorithms can be managed, are less clear. Using a randomized experiment on a large online platform, we investigate the extent to which third party programmers consider downstream effects of widespread adoption of their algorithms when designing them, and whether managers outsourcing pricing algorithms can influence programmer decisions and designs. Our findings have implications for pricing algorithm development and regulation, and for managing third party programmers.
