Competition in Pricing Algorithms

Brown, Zach Y.; MacKay, Alexander

doi:10.2139/ssrn.3856840

Cited by 16 publications

(22 citation statements)

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“…Therefore, a firm must be willing to accept setup costs. That said, this effect could be moderated by other benefits of algorithms, such as a higher frequency of pricing or better demand forecasting (Brown and MacKay, 2022;Miklós-Thal and Tucker, 2019). The coordination problem seems mitigated by the fact that algorithms are generally on the rise, but we note that a rising share of algorithmic players per se does not preclude the coordination problem.…”

Section: Discussionmentioning

confidence: 82%

Human-Algorithm Interaction: Algorithmic Pricing in Hybrid Laboratory Markets

Normann

Sternberg

2022

SSRN Journal

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Section: Discussionmentioning

confidence: 82%

Human-Algorithm Interaction: Algorithmic Pricing in Hybrid Laboratory Markets

Normann

Sternberg

2022

SSRN Journal

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“…Because of the frequent interactions, defection from a collusive agreement is punished more promptly and gains from defection are reaped for a shorter time. Thus, automating a firm's price response to rival's prices through an algorithm provides a firm with an advantage relative to its peers in terms of frequency of price changes and leads to higher prices relative to the competitive ones (Brown & MacKay, 2019).…”

Section: Anti-competitive Effects Of Aimentioning

confidence: 99%

Artificial intelligence, firms and consumer behavior: A survey

Abrardi

Cambini

Rondi

2021

Journal of Economic Surveys

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The current advances in Artificial Intelligence (AI) are likely to have profound economic implications and bring about new trade-offs, thereby posing new challenges from a policymaking point of view. What is the impact of these technologies on the labor market and firms? Will algorithms reduce consumers' biases or will they rather originate new ones? How competition will be affected by AI-powered agents? This study is a first attempt to survey the growing literature on the multi-faceted economic effects of the recent technological advances in AI that involve machine learning applications. We first review research on the implications of AI on firms, focusing on its impact on labor market, productivity, skill composition and innovation. Then we examine how AI contributes to shaping consumer behavior and market competition. We conclude by discussing how public policies can deal with the radical changes that AI is already producing and is going to generate in the future for firms and consumers.

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“…One aspect of algorithmically driven dynamic pricing is the extent of coordination between algorithms. Whilst pricing algorithms can utilize pre-existing customer data, in an active market algorithms that understand price changes by competitors can be a highly effective part of a pricing strategy (Brown & MacKay, 2021). This reflects trends in dynamic pricing where, instead of choosing prices, companies choose pricing algorithms -and therefore it is algorithms rather than prices that compete with each other.…”

Section: Autonomy and Co-ordination Of Algorithmsmentioning

confidence: 99%

“…The impact of this direct algorithmic competition differs from standard price competition. Even when one firm has a superior pricing technology and algorithms than another, research indicates that both firms can benefit from increased prices (Brown & MacKay, 2021). At the same time, this kind of algorithmically driven competitiveness can be harmful for consumers if price increases become detached from market demand.…”

Section: Autonomy and Co-ordination Of Algorithmsmentioning

confidence: 99%