Product Rankings Ai Pricing Algorithms And Collusion
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Product Rankings Ai Pricing Algorithms And Collusion
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Author : Liying Qiu
language : en
Publisher:
Release Date : 2022
Product Rankings Ai Pricing Algorithms And Collusion written by Liying Qiu and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022 with categories.
Reinforcement learning (RL) based pricing algorithms have been shown to tacitly collude to set supra-competitive prices in oligopoly models of repeated price competition. We investigate the impact of ranking systems, a common feature of online marketplaces, on algorithmic collusion in prices. We study experimentally the behavior of algorithms powered by Artificial Intelligence (deep Q-learning) in a workhorse duopoly model of repeated price competition in the presence of product rankings. Through extensive experiments, we find that the introduction of the ranking system significantly mitigates the tacit collusion that stems from RL based pricing. The ranking system increases the incentives for the RL agents to deviate from a collusive price which in turn requires more complicated punishment strategies to prevent deviation and sustain collusive prices. These punishment strategies are harder to learn for RL algorithms in non stationary environments and the high collusive prices are not sustained as a result. The ranking system's mitigation effect is moderated by the horizontal differentiation between the products offered by the firms and the stickiness of product ranks. In particular, when products are more horizontally differentiated from each other and when past sales have a larger influence on product ranks (sticky ranking), the prices charged by the two firms are higher and the ranking system's mitigation effect is weaker. However, in both cases, prices in the presence of ranking are lower than that in the absence of ranking. Our analysis sheds light on the impact of ranking systems on consumer welfare and on design of ranking systems to prevent algorithmic pricing collusion.
Artificial Intelligence Algorithmic Pricing And Collusion
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Author : Emilio Calvano
language : en
Publisher:
Release Date : 2018
Artificial Intelligence Algorithmic Pricing And Collusion written by Emilio Calvano and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018 with Artificial intelligence categories.
Pricing algorithms are increasingly replacing human decision making in real marketplaces. To inform the competition policy debate on possible consequences, we run experiments with pricing algorithms powered by Artificial Intelligence in controlled environments (computer simulations). In particular, we study the interaction among a number of Q-learning algorithms in the context of a workhorse oligopoly model of price competition with Logit demand and constant marginal costs. We show that the algorithms consistently learn to charge supra-competitive prices, without communicating with each other. The high prices are sustained by classical collusive strategies with a finite punishment phase followed by a gradual return to cooperation. This finding is robust to asymmetries in cost or demand and to changes in the number of players.
Understanding Ai Collusion And Compliance
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Author : Justin Johnson
language : en
Publisher:
Release Date : 2020
Understanding Ai Collusion And Compliance written by Justin Johnson and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020 with categories.
Antitrust compliance scholarship, particularly with a focus on collusion, has been an area of study for some time. Changes in technology and the rise of artificial intelligence (AI) and machine-learning create new possibilities both for anti-competitive behavior and to aid in detection of such algorithmic collusion. To some extent, AI collusion takes traditional ideas of collusion and simply provides a technological overlay to them. However, in some instances, the mechanisms of both collusion and detection can be transformed using AI. This handbook chapter discusses existing theoretical and empirical work, and identifies research gaps as well as avenues for new scholarship on how firms or competition authorities might invest in AI compliance to improve detection of wrong doing. We suggest where AI collusion is possible and offer new twists to where prior work has not identified possible collusion. Specifically, we identify the importance of AI to address the “trust” issue in collusion. We also identify that AI collusion is possible across non-price dimensions, such as manipulated product reviews and ratings, and discuss potential screens involving co-movements of prices and ratings. We further emphasize that AI may encourage entry, which may limit collusive prospects. Finally, we discuss how AI can be used to help with compliance both at the firm level and by competition authorities.
Artificial Intelligence And Collusion
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Author : Steven Van Uytsel
language : en
Publisher:
Release Date : 2020
Artificial Intelligence And Collusion written by Steven Van Uytsel and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020 with categories.
The use of algorithms in pricing strategies has received special attention among competition law scholars. There is an increasing number of scholars who argue that the pricing algorithms, facilitated by increased access to data, could move in the direction of collusive price setting. Though this claim is being made, there are various responses. On the one hand, scholars point out that current artificial intelligence is not yet well-developed to trigger that result. On the other hand, scholars argue that algorithms may have other pricing results rather than collusion. Despite the uncertainty that collusive price could be the result of the use of pricing algorithms, a plethora of scholars are developing views on how to deal with collusive price setting caused by algorithms. The most obvious choice is to work with the legal instruments currently available. Beyond this choice, scholars also suggest constructing a new rule of reason. This rule would allow us to judge whether an algorithm could be used or not. Other scholars focus on developing a test environment. Still other scholars seek solutions outside competition law and elaborate on how privacy regulation or transparency reducing regulation could counteract a collusive outcome. Besides looking at law, there are also scholars arguing that technology will allow us to respond to the excesses of pricing algorithms. It is the purpose of this chapter to give a detailed overview of this debate on algorithms, price setting and competition law.
Consumer Search Collusion And Artificial Intelligence
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Author : Mike P. Vo
language : en
Publisher:
Release Date : 2022
Consumer Search Collusion And Artificial Intelligence written by Mike P. Vo and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022 with categories.
We use both economic theory and experiments with Artificial Intelligence (AI) pricing agents to study the roles of consumer search friction on collusion and implications on market prices and consumer welfare. By developing an oligopoly model in which consumers sequentially search for the best product with advertised prices, we find that collusion is easier to sustain with lower search costs. On the other hand, increasing search costs can reduce the collusive price. However, the price reduction is insufficient to increase the consumer surplus if the collusion sustains. Our experiments show that simple reinforcement learning algorithms (Q-learning) manage to adopt a trigger-price strategy to keep prices above the competitive level in a frictional market.
Platform Design When Sellers Use Pricing Algorithms
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Author : Justin P. Johnson
language : en
Publisher:
Release Date : 2020
Platform Design When Sellers Use Pricing Algorithms written by Justin P. Johnson and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020 with categories.
Pricing Via Artificial Intelligence
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Author : Weipeng Zhang
language : en
Publisher:
Release Date : 2023
Pricing Via Artificial Intelligence written by Weipeng Zhang and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023 with categories.
Classic artificial intelligence (Q-learning) algorithms have been capable of consistently learning supra-competitive pricing strategies in infinitely repeated Nash-Bertrand pricing games without human communication. Such algorithms have been able to converge due to the temporal correlation of consecutive states and actions in the learning process, which restores stationarity in an otherwise highly non-stationary setting. It is difficult for more realistic AI algorithms to converge, as the necessary training processes breaks the aforementioned temporal correlation, rendering the algorithms ineffective in learning reward-punishment strategies that result in collusive market outcomes. We adapt several widely used neural network architectures to the framework of model-free reinforcement learning and experimentally explore how the structure of AI algorithms affects market outcomes in a workhorse oligopolistic model of repeated price competition. While it is possible to train advance AI algorithms to always best respond in environments where the rival exercises a fixed strategy, it is unlikely that such algorithms can learn to coordinate in setting supra-competitive prices due to the non-stationarity of multi-agent learning processes, suggesting that algorithmic collusion may not be an immediate concern for antitrust authorities.
Algorithmic Pricing Based On Big Data A Critical Reflection
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Author : Lukas Kern
language : en
Publisher:
Release Date : 2020-08-21
Algorithmic Pricing Based On Big Data A Critical Reflection written by Lukas Kern and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-08-21 with categories.
Master's Thesis from the year 2020 in the subject Business economics - Customer Relationship Management, CRM, grade: 1,0, language: English, abstract: Setting the right product prices is crucial for companies and is part of their marketing mix and image. For instance, deviations from "optimal" sales prices can lead to considerable losses in revenue and margin. However, a huge amount of data affect the "optimal" price and the pricing process requires extensive manual resources. Advanced algorithms like machine learning might have the potential to overcome the aforementioned challenges with almost no manual interactions. Pricing algorithms constantly automate and optimize pricing decisions based on the available data. Besides positive one-time effects of price optimizations, algorithmic pricing enables companies to implement new pricing strategies like dynamic pricing, price personalization, and markdown pricing. This master thesis combines the results of a literature review and expert interviews to solve three questions: What is the research gap between the current state of the literature and business practice regarding the use of advanced algorithms based on big data for algorithmic pricing? What progress and insights have companies made in using algorithmic pricing? And how can algorithmic pricing be enhanced for future application? The master thesis starts by explaining the basic concepts of algorithmic pricing and relevant technologies. Therefore, the results and takeaways are useful for business managers without prior experience in this area. This master thesis then provides corporate decision makers with recommendations on what to consider for new pricing algorithms and on opportunities for future development of existing pricing algorithms.
Algorithmic Pricing Collusion The Limits Of Antitrust Enforcement
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Author : Sumit Bhadauria
language : en
Publisher:
Release Date : 2020
Algorithmic Pricing Collusion The Limits Of Antitrust Enforcement written by Sumit Bhadauria and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020 with categories.
The combination of big data, large storage capacity and computational power has strengthened the emergence of algorithms in making myriads of business decision. It allows business to gain a competitive advantage by making automatic and optimize decision making. In particular, the use of pricing algorithms allows business to match the demand and supply equilibrium by monitoring & setting dynamic pricing. It benefits consumer alike to see and act on fast changing prices. However, on the downside, the widespread use of algorithm in an industry has the effect of altering the structural characteristic of market such as price transparency, high speed trading which increases the likelihood of collusion. The ability of pricing algorithm to solve the cartel incentive problem by quickly detecting and punishing the deviant further strengthen the enforcement of price fixing agreement. In addition, the use of more advance forms of algorithm such as self-learning algorithm allows business to achieve a tacitly collusive outcome in limited market characteristic even without communication between humans. This raises the fundamental challenge for anti-cartel enforcement as the current law in most jurisdictions is ill-equipped to deal with algorithmic facilitated tacit collusion. The legality of tacit collusion is questionable primarily because the pricing algorithm has the ability to alter the market characteristics where the tacitly collusive outcome is difficult to achieve; thus widening the scope of the so-called 'oligopoly problem'. This paper studies the usages of pricing algorithms by business in online markets. In particular, the paper identify the conditions under which the algorithm prices causes the harm to consumers. It seeks to analyze how algorithms might facilitate or even causes the collusive outcome without human interventions. Further, it looks at the legal challenges faced by the competition authorities around the globe to deal with the algorithmic let collusion and examine the various approaches suggested to counter act it.
What Do We Know About Algorithmic Collusion Now New Insights From The Latest Academic Research
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Author : Ai Deng
language : en
Publisher:
Release Date : 2023
What Do We Know About Algorithmic Collusion Now New Insights From The Latest Academic Research written by Ai Deng and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023 with categories.
Algorithmic collusion has captured the attention of the global antitrust community for the past several years. Deng (2020) provided a comprehensive survey of the pertinent literature in economics and computer science and a critical discussion. Over the past three years, new insights have emerged from academic research. These new insights have not only deepened our understanding of the intricate relationship between algorithms and competition but also begun challenging some previous findings once considered compelling evidence supporting the plausibility of autonomous algorithmic tacit collusion. In this article, I discuss these new insights, with a focus on four topics: (1) the nuanced ways algorithms affect prices, (2) the crucial role of algorithmic design, (3) the consequences of third-party pricing algorithms, and (4) some considerations when assessing algorithmic impact in litigation.