(All times CET)
PDF version is here
Please find the abstracts, links to drafts, and all other materials in the online version below.
Thursday, 25 March 2021 | 9:45-18:00 CET
9.45 - 10.00
Introduction and welcome
10.00 – 11.30
Panel 1: Competition and Regulation
The first panel covers some of the legal and economic challenges raised by algorithmic pricing for competition policy and regulation, including algorithmic collusion and the use of AI in arbitration disputes. (Moderator: Francesco Ducci, MWF, LAW)
Rob Nicholls | University of New South Wales
“When the Price is Right: AI in Final Offer Arbitration“
In The European Union, the US and Australia, there are different approaches being taken to address relative bargaining power in the curation and creation of news. On the one side, news content is curated by the large platform businesses Google and Facebook. On the other side, news is created by news media businesses that have historically sold their own advertising cross-subsidise news creation. News curators and creators have a symbiotic relationship where each relies on the other to both create and transfer value. In the EU, the net of that value is a matter of copyright law. In Australia, it is a matter of competition law. This presentation examines the way that Australian law has used the approach of "final offer arbitration" to elicit price offers in an environment where the opening offers from the platforms were zero and the opening asks from the news media businesses were more than $A1 billion. It reviews where the commercial outcomes occurred and examines whether the mediate/arbitrate process adopted could be automated given the structure adopted. In particular, as final offer arbitration merely requires a binary decision, the presentation demonstrates the intractability of such a binary decision to an artificial intelligence application.
Giacomo Calzolari | European University Institute
“Protecting consumers from collusive prices due to AI“
Michal Gal | University of Haifa
“Algorithms as Illegal Agreements and Algorithmic Consumers“
- Gal, Michal and Elkin-Koren, Niva, Algorithmic Consumers (August 8, 2016). Harvard Journal of Law and Technology, Vol. 30, 2017, Available at SSRN: https://ssrn.com/abstract=2876201
- Gal, Michal, Algorithms as Illegal Agreements (May 2, 2018). Berkeley Technology Law Journal, Forthcoming, Available at SSRN: https://ssrn.com/abstract=3171977
Algorithmic Consumers: The next generation of e-commerce will be conducted by digital agents, based on algorithms that will not only make purchase recommendations, but will also predict what we want, make purchase decisions, negotiate and execute the transaction for the consumers, and even automatically form coalitions of buyers to enjoy better terms, thereby replacing human decision-making. Algorithmic consumers have the potential to change dramatically the way we conduct business, raising new conceptual and regulatory challenges. This game-changing technological development has significant implications for regulation, which should be adjusted to a reality of consumers making their purchase decisions via algorithms. Despite this challenge, scholarship addressing commercial algorithms focused primarily on the use of algorithms by suppliers. This article seeks to fill this void. We first explore the technological advances which are shaping algorithmic consumers, and analyze how these advances affect the competitive dynamic in the market. Then we analyze the implications of such technological advances on regulation, identifying three main challenges.
Algorithms as Illegal Agreements : Despite the increased transparency, connectivity, and search abilities that characterize the digital marketplace, the digital revolution has not always yielded the bargain prices that many consumers expected. What is going on? Some researchers suggest that one factor may be coordination between the algorithms used by suppliers to determine trade terms. Simple coordination-facilitating algorithms are already available off the shelf, and such coordination is only likely to become more commonplace in the near future. This is not surprising. If algorithms offer a legal way to overcome obstacles to profit-boosting coordination, and create a jointly profitable status quo in the market, why should suppliers not use them? In light of these developments, seeking solutions – both regulatory and market-driven – is timely and essential. While current research has largely focused on the concerns raised by algorithmic-facilitated coordination, this article takes the next step, asking to what extent current laws can be fitted to effectively deal with this phenomenon. To meet this challenge, this article advances in three stages. The first part analyzes the effects of algorithms on the ability of competitors to coordinate their conduct. While this issue has been addressed by other researchers, this article seeks to contribute to the analysis by systematically charting the technological abilities of algorithms that may affect coordination in the digital ecosystem in which they operate. Special emphasis is placed on the fact that the algorithms is a “recipe for action”, which can be directly or indirectly observed by competitors. The second part explores the promises as well as the limits of market solutions. In particular, it considers the use of algorithms by consumers and off-the-grid transactions to counteract some of the effects of algorithmic-facilitated coordination by suppliers. The shortcomings of such market solutions lead to the third part, which focuses on the ability of existing legal tools to deal effectively with algorithmic-facilitated coordination, while not harming the efficiencies they bring about. The analysis explores three interconnected questions that stand at the basis of designing a welfare-enhancing policy: What exactly do we wish to prohibit, and can we spell this out clearly for market participants? What types of conduct are captured under the existing antitrust laws? And is there justification for widening the regulatory net beyond its current prohibitions in light of the changing nature of the marketplace? In particular, the article explores the application of the concepts of plus factors and facilitating practices to algorithms. The analysis refutes the Federal Trade Commission’s acting Chairwoman’s claim that current laws are sufficient to deal with algorithmic-facilitated coordination.
13.45 – 15.15
Panel 2: Platform Design and Pricing
The focus of the panel is on the problems where platforms are explicitly modelled and either the platform's profit, associated market dynamics, the policy response, or the effect on welfare are of crucial importance. (Moderator: Arthur Dolgopolov, MWF, ECO)
Matthijs Wildenbeest | Indiana University
“Agency Pricing and Bargaining: Empirical Evidence from the e-Book Market”
Heinrich Nax | ETH Zurich & University of Zurich
“Information, Feedback and Pricing Rule Effects in the Continuous Double Auction: an Experimental Perspective”
Relevant paper: https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3131004
Justin Johnson | Cornell University
“Platform Design when Sellers Use Pricing Algorithms”
Relevant paper: https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3691621
15.30 – 16.45
Panel 3: Algorithmic Pricing
The panel covers the broad topic of algorithmization of prices without the focus on algorithmic collusion. These include surge pricing in ride-sharing, online shopping, learning algorithms, and outsourcing. (Moderator: Arthur Dolgopolov, MWF, ECO)
Brendan Lucier | Microsoft Research
“Pricing for Complex Buyers with Auctions and Bidding Agents”
Joseph Harrington | University of Pennsylvania
“Outsourcing Pricing Algorithms and Market Competition”
17.00 – 18.00
Hal Varian | Google
“Ad Costs and Product Prices”
(Moderator: Arthur Dolgopolov, MWF, ECO)
End of first day of workshop
Friday, 26 March 2021 │ 10:00-18:30 CET
10.00 – 11.30
Panel 4: Price Discrimination and Behavioural and Psychographic Targeting
The panel explores the use of software agents to price discriminate and target consumers with personalised communications – social perceptions of such practices, their impact on markets and society and the applicable legal frameworks. (Moderator: Agnieszka Jabłonowska, MWF, LAW)
Andreas Leibbrandt | Monash University
“Behavioral constraints on price discrimination: Experimental evidence on pricing and customer antagonism”
Frederik Zuiderveen Borgesius | Radboud University
“Online price discrimination and non-discrimination law”
Natali Helberger | University of Amsterdam
“Profiling, consumer vulnerability and unfair commercial practices”
14.00 – 15.30
Panel 5: Pricing and Society: Sociological and Historical Approaches
The panel brings together researchers studying how pricing and other market technologies contribute to distributive outcomes, the socio-cultural consequences of markets, as well as various processes of social discrimination, in historical perspective. (Moderator: Giacomo Tagiuri, MWF, LAW)
Franck Cochoy | University of Toulouse
“On the Digitalization of Prices: A Century of Price Display Practices and Technologies (1922–present)”
Abstract: In contemporary markets, price display is subject to an incredible amount of public regulation that set its more or less mandatory character, the place where prices should appear, in what size price information should be printed, the need to indicate the price per kilo, and so on. In parallel, posting prices has been and still is subject to innumerable innovations, ranging from simple handwriting techniques to sophisticated electronic shelf labels. Strangely enough, social sciences have largely ignored these ceaseless and considerable investments made to organise and materialise price appearance, as if the mundane materiality of prices paradoxically made it invisible. In this presentation, I will attempt to fill this gap based on the review of a century of price display practices and techniques as they appear in the US trade magazine Progressive Grocer. More specifically, I will focus on the supposed digitalisation of prices. 'Digital' now means electronic, but the word also long-encompassed numerals—a digit is a number—and body parts—digitus is the Latin word for finger, that is, the index we use to point at things or manipulate them. I will show that all these meanings are embedded in price display history. As we will see, the previous forms of price digitalisation help us understand the most recent ones, the difficulties they meet, as well as their impact on the economy.
- Cochoy, F., Soutjis, B., 2020. “Back to the future of digital price display: Analyzing patents and other archives to understand contemporary market innovations”, Social Studies of Science, vol. 50, no. 1, pp. 3-29, https://doi.org/10.1177/0306312719884643.
- Cochoy, F., Hagberg, J., Kjellberg H., 2018. “The technologies of price display: Mundane retail price governance in the early 20th century,” Economy and Society, vol. 47, no. 4, pp. 572-606, https://doi.org/10.1080/03085147.2018.1528102.
- Cochoy, F., Hagberg, J., Kjellberg H., 2019a. “Price tag technologies and price ceiling policies. Governing prices in the WWII and Postwar US economy (1940-1953)”, Socio-Economic Review, vol. 50, no. 1, pp. 3-29, DOI: https://doi.org/10.1177/0306312719884643.
- Cochoy, F., Hagberg, J., Kjellberg, H., 2019b. “The ethno-graphy of prices: on the fingers of the invisible hand (1922-1947),” Organization, vol. 26, no. 4, pp. 492–516, https://doi.org/10.1177/1350508418790142
- Cochoy, F., Hagberg, J., Kjellberg, H., 2020. “The tower of labels. Labeling goods in the US Grocery store (1922-2018)”, in Mallard, A. and Laurent, B. (eds.), Labeling the Economy, New York, Palgrave MacMillan, pp. 233-270.
- Hagberg, J., Kjellberg H., Cochoy, F., 2020. “The role of market devices for price and loyalty strategies in 20th century U.S. grocery stores,” Journal of Macromarketing, vol. 40, no. 2, pp. 201-220, DOI: https://doi.org/10.1177/0276146719897366.
- Kjellberg, H., Hagberg, J., Cochoy, F., 2019. “Thinking Market Infrastructure: Barcode Scanning in the US Grocery Retail Sector, 1967–2010,” in Kornberger, M., Bowker, Elyachar, J., Mennicken, Miller, P. and Pollock, N. (eds.), Thinking Infrastructures (Research in the Sociology of Organizations, Vol. 62), Bingley, UK: Emerald Publishing Limited, pp. 207-232.
- Soutjis, B., Cochoy, F., Hagberg, J., 2017. “An ethnography of Electronic Shelf Labels. The resisted digitization of prices in contemporary supermarkets,” Journal of Retailing and Consumer Services, vol. 39(C), pp. 296-304, https://doi.org/10.1016/j.jretconser.2017.08.009
Joseph Turow | University of Pennsylvania
“Profiling Customers to Assess Their Value: Where is the Red Line?”
Relevant book: The Voice Catchers (Forthcoming, 2021), https://yalebooks.yale.edu/book/9780300248036/voice-catchers, book description
Tamar Kricheli-Katz | Tel-Aviv University
“The Gender Price Gap”
Abstract: Using data from eBay we show that women receive lower prices than men when selling the exact same products. we further explore why this gender gap obtains and why some products have larger gender price gaps than others. To answer these questions, we exploit the variation in the gender price gap across products found in the earlier eBay data together with new survey data on the perceptions people have about seemingly male-typed and female-typed products and about people’s uncertainty about the prices of products.
16.00 – 17.30
Panel 6: Dynamic Pricing and Learning
The panel explores all aspects of dynamic price change - from Electronic Shelf Labels and the costs associated with rapid price adjustments to the convergence of reinforcement learning pricing algorithms to collusive outcomes and industrial applications of multidimensional pricing models. (Moderators: Arthur Dolgolopov, MWF, ECO & Francesco Ducci, MWF, LAW)
Marian Moszoro | George Mason University & SGH Warsaw School of Economics
Brad Kells | Cargo Chief, Lead Data Scientist
“Pricing Algorithms in the Truck Industry with Multi-dimensional but Limited Data”
Arnoud den Boer | University of Amsterdam
“Tacit Collusion by Data-Driven Price Algorithms”
Abstract: Can price algorithms learn to collude instead of compete against each other, potentially leading to higher consumer prices and lower social welfare? The question is controversial among economists and competition policy regulators. One the one hand, concerns have been expressed that self-learning price algorithms do not only make it easier to form price cartels, but also that this can be achieved within the boundaries of current antitrust legislation – raising the question whether the existing competition law needs to be adjusted to mitigate undesired algorithmic collusion. On the other hand, a number of economists believe that algorithms learning to collude is science fiction, except by using forms of signaling or communication that are already illegal, and argue that there is no need to change antitrust laws. Motivated by this discussion, I will present recent work on learning supra-competitive prices.
Relevant paper: https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3741385
Emilio Calvano | University of Bologna
“Artificial Intelligence, algorithmic pricing and collusion”
17.45 – 18.20
Oren Bar-Gill | Harvard University
“Algorithmic Price Discrimination: When Demand is a Function of Both Preferences and (Mis)perceptions”
(Moderator: Agnieszka Jabłonowska, MWF, LAW)
18.20 – 18.30
Closing remarks and end of workshop
Christo Wilson | Northeastern University
“Auditing the Amazon Buy Box”
(Moderator: Arthur Dolgopolov, MWF, ECO)
Abstract: In this study, we collected data from Amazon Marketplace to study two things: (1) dynamic pricing by merchants, and (2) the behavior of Amazon's Buy Box algorithm. These two systems are intertwined because the Buy Box algorithm determines which merchant will make a sale when a customer clicks the Buy Now button, so there is a strong incentive for merchants not just to compete with each other, but also to tailor their behavior to favor selection by the Buy Box. I will present our observations about the behavior of the Buy Box algorithm and merchants engaged in dynamic pricing, and conclude with thoughts about the design of Amazon's Marketplace.
Relevant paper: https://cbw.sh/static/pdf/amazon-www16.pdf