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The journey begins with Google’s sponsored search business. When Google developed the PageRank algorithm, it not only ranked results but also recommended the most relevant ones to users. Simultaneously, it charged advertisers to display their ‘sponsored’ results atop those organic outcomes. This business model, which underpins our ‘free’ internet today, grew from nonexistence in 2000 to becoming the biggest and possibly most influential business globally, amassing over 600 billion USD in volume worldwide....

Here’s a summary of the paper Persuading Customers to Buy Early: The Value of Personalized Information Provisioning, by Kimon Drakopoulos, Shobhit Jai and Ramandeep Randhawa, published online @ Management Science, in 2021. The paper studies the persuasion and pricing problem for a seller with informational advantage about its inventory level. Model: a seller sells a single good over two period to unit-demand buyers, out of inventory $Q$. The inventory level might be low (type L) or high (type H)....

Optimizing Product Launches in the Presence of Strategic Consumers. By Ilan Lobel, Jigar Patel, Gustavo Vulcano, and Jiawei Zhang. Management Science 2016. DOI https://doi.org/10.1287/mnsc.2015.2189 The paper studies firm’s product launch policy. It is motivated by the industry example, where tech firms iteratively release new models of their products. For example, Apple releasing one new iPhone models almost every 12-18 months, or Nintendo’s upcoming switch 2 that has been overdued 7 years (still is though)....

Here’s a reallly cool paper. Bergemann et al. (2015) The Limits of Price Discrimination. AER. DOI: http://dx.doi.org/10.1257/aer.20130848 ABSTRACT We analyze the welfare consequences of a monopolist having additional information about consumers’ tastes, beyond the prior distribution; the additional information can be used to charge different prices to different segments of the market, i.e., carry out “third degree price discrimination.” We show that the segmentation and pricing induced by the additional information can achieve every combination of consumer and producer surplus such that: (i) consumer sur- plus is nonnegative, (ii) producer surplus is at least as high as profits under the uniform monopoly price, and (iii) total surplus does not exceed the surplus generated by efficient trade....

Regulation restricts the action of economic agents—in general. It is omnipresent. Why does regulation exist? In a free-market economy, why does the government choose to place restrictions on the decisions of certain agents and actions? George Stigler (1911-1991) introduced his “Theory of Economic Regulation” in 1971 trying to answer this question in a well-established framework, on the basis of some previous empirical arguments such as Normative Analysis as a Positive Theory (NPT) or Capture Theory (CT)....

Following yesterday’s post (here), let’s delve deeper into Stackelberg Games and the key points of the paper, particularly the addition of context to the problem setting. Regret Minimization in Stackelberg Games with Side Information Keegan Harris, Zhiwei Steven Wu, Maria-Florina Balcan (2024) | paper’s arxiv link recap of the mode: A Stackelberg Security Game is a structured competitive setting involving a defender and an attacker. The defender commits to a strategy $ \mathbf p \in \mathbb{R}^n $ over $ n $ targets, and the attacker selects a target....

Of course, the general purpose of an academic presentation is multifaceted (see an older post about it), as discussed here. Nevertheless, I’ve once heard someone say that the key purpose of a talk at a conference is to make your audience interested in reading your work after the talk ends. I attended the RAIN seminar yesterday at Y2E2, Stanford, where Nina Balcan presented one of her latest works. Personally, I have a general interest in research that involves complex human behaviors....

I had the very fortune to listen to Nina Balcan giving a talk on one of her latest work, Online learning in Stackelberg Security Games: ABSTRACT In a Stackelberg Security Game, a defender commits to a randomized deployment of security resources, and an attacker best responds by attacking a target that maximizes their utility. While algorithms for computing an optimal strategy for the defender to commit to have been used in several real-world applications, deployed applications require knowledge about the utility function of the potential attacker....

A memoir of Market Mechanism Design course’s final presentation report, based on: Algorithmic Classification and Strategic Effort Jon Kleinberg and Manish Raghavan | ACM SIGecom Exchanges, Vol. 18, No. 2, November 2020, Pages 53–60 motivation: difference in modelling strategic behavior and objectives–between econ/CS perspectives The principal-agent and strategic machine learning literatures appear to share a common goal: how should one structure a decision-making rule to account for the strategic actions of decision subjects?...

speaker: Zizhuo Wang | Prof., The Chinese University of Hong Kong-Shenzhen. Takeaway: point of view of bridging practice and research. For industry solutions: Need to consider a lot of details Need to be fast and intepretation, therefore requires simple solutions Don’t care about theory. For academic works: Need abstract to focus Graced with time Expect some generality, therefore theory. TALK ABSTRACT: In the past years, there have been growing number of companies in China that adopt OR methods in their operations....