-
作者：Golrezaei, Negin; Manshadi, Vahideh; Schneider, Jon; Sekard, Shreyas
作者单位：Massachusetts Institute of Technology (MIT); Yale University; Alphabet Inc.; Google Incorporated; University of Toronto; University Toronto Scarborough; University of Toronto
摘要：In many online platforms, customers' decisions are substantially influenced by product rankings as most customers only examine a few top-ranked products. This induces a race for visibility among sellers, who may be incentivized to artificially inflate their position by employing fake users as exemplified by the emergence of click farms. Motivated by such fraudulent behavior, we study the problem of learning product rankings when a platform faces a mixture of real and fake users who are indisti...
-
作者：Asadpour, Arash; Niazadeh, Rad; Saberi, Amin; Shameli, Ali
作者单位：City University of New York (CUNY) System; Baruch College (CUNY); University of Chicago; Stanford University
摘要：We study a submodular maximization problem motivated by applications in online retail. A platform displays a list of products to a user in response to a search query. The user inspects the first k items in the list for a k chosen at random from a given distribution and decides whether to purchase an item from that set based on a choice model. The goal of the platform is to maximize the engagement of the shopper defined as the probability of purchase. This problem gives rise to a less-studied v...
-
作者：Lorentziadis, Panos L.
作者单位：Athens University of Economics & Business
摘要：In multidimensional auctions, bidders compete in both quality and price, which are combined by a score rule. A well-known problem in procurement management is that nonprice attributes are often poorly measured and unreliably estimated. Adjustments of the reported quality based on the qualities of rival bids can enhance the reliability of the measurement process. We develop a general model of score function that is dependent on the qualities offered by all bidders who differ in terms of their p...
-
作者：Talluri, Kalyan; Tsoukalasb, Angelos
作者单位：Imperial College London; Erasmus University Rotterdam; Erasmus University Rotterdam - Excl Erasmus MC
摘要：Professional service firms (PSFs) such as management consulting, law, accounting, investment banking, architecture, advertising, and home-repair companies provide services for complicated turnkey projects. A firm bids for a project and, if successful in the bid, assigns employees to work on the project. We formulate this as a revenue management problem under two assumptions: a quality-revelation setup, where the employees that would be assigned to the project are committed ex ante, as part of ...
-
作者：Maglaras, Costis; Scarsini, Marco; Shin, Dongwook; Vaccarid, Stefano
作者单位：Columbia University; Luiss Guido Carli University; Hong Kong University of Science & Technology
摘要：This paper studies product ranking mechanisms of a monopolistic online platform in the presence of social learning. The products' quality is initially unknown, but consumers can sequentially learn it as online reviews accumulate. A salient aspect of our problem is that consumers, who want to purchase a product from a list of items displayed by the platform, incur a search cost while scrolling down the list. In this setting, the social learning dynamics, and hence the demand, is affected by the...
-
作者：Gao, Yuan; Kroer, Christian
作者单位：Columbia University
摘要：Linear Fishermarkets are a fundamental economicmodelwith diverse applications. In the finite-dimensional case of n buyers and m items, amarket equilibriumcan be computed using the celebrated Eisenberg-Gale convex program. Motivated by large-scale Internet advertising and fair division applications, we consider a generalization of a linear Fisher market where there is a finite set of buyers and ameasurable itemspace. We introduce generalizations of the Eisenberg-Gale convex program and its dual...
-
作者：Kash, Ian A.; Key, Peter B.; Zoumpoulis, Spyros I.
作者单位：University of Illinois System; University of Illinois Chicago; University of Illinois Chicago Hospital; INSEAD Business School
摘要：In the context of subscription-based services, many technologies improve over time, and service providers can provide increasingly powerful service upgrades to their customers but at a launching cost and the expense of the sales of existing products. We propose a model of technology upgrades and characterize the optimal pricing and timing of technology introductions for a service provider who price-discriminates among customers based on their upgrade experience in the face of customers who are...
-
作者：Cao, Yufeng; Rusmevichientong, Paat; Topaloglu, Huseyin
作者单位：Shanghai Jiao Tong University; University of Southern California
摘要：We consider assortment optimization problems when customers choose under a mixture of independent demand and multinomial logit models. In the assortment optimization setting, each product has a fixed revenue associatedwith it. The customers choose among the products according to our mixture choice model. The goal is to find an assortment that maximizes the expected revenue from a customer. We show that we can find the optimal assortment by solving a linear program. We establish that the optima...
-
作者：Grabisch, Michel; Mandel, Antoine; Rusinowska, Agnieszka
作者单位：Paris School of Economics
摘要：We propose a model of the joint evolution of opinions and social relationships in a setting in which social influence decays over time. The dynamics are based on bounded confidence: social connections between individuals with distant opinions are severed, whereas new connections are formed between individuals with similar opinions. Our model naturally gives rise to strong diversity, that is, the persistence of heterogeneous opinions in connected societies, a phenomenon that most existing model...
-
作者：Duchi, John; Hashimoto, Tatsunori; Namkoong, Hongseok
作者单位：Stanford University; Stanford University; Stanford University; Columbia University
摘要：While modern large-scale data sets often consist of heterogeneous subpopulations-for example, multiple demographic groups or multiple text corpora-the standard practice of minimizing average loss fails to guarantee uniformly low losses across all sub-populations. We propose a convex procedure that controls the worst case performance over all subpopulations of a given size. Our procedure comes with finite-sample (nonparametric) convergence guarantees on the worst-off subpopulation. Empirically,...
