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This paper develops a practical framework for using observational data to audit the consumer surplus effects of AI-driven decisions, specifically in targeted pricing and algorithmic lending. Traditional approaches first estimate demand…

Machine Learning · Statistics 2026-01-06 Zeyu Bian , Max Biggs , Ruijiang Gao , Zhengling Qi

This paper provides a framework to quantify the sensitivity associated with behavioral models based on Cumulative Prospect Theory (CPT). These are used to design dynamic pricing strategies aimed at maximizing performance metrics of the…

Optimization and Control · Mathematics 2021-04-20 Vineet Jagadeesan Nair , Yue Guan , Anuradha M. Annaswamy , H. Eric Tseng , Baljeet Singh

[Purpose] To better understand the online reviews and help potential consumers, businessmen, and product manufacturers effectively obtain users' evaluation on product aspects, this paper explores the distribution regularities of user…

Computation and Language · Computer Science 2022-09-09 Chenglei Qin , Chengzhi Zhang , Yi Bu

The usage of recommendation agents (RAs) in the online marketplace can help consumers to locate their desired products. RAs can help consumers effectively obtain comprehensive product information and compare their candidate target products.…

Computers and Society · Computer Science 2016-06-07 Hui Zhu , Zherui Yang , Carol Xj Ou , Hongwei Liu , Robert M Davison

We study generalizations of online bipartite matching in which each arriving vertex (customer) views a ranked list of offline vertices (products) and matches to (purchases) the first one they deem acceptable. The number of products that the…

Data Structures and Algorithms · Computer Science 2023-06-27 Brian Brubach , Nathaniel Grammel , Will Ma , Aravind Srinivasan

In this paper, we examine the effectiveness of various recommendation strategies in the mobile channel and their impact on consumers' utility and demand levels for individual products. We find significant differences in effectiveness among…

Computers and Society · Computer Science 2021-02-23 Panagiotis Adamopoulos , Anindya Ghose , Alexander Tuzhilin

Though the studies of social contagions are regularly borrowing network models to study the propagation of social influences and opinions to include social heterogeneity. Such studies provide valuable insights regarding these, but the…

Physics and Society · Physics 2023-09-28 Dibyajyoti Mallick , Kumar Gaurav , Saumik Bhattacharya , Sayantari Ghosh

We discuss the influence of information contagion on the dynamics of choices in social networks of heterogeneous buyers. Starting from an inhomogeneous cellular automata model of buyers dynamics, we show that when agents try to adjust their…

Disordered Systems and Neural Networks · Physics 2009-11-07 Gerard Weisbuch , Dietrich Stauffer

Recommender systems operate in an inherently dynamical setting. Past recommendations influence future behavior, including which data points are observed and how user preferences change. However, experimenting in production systems with real…

Information Retrieval · Computer Science 2020-11-17 Karl Krauth , Sarah Dean , Alex Zhao , Wenshuo Guo , Mihaela Curmei , Benjamin Recht , Michael I. Jordan

A large number of empirical studies on applying self-attention models in the domain of recommender systems are based on offline evaluation and metrics computed on standardized datasets, without insights on how these models perform in real…

Information Retrieval · Computer Science 2022-11-30 Marjan Celikik , Jacek Wasilewski , Sahar Mbarek , Pablo Celayes , Pierre Gagliardi , Duy Pham , Nour Karessli , Ana Peleteiro Ramallo

We address the challenging problem of dynamically pricing complementary items that are sequentially displayed to customers. An illustrative example is the online sale of flight tickets, where customers navigate through multiple web pages.…

When tracking user-specific online activities, each user's preference is revealed in the form of choices and comparisons. For example, a user's purchase history is a record of her choices, i.e. which item was chosen among a subset of…

Machine Learning · Statistics 2019-01-01 Sahand Negahban , Sewoong Oh , Kiran K. Thekumparampil , Jiaming Xu

Many online marketplaces personalize prices based on consumer attributes. Since these prices are private, consumers may be unaware that they have spent more on a good than the lowest possible price, and cannot easily take action to pay…

Computer Science and Game Theory · Computer Science 2025-05-01 Aditya Karan , Naina Balepur , Hari Sundaram

We study a dynamic market setting where an intermediary interacts with an unknown large sequence of agents that can be either sellers or buyers: their identities, as well as the sequence length $n$, are decided in an adversarial, online…

Computer Science and Game Theory · Computer Science 2017-03-29 Yiannis Giannakopoulos , Elias Koutsoupias , Philip Lazos

The introduction of new payment methods has resulted in one of the most significant changes in the way we consume goods and services. In this paper, I present results of a field and a laboratory experiment designed to determine the effect…

General Economics · Economics 2022-10-27 Yizhao Jiang

Omnichannel retailing, a new form of distribution system, seamlessly integrates the Internet and physical stores. This study considers the pricing and fulfillment strategies of a retailer that has two sales channels: online and one physical…

Theoretical Economics · Economics 2021-03-15 Yasuyuki Kusuda

This study employs a Bayesian Probit model to empirically analyze peer effects and herd behavior among consumers during the "Double 11" shopping festival, using data collected through a questionnaire survey. The results demonstrate that…

Econometrics · Economics 2024-12-03 Hambur Wang

We introduce a stochastic heterogeneous interacting-agent model for the short-time non-equilibrium evolution of excess demand and price in a stylized asset market. We consider a combination of social interaction within peer groups and…

General Finance · Quantitative Finance 2009-07-20 Gunter M. Schütz , Fernando Pigeard de Almeida Prado , Rosemary J. Harris , Vladimir Belitsky

We consider revenue maximization in online auction/pricing problems. A seller sells an identical item in each period to a new buyer, or a new set of buyers. For the online posted pricing problem, we show regret bounds that scale with the…

Computer Science and Game Theory · Computer Science 2018-09-13 Sébastien Bubeck , Nikhil R. Devanur , Zhiyi Huang , Rad Niazadeh

The proliferation of e-commerce has made web shopping platforms key gateways for customers navigating the vast digital marketplace. Yet this rapid expansion has led to a noisy and fragmented information environment, increasing cognitive…

Information Retrieval · Computer Science 2026-02-16 Sunghwan Kim , Ryang Heo , Yongsik Seo , Jinyoung Yeo , Dongha Lee
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