WINE 2026: The 22nd Conference on Web and Internet Economics
The University of Hong Kong, Hong Kong, China
December 1–4, 2026
Overview
Over the past two decades, researchers from fields such as theoretical computer science, artificial intelligence, operations research, and economics have joined forces to explore the interplay of incentives and computation. These topics are of particular importance for the Internet and enable the interaction of large and diverse populations.
The Conference on Web and Internet Economics (WINE, originally known as the Workshop on Internet & Network Economics until 2013) is an interdisciplinary platform for exchanging ideas and findings on incentives and computation from these varied fields. The WINE conference has been held annually since its inception in 2005, and WINE 2026 (https://wine2026conf.github.io/) will carry on this tradition, taking place on December 1–4, 2026, at University of Hong Kong. WINE 2026 will be an in-person event.
Important Warning: Fraudulent Travel and Hotel Emails
We have been informed that some authors have received unsolicited emails from reservation@gtravelhost.com requesting arrival and departure dates and offering hotel-booking services.
Please note that WINE 2026 has not appointed or authorized any travel agency, and this sender is not affiliated with the conference. Please do not reply, click any links, provide personal or payment information, or make reservations through this email.
Please rely only on information provided through the WINE 2026 official website and communications from the conference organizers. If you receive a similar message, please mark it as spam or phishing and delete it.
Important Dates
Paper submission deadline: July 2, 2026, Anywhere on Earth
Rebuttal period: August 17-20, 2026
Author notification: September 10, 2026
Camera ready: September 30, 2026
Early registration deadline: November 6, 2026, at 11:59 PM Hong Kong local time (HKT)
Conference: December 1-4, 2026
News
Oct, 2026: Registration is now open. For more information, visit the registration page.
Tutorial 1 (9:00–10:30 and 11:00–12:30, December 8): Tournament Design
Organizer: Ariel Schvartzman (Google Research)
Introduction: How should the organizer of a round-robin tournament choose one of n teams as the winner in a fair manner? This is a question that has practical implications for everything from major sports competitions, like the World Cup and the Olympic Games, to theoretical implications for mechanism design and computational social choice. In this tutorial, we aim to present a growing line of work that addresses this question and highlight some elusive open questions and conjectures.
Organizers: Fang-Yi Yu (George Mason University); Xintong Wang (Rutgers University)
Introduction: As forecasts steer real decisions—from allocating vaccines to pricing risk, reliable evaluation and incentives are essential. This tutorial surveys proper scoring rules, the backbone of probabilistic forecast evaluation and designing truthful reporting mechanisms. We introduce proper scoring rules as contracts that reward accurate forecasts and develop their geometric (convex-analytic) intuition. We then generalize to property elicitation, which characterizes which statistics of an outcome (e.g., means, quantiles) are elicitable, and to surrogate (proxy) scoring, which evaluates forecasts using stochastically related observations.
Building on this foundation, we survey applications of proper scoring rules. First, information elicitation aims to design payments to elicit truthful reports or even motivate costly information acquisition. We will survey a family of peer prediction mechanisms using proper scoring rules. Second, prediction markets, which serve as automatic market makers for prediction, use proper scoring rules to design trades that aggregate predictions in real time. We will focus on designing efficient algorithms for markets when the prediction space is large. We close with related topics—wagering mechanisms, forecast competitions and aggregation, and evaluating (multi-)calibration.
Organizers: M. Amin Rahimian (University of Pittsburgh); Juba Ziani (Georgia Institute of Technology); Marios Papachristou (Arizona State University); Yuxin Liu (University of Pittsburgh)
Introduction: The increasing prevalence of data-driven decision making requires robust mechanisms to protect sensitive information while allowing its utility for collective benefit. Differential Privacy (DP) offers a rigorous framework for achieving strong privacy guarantees. This tutorial will explore how differential privacy can be leveraged to facilitate secure and privacy-preserving information sharing in various contexts. We will dive into the fundamental concepts of DP and discuss its application in scenarios where data are acquired, shared, aggregated, or processed to derive collective insights, ensuring individual contributions remain private.
The tutorial will cover recent advances in applying DP to practical challenges in information exchange, including methods for private estimation, learning, and inference, as well as incentive compatible and privacy-preserving mechanisms for optimal data sharing and acquisition. Attendees will gain an understanding of the trade-offs involved in designing DP mechanisms for real-world systems and learn about the techniques that enable effective information flow while mitigating privacy risks. Our discussion will highlight the importance of careful design to balance privacy with the goals of data utility, sharing, and collaborative knowledge generation, as well as open problems and research questions of interest to the WINE community in this space.
Organizers: Wei Tang (Chinese University of Hong Kong); Yiding Feng (Hong Kong University of Science and Technology)
Introduction: This tutorial explores the role of information design in studying and improving calibration for decision making. Calibration is crucial in scenarios where accurate predictions or decisions based on uncertain or incomplete information are necessary, such as in online markets, machine learning, or healthcare. In the first part, we will introduce the foundational concepts of calibration, the challenges in decision-making under uncertainty, and how information design techniques can be leveraged to study and enhance calibration. In the second part, we will delve into advanced topics, including applications of calibration in modern settings. The tutorial aims to equip participants with a deep understanding of how to analyze and improve calibration in decision-making processes using principles from information design.
Session 1A (9:00–10:30, December 9): AI and Game Theory
Multi-Armed Bandits With Machine Learning-Generated Surrogate Rewards Wenlong Ji (Stanford University); Yihan Pan (Northwestern University); Ruihao Zhu (Cornell University); Lihua Lei (Stanford University)
Will AI Trade? A Computational Inversion of the No-Trade Theorem Hanyu Li, Xiaotie Deng (Peking University)
Accelerated Preference Elicitation with LLM Proxies David Huang (Harvard University); Francisco Marmolejo-Cossio (Boston College, Harvard University, IOG); Edwin Lock (University of Oxford); David Parkes (Harvard University)
Misalignment, Learning, and Ranking: Harnessing Users Limited Attention Arpit Agarwal (IIT Bombay); Rad Niazadeh (University of Chicago); Prathamesh Patil (JP Morgan Chase)
Session 1B (9:00–10:30, December 9): Pricing
Bounds on the revenue gap of linear posted pricing for selling a divisible item Ioannis Caragiannis, Zhile Jiang (Aarhus University); Apostolis Kerentzis (Hellenic Air Force)
Optimal Robust Pricing with Minimal Information Yan Ge (Shanghai University of Finance and Economics); Simai He (Shanghai Jiao Tong University); Zhen Wang (Shanghai University of Finance and Economics); Zizhuo Wang (The Chinese University of Hong Kong, Shenzhen)
Repeated Sales with Heterogeneous Buyer Sophistication Rishi Patel, Emmanouil Pountourakis (Drexel University); Samuel Taggart (Oberlin College)
Dynamic Pricing with Adversarially-Censored Demands Jianyu Xu (Carnegie Mellon University); Yining Wang (UT Dallas); Xi Chen (New York University); Yu-Xiang Wang (University of California San Diego)
Session 2A (11:00–12:30, December 9): Fairness and Social Choice
Compatibility of Max and Sum Objectives for Committee Selection and k-Facility Location Elliot Anshelevich, Yue Han (Rensselaer Polytechnic Institute)
Justified Representation: From Hare to Droop Matthew M. Casey, Edith Elkind (Northwestern University)
Bin Packing and Covering: Pushing the Frontier on the Maximin Share Fairness Bo Li, Ankang Sun (The Hong Kong Polytechnic University); Zunyu Wang (Huazhong University of Science and Technology); Yu Zhou (The Pennsylvania State University)
Improved Approximate EFX Guarantees for Multigraphs Alireza Kaviani, Alireza Keshavarz (Sharif University of Technology); Masoud Seddighin (Tehran Institute for Advanced Studies); Amir Mohammad Shahrezaei (Sharif University of Technology)
Session 2B (11:00–12:30, December 9): Behavioral and Decision Theory
Strategic Behavior in Crowdfunding: Insights from a Large-Scale Online Experiment Din Amir, Bar Hoter, Moran Koren (Ben-Gurion University)
Behavioral Study of Dashboard Mechanisms Paula Kayongo (Northwestern Univeristy); Jessica Hullman, Jason Hartline (Northwestern University)
Commitment Gap via Correlation Gap Dimitrios Christou (University of Texas at Austin); Shuchi Chawla (UT Austin)
Online Selection with Uncertain Disruption Yihua Xu, Suleyman Kerimov, Sebastian Perez-Salazar (Rice University)
Session 3A (15:30–17:25, December 9): Mechanism Design
Optimal Automated Market Makers: Differentiable Economics and Strong Duality Michael Curry (University of Illinois Chicago); Zhou Fan, David Parkes (Harvard University)
Achieving Coordination in Non-Cooperative Joint Replenishment Games Junjie Luo (Beijing Jiaotong University); Changjun Wang (University of Chinese Academy of Sciences)
Accelerated Price Adjustment for Fisher Markets with Exact Recovery of Competitive Equilibrium He Chen, Chonghe Jiang, Anthony Man-Cho So (The Chinese University of Hong Kong)
Neighborhood Stability in Assignments on Graphs Haris Aziz (UNSW Sydney); Grzegorz Lisowski (AGH University); Mashbat Suzuki, Jeremy Vollen (UNSW Sydney)
Session 3B (15:30–17:00, December 9): Matching
Two-Sided Fairness in Many-to-One Matching Ayumi Igarashi (University of Tokyo); Naoyuki Kamiyama (Kyushu University); Yasushi Kawase (University of Tokyo); Warut Suksompong (National University of Singapore); Hanna Sumita, Yu Yokoi (Institute of Science Tokyo)
Fair Metric Distortion for Matching with Preferences Jabari Hastings, Prasanna Ramakrishnan (Stanford University)
The Popular Dimension of Matchings Frank Connor, Louis-Roy Langevin, Ndiame Ndiaye, Agnès Totschnig, Rohit Vasishta, Adrian Vetta (McGill University)
Characterizing Super Stability in the Roommate Problem Under Weak Preferences Bin Yu (Guangri Research and Development Institute)
Session 4A (9:00–10:30, December 10): Online Algorithms
New Concentration Bounds and Their Applications in Online Resource Allocation Jinshan Zhang (Zhejiang University); Biaoshuai Tao (Shanghai Jiaotong University); Nan Zhao, Meng Xi, Tao Jin, Jianwei Yin (Zhejiang University)
Robustness of Online Inventory Balancing to Inventory Shocks Yiding Feng (Hong Kong University of Science and Technology); Rad Niazadeh (University of Chicago); Amin Saberi (Stanford University)
Constant Approximation for Network Revenue Management with Markovian-Correlated Customer Arrivals Jiashuo Jiang (The Hong Kong University of Science and Technology)
Potential-Based Greedy Matching for Dynamic Delivery Pooling Hongyao Ma, Will Ma, Matias Romero (Columbia University)
Session 4B (9:00–10:30, December 10): Mechanism Design
Improved Budget-Feasible Mechanisms for Submodular Valuations: Beating 4 Deterministically in Linear Time Kai Han, Pinyan Lu (Shanghai University of Finance and Economics)
Decentralized Signaling Mechanisms Niloufar Mirzavand Boroujeni (Institute for Data Science in Oncology, The University of Texas MD Anderson Cancer Center); Krishnamurthy Iyer, William L. Cooper (University of Minnesota)
Ex-Ante Truthful Distribution-Reporting Mechanisms Xiaotie Deng, Yanru Guan, Ningyuan Li (Peking University); Zihe Wang (Renmin University of China); Jie Zhang (University of Bath)
Inspect or Guess? Mechanism Design with Unobservable Inspection Ali Daei Naby (Rotman School of Management, University of Toronto); Saeed Alaei (Google Research); Azarakhsh Malekian (Rotman School of Management, University of Toronto)
Session 5A (11:00–12:30, December 10): Online Algorithms
Online Job Assignment Farbod Ekbatani (University of Chicago Booth School of Business); Yiding Feng (Hong Kong University of Science and Technology); Ian Kash (UIC); Rad Niazadeh (University of Chicago)
Online Makespan Minimization: Beat LPT by Dynamic Locking Zhaozi Wang (New York University); Zhiwei Ying, Yuhao Zhang (Shanghai Jiao Tong University)
Multi-Unit Combinatorial Prophet Inequalities Shuchi Chawla (UT Austin); Trung Dang (The University of Texas at Austin); Zhiyi Huang (University of Texas at Austin); Yifan Wang (Georgia Institute of Technology)
Prophet Inequalities with Stochastic Choices Shaoyu Wang, Pin Gao, Guillermo Gallego (The Chinese University of Hong Kong, Shenzhen); Su Zhao (Meituan)
Session 5B (11:00–12:30, December 10): Games and Complexity
Constant Inapproximability of Pacing Equilibria in Second-Price Auctions Xi Chen, Yuhao Li (Columbia University)
On the Complexity of Stationary Nash Equilibria in Discounted Perfect Information Stochastic Games Kristoffer Arnsfelt Hansen, Xinhao Nie (Aarhus University)
Price of Anarchy of Algorithmic Monoculture Robert Kleinberg, Erald Sinanaj, Éva Tardos (Cornell University)
Algorithmic and Structural Complexities of Menus in Unit-Demand Auctions Clayton Thomas (Yale University); Daniel Schoepflin (Rutgers University); S. Matthew Weinberg (Princeton University)
Best Paper Awards Session (15:30–16:30, December 10)
The Limits of Interval-Regulated Price Discrimination Kamesh Munagala, Yiheng Shen (Duke University); Renzhe Xu (Shanghai University of Finance and Economics)
Degree-bounded Online Bipartite Matching: OCS vs. Ranking Yilong Feng, Haolong Li, Xiaowei Wu, Shengwei Zhou (University of Macau)
Recent Trends in Market Algorithms Research in GenAI Era Vahab Mirrokni (Google)
Session 6A (9:00–10:30, December 11): Mechanism Design
Optimal Prize Design in Parallel Rank-order Contests Xiaotie Deng (Peking University); Ningyuan Li (Center on Frontiers of Computing Studies, School of CS, Peking University); Weian Li (School of Software, Shandong University); Qi Qi (Gaoling School of Artificial Intelligence, Renmin University of China, Beijing, China)
Less is More: Optimal Contest Design with a Shortlist Hanbing Liu (Gaoling School of Artificial Intelligence, Renmin University of China); Ningyuan Li (Center on Frontiers of Computing Studies, School of Computer Science, Peking University); Weian Li (School of Software, Shandong University); Qi Qi (Gaoling School of Artificial Intelligence, Renmin University of China); Changyuan Yu (Baidu Inc.)
TTC Domains Sumit Goel (New York University Abu Dhabi); Yuki Tamura (Ecole Polytechnique, CREST, IP Paris)
Strategyproof Tournament Rules for Teams with a Constant Degree of Selfishness David Pennock, Daniel Schoepflin, Kangning Wang (Rutgers University)
Session 6B (9:00–10:30, December 11): Fair Division
Incentive Analysis of Collusion in Fair Division Haoqiang Huang (HKUST); Biaoshuai Tao (Shanghai Jiao Tong University); Mingwei Yang (Stanford University); Shengwei Zhou (University of Macau)
A Polynomial-Time Algorithm for Fair and Efficient Allocation with a Fixed Number of Agents Ryoga Mahara (The University of Tokyo)
Fair and Efficient Allocation of Indivisible Mixed Manna Siddharth Barman (Indian Institute of Science); Vishwa Prakash HV (Chennai Mathematical Institute); Aditi Sethia (Indian Institute of Science, Bangalore); Mashbat Suzuki (UNSW Sydney)
On Pareto-Optimal and Fair Allocations with Personalized Bi-Valued Utilities Jiarong Jin, Biaoshuai Tao (Shanghai Jiao Tong University)
Session 7A (11:00–12:30, December 11): Games and Equilibria
Flow Over Time with Tolls Shaul Rosner (Tel Aviv University); Marc Schröder (Maastricht University); Laura Vargas Koch (RWTH Aachen University)
Multiplayer General Lotto game Yan Liu (Renmin University of China); Bonan Ni (Tsinghua University); Weiran Shen, Zihe Wang (Renmin University of China); Jie Zhang (University of Bath)
Integer-splittable Bin Packing Games Bainian Hao (Chang'An University); Carla Michini (University of Wisconsin--Madison)
Cooperation in Bilateral Generalized Network Creation Hans Gawendowicz (Hasso Plattner Institute, University of Potsdam); Pascal Lenzner (University of Augsburg); Lukas Weyand (Hasso Plattner Institute, University of Potsdam)
Session 7B (11:00–12:30, December 11): Auctions
Unending Sequential Auctions Amir Ban (Hebrew University of Jerusalem)
How to Sell High-Dimensional Data Optimally Andrew Li, R. Ravi, Karan Singh, Zihong Yi, Weizhong Zhang (Carnegie Mellon University)
Robust Optimality of Bundling Goods Beyond Finite Variance Tim van Eck, Pieter Kleer, Johan van Leeuwaarden (Tilburg University)
The Role of Prescreening in Auctions with Predictions Yanwei Sun, Fupeng Sun (Imperial College London); Chiwei Yan (University of California, Berkeley); Jiahua Wu (Imperial College London)
Session 8A (15:30–17:00, December 11): Blockchain
Money Burning Improves Mediated Communication Yi Liu (Department of Economics, Yale University); Yang Yu (School of Economics and Management, China University of Petroleum-Beijing)
Time Consensus and Censorship Resistance in Blockchains Arthur Breitman (Tezos Foundation, Switzerland); Dariusz Kowalski, Piotr Krysta (Augusta University)
One-dimensional vs. Multi-dimensional Pricing in Blockchain Protocols Giorgos Panagiotakos (IOHK); Aggelos Kiayias (University of Edinburgh & IOG); Elias Koutsoupias (University of Oxford); Kyriaki Zioga (National Technical University of Athens)
Selling Privacy in Blockchain Transactions Georgios Chionas (University of Liverpool); Piotr Krysta (Augusta University); Olga Gorelkina, Rida Laraki (Université Mohammed VI Polytechnique)
Session 8B (15:30–17:00, December 11): Pricing
Price and Assortment Optimization under the Multinomial Logit Model with Opaque Products Omar El Housni (Cornell University); Adam Elmachtoub, Harsh Sheth, Jiaqi Shi (Columbia University)
Assortment Optimization for the Multinomial Logit Model with Repeated Customer Interactions Ningyuan Chen (University of Toronto, Rotman School of Management); Pin Gao, Chenhao Wang (The Chinese University of Hong Kong, Shenzhen); Yao Wang (Xi'an Jiaotong University); Jianpei Wen (Meituan, Beijing, China)
Pricing and Addiction Control for Digital Services Jiacheng Chang, Xiao Lei, Feng Tian (University of Hong Kong)
Rethinking Pricing in Energy Markets: Pay-as-Bid vs Pay-as-Clear Ioannis Caragiannis, Zhile Jiang, Stratis Skoulakis (Aarhus University)
Keynote Speakers
The WINE 2026 program will feature keynote talks by the following speakers.
Michal Feldman (Tel Aviv University): TBA
TBA
Michael I. Jordan (Inria Paris and UC Berkeley): A Collectivist, Economic Perspective on AI
Abstract:
Information technology is in the midst of a revolution in which
omnipresent data collection and machine learning are impacting the
human world as never before. The word "intelligence" is being used as
a North Star for the development of this technology, with human
cognition viewed as a baseline. This view neglects the fact that
humans are social animals, and that much of our intelligence is social
and cultural in origin. Thus, a broader framing is to consider the
system level, where the agents in the system, be they computers or
humans, are active, they are cooperative, and they wish to obtain
value from their participation in learning-based systems. Agents may
supply data and other resources to the system only if it is in their
interest to do so, and they may be honest and cooperative only if it
is in their interest to do so. Critically, intelligence inheres as
much in the overall system as it does in individual agents. In the
overall system, computation of equilibria replaces computation of
optima. This is a perspective that is familiar in economics, although
without the focus on learning algorithms. A key challenge for
technology is thus to bring (micro)economic concepts into contact with
foundational issues in the computing, statistical, and decision-making
sciences. I'll discuss some concrete examples of problems and
solutions at this tripartite interface.
Bio:
Michael I. Jordan is a researcher at Inria Paris and Professor
Emeritus at the University of California, Berkeley. His research
interests bridge the computational, statistical, cognitive, biological
and social sciences. Prof. Jordan is a member of the National Academy
of Sciences, a member of the National Academy of Engineering, a member
of the American Academy of Arts and Sciences, a Foreign Member of the
Royal Society, and a Foreign Member of the Chinese Academy of
Sciences. He was a winner of a BBVA Foundation Frontiers of Knowledge
Award in 2025 and was the inaugural winner of the World Laureates
Association (WLA) Prize in 2022. He was a Plenary Lecturer at the
International Congress of Mathematicians in 2018. He has received the
Ulf Grenander Prize from the American Mathematical Society, the IEEE
John von Neumann Medal, the IJCAI Research Excellence Award, the David
E. Rumelhart Prize, and the ACM/AAAI Allen Newell Award.
Tracy Xiao Liu (Tsinghua University): Understanding AI Behavior and Human Behavior with AI
Abstract: Generative AI is rapidly evolving into both a tool that supports human decision-making and cognitive tasks and an increasingly autonomous agent in social and economic settings. These expanding roles raise two important questions: how can we understand and interpret AI behavior, and how the use of generative AI may affect individuals' cognitive engagement with tasks and, in turn, their cognitive development. This talk examines these questions through two studies: one combines behavioral economics with AI interpretability to understand AI behavior, while the other uses large-scale student–AI interaction data to examine the cognitive engagement divide in higher education.
The first study focuses on altruism, which is fundamental to human societies and fosters cooperation and social cohesion. While recent evidence suggests that large language models (LLMs) can display human-like prosocial behavior, it remains unclear what gives rise to such behavior within the model. By combining the Dictator Game with sparse autoencoders, an AI interpretability method for identifying interpretable features in a model's internal representations, we identify a set of features associated with altruistic choices. Intervening on these features systematically changes the model's allocations, and the effects generalize to several other social decision-making settings. These findings link economically meaningful behavior in LLMs to internal features that can be identified and causally manipulated.
The second study turns from AI behavior to human behavior with AI. As Generative AI increasingly performs cognitive tasks on people's behalf, a central question is whether users remain actively engaged in thinking or delegate their thinking to AI. We study this question using more than 4.1 million student–AI interactions from 1.28 million students in nearly 30,000 classes across more than 500 higher-education institutions in China. Drawing on the ICAP framework, we characterize how students cognitively engage with an AI tutor and identify substantial heterogeneity in their patterns of use. Students at less selective institutions are less likely to adopt and use the tutor and are more likely to engage in answer-seeking or passive learning. Across institutions, engagement also shifts toward answer-seeking over time. More active cognitive engagement is associated with better subsequent academic performance. Together, these findings reveal a cognitive engagement divide that extends beyond access to and frequency of AI use to how students actually engage with the technology.
Together, the two studies highlight how behavioral economics, in combination with methods and insights from other disciplines, can contribute to understanding both the behavior of increasingly capable AI systems and the ways in which these systems reshape human cognitive engagement and performance.
Bio: Tracy Xiao Liu is a Professor in the Department of Economics at the School of Economics and Management, Tsinghua University. Her research interests include experimental economics, behavioral economics, and the intersection of economics and computer science (Econ-CS). Her work has been published in leading journals, including PNAS, Management Science, Production and Operations Management, and Games and Economic Behavior, as well as in top-tier conferences in computer science and artificial intelligence, including KDD, IJCAI, and WWW. She currently serves as an Associate Editor for Management Science and the Journal of Economic Behavior & Organization.
Ariel Procaccia (Harvard University): No Generation Without Representation
Abstract:
AI systems and democratic processes are confronting similar challenges around representation. I examine two related questions that cut across both domains. First, how can AI enable democratic processes that handle vast spaces of opinions or statements while ensuring proportional representation of a population's views? Second, when AI systems themselves provide normative guidance, whose viewpoints do they reflect, and can we make this precise? Drawing on social choice theory, I present formal frameworks and algorithms for both problems, showing that meaningful representation guarantees are feasible and practical.
Bio:
Ariel Procaccia is the Alfred and Rebecca Lin Professor of Computer Science at Harvard University. He works on a broad and dynamic set of problems related to AI, algorithms, economics, and society. He has helped create systems and platforms that are widely used to solve everyday fair division problems, resettle refugees, distribute food, and select citizens’ assemblies. To make his research accessible to the public, he has written numerous opinion and exposition pieces for publications such as The New York Times, The Washington Post, Bloomberg, Wired, and Scientific American. He is an ACM Fellow (2025), a AAAI Fellow (2024), and a recipient of the ACM SIGecom Mid-Career Award (2024), Social Choice and Welfare Prize (2020), Guggenheim Fellowship (2018), IJCAI Computers and Thought Award (2015), and Sloan Research Fellowship (2015). In 2026, he was named Harvard College Professor in recognition of excellence in undergraduate teaching.
Call for Papers
Over the past two decades, researchers from fields such as theoretical computer science, artificial intelligence, operations research, and economics have joined forces to explore the interplay of incentives and computation. These topics are of particular importance for the Internet and enable the interaction of large and diverse populations.
The Conference on Web and Internet Economics (WINE, originally known as the Workshop on Internet & Network Economics until 2013) is an interdisciplinary platform for exchanging ideas and findings on incentives and computation from these varied fields. The WINE conference has been held annually since its inception in 2005, and WINE 2026 (https://wine2026conf.github.io/) will carry on this tradition, taking place on December 1–4, 2026, at University of Hong Kong. WINE 2026 will be an in-person event.
The program will feature keynotes, tutorials, and paper presentations. All paper submissions will be peer-reviewed and evaluated for their originality, technical soundness, significance, and overall contribution.
Topics
We welcome submissions in the area of Web and Internet Economics, including but not limited to the following topics:
AI safety and alignment
Auctions and pricing
Automated market maker (AMM)
Behavioral economics and behavioral modeling
Blockchain governance and stakeholder voting
Central bank digital currencies (CBDCs)
Computational advertising
Computational aspects of equilibria and solution concepts
Computational social choice
Coalitions, coordination, and collective action
Decentralized finance (DeFi)
Decision theory
Economic and strategic aspects of machine learning models
Fair division
Game-theoretic analysis of blockchains and financial protocols
Information design including contest and contract design
Information elicitation
Learning in games and markets
Market design
Matching markets
Mechanism design
Network games
Online platforms and applications
Privacy, fairness, and security
Revenue management
Social efficiency of equilibria
Social networks
Submissions deemed outside the scope of the WINE conference or not of sufficient interest to the WINE community will be desk-rejected.
Important Dates
Paper submission deadline: July 2, 2026, Anywhere on Earth
Rebuttal period: August 17-20, 2026
Author notification: September 10, 2026
Camera ready: September 30, 2026
Conference: December 1–4, 2026
FOCS, SAGT and AFT Submissions
Authors with submissions under review at FOCS 2026, SAGT 2026 and AFT 2026 may simultaneously submit the same work to WINE 2026. However, if a submission is accepted to those conferences, the authors must promptly withdraw the corresponding submission from WINE 2026. The scheduled notification date of FOCS 2026 is July 3, that of SAGT 2026 is July 9 and that of AFT 2026 is July 15.
Authors are invited to submit papers presenting original research on any research topic related to WINE 2026.
Submissions must be anonymous (see below). A submission should start with the title of the paper followed by a brief summary of the paper’s contributions. This should then be followed by a technical exposition of the main ideas and techniques used to achieve these results, including motivation and a clear comparison with related work. Even if the authors choose the one-page abstract option for the proceedings, they must still submit the full paper as their initial submission to facilitate a comprehensive and rigorous review process.
Submissions must not exceed 12 single-spaced pages excluding the title page and references, and must use a font size of at least 11 points with margins of at least one inch on all sides. If the authors believe that more details are essential to substantiate the claims of the paper, they may include a clearly marked appendix of arbitrary length that will be read at the discretion of the Program Committee. Submissions that clearly deviate from the specified format and length risk desk rejection.
The proceedings of the conference will be published by Springer in the ARCoSS/LNCS series, in an electronic version, and will be available for downloading at the conference. Accepted papers will be allocated 18 pages including references in the LNCS format in the proceedings. Submissions are encouraged, though not required, to follow the LNCS format (in which case the authors may follow the font size and page margins of LNCS). More information about the LNCS format can be found on the author instructions page of Springer.
WINE 2026 will use double-blind reviewing like all other major conferences. Submissions should not reveal the identity of the authors in any way. In particular, authors’ names, affiliations, and email addresses should not appear anywhere in the submission. (In LNCS, \author{} and \institute{} fields should not be included.) Authors should refer to their prior work in a neutral manner (for example, say “XYZ showed” instead of “we showed”). Submissions may include work that has been publicly presented (as long as it has not appeared in published proceedings) or posted on arXiv or similar online repositories, provided that the submission itself is properly anonymized.
Questions regarding the submissions can be directed to the Program Committee Chairs at wine2026chairs@gmail.com.
Rebuttal
The review process includes a rebuttal phase in August, giving authors the opportunity to address questions and concerns raised by the Program Committee.
A conflict of interest (COI) is limited to the following categories:
Family member or close friend
Ph.D. advisor or advisee (no time limit), or postdoctoral or undergraduate mentor or mentee within the past five years
Person with the same affiliation
Involved in an alleged incident of harassment (it is not required that the incident be reported)
Reviewer owes the author a favor (e.g., recently requested a reference letter)
Frequent or recent collaborator whom you believe cannot objectively review your work
Authors should update their HotCRP account information to declare COIs with (Senior) Program Committee members.
Declaring COIs prevents the specified person from reviewing a paper, thereby constraining the matching process and potentially negatively impacting review quality. For this reason, COIs should not be declared automatically based on a prior relationship (coauthor, friend, colleague in the same institution, etc.).
(Senior) Program Committee members can also declare COIs with authors as well as with specific papers.
A Best Paper Award and a Best Student Paper Award will be presented. Only papers published in full length in the proceedings will be eligible for consideration. Up to 3 additional papers will be selected for Outstanding Paper Awards. In total, the awards represent roughly the top 5~7% of accepted papers.
One-Page Abstract Option
We offer the one-page abstract option to accommodate publishing norms in various fields where journals may decline to consider work that has appeared in preliminary form in conference proceedings. This allows authors of accepted papers to request that only a one-page abstract be included in the proceedings, accompanied by a URL linking to the full version of the paper. Authors should guarantee the URL to be reliable for at least two years. Even if authors choose the one-page abstract option for the proceedings, they must still submit the full paper as their initial submission to facilitate a comprehensive and rigorous review process.
Simultaneous Submission
The following submissions are not allowed:
Papers that are currently under review at another archival conference, with the only exception of FOCS 2026, SAGT 2026 and AFT 2026 (see “FOCS, SAGT and AFT Submissions” above)
Papers that have been published or accepted for publication in a journal or archival conference before the WINE 2026 submission deadline
Papers in which one or more of the contributions have previously been published or accepted for publication in a journal or archival conference
Simultaneous submission of results to a journal is allowed only if the authors intend to publish the paper as a one-page abstract in WINE 2026. Papers that are accepted and appear as a one-page abstract may later be submitted to a journal, but may not be submitted to any other archival conference.
ACM TEAC Special Issue for WINE 2026
A special issue of ACM Transactions on Economics and Computation (ACM TEAC) will be organized in connection with WINE 2026. A selection of top papers presented at the conference will be invited to submit extended versions to the special issue, subject to the standard peer-review process of ACM TEAC. Further details will be communicated to the authors of invited papers in due course.
Notes: The forward-to-journal option is restricted to papers that appear in the WINE proceedings as one-page-abstracts. The journal is open to considering forward-to-journal to other areas, if the authors believe a different area is a better fit. If you are interested in submitting an extended version of a paper (not an abstract) that may fit another area, please submit to the corresponding area. Include in your cover letter a discussion of how the journal version differs from the conference version.
If the authors of a paper accepted to WINE 2026 wish to use the Forward-to-Journal option, they may choose to submit a one-page extended abstract by the camera-ready deadline for the conference proceedings. They may then submit their journal version to the selected journal by January 22, 2027.Notice that most Econ, OR and MS journals only allow a one-page extended abstract at archival conferences, in order for the journal submission to be considered. The authors must follow the specific journal’s policy when using the Forward-to-Journal option.
The cover letter to the journal should specify that the submission is part of the WINE 2026 Forward-to-Journal process, and specify how the journal submission differs from the version in the conference proceedings. The authors should also include a formal response document to the WINE 2026 conference reviews and explain how those reviews were addressed in the revised manuscript. In case the particular journal of choice needs a de-anonymized version of the conference reviews on the submission, WINE 2026 will provide them upon request by the journal. Note that a journal’s participation in the WINE 2026 Forward-to-Journal option does not mean that other forms of previous publication of the submission are acceptable for the journal.
The journal’s department editors and associate editors may use the conference reviews to inform their decision-making, in any manner deemed appropriate by the journal. We suspect that the associate editors might choose referees from the set of conference reviewers, especially if they found the conference reviews informative. We emphasize that the conference reviewers are not required to accept such review requests, and that journals are not required to accept these submissions (and may even choose to desk-reject them depending on fit).
Accepted Papers
On the Cost of Non-Adaptivity in Matroid Prophet Inequalities Tianle Jiang (Duke University)
Deviation-Based Learning: Training Recommender Systems Using Informed User Choice Junpei Komiyama (MBZUAI); Shunya Noda (University of Tokyo)
EF(X) Orientations: A Parameterized Complexity Perspective Sotiris Kanellopoulos (National Technical University of Athens and Archimedes, Athena Research Center, Greece); Edouard Nemery (Lamsade, Université Paris Dauphine); Christos Pergaminelis (National Technical University of Athens and Archimedes, Athena Research Center, Greece); Minas Marios Sotiriou (Athens University of Economics and Business and Archimedes, Athena Research Center, Greece); Manolis Vasilakis (Université Paris-Dauphine)
Equitable Auction Design with Provable Regret Guarantees Ruiqin Wang (Shanghai University of Finance and Economics); Çağıl Koçyiğit (University of Luxembourg); Napat Rujeerapaiboon (National University of Singapore)
Multi-agent Adaptive Mechanism Design Qiushi Han, David Simchi-Levi, Renfei Tan (Massachusetts Institute of Technology); Zishuo Zhao (Hong Kong University of Science and Technology (Guangzhou))
Justifiable Priority Violations Josué Ortega (Queen's University Belfast); Pablo Arribillaga (Universidad Nacional de San Luis)
Arrival-Time Incentive Compatibility in Random Order Online Bipartite Matching Arghya Chakraborty (TIFR); Varun Gupta (University of Utah)
The Pareto Secretary Problem Andrés Cristi (EPFL); Yilin Kong (CUHK); Jiechen Zhang (EPFL)
Bayesian Conversations Renato Paes Leme (Google); Jon Schneider (Google Research); Heyang Shang, Shuran Zheng (Tsinghua University)
A Short List Goes A Long Way: Pareto-Optimal Assignment under Stochastic Arrival and MNL Utilities Weicheng Wang (The Chinese University of Hong Kong, Shenzhen); Ankang Sun (School of Computer Science and Technology, Shandong University); Zizhuo Wang (The Chinese University of Hong Kong, Shenzhen)
Improved Parallel Algorithms for EF1 Allocations Kishen N Gowda (University of Maryland); D Ellis Hershkowitz, Richard Z Huang (Brown University); Gregory Kehne (Washington University in St. Louis)
Horizontal or Vertical? Managerial Attention and Organizational Structure Ashley Perry (New York University Abu Dhabi)
Learning to Price in Feature-Based Pool Markets under Censored Feedback Titing Cui (University of Tulsa)
An Entropy Potential for Type-Composition Games Morteza Alimi (University of Augsburg); Merlin de la Haye (Hasso Plattner Institute, University of Potsdam, Potsdam, Germany); Pascal Lenzner (University of Augsburg); Šimon Schierreich (Czech Technical University in Prague); Alexander Skopalik (University of Twente); Marcus Wunderlich (University of Augsburg)
Ordinal Hegselmann-Krause Systems Martin Hoefer, Tim Koglin, Jakob Lindner, Jannis Schramek (RWTH Aachen University)
Competition Versus Complexity in Multiple-Selection Prophet Inequalities Eugenio Cruz (Pontificia Universidad Católica de Chile); Sebastian Perez-Salazar (Rice University); Victor Verdugo (Pontificia Universidad Católica de Chile)
Strategic Disclosure of Action Space in Principal-Agent Contracts Xiaotie Deng, Ningyuan Li (Peking University)
Fractional Assignment with Distance-Based Preferences Yasushi Kawase (Chuo University); Warut Suksompong (National University of Singapore); Hanna Sumita, Yu Yokoi (Institute of Science Tokyo)
Slack and Budget Breaking in Threshold Team Production Benjamin Marsh (Sei Labs and University of Portsmouth); Alejandro Ranchal-Pedrosa (Sei Labs)
Profit Reallocation Mechanisms in Tree-based Data Trading Yunxuan Ma, Wu Xin (Peking University); Jichen Li (Tsinghua University); Yusen Zheng, Xiaotie Deng (Peking University)
Algorithmic Information Design for Searchers with Uncertain Alternatives Zhicheng Du (Renmin University of China); Hu Fu (Shanghai University of Finance and Economics); Ying Qin, Zihe Wang (Renmin University of China)
Social Learning of Ranking: Getting the Top Right despite Local Herding Shahrzad Haddadan (Rutgers Business School); Jie Gao (Rutgers University)
Best-of-Both-Worlds Guarantees with Fairer Endings Telikepalli Kavitha (TIFR, Mumbai); Surya Panchapakesan (National University of Singapore); Rohit Vaish (Indian Institute of Technology Delhi); Vignesh Viswanathan (University of Massachusetts Amherst); Jatin Yadav (Indian Institute of Technology Delhi)
Learning from a Mixture of Information Sources Nicole Immorlica (Microsoft); Brendan Lucier (Microsoft Research); Yaroslav Mukhin (Cornell University); Clayton Thomas (Rensselaer Polytechnic Institute); Ruqing Xu (Amazon)
Packing Linear Programs and Fractional Knapsack using Comparison Oracles Ritabrata Barat, Siddharth Barman, Nirjhar Das (Indian Institute of Science); Sukruta Prakash Midigeshi (Amazon)
Generalized Prophet Inequalities for Online Auctions Twan Kroll, Rebecca Reiffenhäuser (University of Amsterdam)
Quantile Meets Mean: Robust Pricing under Bounded Residual Surplus Dan She (Georgia Institute of Technology); Zhihao Gavin Tang (Shanghai University of Finance and Economics); Shixin Wang (Georgia Institute of Technology)
Time-Windowed Optimal Stopping Nikolai Gravin, Ping Li, Zhihao Gavin Tang (Shanghai University of Finance and Economics)
Identity Falsification and Quotas Sergei Mikhalishchev (HSE)
Information Elicitation by Ordinal Agreement Yiling Chen, Shi Feng (Harvard University); Grant Schoenebeck (University of Michigan); Fang-Yi Yu (George Mason University)
Auctions with Contract Design Xiaolin Bu, Jiarong Jin, Junzhu Ke (Shanghai Jiao Tong University); Pinyan Lu (Shanghai University of Finance and Economics); Biaoshuai Tao (Shanghai Jiao Tong University); Xiang Yan, Chunxue Yang, Haikuo Yang (Huawei Taylor Lab); Zhihua Zhu (Huawei Ads)
Decentralized Dynamics in Trading Networks Simon Finster (Johannes Kepler University Linz); Paul W. Goldberg (University of Oxford); Edwin Lock (King’s College London); Matilde Tullii (CREST - ENSAE)
Candidate Resignation Monotonicity in Approval-Based Committee Elections Yeeseok Oh (The University of Tokyo); Dominik Peters (CNRS, LAMSADE, Université Paris Dauphine)
Optimal Prophet Inequality for Unions of Easy Systems Hanrui Zhang, Yiran Zhang (Chinese University of Hong Kong)
Learning Anonymous Pricing for Online Resource Allocation Yifeng Teng (Google); Yifan Wang (Georgia Institute of Technology)
Individual Rationality in Size-Constrained Hedonic Games: Anonymous and Diversity Preferences Foivos Fioravantes (CVUT); Harmender Gahlawat (Université Clermont Auvergne, CNRS, Clermont Auvergne INP, Mines Saint-Étienne, LIMOS, Clermont-Ferrand, France); Nikolaos Melissinos (Charles University); Šimon Schierreich (Czech Technical University in Prague)
Beyond a Single Optimal Design: A Dynamical Systems Characterization of Online Allocation with Convex Costs Haoxin Sang (University of Alberta); Bo Sun (University of Ottawa); Xiaoqi Tan (University of Alberta)
Competitive Non-Clairvoyant KV-Cache Scheduling for LLM Inference Yiding Feng (Hong Kong University of Science and Technology); Zonghan Yang, Yuhao Zhang (Shanghai Jiao Tong University)
Strategyproof Mechanisms for Euclidean Facility Location Problems under $L_p$-norm Social Cost Hau Chan (University of Nebraska–Lincoln); Jianan Lin (Rensselaer Polytechnic Institute); Chenhao Wang (Beijing Normal University)
Fair and Efficient Allocations: Decision Problems in the Gap of Polynomial Hierarchy Xiaolin Bu, Biaoshuai Tao (Shanghai Jiao Tong University)
Pacing Equilibria in Abstract Mechanisms Salam Afiouni, Christian Kroer (Columbia University)
Does AI Help or Harm? Endogenous Information Acquisition with AI Advice Kexin Chen, Tao Lin, Jianwei Huang (The Chinese University of Hong Kong, Shenzhen)
Incentives and Outcomes in Bug Bounties Serena Wang (Google; The University of British Columbia); Martino Banchio (Università Bocconi; IGIER; Google); Krzysztof Kotowicz (Google); Katrina Ligett (Hebrew University); Preston McAfee, Eduardo Vela Nava (Google)
Feature-Based Dynamic Matching in the Dark Akshit Kumar (University of Toronto)
Preemptive Bipartite Matching with Secondary Chances Yifan Lin (Rutgers University); Yuhao Zhang (Shanghai Jiao Tong University); Weihao Zhu (University of Illinois Urbana-Champaign)
Dynamic Pooling and Regional Participation in Deceased-Donor Organ Allocation Genta Okada (University of Tokyo)
Computational Complexity of Strong and Average Justified Representation Yizhou Ai (University of Toronto); Biaoshuai Tao (Shanghai Jiao Tong University)
A Unified Framework for Single-item Diffusion Auctions Miao Li (ShanghaiTech University); Yao Zhang (Kyushu University); Dengji Zhao (ShanghaiTech University)
Fair and Efficient Investment in Public Transportation Martin Bullinger (University of Bristol); Edith Elkind (Northwestern University); Kassian Köck (Technical University of Munich)
Sample Complexity of the Second-Best Bilateral Trade Qiaoyun Shi (Harbin Institute of Technology, Shenzhen; Great Bay University); Shengxin Liu (Harbin Institute of Technology, Shenzhen); Zongqi Wan (Great Bay University)
Sample-Based Prophet Inequalities for Random Walks Daan Noordenbos, Pieter Kleer, Johan van Leeuwaarden (Tilburg University)
Optimal Subsidy for Envy-Free Allocations with Monotone Valuations in Multigraphs Bo Li (The Hong Kong Polytechnic University); Ankang Sun (School of Computer Science and Technology, Shandong University); Mashbat Suzuki (UNSW Sydney); Shiji Xing (The Hong Kong Polytechnic University)
Nonmonetary Allocation Under Congestion Alexander Estes (University of Maryland); Ankur Mani (Stony Brook University)
Content Generation: Human Creators, AI Learning, and Platform Design Seyedeh Parisa Moosavi (Rotman School of Management, University of Toronto); Ali Makhdoumi (Duke University); Azarakhsh Malekian (University of Toronto)
Beyond Incentive Compatibility: Rational Harm-Proof Transaction Fee Mechanisms Forest Zhang, Ke Wu, Elain Park (University of Michigan)
On the Hardness of Algorithmic Bayesian Persuasion with Succinctly Described Inputs Chirag Pabbaraju (Stanford University)
Tight Efficiency Bounds for the Probabilistic Serial and Related Mechanisms Jugal Garg (University of Illinois at Urbana Champaign); Yixin Tao (Shanghai University of Finance and Economics); László Végh (University of Bonn)
Informal and Privatized Transit: Incentives, Efficiency and Coordination Devansh Jalota (Georgia Institute of Technology); Matthew Tsao (Lyft Inc.)
Safe Strategies in Multi-Unit Auctions: Equilibria, Liquid Welfare, and Revenue Negin Golrezaei (MIT); Sourav Sahoo (Massachusetts Institute of Technology)
Flow Games with Public Arcs: the Least Core and the Nucleolus Tianhang Lu, Han Xiao, Qizhi Fang (Ocean University of China)
Pricing Blockchain Gossip through Bandwidth Fee Mechanisms Eleftheria Fassman (University of Michigan); Mahimna Kelkar (Columbia University); Benjamin Marsh (Sei Labs and University of Portsmouth); Ke Wu (University of Michigan)
Settling PROPm and PROPavg in Graphical Resource Allocations Bo Li (Hong Kong Polytechnic University); Ankang Sun (School of Computer Science and Technology, Shandong University); Ruijie Wang (Hong Kong Polytechnic University)
Explanation Systems for Approval-Based Multiwinner Voting Niclas Boehmer, Luca Kreisel (Hasso Plattner Institute); Jannik Peters (Shanghai University of Finance and Economics)
Degree-Parameterized Analysis of Sampling-Based Online Matching Pan Xu
Prices as Signals: Joint Design of Information and Pricing Zhicheng Du (Renmin University of China); Yanwei Sun (Imperial Business School); Zihe Wang (Renmin University of China); Jiahua Wu (Imperial College London)
Gaps and Augmentations in Bayesian Scheduling Ahuva Mu'alem (HIT)
Personalised versus Posted Pricing from Samples Daan Noordenbos, Pieter Kleer, Johan van Leeuwaarden (Tilburg University)
Online Stochastic Allocation with Increasing Returns Shuo Sun (The University of Wisconsin–Madison); Yunduan Lin (The Chinese University of Hong Kong)
Online Posted Pricing with Unknown Demand Nick Gravin (Shanghai University of Finance and Economics); Hao Li (Wuhan College); Zhiqi Wang (Shanghai University of Finance and Economics)
Simple Delay-Oblivious Policies Are Robust: Overbooking with Delayed Purchases Yiding Feng (Hong Kong University of Science and Technology); Puping Jiang (Shanghai Jiao Tong University); Wei Tang (Chinese University of Hong Kong)
Repeated Descent: A Framework for Online Budget-Feasible Auctions Andreas Charalampopoulos (Columbia University); Dimitris Fotakis, Thanos Tolias (National Technical University of Athens and Archimedes, Athena RC)
Matroid Packing Games: The Core and the Nucleolus Pengfei Liu, Han Xiao, Xin Chen, Qizhi Fang (Ocean University of China)
The Complexity of Justified Representation with Additive Utilities Carmel Baharav (Massachusetts Institute of Technology); Jakob de Raaij (Harvard University); Agnes Totschnig (Massachusetts Institute of Technology)
When Agents Propose Simple Contracts Paul Duetting (Google); Guru Guruganesh, Jon Schneider, Joshua Wang (Google Research)
Selling Surplus Foods Through Surprise Bags: Online Inventory Routing Across Dual Channels Yiding Feng, Chui Shan Lee, Guodong Lyu (Hong Kong University of Science and Technology); Huan Zheng (Shanghai Jiao Tong University)
Robust Learning with Private Information Kyohei Okumura (University of Wisconsin—Madison)
Simple Policies for Joint Pricing and Inventory Management Adam Elmachtoub, Harsh Sheth (Columbia University); Yeqing Zhou (Rotterdam School of Management)
Two-sided Market Design Meets Autobidding Yang Cai (Yale University); Chris Liaw, Aranyak Mehta (Google); Xizhi Tan (Stanford University); Mingfei Zhao (Google Research)
On best of both worlds allocations with subadditive valuations Uriel Feige (Weizmann Institute)
Nash Equilibria in Auctions with Pacing Strategies: Complexity and Inefficiency Aris Filos-Ratsikas, Charalampos Kokkalis, Mohamad Latifian (University of Edinburgh)
Principal-Agent Problems with Subcontracting Guru Guruganesh, Joshua Wang, Jon Schneider (Google Research)
Price of Stability in Failure-Aware Kidney Exchange Itai Feigenbaum, Felix Wilking (City University of New York); Francesco Zeolla (Boston University)
Mechanism Design via Market-Clearing Prices for Value Maximizers under Budget and RoS Constraints Xiaodong Liu (Gaoling School of Artificial Intelligence, Renmin University of China); Weiran Shen, Zihe Wang (Renmin University of China)
Driven to Collusion: Competitive Pricing under Independent Demand Model and Price Imitation Zongsen Yang, Pin Gao, Zizhuo Wang (The Chinese University of Hong Kong, Shenzhen)
Delegated Fair Division Argyrios Deligkas, Michail Fasoulakis, Stavros Ioannidis (Royal Holloway University of London); Alviona Mancho, Evangelos Markakis (Athens University of Economics and Business)
Optimal Metric Distortion for Learning-Augmented Matching on the Line Jabari Hastings (Stanford University); Marena Richter (University of Bonn)
A Markovian Approach for Cross-Category Complementarity in Choice Modeling Omar El Housni (Cornell University); Shuo Sun (The University of Wisconsin–Madison); Rajan Udwani (University of California, Berkeley)
What You Earn from What You Learn: Characterization and Complexity of the Value of Information Ratip Emin Berker, Ioannis Anagnostides, Emanuel Tewolde (Carnegie Mellon University); Brian Hu Zhang (MIT); Tuomas Sandholm, Vincent Conitzer (Carnegie Mellon University)
Network Topology That Excludes Braess’s Paradox and Maintains Monotonicity in Flows Over Time Xujin Chen, Xiyuan Deng, Changjun Wang (Academy of Mathematics and Systems Science, Chinese Academy of Sciences)
Optimal Prophet Inequalities for Gain from Trade Xujin Chen, Xiaodong Hu, Changjun Wang (Academy of Mathematics and Systems Science, Chinese Academy of Sciences); Qingjie Ye (East China Normal University)
Who Is Shown to Whom? Sorting, Screening, and Exposure Design on a Two-Sided Matching Platform Kei Ikegami (Yokohama City University)
When One Good Is Not Enough: EF1 and Pareto Optimality Are Not Compatible for Submodular Valuations Simon Mackenzie, Mashbat Suzuki (UNSW Sydney)
Strategyproof Multi-Resource Allocation in Cloud Computing via Adaptive-Speed Fairness Yunpeng Lou, Junjie Luo (Beijing Jiaotong University)
Signaling in Data Markets via Free Samples Nivasini Ananthakrishnan (University of California Berkeley); Alireza Fallah (Rice University); Michael Jordan (UC Berkeley)
The Economics of Proof-of-Useful-Work Rafael Pass (Pearl Research, Cornell University, Technion)
Call for Tutorials
We invite you to submit proposals for tutorials at WINE 2026. Tutorials are planned to be held in person on December 1 as part of the conference program.
Tutorials provide a valuable opportunity to educate the community, especially younger scholars and researchers, about emerging research areas and topics that deserve greater attention. They offer a structured, formal setting to introduce colleagues to an area of interest. This year, while we welcome alternative formats (which should be described in your proposal), we recommend two possible options: (1) a two-hour session comprising two one-hour blocks of introductory material; or (2) a two-hour session with one hour of introductory material followed by a second hour featuring shorter talks that highlight recent research developments related to the tutorial content. In both cases, the two blocks would be separated by a short break (e.g., coffee break).
Tutorial proposals should be 2–3 pages long and contain:
Title of the tutorial and brief (1–2 paragraph) abstract
Keywords and sub-areas relevant to the WINE community
Names, affiliations, contact information, and short biographies of the organizers
Suggested format and duration of the tutorial
Outline of the content
Rationale for the tutorial (e.g., timeliness and goals)
Target audience and required prior knowledge
Other venues where a similar tutorial has been presented (if any)
Any special accommodations required for the tutorial
The tutorials will take place on December 1, 2026, at the University of Hong Kong. Please find the schedule below.
Morning
Mixed Fair Division: Truth, Justice and Best-of-Both-Worlds Fairness Xinhang Lu
Problem-Dependent Learning and Decision Making Yunbei Xu and Jian Qian
Afternoon
Large Language Models for Revenue Management: Introduction and Recent Advances Jinbiao Chen, Hanzhang Qin, and Ruihao Zhu
Incentives for Early Arrival in Online Cooperative Games: Theory, Mechanisms, and Open Directions Dengji Zhao
Awards
Best Paper Award
The Limits of Interval-Regulated Price Discrimination Kamesh Munagala, Yiheng Shen (Duke University); Renzhe Xu (Shanghai University of Finance and Economics)
Best Student Paper Award
Degree-bounded Online Bipartite Matching: OCS vs. Ranking Yilong Feng, Haolong Li, Xiaowei Wu, Shengwei Zhou (University of Macau)
Outstanding Paper Awards
Improved Budget-Feasible Mechanisms for Submodular Valuations: Beating 4 Deterministically in Linear Time Kai Han, Pinyan Lu (Shanghai University of Finance and Economics)
Constant Inapproximability of Pacing Equilibria in Second-Price Auctions Xi Chen, Yuhao Li (Columbia University)
Bounds on the revenue gap of linear posted pricing for selling a divisible item Ioannis Caragiannis, Zhile Jiang (Aarhus University); Apostolis Kerentzis (Hellenic Air Force)
Graduating Bits
We are excited to continue hosting the Graduating Bits session, dedicated to graduating students and postdoctoral researchers, with priority given to those entering the job market this academic year. Held as a separate session, Graduating Bits will give each participant a few minutes to introduce themselves and present their research in a lightning-talk format. Our goal is to showcase the exciting work of the next generation of our community, highlight their contributions, and foster connections as they transition to the next stage of their careers. Participants need to register for the conference (or receive travel awards for registration waiver).
If you are interested in participating, please email wine2026conf@outlook.com with the subject line: Graduating Bits – [Your Name]. Please attach your CV and indicate whether you are entering the job market this academic year.
Registration
Please register for the 22nd Conference on Web and Internet Economics
(WINE 2026) using this link.
Important Warning: Fraudulent Travel and Hotel Emails
We have been informed that some authors have received unsolicited emails from reservation@gtravelhost.com requesting arrival and departure dates and offering hotel-booking services.
Please note that WINE 2026 has not appointed or authorized any travel agency, and this sender is not affiliated with the conference. Please do not reply, click any links, provide personal or payment information, or make reservations through this email.
Please rely only on information provided through the WINE 2026 official website and communications from the conference organizers. If you receive a similar message, please mark it as spam or phishing and delete it.
Travel Awards for Students and Postdoctoral Fellows
WINE 2026 will offer a limited number of registration waivers to students and postdocs short
on financial support. To apply, please email
wine2026conf@outlook.com
with the title “Travel Award Application” by October 31.
The email shall include a concise description of your name and affiliation, whether you will
be presenting an accepted paper or at the Graduating Bits, and a declaration from your advisor
(for PhD students and postdocs) or your department administration (for other students).
We will contact applicants about the results in early November, before the early-bird deadline.
Early Registration Deadline
Early registration deadline:
November 6, 2026, at 11:59 PM Hong Kong local time (HKT).
Late registration rates apply after this deadline.
Registration Rates
Student
Regular
Early Registration
2,800 HKD
4,000 HKD
Late Registration
3,500 HKD
5,000 HKD
Visa Information
Most international participants do not require a visa to visit Hong Kong for a short stay. Nationals of approximately 170 countries and territories may enter Hong Kong visa-free for periods ranging from 7 to 180 days, depending on nationality and the type of travel document held. Conference attendance and participation in short-term seminars or meetings are generally permitted for visitors. Participants are strongly encouraged to check the requirements applicable to their individual nationality or travel document well in advance of travel. For the official and most up-to-date information on visa requirements, eligibility for visa-free entry, permitted duration of stay, and other entry conditions, please consult the Hong Kong Immigration Department’s Visit Visa / Entry Permit Requirements (the table under Part II is a concise summary of the most important information).
If you do need a visa to travel to Hong Kong, please fill out this form to request an invitation letter.
Local Information
The conference takes place at the University of Hong Kong (specific building / rooms to be announced). See below for information about accommodation and local transportation.
Important Warning: Fraudulent Travel and Hotel Emails
We have been informed that some authors have received unsolicited emails from reservation@gtravelhost.com requesting arrival and departure dates and offering hotel-booking services.
Please note that WINE 2026 has not appointed or authorized any travel agency, and this sender is not affiliated with the conference. Please do not reply, click any links, provide personal or payment information, or make reservations through this email.
Please rely only on information provided through the WINE 2026 official website and communications from the conference organizers. If you receive a similar message, please mark it as spam or phishing and delete it.
Where to stay
HKU has its own station on the MTR Island Line, so any hotel near the line is an easy commute.
The hotels below are grouped by how many stops they are from HKU Station.
There are no special conference rates, so please book directly with the hotel or through a booking site.
Schematic only, not to scale. One Mid-Levels option off the line is listed separately below.
$
Budget
$$
Mid-range
$$$
Upscale
$$$$
Luxury
Price bands are indicative only. Rates vary widely by date, so please check current prices when booking.
Near HKU Station
Walk to the venue, about 10–15 minutes door to door
Quiet residential setting above Central, long popular with academic visitors. Bus route 23 stops near HKU's East Gate, or take a taxi. The hotel also runs a scheduled shuttle to Central and Admiralty.
From the airport to HKU
Hong Kong International Airport (HKG) is about 35 km from HKU. The journey takes about 40–60 minutes depending on how you travel.
All the options below leave from just outside the arrivals hall.
Shek Tong Tsui Complex, Queen's Road West; then about 10 min on foot to campus
Lowest cost
* Bus time excludes waiting and walking; allow longer in traffic. See also HKU's Getting to HKU guide.
Option 1: Airport Express and MTR (recommended)
After collecting your luggage, follow the signs to the Airport Express. The platform is directly opposite the arrivals hall exit.
Ride to the last stop, Hong Kong Station in Central (about 24 minutes).
Follow the signs through the underground walkway to Central Station and take the Island Line towards Kennedy Town.
Get off at HKU (3 stops), or at Sheung Wan or Sai Ying Pun for hotels in those areas.
Pay with an Octopus card or an eligible Visa, Mastercard or UnionPay contactless card (UnionPay debit cards are excluded), or buy a ticket at the Airport Express counter. With a bank card, use the designated contactless gates and the same card or device to enter and exit. With heavy luggage, you can take a taxi from the rank at Hong Kong Station for the last part of the trip (about 10–15 minutes to the HKU area). Airport Express fares and times
Option 2: Taxi
Follow the signs to the taxi rank outside the arrivals hall.
Join the queue for red (urban) taxis. Green and blue taxis do not serve Hong Kong Island.
Show the driver your hotel's name and address, ideally in Chinese as well as English.
Tunnel tolls are added to the metered fare, plus a small charge for each item of luggage in the boot. All taxis must now accept at least two electronic payment methods, but check which ones before boarding; carrying some Hong Kong dollars in cash is a good idea. Taxi information
Option 3: Airport bus
Follow the signs to the bus terminus (Ground Transportation Centre) outside the arrivals hall.
Take Citybus route A10 for Queen's Road West and Kennedy Town, or route A11 for Sheung Wan and Central. Check the route map at the stop for the one nearest your hotel. For HKU, get off A10 at Shek Tong Tsui Complex, Queen's Road West, then walk about 10 minutes to campus.
Pay with Octopus, a supported contactless card, or exact cash in HKD; no change is given.
A10 from the airport (daily): 06:50–09:50 hourly; 10:30; 11:00–00:00 every 30 min; 00:20. Current timetable
Overnight routes NA10 and NA11 run after the Airport Express has stopped for the night; NA10 also stops at Shek Tong Tsui Complex. Cityflyer buses have luggage racks. All Cityflyer routes
Reimbursement: keep your payment record; an invoice may not be available on board.
Getting around
To the campus
Use HKU Station Exit A or C and follow the signs to campus. Follow the conference venue directions for the final walk to your building and room.
The lifts at HKU Station exits A1/A2 provide an accessible route to the Main Campus. HKU Station map (PDF)
Paying for transport
Octopus is accepted on the MTR and many bus, minibus, tram and ferry services, and at participating shops.
Hong Kong hotels fill quickly in December. We recommend booking as soon as your travel plans are confirmed. Check the total price, cancellation policy and any maintenance notices before paying.
WINE 2025 is accepting sponsors! Sponsoring WINE 2025 offers a unique opportunity to connect your organization with the brightest minds in the field. Your support will not only enhance the conference experience for all attendees but will also position your brand at the forefront of innovation, thought leadership, and talent recruitment. If you are interested in becoming a sponsor, please see the sponsorship opportunities below.
🥈 Silver Sponsors ($1,500) 🥈
Your sponsorship will be acknowledged at the conference venue, in the conference program, on the conference website, and in the conference proceedings.
You will have the opportunity to include your promotional materials among the items given to registered participants.
🥇 Gold Sponsors ($3,000) 🥇
In addition to everything above:
You will have the opportunity to give a 15-minute talk about your organization during the conference.
💎 Diamond Sponsors ($5,000) 💎
In addition to everything above:
An event will be named for your organization. For example, it could be our conference dinner that would be advertised as the “conference dinner, sponsored by YOUR ORGANIZATION.”
We will provide you with a complimentary registration.
