About

Quan Wen is a Robert R. Richards Professor of Economics and Associate Chair in the Department of Economics at the University of Washington. He holds a Ph.D. in Economics from the University of Western Ontario, obtained in 1991, and an M.A. in Economics from the same institution earned in 1988. His undergraduate degree is a B.Sc. (Honors) in Mathematics from Jilin University in China, completed in 1985. His research focuses on game theory and microeconomic theory, with notable contributions to the understanding of repeated games, bargaining models, auction mechanisms, and strategic behavior in economic settings. Wen has authored numerous articles in leading journals, exploring topics such as enforcement observability, non-cooperative foundations of competitive divisions, information acquisition, and punishment strategies in repeated interactions. He has also taught advanced microeconomics courses at the graduate and undergraduate levels, contributing to the academic development of students in economic theory.

Research topics

• Economics
• Monetary economics
• Finance
• Microeconomics
• Business
• Financial economics

Selected publications

• On unanimity bargaining with commitment

  Economic Theory Bulletin · 2026-04-08

  articleOpen accessSenior author

  Abstract We study a multilateral bargaining game in which players can attempt short-lived commitments before bargaining. Existing work shows that simultaneous commitments under unanimity lead to inefficient delayed agreements due to players’ strategic over-commitments. We show that this inefficiency is not inherent in unanimity itself, but arises from a coordination failure caused by the timing of simultaneous commitments. We introduce a sequential commitment protocol: Players are randomly ordered to make their commitment attempts after observing prior stochastic commitments, modeling real-time credibility updating during negotiations. Sequential commitment yields efficient and immediate agreements in the unique stationary Markov-perfect equilibrium: The first successful committer effectively becomes the proposer, while subsequent players do not attempt to demand more than their continuation payoffs. The result is robust to heterogeneity in players’ time preferences, commitment powers, and their likelihood to be the proposer. Our findings highlight how inefficiency under unanimity arises from timing frictions—not the rule itself—and demonstrate that structured commitment can promote efficient cooperation.

  PublisherOA PDFDOI

• A multi-operating condition collaborative prediction method for gear pump flow rate based on G-LCC neural network

  Multiscale and Multidisciplinary Modeling Experiments and Design · 2026-04-10

  articleOpen access

  Gear pumps are widely used in hydraulic systems, where accurate flow rate prediction is essential for improving system efficiency, reliability, and intelligent monitoring. However, traditional experimental data acquisition are costly and time-consuming, while the coverage of operating conditions is often insufficient, limiting the effectiveness of data-driven prediction models. To address these challenges, this paper proposes a collaborative prediction framework that integrates ANSYS-FLUENT finite element simulation with a gated neural network. In this study, pressure–flow rate time-series data collected at the meshing position of gear pumps are employed. A Generative Adversarial Network (GAN) is utilized to construct an augmented sample set, and a training dataset incorporating physical mechanisms is established. On this basis, a gated LSTM-CNN-CBAM (G-LCC) neural network is designed, which combines multi-scale feature extraction with a dynamic gating mechanism. Experimental results show that under varying inlet velocities and rotational speeds, the proposed G-LCC achieves average R2 values of 0.749 and 0.833, respectively, corresponding to relative improvements of 10.1% (from 0.673 to 0.749) and 16.9% (from 0.692 to 0.833) compared to the traditional LSTM-CNN model. Furthermore, in cross-equipment tests involving three heterogeneous gear pumps, the model achieves an average R2 of 0.692, verifying both the feasibility of substituting simulations for physical experiments and the strong generalization capability of the proposed approach. This study presents an effective integrated framework that combines CFD-based physical modeling with a gated neural network architecture tailored for gear pump flow prediction. By addressing the spatiotemporal coupling of internal flow fields, the G-LCC model demonstrates superior predictive accuracy and provides a robust tool for the intelligent monitoring of hydraulic systems.

  PublisherOA PDFDOI

• TMEA: Task-Modularized Evolutionary Aggregation for Federated Continual Learning

  2025-11-08

  article

  Federated Learning (FL) preserves data privacy by keeping raw data locally and exchanging only model parameters. Traditional FL methods are built on the assumption of static local datasets, which makes them poorly suited for the realistic scenario where clients continuously gather new tasks with new data. Naively retraining on growing data triggers catastrophic forgetting and erases previously acquired knowledge. Federated Continual Learning (FCL) has been proposed to address this challenge. However, conventional strategies such as generative replay, architecture expansion, and knowledge distillation exhibit markedly inferior performance when confronted with a large number of tasks. To address these challenges, we propose Task-Modular Evolutionary Aggregation (TMEA). For each incoming task, TMEA trains and stores a lightweight task-specific module, thereby isolating and safeguarding prior knowledge of previous tasks. Furthermore, we propose an evolutionary client selection and aggregation mechanism that actively identifies those clients whose local models exhibit the largest parameter divergence. These selected models are fused into a unified global representation, thereby accelerating convergence. Extensive experiments conducted across a variety of benchmarks have demonstrated that TMEA achieves significant improvements in resistance to catastrophic forgetting and aggregation efficiency.

  PublisherDOI

• Coherent forecasts for tourism demand with automated immutability constraints

  Tourism Management · 2025-11-12 · 1 citations

  articleOpen access1st author
  PublisherOA PDFDOI

• Influencing factors of residents’ subjective well-being in rural tourism destinations: A case study of Licha village in Guangdong, China

  Journal of Chinese Architecture and Urbanism · 2025-12-03

  articleOpen access

  Sustainable rural development is increasingly important in the context of globalization, with rural tourism driving spatial revitalization and enhancing residents’ well-being. This study investigates how rural tourism shapes residents’ subjective well-being (SWB) in Licha village, Guangdong, China. Using semi-structured interviews with 23 residents and grounded theory coding (open, axial, selective), we inductively develop a three-stage mechanism linking tourism development to well-being. Our findings are as follows: (i) tourism improves living conditions and creates new opportunities for participation, strengthening social ties and cultural recognition. (ii) Residents’ well-being is formed through a sequence of “structural support, relational embedding, and emotional transformation,” driven by five factors: spatial adaptation, resident participation, relationship reconstruction, identity generation, and place attachment. (iii) While overall effects are positive, boundary conditions—such as cultural commodification and disruptions to everyday routines—can weaken this pathway unless mitigated through participatory governance and heritage stewardship. The main contribution is a resident-centered, transferable framework that explains how rural tourism converts material improvements into durable place attachment and SWB, offering actionable guidance for planning and community management in traditional village destinations.

  PublisherDOI

• Stochastic Commitment in Repeated Games

  SSRN Electronic Journal · 2025-01-01

  preprintOpen accessSenior author
  PublisherDOI

• EXAMINING THE EFFECTS OF PERCEIVED VALUE ON BEHAVIORAL INTENTION OF GREEN TOURIETS IN HULUNBUIR GRASSLAND, CHINA

  PLANNING MALAYSIA · 2025-07-18 · 1 citations

  articleSenior author

  This paper reviews relevant research on green tourism, extends the Theory of Planned behavior (TPB) model, perceived value, and Stimulus-Organism-Response (SOR) theory, and develops a mechanism model to investigate how perceived value influences green tourists' behavioral intentions in the context of the Hulunbuir Grassland. To address the research gap concerning the underlying mechanisms influencing tourists’ behavioral intentions in the context of green tourism, this study collected and analysed data from 311 green tourists. Statistical techniques were employed to examine the data, and Structural Equation Modeling (SEM) was used to test the proposed hypotheses and validate the theoretical framework. Empirical findings indicate that perceived value consists of four dimensions—environmental, emotional, functional, and social value—with environmental value exerting the strongest positive influence on green tourists’ behavioral intentions. However, the effects of behavioral attitude and perceived behavioral control on behavioral intention were found to be statistically insignificant, whereas subjective norms exhibited a significant influence. The primary contribution of this study lies in the integrated application of the Theory of Planned Behavior (TPB), perceived value theory, and the Stimulus–Organism–Response (SOR) framework to the context of green tourism. This comprehensive theoretical model underscores the pivotal role of perceived value in shaping tourists’ behavioral intentions. This provides a scientific basis and practical guidance for policy formulation aimed at green tourism development in Hulunbuir Grassland, thereby promoting its sustainable tourism growth. The novelty of the research stems from its comprehensive analysis of these roles of environmental, emotional, functional, and social values in green tourism through a multidimensional approach to perceived value, addressing gaps in existing literature and enhancing the understanding of factors affecting green tourists' behavioral intentions.

  PublisherDOI

• Pig-to-human kidney xenotransplants using genetically modified minipigs

  Cell Reports Medicine · 2024-09-23 · 46 citations

  articleOpen access

  This study develops an observational model to assess kidney function recovery and xenogeneic immune responses in kidney xenotransplants, focusing on gene editing and immunosuppression. Two brain-dead patients undergo single kidney xenotransplantation, with kidneys donated by minipigs genetically modified to include triple-gene knockouts (GGTA1, β4GalNT2, CMAH) and human gene transfers (hCD55 or hCD55/hTBM). Renal xenograft functions are fully restored; however, immunosuppression without CD40-CD154 pathway blockade is ineffective in preventing acute rejection by day 12. This rejection manifests as both T cell-mediated rejection and antibody-mediated rejection (AMR), confirmed by natural killer (NK) cell and macrophage infiltration in sequential xenograft biopsies. Despite donor pigs being pathogen free before transplantation, xenografts and recipient organs test positive for porcine cytomegalovirus/porcine roseolovirus (PCMV/PRV) by the end of the observation period, indicating reactivation and contributing to significant immunopathological changes. This study underscores the critical need for extended clinical observation and comprehensive evaluation using deceased human models to advance xenograft success. • Successfully completed two pig-to-human kidney transplants in brain-dead human recipients • Renal function restoration in kidney xenografts from genetically modified minipigs • Acute rejection occurred by day 12 without CD40-CD154 blockade • Reactivation of PCMV led to significant immunopathological changes in recipients Yi Wang et al. successfully performed two pig-to-human kidney xenotransplants using genetically modified minipigs, which led to restored renal functions. The study described immunological and pathological changes and the impact of porcine cytomegalovirus reactivation on graft survival, highlighting the potential of this model to advance xenotransplantation toward clinical applications.

  PublisherDOI

• An observability paradox in linked enforcement

  Games and Economic Behavior · 2024-08-03 · 2 citations

  article1st author
  PublisherDOI

• An Observability Paradox in Linked Enforcement

  SSRN Electronic Journal · 2024-01-01

  preprintOpen access1st authorCorresponding
  PublisherDOI

Frequent coauthors

• Lei Jiang

  Kent State University

  244 shared

• Vikas Agarwal

  University of Liechtenstein

  242 shared

• Harold Houba

  Vrije Universiteit Amsterdam

  46 shared

• Evgenia Motchenkova

  Tinbergen Institute

  30 shared

• Turan G. Bali

  Georgetown University

  15 shared

• Jesse A. Schwartz

  McGill University

  10 shared

• Jennie Bai

  Georgetown University

  9 shared

• Avanidhar Subrahmanyam

  9 shared