Signaling Effects Under Dynamic Capacity in Online Matching Platforms: Evidence from Online Health Consultation Communities

Forthcoming at Information Systems Research.

51 Pages Posted: 27 Jan 2024

See all articles by Liwei Chen

Liwei Chen

University of Cincinnati - Lindner College of Business

Arun Rai

Georgia State University - J. Mack Robinson College of Business

Wei Chen

University of Connecticut - Department of Operations & Information Management

Xitong Guo

Harbin Institute of Technology

Date Written: January 24, 2024

Abstract

Match formation is challenging in online matching platforms where suppliers are subject to dynamic capacity constraints. We provide a theoretical foundation for understanding how online matching platforms support the transmission and triangulation of multi-source information for consumers to infer provider service quality and dynamic capacity states, and achieve desirable matching outcomes. Situating this study in the context of an online health consultation community (OHCC) and drawing upon signaling theory, we theorize how physicians' owned and earned signals influence physicians' voluntary online consultations with new patients they have not consulted with previously. Importantly, we articulate how these signaling effects are contingent upon physicians' dynamic capacity in OHCC. We collected longitudinal data from a large OHCC in China and used a hidden Markov model (HMM) to characterize the dynamic physician capacity in the OHCC and test the hypotheses. Our findings reveal that service professionals' owned and earned signals interactively work together to balance supply and demand dynamically, and thereby facilitating matchmaking. In OHCCs, where physicians provide voluntary service beyond their primary jobs at hospitals, we find that owned and earned signals increase patient consultations in different patterns contingent upon physicians’ capacity states. In addition, we discover the complementary and substitute relationships between owned signals and earned signals change when physicians are in different capacity states. The findings have significant implications for our understanding of online match formation under dynamic capacity constraints and the design of OHCCs.

Keywords: Online match formation, dynamic capacity states, hidden Markov model, online health consultation communities, signaling theory, complementary and substitute relationships

Suggested Citation

Chen, Liwei and Rai, Arun and Chen, Wei and Guo, Xitong, Signaling Effects Under Dynamic Capacity in Online Matching Platforms: Evidence from Online Health Consultation Communities (January 24, 2024). Forthcoming at Information Systems Research., Available at SSRN: https://ssrn.com/abstract=4705135

Liwei Chen (Contact Author)

University of Cincinnati - Lindner College of Business ( email )

P.O. Box 210195
Cincinnati, OH 45221-0195
United States

Arun Rai

Georgia State University - J. Mack Robinson College of Business ( email )

P.O. Box 4050
Atlanta, GA 30303-3083
United States

Wei Chen

University of Connecticut - Department of Operations & Information Management ( email )

1 University Pl
Stamford, CT 06902
United States

Xitong Guo

Harbin Institute of Technology ( email )

huanghe road
harbin, heilongjiang 150001
China

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