arbiter
JournalsAccount

Observational Learning and Information Disclosure in Search Markets

Ziying Fan et al.

Management Science2026https://doi.org/10.1287/mnsc.2023.00917article
FT50UTD24AJG 4*ABDC A*
Weight
0.50

Abstract

We develop and estimate a structural model of buyers’ observational learning, search, and bidding, using unique data on in-person home viewings and transactions. We use the estimated model to quantify the welfare impact of different information disclosure rules. Our findings indicate that prohibiting the disclosure of home viewing information while permitting only the disclosure of time-on-market would extend the sale time and raise the transaction price, benefiting sellers but harming buyers on average. This paper was accepted by Raphael Thomadsen, marketing. Funding: Z. Fan gratefully acknowledges financial support from the National Natural Science Foundation of China [Grant 72533006]. X. Weng gratefully acknowledges funding from the National Natural Science Foundation of China [Grants 72225001, 72561160161, and 72192843], as well as from the Wuhan East Lake High-Tech Development Zone (also known as the Optics Valley of China, or OVC) National Comprehensive Experimental Base for Governance of Intelligent Society. L.-A. Zhou gratefully acknowledges support from the National Natural Science Foundation of China [Grant 72192844]. Supplemental Material: The data files are available at https://doi.org/10.1287/mnsc.2023.00917 .

Open via your library →

Cite this paper

https://doi.org/https://doi.org/10.1287/mnsc.2023.00917

Or copy a formatted citation

@article{ziying2026,
  title        = {{Observational Learning and Information Disclosure in Search Markets}},
  author       = {Ziying Fan et al.},
  journal      = {Management Science},
  year         = {2026},
  doi          = {https://doi.org/https://doi.org/10.1287/mnsc.2023.00917},
}

Paste directly into BibTeX, Zotero, or your reference manager.

Flag this paper

Observational Learning and Information Disclosure in Search Markets

Flags are reviewed by the Arbiter methodology team within 5 business days.

Evidence weight

0.50

Balanced mode · F 0.40 / M 0.15 / V 0.05 / R 0.40

F · citation impact0.50 × 0.4 = 0.20
M · momentum0.50 × 0.15 = 0.07
V · venue signal0.50 × 0.05 = 0.03
R · text relevance †0.50 × 0.4 = 0.20

† Text relevance is estimated at 0.50 on the detail page — for your query’s actual relevance score, open this paper from a search result.