Evidence map›Paper›PMID 36714880›Full record

ArticlePNAS nexus2022

Macroscopic properties of buyer-seller networks in online marketplaces.

Alberto Bracci, Jörn Boehnke, Abeer ElBahrawy, Nicola Perra, Alexander Teytelboym, Andrea Baronchelli

Abstract read
In one paragraph

Article in PNAS nexus, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

3 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors.

Alberto BracciDepartment of Mathematics, City, University of London, London EC1V 0HB, UK.ORCID https://orcid.org/0000-0002-9506-5645
Jörn BoehnkeGraduate School of Management, University of California Davis, 1 Shields Ave Davis, CA 95616, USA.ORCID https://orcid.org/0000-0003-0890-7275
Abeer ElBahrawyChainalysis Inc, New York, NY 10011, USA.
Nicola PerraSchool of Mathematical Sciences, Queen Mary University of London, London E1 4NS, UK.ORCID https://orcid.org/0000-0002-5559-3064
Alexander TeytelboymDepartment of Economics, University of Oxford, Oxford OX1 3UQ, UK.ORCID https://orcid.org/0000-0002-6570-1903
Andrea BaronchelliDepartment of Mathematics, City, University of London, London EC1V 0HB, UK.ORCID https://orcid.org/0000-0002-0255-0829

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Online marketplaces are the main engines of legal and illegal e-commerce, yet their empirical properties are poorly understood due to the absence of large-scale data. We analyze two comprehensive datasets containing 245M transactions (16B USD) that took place on online marketplaces between 2010 and 2021, covering 28 dark web marketplaces, i.e. unregulated markets whose main currency is Bitcoin, and 144 product markets of one popular regulated e-commerce platform. We show that transactions in online marketplaces exhibit strikingly similar patterns despite significant differences in language, lifetimes, products, regulation, and technology. Specifically, we find remarkable regularities in the distributions of transaction amounts, number of transactions, interevent times, and time between first and last transactions. We show that buyer behavior is affected by the memory of past interactions and use this insight to propose a model of network formation reproducing our main empirical observations. Our findings have implications for understanding market power on online marketplaces as well as intermarketplace competition, and provide empirical foundation for theoretical economic models of online marketplaces.

Indexed as

buyer–seller networkscomplex networksdark web marketplacesonline marketplaces

Identifiers

PMID36714880
PMCPMC9802486

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.