Evidence map›Paper›PMID 41719310›Full record

ArticlePloS one2026

Research on the mechanism how consumer expected regret affects market access for pirated information products.

Jia Xue, Peng Gao, Youshi He, Zhiwen Li, Hanyang Xu

Abstract read
In one paragraph

Article in PloS one, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing 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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

5 authors.

Jia XueManagement College, Jiangsu University of Technology, Changzhou, China.ORCID https://orcid.org/0009-0001-8940-847X
Peng GaoManagement College, Jiangsu University of Technology, Changzhou, China.
Youshi HeManagement College, Jiangsu University, Zhenjiang, China.
Zhiwen LiManagement College, Jiangsu University, Zhenjiang, China.
Hanyang XuNari Research Institute, Nari Group Corporation, Nanjing, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

In the past, traditional supervision of pirated information products mostly adopted a post incident disposal model. Under the supervision of government departments and the continuous improvement of manufacturer product quality, the gap in quality and user experience between genuine and pirated products is expanding, thereby curbing the spread of pirated products. At present, with the emergence of cloud services, the spread of information products has changed from offline physical transactions to online digital services, and the sales model has changed from a one-time buyout to a subscription system of continuous payment. In this new context, there have been significant changes in the attributes of pirated information products and customer consumption patterns. The utility analysis model of quality preference and law enforcement supervision may not be well adapted in some cases. However, this study introduces regret theory and expected regret parameters to construct an impact analysis model on the market access of pirated information products, which is closer to the behavioral decision-making patterns of consumers in cloud service scenarios. The conclusion of this study indicates that customers' sensitivity to expected regret directly affects the quality and price decisions of product manufacturers. The expected regret negative effect of pirated products also provides a more scientific basis for piracy regulation. Appropriate expected regret is not only beneficial for increasing legitimate consumer surplus and product manufacturer profits, but also promotes an increase in overall social welfare.

Indexed as

Consumer BehaviorEmotionsCommerceHumans

Identifiers

PMID41719310
PMCPMC12923053

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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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.