Evidence map›Paper›PMID 37007730›Full record

ArticleHumanities & social sciences communications2023

The impact of capitalist profit-seeking behavior by online food delivery platforms on food safety risks and government regulation strategies.

Xiaoting Dai, Linhai Wu

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Article in Humanities & social sciences communications, 2023. 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.

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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

2 authors.

Xiaoting DaiSchool of Business, Jiangnan University, Wuxi, China.
Linhai WuSchool of Business, Jiangnan University, Wuxi, China.ORCID 0000-0003-0397-9579

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Capital monopolized platforms that have emerged based on the new "Internet Plus" economic form will undoubtedly distort market competition. Taking the Meituan online food delivery platform in China as an example, this study (1) investigates the game of interests between the platform and restaurants and the resulting impact on food safety risks, and (2) explores the interactions among government regulations, platform profit strategy, and restaurant behavior. An evolutionary game model between the capital-monopolized online food delivery platform and the restaurants was developed with an optional promotion fee and government regulation level as variables. Analysis of four equilibrium situations derived from the evolutionary game model showed that the platform always pursued high overall profit in every equilibrium situation. This capitalist profit-seeking behavior will most likely reduce the profit margins and even the survival space of restaurants on the platform, forcing them to engage in opportunistic behavior and illegal production, thereby resulting in increased food safety risks in online food delivery and consequently increased government regulation costs. Although increased government regulation can change the production strategy of restaurants, it cannot change the platform's capitalist profit-seeking behavior. The platform's overall payoff is not reduced due to increased regulation, which once again proves the profit-seeking nature of capital. The strategy of low commissions but high promotion fees may require greater government regulation to restrain the opportunistic behavior of restaurants. Therefore, the Chinese government regulators can achieve a win-win situation of improved government regulation efficiency and reduced regulation costs by designing new regulatory strategies that do not reduce the platform's overall payoff.

Indexed as

EconomicsEnvironmental studiesSocial policy

Identifiers

PMID37007730
PMCPMC10039440

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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.