Evidence map›Paper›PMID 37089339›Full record

ArticleHeliyon2023

Research on the strategy of knowledge sharing among logistics enterprises under the goal of digital transformation.

Xue Yang, Langxuan Pan, Aifeng Song, Xiangqian Ma, Juan Yang

Abstract read
In one paragraph

Article in Heliyon, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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.

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3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. 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

5 authors.

Xue YangSchool of Management and Economics, North China University of Water Resources and Electric Power, Zhengzhou, 450046, China.
Langxuan PanSchool of Management and Economics, North China University of Water Resources and Electric Power, Zhengzhou, 450046, China.
Aifeng SongSchool of Management and Economics, North China University of Water Resources and Electric Power, Zhengzhou, 450046, China.
Xiangqian MaSchool of Management and Economics, North China University of Water Resources and Electric Power, Zhengzhou, 450046, China.
Juan YangSchool of Management and Economics, North China University of Water Resources and Electric Power, Zhengzhou, 450046, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Accelerating the digital transformation of the traditional logistics industry is an important step toward the high-quality development of China's economy, a fundamental task to ensure the smooth operation of the entire industrial chain, and a necessary path to building the Digital-China. Carrying out knowledge sharing can help promote knowledge integration and absorption among logistics enterprises, optimize the allocation of enterprise resources and enhance their business capabilities. To explore the knowledge sharing strategy selection mechanism of logistics enterprises in the process of digital transformation, this paper establishes a dynamic game model of knowledge sharing among logistics enterprises based on evolutionary game theory, and further demonstrates the reliability of the model by combining enterprise data with Matlab2022a for case analysis. The results show that: (1) the higher the cost of knowledge sharing in the digital transformation of logistics, the lower the willingness of enterprises to share; (2) when a single enterprise provides too much knowledge, it may trigger the breach of trust of the other party to "hitchhiking"; (3) appropriately increasing the amount of penalty for breach of trust helps promote both parties to reach a knowledge sharing strategy; (4) The benefit distribution coefficient significantly affects the knowledge sharing strategies of both parties, and a reasonable benefit distribution coefficient can prompt both parties to reach a stable strategy quickly; (5) Government financial incentives positively promote enterprises' willingness to share knowledge, and both parties can obtain higher revenue when a sharing strategy is reached. Thus, this paper explores the knowledge sharing strategy and evolution mechanism in the process of digital transformation of the logistics industry from the micro perspective of enterprises, which is of great practical significance and reference value.

Indexed as

Digital transformationEvolutionary gameKnowledge sharingLogistics enterprisesStrategy

Identifiers

PMID37089339
PMCPMC10113861

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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.