Evidence map›Paper›PMID 41501117›Full record

ArticleScientific reports2026

Risk network analysis and simulation research in municipal engineering projects contracted by China in Saudi Arabia.

Rami Talal T Alotaibi

Abstract read
In one paragraph

Article in Scientific reports, 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

1 author.

Rami Talal T AlotaibiFaculty of Infrastructure Engineering, Dalian University of Technology, Dalian, 116024, Liaoning, China. ramit@mail.dlut.edu.cn.

Funding

the National Natural Science Foundation of China 52078101
6 · The paper itself

Abstract

This study develops a risk network model using social network analysis (SNA) to address the complex interdependencies among risk factors in municipal engineering projects contracted by Chinese firms in Saudi Arabia. The four-type risk classification framework (Types I-IV) was introduced to categorize risks based on their network positions and characteristics. A case study of a large-scale municipal project was conducted, and the results showed that 34 risk factors were classified into 4 Type I risks, 2 Type II risks, 17 Type III risks, and 11 Type IV risks. Based on the network analysis, tailored preemptive and post-emergency response strategies were formulated for each risk type. Furthermore, a system dynamics simulation was employed for scene analysis of the proposed strategies. The simulation results demonstrated a significant improvement, with the project completion rate increasing from 77 to 90.5% after implementing the targeted risk responses. This work provides a systematic approach for Chinese contractors to understand risk propagation mechanisms and select optimal control strategies, thereby enhancing project success in the Saudi Arabian market.

Indexed as

EngineeringSocial Network AnalysisChinaComputer SimulationHumansRisk AssessmentRisk FactorsSaudi ArabiaGeneral contractingMunicipal engineering projectRisk control strategyRisk relationship networkSNA method

Identifiers

PMID41501117
PMCPMC12780013

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.