Evidence map›Paper›PMID 37554791›Full record

ArticleHeliyon2023

System dynamics simulation of occupational health and safety management causal model based on NetLogo.

Zhonghong Cao, Junjie Zhu, Binbin Tang, Tao Chen

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 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

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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

2 citing papers in PubMed.

  1. Article
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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

4 authors.

Zhonghong CaoSchool of Economics and Management, Hunan University of Science and Engineering, Yongzhou 425199, Hunan, PR China.
Junjie ZhuSchool of Accounting, Wuhan Qingchuan University, Wuhan 430204, Hubei, PR China.
Binbin TangSchool of Economics and Management, Hunan University of Science and Engineering, Yongzhou 425199, Hunan, PR China.
Tao ChenWuhan University of Science and Technology, Wuhan 4300081, Hubei, PR China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The occupational health and safety management factors of construction enterprises are critical influencing factors in their training management, and their causal principles are topics that warrant profound exploration. Drawing upon the conventional five factors, this study initially posited and authenticated a causal model among them, subsequently employing system dynamics on the NetLogo platform to dynamically simulate the model, and ultimately scrutinizing the interrelations and dynamic influence degree among the factors. The results show that the direct causes of management factors include human factors (weight coefficient of 0.583) and method factors (weight coefficient of 0.405), and environmental factors directly affect human factors (weight coefficient of 0.994), whereas material factors directly affect method factors (weight coefficient of 0.918). At the same time, it can be seen from the dynamic simulation results that the influence of human factors and method factors on management factors increases sharply in the nascent phase of the simulation cycle (the highest slope is .90), gradually decreases in the intermediary phase (the slope of the inflection point is .11), and is relatively stable in the final phase (the slope is less than 0.11). Three main conclusions have been drawn from this. Firstly, management factors are directly and positively affected by human factors and method factors respectively. Secondly, the interplay between diverse factors evinces a confluence of periodicity and exponential attributes. Thirdly, in each management cycle (set at 381 steps), the main focus is on controlling the causal factors in the early stages of management, with pivotal control points in steps 25 and 100, and the principal management factors comprising the management organization, operating procedures, and protective measures.

Indexed as

Management causal modelNetLogoOccupational health and safetySEMSystem dynamics

Identifiers

PMID37554791
PMCPMC10404758

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LicenceCC BY
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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.