Evidence map›Paper›PMID 40847117›Full record

ArticleScientific reports2025

How big data analytics improves hospital environmental performance through supply chain innovation, decision quality, and risk taking.

Lu Xinqi, Ye Xinghai, Ye Shengyao, Hashem Salarzadeh Jenatabadi, Nadia Samsudin

Abstract read
In one paragraph

Article in Scientific reports, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0citing papers in PubMed
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1 · What the graph read from it

What it found

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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

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3 · Its place in the literature

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0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

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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.

Lu XinqiDepartment of Medical, Yongjia People's Hospital, Wenzhou, 325000, Zhejiang, China. luxinqi2024@163.com.
Ye XinghaiDepartment of Emergency, Yongjia Hospital of Traditional Chinese Medicine, Wenzhou, 325000, Zhejiang, China.
Ye ShengyaoMental Health Center, Wenzhou Vocational College of Science and Technology, Wenzhou, 325000, Zhejiang, China.
Hashem Salarzadeh JenatabadiDepartment of Econometrics and Business Statistics, School of Business, Monash University Malaysia, 47500, Subang Jaya, Selangor, Malaysia.
Nadia SamsudinFaculty of Social Sciences and Liberal Arts, UCSI University, 56000, Kuala Lumpur, Malaysia. Nadia.Samsudin@ucsiuniversity.edu.my.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Despite big data analytics (BDA) capabilities have been increasingly recognized for their potential to improve sustainability, the underlying mechanisms by which BDA capabilities influence hospital environmental performance in the context of healthcare supply chains are not well understood. This paper aims to bridge this significant empirical void by examining the mediating effect of supply chain innovation, decision-making quality and risk-taking on the links between BDA capabilities and environmental performance for Chinese hospitals. Based on Stimulus-Organism-Response theory, the theoretical model depicts BDA capability as a key stimulus factor affecting the hospital sustainability outcomes. This research employed a quantitative research method, and a structured survey instrument was administered to 653 healthcare providers from various hospitals. The participants were recruited using a random sampling method to achieve broad representation. Variables in the survey include measures of big data analytics capability, supply chain innovation, quality of decision-making, risk-taking, and environmental performance. AMOS was used for Structural Equation Modeling (SEM) analysis to test the proposed relationships and mediation effects among the variables in due diligence. Empirical results support a positive relationship between hospitals' BDA capability and environmental performance, indicating that it is statistically significant. Crucially, this link is to some degree mediated by supply chain innovation, quality of decision-making and risk taking behaviour. In particular, hospitals with high analytical capability were more innovative in their supply chain production, had better decision-making structures, and showed a tendency to be more risk takers, leading to good environmental outcomes. This research limns the manner in which improving BDA capabilities can systematically contribute to hospital sustainability in innovative, informed, and strategically bold supply chain management practices; thereby new theoretical and practical aspects are provided. These results not only enrich current theoretical constructs but also give insights to healthcare managers and policy makers for harnessing the big data analytics to promote environmental sustainability and implement a real change in the healthcare performance.

Indexed as

Big DataData ScienceDecision MakingHospitalsRisk-TakingChinaData AnalyticsHumansSurveys and QuestionnairesData miningDecision-makingHealthcare sustainabilityLogistics managementStimulus-organism-response theory

Identifiers

PMID40847117
PMCPMC12373920

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LicenceCC BY-NC-ND
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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.