Evidence map›Paper›PMID 40181905›Full record

ArticleFrontiers in psychology2025

Decision-making of construction workers' waste reduction behavior: a study based on Cost-Benefit Theory and Cumulative Prospect Theory.

Shuitai Xu, Yuhui Zhou, Simei Xu, Jingkuang Liu, Qirong Chen, Fei Xue, Wenxing Zhu

Abstract read
In one paragraph

Article in Frontiers in psychology, 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

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

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

7 authors.

Shuitai XuSchool of Economics and Management, Jiangxi University of Science and Technology, Ganzhou, China.
Yuhui ZhouSchool of Economics and Management, Jiangxi University of Science and Technology, Ganzhou, China.
Simei XuSchool of Economics and Management, Jiangxi University of Science and Technology, Ganzhou, China.
Jingkuang LiuSchool of Management, Guangzhou University, Guangzhou, China.
Qirong ChenSchool of Civil Engineering, Chongqing University, Chongqing, China.
Fei XueSchool of Economics and Management, Jiangxi University of Science and Technology, Ganzhou, China.
Wenxing ZhuSchool of Economics and Management, Jiangxi University of Science and Technology, Ganzhou, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The rapid advancement of industrialization and urbanization has led to a significant generation of construction waste, causing serious resource wastage and environmental pollution. To promote the sustainable development of the construction industry, this study integrates Cost-Benefit Theory and Cumulative Prospect Theory to develop a decision-making model for construction workers' waste reduction behavior (CWWRB), examining the decision-making process under the influence of self-interested motivations and cognitive biases among construction workers. This study, using a construction project in Shenzhen, China, as a case study, assigns variable values and designs management scenarios based on field interview data to simulate the impact of management measures on the decision-making of CWWRB, and the results indicate that: (1) Increasing the negative incentive level significantly promotes the decision-making of CWWRB, but a diminishing marginal effect is observed. (2) Optimizing the atmosphere for waste reduction exerts a lagging guiding effect on the decision-making of CWWRB. (3) Combined measures can compensate for the diminishing marginal effect and lagging effect of single measures, thereby enhancing management effectiveness. The findings not only enrich the theoretical framework for construction waste management but also provide theoretical support for formulating effective management strategies.

Indexed as

construction wasteCost-Benefit TheoryCumulative Prospect Theorydecision-makingwaste reduction behavior

Identifiers

PMID40181905
PMCPMC11967277

What OpenQuestion holds

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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.