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基于多准则决策方法对越南工业产品和服务在新冠疫情期间及后疫情时代的绩效评估

Performance evaluation of Vietnamese industrial goods and services during and post-COVID-19 era based on multi-criteria decision-making methods.

作者信息

Wang Chia-Nan, Nguyen Tram Thi Mai, Nhieu Nhat-Luong, Chung Yu-Chi

机构信息

Department of Industrial Engineering and Management, National Kaohsiung University of Science and Technology, Kaohsiung, Taiwan.

Department of Business Administration, Faculty of Economics, Ho Chi Minh City University of Technology and Education, Ho Chi Minh City, Vietnam.

出版信息

PLoS One. 2025 May 28;20(5):e0323764. doi: 10.1371/journal.pone.0323764. eCollection 2025.

DOI:10.1371/journal.pone.0323764
PMID:40435355
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC12119014/
Abstract

The industrial goods and services sector is crucial for the advancement of the Vietnamese economy in terms of its substantial economic contribution and positive impact on employment. Performance evaluation has become critical in this industry, which has constantly developed and had an intensive rivalry. This paper aims to analyze the performance of industrial goods and services firms during and after COVID-19 using an objective integrated multi-criteria decision-making technique. This study suggests a three-phase model. Criteria Importance Through Intercriteria Correlation (CRITIC) eliminates human judgment errors, increases accuracy, and maintains objectivity in the evaluation variable weighting phase. Then, Evaluation based on Distance from Average Solution (EDAS) and Technique of Order Preference Similarity to the Ideal Solution (TOPSIS) are used as effective cross-validation techniques to evaluate and rank forty-five Vietnam Stock Exchanges-listed firms for each year from 2020 to 2022. The reliability of the CRITIC-based weights is verified by the Statistical Variance Procedure. The research results reveal that the debt term structure is the most vital among the fifteen financial research indicators reflecting a business's solvency, profitability, growth, operating efficiency, and capital structure. Additionally, the research findings indicate discrepancies in the rankings produced by EDAS and TOPSIS. However, the disparities are not grave, and the top and bottom positions, in particular, remain consistent between the two approaches. PDN was the best firm during COVID-19 and was succeeded by CIA after the pandemic. Pursuing digital transformation, sustainable development, and keeping inventory turnover at high levels are common characteristics of successful businesses in this industry. For the first time, the article provides a performance analysis of Vietnamese industrial goods and services firms. It is a significant reference for domestic and international investors in portfolio selection, financial institutions in loan approval, managers and policymakers in planning and policy development, and researchers conducting investigations within this domain.

摘要

工业产品和服务部门对越南经济的发展至关重要,因为它做出了巨大的经济贡献,并对就业产生了积极影响。绩效评估在这个不断发展且竞争激烈的行业中变得至关重要。本文旨在运用客观的综合多标准决策技术,分析新冠疫情期间及之后工业产品和服务公司的绩效。本研究提出了一个三阶段模型。通过标准间相关性确定标准重要性(CRITIC)消除了人为判断误差,提高了准确性,并在评估变量加权阶段保持了客观性。然后,基于离差最大化法(EDAS)和理想解贴近度排序法(TOPSIS)被用作有效的交叉验证技术,对2020年至2022年每年在越南证券交易所上市的45家公司进行评估和排名。基于CRITIC的权重的可靠性通过统计方差程序进行验证。研究结果表明,在反映企业偿债能力、盈利能力、增长、运营效率和资本结构的15个财务研究指标中,债务期限结构最为重要。此外,研究结果表明EDAS和TOPSIS产生的排名存在差异。然而,差异并不严重,特别是两种方法的 top 和 bottom 位置保持一致。PDN在新冠疫情期间是表现最佳的公司,疫情后被CIA取代。追求数字化转型、可持续发展以及保持高水平的库存周转率是该行业成功企业的共同特征。本文首次对越南工业产品和服务公司进行了绩效分析。它为国内外投资者进行投资组合选择、金融机构进行贷款审批、管理者和政策制定者进行规划和政策制定以及在该领域进行调查的研究人员提供了重要参考。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0f81/12119014/ce250de66f31/pone.0323764.g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0f81/12119014/02e2ec1455fd/pone.0323764.g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0f81/12119014/c93001bc85d0/pone.0323764.g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0f81/12119014/ce250de66f31/pone.0323764.g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0f81/12119014/02e2ec1455fd/pone.0323764.g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0f81/12119014/c93001bc85d0/pone.0323764.g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0f81/12119014/ce250de66f31/pone.0323764.g003.jpg

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