过去十年中,偏最小二乘结构方程模型在物流和供应链管理中的应用进展:结构化文献综述

Siqi Wang, Jun-Hwa Cheah, Chee Yew Wong, T. Ramayah
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引用次数: 1

摘要

本研究旨在评估偏最小二乘结构方程模型(PLS-SEM)在物流与供应链管理(LSCM)相关期刊中的使用情况。基于结构化文献综述法,作者回顾了2014 - 2022年间在15个主要期刊上发表的401篇应用PLS-SEM的LSCM领域文章。分析了采用PLS-SEM的原因、测量模型和结构模型评价标准、先进的分析技术和报告实践。LSCM研究者有时没有明确使用PLS-SEM的原因,如样本量、复杂模型和非正态分布。此外,大多数文章对测量模型和结构模型评估技术的使用有限,导致评估标准的使用不当。此外,先进分析技术的实际实施进展缓慢,并且需要提高报告分析算法的透明度。本研究提供了使用PLS-SEM的明确标准和步骤,丰富了该领域研究方法的理解和进步,为LSCM领域做出了贡献。
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Progress in partial least squares structural equation modeling use in logistics and supply chain management in the last decade: a structured literature review
Purpose This study aims to evaluate the usage of partial least squares structural equation modeling (PLS-SEM) in journals related to logistics and supply chain management (LSCM). Design/methodology/approach Based on a structured literature review approach, the authors reviewed 401 articles in the field of LSCM applying PLS-SEM published in 15 major journals between 2014 and 2022. The analysis focused on reasons for using PLS-SEM, measurement model and structural model evaluation criteria, advanced analysis techniques and reporting practices. Findings LSCM researchers sometimes did not clarify the reasons for using PLS-SEM, such as sample size, complex models and non-normal distributions. Additionally, most articles exhibit limited use of measurement models and structural model evaluation techniques, leading to inappropriate use of assessment criteria. Furthermore, progress in the practical implementation of advanced analysis techniques is slow, and there is a need for improved transparency in reporting analysis algorithms. Originality/value This study contributes to the field of LSCM by providing clear criteria and steps for using PLS-SEM, enriching the understanding and advancement of research methodologies in this field.
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来源期刊
CiteScore
11.20
自引率
10.40%
发文量
34
期刊介绍: IJPDLM seeks strategically focused, theoretically grounded, empirical and conceptual, quantitative and qualitative, rigorous and relevant, original research studies in logistics, physical distribution and supply chain management operations and associated strategic issues. Quantitatively oriented mathematical and modelling research papers are not suitable for IJPDLM. Desired topics include, but are not limited to: Customer service strategy Omni-channel and multi-channel distribution innovations Order processing and inventory management Implementation of supply chain processes Information and communication technology Sourcing and procurement Risk management and security Personnel recruitment and training Sustainability and environmental Collaboration and integration Global supply chain management and network complexity Information and knowledge management Legal, financial and public policy Retailing, channels and business-to-business management Organizational and human resource development Logistics and SCM education.
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