Progress in partial least squares structural equation modeling use in logistics and supply chain management in the last decade - A structured literature review

Oct 20, 2026

Uploaded by SANS

Evaluating the use of partial least squares structural equation modeling (PLS-SEM) in logistics and supply chain management (LSCM), this structured literature review synthesizes evidence from 401 studies published between 2014 and 2022 across 15 major LSCM journals. The analysis examines reasons for adopting PLS-SEM, measurement and structural model evaluation criteria, advanced analysis techniques, and reporting practices. Findings identify unclear justification for PLS-SEM, limited measurement/structural evaluation methods, and slow adoption of advanced techniques, highlighting the need for clearer reporting transparency and practical guidance.

LanguageEnglish

CategoryResearch & Report

FormatPDF

Pages32

Reading Time1 h 21 min

AccessFree to download

Introduction

Purpose and research questions

Review approach and scope

Literature review method and dataset

Findings

Reasons for using PLS-SEM

Measurement and structural model evaluation

Advanced techniques and reporting practices

Methodological background

PLS-SEM development and software tools

Conclusions and contributions

Criteria and steps for using PLS-SEM

The current issue and full text archive of this journal is available on Emerald Insight at: [https://www.emerald.com/insight/0960-0035.htm](https://www.emerald.com/insight/0960-0035.htm) Progress in partial least squares structural equation modeling use in logistics and supply chain management in the last decade: a structured literature review Siqi Wang Business School, Guangdong Ocean University, Yangjiang, China Jun-Hwa Cheah Norwich Business School, University of East Anglia, Norwich, UK Chee Yew Wong Leeds University Business School, University of Leeds, Leeds, UK, and T. Ramayah School of Management, Universiti Sains Malaysia, Gelugor, Malaysia Abstract Purpose – This study aims to evaluate the usage of partial least squares structural equation modeling (PLSSEM) in journals related to logistics and supply chain management (LSCM) . Design/methodology/approach – Based on a structured literature review approach, the authors reviewed 401articles in the field of LSCM applying PLS-SEM published in15 majorjournals between2014and2022. 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 ofLSCM by providing clear criteria and steps for using PLS-SEM, enriching the understanding and advancement of research methodologies in this field. Keywords Partial least squares, Structural equation modeling, PLS-SEM, Logistics and supply chain management, Structured literature review Paper type Research paper 1. Introduction Partial least squares structural equation modeling (PLS-SEM; Lohm€oller, 1989; Wold, 1982), also known as partial least squares path modeling (PLSPM), has served as a powerful multivariate data analysis method for analyzing the intricate relationships between observed variables and latent variables [1] . Guenther et al. (2023) show the use of this method has grown exponentially in the past decade, not only in business fields such as marketing (Sarstedt et al., 2020), human resource management (Ringle et al., 2020), operations management (Peng and Lai, 2012), supply chain management (Kaufmann and Gaeckler, 2015), tourism industry (do Valle and Assaker, 2016) and hotel industry (Ali et al., 2018), but also other fields of scientific inquiry like ecology, agricultural science, engineering and medicine (Sarstedt et al., 2022a) . The advancement of intuitive graphical user interface software of PLS-SEM (i.e. SmartPLS, WarpPLS andADANCO), application guideline articles Progress in PLS-SEM use in LSCM 673 Received 2 June 2023 Revised 16 August 2023 30 August 2023 Accepted 30 August 2023 International Journal of Physical Distribution & Logistics Management Vol. 54 No. 7/8, 2024 pp. 673-704 © Emerald Publishing Limited 0960-0035 DOI 10. 1108/IJPDLM-06-2023-0200 IJPDLM (Cheah et al., 2021; 2023a, b; Hair et al., 2019; Sharma et al., 2023) and manual textbooks 54,7/8 n(eo.gn.-Hair ettechnicaall.P, 2021LS u;sRamersayah et al., 2018; Wong, 2019) have made the method available for Among others, the articles by Peng and Lai (2012; citation count of 1,743) and Kaufmannand Gaeckler (2015; citation count of 167) may have had a significant impact on logistics and supply chain management (LSCM) disciplines [2] . Their review and evaluation of the PLSSEM applications, plus recommendations and guidelines, are very useful. Since then, thePLS-

FAQs

What is the main purpose of this study?

To evaluate how partial least squares structural equation modeling (PLS-SEM) is used in journals related to logistics and supply chain management, and to assess application practices and guidelines.

How was the literature review conducted?

The review used a structured literature review approach, analyzing 401 articles applying PLS-SEM in 15 major LSCM journals published between 2014 and 2022.

What key problems did the study find in existing LSCM research using PLS-SEM?

Researchers sometimes did not clarify why they used PLS-SEM, often showing limited use of measurement-model and structural-model evaluation techniques, which can lead to inappropriate assessment criteria.

Oct 20, 2026

Uploaded by SANS