Keywords = صنعت 4.0
Strategic Management, Sustainability, and Performance Analytics

Analyzing the quality of digitalization in supply chain collaboration models using an integrated fuzzy BWM-TOPSIS approach

Volume 14, Issue 3, Autumn 2024, Pages 224-243

https://doi.org/10.48313/jqem.2025.516446.1513

Shahab Bayatzadeh, Hamidreza Talaie, Ali Sorourkhah

Abstract Purpose: This study aims to evaluate and rank collaboration models in the Iranian rubber industry supply chain from the perspective of digitalization quality. Digitalization quality refers to the effective use of Industry 4.0 technologies to improve transparency, integration, agility, resilience, and sustainability. The rubber industry was selected due to its operational complexity and urgent need for digital transformation.
Methodology: A multi-criteria decision-making approach was adopted, combining the Fuzzy Best-Worst Method (BWM) for weighting the evaluation criteria and TOPSIS for ranking the collaboration models. A sensitivity analysis was also conducted to assess the robustness of the results across varying criterion weights.
Findings: The digital supply chain model ranks highest in digitalization quality, with "technology integration" as the most critical criterion. The sensitivity analysis confirms the rankings' robustness and stability across different weight scenarios.
Originality/Value: This research uniquely addresses the comparative assessment of collaboration models in the rubber industry based on digitalization quality. The use of a Fuzzy BWM-TOPSIS hybrid method and comprehensive sensitivity analysis provides a novel, practical framework for strategic decision-making in digital supply chain transformation.

Designing the establishment and implementation model of quality 4.0 with the integrated approach of interpretive structural modeling and structural equation modeling

Volume 12, Issue 1, Spring 2022, Pages 51-68

https://doi.org/10.48313/jqem.2022.164188

Hamidreza Talaie, Mehran Ziaeian, Pooria Malekinejad

Abstract The purpose of the current research is to design a structure so that it can be used to investigate the drivers of the appropriate implementation of quality 4.0 in the country's steel industry. In order to carry out this research, ten stimuli were initially identified using research literature. Then, using the interpretative structural modeling technique, these stimuli were structured using the opinions of 13 experts. , in order to fit the obtained structure, the structural equation modeling of the tools related to it, including measurement model fitting, structural and general model fitting, were used. For this purpose, a questionnaire containing 33 questions with a five-point Likert scale was designed and in order to complete it, opinions were sought from 214 managers and employees of the country's steel industry. The findings of the research on the high effectiveness of reward stimuli and control of big data in proper implementation have quality 4.0.