Process analysis of a teaching and learning factory environment to demonstrate Industry 4.0 solutions by using the Smart Logistics Zone approach

Behrendt, Fabian; Lehner, Oliver; Rettmann, Alina; Schmidtke, Niels; Wollert, Tim

doi:10.1109/gol53975.2022.9820054

Cited by 5 publications

(2 citation statements)

References 25 publications

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“…For instance, Machado et al proposed a MM for assessing sustainability in operations management [88], and Xing et al developed and validated an MM for measuring the maturity of procurement activities in the construction sector [89]. Furthermore, there are frequent connections between the supply chain, logistics, and other activities, such as manufacturing [90][91][92]. Within the 126 analyzed articles, several specific activities were identified, in addition to supply chain management (79 occurrences) and logistics management (36 occurrences).…”

Section: Scope Criteria Of Mms For Scmlmentioning

confidence: 99%

“…To achieve this, the use of levels, dimensions, and sub-dimensions is necessary and characteristic of a comprehensive MM [10]. However, not all MMs include these elements, such as the number of maturity levels [3,9,76,90], and many do not indicate dimensions and sub-dimensions [26,97,98]. There is no established rule in the literature for determining the number of maturity levels.…”

Section: Design Criteria Of Mms For Scmlmentioning

confidence: 99%

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Trends and Recommendations for Enhancing Maturity Models in Supply Chain Management and Logistics

Ferraro,

Leoni,

Cantini

et al. 2023

Applied Sciences

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Maturity models (MMs) are strategic tools used to assess and improve the current state of processes, objects, or people, with the goal of achieving continuous performance enhancement. While MMs are applied in various fields, their scope, design, and application criteria within Supply Chain Management and Logistics (SCML) lack comprehensive studies. This article aims to address this gap through a systematic literature review. The review analyzes 137 relevant articles using both bibliometric and content analysis techniques. The bibliometric analysis identifies major contributions, popular journals, and the classification and evolution of key keywords. The content analysis focuses on critical criteria related to the scope, design, and application of MMs. The findings reveal a growing emphasis on models assessing Industry 4.0 readiness and sustainability principles. However, several gaps are identified, including limited attention to optimizing and integrating logistic processes, underutilized and unvalidated MMs, and the absence of comprehensive improvement guidelines. Based on these trends and research gaps, this study proposes five recommendations for future developments that benefit both academics and practitioners. These recommendations aim to address the identified limitations and provide guidance for comprehensive and effective improvement strategies.

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