Author
Listed:
- Abishae Noel
(Department of Logistics and Forwarding, Faculty of Architecture, Civil Engineering and Transport Sciences, Széchenyi István University, 9026 Győr, Hungary)
- László Buics
(Department of Corporate Leadership and Marketing, Kautz Gyula Faculty of Business Economics, Széchenyi István University, 9026 Győr, Hungary)
- Eszter Sós
(Department of Logistics and Forwarding, Faculty of Architecture, Civil Engineering and Transport Sciences, Széchenyi István University, 9026 Győr, Hungary)
Abstract
Background : Lean management is widely recognized as an effective approach to process optimization. However, its implementation in Small and Medium Enterprises (SMEs), particularly in logistics and supply chain contexts, remains challenging. Resource constraints and inconsistent organizational commitment often hinder effective implementation. This study examines Lean adoption, leadership commitment, and implementation outcomes in SME logistics and supply chains. Methods : A mixed-methods design was used, combining a systematic literature review guided by PRISMA and PEO frameworks, followed by a structured survey. A total of 780 valid responses from SME professionals were analyzed using descriptive statistics, correlation, regression, and reliability assessment. Results : Top and middle management commitment was identified as a significant predictor of perceived Lean implementation success. A measurable gap was observed between respondents’ knowledge of Lean methods and their practical application, emphasizing the importance of strategic alignment, organizational culture, and employee engagement. Conclusions : The findings provide practical implications for strengthening Lean implementation in SMEs through enhanced managerial commitment and employee involvement. The study is limited by its focus on SMEs from a single country and the literature retrieved from one bibliographic database. Future research should include broader geographical coverage, multiple databases, and objective organizational performance indicators.
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