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Exploring the operational performance of Indian smes: an integrated PLS-SEM and NCA approach
Amit Surya1, Rakesh Kumar1, Rajeev Trehan1
1Department of Industrial and Production Engineering, National Institute of Technology, Jalandhar, 144011, Punjab, India.
None:
This study examines the combined influence of social, quality, and delivery performance practices on the operational performance of Indian textile "small and medium-sized enterprises" (SMEs). In an increasingly competitive and sustainability-driven manufacturing environment, understanding how these factors interact to enhance operational outcomes is essential for both researchers and practitioners. To address this, the study uses a hybrid analytical framework integrating "Partial Least Squares Structural Equation Modelling" (PLS-SEM) and "Necessary Condition Analysis" (NCA). Data were collected from 40 Indian textile SMEs through a structured survey, and the relationships among constructs were empirically validated. The PLS-SEM results show that delivery performance exerts the most significant positive impact on operational performance, followed by social and quality performance. NCA further show that achieving high operational performance requires minimum threshold levels of these three practices, emphasizing their necessity rather than sufficiency. The integrated outcomes show that SMEs can improve operational efficiency by simultaneously optimizing social, quality, and delivery dimensions. This study provides actionable insights for SME managers into how delivery reliability, workforce well-being, and consistent quality management collectively enhance productivity and sustainability outcomes. This work contributes by integrating socio-technical and sustainability perspectives within an operational performance framework and by demonstrating the complementary use of PLS-SEM and NCA in SME performance research. This work provides a comprehensive understanding of performance enhancement pathways and offers a robust methodological foundation for future research in sustainable and lean-oriented manufacturing systems.
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