Lean and dynamic capabilities for SMEs - a holistic framework with an empirical investigation using structural equation modelling

In a dynamic business environment amidst COVID-19 pandemic, adopting best practices like lean, supply chain and knowledge management are considered rational decisions to sustain the organisational performance. Small and medium enterprises (SMEs) manage their business process by focusing on short-term benefits rather than long-term. Moreover, SMEs need a real-time model for framing the roadmap to execute the best practices. Based on the theory of dynamic capability, value and socio-technical system (STS), this study constructed a holistic framework for SMEs to create a synergetic process with lean, supply chain management (SCM) and knowledge management (KM). Partial least square-structural equation modelling (PLS-SEM) was applied to assess the framework model. The model was analysed using the sample size of 132 valid responses from Indian manufacturing SMEs. The current study formulated and studied lean management practices (LMPs) as a holistic approach with lean training, learning culture, supply chain relationship and integration for SMEs performance. The study results also clarified how SMEs could enhance their internal and external capability to improve performance.

Authors

Institutions

Publication Details

Journal
International Journal of Productivity and Quality Management
Published
2025-01-01
DOI
https://doi.org/10.1504/ijpqm.2025.145575
Citations
1
Primary Topic
Quality and Supply Management
Type
article
Field-Weighted Citation Impact
2.28
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Lean and dynamic capabilities for SMEs - a holistic framework with an empirical investigation using structural equation modelling

Ganesan Kannabiran, Sekar Vinodh, Vallinayagam Arumugam, Gaurav Abhishek Tigga
1 citations
International Journal of Productivity and Quality Management
Quality and Supply Management
2.28
article

Lean and dynamic capabilities for SMEs - a holistic framework with an empirical investigation using structural equation modelling

Ganesan Kannabiran, Sekar Vinodh, Vallinayagam Arumugam, Gaurav Abhishek Tigga
article en
1 citations

Abstract

In a dynamic business environment amidst COVID-19 pandemic, adopting best practices like lean, supply chain and knowledge management are considered rational decisions to sustain the organisational performance. Small and medium enterprises (SMEs) manage their business process by focusing on short-term benefits rather than long-term. Moreover, SMEs need a real-time model for framing the roadmap to execute the best practices. Based on the theory of dynamic capability, value and socio-technical system (STS), this study constructed a holistic framework for SMEs to create a synergetic process with lean, supply chain management (SCM) and knowledge management (KM). Partial least square-structural equation modelling (PLS-SEM) was applied to assess the framework model. The model was analysed using the sample size of 132 valid responses from Indian manufacturing SMEs. The current study formulated and studied lean management practices (LMPs) as a holistic approach with lean training, learning culture, supply chain relationship and integration for SMEs performance. The study results also clarified how SMEs could enhance their internal and external capability to improve performance.

International Journal of Productivity and Quality ManagementVol. 44(4)
Birla Institute of Technology, Mesra (IN), National Institute of Technology Tiruchirappalli (IN)
Openalex Percentile: Top 13%
Quality and Supply Management
2.28
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.