Cited by 40Quality and Supply ManagementManagement and Optimization TechniquesDigital Transformation in Industry

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Understanding the linkages between lean practices and performance improvements in Indian process industries

Panwar, Avinash, Nepal, Bimal, Jain, Rakesh, Rathore, Ajay P.S., Lyons, Andrew·2017·Industrial Management & Data Systems

Abstract

Purpose: The purpose of this paper is to investigate the impact of lean practices on performance improvement of process industries in India. Design/methodology/approach: Based on a survey of Indian process industries, this paper proposes two sets of hypothesis to examine if there is any statistically significant impact of lean practices on certain specific performance metrics. First, the sample is classified into two classes of process industries: the adopters of lean and those who have not yet adopted the lean practices in their manufacturing operations. Then statistical tests are conducted to measure the differences in the level of performance between the two classes of Indian process industries with respect to nine performance measures. The survey results are augmented by two in-depth case studies. Case studies include one from lean adopter firms (a refinery) and another from the firms that have not yet adopted the lean practices (a primary metal manufacturing unit). Findings: A survey result of 121 Indian process industries shows that adoption of lean practices results in a positive impact on inventory control, waste elimination, cost reduction, productivity, and quality improvement in process industries. On the other hand, based on the sample data on Indian process industries, no statistically significant improvement could be found on the lot size or space utilization between lean adopters and their counterparts. Practical implications: This research provides guidance to the managers on how adoption of lean practices results in better performance in process industries in several operational areas. Originality/value: To the knowledge, this study is the first attempt to analyze the impact of lean practices on a set of specific performance metrics in Indian process industry. Although this study focuses on the Indian process industry, the authors believe that findings of the research can inform other practitioners and researchers who are considering implementing lean in process industry sector in other developing countries like India.

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Metadata

Authors
Panwar, A., Nepal, B., Jain, R., Rathore, A. P. S., & Lyons, A.
Affiliations
  • Texas A&M University System (US)
  • Malaviya National Institute of Technology Jaipur (IN)
  • University of Liverpool (GB)
Venue
Industrial Management & Data Systems
Publisher
Emerald
Published
2017-03-13
Volume
117
Issue
2
Pages
346-364
ISSN
0263-5577 (ISSN-L)
OpenAlex
W2586025758
Cited by
40
References
54
Citations by year
2026: 1 · 2025: 3 · 2024: 3 · 2023: 2 · 2022: 4 · 2021: 8 · 2020: 6 · 2019: 8 · 2018: 4 · 2017: 1
FWCI
8.88
Type
journal article
Language
en
Open access
closed
Locations
Industrial Management & Data Systems (publishedVersion)
Topics
  • Social Sciences › Business, Management and Accounting › Management Information Systems › Quality and Supply Management
  • Social Sciences › Business, Management and Accounting › Strategy and Management › Management and Optimization Techniques
  • Physical Sciences › Engineering › Industrial and Manufacturing Engineering › Digital Transformation in Industry
Keywords
lean practices, lean adoption, process industry, performance improvement, performance indicators, inventory management, waste elimination, cost reduction, productivity, quality improvement, lot size, space use, Indian manufacturing, refinery

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CoChat. (2026). Citation check: Understanding the linkages between lean practices and performance improvements in Indian process industries. https://app.cochat.ai/papers/10.1108/imds-01-2016-0035
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Panwar, A., Nepal, B., Jain, R., Rathore, A. P. S., & Lyons, A. (2017). Understanding the linkages between lean practices and performance improvements in Indian process industries. Industrial Management & Data Systems. https://doi.org/10.1108/imds-01-2016-0035