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The purpose of this paper is to explore the adoption of lean practices by manufacturing companies in regions of low economic and technological development and to compare findings with previous studies from more developed regions highlighting important contextual differences. The paper uses the contingency theory to explore how contextual variables and scarce resources influence the adoption of lean practices.

A survey of 233 manufacturing firms was conducted in the State of Pará in the Amazon Region of Brazil.

The results demonstrate that six internal lean practices (single minute exchange of dies, human resource management, continuous flow, total productive maintenance, pull and statistical process control) and two external lean practices (supplier feedback and customer involvement) are implemented. However, the two external lean practices of just-in-time delivery by suppliers and supplier development were not implemented. Furthermore, from the 36 operating items comprised in eight lean practices that are being used, 13 were not implemented. As such, compared to developed regions, there is evidence for a more fragmented implementation in less developed regions. The results reveal empirical evidence explained by the contingency perspective, such as national, geographical, strategic context and culture.

There is broad evidence on lean implementation in developed and developing countries in the literature. However, little is known about lean implementation in poorer regions of developing counties. This is one of the first studies mapping lean implementation in a region with low economic and technological development. This has important implications for research and practice, especially to cross-country/cultural research on operation management.

The purpose of this paper is to contribute to the existing knowledge system of lean supply chain management (LSCM), i.e. by using main path analysis, and the authors extract the main development track of LSCM. It is advantageous for relevant scholars to deepen their understanding of this academic field from a bibliometrics view to grasp the future directions better.

Structuring a citation network with the processed data set containing 866 papers and relevant information collected from Web of Science (WoS). Conducting review analyses aiming at the main paths that are extracted from the above citation network.

There are two different evolution paths in LSCM field, i.e. improving corporate sustainability performance through combining lean and green practices, and seeking the balance between lean and agility to structure leagile supply chain for specific industries. LSCM research studies mainly focus on five aspects: (1) establishment and development of LSCM theory; (2) structuration of lean supply chain; (3) research studies of the relationship between LSCM and corporate performance; (4) supply chain evaluation system; and (5) review and vista of LSCM field. The intersection of two knowledge evolute routes would be Industry 4.0, which is an integrated theory system combining lean, agility, green and other supply chain thinking.

The data set collected from WoS cannot contain all the research studies about LSCM is the main research limitation. Sustainability, as represented by environmental performance, will continue to be a major pursuit of this field. Integrating LSCM in Industry 4.0 will be the next hotspot in LSCM field.

Providing the main research contents and common methods of LSCM field. It is conducive to deepening the understanding of relevant practitioners and scholars to LSCM field from a dynamic perspective.

To the best of the authors’ knowledge, it is the first time to reveal the knowledge diffuse trajectories of LSCM under different view with main path analysis. This study is unique that it provides a new view to understand the field of LSCM.

This study aims to highlight the system-wide potential relationships between forms of human bias, selected Lean tools and types of waste in a manufacturing process.

A longitudinal single-site ethnographic case study using digital processing to make a material receiving process Lean was adopted. An inherent knowledge process with internal stakeholders in a stimulated situation alongside process requirements was performed to achieve quality data collection. The results of the narrative analysis and process observation, combined with a literature review identified widely used Lean tools, wastes and biases that produced a model for the relationships.

The study established the relationships between bias, Lean tools and wastes which enabled 97.6% error reduction, improved on-time accounting and eliminated three working hours per day. These savings resulted in seven employees being redeployed to new areas with delivery time for products reduced by seven days.

The single site case study with a supporting literature survey underpinning the model would benefit from testing the model in application to different industries and locations.

Application of the model can identify potential relationships between a group of human biases, 25 Lean tools and 10 types of wastes in Lean manufacturing processes that support decision makers and line managers in productivity improvement. The model can be used to identify potential relationships between forms of human biases, Lean tools and types of wastes in Lean manufacturing processes and take suitable remedial actions. The influence of biases and the model could be used as a basis to counter implementation barriers and reduce system-wide wastes.

To the best of the authors’ knowledge, this is the first study that connects the cognitive perspectives of Lean business processes with waste production and human biases. As part of the process, a relationship model is derived.