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The purpose of this paper is to propose a multivariate-based method to classify products in replenishment categories based on principal component analysis (PCA) along with two classification algorithms, k-nearest neighbor (KNN) and linear discriminant analysis (LDA).

In the propositions, PCA is applied to data describing products’ features and demand behavior, and a variable importance index (VII) is derived based on PCA parameters. Next, products are allocated to inventory replenishment models applying the KNNs to all original variables; the classification accuracy is then assessed. The variable with the smallest VII is removed and a new classification is carried out; this iterative procedure is performed until a single variable is left. The subset yielding the maximum classification accuracy is recommended for future classification. The aforementioned procedure is repeated replacing the KNN by the LDA.

When applied to real data from a consulting company, the KNN classification technique led to higher performance levels than LDA, yielding 89.4 percent average accuracy and retaining about 80 percent of the original variables. On the other hand, LDA reached 87.1 percent average accuracy and retained 95 percent of the variables. Based on such results, the authors’ findings suggest that 14 out of the 24 variables are crucial in determining an inventory replenishment model for a product in a specific location replacement. Several of the retained variables were typically used in reorder point estimation or associated to market profile in specific locals.

The idea of this paper is to remove irrelevant and noisy market metrics that jeopardize the correct allocation of products to the most appropriate replenishment model.

This study aims to provide an overall framework that connects and explains a macro-perspective of the findings from the five studies of this special issue. Through this, we aim to answer two main questions: How can Lean and Industry 4.0 be integrated, and what are the outcomes for workers from such integration?

The special issue received 64 papers that were evaluated in multiple stages until this final sample of five papers that describe different facets of the integration between Lean and Industry 4.0 and their relationship with worker activities. In this introduction, we review the main findings of these five studies and propose an integrative view and associated propositions. A discussion provides directions to advance the field further.

The framework shows that when Lean and Industry 4.0 are integrated, companies will face two types of tensions, dialectical and paradoxical, which require different managerial approaches. By managing such tensions, the Lean-Industry 4.0 integration can help improve social performance, as well as develop systematic problem-solving and cumulative learning capabilities. Five important themes for this field of research are outlined: the importance of work routines, legitimation, competence, sense and mental flexibility.

This study brings a new theoretical perspective to the integration of Lean with Industry 4.0-related digital technologies. The results go beyond the usual view of improving operational performance and dig into the effects on workers. It also shows that the integration process relies on and can enhance human capabilities such as learning and problem-solving.

The purpose of this paper is to plan the layout of the production area of an industrial kitchen of a theme restaurant through the application of the systematic layout planning (SLP) methodology and the establishment of layout indicators with a specific application in the restaurant business.

The authors applied the SLP methodology in the industrial kitchen of a theme restaurant in order to plan and develop layout alternatives. Such layout alternatives were then evaluated according to a set of specific indicators consolidated based on a literature review. Finally, a multi-criteria decision-making tool was used to support the selection of the best layout alternative and suggest to the case study area.

The main results could be highlighted as: first, an area, previously unexplored, of approximately 5.40 m² ended up being used as a productive area for the operations; second, 40 percent reduction in work-in-process by removing the refrigerators of groceries and the freezer from the production area; third, indirect indicators, such as customer satisfaction and the employee’s workplace environment, have increased their performance, since customers were better served and working environment became more conducive to a good employee performance.

Most research in layout planning is typically developed in productive industrial areas, and this paper contributes to the understanding the differences of implementing SLP methodology in a food service business, such as restaurant, and proposes the utilization of specific layout indicators.

The purpose of this paper is to understand the relationship between the implementation of Lean shop floor (LSF) practices and Lean supply chain management, and their effect on quality and inventory turnover.

A survey-based research method was conducted and data were collected from 110 plants located in Brazil. The research constructs were validated through rigorous procedures (unidimensionality and discriminant validity and reliability) through confirmatory factor analysis and two hypotheses were tested using ordinary least square regression.

The results indicate that: Lean supplier relationship positively moderates the effect of LSF practices on inventory turnover; Lean customer relationship negatively moderates the effect of LSF practices on inventory turnover; and Lean supplier relationship positively moderates the effect of LSF practices on quality.

From a theoretical perspective, the results of this study provide evidences supporting the importance of understanding the systemic relationships between Lean implementation at the shop floor and the firm’s relationships with supply chain partners, that was not tested before. As managerial implications, the results suggest that managers should take a decision to foster a Lean supply chain management depending on which performance metrics they need to improve: quality or inventory turnover.

The purpose of this paper is to understand how the association between leadership styles (task or relation orientation) and lean manufacturing (LM) implementation changes due to two contextual variables, team size and the leader’s age.

The authors carried out a survey with 225 leaders from different Brazilian companies that are implementing LM. Research constructs were validated through rigorous procedures using confirmatory factor analysis. Hypotheses were tested using ordinary linear least squares regression.

The results suggest that larger teams and more senior managers were negatively associated with LM implementation. Task-orientation style makes leaders more likely to achieve higher levels of LM than relation-orientation style leaders. Finally, the influence of relation-oriented leaders on LM implementation is contingent upon the size of the team.

Regarding study’s limitations, sample size and respondents’ location restrict results to this contextual condition, indicating that increasing the sample would help provide wider and more generalizable results. It is also worth noting that results are based on respondents’ (leaders) perspective. Hence, future studies may collect data from multiple perspectives, such as leaders and their followers, in order to compare results so as to verify the convergence or divergence among different respondents.

The results suggest that leaders should have different behaviors according to the context in which they are inserted. Therefore, such behavioral prescriptions are useful for managers since they are pressured to achieve high operational performance in short time periods and with few resources. Further, companies undergoing lean implementation may also be able to stimulate proper leadership behaviors and promote development programs accordingly, which is extremely relevant since behavioral changes usually take time.

The evolutionary process for achieving a successful lean enterprise requires different leadership styles according to the context in which leaders are inserted. This research provides arguments to help better understand the recommended leadership behaviors for lean implementation, complementing existing roadmaps by considering the proper leadership style as a contingency issue during lean implementation. Moreover, identifying the effect of contextual variables helps specify the contexts in which lean practices are more likely to be implemented.

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.

This paper aims to understand the patterns of lean production implementation, and the relationship between three context factors (i.e. firm size, positions within the supply chain and time length of the lean initiative) and the adoption of lean production practices in firms of the automotive supply chain in Brazil.

The authors collected data from 65 companies of the automotive supply chain in Brazil. For data analysis, first a cluster analysis was performed to identify common characteristics in the companies’ context factors when considering patterns of lean implementation. Then, multivariate analysis of variance was used to investigate the differences between the context factors and the degree of use of lean practices.

High lean adopters had better performance than low lean adopters in terms of lead time, inventory and turnover. Firms at the first and second tier of the automotive supply chain were “leaner” than firms at the third tier. Large-sized firms were more likely to have a higher degree of use of lean practices than medium and smaller ones. Some, but not all, lean practices followed these patterns. Results also showed that some lean practices were most commonly adopted at the beginning of the lean journey, whereas others took more time to mature.

This paper demonstrated how lean practices were implemented at different positions within the supply chain, and the patterns of implementation often followed. It also considers lean in the context of developing countries such as Brazil.

The purpose of this paper is to define the individual leadership competencies that are necessary to implement and sustain lean systems, based on a multi-method approach.

Data collection involved a literature review of lean competencies, interviews with four experts from the university and the industry, and an empirical survey answered by 91 respondents, who represented companies from several sectors. These techniques provided a mix of qualitative and quantitative data, which set a basis for identifying a list of competencies and discussing its validity.

In total, 16 lean leadership competencies were identified and validated, in terms of content validity, face validity, and predictive validity. Regarding this latter validity type, the survey results indicated that the competencies are positively associated with key operational performance indicators, organizational maturity level of lean, and leaders’ experience with lean systems.

The identified list of competencies may be a basis for the development of formal lean leadership development programs. The list may also support the design of tools for assessing the competencies of leaders in lean companies.

A list of 16 lean leadership competencies was developed based on a verifiable research method that used a mix of data collection techniques. This methodological approach is a distinctive characteristic in comparison with earlier studies, which did not include an empirical validation of the competencies.

This paper aims at examining how different types of shop floor performance feedback affect employee motivation and engagement. Based on this dataset, the authors analyzed the relationship between five types of performance feedback (safety, quality, productivity, improvement and individual performance) and three types of human-related outputs (motivation, role clarity and engagement) in light of socio-technical systems theory.

The authors designed a survey instrument and collected data from 492 employees of a large beverage distribution company. The authors used robust construct validity tests and multiple regression analysis to test the hypotheses.

The findings indicated significant positive effects of feedback on overall production, improvements and individual performance on all human-related outputs. In turn, safety and quality performance feedback had no statistically significant impact in motivation or engagement. These findings highlight the mixed nature of the impact of performance feedback on human-related outputs that have been neglected in the literature.

The joint analysis of the social and technical portion of performance feedback is unusual despite its clear relevance, which characterizes an original contribution of the authors’ work. Although previous literature supports the effect of performance feedback on motivation and engagement, previous studies have not tested how different types of feedback affect those social constructs.

The purpose of this paper is twofold: to classify the risks that affect the lean production implementation (LPI) process, and to demonstrate how that classification can help to identify the relationships between the risks.

Initially, a survey was conducted to identify the probability and impact of 14 risks in LPI, which had been identified based on a literature review. The sample comprised 57 respondents, from companies in the south of Brazil. An exploratory factor analysis was carried out to analyze the results of the survey, allowing the identification of three groups of risks in LPI. Then, a case study was conducted in one of the companies represented in the survey, in order to identify examples of relationships between the risks. Multiple sources of evidence were used in the case study, such as interviews, observations and documents analysis.

The risks that affect LPI were grouped into three categories: management of the process of LPI, top and middle management support and shop floor involvement. A number of examples of relationships between the risks were identified.

The survey was limited to companies from the south of Brazil and therefore its results cannot be completelly generalized to other companies. Moreover, the results of the survey were not subjected to a confirmatory factor analysis.

This study helps to improve the understanding of LPI, as: it re-interprets the factors, barriers and difficulties for LPI from the perspective of risk management, which had not been used for that purpose so far; it presents a classification of the risks that affect LPI, which can support the understanding of the relationships between the risks and, as a result, it can support the development of more effective methods for LPI.