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This paper aims to examine the relationship between the implementation of soft lean practices and organizational resilience development in the service sector.

A mixed-methods explanatory design that relied on two sequential and complementary phases was adopted. In the first phase, a quantitative analysis was performed based on data collected from practitioners from service organizations, allowing the identification of the significance of this relationship. In the second phase, the authors used semi-structured interviews with experts to qualitatively assess how this relationship occurs.

Findings indicated that soft lean practices are positively associated with organizational resilience, although the extent of their relationships varies depending on the resilience ability under analysis. Interviews with experts also provided specific details on how such relationships occur, adding insights to the numerical results.

This study provides a deeper understanding of the implications of lean management, specifically concerning the support of soft lean practices to develop organizational resilience. Additionally, the identification of this relationship (and how it occurs) allows service organizations to deploy human-related strategies to promote broader adoption of certain soft lean practices. As socio-cultural changes are usually time-consuming, anticipating these organizational resilience needs may result in competitive advantages in the face of disruptive events.

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 to examine the digitalization of operational processes and activities in lean manufacturing firms and explore the associated learning implications through the lens of cumulative capability theory.

Adopting a multiple-case design, we examine four cases of digitalization initiatives within lean manufacturing firms. We collected data through semi-structured interviews and direct observations during site visits.

The study uncovers the development of learning capabilities as a result of integrating lean and digitalization. We find that digitalization in lean manufacturing firms contributes to the development of both routinized and evolutionary learning capabilities in a cumulative fashion.

The study adds nuance to the limited theoretical understanding of the integration of lean and digitalization by showing how it cumulatively develops the learning capabilities of lean manufacturing firms. As such, the study supports the robustness of cumulative capability theory. We further contribute to research by offering empirical support for the cumulative nature of learning.

This paper aims at identifying the main contributions of Industry 4.0 (I4.0) technologies to the enhancement of knowledge management (KM).

A scoping review based on two stages was carried out. In the first stage, a numerical and descriptive analysis was conducted. In the second stage, the latent content of those papers was explored through a qualitative analysis, in which papers were assessed regarding the outcome of the implementation of ten I4.0 technologies on 14 KM abilities and 6 KM processes.

Six technologies (e.g. Internet of Things (IoT), big data, cloud computing, simulation, visualisation and industrial robot) were claimed to have a significant contribution on KM, especially for creation, organisation, dissemination and application processes. Overall, results indicated that technologies can significantly contribute to KM, although the extent of such contribution varies across technologies, learning levels, KM processes and abilities.

Existing studies in I4.0 fall short in exploring how embodied knowledge is articulated in practice, especially regarding opportunities to use new technological alternatives in favour of knowledge and learning development. This study complements the existing literature on I4.0 by identifying which technologies can contribute to KM. Also, a framework was proposed to examine the contribution of I4.0 technologies to KM at individual, team, and organisational levels.

The article aims to identify the association between each smart home service category's benefits and barriers to their adoption. The results seek to identify efficient approaches that motivate users to adopt smart homes services and support suppliers to establish strategies to expand and optimize smart home technologies.

The research used the chi-square test of independence to reveal the association between the benefits and barriers perceived by the users during smart home services implementation. Furthermore, the statistical analysis using reliable evidence based on 122 articles reported in the literature provides valuable knowledge for smart home implementation.

The results reveal which barriers and benefits in the smart home are essential for implementing each type of service. Therefore, the association between barriers and benefits with smart home services implementation can support the dissemination of smart home technologies.

The article provides evidence to develop strategies for implementing smart home services, supporting companies with guidelines to be more assertive in disseminating smart homes technologies.

Using the literature as a data source and raising the associations through the chi-square test of independence, the methodology provides a high level of generalization and strong evidence regarding the association of smart home benefits or barriers associated with every smart home service.

The aim of this study reported in this paper was to explore the application of operational excellence methodologies in a global context.

A qualitative interview approach was used to understand the current state, benefits, challenges, success factors, tools and techniques of operational excellence methodology implementation with relevance to logistics companies worldwide. About 16 interviews were undertaken with practitioners working in leading companies and with leading academics in Asia, Europe, Africa, North America, South America and Australia.

The findings show that operational excellence methodologies including Lean, Six Sigma, Lean Six Sigma and Agile can apply in logistics firms to improve operations and productivity and save costs. Top management support and involvement play an important role in the success of operational excellence projects in the logistics service.

The findings will be of interest to top and middle managers and logistics practitioners, with a dual aim of improving logistics performance and saving costs.

The present study has been one of the first global study attempts to explore the implementation of operational excellence methodologies in the logistics sectors.

The purpose of this study is to carry out a comprehensive systematic review of lean implementation frameworks and roadmaps developed over the past decade and report the key findings along with the limitations and the way forward.

A systematic review methodology proposed by Tranfield (2003), was followed to identify the relevant works on the research topic. Articles were searched using a set of inclusion criteria in various databases including Google Scholar, Web of Science and Science Direct over a period of 30 years.

The high failure rate of lean system implementation, reaching a range between 70 and 90% in almost all industries, is a matter of concern. This failure rate is still high even though numerous frameworks and roadmap models exist to streamline lean implementation. There is no standard framework or roadmap identified in the literature and many organisations are implementing lean in their unique ways. However, it would be desirable to develop a practical and systematic roadmap on lean-looking into the cultural and leadership dimensions rather than focusing on a set of tools. Moreover, most frameworks and roadmaps lack the sustenance aspects of lean implementation.

This research only identifies the fundamental gaps with the existing frameworks and roadmaps on lean implementation. The next phase of the research is to develop a roadmap and validate it with a number of organisations in different cultural contexts and leadership styles.

The authors argue that this is one of the most comprehensive systematic review on lean frameworks and roadmaps, ever produced in the literature to date.

Today, proficient practices are required to stimulate along various boundaries of the supply chain (SC) to exploit manufacturing resources economically, effectually and gracefully for retaining operational excellence. Accordingly, varieties of paramount practices, i.e. Lean, Agile, Resilient and Green practices, are integrated in present study with the objective to develop a Decision Support Framework (DSF) to select robust supplier under the extent of Lean-Agile-Resilient-Green (LARG) practices for a manufacturing firm. The framework is developed and validated in the Indian automotive sector, where the primary data is collected based on perceptions of the respondents working in an automotive company.

LARG metrics can ponder ecological balance, customer satisfaction, associations, effectiveness and sustainability and thus, the study consolidated LARG practices in one umbrella to develop a DSF. The analytical approach under DSF is developed by the integration AHP, DEMATEL, ANP, Extended MOORA and SAW techniques in present study to evaluate a robust supplier under the aegis of LARG practices in SC. DSF is developed by scrutinizing and categorizing LARG characteristics, where the selected LARG characteristics are handled by fuzzy sets theory to deal with the impreciseness and uncertainty in decision making.

The study has identified 63 measures (15 for Lean, 15 for Agile, 14 for resilient and 19 for Green) to support the robust supplier selection process for manufacturing firms. The findings of study explicate “Internal communication agility”, “Interchangeability to personnel resources”, “Manufacturing flexibility”, “degree of online solution”, “Quickness to resource up-gradation”, “Manageability to demand and supply change”, “Overstocking inventory practices” as significant metrics in ranking order. Additionally, “Transparency to share information”, “Internal communication agility”, “Manufacturing Flexibility”, “Green product (outgoing)” are found as influential metrics under LARG practices respectively.

A technical DSF to utilize by the managers is developed, which is connected with knowledge-based theory and a case of an automobile manufacturing firm is presented to illustrate its implementation. The companies can utilize presented DSF to impose service excellence, societal performance, agility and green surroundings in SC for achieving sustainable outcomes to be welcomed by the legislations, society and rivals. The framework represents an important decision support tool to enable managers to overcome imprecise SC information sources.

The study presented a proficient platform to review the most significant LARG alternative in the SC. The study suggested a cluster of LARG metrics to support operational improvement in manufacturing firms for shifting gear toward sustainable SC practices. The present study embraces its existence in enrolling a high extent of collaboration amongst clients, project teams and LARG practices to virtually eradicate the likelihood of absolute project failure.

Entering a new era of digital transformation, Industry 4.0 (I 4.0) promises to revolutionize the way business has been done, providing unprecedented opportunities and challenges. This study aims to investigate empirically and comparatively analyse the benefits, challenges and critical success factors (CSFs) of Industry 4.0 across four continents and developing and developed economies.

This study used an online survey to explore the benefits, challenges and CSFs of developed and developing economies. In order to ensure the validity of the survey, a pilot test was conducted with 10 respondents. A total of 149 participants with senior managerial, vice-presidential and directorial positions from developed and developing economies spanning four continents were invited to take part in the survey.

The study ranks benefits, challenges and CSFs across economies and continents. Further, the benefit of Industry 4.0 helping to achieve organizational efficiency and agility differed across the developing and developed economies. Furthermore, the benefit improves customer satisfaction significantly differed across continents; in terms of challenges, Employee resistance to change had a higher proportion in developing economies. The future viability of I 4.0 also differed across the continents. Regarding CSFs, there was no difference across the developing and developed economies. Finally, change management and project management vary across the continents.

This study contributes to a balanced understanding of I 4.0 by providing empirical evidence for comparative analysis. Moreover, it extends the concept of resource dependence theory to explain how organizations in developing economies and developed economies deploy resources to manage external condition uncertainties to implement I 4.0. Furthermore, this study provides a structural framework to understand the specific benefits, challenges and CSFs of implementing I 4.0, which can be utilized by policymakers to promote I 4.0 in their economies or continents.

To the best of the authors’ knowledge, no studies have empirically demonstrated the comparative analysis of benefits, challenges and CSFs across economies and continents and distinguish an original contribution of this work.

The purpose of this study is to identify the critical readiness factors (CRFs) that mainly affect the implementation of Lean Six Sigma (LSS) in an organization and their interactions, and to develop a model that allows the management to assess the Lean Implementation Readiness Level.

The methodology is separated into two main parts: the literature review and the assessment model development. In the literature review, the main CRFs and their interactions for LSS implementation in Scopus Data Base were identified. The second part of the methodology is the model development. It was built on a stepwise framework that considers the relations among the CRFs and their importance. Moreover, it was used fuzzy-based linguistic variables given by the experts working in the company to consider the actual performance rating of each CRF. The model has been validated in the healthcare sector in nine hospitals.

From the model application, it is possible to note that the most frequent level among the nine hospitals interviewed is “Average Ready”. Also, the most extreme level of readiness occurred ones while the most extreme level of not readiness never occurred. Results show that in 78% of the cases, there would have been a high probability of implementation failure. Also, it was possible to identify for each hospital if the CRFs are good, if they are weak and need to change or if another factor needs to be improved before it and what this factor is.

This work proposes a new methodology that eliminates the negative aspects and limitations of the total interpretive structural modeling methodology and the fuzzy logic approach currently applied to evaluate the LSS readiness of a company. The present methodology lies in the fact that it provides a solution not only by defining the weak CRFs but also by giving an indication of priority as it identifies the weak antecedent factors that inhibit the preparedness of the depending factors.