Search results

Evolved from Toyota’s shop floor in Japan, lean bundles are universally accepted for boosting manufacturing performance. However, extant literature shows mixed findings on the effectiveness of lean bundles in non-Japanese settings. This meta-analysis is aimed at understanding the influence of national culture (NC) differences on the lean bundles-performance relationships.

A total of 224 effects from 12,569 observations across 48 empirical studies from 14 countries are meta-analyzed. Also, weighted least squares (WLS) meta-regression using NC scores from the Global Leadership and Organizational Behavior Effectiveness (GLOBE) study are conducted to test the moderating effect of NC dimensions.

The meta-analysis reveals a positive association between the lean bundles and firm performance; though, the strength of the association varies across the individual lean bundles. The meta-regression results show that lean practices are more effective in countries that value high future orientation, high collectivism, low-performance orientation and high assertiveness.

The results contribute to the literature on the role of local cultural influence on strategies and decisions related to the implementation of continuous improvement (CI) programs in cross-cultural settings.

We studied the relationship between job engagement and systematic problem solving (SPS) among shop-floor employees and how lean production (LP) and Internet of Things (IoT) systems moderate this relationship.

We collected data from a sample of 440 shop floor workers in 101 manufacturing work units across 33 plants. Because our data is nested, we employed a series of multilevel regression models to test the hypotheses. The application of IoT systems within work units was evaluated by our research team through direct observations from on-site visits.

Our findings indicate a positive association between job engagement and SPS. Additionally, we found that the adoption of lean bundles positively moderates this relationship, while, surprisingly, the adoption of IoT systems negatively moderates this relationship. Interestingly, we found that, when the adoption of IoT systems is complemented by a lean management system, workers tend to experience a higher effect on the SPS of their engagement.

One limitation of this research is the reliance on the self-reported data collected from both workers (job engagement, SPS and control variables) and supervisors (lean bundles). Furthermore, our study was conducted in a specific country, Italy, which might have limitations on the generalizability of the results since cross-cultural differences in job engagement and SPS have been documented.

Our findings highlight that employees’ strong engagement in SPS behaviors is shaped by the managerial and technological systems implemented on the shop floor. Specifically, we point out that implementing IoT systems without the appropriate managerial practices can pose challenges to fostering employee engagement and SPS.

This paper provides new insights on how lean and new technologies contribute to the development of learning-to-learn capabilities at the individual level by empirically analyzing the moderating effects of IoT systems and LP on the relationship between job engagement and SPS.

While Digitalisation is gaining momentum among practitioners and the scientific world, there is still a struggle to embark on the digitalisation journey successfully. The struggles are more significant for SMEs compared to large companies. Such transformation could face internal resistance, which evokes the need to put it into a socio-technical perspective such as lean. This paper investigates how SMEs could implement digital tools and technologies in their operations.

We relied on a multiple case study design in three SME manufacturing companies in Italy. Based on the experience of those companies, the struggles in the implementation and the lessons learned, we formulate an implementation model of digital tools driven by lean thinking.

Companies tend to implement first digital tools that help with real-time data collection and stress that introducing digital tools becomes challenging without reducing waste in production. The model stresses top management commitment, middle-line involvement and operator training to resist change. All these factors coincide with socio-technical lean bundles developed by seminal works. In addition, the study highlights that financial incentives are not necessarily the common barrier to digital tools implementation in SMEs but rather the cultural aspect.

Our paper enriches the extant body of knowledge by deriving knowledge around digitalisation implementation through lessons learned and corrective actions. It allows managers to benchmark and compare the current state of the implementation process with that of other companies and the one proposed to make corrective actions when necessary.

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 view that dynamic capabilities theory can help explain how lean organizations improve has been put forward by scholars. However, there is still a lack of research on the matching relationship between the application of lean practice and the internal elements of enterprise organization from the perspective of dynamic capabilities. The purpose of this study is to validate the moderating effect of dynamic capabilities on the relationship between lean practices and operational performance.

This study used the method of survey and empirical research to collect sample data from 263 enterprises in China. Through literature review, this study put forward the moderating hypotheses around dynamic capabilities, lean practices and operation performance and used the method of regression analysis to validate these hypotheses.

The results showed that dynamic capabilities have a partially moderating effect on the application of lean practices. Specifically, dynamic capabilities have a significant moderating effect on the relationship between just-in-time, total quality management, total preventive maintenance and operational performance, while dynamic capabilities have no significant moderating effect on the relationship between human resource management and operational performance.

The research conclusion complements and enriches the lean practices literature from the perspective of dynamic capabilities. Existing studies mainly focus on the moderating role of external environmental factors, while there is a lack of empirical research on the role of dynamic capabilities in lean practices literature. The research results will help enterprises further understand the matching relationship between lean practices and dynamic capabilities and then improve the success of lean practices application.

This study aims to investigate the implementation of lean human resource management (HRM) practices in manufacturing small- and medium-sized enterprises (SMEs) and explore how various factors interact to influence their successful adoption. By exploring the interplay among these factors, the research seeks to identify key drivers affecting the adoption of lean HRM in manufacturing SMEs. Ultimately, the research intends to provide insights that can guide organisations, practitioners and policymakers in effectively implementing lean HRM practices to enhance operational efficiency, workforce engagement and competitiveness within the manufacturing SME sector.

The study combined total interpretive structural modelling (TISM) and Matrice d'Impacts Croisés Multiplication Appliquée à un Classement (MICMAC) analysis. TISM helped in understanding the hierarchical relationship among different factors influencing lean HRM implementation, whereas MICMAC analysis provided insights into the level of influence and dependence of each factor on others.

The research revealed that “top management support” emerged as the most independent factor, indicating that strong support from top management is crucial for initiating and sustaining lean HRM practices in manufacturing SMEs. On the other hand, “employee involvement and empowerment” was identified as the most dependent factor, suggesting that fostering a culture of employee engagement and empowerment greatly relies on the successful implementation of lean HRM practices.

While the study provided valuable insights, it has certain limitations. The research was conducted within the specific context of manufacturing SMEs, which might limit the generalizability of the findings to other industries. Expert opinions introduce subjectivity in data collection. Additionally, the study may not cover all critical factors, allowing room for further exploration in future research.

The findings have practical implications for manufacturing SMEs aiming to implement lean HRM practices. Recognising the pivotal role of top management support, organisations should invest in cultivating a strong leadership commitment to lean HRM initiatives. Furthermore, enhancing employee involvement and empowerment can lead to better adoption of lean HRM practices, resulting in improved operational efficiency and overall competitiveness.

This research contributes to the field by offering a comprehensive exploration of the interplay among factors influencing lean HRM implementation. The use of TISM and MICMAC analysis provides a unique perspective on the relationship dynamics between these factors, allowing for a nuanced understanding of their roles in the adoption of lean HRM practices in manufacturing SMEs. The identification of “top management support” as the most independent and “employee involvement and empowerment” as the most dependent factors adds original insights to the existing literature.

The present research aims to investigate how lean project management (LPM) and agile project management (APM) affect project performance outcomes in the construction sector in Jordan. This study focuses on six key project performance outcomes, namely cost, time, quality, client satisfaction, innovation and responsiveness.

The present study employed a quantitative approach to achieve the research objectives. Accordingly, a multi-item survey questionnaire was prepared to gather data from 392 project managers from construction companies in Jordan. The study’s model showed acceptable levels regarding reliability, validity, fit indices and discriminant validity. In order to test the hypotheses of this study, path analysis was employed using Amos 24.0 software.

LPM demonstrated a remarkably high positive impact on cost performance. It also positively affected quality performance and client satisfaction. However, LPM insignificantly affected time, innovation and responsiveness performance measures. On the other hand, APM showed a notably high positive impact on innovation and responsiveness. The findings also revealed that APM positively impacted quality performance and client satisfaction. In addition, APM negatively impacted cost performance and insignificantly impacted time performance.

This study is one of the first comprehensive studies to empirically examine the impact of both LPM and APM on various project performance outcomes in the construction industry in the context of a developing country. It reveals some similarities and differences between LPM and APM with regard to their impacts on project management outcomes. The findings are expected to guide managers in selecting the appropriate project management approach based on the desired performance outcomes. Accordingly, it offers important implications for project managers in construction companies.

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.

Bangladesh's ready-made garment (RMG) industry plays a vital role in the economic growth of this country. As the global trend in the fashion market has introduced a high-mix, low-volume ordering style, manufacturers are facing an increased number of changeovers in their production systems. However, most of the Bangladeshi RMG manufacturers are not yet ready to respond to such small orders and to improve the flexibility of their production systems. Consequently, the industry is falling behind in global market competition. Thus, this study aims to advance the current performance of RMG manufacturing operations to respond to the fast-fashion industry's challenges effectively using quick changeover.

In this study, a Single-Minute Exchange of Dies (SMED) is applied to attain quick changeover following the best practices of lean manufacturing.

This study examined the performance of the SMED technique to reduce changeover time in two case organisations. The changeover time was reduced by 70.76% from 434.56 min to 127.08 min and 42.12% from 2,664 min to 1,542 min for the case organisations, respectively. The results of this study show that companies require improved changeover times to address the demand for high-mix, low-volume orders.

This study will certainly guide practitioners of the RMG industry to adopt SMED to reduce changeover time to meet small batch production.

The primary aim of this research was to investigate the mediating effect of the decision-making structure on the relationship between perceived environmental uncertainty and hospital performance.

Online and manual survey questionnaires were used to collect data in this study. The target population of this study consists of all middle managers within 11 COVID-19 referral hospitals in Surabaya. A total of 189 responses were collected, however, 27 incomplete responses were excluded from the final dataset. Data was analyzed using SEM-PLS.

The study's findings indicate that decision-making structure plays a role in mediating the link between perceived environmental uncertainty and hospital performance assessed via the Balanced Scorecard, highlighting the significance of flexible decision-making processes during uncertain periods. Moreover, based on our supplementary test, respondents' demographic characteristics influence their perceptions of hospital performance.

Hospital administrators can consider the significance of decision-making structures in responding to environmental uncertainties like the COVID-19 pandemic. By fostering adaptable decision-making processes and empowering middle managers, hospitals may enhance their performance and resilience in challenging situations. Additionally, based on supplementary tests, it is found that differences in the perception of the three Balanced Scorecard perspectives imply that hospitals categorized as types A, B, C, and D should prioritize specific areas to improve their overall performance.

This research adds substantial originality and value to the existing body of knowledge by exploring the interplay between decision-making structures, environmental uncertainty, and hospital performance. It contributes to the literature by specifically focusing on the Covid-19 pandemic, a unique and unprecedented global crisis.