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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.

This paper aims to investigate the impact of adopting lean manufacturing principles on operational efficiency by eliminating seven major lean wastes (or Muda) in a Malaysian stationery manufacturer. Much of the research on lean considers its application to larger organisations with stable demand patterns. This research examines a small- and medium-sized enterprise (SME) with a volatile demand pattern.

A process activity mapping (PAM) methodology was utilized to identify the potential for waste elimination. PAM is a visual tool that considers every step in a production process. Value-added and non-value-added activities are therefore examined to understand hidden wastes and their sources.

The results revealed that the adopted lean principles significantly reduce the waiting times. This time reduction resulted in savings (reduction of cycle time) and to a certain extent, can be a crucial driver in continuous improvement sustainability in the production process.

The study focuses on a single case study and provides a springboard for further research. Future studies examining the results across a broader sample of organisations would develop the findings further.

The extant literature cites mixed success for lean implementation programmes. The results demonstrate that lean is still recognised as a powerful approach to improving operations in SMEs.

This paper reflects on the application of lean in a real case study showing the impact of lean on operational performance of an SME.

This study aims to investigate how to identify and address production levelling problems in assembly lines utilising an intensive manual workforce when higher productivity levels are urgently requested to meet market demands.

A mixed-methods approach was used in the research design, integrating case study analysis, interviews and qualitative/quantitative data collection and analysis. The methodology implemented also introduces to the literature on operational performance a novel combination of data analysis methods by introducing the use of the Natural Language Understanding (NLU) methods.

First, the findings unveil the impacts on operational performance that transportation, limited documentation and waiting times play in assembly lines composed of an intensive workforce. Second, the paper unveils the understanding of the role that a limited understanding of how the assembly line functions play in productivity. Finally, the authors provide actionable insights into the levelling problems in manual assembly lines.

This research supports industries operating assembly lines with intensive utilisation of manual workforce to improve operational performance. The paper also proposed a novel conceptual model prescriptively guiding quick and long-term improvements in intensive manual workforce assembly lines. The article assists industrial decision-makers with subsequent turnaround strategies to ensure higher efficiency levels requested by the market.

The paper offers actionable findings relevant to other manual assembly lines utilising an intensive workforce looking to improve operational performance. Some of the methods and strategies examined in this study to improve productivity require minimal capital investments. Lastly, the study contributes to the empirical literature by identifying production levelling problems in a real context.

Grounded on trait activation and social learning theories, this study aims to examine the effects of bottom-line mentality (BLM) and perceived abusive supervisory behaviour on proactive employee work behaviour and employee bottom-line mentality (EBLM) in micro-, small- and medium-sized enterprises (MSMEs) in Ghana. The moderating effects of relational attachment on how abusive supervisory behaviour relates to employee proactive work behaviour (PWB) and BLM were examined.

The study was based on a quantitative approach. An online questionnaire was used in a cross-sectional survey to elicit data from 643 conveniently sampled employees. Structural equation modelling was used to analyse the data.

The results support the proposition that owner-manager bottom-line mentality (OMBLM) positively and significantly predicts abusive supervision. The findings also revealed that owner-manager abusive supervisory behaviour significantly predicts employee PWB and EBLM. While the moderating effect of relational attachment on the relationship between perceived owner-manager abusive supervisory behaviour and EBLM is positive and significant, its effect on perceived owner-manager abusive supervisory and proactive employee work behaviour relationship was positive but insignificant.

The authors studied owner-manager abusive supervisory behaviour to understand how OMBLM relates to proactive employee work behaviour and EBLM among MSMEs in Ghana. The study sets the tone to investigate further the impact of OMBLM and the functional effect of owner-manager abusive supervisory behaviour on manager–employee relationships and outcomes among MSMEs in emerging economies.

This paper examine whether social performance moderates the linkage between financial risk and financial performance in microfinance institutions (MFIs). The study focuses on the financial self-sufficiency and long-term sustainability of MFIs.

The empirical study uses unbalanced panel data of 2,694 worldwide MFIs from 2009 to 2019. In the first step, the study inspects the impact of social performance and risk on financial performance, proxied as return on assets and operational self-sufficiency. In the second stage, moderated hierarchical regression is applied to test whether social performance moderates the relationship between risk and financial performance. Lastly, the study confirms the significant moderation effects with slope tests.

The study detects robust evidence that financial risk is negatively related to financial performance. Though social performance exhibits a weak positive link with financial performance in silos, the evidence of its moderating effects on risk is mixed and significant. Social performance indicators, such as the borrower retention rate and female representation, positively moderate the relationship between financial risk and financial performance. The study documents that social performance impacts financial performance and operational self-sufficiency through risk moderation. Thus, social performance fosters the sustainability of these institutions over the long haul.

The study is relevant to academics and theorists to consider the stakeholder approach in microfinancing. In the context of stakeholder theory, the study advances the specific social responsiveness process, namely stakeholder engagement.

The evidence that socially sensitive operations can curtail the adverse effects of credit risks on financial performance signify the required attention to social performance. For MFI managers and practitioners, the findings justify the business case for social performance. Stakeholder engagement, under the auspices of social responsiveness, acts as a risk-mitigation mechanism to eventually foster financial performance and self-sufficiency.

The study motivates MFIs to do more for their stakeholders and society by highlighting the benefits of social performance.

The study reaffirms that social performance remains at the epicenter of the MFIs' mission and is an essential risk mitigation mechanism. The study adds to the extant literature on stakeholder engagement and its effects on MFIs.

This research aims to enhance the operational excellence and continuous improvement of the retail supply chain in the Saudi Thobe Factory through an integrated approach of Six Sigma DMAIC (Define-Measure-Analyze-Improve-Control) with artificial intelligence (AI).

The study identified the tailoring department as the department with maximum defects by using voice of customer and critical to quality tools. An AI-integrated Six Sigma approach was applied to identify and eliminate nonproductive stages, and a new facility layout was designed to enhance productivity and customer satisfaction.

The use of the factor rating method and simulation using Arena software led to an improved sigma level from 1.597 to 2.237, representing an increment of about 40%. Additionally, the defects per million opportunities reduced from 461,538 to 230,769. The study can help production industry management to optimize facility layouts and improve overall production line efficiency.

This study addresses the lack of published research on the use of an integrated approach of Six Sigma DMAIC with AI in the retail and distribution sector of Saudi Arabia, particularly for small and medium-sized enterprises (SMEs). The study demonstrates how this approach may significantly boost SMEs’ performance and provides a basis for future research in this area.

This study provides a practical example of how an integrated approach of Six Sigma DMAIC with AI can be used in the retail and distribution sector of Saudi Arabia to enhance operational excellence and continuous improvement. The study highlights the potential benefits of this approach for SMEs in the region and provides a framework for future research.

Quality management practitioners have yet to cease the potential of digitalisation. Furthermore, there is a lack of tools such as frameworks guiding practitioners in the digital transformation of their organisations. The purpose of this study is to provide a framework to guide quality practitioners with the implementation of digitalisation in their existing practices.

A review of literature assessed how quality management and digitalisation have been integrated. Findings from the literature review highlighted the success of the integration of Lean manufacturing with digitalisation. A comprehensive list of Lean Six Sigma tools were then reviewed in terms of their effectiveness and relevance for the hybrid digitisation approach to process improvement (HyDAPI) framework.

The implementation of the proposed HyDAPI framework in an industrial case study led to increased efficiency, reduction of waste, standardised work, mistake proofing and the ability to root cause non-conformance products.

The activities and tools in the HyDAPI framework are not inclusive of all techniques from Lean Six Sigma.

The HyDAPI framework is a flexible guide for quality practitioners to digitalise key information from manufacturing processes. The framework allows organisations to select the appropriate tools as needed. This is required because of the varying and complex nature of organisation processes and the challenge of adapting to the continually evolving Industry 4.0.

This research proposes the HyDAPI framework as a flexible and adaptable approach for quality management practitioners to implement digitalisation. This was developed because of the gap in research regarding the lack of procedures guiding organisations in their digital transition to Industry 4.0.

This paper aims to examine the effects of the real exchange rate on trade balance in Algeria and investigates whether it represents a viable tool to sustain and improve trade performance using the nonlinear autoregressive distributed lag (NARDL) estimation technique and data from Algeria over the period 1980–2018. This study also highlights the role of trading partners with large income endowments in enhancing the trade balance.

The NARDL model is used to unveil potential short and long run nonlinear responses of the trade balance to shocks in real exchange rates and detect whether these responses are different in terms of sign and magnitude. The paper also provides a dynamic multiplier analysis that tests the existence of a J-Curve pattern in Algeria with several policy recommendations.

The findings confirm the existence of a J-curve pattern in Algeria where domestic currency depreciation will worsen the trade balance in the short run and improve it in the long run. The authors also find that the asymmetrical effect of real exchange rate on trade balance is different in sign and magnitude. Finally, the results indicate that an increase in trade partners' income increases the trade balance in Algeria. The findings are of utmost importance with several policy implications.

While some works investigated the nonlinear response of trade balance to real exchange rate movements, their results remain inconclusive and seem to depend on the characteristics of the country/region of study. Moreover, the role of trade partners and their potential impact on trade balance has been relatively overlooked in the literature. The authors fill this gap by examining the asymmetric impacts of real exchange rate and the effect of trade partners' income on trade balance in Algeria.

Lean manufacturing (LM) concepts have been widely adopted in diverse industrial sectors. However, no literature review focusing on case studies describing LM implementation is available. Case studies represent the actual implementation and provide secondary data for further analysis. This study aims to review the same to understand the pathways of LM implementation. In addition, it aims to analyse other related review questions, such as how implementing LM impacts manufacturing capabilities and the maturity level of manufacturing organisations that implemented LM, to name a few.

A literature review of case studies that discuss the implementation of LM during the last decade (from 2010 to 2020) is carried out. These studies were synthesised, and content analyses were performed to reveal critical insights.

The implementation pattern of LM significantly varies across manufacturing organisations. The findings show simultaneous improvement in manufacturing capabilities. Towards the end of the last decade, organisations implemented LM with radio frequency identification, e-kanban, simulation, etc.

Reviewing the case studies documenting LM implementation to comprehend the various nuances is a novel attempt. Furthermore, potential future research directions are identified for advancing the research in the domain of LM.

The primary objective of this research is to determine critical success factors (CSFs) that enable textile enterprises to effectively implement Kaizen, a Japanese concept of continuous development, particularly during disruptive situations. The study aims to provide insights into how Kaizen is specifically employed within the textile sector and to offer guidance for addressing future crises.

This study employs a structured approach to determine CSFs for successful Kaizen implementation in the textile industry. The Triple Helix Actors structure, comprising business, academia and government representatives, is utilized to uncover essential insights. Additionally, the Matriced Impacts Croises-Multiplication Applique and Classement (MICMAC) analysis and interpretative structural modeling (ISM) techniques are applied to evaluate the influence of CSFs.

The research identifies 17 CSFs for successful Kaizen implementation in the textile industry through a comprehensive literature review and expert input. These factors are organized into a hierarchical structure with 5 distinct levels. Additionally, the application of the MICMAC analysis reveals three clusters of CSFs: linkage, dependent and independent, highlighting their interdependencies and impact.

Major contribution of this study is understanding how Kaizen can be effectively utilized in the textile industry, especially during disruptive events. The combination of the Triple Helix Actors structure, MICMAC analysis and ISM provides a unique perspective on the essential factors driving successful Kaizen implementation. The identification of CSFs and their categorization into clusters offer valuable insights for practitioners, policymakers and academia seeking to enhance the resilience and sustainability of the textile industry.