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This study aims to quantify and prioritize the main causes of lean wastes and to apply reduction methods by employing better waste cause identification methodologies.

We employed fuzzy techniques for order preference by similarity to the ideal solution (FTOPSIS), fuzzy analytical hierarchy process (FAHP), and failure mode effect analysis (FMEA) to determine the causes of defects. To determine the current defect cause identification procedures, time studies, checklists, and process flow charts were employed. The study focuses on the sewing department of a clothing industry in Addis Ababa, Ethiopia.

These techniques outperform conventional techniques and offer a better solution for challenging decision-making situations. Each lean waste’s FMEA criteria, such as severity, occurrence, and detectability, were examined. A pairwise comparison revealed that defect has a larger effect than other lean wastes. Defects were mostly caused by inadequate operator training. To minimize lean waste, prioritizing their causes is crucial.

The research focuses on a case company and the result could not be generalized for the whole industry.

The study used quantitative approaches to quantify and prioritize the causes of lean waste in the garment industry and provides insight for industrialists to focus on the waste causes to improve their quality performance.

The methodology of integrating FMEA with FAHP and FTOPSIS was the new contribution to have a better solution to decision variables by considering the severity, occurrence, and detectability of the causes of wastes. The data collection approach was based on experts’ focus group discussion to rate the main causes of defects which could provide optimal values of defect cause prioritization.

The aim of this review is to present together the studies on textile-based moisture sensors developed using innovative technologies in recent years.

The integration levels of the sensors studied with the textile materials are changing. Some research teams have used a combination of printing and textile technologies to produce sensors, while a group of researchers have used traditional technologies such as weaving and embroidery. Others have taken advantage of new technologies such as electro-spinning, polymerization and other techniques. In this way, they tried to combine the good working efficiency of the sensors and the flexibility of the textile. All these approaches are presented in this article.

The presentation of the latest technologies used to develop textile sensors together will give researchers an idea about new studies that can be done on highly sensitive and efficient textile-based moisture sensor systems.

In this paper humidity sensors have been explained in terms of measuring principle as capacitive and resistive. Then, studies conducted in the last 20 years on the textile-based humidity sensors have been presented in detail. This is a comprehensive review study that presents the latest developments together in this area for researchers.

Task complexity is one of the significant factors that influences and is used for forecasting employee performance and determining labor cost. However, the complexity level of tasks is unstructured, dynamic and complicated to perform. This paper develops a new method for evaluating the complexity level of tasks in the production process to support production managers to control their manufacturing systems in terms of flexibility, reliability to production planning and labor cost.

The complexity level of tasks will be analyzed based on the structuralist concept. Using the structure of task, the factors that significantly affect the task complexity in an assembly line will be defined, and the complexity level of the task will be evaluated by measuring the number of task components. Using the proportional 2-tuples linguistic values, the difference between the complexity levels of tasks can be compared and described clearly.

Based on the structure of the task, three contributory factors including input factors, process-operation factors and output factors that significantly affect the task complexity in an assembly line are identified in the present study. The complexity level of the task is quantified through analyzing the details of the three factors according to two criteria and six sub-criteria within the textile case study.

The proposed approach provides a new insight about the factors that have an effect on the complexity of tasks in production and remedies some of limitations of previous methods. The combination of experts' experience and scientific knowledge will improve the accuracy in determining the complexity level of tasks.

Industry 4.0 has an inimitable potential to create competitive advantages for the apparel industry by enhancing productivity, production, profitability, efficiency and effectiveness. This study, thus, aims to assess the digitalisation level of the Tanzanian apparel industry through the Industry 4.0 perspectives.

A mixed-methods-based approach was deployed. This study deployed semi-structured interviews, document review and observation methods for the qualitative approach. For the quantitative approach, closed-ended questionnaires were used to ascertain the digitalisation levels and maturity level of the textiles and apparel (T&A) factories and small and medium-sized textile enterprises in Tanzania. The sample size was 110, with participants engaged through the purposive sampling technique.

Industry 4.0 frameworks evolved into practices mainly since 2011 in several service and manufacturing industries globally. For Tanzania, the findings indicate that the overall maturity level of the T&A industries is 2.5 out of 5.0, demonstrating a medium level of adoption. Thus, the apparel industries are not operating under the industry 4.0 framework; they are operating within the third industrial revolution – Industry 3.0 – framework. For such industries to operate within the fourth industrial revolution – Industry 4.0 – that is only possible if there is significantly well-developed industrial infrastructure, availability of engineering talent, stable commercial partnerships, demand from the marketplace and transactional relationship with customers.

This study’s limitations include: firstly, Industry 4.0 is an emerging area; this resulted in limited theoretical underpinnings in the Tanzanian perspectives. Secondly, the studied industries may not suffice the need to generalise the findings for the entire country, thus needing another study.

Although Industry 4.0 conceptual frameworks have been on trial in several industries since 2011, this is amongst the first empirical research on Industry 4.0 in the Tanzanian apparel industry that assesses the digitalisation levels.

The purpose of this paper is to analyze the evolution of the rules of origin (RoO) of Regional Comprehensive Economic Partnership (RCEP).

This analysis is done by comparing them with those of existing FTAs/EPAs of ASEAN with other RCEP member countries, and also examining the impact of recent mega-FTAs/EPAs, such as TPP11 and Japan-EU EPA, in which some of the member countries participated.

RCEP holds great significance in that it connects Japan and China and Japan and South Korea, which previously have not had any EPAs/FTAs, transforms this massive economic sphere from one with minutely divided and differing RoO under ASEAN plus FTAs to one that is seamlessly connected with those of having evolved into the unified RoO under RCEP, and realizes ideal production networks in Asia.

This paper makes it clear that RCEP, while based on ASEAN plus FTAs, reflects progressive provisions of recent mega-FTAs/EPAs, and adopts simpler and more systematic rules. These provisions limit the distortive effect on trade, realize ideal production networks in Asia, and are appropriate as uniform RoO connecting networks across this massive economic sphere. It also points out that there are provisions that have not been introduced and those that are considered to have been incomplete as a result of negotiations, and the possibility of evolving into more ideal RoO by utilizing the system for revisions established under the agreement.

The complexity of succession in family firms is multifaceted and can sometimes lead to turbulence. While structured succession strategies offer a roadmap for smoother transitions, intergenerational differences in family small and medium-sized enterprises (SMEs) can lead to varied interpretations of an effective succession blueprint. This study synergizes the strategic entrepreneurship framework with the socioemotional wealth (SEW) perspective to probe into how formalized succession planning impacts performance in family SMEs. Furthermore, it delves into the mediating role of succession satisfaction, especially in family firms characterized by pronounced SEW and helmed by CEOs from different generational cohorts.

Employing a comprehensive dataset from 1,833 global family businesses, this research utilizes bootstrapping regression models to discern the intertwined effects of mediator and moderator variables and their statistical significance.

The main findings suggest that succession satisfaction does matter for a good succession process and that succession plans work only in family firms with a high degree of SEW and that are led by older family CEOs (e.g. baby boomers).

The results offer fresh perspectives on succession processes, with a particular focus on how to improve the satisfaction of millennial family CEOs.

The study uniquely combines strategic entrepreneurship and SEW to offer a holistic view of succession planning, highlighting satisfaction’s mediating role and SEW’s moderating influence. Additionally, it pioneers the incorporation of generational cohorts into the succession discourse.

The study provides the emergence and evolution of the socioemotional wealth (SEW) concept in the family business field from 2007 (the inception date) until 2021. To provide a better overview of this notion, the study unfolds a deeper understanding of this term throughout the systematic literature review (SLR).

The study applies a systematic literature review (SLR) by analyzing the sample of 185SEW articles extracted from the Scopus database. To identify all relevant studies, the article selection process was carefully designed and divided into two phases with clear steps: identification of studies via databases and identification of studies via previous studies' reference lists. Selected studies were analyzed using the Bibliometrix R-tool, resulting in an analysis of the evolution of the trends in the SEW literature, citation analysis, and network analysis. Finally, this SLR included the content analysis of the 25 most-cited SEW articles.

The study provides a relevant and comprehensive overview facilitating empirical and theoretical research in this field and paving the way to develop new themes. The bottom line of the important findings is that the SEW concept is relatively new, alluding to a wealthy venue for future works. Other results and implications are discussed on the family business and SEW theme. Additionally, the study provides suggestions which could be used for future works in this area.

This is the first article related to the SEW concept in the family business. It portrays a clear picture of this field, providing relevant information on what has been done, as well as what the future possibilities are that might bode the future horizons in family businesses.

This research aims to investigate how manufacturing flexibility can address the challenges of an ever-changing and unpredictable business environment in Bangladesh’s labor-intensive ready-made garment (RMG) industry, which is underserved and situated in a developing country.

Using Partial Least Square Structural Equation Modeling, this study empirically evaluated the relationships between manufacturing flexibility, environmental uncertainty and firm performance. The analysis utilized 320 survey responses from potential RMG experts, representing 95 organizations.

The study achieved a decision-making model for implementing manufacturing flexibility in the RMG industry of Bangladesh with acceptable model fit criterion. The research pinpointed that workforce flexibility plays the maximum mediating among different types of manufacturing in coping with demand and supply uncertainty in the RMG sector.

The study made valuable contributions to theoretical and practical knowledge in the context of manufacturing flexibility in Bangladesh’s RMG and other underserved labor-intensive sectors in developing economies. It suggests that managers should shift from defensive and risky business strategies to more aggressive and proactive approaches by utilizing workforce flexibility resources adaptively to enhance manufacturing capabilities and align with dynamic market demand. Additionally, the study offers recommendations for future research to build upon its findings.

This study is unique in its approach because it presents a decision model for implementing manufacturing flexibility in a labor-intensive industry in a developing economy, specifically the RMG industry in Bangladesh, whereas previous research has primarily focused on high-tech industries in developed economies.

T Education is a leading educational science and technology enterprise in China with technology-driven, talent intimacy and quality leadership as the core development objectives. Since its inception, it has been committed to creating better learning experience for children. As the predecessor of T-education, X-education was founded in Beijing in 2003. At first, it mainly provided after-school math counseling for school-age children. Over the past 10 years, its business has been expanding, covering almost every aspect of school-age education. This case studies accounting issues and business ethics challenges that firms may face when they transform from a single (traditional education) line of business to a multiple channel business.

The paper aims to investigate the comfort-related performances of an innovative solar shading solution based on a new composite patented material that consists of a cement-based matrix coupled with a stretchable three-dimensional textile. The paper’s aim is, through a performance-based generative design approach, to develop a high-performance static shading system able to guarantee adequate daylit spaces, a connection with the outdoors and a glare-free environment in the view of a holistic and occupant-centric daylight assessment.

The paper describes the design and simulation process of a complex static shading system for digital manufacturing purposes. Initially, the optical material properties were characterized to calibrate radiance-based simulations. The developed models were then implemented in a multi-objective genetic optimization algorithm to improve the shading geometries, and their performance was assessed and compared with traditional external louvres and overhangs.

The system developed demonstrates, for a reference office space located in Milan (Italy), the potential of increasing useful daylight illuminance by 35% with a reduced glare of up to 70%–80% while providing better uniformity and connection with the outdoors as a result of a topological optimization of the shape and position of the openings.

The paper presents the innovative nature of a new composite material that, coupled with the proposed performance-based optimization process, enables the fabrication of optimized shading/cladding surfaces with complex geometries whose formability does not require ad hoc formworks, making the process fast and economic.