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In this study, the authors investigate whether supply chain (SC) strategies (lean or agile) improve or hinder the supply chain transparency (SCT) and what factors affect this relation.

The authors measure the level of SC strategy using natural language processing based on the annual financial reports of listed firms. Secondary data analysis is conducted on various databases encompassing 1,241 listed firms in China from 2011 to 2020. Additional tests are performed to assess the robustness of the results, and alternative explanations are duly considered.

The authors find that firms with an advanced level of SC strategy perform better on SCT. Furthermore, the authors observe that Agile SC strategy and Lean SC strategy have different effects on SCT over a firm’s life cycle. Agile SC strategy (the ratio of the proportion of Agile SC strategy word frequency divided by the proportion of Lean SC strategy word frequency greater than 1) has a significantly positive effect on SCT in the maturity stage; Lean SC strategy (the ratio less than 1) has a positive effect on SCT in the growth and decline stages. An increase in online media coverage negatively moderates the impact of the SC strategy (frequency of Lean and Agile SC strategy-related keywords) on SCT in the maturity stage. An increase in government environmental subsidies positively moderates the impact of SC strategy on SCT in the maturity and decline stages. Additionally, an increase in industrial competition intensity positively moderates the impact of the SC strategy on SCT in the decline stage.

The authors' study contributes to the Operations and Supply Chain Management (OSCM) literature by revealing the positive impact of SC strategy on SCT with objective secondary data. Additionally, the authors examine the moderating effects of moderators over the lifecycle of a firm on this relationship in an emerging market context. The authors' findings offer valuable guidance to companies operating in diverse market environments, providing actionable insights to strengthen their SC strategies and enhance SCT.

The textile industry contributes 2 and 3% to the global and Indian Gross Domestic Product (GDP), respectively. India supplies a quarter of global cotton yarn. Yet, most yarn manufacturing companies use outdated methods and lack organisational skills and strategies. Improvement in processes in India could significantly help the industry worldwide.

The variables that influence the performance of the system were identified. Their interrelationships and impact were identified from the employees in the chosen case study, a yarn manufacturing industry. A System Dynamics (SD) approach was employed to study the benefits of implementing 5S lean strategies. The impact of each variable on various performance measures such as throughput, Work In Progress, processing time, waiting time, idle time, over-processing and scraps was analysed.

Improvement in outcomes reflected an enhanced adoption of leanness in the industry. The decision-makers can utilise this study to optimise the necessary parameters in the system and attain the desired productivity levels. Better resource management and reduced processing time helped increase the despatch rate by 9.735% and decrease the WIP by 23.01%. Time management helped to reduce the inventory, idle time and waiting time. Over-processing, defects and scraps were minimised, indicating a shift towards lean.

This study pioneers the use of SD simulation models for optimising yarn manufacturing using lean strategies. Improvement in performance measures by integrating these strategies opens avenues for future research using multiple approaches to address a problem.

Implementing 5S lean principles and simulations enhances productivity, reduces waste and optimises resource management for the yarn manufacturing industry. Decision-makers can employ simulation to witness the outcomes of their changes without investing cost and time and without associated implementation risks.

The use of a simulation model to witness the benefits of incorporating lean strategies in yarn production has not been explored. This approach could help the managers and policymakers understand their existing system's shortcomings and critical areas that require improvement.

The proliferation of lean principles in the construction industry is offset by the enduring uncertainty among industry stakeholders regarding their respective roles in lean implementation. This uncertainty is further compounded by the scarcity of empirical investigations in this area. Consequently, this study undertakes the task of bridging this knowledge gap by identifying the critical roles of lean learners and their indispensable contributions to achieving successful lean implementation.

A qualitative exploratory approach informed by an interpretivism perspective was adopted. The case study strategy was employed to gather data from three contracting organisations that had implemented lean practices. Empirical data was collected through in-depth semi-structured interviews with fifteen industry experts and complemented by document reviews. To analyse the data, a code-based content analysis approach was employed using NVivo software, while Power BI software was utilised to develop a comprehensive force-directed graph visualisation.

The research findings substantiated nine lean learners and unveiled a set of seventy-three roles associated with them. The force-directed graph facilitated the identification of lean learners and their connections to the emerged roles. Notably, the graph highlighted the pivotal role played by project managers and internal lean trainers in ensuring the success of lean implementation, surpassing the contributions of other lean learners.

The implications of findings extend to industry professionals seeking to establish a robust lean learning framework to expedite lean implementation within the construction sector. This study not only provides a comprehensive definition of lean learners’ roles but also transcends specific construction types, making it a significant catalyst for global impact.

This study aims to develop a modular and prescriptive digital transformation maturity model whose constituent elements have conceptual integrity as well as reveal the priority weights of maturity model components.

A literature review with a concept-centric analysis enlightens the characteristics of constituent parts and reveals the gaps for each component. Therefore, the interdependency network among model dimensions and priority weights are identified using decision-making trial and evaluation laboratory (DEMATEL)-based analytic network process (ANP) method, including 19 industrial experts, and the results are robustly validated with three different analyses. Finally, the applicability of the developed maturity model and the constituent elements are validated in the context of the manufacturing industry with two case applications through a strict protocol.

Results obtained from DEMATEL-based ANP suggest that smart processes with a priority weight of 17.91% are the most important subdimension for reaching higher digital maturity. Customer integration and value, with a priority weight of 17.30%, is the second most important subdimension and talented employee, with 16.24%, is the third most important subdimension.

The developed maturity model enables companies to make factual assessments with specially designed measurement instrument including incrementally evolved questions, prioritize action fields and investment strategies according to maturity index calculations and adapt to the dynamic change in the environment with spiral maturity level identification.

A novel spiral maturity level identification is proposed with conceptual consistency for evolutionary progress to adapt to dynamic change. A measurement instrument that is incrementally structured with 234 statements and a measurement method that is based on the priority weights and leads to calculating the maturity index are designed to assess digital maturity, create an improvement roadmap to reach higher maturity levels and prioritize actions and investments without any external support and assistance.

3D printing has been warmly welcomed by clothing enterprises for its customization capacity in recent years. However, such clothing enterprises have to face the digital transformation challenges brought by 3D printing. Since the business model is a competitive weapon for modern enterprises, there is a research gap between business model innovation and digital transformation challenges for 3D-printing garment enterprises. The aim of the paper is to innovate a new business model for 3D-printing garment enterprises in digital transformation.

A business model innovation canvas (BMIC), a new method for business model innovation, is used to innovate a new 3D-printing clothing enterprises business model in the context of digital transformation. The business model canvas (BMC) method is adopted to illustrate the new business model. The business model ecosystem is used to design the operating architecture and mechanism of the new business model.

First, 3D-printing clothing enterprises are facing digital transformation, and they urgently need to innovate new business models. Second, mass customization and distributed manufacturing are important ways of solving the business model problems faced by 3D-printing clothing enterprises in the process of digital transformation. Third, BMIC has proven to be an effective tool for business model innovation.

The new mass deep customization-distributed manufacturing (MDC-DM) business model is universal. As such, it can provide an important theoretical reference for other scholars to study similar problems. The digital transformation background is taken into account in the process of business model innovation. Therefore, this is the first hybrid research that has been focused on 3D printing, garment enterprises, digital transformation and business model innovation. On the other hand, business model innovation is a type of exploratory research, which means that the MDC-DM business model’s application effect cannot be immediately observed and requires further verification in the future.

The new business model MDC-DM is not only applicable to 3D-printing garment enterprises but also to some other enterprises that are either using or will use 3D printing to enhance their core competitiveness.

A new business model, MDC-DM, is created through BMIC, which allows 3D-printing garment enterprises to meet the challenges of digital transformation. In addition, the original canvas of the MDC-DM business model is designed using BMC. Moreover, the ecosystem of the MDC-DM business model is constructed, and its operation mechanisms are comprehensively designed.

With ever-increasing global concerns over environmental degradation and resource scarcity, the need for sustainable manufacturing (SM) practices has become paramount. Industry 5.0 (I5.0), the latest paradigm in the industrial revolution, emphasizes the integration of advanced technologies with human capabilities to achieve sustainable and socially responsible production systems. This paper aims to provide a comprehensive analysis of the role of I5.0 in enabling SM. Furthermore, the review discusses the integration of sustainable practices into the core of I5.0.

The systematic literature review (SLR) method is adopted to: explore the understanding of I5.0 and SM; understand the role of I5.0 in addressing sustainability challenges, including resource optimization, waste reduction, energy efficiency and ethical considerations and propose a framework for effective implementation of the I5.0 concept in manufacturing enterprises.

The concept of I5.0 represents a progressive step forward from previous industrial revolutions, emphasizing the integration of advanced technologies with a focus on sustainability. I5.0 offers opportunities to optimize resource usage and minimize environmental impact. Through the integration of automation, artificial intelligence (AI) and big data analytics (BDA), manufacturers can enhance process efficiency, reduce waste and implement proactive sustainability measures. By embracing I5.0 and incorporating SM practices, industries can move towards a more resource-efficient, environmentally friendly and socially responsible manufacturing paradigm.

The findings presented in this article have several implications including the changing role of the workforce, skills requirements and the need for ethical considerations for SM, highlighting the need for interdisciplinary collaborations, policy support and stakeholder engagement to realize its full potential.

This article aims to stand on an unbiased assessment to ascertain the landscape occupied by the role of I5.0 in driving sustainability in the manufacturing sector. In addition, the proposed framework will serve as a basis for the effective implementation of I5.0 for SM.

Industry 5.0 (I5.0) is eventually set to supersede Industry 4.0 (I4.0), despite the fact that I4.0 continues to gain ground in emerging nations like India. Now India is aspiring to be a global manufacturing hub, and I5.0 offers enormous potential to position India as a forerunner in intelligent and collaborative manufacturing systems. Therefore, this research article aims to understand the relationship between I5.0 and sustainable manufacturing (SM) thoroughly; pinpoint its impact and implementation challenges; analyze its impact on Triple-Bottom-Line (TBL) sustainability; and present an inclusive framework for I5.0 implementation for Indian manufacturing enterprises.

The coexistence of two industrial revolutions raises questions, which necessitates debates and explanations. Thus, the systematic literature review (SLR) approach is used to address this issue and this study used Web of Science, Scopus, Science Direct and Google Scholar databases. Following a critical SLR, 82 research papers have been cited in this article, and the majority of cited articles were published from 2010 to 2022, to ensure a focused analysis of pertinent and recent scholarly contributions.

I4.0 is considered to be technology-driven, however, I5.0 is perceived to be value-driven. I5.0 is not a replacement or a chronological continuation of the I4.0 paradigm. The notion of I5.0 offers a distinct perspective and emphasizes the necessity of research on SM within the TBL sustainability boundaries. I5.0 introduces a new TBL: resilience in value creation, human well-being and sustainable society. Indeed, I5.0 seems to be economically, socially, and environmentally sustainable while manufacturing products with high productivity.

Theoretical implications pertain to restructuring business models and workforce transformation, whereas practical implications underscore the significance for manufacturing enterprises to embrace I5.0 for their sustainable development. By understanding the nuanced relationship between I5.0 and SM, enterprises can navigate implementation challenges, maximize TBL sustainability and embrace an inclusive I5.0 framework for high productivity and resilience.

The existing literature presents the general notion of I5.0 but lacks in-depth TBL sustainability analysis. This research used a systematic and rigorous SLR approach that evaluates the existing literature, enables an in-depth understanding, identifies research gaps and provides evidence-based recommendations for the decision-making process. Furthermore, this research aims to stand on an unbiased assessment, exploring theoretical and practical implications of I5.0 implementation for manufacturing enterprises and suggesting future research avenues.

This paper aims to examine and compare the export performance and competitiveness of Indian and Chinese textile and clothing industry in post-multifibre arrangement (MFA) era.

Balassa’s revealed comparative advantage Index is used to assess the competitiveness of Indian and Chinese textile and clothing exports.

The results indicate that China’s textiles and garments sector holds a greater proportion of the global market compared with India. India has a robust comparative advantage in silk, carpets and cotton post-MFA. Vegetable textile fibers, paper yarn and woven fabrics of paper yarn are also competitive. China had a strong comparative advantage in silk and fabrics; special woven fabrics, tafted textile fabrics, lace, tapestries, trimmings and embroidery in 2005. China also recorded comparative advantage in silk, man-made filaments: strip and the like of man-made textile materials, fabrics; special woven fabrics, tafted textile fabrics, lace, tapestries, trimmings and embroidery and fabrics; knitted or crocheted in 2021.

This study’s results and recommendations could assist the Indian and Chinese Governments develop policies to upgrade their garment industries.

Though vast literature reviews are available for textile and apparel export performance in India and China separately, there are few studies on comparisons. This study is a significant attempt to evaluate India and China’s competitiveness in the global market.

The purpose of this paper is to examine the resistance behavior of smart factories in small and medium-sized enterprises (SMEs). Drawing upon dual factor perspective, this study examines how two types of quality and perceived usefulness impact user resistance as enabling factors and how switching cost, skepticism, habit and inertia contribute to user resistance as inhibiting factors. Additionally, multi-group analysis is employed to compare small and medium enterprises.

Purposive sampling technique was employed to collect 460 Korean SMEs employees, consisting of 235 small enterprises and 225 medium enterprises. Partial least squares structural equation modeling was used for data analysis.

The results reveal that all three inhibiting factors, switching cost, skepticism and habit, are key antecedents of inertia. In small enterprises, skepticism has a greater impact on inertia, which in turn strongly affects resistance. Additionally, system quality is more crucial for small enterprises, whereas information quality holds more importance for medium enterprises in mitigating resistance. Moreover, when the implementation level of a smart factory is high, the effect of perceived usefulness on user resistance diminishes.

This study has revealed the importance of considering both enabling and inhibiting factors for the adoption of smart factory systems in the context of SMEs. Additionally, it has provided evidence that as the level of the smart factory system increases, the effect of perceived usefulness on user resistance decreases, thus making the transition to smart factory systems more challenging.

Offsite construction (OSC) is a modern method of construction (MMC) that involves manufacturing and assembly of buildings. Industry 4.0-driven technological advancements have accelerated OSC uptake causing many skilled construction workers requiring re-skilling or up-skilling. Quantity surveyors currently play an important role throughout a construction project life cycle, and hence, their knowledge on OSC projects is vital for the continuity of quantity surveying (QS) profession. The purpose of this paper is to critically review QS education in an OSC perspective and to propose strategies for up-skilling.

This research includes a detailed literature review of QS and OSC to evaluate how OSC affects the QS profession. Publicly available information on the university websites on accredited QS and construction management degrees was reviewed to identify OSC and MMC references, specifically the content listing and learning outcomes.

Out of the 315 degrees offered by 157 universities, only 69 degrees in 32 universities refer to OSC or MMC. OSC concept is explicitly referred in subjects related to construction technology, production management, lean construction, digital construction and MMC. As such, the research suggests including lean production principles, OSC techniques and design philosophies such as design for manufacture and assembly be added to the QS curricula.

This research is a comprehensive desktop study that does not involve empirical data-based evaluation. Research findings inform strategies to improve QS education and professional competencies.

To the best of the authors’ knowledge, this paper is the first of its kind that evaluates accredited QS degrees and learning requirements in an OSC perspective.