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The complex network structure causes several disruptions in the supply chain that make risk management essential for supply chain management including halal supply chain (HSM). During risk management, several challenges are associated with the risk assessment phase, such as incomplete and uncertain information about the system. To cater this, the authors propose a risk assessment framework that addresses the issues of uncertainty using neutrosophic theory and demonstrated the applicability of the proposed framework through the case of halal supply chain management (HSCM).

The proposed framework is using the capabilities of the neutrosophic number which can handle uncertain, vague and incomplete information. Initially, the risk related to the HSC is identified through a literature review and expert’s input. Further, the probability and impact of each HSM-related risk are assessed using experts’ input through linguistic terms. These linguistic values are transformed into single-value trapezoidal neutrosophic numbers (SVTNNs). Finally, the severity of each HSM-related risk is determined through the multiplication of the probability and impact of each risk and prioritised the risks based on their severity.

A comprehensive risk assessment framework is developed that could be used under uncertainty. Initially, 16 risks are identified related to the HSM. Further, the identified risks are prioritised using the severity of the risks. The high-priority risk is “raw material status”, “raw material wholesomeness” and “origin of raw material” while “information integrity” and “people integrity” are low-priority risks.

HSM risk can be effectively assessed through the proposed framework. The proposed framework applied neutrosophic numbers to represent real-life situations, and it could be used for other supply chains as well.

The proposed method is effectively addressing the issue of linguistic subjectivity, inconsistent information and uncertainty in the expert’s opinion. A case study of the HSC is adopted to illustrate the efficiency and applicability of the proposed risk framework.

The increasing urgency to address climate change in construction has made green construction (GC) and sustainability critical topics for academia and industry professionals. However, the volume of literature in this field has made it impractical to rely solely on traditional systematic evidence mapping methodologies.

This study employs machine learning (ML) techniques to analyze the extensive evidence-base on GC. Using both supervised and unsupervised ML, 5,462 relevant papers were filtered from 10,739 studies published from 2010 to 2022, retrieved from the Scopus and Web of Science databases.

Key themes in GC encompass green building materials, construction techniques, assessment methodologies and management practices. GC assessment and techniques were prominent, while management requires more research. The results from prevalence of topics and heatmaps revealed important patterns and interconnections, emphasizing the prominent role of materials as major contributors to the construction sector. Consistency of the results with VOSviewer analysis further validated the findings, demonstrating the robustness of the review approach.

Unlike other reviews focusing only on specific aspects of GC, use of ML techniques to review a large pool of literature provided a holistic understanding of the research landscape. It sets a precedent by demonstrating the effectiveness of ML techniques in addressing the challenge of analyzing a large body of literature. By showcasing the connections between various facets of GC and identifying research gaps, this research aids in guiding future initiatives in the field.

Due to the importance of quality to customers, this study considers criteria of quality and profit and optimizes both in a multi-echelon cold chain of perishable agricultural products whose quality immediately begins to deteriorate after harvest. The two objectives of the proposed cold chain are to maximize profit and quality. Since postharvest quality loss in the supply chain depends on various decisions and factors, in addition to strategic decisions, the authors consider the temperature setting in refrigerated facilities and transportation vehicles due to the unfixed shelf life of the products which is related to the temperature found by Arrhenius formula.

The authors use bi-objective mixed-integer nonlinear programming to design a four-echelon supply chain. The authors integrate the supply chain echelons to detect the sources and factors of quality loss. The four echelons include supply, processing, storage and customer. The decisions, including facility location, assigning nodes of each echelon to corresponding nodes from the adjacent echelon, allocation of vehicles to transport the products from farms to wholesalers, processing selection, and temperature setting in refrigerated facilities, are made in an integrated way. Model verification and validation in the case study are done based on three perishable herbal plants.

The model obtains a 29% profit against a total cost of 71 and 93% of original quality of the crops is maintained, indicating a 7% quality loss. The final quality of 93% is the result of making a US$6m investment in the supply chain, including the procurement of high-quality raw materials; facility establishment; high-speed, high-capacity vehicles; location assignment; processing selection and refrigeration equipment in the storage and transportation systems, helping to maximize both the final quality of the products and the total profit.

The proposed supply chain model should help managers with modeling decisions, especially when it comes to cold chains for agricultural products. The model yields these results – optimal location-allocation decisions for the facilities to minimize distances between the network nodes, which save time and maintain the majority of the products’ original quality; choosing the most appropriate processing method, which reduces the perishability rate; providing high-capacity, high-speed vehicles in the logistics system, which minimizes transportation costs and maximizes the quality; and setting the right temperature in the refrigerated facilities, which mitigates the postharvest decay reaction rate of the products.

Comparison of the results of the present research with those of the traditional chain (obtained through experts) shows that since the designed chain increases the profit as well as the final quality, it has benefits for the main chain stakeholders, which are customers of agricultural products. This study model is expected to have a positive impact on the environment by placing strong emphasis on quality and preventing excessive waste generation and air pollution by imposing a financial penalty on extra demand production.

Since profit and quality of the final product are two important factors in all cultures and communities, the proposed supply chain model can be used in any food industry around the world. Applying the proposed model induces growth in local industries and promotes the culture of prioritizing quality in societies.

To the best of the authors’ knowledge, this is the first research on a bi-objective four-echelon (supply, processing, storage and customer) postharvest supply chain for agricultural products including that integrates transportation logistics and considers the deterioration rate of products as a time-dependent variable at different levels of decision-making.

This study examines the evidence of the impact of climate change on the financial performance of basic materials companies in Vietnam.

The research sample includes eighty-two basic materials companies listed on the Vietnamese stock market from 2003 to 2022. This study used one-way and two-way fixed-effects feasible generalized least squares (FGLS) estimation methods.

Climate change, measured through variables including changes in temperature, average rainfall, greenhouse gas emissions and rising sea levels, has a negative impact on the financial performance of companies in this industry. The study also found that, with rising temperatures, the financial performance of steel manufacturing companies decreased less than that of coal mining and forestry companies, but increasing greenhouse gases and rising sea levels reduced the financial performance of steel companies. We did not find evidence of any difference in the impact of climate change on the financial performance of basic materials companies before and after the UN Climate Change Conference (COP 21). This is a new finding, which is consistent with empirical studies in Vietnam and different from previous studies in that it provides new evidence on the impact of climate change on the financial performance of basic materials companies in the Vietnamese market and cross-checks the impact of climate change by sector and over time.

To the best of our knowledge, this is one of the first articles on climate change and the financial performance of basic materials companies.

The construction industry is shifting towards becoming more circular by reducing waste, reusing building materials and embracing regenerative solutions for energy generation and biodiversity conservation. Thus, construction professionals must perform diversified services to achieve a circular built environment (CBE). Implementing resource planning and waste management in CBE has already posed challenges to the quantity surveying profession; thus, quantity surveyors (QSs) should be equipped with new roles and competencies to tackle challenges in achieving a CBE. Hence, this study aimed to investigate the functions and competencies of QSs at the design and building material sourcing stages in achieving a CBE according to 3R principles.

The research apprehended a qualitative approach, including two expert interview rounds adhering to the Delphi technique with 14 and 11 experts per each round. Manual content analysis was incorporated to analyse the collected data.

The research findings revealed the important roles and competencies of QSs in achieving a CBE. In addition, essential functions and competencies were categorised according to the 3R principles (reduce, reuse, recycle) to successfully implement CBE during the Design and Building Material Sourcing stages. According to the 3R principles of CBE, cost control, cost planning, feasibility studies, measurement and quantification, risk management, value engineering and innovations and technologies were well-received by most interviewees as essential roles of QSs during the Design and Building Material Sourcing stages. Further, basic/mandatory competencies (personal, interpersonal, professional practice and business skills), economic analysis, BIM management, cost management and risk management are highly regarded by experts for QS as important competencies to achieve CBE.

With new construction trends, QSs must enhance their conventional roles and competencies and search for new skills and competencies. Those skills and competencies could be linked to the CE concept, either directly or indirectly. Since QS holds a prominent place in sustainable construction in CBE, adapting to changes in the construction industry such as CBE is timely for QSs. Further, there is a shortage of literature regarding QSs' roles and competencies in achieving a CBE; thus, this study will contribute by identifying new avenues for QSs in achieving a CBE in the practice and the research.

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.

Fabrics, which are one of the raw materials of the clothing industry, constitute approximately 40–45% of the total cost of an apparel product. Due to the labor-intensive nature of this industry and failure to apply scientific methods along with the manufacturing processes, the wastes in the raw materials, including fabrics, become higher. Besides, quality deficiencies are encountered due to the same reasons. This study aims to determine the optimum total fabric layer height based on the fabric type during the cutting process with a straight knife cutting machine, which provided a decrease in the cutting errors.

Frequently used fabric types in an enterprise operating in organic cotton knitwear were listed. During the cutting tests, the straight knife cutting machine was used as the cutting device. The weight and thickness values of the fabrics were obtained to provide a comparison basis. Two different algorithms were created to evaluate the defective pieces according to fabric type, cutting height and error placement. Cutting resistances of these fabrics were also determined to evaluate the defect reasons. In the end, optimum total fabric layer count and total cutting height suggestions were proposed for each fabric type for a minimum cutting error.

At the end of this study, the error-free layers were identified per fabric type. At the same time, the optimum cutting height was suggested for each fabric basis. For 40/1 single jersey fabrics, the cutting height should be between 2.10 cm and 10.40 cm; for 30/1 single jersey fabrics, between 1.65 cm and 5.70 cm; for 20/1 single jersey fabrics, between 1.83 cm and 6.70 cm; for two-thread fleece fabrics, between 2.13 cm and 4.70 cm; and for three-thread fleece fabrics, between 0 cm and 4.90 cm.

Within the scope of the study, since the products made of knitted fabric were produced more frequently and in large quantities, the study was carried out with 15 different types of knitted fabrics at 10 different layers. The same methods should be applied for woven, denim and nonwoven fabric types, which would shed light on the following studies.

Due to scarce research carried out on the cutting procedure of the clothing industry in regards to sustainability, this study aims to contribute to this area. The main difference between this study and the studies that mostly make mathematical predictions about the cutting procedure is that it is practice-oriented.

The circular economy (CE) represents an industry-wide transition from linear to circular processes. There has been a proliferation of literature on CE in the last decade. However, the existing studies on the adaption of CE in small and medium-sized enterprises (SMEs) are scarce. This study aims to develop a research agenda and the way forward for future researchers focusing on the adoption of CE.

This article analyses the CE concepts through a Systematic Literature Review (SLR). Coding and content analysis are performed to generate emergent themes with the help of “Atlas.ti” software.

The authors uncovered the contemporary significance of adopting CE and the state-of-the-art literature on CE. The study's findings fall into four broad themes: Technical know-how, resource and process optimization, reverse practices and technology and innovation. Ten thought-provoking questions were identified in the four themes that researchers can explore further in embracing CE to achieve sustainability in SMEs.

The study has highlighted the importance of CE adoption and CE's benefits to stakeholders across all three dimensions, i.e. social, economic and ecological. Practitioners can use the agenda in four themes to strengthen the practitioners' existing practices in SMEs to promote CE.

The study's uniqueness is the supply of current knowledge from diverse literature and practical consequences for SMEs. This study opens new lines of inquiry to adopt CE in SMEs, streamlining the existing literature into four themes to focus future research.

This paper aims to uncover the key enablers of an agile supply chain in the manufacturing sector amidst disruptions such as pandemics, trade wars and cross-border challenges. The study aims to assess the applicability of existing literature to manufacturing and identify additional industry-specific enablers contributing to the field of supply chain management.

The research methodology is comprehensively described, detailing the utilization of extent literature and semistructured interviews with mid- and top-level executives in a supply chain. The authors ensure the robustness of the data collection process and results interpretation.

The study identifies six essential dimensions of an agile supply chain: information availability, design robustness, external resource planning, quickness and speed, public policy influencing skills and cash flow management. The study provides valuable insights for industry professionals to develop agile supply chains capable of responding to disruptions in a rapidly changing world.

This study is limited by its focus on the manufacturing sector, and future research may explore the applicability of these findings to other industries. By focusing on these essential dimensions identified in the study, managers can develop strategies to improve the agility and responsiveness of their supply chains. In addition, further research may investigate how these enablers may vary in different regions or contexts.

The COVID-19 pandemic has forced executives to reconsider their sourcing strategies and reduce dependence on suppliers from specific geographies. To ensure business continuity, companies should assess the risk associated with their suppliers and develop a business continuity plan that includes multisourcing their strategic materials. Digital transformation will revolutionize the supply chain industry, allowing for end-to-end visibility, real time insights and seamless integration of business and processes. Companies should also focus on creating a collaborative workforce ecosystem that prioritizes worker health and well-being. Maintaining trust with stakeholders is crucial, and firms must revisit their relationship management strategies. Finally, to maintain business leadership and competitiveness during volatile periods, the product portfolio needs to be diversified and marketing and sales teams must work in tandem with product teams to position new products accordingly.

This work contributes substantially to the literature on supply chain agility (SCA) by adding several new factors. The findings result in a more efficient and cost-effective supply chain during a stable situation and high service levels in a volatile situation. A less complex methodology for understanding SCA provides factors with a more straightforward method for identifying well-springs of related drivers. First, the study contributes to reestablish the factors such as quickness, responsiveness, competency, flexibility, proactiveness, collaboration and partnership, customer focus, velocity and speed, visibility, robustness, cost-effectiveness, alertness accessibility to information and decisiveness as applicable factors for SCA. Second, the study suggests a few more factors, such as liquidity management, Vendors’ economic assessment and economic diversity, that are the study’s unique contributions in extending the enablers of SCA. Finally, public policy influencing skills, local administration connects and maintaining capable vendors are the areas that were never considered essential for SCA. These factors have emerged as a vital operational factor during the lockdown, and academicians may consider these factors in the future to assess their applicability.

This study provides new insights for decision-makers looking to enhance the resilience and agility of their supply chains. The identification of unique enablers specific to the manufacturing industry contributes to the existing body of literature on agile supply chains in the face of disruptions.

Although the significance of technological progress in economic development is well-established in theory and policy, it has remained challenging to agree upon shared priorities for strategies and policies. This paper aims to develop a model of how policymakers can develop effective and easy to communicate strategies for science, technology and economic development.

By integrating insights from economic complexity, competitiveness and foresight literature, a replicable research framework for analysing the opportunities and challenges of technological revolutions for small catching-up countries is developed. The authors highlight key lessons from piloting this framework for informing the strategy and policies for bioeconomy in Estonia towards 2030–2050.

The integration of economic complexity research with traditional foresight methods establishes a solid analytical basis for a data-driven analysis of the opportunities for industrial upgrading. The increase in the importance of regional alliances in the global economy calls for further advancement of the analytical toolbox. Integration of complexity, global value chains and export potential assessment approaches offers valuable direction for further research, as it enables discussion of the opportunities of moving towards more knowledge-intensive economic activities along with the opportunities for winning international market share.

The research merges insights from the economic complexity, competitiveness and foresight literature in a novel way and illustrates the applicability and priority-setting in a real-life setting.