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This study aims to propose guidelines for developing circular products based on waste recovery that are aligned with sustainable production and consumption.

A systematic literature review and case studies on circular product development were conducted. In total, 15 companies with products based on waste recovery and aligned with sustainable production and consumption goal were studied.

The results show the decisions and strategies applied at each stage of the new product development process, including the design for recycling, the use of waste as a raw material for products and the concern for reducing pollution and recovering end-of-life products.

The cases studied meet the goals of efficient use of natural resources and waste reduction by preventing, reducing, recycling and reusing waste. For practitioners, a set of guidelines is proposed to help companies develop circular products based on waste recovery.

Previous studies have not evaluated the new product development process and circularity from the institutional theory and waste valorization perspectives.

The purpose of the study is to analytically as well as numerically investigate the weight of throughflow on the onset of Casson nanofluid layer in a permeable matrix. This study examines both the marginal and over stable kind of convective movement in the system.

A double-phase model is used for Casson nanofluid, which integrates the impacts of thermophoresis and Brownian wave, whereas for flow in the porous matrix the altered Darcy model is occupied under the statement that nanoparticle flux is disappear on the boundaries. The resultant eigenvalue problem is resolved analytically as well as numerically with the help of Galerkin process with the Casson nanofluid Rayleigh–Darcy number as the eigenvalue.

The findings revealed that the throughflow factor postpones the arrival of convective flow and reduces the extent of convective cells, whereas the Casson factor, the Casson nanoparticle Rayleigh–Darcy number and the reformed diffusivity ratio promote convective motion and also decrease the extent of convective cells.

Controlling the convective movement in heat transfer systems that generate high heat flux is a real mechanical challenge. The proposed framework proved that the use of throughflow is one of the most important ways to control the convective movement in Casson nanofluid. To the best of the authors’ knowledge, no inspection has been established in the literature that studies the outcome of throughflow on the Casson nanofluid convective flow in a porous medium layer. However, the convective flow of Casson nanofluid finds many applications in improving heat transmission and energy efficiency in a range of thermal systems, such as the cooling of heat-generating elements in electronic devices, heat exchangers, pharmaceutical practices and hybrid-powered engines, where throughflow can play a significant role in controlling the convective motion.

This study aims to address a systematic literature review (SLR) using bibliometrics on the relationship between academic integrity and artificial intelligence (AI), to bridge the scattering of literature on this topic, given the challenge and opportunity for the educational and academic community.

This review highlights the enormous social influence of COVID-19 by mapping the extensive yet distinct and fragmented literature in AI and academic integrity fields. Based on 163 publications from the Web of Science, this paper offers a framework summarising the balance between AI and academic integrity.

With the rapid advancement of technology, AI tools have exponentially developed that threaten to destroy students' academic integrity in higher education. Despite this significant interest, there is a dearth of academic literature on how AI can help in academic integrity. Therefore, this paper distinguishes two significant thematical patterns: academic integrity and negative predictors of academic integrity.

This study also presents several contributions by showing that tools associated with AI can act as detectors of students who plagiarise. That is, they can be useful in identifying students with fraudulent behaviour. Therefore, it will require a combined effort of public, private academic and educational institutions and the society with affordable policies.

This study proposes a new, innovative framework summarising the balance between AI and academic integrity.

This study aims to focus on model development to analyse key factors affecting trust in virtual project teams (VPTs).

A questionnaire survey was conducted on construction professionals participating in virtual teams. Structural equation modelling technique was performed to establish the effect of relevant factors on trust-building in VPTs.

Team performance is highly affected by the trust among the team members. Trust building can be enhanced by improving the quality of team communication, organisation culture, team bonding and team members’ characteristics.

The model developed in this study would benefit team productivity and team members’ learning in VPTs.

The adoption of e-taxing plays an important role in modernizing tax administration. Ghana, like many other developing countries, has adopted e-taxing to modernize its revenue collection processes and improve its tax-to-GDP ratio. This study aims to examine the current state of e-taxing maturity in Ghana, focusing on the advancements made and what can be done to achieve a mature e-taxing system.

Through qualitative design, interviews were conducted with Ghana Revenue Authority, National Information Technology Agency and Businesses to provide an in-depth understanding of the strengths, weaknesses and opportunities for improving e-taxing maturity.

The study reveals mixed e-taxing maturity. While the digital service aspect of e-taxing has seen progress, digital infrastructure, digital analytics, digital integration and digital culture hinder the full actualization of mature e-taxing.

The findings suggest the need for a comprehensive plan that addresses regulatory, cultural, technical and organizational aspects to drive digital transformation in e-taxing tax implementation.

The lack of resilient infrastructure, especially in rural areas, can worsen societal inequalities. Owing to the lack of telecommunication infrastructure and poor internet connectivity in rural areas, businesses in these areas may lack the needed information for business growth and expansion. This can result in unfair treatment of rural businesses widening the inequality gap between businesses in urban areas and rural areas. Therefore, the study is important from the standpoint that implementing the recommendations will help to bridge the gap between businesses in urban areas and rural areas.

To the best of the author’s knowledge, this study is among the first to conduct an empirical study on e-taxing maturity in Ghana.

The purposes of this study are to identify the ways that luxury fashion brands can leverage in metaverse retailing, and give insights to practitioners in the fashion industry who are planning to launch metaverse retailing.

To offer a balanced view of available evidence, this study adopted a literature review approach and attempted to collect all existing academic journal articles on the issues related to metaverse retailing and luxury fashion brands. A comprehensive literature search was conducted in electronic databases Google Scholar, Web of Science, Scopus, Pro Quest and Science Direct from January 2023 to April 2024. Based on the results of the research in literature, real-life examples of luxury fashion brands were used to explain the ways that luxury fashion brands in the metaverse retailing can be put into practice.

The findings have revealed that there are many ways that luxury fashion brands can leverage in the metaverse retailing. The fusion of metaverse-related technologies provides brands with a wide platform of choices that can create immersive, personalized marketing experiences for customers. Four roles of metaverse are identified: (1) enhance of immersive experience; (2) provide big data interface to smart decision-making; (3) form high-fidelity simulated space; and (4) maintenance economic system and making of identification. To further enhance the four roles of metaverse, four types of technologies and 15 components for metaverse can be adopted by luxury fashion brands.

While this paper provides a literature review and real-life examples of luxury fashion brands in the metaverse retailing to explain the findings, further research is needed to evaluate the effectiveness of current efforts in the development of luxury fashion brands in the metaverse retailing through collecting both quantitative and qualitative data. Also, future studies may attempt to explore the challenges of investigating consumers in response to luxury fashion brands in the metaverse retailing.

The metaverse is turning imagination into reality through the integration of multiple technologies and is gaining momentum in tech. With technology leading the way, business leaders and brands must not only rethink retail but also bring immersive shopping experiences into the future. Metaverse has immense potential to transform the retail industry, thus the leading global and local firms must embrace innovation and new technologies, and prioritize “metaverse transformation” for their business. Based on the results of this study, some emerging practices pertaining to metaverse retailing are provided.

To the best of the authors’ knowledge, it would seem that this is the first work that conducts a literature review of the relevant academic journal articles addressed to the practitioners or managerial audiences in the area of luxury fashion industry who are concerned about the development of metaverse retailing. This paper identifies the ways that luxury fashion brands can leverage in the metaverse retailing and gives insights to practitioners in the luxury fashion industry who are planning to launch metaverse retailing.

Major public cloud providers, such as AWS, Azure or Google, offer seamless experiences for infrastructure as a service (IaaS), platform as a service (PaaS) and software as a service (SaaS). With the emergence of the public cloud's vast usage, administrators must be able to have a reliable method to provide the seamless experience that a public cloud offers on a smaller scale, such as a private cloud. When a smaller deployment or a private cloud is needed, OpenStack can meet the goals without increasing cost or sacrificing data control.

To demonstrate these enablement goals of resiliency and elasticity in IaaS and PaaS, the authors design a private distributed system cloud platform using OpenStack and its core services of Nova, Swift, Cinder, Neutron, Keystone, Horizon and Glance on a five-node deployment.

Through the demonstration of dynamically adding an IaaS node, pushing the deployment to its physical and logical limits, and eventually crashing the deployment, this paper shows how the PackStack utility facilitates the provisioning of an elastic and resilient OpenStack-based IaaS platform that can be used in production if the deployment is kept within designated boundaries.

The authors adopt the multinode-capable PackStack utility in favor of an all-in-one OpenStack build for a true demonstration of resiliency, elasticity and scalability in a small-scale IaaS. An all-in-one deployment is generally used for proof-of-concept deployments and is not easily scaled in production across multiple nodes. The authors demonstrate that combining PackStack with the multi-node design is suitable for smaller-scale production IaaS and PaaS deployments.

This study aims to explore the interrelationships among human-related lean practices, lean production shop floors, process quality, inventory management, operational productivity and business productivity.

This study used a cross-sectional survey approach, and quantitative data were collected from 324 Indian auto-component manufacturing firms. Confirmatory factor analysis was used, followed by structural equation modelling techniques for the conceptual model, which incorporated a complete set of 11 hypotheses.

The results confirmed that human-related lean practices trigger lean production shop floors and improve process quality. Furthermore, the study revealed the positive impact of a lean production shop floor on process quality and inventory management and the positive impact of process quality on both operational and business productivity. Finally, inventory management is of the utmost importance in achieving better operational and business productivity, and operational productivity positively leads to business productivity.

The findings of this study can benefit auto-component manufacturing firms by elucidating the complex relationships between human-related lean practices, lean production shop floors, process quality, inventory management, operational productivity and business productivity. Better knowledge of these relationships will enable firms to enhance efficiency levels, reduce costs and resource wastage and improve their overall performance. This study provides a good understanding of the interplay between lean and quality factors and their influence on inventory management and business performance.

Performance optimization algorithms based on node attributes are of great importance for sharding blockchain systems. Currently, existing studies on blockchain sharding algorithms consider only random selection sharding strategies. However, the random selection strategy does not perfectly utilize the performance of a node to break the bottleneck of blockchain performance.

This paper proposes a blockchain sharding algorithm called TOPSIS Optimization Sharding System (TOSS), which is based on entropy weight method, relative Euclidean distance and the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS). It defines a multi-attribute matrix to assess node performance and applies TOPSIS for scoring nodes. Then, an algorithm based on the TOPSIS method is proposed to calculate the performance score of each data node. In addition, an entropy weighting method is introduced to obtain the weights of each attribute to balance the impact of dimensional differences of attributes on the attribute weights. Nodes are ranked by composite scores to guide partitioning.

The effectiveness of the proposed algorithm in this paper is verified by comparing it with various comparative algorithms. The experimental results show that the TOSS algorithm outperforms the comparison algorithms in terms of performance improvement for the blockchain system, and the throughput metrics are improved by about 20% in comparison.

This study introduces a novel approach to blockchain sharding by incorporating the entropy weight method and relative Euclidean distance TOPSIS into the sharding process. This approach allows for a more effective utilization of node performance attributes, leading to significant improvements in system throughput and overall performance, addressing the limitations of the random selection strategy commonly used in existing algorithms.

Over the last 2 decades, supply chain sustainability research has become a highly dynamic and fruitful study area. This field has garnered significant attention due to its potential to reshape decision-making processes within supply chains. At the same time, the practical side of supply chain operations remains intensely competitive in today’s business landscape. Furthermore, the current academic research aims to outline effective strategies for achieving sustainability across supply chains, particularly in the manufacturing sector. In response to these challenges, this research has conducted an integrated multi-criteria decision-making approach to evaluate sustainable supply chain performance from the triple bottom line perspective, including financial, environmental, and social performance.

The initial stage involves selecting the crucial criteria (short-term and long-term) and alternatives for sustainable supply chain performance (SSCP) from experts and conducting an in-depth literature review. Initially, there were 17 criteria, but after a pilot test with co-authors and online discussions with experts, the number of criteria was subsequently reduced to 9. In the second phase, the Best-Worst Method (BWM) was applied to rank and prioritize the criteria. The third and final stage examined the causal relationship between the identified criteria, utilizing the Decision-Making Trial and Evaluation Laboratory (DEMATEL) technique.

Based on BWM analysis results, the top three criteria in terms of prominence are: (1) return on investment (ROI), (2) product quality, and (3) manufacturing lead time. Out of the three alternatives, financial performance (FP) is the most crucial dimension for SSCP, followed by environmental performance (ENP) and social performance (SP). On the other hand, the DEMATEL approach showed that work health and safety (short-term criterion), asset utilization (long-term criterion), energy consumption (long-term criterion), waste disposal (long-term criterion), manufacturing lead time (short-term criterion), and on-time delivery (short-term criterion) are categorized within the cause group, while criteria such as return on investment (ROI) (long-term criterion), customer-service level (short-term criterion), and product quality (long-term criterion) fall into the effect group.

The proposed study has certain drawbacks that pave the way for future research directions. First, it is worth noting the need for a larger sample size to ensure the reliability of results, the potential inclusion of additional criteria to enhance the assessment of sustainability performance, and the consideration of a qualitative approach to gain deeper insights into the outcomes. In addition, fuzziness in qualitative subjective perception could be imperative when collecting data to ensure its reliability, as translating experts’ perceptions into exact numerical values can be challenging because human perceptions often carry elements of uncertainty or vagueness. Therefore, fuzzy integrated MCDM frameworks are better suited for future research to handle the uncertainties involved in human perceptions, making it a more appropriate approach for decision-making in scenarios where traditional MCDM methods may prove insufficient.

The proposed framework will enable decision-makers to gain deeper insights into how various decision criteria impact SSCP, thus providing a comprehensive evaluation of SSCP that considers multiple dimensions, such as financial, environmental, and social performance within the manufacturing sector.

The proposed study is the first empirical study to integrate both BWM and DEMATEL approaches to evaluate sustainable supply chain performance in the manufacturing context.