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The metaverse is a virtual world where users can communicate with each other in a computer-generated environment. The use of metaverse technology has the potential to revolutionize the way businesses operate, interact with customers, and collaborate with employees. However, several obstacles must be addressed and overcome to ensure the successful implementation of metaverse technology. This study aims to examine the implementation of metaverse technology in the management of an organization's supply chain, with a focus on predicting potential barriers to provide suitable strategies.

Covariance-based structural equation modeling (CB-SEM) was used to test the model. In addition, artificial neural network modeling (ANN) was also performed.

The CB-SEM results revealed that a firm's technological limitations are among the most significant barriers to implementing metaverse technology in the supply chain management (SCM). The ANN results further highlighted that the firm's technological limitations are the most crucial input factors, followed by a lack of governance and standardization, integration challenges, poor diffusion through the network, traditional organizational culture, lack of stakeholder commitment, lack of collaboration and low perception of value by customers.

Because metaverse technology has the potential to provide organizations with a competitive advantage, increase productivity, improve customer experience and stimulate creativity, it is crucial to discuss and develop solutions to implementation challenges in the business world. Companies can position themselves for success in this fascinating and quickly changing technological landscape by conquering these challenges.

This study provides insights to metaverse technology developers and supply chain practitioners for successful implementation in SCM, as well as theoretical contributions for supply chain managers aiming to implement such environments.

The study aims to assess the impact of disruptive frugal digital technology and small and medium-sized enterprises' (SMEs') innovation performance on the food sector in Masvingo urban, Zimbabwe. A descriptive research design was used, and quantitative data were obtained using a questionnaire survey on 50 restaurant employees and 100 customers. The empirical findings demonstrated that the performance of SMEs was significantly improved by social media, cloud computing, virtual reality (VR), augmented reality (AR), and robotics. The study concludes that disruptive digital technologies (social media, cloud computing, AR, VR and robots affect the performance of SMEs by improving food production, streamlining information transfer, and utilizing cutting-edge technical applications. This chapter recommends that the government, through those in charge of formulating policy, educate and encourage the adoption of disruptive digital technology. The application of social media, cloud computing, VR, AR, and robotics will increase local food producers' access to the market. Digitalization will have a significant effect on Zimbabwe's local food system in the future.

The purpose of this study is to develop a systematic approach by demonstrating the Design for Six Sigma (DFSS) approach for reliability improvement of moulded case circuit breaker (MCCB) (current rating 250A).

In this study, the Define, Measure, Analyze, Design and Verify (DMADV) methodology of DFSS has been used to improve the reliability of MCCB. Mechanical endurance test (MET), project risk management, customer-based product development (PD), and other tools and techniques are used appropriately in DMADV methodology for improving the reliability of MCCB.

It has been observed that the reliability of MCCB has been improved from 61.76% to 98.17% for 20,000 operating cycles by implementing suggested improvement measures and the Weibull distribution is the most suitable distribution for reliability analysis of collected data.

This study considered only the aspects of DMADV methodology of the DFSS approach and does not cover other PD approaches such as lean and green PD.

This study clearly shows an enhancement in the reliability of MCCB which further leads to an increase in the warranty period. This will attract more customers and enhance business.

The improvement in the reliability of MCCB would significantly reduce fatal accidents ensuring workplace safety in the industry.

The originality of this study is the reliability assessment using degradation analysis in the design phase of the DMADV process to predict failure during design verification.

The purpose of this study is to investigate the impact of titanium oxide (TiO₂) filler on the abrasive wear properties of bamboo fiber reinforced epoxy composites (BFRCs) using a Taguchi approach. The study aims to enhance the abrasive wear resistance of these composites by introducing TiO₂ filler as a potential reinforcement, thus contributing to the development of sustainable and environmentally friendly materials.

This study focuses on the fabrication of epoxy/bamboo composites infused with TiO₂ particles within the Wt.% range of 0–8 Wt.% using hand layup techniques. The resulting composites were subjected to wear testing according to ASTM G99-05 standards. Statistical analysis of the wear results was carried out using the Taguchi design of experiments (DOE). Additionally, an analysis of variance (ANOVA) was used to determine the influential control factors impacting the specific wear rate (SWR) and coefficient of friction (COF).

The study illuminates how integrating TiO₂ filler enhances abrasive wear in epoxy/bamboo composites. Statistical analysis of SWR highlights abrasive grit size (grit) as the most influential factor, followed by normal load, Wt.% of TiO₂ and sliding distance. Analysis of the COF identifies normal load as the primary influential factor, followed by grit, Wt.% of TiO₂ and sliding distance. The Taguchi predictive model closely aligns with experimental results, validating its reliability. The morphological study revealed significant differences between the unfilled and TiO₂-filled composites. The inclusion of TiO₂ improved wear resistance, as evidenced by reduced surface damage and wear debris.

This research paper aims to integrate TiO₂ filler and bamboo fibers to create an innovative hybrid composite material. TiO₂ micro and nanoparticles show promise as filler materials, contributing to improved tribological properties of epoxy composites. The utilization of Taguchi’s DOE and ANOVA for statistical analysis provides valuable guidance for academic researchers and practitioners in optimizing control variables, especially in the context of natural fiber reinforced composites.