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The purpose of this study is to examine the variables affecting college students’ consumption behaviour in the context of the internet celebrity economy and the We Media environment.

In this study, five independent variables − perceived ease of use, perceived usefulness, attitude, We Media environment and internet celebrity marketing, as well as one mediating variable, consumption intention, are used to analyse college students’ consumption behaviour.

This study concluded that all five independent variables have positive relationships with the consumption intention and that the consumption intention also has a positive relationship with the consumption behaviour.

This study expanded the technology acceptance model and theory of planned behaviour model, which could provide insights for future research on consumption intention and behaviour. In addition, this study gives guidance for businesses considering to join this new industry in the internet celebrity economy.

The purpose of this study is to empirically analyse the fiscal revenue implications for oil-dependent African countries in the face of low-carbon energy transition (LET).

The study combined the novel fully modified ordinary least squares, dynamic ordinary least squares and canonical cointegrating regressions estimators to analyse secondary data between 1990 and 2020 for the three major oil-dependent African Countries (Algeria, Angola and Nigeria).

The result shows that LET reduces oil revenue and non-revenue for specific countries (Algeria, Angola and Nigeria) and the panel, suggesting that low-carbon energy transiting is lowering the fiscal revenue of oil-dependent African nations.

The seeming weakness of this study is its inability to broaden the scope to include all oil-producing African economies. However, since the study selected Africa’s top three oil-producing states, the sample can serve as a model for others with lesser crude oil outputs.

Oil-dependent African countries must urgently engage in sincere economic diversification in sectors like industry and manufacturing, the service sector and human capital development to promote economic transformation that will enhance fiscal revenue.

With the pace of energy transition towards low-carbon energy, it is not business as usual for oil-rich African countries (Algeria, Angola and Nigeria) due to fluctuating demand and price. As a result, it becomes worthy to examine how the transition is affecting oil-dependent economies in Africa. Also, this study’s method is unique as it has not been used in a similar study for Africa.

This study aims to investigate the optimal process parameters of the wire-cut electrical discharge machining (WCEDM) for the machining of the GZR-AA7475 hybrid metal matrix composite (HMMC). HMMCs are prepared with 2 Wt.% graphite and 4 Wt.% zirconium dioxide reinforced with aluminium alloy 7475 (GZR-AA7475) composite by using the stir casting method. The objective is to enhance the mechanical properties of the material while preserving its unique features. WCEDM with a 0.18 mm molybdenum wire electrode is used for machining the composite.

To conduct experimental studies, a Taguchi L27 orthogonal array was adopted. Input variables such as peak current (I_p), pulse-on-time (T_ON) and flushing pressure (P_F) were used. The effect of process parameters on the output responses, such as material removal rate (MRR), surface roughness rate (SRR) and wire wear ratio (WWR), were investigated. The grey relational analysis (GRA) is used to obtain the optimal combination of the process parameters. Analysis of variance (ANOVA) was also used to identify the significant process parameters affecting the output responses.

Results from the current study concluded that the optimal condition for grey relational grade is obtained at T_ON = 105 µs, I_p = 100 A and P_F = 90 kg/cm². Peak current is the most prominent parameter influencing the MRR, whereas SRR and WRR are highly influenced by flushing pressure.

Identifying the optimal process parameters in WCEDM for machining of GZR-AA7475 HMMC. ANOVA and GRA are used to obtain the optimal combination of the process parameters.

It is now well-established that good water quality is associated with economic prosperity, reduced incidence on public health and the good functioning of the various ecosystems found in our environment. Water contamination is mostly related to both diffused (agricultural lands and geologic rock degradations) and point sources of pollution. Mauritius has many water resources which depend solely on precipitation for their replenishment. Water parameters which are of relevance include total dissolved solids (TDS), temperature, pH, electrical conductivity, turbidity, dissolved oxygen, dissolved and particulate organic carbon and major cations and anions. The traditional methods of analysis for these parameters are mostly using electrical and optical methods (probes and sensors in the field), while chemical titrations, Flame AAS and High-Performance Liquid Chromatography techniques are carried out in the laboratory. Image Classification techniques using neural networks can also be used to detect the presence of contaminants in water. In addition to basic water quality parameters, the field sensors range have been extended to cover important major ions and can now be integrated with Artificial Intelligence (AI)-based models for the prediction of variations in water quality to better protect human health and the environment, reduce operation costs of water and wastewater treatment plant unit processes.

The purpose of this paper is to study Al-based green composite. To make composite samples of aluminium alloy (AA3105) with different weight percentages of rice husk ash (RHA) and eggshell (ES) particles as reinforcement, stir casting method was used.

Several other aspects, including the weight percent of reinforcing agent particles, the applied stress and the sliding speed, were taken into consideration. During the course of the wear test, the sliding distance that was recorded varied from a minimum of 1,000 m all the way up to a maximum of 3,135 m (10, 15, 20, 25 and 30 min). The typical range for normal loads is 8–24 N, and their speed is 1.58 m/s.

With the AA/ES/RHA composite, the wear rates decreases when the grain size of the reinforcing particles enhanced. Scanning electron microscopy images of worn surfaces show that at low speeds, delaminating and ploughing are the main causes of wear. At high speeds, ploughing is major cause of wear. Composites with better wear-resistant properties can be used in wide range of tribological applications, especially in the automotive industry. It was found that hardness increases at the same time as the weight of the reinforcement increases. Tensile and hardness were maximized at 10% reinforcement mix in Al3105.

In this work, ES and RHA has been used to develop green metal matrix composite to support green revolution as promoted/suggested by United Nations thus reducing the environmental pollution.

Ever since its emergence, the metaverse has presented opportunities and disruptions to every stakeholder, including individual users and organizations. This article aims to offer valuable perspectives on six identified critical areas that the metaverse could significantly impact: marketing ethics, marketing communication, relationship marketing, retail marketing, supply chain management and transportation management.

Through a multi-perspective approach, this paper gathers valuable perspectives from various invited contributors to each of the six identified key areas that the metaverse could significantly impact.

For each key area identified, the invited contributors first share their valuable perspectives by discussing the roles of the metaverse. Subsequently, the invited contributors discuss their views on vital opportunities, challenges and research agenda concerning the metaverse.

With the widespread metaverse, it is expected that each key area identified is likely to undergo significant levels of disruption. Against this backdrop, this paper contributes to the academic literature and industry by gathering different perspectives from invited contributors on the relevance of the metaverse in marketing and logistics domains.