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In recent years, a number of privileged individuals have entered the music industry in Zimbabwe, either as performers or entrepreneurs. The economic challenges in the country may have prompted these individuals to invest in music as a means of diversifying their income or exploring new business opportunities. To determine whether their interest in music is driven by entrepreneurship or genuine passion, a scholarly examination was deemed necessary.

A qualitative research approach with semi-structured interviews was used as the data collection technique. Narrative analysis was conducted on a sample of musicology students in Gweru, Zimbabwe.

The findings revealed the nepo babies’ interest in music is driven by legacy continuation – the responsibility to carry on with the name of the parent – harsh economic conditions, capitalizing on Internet and digital opportunities and mechanisms for psychological satisfaction during hardships.

Although there is a wide range of literature on musicpreneurship, there are gaps in studies that have examined whether a nepo baby's interest in music is motivated by musicpreneurship or a genuine passion for it. Therefore, the aim of this research is to contribute to the existing body of literature on African musicpreneurship, with a specific focus on Zimbabwe.

As supply chain excellence matters, designing an appropriate health-care supply chain is a great consideration to the health-care providers worldwide. Therefore, the purpose of this paper is to benchmark several potential health-care supply chains to design an efficient and effective one in the presence of mixed data.

To achieve this objective, this research illustrates a hybrid algorithm based on data envelopment analysis (DEA) and goal programming (GP) for designing real-world health-care supply chains with mixed data. A DEA model along with a data aggregation is suggested to evaluate the performance of several potential configurations of the health-care supply chains. As part of the proposed approach, a GP model is conducted for dimensioning the supply chains under assessment by finding the level of the original variables (inputs and outputs) that characterize these supply chains.

This paper presents an algorithm for modeling health-care supply chains exclusively designed to handle crisp and interval data simultaneously.

The outcome of this study will assist the health-care decision-makers in comparing their supply chains against peers and dimensioning their resources to achieve a given level of productions.

A real application to design a real-life pharmaceutical supply chain for the public ministry of health in Morocco is given to support the usefulness of the proposed algorithm.

The novelty of this paper comes from the development of a hybrid approach based on DEA and GP to design an appropriate real-life health-care supply chain in the presence of mixed data. This approach definitely contributes to assist health-care decision-makers design an efficient and effective supply chain in today’s competitive word.

Upper bound on Sharpe ratio helps to evaluate the risk-adjusted performance in real market setting. The purpose of this study is to evaluate the performance of Shariah-compliant indices (SCIs) and also estimate the upper bound on Sharpe ratio in real-market setting. For comparison, the authors also report the same statistics for conventional indices (CIs).

This study considers returns of 12 indices from Asia-Pacific and the USA for the time period May 31, 2013-Aug 25, 2022. These indices are further classified as small-, mid- and large-cap indices. The upper bound is estimated in three settings, an unconstrained setting, correlation constraint and copula constraint.

The authors found that upper bound estimation is sensitive to both the choice of index, geographic location and size of constituents within the index. Interestingly, SCIs outperform CIs both in terms of Sharpe ratio and upper bound estimations. The ability of SCIs to achieve high Sharpe ratio boosts investors’ confidence. The results are robust even after introducing correlation and copula constraints to the model.

Any violation of the upper bound on Sharpe ratio is not necessarily an indication of fraud or dubious Sharpe ratio. It should be interpreted only as a signal for inflated risk-adjusted performance and requires further investigation. Together with risk-adjusted performance, fund managers should report upper bounds to insure investor protection.

Many studies have compared the risk-adjusted performance of SCIs and CI. To the best of the authors’ knowledge, this study is the first effort to evaluate and compare the upper bounds on Sharpe ratio of SCIs in a real-market setting.

Climate change, driven by global warming, poses a significant threat to humanity and disrupts the ecological balance. In Europe, concentrations of air pollutants remain very high, and problems related to air quality and the acceleration of the phenomenon of global warming persist. As a result, carbon taxation has emerged as a key strategy to mitigate climate change. In Romania, environmental taxes are an important instrument of environmental policy as an economic instrument for environmental protection and natural resource management. Using 1990–2021 time series data and an Autoregressive Distributed Lag (ARDL) Bounds cointegration for long-run analysis and the Toda–Yamamoto test for causality analysis, we investigated whether environmental taxes, renewable energy consumption, urbanization and economic growth significantly impact CO₂ emissions in Romania.

This paper differs from the assessment of the Environmental Kuznets Curve (EKC) hypothesis (Grossman and Krueger 1991) and instead aims to determine the impact of environmental taxes, renewable energy consumption, per capita GDP and urbanization on CO₂ emissions in Romania. The study investigates both short- and long-term effects, as well as Toda–Yamamoto causality linkages (Toda and Yamamoto 1995) between these variables. We adopt an ARDL estimation technique with Bound cointegration test and error correction models (Pesaran et al., 2001) to examine the short- and long-term effects.

The findings revealed that environmental taxes positively and significantly reduce CO₂ emissions, while urbanization induces CO₂ emissions, in the long run. Moreover, in the short run, environmental taxes and renewable energy consumption significantly reduce CO₂ emissions while per capita GDP and urbanization significantly increase CO₂ emissions. A unidirectional causality exists between renewable energy consumption and CO₂ emissions. Thus, to realize its 34% target of renewable energy consumption in 2030, Romania should prioritize the implementation of the Casa Verde Plus program and enforce sustainable urban planning to meet near-zero energy standards. Consequently, the government should continue to enforce carbon taxes to promote environmental sustainability.

Empirical evidence supports the cointegration relationship between environmental taxes and CO₂ emissions, with carbon taxes effectively reducing CO₂ emissions and improving environmental quality (Allan et al., 2014; Polat and Polat, 2018; Kiuila et al., 2019, etc.). While existing research (Floros and Vlachou, 2005; Wissema and Dellink, 2007; Aydin and Esen, 2018; Lin and Li, 2011) primarily focuses on country-specific or regional analyses, limited research has been conducted on the impact of carbon taxation on CO₂ emissions in Romania. However, to the best of our knowledge, limited research on this phenomenon in Romania exists in response to recommendations for climate change mitigation. Furthermore, urbanization has significantly contributed to rising atmospheric carbon levels and subsequent global warming and climate change (Woldu, 2021). As economic growth, particularly in countries like Romania, drives urbanization, it leads to increased energy demand, expanding urban areas and mounting environmental concerns. This process involves industrial restructuring, and the development of new infrastructure, all of which exert pressure on energy consumption and CO₂ emissions (Niu and Lekse, 2018). While economic growth is a primary objective, industrialization and urbanization inevitably generate unintended consequences, including CO₂ emissions. However, limited research exists on the impact of urbanization patterns on CO₂ emissions in Romania. This study investigates the dynamic causal relationships among urbanization, per capita GDP, carbon taxes, renewable energy consumption and CO₂ emissions, considering both short-run and long-run effects in Romania.

This paper aims to study boundary and interior layer phenomena in coupled multiscale parabolic convection–diffusion interface problems and to present their efficient numerical resolution and analysis.

This study includes cases in which the diffusion parameters are small, distinct and can differ in order of magnitude. The source term is considered to be discontinuous. The asymptotic behavior of the solution is examined. The layer structure is analyzed, leading to the development of a variant of layer-resolving Shishkin mesh. For efficient numerical resolution, two methods are developed by combining additive schemes on a uniform mesh to discretize in time and an upwind difference scheme away from the line of discontinuity and a specific upwind difference scheme along the line of discontinuity, defined on a variant of layer resolving Shishkin mesh, to discretize in space. The analysis of the numerical resolution is discussed using the barrier function approach. Numerical simulations provide a verification of the theory and efficiency of the approach.

The discontinuity in the source term, along with the inclusion of small and distinct diffusion parameters, results in multiple overlapping and interacting boundary and interior layers. The work demonstrates that the present approach is robust in resolving boundary and interior layers. From a computational cost perspective, the numerical resolution presented in the paper is more efficient than conventional approaches.

Efficient numerical resolution and analysis of boundary and interior layer phenomena in coupled multiscale parabolic convection–diffusion interface problems are provided. The discretization of the coupled system in the approach incorporates a distinctive feature, wherein the components of the approximate solution are decoupled at each time level, resulting in tridiagonal linear systems to be solved, in contrast to large banded linear systems with conventional approaches.

This paper investigates the relationship between foreign direct investment (FDI) and poverty in Uganda.

Using annual time series data from 1983 to 2021, we use the autoregressive distributed lag bounds testing method to cointegration for test the above relationship. Considering the multidimensionality of poverty, we proxy poverty by three proxies: household consumption expenditure, infant mortality rate and life expectancy.

The findings reveal that FDI is important for poverty reduction in both the long- and short-run when using household consumption and infant mortality rate, holding other factors constant. This relationship is robust to alternative specifications and estimation methods. This paper establishes that FDI does matter for poverty reduction in both the short and long run. However, when life expectancy is used to proxy poverty, results show a positive relationship between FDI and poverty.

The long-run relationship between FDI and poverty largely suggests that tackling poverty may require reforming the economic environment by addressing bottlenecks that hinder economic growth, which is a key component in poverty reduction. Thus, it is important to ensure that government expenditure is directed to the productive sectors of the economy, such as education and infrastructure, among others that are paramount in expanding the productive capacity of the economy, which in turn is crucial for poverty reduction.

In this article, we present the numerical solution of fractional Sturm-Liouville problems by using generalized shifted Chebyshev polynomials.

We combine right Caputo and left Riemann–Liouville fractional differential operators for the construction of fractional Sturm–Liouville operators. The proposed algorithm is developed using operational integration matrices of generalized shifted Chebyshev polynomials. We introduce a new bound on the coefficients of the shifted. Chebyshev polynomials subsequently employed to establish an upper bound for error in the approximation of a function by shifted Chebyshev polynomials.

We have solved fractional initial value problems, terminal value problems and Sturm–Liouville problems by plotting graphs and comparing the results. We have presented the comparison of approximated solutions with existing results and exact numerical solutions. The presented numerical problems with satisfactory results show the applicability of the proposed method to produce an approximate solution with accuracy.

The presented method has been applied to a specific class of fractional differential equations, which involve fractional derivatives of a function with respect to some other function. Keeping this in mind, we have modified the classical Chebyshev polynomials so that they involve the same function with respect to which fractional differentiation is performed. This modification is of great help to analyze the newly introduced polynomials from analytical and numerical point of view. We have compared our numerical results with some other numerical methods in the literature and obtained better results.

The purpose of this study is to develop a novel approach that addresses time-cost tradeoffs in repetitive construction projects while considering the uncertainty in activity durations and the risk preferences of planners.

Our study involves work in three aspects. Firstly, it employs triangular fuzzy numbers to represent activity durations in different units, which facilitates the management of scenarios characterized by limited historical data or the presence of ambiguous information. Secondly, it introduces a fuzzy chance-constrained programming model, which is aimed at minimizing the project budget while ensuring that the risks associated with cost overruns and schedule delays are confined to specified limits. Thirdly, it advances an enhanced genetic algorithm, integrating an electromagnetism-like mechanism and a scheduling repair process, to improve the efficiency and effectiveness of the optimization process.

A real-life street renovation project was analyzed to demonstrate the applicability of the proposed algorithm. The analysis explored three common types of risk preferences: risk-averse, risk-neutral and risk-loving. The results indicate that the proposed algorithm surpasses existing fuzzy repetitive scheduling methods in terms of risk management. It effectively generates schedules that align with the risk preferences of planners and provides worst-case estimates of project performance.

This research makes a significant contribution to the field by developing a fuzzy chance-constrained programming model and an associated optimization algorithm that is specifically designed for time-cost tradeoffs in repetitive construction projects. A key distinction is that this study considers the risk preferences of planners, which sets it apart from previously developed models. As a result, it provides a practical approach for effective risk management.

This paper aims to investigate the problem of adaptive bipartite tracking control in nonlinear networked multi-agent systems (MASs) under the influence of periodic disturbances. It considers both cooperative and competitive relationships among agents within the MASs.

In response to the inherent limitations of practical systems regarding transmission resources, this paper introduces a novel approach. It addresses both control signal transmission and triggering conditions, presenting a two-bit-triggered control method aimed at conserving system transmission resources. Additionally, a command filter is incorporated to address the problem of complexity explosion. Furthermore, to model the uncertain nonlinear dynamics affected by time-varying periodic disturbances, this paper combines Fourier series expansion and radial basis function neural networks. Finally, the effectiveness of the proposed methodology is demonstrated through simulation results.

Based on neural networks and command filter control method, an adaptive two-bit-triggered bipartite control strategy for nonlinear networked MASs is proposed.

The proposed control strategy effectively addresses the challenges of limited transmission resources, nonlinear dynamics and periodic disturbances in networked MASs. It guarantees the boundedness of all signals within the closed-loop system while also ensuring effective bipartite tracking performance.

This paper examines the extent to which exchange rate volatility (ERV) is crucial for small island economies. These economies by their very nature and size tend to be net importers and highly dependent on trade for their economic survival. The island of Mauritius is used as a case study.

A GARCH model has been utilized using yearly data for the period 1993–2022. The ARDL bounds cointegration approach has been used to determine the long run relationship between exchange rate volatility and the performance of exports. The ECM-ARDL model has been used to estimate the short-run relationships, that is the speed of adjustments between the variables under consideration.

The findings reveal that exchange rate volatility has a positive and significant effect on exports in the short run as well as in the long run. The study also finds out that export has a long-term relationship with world GDP per capita. Both the presence and degree of exchange rate volatility are important aspects for consideration in policy making.

The literature gap that this study attempts to close is one related to global impacts within the recent time horizon. Recently, numerous important events shaped the financial and economic landscape globally, including but not limited to the financial crisis of 2008 and the COVID-19 pandemic in 2019. Both these events stressed the global volume of trade and the exchange rate markets, and these events affects small islands comparatively more given their heavy dependence on international trade for economic development, albeit economic survival.