VGTU Journals (Vilnius Gediminas Technical University - Vilnius Tech)
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Technology innovation and carbon efficiency in Africa: what is the role of digitalization and digital inclusive finance?
No full textImproving carbon efficiency and mitigating carbon emissions is fundamental to sustainable development and the well-being of human society. Yet, no study highlighted and identified the drivers of carbon efficiency in Africa. Specifically, an empirical study on the role of technological innovation (GTI), digitalization, and digital inclusive finance (DIF) in improving carbon efficiency (CEE) in Africa is rare. To fill this gap, this study investigates the synergistic impact of green technological innovation (GTI), digitalization, and digital inclusive finance (DIF) on improving carbon efficiency (CEE) from the African perspective. A meta-frontier slack-based environmental polluting technology and mixed integervalued data envelopment analysis (DEA) is framed to gauge the carbon efficiency across oil-endowment and non-oil-endowment African countries from 2010 to 2019. The results indicate that only a few African countries appeared to be operating at efficient production levels. The bootstrapped regression results indicated an invented U-shaped nexus is established between carbon efficiency and African economic development via the extended stochastic impacts by regression on population, affluence, and technology (STIRPAT) framework. Internet usage and mobile cellular subscriptions as components of digitalization positively improve Africa’s carbon efficiency. Mobile money transaction innovation (i.e., active mobile money agents per 1000 km2) as a dimension of digital inclusive finance conserves Africa’s environmental efficiency. Green technological innovations did not drive carbon efficiency significantly in Africa and the two groups. Based on the empirical findings, pragmatic policy strategies are further discussed to boost carbon efficiency and mitigate environmental degradation in Africa
Evaluating the performance of Moroccan social incubators: an SFA analysis of youth platforms under the national initiative for human development
No full textPurpose – This study focuses on the evaluation of youth platforms as an important social incubator of the National Initiative for Human Development (NIHD) in Morocco, particularly to promote social entrepreneurship and support very small enterprises (VSE). Numerous social incubators have been created to support social entrepreneurship and foster innovative and effective socio-economic relations. However, their impact remains limited, raising questions about their performance.
Research methodology – Based on a sample of 40 NIHD youth platforms, the stochastic frontier analysis (SFA) method was applied to measure their technical efficiency (TE), and then the determinants of the TE obtained were analysed by a regression using the Tobit model.
Findings – The results indicate that management costs (MC), the number of accompanied project holders (APH) and income improvement actions in social and solidarity economy (II- ASSE) have a significant impact on the creation and development of VSE or cooperatives. In addition, the experience of the platform manager has a positive influence on TE, while age has no significant effect.
Research limitations – The conclusions of the study may not be entirely applicable to the current situation of NIHD youth platforms in Morocco, because they are based on data available at a time conditioned by an exceptional context (e.g., post-covid; government austerity policy, etc.).
Practical implications – This study provides public policymakers and platform managers with actionable insights into optimizing resource use and improving platform operations. Policy-makers can use the findings to allocate funding more effectively, prioritize support services like income improvement actions, and identify platforms that serve as benchmarks for best practices. Additionally, the study highlights the importance of experienced platform managers, guiding recruitment and training policies to improve platform outcomes.
Originality/Value – The study paves the way for future research aimed at exploring in more depth the underlying mechanisms of the efficiency of NIHD youth platforms
Employee commitment in Ghanaian healthcare: a multi-factor analysis
No full textPurpose – The study investigates the factors influencing organizational commitment among employees at a Municipal Health Directorate (MHD) in Ghana. It focuses on identify- ing key organizational and individual factors that drive commitment and examining potential gender differences.
Research methodology – A quantitative approach was employed, using a cross-sectional survey of 204 MHD employees, with a final sample size of 153. A structured questionnaire measured organizational commitment and influencing factors. Multiple regression analysis was used to examine relationships between variables.
Findings – Key drivers of commitment include training and development, salary, leadership style, work environment, job satisfaction, and involvement in decision-making. Training and development were the strongest predictors of commitment, while job-related stress negatively influenced commitment. No significant gender differences in commitment were found. Research limitations – The cross-sectional design limits causality. Future research should adopt longitudinal designs to track changes in commitment over time and explore gender differences in other contexts.
Practical implications – The findings emphasize the importance of investing in employee development, fostering supportive leadership, managing job stress, and involving employees in decision-making to enhance commitment.
Originality/Value – This study provides valuable insights into the determinants of employee commitment in healthcare, contributing to the limited research on organizational commitment in resource-constrained healthcare settings in Ghana.
 
Applying the mean-variance framework: portfolio optimization and comparative performance analysis in the emerging Colombian capital market
No full textPurpose – this paper adopts the mean-variance approach in optimizing portfolios within the Colombian capital market, a setting full of complications such as lack of liquidity and market concentration. It delivers actionable messages for emerging market stakeholders and formulates guidance aimed at enhancing risk-adjusted returns and informing portfolio management in markets with similar structural and economic conditions.
Research methodology – a bi-objective mean-variance model has been used for analyzing the stock prices of 17 stocks on a weekly basis from 2009–2024. Annual rebalancing has made the portfolio responsive to changes in the market, considering the Sharpe ratio as the benchmark to assess risk-adjusted performance.
Findings – optimized portfolios in Colombia outperformed traditional investment funds by realizing better returns while having a balanced risk. Surely, this shows that the model is able to be flexible and react to changes in fluctuation, capture sectoral opportunities, and perform amazingly in a dynamic market.
Research limitations – focusing on adaptability and real-time rebalancing in this work can establish a basis on which future research will operate, refining optimization strategies that incorporate advanced risk measures such as CVaR.
Practical implications – the results present an effective and flexible tool for investors to optimize their portfolios in respect of risk diversification and sustainable returns, considering liquidity constraints and market turmoil.
Originality/Value – this research connects theory and practice and demonstrates the flexibility of the mean-variance model in emerging economies. It emphasizes novelty in portfolio optimization solutions and further development of strategies in sophisticated financial conditions
A numerical scheme to simulate the distributed-order time 2D Benjamin Bona Mahony Burgers equation with fractional-order space
No full textIn this study, a new class of the Benjamin Bona Mahony Burgers equation is introduced, which considers the distributedorder in the time variable and fractional-order space in the Caputo form in the 2D case. The 2D-modified orthonormal normalized shifted Ultraspherical polynomials are derived from 1Dmodified orthonormal normalized shifted Ultraspherical polynomials and 2D-modified orthonormal normalized shifted Ultraspherical polynomials and the orthonormal normalized shifted Ultraspherical polynomials are applied to approximate of the space and time variables, respectively. Moreover, the convergence analysis of these basis functions is investigated. Due to the time variable being in the distributed-order mode and the space variable being in the fractional-order case, to apply the desired numerical algorithm for this type of equation, operational matrices of ordinary, fractional and distributed-order derivatives are computed. In the proposed method, once the unknown function is approximated using the mentioned polynomial, the matrix form of the residual function is derived and then a system of algebraic equations is adopted by applying the collocation approach. An approximate solution is extracted for the original problem by solving constructed equation system. Several examples are examined to demonstrate the accuracy and capability of the method
Fixed point approximation of contractive-like mappings using a stable iterative family and its dynamics via quadratic polynomials
No full textThis study aims at presenting a novel bi-parametric family of iterative methods for computing the fixed points of a contractive-like mapping. We thoroughly analyze the strong and stable convergence of the proposed technique and explore its applicability across various problem domains. Regarding convergence, it is proven that for several operators, the Mann iteration is analogous to the proposed multi-step class, and vice-versa. Moreover, numerical tests demonstrate the superior performance of the new procedures compared to existing three-step schemes. We further examine the dynamic behavior of several fixed-point iterative techniques when applied to quadratic polynomials. Based on the outcomes of these experiments, it can be concluded that the proposed family demonstrates both validity and effectiveness
Enhancing blood glucose control through the fixed point theorem
No full textDiabetes is a chronic condition that poses significant health risks globally, arising from the body’s inability to effectively utilize insulin produced by the pancreas or insufficient insulin production. This paper proposes a novel approach to diabetes management by focusing on optimal control strategies aimed at regulating blood glucose levels to achieve desired targets. We integrate concepts of output controllability into a discrete-time model that captures the dynamics of glucose and insulin interactions. Applying fixed-point theorems, we define permissible control mechanisms for dealing with the challenge of keeping glucose concentrations within optimal ranges. The theoretical framework is supported by numerical simulations that demonstrate the efficacy of the suggested optimal control method in minimizing blood glucose fluctuations. Our findings shed light on the development of advanced blood glucose control systems, eventually leading to enhanced diabetes management and improved quality of life for individuals impacted by the disease
Classification and identification of medical insurance fraud: a case-based reasoning approach
No full textAppropriate classification of medical insurance fraud events can not only be effective in preventing and combating fraud, but also greatly improve the utilization of medical resources. Due to the uncertainty inherent in medical insurance fraud, identifying and classifying the fraud are non-trivial tasks. In addition, the selection of classification radius by traditional methods is often highly subjective. To this end, a case-based reasoning (CBR) approach in probabilistic hesitant fuzzy environment and its application to classifying the severity of medical insurance fraud events are investigated in this article. At first, the probabilistic hesitant fuzzy element (PHFE) is regarded as a discrete probability distribution, and its distribution function is defined. On this basis, a distribution discrepancy degree is proposed to make up for the shortage of existing measures between PHFEs. Then, a probabilistic hesitant fuzzy decision-making method based on CBR is proposed, which considers both decision data and the expert’s own knowledge and experience. Finally, the proposed method is used to classify the severity of medical insurance fraud events, and the rationality and superiority of the method are verified by comparative analysis.
First published online 15 July 202
E-commerce policy, market integration and regional economic disparities: evidence from China’s national e-commerce demonstration cities
No full textUsing panel data of 284 cities at prefecture level and above in China from 2003 to 2022, this paper takes the National E-commerce Demonstration Cities (NEDC) as a quasi-natural experiment, employs the staggered difference-in-difference (DID) model to examine the impact of the NEDC policy on regional economic disparities (RED), and explores the mediating roles of factor and commodity market integration. The main findings are as follows: First, the NEDC policy significantly narrows RED, which still holds after a series of robustness tests. Second, the mechanism analysis demonstrates that the NEDC policy mitigates RED by fostering both factor and commodity market integration. Third, the inhibitory effect of the NEDC policy on RED is more pronounced in non-eastern cities, southern cities, commercial-based cities, ordinary prefecture-level cities and good business environment cities. Fourth, the NEDC policy exhibits a significant synergistic inhibitory effect on RED within 150 km radius of the demonstration cities. Moreover, the inhibitory effect of the NEDC policy becomes more pronounced at lower quantiles of RED. This study elucidates the role of e-commerce policy in narrowing RED and provides valuable policy insights for achieving coordinated regional economic development in the new era.
First published online 16 July 202
Exploring the social and economic consequences of the metaverse: a multi-criteria approach to the SDGs
No full textThis study explores the social implications of the Metaverse, a transformative digital ecosystem, through the lens of the United Nations Sustainable Development Goals (SDGs). The research identifies fourteen key concerns associated with the adoption of Metaverse technologies and assesses their societal impact. A two-stage methodology was employed: an expert panel utilized Grey Step-wise Weight Assessment Ratio Analysis (SWARA) and Grey Combined Compromise Solution (CoCoSo) to assign relative weights and to rank these concerns, reflecting their significance in societal contexts. Following this, an international survey was conducted to quantitatively gauge public perspectives across diverse demographics. Key findings highlight substantial psychological impacts linked to immersive experiences, such as addiction and mental health challenges, which pose a threat to SDG 3 (Good Health and Well-being). The environmental sustainability of Metaverse technologies is also critically examined, stressing the urgent need for green practices to mitigate carbon emissions and reduce energy consumption. Furthermore, ethical issues, particularly surrounding data privacy and user consent, are discussed, emphasizing the importance of robust regulatory frameworks to ensure safe and equitable user experiences. The study reveals the Metaverse’s potential to both foster global connectivity and exacerbate existing social inequalities, advocating for balanced, inclusive approaches to ensure equitable access. By integrating expert insights with broad public opinions, this research provides a comprehensive analysis of the complex relationship between digital technology and societal well-being, offering a foundation for future exploration of the responsible evolution of the Metaverse.
Please view the correction statement: Corrigendum: Exploring the social and economic consequences of the metaverse: A multi-criteria approach to the SDG