Economic Performance Indicators Research Articles

Determination of Location Quotient of Organic Agriculture in Türkiye

The main objective of the study is to determine in which provinces organic agriculture is clustered in Türkiye. Location quotient is one of the most widely used indices in regional concentration measurements and expresses the degree of specialization of a certain production activity within a country/region/sector or the relative concentration of a certain production activity in a certain region. In this direction, within the scope of the study, it is aimed to determine the location quotient of organic agriculture, which provides competitive advantage throughout Türkiye, and it is envisaged to determine the location quotient in this direction. In determining the location quotient, the amount of production, which is one of the best indicators of economic performance, was used. As a matter of fact, the amount of production is the most important indicator showing which production activity is more dominant and the location quotient to be calculated takes a value between 0 and infinity (∞). If the relevant production activity has a score greater than 1, it indicates that the activity is the main production activity that is concentrated/specialised in the region. However, if the score is less than 1, it indicates that the activity is a local one that is not sufficiently concentrated/specialised in the region. Following the analysis, Eastern Anatolia and Central Anatolia are the regions with the highest concentration of organic agriculture production. The top 10 provinces with the most concentrated organic agriculture production are Van (7), Ağrı (6), Ankara (6), Bayburt (6), Erzurum (6), Çanakkale (5), Kars (5), Muş (5), Niğde and Sivas. The most widely produced crops are alfalfa (18), wheat (16), tomato (15), apple (14), maize (12), barley (12), hazelnut (9), sainfoin (9), olive (9), oat (9) and vetch (9). Localized and intensified organic farming systems have proven effective in generating high income per unit of land, optimizing agricultural land utilization, and ensuring sustainability. They also provide specialized labour forces, sector-specific inputs, and the use of advanced technologies. Therefore, it is believed that the formations will enhance the economic, social, and environmental sustainability of the region by increasing productivity and promoting the growth of organic agriculture. This will lead to significant benefits for the region's development.

Sustainability for ship operations in seaport areas: Technical solutions and environmental assessment.

The International Convention for the Prevention of Pollution from Ships (MARPOL) has prohibited ships using of HFO in ports. For this reason, during in port operations, different strategies must be adopted, based on the use of cleaner fuels or on the transition towards marine electrical technologies. In this context, the purpose of the present research is to analyze and compare, from an environmental and economic points of view, different technical solutions for in port operations. Four alternative configurations have been proposed: Solution 1, Battery & Internal Combustion Engine (ICE); Solution 2, Battery & Fuel Cell (FC) with yellow hydrogen; Solution 3, Battery & Fuel Cell (FC) with green hydrogen, and Solution 4, Battery & Cold Ironing (CI). From the environmental perspective, the Well-to-Waves (WTW) analysis has been carried out; from the economic point of view, the investment costs and the operating costs have been calculated and compared. Moreover, an economic performance indicator, the Economic-Environmental Correlation specific Index (ECI), has been introduced and evaluated. Results highlighted that from environmental point of view, the best solution is achieved implementing the Battery & Fuel Cell (FC) solution. On the other hand, the Battery & Cold Ironing (CI) solution represents the best solution from the economic point of view, allowing to obtain the lowest ECI.

Pengaruh Digitalisasi terhadap Penjualan Pelaku Usaha Mikro, Kecil, dan Menengah (UMKM) di Kota Makassar

Understanding the impact of digital technology on Micro, Small and Medium Enterprises (UMKM) in Makassar City is the aim of the research. The descriptive qualitative method used in this research is collecting data through observation, interviews and documentation. Research shows that this has a significant positive impact on the profits of UMKM in Makassar City from Digitalization. On the other hand, one of the factors that hinders UMKM actors in terms of the effectiveness of digitalization is the ability to utilize technological media as an indicator of digital economic performance.

Financial and economic performance of agricultural enterprises: analysis and policy improvement

Purpose. The article aims to develop theoretical and applied foundations for forming a methodology to evaluate financial and economic performance of agricultural enterprises. Methodology / approach. The authors’ methodology for analysing enterprises’ financial and economic performance is formed in the research. This methodology is based on the use of the principal component analysis. Its use involves the composition of a series of empirical indicators of financial and economic performance based on a temporal approach, the calculation of coefficients of significance of indicators and components, and the calculation of combined and integral indicators of financial and economic performance. The developed methodology was tested using the example of 13 agricultural enterprises. The selected enterprises operate in the Lviv region of Ukraine. The study period covers the operational indicators of agricultural enterprises from 2017 to 2022. The Principal Component Analysis (PCA) method was employed to calculate the integral index of financial and economic performance for these agricultural enterprises. Econometric modeling was applied to identify the key determinants influencing the formation of this integral index. Results. The research results showed that despite the availability of resource capacities of agricultural enterprises, the process of forming their financial and economic performance is subject to the destabilising influence of war and market factors. The integral index of agricultural enterprises’ financial and economic performance has significantly impacted their operational efficiency. Through the application of econometric modelling, the primary determinants influencing the formation of this integral index of financial and economic performance in agricultural enterprises have been identified. To improve the financial and economic performance of farming enterprises, a targeted mechanism is developed that is aggregated from such strategic areas as the rationalisation of production costs, the improvement of financial and economic management, better budgeting, the development of management personnel, and the restructuring of market policy. Originality / scientific novelty. The originality of research lies in developing a methodology for assessing enterprises’ financial and economic performance using key indicators and components. This methodology creates an adequate information and analytical basis for improving the management of financial and monetary resources. Practical value / implications. The practical significance of the research results consists in the possibility of their application in the economic activity of agricultural enterprises to improve the process of forming the financial and economic performance of the latter.

ON THE ISSUE OF ASSESSING THE EFFECTIVENESS OF DESIGN SOLUTIONS TO ENSURE THE SUSTAINABILITY OF THE URBAN TRANSPORT SYSTEM

Modern transport problems in many cities around the world are caused by the high level of motorisation of their population and the high frequency of private car use. Despite a number of advantages of using private cars as a means of transport (high speed of communication, the ability to choose a route and travel at a convenient time, high comfort, etc.), the mismatch between the development of motorisation and the existing transport infrastructure leads to traffic congestion, which has a number of negative consequences that make the use of private cars less efficient. These consequences include increased transport delays, reduced traffic speeds and, consequently, increased travel time, and more intensive consumption of non-renewable energy sources. Equally urgent are the issues of road safety and improving the environmental situation in cities. At present, a promising way to solve urban transport problems is to apply the concept of sustainable development of urban transport systems and the methodology of transport demand management. The justification of design solutions to ensure the sustainability of urban transport systems should be based on a model approach and include a comprehensive assessment of a number of social, economic and environmental performance indicators. The adequacy of transport models and the accuracy of the assessment of the consequences of design decisions are crucial for choosing the most appropriate set of measures to ensure the sustainability of transport systems. The article proposes an efficiency criterion for evaluating design solutions to ensure the sustainability of the city's transport system, which contribute to reducing the use of private car. This criterion provides for a comprehensive assessment of the effectiveness of design solutions in terms of economic, social and environmental performance indicators. Based on the analysis of statistical data, it was found that the following distribution of passenger cars by type of fuel consumed is typical for Kharkiv: cars with petrol engines - 48.58%; diesel cars - 14.63%; cars with gas cylinder equipment - 33.58%; electric cars - 3.21%. The established distribution of passenger cars by type of fuel consumed is the basis for establishing average values of variable and fixed operating costs of private car owners and should be taken into account when assessing the environmental impact of the transport process. This is the direction of further research.

Reimagining Sustainable Development and Economic Performance Indicators: A Human-Centric Maslow–Bossel Blueprint

Reflecting the shift from purely quantitative economic growth to broader socio-environmental sustainability, this study proposes a framework for assessing sustainable development (SD) by integrating Maslow’s hierarchy of needs with Bossel’s classification system. As economic development increasingly emphasizes sustainability, numerous organizations and agencies, including the United Nations, have developed indicators to measure sustainable progress. However, subjective dimensions of SD, grounded in individual values and needs, remain underexplored. This study operationalizes Maslow’s “pyramid of needs” alongside Bossel’s system to establish an “SD pyramid”, distinguishing dimensions and indicators that capture social, economic, and environmental complexity. By mapping human needs onto the Sustainable Development Goals (SDGs), this study contributes to delineating (i) the research areas uncovered (or partly covered) with relevant indicators, (ii) a significant lack or partial shortage of pertinent information, and (iii) a combination of a few basic indicators summarizing the necessary information into a unique measure of SD. The outcomes offer a foundation for a quali-quantitative assessment of SD, enhancing the monitoring tools focusing on subjective and contextual needs.

Unveiling the intermediate role of Mexico’s mid-sized metropolises

ABSTRACT This paper analyses the role of metropolises that occupy a secondary place in urban systems and distinguishes between the intermediation and other strategic roles that they can play. As an empirical approximation to secondary cities, the paper operationalises mid-sized cities according to population size and evaluates the economic performance of metropolitan areas within Mexico’s urban system. Drawing on the theories of borrowed size and agglomeration shadows, the paper discusses whether mid-sized metropolitan areas in Mexico have evolved into intermediate urban centres that can drive development and growth. Additionally, the study identifies the economic performance factors across the group of mid-sized metropolises. Different economic performance indicators are calculated and an econometric model is estimated for the period 2008–2018. We find that, with a few exceptions, mid-sized metropolitan areas in Mexico have not evolved into intermediate metropolises and face challenges that limit their strategic role in their respective urban system. This analysis contributes to the literature on secondary cities by studying and providing empirical insights into the functioning and evolution of urban systems that have traditionally been centralised around a single megacity, such as Mexico City.

Restoration and evaluation for severed streams in high-density urban areas based on a multi-objective framework: A case study of Heping Stream in Nanjing

Numerous severed streams that emerge during rapid urbanization has been negatively impacting regional water systems and urban environments. Traditional restoration efforts are prone to focus on water quality, overlooking the complex of urban severed stream as natural-social ecosystems. However, current literature indicates a lack of systematic restoration methods and post-implementation evaluations tailored to severed streams, which adversely affects water resource management and sustainable urban development. This study bases on research of the severed streams in Nanjing’s Hexi New District to develop methods for the restoration and evaluation of severed streams in high-density urban areas. Taking the Heping Stream as a case study, it took three years to complete a full-process study encompassing the design, implementation, and post-occupancy evaluation of the restoration of the severed stream. We developed a multi-objective framework, including five measures for the restoration of severed streams, along with performance evaluation indicators from environmental, social, and economic perspectives to compare the state of the severed-stream before and after the restoration. So as to assess the effectiveness of the restoration methods and to put forward suggestions for the improvement of the restoration measures. The results showed that the method had a positive effect on the quality of the water environment, public evaluation, capital investment and energy consumption. Some of the environmental performance indicators were significantly improved after the restoration, especially the dissolved oxygen content, water flow. Most of the social performance indicators were better after the restoration than before. In terms of economic performance indicators, the use of photovoltaic energy resulted in significant savings in electricity and pumping costs. Performance evaluation confirmed comprehensive benefits of the method, with Run off Control, Waterfalls Construction and Riverbank Ecological Restoration being most effective. To improve the benefits of restoration, diverse strategies should be combined together, including runoff control, artificial wetlands, vegetated buffers, and riverbank restoration. This research can support the optimization of future restoration measures and scientific decision-making in urban severed-stream restoration.

Macroeconomic effects of climate change: Evidence from Canadian provinces

We study the long-term macroeconomic effects of climate change across ten Canadian provinces between 1961 and 2017. Following Kahn et al. (2021a), our econometric strategy links deviations of temperature and precipitation (weather) from their multi-decade historical rolling averages (climate) to various province-specific economic performance indicators at the aggregate and sectoral levels. We show that climate change (proxied by a series of weather shocks) has a long-lasting adverse impact on real output in various Canadian provinces and economic sectors. Adaptation reduces the income losses but cannot offset them entirely. Moreover, in contrast to most cross-country results, our within-country estimates suggest asymmetrical growth effects from precipitation and temperature anomalies. Specifically, persistently higher-than-normal precipitation is associated with lower long-term GDP growth, whereas the effect of below-than-normal precipitation is not statistically significant. As regards temperature, while extended periods of cold spells (temperature persistently below historical norms) is detrimental to growth (though less likely in the future), Canada is not benefiting from a warmer climate as often argued in the literature.

Optimum solution of power flow problem based on search and rescue algorithm

In order to solve the optimal power flow (OPF) problem, a unique algorithm based on a search and rescue method is applied in this study. For the OPF problem under three objective functions, the SAR offers a straightforward and reliable solution. The three objective functions are used to minimize the fuel cost, power loss and voltage deviation as a single objective function. The OPF problem for benchmark test system, including the IEEE-14 bus, IEEE-30 bus, and IEEE-57 bus, are solved by the Search and Rescue algorithm (SAR) under specific objective functions that are determined by the operational and economic performance indices of the power system. To demonstrate the efficacy and possibilities of the SAR algorithm, SAR is contrasted with alternative optimization techniques such as harmony search algorithm, gradient method, adaptive genetic algorithm, biogeography-based optimization, Artificial bee colony, gravitational search algorithm, particle swarm optimization, Jaya algorithm, enhanced genetic algorithm, modified shuffle frog leaping algorithm, practical swarm optimizer, Moth flam optimizer, whale and moth flam optimizer, grey wolf optimizer, cheap optimization algorithm and differential evolution algorithm. The value of minimum power losses based on SAR technique is equal to 0.459733441487247 MW for IEEE-14 bus. The value of minimum total fuel cost based on SAR technique is equal to 8051.12225602148 $/h for IEEE-14 bus. The value of minimum voltage deviation based on SAR technique is equal to 0.0357680148269292 for IEEE-14 bus. The value of minimum power losses based on SAR technique is equal to 2.71286428848434 MW for IEEE-30 bus. The value of minimum total fuel cost based on SAR technique is equal to 798.197578585806 $/h for IEEE-30 bus. The value of minimum voltage deviation based on SAR technique is equal to 0.0978069572088536 for IEEE-30 bus. The value of minimum total fuel cost based on SAR technique is equal to 38017.7691758245 $/h for IEEE-57 bus. The acquired results for the OPF compared to all competitor algorithms in every case of fitness function demonstrate the superiority of the SAR method.

COMPARATIVE ANALYSIS OF THE GDP STRUCTURE OF THE G7 COUNTRIES: ECONOMIC DEVELOPMENTS AND TRENDS

This research article will examine the gross domestic product (GDP), which is one of the most widely used indicators of national economic performance. GDP represents the total output of a national economy over a specified period, with seasonal fluctuations duly adjusted. The most comprehensive measure of GDP is also adjusted for inflation, thereby enabling the assessment of changes in output rather than changes in the prices of goods and services. The significance of this indicator can be demonstrated by the fact that GDP is frequently employed to assess the relative size of national economies. Governments, financial market participants, and business leaders are most interested in changes in GDP over time, as reflected in annual growth or decline rates, because this allows them to make assumptions and develop plans for the future. The government uses previous years' GDP figures to formulate policies on interest rates, taxes, and trade policy. The study of GDP in the G7 countries is particularly important and relevant, as these countries represent the central government of the whole world, have a great influence on the economy, discuss global problems and develop solutions in the shortest possible time. The object of the study is the 7 members of the G7, namely: Canada, France, Germany, Italy, Japan, the United Kingdom, and the United States, while the subject is the basic indicators of the national economy of each individual country, analysed in the dynamics over the past 10 years.

Techno-Economic Analysis of BAU-STR Dryer for Rice Drying: An Approach to Accelerate Adoption

Postharvest food loss and waste offset worldwide agricultural productivity and food security. Insufficient drying and storage are the prominent drivers of food loss and waste in underdeveloped countries. Mechanical grain drying systems have distinct benefits over sun drying but are inaccessible to underserved communities due to high capital costs and energy demand. This study evaluated the techno-economic and financial performance of a half-ton-capacity BAU-STR dryer. The moisture extraction rate, drying rate, drying efficiency, and energy consumption were used as technical performance indicators. In contrast, the net present value (NPV), internal rate of return (IRR), benefit–cost ratio (BCR), and payback period were considered economic performance indicators. The technical performance analysis results revealed that the moisture content of rice was reduced from 19.5% to 13.5 ± 0.15% in 4.0 h with an average drying rate of 1.5%/h and a drying efficiency of 75.1%. The financial performance analysis resulted in a drying cost, NPV, IRR, BCR, and PBP of USD 0.96 per 100 kg of grain, USD 3018, 135%, 3.0, and 0.73 yr., respectively, when the annual use was 240 h. If the yearly use of the dryer increased from 240 to 720 h, a higher NPV, IRR, and BCR, as well as a lower payback period and drying cost, could be achieved. Adopting a BAU-STR dryer for drying grain (rice and corn) among underserved communities could play a key role in postharvest food loss and waste.

Environmental Threat Assessment Framework for Mining Activities in Guinea: An Integrated Approach for Sustainable Development.

The present study aimed to investigate the environmental consequences of mining activities in boke bauxite mining areas and the Kerouane iron mining project in Guinea using a mixed-methods approach that combines quantitative and qualitative data. A reference matrix was used to evaluate the impact of the mining activities, classifying them as negligible, moderate, or significant. Data were collected from October 2022 to January 2023 by assessing their impact on water pollution, soil, noise, air quality, vegetation, fauna, and flora. These findings indicate concerns regarding the water pH, electrical conductivity, and turbidity in both the Boke and Kerouane regions. The soil composition analysis revealed the presence of Cr, Cu, Ni, and Zn in both the Boke and Kerouane project areas. Noise levels exceeded the guideline levels and substantial amounts of particulate matter (PM) were detected, with high levels of PM10 in mining operations. The Kerouane Iron Project resulted in the direct loss of 2929 ha of natural habitats and 466 ha of modified habitats, with the extraction of approximately 1.291 billion tons of ore anticipated over a 22-year mine lifespan. This study proposes an environmental threat assessment framework that integrates technical and human activity data to evaluate the environmental impacts of mining activities comprehensively. To promote sustainable development and minimize the negative impacts of mining, an integrated index of economic and environmental performance in the mining sector is recommended, along with collaboration between researchers and policymakers to develop effective climate-change mitigation strategies.

Performance response analysis and optimization for integrated renewable energy systems using biomass and heat pumps: a multi-objective approach

The focus of this study is to optimize the exploration of biomass-driven multi-energy systems, which include combined heat, power, and gas generation. The objective is to enhance the thermal, environmental, and economic performance indicators of the system. The optimization objectives encompass the quantities of internal combustion engines and air source heat pumps, as well as the dimensions of tanks utilized for anaerobic fermentation. A mathematical model was developed to optimize multiple objectives for combined heat, power, and gas generation systems by employing multi-objective intelligent optimization algorithms. The validation and analysis were conducted using rural residences in Lanzhou, Gansu Province, China, as a case study. The sensitivity analysis of biomass gasification combined heat and power systems was conducted from both technical and cost perspectives, examining the dynamic impact characteristics on the outcomes of multi-objective optimization. The findings indicate that the annual energy-saving rate of the optimized combined generation system decreased from 3.62% to -6.78%, while the growth in carbon emissions reduction rate increased from 76.05 to 81.38%, and the annual cost-saving rate grew from 0.97 to 14.96%. The power generation efficiency of the cogeneration station and hydraulic retention time were found to have a significant impact on the multi-objective optimization results of the combined generation system among the technical parameters. The unit cost of anaerobic fermentation tanks had a more significant impact on the multi-objective optimization results in terms of cost parameters, compared to the price of biogas residue.

Optimizing a hybrid wind-solar-biomass system with battery and hydrogen storage using generic algorithm-particle swarm optimization for performance assessment

This paper investigates the optimal design of a hybrid renewable energy system, integrating wind turbines, solar photovoltaic systems, biomass, and battery and hydrogen storage to ensure a reliable energy supply at the lowest annual cost for a residential load in Kern County, USA. The hybrid generic algorithm particle swarm optimization (GAPSO) algorithm was adopted to determine the optimal configuration of parameters and cost-effectiveness, considering technical, economic, environmental, and social performance indicators. The generic algorithm (GA) and particle swarm optimization (PSO) validate the effectiveness of the proposed technique, showcasing its efficiency in system optimization. The findings indicate that GAPSO outperforms GA and PSO due to its rapid convergence, lowest final fitness value, and stable optimization process. The hybrid GAPSO's performance, combined with the different capacities of wind turbines (4,561 kW), solar PV (8,480 kW), biomass (2,261 kW), battery banks (8,000 kWh), and fuel cells (2,392 kW), resulted in an annual cost of $6,239,193; energy cost and net present value of $0.48/kWh and $101,333,937. The system maintained a supply loss of 0.8 %, achieved an availability index of 99.2 %, a renewable energy fraction of 88.87 %, GHGs emission of 953,615 kg, land use of 3,842,875 m2, and water consumption 528,678 L respectively. GAPSO achieved a 2.17 % and 0.01 % improvement in cost-effectiveness and 11.11 % increase in reliability compared to GA and PSO.

Empowering farmer community with technology modernisation to improve rice farming performance through demonstration farms in East Java, Indonesia

Purpose Rice is a strategic commodity and staple food; thus, rice productivity should grow faster than the population. A public agricultural agency launched technology modernisation to improve rice farm performance. This study aims to assess the impact of technology modernisation on rice farming performance and evaluate farmer acceptance of such technology. Design/methodology/approach This study was conducted in 2023-2024, based on selected demonstration farms (demfarm) carried out during 2021-2022 in East Java, Indonesia, one of the rice bowls. Microeconomic theory of production and the double-differences approach were used as fundamental analyses. Farmers were purposively selected to participate in the demfarm. For comparison, farmers with existing technology adjacent to the demfarm were chosen accordingly. Rice production is considered an economic performance indicator, and factors related to socio-demographic and technical aspects were conceptualised using innovation and diffusion theory. Findings The results of demfarm were apparent. Technology modernisation improved rice farming’s economic performance. Farmer acceptance of such technology was relatively high at the first stage. There was no conflict between technology and local culture and norms. The technological package will likely be disseminated to farmers after adequate socialisation. Research limitations/implications This study engaged farmer innovators and early adopters in the demonstration farm. This needs more actions from farmers who are not categorised as innovators and early adopters, which dominate the farmer population. Practical implications Extension officials need field guidance to ensure continual technology adoption because of technology complexity. Originality/value The originality of the study is based on a field experiment and direct observation throughout a crop cycle, and the analysis is established using a solid theory and analytical framework.

Short communication: Dairy Victory™ Platform: A Novel Benchmarking Platform to Empower Economic Decisions on Dairy Farms.

In the face of diminishing economic margins, dairy farmers globally are compelled to maintain economic competitiveness. Benchmarking emerges as a strategic tool to establish new, achievable improvement objectives that balance ambition with practicality. This typically requires integrating diverse data sources such as feed, milk production, diet, and market prices. However, many farms lack essential, cow-level data like daily milk output and milk income over feed cost (IOFC), which hampers economic performance visibility and informed decision-making. To address this challenge, we introduce “Dairy Victory™ platform (DVP)” a novel cloud-based benchmarking platform designed to simplify complex analyses. The DVP uniquely calculates zootechnical and economic key performance indicators (KPIs) at the cow and herd levels and benchmarks these against a dynamically selected cohort of farms, facilitating comparisons across various farm sizes, and milk production levels. The primary objective of this paper is to demonstrate the utility of DVP as a decision-making tool in supporting farmers and consultants with both operational and strategic decisions. It emphasizes leveraging benchmarking information to enhance decision-making processes, thereby highlighting the significant value that DVP brings to farmers, consultants, and dairy farm stakeholders. Our study analyzed data from 712 farms from December 2023, focusing on several KPIs, such as milk production, milk quality, feed efficiency, and IOFC using Dairy Herd Improvement (DHI) records. This approach showcases DV's ability to utilize minimal data inputs for detailed analysis, leveraging peer performance to set desirable and/or achievable goals. We present a case study demonstrating how the DVP platform can guide dairy farms using anonymized peer data. This approach enables users to potentially improve their IOFC by up to 35%. Our findings highlight DVP's potential as a powerful tool for generating insightful analyses, simulations, and recommendations, primarily from test-day data, but also integrated with market and estimated data. This supports more strategic decision-making in dairy management, including automatic goal-setting based on peer performance.

The Nexus between Corporate Governance and Economic, Social and Environment (ESE) Practices: Bangladeshi Banking Paradox

This study aimed to investigate the relationship between corporate governance and sustainability practices at 45 scheduled commercial banks in Bangladesh. The study specifically focused on the impact of corporate governance on bank sustainability practices, using the Global Reporting Initiative (GRI-4) sustainability guidelines. The resource-based view theory was used to explain the relationship between corporate governance and sustainability practices. Panel data used for this analysis was derived from the annual and sustainability disclosure reports of these banks from 2017 to 2021. This study explores dimensions of corporate governance, including board size, independent board members, CEO duality, gender diversity, audit committees, risk management committees, and audit firm size, highlighting their importance in strategic decision-making. It also explores sustainability practices from a corporate perspective, focusing on economic, social, and environmental performance indicators and emphasizing the importance of strategic resource allocation and disclosure. Four hypotheses were formed, and ordinary least squares (OLS) regression was employed to test the relationship between corporate governance and bank sustainability practices. The statistical results showed that CG has a direct effect on firms overall sustainability as well as social and environmental sustainability practices. It was also seen that the size of the board has a significant effect on the overall sustainability measures (ESE). The study suggests that pro-active measures should be taken to improve sustainability practices in Bangladesh.

Techno-Economic Analysis of Combined Production of Wind Energy and Green Hydrogen on the Northern Coast of Mauritania

Green hydrogen is becoming increasingly popular, with academics, institutions, and governments concentrating on its development, efficiency improvement, and cost reduction. The objective of the Ministry of Petroleum, Mines, and Energy is to achieve a 35% proportion of renewable energy in the overall energy composition by the year 2030, followed by a 50% commitment by 2050. This goal will be achieved through the implementation of feed-in tariffs and the integration of independent power generators. The present study focused on the economic feasibility of green hydrogen and its production process utilizing renewable energy resources on the northern coast of Mauritania. The current investigation also explored the wind potential along the northern coast of Mauritania, spanning over 600 km between Nouakchott and Nouadhibou. Wind data from masts, Lidar stations, and satellites at 10 and 80 m heights from 2022 to 2023 were used to assess wind characteristics and evaluate five turbine types for local conditions. A comprehensive techno-economic analysis was carried out at five specific sites, encompassing the measures of levelized cost of electricity (LCOE) and levelized cost of green hydrogen (LCOGH), as well as sensitivity analysis and economic performance indicators. The results showed an annual average wind speed of 7.6 m/s in Nouakchott to 9.8 m/s in Nouadhibou at 80 m. The GOLDWIND 3.0 MW model showed the highest capacity factor of 50.81% due to its low cut-in speed of 2.5 m/s and its rated wind speed of 10.5 to 11 m/s. The NORDEX 4 MW model forecasted an annual production of 21.97 GWh in Nouadhibou and 19.23 GWh in Boulanoir, with the LCOE ranging from USD 5.69 to 6.51 cents/kWh, below the local electricity tariff, and an LCOGH of USD 1.85 to 2.11 US/kg H2. Multiple economic indicators confirmed the feasibility of wind energy and green hydrogen projects in assessed sites. These results boosted the confidence of the techno-economic model, highlighting the resilience of future investments in these sustainable energy infrastructures. Mauritania’s north coast has potential for wind energy, aiding green hydrogen production for energy goals.

Optimal techno-economic assessment of isolated microgrid integrated with fast charging stations using radial basis deep learning

The global transportation electrification commerce sector is now booming. Stakeholders are paying an increased attention to the integration of electric vehicles and electric buses into the transportation networks. As a result, there is an urgent need to invest in public charging infrastructure, particularly for fast charging facilities. Consequently, and to complete the portfolio of the green environment, these fast-charging stations (FCSs) are designed using 100% of renewable energy sources (RESs). Thus, this paper proposes an optimization model for the techno-economic assessment of FCSs comprising photovoltaic and wind turbines with various energy storage devices (ESDs). In this regard, the FCS performance is evaluated using flywheels and super capacitors due to their high-power density and charging/discharging cycles and rates. Then, optimal sizing of these distributed generators is attained considering diverse technical and economical key performance indicators. Afterwards, the problem gets more sophisticated by investigating the effect of RES’s uncertainties on the selection criterion of the FCS’s components, design and capacity. Eventually, as an effort dedicated to an online energy management approach, a deep learning methodology based on radial basis network (RBN) is implemented, validated, and carried out. In stark contrast to conventional optimization approaches, RBN demonstrates its superiority by obtaining the optimum solutions in a relatively short amount of time.