Search Results (14)

CO₂ sequestration is considered one of the main pillars in achieving the ongoing decarbonization efforts. A myriad of CO₂ sequestration projects targeted sandstone reservoirs since carbonate reservoirs appeared to be unpropitious due to their geological complexity and unfavorable mineralogy and properties. This study investigates CO₂ sequestration potential in a carbonate saline aquifer while considering various geological complexities by capitalizing on numerical simulation. A synthetic anticline reservoir model examined the optimum well location and landing zone for CO₂ sequestration. Additionally, the model evaluated the role of natural fractures in the migration path of CO₂ plume and geochemical reactions throughout the storage process. The study demonstrates that placing the injection well away from the top of the structure in a low-dip region while injecting in the bottom interval would yield the optimum design. After applying a plethora of analyses, geological complexity could impede the migration path of CO₂ but eventually produce a similar path when injected in a similar region. The geochemical interactions between the injected CO₂ and reservoir fluids and minerals reduce the free and trapped CO₂ quantities by dissolving calcite and precipitating dolomite. Furthermore, natural fractures impact the CO₂ quantities during early times only when the fractures cross the top layers. Similarly, the CO₂ migration differs due to the higher permeability within the fractures, resulting in slightly different CO₂ plumes. Consequently, the role of natural fractures should be limited in carbon storage projects, specifically if they do not cross the top of the reservoir. This study reflects a unique perspective on sequestering CO₂ while capturing the roles of natural fractures and well placement in depicting the migration path of the CO₂ plume. A similar systematic workflow and holistic approach can be utilized to optimize the subsurface storage process for potential formations. Full article

This study explored the impacts of ownership structure (OS) on intellectual capital (IC) and its components. Data were gathered from 31 Dhaka Stock Exchange-listed banks for five years, from 2017 to 2021, consisting of 155 observations as balanced panel data. The study used the modified value-added intellectual coefficient (MVAIC) model to track the IC efficiency. The robust fixed effects model was employed for regression analysis to test the hypotheses. The research found that sponsor director ownership is negatively associated with the MVAIC, human capital efficiency (HCE), and structural capital efficiency (SCE) but positively with relational capital efficiency (RCE). High institutional and public ownership are positively linked with SCE but negatively with RCE. Foreign ownership is only positively associated with banks’ MVAIC and HCE. The regression results showed that high institutional ownership (IO) significantly enhanced the MVAIC and HCE. Foreign and public ownership positively influenced banks’ MVAIC, HCE, and capital employed efficiency (CEE) but negatively impacted RCE. The findings of this study will help banks’ policymakers with ownership mixes for the optimum utilization of banks’ resources. Management may assess IC’s efficiency level for proper supervision and use of knowledge resources to boost bank profitability. Also, the findings will help investors make prudent investment decisions. This is the first study to focus on OS and IC with diverse elements in Southeast Asia, especially Bangladesh, an emerging market. Full article

To avert climate change, there has been a rise in the usage of green energy sources that are also beneficial to the environment. To generate sustainable energy in a financially and technically efficient manner, our research attempts to close the gaps. The potential of green sources like photovoltaic (PV) and biomass for a rural community southwest of Sohag Al Gadida City, Sohag, Egypt, is examined in this research considering its techno-economic (TE) and eco-friendly feasibility. The HOMER Pro v3.14 package is used as a scaling and optimization instrument, to calculate the price of the PV/biomass setup and the size and characteristics of its parts. This is to estimate the corresponding electrical production and reduce the total annual cost for the customer. The suggested system structure is validated through the presentation of simulation outcomes and evaluations utilizing MATLAB/SIMULINK R2022a. In addition, a TE-environmental investigation of the optimized PV/biomass structure is performed. The optimum structure is carefully chosen from the best four configurations using the demand predilection by analogy to the perfect technique based on the generation cost, operation cost, energy production, and renewable fraction. The results also indicate that using hybrid PV/biomass is an attractive choice with the initial capital cost (ICC: USD 8.144), net present cost (NPC: USD 11,026), a low cost of energy (LCOE: 0.184 USD/kWh), and the high renewable fraction (RF: 99.9%) of the system. The annual CO₂ emission performance of a PV/biomass system is much better than that of the grid alone and PV/diesel. This method might be applied in rural areas in other developing countries. Full article

Designing modern antenna structures is a challenging endeavor. It is laborious and heavily reliant on engineering insight and experience, especially at the initial stages oriented towards the development of a suitable antenna architecture. Due to its interactive nature and hands-on procedures (mainly parametric studies) for validating the suitability of particular geometric setups, typical antenna development requires many weeks and significant involvement of a human expert. The same reasons only allow the designer to try out a very limited number of options in terms of antenna geometry arrangements. Automated topology development and dimension sizing is therefore of high interest, especially from an industry perspective where time-to-market and expert-related expenses are of paramount importance. This paper discusses a novel approach to unsupervised specification-driven design of planar antennas. The presented methodology capitalizes on a flexible and scalable antenna parameterization, which enables the realization of complex geometries while maintaining reasonably small parameter space dimensionality. A customized nature-inspired algorithm is employed to carry out space exploration and identification of a quasi-optimum antenna topology in a global sense. A fast gradient-based procedure is then incorporated to fine-tune antenna dimensions. The design framework works entirely in a black-box fashion with the only input being design specifications, and optional constraints, e.g., concerning the structure size. Numerous illustration case studies demonstrate the capability of the presented technique to generate unconventional antenna topologies of satisfactory performance using reasonable computational budgets, and with no human expert interaction necessary whatsoever. Full article

Information and communication technology (ICT) companies strive for ceaseless innovation to remain competitive while facing the challenge of maximizing firm value (FV) with limited resources, and increasing the interests of shareholders. However, capital structures have a considerable effect on FV, and the literature still disagrees with the optimum structure in specific industries and countries. Therefore, this study evaluates the FV of ICT companies in terms of profitability efficiency using data envelopment analysis. In addition, this study applies a Tobit regression and Kruskal-Wallis one-way ANOVA to identify the impact of leverage, liquidity, and firm size, which are major capital structure factors influencing FV. The analysis yields three main results. First, in the ICT industry, small and medium companies tend to have better profitability efficiency than companies of other sizes. Second, only small and medium ICT manufacturing companies’ profitability efficiency is positively impacted by the current ratio. Third, only mid-sized service companies’ profitability efficiency is positively impacted by the debt-equity ratio. The results have policy and practical implications for improving the FV of ICT companies. Full article

There are approximately 3.2 million SMEs in Pakistan. It is believed that more than 90% of the economic establishments are SMEs. They contribute 40% of the economic growth and create 70% of Pakistan’s overall employment opportunities. Despite substantial presence and contribution, 95% of SMEs fail within the first five years. Out of the remaining 5%, 25% of the SMEs survive up to four more years, adversely impacting economic growth, employment, and living standards. Previous studies indicated SMEs’ low performance as a significant cause and provoked entrepreneurs to shut down their businesses. Therefore, this study aims to examine the performance of SMEs in Pakistan. Based on the problem, the study contextualized the research model that investigates the relationship between financial capital availability (FCA) and innovative work behavior (IWB), which is believed to be crucial for enhancing small and medium-sized businesses’ performance through accelerated strategic change (SC). In addition, the moderating role of Government support (GS) on SMEs’ performance was also considered. The quantitative, cross-sectional research design was considered appropriate for this research. Data was collected through a structured questionnaire to 340 SMEs in the Pakistan manufacturing sector. The hypothesized relationships were tested through structural equation modeling (SEM) using Smart-PLS 4. Results showed a positive link between FCA, IWB, and SMEs’ performance. Furthermore, FCA and IWB are the key drivers to achieving an optimum level of SME performance, which translates the SC process within the SMEs in Pakistan. Additionally, this research discovered that SC partially mediates the relationship between FCA and IWB on SMEs’ performance. Moreover, GS strengthens the relationship between SC and SMEs’ performance. The present findings offer valuable insight to SME owners, policymakers, and first-line managers to understand the radical change in the process. The study also outlined policy interventions to uplift the diminishing SMEs’ performance. Full article

Innovation has an important role in improving the productivity, safety and sustainability of mining operations. Historically, ore transport was done by diesel trucks, but with the commitment to reduce CO₂ emissions and increase mine safety, mining companies have invested in innovative, more sustainable ore transport technologies. The innovative truckless system, with the intensive use of belt conveyors to transport the ore from the mine to the processing plant, represents a huge project and capital investment. However, operation costs are lower when considering the decrease of fuel use and also maintenance expenses. This paper presents an economic analysis of a mine-to-crusher model to estimate and minimize the operating expenses of an open-pit iron mine located in northern Brazil. The activities at this truckless mine consist of drilling and blasting, loading and primary crushing. In this study, the calibration of the mine-to-crusher model was based on rock fragmentation from the blasting phase. The costs of each mine operation phase were estimated for an optimum 80% passing size (P₈₀). The calibration was conducted with the values of technical and economic parameters in 2019. By considering the structural lithologies of canga and jaspillites, we concluded that the P₈₀ value that minimizes costs might be in the range from 0.31 to 0.34 m. Full article

3D printing, is a newly adopted technique in the construction sector with the aim to improve the economics and alleviate environmental impacts. This study assesses the eco-efficiency of 3D printing compared to conventional construction methods in large-scale structural fabrication. A single-storey 3D-printed house was selected in the United Arab Emirates to conduct the comparative assessment against traditional concrete construction. The life cycle assessment (LCA) framework is utilized to quantify the environmental loads of raw materials extraction and manufacturing, as well as energy consumption during construction and operation phases. The economics of the selected structural systems were investigated through life cycle costing analysis (LCCA), that included mainly the construction costs and energy savings. An eco-efficiency analysis was employed to aggregate the results of the LCA and LCCA into a single framework to aid in decision making by selecting the optimum and most eco-efficient alternative. The findings revealed that houses built using additive manufacturing and 3D printed materials were more environmentally favourable. The conventional construction method had higher impacts when compared to the 3D printing method with global warming potential of 1154.20 and 608.55 kg CO₂ eq, non-carcinogenic toxicity 675.10 and 11.9 kg 1,4-DCB, and water consumption 233.35 and 183.95 m³, respectively. The 3D printed house was also found to be an economically viable option, with 78% reduction in the overall capital costs when compared to conventional construction methods. The combined environmental and economic results revealed that the overall process of the 3D-printed house had higher eco efficiency compared to concrete-based construction. The main results of the sensitivity analysis revealed that up to 90% of the environmental impacts in 3D printing mortars can be mitigated with decreasing cement ratios. Full article

Natural habitats are being altered and destroyed worldwide due to urbanization, leading to a decrease in species abundance and richness. Nevertheless, some species, including tawny owls, have successfully colonized this novel habitat. Consequences at the population level have not been described; thus, our main objective was to describe the effects that urban structure have on the tawny owl population at local and landscape levels. Data were obtained from 527 survey points over 7 months in a large-scale owl survey in the Basque Country (northern Spain) in 2018. At the local scale, the interaction between forest and urban cover affected tawny owl abundance, the optimum being in medium forested areas. The interaction between urban cover and clumpiness index (urban patch distribution) showed a generally negative effect. At the landscape scale, its abundance decreased in complex-shaped urban patches and when distance between them was greater. In conclusion, at the local scale, when a minimal forest structure is present in urbanized areas, the species can exploit it. At the landscape scale, it prefers smaller urban towns to cities. Thinking ahead, the current tendency toward “green capitals” should benefit tawny owl populations. Full article

The capital structure appears to be one of the most researched and the most controversial areas in modern corporate finance. Prior literature on determinants of capital structure has concentrated on firm and country level factors by employing static modeling. Static modeling has certain limitations, which do not allow companies to establish an optimum capital structure in line with economic uncertainty. This study makes a worthy contribution to the existing body of knowledge by filling the gap in the evolution of capital structure by employing a dynamic framework of the financial sector of Pakistan. In addition, the study brings into focus sectors’ importance in determining the firm’s financial behavior. Based on secondary financial sector data from 2006–2019, the article addresses the issues by employing two-step system generalized method of moments (GMM). The findings of the study validated the existence of dynamic capital structure across the financial sector of Pakistan and reinforced the substantial impact of sectors’ unique environment on leverage mechanism. The results are robust under alternative estimation approaches and offer useful policy implications. Full article

In order to reconsider the changes of adjustment speed caused by the recapitalization cost, this research adopted dynamic capital structure theory with adjustment speed as one of the independent variables to analyze the relationship between capital structure and company performance. Instead of applying the commonly used regression models, this research used the decision tree C4.5 algorithm and association rules of priori algorithm. Taking the predictive models created by the decision tree as the main result and supporting it with association rules which help to explain the relationships between capital structure and company performance, this research shows how capital structure influences company performance. As the result presents, a company tends to have better performance when its debt ratio is low, and Tobin’s Q and ROA will turn worse as the ratio gets higher. However, maybe because of the financial leverage, ROE will not decrease when the ratio is high but will increase instead. In addition, this research found out that adjustment speed is negatively related to company performance, meaning that even though a company is more flexible in adjusting itself, it might still perform badly since it is deviating from its optimum leverage. This research found that not only capital structure, but other variables such as price-earnings ratio, research and development expense ratio, and dividend payout ratio also determine a company’s performance. Full article

The main aim of this paper was to investigate the impact of bank characteristics on capital structure empirically. The study employed a panel data analysis, Pooled Mean Group (PMG) and Cross-Sectionally Augmented Autoregressive Distributed Lag (CS-ARDL) estimators were utilized, for the period spans between the years 2008 and 2018. Both the borrowing (leverage) ratio and equity ratio used in the analysis cover short-term deposits and long-term deposits as a fundamental determinant variable on the capital structure. The main findings confirm that the deposit ratio has a positive relationship with the size of the bank. In other words, big banks use more foreign sources than small banks to use the tax shield advantage. At the same time, a percentage increase in bank size and liquidity ratio enhance the bank deposit rate by 0.0068% and 0.479%, respectively, in the long-run, while a percentage change in interest income coverage will reduce the bank deposit rate by 0.004% in the long-run. Meanwhile, the significant causal relationship of growth rate with the bank deposit rate could not be established. In addition, the short-run coefficients of the variables reveal that size, interest coverage, and liquidity have a positive and significant causal relationship with bank deposit rate in the short-run. The findings of the study are in line with the results of capital structure theories, especially the hierarchy theory and balancing theory. Full article

To form optimum firm capital structure strategies to face unanticipated economic events, firm managers should understand the stability of a firm’s capital structure. The aim of this research was to study whether the debt ratio is stationary in listed firms on the Dow Jones Industrial Average (DJIA). Two vital capital structure concepts regarding pecking order and trade-off theory are fairly contradictory. Using opposing theoretical contexts, the Sequential Panel Selection Method apparently categorizes which and how many series are stationary processes in the panel. This method was used to test the mean reverting properties of the 25 companies listed on Dow Jones Industrial Average between 2001 and 2017 in this study, which is expected to fill the current gap in the literature. The overall results show that stationary debt ratios exist in 10 of the 25 studied firms, supporting the trade-off theory. Moreover, the 10 firms utilizing trade-off theory are affected by firm size, profitability, growth opportunity, and dividend payout ratio. These results provide vital information for firms to certify strategies to optimize capital structure. Full article

The present study aims to develop a thermoeconomic-based approach for optimization of steam levels in a steam production and distribution system by use of the specific exergy costing (SPECO) method for determining optimum steam levels to minimize the cost caused by exergy destruction. In the field of total site optimization, incremental cost of the utility system caused by exergy destruction has been selected as an objective function and the result is compared with the case that energy minimization has been selected as the prime objective. The steam levels are optimized considering steam demand at each level, output power generated by turbines, boiler duty, fuel and cold utility requirements as well as capital cost of equipments. The analysis showed that thermoeconomic (exergoeconomic) approach in optimization not only can change the optimum structure of steam levels but also may reduce the total cost of utility system up to 8%. Full article