Profit Improvement Research Articles

Influence of the Incorporation of Recycled Glass Powder on the Fresh State Properties and Compressive, Tensile, and Flexural Strength at 7, 14, and 28 Days of a Sustainable Concrete with f'c = 280 kg/cm², Designed Using the ACI Method, in the City of Lima

Improper solid waste management in Lima, particularly glass, leads to severe environmental, social, and public health problems. The low recycling rate and waste accumulation contaminate soils and groundwater, impacting long-term quality of life. This research aims to evaluate the inclusion of residual glass powder (RGP) in concrete to enhance the sustainability of concrete design, focusing on San Juan de Lurigancho, where the highest amount of waste per person in Lima is generated. The proposed solution involves developing a waterproof concrete design by incorporating residual glass powder (RGP). This approach includes replacing 5%, 10%, and 15% of the cement in the mix to achieve a strength of 280 kg/cm², thereby reducing pollution from glass waste and CO2 emissions. Fresh concrete properties were evaluated and found to improve flow and temperature. The slump of fresh concrete increased gradually with the percentage of residual glass powder (RGP), reaching up to 16.5%. Regarding the properties in the hardened state, in terms of strength, replacing 15% of the cement with RGP resulted in a 2.57% increase in compressive strength. The tensile strength at 28 days increased by 21.53% and 16.8% when replacing 10% and 15% of the cement, respectively. However, replacing 15% of the cement resulted in a 0.4% decrease in flexural strength, while a 10% replacement resulted in a 1.44% increase. On the other hand, replacing cement with 15% RGP reduced CO2 emissions to 53.79 kg/m³. Additionally, a higher percentage of RGP in the concrete allows for cost savings of up to 12.2%, demonstrating a progressive reduction. From the analyses, it was found that the mix including 10% RGP stands out as the optimal option. It shows significant improvements in strength and profitability, reducing production costs by 3.4% and CO2 emissions by 10.83%. This design achieves an ideal balance between performance, cost, and environmental sustainability.

Decision‐making and coordination of a three‐tier fresh agricultural product supply chain considering dynamic freshness‐keeping effort

AbstractThe freshness‐keeping of agricultural products is an essential issue that affects business development, food safety, and human health. Due to the structural characteristics of the supply chain, keeping the freshness of agricultural products involves different entities and multiple links, which is a long‐term strategic issue requiring significant investment. Given the perishability of agricultural products, the aging of preservation facilities, or the decline of technology, it is critical to consider the multitier freshness‐keeping strategy from a dynamic perspective. Therefore, this paper studies dynamic freshness‐keeping and coordination of a multitier agricultural product supply chain. We first construct a differential equation considering the three‐tier freshness‐keeping efforts. Then, we compare the optimal freshness‐keeping efforts, retail price, and system profit between the decentralized and centralized decision‐making models. Finally, two contracts based on cost‐sharing and secondary transfer payment are designed to coordinate the decentralized decision‐making model. Results show that (i) as the decision sequence moves backward, freshness‐keeping effort decreases at each tier for the same freshness‐keeping efficiency; (ii) adopting the centralized decision‐making model offers several advantages, including well‐balanced freshness‐keeping efforts across multiple tiers, a lower retail price, and higher system profit; and (iii) under a specified payment range, the “freshness‐keeping cost‐sharing‐two‐part fee” contract motivates entities to increase freshness‐keeping efforts and realizes individual and system‐wide profit improvements.

Dynamic Pricing Model for E-commerce Products Based on DDQN

This' paper addresses the challenges of intense price competition, price elasticity, and significant demand fluctuations in e-commerce product markets by adopting a dynamic pricing approach. Focusing on a product from the JD.com e-commerce platform, historical data spanning the past three years are analyzed, considering factors such as shipping costs, product inventory, product costs, and the impact of holidays. The study employs the Double Deep Q-Network (DDQN) for dynamic pricing optimization of the product, and compares its performance with the Deep Q-Network (DQN) model. The results indicate that both the DQN algorithm and DDQN algorithm lead to varying degrees of profit improvement for the dynamic pricing of products. Specifically, the pricing profit with the DQN algorithm increased by an average of 1.925% compared with the original pricing profit, while the pricing profit with the DDQN algorithm increased by an average of 11.975% compared with the original pricing profit. These findings demonstrate practical significance.

Analisis Laporan Keuangan Dalam Menilai Kinerja Keuangan Pada PT. Artha Lestari Engineering

Nindy Pertiwi, 2024. "Analysis of Financial Statements as a Basis for Evaluating Financial Performance: A Case Study of PT. Artha Lestari Engineering." Supervised by Johanis dan Meldilians NJ Lenas. This study aims to analyze financial statements to assess the financial performance of PT. Artha Lestari Engineering. Data were collected from PT. Artha Lestari Engineering's financial statements for the period 2019-2023 using a financial ratio analysis approach. The results of the ratio analysis reveal that the liquidity ratio initially experienced a significant decline but improved in the final year. Although the liquidity ratio remains high, the initial decline indicates challenges in liquidity management. The solvency ratios remain low, indicating a reliance on equity rather than debt, with fluctuations in these ratios reflecting the stability of this reliance. Activity ratios show stability with slight decreases, while Inventory Turnover and Receivable Turnover experienced fluctuations and declines, respectively. Profitability performance increased significantly, reflecting improvements in operational efficiency and profitability during the study period.

Clinical outcomes and profitability following rural hospital mergersand acquisitions.

As US hospital markets become increasingly consolidated, empirical evidence is needed on the clinical and financial impacts of mergers on care provided by rural hospitals. We identified characteristics of rural hospitals that underwent mergers or acquisitions and examined changes in profitability, clinical outcomes, and patient experience at acquired versus non-acquired rural hospitals. We identified 145 rural US hospitals that underwent merger or acquisition between 2009 and 2014 and 906 rural non-acquired control hospitals. For each acquisition year, we used a difference-in-differences design to compare that year's acquired hospitals to a randomly chosen set of non-acquired controls. Adjusted linear regression models were used to assess the relationship between acquisition and changes in profitability, patient experience, and clinical outcomes. Compared to non-acquired hospitals, acquired hospitals were more likely to be for-profit (18.6%vs. 4.6%, p<0.001) and tended to have lower total margins (-1.1%vs. 1.2%; p<0.05) despite higher average clinical volumes. Changes in acquired hospitals' total margins, patient satisfaction, and risk-adjusted 30-day mortality rates were not different than changes among control hospitals. However, acquisition was associated with lower improvement in30-day risk-adjusted readmission rates (-0.58 percentage point [p.p.] difference-in-differences, 95% confidence interval -0.88 to -0.28 p.p., p<0.001). Overall, mergers or acquisitions of rural hospitals were not associated with significant improvements in profitability, clinical outcomes, or patient experience. Policymakers may need to closely monitor rural hospital mergers in order to balance preserving access for rural patients with the consequences of health care consolidation.

Rediscovering paternalistic leadership: a powerful engine for startup

ABSTRACT This study investigates the effects of paternalistic leadership, a predominant leadership style in Confucian-influenced East Asia, on the growth and innovation of start-up companies, particularly within the information technology sector. Contrary to the prevailing belief that paternalistic leadership stifles innovation, our findings reveal that this leadership style can significantly enhance business performance. This study identifies key mechanisms, such as fostering employee loyalty, improving decision-making processes, and encouraging proactive behaviours, that drive growth under paternalistic leadership. Empirical evidence shows that employees under such leadership exhibit entrepreneurial behaviours marked by innovation, risk-taking, and initiative, leading to measurable improvements in profitability, customer satisfaction, and market share. These results underscore the role of paternalistic leadership in accelerating the success of East Asian start-ups and provide valuable insights for organisations seeking to balance cultural leadership styles with the demands for innovation.

IMPROVING SME PROFITABILITY: A BUSINESS ECOSYSTEM ANALYSIS PERSPECTIVE

This study aims to determine the influence of the business ecosystem on the improvement of profitability of Small and Medium Enterprises (SMEs) as a form of business success. The method used is descriptive and verificative with several approaches. The unit of analysis in this study is small businesses, with the unit of observation being business owners. Data processing method utilizes Structural Equation Modeling (SEM), and the data used is primary data. The results indicate the presence of a business ecosystem's influence on the increase in profitability, which impacts business success. The research findings demonstrate that a good business ecosystem can affect the enhancement of profitability. This study is expected to be valid for business practitioners and stakeholders in making decisions to achieve long-term business success.

Pengelolaan Sumber Daya pada UMKM ADK Terbang Menggunakan Metode American Productivity Center untuk Meningkatkan Produktivitas dan Profitabilitas

Productivity is the key for business actors to compete in a highly competitive market. Productivity is closely related to the effectiveness and efficiency of using resources in producing output. This research focuses on Flying ADK MSMEs, which shows a significant increase in production in three periods (May 2023 – March 2024). Production achievement that continues to approach the set targets shows great potential for growth, but requires further strategic interventions to improve efficiency and competitiveness. The purpose of the study is to analyze the level of productivity, profitability, and price improvement factors in ADK Fly MSMEs and provide recommendations for improvement. The method used is the American Productivity Center (APC), to measure productivity, profitability, and price improvement factors through optimizing the use of resources such as labor, raw materials, energy, and capital. The measurement results showed an increase in productivity of 1.4% in the second period and 0.4% in the third period. Profitability also increased by 1.4% and 0.4% in the same period. The price improvement index increased every year, reaching 0.97% in the second period and 0.93% in the third period, which had a positive impact on the company's productivity and profitability. This increase was analyzed in detail using a fishbone diagram. The results of this study provide recommendations that can be used by business actors to optimize resources and improve operational efficiency.

All that Glitters is Not Gold! Could M&amp;As Post‐Bank Reforms be Just a Tool for Balance Sheet Embellishment?

AbstractThis study investigates whether the surge of mergers and acquisitions (M&amp;As) that occurred in Italy after the enactment, in 2016, of a new reform of credit cooperative banks (CCBs) ultimately improved their performance. Worldwide, CCBs have proved to play a crucial role in spurring local economic development. With the adoption of a dataset composed of 594 Italian banks and 3933 bank‐year observations from 2008 to 2020, our results show a positive and significant impact of the 2016 reform on M&amp;As among CCBs. However, contrary to the expectations of regulators, our results highlight a puzzling deterioration in bank stability of the CCBs involved in M&amp;As, with no relevant improvement in capitalization and profitability, reinforcing the view that bigger is not always better, at least in the context of CCBs. Our evidence sheds light on the perils underlying a massive consolidation process of local banking industries, calling for a regulatory recalibration and further research investigating the impact of different growth models capable of preserving the diversity and unique characteristics of banks, rather than pursuing a ‘one‐size‐fits‐all’ model.

Optimization of reversible solid oxide cell system capacity combined with an offshore wind farm for hydrogen production and energy storage using the PyPSA power system modelling tool

AbstractEight scenarios where high efficiency reversible solid oxide cells (rSOC) are combined with an offshore wind farm are identified. Thanks to the PyPSA power system modelling tool combined with a sensitivity study, optimized rSOC system capacities, hydrogen storage capacities, and subsea cable connection capacities are investigated under various combinations of rSOC system capital cost, prices paid for hydrogen, and electricity prices, which give indications on the most profitable scenario for offshore hydrogen production from a 600 MW wind farm situated 60 km from shore. Low electricity prices (yearly average 45 £/MWh) combined with mild fluctuations (standard deviation 6 or 13 £/MWh) call for dedicated hydrogen production when the hydrogen price exceeds 4 £/kg. High electricity prices (yearly average 118 or 204 £/MWh), combined with extreme fluctuations (standard deviation between 73 and 110 £/MWh), make a reversible system economically profitable. The amount of hydrogen which is recommended to be reconverted into electricity depends on the price paid for hydrogen. Comparison of the optimized cases to the default case of a wind farm without hydrogen production improved profit by at least 3% and up to 908%. Comparison to the default case of dedicated hydrogen production, showed that in the case of low hydrogen prices, an unprofitable scenario can be made profitable, and improvement of profit in the case of a profitable default case starts at 4% and reaches numbers as high as 324%.

Implementing data-driven financial management systems in SMEs: A case review approach

The adoption of data-driven financial management systems has become increasingly vital for the growth and sustainability of small and medium-sized enterprises (SMEs). This review explores the implementation of such systems through a case review approach, analyzing their impact on financial decision-making, operational efficiency, and overall business performance. SMEs often face challenges in managing their financial processes due to limited resources, inefficient manual methods, and a lack of real-time data insights. Data-driven financial systems, leveraging automation, artificial intelligence (AI), and analytics, offer a solution by streamlining these processes, enhancing accuracy, and improving decision-making. The review examines three SMEs from different sectors manufacturing, retail, and services that have implemented data-driven financial systems. Through qualitative interviews, financial data analysis, and performance assessments before and after system implementation, the research identifies key improvements in cash flow management, profitability, and financial reporting. Each case highlights how automation and real-time data access have led to more strategic financial decisions, reduced costs, and operational efficiency. The findings suggest that data-driven financial systems not only increase financial transparency but also provide a competitive advantage by enabling SMEs to make informed decisions quickly. However, the review also identifies barriers to implementation, such as technical expertise, costs, and employee training, emphasizing the need for tailored solutions based on company size and sector. The review concludes by discussing future trends in financial technology adoption among SMEs and offers recommendations for facilitating successful integration. This research contributes to the understanding of how data-driven financial management can drive sustainable growth in SMEs. Keywords: Data-Driven, Financial Management, SMEs, Review.

Scheduling and assessment of multi-area virtual power plant including flexible resources using swarm intelligence technique

A virtual power plant (VPP) makes the distributed energy resources (DERs) visible to support grid services, promoting clean energy use by offering an alternative to reduce reliance on conventional sources. This paper proposes optimized operation and scheduling of VPP by forming a group of flexible resources that includes renewables i.e., solar, wind power, fuel cell, and co-generation units along with storage facilities to form a holistic network in a multi-area interconnected system framework. Initially, the scheduling is performed for a single area system in which a comparison is made with the available work relevant to the proposed formulation. In addition, the scheduling is further extended to the proposed multi-area based virtual power plant (MAVPP) performed on a day-ahead (DA) basis and the target objective(s) i.e., net profit and emission are optimized. Furthermore, a recently developed marine predator optimization algorithm (MPOA) is employed to solve the proposed problem formulation and the results are compared and discussed extensively with conventional techniques. Also, the analysis pertaining to MAVPP is carried out which is beneficial in terms of economic and environmental perspective. The result reveals that the maximum value of net profit for MAVPP is converging to an optimum value of 59,351.88 $ followed by the attained value of minimum emission of 51,700.73 Kg by consuming an elapsed time of 92.96 and 104.76 s., respectively in 200 iterations. The outcomes are promising and upon comparison with the available literature work, the superiority of the selected technique is evident in terms of computational time, improvement of net profit and reduction in emission followed by the ease of convergence behaviour in fewer iterations.

Synergistic enhancement for energy-saving, emission reduction and profit improvement in iron and steel manufacturing system: Strategies for parameter regulation and technologies integration

The steel industry, characterized by high energy consumption and carbon emission, poses a significant threat to global energy and environmental security. In response to the energy conservation and dual-carbon targets, the steel industry must urgently find sustainable pathways for transformation and development. Steel production structure optimization and the application of cutting-edge technologies have been proven to be highly effective. However, the complexity and variability of actual production conditions highlight the absence of a methodology capable of adapting to real production scenarios, elucidating influencing principles across multiple factors, analyzing synergistic mechanisms of multiple indicators, and proposing collaborative control strategies. Furthermore, the potential for technology applications that are closely integrated with the company’s resource endowment remains uncertain, leading to an unclear overall strategy for energy saving and carbon reduction. This study develops a multi-scale optimization and evaluation model for ISMP, incorporating interconnected and matching processes, as well as nested multi-indicators, in response to the context. Subsequently, the disturbance mechanisms of various factors are accurately identified and a multi-indicator synergistic control strategy and framework are proposed. Following optimization, the exergy loss, energy consumption, carbon emission intensity, cost, and pollutant emissions of ISMP per tonne of steel are reduced by 1418.70 MJ, 42.93 kgce, 154.79 kg, 171.21 CNY, and 0.0168 kg, respectively. Additionally, measures such as reducing moisture content in coking coal can effectively regulate multiple indicators. Based on the proposed sensitivity quantification method, the temperature of hot blast is identified as the most effective controllable factor. Technologies like hydrogen-rich fuel injection, integrated waste heat recovery, and solar photovoltaic & energy storage have shown favorable prospects, according to analysis conducted from various angles regarding economic viability and potential for energy-saving and carbon reduction. However, the application of aforementioned technologies may be limited by financial consideration, necessitating cautious and judicious investment choices.

Effect of production scale on the techno-economic viability and environmental life cycle analysis of lactic acid production in a sugarcane biorefinery

Biorefineries are vital for advancing circular economy and reducing the effects of products fossil fuels derived products on the environment. However, biorefineries often operate at smaller production scales than fossil refineries due to limited feedstock availability, which may be addressed by centralised processing with multiple feedstock sources. Lactic acid (LA) has several industrial applications and is a platform chemical used to produce products like acrylic acid and propylene glycol. The economic and environmental performances of an integrated biorefinery at different production scales, through different levels of feedstock centralization, were investigated, to determine the optimal scale for sugarcane-based LA production. Decreasing values for the minimum selling price (MSP; 1312–849 US$.t−1) and increasing internal rates of return (IRRs; 31–64 %) were observed with increasing conversion scales of sugarcane A-molasses. The MSPs decrease from 90 to 450 ktLA.y−1 with small improvements in profitability beyond 450 ktLA.y−1, as confirmed by stochastic financial uncertainty analysis. In the environmental assessment, a linear increase was observed across all impact categories, mainly due to the added fuel consumption for feedstock transportation. LA production had a GWP100 range of 0.87–0.95 kg CO2-eq.kgLA−1 and an abiotic depletion potential of 12–13 MJ.kgLA−1 which increased as the scale increased. In the ozone depletion category emissions of 9.96×10−8-1.13×10−7 kg CFC-11 eq.kgLA−1 comparable to other studies available in literature. Similarly, emission ranges of 1.11–1.17, 0.63–0.66, and 1581–1641 kg 1,4-DB eq.kgLA−1 were obtained in the human toxicity, freshwater and marine aquatic ecotoxicity categories as the scale increased. Environmentally the smallest scale at which transportation of feedstock was avoided (i.e. 90 ktLA.y−1) is preferred as opposed to 450 ktLA.y−1 for economic performance.

A Meta-analysis of the Profit-Sharing Practices among Engineering, Construction, and Related Firms: Strategy to Increase Company Revenue

This paper explores the impact of profit sharing on employee motivation, productivity, and company performance in the engineering and construction industry. Through a meta-analysis of recent studies, it identifies key factors that influence the effectiveness of profit-sharing programs. The findings reveal that profit sharing significantly boosts employee motivation and productivity, with increases of 15% and 12% respectively. Moreover, job satisfaction rates are 20% higher among employees participating in profit-sharing programs. However, there is a notable preference split, with 60% of employees favoring profit sharing for its potential higher earnings, while 40% prefer fixed salary increases for stability. The research further indicates that frequent and actively managed profit-sharing distributions, such as quarterly payouts, lead to better financial performance, with a 10% increase in overall performance and a 5% improvement in profitability. Project-based profit sharing in the construction sector is particularly effective, resulting in a 25% increase in project completion rates and a 15% reduction in project costs. Additionally, profit sharing is more effective in unionized organizations, with an 18% increase in effectiveness, and mandatory profit-sharing frameworks enhance worker satisfaction and productivity. Based on these findings, the paper recommends developing tailored profit-sharing strategies that cater to different employee preferences, implementing frequent and active management of profit-sharing distributions, adopting project-based profit sharing in project-centric industries, engaging with unions for fair terms, advocating for supportive regulatory frameworks, and continuously monitoring and evaluating the effectiveness of these programs. By adopting these strategies, engineering and construction firms can enhance employee motivation, improve productivity, and achieve better financial performance, driving organizational success.

Different Types of Milk Flow Curves and Factors Affecting Milkability in Buffalo Species

Buffaloes are characterized by longer teats and teat canals and stronger muscular resistance of the teat wall than cattle; it is necessary to have a high vacuum level to open the teat canal and begin milk ejection. In buffalo milking management, milk yield, and flow profiles are essential parameters to record and evaluate. The milking machine is a critical point, and the characteristics of the milking vacuum and the pulsation rate are closely related to milk flow observations. In Italy, the most used vacuum levels are 44-46 kPa (range 40-53 kPa). The data on the milkability traits of the Mediterranean Italian breed made it possible to classify eight different types of milk flow curves due to anatomical, physiological, and management differences. This study aims to evaluate the main factors influencing milkability in dairy buffaloes. The results suggest the detachment of the milking cluster to reduce the decreasing and blind phases with the following advantages: reduction of the total milking time and consequently of the worker's time, improvement of the farmer's profitability and milk quality through decreasing the incidence of mastitis. Milk ability is influenced by physiological, sanitary, management, and genetic factors. In Mediterranean Italian buffaloes milked with the Automatic Milking System (AMS), a considerable variation in milk ejection and, consequently, in the milk flow curve was found compared to the conventional one, with better pre-stimulation, independent milk ejection for each teat, optimal milking of all quarters. In conclusion, continuous milkability monitoring will help optimize milking practices by reducing labor time and increasing farmers’ income through better milk quality. In addition, the identification of buffaloes with desirable types of milk flow curves could be helpful for buffalo breeders’ associations to address farmer management and to define potential new breeding objectives.

Digital Twins in 3D Printing Processes Using Artificial Intelligence

Digital twins (DTs) provide accurate, data-driven, real-time modeling to create a digital representation of the physical world. The integration of new technologies, such as virtual/mixed reality, artificial intelligence, and DTs, enables modeling and research into ways to achieve better sustainability, greater efficiency, and improved safety in Industry 4.0/5.0 technologies. This paper discusses concepts, limitations, future trends, and potential research directions to provide the infrastructure and underlying intelligence for large-scale semi-automated DT building environments. Grouping these technologies along these lines allows for a better consideration of their individual risk factors and use of available data, resulting in an approach to generate holistic virtual representations (DTs) to facilitate predictive analyses in industrial practices. Artificial intelligence-based DTs are becoming a new tool for monitoring, simulating, and optimizing systems, and the widespread implementation and mastery of this technology will lead to significant improvements in performance, reliability, and profitability. Despite advances, the aforementioned technology still requires research, improvement, and investment. This article’s contribution is a concept that, if adopted instead of the traditional approach, can become standard practice rather than an advanced operation and can accelerate this development.

Remanufacturing Closed-Loop Supply Chain Contract Coordination Considering Quality Control

The quality control of remanufactured products in a closed-loop supply chain (CLSC) can significantly influence consumers’ decision-making, and the contract coordination of CLSC has also become a research hotspot. This paper explores the quality control problem in a three-level remanufacturing CLSC consisting of a remanufacturer, a retailer, and a recycler by constructing a system dynamics (SD) model, which contains two contract schemes: quality control contract and quality control–revenue-sharing contract. Subsequently, the proposed SD model is analyzed using various schemes. The findings suggest that without mandatory contracts, CLSC members are frequently unable to fulfill their quality improvement commitments. Among them, recyclers are less likely to improve quality and more prone to breaking promises. The quality control problem in CLSC can be addressed through contract coordination, and the quality control contract scheme can avoid non-compliance with quality improvement commitments. The application of the quality control–revenue-sharing combination contract scheme not only resolves the quality control issue but also promotes profit improvement in the CLSC.

Mathematical Model for Optimal Agri-Food Industry Residual Streams Flow Management: A Valorization Decision Support Tool

We present a mathematical model for agri-food industry residual streams flow management, which serves as a decision support tool for optimizing their valorization. The aim is to determine, under a cost-benefit analysis approach, the best strategy at a global level. The proposed mathematical model provides the optimal valorization scenario, namely the set of routes followed by agri-food industry residual streams that maximizes the total profit obtained. The model takes into account the complete stoichiometry of the residual stream at each step of the valorization route. Furthermore, the model allows for the calculations of different scenarios to support decision-making. The proposed approach is illustrated through a case study using a real-case network of a region. The case study bears evidence that the use of the model can lead to significant profit increases compared to those obtained with current practices. Moreover, notable profit improvements are obtained in the case study if the selling price of all the value-added products considered increases or if the processing cost of the animal feed producer decreases. Therefore, our model enables the detection of key factors that influence the optimal strategy, making it a powerful decision-support tool for optimizing the valorization of agri-food industry residual streams.

La administración sanitaria privada en España: análisis de sus resultados desde 2015 al 2021.

This study details the economic progression of the private healthcare sector in Spain from 2015 to 2021,focusing on the financial statements of the main entities. Using a quantitative approach, data from the SpanishMercantile Register was examined, applying ratio and trend analysis. The results highlight a notable improve-ment in financial profitability and the soundness of the capital structure, evidencing a reduction in long-termindebtedness. The research highlights the predominance of the Quirónsalud group, which demonstrateda substantial increase in equity and achieved outstanding financial profitability. The profitability of thecompanies in the sector is observed to have evolved positively, standing out for their ability to adapt andprosper even in the context of the pandemic. The conclusion emphasises the favourable economic evolutionof the sector, highlighting the improvements in profitability and financial structure of the companies analysed.