Domestic Product Research Articles

Vectors for improving development strategies of Russian enterprises in the context of prerequisites for transformation of the Russian economy

The article provides an analysis of changes in trends in the Russian economy based on macroeconomic indicators (gross domestic product per capita, inflation rate, unemployment rate). The key factors are the historically low unemployment rate (due to demographic trends in society) and the growing number of individual accounts on the Moscow Exchange. These factors force Russian enterprises and companies to change the extensive type of economic growth to the intensive one. The purpose of the study is to highlight main trends of the changes in the economy (on the basis of the analysis of macroeconomic indicators) and possible options for responding to them for domestic enterprises. The work used universal and general scientific methods of cognition, such as dialectical, analytical, and statistical methods. The result of the analysis of the Russian macroeconomic indicators is presented, basic trends that can have a significant impact on the strategies of enterprise development are identified. It is proposed to use elements of the ESG (environmental, social, governance) approach or process-flow model as ways to respond to them. The main tasks that enterprises face are outlined along with the criteria for choosing the direction of improvement.

Обеспечение энергетической безопасности на основе развития внутреннего производства продуктов переработки природного газа

The article presents the results of a study of energy security processes based on the development of domestic production of natural gas processing products. The structure of the global ammonia market has been studied. The possibilities of the Russian Federation for the development of domestic processing of natural gas through the use of volumes previously exported to Europe have been identified.

Economic freedom and foreign direct investment in Brazil: an empirical analysis of determinants and policy implications

PurposeThis paper aims to study the impact of economic freedom and some key macroeconomic variables on the foreign direct investment (FDI) inflow in Brazil.Design/methodology/approachAn econometric model is developed that includes FDI inflow as the dependent variable and macroeconomic variables such as the output, current account balance, the real exchange rate, openness and economic freedom as explanatory variables. Annual time series data from 1995 to 2022 is used. Before carrying out the estimation, the time series properties of the data are diagnosed using unit root tests and cointegration tests. Since the data series were found to be stationary in the first difference form and the variables in the model were cointegrated, an error correction model is developed and estimated.FindingsThe findings demonstrate that the size of the market (gross domestic product), current account balance and the economic freedom index significantly influence FDI inflow to Brazil. Although the signs of openness and the real exchange rate align with theoretical expectations, they do not attain statistical significance.Originality/valueTo the best of the authors’ knowledge, this is the first formal study on the impact of economic freedom on the FDI inflow in Brazil. The finding of this study adds value to the understanding of FDI dynamics in Brazil, highlighting the critical role of economic freedom and market size in attracting foreign investment.

Analyzing Primary Sector Selection for Economic Activity in Romania: An Interval-Valued Fuzzy Multi-Criteria Approach

This study presents an in-depth analysis of the selection process for primary sectors impacting the economic activity in Romania, employing an interval-valued fuzzy (IVF) approach combined with multi-criteria decision-making (MCDM) methodologies. This research aims to identify eight key criteria influencing the selection of Romanian primary sectors, including technology adaptation, infrastructure development and investment, gross domestic product (GDP), sustainability, employment generation, market demand, risk management and government policies. The current analysis evaluates eight primary sector performances against these eight criteria through the application of three MCDM methods, namely, Simple Additive Weighting (SAW), Weighted Product Model (WPM), and Weighted Aggregated Sum Product Assessment (WASPAS). Ten economic experts comprising a committee have been invited to provide their views on the criteria’s importance and the alternatives’ performance. Based on the decision-maker’s qualitative judgement, GDP acquires the highest weightage, followed by environmental impact and sustainability, thus indicating the most critical factors among the group. The IVF-MCDM hybrid model indicates the energy sector as Romanian primary sector with the most potential, followed by the agriculture and forestry sector among the list of eight alternatives. It also explores the robustness of results by considering sensitivity analysis and the potential impacts of political and international factors, such as pandemics or armed conflicts, on sector selection. The findings indicate consistency in sector rankings across the different methodologies employed, underscoring the importance of methodological choice and criteria weighting. Additionally, this study sheds light on the potential influence of political and international dynamics on sector prioritization, emphasizing the need for comprehensive decision-making frameworks in economic planning processes.

Forecasting healthcare service volumes with machine learning algorithms

AbstractAs an efficacious solution to remedying the imbalance of medical resources, the online medical platform has burgeoned expeditiously. Apt allotment of medical resources on the medical platform can facilitate patients in reasonably selecting physicians and time slots, coordinating doctors' clinical arrangements, and generating precise projections of medical platform service volume to enhance patient satisfaction and alleviate physicians' workload. To this end, grounded in the data‐driven method, this paper assembles an exhaustive feature set encompassing hospital features, physician features, and patient features. Through feature selection, appropriate features are screened, and machine learning algorithms are leveraged to accurately forecast doctors' online consultation volume. Subsequently, to glean the influence relationship between online medical services and offline medical services, this paper introduces features of offline medical services such as hospital registration volume and regional gross domestic product (GDP) to solve the prediction of offline medical service volume using online medical information. The findings signify that online data feature prediction can pinpoint superior machine learning models for online medical platform service volume (with the optimal accuracy up to 96.89%). Online features exert a positive effect on predicting offline medical service volume, but the accuracy declines to some degree (the optimal accuracy is 73%). Physicians with favorable reputations on the online platform are more susceptible to attain higher offline appointment volumes when online consultation volume is a vital feature impacting offline appointment volume.

Determining the Future Direction and Amount of Tax Revenue in Indonesia Using an <i>Error Correction Model </i>(ECM)

The characteristics of how tax revenues, as well as the macroeconomic factors that are expected to influence and determine tax revenues, develop have become the basic macroeconomic assumptions by the government in compiling various components of the posture of the state revenue and expenditure budget to maintain and increase the expected economic growth. To understand the evolution of tax revenues and the impacts of these variables, it is important to investigate the relationship between tax revenues and specific macroeconomic variables. This study aims to identify the effect of macroeconomic variables on Indonesian tax revenues in the long and short term using multiple regression analysis in an error correction model (ECM). The macroeconomic conditions and variables used in this study are gross domestic product (GDP), inflation, interest rates, and exchange rates. This study employed the time-series data from 2000–2019. The ECM method was conducted in the following stages: stationarity test, cointegration test, and ECM regression test. The ECM model is declared valid, if the cointegrated variables are supported by a significant and negative ECT coefficient value. The statistical analysis, i.e. t-statistic, the F-statistic, and the coefficient of determination, were used to evaluate the significance of the ECM model. The results showed that among the four of macroeconomic variables used in this study, GDP has the highest significant effect on the tax revenue. GDP has a highly positive and considerable impact on tax revenue. The increasing of GDP growth is in line with the realization of tax revenue. A strong positive long-term (t-statistic = 13.94075*, P-value = 0.0000) and short-term (t-statistic = 5.515026*, P-value = 0.0001) association is also observed between inflation and tax revenue. Inflation has a favorable and considerable impact on tax income either in long (t-statistic = 2.298586**, P-value= 0.0363) or short term (t-statistic = 2.515695**, P-value = 0.0258). On the other hand, Bank Indonesia interest rate has a negative insignificant effect (t-statistic = −1.542970ᵈ, P-value = 0.1437) in the long run on tax revenue. However, it has a negative significant effect (t-statistic = −2.699231**, P-value = 0.0182) in short-term tax revenue. A rise in interest rates results in the lowered tax revenues due to the reduction of public consumption patterns, and a decrease in public consumption. The exchange rate has a negative negligible connection in long term (t-statistic = −1.045768ᵈ, P-value = 0.3122), as well as in short term (t-statistic = 1.250076ᵈ, P-value = 0.2333) with tax revenue, meaning that tax revenue is not significantly affected by changes in exchange rate. In conclusion, total tax revenues and the four macroeconomic variables have a significant long- and short-term association according to the ECM analysis with an adjusted R² value of 0.985866 and 0.792880, respectively. Changes in future tax revenues are largely determined by the stability of macroeconomic variables. Therefore, it is highly recommended that the government maintain the stability of macroeconomic variables, especially GDP, because GDP has a dominant influence on tax revenues in the long and short term so that the target of tax revenues can be achieved. The ECM analysis applied in this study can explain the effect of changes in macroeconomic variables on the tax revenue in the short and long term; so that the future direction and amount of tax revenue can be determined in preparing the State Budget and projecting the expected level of economic activity growth in a nation.

Macroeconomic Dynamics and Profitability of Insurance Firms Listed at Nairobi Securities Exchange, Kenya

Kenya’s insurance industry has been growing steadily since 2013, with premium revenue and capital investment increasing. However, Return on Assets has declined over the past four years and reached an all-time low in 2022 compared to the previous five years which was partly attributed to the reforms introduced to cater the impact of Corona virus pandemic on and the need to close infrastructure gaps. As a result, as gross domestic product grows, firm deposits and loans rise along with interest income and loan losses. This study focused on understanding how macroeconomic dynamics affect the profitability of insurance companies listed on NSE in Kenya. It particularly looked into how changes in exchange rates, interest rates, and the overall price rise in the economy (inflation) influence these companies' profits. The study was guided by the theoretical frameworks of purchasing power parity, deflation, the balance of payment, the classical theory of interest, and the balance scorecard model. The study adopted an explanatory research design and targeted the six insurance firms listed on the NSE. The secondary data collection for this study involved the utilization of secondary data sheets. Data was obtained from the official audited financial statements of the insurance firms for the fiscal years 2016 through 2022. Data analysis involved both descriptive and inferential analysis. Inferential analysis incorporated both correlation analysis and panel regression analysis. The study found that key macroeconomic dynamics had significant impact on the profits of insurance companies listed on the NSE, explaining 57.71% of the changes in profits (R-squared = 0.5771). It discovered that while changes in the exchange rate do not significantly affect profits (β = 0.0761, p = 0.5358), higher interest rates lead to higher profits (β = 2.1647, p = 0.0233), and inflation negatively impacts profits (β = -0.3447, p = 0.0011). The study's validity is supported by strong statistical evidence (F-statistic = 21.0100, p-value = 0.0000). It suggests that insurance companies in Kenya should focus on managing risks related to economic changes to improve their financial performance. This research adds to the understanding of how macroeconomic dynamics affect the profitability of insurance firms in the context of the NSE. Keywords: Exchange rates, insurance profitability, interest rates, inflation impact, Nairobi Securities Exchange

Spanish GDP short-term point and density forecasting using a mixed-frequency dynamic factor model

AbstractWe have assessed the effect of data releases when constructing short-term point and density forecasts of the Spanish gross domestic product growth. For this purpose, we considered a real-forecasting exercise in which we defined several pseudo-data vintages that had a mixture of monthly and quarterly frequencies and were unbalanced towards the end of the sample. We implemented a mixed-frequency dynamic factor model to deal with data features and to produce gross domestic product forecasts. We evaluated the predictive content of data releases from point and density forecast perspectives, the latter aspect of the analysis being previously unexplored in the literature producing Spanish gross domestic product short-term forecasts. We observed significant improvements in point forecasts as information is released throughout the quarter, confirming existing results. Additionally, our findings indicated substantial enhancements in the accuracy of density forecasts as new data releases materialized.

Health and economic burden of insufficient physical activity in Saudi Arabia.

Insufficient physical activity (PA) was estimated to cause 4.8% of deaths and 2.6% of disability-adjusted life-years (DALYs) due to noncommunicable diseases in Saudi Arabia in 2019. While Saudi Arabia is already achieving great improvements, we predict the health and economic burden of insufficient PA up to 2040 to present a case for policy makers to invest more in the uptake of PA. Using a population health model to estimate avoidable health loss, we identified four causes of health loss related to low PA (cardiovascular diseases, diabetes, breast cancer, and colorectal cancer) and estimated the deaths and DALYs from these causes. We projected the expected disease burden until 2040 under alternative assumptions about future PA levels and trends by using three health scenarios: baseline (no change in 2019 PA levels), intervention (81% of the population achieving sufficient PA levels), and ideal (65% of population: moderate PA, 30%: high PA, and 5%: inactive). We applied an "intrinsic value" approach to estimate the economic impact of each scenario. Overall, we estimate that between 2023 and 2040, about 80,000 to 110,000 deaths from all causes and 2.0 million to 2.9 million DALYs could be avoided by increasing PA levels in Saudi Arabia. The average annual economic loss from insufficient PA is valued at 0.49% to 0.68% of the current gross domestic product, with an average of US$5.4 billion to US$7.6 billion annually till 2040. The most avoidable disease burden and economic losses are expected among males and because of ischemic heart disease. This study highlights that low PA levels will have considerable health and economic impacts in Saudi Arabia if people remain inactive and do not start following interventions. There is an urgent need to develop innovative programs and policies to encourage PA among all age and sex groups.

Integration of advanced digital technologies in the hospitality industry: A technological approach towards sustainability

The potential assimilation of Industry 4.0 technologies across diverse sectors unlocks the pathways to achieve sustainability through innovative infrastructure with sustainable approaches. The World Travel & Tourism Council’s (WTTC) 2023 report emphasizes the impact of the hospitality industry contributes $9.5 trillion to the gross domestic product (GDP) and provides a workforce of 320 million globally and also strives towards meeting sustainability. Driven by the facts above, this study conducted a review to explore the potentiality of Industry 4.0 technologies specifically focused on meeting sustainability. Along with the review, the study has proposed a scalable-based architecture with the assimilation of many Industry 4.0 technologies. Further, this study has analyzed the real-world examples of Industry 4.0 technologies adoption in the hospitality industry with an objective of innovation and sustainable practices. Finally, the articles discussed the recommendations that can empower the establishment of resilient infrastructure through Industry 4.0 technologies.

Assessment of Climate Change-Induced Water Scarcity Risk by Using a Coupled System Dynamics and Bayesian Network Modeling Approaches

AbstractThe water scarcity risk induced by climate change is contributing to a sequence of hydrological and socioeconomic impacts. Certain numbers of related impacts are locked in already and are expected to be much greater in the future. So, there is still a lack of understanding of its dynamics, origin, propagation, and the mutual interaction of its drivers. In recent years, several model-based approaches have been introduced to tackle the complexity, dynamics, and uncertainty of water scarcity specifically. However, the coupled modeling while addressing different aspects of the risk of water scarcity under the climate change scenarios has been rarely done. For bridging this gap, in this research, the combination of complementary System Dynamics modeling and Bayesian Network was applied to Qazvin Plain in Iran with five AOGCM models under two Shared Socioeconomic Pathways (SSP) scenarios (126 and 585). Key findings of this research show: 1) Baseline risk assessment indicates a low probability of water scarcity; however, in the future 30-year time horizon with continuous change in hazard, vulnerability, and exposure for SSP126, the risk fell in the extreme category with an average probability of 41%. Under SSP585, the risk varies between extreme and high categories with an average probability of 47%. 2) Economic development, particularly regional gross domestic product (RGDP) in 2045–2054 in SSP585 can diminish the negative projected consequences of climate change and therefore investments in adaptation policies could offset negative consequences, highlighting the role of economic growth in climate resilience. 3) It is projected that crop yield and income will receive the largest negative effects due to cutting back the agriculture area. 4) Considering the interplay of climate change, economic development, and water extraction policies is essential for the design, operation, and management of water-related activities. The proposed integrated methodology provides a comprehensive framework for understanding climate change-induced water scarcity risks, their drivers, and potential consequences. This approach facilitates adaptive decision-making to address the evolving challenges posed by climate change.

Spatial imbalances of the economic development of Ukraine in war conditions: regional dimension

The article analyzes the transformation of the structure of the gross domestic product of Ukraine (by types of economic activity), which took place under the influence of full-scale armed aggression by the Russian Federation. Spatial imbalances in the performance indicators of the construction (in the field of residential and non-residential construction) and transport sectors of the national economy in the regional section are diagnosed. A detailed assessment of the dynamics of the volume of sold products of the Ukrainian processing industry, in particular, the metallurgical industry, was carried out. The vectors were established and the amount of changes in the dynamics of Ukraine's foreign economic operations, which caused a decrease in the ratio of commodity exports to imports, was calculated. The export specialization of the regions of Ukraine by main product groups was determined. Key trends in the formation and development of domestic export potential are outlined.

Transfer payments and carbon reduction in China: The effect of the national comprehensive demonstration city of energy saving and emission reduction fiscal policy

To address climate change and achieve high-quality economic development, China began implementing the Comprehensive Demonstration City of Energy Saving and Emission Reduction Fiscal Policy (ESERFP) in 2011. This policy relies on special transfer payments to increase the integration of various energy conservation and emission reduction fiscal policies, thereby accelerating institutional and mechanism innovation, actively promoting economic structure adjustment and development mode transformation, and achieving energy conservation and emission reduction goals in various regions. This study uses a multi-period difference-in-difference (DID) model to estimate the ESERFP's CO2 emission reduction effect and paths. The findings demonstrate the following: (1) The ESERFP has lessened the CO2 emission intensity of the demonstration city and effectively played a role in reducing CO2 emissions. (2) Mechanism analysis demonstrates that the ESERFP has significantly improved the green travel level of residents in pilot cities and can also reduce cities' total energy consumption. Therefore, the ESERFP can effectively suppress CO2 emissions by improving transportation systems and optimizing energy consumption structures. (3) Further analysis shows that the ESERFP can reduce the CO2 emission scale of the demonstration cities and effectively promote the increase of actual per capita gross domestic product in pilot cities, bringing economic dividends and thus achieving a “win-win” situation of environmental protection and economic growth. (4) Heterogeneity analysis demonstrates that the CO2 emission reduction effect is more significant in non-old industrial-based cities, non-resource-based cities, and urban agglomerations. This study not only evaluates the CO2 reduction effect of the demonstration city but also provides reference significance for the improvement of subsequent environmental regulations. In addition, clarifying the implementation effect of the ESERFP can help alleviate ecological and environmental problems in the process of urban economic development in China and achieve the sustainable development goal of green transformation.

How do digital financial inclusion, ICT diffusion, and education affect energy security risk in top energy-consuming countries?

Energy security has become a crucial issue as the world economy depends more and more on energy supplies. In the context of the top energy-consuming nations, this research examines the connection between digital financial inclusion, information and communication technology (ICT), education, and energy security risk from 2011 to 2022. To that end, the study applies the two-stage least squares and system generalized method of moments estimation techniques. According to our study's findings, digital financial inclusion and associated factors, including automatic teller machines, bank branches, debit cards, and electronic payments, mitigate energy security risks. The energy security risks are also reduced due to ICT, education, gross domestic product, and renewable energy production. However, carbon emissions increase energy security risks. These findings suggest that policymakers in top energy-consuming economies should focus on the digital inclusiveness of the financial sector, ICT diffusion, and human capital to increase the opportunities for investment in the energy sector to mitigate energy security risks.

ICT acceptance, language use and information culture as tools for enhancing information literacy within smallholder maize farmers in Uganda

Purpose This study aims to examine the relationship between tool adoption and information literacy within smallholder farmers (SHFs). Design/methodology/approach A structured questionnaire was used to gather data for this quantitative study from 225 SHFs. Structural equation modelling was done to test the hypotheses. Findings The findings established that tool adoption dimensions (Information and communication technologies (ICT) acceptance, language use and information culture) positively and significantly influenced information literacy. Information culture had the strongest impact. Research limitations/implications The study enriches the situated learning theory (SLT) literature by introducing tool adoption as a predictor of information literacy in a new context of SHFs. Use of tools as independent variables is a positive deviation from previous studies that have used them as mediating variables. Despite the contributions, the cross-sectional design study undermines the ability to solicit more detailed perspectives from the lived in experience of the respondents. Practical implications Managers should promote usage of context-specific tools like local radio stations and mobile phones, but also use language tailored to farmer contexts when disseminating information. Policymakers should leverage on social and cultural settings when designing information interventions. Social implications The study highlights critical factors that significantly promote information use for improved productivity for SHFs, cumulatively increasing the country’s gross domestic product (GDP). Socially, findings may reduce on their poverty levels of farmers. Originality/value This study offers a novel perspective in information literacy domain by using the SLT to delineate contextual tools that are paramount in predicting of information literacy in an under research informal context of SHFs.

Exploring the Relationship Between Manpower and Economic Indicator in Indonesia: A 30-Year Analysis

This research investigates the relationship between manpower and economic Indicator in Indonesia over a 30-year period from 1992 to 2022. Specifically, it examines the influence of Gross Domestic Product (GDP), Education, Age, Final Consumption Expenditure, Foreign Direct Investment, and Inflation on Wages, alongside the effects of employment and economic growth instruments. This study using Error Correction Model (ECM) along with unit root test, cointegration test, and Autoregressive Distributed Lag (ARDL) dependent test approach with the result that all of variables are stationary at the 1st difference level, this study aims to see the long-run and to know short-run relationship among the variables. The findings reveal a significant long-term relationship between wages and factors such as GDP (0.0000), higher education level (0.0006), secondary education level (0.0009) government spending (0.0149), and inflation (0.0312), while other variables such as basic education (0.0751), age of labour (0.3256), and Foreign Direct Investment (0.3417) are insignificant, while the short-run impact is seen to be less significant. This research proves that economic growth will always affect wages and the importance of controlling inflation as well as stabilising economic conditions to influence wages positively. Through rigorous statistical testing, this study contributes to understanding the dynamics affecting wages in Indonesia, highlighting the critical role of economic and demographic factors.

ANALISIS TRANSMISSION OF MONETERY POLICY TERHADAP PERTUMBUHAN EKONOMI DAN KEUANGAN PASCA PEMULIHAN EKONOMI IN FIVE APEC COUNTRIES

The aim of this research is to determine and investigate how the global economic crisis in 2020 affected financial and economic growth after the Covid-19 crisis and the economic recovery that followed. Secondary data covering the period 2013 to 2023 was used in this research. Money supply, real interest rates, exchange rates, investment, inflation, and gross domestic product are the variables taken into account. This research examines the short-term and long-term impacts of monetary policy on financial and economic growth in five Asia Pacific Economic Cooperation (APEC) countries using the Structural Vector Autoregressive (SVAR) approach. Three variables investment, reallinteresttrates, and moneyxsupplyido not significantly influence1economicxor financial growth, according to the study's findings, while two variables inflation and exchange rates have a positive impact on economic and financial growth.

Regional Prediction of Crop Yield Success Rate in the Philippines using Geographic Trend Analysis Algorithm

Agriculture holds an important role in the economy of the Philippines by ensuring the food security of domestic products. It involves about 40 % of Filipino workers and it contributes an average of 20 percent to the Gross Domestic Product. Crop prediction in the Philippine’s agriculture is a big problem. At the present time, farmers are having a difficult time in choosing the right crops due to unnatural climate changes, soil type, rainfall, and other environmental factors. These can affect the economic life of farmers and can make them less familiar in forecasting future crops. This project aims to guide the farmers for sowing the reasonable crops by using geographic trend analysis algorithm. The findings from this study demonstrate the potential of the Geographic Trend Analysis Algorithm as a powerful tool for regional crop yield prediction. The success rate of each region will always equate to 100% in context with the set optimal yield prediction where the crop with highest percentage appears to be the dominant one. Irrigated palay (rice) demonstrates a greater rate of success across diverse Philippine regions when contrasted with rainfed or non-irrigated palay, as well as white and yellow corn. Additionally, the methodology employed by the researchers sets the groundwork for upcoming investigations in the domain of agricultural data analytics and geographic information science. This paves the way for a data-centered and sustainable strategy toward crop production in the Philippines.

IMPACT OF THE BRICS ON THE RUSSIAN ECONOMY AND TRADE

This study explores the influence of the BRICS nations on the Russian economy, with a specific focus on trade dynamics and their impact on Russia's Gross Domestic Product (GDP) growth. Through a comprehensive analysis spanning from 2011 to 2022, this study delves into the volume of trade between Russia and each BRICS country, assessing the stability, trends, and sectoral composition of these trade relationships. The study utilizes regression analysis to evaluate the correlation between Russia's economic indicators and its trade activity within the BRICS framework. The findings indicate a significant impact of trade with BRICS countries on Russia's economic performance, particularly highlighting the role of exports and imports in driving GDP growth. The research also forecasts Russia's GDP from 2023 to 2025, providing insights into the potential future economic trajectory based on trade patterns with BRICS nations. This study contributes to understanding the strategic importance of the BRICS alliance for Russia's economic landscape, suggesting that continued and diversified trade relations within this group could be key to Russia's economic prosperity.

Financial Management Practices and Small and Medium-scale Enterprises' Performance in Sri Lanka

Small and Medium-scale Enterprises (SMEs) add value to an economy by creating employment, contributing to Gross Domestic Production (GDP), making innovations, and minimising poverty. They are partnering with the development of the country. Most small and medium-scale enterprises face issues like lack of knowledge, outdated skills, fear of taxation, adoption of accounting standards, and accounting information records. Therefore, this study aims to identify the relationship between financial management practices and SMEs' performance in the southern province of Sri Lanka. This study measures financial management practices using financial reporting analysis, working capital management, fixed asset management, and accounting information systems. SME performance was measured by the profitability of SMEs using return on assets. Considering data constraints, time constraints, and the COVID-19 situation, 107 Small and Medium Enterprises operating in the manufacturing and service sectors were selected as samples. A questionnaire was chosen as the primary data-gathering method. The sample was chosen using a convenience sampling procedure, and the data were analysed using the Statistical Package for Social Scientists (SPSS) software. Multiple regression analysis was done to examine the hypothetical association. This study found that financial management techniques such as fixed asset management, working capital management, accounting information systems, and financial performance of SMEs have a significant association with performance. The findings support aiding investors, workers, and policymakers in making effective decisions.