Accounting Data Research Articles

Improving model performance in mapping cropland soil organic matter using time-series remote sensing data

Faced with increasing global soil degradation, spatially explicit data on cropland soil organic matter (SOM) provides crucial data for soil carbon pool accounting, cropland quality assessment and the formulation of effective management policies. As a spatial information prediction technique, digital soil mapping (DSM) has been widely used to spatially map soil information at different scales. However, the accuracy of digital SOM maps for cropland is typically lower than for other land cover types due to the inherent difficulty in precisely quantifying human disturbance. To overcome this limitation, this study systematically assessed a framework of “information extraction-feature selection-model averaging” for improving model performance in mapping cropland SOM using 462 cropland soil samples collected in Guangzhou, China in 2021. The results showed that using the framework of dynamic information extraction, feature selection and model averaging could efficiently improve the accuracy of the final predictions (R2: 0.48 to 0.53) without having obviously negative impacts on uncertainty. Quantifying the dynamic information of the environment was an efficient way to generate covariates that are linearly and nonlinearly related to SOM, which improved the R2 of random forest from 0.44 to 0.48 and the R2 of extreme gradient boosting from 0.37 to 0.43. Forward recursive feature selection (FRFS) is recommended when there are relatively few environmental covariates (<200), whereas Boruta is recommended when there are many environmental covariates (>500). The Granger-Ramanathan model averaging approach could improve the prediction accuracy and average uncertainty. When the structures of initial prediction models are similar, increasing in the number of averaging models did not have significantly positive effects on the final predictions. Given the advantages of these selected strategies over information extraction, feature selection and model averaging have a great potential for high-accuracy soil mapping at any scales, so this approach can provide more reliable references for soil conservation policy-making.

Non-monetary motivations of the EU agri-environmental policy adoption. A causal forest approach

This paper investigates the non-monetary motivations of farmers' adoption of agri-environmental policies. Unlike the monetary (income) motivations, non-monetary drivers can not be directly observed but can be identified from observational data within appropriate quasi-experimental designs. A theoretical justification of farmers' choices is first formulated and a consequent natural experiment setting is derived. The latter admits heterogeneous, i.e. Individual, Treatment Effects (ITE) that, in turn, can be interpreted in terms of more targeted and tailored policy expenditure. A Causal Forest (CF) approach is adopted to estimate these ITEs for both the treated and not treated units. The approach is applied to two balanced panel samples of Italian Farm Accountancy Data Network (FADN) farms observed over the 2008–2018 period and concerns agri-environmental policies delivered through the Common Agricultural Policy (CAP). Results show how heterogeneous the farmers’ response and the associated non-monetary motivations can be, thus indicating room for a more efficient policy design.

ПОДАТКОВА ЗВІТНІСТЬ: СУТНІСТЬ ТА ПОРЯДОК СКЛАДАННЯ

The article analyzes the approaches of leading national scholars to the definition of the concept of "tax reporting". The author characterizes the necessity of tax reporting, since it characterizes the status of an enterprise's obligations related to the accrual and payment of taxes and other mandatory payments. Tax reporting is submitted to the tax authorities.&#x0D; The purpose of the article is to deepen theoretical research on the essence of the concept of "tax reporting", to disclose the methodology of its preparation with a view to improving its quality, reliability and objectivity.&#x0D; Summarizing the approaches of scholars to the essence of tax reporting, it is worth noting three approaches. According to the first one, tax reporting is considered as a set of documents containing information on the calculation of tax liabilities; according to the second one, it is considered as a set of actions of the taxpayer on preparation and submission of reports; according to the third one, it is considered as a set of consolidated interrelated indicators characterizing the activities of the enterprise for a certain period.&#x0D; Having studied the essence of the concept of "tax reporting", we propose to supplement Article 14 of the Tax Code of Ukraine with the following definition: tax reporting is reporting containing information on the tax liabilities of an enterprise by type of tax and fees.&#x0D; The Ministry of Finance of Ukraine regulates tax reporting by establishing forms of tax returns, calculations and reports by type of tax and fee.&#x0D; The tax reporting procedure can be divided into 4 stages: Stage 1 - selection of the required form of tax reporting in accordance with the type of tax/fee; Stage 2 - preparation of a tax return for the tax/fee, i.e., entering data directly; Stage 3 - verification of the document for correctness of preparation, compliance of the entered data with the accounting data, correctness of determination of the tax base, taxable object, tax rate; Stage 4 - signing of tax reports.&#x0D; Based on the study of tax reporting on national taxes and fees, it should be noted that not all forms contain information on the procedure for their preparation. For the preparation of individual forms by type of tax and fees, notes are used after the main part of the tax reporting. Therefore, we believe that the central executive body that ensures the formation and implementation of the state financial policy should develop recommendations on the preparation of tax reporting forms for those taxes and fees that do not have them, as this will contribute to better coverage of information on tax liabilities and significantly reduce the number of pages of tax reports.

The use of big data and analytics in external auditing: Does audit firm size matter? Evidence from a developing country

Purpose: The aims of this research are to investigate the reasons for adopting big data (BD) and big data analytics (BDA), determine their extent of usage, and identify potential obstacles to their adoption in a developing country, Egypt. Motivation: Prior literature criticized the audit profession for the slow adoption of BDA, and little is known about the adoption of BD and BDA in developing countries. The reluctance to incorporate BD and BDA into auditing can be attributed to their potential obstacles. In addition, prior studies focused on the Big-4 audit firms in developed countries with little known about adopting BD and BDA in local audit firms and developing countries. Design/methodology/approach:To achieve the objectives of this study, 16 audit practitioners with various positions, specializations, and experience levels were interviewed. The 16 participants belong to audit firms of different sizes: international audit firms, local audit firms, and a governmental auditing agency. Thematic analysis was employed through using the MAXQDA software package to analyze the data. Main findings: The findings revealed that the reasons for using BD and BDA go beyond improving audit efficiency and effectiveness and satisfying clients. All audit firms collect and analyze large volumes of traditional accounting data. However, the Big-4 firms manage and analyze non-financial data and new data items as complementary audit evidence. Also, it was found that the type of audit firm affects the use of these technologies, with international firms being superior to other firms. The Accountability State Authority lags behind other audit firms in adopting BD and BDA. Furthermore, it was found that some obstacles to adopting BD and BDA arise due to the specific characteristics of the Egyptian context, while others are universal. Practical implications/Managerial impact: Determining the reasons for and obstacles to adopting BD BDA is useful for audit firms and regulators to remove these obstacles and encourage using such new audit technologies. The findings might help developers of BDA software packages to enhance their packages to meet auditor requirements. Moreover, academic scholars can benefit from the findings of this study by gaining an understanding of the main differences between developed and developing countries in relation to adopting BD and BDA. Novelty/Contribution: This study was conducted in Egypt, a developing country with a an underdeveloped audit environment. Therefore, this study enriches the relevant literature by providing information about BD and BDA in an unexplored developing environment. Besides, it delves deeper into the reasons and obstacles to using BD and BDA in external financial auditing in a developing country. Also, it adds to the literature by identifying the most common BDA software packages and techniques that auditors use in a developing country. Moreover, it considers audit practitioners’ viewpoints on audit firms of various sizes.

Integrating N‐person Intuitionistic Neutrosophic Soft Games with Neutrosophic Cognitive Maps for Cloud Storage with Accounting Information Systems

Neutrosophic logic is founded on non-standard evaluation. In neutrosophic set (NS), the computation of indefiniteness is explicit, while the membership of truth, falsity, and indeterminacy are non-reliable. Recently, various attractive game theory application is extended by entrenching the fuzzy set logic. The accounting data analysis has to contribute the innovativeness. This includes various characteristics. It applies billions of individuals in the business to develop and design novel products until the sale managing of the enormous sales staff. While cloud storage provides flexibility and scalability, it also comes with related costs, involving data transfer fees, subscription fees, and storage costs. Optimizing and managing cloud storage costs associated with business needs and budgetary constraints is crucial. Cloud-based AIS decreases the necessity for localized infrastructure and hardware, oscillating rate from capital to operational expenditure. This enables organizations to pay only for the used resource, resulting in economic efficiencies. Incorporating cloud technology into accounting information systems (AIS) provides several advantages. To increase the capability of accounting data statistics and analysis, this article introduces an N‐person intuitionistic neutrosophic soft game with Neutrosophic Cognitive Maps (NINSG-NCM) for cloud storage with AIS. The NINSG-NCM technique considered a contemporary accounting data analysis is built based on the block bit sequence evaluation technique and extracts the association rule representative amount of accounting data. Integrated with cloud computing (CC) framework, the NINSG-NCM method is proposed, and the NCM clustering technique is used for realizing the modern accounting data clustering, and the NINSG method could enhance the capability of statistical analysis and parallel computing of accounting data. Lastly, salp swarm algorithm (SSA) is applied for hyperparameter tuning method. The experimental outcomes illustrate that the designed intelligent data evaluation technique makes the parallel computing efficacy high and the statistical evaluation capability of accounting data better.

The determinants of the communication of societal accounting data within companies in Tunisia

The objective of this research is to study the reasons for the communication of societal accounting information in Tunisian companies. In fact, we have discussed the questions of the convergence of sustainability accounting models, the questions of the communication of accounting data or even questions of the participation of the actors. The results of qualitative research on a sample of 16 companies show a certain homogeneity in the assessment of the communication policy of societal accounting information of each type of company. It turns out that the social and societal activities identified come under the initiative of companies, their organizational culture and their extra-economic concerns. The social and societal concerns of these companies remain at the heart of the concerns of managers.

International mergers as a business expansion strategy by Greek companies: A case study of corporate performance analysis for board of directors

This research analyzes a specific international merger involving a Greek publicly traded company in the recent post-COVID-19 and post-sovereign debt crisis era in the Greek market. The primary research aim is to assess the corporate performance of a Greek company listed on the Athens Stock Exchange (ASE) after it underwent an international merger in 2019. The research involves an in-depth analysis of the company’s performance post-merger and calculates various financial ratios using accounting data from four years before and after the international merger. The research results revealed that the merger deal has led the examined Greek listed sample company to a better performance in profitability, but not in liquidity and leverage, thus signalizing some mixed results for the international merger transaction.

Proposta de índice de estado trófico para reservatórios semiáridos brasileiros

ABSTRACT The Brazilian semi-arid region, which is characterized by high climate vulnerability, intense and frequent droughts, and irregular rainfall, has a restricted quantity of water in its reservoirs and low quality at several points. Regarding quality, the literature presents indexes that evaluate eutrophication in different conditions, using specific expressions that may not be applied universally. To assist in decision-making and minimize this problem in the semi-arid region, the present work proposes a new trophic state index (TSI) taking into account data and conditions of reservoirs in the semi-arid region of Ceará. In total, 18 variables and the correlations between them were evaluated. In the years 2014-2022, data was made available by COGERH for 25 reservoirs managed by the company. Descriptive statistics were performed for each variable data set, removing outlier values to analyze trends. An exploratory investigation was also carried out, studying correlations between variables and transparency. Phosphorus, nitrogen, chlorophyll a, and turbidity presented the most significant correlations for the composition of the proposed TSI. An adaptation was made in the base expression of the TSI, which is associated with the values obtained in the semi-arid region of Ceará. Trophic classes were suggested for this new TSI along with their respective expressions. The proposed index yielded comparable results in certain classifications when compared with other established indexes. High concentrations of cyanobacteria occurred in reservoirs classified as eutrophic. To enhance the robustness of this novel index, it is recommended to extend its application to additional reservoirs within the semi-arid region.

Показатель пожарной опасности для лесной среды с использованием метеорологических и GPS-данных на территории Забайкальского национального парка

The main indicators of potential fire hazards are temperature, relative humidity, precipitation, and wind speed readings. Prompt detection of fire risk should be an integral part of forest protection systems. For this purpose, it is essential to use automatic instruments based on comprehensive meteorological observations. In recent years, most forest fires in the Republic of Buryatia have started due to natural rather than anthropogenic causes. To assess the risk of forest fire based on current weather conditions, the Nesterov index is used. Continuous GPS measurements, combined with highprecision geodetic techniques, allow us to regularly obtain data on tropospheric signal delays, which provide information about the total water vapor content in the atmosphere (IWV). The possibility of using the IWV values obtained to assess the fire risk of forest areas is demonstrated, taking into account data from the Ust-Barguzin weather station located on the territory of the Trans-Baikal National Park. Creating an online resource based on Nesterov's complex indicator using GPS measurements and meteorological data would allow for real-time monitoring of fire risk in forests.

РОЛЬ И МЕСТО ЦИФРОВЫХ ТЕХНОЛОГИЙ В ПРАКТИКЕ АНТИКОРРУПЦИОННОГО КОМПЛАЕНСА

The article discusses examples of the use of digital technologies in the framework of anti- corruption compliance. The author defines anti-corruption compliance as a system of measures aimed at preventing and combating corruption violations in organisations and emphasises the role of transparency, responsibility and ethical behaviour at its core. The article highlights the use of artificial intelligence to process data and detect corruption offences, the use of blockchain to create transparent accounting systems and data integrity, and big data analyses to monitor and improve anti-corruption policies. The author emphasises that digital technologies play a key role in modern anti-corruption compliance practices, contributing to more efficient and responsible governance systems.

Transparent and Accountable Training Data Sharing in Decentralized Machine Learning Systems

Transparent and Accountable Training Data Sharing in Decentralized Machine Learning Systems

Utilization of big data and cloud computing platforms for the smooth processing of financial ac-counting system data and its implications for the success of village development

This research aims to analyze the direct and indirect influence of the use of Big Data and Cloud Computing Platforms on the smooth processing of financial accounting system data and its implications for the success of village development. This research used quantitative methods, using Saturation sampling techniques, and obtained a sample of 131 respondents who were village financial information system operators, consisting of 131 villages in Pringsewu Regency, Lampung Province, Indonesia. The data collected from the surveys was then analyzed using Structural Equation Modeling-Partial Least Squares (SEM-PLS). The research and data analysis demonstrate that Cloud Computing Platforms significantly enhance the efficiency of processing financial accounting system data. Additionally, Cloud Computing Platforms have a direct and positive influence on the success of village development. Moreover, the efficient handling of financial accounting system data directly and significantly impacts the progress of village development. Furthermore, the application of Big Data has a direct and substantial impact on the effective processing of data in financial accounting systems, as well as on the achievement of success in village development. Ultimately, the efficient data processing of the Financial Accounting System serves as a partial intermediary between the utilization of Big Data and Cloud Computing Platforms, and the achievement of village development in Pringsewu Regency, Lampung Province, Indonesia. Because the independent variable is able to significantly influence both directly and indirectly the dependent variable.

Firms’ Precautionary Savings and Employment during a Credit Crisis

Can the macroeconomic effects of credit supply shocks be large even when a small share of firms is credit constrained? I use UK firm-level accounting data to discipline a heterogeneous-firm model where the interaction between real and financial frictions induces precautionary cash holdings. In the data, firms increased their cash ratios during the Great Recession, and cash-intensive firms displayed higher employment growth. A tightening of firms’ credit conditions generates the same dynamics in the model. Unconstrained firms preemptively respond to credit supply shocks; this precautionary channel, when appropriately quantified, crucially matters for the aggregate dynamics and firm-level patterns. (JEL D22, E24, E32, E44, G32)

Research on Accounting Quality Management of Enterprises under Financial Sharing Mode

Abstract With the deep integration of the global economy and the continuous individuality of technology, the complexity of enterprise operation and management is increasing, which makes the traditional accounting and accounting methods difficult to meet the needs of modern enterprises. This paper proposes an enterprise accounting accounting method applying information computing technology, which applies association rules to generate frequent item sets of data for the accounting data under the financial sharing mode and obtains the optimal rules through pruning. Based on the time series prediction of the enterprise’s financial data, changes are made. Taking the actual enterprise case study, the association rules involved in accounting are more accurate, the calculation results are basically the same as the actual value, and the final cost accounting value is only nearly 2 million yuan different from the actual value, the accounting error is only 0.02%. Furthermore, the association rule algorithm has a significant impact on improving the efficiency of accounting work. The service time of counter personnel can be reduced by 30% after Bank P applies the management rules to accounting management. The average execution time of the initial ticket examination operation has been accelerated from 10.53 seconds to 5.42 seconds. The association rule algorithm can effectively improve the precision of enterprise accounting and the efficiency of accounting personnel, while also identifying existing problems in the current management system.

Влияние методов амортизации активов на эффективность хозяйственной деятельности транспортной корпорации

The relevance of the study is due to the search for modern, most advanced and convenient approaches for transformation and digitalization, for the formation of financial savings sufficient for the renovation of assets. The study of the dependence of depreciation policy, financial stability and the efficiency of economic activities of transport corporations allows us to determine the main directions of asset renovation. The object of the study is the process of forming a depreciation strategy for transport corporations aimed at creating sufficient financial savings. Sufficiency is determined by the real possibility of providing the required volumes of financing for the renovation of public pension facilities. The purpose of the work is to develop a methodological approach for the formation of a depreciation strategy as part of improving the financial management of national transport corporations. The tasks that required their solution to achieve this goal required: consideration of the general theoretical foundations associated with the study of modern developments on the formation and development of a depreciation strategy for replenishing one’s own sources of investment finan­cing; development of an effective depreciation strategy for a transport corporation. Strategies based on the use of combined methods of calculating depreciation, taking into account their impact on the efficiency of business activities; analysis of methods for calculating depreciation based on objective and reliable information, namely, accounting and tax accounting data. The research is based on the methods of induction, deduction and general cognition. Using the example of an operating passenger suburban railway corporation, the results of a study of the influence of the choice of depreciation methods (depreciation bonus) of the active part of production fixed assets on taxation, efficiency and quality indicators of its production, economic and financial activities are presented. The results of the study have proved that when using methods of logical, statistical and correlation analysis, it is possible to use scenario approaches as the main tool for developing a rational depreciation policy for a suburban passenger railway corporation. The conclusions are based on practical recommendations for the formation of an accounting policy of a railway corporation, allowing to accumulate funds and form strategic savings sufficient for the complete restoration of active fixed assets.

An Abnormal Detection method of Enterprise Financial Accounting Data Based on Bayesian network

An Abnormal Detection method of Enterprise Financial Accounting Data Based on Bayesian network

A risk identification method for abnormal accounting data based on weighted random forest

A risk identification method for abnormal accounting data based on weighted random forest

Importance and determinants of cooperation between fruit farms and the institutional environment

The development of farms requires support from the institutional environment of agriculture. Institutions help introduce innovations and adapt their functioning to the requirements of the European Union. The aim of the research was to determine the factors affecting the cooperation of orchard farms with the institutional environment and the economic effects of this cooperation. The article's novelty answers two questions: what factors on the farm affect cooperation with the institutional environment, and whether such cooperation affects the economic results of orchard farms? The study covered 45 farms from the Małopolska and Pogórze Region in Poland, specializing in cultivating fruit trees and shrubs, which in 2018 kept accounts under the Farm Accountancy Data Network (FADN). The descriptive method, chi-square test, and Spearman's rank correlation coefficient were used in the data analysis. An original relationship index was used to assess fruit producers' cooperation with agricultural organizations. A backward stepwise multiple regression model was used to identify the factors influencing its level. The research showed a statistically significant relationship between the relationship index with the organization and utilized agriculture area, total workload, the value of subsidies to operating activities, direct costs, and the farmer's age. The regression model shows that the value of subsidies to operating activities explains 28.09% of the variability of the relationship index (Ri). Based on the analysis, it can be concluded that the cooperation of fruit producers with the institutional environment positively impacts orchard farms' economic and financial results.

Subsidies and the income inequality in the Hungarian wine sector

The paper investigates the impact of different sources of income on wine farm total income inequality in Hungary using Farm Accountancy Data Network data for the period 2013-2019. The decomposition of the Gini coefficient is applied to focus on the impact of the Common Agricultural Policy (CAP) shift from market to government budgetary support on wine farm total income inequality. Off-farm income has a rather stable impact on wine farm total income inequality. CAP Pillar 1 subsidies have remained more important than CAP Pillar 2 subsidies, both in the structure of wine farm total income and in the reduction of wine farm total income inequality. The most striking finding is regarding a shift in wine farm market income from a negative (losses) to a positive (profit) value and its increasing role in wine farm total income inequalities. The 20% of the largest wine farms created from almost 90% to less than 80% of wine farm total incomes between 2013 and 2019, but during the same period their participation in CAP subsidy payments was reduced much more from more than 80% to around 60%. Subsidies from Pillars 1 and 2 were reduced, and wine market income increased wine farm total income inequality, while it remained constant for off-farm income. The wine farm market income has driven wine farm total income inequalities. This might strengthen because of the ongoing market selection process with the exit of less efficient and loss-making wine farms and the increasing role of surviving profitable wine farms. This market selection process can be related to managerial, entrepreneurial, and innovation activities based on the differentiation and segmentation of wine farm products and their market incomes.

Adapting Corporate Governance for Sustainable Organizational Performance: A Case Study of the Banking Sector in Pakistan amid the COVID-19 Pandemic

Purpose - Corporate governance is a crucial aspect of creating a corporate culture that emphasizes transparency, fairness, and openness. The COVID-19 pandemic has caused a global financial crisis, which has increased attention to corporate governance issues. In light of this, the objective of this study is to examine the impact of corporate governance on the sustainable organizational performance of the banking sector in Pakistan particularly in the context of COVID-19.&#x0D; Study Design/Methodology/Approach - This research analyses the annual reports of sample banks and uses secondary data from 2016 to 2022; therefore, there is no doubt about the reliability and validity of the data. This study measured firm sustainable financial performance based on accounting data, using return on assets, return on equity, and earnings per share. The suggested model was investigated by the generalized method of moments through the Arellano-Bond Dynamic Panel-Data estimator.&#x0D; Findings - The overall findings of the study reveal that corporate governance components such as board size, audit committee independence, number of board meetings, and chief executive officer duality have a significant impact on organizational performance. Furthermore, the Fixed Affect model indicates that CEO duality has no discernible effect on organizational sustainable performance, while board size, audit committee independence, and the frequency of board meetings all positively affect it.&#x0D; Practical and theoretical implications- This study has implications for all stakeholders of the banking system, economic policymakers, and academicians by highlighting the importance of components of corporate governance that enhance overall organizational performance. Theoretically, compliance with corporate governance regulations should lower agency costs, which will improve the overall business's performance now and in the future.&#x0D; Originality/Novelty- This study indicates that the use of corporate governance practices enhances and improves the overall sustainable performance of the banking sector. This study adds value to the existing body of literature by considering corporate governance and its association with organizational performance, particularly from the COVID-19 perspective.