scholarly journals THE IMPACT OF BIG DATA ANALYTICS ON IMPROVING FINANCIAL REPORTING QUALITY

2020 ◽  
Vol 4 (03) ◽  
Author(s):  
Nagat Mohamed Marie Younis
Keyword(s):  
Big Data ◽  
Financial Reporting ◽  
Data Analytics ◽  
Information Quality ◽  
Accounting Information ◽  
Big Data Analytics ◽  
Reporting Quality ◽  
Financial Reporting Quality ◽  
Accounting Information Quality ◽  
The Impact

Purpose – The current study aims to clarify the importance of big data analytics and its role in changing the accounting profession and the roles of accountants, in addition to testing the impact of big data analytics on improving financial reporting quality in the Saudi environment. Design/ methodology/ approach – To achieve the study's goals and validate hypotheses, relevant previous literature and research are referred. Also, a field study is conducted by distributing a questionnaire of (154) individual academics, financial analysts, accountants, and experts in the field of analyzing big data in the Kingdom of Saudi in 2019. Data are analyzed by using the program of Statistical Package for Social Science (SPSS 17.0). Findings – The study concluded that although business organizations face several challenges when analyzing data, big data analytics has a significant role in achieving high competitiveness for institutions, improving the accounting information quality, providing appropriate information that helps in rationalizing decisions within the economic unit, and providing future information affecting stakeholder's decisions. The study also has proved that there is a statistically significant effect of big data analytics on improving the quality of accounting information, as big data analytics clearly affects the characteristics of the accounting information quality, positively affecting the quality of financial reports. Originality/ Value – Originality/ Value – The analytics of big data is one of the most important topics where it positively affects the improvement of accounting information quality, which reflects on financial reporting quality. Hence, academics and institutions should pay attention to this topic and follow their new ideas. The present study is one of the first studies that deal with this topic and examine the relationship between big data analytics and the characteristics of accounting information which positively affecting financial reporting quality.

scholarly journals The Mapping Of Investor Perception On The High Financial Reporting Quality

2021 ◽  
Vol 6 (1) ◽  
pp. 1
Author(s):  
Muljanto Siladjaja ◽  
Yuli Anwar
Keyword(s):  
Financial Reporting ◽  
Information Quality ◽  
Dividend Policy ◽  
Earnings Quality ◽  
Accounting Information ◽  
Reporting Quality ◽  
Financial Reporting Quality ◽  
Future Market ◽  
Maximum Utility ◽  
Accounting Information Quality

This research mapped investor perception on high accounting information quality, particularly the accurate prediction model for future returns. The high financial reporting quality indicates the company's prospective improvement in the future under the right management. This positively affects market price fluctuation, where the investor has minimum distortion on accounting information and low risk. The obedience to accounting standards and tax regulation illustrates actual earnings in reducing agency cost's volatile movement. This study used questionnaires to gather information. The respondents were related parties with dominant influence in investment, specifically 384 samples. Through the structural equation model, the mapping of earnings quality, future market value, and dividend policy played a critical role in minimizing misleading information and improving accounting information quality. The high financial reporting quality indicates the managements' obedience in maximum implementation of regulations with continuous improvements. In this regard, the dividend policy has significantly contributed to the improvement of the earnings quality. The Decision Tree Model was used in mapping investor perception on earnings quality to estimate the high probability of a long or short position for their maximum utility. When the dividend policy is used as a mandatory indirect obligation, the management should provide high accounting information quality.

scholarly journals The effect on the BTD of IFRS adoption and the end of the Transitional Tax Regime (RTT) in Brazil

2022 ◽  
Vol 33 (88) ◽  
pp. 96-111
Author(s):  
Claudio Marcio Pereira da Cunha ◽  
Pedro Paulo Furbino Bretas Barros
Keyword(s):  
Earnings Management ◽  
Financial Reporting ◽  
Cross Sections ◽  
Information Quality ◽  
Accounting Information ◽  
Negative Relationship ◽  
Taxable Income ◽  
Ifrs Adoption ◽  
Accounting Information Quality ◽  
The Impact

ABSTRACT This paper aimed to evaluate the moderation by variables related to incentives for earnings management (indebtedness, profitability, and size) over the effect of the change in standards (accounting or tax) on the book-tax differences (BTD). The end of the Transitional Tax Regime (RTT) enables us to evaluate the symmetry between the divergence and reconvergence of the accounting and tax standards, helping to identify the moderating effect of characteristics such as size, leverage, and profitability over the use of the discretion allowed by the International Financial Reporting Standards (IFRS). Studying the effects of changes in the standards contributes to understanding how they affect accounting information quality, particularly when we observe symmetrical movements of divergence of the accounting and tax standards, such as IFRS adoption, and of reconvergence, with the end of the RTT. The analysis conducted enables us to separate effects of divergence between the tax and accounting standards from the innovations introduced by the IFRS. An understanding of the effect of the standard over accounting information quality contributes to the quality of the work of financial analysts, tax authorities, and regulators. Event studies are conducted to evaluate the effect of IFRS adoption, as well as the end of the RTT, over the BTD (a proxy for earnings management), in cross sections of companies. We use explanatory variables related to incentives to manage book and taxable income (indebtedness, profitability, and size), which could explain the ambiguity of the results in the literature. The article provides evidence that the indebtedness and size of companies influence the effect of IFRS adoption, as well as of the end of the RTT. We observed a negative relationship of indebtedness and size with the impact of changes in standards over differences between book and taxable income (BTD).

scholarly journals IFRS Adoption Impact On Financial And Accounting Information Quality: An Exploratory Study On Moroccan Petroleum And Gas Sector

2016 ◽  
Vol 6 (1) ◽  
pp. 337
Author(s):  
Anass Cherti ◽  
Houria Zaam
Keyword(s):  
Financial Reporting ◽  
Information Quality ◽  
Academic Research ◽  
Accounting Information ◽  
Stock Exchanges ◽  
Financial Reporting Standards ◽  
Financial Variables ◽  
Ifrs Adoption ◽  
Accounting Information Quality ◽  
The Impact

<p class="ber"><span lang="EN-US">The balance of <em>International Financial Reporting Standards</em> (IFRS), after ten years of their implementation, has reflected a positive perception of its impacts on the function “finance and accounting” of companies and issuers. Those companies and issuers observe, in a large majority that the transition to IFRS has increased the quality and the homogeneity of the information produced and the rapidity of their establishment. Unfortunately in academic research, such studies remains not clear as most publications front IFRS adoption impact in general manner which concern all sectors at the same study.</span></p><p class="ber"><span lang="EN-US">The purpose of this article is to present the results of an empirical study of three petroleum and gas companies listed in the <em>Casablanca Stock Exchanges</em> (CSE), to measure the impact of the IFRS adoption on financial and accounting information quality in Moroccan petroleum and gas sector.</span></p><p class="ber"><span lang="EN-GB">The released results show that this impact is positive for the petroleum and gas sector and the majority of the accounting and financial variables of this sector under IFRS dependents on those variables under the General Standardization Code of Morocco (GSCM). </span></p>

Do globalisation and adoption of IFRS by banks in Africa lead to less earnings management?

2019 ◽  
Vol 17 (2) ◽  
pp. 222-248 ◽  
Author(s):  
Mohammed Amidu ◽  
Haruna Issahaku
Keyword(s):  
Financial Reporting ◽  
Design Methodology ◽  
Information Quality ◽  
Accounting Information ◽  
Financial Statements ◽  
International Standards ◽  
Content Type ◽  
Financial Reporting Standards ◽  
Accounting Information Quality ◽  
National Economies

Purpose This paper aims to analyse the implications of globalisation and the adoption of international standards (International Financial Reporting Standards [IFRS]) for accounting information quality. Design/methodology/approach This paper uses a sample of 329 banks across 29 countries leading up to and beyond the implementation of IFRS to test for related hypotheses. Findings First, banks’ financial statements are prepared on the basis of international standards as national economies are integrated when social norms are diffused. Building on these results, the second test suggests that the relatively high-quality earnings among banks in Africa during the period is attributable to the adoption of and interaction of IFRS with globalisation and the strategy of banks to diversify within and across interest and non-interest income. Originality/value The authors investigate how globalisation and the adoption of IFRS affect accounting information quality.

scholarly journals Big Data Analytics for Search Engine Optimization

2020 ◽  
Vol 4 (2) ◽  
pp. 5 ◽  
Author(s):  
Ioannis C. Drivas ◽  
Damianos P. Sakas ◽  
Georgios A. Giannakopoulos ◽  
Daphne Kyriaki-Manessi
Keyword(s):  
Big Data ◽  
Cultural Heritage ◽  
Search Engine ◽  
Data Analytics ◽  
User Behavior ◽  
Big Data Analytics ◽  
Data Types ◽  
Search Engine Optimization ◽  
The Impact ◽  
The Web

In the Big Data era, search engine optimization deals with the encapsulation of datasets that are related to website performance in terms of architecture, content curation, and user behavior, with the purpose to convert them into actionable insights and improve visibility and findability on the Web. In this respect, big data analytics expands the opportunities for developing new methodological frameworks that are composed of valid, reliable, and consistent analytics that are practically useful to develop well-informed strategies for organic traffic optimization. In this paper, a novel methodology is implemented in order to increase organic search engine visits based on the impact of multiple SEO factors. In order to achieve this purpose, the authors examined 171 cultural heritage websites and their retrieved data analytics about their performance and user experience inside them. Massive amounts of Web-based collections are included and presented by cultural heritage organizations through their websites. Subsequently, users interact with these collections, producing behavioral analytics in a variety of different data types that come from multiple devices, with high velocity, in large volumes. Nevertheless, prior research efforts indicate that these massive cultural collections are difficult to browse while expressing low visibility and findability in the semantic Web era. Against this backdrop, this paper proposes the computational development of a search engine optimization (SEO) strategy that utilizes the generated big cultural data analytics and improves the visibility of cultural heritage websites. One step further, the statistical results of the study are integrated into a predictive model that is composed of two stages. First, a fuzzy cognitive mapping process is generated as an aggregated macro-level descriptive model. Secondly, a micro-level data-driven agent-based model follows up. The purpose of the model is to predict the most effective combinations of factors that achieve enhanced visibility and organic traffic on cultural heritage organizations’ websites. To this end, the study contributes to the knowledge expansion of researchers and practitioners in the big cultural analytics sector with the purpose to implement potential strategies for greater visibility and findability of cultural collections on the Web.

Analysis of Big Data Analytics in Healthcare Sector: Applications and Tools

2020 ◽  
Vol 17 (12) ◽  
pp. 5605-5612
Author(s):  
A. Kaliappan ◽  
D. Chitra
Keyword(s):  
Big Data ◽  
Data Analytics ◽  
Health Sector ◽  
Big Data Analytics ◽  
High Volume ◽  
Healthcare Sector ◽  
Genome Database ◽  
Tremendous Amount ◽  
The Impact ◽  
Different Sources

In today’s world, an immense measure of information in the form of unstructured, semi-structured and unstructured is generated by different sources all over the world in a tremendous amount. Big data is the termed coined to address these enormous amounts of data. One of the major challenges in the health sector is handling a high-volume variety of data generated from diverse sources and utilizing it for the wellbeing of human. Big data analytics is one of technique designed to operate with monstrous measures of information. The impact of big data in healthcare field and utilization of Hadoop system tools for supervising the big data are deliberated in this paper. The big data analytics role and its theoretical and conceptual architecture include the gathering of diverse information’s such as electronic health records, genome database and clinical decisions support systems, text representation in health care industry is investigated in this paper.

An experimental investigation of the impact of using big data analytics on customers’ performance measurement

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Marwa Rabe Mohamed Elkmash ◽  
Magdy Gamal Abdel-Kader ◽  
Bassant Badr El Din
Keyword(s):  
Big Data ◽  
Performance Measurement ◽  
Data Analytics ◽  
Positive Impact ◽  
Big Data Analytics ◽  
Unstructured Data ◽  
Future Research ◽  
Web Based ◽  
Content Type ◽  
The Impact

Purpose This study aims to investigate and explore the impact of big data analytics (BDA) as a mechanism that could develop the ability to measure customers’ performance. To accomplish the research aim, the theoretical discussion was developed through the combination of the diffusion of innovation theory with the technology acceptance model (TAM) that is less developed for the research field of this study. Design/methodology/approach Empirical data was obtained using Web-based quasi-experiments with 104 Egyptian accounting professionals. Further, the Wilcoxon signed-rank test and the chi-square goodness-of-fit test were used to analyze data. Findings The empirical results indicate that measuring customers’ performance based on BDA increase the organizations’ ability to analyze the customers’ unstructured data, decrease the cost of customers’ unstructured data analysis, increase the ability to handle the customers’ problems quickly, minimize the time spent to analyze the customers’ data and obtaining the customers’ performance reports and control managers’ bias when they measure customer satisfaction. The study findings supported the accounting professionals’ acceptance of BDA through the TAM elements: the intention to use (R), perceived usefulness (U) and the perceived ease of use (E). Research limitations/implications This study has several limitations that could be addressed in future research. First, this study focuses on customers’ performance measurement (CPM) only and ignores other performance measurements such as employees’ performance measurement and financial performance measurement. Future research can examine these areas. Second, this study conducts a Web-based experiment with Master of Business Administration students as a study’s participants, researchers could conduct a laboratory experiment and report if there are differences. Third, owing to the novelty of the topic, there was a lack of theoretical evidence in developing the study’s hypotheses. Practical implications This study succeeds to provide the much-needed empirical evidence for BDA positive impact in improving CPM efficiency through the proposed framework (i.e. CPM and BDA framework). Furthermore, this study contributes to the improvement of the performance measurement process, thus, the decision-making process with meaningful and proper insights through the capability of collecting and analyzing the customers’ unstructured data. On a practical level, the company could eventually use this study’s results and the new insights to make better decisions and develop its policies. Originality/value This study holds significance as it provides the much-needed empirical evidence for BDA positive impact in improving CPM efficiency. The study findings will contribute to the enhancement of the performance measurement process through the ability of gathering and analyzing the customers’ unstructured data.

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