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    Wyświetlanie 1-3 z 3
    Tytuł:
    Big data management algorithms in artificial Internet of Things-based fintech
    Autorzy:
    Andronie, Mihai
    Iatagan, Mariana
    Uță, Cristian
    Hurloiu, Iulian
    Dijmărescu, Adrian
    Dijmărescu, Irina
    Powiązania:
    https://bibliotekanauki.pl/articles/19902795.pdf
    Data publikacji:
    2023
    Wydawca:
    Instytut Badań Gospodarczych
    Tematy:
    big data management algorithms
    artificial intelligence
    Internet of Things
    fintech
    banking
    capital markets
    Opis:
    Research background: Fintech companies should optimize banking sector performance in assisting enterprise financing as a result of firm digitalization. Artificial IoT-based fintech-based digital transformation can relevantly reverse credit resource misdistribution brought about by corrupt relationship chains. Purpose of the article: We aim to show that fintech can decrease transaction expenses and consolidates firm stock liquidity, enabling excess leverage decrease and cutting down information asymmetry and transaction expenses across capital markets. AI- and IoT-based fintechs enable immersive and collaborative financial transactions, purchases, and investments in relation to payment tokens and metaverse wallets, managing financial data, infrastructure, and value exchange across shared interactive virtual 3D and simulated digital environments. Methods: AMSTAR is a comprehensive critical measurement tool harnessed in systematic review methodological quality evaluation, DistillerSR is harnessed in producing accurate and transparent evidence-based research through literature review stage automation, MMAT appraises and describes study checklist across systematic mixed studies reviews in terms of content validity and methodological quality predictors, Rayyan is a responsive and intuitive knowledge synthesis tool and cloud-based architecture for article inclusion and exclusion suggestions, and ROBIS appraises systematic review bias risk in relation to relevance and concerns. As a reporting quality assessment tool, the PRISMA checklist and flow diagram, generated by a Shiny App, was used. As bibliometric visualization and construction tools for large datasets and networks, Dimensions and VOSviewer were leveraged. Search terms were “fintech” + “artificial intelligence”, “big data management algorithms”, and “Internet of Things”, search period was June 2023, published research inspected was 2023, and selected sources were 35 out of 188. Findings & value added: The growing volume of financial products and optimized operational performance of financial industries generated by fintech can provide firms with multifarious financing options quickly. Big data-driven fintech innovations are pivotal in banking and capital markets in relation to financial institution operational efficiency. Through data-driven technological and process innovation capabilities, AI system-based businesses can further automated services.
    Źródło:
    Oeconomia Copernicana; 2023, 14, 3; 769-793
    2083-1277
    Pojawia się w:
    Oeconomia Copernicana
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Is earnings management impacted by audit fees and auditor tenure? An analysis of the Big Four audit firms in the US market
    Autorzy:
    Santos-Jaén, José Manuel
    Martín de Almagro-Vázquez, Gema
    Valls Martínez, María del Carmen
    Powiązania:
    https://bibliotekanauki.pl/articles/19906103.pdf
    Data publikacji:
    2023
    Wydawca:
    Instytut Badań Gospodarczych
    Tematy:
    earnings management
    auditor tenure
    auditor rotation
    audit fees
    Big Four
    Opis:
    Research background: Audits are intended to ensure the reliability of financial statements, as this is fundamental for different stakeholders. However, both auditor tenure and audit fees could affect the earnings management of companies. In 2014, the European Union established a mandatory audit firm rotation policy. In the United States, although there is still no mandatory regulation in this regard, there has been a large public debate over the advisability of this policy. Another unresolved controversy is whether audit fees determine audit quality. Purpose of the article: The aim of this research is to study the effect of auditor tenure and audit fees on earnings management, i.e., to determine whether a longer-term relationship between the auditor and the audited company, as well as higher audit fees, reduce the audited company's earnings management, thereby making the financial statements more reliable for stakeholders and increasing the quality of the audit report. In addition, the Big Four auditing companies in the United States were analyzed in order to determine the influence of corporate culture. Methods: A sample of companies listed in the S&P 500 stock market index was employed for the analysis, covering the years 2012 to 2021, resulting in a dataset comprising 3,010 observations. To examine the research hypotheses while mitigating the potential bias from omitted variables, a linear regression analysis was conducted using panel data with fixed effects regression. To enhance the robustness of the results, winsorized variables were also employed. Findings & value added: Overall, the results confirm that the quality of financial statements improves as auditor tenure increases, and so implementing a mandatory auditor rotation may not be in a company’s best interests. The results also support the market segmentation theory, as higher audit fees are aligned with higher quality financial reporting. Furthermore, by analyzing the Big Four audit companies in the US, it is shown that the influence of audit fees and auditor tenure on earnings management also depends on the internal aspects of the particular audit firm, especially its ethical culture. In sum, US policymakers should neither set limits on audit fees nor enforce a mandatory audit firm rotation similar to that of the EU.
    Źródło:
    Oeconomia Copernicana; 2023, 14, 3; 899-934
    2083-1277
    Pojawia się w:
    Oeconomia Copernicana
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Artificial intelligence-based decision-making algorithms, Internet of Things sensing networks, and sustainable cyber-physical management systems in big data-driven cognitive manufacturing
    Autorzy:
    Lazaroiu, George
    Androniceanu, Armenia
    Grecu, Iulia
    Grecu, Gheorghe
    Neguriță, Octav
    Powiązania:
    https://bibliotekanauki.pl/articles/19322650.pdf
    Data publikacji:
    2022
    Wydawca:
    Instytut Badań Gospodarczych
    Tematy:
    cognitive manufacturing
    Artificial Intelligence of Things
    cyber-physical system
    big data-driven deep learning
    real-time scheduling algorithm
    smart device
    sustainable product lifecycle management
    Opis:
    Research background: With increasing evidence of cognitive technologies progressively integrating themselves at all levels of the manufacturing enterprises, there is an instrumental need for comprehending how cognitive manufacturing systems can provide increased value and precision in complex operational processes. Purpose of the article: In this research, prior findings were cumulated proving that cognitive manufacturing integrates artificial intelligence-based decision-making algorithms, real-time big data analytics, sustainable industrial value creation, and digitized mass production. Methods: Throughout April and June 2022, by employing Preferred Reporting Items for Systematic Reviews and Meta-analysis (PRISMA) guidelines, a quantitative literature review of ProQuest, Scopus, and the Web of Science databases was performed, with search terms including "cognitive Industrial Internet of Things", "cognitive automation", "cognitive manufacturing systems", "cognitively-enhanced machine", "cognitive technology-driven automation", "cognitive computing technologies", and "cognitive technologies". The Systematic Review Data Repository (SRDR) was leveraged, a software program for the collecting, processing, and analysis of data for our research. The quality of the selected scholarly sources was evaluated by harnessing the Mixed Method Appraisal Tool (MMAT). AMSTAR (Assessing the Methodological Quality of Systematic Reviews) deployed artificial intelligence and intelligent workflows, and Dedoose was used for mixed methods research. VOSviewer layout algorithms and Dimensions bibliometric mapping served as data visualization tools. Findings & value added: Cognitive manufacturing systems is developed on sustainable product lifecycle management, Internet of Things-based real-time production logistics, and deep learning-assisted smart process planning, optimizing value creation capabilities and artificial intelligence-based decision-making algorithms. Subsequent interest should be oriented to how predictive maintenance can assist in cognitive manufacturing by use of artificial intelligence-based decision-making algorithms, real-time big data analytics, sustainable industrial value creation, and digitized mass production.
    Źródło:
    Oeconomia Copernicana; 2022, 13, 4; 1047-1080
    2083-1277
    Pojawia się w:
    Oeconomia Copernicana
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
      Wyświetlanie 1-3 z 3

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