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    Wyświetlanie 1-8 z 8
    Tytuł:
    Violations of social regulation and traffic accidents in road freight transport
    Autorzy:
    Poliak, Miloš
    Beňuš, Ján
    Lazaroiu, George
    Powiązania:
    https://bibliotekanauki.pl/articles/2134941.pdf
    Data publikacji:
    2022
    Wydawca:
    Sieć Badawcza Łukasiewicz. Przemysłowy Instytut Motoryzacji
    Tematy:
    safety
    dummy
    TEMA Automotive
    MSC Adams
    Opis:
    The aim of the work is to analyze violations of social regulation in road freight transport and to propose solutions to prevent these violations. In the first part, we devoted ourselves to the processing of knowledge about road freight transport based on the legislation of the European Union, which is directly oriented to the conditions for the operator of road freight transport with vehicles over 3.5-tons of total weight. Since compliance with the rules also comes with their violations, it is also necessary to consider the traffic accident rate in road freight transport, we specifically identified and compared the traffic accident rate in road freight transport based on traffic accident statistics published on the website of the Ministry of the Interior. In the second part, we gradually processed and evaluated a questionnaire survey, which consisted of questions focused on the violation of social legislation by drivers. In the final part of the work, based on the analysis from the first part of the work and the results from the questionnaire survey in the second part, we proposed solutions to prevent the most frequent violations of social legislation by drivers and carriers.
    Źródło:
    Archiwum Motoryzacji; 2022, 97, 3; 51--59
    1234-754X
    2084-476X
    Pojawia się w:
    Archiwum Motoryzacji
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    The economics of deep and machine learning-based algorithms for COVID-19 prediction, detection, and diagnosis shaping the organizational management of hospitals
    Autorzy:
    Lăzăroiu, George
    Gedeon, Tom
    Rogalska, Elżbieta
    Andronie, Mihai
    Frajtova Michalikova, Katarina
    Musova, Zdenka
    Iatagan, Mariana
    Uță, Cristian
    Michalkova, Lucia
    Kovacova, Maria
    Ștefănescu, Roxana
    Hurloiu, Iulian
    Zabojnik, Stanislav
    Stefko, Robert
    Dijmărescu, Adrian
    Dijmărescu, Irina
    Geamănu, Marinela
    Powiązania:
    https://bibliotekanauki.pl/articles/39832736.pdf
    Data publikacji:
    2024
    Wydawca:
    Instytut Badań Gospodarczych
    Tematy:
    deep and machine learning
    COVID 19
    prediction
    detection
    diagnosis
    organizational management
    hospital
    Opis:
    Research background: Deep and machine learning-based algorithms can assist in COVID-19 image-based medical diagnosis and symptom tracing, optimize intensive care unit admission, and use clinical data to determine patient prioritization and mortality risk, being pivotal in qualitative care provision, reducing medical errors, and increasing patient survival rates, thus diminishing the massive healthcare system burden in relation to severe COVID-19 inpatient stay duration, while increasing operational costs throughout the organizational management of hospitals. Data-driven financial and scenario-based contingency planning, predictive modelling tools, and risk pooling mechanisms should be deployed for additional medical equipment and unforeseen healthcare demand expenses. Purpose of the article: We show that deep and machine learning-based and clinical decision making systems can optimize patient survival likelihood and treatment outcomes with regard to susceptible, infected, and recovered individuals, performing accurate analyses by data modeling based on vital and clinical signs, surveillance data, and infection-related biomarkers, and furthering hospital facility optimization in terms of intensive care unit bed allocation. Methods: The review software systems employed for article screening and quality evaluation were: AMSTAR, AXIS, DistillerSR, Eppi-Reviewer, MMAT, PICO Portal, Rayyan, ROBIS, and SRDR. Findings & value added: Deep and machine learning-based clinical decision support tools can forecast COVID-19 spread, confirmed cases, and infection and mortality rates for data-driven appropriate treatment and resource allocations in effective therapeutic and diagnosis protocol development, by determining suitable measures and regulations and by using symptoms and comorbidities, vital signs, clinical and laboratory data and medical records across intensive care units, impacting the healthcare financing infrastructure. As a result of heightened use of personal protective equipment, hospital pharmacy and medication, outpatient treatment, and medical supplies, revenue loss and financial vulnerability occur, also due to expenses related to hiring additional staff and to critical resource expenditures. Hospital costs for COVID-19 medical care, screening, treatment capacity expansion, and personal protective equipment can lead to further financial losses while affecting COVID-19 frontline hospital workers and patients.
    Źródło:
    Oeconomia Copernicana; 2024, 15, 1; 27-58
    2083-1277
    Pojawia się w:
    Oeconomia Copernicana
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Neuromanagement decision-making and cognitive algorithmic processes in the technological adoption of mobile commerce apps
    Autorzy:
    Andronie, Mihai
    Lăzăroiu, George
    Ștefănescu, Roxana
    Ionescu, Luminița
    Cocoșatu, Mădălina
    Powiązania:
    https://bibliotekanauki.pl/articles/19322445.pdf
    Data publikacji:
    2021
    Wydawca:
    Instytut Badań Gospodarczych
    Tematy:
    mobile shopping app
    mobile commerce platform
    mobile payment service
    Internet-enabled consumer device
    consumer technological adoption
    Opis:
    Research background: With growing evidence of consumer adoption of mobile shopping apps, there is a pivotal need for comprehending Internet-enabled consumer devices in mobile shopping behavior. Mobile shopping platform features and user technological readiness configure consumers' expectations and demands as regards mobile retailing adoption, leading to acceptance of mobile shopping apps and payment services. Purpose of the article: In this research, prior findings have been cumulated indicating that mobile social apps extend throughout consumer attitudes and behaviors by the widespread adoption of smartphones. We contribute to the literature by showing that cutting-edge technological developments associated with customer behavior in relation to mobile commerce apps have resulted in the rise of data-driven systems. Consumer behavioral intention and adoption intention in relation to mobile shopping apps/websites are developed on perceived risk and trust consequences. Methods: Throughout February and March 2021, a quantitative literature review of the Web of Science, Scopus, and ProQuest databases was carried out, with search terms comprising "mobile shopping app", "mobile commerce platform", "mobile payment service", "Internet-enabled consumer device", "consumer technological adoption", and "mobile shopping behavior". As research published between 2018 and 2021 was analyzed, only 330 sources met the suitability criteria. By removing questionable or indeterminate findings (insubstantial/inconsequent data), results unconfirmed by replication, too imprecise content, or having quite similar titles, 66, chiefly empirical, sources were selected. A systematic review of recently published literature was carried out on technological adoption of mobile commerce apps by employing Preferred Reporting Items for Systematic Reviews and Meta-analysis (PRISMA) guidelines. The Systematic Review Data Repository was used, a software program for the gathering, handling, and analysis of data for the systematic review. The quality of the academic articles was determined by harnessing the Mixed Method Appraisal Tool. Findings & value added: The consumer purchase decision-making process in mobile app-based marketing involves consumer engagement and willingness to adopt mobile commerce apps. Further advancements should clarify how technological-based consumer adoption of mobile shopping throughout social commerce can improve the payment for products and services.
    Źródło:
    Oeconomia Copernicana; 2021, 12, 4; 1033-1062
    2083-1277
    Pojawia się w:
    Oeconomia Copernicana
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Comparison of factors influencing liquidity of European Islamic and conventional banks
    Autorzy:
    Musa, Hussam
    Musova, Zdenka
    Natorin, Viacheslav
    Lazaroiu, George
    Martin Boda, Martin
    Powiązania:
    https://bibliotekanauki.pl/articles/19233658.pdf
    Data publikacji:
    2021
    Wydawca:
    Instytut Badań Gospodarczych
    Tematy:
    Islamic banks
    conventional banks
    capital
    liquidity
    efficiency
    Opis:
    Research background: The innovation in Sharīʻah-compliant banking products has resulted in the rapidly increasing size of assets in Islamic banks worldwide. The assets of such banks have been growing twice as fast as those of conventional banks. Islamic banks do not depend on conventional interest, speculation, or complex derivatives stemming from banking operations. Instead, their actions in respect of profit/risk sharing, and the clarity of the contract are consistent with Islamic Sharīʻah principles, which seek to promote a more equal society. Purpose of the article: This research aims to identify and compare factors influencing the liquidity of Islamic and conventional banks in Europe. Candidate factors are sought amongst profitability, credit quality, credit expansion and capital adequacy indicators. Methodology: First, relevant financial ratios for 249 observations on Islamic banks and 2,306 observations on conventional banks are selected and compared for the period 2013?2017. Second, liquidity is explained separately for each type of banks by panel data regression to identify its determinants in a comparative context. Findings & value added: The results indicate that the impact of the net interest margin on the liquidity ratio of Islamic banks is insignificant, which is obviously due to the prohibition of the use of interest (riba). To the contrary, in conventional banking a higher net interest margin results in a reduction in liquidity. Capital adequacy has a positive influence upon liquidity in both types of banks, but in Islamic banking, the influence is 5.4 times greater. The findings strongly suggest that the liquidity of Islamic and conventional banks is affected by different factors.
    Źródło:
    Oeconomia Copernicana; 2021, 12, 2; 375-398
    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
    Tytuł:
    Artificial intelligence algorithms and cloud computing technologies in blockchain-based fintech management
    Autorzy:
    Lăzăroiu, George
    Bogdan, Mădălina
    Geamănu, Marinela
    Hurloiu, Lăcrămioara
    Luminița, Luminița
    Ștefănescu, Roxana
    Powiązania:
    https://bibliotekanauki.pl/articles/19901187.pdf
    Data publikacji:
    2023
    Wydawca:
    Instytut Badań Gospodarczych
    Tematy:
    artificial intelligence algorithms
    cloud computing
    blockchain
    fintech
    green and sustainable finance
    banking
    Opis:
    Research background: Fintech development shapes corporate investment efficiency and economic growth with innovative tools, and can decrease financing constraints of enterprises, enabling direct and indirect financing and furthering inter-bank competition. Crowdfunding- and blockchain-based fintech operations harness deep and maching learning algorithms, augmented and virtual reality technologies, and big data analytics in mobile payment transactions. Purpose of the article: We show that fintechs have reconfigured financial service delivery by harnessing AI-based data-driven algorithms and cloud and blockchain technologies. Fintech optimizes financial organization and services, economic structures and growth, data analysis, and digital banking performance.  Machine learning algorithms can streamline payment operation capabilities and process promptness, ensuring smooth operational flows, assessing risks, and detecting frauds and money laundering by historical data and customer behavior analysis across instant payment networks and infrastructures. Methods: Quality tools: AXIS, Eppi-Reviewer, PICO Portal, and SRDR. Search period: July 2023. Search terms: “fintech” + “artificial intelligence algorithms”, “cloud computing technologies”, and “blockchain technologies”. Selected sources: 40 out of 195. Published research inspected: 2023. Data visualization tools: Dimensions and VOSviewer. Reporting quality assessment tool: PRISMA. Findings & value added: Fintech development enables organizational innovation by mitigating information asymmetry and financing limitations while providing financial assistance and tax incentives in relation to products and services. The fintech growth has influenced the dynamic intermediary function of financial institutions in terms of sustainability and economic development. Fintech and natural resources negatively influence, while green innovations and financial development further, environmental sustainability.
    Źródło:
    Oeconomia Copernicana; 2023, 14, 3; 707-730
    2083-1277
    Pojawia się w:
    Oeconomia Copernicana
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Advanced methods of earnings management: monotonic trends and change-points under spotlight in the Visegrad countries
    Autorzy:
    Kliestik, Tomas
    Valaskova, Katarina
    Nica, Elvira
    Kovacova, Maria
    Lazaroiu, George
    Powiązania:
    https://bibliotekanauki.pl/articles/19233520.pdf
    Data publikacji:
    2020
    Wydawca:
    Instytut Badań Gospodarczych
    Tematy:
    business finance
    change-point
    earnings management
    monotonic trend
    European countries
    Opis:
    Research background: Enterprises manage earnings in an effort to balance their profit fluctuations to provide increasingly consistent earnings in every reporting period. Earnings management is legal and very effective method of accounting techniques and may be used to obtain specific objectives of the enterprises involving the manipulation of accruals. Therefore, there is a need to analyze it in the context of group of countries, while the issue of their detection in the new ways appears.  Purpose of the article: The analysis of annual earnings before interest and taxes (EBIT) of 5,640 enterprises from the Visegrad Four during the period 2009-2018 confirms that the development of earnings management in these countries is not a randomness. Thus, the aim of this article is to determine the existence of positive trend in earnings management and to detect the change-point in its development for each Visegrad country. Methods: Grubbs test, Mann-Kendall trend test and Buishand test were used as appropriate statistical methods. Mann-Kendall test identifies significant monotonic trend occurrence in earnings manipulation in every country. Buishand test indicates significant years, which divides the development of EBIT into two homogenous groups with individual central lines. Findings & Value added: Based on the statistical analysis applied, we rejected randomness in the managing of earning, but we determined the trend of its increasing. The positive earnings manipulation was not homogenous in the analyzed period, however, a change-point was defined. Year 2014 was identified as a break-point for Slovak, Polish and Hungarian enterprises considering the earnings manipulation. Year 2013 was detected as a change-point in Czech enterprises. The methodical approach used may be very helpful for researchers from other countries to determine, detect and understand earnings management as well as for the investors to make decisions based on a specificities of an individual country.
    Źródło:
    Oeconomia Copernicana; 2020, 11, 2; 371-400
    2083-1277
    Pojawia się w:
    Oeconomia Copernicana
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
      Wyświetlanie 1-8 z 8

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