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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:
The importance of Big Data Analytics technology in business management
Autorzy:
Pizło, Wojciech
Kulykovets, Olena
Prokopowicz, Dariusz
Mazurkiewicz-Pizło, Anna
Kałowski, Adam
Paprocka, Małgorzata W.
Stawicka, Ewa
Skarzyńska, Edyta
Powiązania:
https://bibliotekanauki.pl/articles/20311652.pdf
Data publikacji:
2023-10-31
Wydawca:
Akademia Sztuki Wojennej
Tematy:
Big Data management
Digital Twins
new technology management
Big Data
Analytics
Scopus database
Opis:
Data processing, artificial intelligence and IoT technologies are on the rise. The role of data transfer security systems and databases, known as Big Data, is growing. The main cognitive aim of the publication is to identify the specific nature of Big Data management in an enterprise. The paper uses the bibliographic Elsevier and Springer Link databases, and the Scopus abstract database. The distribution of keywords, drawing attention to four main areas related to research directions, is indicated, i.e., Big Data and the related terms „human”, „IoT” and „machine learning”. The paper presents the specific nature of Big Data together with Kitchin and McArdle’s research, indicating the need for a taxonomic ordering of large databases. The precise nature of Big Data management, including the use of advanced analytical techniques enabling managerial decision-making, was identified. The development of Cyber Production Systems (CPS), based on BD, integrating the physical world of an enterprise with the digitisation of information as the concept of Digital Twins (DTs), was also indicated. CPS offer the opportunity to increase enterprise resilience through increased adaptability, robustness and efficiency. With DTs, manufacturing costs are reduced, the product life cycle is shortened, and production quality increases.
Źródło:
Cybersecurity and Law; 2023, 10, 2; 270-282
2658-1493
Pojawia się w:
Cybersecurity and Law
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
The right time for a big bath: asset impairment recognition in earnings management
Autorzy:
Mielcarz, Paweł
Osiichuk, Dmytro
Tselinko, Inna
Powiązania:
https://bibliotekanauki.pl/articles/40713469.pdf
Data publikacji:
2023-06-15
Wydawca:
Akademia Leona Koźmińskiego w Warszawie
Tematy:
Earnings management
Big bath
Asset impairment
Opis:
Purpose – The article investigates the patterns of asset impairment recognition in search of signs of “big bath” earnings management practices across an internationally diversified sample of public companies. It also elucidates the incentives that may underlie such practices and explores possible safeguards embedded in the existing corporate governance mechanisms. Design/methodology/approach – The article applied static panel and binary logit models to an international firm-level panel dataset of 1045 public companies observed between 2003 and 2018. Findings – Our empirical results suggest that recognition of asset impairment has no determinate impact on earnings volatility. Investigating the possibility of “big bath” earnings management practices, the authors found no impact of asset impairment recognition on total senior executive compensation in firms, which pay performance-based remuneration. The quality of corporate governance has appeared to impact the firms’ intertemporal proclivity to recognize asset impairment with those having the more entrenched and management-controlled boards being more likely to time impairment recognition by delaying it during exceptionally good and exceptionally bad years. While generally unlikely, recognition of asset impairment in a period with a recorded negative operating performance is found to be closely associated with key executive departures. Originality/value – The article corroborates the salient role of corporate governance mechanisms in shaping the intertemporal patterns of asset impairment recognition. The possible remedies to the phenomenon should be derived therefrom.
Źródło:
Central European Management Journal; 2023, 31, 2; 189-206
2658-0845
2658-2430
Pojawia się w:
Central European Management Journal
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Wykorzystanie nowych narzędzi analitycznych w zarządzaniu łańcuchami dostaw – studium przedsiębiorstwa LOKAD
The use of new analytical tools in supply chain management – a case study of the company LOKAD
Autorzy:
Brandt, Arkadiusz
Powiązania:
https://bibliotekanauki.pl/articles/32443883.pdf
Data publikacji:
2023
Wydawca:
Uniwersytet Ekonomiczny w Katowicach
Tematy:
big data
data science
zarządzanie łańcuchami dostaw
SCOR
GSCF
Supply Chain Scientist
supply chain management
Opis:
Zarządzanie łańcuchami dostaw w erze współczesnej wymaga stosowania zaawansowanych narzędzi i metodologii, aby sprostać dynamicznym wyzwaniom rynkowym. Celem artykułu jest przedstawienie dwóch modeli referencyjnych w zarządzaniu łańcuchami dostaw: SCOR (Supply Chain Operations Reference) oraz GSCF (Global Supply Chain Forum). Artykuł skupia się na tym, jak wykorzystanie narzędzi big data i data science może wzmocnić te modele, umożliwiając lepsze monitorowanie, optymalizację procesów i reakcję na zmiany rynkowe. Zastosowanie tych metod w rzeczywistych środowiskach biznesowych zostało przedstawione na przykładzie implementacji technologii analizy danych w firmie LOKAD. Wyniki rozważań pokazują, że analiza danych w czasie rzeczywistym pozwala na precyzyjne prognozowanie popytu, optymalizację zapasów i identyfikację ryzyka. Na poziomie operacyjnym i taktycznym narzędzie big data może być wykorzystywane do optymalizacji tras pojazdów, zarządzania flotą, poprawy obsługi klienta i rekomendacji produktów. Na poziomie strategicznym big data wspiera projektowanie produktów, planowanie sieci i strategię biznesową.
Supply chain management in the modern era requires the use of advanced tools and methodologies to meet dynamic market challenges. The article presents two key reference models in supply chain management: SCOR (Supply Chain Operations Reference) and GSCF (Global Supply Chain Forum) and focuses on how the use of big data and data science tools can strengthen these models, enabling better monitoring, process optimization, and response to market changes. The article discusses the applications of big data and data science in supply chain management. Real-time data analysis allows for precise demand forecasting, inventory optimization, and risk identification. At the operational and tactical levels, big data can be used for optimizing vehicle routes, fleet management, improving customer service, and product recommendations. At the strategic level, big data supports product design, network planning, and business strategy. Furthermore, the article presents data science tools developed by LOKAD for supply chain management. LOKAD utilizes advanced forecasting methods, including quantile and probabilistic forecasts, to account for extreme values, and the latest approach based on differential programming enabling simultaneous optimization of multiple supply chain scenarios, ensuring excellent numerical results at minimal costs.
Źródło:
Academic Review of Business and Economics; 2023, 5(2); 65-79
2720-457X
Pojawia się w:
Academic Review of Business and Economics
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Zarządzanie wiedzą
Management of knowledge
Autorzy:
Sienicki, Marcin
Powiązania:
https://bibliotekanauki.pl/articles/27316742.pdf
Data publikacji:
2023-12-05
Wydawca:
Centralna Biblioteka Wojskowa im Marszałka Józefa Piłsudskiego
Tematy:
wiedza
zarządzanie wiedzą
bazy danych
big data
ontologie
taksonomie
katalogi
knowledge
asset management
databases
ontologies
taxonomies
catalogues
Opis:
Artykuł dotyczy zarządzania wiedzą. Celem opracowania jest zaprezentowanie w ujęciu kompleksowym koncepcji zarządzania wiedzą jako strategicznym zasobem każdej organizacji. Wyjaśniono znaczenie wiedzy, omówiono jej rodzaje, przybliżono problematykę zarządzania wiedzą, rozumianego jako proces gromadzenia, organizowania, udostępniania i wykorzystywania informacji i wiedzy w praktycznym działaniu. Szczególną uwagę poświęcono zarządzaniu wiedzą we współczesnych przedsiębiorstwach, które jest istotne z perspektywy prowadzenia biznesu. Dokonano przeglądu podejść do koncepcji zarządzania wiedzą, a także zaprezentowano narzędzia umożliwiające gromadzenie, analizowanie, przechowywanie dużych zbiorów danych i zarządzanie nimi w różnych dziedzinach nauki i przemysłu, takie jak: bazy danych (w tym big data), systemy eksperckie, platformy wyszukiwania informacji oraz technologie sieci semantycznej. Zwrócono uwagę na ontologie, taksonomie i katalogi, czyli narzędzia służące do organizacji wiedzy i danych, pełniące istotną rolę w obszarze zarządzania wiedzą, wyszukiwania danych i budowania semantycznej struktury informacji w dobie transformacji cyfrowej.
This article is about knowledge management. The aim of the study is to present a comprehensive concept of knowledge management as a strategic resource of every organization. The importance of knowledge is explained, its types are discussed, and the issues of knowledge management are presented, understood as the process of collecting, organizing, sharing and using information and knowledge in practical action. Particular attention was paid to knowledge management in modern enterprises, which is important from the perspective of running a business. Approaches to the concept of knowledge management were reviewed, and tools enabling the collection, analysis, storage and management of large data sets in various fields of science and industry were presented, such as: databases (including big data), expert systems, information search platforms and semantic web technologies. Attention is paid to ontologies, taxonomies and catalogues, i.e. tools for organizing knowledge and data, playing an important role in the area of knowledge management and data retrieval and building the semantic structure of information in the era of digital transformation.
Źródło:
Studia i Materiały Centralnej Biblioteki Wojskowej; 2023, 1, 19; 131-148
2354-0435
2719-8618
Pojawia się w:
Studia i Materiały Centralnej Biblioteki Wojskowej
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:
Big data w marketingu — narzędzie doskonalenia relacji z klientami
Big data in marketing — tool for improving customer relationships
Autorzy:
Wieczorkowski, Jędrzej
Chomiak-Orsa, Iwona
Pawełoszek, Ilona
Powiązania:
https://bibliotekanauki.pl/articles/9762473.pdf
Data publikacji:
2022-01-31
Wydawca:
Polskie Wydawnictwo Ekonomiczne
Tematy:
big data
marketing
zarządzanie relacjami z klientami
analityka biznesowa
business intelligence
customer relationship management (CRM)
business analytics
business intelligence (BI)
Opis:
Jednym z podstawowych aspektów zjawiska big data, czyli przetwarzania masowych danych, są możliwości zastosowań jego technik w zarządzaniu. Ich potencjał różni się wyraźnie w zależności od specyfiki organizacji i obszaru jej działalności. Celem artykułu jest wskazanie specyfiki i kierunków zastosowań metod big data w zakresie marketingu, ze szczególnym uwzględnieniem doskonalenia relacji z klientami. W artykule przedstawiono ogólną charakterystykę zjawiska big data w kontekście zarządzania, opisano ewolucję analityki biznesowej związaną z nowymi możliwościami przetwarzania masowych danych oraz wskazano przykładowe obszary zastosowań big data w zakresie doskonalenia relacji z klientami, które potwierdzają tezę o wysokiej przydatności tych metod w marketingu.
One of the fundamental aspects of the big data phenomenon is the possibility of application in management. This potential differs depending on the specifics of the organization and the area of application. The article aims to indicate the specificity and directions of applying big data methods in marketing, with particular emphasis on improving customer relationships. After presenting the general characteristics of the big data phenomenon in management, the evolution of business analytics related to new possibilities of mass data processing was described. Then, the focus was on the examples of big data applications in improving customer relationships, which confirms the thesis that these methods are very useful in marketing.
Źródło:
Marketing i Rynek; 2022, 1; 3-9
1231-7853
Pojawia się w:
Marketing i Rynek
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Implementation of Industry 4.0 Techniques in Lean Production Technology: A Literature Review
Autorzy:
Lucantoni, Laura
Antomarioni, Sara
Ciarapica, Filippo Emanuele
Bevilacqua, Maurizio
Powiązania:
https://bibliotekanauki.pl/articles/2172180.pdf
Data publikacji:
2022
Wydawca:
Polska Akademia Nauk. Czytelnia Czasopism PAN
Tematy:
industry 4.0
lean management
total productive maintenance
big data analytics
VOSviewer
Opis:
Lean thinking and Industry 4.0 have been broadly investigated in recent years in intelligent manufacturing. Lean Production is still one of the most efficient industrial solutions in business and research, despite being implemented for a long time. On the other hand, Industry 4.0 has been introduced referring to the fourth industrial revolution. This study aims to analyze the combination of both Industry 4.0 and Lean production practices through a systematic literature review from a Lean Automation perspective. In this field, 189 articles are examined using VOSviewer for cluster analysis. Then, a more detailed analysis is provided to explore how Industry 4.0 and Lean techniques are integrated from a practical perspective. Results highlighted Big Data Analysis and Value Stream Mapping as the most common techniques, also emphasizing a growing trend toward new publications. Nevertheless, few practical applications are identified in the literature highlighting six gaps in the correlation of LA practices.
Źródło:
Management and Production Engineering Review; 2022, 13, 3; 83--93
2080-8208
2082-1344
Pojawia się w:
Management and Production Engineering Review
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Small Farms as “Data Producers” for the Needs of Agricultural Management Information System
Autorzy:
Zysk, Elżbieta
Mroczkowski, Tomasz
Dawidowicz, Agnieszka
Powiązania:
https://bibliotekanauki.pl/articles/2105521.pdf
Data publikacji:
2022
Wydawca:
Akademia Górniczo-Hutnicza im. Stanisława Staszica w Krakowie. Wydawnictwo AGH
Tematy:
Agriculture Management Information System
agriculture
information technology
big data
precision agriculture
Opis:
In the face of current global threats, including the COVID-19 Pandemic, new technological solutions are needed. Globalization, progressing urbanization, the decreasing availability of cultivable land for food production, water contamination, flood risk and climate change, can all be viewed as potential threats to food safety. According to forecasts and trends, the future of both agricultural policy and agricultural innovation will be based on big data, data analytics and machine learning. Therefore, it is and will continue to be important to develop information systems dedicated to agricultural innovation and the management of food security challenges. The main aim of the study is a classification of data for a uniform AMIS from data from IREIS, GC and AIIS based on survey and expert interview data obtained. We propose to expand the range of data produced by small farmers while keeping in mind the protection of farmers and their rights and the possible benefits of the data provided. The literature recognizes the value of such data but it has not yet been legally regulated, protected, managed and, above all, properly used for agricultural and food security policy purposes. Therefore, we develop the idea of extended farmers’ participation in the production of agricultural activity data. The research used a survey questionnaire and expert interviews. A viable AIIS needs current data that farmers already produce as well as additional data needs which we identify in our research. We propose an architecture of databases and describe their flow in the Agriculture Management Information System (AMIS).
Źródło:
Geomatics and Environmental Engineering; 2022, 16, 3; 79--109
1898-1135
Pojawia się w:
Geomatics and Environmental Engineering
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Kalkulacja różnic memoriałowych a wykrywanie technik rachunkowego kształtowania wyniku finansowego w przedsiębiorstwach przemysłowych
Evaluation of Accruals and Detection of Accrual‑Based Earnings Management in Industrial Enterprises
Autorzy:
Comporek, Michał
Powiązania:
https://bibliotekanauki.pl/articles/1627322.pdf
Data publikacji:
2021-08-10
Wydawca:
Uniwersytet Łódzki. Wydawnictwo Uniwersytetu Łódzkiego
Tematy:
kształtowanie wyniku finansowego
różnice memoriałowe
model Jones
zmodyfikowany model Jones
wielka kąpiel kosztowa
accrual-based earnings management
accruals
the Jones model
the Modified Jones model
big bath
Opis:
Zasadniczym celem artykułu jest scharakteryzowanie rachunkowych różnic memoriałowych powstałych w wyniku zastosowania przy ich obliczaniu podejścia bilansowego bądź kategorii zaczerpniętych z rachunku przepływów pieniężnych, jak również zbadanie relacji zachodzących między wartościami dyskrecjonalnych różnic memoriałowych w przedsiębiorstwach implementujących określone strategie zarządzania zyskiem typu rachunkowego oraz w spółkach niewdrażających tego typu praktyk. Uzyskane wyniki badań empirycznych wykazały między innymi, iż dobór metodologii wyznaczania całkowitych różnic memoriałowych w znacznym stopniu wpływa na wartości parametrów strukturalnych widniejących w określonych modelach ekonometrycznych, służących do predykcji księgowego zarządzania zyskiem. Wszystko to sugeruje, iż przyjęty sposób obliczania różnic memoriałowych w ogromnej mierze wpływać może na dalsze szacunki skali i kierunków intencjonalnego kształtowania wyniku finansowego przedsiębiorstw.
The main aim of the paper was to characterize the accruals arising from the use of the balance sheet approach or categories taken from the cash flow statement in their calculation, as well as to examine the relationships between the values of discretionary accruals in the enterprises implementing specific strategies of accrual-based earnings management and in companies that not implement these practices. The obtained results of empirical research showed, inter alia, that the selection of the methodology for computing of total accruals significantly influenced the values of structural parameters appearing in specific econometric models used to predict AEM practices. All this may suggest that the adopted method of calculating the different subcomponents of accruals may largely affect the further estimates of the scale and directions of intentional shaping of the financial result of enterprises.
Źródło:
Acta Universitatis Lodziensis. Folia Oeconomica; 2021, 3, 354; 35-55
0208-6018
2353-7663
Pojawia się w:
Acta Universitatis Lodziensis. Folia Oeconomica
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Rzeczowe zarządzanie zyskiem jako instrument kształtowania dużych strat w przedsiębiorstwach przemysłowych
Real earnings management as a tool for big bath creating in industrial companies
Autorzy:
Comporek, Michał
Powiązania:
https://bibliotekanauki.pl/articles/1878745.pdf
Data publikacji:
2021-09-30
Wydawca:
Uniwersytet Łódzki. Wydawnictwo Uniwersytetu Łódzkiego
Tematy:
real earnings management
big bath
industrial enterprises
Warsaw Stock Exchange
Roychowdhury models
Opis:
The purpose of the article/hypothesis: The aim of the paper is to show the importance of the implemented real earnings management (REM) in the intentional shaping of large losses in public industrial enterprises listed on the Warsaw Stock Exchange. Methodology: The basic method of assessing the REM activities was compliant with the Roychowdhury methodology, enabling the estimation of the abnormal levels of: operational cash flows, production costs and discretionary expenses. In turn, the modified verision of iosik model was used to assess the impact of REM practices on the frequency of large losses in tested sample. Results of the research: The obtained results show that the REM implemented by means of overproduction, granting above-average rebates and a liberal approach in the field of trade credits may be considered an important path of intentional deepening of the net loss in public industrial companies.
Źródło:
Finanse i Prawo Finansowe; 2021, 3, 31; 25-39
2391-6478
2353-5601
Pojawia się w:
Finanse i Prawo Finansowe
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Big data-driven framework for viral churn prevention: a case study
Autorzy:
Lucantoni, Laura
Antomarioni, Sara
Bevilacqua, Maurizio
Ciarapica, Filippo E.
Powiązania:
https://bibliotekanauki.pl/articles/406954.pdf
Data publikacji:
2020
Wydawca:
Polska Akademia Nauk. Czytelnia Czasopism PAN
Tematy:
Big Data Analytics
Machine Learning
Probability Estimation Trees
Customer Value Management
ICT sector
Opis:
The application of churn prevention represents an important step for mobile communication companies aiming at increasing customer loyalty. In a machine learning perspective, Customer Value Management departments require automated methods and processes to create marketing campaigns able to identify the most appropriate churn prevention approach. Moving towards a big data-driven environment, a deeper understanding of data provided by churn processes and client operations is needed. In this context, a procedure aiming at reducing the number of churners by planning a customized marketing campaign is deployed through a data-driven approach. Decision Tree methodology is applied to drow up a list of clients with churn propensity: in this way, customer analysis is detailed, as well as the development of a marketing campaign, integrating the individual churn model with viral churn perspective. The first step of the proposed procedure requires the evaluation of churn probability for each customer, based on the influence of his social links. Then, the customer profiling is performed considering (a) individual variables, (b) variables describing customer-company interactions, (c) external variables. The main contribution of this work is the development of a versatile procedure for viral churn prevention, applying Decision Tree techniques in the telecommunication sector, and integrating a direct campaign from the Customer Value Management marketing department to each customer with significant churn risk. A case study of a mobile communication company is also presented to explain the proposed procedure, as well as to analyze its real performance and results.
Źródło:
Management and Production Engineering Review; 2020, 11, 3; 38-47
2080-8208
2082-1344
Pojawia się w:
Management and Production Engineering Review
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
How can soft skills be integrated into the process in a helpful way when deciding on an investment request? Intangible asset management and conversation analysis as possible tools for investors
Autorzy:
Lange, Jürgen
Markovic, Peter
Powiązania:
https://bibliotekanauki.pl/articles/2130028.pdf
Data publikacji:
2020
Wydawca:
Instytut Studiów Międzynarodowych i Edukacji Humanum
Tematy:
Investment
Investors
Business Start-up
Intangible Asset Management
Big Data
Communication Analysis
Opis:
According to the latest reports, obtaining a loan as a company seems to be becoming increasingly easy, but it is still noticeable that a good quarter of small and young companies in the start-up phase in particular are still being turned down for financing. In order not to make the failure rate dependent on mathematical-scalable values alone and to give the really good companies and business ideas a realistic chance, more soft skills must be included in the decision-making process in addition to the pure hard facts. Solutions could be found here in Intangible Asset Management and a more in-depth credit discussion analysis with the help of Big Data possibilities.
Źródło:
Humanum. Międzynarodowe Studia Społeczno-Humanistyczne; 2020, 2(37); 107-117
1898-8431
Pojawia się w:
Humanum. Międzynarodowe Studia Społeczno-Humanistyczne
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Wykorzystanie big data w zarządzaniu zielonym łańcuchem dostaw
Use of Big Data in green supply chain management
Autorzy:
Kręt, Paulina
Powiązania:
https://bibliotekanauki.pl/articles/1194485.pdf
Data publikacji:
2020
Wydawca:
Politechnika Wrocławska. Oficyna Wydawnicza Politechniki Wrocławskiej
Tematy:
zarządzanie
łańcuch dostaw
nowe technologie
Big Data
ekologia
management
supply chain
new technologies
ecology
Opis:
The aim of the article was to show the possibility of applying the Big Data concept in the management of a sustainable, green supply chain. This topic was taken up because new technologies and ecology are currently the greatest challenges for logistics. At the beginning of the study, the impact of ecology on logistics was briefly presented. Then, the meaning of the Big Data concept and how the digitization of the supply network manifests itself were shown. Finally, the possibilities of using data analysis in green supply chain management were selected.
Źródło:
Journal of TransLogistics; 2020, 6, 1; 49--56
2450-5870
Pojawia się w:
Journal of TransLogistics
Dostawca treści:
Biblioteka Nauki
Artykuł
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