Search

Research background: Big data-driven artificial Internet of Things (IoT) fintech algorithms can provide real-time personalized financial service access, strengthen risk management, and manage, monitor, and mitigate transaction operational risks by operational credit risk management, suspicious financial transaction abnormal pattern detection, and synthetic financial data-based fraud simulation. Blockchain technologies, automated financial planning and investment advice services, and risk scoring and fraud detection tools can be leveraged in financial trading forecasting and planning, cryptocurrency transactions, and financial workflow automation and fraud detection. Algorithmic trading and fraud detection tools, distributed ledger and cryptocurrency technologies, and ensemble learning and support vector machine algorithms are pivotal in predictive analytics-based risk mitigation, customer behavior and preference-based financial product and service personalization, and financial transaction and fraud detection automation. Credit scoring and risk management tools can offer financial personalized recommendations based on customer data, behavior, and preferences, in addition to transaction history, by generative adversarial and deep learning recurrent neural networks. Purpose of the article: We show that blockchain and edge computing technologies, generative artificial IoT-based fintech algorithms, and transaction monitoring and credit scoring tools can be harnessed in financial decision-making processes and loan default rate mitigation for transaction, payment, and credit process efficiency. Generative and predictive artificial intelligence (AI) algorithmic trading systems can drive coherent customer service operations, provide tailored financial and investment advice, and influence financial decision processing, while performing real-time risk assessment and financial and trading risk scenario simulation across fluctuating market conditions. Fraud and money laundering prevention tools, blockchain and financial transaction technologies, and federated and decentralized machine learning algorithms can articulate algorithmic profiling-based transaction data patterns and structures, credit assessment, loan repaying likelihood prediction, and interest rate and credit lending risk management by real-time financial pattern and economic forecast-based credit analysis across investment payment and transaction record infrastructures. Methods: Research published between 2023 and 2024 was identified and analyzed across ProQuest, Scopus, and the Web of Science databases by use of screening and quality assessment software systems such as Abstrackr, AMSTAR, AXIS, CADIMA, CASP, Catchii, DistillerSR, Eppi-Reviewer, MMAT, Nested Knowledge, PICO Portal, Rayyan, ROBIS, and SRDR+. Findings & value added: The main value added derived from the systematic literature review is that generative AI-based operational risk management, fraud detection, and transaction monitoring tools can provide personalized financial support and services and clarify financial and credit decisions and operations by financial decision-making process automation in dynamic business environments based on fraud detection capabilities and transaction data analysis and assessment. The benefits for theory and current state of the art are that credit risk and financial forecasting tools, artificial IoT-based fintech and generative AI algorithms, and algorithmic trading and distributed ledger technologies can be deployed in financial decisionmaking and customer behavior pattern optimization, credit score assessment, and money laundering and fraudulent payment detection. Policy implications reveal that investment management and algorithmic credit scoring tools can streamline financial activity operational efficiency, design financial planning analysis and forecasting, and carry out financial service and transaction data analysis for informed transaction decision-making and fraudulent behav ior pattern and incident detection, taking into account credit history and risk evaluation and improving personalized experiences. [ABSTRACT FROM AUTHOR]

We inspect the relevant literature on sustainable smart manufacturing in Industry 4.0, providing both quantitative evidence on trends and numerous indepth empirical examples. Building our argument by drawing on data collected from BDC, BDO, Deloitte, eMarketer, McKinsey, and PwC, we performed analyses and made estimates regarding companies deploying artificial intelligence at scale (%, by industry) and applications of Industry 4.0 in small and mid-sized businesses (%). Data collected from 4,300 respondents are tested against the research model by using structural equation modeling. [ABSTRACT FROM AUTHOR]

Employing recent research results covering big data-driven algorithmic decision-making in selecting and managing employees, and building our argument by drawing on data collected from Bright & Company, Corporate Research Forum, Deloitte, Management Events, McKinsey, and Top Employers Institute, we performed analyses and made estimates regarding data-driven approaches in organizations. Structural equation modeling was used to analyze the collected data. [ABSTRACT FROM AUTHOR]

Starting with 1999 the concept of "decent work" was launched, through the Report of the Director-General at the International Labor Conference meeting in its 87th Session; since then it has become the primary goal of the ILO and subject of debate and study for scholars, politicians and specialized organizations. The majority of scholars define a generation by a specific time period and shared history. In Romania, if we focus on 2016's working-age population (persons aged 18 to 65 years old), three generations coexist on the labor market: Baby Boomers (about 20%), Gen Xers (34%) and Millennials (about 46%). From the workaholic Baby Boomers to the nonconformists Millennials, the labor market conditions have been redesigned and reshaped so that to attenuate the generational conflict. This study is focused on Romanian generations' interests that will move the employment in the direction of decent work. [ABSTRACT FROM AUTHOR]

At present, one of the major concerns of the European Union is the creation of a Europe of knowledge where people will be able to live and operate in a competitive environment based on knowledge. The European Council in Lisbon (March 2000) set the strategic goal for Europe to become the most competitive and dynamic knowledge economy in the world, capable of sustainable economic growth, with more and better jobs and increased social cohesion. The educational system of adaptation to the new requirements does not involve copying Western models - in whose framework specialists regularly complain of dysfunctional phenomena - but also compliance with the specific requirements of modern economies, organized on competitive basis; it also means observing the criticism of Western examples and creating own systems that take into account the requirements of European and national social and economic context, because European integration implies a unity in diversity. [ABSTRACT FROM AUTHOR]

The process chosen by our team is called satisfaction survey. To optimize this process, we examined how this procedure is currently conducted and proposed the establishment of a special department to monitor the labor market insertion of graduates at the Spiru Haret University, namely the Faculty of Financial Accounting Management Constanta. [ABSTRACT FROM AUTHOR]

In this paper we propose to evaluate the current state of participative management in Romanian companies. In order to achieve that we used a questionnaire to evaluate managerial functions and we applied it in four Romanian companies. [ABSTRACT FROM AUTHOR]

Improving management in general and human resource management, in particular, is imposing also in Romanian economic practice in a coordinated major of obtaining competitive advantage. We felt that the firm via contact with businesses competitive within the country and abroad has the highest elevation in urgent need of human resource management. So, we based our research on two questionnaires to see which the Romanian human resources management current state is. [ABSTRACT FROM AUTHOR]

Pay systems covered, all that exists in practice and especially in economic theory is a historically accumulated treasure, this treasure of payroll systems extends far diversify and create new ones. We may say that this treasury payroll system is a kind of a ''tool box'' says the English economist Joan Robinson, referring to a set of research methods1. From this "tool box" that continuously enriches compared with the conditions and needs in relation to economic development and possibly acquiring firms adapt systems they need at any stage of economic development. The evolution of pay systems introduces us to the natural history of pay systems, the onset of industrialization and even today. We can say that is a relationship between them as part of the whole. [ABSTRACT FROM AUTHOR]