FOREIGN DIRECT INVESTMENTS AND DOMESTIC INVESTMENTS IN ROMANIA IN THE ECONOMIC CRISIS PERIOD

Investments represent one of the most important factors of the economic growth as well as of the exit from crisis and economic re-launching. The paper analyzes the investments evolution (foreign and domestic) in Romania under the crisis circumstances, taking into account the main factors of influence. Based on the analysis of Romania’s investment process, in the period 2005-2010, several proposals are made aiming at the improvement of investment mechanisms and their sources of funding, including the increase in Romania’s absorption capacity of EU structural and cohesion funds in the period 2007-2013.investment; economic growth; foreign and domestic investments; economic crisis; sources of funding

ECONOMIC EFFICIENCY AND PROFITABILITY

Economic efficiency is a term used to estimate the results of an economic activitycomparing to the efforts involved in the respective activity. Economic efficiency is themain qualitative factor of economic growth, as it assures the absolute growth of theoutcome at the same effort amount. Economic efficiency includes profitability, which is ageneral indicator for efficiency

Dimensions of the company’s efficiency

The synthetic concept of business activity assessment, effectiveness circumscribe their theoretical and practical, a multi-dimensional configuration, which gives supportive and evaluative irrelevant in the field of business. In this sense, can be highlighted five dimensional coordinates business efficiency, coordinated, from different perspectives, trying to capture the synergy of effort and effect involved in the definition of efficiency.Multidimensional approach in four dimensions will be formalized through an array of dimensional coordinates of efficiency, which would allow revealing co-determinations of the defining elements of efficiency, both of those characteristics, their effort and effect, and synthesis of the characteristic of interaction between them.Business efficiency, in its essence and wholeness, integrative evaluative dimension is placed in a network of co-determination and interactions, at least, highlighted dimensional coordinates, measure the effectiveness and could only be realized through a system of interrelated indicators, each revealing a dimensional aspects relevant in a given evaluative context. 

Foreign direct investments and domestic investments in Romania in the economic crisis period

Investments represent one of the most important factors of the economic growth as well as of the exit from crisis and economic re-launching. The paper analyses the investments evolution (foreign and domestic) in Romania under the crisis circumstances, taking into account the main factors of influence. Based on the analysis of Romania’s investment process, in the period 2005-2010, several proposals are made aiming at the improvement of investment mechanisms and their sources of funding, including the increase in Romania’s absorption capacity of EU structural and cohesion funds in the period 2007-2013.  

Analysis of the evolution of foreign direct investment in the European Union, amid the global economic crisis

A particularly important role in global economic growth is played by foreign direct investment. The host country receiving the investment attracts new, updated technologies, efficient management and as such can provide a strong impetus for economic growth. This paper presents the analysis of FDI flow and stock from EU member countries in the period 2000-2013, by groups of countries, sectors and branches of the economy, as well as an international comparative analysis of trends in foreign direct investment in Romania and other countries performed in order to identify similarities and disparities

VAR analysis on Foreign Direct Investment in Romania

A research analysis of the impact of FDI on GDP, exports and imports in Romania, on the basis of econometric models, provides us with an opportunity to examine how they have established in the transition period a number of interdependencies, more or less intense, among the variables mentioned above. In a way, the analysis which we performed gives us an opportunity to see not only the rigid positions of explained and explanatory variables, but also a change in the causality among these, which can be identified, both by different sizes of elasticity coefficients and by applying Vector Autoregresive model (VAR). The purpose of such a quantitative analysis based on patterns of foreign direct investment, was to identify the two-way relationship, with different intensities from one period to another, of the FDI and their determinants as well as among the indicators of performance of the Romanian economy and foreign direct investment, as a major factor of influence. We apply the VAR technique to quantify the parameters of elasticity between FDI, as an explained and/or explanatory variable and other factors in the cause-effect relationship. The VAR analysis was based on data obtained from NOTR (National Office of Trade Registrar), NBR (National Bank of Romania) and NIS (National Institute of Statistics) for FDI, GDP indicators, export and import indicators for the period 1997-2011

Neuromanagement decision making in facial recognition biometric authentication as a mobile payment technology in retail, restaurant, and hotel business models

Research background: With growing evidence of biometric identification techniques as authentication, there is a pivotal need for comprehending contactless payments by use of facial recognition algorithms in retail, restaurant, and hotel business models. Purpose of the article: In this research, previous findings were cumulated showing that harnessing facial recognition payment applications as software-based contactless biometric algorithms results in remarkably qualitative enhancement in purchasing experience. Methods: Throughout March and November 2021, a quantitative literature review of the Web of Science, Scopus, and ProQuest databases was carried out, with search terms including "facial recognition payment technology", "facial recognition payment system", "facial recognition payment application", "face recognition-based payment service", "facial authentication for mobile payment transactions", and "contactless payment through facial recognition algorithms". As the analyzed research was published between 2017 and 2021, only 187 articles satisfied the eligibility criteria. By removing questionable or unclear findings (limited/nonessential data), results unsubstantiated by replication, too general content, or having quite similar titles, 38, mainly empirical, sources were selected. The Systematic Review Data Repository was harnessed, a software program for the gathering, processing, and analysis of data for our systematic review. The quality of the selected scholarly sources was assessed by employing the Mixed Method Appraisal Tool. Findings & value added: Harnessing facial recognition payment applications as software-based contactless biometric algorithms results in remarkably qualitative enhancement in purchasing experience. Subsequent attention should be directed to whether perceived value and trust shape customers' adoption of biometric recognition payment devices

Artificial intelligence algorithms and cloud computing technologies in blockchain-based fintech management

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

Deep Learning-Assisted Smart Process Planning, Robotic Wireless Sensor Networks, and Geospatial Big Data Management Algorithms in the Internet of Manufacturing Things

The purpose of our systematic review is to examine the recently published literature on the Internet of Manufacturing Things (IoMT), and integrate the insights it configures on deep learning-assisted smart process planning, robotic wireless sensor networks, and geospatial big data management algorithms by employing Preferred Reporting Items for Systematic Reviews and Meta-analysis (PRISMA) guidelines. Throughout October 2021 and January 2022, a quantitative literature review of aggregators such as ProQuest, Scopus, and the Web of Science was carried out, with search terms including “deep learning-assisted smart process planning + IoMT”, “robotic wireless sensor networks + IoMT”, and “geospatial big data management algorithms + IoMT”. As the analyzed research was published between 2018 and 2022, only 346 sources satisfied the eligibility criteria. A Shiny app was leveraged for the PRISMA flow diagram to comprise evidence-based collected and handled data. Major difficulties and challenges comprised identification of robust correlations among the inspected topics, but focusing on the most recent and relevant sources and deploying screening and quality assessment tools such as the Appraisal Tool for Cross-Sectional Studies, Dedoose, Distiller SR, the Mixed Method Appraisal Tool, and the Systematic Review Data Repository we integrated the core outcomes related to the IoMT. Future research should investigate dynamic scheduling and production execution systems advanced by deep learning-assisted smart process planning, data-driven decision making, and robotic wireless sensor networks