В умовах воєнної невизначеності та економічної дестабілізації особливої актуальності набувають питання ефективного фінансового забезпечення діяльності підприємств як ключового чинника їх стійкості та відновлення. Визначальним є пошук нових інструментів мобілізації фінансових ресурсів, що сприятимуть післявоєнному розвитку економіки України. Метою статті є поглиблення теоретичних засад і узагальнення практичних аспектів фінансового забезпечення функціонування та розвитку підприємств України з урахуванням впливу воєнних ризиків і нестабільності зовнішнього середовища. У роботі використано комплексний науковий підхід, що поєднує теоретичне узагальнення, системний, порівняльний, структурно-динамічний аналіз. Дослідження базується на статистичних даних за 2013–2024 рр., що дало змогу простежити трансформації у складі джерел фінансування підприємств та оцінити ефективність механізмів фінансового забезпечення. Теоретичне значення роботи полягає у систематизації наукових підходів до визначення сутності поняття «фінансове забезпечення підприємства» та запропоновано власне трактування даної категорії як інтегрованої системи організаційно-економічних, правових, фінансово-управлінських і контрольно-аналітичних механізмів. У ході дослідження здійснено оцінювання структури джерел фінансування підприємств України; виявлено домінування короткострокових зобов’язань і недостатність власних та довгострокових ресурсів. Охарактеризовано трансформацію механізму фінансового забезпечення в умовах війни; систематизовано джерела фінансування у довоєнний, воєнний і повоєнний періоди. Обґрунтовано стратегічні напрями підвищення ефективності фінансового забезпечення діяльності суб’єктів господарювання. Оригінальність дослідження визначається інтеграцією макро- і мікрорівневих аспектів фінансового забезпечення та розробленням адаптивного механізму, що враховує особливості воєнної економіки. Практична цінність полягає у можливості використання запропонованих рекомендацій при формуванні фінансових стратегій підприємств. Подальші дослідження доцільно зосередити на кількісному моделюванні впливу державних і міжнародних джерел фінансування на економічне відновлення підприємств.
Economics as a science, Business records management
Ion Popa, Sorina-Geanina Stănescu, Anișoara Duică
et al.
The food industry faces complex challenges in managing supply chains, significantly
affecting operational performance and costs. This paper explores the critical factors
influencing the efficiency of food supply chains, such as product perishability, seasonality,
climate change, and high logistics costs. The study uses an applied approach based on
modelling a cost function that integrates the main components of supply chain expenses —
procurement, transportation, warehousing, production and distribution — and how they are
affected by industry-specific challenges. The proposed cost function allows for assessing the
impact of these variables on total costs and identifying critical areas for optimisation. The
results obtained demonstrate that monitoring logistical conditions, adjusting stocks based on
seasonal forecasts and optimising transport routes are essential measures to reduce losses and
increase the competitiveness of companies in the food industry. The study's applied impact
consists of providing a practical cost optimisation tool applicable to manufacturers and
distributors. The conclusions emphasise the importance of an integrated approach to risk and
cost management in the food industry, providing recommendations for sustainable practices
and strategies to increase long-term competitiveness.
Nadya Carissa Fernanda Putri, Nabila Kharimah Vedy
This study aims to examine the effects of service quality, customer perceived value, and trust on customer satisfaction, while also analyzing the meditating role of trust. Consumer shopping behavior has shifted alongside the growth of internet usage, leading to the rapid development of online food delivery (OFD) services. Online food delivery enables customers to conveniently order meals online and receive delivery directly to their address. In this highly competitive business environment, understanding the determinants of customer satisfaction is crucial. This study aims to examine service quality, customer perceived value, and trust in relation to customer satisfaction, both directly and to investigate the role of trust as a mediator. A quantitative research design was adopted and analyzed using PLS-SEM with the SmartPLS software. Data were collected through an online survey of 175 ShopeeFood users. The results reveal that service quality, customer perceived value, and trust significantly and positively influence customer satisfaction. Furthermore, trust is confirmed as a significant mediator in the relationship between service quality and customer perceived value toward customer satisfaction.
An axiomatic approach to macroeconomics based on the mathematical structure of thermodynamics is presented. It deduces relations between aggregate properties of an economy, concerning quantities and flows of goods and money, prices and the value of money, without any recourse to microeconomic foundations about the preferences and actions of individual economic agents. The approach has three important payoffs. 1) it provides a new and solid foundation for aspects of standard macroeconomic theory such as the existence of market prices, the value of money, the meaning of inflation, the symmetry and negative-definiteness of the macro-Slutsky matrix, and the Le Chatelier-Samuelson principle, without relying on implausibly strong rationality assumptions over individual microeconomic agents. 2) the approach generates new results, including implications for money flow and trade when two or more economies are put in contact, in terms of new concepts such as economic entropy, economic temperature, goods' values and money capacity. Some of these are related to standard economic concepts (eg marginal utility of money, market prices). Yet our approach derives them at a purely macroeconomic level and gives them a meaning independent of usual restrictions. Others of the concepts, such as economic entropy and temperature, have no direct counterparts in standard economics, but they have important economic interpretations and implications, as aggregate utility and the inverse marginal aggregate utility of money, respectively. 3) this analysis promises to open up new frontiers in macroeconomics by building a bridge to ideas from non-equilibrium thermodynamics. More broadly, we hope that the economic analogue of entropy (governing the possible transitions between states of economic systems) may prove to be as fruitful for the social sciences as entropy has been in the natural sciences.
Vladimir Skavysh, Sofia Priazhkina, Diego Guala
et al.
Computational methods both open the frontiers of economic analysis and serve as a bottleneck in what can be achieved. We are the first to study whether Quantum Monte Carlo (QMC) algorithm can improve the runtime of economic applications and challenges in doing so. We provide a detailed introduction to quantum computing and especially the QMC algorithm. Then, we illustrate how to formulate and encode into quantum circuits (a) a bank stress testing model with credit shocks and fire sales, (b) a neoclassical investment model solved with deep learning, and (c) a realistic macro model solved with deep neural networks. We discuss potential computational gains of QMC versus classical computing systems and present a few innovations in benchmarking QMC.
This study aims to analyze the effects of capital intensity, audit quality, thin capitalization, and gender diversity on tax aggressiveness in state-owned enterprises (SOEs) listed on the Indonesia Stock Exchange (IDX) from 2020 to 2023. This research adopts a quantitative approach with an associative method, and the sample is selected using purposive sampling based on criteria such as SOEs listed on IDX, financial reports expressed in Indonesian Rupiah, and excluding the banking sector. The dependent variable is tax aggressiveness, measured using the Effective Tax Rate (ETR), while the independent variables are capital intensity, audit quality, thin capitalization, and gender diversity. Data analysis is performed using multiple linear regression and classical assumption tests to ensure the validity of the regression model. The findings indicate that capital intensity, audit quality, thin capitalization, and gender diversity significantly affect tax aggressiveness. This research has limitations, such as the restriction to SOEs and a three-year observation period. Future research is suggested to expand the scope by using the IDX-IC classification and extending the study period, as well as considering additional variables such as firm size and ownership structure.
In this chapter I explore the influence of the local ecology, also known as contextual or area effects, on two focal demographic outcomes, fertility and mortality. I start by outlining why ecological effects have been of interest to evolutionary scholars, provide a brief overview of life history theory as a theoretical framework and the type of data from traditional, small-scale populations that have been used to test predictions. Key evolutionary concepts such as extrinsic mortality risk and phenotypic plasticity are explained. I then compare and contrast this perspective to how contextual effects have been tackled by non-evolutionary scholars within demography and related disciplines, drawing on studies mainly from high-income contexts based on broad population register data. In the final part of the chapter I lay out some challenges for this research area, which include addressing selection biases and attaining a greater understanding of underlying causal mechanisms. Future research is likely to be more fruitful if evolutionary and non-evolutionary lines of enquiry become increasingly integrated.
Recent developments in computing, data entry and generation, and analytic tools have changed the landscape of modern demography and health research. These changes have come to be known as computational demography, big data, and precision health in the field. This emerging interdisciplinary research comprises social scientists, physical scientists, engineers, data scientists, and disease experts. This work has changed how we use administrative data, conduct surveys, and allow for complex behavioral studies via big data (electronic trace data from mobile phones, apps, etc.). This chapter reviews this emerging field's new data sources, methods, and applications.
We present the opportunities and limitations of administrative benefits data held by local authorities for data linkage projects. Whilst the richness of this data has been exploited by practitioners for administration, its potential remains little explored by researchers. We discuss data quality, sample selection and legal gateways for data sharing.
Drawing on our experience working with over 40 local authorities, we present the structure of three datasets: the Council Tax Reduction Scheme, the Single Housing Benefits Extract and the Universal Credit Data Share. We show what variables are usually included, under which legal gateways this data can be shared and how the cohorts represented within the data compare with the low-income population. We discuss how these datasets can be linked at the household level with a number of other data held by local authorities such as social rent and Council Tax arrears, Housing Benefit overpayments and Discretionary Housing Payments (DHPs).
Administrative benefits data provides a comprehensive snapshot of a household’s financial situation. Local authorities can proactively use and share this data with external data processors to fulfil their statutory duties if a legal gateway allows. By identifying households at risk of cash shortfalls before they reach a crisis point, councils can target support when administering local welfare schemes and preventing homelessness. By assessing eligibility for benefits, they can run data-driven uptake campaigns. This data captures a proportion of the population on national and local benefits within a local authority at several points in time. Attrition is of concern since households may leave datasets over time. Some will see their income rise and no longer qualify for benefits. Others will move out of the constituency.
Local authorities routinely process longitudinal data on households receiving means-tested benefits by administering housing benefits, council tax support, and discretionary support funds. This data provides a unique real-time insight into the socioeconomic situation of low-income households. Yet, we show that its promising potential for policy research remains largely untapped.
Macroeconomics essentially discusses macroeconomic phenomena from the perspectives of various schools of economic thought, each of which takes different views on how macroeconomic agents make decisions and how the corresponding markets operate. Therefore, developing a clear, comprehensive understanding of how and in what ways these schools of economic thought differ is a key and a prerequisite for economics students to prosper academically and professionally in the discipline. This becomes even more crucial as economics students pursue their studies toward higher levels of education and graduate school, during which students are expected to attain higher levels of Bloom's taxonomy, including analysis, synthesis, evaluation, and creation. Teaching the distinctions and similarities of the two major schools of economic thought has never been an easy task to undertake in the classroom. Although the reason for such a hardship can be multi-fold, one reason has undoubtedly been students' lack of a holistic view on how the two mainstream economic schools of thought differ. There is strong evidence that students make smoother transition to higher levels of education after building up such groundwork, on which they can build further later on (e.g. Didia and Hasnat, 1998; Marcal and Roberts, 2001; Islam, et al., 2008; Green, et al., 2009; White, 2016). The paper starts with a visual spectrum of various schools of economic thought, and then narrows down the scope to the classical and Keynesian schools, i.e. the backbone of modern macroeconomics. Afterwards, a holistic table contrasts the two schools in terms of 50 aspects. Not only does this table help economics students enhance their comprehension, retention, and critical-thinking capability, it also benefits macroeconomic instructors to ...
This study investigates whether earnings quality affects to asymmetric cost behavior, i.e., sticky cost of listed firms of Jakarta Stock Exchange (JKSE). This study analyzes 1032 year-firms observations during 2012-2019 periods. This study investigates earnings quality on listed firms of JKSE during the period of IFRS adoption in 2012 and implementation of sustainability reporting voluntarily. This study finds that earnings quality influence to cost stickiness is supported. However, earnings quality negatively influences cost stickiness. The result of this study indicates that there is likely the effect of IFRS adoption in 2012 and implementation of sustainability reporting voluntarily since 2010 from listed firms on the JKSE on its earnings quality. This result is consistent with study of Banker, Basu, Byzalov, &Chen (2016). So higher earnings quality, lower cost stickiness. This study contributes theoretically to the literature on financial accounting, management accounting and cost management related to the topic of asymmetric cost behavior on earnings characteristics. This research also contributes practically to the ability of earnings quality in listed firms of the JKSE to reflect information on their financial performance related to the earnings quality by investors and financial analysts.
Most explanations of economic growth are based on knowledge spillovers, where the development of some technologies facilitates the enhancement of others. Empirical studies show that these spillovers can have a heterogeneous and rather complex structure. But, so far, little attention has been paid to the consequences of different structures of such cross-technology interactions: Is economic development more easily fostered by homogenous or heterogeneous interactions, by uni- or bidirectional spillovers? Using a detailed description of an r&d sector with cross-technology interactions embedded in a simple growth model, we analyse how the structure of spillovers influences growth prospects and growth patterns. We show that some type of interactions (e.g., one-way interactions) cannot induce exponential growth, whereas other structures can. Furthermore, depending on the structure of interactions, all or only some technologies will contribute to growth in the long run. Finally, some spillover structures can lead to complex growth patterns, such as technology transitions, where, over time, different technology clusters are the main engine of growth.
The analogies between economics and classical mechanics can be extended from constrained optimization to constrained dynamics by formalizing economic (constraint) forces and economic power in analogy to physical (constraint) forces in Lagrangian mechanics. In the differential-algebraic equation framework of General Constrained Dynamics (GCD), households, firms, banks, and the government employ forces to change economic variables according to their desire and their power to assert their interest. These ex-ante forces are completed by constraint forces from unanticipated system constraints to yield the ex-post dynamics. The flexible out-of-equilibrium model can combine Keynesian concepts such as the balance sheet approach and slow adaptation of prices and quantities with bounded rationality (gradient climbing) and interacting agents discussed in behavioral economics and agent-based models. The framework integrates some elements of different schools of thought and overcomes some restrictions inherent to optimization approaches, such as the assumption of markets operating in or close to equilibrium. Depending on the parameter choice for power relations and adaptation speeds, the model nevertheless can converge to a neoclassical equilibrium, and reacts to an austerity shock in a neoclassical or post-Keynesian way.
Economic Policy Uncertainty (EPU) is a critical indicator in economic studies, while it can be used to forecast a recession. Under higher levels of uncertainty, firms' owners cut their investment, which leads to a longer post-recession recovery. EPU index is computed by counting news articles containing pre-defined keywords related to policy-making and economy and convey uncertainty. Unfortunately, this method is sensitive to the original keyword set, its richness, and the news coverage. Thus, reproducing its results for different countries is challenging. In this paper, we propose an unsupervised text mining method that uses word-embedding representation space to select relevant keywords. This method is not strictly sensitive to the semantic similarity threshold applied to the word embedding vectors and does not require a pre-defined dictionary. Our experiments using a massive repository of Persian news show that the EPU series computed by the proposed method precisely follows major events affecting Iran's economy and is compatible with the World Uncertainty Index (WUI) of Iran.
The victorious spirit, which predominates in all the provinces of the United States of
America, penetrates the scale of values in rise concerning the real G.D.P. The symbiosis of
the progresses witnessed by the American nation along of the time, as a result of the
management organized in “American smart style”, have reflection in the values regarding
the real G.D.P. of the United States of America. The aim of this original research pursues to
display the permanent increase regarding the real G.D.P. of the United States of America,
between 2021-2030
The current article presents the influence of critical thinking on the students’ development. The research has been applied in two forms: secondary analysis and primary research, based on survey. Secondary research analyses the evolution of the number of high school students and school units at regional, county and city level.
The primary research was performed using the quantitative method; the survey was applied to 102 students from senior high school level. The questionnaire was implemented during the period May - June 2019 in Râmnicu Sărat, Buzău county, Romania. The quantitative research was chosen due to its fulfilment of the objectives of data collection regarding a problem of general interest.
Abstract Research studies in the past have analyzed the significance of demographic and socioeconomic status influencing investment preference and behavior. However, no study has focused on analyzing their impact on ‘Investment motives’. Hence, this study examines the investment motives and analyzes the significance of the impact of demographic and socioeconomic factors on investment motives. The study uses factor analysis and Multivariate analysis of variance (MANOVA) for this purpose. The data are collected from 753 investors through a structured questionnaire. Results of the study show that investment motives are grouped into six categories i.e., nature of the investment, future financial needs, investor characteristics, safety and stability, investor behavior, and investor options. Further, there exists a main effect of employment, marital status, location, and the number of earning members on investment motives. Likewise, there exists an interaction effect of age and location, gender and income, and age and income on investment motives. The study adds to the existing literature by comprehensively analyzing all the demographic, socioeconomic status with the investment motives.
Natalia A. Sadovnikova, Leysan A. Davletshina, Olga A. Zolotareva
et al.
This article presents the results of a cluster analysis of the regions of the Russian Federation in terms of the main parameters of socio-economic development according to the data presented in the official data sources of the Federal State Statistics Service (Rosstat). Studied and analyzed the domestic and foreign (Eurostat) methodology for assessing the socio-economic development of territories. The aim of the study is to determine the main parameters of territorial differentiation and to identify key indicators that affect the socio-economic development of Russian regions. The authors have carried out a classification of the constituent entities of the Russian Federation not in terms of territorial location and geographical features, but in terms of the specifics and key parameters of the socio-economic situation.