Hasil untuk "Commercial geography. Economic geography"

CIBOTARIU IRINA-ȘTEFANA, CHELBA ANCUȚA-ANISIA

Business digitalization is the premise for ensuring the continuity of companies nowadays. The purpose of this research work is to survey the representatives of 120 companies in Romania in order to present the degree of digitalization of businesses in the context of crises, especially the Covid-19 crisis, but also to capture the forecasts for the next 3 years made by economic agents against the backdrop of existing crises. The first objective considers the review of the specialized literature on digitalization, and the second objective is focused on the analysis of the companies in the research sample. The results consist in providing an overview of the companies in Romania in the situation of "forced" digitalization caused by the Covid-19 crisis, but also on the forecasts made by the representatives of these companies. The companies included in the sample were analyzed between January 2023 and October 2023.

Gurpreet pal Kaur, Harpreet Singh Bedi, Harish Saini

Abstract The study aims to assess the innovativeness–business performance relationship by considering learning orientation as moderator. Data has been gathered from 413 Small and Medium Enterprises (SMEs) in Punjab, India, using a quantitative study design. Structural equation modelling has been used to evaluate the proposed relationships. The results reveal that innovativeness and business performance have a positive relationship, which is moderated by learning orientation. The findings of this study attempts to encourage SMEs for nurturing the culture of continuous learning and experimentation. SMEs may enhance their performance and competitiveness in fast-paced business environments by being innovative and learning-oriented. Theoretical and practical implications are considered, in addition to limitations and future research directions.

Mohamed hani, Habib Badawi

The global financial system, historically dominated by the US dollar since the 1944 Bretton Woods Agreement, is undergoing a significant transformation as BRICS nations (Brazil, Russia, India, China, and South Africa) pursue de-dollarization to reduce reliance on the dollar in trade, reserves, and financial systems. Driven by economic vulnerabilities, geopolitical tensions (e.g., sanctions and the Russia-Ukraine conflict), and technological innovations (e.g., cryptocurrencies and blockchain), these efforts aim to mitigate exposure to US monetary policy and dollar weaponization. BRICS strategies include promoting alternative currencies (e.g., China’s Renminbi), establishing parallel financial institutions (e.g., New Development Bank), and leveraging digital payment systems. However, challenges persist, such as the dollar’s entrenched dominance, internal BRICS divergences, and technical barriers. The shift suggests a gradual move toward a multipolar monetary system rather than an abrupt dollar collapse, with implications for global economic governance, financial stability, and geopolitical power dynamics. Case studies of China, Russia, and Pakistan highlight diverse approaches, from bilateral trade agreements to sectoral energy transitions. This research underscores de-dollarization as a complex, multidimensional process integrating economic, political, and technological factors, signaling an evolving but not yet displaced dollar-centric order.

Xinyu Li

In 2025, intensified Immigration and Customs Enforcement (ICE) raids in Oxnard, California, disrupted the state's \$49 billion agricultural industry, a critical supplier of 75% of U.S. fruits and nuts and one-third of its vegetables. This paper quantifies the economic consequences of these raids on labor markets, crop production, and food prices using econometric modeling. We estimate a 20-40% reduction in the agricultural workforce, leading to \$3-7 billion in crop losses and a 5-12% increase in produce prices. The analysis draws on USDA Economic Research Service data and recent ICE detention figures, which show arrests in Southern California rising from 699 in May to nearly 2,000 in June 2025. The raids disproportionately affect labor-intensive crops like strawberries, exacerbating supply chain disruptions. Policy recommendations include expanding the H-2A visa program and legalizing undocumented workers to stabilize the sector. This study contributes to agricultural economics by providing a data-driven assessment of immigration enforcement's economic toll.

Alejandro Lopez-Lira, Yuehua Tang, Mingyin Zhu

Large language models (LLMs) cannot be trusted for economic forecasts during periods covered by their training data. Counterfactual forecasting ability is non-identified when the model has seen the realized values: any observed output is consistent with both genuine skill and memorization. Any evidence of memorization represents only a lower bound on encoded knowledge. We demonstrate LLMs have memorized economic and financial data, recalling exact values before their knowledge cutoff. Instructions to respect historical boundaries fail to prevent recall-level accuracy, and masking fails as LLMs reconstruct entities and dates from minimal context. Post-cutoff, we observe no recall. Memorization extends to embeddings.

Jinchi Dong, Richard S. J. Tol, Jinnan Wang

Estimating the effects of climate on economic output is crucial for formulating climate policy, but current empirical findings remain ambiguous. Using annual panel model and panel long-difference model with global subnational data from nearly all countries, we find robust evidence that weather shocks have a transient effect on output. The impact on economic growth is large and significant in the short-run but statistically insignificant in the long-run, except in the coldest and hottest places.

Craig S Wright

This paper presents a praxeological analysis of artificial intelligence and algorithmic governance, challenging assumptions about the capacity of machine systems to sustain economic and epistemic order. Drawing on Misesian a priori reasoning and Austrian theories of entrepreneurship, we argue that AI systems are incapable of performing the core functions of economic coordination: interpreting ends, discovering means, and communicating subjective value through prices. Where neoclassical and behavioural models treat decisions as optimisation under constraint, we frame them as purposive actions under uncertainty. We critique dominant ethical AI frameworks such as Fairness, Accountability, and Transparency (FAT) as extensions of constructivist rationalism, which conflict with a liberal order grounded in voluntary action and property rights. Attempts to encode moral reasoning in algorithms reflect a misunderstanding of ethics and economics. However complex, AI systems cannot originate norms, interpret institutions, or bear responsibility. They remain opaque, misaligned, and inert. Using the concept of epistemic scarcity, we explore how information abundance degrades truth discernment, enabling both entrepreneurial insight and soft totalitarianism. Our analysis ends with a civilisational claim: the debate over AI concerns the future of human autonomy, institutional evolution, and reasoned choice. The Austrian tradition, focused on action, subjectivity, and spontaneous order, offers the only coherent alternative to rising computational social control.

IONELA-ALINA ALUPOAEI

The 2024 Romanian European Parliament election gives a significant perspective through which one can assess the growing significance of political marketing, particularly its ethical consequences in a fast changing digital context. As Romania is dealing with its post-communist identity within the wider European Union, political marketing is becoming more sophisticated, using extensive data analytics, targeted social media ads, and algorithm-driven techniques to influence voter behavior. This election cycle highlights the contradictions between successful political communication and ethical boundaries that are sometimes crossed—or downright ignored—in the pursuit of electoral victory. Political parties and candidates in the 2024 campaign used a variety of marketing methods that crossed the line between persuasion and manipulation. Microtargeting, the use of deepfake technology, and the spread of disinformation have all prompted worries about the legitimacy of political debate and the potential decline of democratic principles. These techniques have frequently placed short-term electoral gains over the long-term viability of Romania's democratic institutions, increasing socioeconomic divisions and fueling public skepticism. The 2024 election has seen greater polarization, with campaigners using nationalist and populist themes to gain support. This technique, while effective in gathering particular voting segments, has exacerbated ideological gaps and caused a more destructive political climate. This paper argues that the 2024 Romanian election highlights the risks of unrestrained political marketing, in which ethical considerations are frequently sacrificed to the demands of strategic success. While political marketing is an important tool for engaging voters in a complicated media landscape, its misuse may cause enormous harm, such as manipulating public opinion, spreading misleading information, and eroding democratic legitimacy. The Romanian case emphasizes the urgent need for stronger ethical standards and regulatory monitoring in political marketing tactics.

URECHE ALEXANDRU

A social enterprise is a business with specific social objectives. Like every business endeavor, it is built on a commercial framework, yet the social enterprise aims to make – besides its money-making purpose - a powerful social, and environmental impact on the populace which it serves. Nowadays profit-making shareholders-only, mantra makes it challenging to fund a social enterprise. On the same token, the current volatile economic climate is calling for more such adaptable, and dynamic structures, which provide a solid vehicle for sustaining change, as well as strengthening the fabric of their communities, fostering socio-economic innovation, and sustainable growth. In financing such a bold and complex undertaking, we aim to find sustainable ways of funding a social enterprise, in order to make them attractive to investors, by looking at financial and non-financial return of investment. In analyzing the donor-investor model, we posit that sustainable growth can be fueled by sustainable giving, which in turn nourishes deep brain structures of fulfillment. We aim to escape the profit-loss dualistic paradigm, and expand to the plurality of multiple capitals, hence multiple returns of investment, by promoting business structures acting as pillars of socio-economic stability, in times of rapid business change, by adding new essential business skills such as social entrepreneurship (and intrapreneurship) into today’s economic enterprise, as steps towards a more sustainable business, and socio-economic future.

ALBĂ CLAUDIA DANIELA, POPESCU LILIANA, ȘOȘEA CRISTINA et al.

In today competitive tourism market, with the rise of the web 2.0 era, destinations have shifted their focus from the traditional means of promotion to the online process. This study examined the online marketing of 10 Romanian cities as emerging destinations for cultural tourism based on the content analysis of website content. Using Google search to select tourism websites for analysis and applying eMICA model, a review of 200 websites was made, so as to understand how each city is promoting its image and products online. The results show that only some of the analyzed cities have official tourism websites and quite frequently, they lack interactivity, which is currently seen as a must for any successful destination. Main areas for improvement regarding the online promotion of the Romanian cities are suggested.

Davide Fiaschi, Angela Parenti, Cristiano Ricci

This paper studies the evolution of economic activities using a continuous time-space aggregation-diffusion model, which encompasses competing effects of agglomeration and congestion. To bring the model to the real data, a novel discretization technique over time and space is introduced. This technique effectively disentangles spatial effects into pure topography, agglomeration, repulsion, and diffusion forces, which is crucial for developing robust econometric methods in spatial economics. Our empirical analysis of personal income across Italian municipalities from 2008 to 2019 validates the model's primary predictions and demonstrates superior performance compared to the most common spatial econometric models in the literature.

Anton Pichler, Jan Hurt, Tobias Reisch et al.

The Russian invasion of Ukraine on February 24, 2022 entailed the threat of a drastic and sudden reduction of natural gas supply to the European Union. This paper presents a techno-economic analysis of the consequences of a sudden gas supply shock to Austria, one of the most dependent countries on imports of Russian gas. Our analysis comprises (a) a detailed assessment of supply and demand side countermeasures to mitigate the immediate shortfall in Russian gas imports, (b) a mapping of the net reduction in gas supply to industrial sectors to quantify direct economic shocks and expected relative reductions in gross output and (c) the quantification of higher-order economic impacts through using a dynamic out-of-equilibrium input-output model. Our results show that potential economic consequences can range from relatively mild to highly severe, depending on the implementation and success of counteracting mitigation measures. We find that securing alternative gas imports, storage management, and incentivizing fuel switching represent the most important short-term policy levers to mitigate the adverse impacts of a sudden import stop.

Aditya Saxena, Dr Parizad Dungore

Credit ratings are becoming one of the primary references for financial institutions of the country to assess credit risk in order to accurately predict the likelihood of business failure of an individual or an enterprise. Financial institutions, therefore, depend on credit rating tools and services to help them predict the ability of creditors to meet financial persuasions. Conventional credit rating is broadly categorized into two classes namely: good credit and bad credit. This approach lacks adequate precision to perform credit risk analysis in practice. Related studies have shown that data-driven machine learning algorithms outperform many conventional statistical approaches in solving this type of problem, both in terms of accuracy and efficiency. The purpose of this paper is to construct and validate a credit risk assessment model using Linear Discriminant Analysis as a dimensionality reduction technique to discriminate good creditors from bad ones and identify the best classifier for credit assessment of commercial banks based on real-world data. This will help commercial banks to avoid monetary losses and prevent financial crisis

Xuyang Li, Guangchun Ruan, Haiwang Zhong

Decarbonization of power systems plays a crucial role in achieving carbon neutral goals across the globe, but there exists a sharp contradiction between the emission reduction and levelized generation cost. Therefore, it is of great importance for power system operators to take economic as well as low-carbon factors into account. This paper establishes a low-carbon economic dispatch model of bulk power systems based on Nash bargaining game, which derives a Nash bargaining solution making a reasonable trade-off between economic and low-carbon objectives. Because the Nash bargaining solution satisfies Pareto effectiveness, we analyze the computational complexity of Pareto frontiers with parametric linear programming and interpret the inefficiency of the method. Instead, we assign a group of dynamic weights in the objective function of the proposed low-carbon economic dispatch model so as to improve the computational efficiency by decoupling time periods and avoiding the complete computation of Pareto frontiers. In the end, we validate the proposed model and the algorithm by a realistic nationwide simulation in mainland China.

افشین متقی دستنایی, سعید رجبی

کشورهای مختلف به فراخور ویژ‎گی های متفاوت جغرافیایی که دارند، نقشی چندبعدی در راهبردهای سیاست خارجی بازیگران منطقه ای و جهانی ایفا می کنند. سوریه نیز از این قاعده مستثنا نیست و با توجّه به اختصاصات مختلف جغرافیایی، اقتصادی، فرهنگی و سیاسی که دارد، جایگاهی چندبعدی در سپهر سیاست خارجی ج.ا. ایران ایفا کرده است. باوجود اینکه موقعیت راهبردی سوریه در محور مقاومت دیگر ابعاد اهمیت این کشور را متأثر ساخته است، با این حال سوریه از ظرفیت های ژئوکالچری و ژئواکونومیکی بالایی برخوردار است که در صورت توجّه جدی می تواند به کنش‎گری فعال و چند سویه در راهبردهای سیاست خارجی ایران در آینده بدل شود. این مقاله به روش توصیفی _تحلیلی و با بهره ‎گیری از منابع مختلف کتابخانه ای، در پی پاسخ به این پرسش است که مهم‌ترین فرصت های ژئواکونویکی ایران در فضای پساجنگ داخلی سوریه کدم‌اند؟ یافته بیانگر آن است که سوریه دارای ظرفیت های ژئواکونومیکی مختلفی همچون قرارگیری در کریدور انرژی ایران –عراق- سوریه- اروپا (پرسین پایپ)، کریدور زمینی خلیج فارس- مدیترانه و همچنین محیط مناسبی برای سرمایه‌گذاری ایران در بخش های نفت و معادن، با توجّه به نیاز سوریه به بازسازی های گسترده بعد از جنگ داخلی است. درواقع سوریه را می توان مکمل ژئواکونومیک ایران در حوزه صدور انرژی و همچنین دسترسی به بازارهای اروپایی دانست.

M. S. Tedesco, M. A. Nunez-Ochoa, F. Ramos et al.

The benefits of using complex network analysis (CNA) to study complex systems, such as an economy, have become increasingly evident in recent years. However, the lack of a single comparative index that encompasses the overall wellness of a structure can hinder the simultaneous analysis of multiple ecosystems. A formula to evaluate the structure of an economic ecosystem is proposed here, implementing a mathematical approach based on CNA metrics to construct a comparative measure that reflects the collaboration dynamics and its resultant structure. This measure provides the relevant actors with an enhanced sense of the social dynamics of an economic ecosystem, whether related to business, innovation, or entrepreneurship. Available graph metrics were analysed, and 14 different formulas were developed. The efficiency of these formulas was evaluated on real networks from 11 different innovation-driven entrepreneurial economic ecosystems in six countries from Latin America and Europe and on 800 random graphs simulating similarly constructed networks.

David J. Haw, Christian Morgenstern, Giovanni Forchini et al.

The COVID-19 pandemic and the mitigation policies implemented in response to it have resulted in economic losses worldwide. Attempts to understand the relationship between economics and epidemiology has lead to a new generation of integrated mathematical models. The data needs for these models transcend those of the individual fields, especially where human interaction patterns are closely linked with economic activity. In this article, we reflect upon modelling efforts to date, discussing the data needs that they have identified, both for understanding the consequences of the pandemic and policy responses to it through analysis of historic data and for the further development of this new and exciting interdisciplinary field.

CRISTEA LOREDANA ANDREEA, VODĂ ALINA DANIELA, UNGUREANU DRAGOȘ MIHAI

The government, in most democratic states, has the supreme monopoly characteristic of public services, services that are realized through fiscal policy instruments, respectively through government revenues and expenditures. This research aims to provide the defining substrates of fiscal policy, so that a theoretical model of the fiscal system’s functioning to can be outlined, from the perspective of the three sectors of the state, respectively: the economic, social and political plan. In order to achieve this objective, it was used as a research method, the case study of the specialized literature, being a qualitative research, meant to bring pluses in knowledge. Establishing the fiscal strategy at the level of state's political plan has direct effects on the economic plan, and, depending on the fiscal policy at the national level, there may be influences on the social plan of the country. Thus, any political choice affects the socio-economic component of the state and vice versa. The design of the taxation system can be considered an essential ingredient in public policies, as it mainly finances government spending. Based on the study, it was concluded that the use of public revenues and expenditures in order to influence the degree of the economy’s development, makes fiscal policy to be considered the medicine or the drug of public finances, which can cure or worsen the existing situation.

Julius R. Garzon, Leomarich F. Casinillo

Many students are struggling to learn the concept of algebraic expressions due to poor understanding of how to perform mathematical operations. A 5E guided inquiry model is one of the teaching strategies utilized to support students think and work mathematically. Hence, this study was conducted to examine the effect of 5E Guided Inquiry Model on the achievement of grade 7 students in algebraic expressions. Two intact classes composed of twenty four (24) students each were used as sample assigned to groups based on their first grading grade in Mathematics 7. Control group was taught using traditional strategy while the experimental group was taught using 5E guided inquiry model. Quasi-experimental approach was employed using one-shot experimental design with pretest-posttest instrument used to collect data. Results showed that both student participants under control and experimental group have the positive attitude towards mathematics. This expresses comparable affective aspect among students when they both underwent the model used in this study. The attitude of student participants is not significantly related to their achievement in algebraic expressions. In addition, the achievement in algebraic expressions of students exposed to 5E guided inquiry model significantly higher compared to the achievement of students exposed to traditional strategy. Hence, teaching algebraic expressions with the aid of 5E Guided Inquiry Model gives a positive impact on students’ academic achievement.

Christina Marie Mitcheltree

Abstract Trust in organizations plays an essential role for efficient innovation implementation. However, trust between managers and employees is under-communicated in relation to innovation speed. Innovation speed is related to innovation adoption, concerning new ways of performing laboratory services within the health sector. The purpose of this case study is to investigate how trust mechanisms may enhance innovation speed by reducing employee decisions to perform defensive routines. The focus is related to trust as a social condition for enhancing innovation acceptance in the context of management and organizing styles subject to the Norwegian Work Life Model. The study found that a lack of employee participation and involvement may result in emotional tension, a sense of uncertainty, disconnect, and various defensive mechanisms towards management and the innovation. Consequently, employees’ attention, loyalty, and responsibility might be redirected away from the innovation.