Hasil untuk "Commercial geography. Economic geography"

Thomas Wieland

Market area models, such as the Huff model and its extensions, are widely used to estimate regional market shares and customer flows of retail and service locations. Another, now very common, area of application is the analysis of catchment areas, supply structures and the accessibility of healthcare locations. The huff Python package provides a complete workflow for market area analysis, including data import, construction of origin-destination interaction matrices, basic model analysis, parameter estimation from empirical data, calculation of distance or travel time indicators, and map visualization. Additionally, the package provides several methods of spatial accessibility analysis. The package is modular and object-oriented. It is intended for researchers in economic geography, regional economics, spatial planning, marketing, geoinformation science, and health geography. The software is openly available via the Python Package Index (PyPI) (https://pypi.org/project/huff/); its development and version history are managed in a public GitHub Repository (https://github.com/geowieland/huff_official) and archived at Zenodo (https://doi.org/10.5281/zenodo.18639559).

Akwasi Mensah‐Bonsu, Jacob Ankamah, Wayo Seini

Abstract The production of oil on a commercial scale has led to a ban on fishing in areas close to oilfields in Ghana. This paper uses econometric analysis to examine the effect of the fishing ban on the livelihoods of rural fishing households in offshore oilfields. It contributes to environmental and economic geography by empirically testing how spatial governance of natural resources (marine resource exclusions due to oil extraction) reshapes local livelihoods and exacerbates poverty. We examined poverty status and income diversification measures as key indicators of livelihood. The findings revealed a negative association between poverty status and the degree of income diversification, suggesting a high prevalence of poverty within undiversified fishing households. Socioeconomic and environmental factors, including the number of extension visits, savings, assets, access to credit and a fishing ban (restrictions), have a positive and significant influence on income diversification. We recommend policy interventions aimed at raising awareness and developing skills that encourage participation in multiple income‐generating activities as a potential means of helping fishermen displaced by oil production. These policies are important for reducing poverty in rural fishing communities and preventing potential conflicts arising from changes in the use of common resources.

رضا ملاحسینی اردکانی, محمد طالبی

بخش‌های زیادی از استان یزد به عنوان یکی از مناطق مرکزی کشور را کویرها و بیابان‌ها شکل داده است. این پهنه‌های کویری و بیابانی به دلیل شرایط سخت و ویژه جغرافیایی و اقلیمی خالی از سکنه بوده و دسترسی به برخی نواحی آن نیز دشوار است. همین موضوع سبب شده تا این مناطق به مهمترین کانون‌های تهدیدکننده امنیت استان یزد تبدیل شوند. پژهش حاضر با هدف شناسایی و تحلیل عوامل موثر بر امنیت پایدار استان یزد با تاکید بر مناطق کویری انجام شده است. پژوهش به لحاظ روش، در زمره تحقیقات توصیفی - تحلیلی دسته‌بندی می‌شود و از نوع کاربردی است. علاوه بر مطالعات اسنادی و کتابخانه‌ای، یافته‌های اصلی پژوهش از طریق بررسی‌های میدانی و همچنین با استفاده از تحلیل نظرات کارشناسان از طریق تحلیل کمی پرسشنامه‌های توزیع شده به دست آمده است. بر این اساس، جامعه آماری 65 نفر از متخصصان و کارشناسان حوزه‌های مختلف تخصصی در ارتباط با کویر استان یزد هستند که اطلاعات و نتایج پرسشنامه‌های پژوهش پس از جمع‌آوری با استفاده از نرم‌افزار آماری SPSS مورد تجزیه ‌و تحلیل قرار گرفت. با بهره‌گیری از تحلیل داده‌های آماری، وضعیت موجود امنیت در کویرهای استان یزد بررسی شده است. یافته‌های پژوهش نشان می‌دهد که عوامل نظامی و امنیتی بیشترین تاثیر را بر امنیت پایدار کویرهای استان یزد داشته‌اند. پس از آن نیز عوامل اقتصادی، فرهنگی و اجتماعی، سیاسی و در نهایت عوامل جغرافیایی به ترتیب اهمیت قرار دارند. یافته‌ها حاکی از آن است که حفظ امنیت در مناطق کویری به شدت به حضور و فعالیت نیروهای نظامی و امنیتی وابسته است و در عین حال، عوامل اقتصادی، اجتماعی، فرهنگی و سیاسی نیز نقش بسزایی در امنیت پایدار این مناطق ایفا می‌کنند.

Herbert Dawid, Philipp Harting, Hankui Wang et al.

This paper introduces a methodology based on agentic workflows for economic research that leverages Large Language Models (LLMs) and multimodal AI to enhance research efficiency and reproducibility. Our approach features autonomous and iterative processes covering the entire research lifecycle--from ideation and literature review to economic modeling and data processing, empirical analysis and result interpretation--with strategic human oversight. The workflow architecture comprises specialized agents with clearly defined roles, structured inter-agent communication protocols, systematic error escalation pathways, and adaptive mechanisms that respond to changing research demand. Human-in-the-loop (HITL) checkpoints are strategically integrated to ensure methodological validity and ethical compliance. We demonstrate the practical implementation of our framework using Microsoft's open-source platform, AutoGen, presenting experimental examples that highlight both the current capabilities and future potential of agentic workflows in improving economic research.

Guanzhong Pan, Vishal Chodnekar, Abinas Roy et al.

Large language models (LLMs) are becoming increasingly widespread. Organizations that want to use AI for productivity now face an important decision. They can subscribe to commercial LLM services or deploy models on their own infrastructure. Cloud services from providers such as OpenAI, Anthropic, and Google are attractive because they provide easy access to state-of-the-art models and are easy to scale. However, concerns about data privacy, the difficulty of switching service providers, and long-term operating costs have driven interest in local deployment of open-source models. This paper presents a cost-benefit analysis framework to help organizations determine when on-premise LLM deployment becomes economically viable compared to commercial subscription services. We consider the hardware requirements, operational expenses, and performance benchmarks of the latest open-source models, including Qwen, Llama, Mistral, and etc. Then we compare the total cost of deploying these models locally with the major cloud providers subscription fee. Our findings provide an estimated breakeven point based on usage levels and performance needs. These results give organizations a practical framework for planning their LLM strategies.

Aljen C. Batican, Mary Cris F. Pleños, Jedan A. Cavero et al.

The adoption of cashless payment systems for household utilities faces significant challenges, hindering efficient and modern financial transactions. This study assesses the adoption of cashless payment systems for household utilities in the municipality of Albuera, Leyte, Philippines. The research aimed to determine the factors influencing the adoption of cashless payment system among the residents. Utilizing a sample size of 246 participants, the study employs preference analysis and logit regression for statistical analysis, to evaluate responses from a 5-point Likert scale and open-ended questions. Stata was used for the descriptive statistics, preference analysis and regression analysis, while Smart PLS 4 facilitated the confirmatory factor analysis for the latent variables. The key findings reveal that effort expectancy, performance expectancy, social influence, and perceived risk significantly impact the adoption of cashless payment systems. Conversely, demographic variables such as age, gender, education level, income, as well as the past experience, internet access, and facilitating conditions do not show a significant effect. These highlights the critical factors that utility services, e-wallet providers and policymakers should consider to enhance the adoption of cashless payment methods in Albuera, Leyte. This study contributes to the broader understanding of technology adoption in the context of essential household utilities.

ISAC CLAUDIA

The evolution of technology, digitalization, and the growing interest of investors has led to an impressive increase in the number of unicorn companies globally. The first part of this article aims to provide an overview of the concepts used for these startups, which experience rapid growth towards a market valuation of $1B, impacting capital market dynamics and investment strategies. The second part of the paper presents a statistical overview of the number and value of unicorns, along with their geographical distribution and breakdown by economic sectors.

COSTIN DAN EUGEN, POPESCU MARIUS CĂTĂLIN, PĂSĂRIN LEONARDO DANIEL et al.

Sport has always played an important role in society, bringing joy, excitement and a sense of community as well as national pride. Over the centuries, sport has evolved from simple local competitions to global events watched by millions of people, gaining ever greater socio-political and economic importance. In the paper "Management and prevention of abuses in sports" we make a brief presentation of the types of abuses existing in sports and the solutions that can be used to eliminate these harmful actions, including a survey conducted on this topic.

Subramanyam Sahoo, Kamlesh Dutta

The relentless pursuit of technological advancements has ushered in a new era where artificial intelligence (AI) is not only a powerful tool but also a critical economic driver. At the forefront of this transformation is Generative AI, which is catalyzing a paradigm shift across industries. Deep generative models, an integration of generative and deep learning techniques, excel in creating new data beyond analyzing existing ones, revolutionizing sectors from production and manufacturing to finance. By automating design, optimization, and innovation cycles, Generative AI is reshaping core industrial processes. In the financial sector, it is transforming risk assessment, trading strategies, and forecasting, demonstrating its profound impact. This paper explores the sweeping changes driven by deep learning models like Large Language Models (LLMs), highlighting their potential to foster innovative business models, disruptive technologies, and novel economic landscapes. As we stand at the threshold of an AI-driven economic era, Generative AI is emerging as a pivotal force, driving innovation, disruption, and economic evolution on a global scale.

DongKi Noh, Hyungtae Lim, Gyuho Eoh et al.

In commercial autonomous service robots with several form factors, simultaneous localization and mapping (SLAM) is an essential technology for providing proper services such as cleaning and guidance. Such robots require SLAM algorithms suitable for specific applications and environments. Hence, several SLAM frameworks have been proposed to address various requirements in the past decade. However, we have encountered challenges in implementing recent innovative frameworks when handling service robots with low-end processors and insufficient sensor data, such as low-resolution 2D LiDAR sensors. Specifically, regarding commercial robots, consistent performance in different hardware configurations and environments is more crucial than the performance dedicated to specific sensors or environments. Therefore, we propose a) a multi-stage %hierarchical approach for global pose estimation in embedded systems; b) a graph generation method with zero constraints for synchronized sensors; and c) a robust and memory-efficient method for long-term pose-graph optimization. As verified in in-home and large-scale indoor environments, the proposed method yields consistent global pose estimation for services in commercial fields. Furthermore, the proposed method exhibits potential commercial viability considering the consistent performance verified via mass production and long-term (> 5 years) operation.

Koen Ponse, Aske Plaat, Niki van Stein et al.

Accurate economic simulations often require many experimental runs, particularly when combined with reinforcement learning. Unfortunately, training reinforcement learning agents in multi-agent economic environments can be slow. This paper introduces EconoJax, a fast simulated economy, based on the AI economist. EconoJax, and its training pipeline, are completely written in JAX. This allows EconoJax to scale to large population sizes and perform large experiments, while keeping training times within minutes. Through experiments with populations of 100 agents, we show how real-world economic behavior emerges through training within 15 minutes, in contrast to previous work that required several days. We additionally perform experiments in varying sized action spaces to test if some multi-agent methods produce more diverse behavior compared to others. Here, our findings indicate no notable differences in produced behavior with different methods as is sometimes suggested in earlier works. To aid further research, we open-source EconoJax on Github.

Md. Toaha, Laboni Mondal

The paper examined the impact of agricultural credit on economic growth in Bangladesh. The annual data of agriculture credit were collected from annual reports of the Bangladesh Bank and other data were collected from the world development indicator (WDI) of the World Bank. By employing Johansen cointegration test and vector error correction model (VECM), the study revealed that there exists a long run relationship between the variables. The results of the study showed that agriculture credit had a positive impact on GDP growth in Bangladesh. The study also found that gross capital formation had a positive, while inflation had a negative association with economic growth in Bangladesh. Therefore, the government and policymakers should continue their effort to increase the volume of agriculture credit to achieve sustainable economic growth.

BÎRCĂ ALIC

In this scientific endeavor, the NEET group as a source of employment growth is addressed. Taking into account the economic and social consequences of the NEET group, national government institutions at the national level have been concerned with this category, developing and implementing various measures and policies to reduce their share in the total young population. In this context, a theoretical-conceptual analysis of the NEET group is performed, being presented the opinions of several authors. It also analyzes the composition of the NEET group, as well as the factors that influence it, highlighting both macro and individual factors. Methodologically, the NEET rate was analyzed, as the main reference indicator that characterizes this group. In the case of the Republic of Moldova, the NEET rate was analyzed by age category, gender, place of residence and the education level. Likewise, the NEET rate in the Republic of Moldova is analyzed compared to that registered in the EU Member States, in order to highlight the existing gaps.

Lee Braine, Shreepad Shukla

Central banks are actively exploring central bank digital currencies (CBDCs) by conducting research, proofs of concept and pilots. However, adoption of a CBDC can risk fragmenting both payments markets and retail deposits. In this paper, we aim to provide a mitigation to this fragmentation risk by presenting an illustrative industry architecture that places CBDCs and commercial bank money on a similar footing. We introduce the concept of ecosystems providing a common programmability layer that interfaces with the account systems at both commercial banks and the central bank. We focus on a potential UK CBDC, including industry ecosystems interfacing with commercial banks using Open Banking application programming interfaces.

Matteo Straccamore, Matteo Bruno, Bernardo Monechi et al.

Over the years, the growing availability of extensive datasets about registered patents allowed researchers to better understand technological innovation drivers. In this work, we investigate how the technological contents of patents characterise the development of metropolitan areas and how innovation is related to GDP per capita. Exploiting worldwide data from 1980 to 2014, and through network-based techniques that only use information about patents, we identify coherent distinguished groups of metropolitan areas, either clustered in the same geographical area or similar from an economic point of view. We also extend the concept of coherent diversification to patent production by showing how it represents a decisive factor in the economic growth of metropolitan areas. These results confirm a picture in which technological innovation can lead and steer the economic development of cities, opening, in this way, the possibility of adopting the tools introduced here to investigate the interplay between urban development and technological innovation.

Reza Azizi, Amir Mohammad Haji-yousefi

China's Belt and Road Initiative (BRI) is basically a global project and thus the existing literature has explored it broadly. This article seeks to explore the literature especially those focused on the BRI’s effects in Western Asia. This literature has tried to explain it by employing international relations and political economy theories. By dividing this literature into four categories of realist, liberalist, constructivist, and Marxist, this article argues that despite the importance of the analysis of BRI in Western Asia by the existing literature, they are often based on predictions without enough objective data and are also reductionist. In a way that some have approached it via power politics (realism), some others through politics of wealth (liberalism), some via identity politics (constructivism), and finally some through the class politics (Marxism). By comparing the existing approaches, this article argues that Keohane and Nye’s theory of international regimes, which is not being used in any existing theory about Belt and Road Initiative in Western Asia, provides a better theoretical framework for analyzing the BRI in Western Asia, because it takes into consideration some important factors such as developments in technological field, the growth rate of gross domestic product, and the governments’ objectives in pursuing economic policies and it fits better the objective data and realities of contemporary Western Asia.

Sotaro Sada, Yuichi Ikeda

Global value chains (GVCs) are formed through value-added trade, and some regions promote economic integration by concluding regional trade agreements to promote these chains. However, there is no way to quantitatively assess the scope and extent of economic integration involving various sectors in multiple countries. In this study, we used the World Input--Output Database to create a cross-border sector-wise trade in value-added network (international value-added network (IVAN)) covering the period of 2000--2014 and evaluated them using network science methods. By applying Infomap to the IVAN, we confirmed for the first time the existence of two regional communities: Europe and the Pacific Rim. Helmholtz--Hodge decomposition was used to decompose the value flows within the region into potential and circular flows, and the annual evolution of the potential and circular relationships between countries and sectors was clarified. The circular flow component of the decomposition was used to define an economic integration index, and findings confirmed that the degree of economic integration in Europe declined sharply after the economic crisis in 2009 to a level lower than that in the Pacific Rim. The European economic integration index recovered in 2011 but again fell below that of the Pacific Rim in 2013. Moreover, sectoral analysis showed that the economic integration index captured the effect of Russian mineral resources, free movement of labor in Europe, and international division of labor in the Pacific Rim, especially in GVCs for the manufacture of motor vehicles and high-tech products.

Philip Lubin, Alexander N. Cohen

Large scale directed energy offers the possibility of radical transformation in a variety of areas, including the ability to achieve relativistic flight that will enable the first interstellar missions, as well as rapid interplanetary transit. In addition, the same technology will allow for long-range beamed power for ion, ablation, and thermal engines, as well as long-range recharging of distant spacecraft, long-range and ultra high bandwidth laser communications, and many additional applications that include remote composition analysis, manipulation of asteroids, and full planetary defense. Directed energy relies on photonics which, like electronics, is an exponentially expanding growth area driven by diverse economic interests that allows transformational advances in space exploration and capability. We have made enormous technological progress in the last few years to enable this long-term vision. In addition to the technological challenges, we must face the economic challenges to bring the vision to reality. The path ahead requires a fundamental change in the system designs to allow for the radical cost reductions required. To afford the full-scale realization of this vision we will need to bring to fore integrated photonics and mass production as a path forward. Fortunately, integrated photonics is a technology driven by vast consumer need for high speed data delivery. We outline the fundamental physics that drive the economics and derive an analytic cost model that allows us to logically plan the path ahead.

Rui Wang

We introduce the notion of Point in Time Economic Scenario Generation (PiT ESG) with a clear mathematical problem formulation to unify and compare economic scenario generation approaches conditional on forward looking market data. Such PiT ESGs should provide quicker and more flexible reactions to sudden economic changes than traditional ESGs calibrated solely to long periods of historical data. We specifically take as economic variable the S&P500 Index with the VIX Index as forward looking market data to compare the nonparametric filtered historical simulation, GARCH model with joint likelihood estimation (parametric), Restricted Boltzmann Machine and the conditional Variational Autoencoder (Generative Networks) for their suitability as PiT ESG. Our evaluation consists of statistical tests for model fit and benchmarking the out of sample forecasting quality with a strategy backtest using model output as stop loss criterion. We find that both Generative Networks outperform the nonparametric and classic parametric model in our tests, but that the CVAE seems to be particularly well suited for our purposes: yielding more robust performance and being computationally lighter.

DRĂGAN-CODREAN Cosmina-Ioana, BUGNAR Nicoleta

The paper outlines the types of diplomacy. This brief paper does not include all known and analyzed types of diplomacy. From a certain perspective, diplomacy is also a way of dialogue, of communication between states. Diplomacy seeks to settle and resolve conflicts or remedy differences of an economic, social and other nature. If, for various reasons, they do not find a solution with the help of diplomatic means, only military means are used. From the oldest information about diplomacy, we are informed that the people, respectively the leaders had a certain inclination to try to resolve conflicts, first, through diplomatic means. Even if this process is not necessarily a short-term process, it is preferable to resorting to military means. The latter would cause real disasters and much more material and even human damage. If this happens, it means that at least from a theoretical point of view, negotiations and diplomatic activities have failed. In all this context, it is imperative to take into account the specifics of the actors in question, their language and culture, history, geography, socio-cultural and political influences and, obviously, other elements that could directly influence or indirectly, the activity and the external relations. Thus, without limiting ourselves to these factors, we must admit that the existence of several types of diplomacy is generated. A good external relationship implicitly determines the advantages of those who are involved, advantages of an economic, commercial and other nature. In this way we can distinguish several types of diplomacy, among which we mention: British, German, French and Italian. In general, each state seeks to achieve certain objectives, and to achieve them it is involved in the international diplomatic sphere. Involvement in the diplomatic sphere also means cultivating foreign relations with as many states as possible, especially those with which it seeks to develop business relations, partnerships and agreements in various fields.