Hasil untuk "Commercial geography. Economic geography"

K. Chomitz, D. Gray

Yan Li, Zezi Zeng, Ziwei Zhou et al.

Recent advances in image generation models have expanded their applications beyond aesthetic imagery toward practical visual content creation. However, existing benchmarks mainly focus on natural image synthesis and fail to systematically evaluate models under the structured and multi-constraint requirements of real-world commercial design tasks. In this work, we introduce BizGenEval, a systematic benchmark for commercial visual content generation. The benchmark spans five representative document types: slides, charts, webpages, posters, and scientific figures, and evaluates four key capability dimensions: text rendering, layout control, attribute binding, and knowledge-based reasoning, forming 20 diverse evaluation tasks. BizGenEval contains 400 carefully curated prompts and 8000 human-verified checklist questions to rigorously assess whether generated images satisfy complex visual and semantic constraints. We conduct large-scale benchmarking on 26 popular image generation systems, including state-of-the-art commercial APIs and leading open-source models. The results reveal substantial capability gaps between current generative models and the requirements of professional visual content creation. We hope BizGenEval serves as a standardized benchmark for real-world commercial visual content generation.

Christos Tzanidakis, O. Tzamaloukas, P. Simitzis et al.

Over the past four decades the dietary needs of the global population have been elevated, with increased consumption of animal products predominately due to the advancing economies of South America and Asia. As a result, livestock production systems have expanded in size, with considerable changes to the animals’ management. As grazing animals are commonly grown in herds, economic and labour constraints limit the ability of the producer to individually assess every animal. Precision Livestock Farming refers to the real-time continuous monitoring and control systems using sensors and computer algorithms for early problem detection, while simultaneously increasing producer awareness concerning individual animal needs. These technologies include automatic weighing systems, Radio Frequency Identification (RFID) sensors for individual animal detection and behaviour monitoring, body temperature monitoring, geographic information systems (GIS) for pasture evaluation and optimization, unmanned aerial vehicles (UAVs) for herd management, and virtual fencing for herd and grazing management. Although some commercial products are available, mainly for cattle, the adoption of these systems is limited due to economic and cultural constraints and poor technological infrastructure. This review presents and discusses PLF applications and systems for grazing animals and proposes future research and strategies to improve PLF adoption and utilization in today’s extensive livestock systems.

Raihan Taqui Syed, David Spicer

Abstract The study, with the aim of comprehending the motives and subtleties of developing an entrepreneurial higher education institution (HEI) in Oman, is of significant importance. It explores the interplay among the influencing factors—environmental, organizational, and individual. The findings, which were derived from 36 in-depth, semi-structured interviews involving representatives from key stakeholder groups of an HEI, including prominent external stakeholders such as a government official holding a cabinet rank position and internal stakeholders such as the non-teaching/support staff of the HEI, whose perspectives are often overlooked, shed light on the transformative potential of the ‘Triple Helix Model’ in the entrepreneurial transformation of the HEI. These findings were derived by carrying out thematic analysis using NVIVO software. The research findings illuminate the transformative potential of the ‘Triple Helix Model’ in the entrepreneurial transformation of the HEI. This model, a collaborative effort where the HEI, Government, and Industry work together to create the necessary capital for entrepreneurial development, underscores the importance of organizational leadership. The proactive efforts of the leadership in fostering strong relationships with the other two components drive the entrepreneurial transformation of the HEI, emphasizing the crucial role of each stakeholder in the process. The empirical novelty of this study is threefold: (1) the focus on ‘developing’ an entrepreneurial university, rather than estimating its impact; (2) the incorporation of empirical weight to the knowledge domain of entrepreneurial university through organizational change management concept; and (3) an empirical contribution by applying stakeholder analysis through case study approach. Moreover, the research findings will aid policymakers / governmental agencies in drafting a robust framework for developing entrepreneurial HEIs. This, in turn, would result in producing effective job creators rather than only job seekers, thus alleviating the issue of unemployment and enhancing the pace of societal development.

Gustavo Aggio

Pesquisas recentes na historiografia do pensamento econômico têm evidenciado uma diversidade de tópicos e posições em relação ao comportamento econômico na chamada Revolução Ordinalista. O objetivo deste artigo é recuperar os desenvolvimentos de uma linha teórica que iniciou como crítica aos resultados que se estabeleciam neste movimento. A investigação parte da insistente defesa de W. E. Armstrong sobre a importância da intransitividade da indiferença, baseado em evidências da psicologia experimental que apontavam a impossibilidade de discernimento entre alternativas próximas. Posteriormente, verifica-se como sua ideia foi formalizada por R. D. Luce, um matemático com ampla influência na psicologia, por meio do conceito de semiordem, uma generalização da noção de ordem fraca, a forma padrão de conceptualizar a estrutura de preferências na microeconomia. Por fim, é investigado o papel de P. C. Fishburn neste episódio, considerando que este foi um autor de grande destaque na economia matemática, com diversas contribuições em teoria da escolha individual, sob incerteza e coletiva, inclusive com a hipótese de intransitividade da indiferença.

STAN RAZVAN STEFAN

This paper looks at how drone technology can be used not only as a tool for innovation but also as a practical driver for social and economic change in rural areas. The discussion is built around a planned educational project in Horezu, Romania, scheduled to start in late August 2025. Using a qualitative approach, I combine what we know from literature with a projection of the likely local impact. Although the project is still in preparation, the anticipated results show that drones could provide communities with both new skills and real opportunities — if certain conditions are met. These results are consistent with previous findings on technology-driven rural innovation (Popescu, 2022), which underline that the adoption of emerging technologies requires both educational initiatives and institutional support. The programme has clear replication potential. For successful scaling, several conditions are necessary: the presence of an educational institution or NGO willing to coordinate, access to a minimum of 5–10 drones, and the availability of a trained facilitator. The estimated minimum resources include a budget of approximately €5,000–7,000 for equipment and materials. However, the curriculum and activities must be adapted to the specific context of each community – for instance, focusing on agricultural monitoring in farming regions, or cultural heritage promotion in areas with tourism potential.

Miguel Alves Pereira

This article proposes predictive economics as a distinct analytical perspective within economics, grounded in machine learning and centred on predictive accuracy rather than causal identification. Drawing on the instrumentalist tradition (Friedman), the explanation-prediction divide (Shmueli), and the contrast between modelling cultures (Breiman), we formalise prediction as a valid epistemological and methodological objective. Reviewing recent applications across economic subfields, we show how predictive models contribute to empirical analysis, particularly in complex or data-rich contexts. This perspective complements existing approaches and supports a more pluralistic methodology - one that values out-of-sample performance alongside interpretability and theoretical structure.

Xiquan Zhang, Lizhu Du, Xiaoyun Song

In the context of people-centered and sustainable urban policies, identifying renewal potential based on vitality enhancement is crucial for urban regeneration efforts. This article collected population density data, house price data, and built environment data to examine the spatial pattern characteristics of Harbin’s core area using spatial autocorrelation analysis. Building on these findings, a geographically weighted regression (GWR) model was constructed to further analyze the influencing mechanisms of the relevant factors. The analysis revealed significant spatial development imbalances within Harbin’s core area, characterized by differentiated and uneven development of social and economic vitality between the old city and newly constructed areas. Notably, in certain regions, the construction intensity does not align with the levels of social and economic vitality, indicating potential opportunities for urban renewal. Furthermore, the examination of key influencing factors highlighted that the accessibility of commercial facilities and development intensity had the most substantial positive impact on social vitality. In contrast, the age of construction and the distribution of educational facilities demonstrated a strong positive correlation with economic vitality. By clearly delineating specific areas with urban renewal potential, this study provided a detailed characterization of the urban development pattern in Harbin. Additionally, by depicting the local variations in influencing factors, it established analytical foundations and objective references for urban planning in targeted locations. Ultimately, this research contributes new insights and frameworks for urban renewal analyses applicable to other regions.

Leonardo André Paes Müller

A Filosofia Rural (1763) é a obra mais importante da Fisiocracia. Assinada por Mirabeau, mas escrita em conjunto com Quesnay, ela é descrita pelos autores no capítulo 7 como uma “demonstração anatômica” do corpo político representado no Quadro econômico. O presente artigo leva a sério essa proposta e busca expor, de modo esquemático, as balizas do projeto fisiocrata como uma medicina social, a saber, sua anatomia, fisiologia e etiologia e o modo como elas fundamentam sua clínica, isto é, um diagnóstico, um prognóstico e uma terapia.

Eriko Shigetsugu, Hiroki Sakaji, Itsuki Noda

In this paper, we design indices of economic fluctuation narratives derived from economic surveys. Companies, governments, and investors rely on key metrics like GDP and industrial production indices to predict economic trends. However, they have yet to effectively leverage the wealth of information contained in economic text, such as causal relationships, in their economic forecasting. Therefore, we design indices of economic fluctuation from economic surveys by using our previously proposed narrative framework. From the evaluation results, it is observed that the proposed indices had a stronger correlation with cumulative lagging diffusion index than other types of diffusion indices.

Önder Nomaler, Bart Verspagen

We build on the interpretation of the Economic Complexity method as Correspondence Analysis (CA), and propose that the Canonical form of CA (CCA), which originated in the ecology literature, can be used to calculate multi-dimensional economic complexity. The traditional (CA) way of calculating economic complexity includes no "external" information such as countries' development characteristics to facilitate interpretation of "complexity". This has led to a wide range of fairly ad hoc interpretations of economic complexity on the basis of ex-post correlation to a long list of other variables. By the ex-ante inclusion of a number of country variables in the construction of the complexity indicators, CCA enables better interpretation, also in the case of multi-dimensional indicators. The analysis is further facilitated by another element of the ecologists' toolbox, the so-called biplots, which are CCA-based graph embeddings that represent a lower-dimensional product-space in which products and countries are positioned together, in mutual correspondence to each other. We show that in this way, CCA provides a richer account of development in many of its aspects, especially economic growth.

W. A. Rojas C., A. Zamora

We present an analysis of Bogot'{a}'s sports sector through thermostatistical models applied to economic systems. The study investigates the cross-price elasticity of income ($λ$) to determine whether sports services in Bogot'{a} are normal or inferior goods. Analyzing data from the Sports Satellite Account of Bogot'{a} (CSDB) from 2018 to 2022, we find that demand for sports services is highly elastic, particularly during economic upturns, indicating they are seen as normal or luxury goods. We also calculate the partition function, entropy, and heat capacity, showing consistency with the Boltzmann Principle, which indicates a strong correlation between microstates and the macroeconomic state, supporting the statistical thermodynamic framework. Furthermore, the study employs geometrothermodynamics to assess system stability using Kretschmann and Ricci scalars to identify economic singularities, especially during the pandemic, highlighting its disruptive impact. This approach provides a nuanced understanding of system stability and the effects of external shocks like COVID-19 on the economic structure. Our analysis demonstrates that Bogot'{a}'s sports sector responds elastically to GDP changes, with stability influenced by various macroeconomic factors. However, a decline in heat capacity as economic temperature rises suggests potential growth limitations, necessitating further research to fully grasp the sector's long-term outlook.

RAKOS (BOCA) ILEANA-SORINA, SOLOMON ALINA-GEORGIANA, STOLOJESCU BOGDAN NICOLAE et al.

The authors of this study aim to carry out a dynamic and structural analysis of the revenues and expenses of an economic entity supplying drinking water, for the period 2021-2022, to highlight their evolution as a result of the increase in the water tariff. For the profitability of the activity of the analyzed economic entity, it is particularly important to know the expenses caused by the performance of the specific activity and, respectively, to identify the best ways to improve its performance. As is known, the correlated analysis of expenses and the management of financial, material, and human resources is the basis of the managerial decision-making process of an economic entity. The objective of this research is to develop an analysis of expenses related to incomes in order to highlight their evolution, as well as the factors that influence their size. The research focused on the study of specialized literature, complemented by a case study comprising the vertical analysis of the profit and loss account, as well as the dynamic and structural analysis of the expenses and revenues of a company in the targeted field. The obtained result resides in the observation that, for the analyzed entity, the revenues adversely influence the efficiency of the total expenses. The article ends with the authors’ conclusions regarding how the expenses related to the analyzed entity’s revenues evolved during the mentioned period and the effect over time of the resulting variations.

Jessica Ojo, Kelechi Ogueji

Recent advancements in Natural Language Processing (NLP) has led to the proliferation of large pretrained language models. These models have been shown to yield good performance, using in-context learning, even on unseen tasks and languages. They have also been exposed as commercial APIs as a form of language-model-as-a-service, with great adoption. However, their performance on African languages is largely unknown. We present a preliminary analysis of commercial large language models on two tasks (machine translation and text classification) across eight African languages, spanning different language families and geographical areas. Our results suggest that commercial language models produce below-par performance on African languages. We also find that they perform better on text classification than machine translation. In general, our findings present a call-to-action to ensure African languages are well represented in commercial large language models, given their growing popularity.

Mohamed Assem Ibrahim, Shaizeen Aga

This paper evaluates the efficacy of recent commercial processing-in-memory (PIM) solutions to accelerate fast Fourier transform (FFT), an important primitive across several domains. Specifically, we observe that efficient implementations of FFT on modern GPUs are memory bandwidth bound. As such, the memory bandwidth boost availed by commercial PIM solutions makes a case for PIM to accelerate FFT. To this end, we first deduce a mapping of FFT computation to a strawman PIM architecture representative of recent commercial designs. We observe that even with careful data mapping, PIM is not effective in accelerating FFT. To address this, we make a case for collaborative acceleration of FFT with PIM and GPU. Further, we propose software and hardware innovations which lower PIM operations necessary for a given FFT. Overall, our optimized PIM FFT mapping, termed Pimacolaba, delivers performance and data movement savings of up to 1.38$\times$ and 2.76$\times$, respectively, over a range of FFT sizes.

Balwant Rawat, J. Rawat, S. Purohit et al.

Himalayan mountain forests have been a potential candidate for the investigation of perturbations due to the complex geography in which they sustain and the sensitivity of the species toward human disturbance and climate change. Among various tree species, brown oak (Quercus semecarpifolia), a very important component of the Himalayan mountains, has been identified as a keystone species due to its substantial economic and ecological benefits. Maintenance of microclimate and suitable habitats with a rich source of natural resources makes Q. semecarpifolia the most preferred forest for luxuriant growth of ground flora, shelter for fauna, and multipurpose uses by the local people. In a climax community, it plays a critical role in environmental balance both at the local and regional levels. Unfortunately, it has become one of the most overexploited tree species of the Himalayan region over the last few decades due to its high demand for dry season fodder and firewood. The wide range of seedling distribution 348–4,663 individuals ha–1 is evidence of the disturbance accompanied by poor regeneration in Q. semecarpifolia forests. Moreover, litter accumulation and grass cover adversely affect seed germination. The ecological cost of oak forest degradation is perhaps more important and damage is irreversible. Thus, continuous demand and extensive threats accompanied by poor regeneration have drawn the attention of stakeholders to conserve this species. However, propagation protocol, especially the pre-sowing treatment of the species, has not been impressive for large-scale multiplication. This review is comprehensive information on distribution, phenology, regeneration pattern, human threat, conservation approaches, and management of Q. semecarpifolia in the Himalayan region.

A. Miccoli, Matteo Manni, S. Picchietti et al.

In the last three decades, the aquaculture sector has experienced a 527% growth, producing 82 million tons for a first sale value estimated at 250 billion USD. Infectious diseases caused by bacteria, viruses, or parasites are the major causes of mortality and economic losses in commercial aquaculture. Some pathologies, especially those of bacterial origin, can be treated with commercially available drugs, while others are poorly managed. In fact, despite having been recognized as a useful preventive measure, no effective vaccination against many economically relevant diseases exist yet, such as for viral and parasitic infections. The objective of the present review is to provide the reader with an updated perspective on the most significant and innovative vaccine research on three key aquaculture commodities. European sea bass (Dicentrarchus labrax), Nile tilapia (Oreochromis niloticus), and Atlantic salmon (Salmo salar) were chosen because of their economic relevance, geographical distinctiveness, and representativeness of different culture systems. Scientific papers about vaccines against bacterial, viral, and parasitic diseases will be objectively presented; their results critically discussed and compared; and suggestions for future directions given.

Qingcheng Zeng, Tingyu Lu, Kun-Chin Lin et al.

Abstract One of the advantages of Arctic shipping or the Northern Sea Route (NSR) over the traditional Suez Canal Route (SCR) is its comparatively shorter transport distance between the Atlantic and the Pacific, which makes North East Asia and North Europe seemingly closer geographically and economically. The economic development of the North-East Asia brings further potential for the commercial applications of the NSR. Meanwhile, China's "Belt and Road" Initiative (BRI), the Railway Transport between China and Europe (Railway) has also been developing rapidly. This has led to the possibility of route competition among the NSR, the SCR and the Railway in freight transport between East Asia and Western Europe. In this paper, the market shares of the three transport routes are analyzed using bootstrapped multinomial logit (MNL) model. Further, scenario analysis is provided to examine the change of market share of the NSR under varying development trends related to economic conditions, natural conditions, and shippers' preference. Based on the results, policy implications and suggestions are discussed.

Rongheng Lin, Zezhou Ye, Ziyan Guo et al.

Abstract A hydrogen station is one that fills or stores the hydrogen, which is critical to the commercial development of hydrogen energy and fuel cell vehicle industry. Therefore, its location planning becomes an important issue. Similar to the electric vehicle (EV) charging station's planning, several factors are considered including the location, the demand of the fuel, the driving distance, etc. In this paper, multiple data sources are applied to the site selection model, including the existing petrol-refueling station network data, geographic information system (GIS) data, population data and regional economic data. Based on the operation of the genetic algorithm, combined with the idea of the greedy algorithm and the annealing algorithm, we propose a multi-algorithm hybrid solution, which not only can avoid local optimal, but also can converge quickly. On the basis of the site selection scheme of the hydrogen station in California, we have optimized the location scheme in Beijing. Finally, we present the feasibility proposals for hydrogen station location in Beijing, including the appropriate number of hydrogen stations in different regions, the reasonable coverage distance of hydrogen stations, etc. Due to the huge development prospects for hydrogen energy and the urgent need to reduce the construction cost of hydrogen stations in China, this research can quickly optimize the location of the hydrogen station and further explore potential mathematical relationships, which has certain social significance and economic benefits.

Abstract Background/objective Colombia detected its first COVID-19 case on March 2nd, 2020. From March 22nd to April 25th, it implemented a national lock down that, apparently, allowed the country to keep a low incidence and mortality rate up to mid-May. Forced by the economic losses the government opened many commercial activities, which was followed by an increase in cases and deaths. This paper presents a critical analysis of the Colombian surveillance data in order to identify strengths and pitfalls of the control measures. Methods Descriptive analysis of Polymerase Chain Reaction (PCR) confirmed cases between March and July 25th. Data was described according to the level of measurement. Incidence and mortality rates of COVID-19 were estimated by age, sex, and geographical areas. Sampling rates for suspected cases were estimated by geographical areas, and the potential for case underestimation was assessed using sampling differences. Results By July 25, Colombia (50,372,424 habitants) has reported 240,745 cases and 8,269 deaths (case fatality ratio 3.4%). It has analyzed 1,370,271 samples (27,405 samples per million people) with a positivity ratio of 17%. Sampling rates per million vary by region, from 2,664 to 158,681 per million and, consequently, incidence and mortality rate also vary. Due to geographical variations in surveillance capacity, Colombia may have overlooked up to 82% of the actual cases. Conclusion Colombia has a lower case and mortality incidence compared to other South American countries. This may be an effect of the lock down but also, at some extent, to geographical differences in surveillance capacity. Indigenous populations with little health infrastructure have been hit the hardest.