Hasil untuk "Commercial geography. Economic geography"

SPULBAR LUCIAN

The relationship between legal systems and artificial intelligence decision-making in managing business organizations is becoming increasingly crucial in light of fast-paced technological progress and growing legal complexities. The topic for this research is the role of binding legal norms, exemplified by the EU’s AI Act and data governance laws, in both directly and indirectly conditioning managerial decisions through artificial intelligence systems. The study will be conducted through qualitative comparative research on large global organizations operating in high-risk business environments and will isolate instances of patterns and trends in managing legal risks through artificial intelligence systems and processes. The research will draw on semi-structured, qualitative research on views obtained from compliance professionals, artificial intelligence software engineers, and CXO personnel, and on content and text analysis of corporate governance reports to evaluate the effectiveness of legal compliance in altering organizational behavior patterns. The research will show how legal systems are no longer external influences on business organizations, as they are increasingly being constitutive of organizational behavior through various internal mechanisms, including accountability algorithms, legal risk software, and cross-functional ethics committees, thereby increasingly subjecting artificial intelligence decision processes to a set of legally informed constraints and determinations. This will show how this synthesis of artificial intelligence decision systems and legal systems is leading to a paradigm shift in management decisions and inference, thereby leading to greater resilience and greater trust building in corporate organizations by increasingly positioning the law as a resource, and thereby leading to greater confidence and trust and trust-building in artificial corporate management systems.

Lisseth Gutierrez-Gonzalez, Ernesto Monroy, Melissa Johnson Morgan et al.

Abstract The purpose of this study is to understand employees’ attributions of human resource management (HRM) practices and how these attributions confluence with employees’ creativity. We propose the concept of human resource attribution (HR attribution) as a construct that can aid in understanding employees' creativity. This research studies how human resource (HR) attributions play a part in the creativity of employees in small- and medium-sized enterprises (SMEs) in Colombia's Atlántico Region. Semi-structured interviews were conducted with 12 SME employees. Our results were analyzed with reflexive thematic analysis. Generated themes enclosed individual factors (the HR attribution participants made, and the employees’ level of organizational commitment) and organizational factors (managerial practices). The results indicate that a key construct of employees’ creativity is their interpretation of why HRM practices are implemented. This suggests that the actual HRM practices are not always the elements that matter for employees’ creativity in all contexts. Furthermore, other individual and social constructs were found to be relevant to Colombian employees’ creativity. Future studies should quantitatively test the impact of HR attributions on SME employees’ creativity.

Selim Tüzüntürk, Filiz Giray, Volkan Gürsel

The study’s main purpose is to analyze the effect of wheat producer support on wheat production using panel data methods. The primary independent variable of interest is wheat producer support, and the secondary variables of interest are wheat harvested area, previous period price of wheat, and previous period production of wheat. Panel data include 352 observations from selected 16 countries between 2000 and 2022. All the data are annual and retrieved from the OECD official website. The main finding of this study is that wheat producer support has a positive effect on wheat production. This finding reveals that agricultural support increases agricultural production for wheat crops. The findings indicate that countries should give importance to producer support policies in agriculture and develop new support policies. The secondary findings of this study show that wheat harvested area, previous period price of wheat, and previous period production of wheat have a positive effect on wheat production. The study has significant consequences for the Mediterranean countries, which have a considerable share in world wheat imports during and after the analysis period.

Liwei Qin, Wenke Zong, Kai Peng et al.

In the realm of sustainable city development, evaluating the spatial vitality of urban green spaces (UGS) has become increasingly pivotal for assessing public space quality. This study delves into the spatial heterogeneity of park vitality across diverse urban landscapes at a city scale, addressing limitations inherent in conventional approaches to understanding the dynamics of park vitality. Leveraging geotagged check-in data from 65 parks in the study case of Changsha City, a quantitative analysis was undertaken to assess spatial vitality. The investigation incorporated data concerning internal and external factors influencing park vitality, employing the Multi-scale Geographically Weighted Regression (MGWR) model to dissect nuanced spatial heterogeneity. The research uncovers notable spatial discrepancies in factors influencing park vitality across diverse urban areas, emphasizing the reliance on adjacent residential communities and internal commercial amenities provision. These dependencies correspond with economic development differences among urban locales, revealing distinct geographic trends. This study has a novel perspective and methodology for investigating urban park vitality, providing significant insights for urban green space planning and management. It emphasizes the necessity of acknowledging spatial diversity in urban park planning and design by incorporating the distinct socio-economic characteristics of each urban zone, which is crucial for both urban planners and policymakers.

Thomas Kang, Isabela Menetrier

Este trabalho apresenta uma nova base de dados com estimativas de despesas em educação e alguns indicadores de viés elitista nas políticas educacionais no Brasil entre 1933 e 2010. As estimativas de despesa pública em educação como proporção do Produto Interno Bruto (PIB) (total, educação básica e ensino superior) são semelhantes às apresentadas por Maduro (2007). A novidade do presente trabalho são as séries de estimativas de despesas por ciclo de ensino (EF1, EF2 e EM). A partir destas estimativas, apresenta-se também um indicador de viés elitista: a razão de despesas por estudante no primário (EF1) em relação ao gasto por aluno no ensino superior. Essas razões foram historicamente baixas, mas houve uma elevação abrupta a partir do final da década de 1960. Este aumento se deu mais pela expansão da matrícula no ensino superior do que por uma elevação de gastos por estudante no primário.

TOMA SORIN-GEORGE, GRĂDINARU CĂTĂLIN, MODREANU ANDRA

The digital economy has become a key issue for both theoreticians and practitioners worldwide, especially in the last decade. It is based on various forms of technology, such as the Internet of Things, artificial intelligence and blockchain. The aim of the paper is to briefly present and analyse the evolution of the digital economy in Romania in the period 2019-2022. In this respect, the authors used a qualitative research method. The results show that the period 2019-2022 witnessed a slight decrease in Romania’s performance related to the Digital Economy and Society Index. The paper indicates that despite its efforts, Romania has scored well below the other EU countries. However, the adoption of several measures in favor of digitalisation proved its clear commitment to building a functional digital economy.

Abdelkader SAHED, Hacene KAHOUI

Forecasting electricity consumption is necessary for electric grid operation and utility resource planning, as well as to improve energy security and grid resilience. Thus, this research aims to investigate the prediction performance of the ARIMA and LSTM neural network model using electricity consumption data during the period 1990 to 2020. The time series for electricity consumption is divided into 70% for training data and 30% for test data. The results showed that the LSTM model provided improved forecasting accuracy than the ARIMA model.

G. Zhong, E. Nicolosi

Chunyu Chen, Linglan Bi, Kuanfan Zhu

Urban green space plays an important role in beautifying the environment, improving the quality of life of residents, and promoting sustainable urban development. Rapid urbanization has led to great changes in the spatial structure and layout of urban green space. It is urgent to put forward the sustainable development strategy of green space through the research on the change of urban green space. Based on the geographical spatial differences of urban green space and integrating the factors of economy, society, industry, land use, and the environment, we constructed a research framework of “space-supply-demand” integration of urban green space by GI and geodetector methods, and we conducted an empirical study on the spatial–temporal changes of urban green space and its driving mechanism in prefecture-level cities along the Yangtze River Economic Belt in China. First, the urban green space along the Yangtze River Economic Belt is concentrated in spatial distribution, while uneven development appears in urban greening among the zones. Second, the influence of different factors on urban green space change varies greatly and can be divided into three types: key factors, important factors, and auxiliary factors. The driving mechanism of the spatial distribution of urban green space supply and demand is quite different, but urban population and commercial service facilities land are their key influence factors, having a comprehensive influence on the spatial–temporal changes of urban green space. Third, the factors are classified into three categories of high, medium, and low levels according to the mean of interacting forces; in particular, the factors of per capita GDP, utility land, industrial smoke (dust) emissions, and other factors have a very strong interactive effect with other factors. Fourth, according to the spatial distribution characteristics of urban green space and its driving mechanism, this paper puts forward planning and policy suggestions, providing reference for other areas to deal with the green space change.

Pradeep Chintagunta, Junhong Chu

D. Mannino, K. Higuchi, Tzy-Chyi Yu et al.

BACKGROUND: The morbidity and mortality associated with COPD exacts a considerable economic burden. Comorbidities in COPD are associated with poor health outcomes and increased costs. Our objective was to assess the impact of comorbidities on COPD-associated costs in a large administrative claims dataset. METHODS: This was a retrospective observational study of data from the Truven Health MarketScan Commercial Claims and Encounters and the MarketScan Medicare Supplemental Databases from January 1, 2009, to September 30, 2012. Resource consumption was measured from the index date (date of first occurrence of non-rule-out COPD diagnosis) to 360 days after the index date. Resource use (all-cause and disease-specific [ie, COPD- or asthma-related] ED visits, hospitalizations, office visits, other outpatient visits, and total length of hospital stay) and health-care costs (all-cause and disease-specific costs for ED visits, hospitalizations, office visits, and other outpatient visits and medical, prescription, and total health-care costs) were assessed. Generalized linear models were used to evaluate the impact of comorbidities on total health-care costs, adjusting for age, sex, geographic location, baseline health-care use, employment status, and index COPD medication. RESULTS: Among 183,681 patients with COPD, the most common comorbidities were cardiovascular disease (34.8%), diabetes (22.8%), asthma (14.7%), and anemia (14.2%). Most patients (52.8%) had one or two comorbidities of interest. The average all-cause total health-care costs from the index date to 360 days after the index date were highest for patients with chronic kidney disease ($41,288) and anemia ($38,870). The impact on total health-care costs was greatest for anemia ($10,762 more, on average, than a patient with COPD without anemia). CONCLUSIONS: Our analysis demonstrated that high resource use and costs were associated with COPD and multiple comorbidities.

MARGARETA FĂGĂDAR (GHIȘA)

A constant concern for decision-makers in all countries of the world always remains to provide the framework for sustainable growth. Economic growth cannot be achieved without investigations, from internal or external sources, regardless of the level of development in a country. With the study, we sought to analyze the evolution of spending on investigations and its influence on economic growth, resulting from managerial decisions. Some series of statistical data are presented in this article to show the collective importance of budget revenues and attracting new sources of funding, such as European funds, in order to increase investigation expenditures, even if, in assessing the effort-effect, effort ratio. being easy to identify, and the effect are harder to quantify. The dynamics of investigations in Romania depend on attracting new sources of foreign financing, such as European non-reimbursable funds from the European Union. The absorption of EU funds is an objective of national interest and a solution to stimulate investment and the economy. Public investment is low-efficiency, with management gaps, especially in project preparation, prioritization and public procurement, and private investigations are affected by persistent legal uncertainty and bureaucracy. Fiscal policy changes, poor strategic planning of investigations and delays are real obstacles to the growth of significant investigations in the medium and long term.

X. Duan, Qingwu Hu, P. Zhao et al.

Urban commercial areas can reflect the spatial distribution of business activities. However, the scope of urban commercial areas cannot be easily detected by traditional methods because of difficulties in data collection. Considering the positive correlation between business scale and nighttime lighting, this paper proposes a method of urban commercial areas detection based on nighttime lights satellite imagery. First, an imagery preprocess model is proposed to correct imageries and improve efficiency of cluster analysis. Then, an exploratory spatial data analysis and hotspots clustering method is employed to detect commercial areas by geographic distribution metric with urban commercial hotspots. Furthermore, four imageries of Wuhan City and Shenyang City are selected as an example for urban commercial areas detection experiments. Finally, a comparison is made to find out the time and space factors that affect the detection results of the commercial areas. By comparing the results with the existing map data, we are convinced that the nighttime lights satellite imagery can effectively detect the urban commercial areas. The time of image acquisition and the vegetation coverage in the area are two important factors affecting the detection effect. Harsh weather conditions and high vegetation coverage are conducive to the effective implementation of this method. This approach can be integrated with traditional methods to form a fast commercial areas detection model, which can then play a role in large-scale socio-economic surveys and dynamic detection of commercial areas evolution. Hence, a conclusion can be reached that this study provides a new method for the perception of urban socio-economic activities.

C. Moore, James W. Morley, B. Morrison et al.

Observational evidence shows marine species are shifting their geographic distribution in response to warming ocean temperatures. These shifts have implications for the US fisheries and seafood consumers. The analysis presented here employs a two-stage inverse demand model to estimate the consumer welfare impacts of projected increases or decreases in commercial landings for 16 US fisheries from 2021 to 2100, based on the predicted changes in thermally available habitat. The fisheries analyzed together account for 56% of the current US commercial fishing revenues. The analysis compares welfare impacts under two climate scenarios: a high emissions case that assumes limited efforts to reduce atmospheric greenhouse gas and a low emissions case that assumes more stringent mitigation. The present value of consumer surplus impacts when discounted at 3% is a net loss of $2.1 billion (2018 US$) in the low emissions case and $4.2 billion in the high emissions scenario. Projected annual losses reach $278–901 million by 2100.

DOREL CONSTANTIN CODREAN

Brief presentation together with the personal evaluations of the authors of the most relevant works in the literature on the evolution of financial reporting, analysis and evaluation of performance as well as the most modern techniques for determining the performance of companies.

Houcine JEDER, Sabrine Hattab, Iheb Frija

Food security issue is getting more attention in middle-income countries such as Tunisia after the revolution 2011, where many factors affecting its food security are multiplied. An econometric analysis of food security was done through the Vector Error Correction Model approach (VECM). The result of this approach shows that there is a significant long-term causality between the dependent variables and the explanatory variables. Some signs of variables like land under cereals assert the hypothesis of Ricardo’s land rent theory and also attract attention for the preservation of land fertility in climate change context. However, there is a short-term causal relationship between food security and independents variables like: land under cereals, inflation and food imports. These results confirm that the issue of food security in Tunisia is a question of threat in the short and long-term instability. So, it is important today to readjust some factors to ensure food security in Tunisia like controlling inflation and lowering the food importation as short-term measures and preserving and improving the fertility of land under cereals and adopting climate change as long-term measures.

M Syed Shaahid, M Luai Alhems, K. Rahman

In the present study, the techno-economic feasibility of development of 15 MW wind power plants (wind farms) in the Kingdom of Saudi Arabia has been investigated by analyzing long-term wind speed data. To achieve this aim, two geographically distinct sites covering different non-coastal locations of the Kingdom of Saudi Arabia have been selected. Long-term data indicates that the yearly average wind speed of Kingdom of Saudi Arabia varies from 3.0-4.5 m/s at 10 m height. The wind farms simulated consist of different combinations of 600 kW commercial wind machines (50 m hub-height). The NREL?s (HOMER Energy?s) HOMER software has been employed to perform the analysis. The study presents the monthly variations of wind speed, cumulative frequency distribution profiles of wind speed, monthly and yearly amount of energy generated from the proposed 15 MW wind farms (50 m hub-height) at different non-coastal locations of Kingdom of Saudi Arabia, cost of generating energy ($/kWh), capacity factor (%), etc. The cumulative frequency distribution indicates that the wind speeds are less than 3 m/s for 48% and 59% of the time during the year at Badanah (Northern province) and Khamis-Mashayt (Southern province), respectively. This implies that wind electric conversion systems or wind farms will not produce energy for 48% of the time during the year at Badanah and for 59% at Khamis-Mashayt. The annual energy produced by 15 MW wind farms (50 m hub-height) has been found to be 18778 and 11314 MWh at Northern and Southern provinces, respectively. The cost of wind-based electricity by using 600 kW (50 m hub-height) commercial wind electric conversion systems has been found to be 0.0612 and 0.1016 US$/kWh for Badanah and Khamis-Mushayt, respectively. Also, the capacity factor of the wind-based power plant has been found to vary from 9 to 15% for the considered locations.

Daniela Ganelin, Isaac L. Chuang

Massive open online courses (MOOCs) promise to make rigorous higher education accessible to everyone, but prior research has shown that registrants tend to come from backgrounds of higher socioeconomic status. We study geographically granular economic patterns in ~76,000 U.S. registrations for ~600 HarvardX and MITx courses between 2012 and 2018, identifying registrants' locations using both IP geolocation and user-reported mailing addresses. By either metric, we find higher registration rates among postal codes with greater prosperity or population density. However, we also find evidence of bias in IP geolocation: it makes greater errors, both geographically and economically, for users from more economically distressed areas; it disproportionately places users in prosperous areas; and it underestimates the regressive pattern in MOOC registration. Researchers should use IP geolocation in MOOC studies with care, and consider the possibility of similar economic biases affecting its other academic, commercial, and legal uses.

J. Buono, Kush Mathur, A. Averitt et al.

Farshad Momeni, Ali Arab Mazar Yazdi, Seyed Mohammad Sajjad Najafi

Abstract In recent decades, many efforts have been put into understanding and determining key variables and factors affecting knowledge-based economy. Triple Helix model is a model with relative success in this regard; however, there is still a long way to go until it can provide policy makers and researchers with an inclusive and deep insight. Researchers of the current study strived to distinguish one of the main theoretical shortcomings of the model, i.e., considering reward systems reformation firmly fixed in the institutional framework of society, while introducing an overview of the Triple Helix model and its underlying logic using a descriptive-analytical method based upon theoretical framework of new institutionalism. This paper aims to highlight that, in the developing countries’ path toward a knowledge-based economy, reward systems reformation plays a key role and it is worth to be considered in models of determining the knowledge-based economy, the Triple Helix model, in particular.