Hasil untuk "Commercial geography. Economic geography"

Bruno Barbosa, Emerson Marçal, Pedro Luiz Valls Pereira

Using a Global Vector Autoregressive (GVAR) framework that addresses the curse of dimensionality, we assess linkages between regions and examine how macroeconomic shocks spread across them. This study examines the  Brazilian labor market by identifying and quantifying the regional and temporal propagation of shocks in aggregate economic activity. A key innovation is our use of data from the Brazilian Institute of Geography and Statistics to measure regional linkages by analyzing the infrastructure connections of Brazilian municipalities. We capture regional interdependence by incorporating both economic and infrastructure connections. Our findings indicate that macroeconomic shocks have a particularly strong effect in Brazil’s South, Southeast, and Midwest regions.

AVRĂMESCU TIBERIU-CRISTIAN

Real convergence is a fundamental pillar of the European Union and refers to the reduction of disparities between less developed and more advanced economies. This process began to be studied in the second half of the 20th century and has become increasingly debated with the establishment and expansion of the European Economic Community.The main objective of this paper is to examine real convergence among the Central and Eastern European member states that joined the European Union in 2004 and 2007 and have not yet adopted the single European currency. In this context, we analyzed Romania’s real convergence in comparison with the results of these member states, using the following indicators: Gross Domestic Product per capita, expressed as a percentage of the EU27 average, nominal labor productivity per person, expressed as a percentage of the EU27 average, the unemployment rate and the export-to-import coverage ratio. The results of the study suggest that these member states, including Romania, have made significant progress in terms of real convergence, despite concerns that their accession to the European Union would threaten its stability. Real convergence plays a significant role in ensuring balanced economic growth and reducing regional disparities—key aspects for maintaining social cohesion and economic stability throughout the European area.

CHIRIȚESCU DUMITRU DOREL

The topic of international wealth transfers mediated through commercial exchange is by no means a new one. Throughout history, those who have lost out in such processes—the so-called “colonies”—have accused the beneficiaries, “the metropolises,” of exploitation, while the latter have consistently denied any wrongdoing. Both sides, in a sense, appear to have their own arguments. Yet, there is only one underlying truth, which should orient the debate towards development, accumulation, economic expansion, and prosperity—for both the colony and the metropolis alike. Romania, resembling a colony in certain structural respects, has been experiencing economic imbalances resulting from these transfers. Romanian political populism has often instrumentalised this theme, turning it against the country’s own long-term interests. This occurs under the mistaken belief that such value transfers could be halted through Romania’s economic and political isolation. The present paper aims to examine to what extent this narrative holds true. Before doing so, however, it is necessary to clarify what is meant by the notions of colony of the West or colony of Europe.

Dan Christmas

The Collaborative Environmental Planning Initiative (CEPI) is a one-of-a-kind organization in Unama’ki-Cape Breton. Fittingly, it was brought together through the vision and dedication of Charlie Dennis who was searching for a way to turn around the ecological health of the Bras d’Or Lakes or Pitupaq in Mi’kmaq, an inland estuary in the heart of Cape Breton. This essay will describe the events leading to the founding of CEPI and outline its first seven years of growth as it struggled with its identity. 

Shubashini Velu, Ishraat Saira Wahid, Kayalvily Tabianan

Abstract Recently, there has been a transformation in the teaching and learning methods at universities, with nearly all higher education institutions using Learning Management System (LMS) platforms for course delivery and learning activities. These digital learning environments exhibit limited innovative learning methods, including a deficiency in appropriate artefacts and tools, as well as a lack of personalization and assistance. One of the reasons why Sustainable Development Goal (SDG) goal 4 is important is because it highlights the need to invest resources for advancement of educational tools and facilities towards sustainable development education. The literature indicates a lack of equilibrium between the functions of artefacts, actions, and pedagogy in the ever-changing technology-enhanced learning environment. Therefore, this study aims to examine the relationship between the adoption of artefacts and their impact on innovative learning practices. It integrates Vygotsky’s concept of mediating human activity through the use of artefacts, as well as two foundational theories: connectivism learning theory and growth mindset theory. The data for this quantitative study were obtained through survey. An analysis was conducted on a total of 350 questionnaires, resulting in 241 responses. The survey was conducted among undergraduate students who are currently enrolled at Prince Mohammad bin Fahd University (PMU). The data were analyzed using SmartPLS. Findings: This study addresses the clear correlation of artefacts actions on learners that facilitates innovative learning practices in the context of Saudi Arabia. Students’ innovative learning experiences are defined by their independence and are facilitated by tangible actions. Students valued the inclusion of creative artefacts that promote problem-solving, facilitate student-centered learning, and incorporate gamified components which is essential for scholarly communication within and beyond the classroom. It is important to note that the inclusion of artefacts should not be solely for the sake of showcasing innovation without any meaningful influence on digital acceleration. In order to assess the applicability of these findings, it is recommended that future research be conducted in higher education institutions (HEIs) in other regions of Saudi Arabia or other Gulf Cooperation Council (GCC) countries. Additionally, further investigation should explore the impact of integrating virtual reality and augmented reality as tools, as well as incorporating various pedagogical approaches to test the effectiveness of the innovation in the learning process.

Antonio Russo, Pasquale Scaramozzino, Andrea Zaccaria

Economic complexity measures aim to quantify the capability content or endowment of industries and territories; however, capabilities are not observable, and therefore cannot be directly used in the computations. We estimate such endowments by quantifying the quality and diversity of the skills in the occupations required in specific industries. We refer to this job-based assessment as the hidden complexity, in contrast with the usual revealed complexity, which is computed from economic outputs such as exports or production. We show that our job-based measure of complexity is positively associated to wage levels and labor productivity growth, whereas the classic revealed measure is not. Finally, we discuss the application of these methods at the territorial level, showing their connection with economic growth.

CONSTANTIN IONUT-CONSTANTIN

In a continuously evolving and increasingly competitive environment, as companies and organizations are always subject to change and must adapt accordingly in order to meet the targeted performance and productivity requirements, in order for the human capital - an organization’s most valuable resource - to attain performance and results in the long run, leadership becomes an essential variable, key to not only individual and organizational performance, but also to outgrow competition. In achieving these results, come into play the dynamics of the leaderemployee relationship. In this article, we will discuss how in the present-day, a relationship between leaders and employees based on good communication and mutual trust can influence and impact both individual and organizational performance.

OTILIA-ANA LUNGU , ANGELA-ELIZA MICU

This paper attempts to provide a comprehensive and pragmatic understanding of AI implementation, analyzing its advantages and disadvantages. In addition, the study attempts to identify potential barriers to integrating AI into automated organizational decision-making. The study employs an exploratory research approach through interviews conducted with 26 employees in various positions within the organization, both in the public and private sectors, to capture diverse perspectives within the organization. The analysis identified the prominent effects of AI adoption in the work process, namely data security and privacy, job insecurity, information overload, as well as barriers to the adoption of automated decision-making, which include social interaction, regulations, lack of trust and transparency, dynamic business environments, loss of power and control as well as ethical considerations. This research broadly examines the interactions between technology and humans, offering recommendations for the successful adoption and use of AI in the work process.

GUIU MARIAN-ROMEO

Currently, tax evasion is the most important component of the mechanism of economic-financial crime, and the EU space is faced with an impressive dynamic of the export and import of economic crime, combating this phenomenon becoming the primary goal of specialized bodies, since in essence, evasion fiscal refers to the action of avoiding or evading the payment of taxes and duties to the state. Certain case studies and recent researches at the international level have highlighted the fact that Romania, compared to other EU states, has a gap to recover in terms of tax collection, especially the VAT GAP, which indicates a low degree of compliance with the payment of this tax. In the context of the accentuation of the budget deficit caused to a large extent by the degree of collection of fees and taxes owed by taxpayers, we consider the current topic, the purpose of this paper is to explore whether the increase in the degree of collection of fees and taxes can be influenced by certain factors such as the level of economic development, the existence of a correct compliance environment, the perceived trust in the tax authorities compared to the corruption perception index registered by Romania.

Avichai Snir, Dudi Levy, Dian Wang et al.

Many experimental studies report that economics students tend to act more selfishly than students of other disciplines, a finding that received widespread public and professional attention. Two main explanations that the existing literature offers for the differences found in the behavior between economists and noneconomists are the selection effect, and the indoctrination effect. We offer an alternative, novel explanation. We argue that these differences can be explained by differences in the interpretation of the context. We test this hypothesis by conducting two social dilemma experiments in the US and Israel with participants from both economics and non-economics majors. In the experiments, participants face a tradeoff between profit maximization, that is the market norm and workers welfare, that is the social norm. We use priming to manipulate the cues that the participants receive before they make their decision. We find that when participants receive cues signaling that the decision has an economic context, both economics and non-economics students tend to maximize profits. When the participants receive cues emphasizing social norms, on the other hand, both economics and non-economics students are less likely to maximize profits. We conclude that some of the differences found between the decisions of economics and non-economics students can be explained by contextual cues.

Thiago C. Silva, Paulo V. B. Wilhelm, Diego R. Amancio

This study examines the effects of de-globalization trends on international trade networks and their role in improving forecasts for economic growth. Using section-level trade data from nearly 200 countries from 2010 to 2022, we identify significant shifts in the network topology driven by rising trade policy uncertainty. Our analysis highlights key global players through centrality rankings, with the United States, China, and Germany maintaining consistent dominance. Using a horse race of supervised regressors, we find that network topology descriptors evaluated from section-specific trade networks substantially enhance the quality of a country's GDP growth forecast. We also find that non-linear models, such as Random Forest, XGBoost, and LightGBM, outperform traditional linear models used in the economics literature. Using SHAP values to interpret these non-linear model's predictions, we find that about half of most important features originate from the network descriptors, underscoring their vital role in refining forecasts. Moreover, this study emphasizes the significance of recent economic performance, population growth, and the primary sector's influence in shaping economic growth predictions, offering novel insights into the intricacies of economic growth forecasting.

Yang Xu, Loni Philip Tabb

Research on residential segregation has been active since the 1950s and originated in a desire to quantify the level of racial/ethnic segregation in the United States. The Index of Concentration at the Extremes (ICE), an operationalization of racialized economic segregation that simultaneously captures spatial, racial, and income polarization, has been a popular topic in public health research, with a particular focus on social epidemiology. However, the construction of the ICE metric usually ignores the spatial autocorrelation that may be present in the data, and it is usually presented without indicating its degree of statistical and spatial uncertainty. To address these issues, we propose reformulating the ICE metric using Bayesian modeling methodologies. We use a simulation study to evaluate the performance of each method by considering various segregation scenarios. The application is based on racialized economic segregation in Georgia, and the proposed modeling approach will help determine whether racialized economic segregation has changed over two non-overlapping time points.

Yiting Chen, Tracy Xiao Liu, You Shan et al.

As large language models (LLMs) like GPT become increasingly prevalent, it is essential that we assess their capabilities beyond language processing. This paper examines the economic rationality of GPT by instructing it to make budgetary decisions in four domains: risk, time, social, and food preferences. We measure economic rationality by assessing the consistency of GPT's decisions with utility maximization in classic revealed preference theory. We find that GPT's decisions are largely rational in each domain and demonstrate higher rationality score than those of human subjects in a parallel experiment and in the literature. Moreover, the estimated preference parameters of GPT are slightly different from human subjects and exhibit a lower degree of heterogeneity. We also find that the rationality scores are robust to the degree of randomness and demographic settings such as age and gender, but are sensitive to contexts based on the language frames of the choice situations. These results suggest the potential of LLMs to make good decisions and the need to further understand their capabilities, limitations, and underlying mechanisms.

CECILIA IRINA RĂBONTU, ANA GABRIELA BABUCEA

The digital age continues to amaze us with its spectacular realities, with the changes that are due to the new way of approaching all areas of activity, including services. Services are gaining new connotations in an increasingly digital economy and society and we find more and more situations in which the inseparability between provider and consumer is no longer a defining feature of services. This aspect is due to the digitalization that has penetrated deep into the tertiary sector. From financial services, consulting services, tourism services, telecommunications services, transportation, etc. to health and education services, we find the possibility of providing them in whole or in part through discoveries in the digital age. It is no longer a secret that robots are more and more present in our lives, not that computer applications bring us added value in our personal and professional life, nor that in the near future we will witness major changes in all fields and especially in services. We aim to make a foray into the tertiary sector from the perspective of the impact of the digital age and to present how the services will change, who will provide them, how this will be done and what new services will appear in this context. If the tertiary sector was the one that saved jobs from the last wave of mechanization, today it seems that the threat of job loss is rather felt in this sector. Vendors are already being replaced by online platforms, taxi drivers and truck drivers, robot waiters and waiters, online teaching platform teachers, and more. The world is changing before our eyes in all fields of activity, implicitly in services and we want to present such aspects in this article.

Sándor Juhász, Gergő Pintér, Ádám Kovács et al.

Cities host diverse people and their mixing is the engine of prosperity. In turn, segregation and inequalities are common features of most cities and locations that enable the meeting of people with different socio-economic status are key for urban inclusion. In this study, we adopt the concept of economic complexity to quantify the sophistication of amenity supply at urban locations. We propose that neighborhood complexity and amenity complexity are connected to the ability of locations to attract diverse visitors from various socio-economic backgrounds across the city. We construct the measures of amenity complexity based on the local portfolio of diverse and non-ubiquitous amenities in Budapest, Hungary. Socio-economic mixing at visited third places is investigated by tracing the daily mobility of individuals and by characterizing their status by the real-estate price of their home locations. Results suggest that measures of ubiquity and diversity of amenities do not, but neighborhood complexity and amenity complexity are correlated with the urban centrality of locations. Urban centrality is a strong predictor of socio-economic mixing, but both neighborhood complexity and amenity complexity add further explanatory power to our models. Our work combines urban mobility data with economic complexity thinking to show that the diversity of non-ubiquitous amenities, central locations, and the potentials for socio-economic mixing are interrelated.

Douglas R. Turnbull, Sean McQuillan, Vera Crabtree et al.

Popularity bias is the idea that a recommender system will unduly favor popular artists when recommending artists to users. As such, they may contribute to a winner-take-all marketplace in which a small number of artists receive nearly all of the attention, while similarly meritorious artists are unlikely to be discovered. In this paper, we attempt to measure popularity bias in three state-of-art recommender system models (e.g., SLIM, Multi-VAE, WRMF) and on three commercial music streaming services (Spotify, Amazon Music, YouTube). We find that the most accurate model (SLIM) also has the most popularity bias while less accurate models have less popularity bias. We also find no evidence of popularity bias in the commercial recommendations based on a simulated user experiment.

Ryan Handley, Bert Guerra, Rukkmini Goli et al.

Social VR has experienced tremendous growth in the commercial space recently as an emerging technology for rich interactions themed around leisure, work, and relationship building. As a result, the state of social VR application design has become rapidly obfuscated, which complicates identification of design trends and uncommon features that could inform future design, and hinders inclusion of new voices in this design space. To help address this problem, we present a taxonomy of social VR application design choices as informed by 44 commercial and prototypical applications. Our taxonomy was informed by multiple discovery strategies including literature review, search of VR-themed subreddits, and autobiographical landscape research. The taxonomy elucidates various features across three design areas: the self, interaction, and the environment.

S. Roychoudhury, Anandan Das, P. Sengupta et al.

Pandemics are regarded as large-scale outbreaks of infectious disease that has the potential to significantly increase morbidity and mortality over a wide geographical area, which is accompanied by economic, social and political disruption The likelihood of pandemic, especially caused by viral infectious diseases has increased over the past few years The 21st century is just two decades old but it has already witnessed some of the deadliest viral pandemics having far-reaching consequences These include Severe Acute Respiratory Syndrome Coronavirus (SARS-CoV) (2002), Influenza A virus subtype H1N1 (H1N1) (2009), Middle East Respiratory Syndrome Coronavirus (MERS-CoV) (2012) and Ebola virus (2013) and the Severe Acute Respiratory Syndrome Coronavirus-2 (SARS-CoV-2) (2019-present) The viruses may adopt various mechanisms to invade and hijack the cellular machinery of the host cell, followed by infection-mediated immunomodulation and progressive inflammation, which in turn, may affect the functioning of different organ systems of the body Although effective commercial vaccines are unavailable for most of these viruses, those against SARS-CoV-2 are being developed at an unprecedented speed with few of the vaccines already being approved for commercial distribution Significant policy attention is required to limit the outbreak of such pandemics and to expand and sustain investment to build preparedness and health capacity © 2021 All Rights Reserved

F. Caló, C. R. Girelli, F. Angilè et al.

Considering the growing number of extra virgin olive oil (EVOO) producers in the world, knowing the influence of olive oils with different geographical origins on the characteristics of the final blend becomes an interesting goal. The present work is focused on commercial organic EVOO blends obtained by mixing multiple oils from different geographical origins. These blends have been studied by 1H-NMR spectroscopy supported by multivariate statistical analysis. Specific characteristics of commercial organic EVOO blends originated by mixing oils from Italy, Tunisia, Portugal, Spain, and Greece were found to be associated with the increasing content of the Italian component. A linear progression of the metabolic profile defined characteristics for the analysed samples—up to a plateau level—was found in relation to the content of the main constituent of the Italian oil, the monocultivar Coratina. The Italian constituent percentage appears to be correlated with the fatty acids (oleic) and the polyphenols (tyrosol, hydroxytyrosol, and derivatives) content as major and minor components respectively. These results, which highlight important economic aspects, also show the utility of 1H-NMR associated with chemometric analysis as a powerful tool in this field. Mixing oils of different national origins, to obtain blends with specific characteristics, could be profitably controlled by this methodology.

Osama Ahmed

Egypt is considered a net wheat importer, with the Egyptian market being vulnerable to future wheat markets because of the effect future market price discovery can have on the stability of spot prices. This study assesses the relationship between Egyptian wheat spot prices and future wheat prices in Paris (MATIF) and USA (CBOT). Markov switching-vector error correction methods are used to estimate two regimes by splitting the sample into high and low volatility regimes. This study also examines the dynamic conditional correlation between the prices considered using the asymmetric DCC-GARCH. Results suggest a high volatility regime observed, especially during the extreme market events of the food crisis in 2007-08 and 2010 and following the two revolutions in Egypt in 2011 and 2013 and the time of the economic reform in 2016. This leads to an unstable market and negative impacts on consumers’ welfare and food affordability, meaning that futures markets failed to hedge spot wheat market against price volatility. In addition, results from impulse response functions indicate that a 1% shock in futures markets will lead to a positive shock in the wheat spot market, while for the low volatility regime no significant effect.