Hasil untuk "Commercial geography. Economic geography"

Sina Hardaker

ȚÂRĂU ALEXANDRA, MUNTEAN EMIL , RĂZVAN ARICI et al.

The present paper aims to analyze the interdependencies between cost calculation, managerial decision-making, and performance evaluation within the food industry, with concrete applications in the bakery sector. Using a case study on a Romanian bakery firm, this research highlights the importance of management accounting methods, such as standard costing and activity-based costing (ABC), and their influence on improving economic performance and decision quality

Shimekit Kelkay Eshete, Kenenisa Lemi Debela, Taye Amogne Kebede

Abstract This systematic review synthesizes empirical evidence from peer-reviewed journal articles published between 2010 and 2023 to investigate the impact of personality factors on workplace employees’ performance. The purpose of the study is to determine whether aspects of personality have a major impact on improving worker performance in various organizational contexts. Reputable electronic databases were searched extensively for relevant publications. Out of the 896 records that were first found, 81 pertinent studies were chosen as a consequence of the review procedure, which followed PRISMA 2023 recommendations. The results show that extraversion, conscientiousness, agreeableness, openness to experience, and emotional stability—five fundamental personality traits—have a beneficial impact on task, adaptive, and contextual performance, among other aspects of professional performance. On the other hand, there was a persistent negative correlation between neuroticism and performance outcomes. These findings highlight how important personality is in influencing worker productivity and behavior in a variety of organizational settings. The study's conclusions imply that companies ought to use personality tests in their hiring, team-building, and performance-management plans. Employers can improve employee engagement, job happiness, and overall performance by matching individual personality profiles with job positions and workplace expectations.

Natasha Root

Gwe’, teluisi Natasha Root. I am a Two-spirited Mi’gmaw woman from Listuguj First Nation, which is in the traditional district of Gespeg, in the unceded territory of the Mi’gmaq, known as Mi’gma’gi. I am a Mixed Media Artist who specializes in painting & digital designs.

Yuliia Kazmina, Eelke M. Heemskerk, Emilia van der Kooij et al.

The promise of equal opportunity is a cornerstone of modern societies, yet upward economic mobility remains out of reach for many. Using a decade of population-scale social network data from the Netherlands, covering over a billion family, school, workplace, and neighborhood ties, we examine how structural inequality and social capital jointly shape economic trajectories. Parental background is a strong early predictor of economic outcomes, but its influence fades over time. In contrast, bridging social capital is what positively predicts long-term mobility, particularly for economically disadvantaged groups. Reducing the dimensionality of an individual's network composition, we identify two key dimensions: exposure to affluent contacts and socioeconomic diversity of one's network. These are sufficient to capture the core aspects of social capital that matter for economic mobility. Overall, our findings demonstrate that while inherited advantage shapes the starting point of economic trajectory, social capital can powerfully reshape it, especially for the poor.

Horst Treiblmaier

Dee Hock, the founder of Visa, coined the term 'chaordic' to describe simultaneously chaotic and ordered systems. Based on his reasoning, we introduce the Theory of Chaordic Economics to explain how economic systems are transformed by two disruptive technologies: namely Artificial Intelligence and Blockchain. Artificial intelligence can generate novel output through algorithmic yet rather unpredictable processes. Blockchain creates deterministic results without central authorities and relies on elaborated protocols that prescribe how consensus can be reached within a network of peers. The amalgamation of chaos and order produces chaordic economic systems and can yield hitherto unthinkable economic structures.

Lingyu Zhao, Yuankai He

As the automotive industry embraces software-defined vehicles (SDVs), the role of user interface (UI) design in ensuring driver safety has become increasingly significant. In crashes related to distracted driving, over 90% did not involve cellphone use but were related to UI controls. However, many of the existing UI SDV implementations do not consider Drive Distraction and Inattention (DDI), which is reflected in many popular commercial vehicles. This paper investigates the impact of UI designs on driver distraction and inattention within the context of SDVs. Through a survey of popular commercial vehicles, we identify UI features that potentially increase cognitive load and evaluate design strategies to mitigate these risks. This survey highlights the need for UI designs that balance advanced software functionalities with driver-cognitive ergonomics. Findings aim to provide valuable guidance to researchers and OEMs to contribute to the field of automotive UI, contributing to the broader discussion on enhancing vehicular safety in the software-centric automotive era.

Neeraj Pandey, Abhineet Agarwal, Raju Roychowdhury et al.

Analysis of the urban population fraction data for sixteen populous countries over the last fifty years reveals a universal increase in urbanization, exhibiting four qualitatively distinct temporal patterns: (i) continuously accelerating growth, (ii) continuously decelerating growth, (iii) two-phase growth transitioning from acceleration to deceleration, and (iv) two-phase growth transitioning from deceleration to acceleration. To understand the origin of these diverse urbanization trajectories, we develop a simple coarse-grained model in which a country is segregated into two regions, a rural and an urban region. Population in each region evolves due to natural (sexual) growth and migration from rural to urban areas, with the migration rate governed by economic inequality, quantified through the difference in GDP per capita between the two regions. The GDP per capita of both regions is assumed to grow exponentially with distinct rates. We demonstrate that this minimal model, involving four dynamical variables and a small number of demographic and economic parameters, is capable of reproducing all four empirically observed urbanization patterns. Assuming demographic and economic parameters remain approximately constant over a 50-year timescale, we estimate coarse-grained parameters for the United States using empirical data and obtain optimized values that accurately reproduce its observed urbanization trajectory. Our results highlight how simple demographic-economic interactions can generate rich and diverse urbanization dynamics.

Martin Henning, Luís Carvalho

Mauro Sayar Ferreira, Marcelo Randolfo da Costa Januário

The traditional terms of trade (TOT) shock analysis may be an unrealistic experiment, especially for a small open economy where the state of the world economy endogenously determines TOT. The dynamic relation between TOT and the trade balance needs to consider the nature of the global shock that jointly moves price and income, globally and domestically. We estimate Bayesian global SVARs for Brazil using a structure that easily communicates to traditional DSGE models to evaluate the presence of the J-curve and the Marshall-Lerner condition (MLC) following innovations we claim to resemble world supply and demand shocks. We do not encounter a J-curve for aggregate trade nor for trade in fuel, and capital and consumption goods. MLC is not verified only for trade in capital goods, but even in the cases where MLC is present, we observe that TOT and the volume exported are not correlated as expected, since improvement in the volume exported happens when TOT appreciates. Our results suggest that income effect plays the most prominent role for the dynamics of the trade balance and for the validity of the MLC, dominating the TOT effect.

CUC Mădălina

This paper explores how the integration of Artificial Intelligence (AI) into research methodologies is changing the research paradigm by improving data analysis, efficiency and innovation in a variety of fields. All the emerging and disruptive technologies based on AI and BIG DATA will thus allow researchers to model, train, calibrate and ultimately simulate very complex research scenarios by accelerating and simplifying current quantitative testing methods, allowing to work with sample sizes close to those of the analyzed population. Emerging and innovative research methodologies based on the application of AI tools are thus presented, which actually revolutionize traditional ways of research by adopting artificial intelligence algorithms on each hypothesis and creating specific working models for each tested hypothesis, obtaining valuable insights regardless of the validation or not of a hypothesis by classical quantitative analysis. In the particular situation presented, it will be explained how the Elaboration Likelihood Model will be applied to the marketing of social networks, with an emphasis on the cognitive process and the expression of attitude within them, depending on the characteristics of the message and the involvement of users. This proposed research will also consider the ELM framework and increase its dimension, providing a more contemporary perspective on persuasion and cognitive engagement by introducing AI and big data as part of the dimension of ELM methodologies, thus illustrating a paradigm shift in research and representing a model approach to moving from methodologies based on traditional qualitative and quantitative methods to emerging ones based on AI and BIG DATA

PÎRVU DANIELA, BĂNICĂ GENIFERA CLAUDIA

The overlap of crises that most countries in the world are currently facing generates the need to increase tax revenues, so the analysis of the factors that influence tax revenues is useful and important. There are many factors that influence the level of tax revenues, but those related to the activity of the tax administration and the tax behavior of taxpayers are of great importance. The multifactorial linear regression model developed in this paper demonstrates the existence of a direct and positive correlation between tax revenues: % of GDP and the number of tax inspections, the number of tax penalties and the degree of tax compliance, and a direct and negative correlation between tax revenues: % of GDP and the cost of tax revenue collection. The developed model offers the possibility to make predictions for approaching tax administration strategies aimed at increasing tax compliance and streamlining the activity

SANDA GABRIEL

In the introduction , we are making historical backgroundof the concept of the sustainable tourism. We explained also what requires the implementation of sustainaible tourism principles and also the aims of sustainable tourism. The article presents the main ideas of sustainable tourism – new form of tourism promoted by authorities, environmental and social institutions and international organizations. It implies taking into account economic, environmental, and socio-cultural aspect by planning and management of tourism. The article presents the main international events concerning this topic and also highlights negative effects of tourism that can be prevented by applying the principles of sustainable development.

FĂRCAȘ IOANA GEORGIANA

Financial literacy plays an important role in the investment behavior of households and companies within an economy. The increase in financial literacy might be influenced by the government’s actions, as well as by the public events organized by financial institutions. This study aims to analyze the level of financial literacy within Romania by using a questionnaire. Obtaining 117 responses from 22 different fields of activity, the main findings show that respondents present a more advanced financial literacy level than those presented in previous empirical studies conducted so far in Romania. This might be explained by the high number of seminars offered free by financial institutions lately. Nevertheless, the media promotes constantly the importance of possessing financial knowledge. These results have significant implications for investment behavior. Those who are characterized by a higher level of financial knowledge are more inclined to save money or to invest in stock shares or bonds

DURA CODRUȚA CORNELIA

There is growing concern that the Sustainable Development Goals (SDGs) may not be achieved within the proposed timeline, partly due to the insufficient focus on the sustainable development of small and medium-sized enterprises (SMEs). SMEs play a pivotal role in the global economy but are often overlooked in sustainability initiatives. To address this gap, this study conducted a systematic literature review to map existing research on SMEs sustainable development. The PRISMA framework was adopted for this study. Scopus was utilized to identify relevant literature, covering a 10-year period from 2015 to 2024. Data analysis was conducted using Microsoft Excel for descriptive analysis and SPSS (version 25) for literature classification. The review revealed a growing interest in SMEs sustainability, with research in this area gradually increasing. The study identified seven primary drivers of SMEs' sustainable development: societal influence, regulatory pressure, sustainable finance, corporate culture, cost savings, digitalization, and bricolage.

Kelly Lendsay, Craig Hall

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Khatab Alqararah

Abstract This research paper introduces a methodology to assess the robustness of the Global Innovation Index (GII), by comparing the rankings provided in it with those achieved using alternative data-driven methodologies such as data envelopment analysis (DEA) and principal component analysis (PCA). With it, the paper aims to reduce the level of subjectivity in the construction of composite indicators regarding weight generation and indicator aggregation. The paper relies on PCA as a weighting-aggregation scheme to reproduce the 21 sub-pillars of the GII before the application of DEA to calculate the relative efficiency score for every country. By using the PCA-DEA model, a final ranking is produced for all countries. The random forests (RF) classification is used examine the robustness of the new rank. The comparison between the new rank and that of the GII suggests that the countries positioned at the top or the bottom of the GII rank are less sensitive toward the modification than those in the middle of the GII, the rank of which is not robust against the modification of the construction method. The PCA-DEA model introduced in this paper provides policymakers with an effective tool to monitor the performance of national innovation policies from the perspective of their relative efficiency. Ultimately, the contribution made in this paper could be instrumental to enhance the effectiveness and the efficiency of the practice of innovation management at the national level.

KLEJDA GABESHI

Construction has become one of the main sectors supporting economic growth in Albania in recent years. Some of the factors that have boosted the growth are: the increase of residential projects, the continuation of postearthquake reconstruction works and public investments, mainly in road construction. A VEC model will be presented in this paper that uses bank credit for real estate as a cointegrated variable with GDP growth, as the construction sector in Albania occupies a very important role in the economy. The objective of this model is to identify the shortterm and long-term causal relationship between this credit activity and economic growth in Albania. The analysis by subject and purpose of credit use shows that real estate investment credit for individuals occupies the largest share of the total credit portfolio, followed by real estate credit granted to businesses. From the results of the econometric model it was concluded that credit to the real estate sector has a positive effect on long-term economic growth. The construction sector is one of the sectors that contribute the most to GDP and, at the same time, to the growth of the banks' loan portfolio. Lending to this sector, according to the results of this model, has a positive influence on the economy.

Christoph F. Strnadl

Ecosystems enjoy increasing attention due to their flexibility and innovative power. It is well known, however, that this type of network-based economic governance structures occupies a potentially unstable position between the two stable (governance) endpoints, namely the firm (i.e., hierarchical governance) and the (open) market (i.e., coordination through the monetary system). This paper develops a formal (mathematical) theory of the economic value of (generic) ecosystem by extending transaction costs economics using certain elements from service-dominant logic. Within a first-best setting of rational actors, we derive analytical solutions for the hub-and-spoke and generic ecosystem configurations under some uniformity assumptions of ecosystem participants. Additionally, we are able to infer a generic condition for the welfare-maximizing and utility-maximizing price of the hub-and-spoke configuration in the familiar form of Lerner indices and elasticities. Relinquishing a first-best rational actors approach, we additionally derive several general propositions on (i) necessary conditions for the economic feasibility of ecosystem-based transactions, (ii) scaling requirements for ecosystem stability, and (iii) a generic feasibility condition for arbitrary provider-consumer ecosystems. Finally, we present an algebraic definition of business ecosystems and relate it to existing informal definition attempts. Thereby we demonstrate that the property of "being an ecosystem" of a network of transacting actors cannot be decided on structural grounds alone.

Andrea Gabrio

In 2016, the Dutch National Health Care Institute issued new guidelines that aggregated and updated previous recommendations on key elements for conducting economic evaluation. However, the impact on standard practice after the introduction of the guidelines in terms of design, methodology and reporting choices, is still uncertain. To assess this impact, we examine and compare key analysis components of economic evaluations conducted in the Netherlands before (2010-2015) and after (2016-2020) the introduction of the guidelines. We specifically focus on two aspects of the analysis that are crucial in determining the plausibility of the results: statistical methodology and missing data handling. Our review shows how many components of economic evaluations have changed in accordance with the new recommendations towards more transparent and advanced analytic approaches. However, potential limitations are identified in terms of the statistical software and information provided to support the choice of missing data methods.