Sistema Regional de Información
en línea para Revistas Científicas de América Latina,
el Caribe, España y Portugal

Employability refers to the process of gaining initial employment, maintaining employment, and successfully obtaining new employment if required. In simple terms, employability is about being capable of obtaining and keeping fulfilling work. Employability is having a set of skills, including knowledge, understanding, and personal attributes that make a person more likely to choose and secure occupations in which they can be satisfied and successful. Employability depends on knowledge (what you know), skills (what you do with what you know), and attitudes (how you approach things). In higher education, the employment of university graduates is influenced by many factors including institutional ranking, image, branding, and program structure. Therefore, university reputation in specific programs is important and affects the employability of graduates directly. In a recent paper by the corresponding author, we argued that university branding is critical for developing a favorable image and impacts one’s identity formation and promotion substantially, thus differentiating and placing one in a highly competitive context. In this paper, we will investigate the factors that influence employability among university graduates and determine which ones can affect the overall graduate employability of university graduates in Egypt. These factors include academic branding, academic performance, technical skills, communication skills, personality, leadership and motivational skills, and teamwork and problem-solving skills, taken as independent variables, while overall graduate employability was considered the dependent variable. In addition, we consider the impact of the university’s reputation on graduate employability. Survey methods were used on 500 graduates and undergraduates (fourth level) from different Egyptian universities who have not yet performed employability behavior, chosen at random, by using exploratory factor analysis to validate the items under those independent variables and structural equation modeling with AMOS to test the hypothesized relationship between the independent variables and the dependent variable. The questionnaire had 20 questions, including demographic inquiries and questions about the abovementioned topics. The findings of this study can help scholars further investigate the employability aspects and guide fresh graduates in acquiring the required employability skills while assisting companies in recruiting suitable people with the required skills and performance.

Anchored on Simunic’s audit fees model, this study examined the influence of a few board attributes on pricing behavior of external auditors in Nigeria. Besides, political connections that are largely prevalent among corporate entities in Nigeria, is also introduced as part of explanatory variables. Data were gathered from audited annual accounts and reports of 50 quoted non-financial firms for 7 years from 2014 – 2020, culminating into 350 data/set observations. Both statistical learning (SL) and machine learning (ML) data analytic techniques were adopted to estimate model specified for the study. The results indicated that firm size and political connections are effective determinants of pricing behaviour of auditors, accounting for 80% variations therein. This is similar to results obtained from machine language analysis. However, board attributes, as well as profitability (return on total assets), in addition to firm size and political connections, displayed positive and statistical significant relationship when BIG4 was adopted as proxy for pricing behavior of auditors. The statistical and machine learning analyses accounted for 21% and 86% variations in pricing behavior of auditors respectively. This study largely conforms to extant studies and aligns with demand-based perspective linking board attributes and audit pricing behavior. Consequently, board attributes, political connections, firm size and profitability are active variables available to firms, which must be effectively managed in order to influence the amount charged by external auditors in Nigeria.           

This study has run for investigating the impacts of social media advertising among the young group of people's buying decision of Bangladesh. To run this study the authors has developed a structured survey questionnaire by using the digital survey tool, through Google form. For this research an online survey through the social media platform, Facebook has used for collecting data from a convenience sample of 244 respondents, living throughout the Dhaka city. Besides, snowball sampling technique exerted for leveraging the referrals of the participating respondents within their acquaintance network through Facebook. Moreover, the Multiple Regression Analysis was performed to test the research hypotheses. Results show that among the six predictors, Source of Information, Uniqueness of Advertising, Time Saving, Security, Convenience of Ordering and Feedback significantly affects in young people's buying decision. Accordingly, all research hypotheses are supported by survey data: social media marketing increased by unit favorably influences Bangladeshi youth purchasing behavior by 53.5%, and the remaining 46.5% may be influenced by other non-market external and internal variables. Finally, the limitations and managerial implications of the study, along with future research avenues, have been discussed.

After the crisis of 2008, the reduction of unemployment has become one of the priority objectives of economic policy in Spain. The job reinsertion of the unemployed is influenced by a multitude of factors, from the effectiveness of education and training policies, to the policies of intermediation and activation of the unemployed. From the point of view of the individual, the method used in the process of searching for a job is another of the fundamental factors to increase the probability of finding work, so that the effectiveness of these methods is crucial not only at an individual level but also at a macroeconomic level due to its effects on the frictional unemployment rate. In this work, based on a survey carried out in the Community of Madrid during the economic crisis and using semi-parametric models of duration, an analysis will be made to measure how the different search methods influence the probability of finding a job.

The main objective of this work is to try to construct a stratification of the census tracts of the city of Madrid, grouping them according to a serie of socio-demographic characteristics. This objective is carried out in two steps. Given that the number of variables to be analysed is high, a first step is proposed to reduce the dimensions of analysis, in order to then use the new dimensions as information for the grouping process. Based on the results of the previous step, the sections are grouped into groups or clusters. For step 1, the objective is also to evaluate the result obtained by applying two multivariate techniques: reducing the starting dimension by means of principal component analysis and apply multidimensional scaling as a reduction technique.

This study examines the impact of financial development on domestic investment in Cote d’Ivoire. Using the Autoregressive Distributed Lag (ARDL) bounds testing approach and domestic credit to private sector as share of GDP as proxy for financial development along with the other control variables, we estimate a private investment function for the 1975-2019 period. The main finding of the study is that domestic credit to private sector has a negative effect on private investment rate. Further, the results show that real GDP per capita and trade openness are positively related to private investment rate.

The objective of this research is to investigate and study the new investment trends in Private Banking, the reasons why they are increasing their presence in the markets and the creation of different model portfolios based on the risk profile of each client. To better understand the needs and demands of each client, 84 Spanish bankers were surveyed via LinkedIn. Firstly, based on the conclusions obtained through the survey, the economic environment and each of the new investment trends proposed are studied: Revolution 4.0: robotics and artificial intelligence, new sustainable trends, new trends in wellbeing and consumption, digitalisation and connectivity of society, biotechnology and medical technologies and new trends in education. Finally, based on the five risk profiles accepted in the market (defensive, conservative, moderate, decisive and equities), a thematic investment portfolio has been created, adjusted to the return and risk needs of each of these.

The objective of the paper is to assess the resilience of the economy of South Korea following the Covid-19 pandemic that hit the global economy. Quarterly growth rates (annualized) of the Real GDP of South Korea and Japan are forecasted between Q2 2022 and Q4 2050. Two sets of forecasts are generated: forecasts using historical data including the pandemic (from Q1 1998 to Q1 2022) and excluding the pandemic (from Q1 1998 to Q3 2019). The computation of the difference of their averages is an indicator of the resilience of the economies during the pandemic. Used as a benchmark, Japan’s economy shows a lower resilience to the Covid-19 pandemic (+0.17%) than South Korea’s economy (+0.43%) based on Q2 2022-2050 forecasts. Driven by stronger growth than Japan, South Korea's GDP is expected to exceed Japan's by 2060.

Over the last years, the share of E-commerce has increased in all market segments and the European e-commerce market has become the largest market in the world. In the digital economy, the leading role of e-commerce is to achieve the goals of sustainable development, to ensure flexibility and adaptability of the management system. This study investigates patterns in e-commerce activities and their impact on energy efficiency for a group of 29 European countries by using a unique panel dataset spanning the years 2011–2019 collected from EUROSTAT. The empirical approach involves the specification of a difference one-step GMM estimation method. Our results suggest that e-commerce has the potential to facilitate more sustainable production processes and consumption patterns and ensure more circularity.

Data science combines several extensions, including, e.g., statistics, scientific methods, artificial intelligence (AI) and data analysis to extract value from raw data. Analytical applications and data scientists can then verify and defer the results to discover patterns and trends. In this way, they allow business leaders to gain enlightened knowledge about the market. Companies have kept a wealth of data with them. As modern technology allowed for the creation and storage of ever-increasing amounts of information, data volumes popped. The wealth of data collected and stored by these technologies can bring regenerative benefits to organizations and societies around the world, but only if they can interpret it. That's where data science comes in. So, the applied economics refers to the application of economic theory and analysis. In this article we intend to present several software that are available for the application of economic analysis. Analysis can be performed on any type of data and is a way of looking at raw data and find useful information. There are several technologies available for economic analysis, with more or less characteristics, some of which are not only intended for this single purpose, and cover a wider spectrum of functionalities. Some of the technologies we will use are, e.g., Rstudio, SPSS, Statis and SAS/Stata. These are very common technologies when talking about economic or business analysis. The intention is to demonstrate how each of these software analyse the data and subsequently the interpretations that we can draw from that scrutiny. Organizations are using data science teams to turn data into a competitive advantage by refining products and services and cost-effective solutions. We will use some different algorithms to verify how they are processed by the different technologies, namely we will use metrics such as maximum, minimum, covariance, standard deviation, average and multicollinearity and variance, even the use of types of regression models.