Emerging interaction of artificial intelligence with basic materials and oil & gas companies: A comparative look at the Islamic vs. conventional markets

As part of the artificial intelligence (AI) industry there are many companies engaged in providing hardware that enhances the use of artificial intelligence technology for big data analysis, along with companies that are involved in data analytics, software, system software, and artificial intelligence software. This paper examines the quantiles-based connectedness and non-linear causality-in-quantiles nexus of AI enterprises with basic materials and oil & gas companies, and their Islamic markets. Formally, we consider two perspectives, including before and after the pandemic of COVID-19 (for period May 18, 2018–June 01, 2022). It is observed that in the network of AI-based investments and companies related to basic materials and oil & gas industries, AI is a net recipient of shocks before and during the COVID-19 era, with a higher intensity of shock-receiving in the normal market and during COVID-19-affected period than in the upper and lower tails and prior to COVID-19 period. However, AI could serve as the cause-in-quantiles of oil & gas-related companies in the Islamic markets (in both pre-COVID-19 and COVID-19 timeframes) and conventional oil & gas firms (only within COVID-19). On the other hand, both the Islamic and the conventional basic materials and oil & gas businesses appear to be a non-linear cause-in-variance of the AI technology in the middle quantiles of the COVID-19 situation. Aside from this, the only causal factors from resources-based markets to AI are Islamic and conventional basic materials companies, as observed only during COVID-19. Based on our analysis, COVID-19 presented an excellent opportunity for improving the involvement of AI innovations with basic materials and oil & gas companies. As a consequence, the basic materials market may be able to provide hardware and software infrastructures to support the technology of artificial intelligence. Also, the inventions that enter the oil & gas industry due to the use of artificial intelligence could have a significant impact on their average performance. In this light, AI could be recognized as a strategic link in the supply chain of basic materials and oil & gas companies. There are many implications arising from these new insights for the developers of AI applications, resource policy-makers and managers, as well as investors who are interested in investing in new technologies.

Do Smart Cities Represent the Key to Urban Resilience? Rethinking Urban Resilience.

The pandemic disrupted all activities, so it became necessary to understand, but also rethink, the complexity of economic resilience to better deal with future shocks. A component that can signal the resilience potential of a socio-economic system is smart city response, using technology to make services more efficient. This paper aims to analyze the relationship between smart cities and urban resilience to determine whether urban resilience is significantly influenced by urban smartness. Given the EU SDGs Strategy and the Implementation of RRF Programs, we have also identified the main driving forces that can amplify the impact of smart city development policies on local resilience. The results highlighted that at the European level, smart cities are significantly correlated with urban resilience; urban resilience is explained by the variation in urban smartness; resilience is correlated with all smart city dimensions, highly in (post-)pandemic, redefining a "new normal" in resilience approaches for smart cities. We also stressed the emerging, more complex content of the economic resilience concept and the new structural approach of smart cities resilience for the post-COVID-19 period.

The Weighted Average Cost of Capital and Its Universality in Crisis Times: Evidence from the Energy Sector

Recent economic anomalies, including the unprecedented lockdown generated by the COVID-19 crisis, have demonstrated that the weighted average cost of capital (WACC) remains an actual topic in the financial literature and in practice. Companies operate in an increasingly volatile environment, due to twin transitions and interlinked crises, and so they must have specific tools for measuring risk and profitability, in order to enable them to have a sound financial policy. Based on the earlier results obtained by Modigliani and Miller (1963), Harris and Pringle (1985), and Farber, Gillet, and Szafarz (2006), this study shows the relationship between WACC and interest rate. It offers a modified WACC formula that considers unstable market circumstances. The new redefined WACC can be a valuable tool in business planning for companies from different fields. The companies in the energy sector are very interested in the topic of WACC, considering not only the complex nature of the investments made and the long-term nature of investment recovery but also the multiple risks that have an impact on their activity and that can be found in different economic, social, and geopolitical spheres.

NFTs and Cryptocurrencies—The Metamorphosis of the Economy under the Sign of Blockchain: A Time Series Approach

Although NFTs (non-fungible tokens) and cryptocurrencies are active on the same market, their prices are not so closely related over time. The objective of this paper is to identify the relationship between the two types of assets (NFTs and the cryptocurrencies Ethereum, Crypto Coin, and Bitcoin), using data for the period between September 2020 until February 2022. The conclusions of the study are useful for cryptocurrency and NFT issuers, but also for investors on the financial market who are reconfiguring their portfolios with increasing frequency, and use these new assets for speculative or hedging purposes based on blockchain technology. The results highlighted relationships between NFTs and Ethereum, between Ethereum and Crypto Coin, and between Bitcoin and Ethereum, Ethereum being a bridge between all four. Therefore, NFTs present a relationship with Ethereum, the NFTs price had a causal effect on the price of Ethereum.

Public Opinion on European Health Policy, Lessons from the COVID-19 Pandemic.

Often, global crises, such as the COVID-19 pandemic, bring to light crucial weaknesses in political, economic, social and health systems. First, there are governments who formulate and implement policies and, second, there are the citizens who support them, thus contributing a great deal to their success. Our paper investigates the European citizens' opinion on health policy, focusing on their preference for European health policy during the coronavirus pandemic. The paper uses bibliometric analysis, descriptive statistics, and logistic regression to discuss the public opinion on health policy, the factors of influence, the change in perspectives between 2020 and 2021, and the socio-demographic profile of those favorable for the development of a European health policy in response to the coronavirus pandemic. Our findings show that citizens from southern and central European countries are more likely to prioritize the development of a European health policy, as compared to Nordic countries. Between 2020 and 2021, pro-European health policy citizens profile changes and becomes clearer, from pensioners to young working age males with medium education. In general, people prioritizing a European health policy value health as the most important issue at a national level are generally satisfied with the European Union and do not trust their national government.

Agile Leadership and Perceived Career Success: The Mediating Role of Job Embeddedness.

Agile leadership is an important managerial function in which responsiveness and innovation appear to be essential elements for the long-term development and success of any business. The world has become increasingly volatile, uncertain, complex, and ambiguous (VUCA) during and post COVID-19. Managers are required to possess agile leadership to facilitate their employees' successful careers. Therefore, this study aims to find out the relationship between agile leadership and career success by examining the mediation of job embeddedness in healthcare organizations. The descriptive research design and survey method were employed in this study. The data were collected by using three scales from healthcare employees in healthcare organizations in Turkey. Hypotheses were tested using structural equation modelling (SEM). The data were analysed by using SPSS and AMOS programs. The findings of this study showed that agile leadership behaviours enhance career success. Moreover, the relationship between agile leadership and career success is mediated by job embeddedness. The role of agile leadership in promoting employees' career success has rarely been studied in the literature. This is one of the first studies to examine the effect of agile leadership on career success along with the mediating role of job embeddedness. Healthcare managers have faced many critical challenges at their workplace during the COVID-19 pandemic. Through the lens of managing efficient healthcare organizations in many contexts, this research sheds some important light on the association between agile leadership, career success, and job embeddedness. Managers with high agility levels used strategies such as group decision making, problem solving, effective internal and external communication, and adaptation to uncertain environment in order to increase their career success.

Sustainable Tourism Issues in European Countries during the Global Pandemic Crisis

Sustainable economic growth can be achieved through tourism by protecting the environment, maintaining natural resources, creating employment, improving cultural diversity, and recognizing cultural heritage values. The concept of tourism sustainability is gradually growing globally and becoming a dominant aspect in modern business, as companies need to meet stakeholders' demands regarding environmental management. Sustainable tourism incorporates environmental, social, economic, and cultural issues into operations. The demand for green tourism, ethical consumption, protection of natural resources, and living close to nature is expected to increase. In particular, the latter gains more and more popularity due to the stress caused by the global pandemic and also because values have been re-evaluated at every level of society. In this paper, we explore sustainability in the tourism industry within the international context during the COVID-19 pandemic, with a specific focus on tourism in 35 European countries for the period between January 2020 and September 2021. We aimed to study the impact of tourism on sustainability based on the Eurostat database, using cluster analysis and descriptive statistics. The results indicate that tourism will recover slightly, even though the pandemic will continue, recording different effects in European countries. Furthermore, we highlight the relationship between income and tourism, the clusters on tourism being significantly different according to income. The results also identify potential recovery options to align this business area with global sustainable development goals, generate effective transformational change, and suggest how to create a viable growth process pushed by a glocal perspective.

Forecasting the Romanian Unemployment Rate in Time of Health Crisis-A Univariate vs. Multivariate Time Series Approach.

Economic crises cause significant shortages in disposable income and a sharp decline in the living conditions, affecting healthcare sector, hitting the profitability and sustainability of companies leading to raises in unemployment. At micro level, these sharp decreases in earnings associated with unemployment and furthermore with the lack of social protection will impact the quality of life and finally the health of individuals. In time of crisis, it becomes vital to support not only the critical sectors of the economy, the assets, technology, and infrastructure, but to protect jobs and workers. This health crisis has hit hard the jobs dynamics through unemployment and underemployment, the quality of work (through wages, or access to social protection), and through the effects on specific groups, with a higher degree of vulnerability to unfavorable labor market outcomes. In this context, providing forecasts as recent as possible for the unemployment rate, a core indicator of the Romanian labor market that could include the effects of the market shocks it becomes fundamental. Thus, the paper aims to offer valuable forecasts for the Romanian unemployment rate using univariate vs. multivariate time series models for the period 2021-2022, highlighting the main patterns of evolution. Based on the univariate time series models, the paper predict the future values of unemployment rate based on its own past using self-forecasting and implementing ARFIMA and SETAR models using monthly data for the period January 2000-April 2021. From the perspective of multivariate time series models, the paper uses VAR/VECM models, analyzing the temporal interdependencies between variables using quarterly data for the period 2000Q1-2020Q4. The empirical results pointed out that both SETAR and VECM provide very similar results in terms of accuracy replicating very well the pre-pandemic period, 2018Q2-2020Q1, reaching the value of 4.1% at the beginning of 2020, with a decreasing trend reaching the value of 3.9%, respectively, 3.6% at the end of 2022.

Financial Inclusion Paradigm Shift in the Postpandemic Period. Digital-Divide and Gender Gap.

Financial inclusion is strongly differentiated by age groups and countries and the pandemic has highlighted the increased gaps and inequalities but also the weaknesses of the system, in terms of flexibility, access and facilities of the customer-bank relationship and also from the perspective of the financial education of young generations and vulnerable people, active in the labor market. Based on the available data provided by the Global Findex database, and some findings after more than one year of COVID-19 crisis we outlined the main aspects of financial digitization, by categories of people and countries. At the same time, we identified the challenges and problems during the pandemic that significantly adjusted the consumption pattern of citizens and increased the need for on-line access for financial transactions. Starting from the analysis of the inequality of access to financial instruments in the last years, from the informational asymmetry in financial education and the challenges of the pandemic period, we underlined the main coordinates of changing the model of sustainable financial inclusion-based on five pillars-access, education, support tools, CSR and resilience. The research results highlight the need for convergence in providing opportunities to consider financial inclusion as a public good and an active tool to increase consumers' satisfaction and the quality of life of individuals.

Socioeconomic Effects of COVID-19 Pandemic: Exploring Uncertainty in the Forecast of the Romanian Unemployment Rate for the Period 2020–2023

During the health crisis, it is vital to protect not only the critical sectors of the economy, the assets, technology, and infrastructure, but first and foremost, it is fundamental to protect jobs and workers. The current COVID-19 pandemic has had a strong impact on the labor market from three main perspectives: number of jobs (through unemployment and underemployment), quality of work (through wages, or access to social protection), and through the effects on specific groups, with a higher degree of vulnerability to unfavorable labor market outcomes. The measures aiming to reduce economic activity and social contacts lead to a reduction of labor demand and implicitly to the increase of the unemployment rate. In this context, it becomes even more relevant to be able to monitor the unemployment rate, providing relevant forecasts that include the effects of market shocks. Thus, our paper aims to forecast the unemployment rate for the period 2020–2023 using the Box-Jenkins methodology based on ARIMA models, exploring also the uncertainty based on fan charts. Although the baseline forecast offers valuable information, a good understanding of risks and uncertainties related to this forecast is equally important. The empirical results highlighted an ascending trend for unemployment rate during 2020, followed by a slow and continuous decrease until the end of 2023 with a high probability for the forecast to be above the central projection.

Comparative Analysis of Different Univariate Forecasting Methods in Modelling and Predicting the Romanian Unemployment Rate for the Period 2021-2022.

Unemployment has risen as the economy has shrunk. The coronavirus crisis has affected many sectors in Romania, some companies diminishing or even ceasing their activity. Making forecasts of the unemployment rate has a fundamental impact and importance on future social policy strategies. The aim of the paper is to comparatively analyze the forecast performances of different univariate time series methods with the purpose of providing future predictions of unemployment rate. In order to do that, several forecasting models (seasonal model autoregressive integrated moving average (SARIMA), self-exciting threshold autoregressive (SETAR), Holt-Winters, ETS (error, trend, seasonal), and NNAR (neural network autoregression)) have been applied, and their forecast performances have been evaluated on both the in-sample data covering the period January 2000-December 2017 used for the model identification and estimation and the out-of-sample data covering the last three years, 2018-2020. The forecast of unemployment rate relies on the next two years, 2021-2022. Based on the in-sample forecast assessment of different methods, the forecast measures root mean squared error (RMSE), mean absolute error (MAE), and mean absolute percent error (MAPE) suggested that the multiplicative Holt-Winters model outperforms the other models. For the out-of-sample forecasting performance of models, RMSE and MAE values revealed that the NNAR model has better forecasting performance, while according to MAPE, the SARIMA model registers higher forecast accuracy. The empirical results of the Diebold-Mariano test at one forecast horizon for out-of-sample methods revealed differences in the forecasting performance between SARIMA and NNAR, of which the best model of modeling and forecasting unemployment rate was considered to be the NNAR model.

Shedding Light on the Main Characteristics and Perspectives of Romanian Medicinal Oxygen Market.

Medicinal oxygen plays an important role in healthcare, being essential for the existence and maintenance of the health of millions of people, who depend on medicinal oxygen every day, both in hospitals and at home. Medicinal oxygen is the primary treatment administrated to the majority of patients suffering from respiratory problems and low levels of oxygen in the blood, and in the context of the actual health crisis caused by the new COVID-19, the challenge is represented by increasing the supply of medicinal oxygen while reducing cost so that it is accessible where it is needed most, free at the point of use. It will take increased investment and commitment to put oxygen at the center of strategies for universal health coverage. In this context, it becomes essential to investigate the main characteristics of the Romanian market of medicinal oxygen, highlighting top key players, market development, key driving factors, types of products, market perspectives as well as shedding light on the segmentation of this particular market based on considerations regarding regions, hospital competence class and hospital specialization. Also, the research aims to explore the regional disparities in the decision of using O93%medicinal oxygen, revealing the main factors related to the usage of this type of product among Romanian public hospitals. The research relies on the first quantitative survey regarding medicinal oxygen usage among 121 public hospital units from a total of 461 public hospitals in 2018, which meet the specific requirements: includes the entire population according to the list published on the website of the Ministry of Health, is the most recent data and does not show repetition. The sampling was of probabilistic stage-type stratification, with the following sampling layers: hospital county distribution, hospital competence class officially assigned by the Ministry of Health and also area of residence (urban/rural). In order to analyze the main characteristics of the Romanian oxygen market, the following methods have been used: analysis of variance (ANOVA) together with Kruskal-Wallis, Pearson correlation coefficient as well as Goodman and Kruskal gamma, Kendall's tau-b and Cramer's V, as well as multilevel logistic regression analysis using hierarchical data (hospitals grouped in regions). The Romanian market of medicinal oxygen is rather an oligopoly market characterized by the existence of a small number of producers and two types of products currently used for the same medical purpose and having a substitutable character: medicinal oxygen O99.5%, and medicinal oxygen O93%. An overwhelming proportion of public hospitals agree that both types of medicinal oxygen serve the same therapeutic purpose. The Romanian market of medicinal oxygen highlighted a significant segmentation on considerations based on regions, hospital competence class and hospital specialization. Regarding the main perspectives, the Romanian market of medical oxygen keeps the growth trend registered globally, with development perspectives for competitors. Exploring the regional disparities in the decision of using O93 medicinal oxygen, the empirical results acknowledged the important role of unitary price, hospital capacity and the relevance of this product seen as a medicine. Medicinal oxygen is vital in sustaining life, proving its utility mainly in the context of the actual health crisis. In this context, the Romanian local market exhibits prospects for further development, being characterized by an important segmentation depending on regions, hospital competence class and hospital specialization.