The ultimate objective of the study was to investigate the effects of being landlocked on the living standards in Sub-Saharan African (SSA) countries from 1991 to 2019. Adopting the two-step estimation technique of System GMM (generalized method of moments), the study found that being landlocked has a negative and significant effect on the living standards in SSA countries when using GDP per capita as the living standard measure. Moreover, the historical living standard experiences of SSA countries have a positive and significant influence on the current living standard level. In addition, the population growth rate has a positive and significant effect on the living standards in SSA countries. On the other hand, the official exchange rate, broad money as a percentage of GDP, and inflation have a negative and significant effect on the living standards in SSA countries. Generally, the estimated result reveals the existence of a significant variation in the living standards in landlocked and coastal SSA countries. This study suggests that regional integration between landlocked and transit countries should be improved to minimize entry costs and increase access to global markets for landlocked countries. We argue that this study is of interest to landlocked and coastal countries to increase trade integration and promote the development of both groups, and it will contribute to the scarce empirical evidence.

Recognizing the discipline category of the abstract text is of great significance for automatic text recommendation and knowledge mining. Therefore, this study obtained the abstract text of social science and natural science in the Web of Science 2010-2020, and used the machine learning model SVM and deep learning model TextCNN and SCI-BERT models constructed a discipline classification model. It was found that the SCI-BERT model had the best performance. The precision, recall, and F1 were 86.54%, 86.89%, and 86.71%, respectively, and the F1 is 6.61% and 4.05% higher than SVM and TextCNN. The construction of this model can effectively identify the discipline categories of abstracts, and provide effective support for automatic indexing of subjects.

This research examines the intricate connection between tourism and environmental destruction in 28 Asian countries, concentrating on the non-linear impacts of tourism. Moreover, this study contemplates how tourism can mitigate the effects of economic growth on environmental decline. Westerlund, Johansen-Fisher, and Pedronico-integration tests are necessary to detect the co-integration connection between the proposed factors. The research also uses the Augmented Mean Group; the dynamic system generalized method of moments, and fully changed Ordinary Least Squares (OLS). These tools help address econometric and economic problems such as co-integration, dynamism, variation, inter-sectional dependence, and endogeneity. The results demonstrate a U-shaped non-linear connection between ecological footprint and Tourism in Asian nations. Primarily, the tourism industry can initially decrease environmental damage. However, as it increases in size, it can worsen the harm. Additionally, the study suggests that tourism negatively influences how economic growth affects ecological footprint. This research contributes to the existing literature on tourism’s effects on the environment. The research suggests that tourism significantly impacts the environment; therefore, initiatives to reduce damage should be aimed at tourism.

The application of optimization algorithms is crucial for analyzing oil and gas company portfolio and supporting decision-making. The paper investigates the process of optimizing a portfolio of oil and gas projects under economic uncertainty. The literature review explores the advantages of applying various optimizers to models that consider the mean and semi-standard deviations of stochastic multi-year cash flows and revenues. The methods and results of three different optimization algorithms are discussed: ranking and cutting algorithms, linear (Simplex) and evolutionary (genetic) algorithms. Functions of several key performance indicators were used to test these algorithms. The results confirmed that multi-objective optimization algorithms that examine various key performance indicators are used for efficient optimization in oil and gas companies. This paper proposes a multi-criteria optimization model for investment portfolios of oil and gas projects. The model considers the specific features of these projects and is based on the Markowitz portfolio theory and methodological recommendations for project assessment. An example of its practical application to oil and gas projects is also provided.

Objective: This research analyzed the psychometric properties of the Ambivalent Classism Inventory (ICA) in Peru. Methodology: A critical review of literature related to poverty, inequality, and structural gaps was conducted, involving 882 participants aged 14 to 89 years (M = 24.61, SD = 9.07). Results: Exploratory-confirmatory factor analyses were satisfactory, finding a similar factorial structure to the original scale and the adaptation (hostile classism, protective paternalism, and complementary class differentiation). Regarding items, there was a reduction, leaving only 12; however, comparing alternative models, the three-factor structure with 12 reagents showed adequate fit (χ² = 214.588, df = 51, p < 0.001; CFI = 0.996; RMSEA = 0.060; SRMR = 0.033), allowing for invariance testing. Practical Implications: The scale allows for investigating attitude profiles of individuals with privileged social class. Contribution: The instrument is a valuable contribution, considering that the nation has a high poverty rate, leading to economic, political, and social inequality among the population.

Most countries have adopted a more liberal policy to socialize public relations under the influence of neoliberalism and lobbying by economic elites to strengthen the role of market mechanisms and citizens’ entrepreneurial activity. The nature, scale, sequence, and strategy of economic and social reforms in each country have their specifics. Today multi-vector and large-scale changes are taking place in social and labor policy, and they do not always have an internal logic. The study assesses prospects for the development of the labor market in the context of global transformations. Within the framework of this study, the collected information was processed gradually. Data processing was modified during the study phase. At the first stage, data processing results were used to determine total and non-farm self-employment for two groups of countries with developing economies and estimate the scale of vulnerable employment. At the second stage, indicators were identified that characterize various categories of economically active population that belong to the precariat. At the third stage, the authors analyzed data on non-standard forms of employment. The authors assumed that these forms have a right to exist and will be implemented more often. There is an imbalance between standard and non-standard forms of employment. Further research should consider the transformation of labor from material and intangible dominants to creativity.