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This brief note sheds light on the links between Journal of Economic Literature (JEL) codes and the Sustainable Development Goals (SDGs) of the United Nations.

Three alternative methods based on keyword overlap to establish links between SDGs and JEL codes are presented.

These simple linkages illustrate that the themes of SDGs have corresponding closely related JEL classification codes.

The mappings presented in this note are based on simple keyword overlap and are therefore necessarily imperfect and incomplete. There is plenty of room for further development.

Despite the demonstrated possibility of linking SDGs to existing JEL codes, introducing a specific JEL code for each SDG would reduce search costs for those searching for economic research related to specific SDGs.

The first and preliminary attempt to link SDGs and JEL codes.

In literature, it is recognized that there is no universal set of critical success factors (CSFs) applicable to all projects. The goal of this research is to validate a theoretical model which considers that CSFs’ influence on project success (PS) is configurational, that CSFs combine to influence PS.

The authors proposed a theoretical framework which operationalizes CSFs considering contingency and institutional theories' terms, as external contingencies, organizational resources and project strategies, which influence PS. The framework is validated through a qualitative approach on 18 social projects implemented by nongovernmental organizations (NGOs). Based on the conducted semistructured interviews with NGO managers or project managers, 91 instances when CSFs combine to influence PS were identified.

The dominant path reveals the combination of CSFs in terms of strategies adopted to face contingencies (70 instances), another as resources which moderate managers' strategies (14 instances), and in seven instances positive contingencies and resources combine and influence the PS. The results reveal that CSFs combine in reactive and dynamic ways to influence PS.

The research contributes to the vast literature on projects' success by adopting a different perspective. Configurational theory explains project management and projects' complexity better than the traditional approaches, which have a rather correlational perspective.

The purpose of this paper is to investigate the resource rents–quality-adjusted human capital nexus and the impact of quality of institutions.

For a large data set of 161 countries for the period 1996–2018 (yearly and 4-year periods), fixed effect estimation method is applied to investigate the impact of resource rents on quality-adjusted human capital and the role of quality of institutions on this relationship.

The paper found little evidence on the negative, significant and direct impact of total resource rents on quality-adjusted human capital. However, the results show that the negative effect of resource rents can be mediated by the quality of institutions. This result is robust to a long list of controls, different specifications and estimation techniques, as well as several robustness checks. Therefore, institutional quality seems to play a critical role in determining the indirect impact of natural resources on human capital. Moreover, the obtained results demonstrate that this resource adverse effect depends on the type of resource rents; in particular, high dependency on oil rents in developing countries appears to harm human capital.

The paper shows that it is not obvious that total resource rents decrease human capital and found that the coefficient is no longer significant in the two-way fixed effects model. However, the analysis has emphasized the crucial role of political institutions in this relationship and has shown that countries with higher quality of institutions make the most of their resource rents transiting to a better human capital environment. This result is found to be robust to a list of controls, different specifications and estimation techniques, as well as several robustness checks. In addition, we demonstrate that not all resources affect human capital in the same way and found that oil rents have a significant negative effect on human capital. This is an important distinction since several countries are blessing from oil rents. From this we conclude that the effect of natural resources on human capital varies across different types of commodities. On the other hand, the interaction between institutions and the sub-categories of resource rents shows that oil rents can increase human capital only in developing countries with higher quality of institutions (above the threshold). This result is also still hold while using alternative measures of political institutions.

The results in this paper have important policy implications. In particular, results highlight important heterogeneities in the role resource rents to the economy. As international commodity prices have shown high volatility in recent years, it is important for policy makers to understand the rents. Rents which are the difference between the price of a commodity and the average cost of producing it can have different effects in the economy, including the human capital. It is shown that in countries with low-quality institutions, natural resource rents negatively affect institutional quality, leading to conflicts, corruption and fostering rent-seeking activities. Overall, this reinforces the elite at the power that, obviously, is interested in preserving the status quo. In other words, there is a vicious circle between resource rents and low-quality institutions that impedes institutional change. How to regulate this in the best possible way requires a good understanding of how resource rents are generated and appropriated for different sectors, their different effects and how people react to these rents. The evidence suggests the policy toward better political institutions may help countries to improve social outcomes such as health and education which offer high social returns.

The paper is part of the author's PhD research and is an original contribution.

The purpose of this paper is to analyze the determinants of scholastic performance using an efficiency analysis perspective.

The authors apply data envelopment analysis (DEA) at the pupil level using the 2009 PISA survey in Azerbaijan. Before applying DEA with multiple outputs, this paper integrates the maximum amount of available information on inputs via the use of correspondence analysis.

The results show that scholastic efficiency depends positively on the externalities due to the resources of the school and to a peer effect. The analysis of the determinants of these externalities shows how they influence scholastic performance and has some policy implications.

Education policies should promote the resource externality, because its effect is more homogeneous among pupils. The mechanisms generating school externalities should be taken into consideration by educational authorities, when allocating resources to school and should give some guidelines about how to use these resources and how to manage a school in order to promote peer effects externalities.

The authors distinguish various sources of efficiency: that of the pupil and that due to school externalities operating via resources and peer effects. The authors relate the efficiency due to school externalities to individual, family and school characteristics.

The purpose of this paper is to introduce the current state of education in the field of social enterprise in Slovakia and its support, share the experience of social entrepreneurship education providers and formulate recommendations for the development of human resources in the context of supporting social enterprise.

This paper is presented as a case study. It is based on the initial experience of education providers in the field of social entrepreneurship in Slovakia, as the concept of integrating social entrepreneurship into education in Slovak conditions is currently in the phase of gradual establishment.

One of the biggest barriers of the development of education is insufficient awareness and overall promotion of social enterprise in Slovakia. The general public lacks awareness on the topic of social enterprise and a general platform on social enterprise, which would provide information on the possibilities of formal and non-formal education, is missing.

The findings of this paper are based on the limited experience of social entrepreneurship education providers, as the systematic concept of integrating social entrepreneurship into education in Slovak conditions is currently in the phase of gradual establishment.

To the best of the authors’ knowledge, this is the first study, which provides an overview of the present situation of education in the field of social enterprise from the perspective of the experience of the addressed organizations, their opinions and perception.

The purpose of the work is to solve the set problem and to study the competition and perspectives of division of labor of humans and machines during creation of intangible assets in Industry 4.0.

The research is performed with the help of regression and comparative analysis by building regression curves and with the help of the qualitative structural and logical analysis.

The authors perform an overview of the factors that determine the advantages and limits of participation in creation of intangible assets in Industry 4.0, determine the perspectives and compile recommendations for division of human and machine labor during creation of intangible assets in Industry 4.0.

The results of the performed research confirmed the general hypothesis that machine technologies allow improving the innovative, marketing and organizational and managerial activities and activities in the sphere of R&D through automatization of certain stages of the process of creation of intangible assets. The authors determine the factors that define the contribution of machine technologies in this process and their competitive advantages as compared to human intellectual capital during creation of intangible assets. These advantages prove the possibility and expedience of division of human and machine labor during creation of intangible assets.

The purpose of the research is to determine the perspective directions of state regulation of competition between human and artificial intellectual capital in Industry 4.0 and to develop scientific and methodological recommendations for their implementation. For this, the directions of state regulation of competition between human and artificial intellectual capital are described, monitoring of competition between human and artificial intellectual capital by the example of modern Russia (2019) is performed and scientific and practical recommendations for state regulation of competition between human and artificial intellectual capital are developed, with their approbation by the example of modern Russia (2019).

A method of expert evaluation is used for collection of the information and empirical data. The method of comparative analysis is used for comparing the successfulness of implementing the distinguished directions of state regulation of competition between human and artificial intellectual capital (4.1) according to the official statistics to their current evaluation according to the interested parties. Also, future evaluation (forecasts) according to the interested parties (until 2045) is determined.

It is substantiated that during evaluation of state regulation of competition between human and artificial intellectual capital in Industry 4.0, one cannot use only the official statistics, as these data are fragmentary and indirect. Fuller and more precise data are provided by assessment according to the interested parties. They allow determining the current and the future state of affairs and, based on it, compiling a forecast and developing a long-term strategy of state regulation of competition between human and artificial intellectual capital in Industry 4.0.

The perspective directions of state regulation of competition between human and artificial intellectual capital in Industry 4.0 are as follows: stimulation of competition in the market of intellectual capital, social risk management of the market of intellectual capital, managing international competition in the market of intellectual capital and ecological risk management of the intellectual capital market. As the experience of modern Russia shows, even at the initial stage of transition to Industry 4.0, the measures of state regulation of competition between human and artificial intellectual capital are not enough, but their deficit is moderate. In the course of development of Industry 4.0, the necessity for the measures of regulation will grow, and their deficit will increase. That's why there's a need for strategic approach to their implementation, which envisages their systemic reconsideration and supplementing. An author's algorithm is offered for this.

The purpose of this paper is to empirically investigate whether market size and its growth rate, along with financial development indicators, affect human capital in selected south Asian economies over the time period from 1984 to 2015.

The stationarity of the variables are checked by LLC, IPS, ADF and Phillips–Perron panel unit-root tests. Pedroni’s and Kao’s panel co-integration approaches are employed to examine the long-run relationship among the variables. To estimate the coefficients of co-integrating vectors, both PDOLS and FMOLS techniques are used. The short-term and long-run causalities are examined by panel granger causality.

From the empirical results, the authors found that both the market size and financial development play an important role in the development of human capital in the selected south Asian economies. It is evident that a large market size and faster degree of financial development in the selected countries result in better human capital formation.

There are a number of studies on the impact of financial development indicators on human capital and economic growth, but there is hardly any study that considers market size and its growth rate along with financial development indicators with human capital in the context of south Asian economies. The study fills this research gap.

The purpose of the paper is to develop a concept of organization of the system of science and education in the form 4.0 based on human and artificial intellectual capital.

The methods of regression and correlation analysis are used. The role of human and artificial intellectual capital for provision of effectiveness and competitiveness of the system of science and education is determined, as well as its correspondence to the modern challenges. Analysis of perspectives and limitations of automatization of the system of science and education based on AI is conducted; a model of organization of the system of science and education in the form 4.0 based on human and artificial intellectual capital is compiled.

It is established that in the system of science and education, the decisive production factor is intellectual capital, but human intellect does not necessarily have to dominate in its structure. AI is one of the most popular technologies of Industry 4.0 in the system of science and education, which has wide perspectives of practical implementation. As experience of the leading world universities, which had the highest level of digitization in 2018, showed, foundation on non-breakthrough digital technologies (computer equipment and Internet) does not allow opening the potential of increase of indicators of effectiveness and competitiveness of the system of science and education and bringing it in correspondence to the modern challenges based on digitization. However, correlation of activity of application of artificial intellectual capital with these indicators is four times higher (0.2), as compared to correlation of these indicators with activity of application of human intellectual capital (0.05). This shows demand for digitization of the system of science and education, but based on breakthrough digital technologies, of which AI should become the key one.

It is substantiated that higher education could be automatized based on AI by 85% and science by 63%. Therefore, on the whole in the system of science and education, the share of AI in the structure of intellectual capital could reach 74% ((85 + 63)/2). It is recommended to use the developed model of organization of the system of science and education in the form 4.0 based on human and artificial intellectual capital.

The importance of workers in labour-intensive industries, such as tourism, is undeniable. In this sense, it has been investigated for decades from various methodological approaches. However, in the academic literature on tourism, the partial least squares-structural equation modelling (PLS-SEM) technique has hardly been used.

Therefore, this work uses that technique to contrast which factors define the employees' wages in the Spanish tourism industry. Additionally, an importance-performance map analysis (IPMA) analysis is carried out, which provides informed decision-making.

Thus, the main results obtained are the verification and measurement of the relationships of Human Capital, Labour Conditions and Market with Wages, and the relation between Human Capital and Labour Conditions. Besides, the improvement points in each variable are identified. Especial emphasis is given to those related to Human Capital and, partially, to the Market.

However, there are certain limitations to this study. Mainly, as the indicators used are given by the 2018 Salary Structure Survey, they are stiff and so the design of the model turns to be more difficult.

Considering the turning point that the temporary cessation of the tourism industry activity due to the COVID-19 pandemic has been, it is essential to take advantage of it to identify and correct existing deficiencies. Therefore, this work aims to be a base document for the identification of these problems.

La importancia de los trabajadores de industrias intensivas en mano de obra, como el turismo, es innegable. En este sentido, se ha investigado durante décadas desde diferentes metodologías. Sin embargo, en la literatura académica en turismo, la técnica PLS-SEM path modelling apenas ha sido utilizada.

Por ello, este trabajo emplea esta técnica para contrastar los factores que definen los salarios de los empleados en la industria turística española. Además, se lleva a cabo un análisis IPMA, que permite la toma de decisiones informada.

Así, los principales resultados obtenidos son la verificación y medida de las relaciones del Capital Humano, Condiciones Laborales y Mercado con los Salarios, y la relación entre Capital Humano y Condiciones Laborales. Además, se identifican los puntos de mejora de cada variable. Se presta un interés especial a aquellos relacionados con el Capital Humano y, parcialmente, el Mercado.

Considerando el punto de inflexión que el cese de actividad temporal de la actividad de la industria turística ha supuesto a causa de la pandemia COVID-19, es esencial aprovechar para identificar y corregir las deficiencias existentes. Además, este trabajo pretende ser un documento base para la identificación de estos problemas.

No obstante, existen algunas limitaciones en este estudio. Principalmente los indicadores utilizados proceden de la Encuesta de Estructura Salarial de 2018, son fijos y, por ende, el diseño del modelo se torna más difícil.