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The purpose of this paper is to emphasize that the growing of competitiveness at any level may be possible through more responsibility (business ethics) on the one hand and less corruption (as lack of business ethics) on the other.

The objective of the paper is to identify the double‐way relationships between competitiveness and the responsible (beyond ethics) behaviour. In order to do this, the authors used correlation indexes CORREL and R² and the graphic representation able to illustrate the above‐mentioned interrelations.

The authors observed that there is a strong and direct correlation between GCI, RCI and CPI – at national level, and six possible situations which reflect the interrelations between NP and FGP.

The paper may be continued with specific behavioural models of MNEs in different host countries – integrating different approaches of business ethics.

The practical implications of the paper consist in offering some guidelines/starting points for firms in the search of global competitiveness through responsible/ethical conduct.

The paper develops a new conceptual framework, which integrates two “obsessions” of nowadays (competitiveness and responsibility) into the concept of global performance – national and firm related.

This study aims to establish the position of the European Union (EU-28) countries in the dynamics of international trade openness linkages and the Global Competitiveness Index (GCI) in correlation with the gross domestic product (GDP) per capita, research and development (R&D) expenditures, innovation capability and information and communication technology (ICT) adoption.

In the panel data set, comparative analyses were applied to scatter diagrams, correlation and regression analyses and structural equation models using Eurostat and World Economic Forum (WEF) data for the EU-28 countries in the period 2008–2019.

The empirical results did not confirm the hypotheses that a positive correlation exists between GCI and trade openness indicators and between GDP per capita and GCI. The ICT adoption and innovation capability increase GCI, which affects GDP per capita.

The empirical results provide a better understanding of the importance of trade policies, particularly in terms of trade openness and trade shares of the EU-28 countries, as it could contribute to increasing the GCI of the EU-28 countries. Furthermore, the results of this study underline the importance of ICT adoption and innovation capability and the need for appropriate government policies that improve global competitiveness.

This study, through empirical analysis, demonstrates the existence of correlations between trade openness (exports as % of GDP, imports as % of GDP and export market shares as % of world trade), R&D expenditures, innovation capability, ICT adoption, GDP per capita and the GCI in the EU-28 countries. In addition, this study contributes managerial and policy-based implications on driving forces of global competitiveness.

The purpose of this paper is to examine the role that information and communication technologies (ICT) maturity plays in the achievement of global competitiveness at the country level. The paper investigates the socio‐economic and technological factors that are most likely to be associated with ICT maturity, and then assesses their role in driving the global competitiveness wheel forward.

Secondary data were used, based on data sets generated by the World Bank, World Economic Forum, and UNESCO for the years 2003‐2007. The countries common to all reports were included, yielding a study sample of 93 cases. Cluster analysis was used to categorize countries in terms of ICT usage, readiness, and environment. Structural equation modeling was used to test the fit of a model employing these factors.

First, it was found that ICT plays an important role in driving a country's global competitiveness forward, with a stronger relationship existing in high readiness countries than in low readiness countries. Second, ICT maturity was found to mediate the relationship between ICT quality and R&D spending on one hand and global competitiveness on the other. Finally, the relationship between R&D spending and global competitiveness was found to be stronger for low readiness countries than for high readiness countries.

The paper's findings provide insights to managers and government policy makers regarding the effects of economic, social and technological factors on ICT maturity, as well as the relationship between ICT maturity and global competitiveness. Such insights can influence the standards, programs, and strategies that governments implement in order to attain and maintain global competitiveness.

The paper presents a holistic model that depicts the ICT maturity factors and their dynamic contributions to global competitiveness. Despite the considerable contributions of existing research in this domain, there is a lack of substantive research that examines the relationship at the country level between ICT maturity and its indicators on one hand and global competitiveness on the other. The paper is an attempt to fill this gap.

This study aims to evaluate the competitiveness of nations and seeks to answer the following research question: how does the competitiveness of nations include improvements in the quality of life, thus influencing and contributing to social progress in both social and economic indices?

This paper collected secondary data from the World Economic Forum and the socioeconomic dimensions of the Social Progress Imperative Index and considered the dimensions of these indices, which were demonstrated using Pearson’s correlation coefficient. The main focus was on the documentary analysis that was carried out to explain the realities of 121 countries from 2014 to 2017 as taken from these indices, considering the 10 countries at the top and bottom.

This study showed the use of new measures for the performance of nations that are less dependent on economics and focus more on social development, which may be a trend for the future of nations, and produce a more holistic view for the study. “Innovation” is the factor with the weakest relationship with social progress, which is justified by a weaker relationship with one of the subcategories, “basic human needs”, when analyzed in isolation. However, when the authors analyze the best and worst nations, the authors observe that economic factors are still prevalent, with the “institutions” and “infrastructure” factors being effective for improving competitiveness and the quality of life.

The findings represent a new, emerging configuration in country performance, but the study has its limitations, such as the use of only two pooled variables and the fact that it does not correlate their dimensions or variables.

This study can represents an expansion logic for measuring the performance of countries considering social factors. The main contributions of this study are its statistical evidence and documentary analysis of the relationship between economic and social variables. The main contribution of this paper is to show that over time (2014–2017) economic factors, as measured by the competitiveness index of nations, relate to aspects of social welfare, as measured by the social progress index.

This study aims to examine the trend of industrial competition between the US and China, which is the most crucial determinant in the future development of the global economy. For decades, the global economy has strengthened the global production network based on the division of labor between countries. Thus, the ripple effect of competition between the two countries should be analyzed in terms of the global production network. Therefore, this study uses the product space model, which explains the development process of industries with comparative advantage by country. We constructed the model based on the products of HS 4-digit code for the 2010–2019 period. The analysis results on the trend of the industrial competitiveness of major countries are as follows. First, the current industrial competitiveness of China is concentrated on low-tech industries. In the case of high-tech items, China shows a tendency of lower export sophistication compared to major manufacturing powerhouses such as Germany, the US, Japan, and Korea. Second, with respect to the possibility of a future industrial structure upgrade evaluated by density, the trend of China overtaking other manufacturing powerhouses is observed. As implied by the product space model, the advancement of the industrial structure through active participation in international trade enhances the industrial competitiveness. Therefore, the outcome of US-China industrial competition depends on who ensures more openness and industrial complexity.

This study aims to present diverse proposals for the measurement of tourism destination competitiveness that serve as alternatives to the travel and tourism competitiveness index (TTCI).

The proposal includes principal component analysis, the DP2-distance method, goal programming, data envelopment analysis and the Borda count. The study evaluates 17 destinations from Central America and the Caribbean.

These include the feasibility that the methodologies provide reliable competitiveness rankings and the possibility of using less information due to the strength of the statistical methodologies. International tourist arrivals, income from international tourism and travel and tourism contribution to the gross domestic product could be used as approximations of tourism destination competitiveness.

The main limitation is the absence of major destinations from the region that constitutes fierce competitors.

New aggregation methods can build composite indicators for competitiveness measurement and their presentation in a more comprehensible way.

The results serve as an alternative for countries that have yet to be considered in international tourism competitiveness comparisons.

A better explanatory power of the proposed index is given, thanks to their decomposition capacity and the reduction of the limitations of the original TTCI. Moreover, the proposals facilitate the inclusion of external information or the execution of a completely objective methodology.

本研究旨在为衡量旅游目的地竞争力提出多样化的建议, 并作为旅行和旅游竞争力指数的替代方案。

该提案包括主成分分析、DP₂ 距离方法、目标规划、数据包络分析和 Borda 计数。 该研究评估了中美洲和加勒比地区的 17 个目的地。

结果包括这些方法提供可靠的竞争力排名的可行性, 以及由于统计方法的优势而使用较少信息的可能性。 国际旅游人数、国际旅游收入以及旅行和旅游对 GDP 的贡献可以用作旅游目的地竞争力的近似值。

主要局限是该地区没有竞争激烈的主要目的地。

新的聚合方法可以为竞争力测量建立综合指标, 并以更易于理解的方式呈现。

结果可作为国际旅游竞争力比较中, 衡量尚未考虑国家的替代方案。

由于其分解能力和原始 TTCI 限制的减少, 所提出的指数具有更好的解释力。 此外, 这些建议有助于纳入外部信息及执行完全客观的方法。

El presente estudio busca presentar diversas metodologías para medir la competitividad de los destinos turísticos, de modo que sirvan como alternativa al Índice de Competitividad de Viajes y Turismo.

La propuesta incluye Análisis de Componentes Principales, el método de distancia DP₂, Programación por Metas, Análisis Envolvente de Datos y el Recuento de Borda. Se analizan 17 destinos de Centro América y el Caribe.

Estos incluyen la validez de las metodologías para obtener rankings de competitividad fiables y la posibilidad de emplear menor cantidad de información, dadas las fortalezas de los procedimientos estadísticos propuestos. Las Llegadas de Turistas Internacionales, los Ingresos por Turismo Internacional, y la Contribución del Turismo al PIB podrían ser buenas aproximaciones para medir competitividad turística

La principal limitación es la ausencia de destinos importantes de la región, que se consideran importantes competidores.

Novedosos procedimientos de agregación para crear indicadores sintéticos para medir la competitividad turística y su presentación de un modo más comprensible.

Los resultados sirven como alternativa para otros destinos que aún no han sido considerados en comparaciones internacionales de competitividad turística.

Un mejor poder explicativo de los índices propuestos, gracias a su capacidad de descomposición, y la reducción de las limitaciones del índice del WEF. Además, las propuestas facilitan la inclusión de información externa o la ejecución de un método completamente objetivo.

The purpose of this paper is to explore the competitiveness and convergence of the G7 and big emerging markets (BEM) nations using various economic, demographic, trade, investment, and freedom and governance criteria.

The two groups of nations, G7 and BEM, are compared on the basis of various longitudinal and cross‐sectional variables. The longitudinal variables are GDP and real GDP growth, per capita GDP, international trade, foreign direct investment, index of ageing, and life expectancy at birth. Cross‐sectional competitive indices are Global competitiveness index, index of economic freedom, Democracy index, Human development index, Gini index, Government effectiveness, and Corruption perception index.

The findings show that BEM is growing faster than G7 in most economic indicators including GDP, trade, and investment. The growth results in some form of convergence. The freedom and governance infrastructure of the BEM is relatively weak to support their economic growth. The primary challenge of the BEM is coming from the economic interdependence they create in a globalized economy. Overall, the growth presents a new political reality that the world must recognize.

National competitiveness is a long‐term issue. A 30‐year longitudinal analysis may not be long enough to accurately reflect a nation's performance. Evidently, wealth creation in the emerging markets has profound influence in noneconomic areas. Political polarization and military confrontation are not unlikely.

Governments and businesses in G7, BEM, or the Association of Southeast Asian Nations (ASEAN) nations and institutions involved in global governance (e.g. World Bank, IMF, and WEF) may use the findings of the study to determine their policies. We should pay special attention to the global economic interdependence and guard against the negative effects of emerging markets' growth.

The comparative analysis between the G7 and BEM in terms of competitiveness and convergence is an original contribution. Also, the author's insight beyond economics is a unique section to follow. The author is not aware of any other study that has used the two concepts competitiveness and convergence together to understand the emerging markets.

Introduction: Today the ability of nations to develop and implement innovations is core for their international competitiveness. Ukraine is striving for innovation progress; however, its innovation performance is relatively low. The research problem is to find the bottlenecks, affecting Ukraine’s innovation capability.

Purpose: This study aims to research the national innovation capability profiles, based on cluster analysis, to develop an understanding of drivers and threats for the innovation capability of Ukraine.

Need of the study: The knowledge-based economy, which had already turned into one of the most efficient developmental models of the 21st century, became a key driver of international competitiveness for the leading developed countries due to their progressive structural shifts towards the growth of high-technology manufacturing and knowledge-intensive sectors. These trends are significant to capture for the sake of increasing the innovation capability of the economy of Ukraine.

Methodology: The study is based on the K-means clustering method, which is employed for identifying 10 country clusters based on the indicators of their R&D and innovation activities, which allowed us to assess the innovation capability of Ukraine in comparison with 140 countries of the world. Data selection and normalisation were based on the 2019 Global Competitiveness Report indicators.

Findings: The study showed that Ukraine’s innovation capability problems are typical for most developing countries and are prevalently connected to low R&D expenditures, patent applications, and international co-invention activities. Most countries, except for the technologically developed ones, follow the so-called ‘passive technological learning’ strategies, which usually result in low economic productivity.

Practical implications: Several innovation policy implications have been developed for the government of Ukraine based on the cluster analysis results and accounting for the problems of the national innovation system (NIS).