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The conflict in Russian Ukraine is a problem for the world economy because it hinders growth and drives up inflation when it is already high. The trade route between India and Russia is also impacted by the Russia-Ukraine crisis. This study aims to compile the most recent data on how the present global economic crisis is affecting it, with particular emphasis on the Indian economy.

This research develops a mathematical forecasting model to evaluate how the Russia-Ukraine crisis would affect the Indian economy when perturbations are applied to the major transport sectors. Input-output modeling (I-O model) and interval programing (IP) are the two precise methods used in the model. The inoperability I-O model developed by Wassily Leontief examines how disruption in one sector of the economy spreads to the other. To capture data uncertainties, IP has been added to IIM.

This study uses the forecasted inoperability value to analyze how the sectors are interconnected. Economic loss is used to determine the lowest and highest priority sectors due to the Russia-Ukraine crisis on the Indian economy. Furthermore, this study provides a decision-support conclusion for studying the sectors under various scenarios.

In future studies, other sectors could be added to study the Russian-Ukrainian crises’ effects on the Indian economy. Perturbation is only applied to transport sectors and could be applied to other sectors for studying the effects of the crisis. The availability of incomplete data is a significant concern in this study.

Russia-Ukraine conflict is a significant blow to the global economy and affects the global transportation network. This study discusses the application of the IIM-IP model to the Russia-Ukraine conflict. It also forecasts the values to examine how the crisis affected the Indian economy. This study uses a variety of scenarios to create a decision-support conclusion table that aids decision-makers in analyzing the Indian economy’s lowest and most affected sectors as a result of the crisis.

Long regarded as a far-fetched notion, companies from post-socialist economies (PSEs) increasingly compete with companies from advanced economies in their domestic markets and abroad. This study identifies PSE companies' motives and determinants of outward foreign direct investment (OFDI) in advanced economies.

This study analyses Slovenian business activities in Germany by juxtaposing eight Slovenian investors and three exporters using a multiple case study approach. The authors use content analysis to examine rich data from semi-structured interviews, databases and internal and external documents to provide comprehensive and in-depth insights into PSE investments in advanced economies.

The authors identify market-seeking motives and competitive advantages which differ from those of other emerging economy companies and offer theoretical suggestions. In contrast to findings from other emerging economies, the authors identify firm- and country-specific advantages, such as high technology, high service quality, a highly educated labour force, and European Union membership, which Slovene companies have employed to enter the advanced German market.

This study represents the first application of springboard theory to explain PSE company investment in advanced economies. The authors offer contextualised explanations of PSE investments in advanced host economies, which have been lacking thus far. The authors also contribute to the scarcity of studies on the effects of supranational institutions on OFDI from emerging economies.

Infrastructure financialization plays a critical role in infrastructure development and urban growth around the world. However, on the one hand, the existing research on the infrastructure financialization focuses on qualitative and lacks quantitative country-specific studies. On the other hand, the spatial heterogeneity and influencing factors of infrastructure financialization are ignored. This study takes China as a typical case to identify and analyze the spatial characteristics, development process and impact factors of infrastructure financialization.

To assess the development and characteristics of infrastructure financialization in China, this study constructs an evaluation index of infrastructure financialization based on the infrastructure financialization ratio (IFR). This study then analyzes the evolution process and spatial pattern of China's infrastructure financialization through the spatial analysis method. Furthermore, this study identifies and quantitatively analyzes the influencing factors of infrastructure financialization based on the spatial Dubin model. Finally, this study offers a policy suggestion as a governance response.

The results demonstrate that infrastructure financialization effectively promotes the development of infrastructure in China. Second, there are significant spatial differences in China’s infrastructure financialization. Third, many factors affect infrastructure financialization, with government participation having the greatest impact. In addition, over-financialization of infrastructure has the potential to lead to government debt risks, which is a critical challenge the Chinese Government must address. Finally, this study suggests that infrastructure financialization requires more detailed, tailored,and place-specific policy interventions by the government.

This study not only contributes to enriching the knowledge body of global financialization theory but also helps optimize infrastructure investment and financing policies in China and provides peer reference for other developing countries.

This study aims to analyze the emergence of a new structural configuration of globalization, with the 2008 global financial crisis serving as the first symptom of this change. By introducing the “Evolutionary Structural Triptych” (EST), this research seeks to understand the basic components of the new evolutionary trajectory of global capitalism post-2008. The study places emphasis on its interdependent and coevolving economic, political and technological dynamic facets.

This research introduces the EST framework, critically contrasting it with conventional understandings in international political economy (IPE) to provide a comprehensive and structured analysis of global developments after 2008. It traces the phases of global capitalism since Second World War, examines the central dynamic dimensions during each evolutionary phase, identifies the basic patterns and delves into the foundational elements of the emerging era of globalization.

The analysis reveals three key findings. First, the emerging restructured globalization indicates a need for a new balance in the contemporary world system; however, this balance cannot be achieved within the architecture of the old system. Second, the new era of globalization necessitates a re-equilibrated approach across different dimensions of geopolitical stability, economic development and innovation. This approach should emphasize sustainability, adaptability, resilience and inclusivity and lean toward responsible, open and organic innovation models for a revamped global structure. Third, while many current IPE theories tend to compartmentalize aspects of the new globalization, the EST advocates for a holistic perspective that integrates politics, economics and technology within the framework of global trends. This perspective bridges existing gaps and offers actionable insights for a dynamic and inclusive global future.

The paper presents the EST as a novel analytical instrument in the realm of the modern IPE. This tool uniquely places technology and innovation at the forefront, parallel to economic and political spheres, to comprehend the progression of globalization. In doing so, it highlights the intertwined relationship of these structural dimensions in shaping the future of the subject of the IPE.

The COVID-19 pandemic and the onset of the conflict in Ukraine led to a sustained downturn in tourist arrivals (TA) in Russia. This paper aims to explore the influence of geopolitical risk (GPR) and other indices on TA over 1995–2023.

We employ a nonlinear autoregressive distributed lag (NARDL) model to analyze the effects, capturing both the positive and negative shocks of these variables on TA.

Our research demonstrates that the NARDL model is more effective in elucidating the complex dynamics between macroeconomic factors and TA. Both an increase and a decrease in GPR lead to an increase in TA. A 1% negative shock in GPR leads to an increase in TA by 1.68%, whereas a 1% positive shock in GPR also leads to an increase in TA by 0.5%. In other words, despite the increase in GPR, the number of tourists coming to Russia increases by 0.5% for every 1% increase in that risk. Several explanations could account for this phenomenon: (1) risk-tolerant tourists: some tourists might be less sensitive to GPR or they might find the associated risks acceptable; (2) economic incentives: increased risk might lead to a depreciation in the local currency and lower costs, making travel to Russia more affordable for international tourists; (3) niche tourism: some tourists might be attracted to destinations experiencing turmoil, either for the thrill or to gain firsthand experience of the situation; (4) lagged effects: there might be a time lag between the increase in risk and the actual impact on tourist behavior, meaning the effects might be observed differently over a longer period.

Our study, employing the NARDL model and utilizing a dataset spanning from 1995 to 2023, investigates the impact of GPR, gross domestic product (GDP), real effective exchange rate (REER) and economic policy uncertainty (EPU) on TA in Russia. This research is unique because the dataset was compiled by the authors. The results show a complex relationship between GPR and TA, indicating that factors influencing TA can be multifaceted and not always intuitive.

The study investigates the inter-linkages between geopolitical risk (GPR) and food price (FP).

By employing the bootstrap full- and sub-sample rolling-window Granger causality tests.

The empirical results show that there is a time-varying bidirectional causality between GPR and FP. High GPR leads to a rise in FP, suggesting that geopolitical events usually may disrupt supply and demand conditions in food markets, and even trigger global food crises. However, the negative effect of GPR on FP does not support this view in certain periods. This is mainly because GPR is also related to the global economic situation and oil price, which together have impacts on the food market. These results cannot always be supported by the inter-temporal capital asset pricing model, which states that GPR affects FP in a positive manner. Conversely, there is a positive impact of FP on GPR, indicating that the food market is an effective tool that can reflect global geopolitical environment.

In the context of the Russia–Ukraine conflict, these analyses can assist investors and policymakers to understand the sensitivity of FP to GPR. Also, it will provide significant revelations for governments to attach importance to the role of food price information in predicting geopolitical events, thus contributing to a more stable international environment.

This study empirically examines the moderating role of geopolitical risk on the tourism–economic growth nexus by applying a recent geopolitical risk indicator developed by Caldara and Iacoviello (2022) in a cross-country panel data growth model context for a sample of 24 countries.

A Dummy Variable Least Squares panel data model, nonparametric covariance matrix estimator and SYS-GMM estimation techniques are employed for the analysis. The authors capture the GPR moderating effect by disaggregating the cross-country sample according to low versus high country GPR score and through a GPR interaction coefficient. Several controls are included in the models such as gross fixed capital formation and—consistent with Barro (1990)—government consumption. Trade openness is used to account for the export-led growth effect. In line with neoclassical growth theory (e.g. Barro, 1991), the authors also include the real interest rate, to account for policy makers' commitment to macroeconomic stability, financial depth, as a proxy for financial development, population growth and the level of secondary school education. The authors also control for unobserved country-specific and time-invariant effects.

The research finds that the interaction term of geopolitical risk significantly contributes to the predictive ability of the regression and provides empirical evidence that confirms that only in low geopolitical risk countries international tourism positively and significantly contributes to economic growth. Important theoretical and policy implications flow from these findings.

The study not only contributes to advancing academic knowledge on the tourism–growth nexus, it also has impact beyond academia. Many countries have in the past pursued and many continue to pursue, tourism specialization and/or tourism-led growth strategies based on the theoretically well-established and empirically validated positive link between inbound tourism and economic growth. The findings alert policy makers in such countries to the significant moderating role that geopolitical risk plays in affecting the above-mentioned relationship and to the importance of prioritizing geopolitical stability as a policy precursor for the successful implementation of such strategies.

This paper aims to examine the reaction of energy inflation to geopolitical risks in the European Economic Area between 1990 and 2015.

This study applies the nonparametric time-varying coefficient panel data model with fixed effects. In addition, to further reveal potential tail effects that may not have been captured by conditional mean-based regressions, the method of moments quantile regression was also used.

The findings of this study are as follows: first, as European countries get exposed to geopolitical tensions, it is expected that energy prices will surge. Second, the ability of geopolitical risk to trigger energy inflation in recent times is not as powerful as it used to be. Third, countries with a lower inflation rate, when exposed to geopolitical risks, experience smaller increases in energy inflation compared to countries with a higher inflation rate.

The findings of this study lead us to the conclusion that transitioning from nonrenewable to renewable energy use is one channel through which the sampled countries can battle the energy inflation, which geopolitical risks trigger. A sound macroeconomic policy for inflation control is a complementary channel through which the same goal can be achieved.

Given the increasing level of energy inflation and geopolitical risks in the world today, this study is an attempt to reveal the time-varying characteristics of the relationship between these variables in European countries using a nonparametric time-varying coefficient panel data model and method of moments quantile regression with fixed effects.

In an era marked by heightened geopolitical uncertainties, such as international conflicts and economic instability, the dynamics of energy markets assume paramount importance. Our study delves into this complex backdrop, focusing on the intricate interplay the between traditional and emerging energy sectors.

This study analyzes the interconnections among green financial assets, renewable energy markets, the geopolitical risk index and cryptocurrency carbon emissions from December 19, 2017 to February 15, 2023. We investigate these relationships using a novel time-frequency connectedness approach and machine learning methodology.

Our findings reveal that green energy stocks, except the PBW, exhibit the highest net transmission of volatility, followed by COAL. In contrast, CARBON emerges as the primary net recipient of volatility, followed by fuel energy assets. The frequency decomposition results also indicate that the long-term components serve as the primary source of directional volatility spillover, suggesting that volatility transmission among green stocks and energy assets tends to occur over a more extended period. The SHapley additive exPlanations (SHAP) results show that the green and fuel energy markets are negatively connected with geopolitical risks (GPRs). The results obtained through the SHAP analysis confirm the novel time-varying parameter vector autoregressive (TVP-VAR) frequency connectedness findings. The CARBON and PBW markets consistently experience spillover shocks from other markets in short and long-term horizons. The role of crude oil as a receiver or transmitter of shocks varies over time.

Green financial assets and clean energy play significant roles in the financial markets and reduce geopolitical risk. Our study employs a time-frequency connectedness approach to assess the interconnections among four markets' families: fuel, renewable energy, green stocks and carbon markets. We utilize the novel TVP-VAR approach, which allows for flexibility and enables us to measure net pairwise connectedness in both short and long-term horizons.

This study aims to address the macroeconomic factors effect on the travel and leisure (T&L) industry throughout Europe within the context of the Russo-Ukrainian war that have started on 24 February 2022. Specifically, top tourist destinations are analysed, such as Spain, France, Italy and Portugal, as well as Europe in general.

This study adopts the panel regression approach based on the data that is provided on a daily basis, and it covers a period of nearly 14 months, starting on 24 February 2022 and ending on 15 April 2023.

The findings indicate that the European T&L sector is impacted by macroeconomic variables. Namely, the T&L sector is significantly impacted by interest rates, geopolitical risk, oil and gas, whereas inflation has a muted effect, indicating a comparatively lesser influence on the dynamics of the industry. This research contributes to existing literature by providing one of the first quantitative analyses of how macroeconomic factors impact the European T&L business in the context of a geopolitical conflict.

A study of the Russian–Ukrainian war may be limited by a number of research constraints. The continuing nature of the conflict, the lack of communication between the parties and potential political prejudice are some of these difficulties. Any research on the Russo-Ukrainian war should be done with these limits in mind.

Macroeconomic variables play a significant role on the T&L sector development; therefore, when designing resilience strategies, they need to be accounted for.

To the best of authors’ knowledge, this is one of the first studies to analyse how macroeconomic factors affected the European T&L business using a quantitative approach. The macroeconomic variables that were taken into account in this study included interest rates, inflation, oil and petrol prices, as well as the geopolitical risk index.