ABSTRACT This article explores how Post-Millennials in Central and Eastern Europe perceive and respond to multiple, overlapping crises, including war, pandemics, climate change, and digital transformation. Drawing on eight group interviews with students from Austria, Czechia, Poland, and Ukraine, the study analyses how generational experiences shape attitudes toward political, social, and environmental challenges. Building on Karl Mannheim’s concept of generation and Erikson’s theory of psychosocial development, the article explores how shared historical and cultural contexts – or their absence – influence generational crises understanding. The findings indicate that Ukrainian students, who experience war firsthand, perceive crises as continuous and deeply personal. This is a perspective that fosters greater intergenerational closeness. In contrast, Polish, Czech, and Austrian students tend to experience crises more distantly, while their awareness is shaped by global processes and digital issues. Key differences emerge in technological literacy, engagement with digital media, and perceptions of responsibility for the future, underscoring the proximity, socialisation, and digital competence in shaping crisis perceptions. Overall, the study contributes to a deeper understanding of how contemporary geopolitical and societal disruptions intersect with generational identity, offering insights into the attitudes, values, and social behaviours of Post-Millennials in Central and Eastern Europe.

Do members of the European Parliament (MEPs) experience the rally-around-the-flag effect? What explains the consensus and dissensus in the European Parliament (EP) when responding to geopolitical crises? Guided by these questions, we compare how MEPs debate the EU’s initial response to the Russian invasion of Ukraine in 2022 and annexation of Crimea in 2014. Considering that the EP is a multi-level and transnational context, we explore the patterns of consensus and dissensus on the EP level, on the EP party group level, and on the regional level of East versus West Europe. To this end, we use an original dataset of hand-coded speeches of MEPs in 12 EP debates. We identify three types of reasoning behind the MEPs’ speech acts in terms of the optimal EU response: power-driven, value-driven, and non-response. Each sentence from MEPs’ interventions is coded under one of the three categories. Consequently, we create a three-dimensional space where we can locate each individual MEP as well as aggregate MEP positions into a party group, regional, or the EP level. This allows to estimate geometric distances between MEPs’ positions and that of their party group, region, and the EP. Basing these estimations on speech acts makes a mixed-methods design possible. We first conduct regression analysis to explore what explains the variance in the distances and then compare patterns of consensus and dissensus across parties and regions qualitatively. We find evidence for the rally-around-the-flag effect, but also show that the effect is not uniform across party groups.

The Palestine-Israel war has become a public concern because the genocide in Palestine has caused security disturbances and political shocks that have occurred in the world. This study aims to determine the effect of war events on market reactions that will be reflected in the Abnormal Return (AR) and Trading Volume Activity (TVA) values around the event window period. The event window used is twenty-one trading days, namely ten days before (t-10) and ten days after (t+10), and the event date (t-0) which falls on October 9, 2023. This study is a quantitative study using secondary data. The sample was used by 33 companies engaged in the hotel, tourism, and restaurant sub-sectors and listed on the IDX. Researchers in this quantitative study used the documentation method to obtain research data and used the market−customized model method to calculate the Abnormal Return (AR) value and Trading Volume Activity (TVA). The results of the study show that the Palestine-Israel war had no impact on Abnormal Returns (AR) in the Indonesian capital market but had an impact on Trading Volume Activity (TVA). This findings make significant contribution, as they demonstrates that geopolitical shocks can influence investor trading behavior without immediately affecting price, challenging the efficient market hypothesis in the context of emerging markets during geopolitical crises. The study provides implications that investors, portfolio managers, and policymakers need to understand market dynamics during international conflict.

This study examines the dynamic interdependence between Clean Energy indices, AI Robotics ‎Index, and selected NFT and DeFi tokens across three major geopolitical crises: COVID-19 ‎pandemic (January 2020–April 2021), Russia-Ukraine war (February 2022–December 2022), ‎and Iran-Israel conflict (October 2023–June 2024). Employing continuous wavelet transform, ‎wavelet coherence, and partial wavelet coherence techniques, we decompose relationships ‎across short-term, medium-term, and long-term horizons using daily data from Bloomberg. ‎Descriptive statistics reveal fundamental differences between sustainable investments and ‎digital assets: Clean Energy (mean: 0.0008, variance: 0.0004) and AI Index (mean: 0.0003, ‎variance: 0.0002) demonstrate positive returns with low volatility, while NFT and DeFi tokens ‎exhibit negative average returns and substantially higher volatility, with AAVE showing ‎extreme kurtosis (773.27) and variance (0.0167). Wavelet coherence analysis reveals crisis-‎dependent and scale-specific patterns. During COVID-19, only short-term and medium-term ‎coherence emerged, indicating transitory speculative relationships. The Russia-Ukraine war ‎marked a structural shift, with AAVE demonstrating long-term coherence with Clean Energy, ‎suggesting deeper market integration driven by energy market disruptions. The Iran-Israel ‎conflict exhibited the most complex patterns, with broader long-term coherence across ENJ ‎Coin, Theta, Synthetix, Maker, and SUPERf, indicating structural convergence between energy ‎transition narratives and selected DeFi/NFT projects. These findings demonstrate that ‎NFT/DeFi-sustainable investment relationships are crisis-dependent, scale-specific, and ‎selectively integrative, with significant implications for portfolio diversification strategies and ‎systemic risk monitoring during geopolitical crises‎.

Background: In this new era, marked by increasing environmental concerns, geopolitical crises, and global disruptions, traditional efficiency-focused supply chains have shown significant vulnerabilities. As a result, the shift toward new strategies to maintain sustainability has become more crucial. Meanwhile, to withstand disruptions, supply chains must develop robustness and resilience. More recently, attention has turned toward viability to enable sustainable supply chain operations over the long term under uncertainty. Methods: This study conducts a systematic literature review (SLR) to explore the links between green supply chain management (GSCM), supply chain resilience (SCRES), and supply chain viability (SCV), guided by the PRISMA framework and structured using the PICO approach as a high-level scoping tool. We reviewed 70 peer-reviewed journal articles published between 2010 and 2024. Result: The study identified widely adopted green practices and explored their impact on supply chain resilience and sustainable performance. Many studies address GSCM, SCRES, and SCV either separately or in pairs, but few integrate all three dimensions. GSCM fosters resilience, and when the three aspects are combined, they serve as the cornerstones of viable supply chains. However, their potential contribution to supply chain viability is still unexplored. Conclusions: These insights provide useful guidance for creating supply chains that balance long-term continuity, disruption-readiness, and environmental goals. They also suggest a future research agenda to better align these three priorities.

The current geopolitical tensions between the United States, Israel, and Iran, fake news has grown to be a serious threat. The recent conflict between the United States and Iran has highlighted the increased risk in 5th generation warfare in addition to conventional warfare, following the wars in Ukraine and the Gaza Strip. Artificial intelligence tools have been widely used in this new conflict to produce fake news, images, and videos during recent protests in Iran. In this regard, the article explores how artificial intelligence contributed to the creation and spread of misinformation during the US-Israel and Iranian crisis. The study demonstrates how new technologies increase the speed, scope, and seeming credibility of false narratives by analyzing content produced by artificial intelligence. The study examines pertinent case studies and recurrent trends in misinformation produced by artificial intelligence. The conclusions highlight the necessity of international regulatory frameworks and efficient methods for identifying false information in order to counteract AI-facilitated information manipulation in conflict areas. Researchers, journalists, policymakers, and cybersecurity experts who are worried about how new technologies will affect the information environment might find this paper interesting.

ABSTRACT This special issue examines how successive geopolitical crises, from Syria and Afghanistan to Ukraine and Gaza, have produced overlapping waves of forced displacement that now define Eurasia’s migration landscape. The articles in this issue advance a reconceptualization of refugee mobility by dissolving the migrant–refugee binary, foregrounding refugee agency, and acknowledging the overlapped phenomenon from international, regional, and domestic levels of analysis. Across cases, displacement emerges from cascading geopolitical vacuums, while institutional architectures mediate divergent protection outcomes. Refugees act as strategic navigators, pursuing mobility, legality, and livelihood within highly constrained environments. The contributions demonstrate that refugee governance in Eurasia is not determined by law or norm alone but by the contingent intersection of power politics, regional regime complexity, and state-level political incentives. By tracing these dynamics across Poland, South Korea, Uzbekistan, Tajikistan, and Jordan, the issue repositions Eurasia as a critical site for rethinking global refugee paradigms.

ABSTRACT This study examines the impacts of the Russia–Ukraine war on global supply chains across key industries, including food, energy, automotive, electronics, and shipping, and explores the countermeasures employed by these sectors. Using a qualitative methodology, the research synthesizes existing literature, industry reports, and news sources due to the limited availability of peer‐reviewed studies on this crisis. The findings reveal severe disruptions in the energy and food supply chains, while the automotive, electronics, and shipping sectors have faced varying degrees of impact. To address these challenges, this study proposes a strategic framework for enhancing supply chain resilience amid geopolitical crises. Understanding these impacts is crucial for economic and strategic reasons, assisting industries and policymakers to develop risk mitigation strategies, ensure economic stability, and reinforce global business continuity. This study provides valuable insights into the state of various industries’ supply chains during the crisis and their responses, addressing a critical gap in the literature on the impact of conflict on GSCs.

This study examines the impact of the Russian invasion of Ukraine on energy transformation and public opinion within the Visegrád Group (V4) countries—Czechia, Hungary, Poland, and Slovakia. Employing the Multi-Level Perspective (MLP) framework on sociotechnical transitions, the research investigates how macro-level disruptions, meso-level regime adaptations, and micro-level innovations interact to reshape energy systems. The study focuses on public attitudes toward reducing dependency on Russian energy and investing in renewables, contextualized through the Eurobarometer survey data (Wave 98.2, 2023). Bayesian multilevel logistic regressions were applied to evaluate the relationships between perceptions of war-related consequences (security, economic impacts) and attitudes toward energy policies. Findings reveal strong public support in Poland and Hungary for reducing reliance on Russian hydrocarbons and adopting renewable energy, while Czechia and Slovakia show moderate support. Security concerns were identified as a key driver of pro-renewable sentiments, particularly among younger cohorts and those perceiving war-related threats. The study highlights how geopolitical shocks can catalyze energy policy shifts, though entrenched sociotechnical regimes present challenges. Practical implications include leveraging public support for renewables to accelerate European Union (EU) energy transition goals. This research contributes novel insights into the interplay between energy transformation and geopolitical crises, emphasizing the V4’s pivotal role in Europe’s green transition.

Consumer attitudes toward brand supportive communication during geopolitical crises

Geopolitical crises, financial markets, and intraday volatility spillovers

RESEARCH OBJECTIVE: This article develops an integrated seven-layer theoretical model combining Faulkner’s Tourism Disaster Management Framework with geopolitical approaches to tourism Hall & Seyfi (2020), Neumayer (2004) and Lee et al. (2020). The aim was to fill this gap in the literature by combining the material and constructivist dimensions of crisis in a single model and then empirically testing it on a case study of Ukraine during the 2013–2014 geopolitical crisis. THE RESEARCH PROBLEM AND METHODS: The research problem was the inadequacy of traditional crisis management models to explain geopolitical crises in tourism. The empirical component employs quantitative data (UkrStat, Eurostat, Geopolitical Risk Index) and qualitative sources (BBC, EU policy documents). The research period covered the years 2013–2018. THE PROCESS OF ARGUMENTATION: A seven-layer model was developed through abductive reasoning by integrating three sources of knowledge: (1) classical models of tourism crisis management for analysing the crisis cycle; (2) theories of international relations to capture the material, institutional and discursive dimensions of the crisis; (3) a GPR Index reflecting the dynamics of political shocks. RESEARCH RESULTS: The 2014 crisis caused a multidimensional shock. The GPR index jumped sharply in March of that year. Perceived safety decreased, as did international arrivals and tourism revenues. The premium segment shrank by 70–75%. There was a profound reorientation of tourist flows within the country. These effects were significantly exacerbated by the media, which painted Ukraine as a country engulfed in conflict and detached the perception of risk from its actual geography. CONCLUSIONS, INNOVATIONS, AND RECOMMENDATIONS: The integrated model proposed in this study enables the identification of key mediating processes such as GPR index, media amplification and regional spillover effects. The Ukrainian case demonstrates the model’s explanatory value for understanding tourism behaviour under political instability and highlights practical implications for destination management: the need to incorporate geopolitical scenarios into crisis planning, diversify source markets, strengthen communication strategies and counteract distorted media narratives.

Objective - In this paper, the author will explore how McDonald's overcame geopolitical tensions and consumer activism between 2022 and 2025 by applying stakeholder theory, institutional adaptation, and digital resilience as a cohesive crisis management strategy. Methodology/Technique – The analysis has been performed in a qualitative case study design, which implies a combination of thematic interpretation with a critical discourse analysis (CDA) and quantification based on sales trends, sentiment tracking, and data on foot-traffic. This evidence has revealed that a broken stakeholder expectation compels multinational corporations to make trade-offs between corporate governance and franchise autonomy. Finding – The exposure to reputational risk in politically sensitive markets is mitigated by institutional adaptation, including strategic acquisitions and localized CSR. Findings further suggest that negative sentiment is a precursor to a noticeable financial effect, and therefore, real-time tracking is needed during periods of geopolitical instability. Digital transformation, especially sentiment analytics, driven by AI, and enhancing personalized engagement systems, makes crisis resilience stronger and helps recover post-crisis. Novelty – The research introduces an integrated model of crisis management that connects sentiment-based analysis, franchise government systems, and digital resilience capabilities, which multinational corporations can use in geopolitical crises. Through integrative real-time sentiment tracking and institutional and stakeholder-based theory, the research shows the ability of digital tools to anticipate the escalation of the situation and to provide evidence-based response frameworks. Type of Paper: Empirical JEL Classification: F23, M14, M16, M21, L83, D22 Keywords: Geopolitical conflicts, crisis management, stakeholder theory, digital resilience, consumer activism, sentiment analysis, institutional adaptation, brand reputation. Reference to this paper should be referred to as follows: Thani, S.A. (2025). Crisis Management in Geopolitical Conflicts: Strategic Adaptation and Digital Resilience in Multinational Corporations, GATR-Global J. Bus. Soc. Sci. Review, 13(4), 127–139. https://doi.org/10.35609/gjbssr.2025.13.4(4)

With the heightening financial globalization, the market risk has increased strongly especially at times of geopolitical uncertainty. Gold that has traditionally been considered a safe-haven asset is highly volatile when there is an escalation of geopolitical tensions. Nonetheless, the variability that occurs to the spot and futures markets has not been fully investigated. The paper determines the factor of Geopolitical Risk (GPR) on conditional volatility of gold futures and spot returns by the GARCH-X(1,1) model that incorporates the Student-t innovations. A standardized GPR index is introduced as an exogenous variable in the equation of variance using monthly data between the year 1980 and 2023. We find that, lagged GPR has a positive effect on futures volatility, but that effect is somewhat significant, indicating that futures markets that are more vulnerable to geopolitical shocks are speculative and leveraged derivatives markets. By comparison, the spot market volatility does not exhibit any important effect of GPR, meaning that it is self-enhanced by past shocks. Ljung-Box diagnostics indicate some residual autocorrelation in the futures model, indicating that there is some possibility to refine the model by using alternative GARCH specification, or adding more terms to the mean equation. GARKH-X(t) model is highly suitable in terms of volatility dynamics in the futures, whereas spot volatility is more stable. The study has significant implications on risk management, portfolio hedging policies, and regulatory controls on derivatives markets in times of geopolitical crises.

ABSTRACT As environmental and geopolitical crises deepen and global production networks (GPNs) reorganize, countries proximate to large consumer markets are becoming more attractive investment destinations. This argument has recently gained ground but lacks theoretical and empirical validation. This article opens up space for addressing this gap in two ways. Theoretically, it argues for conceptualizing proximity in multi-dimensional and macro-regional terms in the GPN literature, as this allows for a broader range of proximity benefits that firms might seek to exploit through nearshoring to be identified. Empirically, it performs a country-level panel data analysis of Italian and German nearshoring to Central and Eastern Europe between 2005 and 2019. The analysis found a significant correlation between nearshoring and environmental certification, while the results for regulatory and institutional certainty are inconclusive. The article concludes with a mixed-methods research agenda for the study of nearshoring as de-risking in economic geography.

Type of the article: Research ArticleThe global recovery from recent economic, health, and geopolitical crises, including the COVID-19 pandemic and the Russia–Ukraine war, increasingly depends on how economies mobilize human capital, migration, and financial flows. This article examines how human capital and its reallocation through migration and remittances, under different institutional conditions and economic system types, relate to configurations of human capital, net migration, political stability, and remittances that support sustained post-crisis economic recovery. Using a panel of 73 economies from 2010 to 2023, the empirical strategy combines descriptive rankings, multiple linear regression (MLR), and decision-tree classification, with an 80/20 split of the sample, primarily drawing on the WDI. Descriptive patterns highlight large asymmetries in both migration and growth: some advanced and emerging economies combine sizeable net migration inflows with robust GDP growth, whereas conflict-affected and fragile states, including the Syrian Arab Republic, Yemen, and Ukraine, experience substantial net outflows alongside persistent output losses. However, regression results indicate that differences in human capital primarily drive cross-country variation in post-crisis growth: HCI is the only statistically significant predictor, while net migration, political stability, and remittances display small and insignificant linear effects (R² ≈ 0.15; adjusted R² ≈ 0.10; n = 73). DTC reveals complex, non-linear relationships between migration, human capital, financial flows, and economic recovery, with outcomes concentrated in economies that combine higher skills and sizable remittances with stable institutions, effectively converting them into productive human capital.Acknowledgments The research was carried out with funds from the budget of the Ministry of Education and Science of Ukraine on the topic of the research project "Modeling educational transformations in wartime to preserve the intellectual capital and innovative potential of Ukraine" (0123U100114).

Using a time-frequency and quantile connectedness approach, our study examines the complex return spillovers dynamics between BRICS Plus stock markets, the volatility index (VIX), and the global geopolitical risk index (GPRD). By employing advanced models such as TVP-VAR, quantile connectedness, and spectral decomposition, we demonstrate how these markets interact across different market conditions and periods. Our results indicate that the VIX consistently acts as the dominant net transmitter of shocks, especially during periods of heightened uncertainty such as the COVID-19 pandemic, the Russian-Ukraine conflict, and the Trump-era U.S.-China trade tensions. In contrast, the GPRD functions predominantly as a net receiver of shocks, indicating its potential role as a hedge during geopolitical crises. BRICS Plus markets exhibit heterogeneous behavior: Brazil, South Africa, and Russia frequently emerge as net transmitters, while China, India, Egypt, Saudi Arabia, and the UAE primarily act as net receivers. Spillovers are strongest at the extremes of the return distribution and are mainly driven by short-term dynamics, underscoring the importance of high-frequency reactions over persistent long-term effects. These findings highlight the asymmetric, nonlinear, and state-dependent nature of global financial contagion, offering important insights for risk management, asset allocation, and macroprudential policy design in emerging market contexts.

Abstract Against the background of the corona pandemic, economic, and geopolitical crises in the past years, the question of how to achieve a sustainable development recovery has become a critical issue for many organizations and governments. For this reason, in the context of a huge technological leap, our research approach aims to advance the discussion about the triad on which stable and prosperous societies must be laid, is made up of the three pillars: classic, social and public entrepreneurship. This conceptual paper proposes a theory that focuses on the connections and the complementarity of the three types of entrepreneurship. Using a comparative analysis, we adapted and extended the framework proposed by Austin et al. (2006); we started from their proposed four key variables to guide our analysis – mission, market failure, resource mobilization, performance measurement – and we added two other variables: knowledge and technology. We also used the triadic model as a background (Scarlat, 2017). Using the theoretical foundations we laid out, this paper develops a new understanding of social and public entrepreneurship. It also suggests areas for researchers to explore further and makes some practical recommendations for public and social entrepreneurs.

This study aims to compare the effectiveness of financial distress prediction models (Altman Z-Score, Springate, Zmijewski, Taffler, Grover, and Ohlson) for food and beverage companies in Indonesia impacted by multidimensional crises: the COVID-19 pandemic, community activity restrictions (PPKM), and the boycott of pro-Israel products. The research objects include four companies listed on the Indonesia Stock Exchange (MAPI, MAPB, PZZA, FAST) that faced operational and financial pressures due to these phenomena. A quantitative method with a causal-comparative design was employed, analyzing secondary financial report data from 2020–2023 through descriptive statistics and predictive analysis. Results revealed variations in model accuracy depending on the crisis context: Springate achieved the highest overall accuracy (75%), attributed to its integration of liquidity, profitability, and leverage variables relevant during the pandemic and PPKM. Meanwhile, Ohlson excelled during the 2023 boycott period (100% accuracy) due to its sensitivity to non-financial factors like reputation and demand shifts. Conversely, Zmijewski (31%) and Grover (44%) underperformed, limited by their inability to capture external dynamics. The implications emphasize the importance of selecting context-specific models—liquidity-focused models (e.g., Taffler) for sudden economic shocks and multifactor probabilistic models (e.g., Ohlson) for geopolitical disruptions. For practitioners, product diversification and cost efficiency are key to resilience, while investors should integrate non-financial risks into decision-making. This study contributes to literature by integrating geopolitical crises into financial distress analysis, though limited by its small sample and historical data. Future research should expand sector coverage and develop hybrid models incorporating qualitative metrics.

This work looks for the optimal allocation of different assets, namely, the G7 stock indices, commodities (gold and WTI crude oil), cryptocurrencies (Bitcoin and Ripple), and S&P Green Bond, over four periods: before the COVID-19 crisis, during the COVID-19 crisis and before the Russia–Ukraine war, during the COVID-19 crisis and Russia–Ukraine war, and after the COVID-19 pandemic and during the Russia–Ukraine war. Metaheuristics, Non-dominated Sorting Genetic Algorithm (NSGAII), Strength Pareto Evolutionary Algorithm (SPEA2), and Particle Swarm Optimization (PSO) are applied to find the best allocation. The results reveal that there a significant preference for the S&P Green Bond during the four periods of study according to three algorithms, thanks to its portfolio diversification abilities. During the COVID-19 pandemic and the geopolitical crisis, the most optimal portfolio was Nikkei 225 because of its quick recovery from the pandemic and poor reliance on the Russia–Ukraine markets, while WTI crude oil and both dirty and clean cryptocurrencies were poor contributors to the investment portfolio because these assets are sensitive to geopolitical problems. After the end of the pandemic and during the ongoing Russia–Ukraine war, the three algorithms obtained remarkably different results: the NSGAII portfolio was invested in various assets, 32% of the SPEA2 portfolio was allocated to the S&P Green Bond, and half of the PSO portfolio was allocated to the S&P Green Bond too. This may be due to changes in investors’ preferences to protect their fortune and to diversify their portfolio during the war. From a risk-averse perspective, NSGAII does not underestimate the risk, while in terms of forecasting accuracy, PSO is an adequate algorithm. In terms of time, NSGAII is the fastest algorithm, while SPEA2 requires more time than the NSGAII and PSO algorithms. Our results have important implications for both investors and risk managers in terms of portfolio and risk management decisions, and they highlight the factors that influence investment choices during health and geopolitical crises.