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The aim of this paper is to examine the practice of performance management in a cross-border context in times of global uncertainty.

This is a conceptual paper.

The findings expose global uncertainty to be wielding a significant influence on performance management.

A practical framework is developed using real options theory. This approach offers suggestions for multinational corporations to increase the effectiveness of their performance management while at the same time focusing on profit-maximisation.

This paper enhances international management research by recognizing that real options theory can effectively be applied to improve the effectiveness of performance management in global uncertainty.

This paper aims to deepen the understanding of the relationship between global economic uncertainty and price volatility, specifically focusing on commodity, industrial materials and energy price indices as proxies for global inflation, analyzing data from 1997 to 2020.

The dynamic conditional correlation generalized autoregressive conditional heteroscedasticity model is used to study the dynamic relationship between variables over a while.

The results demonstrated a positive relationship between commodity prices and the global economic policy uncertainty (GEPU). Except for 1999–2000 and 2006–2008, the results of the energy price index model were very similar to those of the commodity price index. A predominant positive relationship is observed focusing on the connection between GEPU and the industrial material price index. The results of the pairwise Granger causality reveal a unidirectional relationship between the GEPU – the Global Commodity Price Index – and the GEPU – the Global Industrial Material Price Index. However, there is bidirectional causality between the GEPU – the Global Energy Price Index. In sum, changes in price indices can be driven by GEPU as a political factor indicating unfavorable economic conditions.

This paper provides a deeper understanding of the role of global uncertainty in the global inflation process. It fills the gap in the literature by empirically investigating the dynamic movements of global uncertainty and the three most important groups of prices.

This paper aims to highlight the importance of developing capabilities to thrive amid global uncertainty. The study builds a framework to help managers assess uncertainty in the global business environment and develop capabilities to prosper amid uncertainty. In doing so, the paper explains three capabilities – sensing the context, driving the market and redesigning the business – providing examples to capture each capability and managerial implications.

The framework of this study is based on academic research in dynamic capabilities and the author’s scholarly study on global strategy. The paper develops managerial guidelines and illustrates those with practical examples of multinational enterprises to make the case for why managers need to develop the three core capabilities for thriving amid uncertainty to achieve competitive advantage.

This study identifies three core capabilities that organizations should build if they are to thrive amid global uncertainty, namely, sensing the context, driving the market and redesigning the business. The key practical guidelines to manage this process are provided, including a managerial tool with 10 steps to developing capabilities to thrive amid global uncertainty.

The framework allows for developing dynamic capabilities in a world of new uncertainties such as digital disruption and de-globalization. It offers key guidelines for the journey, thus enabling managers to steer their firms toward thriving in an uncertain global environment.

The augmented uncertainty of the global business environment presents new challenges. The value of this paper lies in the simplicity and practicality of the framework and its focus on the role of an uncertain global environment in developing dynamic capabilities.

This study aims to investigate the influences of global uncertainty indicators volatility on the domestic socioeconomic and environmental vulnerability in a sample of 54 developing countries.

The two-step system generalized method of moments estimator is recruited to deal with autoregression and endogeneity matter in our dynamic panel data. Seven different global uncertainty indicators (US trade uncertainty; world trade uncertainty; economic policy uncertainty; world commodities and oil prices; the geopolitical risk index and the world uncertainty index) have been mobilized and compared for their empirical impact on the economic (growth and GDP), social (the misery index and income inequality) and environmental (CO₂ emissions) vulnerabilities of nations.

Our empirical estimations suggest that the socioeconomic and environmental vulnerability cannot be solved through the same pattern: all decrease of a particular aspect will necessarily have a cost and an opposite influence on at least one of the other aspects of the nations' vulnerability.

The originality of this article is to combine these three dimensions of vulnerability in the same investigation. To our knowledge, our research is one of the few providing a joint analysis of the influence of global uncertainty on the economic and socioenvironmental countries' vulnerabilities – given the fact social, economic and environmental aspects are at the heart of the UN sustainable goals, our study can be seen as an investigation of the nations' capabilities to work proactively on meaningful sustainable goals in an increasingly uncertain world.

This study examines dynamics of global and regional financial market efficiency; and how specific features of the market and other conditions influence variability in such efficiency.

The study employs fixed effects statistical approach in its examination of how specific features of financial markets influence variability in its efficiency.

This study finds that individual IMF defined economic regions tend to exhibits significantly different financial market efficiency characteristics given specific market features and conditions. In regional level comparative analysis (e.g. Europe, Africa, Asia–Pacific etc.) this study finds that incidence of financial market uncertainty is the dominant condition with significant effect on financial market efficiency across all the IMF regions. In the global level analysis, empirical estimates presented suggest that financial market uncertainty, financial institutional depth and financial institutional efficiency tend to have significant positive influence on global financial market efficiency all things being equal. In the same analysis however, this study finds that financial market and financial institutional access growth has significant negative impact on financial market efficiency.

The uniqueness of this study compared to related ones found in the literature stems from its focus on financial market efficiency at the global, and IMF defined regional block level instead of on a specific economy as often found in the literature. Additionally, in contrast to other related studies, this study further examines the role of global financial market uncertainty in its financial market efficiency analysis. Financial market uncertainty variable may be unique to this study because the variable is derived through an econometric process from a base variable.

The use of social media and information exchange increased during Covid-19 pandemic because people are isolated and working from home. The use of social media enhances information exchange in a global society, therefore customers are uncertain and not in a better position to take decisions before the situation goes worst everywhere in the world. The current study helps to understand how social media facilitate social and global engagement and information exchange which ultimately leads to the development of the customer psychology of stockpiling. This study aims to develop a research framework which helps to understand the customer psychology of stockpiling during a global pandemic.

This study opted for a social constructionist approach because it can help to understand both individual and social subjective realities with respect to stockpiling behaviour due to the fear and risk of Covid-19 pandemic. For this purpose, the researcher collected data from 40 customers of UK retail stores who actively use social media. The data were collected during telephonic interviews and thematic analysis was used for data analysis.

Results highlighted that institutional communication and social public interpretation of uncertainties and risk enhanced misinformation and sensationalism through social media platforms; therefore, stockpiling behaviour increased during Covid-19 pandemic. The fear of items being out of stock, illness, misinformation, family fear and going out were some of the possible causes that led to the development of panic stockpiling behaviour. The global uncertainty proof, as well as a public social consensus for staying at home and protecting the future also increased customers’ intention to buy in bulk for their future. Although social media played an important role in transferring relevant and timely information, it also increased uncertainty and social proof which may have led to stockpiling of retail products.

The results of this study are beneficial for understanding how Covid-19 creates and enhances uncertainties and risks at both global and national level which developed into customer panic stockpiling behaviour, even when there is no promotional scheme or decrease in prices. This study helps marketers understand the psychology of customer stockpiling during a global pandemic. This study also helps to understand the role of social media, which promotes social interpretations of uncertainties and risk which ultimately enhance panic stockpiling among customers.

Limited research is available which provides an understanding of how social media can play a role in socially generated uncertainties and risks, which enhance misinformation and sensationalism, as well as the development of stockpiling behaviour. This study provided a stockpiling behaviour model based on the theory of uncertainty and social proof. The results of this study are unique as there is limited literature available which connects social media, uncertainties and risk, Covid-19 pandemic and stockpiling behaviour among educated people.

Using a phenomenon known as the bullwhip effect, the authors explore why additional uncertainty in the marketplace can create severe disruptions in global supply chains (GSCs). The purpose of this paper is to analyze related risks in regional vs GSCs during low and high levels of uncertainty. The authors propose and discuss a number of potential implications alongside some tactics that may help mitigate disruptions in some cases before they become terminal problems for the supply chain sustainability.

Monte Carlo simulation is used to generate the conditions of uncertainty and various scenarios that may emerge to challenge GSCs. Vensim software is utilized as a tool for simulation purposes. The authors considered scenarios applicable to manufacturing and retail sectors specifically because of storability property of goods.

Regional supply chains, as opposed to global ones, are more stable and reliable (less risk of disruption) during low and high levels of uncertainty. During uncertain times, upstream suppliers are at greater risk in GSCs. Firms must make strategic decisions that will secure its supply chain functionality and assess the likelihood of such events since many firms entered emerging markets.

Building on internalization theory, it shows that risk and survival are components of decision making that are further complicated by supply chains now operating globally in emerging markets. The paper demonstrates with simulation that GSCs are riskier than regional supply chains in low and high levels of uncertainty, particular as it relates to the bullwhip effect. It also provides recommendations about supply chain restructure and investments in communication improvements to reduce the bullwhip effect in the supply chain.

The purpose of this paper is to investigate the risk and economic policy uncertainty (EPU) shocks on China’s equity markets while controlling for changes in sentiments and liquidity.

The GED-TARCH(1,1)-M procedure is used in estimations to deal with the heteroscedasticity problem.

Evidence shows that stock returns are positively correlated with predictable volatility and lagged downside risk. This study indicates that the stock returns are negatively correlated with both local and global uncertainty innovations. The test results are robust across different measures of stock returns and model specifications. The global EPU innovations have more profound impact on stock returns than that of Chinese EPU.

The findings are based on the data in the China’s stock market, other global markets may be considered in the future research.

Evidence indicates that a rise in EPU produces a negative effect on stock returns at the time news hits a market; however, investors will be rewarded by a premium as prices rebound in the subsequent period for compensating the investment decision made at a high uncertainty period.

The excess stock returns are negatively related to the EPU innovations, regardless of whether EPU originates from a domestic source or external sources.

This paper aims to investigate how different uncertainty shocks affect international housing prices.

The authors set up a model of housing price instability with four uncertainty variables and apply the panel generalized method of moments method and quantile regression to estimate the linear and non-linear linkages among the variables based on data of 56 countries from 2001Q1 to 2018Q2.

Some empirical findings are as follows. Higher macroeconomic uncertainty and global economic policy risk increase housing price instability, whereas greater financial uncertainty and geopolitical risk present reverse effect. Four uncertainty variables are good signals for housing price changes in Asia, and geopolitical risk takes leading role in Europe. Macroeconomic uncertainty positively impacts housing price instability only at a low or middle level in all regions, as financial uncertainty, global economic policy uncertainty and geopolitical risk effects in all regions are smaller at the middle or high level of housing price instability; this confirms the existence of non-linear correlation between each variable.

The findings help investors and policymakers gain a better notion of housing price instability and control into uncertainty signal that could cause housing price instability crash.

This paper aims to examine the return and volatility transmission among economic policy uncertainty (EPU), geopolitical risk (GPR), their interaction (EPGR) and five tradable precious metals: gold, silver, platinum, palladium and rhodium.

Applying time-varying parameter vector autoregression (TVP-VAR) frequency-based connectedness approach to a data set spanning from January 1997 to February 2023, the study analyzes return and volatility connectedness separately, providing insights into how the data, in return and volatility forms, differ across time and frequency.

The results of the return connectedness show that gold, palladium and silver are affected more by EPU in the short term, while all precious metals are influenced by GPR in the short term. EPGR exhibits strong contributions to the system due to its elevated levels of policy uncertainty and extreme global risks. Palladium shows the highest reaction to EPGR, while silver shows the lowest. Return spillovers are generally time-varying and spike during critical global events. The volatility connectedness is long-term driven, suggesting that uncertainty and risk factors influence market participants’ long-term expectations. Notable peaks in total connectedness occurred during the Global Financial Crisis and the COVID-19 pandemic, with the latter being the highest.

Using the recently updated news-based uncertainty indicators, the study examines the time and frequency connectedness between key uncertainty measures and precious metals in their returns and volatility forms using the TVP-VAR frequency-based connectedness approach.