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In addition to leading a new tide of global financial technology, blockchain delivers advantages in terms of risk control compared to traditional financial systems. By exploring the relationship between blockchain technology and macroeconomic uncertainty, this study aims to identify the hedge risk attribute of blockchain technology.

From a data set comprising 6,323 Chinese firms with A-shares listed on the Shenzhen and Shanghai Stock Exchanges in 2015–2018, the authors obtain the use of blockchain technology by listed companies on the basis of annual reports, news reports, search engines and prospectuses. These documents are then subjected to text analyses based on computer technology. Cross-sectional and propensity score matching analyses are used to ensure robustness.

The empirical results show that with an increase in macroeconomic uncertainty, blockchain technology can potentially enable companies to reduce their systemic risks and enhance their investment efficiency.

This study expands the literature on the application of blockchain technology, offers references for enterprises to address future risks based on specific macroeconomically uncertain environments and provides guidelines for governments to maintain financial market stability.

Integrating anxiety and uncertainty management (AUM) theory and theory of organizing, this study aims to contribute to the knowledge management literature by examining the interdependent and bidirectional nature of knowledge transfer between expatriates and host country nationals (HCNs). Specifically, the authors investigate how receivers’ cognitive response to senders’ behaviors during their interactions becomes an important conduit between senders’ behaviors and the successful transfer of knowledge.

The authors used the actor partner interdependence model to analyze data from 107 expatriate-HCN dyads. The authors collected the responses of these expatriate-HCN dyads in Shanghai, Taipei, Hong Kong, Vietnam, South Korea, Malaysia, Thailand, Indonesia and India.

Receivers’ interaction anxiety and uncertainty, as a response to senders’ relationship building behaviors, mediate the relationship between senders’ relationship building behaviors and successful knowledge transfer. When senders are expatriates, senders’ communication patience and relationship building behaviors interact to reduce the direct and indirect effects of both receivers’ interaction anxiety and uncertainty. However, when senders are HCNs, the moderation and moderated mediation models are not supported.

The study contributes to the knowledge management literature by investigating knowledge transfer between expatriates and HCNs using an interpersonal cross-cultural communication lens. The authors make refinements to AUM theory by going beyond the sender role to highlighting the interdependence between senders and receivers in the management of anxiety and uncertainty which, in turn, influences the effectiveness of cross-cultural communication. The study is also unique in that the authors underscore an important yet understudied construct, communication patience, in the successful transfer of knowledge.

This paper aims to investigate the effect of presidential elections on stock return volatility in five leading stock markets in sub-Saharan Africa.

This paper uses various criteria to select an appropriate generalized autoregressive conditional heteroscedasticity model to estimate the second moment of the return distribution with the inclusion of pre- and post-presidential election dummy variables that capture the effect of presidential elections on stock market volatility.

The empirical results show that high pre-election uncertainty increases volatility in the Nairobi Stock Exchange, Stock Exchange of Mauritius and the Nigeria Stock Exchange. Furthermore, the results show that volatility in stock return is reduced 90 days after an election in Nigeria and South Africa but increases 90 days after elections in Ghana.

Contrary to the previous studies that are conducted in a single country with focus on specific elections, this paper provides a comparative analysis of presidential elections and stock return volatility in five leading stock markets in sub-Saharan Africa.

National cultures significantly explain cross-country differences in the relation between asset growth and stock returns. Motivated by the notion that managers in individualistic and low uncertainty-avoiding cultures have a higher tendency to overinvest, this study aims to show that the negative relation between asset growth and stock returns is stronger in countries with such cultural features. Once the researchers control for cultural dimensions, proxies associated with the q-theory, limits-to-arbitrage, corporate governance, investor protection and accounting quality provide no incremental power for the relation between asset growth and stock returns across countries. Evidence of this study highlights the importance of the overinvestment hypothesis in explaining the asset growth anomaly around the world.

This paper aims to minimize the mean-risk cost of sustainable and resilient supplier selection, order allocation and production scheduling (SS,OA&PS) problem under uncertainty of disruptions. The authors use conditional value at risk (CVaR) as a risk measure in optimizing the combined objective function of the total expected value and CVaR cost. A sustainable supply chain can create significant competitive advantages for companies through social justice, human rights and environmental progress. To control disruptions, the authors applied (proactive and reactive) resilient strategies. In this study, the authors combine resilience and social responsibility issues that lead to synergy in supply chain activities.

The present paper proposes a risk-averse two-stage mixed-integer stochastic programming model for sustainable and resilient SS,OA&PS problem under supply disruptions. In this decision-making process, determining the primary supplier portfolio according to the minimum sustainable-resilient score establishes the first-stage decisions. The recourse or second-stage decisions are: determining the amount of order allocation and scheduling of parts by each supplier, determining the reactive risk management strategies, determining the amount of order allocation and scheduling by each of reaction strategies and determining the number of products and scheduling of products on the planning time horizon. Uncertain parameters of this study are the start time of disruption, remaining capacity rate of suppliers and lead times associated with each reactive strategy.

In this paper, several numerical examples along with different sensitivity analyses (on risk parameters, minimum sustainable-resilience score of suppliers and shortage costs) were presented to evaluate the applicability of the proposed model. The results showed that the two-stage risk-averse stochastic mixed-integer programming model for designing the SS,OA&PS problem by considering economic and social aspects and resilience strategies is an effective and flexible tool and leads to optimal decisions with the least cost. In addition, the managerial insights obtained from this study are extracted and stated in Section 4.6.

This work proposes a risk-averse stochastic programming approach for a new multi-product sustainable and resilient SS,OA&PS problem. The planning horizon includes three periods before the disruption, during the disruption period and the recovery period. Other contributions of this work are: selecting the main supply portfolio based on the minimum score of sustainable-resilient criteria of suppliers, allocating and scheduling suppliers orders before and after disruptions, considering the balance constraint in receiving parts and using proactive and reactive risk management strategies simultaneously. Also, the scheduling of reactive strategies in different investment modes is applied to this problem.

The purpose of the research is to analyze the impact of world uncertainty and pandemic uncertainty on Islamic financial markets. For representing Islamic financial markets four different Islamic indices (DJ Islamic index, DJ Islamic Asia–Pacific index, DJ Islamic-Europe index and DJ Islamic-US) are taken.

The study employs quantile-on-quantile regression approach to see the overall dependence structure of variables based on quarterly data ranging from 1996Q1 to 2020Q4. This technique considers how quantiles of world uncertainty and pandemic uncertainty asymmetrically affect the quantiles of Islamic stocks by giving an appropriate framework to apprehend the overall dependence structure.

The findings of the study confirm a strong negative impact of world uncertainty and world pandemic uncertainty on regional Islamic stock indices but the strength of the relationship varies according to economic conditions and across the regions. However, the world pandemic effect remains the same and does not change. Conversely, pandemic uncertainty has a larger effect on Islamic indices as compared to world uncertainty.

Our findings have significant implications for investors and policymakers to take proper steps before any uncertainty arise. A coalition of the central bank, government officials and investment bank regulators would be needed to tackle this challenge of uncertainty.

To the best of the authors' knowledge, none of the current works has considered the asymmetric impact of world and pandemic uncertainties on Islamic stock markets at both the bottom and upper quantiles of the distribution of data.

This study seeks to build a financial uncertainty index for Saudi Arabia. This index serves as a leading indicator of Saudi economic activity and helps to describe economic fluctuations and forecast economic trends.

This study adopts an extension of the Jurado et al. (2015) procedure by combining financial uncertainty factors with their net spillover effects on GDP and inflation to construct an aggregate financial uncertainty index. The authors consider 13 monthly financial variables for Saudi Arabia from January 2010 to June 2021.

The empirical results show that the constructed financial uncertainty estimates are good leading indicators of economic activity. The robustness analysis suggests that the authors’ proposed financial uncertainty estimators outperform the alternative estimates used by other existing approaches to estimate the financial conditions index.

To the best of the authors’ knowledge, this is the first attempt at constructing a financial uncertainty index for Saudi Arabia. This study extends the empirical literature, from which the authors propose a novel conceptual framework for building a financial uncertainty index by combining the approach of Jurado et al. (2015) and the time-varying connectedness network approach proposed by Antonakakis et al. (2020)

This study aims to examine the impact of environmental scanning on organizational resilience through organizational learning based on organizational information processing theory (OIPT) in Egyptian small and medium-sized enterprises (SMEs) during the COVID-19 pandemic. Furthermore, this study aims to examine the moderating role of environmental uncertainty in this relationship.

The data for the mediation analysis was obtained using a cross-sectional design. Using a self-administered questionnaire, the authors collected data from a sample of 249 Egyptian SMEs. The authors tested the hypotheses using the smart partial least square structural equation modeling approach.

Organizational learning affects organizational resilience. Environmental scanning does not have a direct effect on organizational resilience. However, organizational learning fully mediates the relationship between environmental scanning and organizational resilience. Furthermore, environmental uncertainty does not moderate the indirect relationship between environmental scanning and resilience.

The sample included only Egyptian manufacturing SMEs. The results in the service sector and in other countries may differ. This study was cross-sectional, which was limited in its ability to trace the long-term effects of environmental scanning and organizational learning on organizational resilience.

Egyptian SMEs’ managers should experience organizational learning as a pathway for environmental scanning to build organizational resilience.

To the best of the authors’ knowledge, this study is the first to investigate the role of environmental scanning in building organizational resilience through organizational learning and the moderating role of environmental uncertainty in this relationship.

This paper proposes a two-level supply chain including suppliers and manufacturers. The purpose of this paper is to design a resilient fuzzy risk-averse supply portfolio selection approach with lead-time sensitive manufacturers under partial and complete supply facility disruption in addition to the operational risk of imprecise demand to minimize the mean-risk costs. This problem is analyzed for a risk-averse decision maker, and the authors use the conditional value-at-risk (CVaR) as a risk measure, which has particular applications in financial engineering.

The methodology of the current research includes two phases of conceptual model and mathematical model. In the conceptual model phase, a new supply portfolio selection problem is presented under disruption and operational risks for lead-time sensitive manufacturers and considers resilience strategies for risk-averse decision makers. In the mathematical model phase, the stages of risk-averse two-stage fuzzy-stochastic programming model are formulated according to the above conceptual model, which minimizes the mean-CVaR costs.

In this paper, several computational experiments were conducted with sensitivity analysis by GAMS (General algebraic modeling system) software to determine the efficiency and significance of the developed model. Results show that the sensitivity of manufacturers to the lead time as well as the occurrence of disruption and operational risks, significantly affect the structure of the supply portfolio selection; hence, manufacturers should be taken into account in the design of this problem.

The study proposes a new two-stage fuzzy-stochastic scenario-based mathematical programming model for the resilient supply portfolio selection for risk-averse decision-makers under disruption and operational risks. This model assumes that the manufacturers are sensitive to lead time, so the demand of manufacturers depends on the suppliers who provide them with services. To manage risks, this model also considers proactive (supplier fortification, pre-positioned emergency inventory) and reactive (revision of allocation decisions) resilience strategies.

We explore the driving forces behind the channel choices of the manufacturer and the platform by considering asymmetric selling cost and demand information.

This paper develops game-theoretical models to study different channel strategies for an E-commerce supply chain, in which a manufacturer distributes products through a platform that may operate in either the marketplace channel or the reseller channel.

Three primary models are built and analyzed. The comparison results show that the platform would share demand information in the reseller channel only if the service cost performance is relatively high. Besides, with an increasing selling cost, the equilibrium channel might shift from the marketplace to the reseller. With increasing information accuracy, the manufacturer tends to select the marketplace channel, while the platform tends to select the reseller channel if the service cost performance is low and tends to select the marketplace channel otherwise.

All these results have been numerically verified in the experiments. At last, we also resort to numerical study and find that as the service cost performance increases, the equilibrium channel may shift from the reseller channel to the marketplace channel. These results provide managerial guidance to online platforms and manufacturers regarding strategic decisions on channel management.

Although prior research has paid extensive attention to the driving forces behind the online channel choice between marketplace and reseller, there is at present few study considering the case where a manufacturer selling through an online platform faces a demand information disadvantage in the reseller channel and sales inefficiency in the marketplace channel. To fill this research gap, our work illustrates the interaction between demand information asymmetry and selling cost asymmetry to identify the equilibrium channel strategy and provides useful managerial guidelines for both online platforms and manufacturers.