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Fake news on social media about COVID-19 pandemic and its associated issues (e.g. lockdown) caused public panic that lead to supply chain (SC) disruptions, which eventually affect firm performance. The purpose of this study is to understand how social media fake news effects firm performance, and how to mitigate such effects.

Grounded on dynamic capability view (DCV), this study suggests that social media fake news effects firm performance via SC disruption (SCD) and SC resilience (SCR). Moreover, the relation between SCD and SCR is contingent upon SC learning (SCL) – a moderated mediation effect. To validate this complex model, the authors suggest effectiveness of using partial least squares structural equation modeling (PLS-SEM). Using an online survey, the results support the authors’ hypotheses.

The results suggest that social media fake news does not affect firm performance directly. However, the authors’ serial mediation test confirms that SCD and SCR sequentially mediate the relationship between social media fake news and firm performance. In addition, a moderated serial mediation test confirms that a higher level of SCL strengthens the SCD–SCR relationship.

This work offers a new theoretical and managerial perspective to understand the effect of fake news on firm performance, in the context of crises, e.g. COVID-19. In addition, this study offers the advancement of PLS as more robust for real-world applications and more advantageous when models are complex.

Prior studies in the SC and marketing domain suggest different effects of social media fake news on consumer behavior (e.g. panic buying) and SCD, respectively. This current study is a unique effort that investigates the ultimate effect of fake news on firm performance with complex causal relationships via SCD, SCR and SCL.

We determine the effects of micro‐inertia density and the vortex viscosity on laminar free convection boundary layer flow of a thermomicropolar fluid past a vertical plate with exponentially varying surface temperature as well as surface heat flux. The governing nonsimilarity boundary layer equations are analyzed using: first, a series solution for small ξ (a scaled streamwise distribution of micro‐inertia density), second, an asymptotic solution for large ξ and, third, a full numerical solution implicit finite difference method together with Keller‐box scheme. Results are expressed in terms of local skin friction and local Nusselt number. The effects of varying the vortex viscosity parameter, Δ, surface temperature and the surface heat flux gradient n and m respectively against ξ for fluids having Prandtl number equals 0.72 and 7.0 are determined.

Grounded in dynamic capabilities theory, this study aims to examine how dynamic capabilities and a transactive memory system (TMS) can build the resilience of service organizations and improve their financial performance. Limited studies examine the link between a TMS and organizational resilience.

The authors test a theoretical model on a sample of 350 UK service firms that were impacted by the COVID-19 pandemic and analyze the data using partial least square structural equation modeling.

Results highlight the positive effects of a TMS and dynamic capabilities on organizational resilience. Only a TMS and organizational resilience have direct positive effects on financial performance.

To the best of the authors’ knowledge, this is the first study to ascertain the influence of a TMS on organizational resilience in service firms following adversity.

Using dynamic capabilities (DCs) theory, the authors assess whether micro, small and medium-sized enterprises (MSMEs) can leverage DCs to improve operational capabilities (OCs) during the COVID-19 pandemic. The authors also identify whether organizational learning (OL) affects the relationship between DCs and OCs.

The authors test these propositions on a sample of 419 MSMEs from Australia and New Zealand.

DCs have no direct effect on OCs, technological or marketing capabilities (TCs or MCs). OL moderates the effect of DCs on both TCs and MCs.

The study assesses only MCs and TCs as OCs and does not explicitly measure pandemic impacts on organizations. However, the results illustrate the importance of OL during crises for recovery purposes.

Managers can use the findings to improve structure, processes and knowledge management emanating from MCs and TCs within organizations impacted by the COVID-19 pandemic.

The authors use a multi-dimensional measure of OL and show that during the pandemic, OL is a critical factor that allows organizations to transform the benefits conferred by DCs into MCs and TCs.

Arsenic contamination in shallow groundwater aquifers in the lower Gangetic basin constitutes a major health hazard in the Bengal basin extended over Bangladesh and India. It has been estimated that at least 35 million people in Bangladesh and 6 million people in India are severely affected by arsenic-contaminated water. More so, about 57 and 9 million people in Bangladesh and West Bengal, respectively, are exposed to arsenic-contamination risk. The use of hazardous, arsenic-bearing groundwater for drinking, cooking, and irrigation in West Bengal and Bangladesh has led to what has been described by the WHO as the worst case of mass poisoning in human history. In case of West Bengal, the problem of arsenic contamination was discovered in the 1980s; since then several mitigation measures were adopted by the provincial and federal governments, community organizations, and NGOs. Yet, poor infrastructural arrangements, dire poverty, lack of awareness, and education increased the risk of arsenic exposure over the decades. In this chapter, an effort has been made to critically analyze the extent of mitigation measures adopted so far in the state of West Bengal. It discusses in detail the chronological responses of the provincial government in arsenic risk mitigation, implementation of adopted mitigation measures, and the consequent response and actions of arsenic-affected communities in West Bengal. The chapter also highlights the emerging challenges of arsenic risk mitigation in West Bengal and proposes a “system-based” framework for risk mitigation.

Drawing on a dynamic capability view, this study develops a decision support model that determines the most suitable configuration of strategies and challenges to adopt additive manufacturing (AM) to expedite digital transformation and performance improvement of the surgical and medical device (SMD) supply chain.

To investigate the research objective, a multi-method and multi-study research design was deployed using quality function deployment and fuzzy set qualitative comparative analysis.

The study finds that only resilience strategies or negation (i.e. minimisation) of challenges are not enough; instead, a configuration of resilience strategies and negation of challenges is highly significant in enhancing performance.

SMD supply chain decision-makers will find the decision support model presented in this study as beneficial to be resilient against various challenges in the digital transformation of service delivery process.

This study builds new knowledge of the adoption of AM technology in the SMD supply chain. The decision support model developed in this study is unique and highly effective for fostering digital transformation and enhancing SMD supply chain performance.

An analysis is performed to study the skin‐friction, the couple‐stress and heat transfer characteristics of a laminar free‐convection boundary layer flow of a micropolar fluid past an isothermal plate inclined at a small angle to the horizontal. When the inclination is positive, series solutions, one valid near the leading edge and the other at a large distance from it, are obtained. Introducing a strained coordinate transformation, the local nonsimilar boundary layer equations are also derived for the flow from the leading edge to downstream, solutions of which are obtained by using an implicit finite difference method. When the inclination is negative, the boundary layer separates. The effects of the material parameters on the skin‐friction, the local couple‐stress, the local Nusselt number and the point of separation for a negatively inclined plate have been investigated.

Salinity is one of the major problems in the coastal region of Bangladesh that contributes to 20% of the total land area. About 53% of the coastal region is affected by different degrees of salinity. Salinity intrusion in this area is mainly derived through climate change as well as anthropogenic factors that make this region more vulnerable. Hence, salinity intrusion has adverse effects on water, soils, agriculture, fisheries, ecosystem, and livelihoods of this region. To ensure the availability of food as well as drinking water, this chapter highlights how individual and community people have endeavored several adaptation measures to minimize salinity effects. Moreover, it further discloses governmental and other development organizations’ actions toward salinity to reduce its impacts.

It is well known that stress singularity may exist at the edges of a bonded bi‐material interface due to the discontinuity of material properties. This stress singularity causes difficulty in accurately determining the bi‐material interface bonding strength. This paper aims to present a new design of specimen geometry to eliminate the stress singularity and present an experimental procedure to more accurately determine the bonding strength of the bi‐material interface.

The design is based on an asymptotic analysis of the stress field near the free edge of bi‐material interface. The critical bonding angle, which delineates the singular and non‐singular stress field near the free edge, is determined.

With the new designed specimen and a special iterative calculation algorithm, the interface bonding strength envelope of an epoxy‐aluminum interface was experimentally determined.

This new design of specimen, experimental procedure and iterative algorithm may be applied to obtain more reasonable and accurate bonding strength data for a wide range of bi‐material interfaces.