ABSTRACT
Organizations in recent times are increasingly investing in building supply chain resilience following disruptions due to natural disasters, geo-political crises, and pandemics. A lack of government support has exacerbated the disruption to supply chains in some regions of the world. The positive influence of digitalization on social inclusion, government accountability, and creating a more open environment is well understood. Despite this, different countries have shown varying degrees of digital responsiveness during the pandemic as they attempted to deal with the effects of various COVID strains. The influence of government policies on the supply chain has not been examined in the literature so far and, hence, to address this research gap, we examine the interaction effect of government support effectiveness i.e., tax credits, interest deferral, digital investment, soft loans on dynamic capabilities i.e., digital adaptabilities and digital agilities and on supply chain resilience, using a multi-method approach. To understand how digital adaptability and agility improve supply chain resilience, we conducted 13 semi-structured interviews. Additionally, we pretested our measurement instrument using qualitative semi-structured interviews to validate our hypothesized relationships. We collected data at a specific point of time using a survey-based instrument (N = 203) to address our research questions. Based on data analyses of both the qualitative and survey-based data, our findings indicate that digital adaptability is an important driver of digital agility. Furthermore, the results indicate that government effectiveness is crucial to enhancing supply chain resilience by enhancing digital adaptability and agility. Our research makes some useful contributions to the dynamic capability view by enhancing theoretical understanding, of the role of government in building digital capabilities in uncertain times, to improve supply chain resilience. It also bridges the research gaps between macro and micro perspectives, as identified by management scholars. Lastly, we noted the weaknesses and limitations in the study and therefore we have offered multiple research directions forward, that could help researchers to further develop our current work. © 2023 The Authors
ABSTRACT
Undoubtedly, due to the increasingly competitive pressures and the stride of varying demands, volatility and disturbance have become the standard in today's global markets. The spread of Covid-19 is a prime example of that. Supply chain managers are urged to rethink their competitive strategies to make use of Big Data Analytics (BDA), due to the increasing uncertainty in both demand and supply side, the competition among the supply chain partners and the need to identify ways to offer personalised products and services. With many supply chain executives recognising the need of 'improving with data', supply chain businesses need to equip themselves with sophisticated BDA methods/techniques to create valuable insights from big data, thus, enhancing the decision-making process and optimising the efficiency of Supply Chain Operations (SCO). This paper proposes the building blocks of a theoretical framework for understanding the impact of BDA on SCO. The framework is based on a Systematic Literature Review (SLR) on BDA and SCO, underpinned by Task-Technology-Fit theory and Institutional Theory. The paper contributes to the literature by building a platform for future work on investigating factors driving and inhibiting BDA impact on SCO.
ABSTRACT
On December 2019, a new coronavirus disease (COVID-19) emerged in China and spread worldwide, causing acute severe respiratory syndrome. Due to the increased transmission rate of the virus, it became of great importance the early diagnosis of the disease. The coronavirus pandemic led to the development of numerous tests in order to mass screening population for active viral load and for the identification of antibodies for epidemiological purposes. This review summarizes the different diagnostic tests available to the clinicians for the diagnosis and follow up of the SARS COV-2 infections.