Online consumer resilience during a pandemic: An exploratory study of e-commerce behavior before, during and after a COVID-19 lockdown

The COVID-19 pandemic has disrupted retail and accelerated the trend towards electronic commerce. This study explores the reasons for and the implications of this shift. Our study builds on the consumer behavior literature, emerging COVID-19 research, and the environmentally imposed constraints perspective to describe how online purchasing behavior evolved during the COVID-19 crisis. The objective is to better understand how consumers use e-commerce to react to, cope with and adapt to periods of environmentally imposed constraints. Based on multiple sources including transaction and search data from a major French online retailer, we describe how consumer behavior evolves during such stressful life events as COVID-19. Our results support the usefulness of the multi-perspective react-cope-adapt framework of constrained consumer behavior in an online environment. Graphical Image 1

COVID-19 vaccine hesitancy: a social media analysis using deep learning.

Hesitant attitudes have been a significant issue since the development of the first vaccines-the WHO sees them as one of the most critical global health threats. The increasing use of social media to spread questionable information about vaccination strongly impacts the population's decision to get vaccinated. Developing text classification methods that can identify hesitant messages on social media could be useful for health campaigns in their efforts to address negative influences from social media platforms and provide reliable information to support their strategies against hesitant-vaccination sentiments. This study aims to evaluate the performance of different machine learning models and deep learning methods in identifying vaccine-hesitant tweets that are being published during the COVID-19 pandemic. Our concluding remarks are that Long Short-Term Memory and Recurrent Neural Network models have outperformed traditional machine learning models on detecting vaccine-hesitant messages in social media, with an accuracy rate of 86% against 83%.

Supply chain resilience in the UK during the coronavirus pandemic: A resource orchestration perspective.

The COVID-19 pandemic caused significant disruptions to global operations and supply chains. While the huge impact of the pandemic has nurtured important literature over the last couple of years, little is being said about the role of resource orchestration in supporting resilience in highly disruptive contexts. Thus, this study aims to this knowledge gap by proposing an original model to explore supply chain resilience (SCRE) antecedents, considering supply chain alertness (SCAL) as a central point to support resilience. This study focuses on the resource orchestration theory (ROT) to design a conceptual model. The partial least squares structural equation modeling (PLS-SEM) served to validate the model, exploring data from the UK supply chain decision-makers. The study reveals a number of both expected and unexpected findings. These include the evidence that supply chain disruption orientation (SCDO) has a strong positive effect on the SCAL. In addition, SCAL plays a strong positive effect in resource reconfiguration (RREC), supply chain efficiency (SCEF) and SCRE. We further identified a partial mediation effect of RREC on the relationship between SCAL and SCRE. Surprisingly, it appeared that SCAL strongly influences SCEF, while SCEF itself does not create any significant effect on SCRE. For managers and practitioners, the importance of resource orchestration as a decisive approach to adequately respond to huge disruptions is clearly highlighted by our results. Finally, this paper helps to grasp better how important resource orchestration in operations and supply chains remains for appropriate responses to high disruptions such as the COVID-19 impacts.

A structured literature review on the interplay between emerging technologies and COVID-19 - insights and directions to operations fields.

In recent years, emerging technologies have gained popularity and being implemented in different fields. Thus, critical leading-edge technologies such as artificial intelligence and other related technologies (blockchain, simulation, 3d printing, etc.) are transforming the operations and other traditional fields and proving their value in fighting against unprecedented COVID-19 pandemic outbreaks. However, due to this relation's novelty, little is known about the interplay between emerging technologies and COVID-19 and its implications to operations-related fields. In this vein, we mapped the extant literature on this integration by a structured literature review approach and found essential outcomes. In addition to the literature mapping, this paper's main contributions were identifying literature scarcity on this hot topic by operations-related fields; consequently, our paper emphasizes an urgent call to action. Also, we present a novel framework considering the primary emerging technologies and the operations processes concerning this pandemic outbreak. Also, we provided an exciting research agenda and four propositions derived from the framework, which are collated to operations processes angle. Thus, scholars and practitioners have the opportunity to adapt and advance the framework and empirically investigate and validate the propositions for this and other highly disruptive crisis.

Impacts of epidemic outbreaks on supply chains: mapping a research agenda amid the COVID-19 pandemic through a structured literature review.

The coronavirus (COVID-19) outbreak shows that pandemics and epidemics can seriously wreak havoc on supply chains (SC) around the globe. Humanitarian logistics literature has extensively studied epidemic impacts; however, there exists a research gap in understanding of pandemic impacts in commercial SCs. To progress in this direction, we present a systematic analysis of the impacts of epidemic outbreaks on SCs guided by a structured literature review that collated a unique set of publications. The literature review findings suggest that influenza was the most visible epidemic outbreak reported, and that optimization of resource allocation and distribution emerged as the most popular topic. The streamlining of the literature helps us to reveal several new research tensions and novel categorizations/classifications. Most centrally, we propose a framework for operations and supply chain management at the times of COVID-19 pandemic spanning six perspectives, i.e., adaptation, digitalization, preparedness, recovery, ripple effect, and sustainability. Utilizing the outcomes of our analysis, we tease out a series of open research questions that would not be observed otherwise. Our study also emphasizes the need and offers directions to advance the literature on the impacts of the epidemic outbreaks on SCs framing a research agenda for scholars and practitioners working on this emerging research stream.