The resistance toward COVID-19 contact tracing apps: A study of psychological reactance among young adults in Italy.

Western governments' attempts to encourage young adults to adopt COVID-19 contact tracing apps (CTAs) have been unsuccessful. Drawing on psychological reactance theory, we propose that government-imposed containment measures (e.g.

Assessing the potential of plastic waste management in the circular economy: a longitudinal case study in an emerging economy.

Unlabelled: Plastic waste management represents a fundamental challenge in terms of environmental pollution and health in many emerging countries. Yet, some firms believe improved plastic waste management could lead to value creation and capture, especially from a circular economy perspective. This study draws on a longitudinal research approach that involved 12 organizations in assessing plastic waste management's contribution to Cameroon's circular economy.

The Ethics of Freedom in Consumption: An Ethnographic Account of the Social Dimensions of Supermarket Shopping for Moroccan Women.

This research brings together insights from philosophy, political theory, and consumer research in conceptualizing and empirically examining the social dimension of negative and positive freedom in consumption. Drawing from ethnographic observations and interviews with Moroccan women regarding their shopping at the supermarket, the findings detail the roles of husbands, store employees, extended family members and friends as constrainer, protector, enabler, facilitator, indulger, and witness. The discussion explains a 'domino effect' in such innovative marketplaces, as these market and social actors together enact positive and negative forms of freedom in consumption in ways that co-disrupt social traditions.

Method and evaluations of the effective gain of artificial intelligence models for reducing CO2 emissions.

Nowadays, there is an increasing use of digital technologies and Artificial Intelligence (AI) such as Machine Learning (ML) models that leverage data to optimize the performances of systems in almost all activity sectors, including ML models for optimizing solutions related to CO2 capture from the atmosphere or CO2 emissions reduction from human activities. However, on the other hand, the use of AI models is leading to an increasing energy consumption that also raises environmental issues (in terms of CO2 emissions) which are less studied in the literature. This then raises the new question of a more realistic estimate of the carbon footprint (CO2 emissions in particular) of AI models in general, and particularly AI models aimed at reducing CO2 emissions.

Extending artificial intelligence research in the clinical domain: a theoretical perspective.

Academic research to the utilization of artificial intelligence (AI) has been proliferated over the past few years. While AI and its subsets are continuously evolving in the fields of marketing, social media and finance, its application in the daily practice of clinical care is insufficiently explored. In this systematic review, we aim to landscape various application areas of clinical care in terms of the utilization of machine learning to improve patient care.

Adoption of Industry 4.0 technologies by organizations: a maturity levels perspective.

This study employs a structured literature analysis considering Industry 4.0 technologies and their adoption stages (intention, adoption, implementation, routinization, continuance, and diffusion). We identify the technology adoption stage for each technology type, which in turn supports a maturity level categorization, as well as future research suggestions and challenging open research questions.

Intensive care units nurses' burnout, organizational commitment, turnover intention and hospital workplace violence: A cross-sectional study.

Aims: This study aimed to (1) assess the relationship between intensive care unit (ICU) nurses' burnout, organizational commitment and turnover intention, (2) examine the moderating effect of the organizational commitment on the relationship between ICU nurses' burnout and turnover intention, and (3) explore the prevalence and influencing factors of hospital workplace violence among ICU nurses.

Design: Cross-sectional study design.

Methods: Data were collected from August to October 2020 and a convenience sample of registered nurses was recruited.

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.

Artificial intelligence in E-Commerce: a bibliometric study and literature review.

This paper synthesises research on artificial intelligence (AI) in e-commerce and proposes guidelines on how information systems (IS) research could contribute to this research stream. To this end, the innovative approach of combining bibliometric analysis with an extensive literature review was used. Bibliometric data from 4335 documents were analysed, and 229 articles published in leading IS journals were reviewed.

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.

A Framework Based on Blockchain, Artificial Intelligence, and Big Data Analytics to Leverage Supply Chain Resilience considering the COVID-19.

In the global supply chains era, firms are more connected, integrated, and interdependent, bringing along a set of benefits and a number of risks. It is clear that the singular COVID-19 epidemic outbreak has led to unparalleled disruptions and considerable challenges for supply chains (SCs). For example, the sluggish economic environment provoked by the COVID-19 has negatively impacted the flow of goods, generating shortages and interruptions through the SCs.

Drivers and social implications of Artificial Intelligence adoption in healthcare during the COVID-19 pandemic.

The COVID-19 pandemic continues to impact people worldwide-steadily depleting scarce resources in healthcare. Medical Artificial Intelligence (AI) promises a much-needed relief but only if the technology gets adopted at scale. The present research investigates people's intention to adopt medical AI as well as the drivers of this adoption in a representative study of two European countries (Denmark and France, N = 1068) during the initial phase of the COVID-19 pandemic.

Hospital competition in a national health service: Evidence from a patient choice reform.

We study the impact of exposing hospitals in a National Health Service (NHS) to non-price competition by exploiting a patient choice reform in Norway in 2001. The reform facilitates a difference-in-difference approach due to plausibly exogenous (geographical) variation in pre-reform market structure. Employing rich, administrative data, covering the universe of hospital admissions from 1998 to 2005, we estimate models with hospital and treatment (DRG) fixed-effects and use only emergency admissions to limit patient selection issues.

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.

Responsible Artificial Intelligence as a Secret Ingredient for Digital Health: Bibliometric Analysis, Insights, and Research Directions.

With the unparallel advance of leading-edge technologies like artificial intelligence (AI), the healthcare systems are transforming and shifting for more digital health. In recent years, scientific productions have reached unprecedented levels. However, a holistic view of how AI is being used for digital health remains scarce.

Assessment of mHealth Interventions: Need for New Studies, Methods, and Guidelines for Study Designs.

This viewpoint argues that the clinical effects of mobile health (mHealth) interventions depends on the acceptance and adoption of these interventions and their mediators, such as usability of the mHealth software, software performance and features, training and motivation of patients and health care professionals to participate in the experience, or characteristics of the intervention (eg, personalized feedback).

Labour accidents and financial performance: empirical analysis of the type of relationship in the Spanish context.

This article performs empirical research and finds a negative relationship between accidents in the workplace and financial performance. The relationship is stronger and more persistent for performance 1 year ahead than for the current year. We find no significant evidence of curvilinear U-shaped or inverted U-shaped relationships.

Navigating Between the Plots: A Narratological and Ethical Analysis of Business-Related Conspiracy Theories (BrCTs).

This paper introduces the concept of business-related conspiracy theories (BrCTs). Drawing on Aristotelian virtue ethics and undertaking a narratological and ethical analysis of 28 BrCTs found online, I emphasize that BrCTs are narratives with structures rooted in other latent macro- and meta-narratives, including centuries-old myths. In particular, I reconstruct the fictional world (diegesis) of BrCTs - one in which CSR and social contracts have failed - before identifying eight different types of actors as which people can morally situate themselves in their relationships with business.

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.