Artificial intelligence and discrete-event simulation for capacity management of intensive care units during the Covid-19 pandemic: A case study.

The Covid-19 pandemic has pushed the Intensive Care Units (ICUs) into significant operational disruptions. The rapid evolution of this disease, the bed capacity constraints, the wide variety of patient profiles, and the imbalances within health supply chains still represent a challenge for policymakers. This paper aims to use Artificial Intelligence (AI) and Discrete-Event Simulation (DES) to support ICU bed capacity management during Covid-19.

Investigating the revised international marketing strategies during COVID-19 based on resources and capabilities of the firms: A mixed method approach.

This paper aims to identify the revised international marketing strategies in communication during the COVID-19 pandemic by utilizing the firm's resources and capabilities. We conducted in-depth interviews and a questionnaire survey with key stakeholders of retail organizations which changed their digital marketing strategies during COVID-19. The data is collected from 587 respondents from different parts of the world through resource orchestration theory.

Estimation of Lockdowns' Impact on Well-Being in Selected Countries: An Application of Novel Bayesian Methods and Google Search Queries Data.

Lockdowns introduced in connection with the COVID-19 pandemic have had a significant impact on societies from an economic, psychological, and health perspective. This paper presents estimations of their impact on well-being, understood both from the perspective of mental health and considering economic security and similar factors. This is not an easy task because well-being is influenced by numerous factors and the changes happen dynamically.

People and place attachment: Exploring compliance in neighborhood health centers.

This article explores the roles of place attachment and social relationships in encouraging clients of a health center to comply with their health providers' directives. We draw on place attachment theory to explore the extent to which emotional bonds between clients and the center promote compliance. Next, we draw on place social bonding to explore whether clients' experiences derived from interactions at the center encourage compliance.

The impact of perceived crisis severity on intention to use voluntary proximity tracing applications.

During a crisis such as COVID-19, governments ask citizens to adopt various precautionary behaviours, such as using a voluntary proximity tracing application (PTA) for smartphones. However, the willingness of individual citizens to use such an app is crucial. Crisis decision theory can be used to better understand how individuals assess the severity of the crisis and how they decide whether or not to adopt the precautionary behaviour.

Has Covid-19 accelerated opportunities for digital entrepreneurship? An Indian perspective.

Covid-19 has challenged many businesses to orient themselves towards digital solutions for their survival. Due to the rising digital wave during Covid-19, there has been a plethora of opportunities for aspiring entrepreneurs to enter the market. Hence, this study focuses on understanding emerging areas and technologies for digital entrepreneurship.

Big data applications with theoretical models and social media in financial management.

This study presents big data applications with quantitative theoretical models in financial management and investigates possible incorporation of social media factors into the models. Specifically, we examine three models, a revenue management model, an interest rate model with market sentiments, and a high-frequency trading equity market model, and consider possible extensions of those models to include social media. Since social media plays a substantial role in promoting products and services, engaging with customers, and sharing sentiments among market participants, it is important to include social media factors in the stochastic optimization models for financial management.

Exploring the factors that affect user experience in mobile-health applications: A text-mining and machine-learning approach.

Recent years have witnessed an increased demand for mobile health (mHealth) platforms owing to the COVID-19 pandemic and preference for doorstep delivery. However, factors impacting user experiences and satisfaction levels across these platforms, using customer reviews, are still largely unexplored in academic research. The empirical framework we proposed in this paper addressed this research gap by analysing unmonitored user comments for some popular mHealth platforms.

Using network data envelopment analysis to assess the sustainability and resilience of healthcare supply chains in response to the COVID-19 pandemic.

The widespread outbreak of a new Coronavirus (COVID-19) strain has reminded the world of the destructive effects of pandemic and epidemic diseases. Pandemic outbreaks such as COVID-19 are considered a type of risk to supply chains (SCs) affecting SC performance. Healthcare SC performance can be assessed using advanced Management Science (MS) and Operations Research (OR) approaches to improve the efficiency of existing healthcare systems when confronted by pandemic outbreaks such as COVID-19 and Influenza.

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.

Approach with initiative or hold on passively? The impact of customer-perceived dependence on customer forgiveness in service failure.

Service failure is almost inevitable with the intensifying competition in the service market and expectation of heterogeneous customers. The customer-firm relationship can significantly influence customers' subsequent attitudes and behaviors to the service provider when they encounter service failure. This study proposes a theoretical model to examine how customer-perceived dependence affects their forgiveness toward a service failure in attribution logic.

Assessing risk of supply chain disruption due to COVID-19 with fuzzy VIKORSort.

The rapid spread of the COVID-19 pandemic has disrupted many economic activities around the world. The complete and partial lockdown policies, as well as the closure of borders by many countries has halted trade, consequently disrupting domestic and international supply chain networks. Like many other countries, various economic sectors in Pakistan also bore high economic losses due to these disruptions.

A retrospective analysis of the evolution of ergonomics for environmental sustainability (2011-2021).

has been rapidly gaining attention in the scientific community. So far, a large part of the literature has focussed on specific dimensions of , such as green designs, green buildings, environmental education, and sustainability frameworks. However, there is a necessity for an integrated study that presents the summary of published literature supported by detailed bibliometric characteristics.

A multi-objective optimization model for a multi-period mobile facility location problem with environmental and disruption considerations.

The present work addresses a multi-period facility location decision during crisis-Pandemic-situation with highly uncertain demand. Our paper identifies failing distribution centres (DCs) over several periods of time and decides about relocation. Several scenarios arise: DCs can be opened, displaced from one location to another, closed or even reopened during a certain time, using mobile facility.

Decision optimization in cooperation innovation: the impact of big data analytics capability and cooperative modes.

Data-driven innovation enables firms to design products that are more responsive to market needs, which greatly reduces the risk of innovation. Customer data in the same supply chain has certain commonality, but data separation makes it difficult to maximize data value. The selection of an appropriate mode for cooperation innovation should be based on the particular big data analytics capability of the firms.

Checking consistency for Group-PAHP: a case study of tourism facilities in COVID-19 pandemic.

The pandemic situation due COVID-19 highlighted a great vulnerability of tourism systems in the world, defined a scenario characterized by strong uncertainties, unfavorable prospects and widespread fragility (Michie 2020). Our work proposes the use of Multi-Criteria Decision Aiding (MCDA) for analyzing the potentiality of local territory development through the improvement of the tourism facilities. More precisely, we propose the use of the Parsimonious AHP (Abastante et al.

Victim crisis communication strategy on digital media: A study of the COVID-19 pandemic.

The COVID-19 pandemic and the lockdown bore a devastating impact on organizations across the globe. In this crisis, organizations belonged to the victim cluster, with a low crisis responsibility. Nevertheless, organizations needed to strategize their crisis responses and communicate with stakeholders to reduce the threat to reputational capital and manage stakeholder reactions in the pandemic.

Corporate Users' Attachment to Social Networking Sites: Examining the Role of Social Capital and Perceived Benefits.

The debate on the pros and cons of employee attachment to social networking sites (SNS) has led to social media policy paralysis in many organizations, and often a prohibition on employee use of SNS. This paper examines corporate users' attachment to SNS. An analysis of 316 survey responses showed that corporate users' socialization in large public SNS was steeped in perceived work-related benefits, which in turn nourished their SNS attachment.

Crowdsourcing and COVID-19: How Public Administrations Mobilize Crowds to Find Solutions to Problems Posed by the Pandemic.

We discuss how public administrations have used crowdsourcing to find solutions to specific problems posed by the COVID-19 pandemic, and to what extent crowdsourcing has been instrumental in promoting open innovation and service co-creation. We propose a conceptual typology of crowdsourcing challenges based on the degree of their openness and collaboration with the crowd that they establish. Using empirical evidence collected in 2020 and 2021, we examine the extent to which these types have been used in practice.

The future is yesterday: Use of AI-driven facial recognition to enhance value in the travel and tourism industry.

This study aims to investigate the role of artificial intelligence (AI) driven facial recognition to enhance a value proposition by influencing different areas of services in the travel and tourism industry. We adopted semi-structured interviews to derive insights from 26 respondents. Thematic analysis reveals the development of four main themes (personalization, data-driven service offering, security and safety, and seamless payments).

Examining the relationship between fear of COVID-19, intolerance for uncertainty, and cyberloafing: A mediational model.

After the COVID-19 pandemic began, organizations had to pivot and move to online remote work. As companies moved to digital platforms and technologies for remote working, a key concern was the increase in workplace withdrawal behaviors during the pandemic, including cyberloafing, a form of workplace deviance. Cyberloafing can be described as the action of using the internet for non-work-related activities or personal use during working hours.

Exploring transformative policy imaginaries for a sustainable Post-COVID society.

The COVID-19 crisis and its underlying health, socio-economic and environmental challenges warrants a discussion about transformative policies for a more sustainable, post-pandemic world. At EU level, policy packages and initiatives such as the European Green Deal (EGD), the Bioeconomy Strategy (BES) or the Circular Economy Action Plan (CEAP) may have the prerequisites to support a sustainable socio-economic transformation. But can these initiatives live up to public imaginaries of a sustainable post-pandemic world? To answer this question, we conducted a qualitative media analysis in order to outline emerging public imaginaries, as well as different policy suggestions put forth by different media outlets.

Performance effects of analytics capability, disruption orientation, and resilience in the supply chain under environmental uncertainty.

The relationship between Analytics Capability of an Organization (ACO) and both Supply Chain Disruption Orientation (SCDO) and Supply Chain Resilience (SCR) in order to achieve adequate operational performance in an era of environmental uncertainty is carried out in this study. Total three hypotheses (seven sub-hypotheses) using a survey of 405 respondents are collected via a pre-tested instrument and tested further. Results indicated the influence of ACO on both SCDO and SCR to achieve the desired degree of operational performance.

Disruptive Technologies for Achieving Supply Chain Resilience in COVID-19 Era: An Implementation Case Study of Satellite Imagery and Blockchain Technologies in Fish Supply Chain.

In supply chains where stakeholders belong to the economically disadvantaged segment and form an important part of the supply chain distribution, the complexities grow manifold. Fisheries in developing nations are one such sector where the complexity is not only due to the produce being perishable but also due to the livelihood dependence of others in the coastal regions that belong to the section of economically disadvantaged. This paper explains the contextual challenges of fish supply chain in a developing country and describes how integrating disruptive technologies can address those challenges.