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The authors examine the role of analysts’ prior experience of forecasting for firms exposed to epidemics on analysts’ forecast accuracy during the COVID-19 pandemic.

The authors examine the impact of analysts’ prior epidemic experience on forecast accuracy by comparing the changes from the pre-COVID-19 period (calendar year 2019) to the post-COVID period extending up to March 2023 across HRE versus non-HRE analysts. The authors consider a full sample (194,980) and a sub-sample (136,836) approach to distinguish “Recent” forecasts from “All” forecasts (including revisions).

The study's findings reveal that forecast accuracy for HRE analysts is significantly higher than that for non-HRE analysts during COVID-19. Specifically, forecast errors significantly decrease by 0.6% and 0.15% for the “Recent” and “All” forecast samples, respectively. This finding suggests that analysts’ prior epidemic experience leads to an enhanced ability to assess the uncertainty around the epidemic, thereby translating to higher forecast accuracy.

The finding that the expertise developed through an experience of following high-risk firms in the past enhances analysts’ performance during the pandemic sheds light on a key differentiator that partially explains the systematic difference in performance across analysts. The authors also show that industry experience alone is not useful in improving forecast accuracy during a pandemic – prior experience of tracking firms during epidemics adds incremental accuracy to analysts’ forecasts during pandemics such as COVID-19.

The study findings should prompt macroeconomic policymakers at the national level, such as the central banks of countries, to include past epidemic experiences as a key determinant when forecasting the economic outlook and making policy-related decisions. Moreover, practitioners and advisory firms can improve the earning prediction models by placing more weight on pandemic-adjusted forecasts made by analysts with past epidemic experience.

The uncertainty induced by the COVID-19 pandemic increases uncertainty in global financial markets. Under such circumstances, the importance of analysts’ role as information intermediaries gains even more importance. This raises the question of what determines analysts’ forecast accuracy during the COVID-19 pandemic. Building upon prior literature on the role of analyst experience in shaping analysts’ forecasts, the authors examine whether experience in tracking firms exposed to prior epidemics allows analysts to forecast more accurately during COVID-19. The authors find that analysts who have experience in forecasting for firms with high exposure to epidemics (H1N1, Zika, Ebola, and SARS) exhibit higher accuracy than analysts who lack such experience. Further, this effect of experience on forecast accuracy is more pronounced while forecasting for firms with higher exposure to the risk of COVID-19 and for firms with a poor ex-ante informational environment.

Design of architecture, engineering and construction (AEC) project organizations expose project management practitioners (PMPs) to poor mental health due to the influence of project organization designs on project management activities assigned to the PMPs. The AEC project organization design comprises the integration of permanent organization, project organization and external environment layers. In spite of the link between project organization design and mental health, limited studies have examined the impact of permanent organization factors, project organization factors and external environmental factors on mental health management practices. Therefore, this study aims to examine the interactive relationships between permanent organization factors, project organization factors, external environment factors and mental health management indicators.

Four organizational theories: institutional theory, agency theory and resource-based theory were integrated to develop a theoretical model guiding the aim of the study. Eighty-two survey data were collected from PMPs in AEC firms in Australia. Structural equation modelling was used to test the relationships between the constructs.

The study found that mental health management indicators are predicted by the interactive and direct effects of permanent organizational factors, project organizational factors and external environmental factors. The results of the interactive effects of the factors and mental health management indicators revealed that 20 of 26 proposed hypotheses were supported. Based on the established hypotheses, economic factors, technological factors, environmental factors, legal factors and organizational culture positively correlated with mental health management indicators. Likewise, human resources management (HRM), corporate governance, project governance and integrated project delivery (IPD) positively impact mental health management indicators. However, political factors, social factors, knowledge management and project management skills negatively impact mental health management indicators. Moreover, political factors, economic factors, technological factors, environmental factors, legal factors and organizational culture are positively related to corporate governance. Additionally, organizational culture positively impacts corporate governance, project governance and HRM, whereas project governance positively correlated with IPD and knowledge management.

The findings provide guidelines to AEC firms on achieving positive mental health management indicators through concentration on project organization design.

To elaborate the picture of credibility assessment by examining how participants of online discussion evaluate the informational credibility of conspiracy theories.

Descriptive quantitative analysis and qualitative content analysis of 2,663 posts submitted to seven Reddit threads discussing a conspiracy operation, that is, the damage of the Nord Stream gas pipelines in September 2022. It was examined how the participants of online discussion assess the credibility of information constitutive of conspiracy theories speculating about (1) suspected actors responsible for the damage, (2) their motives and (3) the ways in which the damage was made. The credibility assessments focussed on diverse sources offering information about the above three factors.

The participants assessed the credibility of information by drawing on four main criteria: plausibility of arguments, honesty in argumentation, similarity to one's beliefs and provision of evidence. Most assessments were negative and indicated doubt about the informational believability of conspiracy theories about the damage. Of the information sources referred to in the discussion, the posts submitted by fellow participants, television programmes and statements provided by governmental organizations were judged most critically, due to implausible argumentation and advocacy of biased views.

As the study focuses on a sample of posts dealing with conspiracy theories about a particular event, the findings cannot be generalized to concern the informational credibility conspiracy narratives.

The study pioneers by providing an in-depth analysis of the nature of credibility assessments by focussing on information constitutive of conspiracy theories.

Architectural, engineering and construction (AEC) project organizations are under constant pressure to improve the mental health of project management practitioners (PMPs) due to complexity and dynamism involved in project management practices. Drawing on institutional theory, this research explores how external environmental factors, political factors, economic factors, social factors, technological factors, environmental factors and legal factors (PESTEL), influence mental health management indicators that contribute to positive mental health.

Purposive sampling method was used to collect survey data from 82 PMPs in 60 AEC firms in Australia. Structural equation modelling was used to test the hypotheses based on 82 items of data collected from PMPs.

Overall, this study revealed interesting findings on the impact of external environmental factors on mental health. The hypothesized positive association between political factors and mental health management indicators was rejected. The data supported the proposed hypothetical correlation between economic factors and mental health management indicators and the influence of social factors on mental health management indicators. Moreover, a hypothetical relationship between technological factors and mental health management indicators was supported. The significant positive impact of environmental factors on mental health management indicators proposed was supported, and legal factors’ positive correlation on mental health management indicators was also supported.

Despite the limitations, the present findings suggest that all the external environment factors except political factors shape mental health management outcomes.

The crude oil supply chain (COSC) is one of the most complex and largest supply chains in the world. It is easily vulnerable to extreme events. Recently, the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) (often known as COVID-19) pandemic created a massive imbalance between supply and demand which caused significant price fluctuations. The purpose of this study is to explore the influential factors affecting the international COSC in terms of consumption, production and price. Furthermore, it develops a model to predict the international crude oil price during disease outbreaks using Random Forest (RF) regression.

This study uses both qualitative and quantitative approaches. A qualitative study is conducted using a literature review to explore the influential factors on COSC. All the data are extracted from Web sources. In addition to COVID-19, four other diseases are considered to optimize the accuracy of predictive results. A principal component analysis is deployed to reduce the number of variables. A forecasting model is developed using RF regression.

The findings of the qualitative analysis characterize the factors that influence international COSC. The findings of quantitative analysis emphasize that production and consumption have a higher contribution to the variance of the data set. Also, this study found that the impact caused to crude oil price varies with the region. Most importantly, the model introduced using the RF technique provides a high predictive ability in short horizons such as infectious diseases. This study delivers future directions and insights to researchers and practitioners to expand the study further.

This is one of the few available pieces of research which uses the RF method in the context of crude oil price forecasting. Additionally, this study examines international COSC in the events of emergencies, specifically disease outbreaks using machine learning techniques.

Due to the frenetic and dynamic working conditions ascribed to architecture, engineering and construction (AEC) project organizations, enormous research has addressed the poor mental health propensity of project management practitioners (PMPs). However, research has not considered the distant factors related to organizational design causing poor mental health. Therefore, this study addresses the problem by integrating institutional theory, agency theory and resource-based theory (RBT) to explore the relationship between organizational design elements: project governance, knowledge management, integrated project delivery, project management skills and mental health management indicators. Examples of mental health management indicators include social relationships, work-life balance and project leadership.

Purposive sampling method was adopted to collect survey data from 90 PMPs in 60 AEC firms in Australia. Structural equation modelling (SEM) was utilized to test the relationship between the variables.

The research found that project governance, knowledge management and integrated project delivery are positively correlated to mental health management indicators. However, the research finding suggests that project management skills have a negative impact on mental health management indicators.

The findings offer guidelines to AEC firms on achieving positive mental health management outcomes through concentration on project governance, knowledge management and integrated project delivery. It further calls for a reconsideration of existing project management skills causing poor mental health management outcomes.

The purpose of the study is to analyse the impact of COVID-19 on the hospitality industry during the rise of worldwide pandemic crises using Twitter analysis. The study is based on 57,794 English-language tweets mined from Twitter from 1 April 2020 to 15 October 2020. Based on thematic and sentiment analysis, the study found that overall sentiments expressed on Twitter were negative. This chapter contributes to existing knowledge about the COVID-19 crisis and broadens the respondents’ understanding of the potential impacts of the crisis on the most vulnerable tourism and hospitality industry. This research emphasises the sustainable revival of the hospitality industry.

The authors believe the COVID-19 pandemic has an impact on supply and demand. The potential decline in real sector performance leads to lower expectations of securities performance. The uncertainty of future performance can change investor behaviour. This study tried to gain insight into stock investor behaviour during the COVID-19 pandemic. The results showed that the majority of the investor realized and believed the pandemic would affect the stock market performance. Hence, they did not show herding behaviour and were very confident during the COVID-19 pandemic. The survey also indicates that investors tend to avoid risk rather than take the opportunity to buy at a lower price. Moreover, investors believe that the COVID-19 vaccine will soon be found, and the economy will return to normal. Government and self-regulated organizations (SRO) are responsible for making effective policies to convince the investors about the future prospect.

Joint research is pointed out by the literature as a potentially virtuous cooperation scheme to generate learning in the public sphere and beneficial effects in society. The purpose of this study, based on the Argentine experience in the COVID-19 pandemic, is to analyze the network of capacities, relationships and effects generated, over time, by a series of projects financed by the State in 2010, to clarify the link between learning effects and social effects.

A qualitative methodology focused on the multiple case study method was used. Each case covers joint R&D projects financed 10 years ago by the state that subsequently led to different solutions for COVID-19.

The work identifies a public learning process that integrates both industry’s contributions and the intellectual dimension of economic benefits and their translation into specific capabilities; conceptualizes the capacities accumulation process as a multiplier of social effects (direct and indirect) that emerge as knowledge is reused; identifies the articulation between different schemes as a condition for learning effects and social effects to manifest over time.

An aspect not studied in the literature is addressed, the relationship between the learning process induced by joint research, in terms of capabilities, and the social effects specifically generated over time. This is taking place in a context, such as the COVID-19 pandemic, where calls from the scientific and academic community to promote science–industry cooperation are multiplying.