Search results

This paper aims to examine the dynamic return and volatility connectedness for six major industrial metals (tin, lead, nickel, zinc, copper and aluminium) and the coronavirus media coverage index (MCI).

To that purpose, this study applies the fresh time-varying parameter vector autoregression methodology (TVP–VAR model) during the sample period between 2 January, 2020, and 16 April, 2021, that is, covering the three waves of the COVID-19 pandemic crisis.

This study’s results show interesting findings. First, dynamic total return and volatility connectedness changes over time, highlighting a significant increase during the third wave of the pandemic. Second, the MCI index is a leading net transmitter in terms of return and volatility at the introduction of the SARS-CoV-2 coronavirus crisis. Third, this study clearly distinguishes two profiles among industrial metals: copper and tin/zinc as net transmitters and lead and aluminium as net receivers. Finally, the most relevant differences between them are concentrated not only at the beginning of the COVID-19 pandemic (first wave) but also during the second and third waves of the coronavirus outbreak.

To the best of the authors’ knowledge, this is the first research that explores the dynamic return and volatility connectedness in the industrial metal market, applying the TVP–VAR methodology during the first waves of the COVID-19 pandemic crisis.

The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pandemic has drastically affected the public discourse on tourism in news reporting and on social media, potentially changing social perceptions of travel and its utility for conspicuous consumption. Prestige enhancement is a common tourist motivation, yet, as tourists have been portrayed as irresponsible and even dangerous during the pandemic, the benefits of travel for personal prestige may have been affected. The purpose of this study is to monitor changes in tourists’ personal prestige during the early pandemic in 2020.

The authors developed an innovative study design implicitly measuring the personal prestige of tourists shown on experimentally manipulated social media posts. Three measurement waves were issued to compare the personal prestige of tourists just before, during and after the first lockdown situation in Germany.

Differences regarding evaluations of tourists’ prestige were found for prestige dimensions of hedonism, achievements, wealth and power, suggesting that prestige ascription to tourists has been affected by the changing discourse on leisure travel.

This study contributes to the discussion of the socio-psychological effects of the SARS-CoV-2 pandemic on customer benefits of leisure travel. It exposes possible impacts of the pandemic on tourisms’ value for conspicuous consumption and prestige enhancement.

This study aims to investigate the impact of the COVID-19 pandemic on both of stock prices and investor's sentiment in China during the onset of the COVID-19 crisis.

In this study, the ADCC-GARCH model was used to analyze the asymmetric volatility and the time-varying conditional correlation among the Chinese stock market, the investors' sentiment and its variation. The authors relied on Diebold and Yilmaz (2012, 2014) methodology to construct network-associated measures. Then, the wavelet coherence model was applied to explore the co-movements between these variables. To check the robustness of the study results, the authors referred to the RavenPack COVID sentiments and the Chinese VIX, as other measures of the investor's sentiment using daily data from December 2019 to December 2021.

Using the ADCC-GARCH model, a strong co-movement was found between the investor's sentiment and the Shanghai index returns during the COVID-19 pandemic. The study results provide a significant peak of connectivity between the investor's sentiment and the Chinese stock market return during the 2015–2016 and the end of 2019–2020 turmoil periods. These periods coincide, respectively, with the 2015 Chinese economy recession and the COVID-19 pandemic outbreak. Furthermore, the wavelet coherence analysis confirms the ADCC results, which revealed that the used proxies of the investor's sentiment can detect the Chinese investors' behavior especially during the health crisis.

This study provides two main types of implications: on the one hand, for investors since it helps them to understand the economic outlook and accordingly design their portfolio strategy and allocate decisions to optimize their portfolios. On the other hand, for portfolios managers, who should pay attention to the volatility spillovers between investor sentiment and the Chinese stock market to predict the financial market dynamics during crises periods and hedge their portfolios.

This study attempted to examine the time-varying interactions between the investor's sentiment proxies and the stock market dynamics. Findings showed that the investor's sentiment is considered a prominent channel of shock spillovers during the COVID-19 crisis, which typically confirms the behavioral contagion theory.

The main objective of this paper is to examine the impact of COVID-19 on the tourism flows of eight Asia-Pacific Countries: Australia, Hong Kong, Malaysia, New Zealand, the Philippines, Singapore, Taiwan and Thailand.

Using monthly data from 2019M1 to 2021M10 and 48 origin and eight destination countries in a panel Poisson pseudo-maximum likelihood (PPML) estimation technique and gravity equation framework, this paper finds that after controlling for gravity determinants, COVID-19 periods have a 0.689% lower tourism inflow than in non-COVID-19 periods. The total observations in this paper are 12,138.

A 1% increase in COVID-19 transmission in the origin country leads to a 0.037% decline in tourism flow in the destination country, while the reduction is just 0.011% from the destination. On the mortality side, the corresponding decline in tourism flows from origin countries is 0.030%, whereas it is 0.038% from destination countries. A 1% increase in vaccine intensity in the destination country leads to a 0.10% improvement in tourism flows, whereas vaccinations at the source have no statistically significant effect. The results are also robust at a 1% level in a pooled OLS and random-effects specification for the same model.

The findings provide insights into managing tourism flows concerning transmission, death and vaccination coverage in destination and origin countries.

The COVID-19-induced tourism decline may also be considered another channel through which the global recession has been aggravated. If we convert this decline in terms of loss of GDP, the global figure will be huge, and airline industries will have to cut down many service products for a long time to recover from the COVID-19-induced tourism decline.

It is to be realized by the policymaker and politicians that infectious diseases have no national boundary, and the problem is not local or national. That’s why it is to be faced globally with cooperation from all the countries.

This is the first paper to address tourism disruption due to COVID-19 in eight Asia-Pacific countries using a gravity model framework.

1. Asia-Pacific countries are traditionally globalized through tourism channels

2. This pattern was severely affected by COVID-19 transmission and mortality and improved through vaccination

3. The gravity model can be used to quantify the loss in the tourism sector due to COVID-19 shocks

4. Transmission and mortality should be controlled both at the origin and the destination countries

5. Vaccinations in destination countries significantly raise tourism flows

Asia-Pacific countries are traditionally globalized through tourism channels

This pattern was severely affected by COVID-19 transmission and mortality and improved through vaccination

The gravity model can be used to quantify the loss in the tourism sector due to COVID-19 shocks

Transmission and mortality should be controlled both at the origin and the destination countries

Vaccinations in destination countries significantly raise tourism flows

This chapter explores the gap between social expectations and actual sustainability performance in the business world and identifies the root causes of this discrepancy. The author reviews corporate social responsibility (CSR) and sustainability, and their relationship with the Sustainable Development Goals (SDGs). This chapter also compares the connections and differences between the Millennium Development Goals (MDGs) and the SDGs. The author analyzes possible solutions to bridge the gap, including renewing the social contract between businesses, society and institutions. This involves rethinking the role of businesses and institutions in promoting sustainability and creating new systems and structures that incentivize sustainable practices. This chapter concludes by discussing the pathway to a sustainable and inclusive world through systems innovation and change. When embracing a systems thinking approach, individuals and organizations can identify and address the root causes of unsustainability, and create more resilient and sustainable systems that benefit both people and the planet.

Synergy indicators and social network analysis (SNA), as practical tools, provide the possibility of explaining the pattern of scientific collaboration and visualization of network relations. Recognition of scientific capacities is the basis of synergy. The present study aims to measure and discover the synergistic networks of COVID-19’s top papers at the level of co-authorship, countries, journals, bibliographic couples and titles.

The synergy indicator, co-authorship co-citation network analysis methods were applied. The research population comprises COVID-19’s top papers indexed in Essential Science Indicator and Web of Science Core Collection 2020 and 2021. Excel 2016, UCINET 6.528.0.0 2017, NetDraw, Ravar Matrix, VOSviewer version 1.6.14 and Python 3.9.5 were applied to analyze the data and visualize the networks.

The findings indicate that considering the three possible possibilities for authors, countries and journals, more redundancy and information are created and potential for further cooperation is observed. The synergy of scientific collaboration has revealed that “Wang, Y,” “USA” and “Science of the Total Environment” have the most effective capabilities and results. “Guan (2020b)” and “Zhou (2020)” are bibliographic couplings that have received the most citations. The keywords “CORONAVIRUS DISEASE 2019 (COVID-19)” were the most frequent in article titles.

In a circumstance that the world is suffering from a COVID-19 pandemic and all scientists are conducting various researches to discover vaccines, medicines and new treatment methods, scientometric studies, and analysis of social networks of COVID-19 publications to be able to specify the synergy rate and the scientific collaboration networks, are not only innovative and original but also of great importance and priority; SNA tools along with the synergy indicator is capable of visualizing the complicated and multifaceted pattern of scientific collaboration in COVID-19. As a result, analyses can help identify existing capacities and define a new space for using COVID-19 researchers’ capabilities.

This study investigate the return and volatility spillover among agricultural commodities and emerging stock markets during various crises, including the COVID-19 pandemic and the Russian-Ukrainian war.

This return and volatility spillover is estimated using Diebold and Yilmaz (2012, 2014) approach.

The results reveal the weak connectedness between agricultural commodities and emerging stock markets. Corn and sugar are the highest and lowest transmitters, respectively, whereas soya bean and coffee are the largest and smallest recipients of spillover over time. Most equity indices are the net recipient except for India, China, Indonesia, Argentina and Mexico, during the entire sample period. Most commodities are net transmitters of volatility spillover except coffee and soya bean. At the same time, major equity indices are the net recipient of the volatility spillover except for India, Indonesia, China, Argentina, Malaysia and Korea. In addition, the return and volatility spillover increase during various crises like the COVID-19 pandemic and the Russian-Ukrainian war, but the major increase in spillovers occurs during the COVID-19 pandemic.

The empirical results show a weak relationship between agricultural commodities and emerging stock markets which is helpful for investors and portfolio managers in the construction and reallocation of their portfolios under different periods, most notably under COVID-19 and the Russian-Ukrainian war.

It is an original paper.

This study aims to measure the global research landscape of the National Institute of Pharmaceutical Education and Research (NIPER) of India on a set of quantitative and qualitative metrics in terms of research output toward exploring research trends and give an overview of collaborative practices by researchers of NIPERs.

The present study has selected the Scopus database as a tool to retrieve potential publications of studied NIPERs during the last 12 years (2010–2021). NIPER-Mohali, NIPER-Hyderabad, NIPER-Ahmedabad, NIPER-Guwahati and NIPER-Kolkata have been selected for the study. The study has adopted a comprehensive search strategy to extract 3,926 publications data. VOS viewer 1.6.17, BibExcel and Microsoft Excel were used for data analysis and visualization.

The global scientific research output of NIPERs accrued 3,926 publications with an average of 327 publications per year. The retrieved publications fetched a total of 67,772 citations with an average citation impact of 17.26. There observed a steady growth of publications from 168 to 509 registered with an average growth rate of 18.44%. The mean relative growth rate and doubling time of research output are 0.26 and 2.94. The authorship patterns explore collaborative trends as most of the publications were published by multiple authors (99.39%). NIPERs have expanded their outreach to collaborate with the USA, Malaysia, Saudi Arabia, Australia and the UK to collaborate on research and regulatory reforms exhibits in the USA as a major contributor.

The present study is the first effort to evaluate the global research productivity of NIPERs and assess the current research trends on a set of quantitative and qualitative metrics to provide some insights into the complex dynamics of research productivity. The study’s outcome may help to identify the current research progress of NIPERs at the global level.

COVID-19 is expected to enhance hospitality robotization because frontline robots facilitate social distancing, lowering contagion risk. Investing in frontline robots emerges as a solution to recover customer trust and encourage demand. However, we ignore how customers perceive these initiatives and, therefore, their efficacy. Focusing on robot employment at hotels and on Generation Z customers, this study aims to analyze guests’ perceptions about robots’ COVID-19 prevention efficacy and their impact on booking intentions.

This study tests its hypotheses combining an experimental design methodology with partial least squares. Survey data from 711 Generation Z individuals in Spain were collected in 2 periods of time.

Generation Z customers consider that robots reduce contagion risk at hotels. Robot anthropomorphism increases perceived COVID-19 prevention efficacy, regardless of the context where the robots are used. Robots’ COVID-19 prevention efficacy provokes better attitudes and higher booking intentions.

The sampling method used in this research impedes this study’s results generalization. Further research could replicate this study using random sampling methods to ensure representativeness, even for other generational cohorts.

Employing robots as a COVID-19 prevention measure can enhance demand, especially if robots are human-like. Hoteliers need to communicate that robots can reduce contagion risk, particularly in markets more affected by COVID-19. Robots must be employed in low social presence contexts. Governments could encourage robotization by financially supporting hotels and publicly acknowledging its benefits regarding COVID-19 prevention.

This study combines preventive health, robotics and hospitality literature to study robot implementation during the COVID-19 pandemic, focusing on Generation Z guests – potential facilitators of robot diffusion.