Has COVID-19 Changed Consumers' Satisfiers and Dissatisfiers? Evidence from Online Reviews of 5-Star Hotels in Shanghai and Beijing

Many studies have analyzed the asymmetric relationship between hotel service quality attributes and satisfaction, and tried to find consumers' satisfiers and dissatisfiers, aiming at enhancing satisfaction more efficiently. However, the impact of COVID-19 has led to changes in consumers' expectations for hotel services, and the above findings might face invalidation. To date, we are still unknown whether consumers' satisfiers/dissatisfiers changed. This study fills this research gap by mining online reviews of five-star hotels from Shanghai and Beijing before and during the pandemic. The results found that the asymmetric categories of Sleep quality and Internet/Wi-Fi attributes have changed. Specifically, Sleep quality and Internet/Wi-Fi became dissatisfiers from hybrids, indicating that hoteliers only need to maintain their normal performance, and do not invest too many resources because they bring no satisfaction;attributes like Room, decoration, etc. remain hybrids. Additionally, we performed opinion extraction for the dissatisfier attributes to further understand what causes consumer dissatisfaction. The results contribute to the literature by shedding light on the pandemic's impacts on the asymmetric effects of service quality attributes. The cause analysis can help hoteliers develop specific measures to mitigate the adverse effects of COVID-19.

Investigating asymmetric impacts of total factor energy efficiency on carbon emissions in India.

As many complex energy relations are not linear and have diminishing returns, assuming a symmetric (linear) effect of energy efficiency (ENEF) on carbon emissions (CAE) has limited our understanding of the emission-ENEF nexus. This research, therefore, initially estimates total factor energy efficiency by applying a stochastic frontier technique using sample panels for India encompassing the period from 2000 to 2014. Further, a nonlinear panel autoregressive distributed lag modelling framework is utilised in order to investigate the asymmetric (nonlinear) long- and short-run impacts of ENEF on CAE. The findings demonstrated that ENEF has asymmetric long- and short-run impacts on CAE in India. Based on the outcomes, numerous crucial implications are discussed with a particular reference to developing economies like India.

Asymmetric effects and volatility transmission from metals markets to solar energy stocks: Evidence from DCC, ADCC, and quantile regression approach

Detrimental environmental repercussions have recently given rise to an interest in green investments. Although solar energy stocks are appealing assets for ethical investors, little is known about their dynamic correlations and linkages with metal (silicon, lithium, and rare earth) markets, particularly during economic events which is essential for hedging effectiveness and asset allocation. This study investigates the nexus between metal markets, oil price volatility (OVX), market sentiments (VIX), and solar energy markets using DCC, ADCC models, and the quantile regression approach. The results show both symmetric and asymmetric shock spillover between metals markets, VIX, OVX, and solar energy markets which are more prominent during COVID-19 pandemic, US-China trade frictions, and Russian invasion of Ukraine. For portfolio management, the hedging effectiveness of lithium stocks is highest, followed by silicon and rare earth metals. However, the hedge ratios are time-varying, and the variability is highest during US-China trade frictions. The quantile regression estimates reveal that lithium market is the most persistent determinant of solar energy stocks followed by silicon market even after segregating the periods into Paris Agreement and COVID-19 pandemic. Thus, lithium and silicon are driving markets of solar energy markets and can be a cause of omitted variable bias if stay unobserved. Nonetheless, there is little influence of VIX, rare earth metals, and OVX on solar energy stocks. Lastly, the estimations of threshold regression suggest that market sentiments change the association between metal markets and solar energy markets after the VIX reaches a certain threshold level. © 2023

The dynamics in asymmetric effects of multi-attributes on customer satisfaction: evidence from COVID-19

Purpose: This study aims to explore how the "new normal” induces the dynamics in the asymmetric relationship between service quality attributes and customer satisfaction. Design/methodology/approach: This study analyzes online reviews for hotels in New York City. The authors use multi-attribute models to examine how a situational factor – the COVID-19 outbreak – creates dynamics in the asymmetric effect of service quality attributes on customer satisfaction. Then, the authors examine the change in these dynamics over time after adjusting to the "new normal.” Findings: The COVID-19 pandemic has introduced dynamics into the asymmetrical relationship between hotel service attribute performances and customer satisfaction. The pandemic magnified the asymmetric influences of particular attributes on satisfaction in the hospitality industry. In addition, the findings indicate the changes in such dynamics over time. Practical implications: The findings emphasize that hotel managers should consider situational factors when understanding customer satisfaction. Particularly, this study suggests developing tailored strategies for responses during the COVID-19 pandemic. Hotel managers need to address changing customer expectations of service attributes to overcome unprecedented difficulties because of the limitations and new needs imposed during the pandemic. Originality/value: This study contributes to the hospitality literature with an understanding of the significance of situational factors in asymmetric analysis. © 2023, Emerald Publishing Limited.

Hedging effectiveness of cryptocurrencies in the European stock market

The aim of the paper is twofold: first, to examine the hedging effectiveness of cryptocurrencies and cryptocurrency portfolios for European equities in bearish and bullish market conditions, and second, to contrast cryptocurrencies with gold as a safe haven asset. To this end, daily data from 2018 to 2022 were employed in a linear and nonlinear Autoregressive Distributed Lag (ARDL) framework. The findings have significant implications for investors, financial intermediaries and regulators. © 2023 Elsevier B.V.

Online learning attributes on overall tourism and hospitality education learning satisfaction: Tourism Agenda 2030

PurposePromoting "Quality Education” as part of Sustainable Development Goal 4 requires educational stakeholders to understand the nature of online learning from the learners' perspective. This study aims to explore the asymmetric effects of online learning attributes on overall learning satisfaction in tourism and hospitality education.Design/methodology/approachThe authors adopt the three-factor satisfaction theory and the three analytical steps penalty–reward contrast analysis, impact range performance analysis (IRPA) and impact asymmetry analysis. The authors then juxtapose the results of such analytical approaches to the traditional importance–performance analysis (IPA) for further insights.FindingsTraditional IPA suggests nine high importance and performance online attributes. However, the IRPA reveals that only four attributes fall within high performance and high range of impact on satisfaction. The attribute "secure” had a low performance despite a significant impact on satisfaction.Research limitations/implicationsBy exploring asymmetric effects, scholars, service providers and participants of online education can have a deeper insight into the nature and dynamic effect of attributes on overall satisfaction.Originality/valueBy exploring the asymmetric impacts of online learning attributes on overall learning satisfaction, the findings provide a novel insight into the multidimensionality of online learning attributes.

Estimating the link between trade uncertainty, pandemic uncertainty and food price stability in Togo: New evidence for an asymmetric analysis

Globally, the outbreak of COVID‐19 and the associated containment measures adopted by governments are causing disruptions that sow uncertainty in several sectors of the economy. In this study, we explore the asymmetric impact of pandemic uncertainty and global trade policy on food prices in Togo. The study uses a nonlinear autoregressive distributive lag (NARDL) framework and causality tests for the period 2000 M1–2021 M5. The results show that the different types of uncertainty affect food price stability in the short and long run, but the shock is more pronounced in the case of pandemic uncertainty, as they are sudden and disrupt food price stability. The main findings remain significant when we use various alternative methods and estimation techniques. However, our results suggest that the Togolese food market is facing pandemic uncertainty and trade policy, which should lead policymakers and stakeholders to take corrective measures to control losses.

Estimating the link between trade uncertainty, pandemic uncertainty and food price stability in Togo: New evidence for an asymmetric analysis

Globally, the outbreak of COVID-19 and the associated containment measures adopted by governments are causing disruptions that sow uncertainty in several sectors of the economy. In this study, we explore the asymmetric impact of pandemic uncertainty and global trade policy on food prices in Togo. The study uses a nonlinear autoregressive distributive lag (NARDL) framework and causality tests for the period 2000 M1-2021 M5. The results show that the different types of uncertainty affect food price stability in the short and long run, but the shock is more pronounced in the case of pandemic uncertainty, as they are sudden and disrupt food price stability. The main findings remain significant when we use various alternative methods and estimation techniques. However, our results suggest that the Togolese food market is facing pandemic uncertainty and trade policy, which should lead policymakers and stakeholders to take corrective measures to control losses.

Online learning attributes on overall tourism and hospitality education learning satisfaction: Tourism Agenda 2030

PurposePromoting "Quality Education" as part of Sustainable Development Goal 4 requires educational stakeholders to understand the nature of online learning from the learners' perspective. This study aims to explore the asymmetric effects of online learning attributes on overall learning satisfaction in tourism and hospitality education. Design/methodology/approachThe authors adopt the three-factor satisfaction theory and the three analytical steps penalty-reward contrast analysis, impact range performance analysis (IRPA) and impact asymmetry analysis. The authors then juxtapose the results of such analytical approaches to the traditional importance-performance analysis (IPA) for further insights. FindingsTraditional IPA suggests nine high importance and performance online attributes. However, the IRPA reveals that only four attributes fall within high performance and high range of impact on satisfaction. The attribute "secure" had a low performance despite a significant impact on satisfaction. Research limitations/implicationsBy exploring asymmetric effects, scholars, service providers and participants of online education can have a deeper insight into the nature and dynamic effect of attributes on overall satisfaction. Originality/valueBy exploring the asymmetric impacts of online learning attributes on overall learning satisfaction, the findings provide a novel insight into the multidimensionality of online learning attributes.

Exchange rate volatility and trade flows in Indonesia and ten main trade partners: asymmetric effects

Purpose This paper aims to examine whether Indonesian cross-border trade responds asymmetrically to exchange rate volatility (ERV). Design/methodology/approach An exponential generalized autorgressive conditional heteroscedasticity model is applied to estimate the ERV of Indonesia and ten main trade partners using quarterly data from 2006 to 2020. A nonlinear autoregressive distributed lag estimation is applied to estimate the impact of ERV on cross-border trade. Impacts from the global financial crisis (GFC) of 2008 and the COVID-19 pandemic are covered. Dynamic panel data is used for the robustness test. Findings In the short-run, ERV significantly affects exports to most of the top partners (positively, negatively or both). In the long run, asymmetric effects occur in Indonesia's exports to five top destinations. The weakening of the Indonesian Rupiah mainly supports exports in the short term. Imports from top partners are also affected by ERV in both the short run and, to a lesser extent, in the long run. Both the GFC and the COVID-19 pandemic reduced trade: for most cases, in the short run. The dynamic panel model suggests that ERV has asymmetric impact on cross-border trade in the long run. Practical implications Exchange rate strategies need to avoid a single-side policy approach and, instead, account for exporter and importer differences in risk behaviour and an asymmetric response to ERV in trade. Policymakers need to consider policies that stabilise the currency. Originality/value This study provides evidence that cross-border trade can react asymmetrically to the exchange rate uncertainty and that the impacts of real ERV are asymmetric as well. The authors also apply a dynamic panel that signals that ERV matters in the long run for Indonesian trade with top partners.

Asymmetrical relationship between COVID-19 global fear index and agricultural commodity prices

Grains and oilseed crops are widely used as key input elements for global food safety in food and livestock sub-sectors, as well as in other sectors such as energy, services and industry. In addition, they play an active role in the international agricultural markets. Therefore, price structure in the grain and oilseed market is important for agriculture and many other sectors. This study was designed to reveal how the fear of COVID-19 has globally affected grain prices. The study covered the one-year period from March 11, 2020, when COVID-19 was first recognized as a pandemic, to March 11, 2021. The Global Fear Index (GFI) and the price sub-indices created by the Grain Oil Council were used to determine the impact of the fear caused by COVID-19 on grain prices. Assuming an asymmetrical relationship between variables, the Nonlinear Autoregressive Distributed Lag model was used to determine this relationship. According to the model results, it was found that in the long term, agricultural commodity prices gave an increase (decrease) response to the positive (negative) effects in the GFI, and that the effect of an increase in the GFI on agricultural commodity prices was greater than the effect of a decrease. Accordingly, it is thought that the analysis and predictions which take into account the asymmetrical effect would give more realistic results and thus contribute considerably to the market regulations. It will also help policymakers make more rational decisions in their search for solutions to the problems in the cereal market. © 2022

Asymmetric effects of fine particulate matter and stringency policy on COVID-19 intensity.

This study aims to examine the influence of environmental performance (PM2.5) on COVID-19 intensity . For this purpose, we employ the newly introduced Hidden Panel Cointegration test and Nonlinear Panel Autoregressive Distributed Lag model. Results indicate the asymmetric linkages between PM2.5 and COVID-19 intensity, as the positive shock in PM2.5 raises the COVID-19 intensity by 21%, whereas the negative shock in PM2.5 decreases COVID-19 intensity by 12% in long-run. On the contrary, the positive shock in stringency measures decreases COVID-19 intensity by 42.8%, while the negative shock in stringency policy increases COVID-19 intensity by 66.7%. These findings imply that higher pollution increases the COVID-19 severity while higher stringency measures slow down people's movement and reduce COVID-19 intensity. However, a sudden negative shock in lockdown increases people's interaction, leading to a higher spread of the virus. These results suggest that governments should adopt stringent action plans to contain the transmissibility of COVID-19.

The asymmetric nexus between air pollution and COVID-19: Evidence from a non-linear panel autoregressive distributed lag model.

The emergence of a new coronavirus (COVID-19) has become a major global concern that has damaged human health and disturbing environmental quality. Some researchers have identified a positive relationship between air pollution (fine particulate matter PM2.5) and COVID-19. Nonetheless, no inclusive investigation has comprehensively examined this relationship for a tropical climate such as India. This study aims to address this knowledge gap by investigating the nexus between air pollution and COVID-19 in the ten most affected Indian states using daily observations from 9th March to September 20, 2020. The study has used the newly developed Hidden Panel Cointegration test and Nonlinear Panel Autoregressive Distributed Lag (NPARDL) model for asymmetric analysis. Empirical results illustrate an asymmetric relationship between PM2.5 and COVID-19 cases. More precisely, a 1% change in the positive shocks of PM2.5 increases the COVID-19 cases by 0.439%. Besides, the estimates of individual states expose the heterogeneous effects of PM2.5 on COVID-19. The asymmetric causality test of Hatemi-J's (2011) also suggests that the positive shocks on PM2.5 Granger-cause positive shocks on COVID19 cases. Research findings indicate that air pollution is the root cause of this outbreak; thus, the government should recognize this channel and implement robust policy guidelines to control the spread of environmental pollution.

Asymmetric risk transfer in global equity markets: An extended sample that includes the COVID pandemic period

This paper studies risk transmissions in six global markets: the US, Japan, Canada, Germany, the UK, and France. The paper distinguishes between the good volatility from increases in intra-day prices and the bad volatility that arises from intra-day price declines. Our results indicate persistent and uniform asymmetries in the information transmission mechanism: the bad volatility spillovers in the system are higher than the spillovers of good volatility. These pronounced asymmetries are countercyclical because they strengthen after the interest rate declines and weaken after it rises. Finally, there are clear bursts in risk transfer and asymmetries during the times of the global financial crisis and the COVID pandemic crisis. These findings have important implications for risk forecasting, asset pricing, and portfolio diversification.