The COVID-19 state sales tax windfall.

Policymakers were surprised to find increases in sales tax revenues in 2020 due to expectations that they would drop 8-20%. We investigate this puzzle and provide novel insights into consumption taxes based on this experience. Using a case study from the State of Utah, we document that shifts in the structure of consumption played a significant role in the robustness of sales tax revenue. Two factors stand out in our results. The first factor is the structure of the tax base for sales taxes in the USA. This tax base covers only a subset of personal consumption, excluding, for example, many services. During the pandemic, when services were restricted or shut down, this caused a shift in spending toward goods that are more likely to be in the sales tax base. The second factor is the boom in e-commerce during the pandemic, which boosted sales tax collections. This was catalyzed by recent legal changes that made the collection of sales taxes in e-commerce easier. Interestingly, this e-commerce boost also shifted the point of sale and related sales tax revenues away from urban areas toward suburban areas. Our case study of the pandemic's effect on sales taxes in the USA generally, and Utah's experience specifically, provides lessons for consumption taxes, such as the VAT more broadly, and lessons on the role of consumption taxes for tax revenue volatility.

The COVID-19 state sales tax windfall

Policymakers were surprised to find increases in sales tax revenues in 2020 due to expectations that they would drop 8–20%. We investigate this puzzle and provide novel insights into consumption taxes based on this experience. Using a case study from the State of Utah, we document that shifts in the structure of consumption played a significant role in the robustness of sales tax revenue. Two factors stand out in our results. The first factor is the structure of the tax base for sales taxes in the USA. This tax base covers only a subset of personal consumption, excluding, for example, many services. During the pandemic, when services were restricted or shut down, this caused a shift in spending toward goods that are more likely to be in the sales tax base. The second factor is the boom in e-commerce during the pandemic, which boosted sales tax collections. This was catalyzed by recent legal changes that made the collection of sales taxes in e-commerce easier. Interestingly, this e-commerce boost also shifted the point of sale and related sales tax revenues away from urban areas toward suburban areas. Our case study of the pandemic's effect on sales taxes in the USA generally, and Utah's experience specifically, provides lessons for consumption taxes, such as the VAT more broadly, and lessons on the role of consumption taxes for tax revenue volatility.

Exploring the Over-Time Variation in Customer Concerns on Sharing Economy Services

The sharing economy represented by Airbnb has evolved rapidly. It is particularly important to identify and understand how consumer concerns change over time. As a result, this study employs structural topic modelling using room type and time as covariates to extract topics from 896,658 Airbnb reviews in London and to observe the variation in the prevalence of topics over time. The findings show that the topic proportion changed relatively sharply in the early years of Airbnb (2010-2013) and during the COVID-19 pandemic (2020-2022), but relatively smoothly in the middle period (2014-2019). This research also discovered that the proportion of topics on customers' special experiences has been decreasing while the proportion of topics on their overall experience has been increasing. This shift could be attributed to an increase in the number of professional hosts, which has accelerated the standardisation of the Airbnb service.

Revealing industry challenge and business response to covid-19: A text mining approach

Purpose: This study aims to conduct a "real-time" investigation with user-generated content on Twitter to reveal industry challenges and business responses to the coronavirus (Covid-19) pandemic. Specifically, using the hospitality industry as an example, the study analyses how Covid-19 has impacted the industry, what are the challenges and how the industry has responded. Design/methodology/approach: With 94,340 tweets collected between October 2019 and May 2020 by a programmed Web scraper, unsupervised machine learning approaches such as structural topic modelling are applied. Originality/value: This study contributes to the literature on business response during crises providing for the first time a study of using unstructured content on social media for industry-level analysis in the hospitality context. (PsycInfo Database Record (c) 2023 APA, all rights reserved)

Is negative e-WOM more powerful? Multimodal data analysis on air passengers’ perception of COVID-19 safety measures

During the normalization stage of the COVID-19 epidemic prevention and control, the safety threats caused by improper epidemic prevention measures of airlines have become the primary concern for air passengers. Negative e-WOM related to safety perception obtained based on online multimodal reviews of travel websites has become an important decision-making basis for potential air passengers when making airline choices. This study aims to examine the relationship between potential air passengers’ negative safety perception and the usefulness of online reviews, as well as to test the moderating effect of review modality and airline type. It also further explores the effectiveness and feasibility of applying big data sentiment analysis to e-WOM management. To this end, the theoretical model of negative safety perception, review modality, and airline type affecting review usefulness was constructed. Then we select 10 low-cost airlines and 10 full-service airlines, respectively, according to the number of reviews sorted by the TripAdvisor website, and use crawling techniques to obtain 10,485 reviews related to COVID-19 safety of the above companies from December 2019 to date, and conduct safety perception sentiment analysis based on Python’s Textblob library. Finally, to avoid data overdispersion, the model is empirically analyzed by negative binomial regression using R software. The results indicate that (1) Negative safety perception significantly and negatively affects review usefulness, that is, extreme negative safety perception can provide higher review usefulness for potential air passengers. (2) Review modality and airline type have a significant moderating effect on the relationship between negative safety perception and review usefulness, in which multimodal reviews and full-service airlines both weakened the negative impact of negative safety perception on review usefulness. The theoretical model in this paper is both an extension of the application of big data sentiment analysis techniques and a beneficial supplement to current research findings of e-WOM, providing an important reference for potential air passengers to identify useful reviews accurately and thus reduce safety risks in online decision-making.

Probability-Based Estimates of Severe Acute Respiratory Syndrome Coronavirus 2 Seroprevalence and Detection Fraction, Utah, USA.

We aimed to generate an unbiased estimate of the incidence of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection in 4 urban counties in Utah, USA. We used a multistage sampling design to randomly select community-representative participants >12 years of age. During May 4-June 30, 2020, we collected serum samples and survey responses from 8,108 persons belonging to 5,125 households. We used a qualitative chemiluminescent microparticle immunoassay to detect SARS-CoV-2 IgG in serum samples. We estimated the overall seroprevalence to be 0.8%. The estimated seroprevalence-to-case count ratio was 2.5, corresponding to a detection fraction of 40%. Only 0.2% of participants from whom we collected nasopharyngeal swab samples had SARS-CoV-2-positive reverse transcription PCR results. SARS-CoV-2 antibody prevalence during the study was low, and prevalence of PCR-positive cases was even lower. The comparatively high SARS-CoV-2 detection rate (40%) demonstrates the effectiveness of Utah's testing strategy and public health response.

Do news media and citizens have the same agenda on COVID-19? an empirical comparison of twitter posts.

This study analyses the agenda setting on social media in the COVID-19 pandemic by exploiting one of the disruptive technologies, big data analytics. Our purpose is to examine whether the agenda of news organisations matches the public agenda on social media in crisis situations, and to explore the feasibility and efficacy of applying big data analytics on social media data. To this end, we used an unsupervised machine learning approach, structural topic modelling and analysed 129,965 tweets posted by UK news media and citizens during April 2, and 8, 2020. Our study reveals a wide diversity of topics in the tweets generated by both groups and finds only a small number of topics are similar, indicating different agendas set in the pandemic. Moreover, we show that citizen tweets focused more on expressing feelings and sharing personal activities while news media tweets talked more about facts and analysis on COVID-19. In addition, our results find that citizens responded more significantly to breaking news. The findings of the study contribute to the agenda setting literature and offer valuable practical implications.

Revealing industry challenge and business response to Covid-19: a text mining approach

PurposeThis study aims to conduct a “real-time” investigation with user-generated content on Twitter to reveal industry challenges and business responses to the coronavirus (Covid-19) pandemic. Specifically, using the hospitality industry as an example, the study analyses how Covid-19 has impacted the industry, what are the challenges and how the industry has responded.Design/methodology/approachWith 94,340 tweets collected between October 2019 and May 2020 by a programmed Web scraper, unsupervised machine learning approaches such as structural topic modelling are applied.Originality/valueThis study contributes to the literature on business response during crises providing for the first time a study of using unstructured content on social media for industry-level analysis in the hospitality context.

Global COVID-19 pandemic demands joint interventions for the suppression of future waves.

Emerging evidence suggests a resurgence of COVID-19 in the coming years. It is thus critical to optimize emergency response planning from a broad, integrated perspective. We developed a mathematical model incorporating climate-driven variation in community transmissions and movement-modulated spatial diffusions of COVID-19 into various intervention scenarios. We find that an intensive 8-wk intervention targeting the reduction of local transmissibility and international travel is efficient and effective. Practically, we suggest a tiered implementation of this strategy where interventions are first implemented at locations in what we call the Global Intervention Hub, followed by timely interventions in secondary high-risk locations. We argue that thinking globally, categorizing locations in a hub-and-spoke intervention network, and acting locally, applying interventions at high-risk areas, is a functional strategy to avert the tremendous burden that would otherwise be placed on public health and society.

Focus on Characteristics of COVID-19 with the Special Reference to the Impact of COVID-19 on the Urogenital System.

Coronavirus disease 2019 (COVID-19) is a new infectious disease that first emerged in December 2019. It has infected more than 4,890,000 people in more than 200 countries. This virus can cause progressive respiratory symptoms and severe diseases such as organ failure and death. The complete genomic sequence of SARS-CoV-2 was determined after the virus's identification, and the sequence analysis showed that SARS-CoV-2 strains are genetically similar to SARS-CoV. Angiotensin converting enzyme II is an entry receptor for SARS-CoV-2, which is highly expressed in the kidney, so some patients had symptoms of kidney damage. Here we reviewed the current progress of COVID-19 and its urogenital manifestations. In this rapidly moving field, this review was comprehensive as of May 30, 2020.