Can tourism development and economic growth mutually reinforce in small countries? Evidence from Singapore

This study investigates the causal relationships between international tourism development and the economic growth of a global city-state - Singapore - drilling into the temporal details of the tourism-economy nexus in small countries. Many studies have examined whether the tourism-led growth hypothesis or the economy driven-tourism growth hypothesis holds in large developed and emerging countries. Still, relatively few studies examine small countries' tourism-economy nexus, and the temporal details of the nexus have not been adequately examined. We examine the tourism-economy nexus in Singapore using quarterly data from 1991Q1 to 2020Q4 and the Autoregressive Distributed Lag (ARDL) Model, with the long- and short-run dynamics and the feedback loop of the nexus considered. Our statistical findings show that international tourism development leads economic growth by two quarters in Singapore. Also, there are both 'consistent' and 'contemporaneous' positive feedback loops between tourism development and economic growth, but those loops cannot last for more than a quarter. From the economic perspective, our study reveals that improving tourism activities may accelerate the post-Covid economic recovery of some small countries that rely on tourism. Yet, continuous input is required to sustain the tourism-economy synergy.

On the Volatility and Market Inefficiency of Bitcoin During the COVID-19 Pandemic

The COVID-19 pandemic has been causing unprecedented economic downturn worldwide. As it wreaks havoc on every aspect of global economic activities, stakeholders are wondering how its impact can be quantified to craft viable responses. In the exotic field of cryptocurrencies, prior to the pandemic, everyone was excited about Bitcoin and its multitude of potentials. However, a day after COVID-19 was officially announced by the World Health Organization as a pandemic, the rate of return to Bitcoin dropped by an unheard-of one-day decline of-46.5%, and people started to rethink the prospects of Bitcoin. A day after this steep decline, Bitcoin recovered and started a sustained bull run which lasted for almost a year and even posted an all-time high daily uptick of 59.6%. By the end of July 2021, the price reached its all-time high but lost more than half of it at the end of the sample period. This study aims to empirically analyze the risk-return profile and the market efficiency of Bitcoin utilizing a 1,306-day data set conveniently subdivided into pre-pandemic and pandemic periods. The general conclusion of the study is: During the pandemic, Bitcoin is extremely volatile and does not subscribe to the efficient market hypothesis. © 2023 by De La Salle University.

Influence of Transformational Leadership on Organizational Citizenship Behavior and Organizational Task Performance Cross Level Analysis on Micro Small and Medium Enterprises in Indonesia: Acces la Success

In industry 4.0, individual behavior in organization is still very much considered as the main determinant of organizational performance. Organizational citizenship behavior (OCB) is one of the unique behavior of individuals affecting the effectivity of the organization. This study focuses on organizational citizenship behavior (OCB) based on the aspects of antecedents and their consequences. This study aims at examining (1) the indirect influence of transformational leadership on individual performance through organizational citizenship behavior motivation (OCBM) and OCB, (2) the direct influence of OCB on individual performance and organizational performance, (3) the direct influence of OCB for individual performance and organizational performance. This study was conducted to 66 heads of small business and 410 employee at small business in West Sumatera and analyzed using cross level methods and hypothesis testing using hierarchical linear modeling (HLM). This study found that 1). OCBM and OCB simultaneously mediate the relation between transformational leadership with individual performance and also have role in elevating the individual performance, 2) individual performance is the mediator between OCBM with organizational performance and it contributes in elevating the organizational performance. The theoretical and practical implications of this study are the tranformational leadership (TL) is able to motivate the members to carry out OCB actively in organizations. Some limitations and future research directions are discussed.

If and to What Extent Does Organizational Learning Culture Predict Turnover Intentions of Telecommuting Call Center Agents?

This study focuses on measuring the relationship between organizational learning culture (OLC) and turnover intentions of telecommuting call center agents. Although many studies involve the call center industry from different perspectives, the literature is scant in studies that have assessed the relationship between OLC and turnover intent in telecommuting call center agents. Call centers exist in almost every organization worldwide. Organizations have centralized their customer service process through computerbased technologies allowing call center agents to work from home. In addition, in the post-COVID-19 era, telecommuting has become a permanent option for many call center employees. Indeed, in the call center industry, telecommuting has become an essential part of the business strategy that seeks to attract new and maintain current employees. In the call center industry, learning is a factor that influences job satisfaction and turnover intentions. Specifically, OLC increases job satisfaction and performance in telecommuting call center agents, influencing employees' turnover intentions. The study 's findings indicate that OLC is a needed factor that helps lower turnover intentions of telecommuting call center agents in the United States.

Pandemic Highlights Urgency for New Methodologies for Evidence Generation

Randomized controlled trials, which many consider to be the gold standard of clinical research, were developed in the 1940s. [...]individual patients in the real world react often very differently to a specific drug than what has been predicted by the "mean" of a clinical trial. Many biopharmaceutical companies and AI startups are betting that with enough data, these methods will work so well that they will help to accelerate the discovery of new therapies for the novel corona virus, 2019-nCoV (see go.nature.com/3aLd0ll). * Causal AI methods might be uniquely positioned to discover underlying causes of disease and clinical response to treatment on an individual level, making personalized medicine real.

Identifying Safety Subgroups at Risk: Assessing the Agreement Between Statistical Alerting and Patient Subgroup Risk: An International Journal of Medical Toxicology and Drug Experience

Introduction Identifying individual characteristics or underlying conditions linked to adverse drug reactions (ADRs) can help optimise the benefit-risk ratio for individuals. A systematic evaluation of statistical methods to identify subgroups potentially at risk using spontaneous ADR report datasets is lacking. Objectives In this study, we aimed to assess concordance between subgroup disproportionality scores and European Medicines Agency Pharmacovigilance Risk Assessment Committee (PRAC) discussions of potential subgroup risk. Methods The subgroup disproportionality method described by Sandberg et al., and variants, were applied to statistically screen for subgroups at potential increased risk of ADRs, using data from the US FDA Adverse Event Reporting System (FAERS) cumulative from 2004 to quarter 2 2021. The reference set used to assess concordance was manually extracted from PRAC minutes from 2015 to 2019. Mentions of subgroups presenting potential differentiated risk and overlapping with the Sandberg method were included. Results Twenty-seven PRAC subgroup examples representing 1719 subgroup drug-event combinations (DECs) in FAERS were included. Using the Sandberg methodology, 2 of the 27 could be detected (one for age and one for sex). No subgroup examples for pregnancy and underlying condition were detected. With a methodological variant, 14 of 27 examples could be detected. Conclusions We observed low concordance between subgroup disproportionality scores and PRAC discussions of potential subgroup risk. Subgroup analyses performed better for age and sex, while for covariates not well-captured in FAERS, such as underlying condition and pregnancy, additional data sources should be considered.

Fitting Percentage of Body Fat to Simple Body Measurements: College Women

Percentage of body fat, age, weight, height, and 14 circumference measurements (e.g., waist) are given for 184 women aged 18–25. Body fat, one measure of health, was accurately determined by an underwater weighing technique which requires special equipment and training of the individuals conducting the process. Modeling body fat percentage using multiple regression provides a convenient method of estimating body fat percentage using measures collected using only a measuring tape and a scale. This dataset can be used to show students the utility of multiple regression and to provide practice in model building.

Industry Structure of Commercial Districts and the Impact of COVID-19

This paper aims to empirically analyze the difference in the closure rate of the commercial district according to the industry structure of the commercial district. Theoretically, the larger the number of stores in a commercial district, the greater the positive externality caused by the agglomeration economies in consumption, namely, the external economies of scale. However, the agglomeration economies could occur from comparison shopping or one-stop shopping, depending on the business structure of the commercial district. According to the empirical results of the regression analysis of all 1164 commercial districts in Korea, the more specialized a commercial district is by stores in a specific industry, the lower the closure rate of that commercial district. This means that the agglomeration economies in consumption are driven by comparison shopping rather than by one-stop shopping and implies that it is necessary to introduce incentives that allow stores in the same industry to cluster together in terms of policy. Meanwhile, if the closure is limited to a specific industry, it will cause an endogeneity problem since it affects the industry structure of the commercial district. Considering this, as a result of additional estimation by 2SLS and GMM using instrumental variables, the error in estimation due to the endogeneity problem was not large, confirming that COVID-19 corresponds to an overall external shock that is not limited to a specific industry. In addition, this paper presents diagnostic indicators for commercial districts to measure the impact of COVID-19. Through this, it will be possible to alleviate conflicts between social classes over compensation or subsidies for sanctions for quarantine. To the best of our knowledge, it is the first time to use all commercial districts in Korea for a research in evaluating the impact of COVID-19, and empirical results on agglomeration economies focusing on the consumption side are limited.

Íkiz Açık Hipotezi Türkiye'de Geçerliliği: Zamanla Değişen Nedensellik Analizi

Finansal ve ekonomik istikrarın sürdürülebilirliği açısından iç ve dış dengenin birlikte sağlandığı maliye politikalarının uygulanması son derece önem arz etmektedir. Bu nedenle, cari işlemler ile bütçe açıkları arasındaki ilişkinin incelenmesi politika yapıcılar, araştırmacılar ve ekonomistler arasında tartışılan önemli konulardan biri haline gelmiştir. Bu kapsamda, çalışmada Türkiye için Ocak 1998 – Aralık 2021 döneminde ikiz açık hipotezi, Granger nedenselliğin geçici istikrarını yeniden değerlendirmek amacıyla kullanılan yinelemeli algoritmalar kullanılarak araştırılmaktadır. Zamanla değişen Granger nedensellik analizden elde edilen bulgular, Türkiye'de ele alınan dönemde cari işlemler dengesi ve bütçe açığı arasında çift yönlü bir nedensellik ilişkisi olduğunu ortaya koymaktadır. Bu sonuç, Türkiye'de ikiz açık hipotezinin geçerli olduğunu ifade etmektedir. Aynı zamanda, nedensellik ilişkisinde anlamlı geçici değişimlerin olduğu gözlenmektedir. Seçim ve kriz dönemlerinde ikiz açık hipotezinin varlığı mevcut iken, 2002-2008 ve 2015-2021 dönemlerinde cari işlemler hedeflemesi politikası uygulanmaktadır. COVID-19 pandemisi döneminde ise, cari işlemler dengesi ve bütçe açığı arasında çift yönlü asimetrik aktarım mekanizmasının işlediği ifade edilebilir.Alternate :Implementing fiscal policies to ensure domestic and foreign balances together is of vital importance to sustain financial and economic stability. Therefore, investigating the relationship between budget deficit and current account deficit is one of the issues debated by popolicymakersnd economists. In this context, the existence of the win deficit hypothesis in Turkey is researched through recursive algorithms used to revaluate the temporal stability of Granger causality for the periods of January 1998-December 2021. The findings from time-varying Granger causality analysis reveal the existence of a bidirectional causality relationship between budget deficit and current account deficit. This result means the validity of the twin deficit hypothesis in Turkey. Also, the temporal changes in the so-called casualty relationships are observed significantly. During the electoral and crisis periods there is the existence of the twin deficit hypothesis wthe hileaccountnt acount targeting policy is implemented during the periods of 2002-2008 and 2015-2021. In the COVID-19 period, a bidirectional asymmetric transmission mechanism between budget deficit andcurrentt account deficit is worked can be stated.

Research on the physical health changes of college students during the new crown epidemic based on big data analysis technology

Multiple comparisons are general term for hypothesis testing of whether there is a significant difference between the means of each sample after analysis of variance. ANOVA can only determine whether there is a difference between the population means, and multiple comparisons can further test the differences between the sample means. This study will select the LSD (Least significant difference) test method in the multiple comparison method to conduct a differential test on the physical fitness test data of four different grades from 2018 to 2021 since the COVID-19 epidemic, and analyze the physical fitness of Chinese students under the background of new coronavirus epidemic. Change characteristics of health level, and summarize relevant experience, urge relevant personnel to make targeted improvements to the future work of students' physical health training, and scientifically improve the physical health level of Chinese students. © 2023 SPIE.

Environmental regulation and corporate financialization: insight from Blue Sky Protection Campaign in China.

Environmental regulation restricts corporate pollution emissions and affects corporate investment decisions and asset allocation. Based on the data of A-share listed enterprises in China from 2013 to 2021 and the difference in differences (DID) model, this paper identifies the impact of environmental regulation on corporate financialization with the help of the "Blue Sky Protection Campaign (2018-2020)" (BSPC) of China. The results indicate that environmental regulation has a crowding-out effect on corporate financialization. Enterprises with stricter financing constraints receive more significant crowding-out effects. This paper provides a new perspective on the "Porter hypothesis." Under the constraint of financial resources and high environmental protection costs, enterprises carry out innovative activities and environmental protection investments by consuming financial assets to reduce the risk of environmental violations. The government's environmental regulation is an effective way to guide the financial development of enterprises, control environmental pollution, and promote enterprise innovation.

Robotic Chef Versus Human Chef: The Effects of Anthropomorphism, Novel Cues, and Cooking Difficulty Level on Food Quality Prediction.

Robots have been increasingly common in hospitality and tourism, especially being favored under the threat of COVID-19. However, people generally do not think robots are appropriate for cooking food in hotels and restaurants, possibly because they hold low quality predictions for robot-cooked food. This study aimed to investigate the factors influencing people's quality prediction for robot-cooked food. In three experiments, participants viewed pictures of human and robotic chefs and dishes cooked by them, and then made food quality predictions and rated their perceptions of the chefs. The results showed that participants predicted the foods cooked by robotic chefs were above average quality; however, they consistently held lower food quality prediction for robotic chefs than human chefs, regardless of dishes' cooking difficulty level, novel cues in chefs and food, or the anthropomorphism level of robotic chefs. The results also showed that increasing the appearance of robotic chefs from low or medium to high anthropomorphism, or enabling robotic chefs to cook high cooking difficulty level food could promote food quality prediction. These results revealed the current acceptance of robot-cooked food, suggesting possible ways to improve food quality predictions.

The impact of pandemic mental cognition on cultural values: an empirical study based on social media.

BACKGROUND: COVID-19 has triggered a global public health crisis, and had an impact on economies, societies, and politics around the world. Based on the pathogen prevalence hypothesis suggested that residents of areas with higher infection rates are more likely to be collectivists as compared with those of areas with lower infection rates. Many researchers had studied the direct link between infectious diseases and individualism/collectivism (infectious diseases→ cultural values), but no one has focused on the specific psychological factors between them: (infectious diseases→ cognition of the pandemic→ cultural values). To test and develop the pathogen prevalence hypothesis, we introduced pandemic mental cognition and conducted an empirical study on social media (Chinese Sina Weibo), hoping to explore the psychological reasons behind in cultural value changes in the context of a pandemic. METHODS: We downloaded all posts from active Sina Weibo users in Dalian during the pandemic period (January 2020 to May 2022) and used dictionary-based approaches to calculate frequency of words from two domains (pandemic mental cognition and collectivism/individualism), respectively. Then we used the multiple log-linear regression analysis method to establish the relationship between pandemic mental cognition and collectivism/individualism. RESULTS: Among three dimensions of pandemic mental cognition, only the sense of uncertainty had a significant positive relationship with collectivism, and also had a marginal significant positive relationship with individualism. There was a significant positive correlation between the first-order lag term AR(1) and individualism, which means the individualism tendency was mainly affected by its previous level. CONCLUSIONS: The study found that more collectivist regions are associated with a higher pathogen burden, and recognized the sense of uncertainty as its underlying cause. Results of this study validated and further developed the pathogen stress hypothesis in the context of the COVID-19 pandemic.

Stock return anomalies identification during the Covid-19 with the application of a grouped multiple comparison procedure.

This study investigates the impact of COVID-19 pandemic on the Chinese stock market in 2020. Using daily data of three industries, this study addresses the identification of abnormal stock returns as a multiple hypothesis testing problem and proposes to apply a grouped comparison procedure for better detection. By comparing the numbers of daily signals and numbers of stocks with abnormal positive and negative returns, the empirical result shows that the three industries perform differently under the pandemic. Compared to the non-grouped testing procedure, the signals found by the grouped procedure are more prominent, which is advantageous for some situations when there tends to be abnormal performance clustering at the occurrence of major event. This paper on stock return anomalies gives a new perspective on the impact of major events to the stock market, like the global outbreak disease.

Institutional Environment and Tourism: Moderating Role of Host Countries' Health System

Tourism has gradually emerged to become a significant factor for sustainable economic growth around the globe. Along with other variables, the institutional environment has a significant influence on the growth of the tourism industry. Consequently, there are two primary goals for this study: firstly, to improve the body of knowledge already available on the institution-tourism nexus;secondly, to investigate how the health systems of the host countries contribute to the said nexus. To analyze these relations, we collected data from 50 countries across 10 years (2009-2018). We apply multiple regression analysis to a balanced panel dataset of 500 observations. Furthermore, we also used an interactive variable in conjunction with the primary independent, dependent, and control variables of the study to determine the moderating effect of the host countries' health systems. The study's findings demonstrated the significance of an efficient institutional structure in boosting tourism. Additionally, the health systems of the host nations play a significant role in strengthening the connection between institutions and tourism, especially in the post-COVID-19 period. Through the creation of institutional frameworks and health infrastructure, the study's findings will assist policymakers in developing efficient tourism policies. All of the above strategies will eventually lead to a trustworthy, safe, and healthy environment for both locals and visitors.

The Association of Inflammatory Marker Levels on Severity of Infection and in-Hospital Mortality among Covid-19 Confirmed Patients

Intro: COVID-19 is a respiratory and systemic disease with varying severity, caused by SARS-CoV-2 virus. The pathophysiology of COVID-19 has been postulated to be due to a release of pro-inflammatory cytokines causing cytokine storm. Several inflammatory markers have been studied to prognosticate the course of the disease but with varying results. Baseline inflammatory marker levels may be helpful in early recognition of disease severity which may translate to early aggressive treatment and better outcomes. The objective of this study is to determine the association of the initial levels of procalcitonin, CRP, LDH, Ferritin and D-Dimer on severity of infection and in-hospital outcomes among COVID-19 confirmed patients admitted at Our Lady of Lourdes Hospital Methods: A total of 238 subjects admitted from March 2020-June 2021 were included. Chart review was done and demographic and laboratory data were obtained. Subjects were categorized by disease severity and outcome. SASTM On Demand was used for data analysis: ordinal logistic regression to determine the association of initial inflammatory marker levels on the severity, while Binomial logistic regression to determined the association on the in-hospital outcome. Null hypothesis was rejected at 0.05-alpha level of significance. Finding(s): The study showed a significant association between LDH and severity of infection (p-value 0.014, Risk ratio 1.002), as well as on mortality (p-value 0.004, Risk ratio 1.003). There was no significant association between procalcitonin and severity of infection but there was significant association between procalcitonin and mortality. No significant association was noted between CRP, Ferritin and D-Dimer with severity of infection nor mortality. Conclusion(s): Patients with higher LDH levels were more at risk of severe and/or critical COVID-19 and in-hospital mortality. There was also significant association in the PCT levels and mortality but not with disease severity. There was no significant association between ferritin, D-DimeCopyright © 2023

Is TNF alpha a mediator in the co-existence of malaria and type 2 diabetes in a malaria endemic population?

Malaria remains a disease of public health importance globally, especially in sub-Saharan Africa. Malaria deaths reduced globally steadily between 2000-2019, however there was a 10% increase in 2020 due to disruptions in medical service during the COVID-19 pandemic. Globally, about 96% of malaria deaths occurred in 29 countries; out of which, four countries (Nigeria, the Democratic Republic of the Congo, the Niger, and the United Republic of Tanzania) accounted for just over half of the malaria deaths. Nigeria leads the four countries with the highest malaria deaths (accounting for 31% globally). Parallelly, sub-Saharan Africa is faced with a rise in the incidence of Type 2 diabetes (T2D). Until recently, T2D was a disease of adulthood and old age. However, this is changing as T2D in children and adolescents is becoming an increasingly important public health problem. Nigeria has been reported to have the highest burden of diabetes in Africa with a prevalence of 5.77% in the country. Several studies conducted in the last decade investigating the interaction between malaria and T2D in developing countries have led to the emergence of the intra-uterine hypothesis. The hypothesis has arisen as a possible explanation for the rise of T2D in malaria endemic areas; malaria in pregnancy could lead to intra-uterine stress which could contribute to low birth weight and may be a potential cause of T2D later in life. Hence, previous, and continuous exposure to malaria infection leads to a higher risk of T2D. Current and emerging evidence suggests that an inflammation-mediated link exists between malaria and eventual T2D emergence. The inflammatory process thus, is an important link for the co-existence of malaria and T2D because these two diseases are inflammatory-related. A key feature of T2D is systemic inflammation, characterized by the upregulation of inflammatory cytokines such as tumor necrosis factor alpha (TNF-α) which leads to impaired insulin signaling. Malaria infection is an inflammatory disease in which TNF-α also plays a major role. TNF-α plays an important role in the pathogenesis and development of malaria and T2D. We therefore hypothesize that TNF-α is an important link in the increasing co-existence of T2D.

Uncertain hypothesis test for uncertain differential equations

Uncertain hypothesis test is a statistical tool that uses uncertainty theory to determine whether some hypotheses are correct or not based on observed data. As an application of uncertain hypothesis test, this paper proposes a method to test whether an uncertain differential equation fits the observed data or not. In order to demonstrate the test method, some numerical examples are provided. Finally, both uncertain currency model and stochastic currency model are used to model US Dollar to Chinese Yuan (USD–CNY) exchange rates. As a result, it is shown that the uncertain currency model fits the exchange rates well, but the stochastic currency model does not.

Immune interference in effectiveness of influenza and COVID-19 vaccination.

Vaccines are known to function as the most effective interventional therapeutics for controlling infectious diseases, including polio, smallpox, rabies, tuberculosis, influenza and SARS-CoV-2. Smallpox has been eliminated completely and polio is almost extinct because of vaccines. Rabies vaccines and Bacille Calmette-Guérin (BCG) vaccines could effectively protect humans against respective infections. However, both influenza vaccines and COVID-19 vaccines are unable to eliminate these two infectious diseases of their highly variable antigenic sites in viral proteins. Vaccine effectiveness (VE) could be negatively influenced (i.e., interfered with) by immune imprinting of previous infections or vaccinations, and repeated vaccinations could interfere with VE against infections due to mismatch between vaccine strains and endemic viral strains. Moreover, VE could also be interfered with when more than one kind of vaccine is administrated concomitantly (i.e., co-administrated), suggesting that the VE could be modulated by the vaccine-induced immunity. In this review, we revisit the evidence that support the interfered VE result from immune imprinting or repeated vaccinations in influenza and COVID-19 vaccine, and the interference in co-administration of these two types of vaccines is also discussed. Regarding the development of next-generation COVID-19 vaccines, the researchers should focus on the induction of cross-reactive T-cell responses and naive B-cell responses to overcome negative effects from the immune system itself. The strategy of co-administrating influenza and COVID-19 vaccine needs to be considered more carefully and more clinical data is needed to verify this strategy to be safe and immunogenic.