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Developing ecotourism services is a suitable solution to help developing countries improve the status of sustainable development indicators and protect their environment. The primary purpose of this paper is to find out the effects of green governance variables and carbon dioxide emissions on ecotourism for 40 developing economies from 2010 to 2021. The results confirmed a uni-directional causal relationship between the green governance indicator and the inflation rate of the ecotourism indicator. In addition, with a 1% improvement in the green governance index of developing countries, the ecotourism of these countries will increase by 0.43%. In comparison, with a 1% increase in the globalization index of these countries, ecotourism will increase by 0.32%. Moreover, ecotourism in developing countries is more sensitive to macroeconomic variables changes than in developed economies. Geopolitical risk is an influential factor in the developing process of ecotourism. The practical policies recommended by this research are developing the green financing market, establishing virtual tourism, granting green loans to small and medium enterprises, and government incentives to motivate active businesses.
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The era of smart tourism has arrived. In the context of big data information, based on the thinking of the entire tourism activity, it is worth thinking about the role of tourism information in tourism activities. This paper proposes a method for evaluating the psychological expectations of tourist destinations by applying the quality function configuration. According to the needs of tourists, the relevant product characteristics of the tourist destination are selected, an evaluation quality house is established, and various relationships within the quality house are weighed, and established a mathematical model for the evaluation of tourists' psychological expectations in tourist destinations. Bringing the methods of machine learning (ML) and data mining (DM) into the research of tourists' psychological expectation value evaluation, ML is one of the main methods to solve the problem of DM. ML is the process of using the system itself to improve itself, therefore, ML is widely used in data mining. The research combines psychology and tourism research, through empirical research, to establish a structural equation model. It analyzes the influence of tourism information on tourists' behavioral decisions, increases the media's variable expectations of tourism, and uses tourist satisfaction and behavior as dependent variables. The results showed that the effect of tourism information on tourists is significantly greater than the expected effect (p = 0.510, P is significant at 0.001 level) than the effect of tourist satisfaction (p = 0.290, P is significant at 0.05 level). Therefore, in order to create good expectations for tourists, the general image of a tourist destination must match the actual local conditions. Using the support vector machine algorithm with the introduction of optimization mechanism to train the feature set of the user data, and then predict the links in Sina Weibo, and obtain higher prediction accuracy and prediction speed. The psychological expectation evaluation model of tourists in tourist destinations can effectively calculate the perceived value of psychological expectation evaluation of tourists in tourist destinations, and help tourists choose reasonable and satisfactory travel plans.
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This research probes the influence of the construction of the China-Pakistan Economic Corridor (CPEC) on the tourism development behavior of local residents. By applying social exchange theory (SET), this study examines the impact of the community dimension on tourism development behavior through overall attitude. In addition, this study also examines the use of social media as a moderator in the relationship between overall attitude and tourism development. A survey tool has been used to obtain data from the people of Gilgit-Baltistan. Hypotheses were examined using the structural equation method (SEM) on 417 survey responses. The findings indicated community satisfaction and an overall positive attitude to the effects of development, although a negative attitude regarding concerns about community resources. Overall, attitude has a significant impact on tourism development behavior. Additionally, the use of social media strengthens the relationship between overall attitude and behavior that favors tourism development.
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The domestic situation of the past few years shows the practices of employees' unpaid leave and layoffs and the constant drain on capital, talent, and technologies in hospitality. Owners expect to reduce the losses to as low as possible by saving on human costs. Nevertheless, in face of such a changing environment, hospitality has to accumulate high-quality human capital through systematic investment, sensitive development, and continuous learning and growth to discover competitive advantages through the cultivation of human capital. The pre-service education of new employees could accelerate their familiarity with the operations of the company and their understanding of their job role and duties. More importantly, with good planning, it could make employees feel emphasized with and respected with the result of largely changing their thoughts and working habits. Aiming at supervisors and employees in hospitality in Zhejiang as the research objects, a total of 420 copies of our questionnaire are distributed, and 357 valid copies were retrieved, with a retrieval rate of 85%. According to the results to propose discussions, it is expected to generate systematic and proper education methods for the pre-service education in hospitality, promote the education effectiveness, and promote employees' capability and organizational performance.
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This study examined how social media marketing activities (SMMA) influence consumers' engagement behaviour in developing countries. Based on the stimulus-organism-response theory, we examined the effect of SMMA on consumers' engagement intention and further investigated the moderating effect of social media sales intensity. The study employed a time-lagged design with two waves to confirm the hypothesised framework. The study findings showed that SMMA positively influence consumers' engagement intention and engagement behaviour. In addition, social media sales intensity strengthens the link between engagement intention and engagement behaviour. This study adds to the literature on social media and discusses its practical implications.
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This study analyzes the conflicting effects of investors' sentiment caused by public health emergencies and uses event analysis methods and linear regressions to examine the impact of such emergencies on the stock prices of insurance companies. The study shows that public health emergencies have a positive and significant impact on insurance companies' portfolios through investors' sentiment, which is persistent. However, the investor fear index triggered by public health emergencies is negatively associated with insurance stock portfolio returns. Meanwhile, insurers with smaller market capitalization are more strongly influenced by investors' sentiment than those with larger market capitalization.
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COVID-19 , Salud Pública , Actitud , Humanos , Aseguradoras , Inversiones en SaludRESUMEN
The existing models that measure the environmental pollution impact of ecotourism suffer from the problems of low success rate and poor accuracy. We propose a new model to evaluate the environmental pollution impact better. Environmental pollution data are first obtained from the scenic areas of ecotourism. Then, based on the primary parameters of scenic spots, pollution coefficients are determined, and conversion data are used to construct a model to evaluate the pollution impact of ecotourism on scenic spots. Based on the analysis of carbon emission amounts, the monetary value of environmental pollution is determined. Experimental results are provided to show that our proposed model performs better than the existing models.
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Conservación de los Recursos Naturales , Contaminación Ambiental , Carbono , Monitoreo del AmbienteRESUMEN
The coronavirus pandemic has highlighted the capitalist dysfunction showing that considering profit over people can be deadly. The study reveals the LME economies were more responsive toward the impact of the disease outbreaks as compared to the CME economies wherein the impact of the disease was moderated by the government involvement. This allows us to draw that the impact of the disease outbreaks can be moderated by increasing the involvement of the government authorities.
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COVID-19/economía , Comercio/economía , Comercio/estadística & datos numéricos , Brotes de Enfermedades/economía , Brotes de Enfermedades/estadística & datos numéricos , Pandemias/economía , COVID-19/epidemiología , Humanos , Modelos Teóricos , Pandemias/estadística & datos numéricos , SARS-CoV-2RESUMEN
The economic stability of a country, such as Pakistan is dependent on the construction of mega-projects, such as the China-Pakistan Economic Corridor (CPEC). However, certain external factors and project characteristics may delay the construction of infrastructure projects; scholars have not investigated the development of CPEC from this perspective. In addition, the COVID-19 outbreak has hindered CPEC initiatives. This analysis will examine the effect of external environment factors on CPEC, and benchmark the project's effects on economic stability through CPEC's development by incorporating 523 samples obtained from employees of various CPEC projects. Structural equation modeling was used to analyze all hypotheses proposed here on AMOS 21.0 tools. According to the findings of this study, the CPEC external environment and project benchmark characteristics have a negative effect on the construction of CPEC development. Furthermore, the development of CPEC is found to have a significant effect on economic stability. However, fear of COVID-19 has weakened the relationship between CPEC development and economic stability. Finally, we also discuss the implications and limitations of the study.
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This paper uses the daily seasonally-adjusted data for net revenues and openings of small businesses in the accommodation, food services, leisure, and hospitality sectors in the United States from January 10, 2020, to June 24, 2021. The results from the Dorta-Sanchez bootstrap unit-root test for a random walk with drift show that the COVID-19 crisis has significantly affected revenues and openings of small leisure and hospitality firms. Moreover, the results remain valid when the data for the national level and 51 states are considered.
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COVID-19 , Pequeña Empresa , Humanos , Actividades Recreativas , SARS-CoV-2 , Estados UnidosRESUMEN
Computerized cognitive training (CCT) has been found to improve a range of skills such as attention, working memory, inhibition control, and decision making. However, the relationship between the initial performance, amount of improvement, time constant, and asymptotic performance level in CCT is still unclear. In the current study, we performed selective attention training on college students and addressed this issue by mathematically modeling the learning curve with an exponential function. Twenty-nine students completed approximately 10 days of CCT. Presentation time served as the dependent variable and was measured by three-down/one-up adaptive algorithms. We fitted an exponential function to the estimated block thresholds during CCT and obtained three learning parameters (amount of improvement, time constant, and asymptotic performance level) for all subjects. The initial performance was defined by the sum of the amount of improvement and the asymptotic performance level. Pearson correlation analyses were conducted between the initial performance and the three leaning parameters. The initial performance was positively correlated with the amount of improvement and asymptotic performance level, but was negatively correlated with the time constant. The time constant was negatively correlated with the amount of improvement and asymptotic performance level. Poorer initial performance was linked to a larger amount of improvement, shorter time constant, and higher asymptotic threshold, which supported the compensation account. Our results may help improve the present understanding of the nature of the CCT process and demonstrate the advantages of using a customized training protocol to enhance the efficiency of cognitive training in practical applications.
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Trastornos del Conocimiento , Atención , Cognición , Humanos , Memoria a Corto Plazo , EstudiantesRESUMEN
This study aimed to examine the impact of information publicity on the intention of tourists to visit rural destinations in developing countries. Based on the theory of planned behavior (TPB), we examined the indirect effect of information publicity on intention to visit via subjective norms and further investigated the moderating effect of social media disposition and social media use. The study used data from a time-lagged design with three waves which supported the hypothesized model. The findings revealed that information publicity has an influence on the intention of tourists to visit through the mediating effect of subjective norms. Moreover, the social media disposition strengthened the relationship between information publicity and subjective norms. Furthermore, social media use positively moderated the relationship between subjective norms and intention to visit. Besides the core TPB constructs, the added variables indeed exerted a substantial impact on the visit intention of tourists. The study contributed to the tourism-related literature on social media and the practical implications were discussed.
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The changes in urinary crystal properties in patients with calcium oxalate (CaOx) calculi after oral administration of potassium citrate (K3cit) were investigated via atomic force microscopy (AFM), scanning electron microscopy (SEM), X-ray powder diffractometry (XRD), and zeta potential analyzer. The AFM and SEM results showed that the surface of urinary crystals became concave, the edges and corners of crystals became blunt, the average size of urinary crystallines decreased significantly, and aggregation of urinary crystals was reduced. These changes were attributed to the significant increase in concentration of excreted citrate to 492 ± 118 mg/L after K3cit intake from 289 ± 83 mg/L before K3cit intake. After the amount of urinary citrate was increased, it complexed with Ca(2+) ions on urinary crystals, which dissolved these crystals. Thus, the appearance of concave urinary crystals was a direct evidence of CaOx dissolution by citrate in vivo. The XRD results showed that the quantities and species of urinary crystals decreased after K3cit intake. The mechanism of inhibition of formation of CaOx stones by K3cit was possibly due to the complexation of Ca(2+) with citrate, increase in urine pH, concentration of urinary inhibitor glycosaminoglycans (GAGs), and the absolute value of zeta potential after K3cit intake.
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The property changes of urinary nanocrystallites in 20 cases of uric acid (UA) stone formers after 1 week of potassium citrate (K3cit) intake were comparatively studied by X-ray diffraction analysis, Fourier transform infrared spectroscopy, nanoparticle size analysis, and transmission electron microscopy. Before K3cit intake, the urinary crystallites mainly contained UA and calcium oxalate. After K3cit intake, the components changed to urate and UA; the qualities, species, and amounts of aggregated crystallites decreased; urine pH, citrate, and glycosaminoglycan excretions increased; and UA excretion, Zeta potential, and crystallite size decreased. The stability of crystallites followed the order: controls>patients after taking K3cit>patients before taking K3cit. Therefore, the components of urinary stones were closely related to the components of urinary crystallites.