With the advent of the Online to Offline (O2O) era, the rise of various food delivery platforms not only provides consumers with more choices, but also allows restaurant operators to reach more potential consumers and increase their additional revenue. This study is based on theory of planned behavior (TPB), and includes the ‘utilitarian value’ and ‘hedonic value’ as research variables. Structural equation modeling (SEM) was used to verify the research hypotheses, and to analyze consumers’ purchase intentions toward online food delivery platforms. An online survey was also conducted, and a total of 1300 questionnaires were distributed. After excluding invalid questionnaires with incomplete answers, a total of 1082 questionnaires were deemed valid, and the effective recovery rate was 83.23%. The research results were as follows: (1) the attitude, subjective norms, and perceived behavioral control of consumers will have a significant positive effect on utilitarian value and hedonic value; (2) the utilitarian and hedonic values have a significant positive effect on purchase intention; and (3) the utilitarian and hedonic values have a mediating effect on attitude, subjective norms, perceived behavioral control, and purchase intention. Based on the above results, food delivery platform operators can identify the key factors that drive consumers to use their services in order to formulate effective management strategies and create greater business opportunities for their organizations.

Climate change is regarded as one of the major factors enhancing the transmission intensity of dengue fever. In this study, we estimated the threshold effects of temperature on Aedes mosquito larval index as an early warning tool for dengue prevention. We also investigated the relationship between dengue vector index and dengue epidemics in Taiwan using weekly panel data for 17 counties from January 2012 to May 2019. To achieve our goals, we first applied the panel threshold regression technique to test for threshold effects and determine critical temperature values. Data were then further decomposed into different sets corresponding to different temperature regimes. Finally, negative binomial regression models were applied to assess the non-linear relationship between meteorological factors and Breteau index (BI). At the national level, we found that a 1°C temperature increase caused the expected value of BI to increase by 0.09 units when the temperature is less than 27.21 °C, and by 0.26 units when the temperature is greater than 27.21 °C. At the regional level, the dengue vector index was more sensitive to temperature changes because double threshold effects were found in the southern Taiwan model. For southern Taiwan, as the temperature increased by 1°C, the expected value of BI increased by 0.29, 0.63, and 1.49 units when the average temperature was less than 27.27 °C, between 27.27 and 30.17 °C, and higher than 30.17 °C, respectively. In addition, the effects of precipitation and relative humidity on BI became stronger when the average temperature exceeded the thresholds. Regarding the impacts of climate change on BI, our results showed that the potential effects on BI range from 3.5 to 54.42% under alternative temperature scenarios. By combining threshold regression techniques with count data regression models, this study provides evidence of threshold effects between climate factors and the dengue vector index. The proposed threshold of temperature could be incorporated into the implementation of public health measures and risk prediction to prevent and control dengue fever in the future.

This study examines how experience of severe acute respiratory syndrome (SARS) influences the impact of coronavirus disease (COVID-19) on international tourism demand for four Asia-Pacific Economic Cooperation (APEC) economies, Taiwan, Hong Kong, Thailand, and New Zealand, over the 1 January–30 April 2020 period. To proceed, panel regression models are first applied with a time-lag effect to estimate the general effects of COVID-19 on daily tourist arrivals. In turn, the data set is decomposed into two nation groups and fixed effects models are employed for addressing the comparison of the pandemic-tourism relationship between economies with and without experiences of the SARS epidemic. Specifically, Taiwan and Hong Kong are grouped as economies with SARS experiences, while Thailand and New Zealand are grouped as countries without experiences of SARS. The estimation result indicates that the number of confirmed COVID-19 cases has a significant negative impact on tourism demand, in which a 1% COVID-19 case increase causes a 0.075% decline in tourist arrivals, which is a decline of approximately 110 arrivals for every additional person infected by the coronavirus. The negative impact of COVID-19 on tourist arrivals for Thailand and New Zealand is found much stronger than for Taiwan and Hong Kong. In particular, the number of tourist arrivals to Taiwan and Hong Kong decreased by 0.034% in response to a 1% increase in COVID-19 confirmed cases, while in Thailand and New Zealand, a 1% national confirmed cases increase caused a 0.103% reduction in tourism demand. Moreover, the effect of the number of domestic cases on international tourism is found lower than the effect caused by global COVID-19 mortality for the economies with SARS experiences. In contrast, tourist arrivals are majorly affected by the number of confirmed COVID-19 cases in Thailand and New Zealand. Finally, travel restriction in all cases is found to be the most influencing factor for the number of tourist arrivals. Besides contributing to the existing literature focusing on the knowledge regarding the nexus between tourism and COVID-19, the paper’s findings also highlight the importance of risk perception and the need of transmission prevention and control of the epidemic for the tourism sector.

The proliferation of Internet has accelerated the dissemination of information, which has given birth to the term “Internet meme”. Social network is one of the pivotal media in spreading an Internet meme. Marketers utilize Internet memes to carry out marketing activities to significantly improve their Internet exposure. We thus verify whether consumers generate purchase intention after being attracted to an Internet meme, as no such research prevails. We employ the value–attitude–behavior model as its theoretical core and discuss how the values formed by consumers under the impact of an Internet meme influence their purchasing behaviors through their attitudes. The participants of the study are Internet users who are habitual to checking Facebook. We adopted convenience sampling and developed 380 valid questionnaires. Structural equation modeling is applied to verify the study’s hypotheses. The research results reveal that utilitarian and hedonic values influence the Purchase Intention through utilitarian and hedonic attitudes. In light of the aforementioned findings, it is suggested that marketers and relevant participants focus on the hedonic value brought by an Internet meme and design fun and witty Internet memes to attract consumers.

The main purpose of this study was to investigate how climate change affects blood vessel-related heart disease and hypertension and to estimate the associated economic damage. In this paper, both the panel data model and the contingent valuation method (CVM) approaches are applied. The empirical results indicate that the number of death from cardiovascular diseases would be increased by 0.226% as the variation in temperature increases by 1%. More importantly, the number of death from cardiovascular diseases would be increased by 1.2% to 4.1% under alternative IPCC climate change scenarios. The results from the CVM approach show that each person would be willing to pay US$51 to US$97 per year in order to avoid the increase in the mortality rate of cardiovascular diseases caused by climate change.