Search results

The authors examine the Taiwanese government's budgetary responses to COVID-19, with a focus on the special budgets created for containing the virus, undertaking bailouts and providing economic stimulus. The authors assess the short-term and long-term fiscal implications of the budgetary measures and discuss how Taiwan's experiences could provide lessons for other countries for future emergencies.

The authors collect data from Taiwan's official documents and news reports and compare the special budgets proposed by the Taiwanese government during the Great Recession and the COVID-19 pandemic. The authors discuss lessons learned from the 2008–09 special budget and possible concerns of the 2020 special budgets. In the conclusions, the authors discuss potential long-term implications for Taiwan's budgetary system as well as possible lessons for other countries based on Taiwan's experiences

The authors found that the 2008–09 special budgets focused only on economic stimulus, whereas the 2020 special budgets covered COVID-19 treatments, bailouts and economic stimulus. In 2020, the Taiwanese government devised targeted bailout plans for industries and individuals most affected by the pandemic and created the Triple Stimulus Vouchers to boost the economy. Since the special budgets were largely funded through borrowing, the authors pointed out concerns for fiscal sustainability and intergenerational equity.

COVID-19 has changed how the world functions massively. This work adds to the literature on COVID-19 by providing Taiwan's budgetary responses to the pandemic. This work also identifies ways for Taiwan to improve the existing budgetary system and discusses lessons for other countries.

Constant or decreasing returns and increasing returns to scale are two kinds of mechanism in economic growth. The goal of supply-side structural reform is to promote the establishment of the mechanism with increasing returns to scale. The paper aims to discuss this issue.

This paper argues that the overall economic structure of the developing economy has been divided into the sector of constant or decreasing returns to scale and the sector of increasing returns to scale due to the dual economic structure. Among them, the supply-side structural reform is mainly to reduce the sector of decreasing returns to scale and increase the sector of increasing returns to scale. Based on the hypothesis of such two-sector economic structure in the supply side of developing economies and on the industrial data, this paper empirically tests the returns to scale of China’s supply structure. The result suggests that so far the sector of constant or decreasing returns to scale dominates the supply structure of China’s economic growth, which results in the state of decreasing returns to scale in China’s overall economy.

Therefore, to realize the long-term sustained growth and transformation of the development pattern of China’s economy, the authors must carry out the supply-side structural reform, vigorously develop the modern industrial sectors characterized by modern knowledge and technology, and promote the development of an innovation-driven economy.

Besides, the authors must accelerate the transformation from traditional industrial sectors to modern industrial sectors, actively promote China’s industrial structure toward rationalization and high gradation, as well as build a modern industrial system so as to facilitate the formation of the mechanism of increasing returns to scale and accelerate the transformation of the driving force of China’s economic growth.

Microblogging is an important channel used to disseminate online public opinion during an emergency. Analyzing the features and evolution mechanism of online public opinion during an emergency plays a significant role in crisis management.

This paper uses the event of Hurricane Irma and combines it with the life cycle of online public opinion evolution to understand the effect of different types of emotional (joy, anger, sadness, fear, disgust) microblogs (tweets) on information dissemination. The research was performed in the context of Hurricane Irma by using tweets associated with that event.

This paper demonstrates that negative emotional information has a greater communication effect, and further, the target audience that receives more exposure to negative emotional microblogs has a stronger tendency to retweet. Meanwhile, emotions expressed in tweets and the life cycle of public opinion evolution exert interactive effects on the retweeting behavior of the target audience.

For future research, a professional dictionary and the context should be taken into consideration to make the modeling in the text more normative and analyzable.

This paper aims to reveal how the emotions of a tweet affect its virality in terms of diffusion volume in the context of an emergency event.

The conclusion made in this paper can shed light on the real-time regulation and public opinion transmission, as well as for efficient intelligence service and emergency management.

In this study, Hurricane Irma is taken as an example to explore the factors influencing the information dissemination during emergencies on the social media environment. The relationship between the sentiment of a tweet and the life cycle of public opinion and its effect on tweet volume were investigated.

Identifying tools for predicting fiscally distressed local governments has received heightened attention following the Great Recession of 2007–2009. Despite the recent expansion of research, measuring fiscal distress is challenging because of the operational complexity associated with the term. Furthermore, many local governments are too small to produce a Comprehensive Annual Financial Report (CAFR), upon which many empirical studies of fiscal condition or fiscal distress are based. This study designs a parsimonious tool for identifying fiscally distressed entities based on existing literature. The authors examine Nebraska's 93 counties over a nine-year period (from 2010 to 2018). In order to ensure the validity of our tool, we replicate two well-known empirical approaches of assessing local fiscal condition and compare the results with ours. The authors find nearly all counties in Nebraska to be free from fiscal distress in the past decade. However, since most counties in Nebraska have small populations and are far from urban centers, they may still be vulnerable to future fiscal shocks and may need to closely monitor their fiscal condition.

The authors offer a parsimonious method for assessing the existence of fiscally distressed counties. They select predictors of fiscal distress based on two criteria. First, for the purpose of this study, the authors use financial information that is uniform, easily accessible and does not rely on CAFRs. In order to make their model parsimonious and replicable, the authors only consider factors that have the most decisive effects on local fiscal conditions. Second, the authors draw on indicators that have been consistently supported by previous studies (e.g., Kloha et al., 2005; Gorina et al., 2018). The authors test the validity of this approach using correlation analysis and regression modeling, similar to Wang et al. (2007).

The authors’ fiscal distress measure shows encouraging signs. Results show that all but Brown's model are highly correlated. The decile and standard deviation models have the strongest correlation (r = 0.955, p < 0.01). These two models are also significantly associated with Kloha et al.'s model. Their correlation coefficients are 0.812 and 0.830, respectively. Consistent with Wang et al. (2007), the authors find modest associations between our fiscal measures and socioeconomic measures.

Limitations include questions of generalizability – we are only studying Nebraska counties. The extent to which the findings are generalizable to counties in other states remains to be seen. We advise readers and policymakers to bear in mind that at this point, there is no perfect way to measure local fiscal condition or fiscal distress. Specifically, with our model, the foremost advantages of parsimony are data accessibility and replicability. However, unlike other existing tools that consider dozens of indicators, our tool bears the cost of not employing a more comprehensive perspective that may be required to capture a full picture of local fiscal condition.

The purpose of this research was to construct and present a parsimonious way of identifying local fiscal distress that is easily replicated and applied in practice. The challenges were operational – both in terms of definition and measurement. Fiscal distress is a nebulous concept that can vary based on the researcher's intent. Our chosen set of indicators have two characteristics: accessibility of financial information and consistency with past studies. Thus, we assess two of the four dimensions of solvency: budgetary solvency and long-run solvency. The authors suggest that this effort should not be used as a tool by state lawmakers to accuse and judge local governments. Instead, it should be used to assist local governments as Iowa and Colorado do. The findings could be the beginning of a conversation between the state and local governments to determine the best course(s) of action. As previously mentioned, there are many causes of fiscal distress and poor decision-making is not very common. Looking into the future, the authors expect more local governments to become fiscally distressed and the primary cause would be economic/demographic change. Since many local governments in Nebraska have very small populations and are far from the urban centers of Omaha and Lincoln, they might be vulnerable to future fiscal shocks. Thus, state lawmakers need to begin considering strategies to deal with local fiscal distress. The authors do have limitations in measurement. However, if used appropriately, this research can add value to the discussion of managing local government fiscal distress in Nebraska and other similar states.

While the analysis finds little fiscal distress currently in Nebraska, there is concern that with population migration to the urban areas and the “graying” of the state, local governments in rural areas (the vast majority in Nebraska) could face more serious issues in future years. A recent study showed that local fiscal condition is negatively associated with the distance from the municipality to the urban centers of Omaha and Lincoln (Maher et al., 2019). These spatial effects could be further exacerbated in a state that ranks near the bottom in financial support of local governments and policy makers are committed to “controlling” property taxes.

This study, while building on prior work, is unique in that it focuses on counties as opposed to municipalities, which are the most common units of analysis. The authors also offer a model for assessing fiscal distress in a state that currently does not have state-level systems to monitor local finances. Finally, rather than relying on audited annual financial reports which would disqualify many smaller local governments, the authors offer a parsimonious tool that is easily replicated and can be used by all local governments that submit uniform financial reports to their states.

There are over 300,000 male migrant workers in Singapore. Around 600 major workplace injuries are reported in Singapore each year, mainly in the manufacturing and construction injuries. Migrant workers who are affected by workplace injuries often face many challenges, including not being able to work and thus may be repatriated to their home countries, which affects their financial status and that of their families, whom they support. This research aims to explore the knowledge, attitudes and beliefs of injured migrant workers in Singapore, towards disability and vocational rehabilitation.

Fifteen male migrant workers, from Bangladesh, China and India, who had acquired disabling injuries in their workplaces in Singapore, were identified through purposive sampling. They were interviewed by a male interviewer, either in Mandarin Chinese or with the assistance of interpreters for Bengali-English and Tamil-English. Interviews were recorded, transcribed, translated to English, then analysed thematically.

The interviewees generally had a pessimistic outlook on their disability, which often impacted negatively on their self-worth and familial relationships. Many of them also had little knowledge of vocational rehabilitation and had not yet seriously considered future job prospects.

To the best of the authors’ knowledge, there are no similar studies exploring the knowledge, attitudes and beliefs of injured migrant workers in Singapore towards disability and vocational rehabilitation.

Metaheuristic algorithms based on biology, evolutionary theory and physical principles, have been widely developed for complex global optimization. This paper aims to present a new hybrid optimization algorithm that combines the characteristics of biogeography-based optimization (BBO), invasive weed optimization (IWO) and genetic algorithms (GAs).

The significant difference between the new algorithm and original optimizers is a periodic selection scheme for offspring. The selection criterion is a function of cyclic discharge and the fitness of populations. It differs from traditional optimization methods where the elite always gains advantages. With this method, fitter populations may still be rejected, while poorer ones might be likely retained. The selection scheme is applied to help escape from local optima and maintain solution diversity.

The efficiency of the proposed method is tested on 13 high-dimensional, nonlinear benchmark functions and a homogenous slope stability problem. The results of the benchmark function show that the new method performs well in terms of accuracy and solution diversity. The algorithm converges with a magnitude of 10-4, compared to 102 in BBO and 10-2 in IWO. In the slope stability problem, the safety factor acquired by the analogy of slope erosion (ASE) is closer to the recommended value.

This paper introduces a periodic selection strategy and constructs a hybrid optimizer, which enhances the global exploration capacity of metaheuristic algorithms.

In this study, the Models-3/Community Multiscale Air Quality Model (CMAQ) coupled with the Mesoscale Modeling System Generation 5 (MM5) was employed to simulate the air pollution episodes over East Asia, northern China Plain (NCP), and southern Hebei (SHB), at a grid resolution of 36, 12, and 4 km, respectively in Oct. 2012. The PM₁₀ concentrations over SHB at 12-km are overpredicted with NMBs of 34.6% to 45.7% and also overestimated with that of 72.1% to 97.5% at 4-km which applied such a fine grid resolution over the SHB for the first time. It indicated that the simulation at 12-km performs better than the 4-km which may be related to the spatial allocation of the emissions, the lack of dust emissions and the limitations of model treatments. Five heavy episodes show the characteristics of sawtooth-shaped cycles over the NCP in fall (i.e. the maximum of PM₁₀ was up to 885.1 µg m⁻³ and PM_2.5 was up to 438.4 µg m⁻³ in Handan city) which resulting in the deterioration of visibility and periodically haze days. The concentrations of OC, EC, SO₄²⁻, NO₃⁻ and NH₄⁺ were significantly higher in heavy episodes than non-heavy pollution episodes. In comparison with other cities ([NO₃⁻]/[SO₄²⁻] > 1) at 12-km, the monthly-mean mass ratio of [NO₃⁻]/[SO₄²⁻] at Taiyuan (0.17−0.73), Shijiazhuang (0.28−2.34) was 0.43, 0.84 respectively, which means the stationary sources emissions were more important than the vehicle emission in the source areas. The influence of the regional transportation for pollutants compared with local emission was also an important factor for heavy pollution episodes. The regional joint framework should be established along with controlling the local emission over the SHB in China to improve the air quality.

Big data have rapidly developed as a viable solution to many problems faced in engineering industries. Specifically, in the industry of water resource engineering, where there is a tremendous amount of data, various big data techniques could be applied to achieve innovative and efficient solutions for the industry. This study reviewed the proposal of big data as potential approaches to solve various difficulties encountered in managing water resources and related applications in Malaysia. The advantages and disadvantages of big data applications have also been discussed along with a brief literature review and some examples of case studies.

The purpose of this study was to conduct a content analysis of humor styles used in US and Mexican television advertising.

A total of 97 television commercials broadcasted by major US and Mexican national television networks were classified under the four humor styles described by Martin et al.

Humor styles used in television advertising significantly differ between the two countries. US commercials use more affiliative, aggressive, and self‐defeating humor than do Mexican advertisements, while self‐enhancing humor is the predominant humor style of Mexican commercials and is used more frequently in Mexico when compared to the USA.

The findings reveal the frequency and types of humorous television commercials used in the USA and Mexico.

The study suggests that cultural differences should be taken into consideration when humorous advertising is used across borders.

The purpose of this study is to explore the role of various superstitious beliefs in consumers' information processing and evaluation of brand logos.

When consumers encounter a brand logo without actually experiencing the company's offerings, superstition may be deployed to fill the void of the unknown to evaluate the brand logo and judge the benefits from the offerings represented by the brand. Multiple regression analysis was used to investigate the relationship between consumers' brand logo sensitivity and a number of antecedental superstition beliefs.

The results indicate that consumers' belief in fate has a negative effect on brand logo sensitivity, and consumers' belief in fortune‐tellers, belief in magic and fictional figures, belief in lucky charms, and belief in superstitious rituals have positive effects on brand logo sensitivity, respectively.

From a consumer perspective, the authors' findings reveal that the more positive attitude consumers have towards a company's visual identity system, the more favorable brand image consumers have toward the company and its offerings.

Marketers should study and understand consumer superstition when attempting to build consumer‐friendly, culturally‐robust, and trouble‐free brands in the marketplace. Managerial implications and corporate branding strategies are suggested to avoid branding pitfalls and maximize brand equity in the consumer market.

The study offers a non‐traditional approach to explaining consumer‐based brand image and brand equity.