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This research paper aims to analyze the stock exchanges of developed, emerging and developing countries to investigate the volatility in stock markets and to evaluate the rate of mean reversion.

The stock exchanges included in the research are NASDAQ, Tokyo stock exchange, Shanghai stock exchange, Bombay stock exchange, Karachi stock exchange and Jakarta stock exchange. Secondary daily data from Bloomberg are used to conduct the research for the period from January 2011 to December 2018. Generalized autoregressive conditional heteroskedasticity (GARCH) (1,1) model was applied to examine volatility and the half-life formula was used to calculate mean reversion in days.

The research concluded that all the stock exchanges included in the research satisfy the assumptions of mean reversion. Developing countries have the lowest volatility while emerging countries have the highest volatility which means that the rate of mean reversion is fastest in developing countries and slowest in emerging countries.

Future studies can determine the reasons for fastest rate of mean reversion in developing countries and slowest rate of mean reversion in emerging countries.

Developing countries show the lowest mean reversion in days while the emerging countries show the highest mean reversion in days indicating that developing countries take less time to revert to their mean position.

The majority of previous studies on univariate volatility models are mostly on applications of the models. Only a few researchers have taken the robustness of the models into account when applying them in emerging countries and not in developed, developing and emerging countries in one place. This makes the current study unique and more rigorous.

The purpose of this article is to investigate factors related to the time students spent on remote activities during the coronavirus (COVID-19) pandemic in 2020. Specifically, it analyzes whether the school’s relationship with the family and the guardians’ support are associated with longer study times for children and youth.

This was performed using an ordered logit model on data from two waves of the survey Remote Education in the Perspective of Students and Their Families (PENP) with a nationally and regionally representative sample of Brazilian public school students.

Results show the importance of contact between the school and the family and, to a greater extent, the direct support of parents or guardians. The odds of learners spending more hours studying increase 36% when schools provide guidance for parents and guardians; in turn, when they provide support for students during activities, these odds increase 144%.

Moreover, students spend more time doing school activities in the later years of elementary school, high school and when they attend a state school.

The success of an Electronic Health Record (EHR) system is determined by the numerous facilitators and obstacles that influence physicians' intentions toward using these technologies. This study examines physicians' intentions to use EHR by applying the extended technology readiness and acceptance model (TRAM) factors, the result demonstrability, colleagues' opinions, perception of external control, and organizational support.

Convenience sampling was used to collect data from physicians in Egypt (n = 520). To evaluate the model's hypotheses, this study used the partial least squares structural equation modeling (PLS-SEM) method with WarpPLS.7.

The results revealed that positive TR factors (innovativeness and optimism) positively affect perceived usefulness and ease of use, while negative TR factors (discomfort and insecurity) negatively impact perceived usefulness and ease of use. Furthermore, the result demonstrability and colleagues' opinions positively influence perceived usefulness, while the perception of external control and organizational support positively influence perceived ease of use. In addition, significant relationships between perceived ease of use and usefulness and adoption intention were identified.

This is the first study to apply the TRAM to understand physicians' adoption intentions to use EHR systems. Moreover, this study determined the different roles of positive and negative TR affecting physicians' cognition regarding using EHR systems.

Sports advertisements such as the Super Bowl showcase products and brands that have invested increasingly large sums financially to gain viewers’ attention. However, how audio features in advertisements impact viewers' behavior remains unexplored.

Using the lens of signaling theory, this research uses advanced data analytics of voice and music audio in Super Bowl advertisements to examine its impacts on viewers.

Results show that advertisement viewers prefer more voiced frames and have a greater liking behavior of voiced frames with a low intensity (less loud) and a higher F1 frequency, which is typically associated with male vocal tracts. A fast music tempo works better for longer advertisements. The model controls for various types of ad appeals. The research underlines the importance of voice and music in signaling successful brand features that are likely to increase the ad-liking behavior of consumers (positive effect).

The current research implies that brands advertising through sports ads must carefully select voice actors and music in order to provide the most positive signals for a brand to have the most significant effect and, thus, a greater return on the high sums invested in the ads.

First, this research contributes in terms of a new research process for using audio analytics in advertising. The detailed research process outlined can be used for future research examining audio and music from advertisements. Second, our findings provide additional support to the important role of voice features (e.g. intensity and frequency) as signals in inducing responses from consumers (Biswas et al., 2019; Hagtvedt and Brasel, 2016). Third, the study surfaces a new theoretical association: the effect of tempo in moderating the relationship between duration and propensity to like an ad.