ABSTRACT
The study investigates the asymmetric effect of investors sentiments on herding behavior and stock returns of S&P 500 markets during pre and post covid 19. We analyze daily data from May 15, 2000 (Pre Covid) to 20 Feb 2020 and form 20 Feb to –13 May, 2022 (Post Covid). We conduct Modified multiple regression Analysis by introducing investors sentiments proxy i.e., trading volume into the Chang et al., (2000) herding model named as cross-sectional absolute deviation along with Vector Autoregressive Regression and Granger Causality tests. We establish that trading volume increases herding asymmet-ric. Post COVID-19 has significant negative effects on herding behaviour. The findings illustrate that COVID-19 increased herding behavior in S&P 500 markets and became more intensified during COVID-19, which contributes to ac-centuate and elongate it. The study also documents significant positive effect of investor sentiment on stock returns, whereas COVID-19 has negative effect on S&P 500 stock returns. We propose that investor sentiments may present extrapolative or predictive feature of herding behaviour. The study will be ben-eficial to shape an understanding of different dynamics associated with portfolio and market in-efficiency, trading strategies as well as risk management perspective. © 2023, Economic Laboratory for Transition Research. All rights reserved.
ABSTRACT
The demand for daily food purchases has increased dramatically, especially during the Covid-19 pandemic. This requires suppliers to face a huge and complex problem of delivering products that meet the needs of their customers on a daily basis. It also puts great pressure on managers on how to make day-to-day decisions quickly and efficiently to both satisfy customer requirements and satisfy capacity constraints. This study proposes a combination of the cluster-first ??? route-second method and k-means clustering algorithm to deal with a large Vehicle Routing Problem with Time Windows (VRPTW) in the logistics and transportation field. The purpose of this research is to assist decision-makers to make quick and efficient decisions, based on optimal costs, the number of vehicles, delivery time, and truck capacity efficiency. A distribution system of perishable goods in Vietnam is used as a case study to illustrate the effectiveness of our mathematical model. In particular, perishable goods include fresh products of fish, chicken, beef, and pork. These products are packed in different sizes and transferred by vehicles with 1000 kg capacity. Besides, they are delivered from a depot to the main 39 customers of the company with arrival times following customers??? time window. All of the data are collected from a logistics company in Ho Chi Minh city (Vietnam). The result shows that the application of the clustering algorithm reduces the time for finding the optimal solutions. Especially, it only takes an average of 0.36 s to provide an optimal solution to a large Vehicle Routing Problem (VRP) with 39 nodes. In addition, the number of trucks, their operating costs, and their utilization are also shown fully. The logistics company needs 11 trucks to deliver their products to 39 customers. The utilization of each truck is more than 70%. This operation takes the total costs of 6586215.32 VND (Vietnamese Dong), of which, the transportation cost is 1086215.32 VND. This research mainly contributes an effective method for enterprises to quickly find the optimal solution to the problem of product supply.
ABSTRACT
This paper analyzes the statistical impact of COVID-19 on the S&P500 and the CSI300 intraday momentum. This study employs an empirical method, that is, the intraday momentum method used in this research. Also, the predictability of timing conditional strategies is also used here to predict the intraday momentum of stock returns. In addition, this study aims to estimate and forecast the coefficients in the stock market pandemic crisis through a robust standard error approach. The empirical findings indicate that the intraday market behavior an unusual balanced;the volatility and trading volume imbalance and the return trends are losing overwhelmingly. The consequence is that the first half-hour return will forecast the last half-hour return of the S&P500, but during the pandemic shock, the last half-hour of both stock markets will not have a significant impact on intraday momentum. Additionally, market timing strategy analysis is a significant factor in the stock market because it shows the perfect trading time, decides investment opportunities and which stocks will perform well on this day. Besides, we also found that when the volatility and volume of the S&P500 are both at a high level, the first half-hour has been a positive impact, while at the low level, the CSI300 has a negative impact on the last half-hour. In addition, this shows that the optimistic effect and positive outlook of the stockholders for the S&P500 is in the first half-hours after weekend on Monday morning because market open during the weekend holiday, and the mentality of every stockholder's indicate the positive impression of the stock market.
ABSTRACT
The Covid-19 pandemic has caused changes in the social and economic environments for healthcare. Particularly, to avoid spreading the Coronavirus pandemic, release the stress among healthcare workers, and make them work effectively during the epidemic, high-reliability healthcare organizations give great importance to the improvement of their functions. This study aims to show the importance of high-reliability healthcare organizations comparing their effectiveness during a pandemic by applied qualitative research method with many statistical analyses. In order to achieve the aim of the study, a Likert scale survey technique is used to collect the data by using an online survey. 280 healthcare workers filled the survey from January 17, 2021, to February 22, 2021. Based on the outcomes of the analyses, it has been found that such functions as shared knowledge pattern, provision of self-care, awareness of the coronavirus consequences at the workplace of high-reliability healthcare organizations have a positive and significant relationship at p < 0.01 level with taken appropriate measures against coronavirus variable. Self-awareness of organizational role, organizational resources to provide safety, flexibility of work, environmental safety, and collective mindfulness do not have any relationship with the appropriate measures against Covid-19 variable. This outcome indicates that shared knowledge pattern, provision of self-care, and awareness of the coronavirus consequences at the workplace have a more important role in combating Covid-19 in high-reliability healthcare organizations. © Imran Sarihasan, Judit Oláh, Main Al-Dalahmeh, Allam Yousuf, Krisztina Dajnoki, 2021
ABSTRACT
This study aims to examine the impact of COVID-19 and sustainable e-commerce in Hungary and Kenya. COVID-19 has devastated the global economy, resulting in financial and job losses. Routine changes in spending have moved the focus from non-essential to essential items, due to the impact of COVID-19, the associated economic meltdown, and the deterioration of people’s physical and mental health. However, e-commerce can be a better option to stop the spread of COVID-19 due to its real benefits and usefulness in solving the challenges faced. The methodology used in this paper is the collection of primary data from an online survey questionnaire, and secondary data from several databases,e.g.,the World Health Organisation (WHO) and Johns Hop-kins Centre websites. The results show the negative impact of COVID-19 on society and the economy, as well as the positive and significant effects ofthe growth of e-commerce during COVID-19, where most of the goods being purchased are medical supplies: masks, medicines, and food. This has been made possibleby the rise of e-commerce platforms as a link in sustainable e-commerce after the significant disruption to the worldwide supply chain due to total lockdown. E-commerce has shown growth during the COVID-19 pandemic period as a sustainable platform. In conclusion, this study proposes policies that support e-commerce in developing countries during and after COVID-19. Furthermore, theoretical, and managerial implications are proposed in the study. It is high time to warn businesses to adopt information and communications technology (ICT) to flourish and thrive during times of financial and economic hardship, such as the use of e-commerce with the right policies enacted to support sustainable e-commerce. © 2021, WSB University. All rights reserved.