• The Journal of Asian Finance, Economics and Business
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• v.7 no.7
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• pp.131-137
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• 2020

The research investigates the impact of the lockdown period caused by the COVID-19 to the stock market of India. The study examines the extent of the influence of the lockdown on the Indian stock market and whether the market reaction would be the same in pre- and post-lockdown period caused by COVID-19. Market Model Event study methodology is used. A sample of 31 companies listed on Bombay Stock Exchange (BSE) are selected at random for the purpose of the study. The sample period taken for the study is 35 days (24 February-17 April, 2020). An event window of 35 days was taken with 20 days prior to the event and 15 days during the event. The event (t1) being the official announcement of the lockdown. The results indicate that the market reacted positively with significantly positive Average Abnormal Returns during the present lockdown period, and investors anticipated the lockdown and reacted positively, whereas in the pre-lockdown period investors panicked and it was reflected in negative AAR. The study finds evidence of a positive AR around the present lockdown period and confirms that lockdown had a positive impact on the stock market performance of stocks till the situation improves in the Indian context.

• International Journal of Computer Science & Network Security
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• v.22 no.4
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• pp.39-46
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• 2022

The spread of Omicron, a mutated version of COVID-19 across several countries is leading to the discussion of lockdown once again for curbing the spread of the new virus. In this context, this research is showing the impact of lockdown for the successful control of the COVID-19 pandemic in Saudi Arabia. The outbreak of the COVID-19 pandemic around the globe has affected Saudi Arabia with around 2,37,803 confirmed cases within the initial 4 months of transmission. Saudi Arabia has announced a 21-day lockdown from March 23, 2020, to reduce the transmission of the COVID-19 pandemic. Machine Learning-based, Multinomial logistic regression was applied to understand the relationship between daily COVID-19 confirmed cases and lockdown in the 17 most-affected cities of KSA. We used secondary published data from the Ministry of Health, KSA daily dataset of COVID-19 confirmed case counts. These 17 cities were categorized into 4 classes based on lockdown dates. A total of three scenarios such as night lockdown, full lockdown, and no lockdown have been analyzed with the total number of confirmed cases with 4 classes. 15 out of 17 cities have shown a strong correlation with a confidence interval of 95%. These findings provide evidence that the COVID-19 pandemic may be partially suppressed with lockdown measures.

• Asia Marketing Journal
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• v.24 no.3
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• pp.109-120
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• 2022

The COVID-19 lockdown has had an unprecedented impact on people in various ways. This study evaluates the effect of lockdown repeal from both marketing and public-policy perspectives. Combining the Bayesian multilevel model with the difference-in-differences design, we find that a lockdown repeal has had a negative impact on socialization. Furthermore, the results show that those who have a low level of risk perception are less affected by lockdown repeal. Also, the negative effect of lockdown repeal varies depending on past socialization behaviors; that is, the lockdown-repeal effect is attenuated for those who socialized more than others in the past. Our findings contribute to the intersection of public policy and marketing literature and provide both academic and practical implications.

• IEMEK Journal of Embedded Systems and Applications
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• v.17 no.1
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• pp.59-65
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• 2022

Virtual memory is used as the method to ensure the safety of the system through memory protection in the real-time system. TLB miss caused by using virtual memory makes the real-time system WCET more pessimistically. TLB lockdown can be applied as a method to improve this problem. However, processors with limited TLB lockdown entries, a selection criterion is needed to efficiently utilize the TLB lockdown entry. In this paper, the most frequently accessed virtual pages in the process are applied to the TLB lockdown by analyzing memory profiling. The results showed that micro data TLB miss stall cycle and main data TLB miss stall cycle of the processor decreased by at least 4.7% and up to 29.7%.

• Asian Journal for Public Opinion Research
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• v.8 no.3
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• pp.393-406
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• 2020

The discourse on the lockdown in Indonesia is getting stronger due to the increasing number of positive cases of the coronavirus and the death rate. As of August 12, 2020, the confirmed number of COVID-19 cases in Indonesia reached 130,718. There were 85,798 victims who have recovered and 5,903 who have died. Data show a significant increase in cases of COVID-19 every day. For this reason, there needs to be an evaluation of the government policy of the Republic of Indonesia in dealing with the COVID-19 pandemic in Indonesia. An evaluation of policies for handling the pandemic must include public opinion to determine any weaknesses of this policy. The development of public opinion about the lockdown policy can be understood through social media. During the COVID-19 pandemic, measuring public opinion through traditional methods (surveys) was difficult. For this reason, we utilized big data on social media as research data. The main purpose of this study is to understand public opinion on the lockdown policy in overcoming the COVID-19 pandemic in Indonesia. The things observed included: volume of Twitter users, top influencers, top tweets, and communication networks between Twitter users. For the methodological development of future public opinion research, the researchers outline the obstacles faced in researching public opinion based on big data from Twitter. The research results show that the lockdown policy is an interesting issue, as evidenced by the number of active users (79,502) forming 133,209 networks. Posts about the lockdown on Twitter continued to increase after the implementation of the lockdown policy on April 10, 2020. The lockdown policy has caused various reactions, seen from the word analysis showing 14.8% positive sentiment, 17.5% negative, and 67.67% non-categorized words. Sources of information who have played the roles of top influencers regarding the lockdown policy include: Jokowi (the president of the Republic of Indonesia), online media, television media, government departments, and governors. Based on the analysis of the network structure, it shows that Jokowi has a central role in controlling the lockdown policy. Several challenges were found in this study: 1) choosing keywords for downloading data, 2) categorizing words containing public opinion sentiment, and 3) determining the sample size.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.7
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• pp.2169-2190
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• 2022

The COVID-19 pandemic has affected many aspects of human life. The pandemic not only caused millions of fatalities and problems but also changed public sentiment and behavior. Owing to the magnitude of this pandemic, governments worldwide adopted full lockdown measures that attracted much discussion on social media platforms. To investigate the effects of these lockdown measures, this study performed sentiment analysis and latent Dirichlet allocation topic modeling on textual data from Twitter published during the three lockdown waves in Malaysia between 2020 and 2021. Three lockdown measures were identified, the related data for the first two weeks of each lockdown were collected and analysed to understand the public sentiment. The changes between these lockdowns were identified, and the latent topics were highlighted. Most of the public sentiment focused on the first lockdown as reflected in the large number of latent topics generated during this period. The overall sentiment for each lockdown was mostly positive, followed by neutral and then negative. Topic modelling results identified staying at home, quarantine and lockdown as the main aspects of discussion for the first lockdown, whilst importance of health measures and government efforts were the main aspects for the second and third lockdowns. Governments may utilise these findings to understand public sentiment and to formulate precautionary measures that can assure the safety of their citizens and tend to their most pressing problems. These results also highlight the importance of positive messaging during difficult times, establishing digital interventions and formulating new policies to improve the reaction of the public to emergency situations.

• Journal of Trauma and Injury
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• v.35 no.2
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• pp.108-114
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• 2022

Purpose: The coronavirus disease 2019 (COVID-19) pandemic has had major effects worldwide, including sudden and forceful setbacks to the healthcare system. The COVID-19 pandemic has also led to changes in the plastic and reconstructive management of emergency cases, including those due to road traffic accidents. This study analyzed changes in patterns of plastic surgery emergencies and modifications in consultation policies to minimize the exposure of healthcare workers. Methods: Data on plastic surgery emergency calls received from the trauma and emergency department were collected for a period of 2 months before and during lockdown. The data were then analyzed with respect to the cause, mechanism, and site of the injury, as well as other variables. Results: During lockdown, there was a 40.4% overall decrease in the plastic surgery emergency case volume (168 vs. 100). The average daily number of consultations before lockdown was 2.8 as compared to 1.6 during lockdown. Road traffic accidents remained the most common mechanism of injury in both groups (45.8% vs. 39.0%) but decreased in number during the lockdown (77 vs. 39). Household accidents, including burns, were the second most common cause of injury in both phases (7.7% vs. 20.0%), but their proportion increased significantly from 7.7.% to 20.0% in the lockdown phase (P=0.003). The percentage of minor procedures done in the emergency department increased from 53.5% to 72.0% during lockdown (P=0.002). Procedures in the operating room decreased by 73.1% during lockdown (67 vs. 18, P=0.001). Conclusions: The COVID-19 pandemic and lockdown orders in India greatly influenced trends in traumatic emergencies as observed by the plastic surgery team at our tertiary care center. Amidst all the chaos and limitations of the pandemic period, providing safe and prompt care to the patients presenting to the emergency room was our foremost priority.

• The Journal of Asian Finance, Economics and Business
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• v.8 no.5
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• pp.777-784
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• 2021

This study explores the impact of COVID-19 pandemic and the lockdown policies that are used to tackle the pandemic on stock market returns in Indonesia. This study uses fixed-effects panel-data regression method to evaluate the impact of the growth in COVID-19 total confirmed cases and death as well as the lockdown policies on daily stock returns of 272 firms that are listed on the Indonesia Stock Exchange's main board and operate in the real sector from 2 March 2020 to 27 November 2020. The study confirms the significantly adverse impact of growth in the total of confirmed cases and death due to COVID-19 on Indonesia's daily stock returns. Moreover, the lockdown policies regardless how strict they are, have a positive and significant impact on the Indonesia's daily stock returns. This study further considers the different impact of COVID-19 pandemic on each of eight observed sectors; where the sector of property as well as trade, service and investment have a significantly negative performance; while the sector of basic industry, consumer goods and mining have a significantly better performance. This study suggests that COVID-19 pandemic and the lockdown policies have a mixed impact on the Indonesia's stock market returns.

• The Journal of Asian Finance, Economics and Business
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• v.8 no.5
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• pp.707-715
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• 2021

This article examines the potential impact of the Covid-19 Lockdown on earnings manipulation and stock market sensitivity to earnings announcements. It also explores the effects of earnings manipulation after the COVID-19 outbreak on the share price sensitivity to the earnings disclosures. The study uses a quantitative method to analyze the financial data consisting of 87 firms listed on the Iraq Stock Exchange for the period from 2018 to 2020, which constitutes a total of (174 observations). We used Ohlson (1995) model to estimate financial market reaction and sensitivity to earnings manipulation fluctuations and accounting information. The results show that companies practice earnings manipulation to maintain earnings over a time series, which means a negative impact of earnings manipulation on all earnings measures' value relevance (EPS, BVS, and CFS). Accordingly, earnings manipulation negatively influences investor behavior in the financial market, based mainly on financial reporting. The value relevance of financial reports has also decreased because of the COVID-19 outbreak and related economic Lockdown. These results reflect a long-term adverse impact of earnings manipulation on investor behavior and financial statements reliability.

• International Journal of Knowledge Content Development & Technology
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• v.11 no.2
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• pp.7-21
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• 2021

The study was a descriptive cross-sectional survey which investigated the reading preferences of secondary school students in Nigeria during the lockdown occasioned by COVID-19 pandemic. A hundred secondary school students in Ile- Ife and Ilesa in Osun State, Nigeria were the study respondents. Close ended self-administered questionnaire was used to obtain data. Of the one hundred questionnaire which were applied to the study respondents, ninety-three were retrieved. Data obtained were analyzed using simple frequencies and percentages. The study established that majority of respondents were not pressured to read but read for pleasure. Preference for a wide range of fiction and non-fiction books which was read for purposes ranging from academic, social, relaxation and information was indicated by respondents. Availability of reading materials determined reading preference of majority of respondents as many could not afford to access electronic books whether free or not. The researchers recommended that different types of reading materials that suit the reading preferences and meet the diverse purpose of reading should be provided for the secondary school students during lockdown to improve their reading habits. Public libraries should function during this lock down period within the guidelines of the appropriate health authorities, while school libraries should be equipped to offer virtual services during the lockdown and the students should be exposed to e-books for their reading pleasure.