scholarly journals Analysis of COVID-19 infections in GCC countries to identify the indicators correlating the number of cases and deaths

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Ben George Ephrem ◽  
Samuel Giftson Appaadurai ◽  
Balaji R. Dhanasekaran
Keyword(s):  
Strong Correlation ◽  
Total Population ◽  
Labour Force ◽  
Research Work ◽  
Research Paper ◽  
Data Set ◽  
Content Type ◽  
Road Map ◽  
Gcc Countries ◽  
The World

Purpose The world has faced various epidemic situations caused by different viruses such as SARS-Cov, MERS-Cov, Ebola and many more during the past few decades, SARS-Cov-2 (COVID-19) is the genetic variant of newly the discovered Coronavirus, which has been believed to spread from China during December 2019, which has created a catastrophic effect for the whole world. In the first quarter of 2020, the virus started to spread to different countries, in addition, the severity of cases, the mortality rate and the recovery rate varied between countries. In the Sultanate of Oman and different parts of the world, the COVID started to spike during the end of March 2020. In this research paper, COVID data for Gulf Cooperation Council (GCC) countries are extracted and analysis has been made based on different parameters. The analysis has been divided into two categories – the first part focuses on the total number of cases, the total number of recoveries and the total number of deaths and comparison has been made for different GCC countries, from these analyses, it gives a clear picture of the days of a particular month, which contributes to the increase of COVID cases. The second part focuses on finding out the indicators that are correlating with the COIVD-19 cases and deaths; it has been found that there is a very strong correlation between the total population and labour force of every GCC country with the corresponding COVID cases and deaths. Design/methodology/approach The entire research steps involved starts with data collection, data pre-processing and data analysis. The analysis has been divided into two categories – the first part focuses on the total number of cases, the total number of recoveries and the total number of deaths and comparisons has been made for different GCC countries. The second part focuses on finding out the indicators that are correlating with COIVD-19 cases and deaths. Findings It has been found that there is a very strong correlation between the total population and labour force of every GCC country with the corresponding COVID cases and deaths. Research limitations/implications The data set considered is limited and can be extended further. Social implications This research paper definitely provides a road map for practice, as this research provides details about the total number of active cases, death based on the days in different GCC countries. It has been observed that during the end of each month and during weekends, the total number of cases increases drastically, so by taking into consideration the governing bodies can impose a lockdown during these spike durations. In addition to it, the citizens and residents should make a practice to avoid or limit their movement during the spike durations, which was analysed by this research work. Originality/value The idea is the own idea and not copied from any other source.

Twitter users exhibited coping behaviours during the COVID-19 lockdown: an analysis of tweets using mixed methods

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Ruchi Mittal ◽  
Wasim Ahmed ◽  
Amit Mittal ◽  
Ishan Aggarwal
Keyword(s):  
Data Analysis ◽  
The Body ◽  
Data Set ◽  
Content Type ◽  
Twitter Data ◽  
Long Run ◽  
The World ◽  
Twitter Users ◽  
The Government ◽  
Using Data

Purpose Using data from Twitter, the purpose of this paper is to assess the coping behaviour and reactions of social media users in response to the initial days of the COVID-19-related lockdown in different parts of the world. Design/methodology/approach This study follows the quasi-inductive approach which allows the development of pre-categories from other theories before the sampling and coding processes begin, for use in those processes. Data was extracted using relevant keywords from Twitter, and a sample was drawn from the Twitter data set to ensure the data is more manageable from a qualitative research standpoint and that meaningful interpretations can be drawn from the data analysis results. The data analysis is discussed in two parts: extraction and classification of data from Twitter using automated sentiment analysis; and qualitative data analysis of a smaller Twitter data sample. Findings This study found that during the lockdown the majority of users on Twitter shared positive opinions towards the lockdown. The results also found that people are keeping themselves engaged and entertained. Governments around the world have also gained support from Twitter users. This is despite the hardships being faced by citizens. The authors also found a number of users expressing negative sentiments. The results also found that several users on Twitter were fence-sitters and their opinions and emotions could swing either way depending on how the pandemic progresses and what action is taken by governments around the world. Research limitations/implications The authors add to the body of literature that has examined Twitter discussions around H1N1 using in-depth qualitative methods and conspiracy theories around COVID-19. In the long run, the government can help citizens develop routines that help the community adapt to a new dangerous environment – this has very effectively been shown in the context of wildfires in the context of disaster management. In the context of this research, the dominance of the positive themes within tweets is promising for policymakers and governments around the world. However, sentiments may wish to be monitored going forward as large-spikes in negative sentiment may highlight lockdown-fatigue. Social implications The psychology of humans during a pandemic can have a profound impact on how COVID-19 shapes up, and this shall also include how people behave with other people and with the larger environment. Lockdowns are the opposite of what societies strive to achieve, i.e. socializing. Originality/value This study is based on original Twitter data collected during the initial days of the COVID-19-induced lockdown. The topic of “lockdowns” and the “COVID-19” pandemic have not been studied together thus far. This study is highly topical.

Which professional skills value more under digital transformation?

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Sofia Paklina ◽  
Elena Shakina
Keyword(s):  
Text Mining ◽  
Labour Market ◽  
Empirical Evidence ◽  
Labour Force ◽  
Sample Selection ◽  
Large Data ◽  
Hedonic Pricing ◽  
Data Set ◽  
Content Type ◽  
Computing Skills

PurposeThis study seeks to explore the demand side of the labour market influenced by the digital revolution. It aims at identifying the new composition of skills and their value as implicitly manifested by employers when they look for the new labour force. The authors analyse the returns to computing skills based on text mining techniques applied to the job advertisements.Design/methodology/approachThe methodology is based on the hedonic pricing model with the Heckman correction to overcome the sample selection bias. The empirical part is based on a large data set that includes more than 9m online vacancies on one of the biggest job boards in Russia from 2006 to 2018.FindingsEmpirical evidence for both negative and positive returns to computing skills and their monetary values is found. Importantly, the authors also have found both complementary and substitutional effects within and between non-domain (basic) and domain (advanced) subgroups of computing skills.Originality/valueApart from the empirical evidence on the value of professional computing skills and their interrelations, this study provides the important methodological contribution on applying the hedonic procedure and text mining to the field of human resource management and labour market research.

Improving the detection and reporting of suspicious financial transactions: the Spanish case

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Joel Harry Clavijo Suntura
Keyword(s):  
European Community ◽  
Money Laundering ◽  
Financial Institution ◽  
Research Work ◽  
Research Paper ◽  
External Control ◽  
Content Type ◽  
European Community Directive ◽  
Control Body ◽  
Community Directive

Purpose The purpose of this paper is to analyze the obligation of regulated entities to detect unusual and suspicious transactions and to report them to external control bodies, as established by the Financial Action Task Force (FATF) recommendations, the European Community Directive and also the Spanish regulations for the Prevention of Money Laundering. This research paper also aims to create a model to identify and report suspicious transactions to improve financial institutions’ current procedures. Design/methodology/approach According to the Spanish regulations which comply with the FATF recommendations and the European Community Directive on the Prevention of Money Laundering, regulated entities must detect unusual and suspicious transactions. Within this framework, the present research work analyzes both criteria and procedures used by the regulated entities to report suspicious operations. It also assesses the efficiency of the reports sent to an external control body. For this purpose, both analytical and interpretative methods are used in this research paper. Findings In Spain, the current procedures followed by regulated entities to analyze unusual transactions are complex. This results in difficulties to report suspicious transactions involving money laundering. As a consequence, the cases of suspicious transactions reported to the external control body are often unclear and the related process is inefficient. Originality/value The creation of a harmonized model with the aim of detecting suspicious operations and analyzing them will improve the detection and the effectiveness of the suspicious operations procedure which are reported to the external control body. However, such unified model should take into account the currently used activities proposed by each financial institution.

Structure and growth of employment: evidence from India KLEMS data

2019 ◽  
Vol 12 (2) ◽  
pp. 202-228
Author(s):  
Suresh Chand Aggarwal ◽  
Bishwanath Goldar
Keyword(s):  
Growth Rate ◽  
Employment Growth ◽  
Labour Force ◽  
Participation Rate ◽  
Labour Force Participation ◽  
Recent Period ◽  
Data Set ◽  
Labour Force Participation Rate ◽  
Content Type ◽  
Employment Elasticity

Purpose This study aims to analyze the structure and trend in employment in the Indian economy between 1980-8081 and 2015-2016. Design/methodology/approach Use of India KLEMS data set. Estimate growth rate of employment and discuss employment prospects using “Point” employment elasticity. Findings Whilst India’s GDP growth rate has been quite impressive since the reforms of 1991, the rate of employment growth, especially in the recent period of 2003-2015, has been quite slow (1 per cent) with low employment elasticity (0.1). The pattern of employment growth has also been imbalanced with slow rate of employment growth in manufacturing and rapid growth rate in the construction sector. India now also has low labour force participation rate and a large share of informal employment in the economy. Research limitations/implications The limitation is the lack of reliable data on employment for the recent period. Practical implications With overall low employment elasticity, India would have to explore sectors where more employment opportunities could be created. Social implications India has to create not only more jobs but also “good” jobs. Originality/value The India KLEMS data provide a time series for employment, which has been used in this paper to find “Point” elasticity instead of arc elasticity of employment and is an improvement over existing employment elasticity estimates.

The impact of national cultural values on retail structure

2016 ◽  
Vol 33 (6) ◽  
pp. 894-920 ◽  
Author(s):  
Boryana V. Dimitrova ◽  
Bert Rosenbloom ◽  
Trina Larsen Andras
Keyword(s):  
Cultural Values ◽  
National Culture ◽  
Retail Operations ◽  
Data Set ◽  
Content Type ◽  
The World ◽  
Primary Focus ◽  
Retail Structure ◽  
The Impact ◽  
The Relationship

Purpose The purpose of this paper is to investigate the relationship between national cultural values and retail structure. Design/methodology/approach The authors use a panel data set of 67 countries over the period 1999-2012. Findings The results demonstrate that national cultural values, measured with the World Values Survey’s traditional/secular-rational and survival/self-expression dimensions, affect retail structure. Research limitations/implications While marketing scholars have examined the relationship between demographic and competitive factors and retail structure, there has been a substantial body of anecdotal evidence showing that national culture can also drive retail structure development. In order to enhance the understanding of the relationship between national culture and retail structure, the authors empirically examine the impact of national cultural values on retail structure. Originality/value This study is the first one to empirically examine the impact of national culture on retail structure. The authors thus help advance retail structure research the primary focus of which has been on investigating the impact of demographic and competitive factors on retail structure. This study is especially relevant to international retail managers who coordinate retail operations in multiple countries around the world. These managers need insight into the impact of national cultural values on retail structure in order to devise effective retail strategies for each host market.

Financial development, human capital and its impact on economic growth of emerging countries

2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Aaqib Sarwar ◽  
Muhammad Asif Khan ◽  
Zahid Sarwar ◽  
Wajid Khan
Keyword(s):  
Economic Growth ◽  
Human Capital ◽  
Financial Development ◽  
Emerging Economies ◽  
Generalized Method Of Moments ◽  
Emerging Countries ◽  
Data Set ◽  
Content Type ◽  
The World ◽  
The Impact

Purpose This paper aims to investigate the critical aspect of financial development, human capital and their interactive term on economic growth from the perspective of emerging economies. Design/methodology/approach Data set ranged from 2002 to 2017 of 83 emerging countries used in this research and collected from world development indicators of the World Bank. The two-step system generalized method of moments is used to conduct this research within the endogenous growth model while controlling time and country-specific effects. Findings The findings of the study indicate that financial development has a positive and significant effect on economic growth. In emerging countries, human capital also has a positive impact on economic growth. Financial development and human capital interactively affect economic growth for emerging economies positively and significantly. Research limitations/implications The data set is limited to 83 emerging countries of the world. The time period for the study is 2002 to 2017. Originality/value This research contributes to the existing literature on human capital, financial development and economic growth. Limited research has been conducted on the impact of financial development and human capital on economic growth.

Analyzing time pressure for software economics

2019 ◽  
Vol 32 (5) ◽  
pp. 758-777
Author(s):  
Seher Razzaq ◽  
Jianglin Huang ◽  
Hongyi Sun ◽  
Min Xie
Keyword(s):  
Communication Complexity ◽  
Time Pressure ◽  
Research Work ◽  
Well Being ◽  
Data Set ◽  
Content Type ◽  
Team Members ◽  
Software Economics ◽  
Free Environment ◽  
The Impact

Purpose The research on people and project factors is found extensively in general but not specific to software engineering. Secondly, the existing research has not concentrated on the communication and time complexity of the teams on software economics. The purpose this paper is to develop a model to investigate and quantify the impact of time pressure (TP) on software economics through the communication influence of software team sizes (TS). Design/methodology/approach A research model and five hypotheses are developed based on the gaps in the literature. The data set from International Software Benchmarking Standards Group repository is used for testing the hypotheses. Findings Important findings include: smaller TS tends to exert less TP on average; TP is directly proportional to software economics, however; and TP does not affect the productivity required for the software. Research limitations/implications The study has the following implications: Selection of an appropriate TS for project completion that ensures minimum pressure on team members; and maximize software outcomes in stress-free environment. Practical implications This work is useful for organizations carrying out software projects with teamwork. The project managers can benefit from the results while planning the team factors for achieving the project goals. Social implications The results uphold not to exert pressure on the team as it will not only affect the duly completion of the project but also the well-being of employees. Originality/value The paper is the first one where the proposition of TP estimation is done using TS and communication complexity, and empirically evaluating the impact of TP on four major software economics are the major key contributions of this research work.

Patent Insurance: A Road Map Towards Sustainability of Patent Protection in India

2017 ◽  
Vol 12 (01) ◽  
Author(s):  
Pawan Gupta ◽  
Surabhi Goyal
Keyword(s):  
Conceptual Framework ◽  
Patent Protection ◽  
Research Paper ◽  
Strategic Decision ◽  
Road Map ◽  
Indian Context ◽  
The World ◽  
Conceptual Research

In today’s world of competitiveness and innovation, leading the world technologically is very important. Many economies have identified that patent protection is a very crucial strategic decision to lead in a technological industry. Patent insurance is one of the tools to support this thought. In this conceptual research paper, a trail has been to find the possibility of acceptance of patent insurance as a financial tool of securing the patents from infringements in India. Also, a conceptual framework is also framed in the form of suggestive measures to support the importance of such concept in Indian context.

What determines financial inclusion in Sub-Saharan Africa?

2017 ◽  
Vol 8 (1) ◽  
pp. 8-18 ◽  
Author(s):  
Sydney Chikalipah
Keyword(s):  
International Development ◽  
World Bank ◽  
Financial Inclusion ◽  
Sub Saharan Africa ◽  
Data Set ◽  
Content Type ◽  
The World Bank ◽  
The World ◽  
Sub Saharan ◽  
Ssa Countries

Purpose The purpose of this paper is to investigate the determinants of financial inclusion (FI) in Sub-Saharan Africa (SSA). Design/methodology/approach The paper uses the World Bank country-level data from 20 SSA countries for the year 2014. Findings The empirical findings in this study indicate that illiteracy is the major hindrance to FI in SSA. The findings provide useful information to government agencies and international development organisations. Also, the findings can help accelerate and strengthen FI strategies among SSA countries. Research limitations/implications Some countries were excluded from the final analysis due to lack of data. Practical implications In the last two decades, there has been renewed interest in fighting financial exclusion in Africa. Therefore, this study provide evidence which clearly shows that enhancing literacy levels in a country can immensely contribute towards building the financially inclusive societies in the SSA region. Originality/value To the best of the author’s knowledge, this is the first study to empirically test the determinants of FI in SSA using the World Bank FI data set. Furthermore, this is the first attempt to estimate the determinants of FI with a combined data of SSA countries.

Cointegration-causality analysis between terrorism and key macroeconomic indicators

2014 ◽  
Vol 41 (8) ◽  
pp. 664-682 ◽  
Author(s):  
Aisha Ismail ◽  
Shehla Amjad
Keyword(s):  
Research Work ◽  
Cointegration Analysis ◽  
Gdp Per Capita ◽  
Gdp Growth ◽  
Data Set ◽  
Content Type ◽  
Long Run ◽  
Macroeconomic Indicators ◽  
Per Capita ◽  
The Relationship

Purpose – The purpose of this paper is two folds: first, to analyze the long-run relationship between terrorism and key macroeconomic indicators (GDP growth, GDP per capita, inflation and unemployment) and second, to determine the direction of causality between these variables in Pakistan. Design/methodology/approach – The relationship between terrorism and various macroeconomic indicators is analyzed by applying Johansen cointegration analysis. Furthermore, the causality between terrorism and macroeconomic indicators is tested by applying Toda Yamamoto Granger causality test. Findings – The results show that there exists a long-run relationship between terrorism and key macroeconomic indicators. Furthermore, the results suggest that there exists a bi-directional causality between terrorism and inflation. The causality between GDP per capita, unemployment, GDP growth and terrorism is unidirectional. Originality/value – There is a lack of research work conducted to analyze the long-run relationship and direction of causation between terrorism and various macroeconomic indicators specifically for Pakistan. The current paper fills the gap in the literature by using sophisticated econometric techniques and recent data set to provide the evidence of the relationship between terrorism and various macroeconomic indicators.

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