Purpose
The outbreak of COVID-19 in China has spread to the whole world within a short period. The spread of COVID-19 has caused innumerable economic and social losses. The coronavirus spread directly from individual to individual. WHO and other governing bodies made guidelines and remedial activities to minimize the spread of COVID-19. This study aims to analyze and prioritize infection prevention and control activities for SARS-CoV-2.
Methods
An analytical study was conducted between medical representatives and scientists to check the impact of these precautionary measures (social distancing, shaking hands and hugging peoples, unnecessary touching things, hygiene, and sharing personal items) on COVID-19. The Analytical Hierarchical Process (AHP) method has been utilized to evaluate and prioritize the preventive measures of COVID-19.
Results
The results of this investigation shows, unnecessary travel, 3Cs, and touching own body parts should be avoided. Wearing a mask and proper hand washing are important to reduce the spread of coronavirus.
Conclusion
The SARS-CoV-2 has affected more than 11 million people around the world. The second spike of COVID-19 is also alarming for people. It is important to follow the instruction provided by the WHO, CDC, and other national and international governing bodies. The AHP method was used to check various measures that are spreading the coronavirus disease. It demonstrated that 3Cs (spaces that are closed, crowded, and involve close contacts) and travel, shaking hand, unnecessary touching own body parts should be avoided.
Purpose
The organizational success to achieve and maintain its competitiveness is ascribed in the effectiveness of its knowledge management (KM) system, which depends on its employees’ impetus to exhibit knowledge sharing behavior. When an employee hides knowledge, an organization somewhat loses its part of knowledge, which causes loss to the organization eventually. This study aims to examine the impact of personality traits and one’s ethnicity on knowledge hiding behavior (KHB) by focusing on mediating role of team member exchange (TMX).
Design/methodology/approach
A total 308 questionnaires are collected from the public sector organizations (Livestock and Dairy Development Department, Punjab, Pakistan), out of them 300 are used in the analysis. Through Google e-survey form, cross-sectional data using convenience sampling are collected from the Gazetted officers (managerial level) of the department.
Findings
The paper provides empirical insights about three personality traits, i.e. openness, conscientiousness and neuroticism, and ethnicity have positive relation with KHB, whereas TMX as a mediator converts this positive relation into negative. Remaining two personality traits, i.e. extraversion and agreeableness, have negative relation with KHB, whereas TMX as a mediator strengthens this negative relationship with KHB.
Research limitations/implications
The broad context of research and large number of items made it difficult to collect the responses. In future studies, 50 items of big five should be replaced with mini scale. Empirical explanation of the relation between ethnicity and knowledge hiding is an addition to body of knowledge in general, particularly in context of Pakistan.
Practical implications
This study has the power to help managers in managing their team members and to understand what kind of personality and social group involvements promote knowledge sharing culture within the organization.
Originality/value
To broaden the understanding of KM domain, this study adds value in the relationship between big five personality traits, ethnicity and KHB of employees by finding the mediating effect of TMX in the context of Pakistani organizations.
Resilience is the capability of a system to adjust its functionality during a disturbance or perturbation. The present work attempts to quantify resilience as a function of reliability, vulnerability, and maintainability. The approach assesses proactive and reactive defense mechanisms along with operational factors to respond to unwanted disturbances and perturbation. This article employs a Bayesian network format to build a resilience model. The application of the model is tested on hydrocarbon-release scenarios during an offloading operation in a remote and harsh environment. The model identifies requirements for robust recovery and adaptability during an unplanned scenario related to a hydrocarbon release. This study attempts to relate the resilience capacity of a system to the system's absorptive, adaptive, and restorative capacities. These factors influence predisaster and postdisaster strategies that can be mapped to enhance the resilience of the system.
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