Analyzing COVID-19 Impact on the Researchers Productivity through Their Perceptions
Source abstract
Abstract
Context: Since the end of 2019, the COVID-19 pandemic had a worst impact on world’s economy, healthcare, and education. There are several aspects where the impact of COVID-19 could be visualized. Among these, one aspect is the productivity of researcher, which plays a significant role in the success of an organization. Problem: There are several factors that could be aligned with the researcher’s productivity of each domain and whose analysis through researcher’s feedback could be beneficial for decision makers in terms of their decision making and implementation of mitigation plans for the success of an organization. Method: We perform an empirical study to investigate the substantial impact of COVID-19 on the productivity of researchers by analyzing the relevant factors through their perceptions. Our study aims to find out the impact of COVID-19 on the researcher’s productivity that are working in different fields. In this study, we conduct a questionnaire-based analysis, which included feedback of 152 researchers of certain domains. These researchers are currently involved in different research activities. Subsequently, we perform a statistical analysis to analyze the collected responses and report the findings. Findings: The results indicate the substantial impact of COVID-19 pandemics on the researcher’s productivity in terms of mental disturbance, lack of regular meetings, and field visits for the collection of primary data. Conclusion: Finally, it is concluded that researcher’s daily or weekly meetings with their supervisors and colleagues are necessary to keep them more productive in task completion. These findings would help the decision makers of an organization in the settlement of their plan for the success of an organization.
Source: openalex_inverted_index · Quality: baseline
Research context
OpenAlex topics: COVID-19 and Mental Health · COVID-19 Pandemic Impacts · Mental Health via Writing
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
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