European Journal of Computer Science and Information Technology (EJCSIT)

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Multiple Prediction of Research Productivity: H-Index

Abstract

Research Productivity, h-index, of faculty is predicted on their job-satisfaction, persistence, optimism, self-discipline, motivation, and procrastination. Never has been a better answer than H-Index in the history of science to the question of how to quantify the cumulative productivity, accomplishments, impact, and relevance of a researcher’s scientific work. Multiple Prediction design of correlational research method was adopted in the investigation. Faculty in natural sciences in universities around the world constituted the population. A multistage random sample of 180 faculty, 30 from each continent 7 or 8 from each of 24 universities, and 4 universities from each of 6 continents made the sample. Results showed statistically significant 21 correlation coefficients among the seven variables. The six independent variables taken together, significantly predicted research productivity [F (6,   173) = 72.379, p < .01, R2 = .715]. Each of persistence, optimism, self-discipline, and procrastination unilaterally predicted research productivity significantly. Neither job-satisfaction nor motivation singlehandedly predicted research productivity. Multiple regression equation was created for the prediction of research productivity from the six independent variables. Predicted values and residuals for each participant were tabulated.

Keywords: Continents in the world, Correlational research method., Faculty, H-index; Multiple prediction, Job Satisfaction, Motivation, Optimism, Persistence, Procrastination, Research productivity, Research productivity h-index, Self-discipline

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This work by European American Journals is licensed under a Creative Commons Attribution-NonCommercial-NoDerivs 4.0 Unported License

 

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Email ID: editor.ejcsit@ea-journals.org
Impact Factor: 7.80
Print ISSN: 2054-0957
Online ISSN: 2054-0965
DOI: https://doi.org/10.37745/ejcsit.2013

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