Scientometrics
Mariam Keshvari; Farideh Osareh; Faramarz soheili
Abstract
Background/Purpose: the most important goal of the present dissertation is the designing of the top authors’ scientific productivity model so as to achieve a combined set of quantitative and qualitative indicators and items influencing the scientific productivity and take a step towards the improvement ...
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Background/Purpose: the most important goal of the present dissertation is the designing of the top authors’ scientific productivity model so as to achieve a combined set of quantitative and qualitative indicators and items influencing the scientific productivity and take a step towards the improvement of the scientific productivity’s evaluation.Methodology: the present study has been conducted based on a mixed (quantitative-qualitative) method; the qualitative section uses the ideas and notions of the experts in the scientific productivity domain and the quantitative section deals with the application of the statistical tests and scientometrics’ indicators. Two statistical populations have taken part in the present study: 12 domestic and foreign experts in the scientific productivity field; 235 highly cited authors from around the globe. The study data have been collected using checklist, questionnaires and Clarivate Analytics-Web Of Science database. To analyze the data, SPSS 19 and LISREL 8 were used. The scientific productivity model has been verified based on the experts’ ideas in the population of the top authors using second order confirmatory factor analysis.Findings: the present study’s findings indicate that the scientific productivity model based on the experts’ notions in population of the studied top authors features a favorable goodness of fit. Considering the factor loads in the confirmatory factor analysis, the “bibliometrics component” with a factor load of 1, the “individual component” with a factor load of 0.69 and the “organizational component” with a factor load of 0.63 in the population of highly cited authors are influential in the scientific productivity model. Discussion and Conclusion: the findings of the present study indicate that a collection of organizational, individual and bibliometric factors influence the scientific productivity of the top authors and the tri-component model features a favorable goodness of fit. Combination of the quantitative and qualitative items can offer a more thorough image of the status of the individuals’ scientific productivity; the items offered in this model can be employed as solution by the individuals and organizations for enhancing scientific productivity.
