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Quantity versus quality in publication activity: knowledge production at the regional level

Published 15 Nov 2023 in econ.GN and q-fin.EC | (2311.08830v1)

Abstract: This study contributes to the ongoing debate regarding the balance between quality and quantity in research productivity and publication activity. Using empirical regional knowledge production functions, we establish a significant correlation between R&D spending and research output, specifically publication productivity, while controlling for patenting activity and socioeconomic factors. Our focus is on the dilemma of research quantity versus quality, which is analysed in the context of regional thematic specialization using spatial lags. When designing policies and making forecasts, it is important to consider the quality of research measured by established indicators. In this study, we examine the dual effect of research quality on publication activity. We identify two groups of quality factors: those related to the quality of journals and those related to the impact of publications. On average, these factors have different influences on quantitative measures. The quality of journals shows a negative relationship with quantity, indicating that as journal quality increases, the number of publications decreases. On the other hand, the impact of publications can be approximated by an inverse parabolic shape, with a positive decreasing slope within a common range of values. This duality in the relationship between quality factors and quantitative measures may explain some of the significant variations in conclusions found in the literature. We compare several models that explore factors influencing publication activity using a balanced panel dataset of Russian regions from 2009 to 2021. Additionally, we propose a novel approach using thematic scientometric parameters as a special type of proximity measure between regions in thematic space. Incorporating spatial spillovers in thematic space allows us to account for potential cross-sectional dependence in regional data.

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