Evaluating the nexus of funding and scientific output in Kazakhstan

Abstract

This study examines the dynamics and effectiveness of investments in Kazakhstan’s research and development (R&D). The primary aim is to assess the efficiency of scientific research activities in Kazakhstan by analyzing the relationship between R&D investments and scientific outputs across different periods. As a methodological approach, Data Envelopment Analysis (DEA) calculates efficiency indicators by transforming multiple inputs into outputs. Descriptive analysis comprehensively explains trends and patterns in R&D funding, scientific publications, and patent registrations. The results reveal a substantial increase in R&D expenditure. Despite this, the share of domestic R&D expenditures from the gross domestic product (GDP) declined from 0.25% to 0.12%. The analysis also uncovered a significant surge in scientific publications, with Scopus publications increasing from 1,799 to 28,280 and Web of Science publications rising from 1,468 to 20,532 across the study period. However, a contrasting trend was observed in patent registrations, which decreased from 6,968 to 2,612, indicating potential inefficiencies in translating research into innovations. The study concludes that while Kazakhstan has demonstrated notable progress in enhancing research output, the decline in patent registrations relative to the increase in R&D investments underscores the need for strategic initiatives. These should strengthen industry-academia collaboration, enhance innovation infrastructure, and balance incentives for publications and patents, ensuring that R&D investments translate into tangible innovations and contribute effectively to the nation’s socio-economic development. Acknowledgment This research article has been supported bу the Ministry of Education and Science of the Republic of Kazakhstan within the project «Development of а model for evaluating the effectiveness of research activities of universities in Kazakhstan based on non-parametric and semi-parametric data analysis» (IRN AP13268842). А.I.Р. thanks the lnstitute of Solid-State Physics, University of Latvia. ISSP UL as the Center of Excellence is supported through the Framework Program for European universities, Union Horizon 2020, H2020-WIDESPREAD-01-2016-2017 TeamingPhase2, under Grant Agreement No. 739508, CAMART2 project.