Export of high-tech goods in the context of innovation transfer for social-economic development: factor analysis

dc.contributor.authorHabenko, M.
dc.date.accessioned2023-07-03T11:37:24Z
dc.date.available2023-07-03T11:37:24Z
dc.date.issued2023
dc.description.abstractThe purpose of the study is to determine factors that have the greatest influence on the growth of export of high-tech goods in the context of innovation transfer for social-economic development. Factor analysis tools, including principal component analysis and the Varimax rotation (orthogonal transformation) method in Statgraphics software, are used to identify the most significant indicators of the impact on export of high-tech goods, as a key determinant characterizing the quality of scientific and educational potential, and to determine the latent signs of their interaction. A modified logistic function is used to normalize input data for 11 investigated factors in a sample of 28 countries. Ten linear combinations of variables are obtained, which explain most of the data variability. The first four components have eigenvalues greater than or equal to 1.0. Together, they account for 88.520% of the variability of the original data. After orthogonal transformation by the Varimax method, the factor load matrix is obtained. The econometric models, which describes the influence of independent indicators on the export of high-tech goods, are represented. Next, the four most influential indicators from the 11 investigated factors are revealed, namely: the country’s research and development expenditure, GDP in current prices, research staff and researchers in the sector of business enterprises, the percentage of ICT staff from total employment. They are taken to develop multiple linear regression models, which describes the influence of independent indicators on the effective export of high-tech goods. The quality results of the factor analysis are confirmed using the Kaiser-Meier-Olkin test and the Bartlett test. Regression analysis with strict screening of non-significant variables using the Backward Stepwise Selection tool confirms the significance of the indicator of scientific research personnel and researchers in the sector of business enterprises, which has the greatest impact on the export of high-tech goods. A pair regression model is obtained, and it is confirmed that increase of research staff and researchers in the sector of business enterprises by 1% causes increase of export of high-tech goods in average by 0,73%.en_US
dc.identifier.citationHabenko, M. (2023). Export of high-tech goods in the context of innovation transfer for social-economic development: factor analysis. SocioEconomic Challenges, 7(2), 152-160. https://doi.org/10.21272/sec.7(2).152-160.2023.en_US
dc.identifier.urihttps://essuir.sumdu.edu.ua/handle/123456789/92259
dc.language.isoenen_US
dc.publisherSumy State Universityen_US
dc.rights.uriCC BY 4.0en_US
dc.subjectбізнесen_US
dc.subjectbusinessen_US
dc.subjectкоопераціяen_US
dc.subjectcoopetitionen_US
dc.subjectосвітаen_US
dc.subjecteducationen_US
dc.subjectвисокотехнологічнийen_US
dc.subjecthigh-techen_US
dc.subjectінноваційністьen_US
dc.subjectinnovationen_US
dc.subjectдосвідen_US
dc.subjectknowledgeen_US
dc.subjectНДДКРen_US
dc.subjectR&Den_US
dc.subjectнаукаen_US
dc.subjectscienceen_US
dc.subjectтехнологіїen_US
dc.subjecttechnologyen_US
dc.subjectтрансферen_US
dc.subjecttransferen_US
dc.titleExport of high-tech goods in the context of innovation transfer for social-economic development: factor analysisen_US
dc.typeArticleen_US

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