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Record W3116952265 · doi:10.5267/j.ijdns.2020.11.006

The effect of digital technology development on economic growth

2020· article· en· W3116952265 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

venuePublished in a venue whose home country is Canada.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueInternational Journal of Data and Network Science · 2020
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicEconomic Issues in Ukraine
Canadian institutionsnot available
Fundersnot available
KeywordsGross domestic productReal gross domestic productUkrainianForeign direct investmentEconomicsInvestment (military)Digital economyEconomic indicatorBusinessEconomyIndustrial organizationMacroeconomicsComputer science

Abstract

fetched live from OpenAlex

The article simulates the impact of the digital technologies’ development on economic growth, which makes it possible to find ways to improve the quality of various spheres of life and identify areas of the economy, the accelerated digitalization of which will ensure an increase in gross domestic product (GDP). The research used groupings of economic activities that directly influence the development of the digital economy. Using the data of regression models, the coefficients of GDP elasticity from the development of the studied sectors were calculated and used to forecast GDP under the development influence of the studied sectors while maintaining the existing trends. The dynamics of the e-commerce market development in Ukraine, the dynamics of production volumes of products (services) of the main types of economic activities in the field of digital transformation of the economy in Ukraine, the dynamics of financial results of enterprises in the information and telecommunications sector in Ukraine, the dynamics of capital investments in the field of information and communications of Ukraine, the dynamics of foreign investment in the development of the type of economic activity “information and telecommunications” in Ukraine, the dynamics of the development of the main areas of digitalization of the Ukrainian economy in 2010-2018 and the dynamics of GDP in actual prices were revealed. A correlation and regression analysis of the impact of the main indicators of the digital technologies sectors development on Ukraine's GDP is also carried out. The forecast extrapolation trend of production growth volumes of products and services in the information sector of Ukraine was built. A forecast of GDP growth in Ukraine has been constructed, taking into account the processes of digitalization of the economy in accordance with certain trends. The forecast dynamics of changes in GDP under the influence of the IT sector development until 2023 was also illustrated. It was found that Ukraine lags significantly behind most developed countries in terms of the level of industrial production development of information and communication technologies and equipment, Ukraine is completely import-dependent in this area. It has been proved that stimulating the development of information and communication technologies has significant prospects for activating digitalization processes in all spheres of the economy and society and increasing GDP.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.874
Threshold uncertainty score0.333

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0020.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.028
GPT teacher head0.265
Teacher spread0.237 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it