GDII Methodology
GCI, GDI, and GDII
Fullscreen ViewTheoretical Basis
At the foundation of the GDII is French economist Jean-Baptiste Say’s theory of the three factors of production. Under this model, the value of goods is determined by the labor, capital, and land involved in their production. The GDII maps these physical factors to new digital counterparts: data, ICT talent, and digital and intelligent technologies. Together, these digital factors drive production in the digital economy. Data is like our new land. Its circulation and utilization drives national competitiveness. Digital and intelligent technologies, like networks, computing, storage, AI, and energy systems, are our new tools of production. They transform data into knowledge and empower industrial upgrade. Finally, skilled ICT workforces drive innovation and growth.
Fullscreen ViewResearch Model
Generation of data through broadband users, mobile networks, IoT devices, and smart terminals.
Quality of transmission and connectivity across fiber optics, 4G/5G networks, backbone infrastructure, and IPv6 deployment.
Infrastructure and capabilities for computing and storing data, including cloud investments, AI token consumption, and business continuity Capacity.
Utilization of data across sectors such as enterprise digitalization, AI adoption, e-commerce, and digital government services.
Sustainable energy infrastructure supporting digital systems, including renewable energy investments and the economic efficiency of green power Generation.
National-level regulatory, legal, investment, and sustainability frameworks that underpin digital economic growth.
The human and innovation ecosystem, encompassing ICT professionals, STEM graduates, startups, open-source contributors, and online community engagement.
By tracking the full data lifecycle - from creation to application - the GDII provides actionable insights for policymakers, investors, and businesses to identify bottlenecks, prioritize investments, and benchmark progress. It redefines digital maturity not by infrastructure ownership, but by intelligent value creation.
Fullscreen ViewGDII Indicators
Fullscreen ViewScoring and Aggregation
For each variable, economies receive a rating of 1 (low) to 10 (high), depending on the data input. The scale used for each indicator is based on realistic target values for 2030, where a score of “10” indicates that the target value has been reached.
These target values are extrapolated from market penetration projections based on the highest ranked economies, historical market performance, and expert analysts’ forecasts. Each economy’s score is then determined by its normalized raw data value in relation to this scale. In most baseline cases, a value that is less than 10% of the target value will be allocated a score of 1. A value of between 10% and 20% of the target value is allocated a score of 2,and so on, when an indicator score exceeds 10 points, it means the target value for that indicator has been achieved.
These indicator scores are then aggregated to form a total score for each of the GDII’s seven functional pillars: Data Creation, Data Transfer, Data Processing & Storage, Data Application, Digital Energy, Policy, Talent & Ecosystem.
Each pillar’s weighting in these economies’ final GDII score has been determined through factoranalysis, which derives an index variable from an optimally weighted linear combination of the items, known as Factor Scores. The weight assigned to each item is based on its factor loading, in order to reflect the strength of its relation to the factor (GDII). Consequently, Data Creation has given a 20% weighting, Data Transfer a 25% weighting, Data Processing & Storage a 15% weighting, and Data Application, Policy, Talent & Ecosystem, and Digital Energy each have a 10% weighting. The final index score is then calculated by aggregating the seven segments:
