Topic 8.4

Measurement Methods & Indices

Benchmark how researchers and policymakers quantify the digital economy. Compare bibliometrics, composite indices, topic modelling, and data source strategies—then evaluate gaps in sustainability, compute equity, and inclusion coverage.

⏱️Approx. 30 min
📊Methodology Lab
🧭Stage 4 · Measurement

Methodology Navigator

Switch between methodologies to review use cases, data requirements, and limitations.

Bibliometrics & Meta-Analysis

Maps the intellectual structure of the field—co-citation, co-authorship, keyword evolution—using tools such as VOSviewer and Bibliometrix.

  • Use cases: Literature reviews, identifying gaps, thematic clusters
  • Data: Scopus, Web of Science, Dimensions
  • Limitations: English-language bias, lag in coverage for emerging outlets
  • Best practice: Combine quantitative mapping with qualitative lens to interpret clusters.

Indicator Pillars & Sources

Use the pillar table as a blueprint for composite index design or dashboard development.

Pillar Example Indicators Primary Sources Policy Lever
Connectivity & Infrastructure Fibre coverage, 5G readiness, data centre density ITU, Telegeography, hyperscaler disclosures Spectrum auctions, infrastructure PPPs, public compute hubs
Compute & Data Assets GPUs per million, AI training expenditure, data capital stock AI Index, TOP500, OECD data satellite accounts Compute grants, intellectual property, data governance frameworks
Skills & Participation Digital skills proficiency, STEM graduates, meaningful use metrics World Bank, UNESCO, ITU Digital Skills Education policy, digital inclusion programmes, affordability subsidies
Innovation & Value Creation Digital startups per capita, venture investment, platform exports Crunchbase, national business registries, OECD TiVA Innovation grants, regulatory sandboxes, trade policy
Sustainability & Resilience PUE, GHG intensity, water footprint, circularity rate IEA, CADiS, corporate ESG reports Green standards, carbon pricing, right-to-repair regulation

Limitations & Research Gaps

Under-measured Dimensions

  • Sustainability externalities (carbon, water, circularity)
  • Compute equity and public access
  • Digital labour and inclusion quality-of-use
  • Cross-border data flows & valuation of user-generated data

Methodological Cautions

  • Composite indices sensitive to weighting; publish sensitivity analysis.
  • Bibliometric datasets undercount non-English scholarship; complement with regional databases.
  • Topic models require careful validation (coherence scores, expert review).
  • Administrative/big data raise privacy and ethical governance considerations.

🎯 Key Takeaways

  • Measurement portfolios combine bibliometrics (map knowledge), composite indices (benchmark readiness), topic modelling (track narratives), and integrated datasets (harmonise indicators).
  • Transparency—weights, normalisation, metadata—is crucial for policy credibility and scholarly reuse.
  • Sustainability, compute equity, and inclusion remain the weakest measurement pillars; integrating CADiS metrics and compute indicators closes systemic gaps.
  • Mixed-method triangulation (quant + qual + expert review) improves validity across heterogeneous data sources.
  • Invest in statistical capacity and open data infrastructures to reduce geographic and linguistic blind spots.