5. Measurement of the Energy Innovation System – Comprehensive Study Notes

Context and Objectives

Working paper: “Measurement of the Energy Innovation System” (Diran Soumonni & Rendani Mamphiswana, Strategic Management of Energy Innovation – MM ELP, 09\,\text{July}\,2025)
Core goal: Design and demonstrate a framework of indicators that can gauge how well South Africa’s energy-innovation activities translate into tangible socio-economic and environmental outcomes.
Motivation: “What gets measured gets managed,” but in innovation, many vital processes are invisible unless we build multi-dimensional metrics.

Key Inspirational Quote

“Not everything that can be counted counts and not everything that counts can be counted.” – Attributed to Albert Einstein
➜ Serves as a philosophical caution: purely quantitative metrics risk missing qualitative, systemic, or distributive aspects of innovation.

Overview of South Africa’s Energy Sector

Energy source landscape
• Renewable: hydropower, solar, biomass, wind, geothermal.
• Non-renewable: coal, oil, natural gas, nuclear.
• Electricity & liquid-fuel subsystems span generation, transmission, refining, distribution.
Institutional ecosystem spans Department of Science & Innovation (DSI), Department of Mineral Resources & Energy (DMRE), South African National Energy Development Institute (SANEDI), Eskom, IDC, TIA, NACI, HSRC, higher-education institutions, private investors.

Energy Consumption Patterns (latest cited figures)

Electricity end-use
• Commercial: 68\%
• Domestic/Residential: 23\%
• Other: 9\%
Liquid fuels end-use
• Transport: 53\%
• Industry (+ non-energy uses): 25\%
• Hydrocarbon sector: 11\%
• Residential + services + agriculture: 11\%
Access & fuel stacking
• Electricity access: 89.3\% of population.
• Energy-poor households still rely on wood (cooking/heating) and paraffin/candles (lighting).

Research Problem Statement

Inclusive socio-economic development requires affordable, reliable, clean energy.
Paradox: High access ≠ low energy-poverty because incomes are low and tariffs high.
Fossil-fuel dominance → air, land & water pollution + climate-change externalities.
Decarbonisation tech in the STI Decadal Plan stuck at prototype stage (TRL ≤4); DMRE strategies lack explicit innovation thrusts.
Need a bespoke measurement framework to:
• Map activities ↔ outcomes,
• Identify bottlenecks,
• Align policy instruments with “directionality” toward inclusive, green growth.

Literature Review Highlights

Shift from linear model (R→D→Demonstration→Deployment) to interactive, chain-linked models stressing feedback & co-creation.
Empirical insights on RE innovation systems:
• East Africa manufacturing (Lema et al., 2018)
• Knowledge & learning studies: Denmark/Holland (Kamp et al., 2004), Africa (Soumonni 2013).
• Technological systems of innovation (TSI): Tigabu et al. 2015 (East Africa).
• Adoption studies: EU, China, Mexico, UK (Calvo-Gallardo 2021; Kim & Wilson 2019; de Jesus Fernandez 2022; Winskel 2014).
Four complementary learning mechanisms:
• Learning by Searching (formal R&D)
• Learning by Doing (process/manufacturing know-how)
• Learning by Using (user feedback)
• Learning through DUI (Doing-Using-Interacting across communities, producers & users).

Conceptual Foundations: Energy Technological Innovation Systems (ETIS)

Actors & Institutions: entrepreneurs, incumbents, state labs, financiers, regulators.
Knowledge functions: R&D, demonstration, diffusion.
Market functions: niche creation, incentives, price signals, phase-out of incumbents.
Resources: finance, skills, infrastructure.
Shared expectations guide investment direction and speed (“directionality”).

Methodology

(1) Indicator Architecture

Merge
• DSI Logical Indicator Framework (Input → Output → Outcome) with
• Hu et al. (2018) Energy-indicator typology (adds Flows/Linkages).
Categories adopted:
• Inputs / Enablers
• Outputs
• Outcomes / Impact
• Flows & Linkages (incl. finance, non-R&D innovation, directionality).
Data sources: national databases (NACI, HSRC, SANEDI, StatsSA) + international (IEA, IRENA, OECD, World Bank, UN SDGs).

(2) Benchmarking Logic

South Korea chosen as comparator: similar industrialising context, strong catch-up record.
• Stand-alone figures can mislead; relative performance versus an international frontier reveals gaps (DSI 2022).
Outcomes aligned with SDGs, NDP 2030, Paris Agreement.
Directionality metrics gauge progress toward “inclusive catch-up” (e.g., falling energy intensity, rising RE share).
Historical framing: “energy pluralism” & priority orders (Diop 1985; Lee 1991) inform indicator emphasis on diversity/democratisation.

Understanding Energy Innovation – Actor × Phase Matrix (Hu et al., 2018)

Generation → Adoption & Use continuum features:
• Tech-push (R&D) vs. market-pull (incentives).
• Demonstration projects and niche markets spawn learning cycles.
• Relative advantage & user preferences shape diffusion.
• Phase-out policies (e.g., coal de-commissioning) complement new-tech support.

Measurement Framework – South Africa vs. South Korea (Snapshot)

Inputs

Population:
• SA =59.89\,\text{million}, SK =51.63\,\text{million}
Public energy RD&D (IEA 2021):
• SA =\$\,77.879\,\text{million}
• SK =\$\,691.466\,\text{million}
Total R&D intensity:
• SA 0.62\%\,\text{of GDP}; AU target 1\% by 2024
• SK 4.93\% (global top-tier)
Renewable-energy (RE) investment 2011{-}2022: SA \$\,12.81\,\text{billion}.
RE manufacturing investment 2022: SK \$\,464.6\,\text{million} (No SA data).
Human resources:
• R&D personnel: SA 82\,744; SK 785\,594.
• O&M/services: SA 545; SK 5\,690.
• Manufacturing: SK 11\,864 (No SA data).

Outputs

Manufacturing firms in RE value chain: SK 536 (No SA data).
Installed RE capacity: SA 6,280.2\,\text{MW}; SK 32,582\,\text{MW}.
Knowledge production:
• RE publications 1990{-}2024: SA 1,044; SK 633 (!).
• Climate-mitigation energy patents 1999{-}2020: SA 297; SK 13,789.

Outcomes

Electricity access: SA 89.3\%; SK 100\% (SDG 7 target: 100\% by 2030).
Clean-cooking access: SA 88\%; SK 95\%.
Annual RE electricity generation: SA 21,793\,\text{GWh}; SK 105,278\,\text{GWh}.
Share of RE in electricity mix: SA 8.4\%; SK 7.4\% (SA > SK due to nuclear/gas mix).
Export value of RE manufacturing (2022): SK \$\,2.9\,\text{billion} (No SA data).
CO$_2$ emissions: SA 391.746\,\text{Mt}; SK 558.62\,\text{Mt}.

Directionality, Flows & Linkages

RE supply change 2019{-}2020:
• SA -20.5\% (decline)
• SK +2.5\%
Non-RE supply change 2019{-}2020: SA -7.1\%; SK -1.8\%.
Emissions trend: SA -14.2\%; SK 0\%.
Energy intensity:
• SA 7.0\,\text{MJ}/\text{(US\$ GDP)}
• SK 5.3\,\text{MJ}/\text{(US\$ GDP)}
• Paris target: -3.1\,\text{MJ}/\text{GDP} by 2050.

Detailed Indicator Sets for South Africa

A. Liquid-Fuels-Focused Matrix

Inputs
• R&D & demonstration expenditure, asset finance, subsidies, state-lab funding.
• Human capital counts across R&D, manufacturing, O&M.
Outputs
• Scientific publications, patent filings.
• Installed capacity by feedstock:
– Coal, Crude, Natural Gas, Biofuel (units: \text{bbl/day}).
• Unit cost (R/\text{bbl}); import-vs-domestic refining split (currently 40\% local, 60\% imports).
Outcomes
• Energy access %, jobs created, tonnes of CO$_2$ avoided.

B. Recommended Generic Indicators (Input Side)

R&D Expenditure (R’m)
• Capture basic + applied + experimental research across public, private & foreign sources (HSRC R&D Survey).
State Labs (R’m)
• Funding to move tech from \text{TRL}=1{-}3 (proof of concept) to \text{TRL}=4 (bench-scale).
Demonstration Expenditure (R’m)
• Pilot & industrial-scale demos (captured via TIA, SANEDI, IDC).
Personnel (head-counts) along full innovation chain (data: NACI, SANEDI, HSRC).
Asset Finance (R’m) for first-of-a-kind commercial installations & local manufacturing.
Subsidies (R’m) to early adopters (e.g., IPP Programme feed-in support).
Research & Technology Collaborations (count & R’m) across academia, industry, international partners.

C. Recommended Generic Indicators (Output Side)

Scientific Publications (count) by source & technology.
Patent Applications (count) by tech field.
Technology Imports / Exports (count, value) by energy source & chain segment.
Locally Developed Technologies (count) with TRL mapping.
Manufacturing Capacity (count of firms) for electricity, liquid fuels, green hydrogen, etc.
Installed Capacity (GW, bbl/day, t H$_2$/yr, etc.).

Conclusions & Policy Implications

Paradigm shift: from tracking static energy mix to tracking innovation dynamics → richer insights for inclusive energy security.
Indicator framework reveals intentionality (policy coherence) & performance (actual progress) of actors.
Must incorporate inclusivity (affordability, access) and evaluative criteria (directionality, sustainability, learning effects).
Manufacturing and workforce capabilities are critical leverage points; policy should nurture them.
Non-R&D/service innovation (e.g., new business models, fintech for mini-grids) deserves equal measurement weight.
Framework doubles as groundwork for an eventual Energy-Technology Localisation Roadmap (local supply-chain build-out).

Ethical, Sustainability & Real-World Considerations

Justice dimension: Reducing energy poverty while decarbonising avoids a “green divide.”
International obligations: Aligns with SDG 7 (Affordable & Clean Energy) and Paris Agreement pathways.
Systemic risk: Over-reliance on coal threatens water security & health; innovation metrics can monitor mitigation progress.
Policy learning: Benchmarking against South Korea illustrates feasible catch-up trajectories but also warns of possible lock-ins (e.g., nuclear dependence).

Links to Broader Curriculum / Previous Lectures

Builds on earlier sessions on National Innovation Systems (Freeman, Lundvall) and Sectoral Systems (Malerba).
Connects with Strategic Management theories (resource-based view, dynamic capabilities) by operationalising how capabilities accumulate across the energy value chain.
Provides empirical complement to lectures on Technology Policy Instruments (R&D tax credits, feed-in tariffs, green bonds).

Key Formulas & Numerical Benchmarks Mentioned

Energy intensity target: \text{MJ per US\$ GDP} \downarrow 3.1 by 2050 (Paris alignment).
Total-factor R&D intensity target: \text{GERD}/\text{GDP} \ge 1\% for AU by 2024.
Electricity‐access universalisation: 100\% by 2030 (SDG 7).