- About Us
- Our Services
- Making Canada the Best Place to Start and Grow an Ocean Company
- Collaborating to Drive Change: Discover Novarium’s Innovation Campus
- Global Blue Economy Trends
- Global Sub-Sector Startup Analysis
- Global Blue Economy Ranking: Top 25 + 10 Runners-Up
- The Vast Potential for AI in the Blue Economy
- Why It’s Time to Invest in the Blue Economy
- Top Blue Economy Ecosystem Players
- Top Five Ecosystems by Region & Ecosystems to Watch
- How Mississippi’s Gulf Blue Initiative is Building on Established Strengths to Drive Innovation
- Meet GCE Ocean Technology, the Norwegian Cluster Helping Startups Unlock the Potential of the Blue Economy
- Ecosystem Pages
- Methodology & References
- Acknowledgments & Partners
Methodology & References
The Startup Genome quantitative data infrastructure includes data on over 3 million companies, 280+ ecosystems, and survey data from more than 10,000 startup executives across the globe.
These are the main datasets that make up this data science infrastructure:
- Startup Genome proprietary data:
- Interviews with 100+ experts
- 2017–2022 Startup Ecosystem Survey with more than 10,000 participants per year
- Crunchbase: global dataset on funding, exits, and locations of startups and investors
- Dealroom: global dataset on funding, exits, and locations of startups and investors
- PitchBook: private capital market data provider
- Local partners (accelerators, incubators, startup hubs, investors):
- list of startups
- list of local exits and funding events
- CB Insights: global dataset on unicorns
Definition: The Blue Economy is the sustainable use of ocean resources for economic growth, improved livelihoods, and job creation while preserving the health of the ocean ecosystem. It is a sector that seeks to promote economic growth, social inclusion, and the preservation of livelihoods while at the same time ensuring environmental sustainability of the oceans and coastal areas.
The following sub-verticals are included in the Blue Economy:
Marine energy (or ocean energy) encompasses wave, tidal stream, tidal range, ocean thermal, ocean current, run-of-river, and salinity, etc., through which energy can be harnessed from oceans. Oceans are the source of enormous untapped energy that is accessible to most coastal countries.
The farming of aquatic organisms including fish, molluscs, crustaceans, and aquatic plants. Farming implies some sort of intervention in the rearing process to enhance production, such as regular stocking, feeding, protection from predators, etc. Farming also implies individual or corporate ownership of the stock being cultivated, the planning, development and operation of aquaculture systems, sites, facilities and practices, and production and transport.
Maritime transport refers to a means of transport where goods or people are transported via sea routes. In some cases, maritime transport can encompass pre- and post-shipping activities.
Tourism is a growth industry in many coastal communities and is based on the natural and cultural heritage of local communities. There are a number of ocean-based tourism activities, such as sailing, diving, fishing, and whale watching. Growing numbers of tourists are putting greater pressure on the environment, resources, and coastal communities.
Plastic marine litter has the potential to persist in the marine environment for long periods, to travel considerable distances, and to accumulate in habitats far from its point of origin. This makes it a growing transboundary global problem that recognises no national borders and spreads from coasts to open oceans. Companies that develop and scale technologies to get rid of the world’s oceans of plastic fall under this category.
Primary Data Sources
- Startup Genome LLC (2017–2022). StartupGenome.com Database
- Dealroom.co BV. (2017–2022). Dealroom.co Database
- Crunchbase (2017–2022). Crunchbase.com Database
- CB Insights (2019–2022). CBInsights.com Database
- PitchBook (2018–2022), a private capital market data provider Database
Secondary Data Sources
- Shanghai Rankings
Blue Economy Sub-Sectors Ranking Methodology
The overall global ecosystem ranking is a weighted average of the following factor scores:
- Performance: 25%
- Funding: 20%
- Startup Experience: 10%
- Knowledge: 20%
- Talent: 5%
- Focus: 15%
- Legacy: 5%
The success factors are weighted by the above percentages to establish the overall rank of each ecosystem.
The weights of the factors were determined from research and experience. This method takes into account what is deemed to be of importance in ecosystem mapping and analysis overall and across all ecosystem sizes. We have used our research in the period 2009–2020 and correlation analysis and modeling work based on linear regression analyses, using factor indexes as independent variables with the performance index as dependent variable.
Adding the actual Performance Index to the ranking formula serves to include the influence of unobserved factors on the performance of an ecosystem.
Captures the actual leading, current, and lagging indicators of ecosystem performance.
- 40% number of $50 million+ exits Apr 1, 2017–Mar 31, 2022
- 20% number of all exits Apr 1, 2017–Mar 31, 2022
- 30% log of output (number of startups in the Blue Economy ) Jan 01, 2012–Dec 31, 2021)
- 10% number of founders with an active role in the Blue Economy
Quantifies funding metrics important to the success of early-stage startups.
- 90% log of number of early-stage funding deals Apr 1, 2017–Mar 31, 2022
- 10% log of number of Series B funding deals Apr 1, 2017–Mar 31, 2022
Quantifies the activity of technology knowledge space by measuring the published innovation.
- 20% number of patents (log of number of patents related to the sub-sector) Jan 1, 2011–Dec 31, 2020
- 20% Technology Potential, a measure calculated at the technology class level globally and calculated for each ecosystem based on the technologies it produces Jan 1, 2011–Dec 31, 2020
- 20% Ecosystem Complexity, a measure of the capacity of the ecosystem for producing patents in complex technology classes, calculated by measuring the diversity and commonness of the published patents globally
- 40% number of published research and journal papers related to the Blue Economy Jan 1, 2017–Dec 31, 2021
Assesses the talent that relevant startups have access to. We analyzed all subjects included in Shanghai Rankings and matched to the relevant startup sub-sectors to calculate the following metrics:
- 35% Average of TOP score from Shanghai Rankings
- 30% Average of CNCI score from Shanghai Rankings
- 30% Average Q1 Score from Shanghai Rankings
- 5% number of programs
- 20% Venture A funding (log of number of historical Series A funding deals, as a proxy for number of teams that raised funds in the ecosystem Apr 1, 2012–Mar 31, 2022
- 20% exits (log of number of historical exits over $50 million, as a proxy for number of scaled teams in the ecosystem Apr 1, 2012–Mar 31, 2022
- 60% startup creation, all time
Quantifies the concentration of early startups and the availability of infrastructures to support their mentorship and scaling.
- 60% share of startups in the sub-sector, shows the concentration of startups in the sub-sector Jan 1, 2012–Dec 31, 2021
- 40% number of Blue Economy-focused accelerators and incubators Jan 1, 2017–Dec 31, 2021
Quantifies the backbone and large companies in the ecosystems, which are important sources of networks, partnerships, and mentorship and attract investor attention.
- 30% log sum of market value for public companies in Marine Transport, Ocean Energy, and Aquaculture
- 30% log normalized market value for Marine Transport, Ocean Energy, and Aquaculture public companies by population
- 40% log of number of Marine Transport, Ocean Energy, and Aquaculture public companies with more than 250 employees
Key Concepts and Definitions
The ranking is primarily driven by one question: In which ecosystems do early-stage startups have the best chance of building global success?
A technology-enabled business that is less than 10 years old. Steve Blank defines a startup as a “temporary organization in search of a repeatable and scalable business model. We use this definition to look across sectors and sub-sectors, including software, hardware, health, energy, and others, and we use these parameters for data collection purposes.
A shared pool of resources, generally located within a 60-mile (100-kilometer) radius around a center point in a given region, with a few exceptions based on local realities. Resources typically include policymakers, accelerators, incubators, coworking spaces, educational institutions, and funding groups.
Ecosystem Success Factors Model
Our principal analytical tool, this measures different dimensions that support the performance of local startups. We look at multiple factors for our rankings: one measuring actual performance, with other Success Factors associated with performance, each comprising sub-factors and metrics. These factors are highlighted in our Ranking Methodology section, as well as in each rankings section.
- Performance: A combination of leading, lagging, and current indicators that capture economic outcomes in a startup ecosystem.
- Funding: The level and growth of early-stage funding, looking at both access and quality.
- Startup Experience: The depth and diversity of the pool of prior startup experience in an ecosystem.
- Talent: Measures the accessibility, quality, and cost of software engineering expertise.
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Insights & Rankings
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