Every innovation agency eventually builds a building. The logic is irresistible: a capital budget is easier to secure than an operating one, a building can be opened by a minister, and occupancy is a metric that rises. Two years later the building is full, the tenants are pleasant, and the agency cannot name a company that is bigger because it was there. This is the real-estate trap, and most of the world’s publicly funded incubators are in it. This article explains how the trap works, what the research says about the designs that escape it, and what a government should specify when it commissions an incubator or accelerator that is meant to change outcomes rather than fill floors.
The idea in brief. Incubators and accelerators are program businesses that are frequently financed as property businesses, and the financing shapes the behaviour: rent-dependent operators select for tenants who pay, not ventures that grow. The research is clear that what changes outcomes is the program — selection, intensity, structured mentoring, demand-side connections and a time limit — and that the space is incidental. Because a small share of young firms create most new jobs, selection and follow-through matter more than capacity. Agencies should fund operators on outcomes, cap the share of revenue that can come from rent, and design the accelerator as a cohort program with a building attached rather than a building with a program attached.
The real-estate trap, explained
The trap has three mechanisms, and understanding them is the first step to designing around them.
Capital is easier than operating money. Public budgeting treats a building as an asset and a program director’s salary as a cost. A ministry can justify a one-time capital grant for an innovation centre far more easily than a decade of operating funding for coaching, mentoring and follow-up. The building gets built; the program that would make it useful is funded for a year, then two, then reviewed.
Rent is the only revenue that arrives monthly. Once operating money is scarce, the operator discovers that desks, offices and event space generate predictable income and that programs do not. Within a few budget cycles the operator is a landlord who runs events, and its selection criterion has quietly become the ability to pay rent — which selects for consultancies, service firms and comfortable small businesses rather than the risky young companies the centre was built for.
Occupancy is the metric that rises. Because the building is the visible investment, occupancy becomes the reported KPI, and occupancy rewards exactly the wrong tenants: stable ones who stay. A well-functioning accelerator has high churn by design — ventures arrive, are transformed or stopped, and leave. A landlord’s dashboard reads that churn as failure.
The trap is not a moral failing of operators. It is the predictable response to how the centre was financed. Escaping it requires changing the financing, not exhorting the operator.
What the research says about sponsorship and accelerators
The scholarly literature on incubation and acceleration has matured over the past fifteen years, and its findings point in one direction.
Alejandro Amezcua and colleagues’ 2013 study in the Academy of Management Journal, examining thousands of incubated firms, found that the benefit of organisational sponsorship — incubation — depended heavily on the founding environment: sponsorship helped most where resources were scarce and competition intense, and could even be neutral or negative where the environment was already rich. Incubation, in other words, is a substitute for a missing ecosystem, not a supplement to a present one — a finding with direct implications for where governments should locate centres.
Susan Cohen, Daniel Fehder, Yael Hochberg and Fiona Murray’s 2019 paper in Research Policy mapped the design of accelerators — the fixed-term, cohort-based, mentorship-driven programs that end in a demo day — and showed how much variation hides inside the label: in selection, in the intensity and structure of mentoring, in the role of the sponsoring organisation, and in whether the program takes equity. Their typology is the most useful starting point for any agency specifying a program, because it turns “accelerator” from a brand into a set of design choices.
The outcome evidence, discussed in article 31, adds the mechanism: Benjamin Hallen, Susan Cohen and Christopher Bingham’s 2020 study in Organization Science found that effective accelerators compress learning through intensive, structured consultation; Sandy Yu’s 2020 analysis in Management Science found that accelerated ventures resolve uncertainty faster — including by closing sooner when the idea does not work; and the Start-Up Chile evaluation found that space and cash without schooling did nothing measurable. Across these studies the building never appears as a variable that matters. The program does.
The vital few: why selection matters more than capacity
A second body of research explains why incubators should be selective rather than capacious. John Haltiwanger, Ron Jarmin and Javier Miranda’s 2013 study in the Review of Economics and Statistics established that it is young firms, not small firms, that drive net job creation in the United States — and that most young firms either fail or stay small, while a minority grow rapidly and account for the bulk of the jobs. Ryan Decker and colleagues’ 2014 review in the Journal of Economic Perspectives extended the point: entrepreneurship’s economic contribution is concentrated in a small share of high-growth ventures. Nesta’s much-cited British analysis, The Vital 6%, found that a small minority of firms generated more than half of net new jobs over the period studied.
For incubator design the implication is stark. If outcomes are concentrated in a few ventures, an incubator’s value lies in finding and intensively supporting those few — which argues for selective intake, deep support per venture, and follow-through after the program — not in hosting as many companies as the floor plate allows. A centre that supports two hundred tenants lightly is unlikely to contain the vital few; a program that supports twenty ventures intensively, selected with care and connected to demand and capital, might. The building’s capacity is the wrong unit of ambition.
Five operating models, and what each is for
| Model | Primary revenue | Selects for | Typical outcome | Best use |
|---|---|---|---|---|
| Real-estate incubator | Rent and services | Ability to pay | High occupancy; low venture growth | Managed workspace — call it that |
| University incubator | University budget; grants | Affiliation; research links | Continuity for student and research ventures; weak market pull | The continuation pathway for campus and research programs (articles 33 and 34) |
| Corporate accelerator | Corporate innovation budget | Fit with the sponsor’s needs | Pilots and procurement; risk of capture | Demand-side connection for a sector program |
| Government-funded accelerator | Public grant; sometimes equity | Policy priorities; readiness | Depends entirely on design and operator | National and sector founder pipelines, when run as a cohort program |
| Network or virtual program | Fees; sponsorship; equity | Founder quality; remote reach | Reach without density; variable depth | Tier-two cities and cross-border cohorts |
The models are not exclusive, and the strongest ecosystems contain all five. The error is to fund one model while expecting the outcomes of another — most commonly, to fund a real-estate incubator and expect the outcomes of a government accelerator.
The economics: cost per outcome, not cost per desk
The unit that should govern the design is cost per venture operating at 24 months — the same measure proposed for founder programs in article 31 and for ecosystem measurement in article 32. The chart below is an illustrative model, indexed to the space-led incubator, of how that cost typically compares across three operating models when program costs, occupancy, selection and follow-through are modelled honestly.
The model’s logic is simple. The space-led incubator has high fixed costs, broad and shallow intake and low conversion, so its cost per operating venture is high even though its cost per desk is low. The grant-led model spends less on fixed costs but, without intensive support, converts only modestly better. The program-led accelerator has higher costs per venture during the program but selects tightly and converts far better, so its cost per outcome is lowest. The numbers in any real case will differ; the ordering rarely does.
Three financing rules follow for public funders. Fund the program, not only the building: a multi-year operating grant tied to outcomes is worth more than a capital grant of ten times the size. Cap rent dependence: if more than a modest share of an operator’s revenue comes from tenants, its incentives have already changed; a cap written into the funding agreement keeps them honest. Pay for outcomes at the margin: a base grant for running the program plus a performance element for ventures operating, revenue and capital raised at 24 months, verified.
The equity question deserves its own answer. Private accelerators take equity because it aligns them with their ventures’ growth. Public programs should generally not: equity introduces a conflict between a public body and the founders it exists to serve, complicates the founders’ later financing, and produces returns on a timescale no budget process respects. Where a government wants upside, the cleaner instrument is a fund-of-funds that invests in private managers who take equity (article 39), with the accelerator kept equity-free and outcome-funded.
Design principles for an accelerator that accelerates
- Selection with a threshold and a bar. Structured criteria; a quality threshold every venture must clear; then allocation among qualifiers with humility about fine rankings — and, where oversubscribed, transparently, to create the comparison group the program will later need.
- Cohorts, not tenants. Fixed intake dates, fixed duration, a defined end. The time limit is a feature: it forces decisions and prevents the drift into tenancy.
- Intensity with accountability. Weekly milestones, structured check-ins, peer pressure within the cohort — the mechanism through which learning is compressed.
- Mentors with obligations. Committed hours, assigned ventures, sector fit, and conflict disclosure; a mentor bench, not a mentor list.
- Demand-side partners with budgets. Corporates, public bodies and state-owned enterprises that have agreed to pilot, procure or evaluate — the connection that turns a prototype into a customer.
- A capital pathway. Named investors who attend, a fund-of-funds relationship, or a follow-on grant instrument; the program ends where the next financing begins.
- Alumni as infrastructure. Alumni who return as mentors, customers and investors are the program’s compounding asset and its cheapest network.
- Outcome measurement by design. Consent at intake; cohort accounting; 12, 24 and 36-month follow-up; verification against administrative data.
- A building, if at all, sized to the cohort. Space for the ventures in the program, not for tenants who fund it.
Selection in practice: what a good intake looks like
Because the vital few are the point, the intake process is where an accelerator earns or loses its value, and the practice that works is unglamorous. Applications are scored against published criteria — team completeness and commitment, evidence of customer conversations, a problem the program’s demand-side partners actually have, and readiness to use twelve intensive weeks — by a panel that includes operators and investors as well as the program’s staff. Ventures that clear the threshold are then observed, not just interviewed: a short pre-program task, such as producing evidence from ten customer conversations in two weeks, reveals more about a founding team than any pitch. Where qualified applicants exceed places, allocation among them is transparent, and the program records the qualifiers it turned away so that it can compare their outcomes later. The intake is, in this sense, both the program’s quality control and the beginning of its evidence base — a point developed in article 40, which reviews what the research says about the founder characteristics worth selecting for.
A note on tier-two cities and virtual programs
The Amezcua finding — that sponsorship helps most where the surrounding environment is thin — argues for locating intensive programs in cities that lack density rather than adding another accelerator to a saturated metro. India’s tier-two cities, discussed in article 10 of this series, are the obvious candidates, and the Gulf’s smaller states face the same question at national scale. The trade-off is that thin environments also lack the mentors, customers and investors a program needs, which is where the network model earns its place: a cohort physically based in a tier-two city, with a program run partly remotely, mentors drawn from a metro or from across the corridor, and demand-side partners connected by design rather than proximity. The building, once again, is the least important component; the connections are the program.
The Indian and Gulf landscapes
India has one of the world’s largest incubation infrastructures. The Atal Innovation Mission‘s incubation centres, the Department of Science and Technology’s long-running technology business incubators and NIDHI programs, sector incubators such as those supported by BIRAC in biotechnology, state-backed flagships such as Hyderabad’s T-Hub, the software-park network and hundreds of university and private incubators together host thousands of ventures. Capacity is not the constraint. The distribution of quality is: a minority of centres run genuine programs with selection, mentoring and capital pathways, and a majority are, in the terms of this article, managed workspace with events. The policy opportunity is to shift funding from capacity to programs — to pay the strong operators to run cohorts on outcome-linked terms and to let the rest be honest about what they are.
The Gulf’s landscape is younger, smaller and better capitalised. Abu Dhabi’s Hub71, Dubai’s cluster of free-zone programs, Saudi Arabia’s enterprise-agency and fund-backed accelerators, and Bahrain’s and Qatar’s national programs were mostly designed in the cohort-accelerator era and have avoided the worst of the real-estate trap by starting from programs rather than buildings. Their constraint is the opposite of India’s — pipeline and density — which is why the strongest Gulf programs recruit internationally, and why paired corridor cohorts with Indian ecosystems (article 36) are a natural extension.
A composite case: eighty per cent occupied, zero per cent effective
A composite from several engagements; details altered.
A regional innovation centre built with a large capital grant had, after four years, eighty per cent occupancy, a full events calendar and an annual report that led with both. Its tenants were mostly small services firms and the regional offices of established companies; its handful of genuine startups had arrived through personal connections. The ministry that funded it asked the question this series keeps returning to — which ventures were larger because the centre existed? — and the answer was none the centre could evidence.
The redesign kept the building and changed the business. Half the floor plate was leased commercially as managed workspace under a separate brand, generating income with no pretence of impact. The other half became the home of a cohort accelerator: two intakes a year of fifteen ventures each, selected against a published threshold, with a twelve-week program, a mentor bench drawn from the region’s corporates, demand-side partners with pilot budgets, an equity-free milestone grant, and a fund-of-funds relationship for follow-on capital. The operator’s funding agreement capped rent at a minor share of program revenue and tied a third of its grant to 24-month outcomes. Occupancy, as a metric, was retired. Three years on, the centre’s report led with cohort outcomes — ventures operating, revenue bands, capital raised, jobs — and the ministry had, for the first time, a number it could compare with the cost.
What could go wrong
- Building first. The centre is built before the program is designed. Antidote: fund the operator and the program; size any building to the cohort.
- Rent creep. Operating money runs out; rent fills the gap; selection follows. Antidote: multi-year operating grants and a rent cap in the agreement.
- Occupancy as KPI. Antidote: retire it; report cohort outcomes.
- Mentor decoration and demo-day theatre. Names on a wall; pitches to an audience that cannot buy or invest. Antidote: obligations for mentors; demand-side partners and investors with budgets in the room.
- Equity in public programs. Conflicts, complexity and illiquid returns. Antidote: equity-free programs; upside through fund-of-funds.
- Capture by the sponsor. A corporate accelerator that selects only for its sponsor’s needs. Antidote: mixed sponsorship and founder-first governance.
- No follow-through. The program ends and the ventures vanish from the data. Antidote: consent at intake; alumni structures; 36-month tracking.
Questions ministers and agency heads actually ask
“Should we build an innovation centre?” Design the program first. If the program needs a building, build one sized to it. If the region needs managed workspace, build that and call it that. Do not confuse the two in one budget line.
“What occupancy should we target?” None. Target ventures operating at 24 months per unit of cost, by cohort.
“Who should run it?” An operator with outcome data from previous cohorts, funded on a multi-year operating basis with a rent cap and a performance element. If no such operator exists locally, contract one and build local capacity alongside.
“Should the program take equity?” Not if it is public. Keep the accelerator equity-free and put the government’s upside into a fund-of-funds that backs private managers.
“How many ventures a year?” Fewer than the building could hold and more than a single cohort: two or three intakes of fifteen to thirty, run well, replicated across sectors and cities as the operator proves its numbers.
Methodology & data notes
Findings from the academic literature are summarised approximately and readers should consult the papers for effect sizes and boundary conditions. The vital-few chart reproduces the headline finding of Nesta’s analysis of UK firms over a specific period and should not be read as a universal constant, though the concentration of job creation in a minority of young firms is well established across countries. The cost-per-outcome chart is an illustrative model with indexed values, not a dataset; the ordering, not the magnitudes, is the claim. The composite case combines several engagements with details altered. Companion articles cover founder-program design (article 31), ecosystem measurement (article 32), research and campus continuation pathways (articles 33 and 34) and national innovation-agency and fund-of-funds design (article 39).
References & further reading
- Amezcua, A., Grimes, M., Bradley, S. & Wiklund, J. (2013) — Organizational Sponsorship and Founding Environments: A Contingency View on the Survival of Business-Incubated Firms, Academy of Management Journal
- Cohen, S., Fehder, D., Hochberg, Y. & Murray, F. (2019) — The design of startup accelerators, Research Policy
- Hallen, B., Cohen, S. & Bingham, C. (2020) — Do Accelerators Work? If So, How?, Organization Science
- Yu, S. (2020) — How Do Accelerators Impact the Performance of High-Technology Ventures?, Management Science
- Haltiwanger, J., Jarmin, R. & Miranda, J. (2013) — Who Creates Jobs? Small versus Large versus Young, Review of Economics and Statistics
- Decker, R., Haltiwanger, J., Jarmin, R. & Miranda, J. (2014) — The Role of Entrepreneurship in US Job Creation and Economic Dynamism, Journal of Economic Perspectives
- Nesta — The Vital 6%: How high-growth innovative businesses generate prosperity and jobs
- Global Accelerator Network — accelerator practice and data
- Atal Innovation Mission, Department of Science and Technology and BIRAC — India’s public incubation programs
- Hub71 — Abu Dhabi’s technology ecosystem platform
- World Bank — infoDev research on business incubation in developing economies
HexGn designs and operates cohort accelerators and incubation programs for governments and agencies — selection, program, mentor bench, demand-side partners and outcome tracking — funded on outcomes rather than occupancy.