When a new entrepreneurial ecosystem (EE) is trying to prove its worth, how does it convince the world — investors, talent, partners, media — that it is credible and worth joining? This paper argues that the answer lies in signaling: deliberate and sometimes unintentional acts that communicate quality, intention, and trustworthiness.
The authors study Marina de Empresas (MdE), a privately governed entrepreneurial ecosystem in Valencia, Spain, created by entrepreneur Juan Roig. By analyzing 24 interviews, 1,000+ pages of documents, and direct field observations, they develop a multilevel model that explains how emerging EEs gain legitimacy through signaling — both from inside the ecosystem outward, and from outside inward.
Signaling theory has been widely used to study individual entrepreneurs seeking funding, but almost no research had applied it to entire ecosystems. The authors show that ecosystems are not just passive environments — they actively send and receive signals to build trust and attract actors.
The paper sits at the intersection of two big ideas: signaling theory and entrepreneurial ecosystem (EE) theory. Bringing them together allows the authors to examine how trust and credibility are built in complex, multi-actor settings — not just between two parties like an entrepreneur and an investor.
Signaling theory (originally from economics and biology) explains how parties with unequal information communicate quality. When one party knows more than the other, they send observable signals — cues that represent their underlying qualities — to reduce uncertainty.
Intentional signals
Deliberate cues sent to persuade — pitch decks, press coverage, investor endorsements, accelerator rankings.
Unintentional signals
Observable cues that audiences interpret even if not designed to signal — physical location, culture, community behaviour.
An EE is a regional community of interconnected actors — entrepreneurs, investors, universities, incubators, governments — that collectively produce the conditions for entrepreneurship to thrive. The paper treats MdE as a nascent, privately governed EE with three core institutions:
- EDEMA private nonprofit entrepreneurial university centre affiliated with two public universities in Valencia.
- LanzaderaA startup incubator and accelerator housing 300 startups, ranked 19th in the FT list of Europe's leading startup hubs.
- Angels CapitalAn entrepreneurial financing company with a portfolio of 50 ventures.
Cognitive legitimacy
The ecosystem is understood — people know what it does and why. Built through common knowledge, narratives, and recognisable success stories.
Evaluative legitimacy
The ecosystem is valued — people believe it is desirable, appropriate, and worthwhile. Built through shared social norms, visible values, and community endorsement.
The paper's title captures the directional nature of signaling. Inside-out signals emerge from actors within the ecosystem (entrepreneurs, investors, institutions) and radiate outward to attract external resources and attention. Outside-in signals flow from external recognition — rankings, media coverage, policy endorsement — back into the ecosystem, reinforcing internal confidence and cohesion.
The study uses a qualitative, embedded case study design — the ideal approach when a phenomenon is complex, contextual, and not yet well understood. The authors had unrestricted access to MdE, including attendance at investment forums and ecosystem events.
🎤 Interviews
24 semi-structured interviews with 21 actors. Total: 22.1 hours. Internal (entrepreneurs, directors, investment managers) and external (CEOs, investors, bankers).
📄 Documents
1,000+ pages of identity artifacts, strategic documents, image materials, operational records, and financial documentation from MdE.
👁️ Observation
Direct field observation of investment forums and ecosystem events, with detailed field notes and voice notes capturing real-time signaling interactions.
The authors used a three-stage grounded theory coding process inspired by the Gioia method:
- Stage 1First-order codes: 243 codes generated from informant-centred statements using in vivo, narrative, open, process, and values coding.
- Stage 2Second-order themes: axial coding clustered the 243 codes into 10 coherent themes by searching for patterns and conceptual similarities.
- Stage 3Aggregate dimensions: the 10 themes were synthesised into 4 aggregate dimensions, forming the final conceptual model.
The study's main contribution is a three-level conceptual model of how signaling works within an EE. Each level has distinct actors, signal types, and legitimacy-building mechanisms. Signals also travel across levels, creating a dynamic, self-reinforcing system.
| Level | Who controls it | Cognitive legitimacy signals | Evaluative legitimacy signals |
|---|---|---|---|
| Macro (Context & Collective Action) | Founder + regional actors collectively | Startup counts, investment volume, success narratives, event hosting, media coverage | Business-friendly legislation, talent attraction, regional economic vibrancy |
| Meso (Institutions) | Core EE organisations (EDEM, Lanzadera, Angels) | Accelerator rankings, university affiliations, portfolio size, innovation hubs | Shared mission alignment, values consistency, professional norms |
| Micro (Individuals) | Individual entrepreneurs and investors | Investor track records, entrepreneur expertise, credentials, past performance | Impression management, social compliance, symbolic action, passion signals |
One of the paper's most original findings is that signals do not stay at one level. Individual micro-level behaviors — an entrepreneur's passion, an investor's endorsement — accumulate upward to reinforce institutional reputation. Institutional signals then condition individual behavior. And macro-level context shapes what signals are even possible to send.
The paper's second major contribution is identifying a boundary condition for signaling in EE contexts: audience proximity. Whether a signal produces cognitive or evaluative legitimacy depends heavily on how close (geographically and psychologically) the audience is to the ecosystem.
Insider audiences
Interpret signals through community values, long-term relational logic, and shared culture. Respond to evaluative legitimacy cues about belonging and mission.
Outsider audiences
Interpret signals through market-based logic — financial metrics, returns, rankings, and performance. Respond to cognitive legitimacy cues about credibility and results.
- Theory extensionApplies signaling theory to the EE level — a largely unexplored intersection — introducing new concepts of multilevel and bidirectional signaling.
- Boundary conditionsAudience proximity (inside vs. outside the EE) is established as a key boundary condition governing how signals are decoded.
- MethodDemonstrates the power of embedded case study and Gioia-inspired coding for studying complex, situated social phenomena like ecosystem legitimacy.
- Collective actionBrings Ostrom's collective action framework into EE and signaling research, showing how shared governance shapes what signals are possible.
- Ecosystem designPolicy cannot simply mandate legitimacy. Nascent EEs need deliberate spaces — events, co-location, narratives — that generate common knowledge and shared identity.
- Beyond metricsPurely economic indicators (jobs, investment) are necessary but not sufficient. Evaluative legitimacy requires cultural, relational, and mission-based signals too.
- Regional strategyPlace-based EEs succeed when they build both cognitive comprehensibility (outsiders can understand them) and evaluative desirability (insiders believe in them).
- FoundersYour ecosystem affiliation is itself a signal. Choosing the right EE — one with both insider culture and outsider credibility — shapes how investors and partners perceive you before you even pitch.
- InvestorsEE-level signals (rankings, event quality, founder density, co-location) provide reliable low-cost information about deal flow quality in nascent markets.
- Ecosystem buildersManage both inside-out and outside-in signals deliberately. Do not rely solely on market performance metrics; cultivate community culture as a legitimacy mechanism.
- Context specificityMdE is a unique, privately governed ecosystem founded by a single high-profile entrepreneur. Findings may not transfer directly to publicly governed or less-resourced ecosystems.
- Single caseA single case study offers depth but not breadth. Future research should test the model comparatively across multiple EEs.
- Temporal scopeThe study captures a snapshot of a maturing nascent ecosystem. Longitudinal work is needed to track how signaling strategies evolve as EEs develop.
- TitleInside-out and outside-in: How entrepreneurial ecosystems can build legitimacy through signaling
- AuthorsColin Donaldson · Jorge Villagrasa · Christina Theodoraki
- JournalJournal of Small Business Management
- Outlet statusABDC-A
- Year2025
- Volume / PagesVol. 63, No. 4, pp. 1552–1593
- DOI10.1080/00472778.2024.2394499
- SettingMarina de Empresas, Valencia, Spain
- MethodEmbedded qualitative case study · Gioia-inspired coding · Reflexive thematic analysis
- Key theoriesSignaling theory · Entrepreneurial ecosystem theory · Legitimacy theory · Collective action
This paper brings a fresh and important lens to entrepreneurship: not just how individual founders signal quality, but how the communities and ecosystems around them send and receive signals to build collective credibility. It is essential reading for anyone thinking about how to build, join, or support an emerging entrepreneurial hub.