Every entrepreneur who has watched a competitor’s strategy succeed in one market and tried to replicate it in another has encountered the contagion problem, usually without realising that’s what it is. The assumption driving the failure is that trends spread like information — that a good idea, given sufficient visibility, will propagate through any market. The research says otherwise.

Simple contagion versus complex contagion

Damon Centola and Michael Macy’s 2007 paper in the American Journal of Sociology drew the distinction that changes how adoption should be understood. Information and disease are simple contagions — a single contact is sufficient for transmission. Business behaviours, new practices, and unproven technologies are complex contagions, requiring multiple independent sources of social reinforcement before an individual will adopt them. Four mechanisms create the complexity: coordination (the innovation only becomes valuable when others adopt it), credibility (it lacks legitimacy until seen in trusted peers), legitimacy (social proof must come from similar others rather than distant influencers), and risk (costly or status-threatening behaviours require more than one endorsement before action).

The structural consequence is significant. Viral marketing assumes that wide networks and long bridges — connections to distant, loosely-connected audiences — are the optimal spread mechanism, which holds for simple contagions. For complex contagions, wide bridges underperform wide bridges — multiple overlapping connections between clusters of similar people. A trend enters a tight-knit community of professionals who share strong ties and it spreads. Enter it through a loose network of distant influencers and it dies, regardless of how loudly it is promoted.

The 25% threshold

Centola, Becker, Brackbill and Baronchelli’s 2018 controlled experiment across 10 groups of 20 participants produced the most precise tipping point data available. Groups where the committed minority pushing a norm change reached 25% of the group showed rapid, abrupt adoption of the new norm across the majority. Groups where the committed minority was 21% consistently failed. In one trial, a single additional person made the difference between complete failure and complete norm reversal. Even when participants were paid double or triple to maintain the existing norm, a 25% committed minority still overturned it.

The abruptness of the transition is commercially important. There was no gradual climb — there was a phase shift. Below the threshold, the challenge consistently failed. Above it, the majority flipped rapidly. For entrepreneurs watching a trend gain advocates, visibility, and genuine early adoption in a market yet still fail to propagate, the mechanism is often position relative to this threshold. The market does not gradually resist. It simply does not flip, and there is no visible signal indicating how close or far the adoption sits from the point at which it would.

Rogers’ S-curve and the chasm that kills most trends

Everett Rogers’ Diffusion of Innovations mapped the adoption curve across five empirically derived segments. Innovators account for 2.5% of the population and tolerate risk freely. Early Adopters make up 13.5% and respond to strategic advantage and social proof from respected peers. The Early Majority — the 34% that determines whether a trend achieves scale — are deliberate pragmatists requiring proven value, reduced uncertainty, and visible reference customers before committing.

The gap between Early Adopters and the Early Majority is the critical failure point. A trend can capture the first 16% of the market — Innovators and Early Adopters combined — and still fail entirely if it cannot cross to the Early Majority, because the two segments respond to fundamentally different inputs. Early Adopters respond to novelty and vision. The Early Majority respond to evidence that people like them have already adopted and benefited. A trend marketing itself as new and exciting captures the first 16% and stalls. Markets where trends successfully cross the chasm already have the social infrastructure to bridge it: dense professional communities, credible Early Majority opinion leaders, and environments where peer observation is high and frequent enough to generate the multiple reinforcement signals complex contagion requires.

Cultural tightness-looseness as a structural moderator

Michele Gelfand’s foundational research on cultural tightness and looseness adds the cross-market dimension. Tight cultures have strong social norms and low tolerance for deviation; loose cultures have weak norms and high tolerance for it. Li, Gordon and Gelfand demonstrated in the Journal of Consumer Psychology that product diffusion follows different pathways in tight versus loose cultures — in tight cultures, advertising themes emphasising conformity and norm-consistency outperform novelty framing, while the reverse holds in loose cultures.

The adoption dynamics are structurally different as a result. In tight cultures like Japan and Singapore, adoption requires norm endorsement from the top of the social hierarchy before it propagates laterally. In loose cultures like the US and Australia, adoption can propagate horizontally through peer networks without hierarchical sanction. A trend seeded through horizontal peer networks in a tight culture will stall not because of product-market misfit but because the contagion mechanism requires a different structural pathway than the one being used.

Opinion leadership and concentrated contagion

Iyengar, Van den Bulte and Valente’s study of new product diffusion among physicians found that social contagion in professional markets concentrates along specific relational pathways rather than distributing uniformly across the network. Opinion leaders — those who self-identify as influential within their professional community — were both more likely to transmit adoption signals and more likely to be influenced by other opinion leaders rather than by ordinary adopters.

For entrepreneurs entering a new market, seeding a trend with high-usage opinion leaders in the target segment produces qualitatively different contagion dynamics than seeding it with a broad early adopter base. Markets with dense, identified opinion leader networks — active industry associations, well-connected trade publications, tight professional communities — are structurally more receptive to trend diffusion than fragmented markets where opinion leaders are dispersed and less connected to each other.

What Uber’s failures demonstrate

Uber’s international expansion illustrates the structural failure mode directly. In US markets, the model spread through an early adopter network with dense peer connections, high trust in the platform model, and cultural looseness around disrupting existing industries. In Southeast Asia, cultural-cognitive legitimacy differences — local consumption culture, cash payment norms, and different relational dynamics between service providers and customers — created adoption resistance that local competitor Grab had accounted for and Uber had not. In China, Uber spent years and billions before exiting entirely in 2016, selling to Didi Chuxing — an operator that had already built the network density and local relational legitimacy required for complex contagion to function.

The same business model, the same technology, categorically different adoption trajectories — determined not by product quality but by whether each market’s social structure supported the specific type of contagion the model required.

Book worth reading on this

How Behavior Spreads by Damon Centola is the most directly relevant treatment of why the viral metaphor fails for business adoption and what the actual mechanics of behavioural spread look like. Centola synthesises a decade of complex contagion research and applies it to technology adoption, social movements, and organisational change — showing across each domain why the strategies that work for spreading information reliably fail for spreading behaviours, and what the alternative looks like in practice. For any entrepreneur trying to understand why their product is not spreading despite genuine early adoption, or why a competitor’s model succeeded in one market and is stalling in another, this is the book that makes the mechanism legible rather than mysterious.

If the dynamics described here are significantly affecting your wellbeing, speaking with a psychologist is the right next step. UK: Samaritans (116 123, free, 24/7). Mind (0300 123 3393). BACP: bacp.co.uk/search/Therapists. Crisis Text Line — text HOME to 741741 (US, UK, Canada, Ireland). International: internationaltherapistdirectory.com.

This article is for educational and informational purposes only. Sources: Centola, D. & Macy, M. (2007), Complex Contagions and the Weakness of Long Ties, American Journal of Sociology, 113(3), 702–734. Centola, D., Becker, J., Brackbill, D. & Baronchelli, A. (2018), Experimental Evidence for Tipping Points in Social Convention, Science, 360(6393), 1116–1119. Rogers, E.M. (2003), Diffusion of Innovations, 5th ed., Free Press. Gelfand, M.J., Nishii, L.H. & Raver, J.L. (2006), On the Nature and Importance of Cultural Tightness-Looseness, Journal of Applied Psychology, 91(6), 1225–1244. Li, R., Gordon, S. & Gelfand, M.J. (2017), Tightness-Looseness: A New Framework to Understand Consumer Behavior, Journal of Consumer Psychology. Iyengar, R., Van den Bulte, C. & Valente, T.W. (2011), Opinion Leadership and Social Contagion in New Product Diffusion, Marketing Science, 30(2), 195–212. Risselada, H., Verhoef, P.C. & Bijmolt, T.H.A. (2015), Understanding Social Contagion in Adoption Processes Using Dynamic Social Networks, PLOS One, 10(10).