This chapter develops the conceptual foundation for Hype Studies by reviewing how hype is treated across different fields and proposing seven core tenets for its analysis. It clarifies how hype overlaps with, but is distinct from, concepts such as speculative bubbles, fashions, organising visions, and promises. Despite its prevalence, hype remains inconsistently defined and theoretically underdeveloped. To address this, we synthesise insights from Science and Technology Studies (STS), especially the Sociology of Expectations; Organisation and Management Theory (OMT); Information Systems (IS); Economics; Economic Sociology; and Cultural Entrepreneurship. Each of the seven tenets addresses a key dimension of hype, offering a framework to better understand how it operates and why it matters. This set of tenets is not intended to be exhaustive – especially when considering areas beyond the digital economy – and some are illustrated more fully than others. Nonetheless, they introduce and foreground the central themes developed in the chapters that follow, and we hope they provide a helpful foundation for the approach to hype advanced in this book.
2.1 Tenet One: Who Creates Hype – Beyond Promise Entrepreneurs to Collective Promissory Arenas
Brown (Reference Brown2003, p. 13) asks, ‘Where do expectations of the future originate’, and ‘by what means do they come to take hold of our imaginations and actions?’. Building on that provocation, we ask whether hype is created by singular ‘promise entrepreneurs’ or emerges from broader ‘promissory arenas’ in which future claims circulate and gain force.
Much existing work emphasises charismatic narrators. Economic analyses of technological bubbles point to ‘narrative accelerators’ (Shiller, Reference Shiller2019; Goldfarb & Kirsch, Reference Goldfarb and Kirsch2019). Cultural Entrepreneurship research foregrounds entrepreneurial ‘storytelling’ and ‘projective storytelling’ as mechanisms for mobilising audiences and resources (Lounsbury & Glynn, Reference Lounsbury and Glynn2001; Garud et al., Reference Garud, Schildt and Lant2014b). STS scholars similarly identify the ‘promise entrepreneur’, who crafts promissory claims to galvanise action (Joly & Le Renard, Reference Joly and Le Renard2021).
Yet such individualised accounts risk creating heroic, actor-centred narratives that retrospectively attribute innovation success to persuasive entrepreneurs while overlooking the institutional, relational, and infrastructural conditions that render their narratives actionable. They also invite survivor bias, leading to an overemphasis on successful innovation stories and an under-representation of those involving failed innovation (Geels & Smit, Reference Geels and Smit2000).
We therefore foreground ‘promissory arenas’ – the collective platforms, networks, and communities through which future-oriented narratives circulate, compete, reinforce one another, and gain power (Bakker et al., Reference Bakker and Budde2012). Individual storytellers matter, but they draw influence from broader infrastructures of promise-making that enrol multiple actors and interacting narratives.
The Sociology of Expectations provides a helpful lens for analysing these promissory arenas. Van Lente’s (Reference Van Lente1993) classic work introduced ‘promise‑requirement cycles’ in technological development: an initial generic promise mobilises interest; users, funders, regulators, and other stakeholders translate that promise into more specific requirements; progress is subsequently assessed against emerging milestones; and promises are recalibrated – strengthened, qualified, or withdrawn – in light of results. Gaps between promise and performance may be tolerated; success builds credibility and mobilises additional support, while shortfalls prompt adjustments or raise doubts. Importantly, the cycle repeats: promises are updated, expectations reset, and resources mobilised or withdrawn depending on whether interim results ‘live up’ to prior claims.
Such longitudinal, cyclical work shows that hype must be continually sustained and negotiated throughout the innovation process. When bold claims remain unproven, actors engage in repair work – adjusting narratives, supplying evidence, or reframing trajectories to maintain credibility (Garud et al., Reference Garud, Schildt and Lant2014b; Hampel & Dalpiaz, Reference Hampel and Dalpiaz2025). In this sense, hype is not a one-off act of overstatement but an evolving dialogue between promise-makers and promise-takers that unfolds over time.
Subsequent scholarship extends analysis from local promise‑requirement exchanges to the broader ecology of discursive and institutional formations that support and contest technological futures (Bakker et al., Reference Bakker, Van Lente and Meeus2011). These studies highlight ‘arenas of expectations’, field-level settings in which entrepreneurs, investors, corporations, regulators, media, analysts, and others contend over competing technological visions (Bakker et al., Reference Bakker, Van Lente and Meeus2011). Multiple arenas may coexist at different levels of aggregation (Bakker et al., Reference Bakker, Van Lente and Meeus2011).
Ruef and Markard (Reference Ruef and Markard2010) identify three levels of expectations that operate across and within such arenas. First, specific expectations are often attached to particular innovations or projects and can be volatile. Second, more general expectations concern the trajectory of a broader technological field and tend to be more durable. Third, higher-level societal imaginaries articulate the technology’s role in society and typically endure longest.
The promissory world is complex and loosely bounded, encompassing multiple expectational alignments of differing intensity, duration, and scale. As Joly (Reference Joly, Akrich, Barthe, Muniesa and Mustar2010, p. 4) argues, this calls for attention to the ‘diversity of arenas’ and for mapping the ‘topology of this space’ of expectations in what he terms the ‘economics of techno-scientific promises’. We build on this point to foreground how hype now underpins a market of its own – a coordinated set of actors and tools devoted to producing and exploiting promissory narratives. In our account, this diversity of arenas is no longer simply a descriptive feature of the promissory world but the basis of an organised economic field in which specialist actors occupy distinct niches, develop proprietary tools, and trade in the management of expectations. By tracing how these arenas interconnect and transact, we show how the business of hype operates as a structured market within the broader economy of expectations.
2.2 Tenet Two: Not All Technologies Generate Hype Equally
Hype is often seen as pervasive in today’s digital economy, but do all technologies generate it to the same extent? Garud et al. (2018, p. 4) raise this question directly, asking whether ‘all fields experience hype cycles’ – prompting us to consider what varies when hype takes shape. Our analysis suggests that hype is far from uniform: both its prevalence and character are uneven. Some domains are intensely saturated with hype, while others remain relatively muted – or even appear ‘hype-resistant’ (Potts, Reference Potts and Potts2017). We identify at least three dimensions along which hype varies: how it functions as a resource, how it operates as a structure, and who (and what) serve as its key catalysts.
2.2.1 Hype as a Resource
Hype confers legitimacy, direction, and coordination capacity in early innovation, yet it also creates obligations that can later backfire. Van Lente (Reference Van Lente2012) conceptualises hype as a resource that performs three critical functions in innovation processes. First, it provides legitimacy, helping to support emerging technologies and create ‘protected spaces’ where promissory narratives can circulate with fewer challenges (van Lente & Rip, Reference Van Lente, Rip, Disco and van der Meulen1998). Second, it offers direction, reducing uncertainty by suggesting plausible technological trajectories and guiding actors through moments of indeterminacy (Deuten & Rip, Reference Deuten and Rip2000). Third, it enables coordination, helping to align diverse stakeholders by defining roles, expectations, and responsibilities within innovation networks.
Yet this resource is not without risk. As van Lente et al. (Reference Van Lente, Spitters and Peine2013) caution, hype can unravel when expectations are not met. Ruef and Markard (Reference Ruef and Markard2010) expand on this, warning that declining hype can lead to disappointment, resource withdrawal, and a loss of momentum, as attention wanes and actors begin to exit the field. Similarly, Logue and Grimes (Reference Logue and Grimes2022, p. 1055) characterise hype as a ‘short-term resource but long-term risk’, suggesting that while hype may initially attract interest and support, it can also generate a growing burden of accountability. Over time, the promises embedded in hype create a sense of obligation between ventures and their audiences – obligations that may prove challenging to satisfy and that can backfire when expectations are not met.
2.2.2 Hype as Structure
When many actors repeatedly draw on hype as a resource, their efforts can sediment into broader structures of expectation. Palavicino (Reference Palavicino2016, p. 26) distinguishes between individual ‘hyping practices’ and the emergence of ‘meta-level’ hype phenomena, such as categories. In practice, this means repeated promotional storytelling around a technology can crystallise into a shared narrative or category that transcends any promoter. The case of Juvo’s FIDaaS category exemplifies this process, where what began as a strategic label for a single venture evolved into a recognisable market category. Rip and Voß (2009) characterise as an ‘umbrella term’ the categories that structure expectations and align actors.
This analytical aspect raises important questions about how hype evolves from individual performance to collective infrastructure. Van Lente and Rip (Reference Van Lente, Rip, Disco and van der Meulen1998) offer a helpful lens, theorising how emergent hype categories can become ‘macro actors’ – entities that not only gain visibility but also shape the contours of a field, including its dominant narratives and key players. Logue and Grimes (Reference Logue and Grimes2022, p. 1055) similarly stress the importance of ‘collective expectations’ and argue that individual acts of entrepreneurial hyping – however compelling – may fail unless embedded in a ‘corresponding vision that is collectively espoused and increasing in attention’. They suggest that projective storytelling risks ringing hollow without this shared uptake, lacking the structural support necessary to mobilise wider belief and engagement.
2.2.3 Hype’s Catalysts
Building on the insight above that multiple actors inhabit promissory arenas, we ask who amplifies or filters hype, and what events set hype in motion. Research in the Sociology of Expectations and further afield has differentiated between types of actors, noting that not everyone involved in innovation contributes to hype equally. For instance, Konrad and Alvial-Palavicino (Reference Konrad, Alvial-Palavicino, Konrad, Rohracher and von Schomberg2017) draw a line between ‘innovation creators’ and ‘hype creators’. Scientists or developers (‘innovation creators’) may focus on making the technology and only engage in minimal ‘expectation work’ if necessary. In contrast, other actors – specialised journalists, consultants, and analysts (‘hype creators’) – devote much of their effort to shaping narratives about innovations, despite not being directly involved in building the innovations themselves.
Bakker and Budde (Reference Bakker and Budde2012) offer a complementary typology, distinguishing between ‘hype enactors’ – such as innovators and entrepreneurs – and ‘hype selectors’ – including investors, adopters, and industry analysts. Hype enactors are those directly engaged in developing technologies or promoting specific futures, whereas hype selectors evaluate these futures, deciding whether to allocate resources, endorse claims, or adopt emerging solutions. Selectors’ due diligence and critical distance are vital: their filtering function strongly conditions whether hype diffuses, stalls, or dissipates (Bakker & Budde, Reference Bakker and Budde2012).
Moreover, hype often coalesces around ‘trigger events’ – moments that amplify attention, mobilise interest, and shape early public perceptions (Kiefer, Reference Kiefer2013). For example, Simakova and Coenen (Reference Simakova, Coenen, Owen, Bessant and Heintz2013) emphasise the role of ‘conferences’ in animating hype, which Garud and colleagues (Reference Garud2008) conceptualise as ‘field-configuring events’ – events that serve as pivotal interventions that help construct and legitimise technological futures by establishing early narratives and drawing diverse actors into alignment. Brown (Reference Brown2003) draws attention to the ‘press release’ in scientific contexts, framing it as a ‘point of translation’ through which technical research is transformed into accessible and often promissory public narratives. Similarly, Pontikes and Barnett (Reference Pontikes and Barnett2017) examine ‘vital events’ such as major venture capital (VC) funding rounds, which generate visibility and credibility, helping to construct ‘hot markets’ around nascent technologies. As Konrad et al. (Reference Konrad, Van Lente, Groves, Selin, Felt, Fouché, Miller and Smith-Doerr2016) noted, government investment initiatives also operate as trigger events, signalling institutional commitment to specific futures and lending weight to accompanying promotional claims.
2.2.4 Uneven Distribution of Hype
Returning to our guiding question, hype accompanies most innovations to some degree, but its intensity, reach, and duration vary widely. Most innovations are subject to some level of heightened expectation, driven by the inherent uncertainty surrounding their outcomes. However, hype’s intensity, reach, and duration can vary considerably depending on the nature of the technology. In some cases, hype remains localised and short-lived; in others, it becomes widespread, sustained, and strategically cultivated over long periods.
Radical or disruptive innovations are especially prone to attracting significant public interest and media attention (Beckert, Reference Beckert2016; Byrne & Giuliani, Reference Byrne and Giuliani2025; Magalhães & Smit, Reference Magalhães and Smit2025). These technologies typically involve ambitious long-term visions, requiring substantial investment and extended timelines before outcomes can be realised. Gaining support thus demands a particularly proactive process of mobilising expectations and sustaining belief across multiple stakeholders. As Beckert (Reference Beckert2016) argues, the more uncertain the future path of an innovation, the greater the effort required to coordinate imaginations – and the more intense the surrounding hype tends to be (see also van Lente & Bakker, Reference Van Lente and Bakker2010).
By contrast, incremental innovations often receive lower (and more localised) levels of hype, even though they may deliver significant cumulative gains (Gardner et al., Reference Gardner, Samuel and Williams2015). Why is this? Several factors help explain this disparity. Incremental developments usually emerge within established technological communities, where claims can be more easily evaluated and scrutinised through existing relationships and accountability mechanisms. Familiarity with vendors and prior evaluation criteria may thus reduce the space for exaggerated expectations.
Certain technologies draw more hype for other reasons. Some are more ‘hype-able’ than others (Potts, Reference Potts and Potts2017). For example, in the 1980s, industrial robots dominated public and policy discourse, while other, arguably more impactful automation tools, such as programmable logic controllers, received far less attention (Fleck et al., Reference Fleck, Webster and Williams1990). The robot served as a striking, media-friendly figure, offering a simplified and intelligible representation of complex developments. In contrast, less visually or imaginatively compelling technologies, such as programmable logic controllers, despite their profound real-world effects, remained largely invisible in public and policy discussions.
This asymmetric distribution of hype has significant consequences. If hype is understood as a resource, visibility becomes a critical currency in the digital economy. While all technologies require attention to progress, only a select few succeed in attracting the concentrated expectations that unlock funding, legitimacy, and broader momentum (Faxon et al., Reference Faxon, Fields and Wainwright2024).
Crucially, the capacity to generate and circulate hype appears to be unevenly distributed (Byrne & Giuliani, Reference Byrne and Giuliani2025). As Brown (Reference Brown2003, p. 5) observes, hype reflects the ‘asymmetries between people and groups in their access to information within the knowledge economy of expectations’. This leads to a spotlight effect, where highly hyped technologies overshadow other promising innovations (Potts, Reference Potts and Potts2017). Technologies lacking access to influential sponsors or gatekeepers may struggle to gain visibility, regardless of their technical merits. As Bakker and Budde (Reference Bakker and Budde2012) suggest, such innovations often falter due to insufficient attention and resource mobilisation. In some cases, this may even contribute to the emergence of ‘innovation deserts’ – fields that remain underdeveloped not because of a lack of potential but because of a lack of hype (Sharma & Meyer, Reference Sharma and Meyer2019).Footnote 1
2.3 Tenet Three: Hype’s Conceptual Boundaries – Overlaps with but Distinct from Similar Concepts
Research identifies various ‘modes of constructing the future’ (Konrad et al., Reference Konrad, Van Lente, Groves, Selin, Felt, Fouché, Miller and Smith-Doerr2016, p. 11), including speculative bubbles, fashions, promises, visions, and imaginaries. What is the relationship between hype and these other related future-based concepts? It is interesting to explore how various contributions with different disciplinary roots and concerns have converged on a specific area of expectations (with many explicitly considering hype). Notwithstanding this convergence, the multiple traditions have their own conceptual baggage and concerns. These concepts share commonalities with hype, but each operates through distinct mechanisms and emphasises different dynamics. In our view, hype is a defining (if variable) feature of emerging technology futures, surfacing in diverse forms under conditions of uncertainty. While related to these concepts, hype also has unique characteristics that warrant closer examination. Below, we consider six adjacent concepts – speculative bubbles, management fashions, organising visions, promise, sociotechnical visions, and imaginaries – to clarify where hype aligns with and diverges from each.
2.3.1 Speculative Bubbles
Speculative bubbles are a market phenomenon in which asset prices rise rapidly to levels far exceeding their intrinsic value, often fuelled by ‘irrational exuberance’ and ‘herd behaviour’ (Shiller, Reference Shiller2015; Goldfarb & Kirsch, Reference Goldfarb and Kirsch2019). Kindleberger and Aliber (Reference Kindleberger and Aliber2005, p. 25) define an asset pricing bubble as an ‘upward price movement over an extended period of 15–40 months that then implodes’, while Taleb (Reference Taleb2010) highlights the role of collective overconfidence in sustaining these inflated valuations. Central to bubbles is Greater Fool Theory – how investors buy overvalued assets expecting to sell them to someone else at a higher price (Barlevy, Reference Barlevy2015).
Hype and bubbles share common patterns of rapid escalation in attention and investment. Both are fuelled by optimism and anticipation, often amplifying expectations well beyond current realities. However, while speculative bubbles are typically followed by a sharp correction or dramatic collapse, hype does not necessarily follow the same trajectory. As Goodnight and Green (Reference Goodnight and Green2010, p. 116) put it, bubbles are ‘temporary departures from rational norms awaiting correction’. Floridi (Reference Floridi2024, p. 127) notes that while hype cycles may resemble ‘tech bubbles in the making’, they do not always culminate in collapse. All bubbles involve hype, but not all hype produces bubbles. Hype may instead persist, evolve, or taper without implosion – especially when underlying promises begin to be realised. As Logue and Grimes (Reference Logue and Grimes2022) observe, bubbles tend to implode when expectations are not met, whereas hype can stabilise and mature if evidence emerges that supports its claims.
2.3.2 Management Fashions
Management fashions are transitory waves of managerial ideas that diffuse and fade as attention shifts among knowledge consumers. OMT has long used the concept of management fashions to describe the fads and waves of popular ideas in the business world, such as Total Quality Management, Six Sigma, and Business Process Reengineering. Abrahamson and Fairchild (Reference Abrahamson and Fairchild1999, p. 709) define management fashions as ‘relatively transitory collective beliefs that certain management techniques are at the forefront of rational management progress’. Like hype, fashions generate bursts of enthusiasm, creating temporary spaces for exploration and experimentation before enthusiasm wanes and the field moves on (Rip, Reference Rip2000).
Yet there are critical differences between fashions and hype, and we foreground one in particular: carrying capacity. Abrahamson and Fairchild (Reference Abrahamson and Fairchild1999, p. 713) argue that management fashions have a ‘finite carrying capacity’, because ‘knowledge consumers can only attend to a limited number of fashions simultaneously’. In other words, the management world can only sustain a handful of dominant fashions at any one time; the collapse of one would free up space for another to take its place.
Hype, by contrast, appears to operate on a very different scale and is not subject to the same dynamics. Industry analysts now track hundreds of concurrent ‘hype cycles’ in the digital economy (see Chapter 6), where management fashions once moved in relatively slow, sequential waves. Hype more closely resembles a ‘sea of expectations’ – to borrow van Lente’s (Reference Van Lente2012) evocative phrase – with countless overlapping narratives simultaneously competing for attention. This proliferation suggests that hype has far greater carrying capacity: it can sustain a crowded, turbulent ecosystem of expectations without requiring one narrative to collapse before another can rise.
2.3.3 Organising Visions
Organising visions are practitioner‑anchored community ideas that make a digital innovation intelligible, useful, and actionable (Swanson & Ramiller, Reference Swanson and Ramiller1997). An organising vision provides a shared way for practitioners to name, explain, and justify an emerging technology: what it is, why it matters, and how it might be implemented. Swanson and Ramiller (Reference Swanson and Ramiller1997, p. 460) define an organising vision as a ‘focal community idea for the application of information technology in organisations’. By furnishing a common vocabulary and set of usage scenarios, organising visions helps align users, vendors, consultants, and other stakeholders around a technology’s potential.
Organising visions have temporal ‘careers’ (Ramiller & Swanson, Reference Ramiller and Swanson2003). They often emerge in vague form, struggle for legitimacy, and – if they gain traction – diffuse, stabilise, and eventually fragment or decline as new visions take their place (Swanson et al., Reference Swanson, Ramiller and Wang2025). Classic examples include Enterprise Resource Planning (ERP) and Customer Relationship Management (CRM) (see Chapter 7).
Because organising visions must support implementation conversations, they usually require a threshold level of stability and clarity; practitioners need to be able to discuss scope, benefits, and integration choices to act (Swanson et al., Reference Swanson, Ramiller and Wang2025). Hype, by contrast, can thrive on ambiguity, allowing multiple audiences to project their hopes and interpretations onto an innovation well before a coherent community forms. Put differently, an organising vision acts as a sense‑making device for a community; hype functions as an attention‑making device that can precede community formation and, at times, help bring one into being.
2.3.4 Promise
In the Sociology of Expectations, a promise is a problem‑oriented commitment that maps a pathway from an identified challenge to a prospective technological solution. Numerous terms – such as promise, expectations, visions, and imaginaries – have been used within the Sociology of Expectations with varying consistency and are often employed in overlapping ways. These differences in terminology can partly be attributed to the distinct initial problems they address, with each term carrying a heritage that has influenced subsequent discourse. The concept of promise, for example, forms the foundation of the Sociology of Expectations, yet it is frequently discussed alongside the notion of vision. For instance, Borup et al. (Reference Borup, Brown, Konrad and van Lente2006) often refer to ‘expectations and visions’ in tandem, reflecting their interconnected roles.
Promise is also used interchangeably with hype, yet each concept encapsulates distinct dynamics. Brown and Michael (Reference Brown and Michael2003, p. 3) describe promises as ‘crucial to providing the dynamism and momentum upon which so many ventures in science and technology depend’, highlighting their role in framing a pathway towards specific solutions. Similarly, Joly (Reference Joly, Akrich, Barthe, Muniesa and Mustar2010, p. 5) observes that promises focus on addressing a clearly defined ‘problem which has to be fixed’, making them particularly compelling when the problem is urgent and widely recognised.
While hype and promise share a focus on mobilising attention and resources, they diverge in scope and emphasis. Research on promises examines how generic claims are translated into specific, achievable requirements and obligations over time. Promises are typically more structured and directed, anchoring innovation as a targeted response to particular stakeholders or societal challenges. In contrast, hype operates more diffusely, amplifying the urgency and visibility of promises while broadening their appeal. It thrives on creating excitement and attention across a competitive landscape, emphasising the potential of multiple innovations to dominate the field and securing resources for expected winners.
Promises are foundational elements in the innovation narrative, setting precise trajectories for development and offering a rationale for investment and support (Berkhout, Reference Berkhout2006). Hype, however, magnifies the scope of these promises, leveraging the dynamics of attention and commitment to generate widespread anticipation. Where promises articulate targeted goals and solution pathways, hype acts as a force multiplier – extending reach, intensifying urgency, and inserting those promises into broader competitive contexts.
2.3.5 Sociotechnical Visions
Sociotechnical visions articulate value‑laden images of preferred futures that link technological change to social orders, policy goals, and cultural commitments. The work on visions starts with the problem faced by technology application developers and later emerging technology R&D programmes in envisioning a future technology and the world it would operate in. Arguably, the starting point was the concept of ‘script’ arising from Akrich’s (Reference Akrich, Bijker and Law1992) early work on user representations. The vision concept was used to analyse the sociopolitical agendas informing particular design choices. A key challenge with novel technologies is that there are no actual users or markets in the early stages of radical innovation. Therefore, what mobilises support is visions of potential users and uses. Scholarship here aims to make explicit the (often tacit) sets of ideas that shape the development effort. Innovators are seen to mobilise visions and expectations, with visions thus having a normative role in motivating support (while temporarily ignoring counter-programmes and their dystopian vision) (Berkhout, Reference Berkhout2006). So, envisioning is the work of bringing these representations into existence and mobilising support around particular representations and scripts.
Visions represent broad, collective images of the future that capture a community or society’s shared expectations regarding the trajectory and benefits of scientific and technological advancements (Konrad et al., Reference Konrad, Van Lente, Groves, Selin, Felt, Fouché, Miller and Smith-Doerr2016). As Berkhout (Reference Berkhout2006, p. 300) notes, ‘visions of the future tend to be ‘moralised’, in the sense of being encoded and decoded as either utopias or dystopias’. Thus, visions are deeply rooted in cultural values and societal goals, providing a framework for conceptualising and working towards a collective future that influences the direction of technological development by aligning research, policy, and social objectives. Similarly, as Konrad et al. (Reference Konrad, Van Lente, Groves, Selin, Felt, Fouché, Miller and Smith-Doerr2016, p. 3) note, visions ‘imply normative connotations, often being statements of desirable or preferable futures, while not necessarily including assessments of likelihood or plausibility’.
In contrast, while hype is more focused on capturing immediate attention and tends to be short-lived, visions are longer-term, stable, and woven into societal frameworks. Hype can support a vision by attracting attention and resources to bring about a particular future; however, a vision is not solely reliant on hype. Instead, they form part of a larger narrative about society’s aspirations for its technological potential. While hype typically builds around specific visions, the latter, as Konrad et al. (Reference Konrad, Van Lente, Groves, Selin, Felt, Fouché, Miller and Smith-Doerr2016, p. 3) point out, ‘relay a fuller portrait of an alternative world that includes revised social orders, governance structures, and societal values’.
2.3.6 Sociotechnical Imaginaries
Sociotechnical imaginaries extend visions by embedding future technologies within institutionally stabilised, publicly performed narratives about desirable social orders. Imaginaries present a future technology and the world in which it is embedded, providing commentary on why particular collectively imagined societies are emerging and being upheld through institutions and public discourse. The notion of imaginary thus extends the account of the better world into which technology will be introduced and explicitly recognises the roles and practices involved. Though the term can be traced back to Gregory (Reference Gregory2000) and Hyysalo (Reference Hyysalo2006), Jasanoff has popularised it. Jasanoff and Kim (Reference Jasanoff and Kim2015, p. 6) define sociotechnical imaginaries as ‘collectively held, institutionally stabilised, and publicly performed visions of desirable futures, animated by shared understandings of forms of social life and social order attainable through, and supportive of, advances in science and technology’. Hype differs from an imaginary in that it does not ask you to judge the direction of innovation or choose a desirable or preferred future. Instead, it generates interest in innovation, bringing it to the attention of key players in the innovation landscape and facilitating the securing of investments.
2.3.7 Hype’s Characteristics
Having compared hype with related concepts, we can now provisionally distil what makes it distinctive as a phenomenon of interest. We identify four core characteristics that differentiate hype and help explain its influence on technologies: (i) mobilisation and interessement, (ii) exaggeration and the ‘Hiding Hand’, (iii) uncertainty amplification, and (iv) shifting focus and demobilisation. Together, these dynamics illuminate how hype mobilises resources, amplifies excitement, directs (and redirects) attention, and shapes the innovation process.
2.3.7.1 Mobilisation and Interessement
Hype primarily functions to mobilise attention and resources, especially in contexts marked by uncertainty and unpredictable outcomes, such as the projections surrounding radical technologies. At its core, hype generates attention and the conditions for investment in radical or disruptive technologies. It concentrates attention and attracts resources in the face of high uncertainty, drawing diverse actors into provisional alignment – what Callon (Reference Callon1984) terms interessement.
The funding and interest that hype attracts can accelerate innovation. Brown (Reference Brown2003, p. 11) observes that the resources mobilised by hype are ‘fundamental to producing the incentives and obligations necessary’ for a new technological sector to grow. By priming audiences and committing resources before performance evidence exists, hype can speed technological development beyond what incremental, evidence‑led investment would permit. Its generativity lies in its capacity to embed a technology in the collective imagination, reshaping expectations ahead of demonstrable proof.
Radical innovation requires that belief precede evidence. While some view this as hype producing ‘misleading claims’ – implying unproductive technologies or overreach (Vinsel & Russell, Reference Vinsel and Russell2020; Min, Reference Min2024) – early unverifiability need not imply deception. There are many reasons why claims cannot be fully verified at the outset (Konrad, Reference Konrad2006):
Limited Evidence. A technology may be beneficial, but there has not yet been sufficient time or opportunity to collect and appraise performance data. Radical novelty can generate Knightian uncertainty (Knight, Reference Knight1921; see Chapter 3).
Social Learning. Novel technologies are often immature and require iterative refinement – in the product/service and the surrounding socio‑technical context – before productivity can be realised (Arrow, Reference Arrow1962; Sørensen, Reference Sørensen1996).
Scaling Dependencies. Without a critical mass of users and complementary producers, cost‑effectiveness, profitability, and sustainability remain indeterminate (Williams et al., Reference Williams, Stewart and Slack2005).
Given these constraints, some level of inflated expectation is necessary – and, some would argue, beneficial (Potts, Reference Potts and Potts2017) – enabling promising technologies to move towards realisation. Therefore, the test of whether hype is productive relies not on whether it is true but on whether it is ‘performative’ – insofar as it allows a promising technology to come to fruition. By enabling investors, entrepreneurs, and collaborators to behave as though the proposed outcomes are real, hype helps bring those outcomes about. In short, hype is more than mere optimism – it propels investment, collaboration, and experimentation towards the hyped vision (see Tenet Five for how this process unfolds).
2.3.7.2 Exaggeration and the ‘Hiding Hand’
How might we conceptualise the role of exaggeration in hype? On the face of it, overstated promises and inflated expectations seem problematic, setting the stage for inevitable disappointment. Yet in the history of innovation, exaggeration often appears to have a generative role. Rather than merely distorting, it can stimulate action and commitment that might not otherwise occur.
Hirschman’s (Reference Hirschman1967) idea of the ‘Hiding Hand’ provides one way to make sense of this paradox. The idea suggests that actors often embark on ambitious projects with misplaced or ‘blind’ confidence without fully understanding the challenges. While this initial misjudgement might appear detrimental, Hirschman (Reference Hirschman1967) posits that the subsequent confrontation with unforeseen challenges triggers a resourceful and creative response, ultimately transforming potential failure into success. Ironically, as Hirschman sees it, misplaced confidence – believing a project will be more straightforward than it is – enables the courage to start it in the first place. As Hirschman (Reference Hirschman1967, p. 13) explains, the hiding hand’s value lies in ‘inducing risk-averters to commit themselves to risk-taking behaviour’, thereby enabling an ‘acceleration of economic growth’.
This principle is especially instructive in analysing hype. The ‘exaggeration of benefits’ (Hirschman, Reference Hirschman1967, p. 26), a hallmark of hype, serves a similar purpose: warding off the ‘missed opportunity’ of inaction driven by uncertainty or scepticism. The utility of hype extends beyond generating initial enthusiasm; it also fosters resilience and adaptability when unexpected challenges arise. As Hirschman (Reference Hirschman1967, p. 15) describes, market actors who have committed significant resources and energy to a project become motivated to ‘generate all the problem-solving energy of which they are capable’. In this way, hype, like the Hiding Hand, transforms adversity into a catalyst for innovation and progress. This interplay between optimism and adaptability is central to transforming hype into realised innovations. It aligns with the broader discussions in After Hype, where hype is framed not merely as a by-product of innovation cycles but as a strategic tool for navigating the complexities and uncertainties of technological futures (Mouritsen & Kreiner, Reference Mouritsen and Kreiner2016).
2.3.7.3 Uncertainty Amplification
Hype is closely associated with breakthrough or disruptive technologies. Radical claims strain established evaluative frameworks, opening contested arenas in which bold projections proliferate. Beckert (Reference Beckert2016, p. 186) notes that ‘while levels of uncertainty differ among innovations, growth dynamics and high profits tend to come from the most radical ones, which are generally also the ones with the highest levels of uncertainty’. Felt et al. (Reference Felt, Wynne, Callon, Gonçalves, Jasanoff, Jepsen, Joly, Konopasek, May, Neubauer, Rip, Siune, Stirling and Tallacchini2007) similarly show that hype both draws on and magnifies uncertainty about the future.
Crucially, the most‑hyped technologies are framed as radically disruptive, and their claims can destabilise – or even render obsolete – established evaluative frameworks. McBride et al. (Reference McBride, Packard and Clark2024, p. 410) describe this as the ensuing ‘battle for assessment contexts’ as actors compete to define the metrics by which these technologies should be judged. When no settled measures exist, bold projections more easily ‘get a hearing’ (Borup et al., 2006, p. 410). Each wave of radical announcements enlarges this vacuum, triggering new rounds of hype. This destabilisation is not a side effect; it is what allows hype to flourish. By undermining established evaluative infrastructures, disruptive technologies create profound Knightian uncertainty (Knight, Reference Knight1921; see Chapter 3), where new claims can circulate freely, inviting a proliferation of related projections (see Figure 2.1).
Figure 2.1 Long description
The diagram has four elements connected via arrows in a cyclical arrangement. The elements in the clockwise order are as follows: Announcement of radical technologies, Creates Knightian uncertainty, Existing evaluation frameworks become obsolete, and Creates
environment for unrestricted mobilisation of hype.
Our book captures the moment when radically framed technologies prompted industry analysts to develop new evaluation tools. They initially lacked metrics that could accommodate two critical developments: (i) the rise of emerging technologies (Chapters 6 and 7) and (ii) the proliferation of disruptive start-ups (Chapters 4 and 5). Both shifts initially sat outside established evaluative frameworks, creating fertile ground for hype to take hold. Metrics designed for mature products – such as the Magic Quadrant – proved inadequate. We show how industry analysts – initially slow to recognise these developments – were eventually compelled to respond. They introduced instruments like the Hype Cycle Chart (HCC) and Cool Vendors, which foreground the prospective performance of emerging technologies and new ventures.
2.3.7.4 Shifting Focus and Demobilisation
Hype Rarely Stands Still. Unlike relatively stable expectations (imaginaries, visions, promises), hype is transient and shifting: it may surge rapidly to attract interest and investment, then fade, fragment, or migrate to the next opportunity. Because hype is transient, support can unwind, and attention can shift rapidly, disengaging actors from current projects and redirecting them towards the next opportunity. Its transient nature introduces phases of demobilisation: when expectations stall or disappoint, attention, investment, and organisational commitment can contract (Ruef & Markard, Reference Ruef and Markard2010). Importantly, hype not only generates new interest; it also reallocates attention, pulling resources away from ongoing developments. Stakeholders with weaker ties can switch allegiance quickly when a new, more hyped innovation appears (Bakker & Budde, Reference Bakker and Budde2012).
Promoting a new hyped technology often entails a strategic distancing from incumbent alternatives. Proponents typically have to ‘fight against old technologies’, and, as Joly (Reference Joly, Akrich, Barthe, Muniesa and Mustar2010, p. 4) points out, that ‘battle is not easily won’. Emphasising radical novelty helps recast existing solutions as outdated.
One way hype accelerates such shifts is by creating a sense of urgency. Innovation is often portrayed as a global race, with the implication that there is ‘no time to lose’ (Felt et al., Reference Felt, Wynne, Callon, Gonçalves, Jasanoff, Jepsen, Joly, Konopasek, May, Neubauer, Rip, Siune, Stirling and Tallacchini2007, p. 79). Hype pressures as well as excites. Fear of missing out (FOMO; Vinsel & Russell, Reference Vinsel and Russell2020) implies that only early adopters – those bold enough to embrace the latest breakthrough – will emerge as winners. Under the grip of such promissory narratives, we may, Felt and colleagues caution, ‘risk subordinating ourselves’ to the imagined futures they project (2007, p. 79).
2.4 Tenet Four: Hype as an Actor Concept – Used and Managed Knowingly by Practitioners
Up to now, we have been examining hype from an analytical perspective – how we, as researchers, might conceptualise hype’s origins, distribution, and distinct features. However, we want to shift the view to consider how market actors involved in innovation themselves understand and manage hype. We will argue that hype is not just an analyst’s category; it is also an actor’s category. While concepts such as imaginaries, promises, and visions function purely as analyst constructs, hype uniquely operates as both. The very word ‘hype’ is used by practitioners, investors, industry commentators, etc., as part of their everyday vocabulary. Put differently, hype functions as a ‘folk concept’ (Swedburgh, Reference Swedberg2018) in innovation, meaning that it carries practical significance for those actors involved.
Recognising hype as an actor concept has important implications. It implies the existence of a lay theory of hype – one that may diverge from social‑science accounts. Academic treatments often frame hype as noise or misleading exaggeration, yet our fieldwork indicates that market actors deploy a richer taxonomy of hype distinctions than scholars often credit (Swedberg, Reference Swedberg2018). They sort ‘good’ from ‘bad’ hype and calibrate their language accordingly.
Take, for example, analyst relations (AR) experts – the professionals discussed in this book who coach technology ventures on how to pitch to industry analysts. They provide detailed guidance on crafting promissory narratives and explicitly caution against using specific ‘hyped-up’ terms that may undermine credibility. These include phrases like ‘game changer’, ‘best in class’, ‘industry-leading’, ‘world-beating’, and ‘we have no competitors’. When overused, such language serves as a red flag to seasoned analysts, signalling either a lack of substance or naive over-enthusiasm.
This kind of practitioner insight forms part of what we mean by hype as an actor concept (see De Togni et al., Reference De Togni, Erikainen, Chan and Cunningham-Burley2024). To illustrate this, we compiled a list of commonly discouraged hype terms (see Box 2.1), drawn from AR advisory materials, showing that practitioners operate with their own informal heuristics for evaluating and deploying hype.
‘First’
‘Game changer’
‘Only’
‘Superiority’
‘Best in class’
‘World class’
‘The Leader’ and related…’
‘Industry leading’
‘Market leading’
‘We always beat [a market leader]’
‘Top tier’
‘We have no competitors’ and related…’
‘Our only competition is in-house development’
‘Only indirect competitors are enterprise home-grown applications’
‘We never see [a market leader]’
‘We’ve open sourced our code’
Why does it matter that market actors have a rich understanding of hype? For one, it suggests that academic analysis tends to produce a simplified, ‘thin’ account. Pollner (Reference Pollner and Woolgar2002) warns of the dangers of ‘conceptual deflation’, where scholarly work fails to provide new insights or challenge taken-for-granted assumptions. The upshot is that we tell those we study what they already know (or even less than they know).
One example is the growing number of academic studies suggesting that particular technologies have entered a ‘hype cycle’ (e.g. Geiger & Gross, Reference Geiger and Gross2017). Though such an observation may be helpful, scholarly discussion needs to do more than reproduce actor terms, which may simply confirm rather than challenge prevailing perceptions. One goal of this book is to develop a more nuanced empirical understanding of how hype is generated, assessed, and consumed, as well as its impact. If our existing analytical concepts are not significantly different (or perhaps even inferior) to those of the individuals we study, then we may need to develop new ones. In this book, we use the actor term but locate it within a more carefully considered framework.
While scholarship has not shown much interest in hype as an actor concept, some exceptions exist. A frequent starting point has been to emphasise the colloquial connotations of hype as overstatement. Thus, Palavicino (Reference Palavicino2016, p. 149) describes hype as a ‘strategic act of exaggeration by innovation actors’. However, Wüstenhagen et al. (Reference Wüstenhagen, Wuebker, Bürer, Goddard, Truffer, Markard, Wüstenhagen and Wiek2009, p. 123) note innovators’ awareness of expectation dynamics and how they ‘use them to their advantage, communicating (and sometimes overstating) the promise of the technology to garner these resources’ (see also Minkkinen et al., Reference Minkkinen, Zimmer and Mäntymäki2023).
Birch’s (Reference Birch2023) concept of ‘reflexive expectations’ goes further, highlighting actors’ gameful generation of strategic narratives. He notes that actors are ‘deliberately and consciously generating stories or acting reflexively concerning them as part of their investment expectations, decisions, and strategies’ (Birch, Reference Birch2023, p. 45). This means that at least some actors are self-aware about the game of hype – they know they are constructing narratives and do so with intent, adjusting their message as needed to keep investors interested.
One striking example of an actor concept is the Hype Cycle Chart (HCC), which Rip (Reference Rip2019) characterises as a ‘folk theory’. Developed by the analyst firm Gartner, the HCC depicts the typical trajectory of hype associated with emerging technologies. While Rip critiques the model as being ‘plainly wrong’ in empirical terms, he also acknowledges its resonance, describing it as offering a ‘plausible storyline about how things go’ (2019, p. 361).
This discussion highlights a broader tension in scholarly debates around such tools. The assumption is that their value may not lie in empirical accuracy but in their social robustness and performative influence. As Rip puts it, the power of folk theories stems from their widespread circulation – ‘their robustness derives from their being generally accepted, and thus part of a repertoire current in a group or in our culture more generally’ (2019, p. 361). This insight invites us to take seriously how these devices operate, not just as representations but as instruments of coordination and influence.
Indeed, academic criticism of hype tools like the HCC can miss their practical significance. For instance, Borup and colleagues (Reference Borup, Brown, Konrad and van Lente2006, p. 292) have criticised the HCC for producing a ‘highly linear understanding of a technology’s path dependency and fails to account for the way artefacts or technologies actually change over time in a continual and practical process of reconfiguring and being reconfigured in use’. While these critiques are valid from an innovation scholar’s standpoint, they overlook how such tools have become embedded in practice. Many decision-makers are aware that technologies may deviate from the HCC pattern (Chapter 6), but the key point is that it has become integral to the actor’s toolkit, influencing market behaviour. Therefore, studies of hype should incorporate how such folk theories of hype shape real-world actions (rather than only pointing out their flaws).
More scholarly attention could be dedicated to understanding hype as an actor concept. This is particularly important, given the emergence of hype’s new actors and industry analyst tools like the HCC, which potentially encourage innovation communities to react differently to the uncertainties generated by the sea of competing claims. Embracing hype as an actor concept pushes us to ask new questions. For instance, how does introducing tools like the HCC change how technology adopters navigate hype? We suspect that with the institutionalisation of such hype tools, market actors no longer react to hype in the way they did before their introduction. For instance, as discussed in Chapter 6, the very act of saying a specific technology is in ‘The Trough of Disillusionment now’ (one of the HCC’s stages) provides a narrative for timing investments that differs from the past.
This evolution suggests that the phenomenon of hype itself is changing. As actors become more reflexive – aware of recurring patterns and increasingly equipped with tools to manage them – hype waves may now inflate and deflate in ways that differ from the past. Hype is shifting from something that simply happens to actors to something they actively navigate and shape. This transformation invites a corresponding shift in scholarly approaches.
2.5 Tenet Five: Hype’s Influence – From Performativity (Enacting Futures) to Reflexivity (Adapting Narratives)
One of the most contested questions in the study of hype concerns its ability not merely to describe possible futures but to help bring them into being. Does hype simply gesture towards a potential horizon, or can it actively contribute to realising that future (performativity) by mobilising belief, investment, and coordinated action? Or must it adapt as reality unfolds (reflexivity)?
Early work in the Sociology of Expectations and related fields focused on the performativity of expectations, suggesting that strong expectations can become self-fulfilling (Kriechbaum et al., Reference Kriechbaum, Posch and Hauswiesner2021). Brown (Reference Brown2003, p. 5) argued that ‘hype is constitutive’, mobilising the ‘future into the present’. Beckert (Reference Beckert and Musselin2013, p. 226, our emphasis) likewise suggested that ‘imaginings of future states become determinate’. Garud et al. (Reference Garud, Gehman and Giuliani2014a, p. 1183, our emphasis) observed that ‘innovation is driven by entrepreneurs’ imagination of the future’. More recently, Bareis and Katzenbach (Reference Bareis and Katzenbach2022, p. 876) pointed to the performativity of national artificial intelligence (AI) strategies. As they note, governments do not simply describe technological futures – they actively participate in ‘coproducing the instalment of these futures’ by backing visions with ‘massive resources and investments’, thereby ‘locking in’ particular ‘trajectories’.
Together, these arguments support a performative view of hype: it does not just forecast; it can help enact what it proclaims by attracting resources and framing problems and solutions. This perspective offered a powerful rejoinder to dismissals of hype as mere exaggeration or noise. Traditional academic perspectives struggled with the fact that future outcomes are unknowable until hindsight reveals them – often too late to be useful (Master & Resnik, Reference Master and Resnik2013). Performativity shifted the analytical focus: rather than asking whether early claims are ‘true’, it examined how they mobilise actors and resources in ways that can change what eventually becomes true.
However, the performativity thesis has not gone unchallenged. Critics note that it does not fully explain why some expectations become self-fulfilling while others are revised, deferred, or abandoned (Oomen et al., Reference Oomen, Hoffman and Hajer2022). In addition, the presumed performativity of hype often rests on episodic case studies that focus on the articulation of visions while implicitly assuming their eventual realisation. In doing so, researchers risk being drawn into the narrative frames of ‘promise entrepreneurs’, blurring the line between aspirational rhetoric and unfolding reality (e.g. Goldfarb & Kirsch, Reference Goldfarb and Kirsch2019, p. 61).
While the concept of performativity offers valuable insight, it requires more qualified application. The idea of simple performativity – where an a priori vision cleanly and fully shapes reality – is arguably no more plausible than imagining an engineer or manager could specify a successful innovation entirely in advance and then implement it exactly as planned (MacKenzie, Reference MacKenzie2009). When such direct performative effects do occur, they are often linked more to failure than to success (see MacKenzie, Reference MacKenzie2006, on counter-performativity). For example, branding a technology as ‘overhyped’ can dampen investment and support, potentially derailing a project that might otherwise have succeeded – though such negative feedback loops remain underexplored and merit further empirical study.
Crucially, context matters – and particularly the stage of innovation. In early-stage, exploratory science, hype can play a constitutive role in shaping the very emergence of a field. Stephens, Kind, and Lyall (Reference Stephens, King and Lyall2018) demonstrate how exaggerated future claims surrounding nanotechnology helped secure sustained R&D funding, attracting resources, attention, and talent over time.
Yet as innovations move towards commercialisation and broader diffusion, the role of hype often changes. In later-stage, market-facing contexts, hype is tempered by immediate feedback and heightened accountability. Narratives face closer scrutiny and must continually evolve to meet the shifting expectations of diverse, discerning audiences. Under these conditions, the kind of straightforward performativity sometimes seen in earlier stages becomes far less likely. Instead, hype takes on a more transitional (O’Connor, Reference O’Connor, Hjorth and Steyaert2004) or provisional (Mützel, Reference Mützel2022) character – constantly reshaped as ventures pivot, iterate, and reposition themselves in response to ongoing evaluation.
To capture this adaptive narrative work, we draw on Birch’s (Reference Birch2023) concept of reflexive expectations. While initial expectations often stem from compelling visions of radical innovation, they rarely remain static. As ventures transition from technoscientific promise to financial and commercial arenas, their narratives pivot to engage new evaluative audiences and criteria. These stories are continually revised as financing processes unfold and strategic roadmaps are recalibrated. As Birch (Reference Birch2023, p. 45) observes, entrepreneurs ‘construct new stories or amend old ones to make valuation judgements and attract investment’.
In the Juvo case, for example, we observed how an initial focus on the product’s disruptive technological potential gradually gave way to stories about market readiness, customer adoption, and value creation. These shifts did not occur in a straight line, nor were they under the sole control of the start-up founder. Instead, they were collaborative and iterative, involving analysts, AR specialists, investors, and other audiences who each contributed to reshaping the narrative.
Reframing hype’s influence from performativity alone to a combination of performativity and reflexivity offers a more nuanced understanding of the complex, adaptive life of hyped expectations. Rather than a one-off performative act, hype – particularly in later stages – operates as a dynamic, negotiated, and recursive process in which claims are continually reworked in response to shifting evidence, audiences, and incentives. As Chapter 4 will show through its analysis of start-up storytelling, entrepreneurs must learn to adapt and recalibrate their narratives as they move from early-stage funding pitches to later-stage analyst briefings.
2.6 Tenet Six: When Hype Matters – Shifting Roles across the Innovation Lifecycle
The previous discussion highlights a critical gap in current scholarship where it fails to adequately engage with the different temporal settings of hyped expectations, particularly how hype operates across both early and later stages of innovation. While the Sociology of Expectations scholarship focused primarily on early-stage developments, our analysis reveals hype’s crucial role throughout the innovation lifecycle, especially in processes of market making and market operation. This limitation is problematic because it tacitly underplays or ignores how hype continues into later phases, leaving us with a dearth of studies on how hype operates in market situations.
Prior research overwhelmingly positions hype as a ‘front‑end’ phenomenon. Brown (Reference Brown2003, p. 11) places hype in the ‘opening moments of resource and agenda building’, emphasising how ‘the whole language of novelty, newness and revolutionary potential is actually part and parcel of the hyperbolic discourse surrounding the early or opening moments of resource and agenda building’. Similarly, Wüstenhagen et al. (Reference Wüstenhagen, Wuebker, Bürer, Goddard, Truffer, Markard, Wüstenhagen and Wiek2009, p. 123) emphasise expectation dynamics in ‘earliest stages of technology-driven innovation’, while Palavicino (Reference Palavicino2016, p. 144) notes how hype ‘brings actors together in early stages of technology development to take high-risk decisions under high uncertainty’. Taken together, these accounts suggest that once technologies solidify – products exist and markets form – hype recedes behind more concrete considerations.
This upstream bias has consequences. We know far more about hype before markets exist than about how it is translated, operationalised, and governed once market actors must buy, sell, compare, and adopt competing offerings (Gardner et al., Reference Gardner, Samuel and Williams2015). Integrating upstream expectation work with downstream market decision‑making remains rare (Rotolo et al., Reference Rotolo, Hicks and Martin2015). Hardly any scholarship has integrated this with the downstream world of market actors and organisational decision-makers, who decide whether to invest in particular firms or the decisions facing organisational users concerning the adoption of specific products. Despite its concerns about addressing futures, scholarship has failed to engage with these different temporal settings and how processes of creating, circulating, and consuming hype are differently modulated between early and later phases.
We extend hype analysis across the innovation lifecycle. Hype does not dissipate at market entry; it evolves – and can even intensify – as stakes, competition, and formal structures grow. Our research aims to bridge this gap by extending hype analysis to later phases, specifically the development of applications and their adoption by market actors, such as technology adopters. We contend that hype evolves its role throughout the innovation lifecycle rather than merely being a transient wave that dissipates after the introductory phase. For instance, by the time an innovation reaches the market, there are often more financial resources at stake, more competitors, and more formal structures in place – all of which shape the form of hype.
To help unpack this, we distinguish four overlapping stages that recur across many innovation journeys (Bergek et al., Reference Bergek, Jacobsson, Carlsson, Lindmark and Rickne2008): (1) exploratory science/field‑forming (pre‑market); (2) translational/venture‑building (pre‑commercial); (3) early market/market‑making (initial customers, few vendors); and (4) established market/market operation (wider adoption, comparative evaluation). These stages provide a helpful framework for understanding how the role and management of hype shift over time. Hype plays different roles and is mediated by various actors and instruments at each stage of the process.
We find Konrad and Palavicino’s (Reference Konrad, Van Lente, Groves, Selin, Felt, Fouché, Miller and Smith-Doerr2016) study of graphene useful in this regard. While early hype helped spawn a research field and initial start-ups (stages 1 and 2), one might have expected that hype would die down once the initial excitement settled. However, their study shows that hype continued to shape the field over time (stage 3). A pivotal trigger came when the Nobel Prize was awarded for graphene research in 2010: the award reignited interest, attracted additional funding, conferred credibility, and fuelled renewed promises of applications.
Moreover, they note that the management of hype – and the actors involved in doing so – changed in these later phases. Konrad and Bohle (Reference Konrad and Böhle2019, p. 102) elaborate on how the graphene field witnessed an influx of policymakers and market actors engaging in ‘practices of futuring’, where there was the provision of ‘market forecasts, carrying out foresight processes (e.g. Delphi studies), hype assessments, or developing dynamic models, scenarios or roadmaps’. These are hallmarks of stage 3 (early market) and stage 4 (established market), where more formalised instruments and governance structures begin to shape the trajectory of innovation. Konrad and colleagues argue that this moved graphene into a new phase with enhanced structure, governance, and planning. Yet despite these shifts, hype remained a driving force – now institutionalised through strategic roadmaps, government initiatives, and industry consortia.
In these later stages (3 and 4), hype also begins to perform boundary-setting and coordination functions. Logue and Grimes (Reference Logue and Grimes2022, p. 7) point out that in later stages, actors leverage hype to formalise field boundaries and networks: actors ‘take advantage of hype to configure boundaries around the field, create more efficient exchanges within the field, and situate their own ventures relationally within important networks’.
Our book will highlight how a key aspect of the digital economy is the prominent role of market gatekeepers, such as industry analysts, in these later stages. These actors typically enter when an emerging technology is on the verge of broader adoption – in the early market or established market phase (stages 3 and 4). They translate diffuse expectations into actionable decision inputs for buyers. Their focus is on the near future rather than the distant horizon. They introduce promissory products (like categories and rankings) that effectively operationalise hype, turning it into something that can be rated, ranked, and digested by decision-makers. By doing so, they bring a certain closure to the open-ended hype of earlier stages.
However, our book shows that these market gatekeepers are beginning to enter the process earlier, as the transition from stage 2 (venture-building) to stage 3 (early market) occurs, with technologies moving from translational efforts to initial commercialisation. Industry analysts, for instance, often produce their first reports on a technology when a handful of vendors begin to sell to customers, even if the technology is not yet mainstream (e.g. Cool Vendor appellations and HCCs).
Our contribution – and the focus of the empirical chapters that follow – is to demonstrate how hype is managed, particularly in stages 2, 3, and 4, when technologies transition from emergence to market consolidation. As technologies become more established, hype does not evaporate; it becomes embedded in promissory products that continue to shape expectations and flows of resources.
2.7 Tenet Seven: Living Up to the Hype – Emerging Accountability Mechanisms
A common presumption is that actors are rarely held accountable for the claims they make, creating a grace period in which bold assertions face little immediate scrutiny or sanction if they are not substantiated. This assumption rests on two key conditions: (i) the belief that there is little in the way of an evaluative infrastructure surrounding hyped claims; and (ii) the observation that proof often arrives only after attention, actors, and market conditions have shifted. In such circumstances, those who make grand claims may never be penalised; the accountability window can close before verdicts are rendered.
First, Joly (Reference Joly, Akrich, Barthe, Muniesa and Mustar2010, p. 7) notes, ‘there are few ways to assess [hype’s] validity’; Grodal and Granqvist (Reference Grodal, Granqvist, Ashkanasy, Zerbe and Härtel2014, p. 141) similarly argue that without ‘existing benchmarks for evaluation’, this means that expectations ‘become self-perpetuating and give rise to fads, hypes, and bubbles’. Second, Rip (Reference Rip, Hisschemöller, Hoppe, Dunn and Ravetz2018) highlights the innovator’s dilemma: they must hype their ideas enough to gain support, but the evidence to confirm or refute their claims will only emerge later, by which point audiences may have moved on (van Lente, Reference Van Lente2012; Master & Resnik, Reference Master and Resnik2013). By then, the evaluative context may have changed, and the original promissory conditions may no longer apply.
Indeed, according to Joly (Reference Joly, Akrich, Barthe, Muniesa and Mustar2010), tools like the Gartner HCC have helped normalise deferred disappointment by building a ‘Trough of disillusionment’ into the expected trajectory. As he notes, ‘[o]ne of the effects of the cycle is to naturalise the disillusionment’ – the ‘Trough of disillusionment’ is built into the tool as a natural, even necessary step in the innovation process (Joly, Reference Joly, Akrich, Barthe, Muniesa and Mustar2010, p. 13), thus further institutionalising the deferral of evaluation and deepening the accountability gap.
These perspectives rightly highlight the fluid and promissory nature of hype. However, a central argument of this book is that expectations are no longer as unaccountable as they once were. We contend that the landscape has shifted: hyped claims are increasingly subject to scrutiny and formal evaluation. In contrast to earlier eras where hype could run free (until a ‘crash’: see Garud et al., Reference Garud, Schildt and Lant2014b), today we see emerging mechanisms that hold promise-makers to account (albeit in new ways).
As innovation moves from speculative projections to more concrete phases of market implementation, new forms of accountability begin to crystallise. Yet we still know little about how these mechanisms function in practice. Beckert and Ergen (Reference Beckert2021, p. 13) observe that the ‘evaluative structures’ surrounding hyped expectations represent a ‘vast and understudied research field’, highlighting the need for deeper empirical and conceptual enquiry.
Martin (Reference Martin2015) offers a useful framing for how accountability tightens over time, contrasting a ‘regime of hope’ with a ‘regime of truth’. In the regime of hope, ventures like start-ups operate within a speculative space characterised by uncertainty and anticipation: they may have ‘no products on the market’, remain ‘poorly integrated’ into existing industry structures, and trade promissory assets that cannot yet be fully valued (Martin, Reference Martin2015, p. 434). Here, hype functions as a key mechanism for attracting attention, credibility, and resources.
By contrast, the regime of truth marks a more mature stage of market engagement, where ventures have ‘products on the market, significant sales and profits, a relatively large number of products in late-stage development’, and are ‘well-integrated’ into the industry – what Martin calls ‘the real economy’ (2015, p. 437). At this point, the scope for speculation narrows, and demands for demonstrable results intensify (see also Hogarth, Reference Hogarth2017).
Beckert’s (Reference Beckert2016) analysis also captures this shift, showing how early ‘myths’ about the future give way to demands for evidence and performance. Cultural Entrepreneurship scholars make a similar point: while exaggerated narratives may help attract initial interest and investment, they eventually entangle entrepreneurs in webs of accountability. Lounsbury and Glynn (Reference Lounsbury and Glynn2001), for instance, demonstrate that ventures founded on unverifiable or overly grandiose claims face reputational risks. Garud et al. (Reference Garud, Schildt and Lant2014b) show how, during the dotcom crash, many firms were forced to revise their stories in light of missed milestones and shaken investor confidence.
In short, expectations remain pliable only up to a point. Logue and Grimes (Reference Logue and Grimes2022) argue that ventures become bound by the stories they tell; to ‘live up to the hype’, they must ultimately deliver evidence. Early in this process, proxies in the form of ‘social proof’ – endorsements, awards, media coverage – can sustain credibility. But without the progressive accumulation of such markers, legitimacy erodes, and audiences begin to question not only the promise but the venture’s capacity to perform.
While Logue and Grimes (Reference Logue and Grimes2022) effectively illuminate the role of informal accountability mechanisms – such as social proof – in sustaining hype, we argue that more structured and formalised evaluation processes are playing an increasingly influential role in the digital economy. These include rankings, ratings, certifications, league tables, and other structured performance metrics that make technologies more comparable, auditable, and governable.
Among the most significant actors in this shift are industry analysts, who shape how hype is interpreted and made accountable. Unlike informal endorsements, which rely on reputation, charisma, or peer validation, analysts offer structured and ostensibly objective assessments that influence how technologies are understood, valued, and prioritised within markets. Taken together, this progression – from soft to institutionalised forms of accountability – is central to understanding how the digital economy governs its futures. Hype is not sustained by exuberant promissory narratives alone but also by the infrastructures that discipline, translate, and, at times, tame them.
Several important questions remain unresolved: How does the digital economy transition from a ‘regime of hope’ to a ‘regime of truth’? Who mediates the shift from promissory claims to demonstrable outcomes? At what point do audiences begin to demand evidence beyond social proof? And how do evaluation tools influence both the timing and content of narrative pivots? These are questions we take up in the chapters that follow.
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Together, these seven tenets provide a foundation for treating hype not as a peripheral phenomenon but as a dynamic, structured, and strategic resource shaping the digital economy. They also set the stage for a critical shift in focus: from understanding what hype is to examining how actors respond to it. In Chapter 3, we explore how organisations navigate the uncertainties generated by hype, sometimes treating it as a source of risk to be mitigated, and at other times as a resource to be cultivated.
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