Dag Øivind Madsen
Kåre Slåtten*- Department of Business, Marketing and Law, USN School of Business, University of South-Eastern Norway, Hønefoss, Norway
Management fashions have long been explained as the result of charismatic gurus, consultants, and professional media who confer legitimacy on new ideas. In the platform era, however, the circulation of management ideas is increasingly mediated by algorithms that privilege certain communicative forms while obscuring others. Building on management fashion theory, this paper conceptualizes algorithms as non-human actors that participate in the communicative construction of authority and legitimacy. The analysis draws on the concept of algorithmic meta-capital to explain how human actors navigate and exploit platform logics through reflexive adaptation. Using the diffusion of Agile as an illustrative example, the paper shows how visibility and meaning shift across platforms such as LinkedIn, YouTube, and TikTok. Legitimacy is reframed as a hybrid outcome of authenticity performance and algorithmic amplification, extending management fashion theory into the domain of organizational communication. Six propositions outline how algorithmic authority, amplification, and meta-capital reshape diffusion dynamics, communicative lifecycles, and the politics of visibility in the platform age.
1 Introduction
The study of management fashions has long emphasized the central role of human actors in shaping which ideas gain traction and legitimacy. Classic examples such as Total Quality Management in the 1980s and Business Process Reengineering in the 1990s illustrate how charismatic gurus, consultancies, and business media created surges of attention around particular practices (Abrahamson, 1996; Jung and Kieser, 2012; Piazza and Abrahamson, 2020; Sturdy et al., 2019a). These actors built authority through a combination of institutional credentials, professional reputation, and charismatic performance (Collins, 2019; Huczynski, 1993). In this traditional framing, management fashions were understood as the outcome of human agency, mediated by established broadcast infrastructures such as books, conferences, and magazines (e.g., Alvarez, 1998; Furusten, 1999; Kieser, 1997; Sahlin-Andersson and Engwall, 2002).
The rise of digital platforms has unsettled this human-centered view of management fashion diffusion (Madsen and Slåtten, 2015, 2025b). In contrast, more recent ideas, such as Agile, ESG, and Industry 5.0, have circulated heavily through digital platforms, where visibility is shaped less by traditional gatekeepers and more by the algorithmic amplification of posts, videos, and hashtags, and trending lists (Bucher, 2018; Gillespie, 2010, 2018). These systems actively curate attention by amplifying some ideas while suppressing others, shaping what managerial audiences perceive as legitimate or fashionable (Madsen and Slåtten, 2025b). Scholars describe this as algorithmic authority (Gillespie, 2014; Shin, 2025; Shirky, 2009) with algorithmic amplification (Madsen and Slåtten, 2025b) now seen as a defining feature of digital knowledge diffusion.
This reframing raises important theoretical questions. If fashion diffusion has always depended on the authority of certain figures, how should we understand the role of algorithmic systems that now co-produce authority? Algorithms lack charisma or intentionality, yet they exert symbolic power by structuring visibility, rewarding authenticity performances, and accelerating diffusion. By theorizing algorithms as sources of authority, this paper extends management fashion theory beyond its traditional focus on human actors such as consultants, gurus, and academics to include the technical infrastructures that increasingly shape what counts as credible management knowledge.
To illustrate these dynamics, the paper uses the diffusion of Agile as a running example. Agile is well established as a management fashion (Cram and Newell, 2018; Frantsen and Heusinkveld, 2022; Madsen, 2020; Onay and Ercek, 2025) and offers a clear view of how digital platforms shape the visibility and meaning of managerial ideas. Its presence across LinkedIn, YouTube, and TikTok demonstrates how the same concept is recontextualized through platform-specific logics of amplification, authenticity, and engagement.
For organizational communication scholars, the diffusion of management fashions is not only a question of adoption but also of mediated visibility. Algorithms should therefore be understood as communicative infrastructures that shape how authority and legitimacy are performed, circulated, and interpreted within digital platforms.
The remainder of the paper proceeds as follows. Section 2 outlines the conceptual framework, and Section 3 examines algorithms as curators in the platform era. Section 4 discusses the implications for management fashion theory. Section 5 develops the research propositions and outlines a future research agenda, while Section 6 addresses limitations and challenges. Section 7 concludes by summarizing the paper’s contributions and suggesting directions for further inquiry.
2 Conceptual framework: from charisma to algorithmic authority
2.1 Authority in the broadcast era
The contrast between the broadcast and platform eras can be understood as a shift in how authority is constructed in management fashion diffusion. In the broadcast era, legitimacy was closely tied to the charisma of the guru and the endorsement of established institutions like Harvard and Stanford. Management thinkers such as Peter Drucker, Tom Peters, and Stephen Covey gained recognition through a combination of rhetorical skill, publishing success, and professional credentials (Collins, 2019; Jackson, 2001). Authority was conferred through human performance and institutional validation, with credibility flowing from personal charisma and reputational capital.
Yet the broadcast era was not devoid of virality or rapid diffusion. Business magazines, bestseller lists, consultancy reports, and professional conferences also functioned as amplifiers that selected and repeated successful ideas. Media gatekeeping operated through its own algorithms of reputation and relevance—editorial routines, bestseller rankings, and citation loops that privileged recognizable names and simple models. In this sense, the platform era extends rather than replaces earlier forms of mediated visibility. What distinguishes it is not the existence of amplification but its automation and opacity: decisions once made by editors and publishers are now executed by computational systems at scale.
In the platform era, however, authority is increasingly shaped by algorithmic systems. Algorithms determine what content appears in feeds, what trends circulate, and which ideas gain visibility. This process exemplifies what scholars have described as algorithmic authority, a term first proposed by Shirky (2009) in a widely cited blog post, and later elaborated in studies of platforms and infrastructure (e.g., Gillespie, 2014; Shin, 2025). Importantly, authority is no longer conferred solely by human figures or institutions but also by the technical infrastructures that govern visibility.
2.2 Algorithmic authority and amplification in the platform era
Closely related is the phenomenon of algorithmic amplification (Farid, 2021; Huszár et al., 2022; Milli et al., 2025). Rather than operating as neutral conduits, algorithms reward engagement and resonance, creating feedback loops that elevate some ideas while silencing others. Popularity metrics such as likes, shares, downloads, and watch time become proxies for credibility, allowing ideas to spread rapidly through viral circulation. This does not eliminate the role of human performance—gurus and influencers still cultivate authenticity and connection—but it reframes legitimacy as a hybrid outcome of charismatic self-presentation and algorithmic amplification (Madsen and Slåtten, 2025b).
A clear example is the ongoing diffusion of Agile. On LinkedIn, Agile circulates through professional endorsements and “success story” posts that frame adoption as a marker of progressive leadership. On YouTube, Agile is reinterpreted through tutorial and explainer videos that emphasize process mastery and certification pathways. On TikTok, by contrast, the same idea often appears in humorous skits about daily stand-ups or sprint fatigue—formats optimized for short-form engagement. Across these platforms, the communicative form of Agile shifts according to each algorithm’s logic of amplification, illustrating how visibility determines not just reach but meaning.
This shift from charisma to code marks a fundamental transformation in management fashion diffusion. Authority now emerges not only from who speaks and how persuasively they perform, but also from how algorithms recognize, amplify, and sustain their visibility. Legitimacy thus reflects the interplay between human expression and non-human curation, producing a new kind of symbolic power in the fashion arena. This framing links management fashion theory to organizational communication by emphasizing that legitimacy is communicatively constructed. In the broadcast era, communication was mediated through professional outlets such as business media and conferences. In the platform era, algorithms themselves act as communicative filters, privileging some forms of discourse and interaction while suppressing others.
Here, Actor–Network Theory (ANT) (Callon, 1986; Latour, 2005) provides a useful analogy. While its ontological commitments differ from those of management fashion theory, ANT reminds us that legitimacy emerges from networks of heterogeneous actors, rather than from human figures alone. In this spirit, algorithms are treated here not as neutral tools but as actants that actively participate in diffusion. While management fashion theory has traditionally focused on human actors such as gurus, academics, and consultants, ANT suggests that technologies, infrastructures, and artifacts can also be seen as participants in networks of diffusion. Without adopting the full ontology of ANT, this paper draws inspiration from this insight by considering algorithms as actants that actively mediate visibility and legitimacy within the fashion-setting community.
2.3 Social authorization and social proof as legitimacy mechanisms
In addition to charisma and algorithmic authority, legitimacy has also long depended on what might be called social authorization. In the broadcast era, this often took the form of high-profile adopters—celebrity CEOs, prestigious firms, or influential consultants—whose visible use of a management idea signaled credibility to wider audiences (Kieser, 1997; Staw and Epstein, 2000). In the platform era, however, social authorization is increasingly mediated through digital signals of popularity such as likes, shares, and influencer endorsements. This dynamic resonates with theories of social proof (Cialdini, 2006), where individuals infer credibility from visible collective adoption. On social media platforms, social proof is hyper-visible and quantified, with follower counts, hashtags, and trending signals serving as markers of legitimacy (see Table 1).
Table 1. Sources of authority in broadcast vs. platform eras.
3 Algorithms as curators in the platform era
3.1 Mechanisms of algorithmic curation
In the platform era, the diffusion of management fashions is increasingly governed by algorithms rather than editors or publishers. Recommendation systems, trending lists, and search rankings shape what content becomes visible, how it circulates, and which voices gain authority. Whereas in the broadcast era, gatekeeping was a human-driven process tied to editorial judgment, in the platform era, it is largely automated, governed by opaque computational systems designed to maximize engagement (Bucher, 2018; Gillespie, 2014).
Algorithms are not passive conduits of human intention but active curators. They decide, through coded rules and data-driven optimization, which ideas appear at the top of feeds, playlists, and searches, and which remain invisible. As Noble (2018) shows, these systems embed values and biases, privileging certain kinds of content while marginalizing others. In the context of management fashions, algorithms privilege ideas that generate clicks, shares, and sustained attention, regardless of their intellectual rigor. This shifts the criteria of legitimacy away from institutional credentials and toward visibility metrics.
A central feature of algorithmic curation is its reliance on engagement metrics as proxies for relevance and authority. Likes, downloads, shares, and comments serve as signals that feed back into recommendation systems, creating a feedback loop in which popular content is made even more visible. This recursive logic means that ideas can gain authority not because they are substantively better but because they are algorithmically rewarded. In this sense, algorithms perform a function similar to that of gurus in the broadcast era: they elevate certain ideas, frame them as worthy of attention, and suppress alternatives.
Agile provides a good illustration. Posts using Agile hashtags on LinkedIn often resurface cyclically when engagement spikes, regardless of novelty. Algorithms revive older content that momentarily fits trending patterns, making past advice appear timely again. This illustrates how algorithmic resurfacing extends the lifecycle of managerial ideas beyond their initial peaks of attention.
The curatorial role of algorithms can be differentiated into distinct functions. Table 2 summarizes key modes of algorithmic curation and their effects on the diffusion of management fashions. By distinguishing these mechanisms, it becomes clear that algorithms do not merely filter information but actively shape the temporalities and hierarchies of managerial ideas.
Table 2. Forms of algorithmic curation in management fashion diffusion.
3.2 The rise of new actors: influencers, podcasters, and micro-celebrities
Another consequence of algorithmic curation is the emergence of new actors in the fashion arena. Whereas the broadcast model privileged elite consultants and credentialed experts, platforms allow micro-influencers, podcasters, and independent creators to reach large audiences if their content resonates with algorithmic systems. Research on digital influence highlights how these creators build credibility by performing authenticity and cultivating perceived intimacy with audiences (Abidin, 2018; Giles, 2018). Yet their ability to gain visibility is contingent on algorithmic recognition, underscoring how human performance and non-human curation are intertwined.
These new actors also reshape the economy of legitimacy within management discourse. Visibility no longer depends solely on institutional prestige but on the capacity to sustain engagement across multiple platforms. Many consultants and business educators now operate as hybrid figures—simultaneously scholars, entrepreneurs, and influencers—who translate managerial ideas into platform-friendly formats such as podcasts, short-form videos, and carousel posts (Madsen and Slåtten, 2025a,b). From a management fashion perspective, these actors function as contemporary fashion setters: they package and popularize ideas, interpret trends, and act as intermediaries between expert knowledge and public consumption. Yet, unlike the traditional gurus and consultancies described by Abrahamson and others, their authority is conditional on algorithmic amplification. This hybridization diversifies who can shape managerial discourse while deepening dependence on opaque digital infrastructures that determine visibility and reach.
3.3 Algorithmic meta-capital and reflexive adaptation
While algorithms act as curators, human actors are not passive recipients of their logic. Consultants, influencers, and thought leaders increasingly learn how to make their content algorithm-friendly—adapting titles, tone, and timing to platform demands. This strategic responsiveness can be understood as a form of algorithmic meta-capital (Ling and Yan, 2025; Lundahl, 2022). It refers to the capacity to understand, anticipate, and exploit algorithmic preferences to accumulate visibility and symbolic power.
In the context of management fashions, algorithmic meta-capital represents a new dimension of professional competence. Those who possess it can align their authenticity scripts, visual presentation, and posting rhythm to the metrics that drive amplification. For instance, Agile advocates on LinkedIn often deploy storytelling and vulnerability posts to trigger interaction, while YouTube creators use tutorial formats that sustain watch time. Such reflexive adaptation blurs the line between genuine expression and strategic performance. This tension reveals a central paradox of platform visibility: authenticity is rewarded only when it is carefully staged for algorithmic recognition.
Recognizing algorithmic meta-capital highlights that authority in the platform era is co-produced: algorithms reward engagement, but human actors learn to engineer that engagement. This dynamic further complicates the notion of authenticity, revealing it as both a cultural ideal and a calculative practice embedded in platform infrastructures.
3.4 Temporalities of diffusion: acceleration, truncation, and resurfacing
The implications for management fashion diffusion are profound. Algorithms determine not only who gets heard but also how long ideas remain visible. For instance, Agile’s online presence fluctuates sharply. A new certification program or viral post can create sudden spikes in attention, followed by rapid decline. Yet the same content is often resurfaced months later through platform recommendation loops, illustrating the recursive temporality of algorithmic diffusion.
From a management fashion perspective, this dynamic alters the rhythm of idea lifecycles. What Abrahamson (1996) described as periodic waves of popularity now unfolds as overlapping micro-cycles of algorithmic visibility. Instead of predictable phases of emergence, enthusiasm, and decline, fashions now experience bursts of virality punctuated by algorithmic afterlives—short-lived revivals that sustain discursive relevance without renewed innovation. The cyclical and data-driven logic of platforms thus transforms diffusion from a primarily social process into a socio-technical feedback system in which algorithms and audiences continually recalibrate one another.
Algorithms therefore accelerate lifecycles by enabling rapid virality, truncate them by quickly shifting attention elsewhere, and sometimes resurrect older fashions by resurfacing archived content. In this way, they act as non-human fashion setters, shaping the temporalities, visibility, and legitimacy of managerial ideas in ways that rival or even surpass human actors.
4 Implications for management fashion theory
4.1 Reframing the fashion-setting community
Recognizing algorithms as sources of authority has several implications for management fashion theory. Classic accounts identified a fashion-setting community composed of consultants, gurus, and business media who supplied organizations with ideas and shaped their trajectories of rise and decline (Abrahamson, 1996; Benders and Van Veen, 2001; Kieser, 1997). Recently, Piazza and Abrahamson systematized this view by describing how fashions move through cycles of innovation, diffusion, retention, abandonment, and rebirth (Abrahamson and Piazza, 2019; Piazza and Abrahamson, 2020). In both framings, the central actors were human, with authority grounded in charisma, credentials, or institutional affiliation.
Incorporating algorithms into the fashion-setting community loosely parallels ANT-inspired accounts that foreground heterogeneous assemblages of actors (Latour, 2005). Just as ANT analyses reassemble the social by highlighting how both human and material elements interact, management fashion theory can be extended by recognizing algorithms as non-human participants that co-produce legitimacy. While ANT and fashion theory emerge from different theoretical traditions, both share an interest in understanding how authority is distributed across complex networks rather than residing in a single figure.
4.2 From credential-based to metric-based legitimacy
The platform era disrupts this anthropocentric model by introducing algorithms as non-human actors that co-produce authority. Algorithms perform functions parallel to those of consultants or media editors in the broadcast era: they select, frame, and promote ideas. However, unlike human actors, algorithms exercise authority through computational logics optimized for engagement and visibility, rather than for professional credibility or reputational standing (Gillespie, 2014; Noble, 2018). This reorients legitimacy from being credential-based to being metric-based.
Algorithmic authority also reshapes the temporalities of fashion cycles. Algorithms compress diffusion, producing volatile bursts of virality, and they reintroduce older ideas through resurfacing mechanisms. This dynamic reflects algorithmic amplification as a recursive process: ideas are not only spread quickly but may be periodically revived, disrupting linear models of fashion lifecycles. Such dynamics align with perspectives arguing for looping and recursive diffusion (Reinmoeller et al., 2019; Røvik, 2011), but with the added twist that these loops are now triggered by platform logics rather than organizational adaptation alone.
4.3 Platform logics and affordances
Yet algorithms do not operate uniformly across platforms, and the affordances of each environment profoundly shape diffusion dynamics (Bucher and Helmond, 2018; Ronzhyn et al., 2023). Open platforms such as YouTube, for example, reward average view duration, which incentivizes creators to produce narrative-driven, emotionally resonant content rather than abstract theoretical analysis. TikTok emphasizes engagement velocity, privileging performance, humor, and rapid bursts of virality. LinkedIn, as a semi-professional network, amplifies thought-leadership content that aligns with authenticity scripts and stimulates interaction (Orgad, 2024; TorontoDigits, 2025). Substack, by contrast, cultivates niche legitimacy through subscription-based trust, sustaining more theoretical or technical writing. Discord exemplifies a community-driven model where fashions are co-constructed within bounded groups, rather than being broadcast algorithmically.
The comparison in Table 3 shows that diffusion dynamics depend heavily on platform-specific logics. On YouTube, the emphasis on average view duration incentivizes narrative and storytelling formats. TikTok privileges speed and virality, making management fashions more volatile. LinkedIn relies on social proof and professional connections to amplify thought leadership content, thereby triggering engagement. Substack rewards sustained attention from niche communities, allowing more theoretical and technical analysis to persist even if it lacks viral appeal. Discord, finally, demonstrates a community-driven model where fashions are not amplified algorithmically at scale but are co-constructed and debated within bounded groups.
Table 3. Platform logics and the diffusion of management fashions.
These contrasts can be seen in how Agile adapts across platforms. On LinkedIn, engagement metrics reward managerial reflection and team success narratives, reinforcing Agile’s legitimacy as a modern leadership practice. On YouTube, algorithms favor long-form storytelling and visual explanation, prompting creators to present Agile as a structured toolkit. Meanwhile, TikTok’s velocity-driven feed compresses complex ideas into performative humor, reducing Agile to workplace stereotypes. Such differences confirm that platform architectures do not merely distribute content—they transform its communicative substance.
4.4 Politics of visibility and inequality
Finally, treating algorithms as authoritative actors highlights the politics of visibility in management fashions. If engagement-driven algorithms decide which ideas are amplified, then biases embedded in platform design risk reinforcing existing inequalities (Noble, 2018; Van Dijck et al., 2018).
In the case of Agile, short motivational clips and leadership anecdotes are far more visible than reflective critiques or empirical analyses. The visibility bias thus favors performative enthusiasm over technical depth, reinforcing a communicative hierarchy that privileges style and emotion over substance.
Social authorization also intersects here: digital social proof—likes, shares, endorsements—interacts with algorithmic logics to amplify some voices while silencing others. Management fashion theory must therefore expand from describing diffusion patterns to interrogating how digital infrastructures and visible social proof jointly privilege certain actors, suppress others, and potentially distort the evaluative criteria of managerial knowledge. A key question for future research is therefore: which managerial voices are consistently amplified or suppressed across platforms, and what does this mean for the democratization—or stratification—of management knowledge?
This reframing also broadens the dialogue between management fashion theory and organizational communication. In both traditions, legitimacy is communicatively performed rather than simply possessed. The rise of algorithmic mediation reveals how communicative infrastructures now shape not only who speaks but also how speech acquires credibility. Authority becomes a function of visibility, format, and engagement—core communicative dimensions rather than external validations. By foregrounding these mechanisms, management fashion theory enters closer conversation with organizational communication research concerned with media logics, visibility politics, and the construction of symbolic authority within digital environments.
4.5 An integrative model of hybrid authority
The developments outlined above suggest that authority in management fashion diffusion should be understood as hybrid, produced through the interplay of human and non-human actors. In the broadcast era, this hybrid combined charismatic performance with institutional endorsement. Gurus and consultants established authority through rhetorical skill, narrative charisma, and reputational capital (ten Bos and Heusinkveld, 2007), while gatekeeping institutions such as publishers and consultancies reinforced their legitimacy (Nijholt et al., 2014). Social authorization, often enacted through high-profile adopters, further amplified legitimacy by signaling the credibility of particular fashions to wider audiences (Røvik, 2002; Staw and Epstein, 2000).
In the platform era, the components of this hybrid have shifted. Authority is now increasingly co-produced by authenticity performance and algorithmic amplification (Madsen and Slåtten, 2025b). Influencers and content creators stage legitimacy through vulnerability narratives, informal tone, or emotionally resonant storytelling (Abidin, 2018; Orgad, 2024). Algorithms, in turn, amplify these performances by rewarding engagement metrics such as likes, shares, and watch time (Bucher, 2018). At the same time, social proof—quantified through visible popularity metrics—has become a powerful marker of legitimacy, functioning as a digital form of social authorization (Cialdini, 2006). Platform-specific affordances (Bucher and Helmond, 2018) further condition the form managerial ideas take: YouTube privileges narrative depth, TikTok rewards performance and speed, LinkedIn amplifies professional signaling, Substack sustains theoretical reflection, and Discord fosters community-based co-construction.
Figure 1 illustrates this conceptual shift. In the broadcast era, authority was secured through the combination of charisma and institutional endorsement. In the platform era, legitimacy emerges from the convergence of authenticity scripts, algorithmic amplification, social proof, and platform-specific affordances. Recognizing authority as hybrid and historically contingent highlights the need for management fashion theory to account for both human performances and non-human infrastructures.
Figure 1. Integrative model of hybrid authority (conceptual illustration).
This figure underscores that authority in management fashion diffusion has always been hybrid, but the components of the hybrid have shifted. Charisma and institutional validation once underpinned legitimacy in the broadcast era. In the platform era, authority is increasingly produced through the co-dependence of human authenticity performances and algorithmic amplification. In both cases, the outcome is the legitimacy of management ideas. Recognizing this shift is crucial for updating management fashion theory to account for non-human infrastructures as active participants in the diffusion process.
These developments underscore that management fashion diffusion in the platform era is not simply faster or more visible but structurally different. Authority, legitimacy, and resonance are now co-produced through a dynamic interplay of human expression, algorithmic mediation, and reflexive adaptation. Charisma has been partially replaced by calculative awareness, where actors must perform authenticity while understanding how platforms interpret engagement. This synthesis foregrounds several theoretical implications: the redefinition of legitimacy as communicative visibility, the emergence of algorithmic meta-capital as a new basis of authority, and the recursive, uneven nature of diffusion shaped by algorithmic design. The following propositions consolidate these insights into specific avenues for future research.
5 Research propositions and future research agenda
5.1 Propositions
The conceptual framework developed here highlights how algorithmic authority and algorithmic amplification reshape management fashion diffusion. Building on this framework, we advance six research propositions, each justified by shifts in how legitimacy, diffusion, and visibility are constructed in the platform era.
5.1.1 Proposition 1. Algorithmic authority reconfigures communicative legitimacy
In the broadcast era, legitimacy was conferred through endorsement by gurus, consultants, and established media outlets, with diffusion supported by outlets such as Harvard Business Review (Brindle and Stearns, 2001) and elite consultancies such as McKinsey (O’Mahoney and Sturdy, 2016). In the platform era, algorithms act as communicative infrastructures, granting authority by determining what is surfaced, ranked, and repeated (Gillespie, 2014; Shirky, 2009). This shift implies that communicative prominence—being made visible—has become a substitute for institutional endorsement.
5.1.2 Proposition 2. Algorithmic amplification destabilizes communicative lifecycles
Management fashions have traditionally followed relatively stable cycles of rise, peak, and decline (Abrahamson, 1996; Kieser, 1997; Piazza and Abrahamson, 2020). Algorithms destabilize these lifecycles by rewarding immediacy and engagement, producing volatile bursts of communicative attention followed by rapid decline (Bucher, 2018; Bucher and Helmond, 2018). They also resurface older content, echoing the idea of cyclical diffusion, where older fashions return after their decline (Reinmoeller et al., 2019; Røvik, 2011), by showing how algorithmic logics intensify these resurfacing dynamics.
5.1.3 Proposition 3. Authenticity scripts interact with algorithmic logics through reflexive adaptation and algorithmic meta-capital
In the platform era, authority is co-produced through both performance and calculation. Human actors learn to read and respond to algorithmic signals—timing, tone, and format—to enhance visibility. This strategic responsiveness constitutes algorithmic meta-capital (Ling and Yan, 2025; Lundahl, 2022), a resource that allows creators to align authenticity performances with algorithmic amplification. Legitimacy thus emerges from the convergence of emotional resonance and technical know-how: those able to stage credible authenticity while optimizing for engagement gain disproportionate visibility and influence.
5.1.4 Proposition 4. Algorithmic curation privileges communicative voices with high levels of algorithmic meta-capital
Algorithms embed values and biases that reward content optimized for platform logics—brevity, emotion, and interaction. Actors who possess algorithmic meta-capital can exploit these affordances more effectively, securing sustained amplification. Conversely, those lacking this reflexive skill remain peripheral, even when producing substantively strong content. Authority in management fashion diffusion, therefore, depends not only on the quality of ideas but also on the capacity to navigate and “game” the algorithmic environment.
5.1.5 Proposition 5. Platform-specific designs generate divergent communicative diffusion patterns
Different platforms privilege different communicative forms: YouTube rewards sustained narrative depth through average view duration, TikTok accelerates virality through short-form performance, LinkedIn amplifies thought-leadership tied to professional interaction, and Substack sustains long-form essays through subscription-based trust (Bucher, 2018; Bucher and Helmond, 2018; Gillespie, 2014). These design differences mean that the same management fashion can take on divergent communicative forms depending on platform affordances.
5.1.6 Proposition 6. Platform affordances shape the communicative substance of managerial knowledge
Beyond diffusion speed, platform infrastructures (Bucher and Helmond, 2018) shape the communicative substance of managerial ideas themselves. On YouTube, fashions are rearticulated as narrative storytelling; on TikTok, as humorous or spectacular performances; on LinkedIn, as professional self-branding; on Substack, as extended theoretical reflection; and on Discord, as collaborative conversational sensemaking. These affordances do not merely transmit ideas but actively transform their form and meaning in practice.
Table 4 provides a summary of the research propositions.
Table 4. Summary of research propositions.
5.2 Research agenda
Future research should extend management fashion theory by systematically analyzing how algorithmic authority and algorithmic amplification reshape the communicative legitimacy of ideas. The six propositions advanced here suggest multiple avenues for inquiry, each requiring methods that capture both discourse and infrastructure.
Proposition 1 highlights the need to examine algorithmically conferred communicative legitimacy. Experiments and surveys could test whether managers and audiences treat content as more credible when accompanied by visible social proof such as trending tags, follower counts, or engagement metrics (Baym, 2015; Cialdini, 2006). Studies of perception could assess whether algorithmic endorsement substitutes for institutional endorsement (Gillespie, 2014).
Proposition 2 calls for longitudinal mapping of communicative lifecycles. Digital trace analysis and time-series methods could be used to chart the rise and decline of fashions such as Agile or ESG across platforms, and to compare these trajectories with earlier broadcast-era cycles (Abrahamson and Piazza, 2019; Piazza and Abrahamson, 2020). Such work would also extend the idea of cyclical diffusion, where older fashions return after their decline, by showing how algorithmic logics intensify these resurfacing dynamics (Reinmoeller et al., 2019; Røvik, 2011).
Future analyses could trace how algorithmic resurfacing affects the persistence of particular fashions such as Agile. Longitudinal tracking across LinkedIn or YouTube could reveal how engagement-driven resurfacing revives older content, creating cyclical waves of visibility independent of conceptual novelty. Such patterns would extend understanding of temporal recursion within digital diffusion.
Proposition 3 emphasizes the interaction between authenticity scripts, reflexive adaptation, and algorithmic logics. Digital ethnographies and discourse analyses could examine how consultants and influencers deliberately adjust tone, framing, and posting rhythms to align with platform incentives. Combining qualitative interviews with engagement-metric analysis would help operationalize algorithmic meta-capital (Ling and Yan, 2025; Lundahl, 2022)—the capacity to navigate and exploit algorithmic systems for visibility. These studies would reveal how strategic reflexivity now complements charisma as a foundation of legitimacy.
Proposition 4 calls for critical examination of inequality in algorithmic visibility. Researchers could employ algorithm audits or simulated posting experiments to assess how content optimized through meta-capital performs relative to more traditional, text-heavy communication. The findings would clarify how possession of meta-capital produces new hierarchies of authority, privileging those fluent in the language of platforms. This also links management fashion theory to debates on digital inequality and symbolic power in organizational communication.
Proposition 5 underscores the importance of cross-platform comparison. Mixed-method approaches combining trace data with multimodal analysis could reveal how the same managerial fashion takes divergent communicative forms across platforms (Bucher, 2018; Bucher and Helmond, 2018; Gillespie, 2014). Comparative studies could explore how narrative, performance, professional signaling, and reflection are privileged in YouTube, TikTok, LinkedIn, and Substack, respectively.
Proposition 6 directs attention to the communicative substance of managerial knowledge. Here, multimodal textual and visual analysis could show how ideas are rearticulated as stories, memes, essays, or conversational exchanges, depending on platform affordances (Bucher and Helmond, 2018). Discord-based ethnographies could capture how managerial ideas are collaboratively reframed within bounded communities. This would advance fashion theory by linking the form of communication directly to the perceived legitimacy of ideas.
Taken together, these directions push management fashion theory into dialogue with organizational communication by foregrounding the communicative forms and infrastructures through which legitimacy is produced. Future work should not only map the speed or popularity of fashions but also analyze the communicative practices and platform logics that shape their very substance. Across these research directions, Agile remains a useful comparative case. Its sustained digital presence allows multi-platform tracing of diffusion dynamics, authenticity performances, and algorithmic amplification over time.
6 Limitations and challenges
Like any conceptual contribution, this paper faces several limitations that should be acknowledged. First, the argument risks being interpreted as anthropomorphizing algorithms. The claim advanced here is not that algorithms have intentionality comparable to human gurus or consultants, but rather that they function as actants that shape diffusion outcomes by structuring visibility and legitimacy. In this respect, the use of ANT is meant as a loose analogy rather than a wholesale adoption. It provides a vocabulary for considering non-human participation in networks of diffusion, without committing management fashion theory to ANT’s ontological assumptions.
Second, the paper is deliberately exploratory and does not present empirical evidence. This choice reflects the aim of developing a conceptual framework and setting out research propositions. Future empirical work will be needed to substantiate, qualify, or challenge these claims. Comparative platform studies, digital ethnographies, and algorithm audits are especially promising ways to test the propositions outlined here.
Third, the paper draws on a wide range of platforms—YouTube, TikTok, LinkedIn, Substack, and Discord—to illustrate how affordances shape diffusion. The breadth of coverage risks stretching the argument thin. The examples provided here should therefore be understood as illustrative, not exhaustive. More focused studies of particular platforms or ideas will be necessary to establish the precise mechanisms at work.
Fourth, while the paper uses Agile as an illustrative case, the mechanisms described are not limited to this example. Similar dynamics likely characterize the diffusion of other digitally mediated fashions such as ESG, Design Thinking, or Industry 5.0.
Finally, the concept of legitimacy itself is used here in a broad sense, referring to the credibility and acceptance of management ideas. Future work should refine this concept further, distinguishing more carefully between different forms of legitimacy and how they operate in digital settings.
Despite these limitations, the framework provides a structured vocabulary for studying how digital infrastructures participate in organizational sensemaking and legitimacy production. Acknowledging these limitations makes it clear that the paper should be read as a conceptual provocation. Its goal is not to provide definitive empirical answers, but to reframe management fashion theory for the platform era by foregrounding algorithms as participants in the diffusion of ideas.
7 Conclusion
Management fashion theory has traditionally centered on human actors—gurus, consultants, and business media—as the primary agents shaping the rise and fall of managerial ideas (Abrahamson, 1996; Jung and Kieser, 2012). In the broadcast era, these figures relied on charisma, institutional endorsement, and editorial gatekeeping to construct authority and confer legitimacy.
In the platform era, however, authority is increasingly mediated by algorithms. These systems lack charisma or intentionality, yet they wield symbolic power by structuring visibility, rewarding particular performances of authenticity, and accelerating cycles of diffusion. This marks a shift from credential-based legitimacy to algorithmic authority, where recognition is conferred through engagement-driven amplification.
Building on this reconceptualization, the paper has developed six research propositions that open new avenues for empirical and theoretical work. Algorithms not only reconfigure legitimacy (Proposition 1) and destabilize lifecycles (Proposition 2), but they also interact with human authenticity scripts (Proposition 3), privilege some actors while marginalizing others (Proposition 4), and generate divergent diffusion patterns depending on their design (Proposition 5). Crucially, platform-specific affordances also shape the form and substance of managerial knowledge (Proposition 6), determining whether fashions appear as narrative storytelling, short-form performance, professional signaling, or niche expertise.
The future research agenda outlined here emphasizes the need to empirically map diffusion across platforms, to study how human and algorithmic logics co-produce authority, and to interrogate the ethical and political implications of algorithmic visibility. Attention to platform affordances is especially critical: management fashions do not simply rise and fall faster in the digital age, they are also reshaped in form by the infrastructures that govern how knowledge circulates.
Management fashions continue to rise and fall (Abrahamson and Piazza, 2019; Sturdy et al., 2019b), but the mechanisms of their diffusion have fundamentally changed (Madsen and Slåtten, 2015, 2025b). By theorizing algorithms as authoritative actors and by accounting for platform-specific affordances, management fashion theory can be extended to better capture the algorithmically mediated and variably structured construction of legitimacy in the platform age. This extension aligns with broader sociological efforts, including those inspired by ANT, to take seriously the agency of non-human actors in shaping organizational life. Without collapsing the distinctions between management fashion theory and ANT, the analogy underscores that algorithms should be treated not merely as background tools but as visible participants in the construction of managerial legitimacy.
The diffusion of management fashions is increasingly shaped by reflexive interactions between human and algorithmic actors. The introduction of algorithmic meta-capital clarifies how individuals and organizations acquire authority not merely by producing persuasive ideas but by mastering the mechanics of visibility. This competence—knowing how to perform authenticity, time communication, and optimize engagement—has become a new form of symbolic capital in the platform age. Management ideas such as Agile illustrate how diffusion now depends as much on strategic mediation as on conceptual novelty, marking a subtle but important transformation in how legitimacy is created, circulated, and sustained.
By integrating insights from management fashion theory with debates on algorithmic authority, this paper not only updates the theory for the platform age but also contributes to broader organizational scholarship on how non-human infrastructures mediate legitimacy. For management fashion theory, the key contribution is to reconceptualize diffusion as a socio-technical process shaped by both communicative performances and algorithmic infrastructures. For organizational communication, the key contribution is to show that legitimacy is not only a rhetorical or discursive achievement but also the outcome of algorithmic infrastructures that structure visibility and communicative form.
Understanding how algorithms curate managerial knowledge is therefore essential not only for scholars of management ideas but also for practitioners seeking to communicate, teach, or evaluate them in increasingly platform-dependent environments. The study invites scholars to view platforms not as neutral channels but as active agents in the social construction of managerial legitimacy.
Author contributions
DM: Conceptualization, Investigation, Resources, Validation, Visualization, Writing – original draft, Writing – review & editing. KS: Conceptualization, Investigation, Resources, Validation, Writing – review & editing.
Funding
The author(s) declare that no financial support was received for the research and/or publication of this article.
Conflict of interest
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Keywords: management fashions, algorithmic authority, algorithmic amplification, algorithmic meta-capital, reflexive adaptation, legitimacy, visibility, authenticity
Citation: Madsen DØ and Slåtten K (2025) The algorithmic mediation of management fashions: authority, amplification, communication. Front. Commun. 10:1713428. doi: 10.3389/fcomm.2025.1713428
Edited by:
Jun (Justin) Li, South China Normal University, ChinaReviewed by:
Alexander Yu. Krouglov, Herzen University, RussiaSiyuan Yan, East China University of Science and Technology, China
Copyright © 2025 Madsen and Slåtten. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
*Correspondence: Kåre Slåtten, a2FyZS5zbGF0dGVuQHVzbi5ubw==