A THEORY OF CROWDS IN TIME AND SPACE: EXPLAINING THE COGNITIVE FOUNDATIONS OF A NEW MARKET

Sorah Seong

ABSTRACT

The ubiquity of digitally intermediated interactions is changing the ways in which social interaction creates the cognitive and institutional underpinnings of new markets. Logics that define markets used to be localized, but they now emerge from crowds that span – and persist – across time and space. This article builds a theory of how crowds emerge and evolve in a way that influences the emergence of shared logics and helps explain why some markets are viable while others are not. What is revealed is that a crowd has a hidden niche structure that determines the fate of a new market.

Keywords: Market emergence; crowds; collective behavior; sensemaking; logics; conceptual paper

INTRODUCTION

In 2007, an annual listing of trending market spaces by the Gartner Group first cited “3D printing” as a rising category. Another analyst firm, International Data Corporation (IDC), announced that by 2019, the 3D printing market would reach over $26.7 billion USD in global spending, up from $11 billion in 2015, an annual growth rate of 27%. The increasing commercialization of 3D printing applications for both enterprises and consumers are reported to be the engine behind such significant market growth. In contrast, in 2004–2006, Gartner identified “DNA logic” as an emerging market space whose occupants would utilize the properties of DNA molecules for storage and processing. Yet this category completely disappeared and had not re-emerged as a focus of discussion a decade later.

The emergence of a new market is highly consequential for organizational life chances. Two firms building an identity in 2005, one saying it was developing 3D printing technologies and the other positioning itself as a DNA logic firm, have likely experienced different fates. Past studies have shown that for stable market demands to be established, there must be shared cognitions that support price formation and alternative comparison. Without the comparability of products and producers in place, such as in the case of overlapping niches or sociocognitive categories, a new market cannot emerge and function properly (Khaire & Wadhwani, 2010; Pólos, Hannan, & Carroll, 2002; Porac, Thomas, Wilson, Paton, & Kanfer, 1995). But, why are some proto-markets viable, while others are not?

In answering this question, the present article builds a theory of how crowds emerge and evolve in a way that influences the emergence of market logics. The crowd here may be defined as a non-hierarchical assembly of actors in a shared conversation about new market opportunity. Using crowds’ emergent discourse (Phillips, Lawrence, & Hardy, 2004) as an analytical window into the social process by which a new market’s cognitive foundations are laid out from collective meaning emergence, this theory addresses the following questions: (1) Why do some actors form crowds (i.e., crowd formation)? (2) Why do some crowds form contested markets (i.e., crowd differentiation)? (3) Why do some contested markets form stable markets (i.e., market formation)? Throughout the article, I focus on what White (1981b) terms a “production market,” a closed clique of producers who monitor one another, as opposed to a two-sided platform whose purpose is to facilitate exchange.

In the past 40 years, the study of markets as social structures, rather than the abstractions posited by neoclassical economics, has advanced significantly. For example, White (1981a, 1981b) set forth a sociological theory of markets based on the idea that a market emerges from the interlocking choices of a clique of supply-side actors who observe one another’s unit sales and revenues. Fligstein and Mara-Drita (1996) characterize a market as a set of firms who orient their actions to one another. Uzzi (1997) suggests that effective firms combine a market’s typical arm’s-length relationships with special ones that are socially embedded, enabling fine-grained information exchange and joint problem solving in an atmosphere of trust (for a review of the development of more sociological approaches to markets, see Swedberg, 2003).

However, most sociological scholarship studying the emergence and operations of markets pre-dates the widespread usage of the Internet and social media that is such a prominent feature of the contemporary landscape. The markets that sociologists and economists studied were typically anchored in space and synchronous in time even if they had some virtual components (e.g., stocks and futures markets where participants bought and sold via telephone or telegraph). Nowadays, with the rapid expansion of information and communications technology, many significant markets are either purely online or meld significant online and offline elements. The ubiquity of digitally intermediated interactions has compressed spatial and temporal distances in social interaction (Harvey, 1989), increasingly lifting out market activities from the particularities of local contexts (Giddens, 1990). The effects of this compression of time and space have been under-studied.

Time is compressed in two ways. First, the time between interactions is compressed so they occur in what is socially defined as “real time.” Second, the past and present are compressed because search and hyperlinking technologies make it as easy to access and consider archived messages from the past as those transmitted recently. Space is compressed because geographic distance per se is irrelevant online – simultaneous postings from Johannesburg, Moscow, and Singapore are received by someone in New York at about the same time. Time-space compression is of tremendous import in the emergence of markets, because it affects the way in which social interaction creates the cognitive and institutional underpinnings of a new market. The emergence of such underpinnings depends on social processes that explain why some markets become established (e.g., 3D printing) while others do not (e.g., DNA logic).

For many markets, especially those where the value of products is intangible, local variations are less important, and production costs are low, those social processes are shaped by the emergence of shared logics from actors’ sensemaking in a crowd (Killian & Turner, 1987; Weick, 1979, 1995). Unlike purely physical crowds that experience only a small set of shared collective emotions (crowd psychology; Le Bon, 1896), today’s crowds occur in “a virtual social space next to, or interwoven with, face-to-face social interaction” (Groenewegen & Moser, 2014, p. 466). The ease at which a crowd can form across the local and distant forces of communication increases the magnitude of intersubjective meaning divergence and convergence over time (Schutz, 1967), which in turn provides distinctive growth paths for a market to develop rapidly.

The article proceeds as follows: I first examine some of the existing approaches to understanding market emergence and their underlining assumptions rooted in social movement theory. I then conjoin collective behavior theory to sensemaking to suggest a new crowd approach that specifically accommodates the changing conceptions of time and space that are characteristic of modern markets. This approach leverages what we already know from social movement theory without being constrained by the assumption that actions are almost always coordinated from a fixed time and space. The socio-cultural evolutionary framework of meaning variation, selection, and retention (Campbell, 1969) is proposed to model the role of crowd dynamics in creating a cognitive and institutional context for a new market’s emergence. What is revealed is that a crowd has a hidden niche structure supported by emergent logics that determines the fate of a new market. The article ends with a discussion of the implications of this theory for organizations that must map a commercial identity onto the shifting market landscape in order to survive and thrive.

MARKET EMERGENCE AND CROWDS

Market Emergence: Existing Approaches

The topic of market emergence has a rich academic heritage dating back to the origins of the social sciences. In sociology, scholars have traditionally argued for the social embeddedness of economic relations as a reaction to the neoclassical economic model of market functioning (Granovetter, 1985). Markets are generally conceived of as social structures of interlocking perceptions and actions (White, 1981a, 1981b) that are believed to “function when the participants in exchange, producers and consumers, establish a stable social organization with roles and niches (Fligstein & Dauter, 2007; Porac et al., 1995; White, 2002)” (Weber, Heinze, & DeSoucey, 2008, p. 531). Since markets are constituted of a complex web of social relations that bind actors in one way or another (White, 2002), their emergence often involves collective actions of resource mobilization that span economic, cultural, and socio-political realms (Fligstein, 1996; Swedberg, 2005).

Organizational sociologists’ interest in the bottom-up dynamics of collective projects have led to a burgeoning body of work on the dynamics of a social movement or a “purposive and collective attempt of a number of people to change individuals or societal institutions and structures” (Zald & Ash, 1966, p. 329). In particular, the marriage of social movement theory and organization studies in recent decades has provided some important breakthroughs in our understanding of how novelty emerges in organizational and market settings (Davis, McAdam, Scott, & Zald, 2005). In organizational theory, this integrative approach has helped the organization ecologists explain the emergence of new forms and the growth of new niches (Carroll & Swaminathan, 2000; Ruef, 2000; Sine & Lee, 2009). Also, it has helped the institutional theorists explain how new practices and structures, markets and industries are introduced through cultural strategies, such as storytelling and employing frames (Lounsbury, Ventresca, & Hirsch, 2003; Wry, Lounsbury, & Glynn, 2011).

While most of the existing studies drawing on social movement mechanisms are concerned with alternative selection, often in established markets, there are emerging research streams focusing on the role of social movements in alternative generation in nascent markets (David, Sine, & Haveman, 2013; Weber et al., 2008). The socio-cultural change brought forth by intended and/or unintended interfaces of actions and interactions lies at the heart of these recent studies. In a similar vein, the current article examines the development of emergent logics that come to support new niches and thereby demarcate the symbolic and social boundaries of a new market (Lamont & Molnár, 2002). In doing so, I revisit one crucial assumption underlining social movement theory – that a coordinated form of change (i.e., collective action) is necessary for variations to be successful.

Market Emergence: A Call for a New Approach

Let us first take a look at the recent advancement of the Internet of Things (IoT), a computing concept that describes “[connecting] every thing with everyone in an integrated global network” (Rifkin, 2014, p. 11). It is estimated that the IoT market will reach 25 billion connected “things” by 2020 (Gartner, 2015), with an annual economic impact exceeding $11 trillion by 2025 (Manyika et al., 2015). Although the phrase “Internet of Things” first appeared in 1999 (Ashton, 2009), it was not until the beginning of this decade that it became a global buzzword. The sudden spurt in market interest and growth has generated a high degree of definitional and conceptual multiplicities, leaving many producers to use the term in a rather ambiguous and incoherent manner. Nonetheless, we are witnessing some strong cases of niche formation based on the IoT’s multiple market applications. Some may attribute the increasing number and types of connected things to the rapid diffusion of mobile devices as well as the reduction in the cost and size of embedded chip sets (Fenn & LeHong, 2011). The question remains, however, as to how the IoT space has come to “establish a stable social organization with roles and niches” (Weber et al., 2008, p. 531) in such a short time period, especially in the absence of dominant market players.

I find one salient reason in the rise of the crowd’s online conversations that go beyond the initial close (or closed) discussion among engineers and early adopters. The expansion of online platforms, such as social networking services, blogs, and online discussion forums, now allows anyone with an interest in the IoT to easily assemble in a shared virtual space and identify what’s being talked about and by whom. Initially, this led to a proliferation of inchoate and asynchronous articulations about the technology, which in turn generated equally idiosyncratic, one-off transactions. Over time, there emerged across the crowd some “vocabularies of practice” (Thornton, Ocasio, & Lounsbury, 2012, p. 150) that gave consensually validated structure to the niches that now constitute the IoT market. Examples of these niches include “healthcare” (e.g., wearables to monitor bodily functionings), “manufacturing” (e.g., 3D printing to produce prosthetics), and “transportation and logistics” (e.g., drones for delivery), where censors and antennas are used to collect and analyze communications data.

As illustrated above, markets are emergent rather than premeditated. The social process by which new markets emerge “cannot be explained by prior social organization, norms, and culture, because [their] movements are emergent forms that acquire organization during their life cycles” (Morris & Herring, 1984). Unlike social movements, which “require some form of organization” (Davis et al., 2005, p. 6), emergent markets do not require a premeditated form of change. What is required is an “arena” (White, 1992) like the crowd’s shared discourse space, where new interpretations are selected and excluded. The locus of collective action is no longer tied to a select few mobilizers, who employ “frames” (Goffman, 1974; Snow, Rochford, Worden, & Benford, 1986) to align their own “means-ends relations” (i.e., logics of action; Bacharach, Bamberger, & Sonnenstuhl, 1996) with those of potential adherents. In today’s communication-rich environment, just getting attention might be a feat in and of itself. Would-be institutional entrepreneurs (Tolbert, David, & Sine, 2011) can at best surf and to some extent influence the surging tide of symbols and practices within the crowd by letting their frames be “disintegrated into their constituent elements and … brought together again into new relations” (Park & Burgess, 1924, pp. 924–925). As the crowd converges on logics through continued sensemaking, frames emerge organically “to organize experience and guide action, whether individual or collective” (Snow et al., 1986, p. 464).

Certainly, not every crowd can evolve into a market. A crowd at a sporting event or political rally would not suddenly morph into a production market. Markets emerge from crowds only when enough meaning variation, selection, and retention occurs at the level of social interaction (Wiley, 1988) to establish a “shared definition of social reality” (Scott, 1987, p. 496). This condition was rare in the past, as crowds typically did not last long enough to support the process of intersubjective meaning evolution (McPhail, 1991). Their emergent properties were generally only specific to a particular location in time and space. Now, crowds are not so temporal anymore, and their constituents are not necessarily co-located in time and space. Such changing characteristics allow different dynamics to emerge that provide a distinctive growth path for markets, allowing them to morph rapidly at reduced search costs. As we set out to explore the dynamics of market formation from crowd activities, I suggest that we take up the theoretical lens of crowds and their collective behavior.

CROWD DYNAMICS IN MARKET EMERGENCE

Crowds and Collective Behavior

When the Arab Spring swept across the countries of the Arab League and its surroundings in 2011, the world was reminded of the power of web-enabled crowds. The idea that the era of crowds had dawned upon humanity famously dates back to the late 19th century, when France was going through an unprecedented surge of crowd-initiated political and social upheaval, to the horror of its elites. This historical background provided the basis of Le Bon’s (1896) seminal writing on crowds, which assumed that the crowd is always irrational and individuals undergo a radical psychological transformation once they become part of the crowd. This transformation explanation was further developed by prominent scholars at the Chicago School of Sociology, Park and Burgess (1921) and Blumer (1969 [1939]). They followed Le Bon’s original conception of the crowd as a template for analyzing collective behavior and sought an explanation of social change in the activities of crowd constituents. In the same spirit, I treat the crowd and collective behavior synonymously throughout this article.

The collective behavior theory took a decisive turn when its later scholars, most notably Killian and Turner (1957, 1972, 1987) and Smelser (1963), broke away from the theory’s underlying assumption. In particular, Turner and Killian are best known for their selective retention of Blumer’s (1969 [1939]) symbolic interactionism to propose that collective behavior takes place when rational actors with differential motives and expression come together to make sense of uncertain situations. In the absence of established institutional patterns, by proffering their own interpretations of reality and observing those of others (Killian & Turner, 1987), crowd members give rise to emergent properties that are characteristic of the crowd’s internal patterns of action and interaction (Blau, 1964). The perspective of intersubjective sensemaking links the subjectivity of actors’ individual interpretations with the crowd’s collective behavior, which together come to constitute the actors’ shared reality.

Throughout the 1960s and 1970s, the collective behavior theory (or theories) gave way to the more politically oriented social movement theory. One reason for this shift was that the latter theory group’s emphasis on the coordinated form of change, as opposed to the social psychology of crowd behavior, resonated better with the spirit of a time that was largely shaped by social protests (Davis et al., 2005; McPhail, 1991). Since then, the theoretical primacy within sociology and organization studies has been given to the coordination of collective actions, relegating to the periphery spontaneous (Snow & Moss, 2014) and non-institutional elements of any movement-like phenomenon. Some scholars have persistently called for a revival of the collective behavior theory, but the general lack of theoretical coherency across the “crowd” research, as well as the underexplored empirical challenges associated with studying crowds, has largely resulted in the sub-optimal fulfillment of the call.

Today, the term “crowd” appears most frequently in the innovation literature, where it is used without associated theoretical definitions to refer simply to external online contributors. Such atheoretical usage of the term has shown a clear benefit in the building up of a growing body of work testing the nature and extent of the “wisdom of crowds” (Keuschnigg & Ganser, 2016; Surowiecki, 2005) in multiple organizational settings. For example, crowds have been studied in the context of organizational problem solving (i.e., crowdsourcing; Belleflamme, Lambert, & Schwienbacher, 2014; Boudreau & Lakhani, 2013; Piezunka & Dahlander, 2015), fundraising (i.e., crowdfunding; Fleming & Sorenson, 2016; Mollick & Nanda, 2015), and innovation (i.e., collective or user innovation; O’Mahony, 2003; von Hippel, 2009; von Hippel & von Krogh, 2003). The implicit assumption and implication of these studies is that the focal organization has control over an entire crowd or its particular subset that can be mobilized as a community with the aim of meeting specific organizational needs (Seidel & Stewart, 2011). (For a more detailed comparison of crowds and communities, see the “Discussion” section.) Indeed, with the rapid diffusion of mobile technology, the identification and coordination of external contributors’ innovative power has become much easier than before. The contemporary relevance and usefulness of managing crowds, however, tells only half the story. The other half is the inherently innovative power of uncoordinated crowds.

Crowds as Interaction Structure across Time and Space

As we enter the era of web-enabled crowds, we need to shift our attention back to the type of collective behavior that falls largely outside the focal organization’s cognitive awareness, let alone direct control. A crowd can form easily and extensively when there is mutual recognition of opportunity space, and it generates distinctive patterns of intersubjective meanings that allow new markets to emerge. In other words, today’s crowds (versus purely physical crowds of the past) provide interaction structure that is simultaneously local and distant, and past and present.

At any given point in time, a crowd covers both local and distant spaces. Each crowd member’s subjective interpretation, whether formed through one’s involvement in offline events or online interaction across local networks, can instantly become available for distant others to see and translate into a shared objectivity using highly abstract vocabularies (i.e., objectivation; Berger & Luckmann, 1966). This process, in return, can influence the same crowd member’s subsequent meaning propagation in such a way that it either conforms to or deviates from what is “legitimized and ultimately, taken-for-granted as a social fact” (Rao, Morrill, & Zald, 2000, p. 242) within the crowd. With the continuous supply of meaning variations stemming from the myriad intersections of local and distant spaces, the crowd’s discursive reservoir gets updated in real time.

At any given point in space, the crowd’s time is compressed between the past and present. The persistence of the past in the present form is nothing new. Past studies on imprinting (Stinchcombe, 1965) inform us that the crowd’s early conversations are shaped by the internal and external characteristics of its founding members and that they are bound to persist beyond the crowd’s founding phase (Marquis & Tilcsik, 2013). What is new now is the increasing accessibility of the past through digital achieves. Although online postings are of the moment, they are archived indefinitely, making some of the artifacts of a crowd easily searchable. Those who have already left the crowd end up influencing the ongoing discussion, not only because they have imprinted the crowd in the first place (e.g., a few seminal blog posts keep getting co-cited in the current discussion), but also because anyone at later time points can find their original text and break away from its existing path-dependent sequences (Mahoney, 2000). When the past’s artifacts are modified in real time across the crowd’s historical layers, the present becomes a complex mosaic of those who have been “imprinted” and those who are currently “imprinting.”

Based on the abovementioned notion that the crowd offers a discursive arena that spans time and space, I will develop an evolutionary framework that models the progression of crowd dynamics in creating a context within which emergent logics come to demarcate a new market.

Crowd Formation: Meaning Variation

When there is mutual recognition of a new market opportunity – that “there must be something there” – it provides a common focus of attention for individually motivated actors to assemble in a shared space and turn to one another for an appropriate action (Killian & Turner, 1987; Weick, 1979, 1995). This initial sensemaking process via crowd formation is vitally important for the fate of the newly identified opportunity, as it shapes a basic structure of market identities and categories from which more organized structures and practices can emerge later (Weick, Sutcliffe, & Obstfeld, 2005). The challenge here is that actors must identify and connect to others with a shared interest in order to develop the shared sense of a crowd.

I suggest that some actors are likely to form a crowd because they have reached a critical mass of interrelated interpretations (e.g., drones x military, drones x delivery, drones x photography) in the form of trending hashtags, related search terms, and links to the same forum, just to name a few. Using social media as a window into the socially emergent cognitions around the opportunity, anyone can easily identify who’s in the same discourse and who’s not at reduced search costs – without personal relationships (e.g., communities of practice; Lave & Wenger, 1991) or external institutionalizing forces (e.g., industry journals).

First, personal relationships are not a prerequisite for crowd formation. In fact, given the typical size and growth rate of online conversations (e.g., the number of daily Tweets about the IoT averages around 50K¹), building personal ties with every relevant actor in the crowd becomes a cognitively impossible (Cyert & March, 1963) and strategically inadvisable task. Rather than focusing on a limited number of personal contacts, an actor wishing to find an optimal market position must “heed” (Weick & Roberts, 1993) what emerges across the crowd’s numerous interfaces of local and distant, past and present, discourse spaces. This may include intersubjective typifications of crowd members and their roles (Schutz, 1967) that are “progressively anonymous as they are removed from the ‘here and now’ of the face-to-face situation” (Berger & Luckmann, 1966, p. 47). As the process of typification unfolds, there emerge one or two central nodes associated with broad roles, such as those of producers (e.g., entrepreneurs), resource providers (e.g., suppliers), and legitimators (e.g., consumers and investors). However rudimentary, emerging role structure (White, 1981a) gives materiality to the crowd by delineating potentially aligning logics of action across actors.

Second, crowd formation occurs without external institutional actors, such as market reports and statistics, trade journals and associations, academic conferences, and reference sites, imposing on sensemaking actors specific symbolic codes (Weick, 1995). In the absence of institutional constraints, actors freely interact with one another to produce a multitude of individualistic interpretations and logics of action, which, together, constitute the opportunity space that they are co-constructing. There certainly are identifiable patterns of interpretive interrelatedness across these actors, but they are not yet stabilized due to the constant ebb and flow of crowd members and their local meaning variations (Weick, 1995; Wry et al., 2011). The ongoing discursive cacophony also makes it difficult for external legitimating forces to come in and select out what needs to be institutionalized and what does not. Simply put, the crowd’s sensemaking occurs in the absence of established social norms (Killian & Turner, 1987), which subsequently produces some basic elements of typifications and classifications (Berger & Luckmann, 1966) that may be too “raw” for external validation but that will eventually become the “feedstock for institutionalization” (Weick, 1995, p. 35) at later stages of crowd evolution. Without taken-for-granted examples of what worked and what didn’t (Aldrich & Fiol, 1994), signature deals or sales cannot be established.

Reduced search costs lead to increases in the speed and size of crowd formation in the absence of institutions, incurring enough meaning variation to generate distinctive growth paths for market comparables (White, 1992). One may argue that physical co-location in time and space is one way to lower search costs. Most notably, institutional actors are known to create crowds regularly: Governments holding elections, organizations arranging major sporting events, and associations hosting conferences are just a few examples. These crowds, however, quickly reach an asymptote – one can only fit so many people in a given physical space (e.g., approximately a million in Tiananmen Square).

One salient example of crowd formation is Bitcoin, a virtual currency and a payment system governed by transparent computer code (Chuen, 2015). The Bitcoin protocol was proposed by a mysterious figure or figures under the pseudonym Satoshi Nakamoto in 2008 as an alternative to conventional currency and does not require powerful intermediaries like banks to authenticate and settle transactions (Nakamoto, 2009). For the first few years, nobody could predict the future of this new technology. Only a handful of experimental transactions took place among programmers and early adopters, and there were not enough referent companies to generate stable market demands. Nevertheless, the mutual recognition that Bitcoin could potentially start a currency revolution brought together interested actors ranging from academics and regulators to financiers and entrepreneurs in a shared discourse across numerous online platforms. What emerged from the conversation was a complex patchwork of common versus idiosyncratic vocabularies, shared versus isolated use cases, and taken-for-granted versus contested resolutions. However inchoate the initial conversation was, it effectively nurtured a shared sense of crowd across the conversation participants, marking the beginning of a cognitive underpinning required of a new market.

Proposition 1a. A crowd forms when actors forge a critical mass of interrelated interpretations that constitute a common discourse space.

Proposition 1b. The speed at which a crowd forms and its size depends on the search costs of finding other actors in the discourse space.

Proposition 1c. The presence of external institutional actors is minimal at the initial stage of crowd formation.

Crowd Differentiation: Meaning Selection

But why do some crowds develop into contested markets? Amid the growing discursive cacophony, crowd members start to pay selective attention (Ocasio, 2011) to ease the burden of simultaneous information processing (Cyert & March, 1963). In doing so, they continue to turn to one another to help make sense of the environmental uncertainty and converge on what appears to be an appropriate action (Killian & Turner, 1987; Weick, 1979, 1995). This results in the convergence of individualistic interpretations and logics of action via discovery mechanisms (e.g., search engines and social media hashtags); mutual referencing (e.g., URL cross-citations and post retweets); and common platforms (e.g., online magazines, forums, and blogs). As they converge into the realm of intersubjectivity, some individualistic logics remain in their original form, some undergo marginal modifications, and some get transformed into a more complex form of logic constellations (Baker & Nelson, 2005; Tracey, Phillips, & Jarvis, 2011; Vaerlander, Hinds, Thomason, Pearce, & Altman, 2016). The selection of meanings then manifests as the formation of sub-crowds (i.e., crowd differentiation), which occupy niches that are characteristically different from one another in terms of how meanings are aligned between relevant actors (DiMaggio, 1986; Hsu & Hannan, 2005; McPherson, 1983). During this transitional stage of meaning variation and selection, sub-crowds are constantly in flux and their associated niches have yet to be fully differentiated.

To go back to our earlier example of Bitcoin, this space has seen the emergence of two generally recognized sub-crowds since its formation. The first sub-crowd was initiated by tech startups, early adopters, and investors, whose respective logics of action subsequently converged on realizing the potential of Bitcoin as an alternative to the incumbent payment networks like credit cards and PayPal. Through their continued social interaction, somewhat systematic transactions started to emerge rapidly, driving significant increases in the early-stage investments. By 2013, the daily transaction volume of Bitcoin had surpassed that of Western Union; and by 2015, over $373M USD in venture capital money streamed into the Bitcoin space within the first half of that year alone. By comparison, the second sub-crowd was initiated by leading banks, payment processors, and other financial institutions, whose shared interest centered on Bitcoin’s underpinning “blockchain” technology, a global distributed ledger of all Bitcoin transactions. The emergent view was that the industrial application of blockchain, more than Bitcoin itself, would have a greater potential to change the financial services industry. Examples of its application have since appeared in trading, file storage, and identity management.

Right now, these two sub-crowds are occupying highly overlapping niches, each allowing for only quasi-stable market transactions. There may appear to be some degree of shared vocabularies, stories (Lounsbury & Glynn, 2001; Martens, Jennings, & Jennings, 2007), and labels (Grodal, Gotsopoulos, & Suarez, 2015) characterizing the overall Bitcoin and blockchain space in the eyes of external audiences, but there are yet to be taken-for-granted cognitive structures shared across the crowd that can clearly distinguish its embedded niches, both old and new (i.e., legitimate distinctiveness; Navis & Glynn, 2010, 2011). This means that while there are high entry barriers for newcomers who may lack the appropriate knowledge of the language, there are relatively low mobility barriers for existing crowd members. For instance, there are increasing cases of Bitcoin startups changing their identities to become more general blockchain platforms. This trend has been followed by major shifts in the investment money and government attention. As one recent article noted: “[A] funny thing is happening: Bitcoin, the very reason for that [blockchain] architecture, is often going completely unmentioned” (Rosenfeld, 2016).

The Bitcoin example demonstrates that when a crowd lacks agreed-upon cognitive structures, it typically faces heightened categorical ambiguity with overlapping niches (Pontikes, 2012). This is exemplified by the fact that the word “Bitcoin” is used to mean many different things. As one venture capitalist stated: “We used to call bitcoin (the currency) ‘bitcoin’, Bitcoin’s blockchain ‘Bitcoin’, and we used to call the technology or concept ‘Bitcoin’. It was a little confusing …” (Torpey, 2015). Without fully differentiated niches and their cognitive associations, a stable market cannot form based on alternative comparison (Khaire & Wadhwani, 2010). At a time of continuous sub-crowd differentiation, a crowd functions as a contested market supported by quasi-routine transactions.

Proposition 2a. A crowd differentiates into sub-crowds with high overlap when actors’ intersubjective sensemaking triggers meaning convergence with local variations.

Proposition 2b. The persistence of high niche overlap hinders the development of stable markets.

Market Formation: Meaning Retention

Why then do some contested markets effectively turn into stable markets? The inherent uncertainty associated with niche instability prompts crowd members to further converge on their existing identities and belief systems through continued social interaction (Killian & Turner, 1987; Weick, 1979, 1995). What come out of this process are more tightly aligned shared cognitions that can be used by external legitimating forces to define the market space. For new markets to form and function properly, institutional actors must be present to separate out and legitimate certain shared logics of action that the crowd has spawned. They do not create or mobilize markets as social movements do, but they selectively validate “social codes that specify the properties that an entity can legitimately possess” (Pólos et al., 2002, p. 85) so that the crowd can evolve stable niches with low overlap. The crowd can produce raw material for institutionalization, but it cannot create institutions from scratch. For example, flea markets can and do emerge around the crowd in a football stadium, but this same crowd cannot spontaneously decide to become a production market without a consensually validated set of comparables. Offering would become a “missionary sale” and only the biggest risk-taking early adopters would become potential customers.

Once certain shared logics are legitimated, they become institutional logics (Thornton et al., 2012) that provide “rules of action, interaction, and interpretation” (Thornton & Ocasio, 1999, p. 804) for social domains reaching beyond particular means-ends exchange relations to more general organizational mission, attention, strategy, and legitimacy pursuits (McPherson & Sauder, 2013; Thornton, 2004; Thornton & Ocasio, 1999). The crowd now has a distinctive set of “material practices, assumptions, values, beliefs, and rules by which individuals produce and reproduce their material substance, organize time and space, and provide meaning to their social reality” (Thornton & Ocasio, 1999, p. 804). Supported by institutional logics giving consensually validated structure to the definition of offerings, substitutes, and complements, a crowd has now become a stable market occupying relatively non-overlapping niches.

For example, the 3D printing market space has achieved a significant degree of legitimacy since its first appearance on Gartner’s hype cycle in 2007. Its two major niches, “consumer 3D printing” and “enterprise 3D printing,” have received much media attention, especially in the past few years, and they are now staples at global tech conferences. Such involvement of various media channels, conference organizers, and government agencies has helped the overall market space of 3D printing establish a collective meaning system that enables routine transactions. The 3D printing market can scale on its own.

Proposition 3. A crowd evolves stable niches with low overlap when external institutional forces separate out and selectively retain the logics that the crowd has spawned.

Crowd Dynamics: Micro-Level Tensions

Underneath the macro social process of a crowd’s progression into a fully functioning market, there lies an inevitable tension at the level of crowd members. To the degree that all members can be heard faster and more extensively than before, they may be subjected to the heightened social influence (Cialdini & Goldstein, 2004) stemming from the increasing availability and immediacy of information online. Due to the temporal and spatial nonlinearity of online discourse, the social influence is also multi-directional and often conflicting in meaning. This leads to my argument that any given crowd’s socially emergent cognitions are a mixture of the Internet’s enabling and constraining pressures: If the former outweighs the latter, the crowd is likely to diverge indefinitely with multiple and often conflicting individualistic interpretations. If the latter outweighs the former, the crowd is likely to be engulfed by a sub-optimal collective mind that can subjugate the individuality (Le Bon, 1896) and beget premature niche convergence. I argue that the crowd can become a stable market only when these dual pressures are balanced across time.

During meaning variation, a crowd must have multiple independent and decentralized actors with limited subjectivity to social influence to induce an aggregation of alternatives that are diverse and each worthy of selection (i.e., wise crowds; Surowiecki, 2005). Once enough variation is achieved, these actors must turn to one another (Killian & Turner, 1987) and willingly subject themselves to a moderate level of social influence. This is to patch together disparate pieces of their shared online discourse and achieve a consensual definition of the opportunity space identified. When the crowd members strike the right balance between “influencing” and “being influenced” sequentially across the meaning divergence and convergence stages of crowd evolution, the initial discursive cacophony will effectively settle into recognizable patterns of sociocognitive distinctions (Table 1).

Proposition 4. A crowd progresses into a stable market when actors are independent and decentralized during meaning variation, and are moderately subjected to social influence during meaning selection and retention.

Table 1. Multi-Level Dynamics of a Crowd’s Progression into a Market.

DISCUSSION AND CONCLUSION

Crowds, Communities, and Social Movements

Crowds and Communities

One may wonder how crowds are conceptually differentiated from communities. Although both constructs are known for their definitional multiplicities (McPhail, 1991; O’Mahony & Lakhani, 2011), a careful reading of existing scholarship tells us that they are different on multiple grounds. First, they share different ontological bases: While crowds self-organize when individually motivated actors assemble in a shared space to use one another’s interpretation and response for sensemaking (Killian & Turner, 1987; Weick, 1979, 1995), communities are “collections of actors whose membership in the collective provides social and cultural resources that shape their action” (Marquis, Lounsbury, & Greenwood, 2011, p. xvi). In other words, crowds emerge in the absence of normative order, social structure, or communication channels, whereas communities form around a specific purpose and set of shared goals. While a community is not a precondition for a crowd to form, a crowd can fragment into communities around shared cultures and norms.

Such ontological differences have implications for their internal operation: While the locus of crowds lies with the emergent properties of actors distributed across time and space, communities are rooted in personal relationships in specific places. Consequently, crowds have no internal organization but a simple network structure with some actors more central than others, whereas communities have well-defined internal organization based on shared cultures and social norms. Without binding social relations, crowd members are free to move around disparate sub-conversations, resulting in the continuous emergence and dissolution of sub-crowds. This should arouse our field’s latent interest in, and urgency about, studying crowds’ collective behavior, from which some unexpected novelty may arise.

Crowds and Social Movements

Despite the divergent historical paths taken by scholars of crowds and those of social movements, the former have not been entirely agnostic about social movements. In fact, the Chicago School sociologists were distinguished from their European counterparts in their open inclusion of social movements as a more advanced form of collective behavior (McPhail, 1991). While Park and Burgess were relatively silent on the subject, Blumer saw social movements as originating from more elementary processes of collective behavior. Similarly, Killian and Turner considered them as one type of collective behavior that happens to fall “near the boundary that separates collective behavior from strictly organized and institutionalized behavior” (Killian & Turner, 1987, p. 230). The collective behaviorists’ view of social movements was one that illuminated the life cycle of a crowd – that is, from a crowd to an institution, and from collective behavior to collective action.

Such an evolutionary take on social movements provides a useful theoretical framework for examining how a crowd might precede either a market or a social movement – the former by establishing shared logics of product comparability, and the latter by bringing a group of similar actors into a shared social (identity) space (Fiol & Romanelli, 2012). First, the crowd-to-market progression is achieved when a crowd forms around some mutually identified market opportunity and converges on shared logics that ultimately get legitimated as the market’s “background of routines” (Berger & Luckmann, 1966). In the process, contestation is inevitable due to the lack of institutional constraints in a nascent space. Crowd members’ uncoordinated interaction, especially in the compression of time and space, results in a wide range of market definitions that also morph rapidly over time. The magnitude and speed of crowd formation and differentiation online makes it impossible for any given crowd to enter seamlessly into the state of stability without this intermediary step. As the crowd’s individualistic logics mature into shared logics and finally to institutional logics, the crowd “increasingly lose[s] the distinctive features of collective behavior” (Killian & Turner, 1987, p. 230) and converts into a market whose collective action is governed by institutional frameworks.

Second, the crowd-to-social movement progression is achieved when a select few institutional entrepreneurs (Rao et al., 2000) or ideological activists (Snow et al., 1986) mobilize a crowd or sub-crowds by actively theorizing about the underlining values of a desired change (DiMaggio, 1988). One could imagine a group of similarly minded entrepreneurs – for example, the Open Hand Project and Open Bionics, whose goal is to make robotic prosthetics more accessible to amputees around the world – uniting some sub-sets of the 3D printing crowd around their prosocial goal. Since the crowd has already formulated distinctive patterns of cognitive and institutional elements through intersubjective sensemaking, it can provide some useful raw material for purposive and collective change actions.

While acknowledging the theoretical importance of both cases, this article has focused on the emergence of markets from crowds (Table 2).

Table 2. Comparison of Crowds, Communities, and Social Movements.

Organizational Consequences

I limit the discussion of organizational consequences to producer-organizations such as entrepreneurial firms in an emerging market. We know from the category and categorization literature that organizations must define their identities in such a way that they can be mapped onto a clear and focused niche (Hsu, Hannan, & Koçak, 2009; Negro & Leung, 2013; Pontikes, 2012; Zuckerman, 1999, 2000). There is a tremendous premium to being a first-mover in a defined space (Lieberman & Montgomery, 1988), as opposed to stretching material and symbolic resources across multiple spaces. We also know from the recent work on legitimate distinctiveness that organizations benefit from stronger attention, recognition, and market advantage if they are perceived as members of an accepted niche but can still be differentiated from their competitors (Navis & Glynn, 2010, 2011). These research streams suggest that an entrepreneurial producer wishing to acquire a profitable niche position must act fast before the crowd has become fully stabilized with differentiated niches.

One can do so by joining the conversation early on. When the market space is still in its preliminary stages, an entrepreneur faces the challenge of having to tell coherent stories about the market (Lounsbury & Glynn, 2001; Martens et al., 2007) even when the crowd is not yet fully formed or its niches are highly overlapping. This process of enacting an appearance of coherency, whether or not it really exists, is crucial for securing investors’ trust in the market early on – before competitors start flooding in to occupy differentiated niches. Telling a story of collective identity (e.g., forward-looking cognition; Gavetti & Levinthal, 2000), while maintaining one’s own distinctiveness within the bounds of this identity (e.g., backward-looking experiential learning; ibid.), requires one to be extremely attuned to the cross-level, intertemporal tension between “what may work for the crowd” and “what is working for me.” It is only when this tension is balanced in imaginative and improvised ways (Miner, Bassof, & Moorman, 2001), leveraging the increasing prevalence of online communication, that an entrepreneur can truly carve out a market position that is not imitable and substitutable (Barney, 1991).

Taken together, “time” seems to be a central element in thinking about the organizational implications of crowd dynamics. How do entrepreneurs come to find comparables amid the crowd’s shifting collective mind? How do their collective identification processes (Ashforth, Harrison, & Corley, 2008) influence their propagation of a stable identity? Answering these questions would help us move away from one prevailing assumption underlying much of our existing scholarship – that in nascent markets, similar actors have already been formed into an organized cluster and there is a presumed collective identity for these similar actors to converge on (Fiol & Romanelli, 2012). The diffusion of social media and mobile technology has opened up an empirical window into the formative phases of nascent markets and their co-evolution with entrepreneurial actions. It may be our responsibility as organizational scholars to catch up with the spirit of our time, and explore how entrepreneurs navigate their way around the uncoordinated landscape of a crowd to pave their own conscious, innovative paths.

Implications for Existing Literatures

Emergence

Although the topic of emergence has garnered much scholarly attention in recent decades (Romanelli, 1991), very few scholars would be able to answer with confidence the question of how new alternatives are born in the first place. This seemingly simple question is surprisingly elusive, as shifts in meaning often entail “a thick and tangled bush of branchings, recombinations, transformations, and sequential path-dependent trajectories” (Padgett & Powell, 2012, p. 2). The present article has attempted to untangle this thick and tangled bush in the context of new market emergence. Before there is a shared meaning system delineating what and whom to compare – before it is possible to make that first exchange of products – how are new markets laid out in the first place? In addressing this question through the lens of crowd behavior and sensemaking, I have offered a theoretical framework that is not agnostic to the social world but that can bring back sociality into emergent studies.

Collective Behavior Theory

Collective behavior theory contains a wealth of knowledge that pertains to the process of emergence in the absence of institutional constraints. This provides a fitting theoretical approach toward understanding the formative dynamics of a new market where there is no pre-existent social norms to confer legitimacy onto particular structures or practices. The rise of web-enabled crowds, in particular, may suggest to us that the time is ripe to revive the centrality of collective behavior in understanding how new markets come into existence from the emergence of uncoordinated crowds that are compressed in time and space and that allow for distinctive growth paths to emerge rapidly.

Certainly, there are some elements of commonality between the novelty emergence from collective behavior and that arising from “community-forms” of organizing (Marquis et al., 2011): They both acknowledge the emergent nature of social interaction in collectives (Blau, 1964). However, the difference is that in the case of uncoordinated crowds’ novelty generation, there is no distinguishable form of governance giving structure to the process of innovation (O’Mahony & Ferraro, 2007). Community is no longer a necessary condition for a new market to organize and further develop. Rather, a new market can emerge directly from the crowd’s intersubjectivity that precedes any coordinated form of institutional change. I believe the evolutionary view of a crowd’s progression into a market would rekindle the organizational scholars’ interest in the study of collective behavior.

Institutional Logics

Since its original conceptualization by Friedland and Alford (1991), the topic of institutional logics has become the staple of institutional theory. In the past few decades, we have seen a shift of attention from the sectoral logics to the logics at more intermediate levels in order to “bridge between macro, structural perspectives and more micro, process approaches” (Thornton & Ocasio, 2008, p. 99). The micro-macro link via logics has taught us much about the tensions inherent in different logics and how they can be used as key resources for organizational and institutional change. However, we still know much less about how these logics originate. In line with some recent scholars’ attempts to uncover the discursive process by which new logics emerge (Jones, Maoret, Massa, & Svejenova, 2012; Reay & Jones, 2015; Suddaby & Greenwood, 2005), the current article wishes to shed light on the temporal dimensions of logic formation and change by examining the interrelated life cycles of logics – from the “individualistic” to the “intersubjective” and finally to the “institutional.”

Our evaluation of crowd-initiated logics may also hold out one interesting implication for community logics that are known to moderate the influence of societal logics on geographically situated actors (Lee & Lounsbury, 2015). With the growing number of markets emerging directly from crowds, crowds’ emergent logics are expected to interact frequently with geographically fixed community logics in the lead up to, and during, their institutionalization. How would such interaction play out and influence market practices, structures, and cultural beliefs in local settings? This is a research venue that I propose to scholars of crowds, communities, and social movements.

Innovation Diffusion

The focus on logic variation would also speak to the innovation diffusion scholarship, where the recent focus has been on identifying cultural antecedents to diffusion (Strang & Soule, 1998). Explaining why and by whom something gets selected to diffuse in the first place is more difficult than explaining how that something, once chosen, diffuses across the existing structural landscape of a system. A majority of today’s innovation in production markets arises from both tangible (technological) and non-tangible (symbolic) sources, and their values cannot be ranked on a decisive effectiveness-efficiency scale. For example, Apple was able to dominate – or rather, create – the market for smartphones, not because its technology was groundbreaking, but because its symbolic features changed the ways in which people thought about smartphones. Such non-straightforwardness of diffusion brings an enormous challenge to our understanding of what will diffuse next. The current article’s sociocognitive approach to market emergence – that new markets emerge from online crowds’ co-construction of shared meanings – can provide informed insights into the preselection stage of innovation diffusion.

CONCLUSION

In this article, I asked how we ought to understand the cognitive and institutional underpinnings of new markets, especially those that are affected by today’s time-space compression in social interaction (e.g., markets where the value of products is intangible, local variations are less important, and the production costs are low). As a response, I developed a theoretical framework of how crowds emerge and evolve in a way that influences the emergence of market logics and helps explain why some proto-markets are viable, while others are not. What is revealed is that a crowd has a hidden niche structure supported by emergent logics, and this niche structure determines the fate of a crowd’s successful progression into a market. The argument is simple: A crowd forms through actors’ mutual identification at reduced costs. A crowd then reduces the discursive cacophony incurred by all-to-all interactions in time-space compression, so that markets can emerge around shared logics that enable comparison and exchange.

NOTE

1. Figures obtained by using relevant search words (e.g., Internet of Things, IoT, Internet of Objects, Internet of Everything, ubiquitous computing, pervasive computing, machine-to-machine communication, Web of Things, Web of Systems, etc.) on Crimson Hexagon between 2009 and 2016, www.crimsonhexagon.com

ACKNOWLEDGMENTS

I have greatly benefited from the feedback and guidance of the two editors. I am also grateful to Philip Anderson and Rolf Hoefer for their insightful comments on earlier drafts of the manuscript. All errors are my own.

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