Exploring the Links between Reputation and Fame: Evidence from French Contemporary Architecture

Abstract

Why are some organizations famous? We argue that fame results from a conjunction of several audience-specific reputations. Expert reputation (i.e. reputation among members of a knowledgeable group, such as a cultural elite or critics) acts as a mediator for achieving fame for organizations held in high esteem by their peers and clients. Based on a unique database of 103 architectural companies in France, our analysis uses structural equation modelling (SEM) combined with mediation effects to reveal that expert reputation can lead to fame by mediating peer and client reputations. We contribute to the literature by explaining why only some organizations already reputed among peers and clients are famous in society at large.

Keywords

architecture creative industries fame mediation reputation selection system theory structural equation model

Introduction

Why is Armani a famous organization in fashion? Why is Joël Robuchon’s restaurant known worldwide for its culinary excellence? Research in sociology has defined fame as the volume of public discourse about a person, or a continuum composed of ‘sheer numbers of people who know one’s name’ (Currid-Halkett, 2010, p. 66); the term is used for both loved and hated entities (Van de Rijt, Shor, Ward, & Skiena, 2013). Fame is not a matter of success or failure, but has been argued to be an important social approval asset that allows organizations to earn power, status or attractiveness among audiences (Frank & Cook, 1995; Gamson, 1994; Rein, Kottler, & Stoller, 1987; Van de Rijt et al., 2013). Fame has been characterized as a self-reinforcing process (Van de Rijt et al., 2013). It is subject to both the snowball effect, whereby a ‘small initial burst of support for fame can lead to cumulative and self-reinforcing support over time’ (Cowen, 2000, p. 14), and the Matthew effect, accruing from disproportionately greater recognition of the already-well-known (Merton, 1968).

Fame has been argued to reverberate with other social approval assets, such as reputation (e.g. Boyd, Bergh, & Ketchen, 2010; Brooks, Highhouse, Russell, & Mohr, 2003; King & Whetten, 2008; Turban, 2001). However, the interactions between fame and reputation still remain in the shadows (Ferris, 2007). Fame has been considered to be a dimension of reputation – ‘being known for something’ (Lange, Lee, & Dai, 2011) that has meaning and value to the particular audience (Carter & Deephouse, 1999; Dollinger, Golden, & Saxton, 1997; Mishina, Block, & Mannor, 2012) – or to be an antecedent of reputation (Boyd et al., 2010; Brooks et al., 2003; Turban, 2001; Turban & Cable, 2003).

This paper explains how fame can be a consequence of reputation held by an organization. In the field of fashion, the Armani company is famous among other cultural industries, such as the movie industry (through dressing movie stars), and fashion-conscious buyers, since launching its revolutionary ‘man jacket’ in the late 1970s (Vogue, 2015). From the early 1980s onwards, business experts increasingly reported the company’s works in The New York Times, The Globe and Mail, the Financial Times and other mass media (Factiva, 2015), contributing to its fame among buyers of fashion goods. However, it could be argued that Armani became famous after its reputation had been established within the fashion community (Kawamura, 2005). So how does reputation influence fame? Is fame one consequence of having a reputation? And how might this unfold in industries where the quality of a product or service is difficult to assess or value, and where issues of fame and reputation assume central importance?

To address these questions, we focus on creative and hard-to-value industries (Priem, 2007) – i.e. creative industries where outsiders, such as art critics, are needed to provide guidance for end-consumers (who may not have the necessary knowledge of, or expertise in, buying or assessing artwork). We develop a theoretical model for fame being a consequence of reputation, and use structural equation modelling (SEM) to test this on French architectural companies. Architecture has been argued to be a creative industry (Alvarez, Mazza, Pedersen Strandgard, & Svejenova, 2005) as it involves elements of art, markets and social approval; organizations conceive and disseminate novel proposals and artefacts that often have aesthetic and symbolic properties. As reputation is highly important and visible in this sector (Becker, 1982; Bowness, 1990; Lang & Lang, 1988) – and guides external actors on whom to talk about, buy from and invest in – architecture is a suitable field in which to observe how reputation may (or may not) nurture fame.

We offer two contributions to the understanding of the relationship between two key social approval assets: reputation and fame. First, our study reveals that reputation is an antecedent of an organization’s fame, and that the latter can be achieved through linking different audience-specific reputations. We therefore provide new theoretical and empirical insights into linking different reputations to fame, suggesting that the relationship between fame and reputation is not simply linear but rather more complex (Boyd et al., 2010; Brooks et al., 2003; Lange et al., 2011; Turban, 2001; Turban & Cable, 2003). Second, we show how experts can transform specific reputations among peers and clients into fame. In the context of creative industries, critics do not necessarily participate in turning little-known avant-gardism or non-conformance into conventionality with a wide appeal in order to make organizations famous (Rindova, Pollock, & Hayward, 2006). Rather, they can ‘decode’ or ‘decrypt’ avant-gardism and innovation for novices, generating a broader understanding of these factors for the general public, so that an organization can become more widely known, and also be able to strike a balance between the simultaneous needs to be avant-garde and to be familiar and sufficiently comprehensible (Caves, 2000; Lampel, Lant, & Shamsie, 2000; Slavich & Castellucci, 2016).

We start by exploring how different types of reputation influence fame. We test these hypotheses on a sample of 103 French architectural companies. Our results reveal the important role of experts in mediating between peer reputation, market reputation and fame.

Theory Development: Perspectives on Fame and Reputation

Fame

We define the sociological concept of fame as the indication of the volume of public discourse about an entity, or the entity’s position on a continuum that has as its end-points being talked about by a small group of people, and being talked about by a broad, general and potentially international audience (Braudy, 1986; Currid-Halkett, 2010; Van de Rijt et al., 2013), i.e. by a very large number of people. Fame literally corresponds to ‘the sum of all people who have heard a person’s name’ (Currid-Halkett, 2010, p. 29), be it in a positive or a negative way. For instance, those who dislike Picasso’s work may contribute to his fame as much as those who admire it.

We argue that the gap between highly famous people and those known only among close circles of friends and family can be preserved through the Matthew effect (Merton, 1968), cumulative media attention, network ties (Meyer & Gamson, 1995), ‘satellite effects’ (i.e. the benefits of being associated with luminaries) and ‘elite connections’ (Lang & Lang, 1988, pp. 95, 97). While ephemeral fame is often limited to a distinct event, organizations’ names become ‘locked into’ people’s minds when an event – or preferably several events related to these organizations – attract the attention of the media and public, who then want to know more about those involved in the event (Van de Rijt et al., 2013).

While the original conceptualization of fame was not dedicated to a particular level of entity (Braudy, 1986), it became progressively centred at the individual level (e.g. Currid-Halkett, 2010; Van de Rijt et al., 2013). We suggest that the concept of fame and its attributes can be transposed to other levels, such as the whole organization. Indeed, one can speak about a famous museum (such as the Met in New York or the Louvre in Paris), a famous company (say, Armani or Chanel) or even a famous event (e.g. the US Super Bowl or the Rio Carnival).

Reputation

Reputation is defined as the ‘stakeholder-specific assessment regarding an organization’s capability to create value based on its characteristics and qualities’ (Mishina et al., 2012, p. 460) among audiences, including the media (e.g. Deephouse, 2000; Rindova, Petkova, & Kotha, 2007), regulators (Deephouse & Carter, 2005; Elsbach, 1994), investors, and advocacy groups (Rao, Morrill, & Zald, 2000), each of which confers a certain type of reputation (Bermiss, Zajac, & King, 2014). Considering reputation as audience-specific echoes the ‘being known for something’ attribute developed by Lange et al. (2011) – rather than the other dimension they present, an overall ‘generalized favourability’ or general esteem, i.e. esteem that does not depend on the view of one distinct audience. Reputation therefore differs from fame in that it is audience-specific (while fame may not be) and that it is based on the appreciation of an organization’s positive attributes (while fame can be both positive and negative) (Dollinger et al., 1997; Mishina et al., 2012).

We define an audience as a group of organizations or individuals that have similar roles, values and characteristics, and that can be referred to by a common name. An audience is characterized by three elements: degree of expertise in assessing members of a domain of activity, similar values, and common media through which to exchange information. Degree of expertise refers to audience-dependent knowledge and experience (in a particular domain of activity) that make the audience members more or less capable of assessing work and people in that domain. A high degree of expertise makes their assessments more credible. The members of such audiences need to share common values and expectations about the behaviours that result in outcomes assessable by the audience (Fombrun, 1996; Pfarrer, Pollock, & Rindova, 2010). Thus, an audience also acts as a community, with dedicated ways of exchanging information and reducing uncertainty (Fombrun & Shanley, 1990) via common monitors such as media – i.e. specialized information intermediaries that convey news about an organization’s actions, influence the audience’s collective mind, and promote closeness among the audience members (Deephouse, 2000). Thus, an organization can be reputed among a small audience (a small group of people who have a certain expertise in the particular activity) and, at the same time, be famous in society at large.

Selection system perspective

While reputation studies have recognized the audience-specific dimension of reputation, this aspect can benefit from more theoretical development. To gain further insights into the key audience types that an organization may have, scholars have drawn on a social approval perspective that echoes stratification systems, namely selection system theory (Wijnberg, 2004; Wijnberg & Gemser, 2000). This theory explains how audiences both assess organizations and select the preferred ones. It also provides insights into how organizations can have multiple reputations, by examining how and by whom value is shaped in competitive processes, particularly in hard-to-value industries (Priem, 2007; Wijnberg & Gemser, 2000). Selection system theory describes competitive processes as being governed by a particular selection system (or a combination of several such systems). Three ‘ideal types’ of audience have been identified: market, peer and expert. Each selection system consists of ‘selectors’ and the ‘selected’. Each selection system is audience-specific, and reputation is built within each audience, especially in the case of hard-to-value industries such as arts, higher education and consultancy, where expertise is required to assess quality. Selection system theory also explains the effects of different types of reputation (Ebbers & Wijnberg, 2011).

Selection system studies provide insights into the competitive process in general, and more specifically into reputational dynamics in hard-to-value creative industries (Boutinot, Ansari, Belkhouja, & Mangematin, 2015; Gemser, Leenders, & Wijnberg, 2008; Wijnberg & Gemser, 2000), where the established system is mostly peer-based or expert-based. This type of system occurs when hard-to-value products or services are potentially unsuited to mass production; and when final consumers need experts’ knowledge and guidance in order to know what to buy, or in order to assess what is of high quality. In line with selection system theory, we segment audiences into peer, market and expert audiences as a theoretical instrument to develop our notion of audience-specific reputations in creative industries. However, we slightly adapt the profiles – or the target publics – of market and expert audiences. This is because, in certain expert-based contexts – such as architecture, advertising, design and fashion (especially haute couture) – the associated publics might differ. In architecture, for instance, experts deal with members of the general public who appreciate the creative good but do not necessarily buy it (i.e. individual people who may reside in, observe or visit a building). The market audience includes purchasers (clients) such as public authorities and private companies (which buy creative goods for business or societal purposes – headquarters buildings, offices, libraries etc.).

Drawing on previous studies that consider reputation to have audience-specific forms (Boutinot et al., 2015; Carter & Deephouse, 1999; Dollinger et al., 1997; Mishina et al., 2012), we argue that one kind of audience confers one kind of reputation, and that an organization in creative industries can have – and combine – three reputations: peer, market and expert.

Peer, market and expert reputations in hard-to-value creative industries

In hard-to-value creative industries, peer reputation corresponds to fellow producers’ assessment of an actor’s capability to create value, based not only on integrity, creativity, differentiation and merit (Becker, 1982; Delmestri, Montanari, & Usai, 2005; Florida, 2002; Jones, Anand, & Alvarez, 2005) through artistic outputs (Lang & Lang, 1988), but also on factors such as craft, vision and authenticity. For instance, before Impressionism, the valuation of paintings was a peer-based system composed of established artists who selected new artists’ works (Wijnberg & Gemser, 2000).

Market reputation refers to the more commercial side of reputation, corresponding to purchasers’ assessment of an actor’s capability to create value for their projects (business-related, societal etc.). For instance, in the advertising field, market reputation is defined as positive perceptions of quality and creativity. As such, market reputation is based on trustworthiness – organizations must show their ability to deliver what they promised (Mayer, Davis, & Schoorman, 1995), or at least to meet the minimum quality expected.

Finally, expert reputation is conferred not by fellow producers or clients, but by third parties whose opinions are important in determining who is successful. Here, expert reputation refers to the expert-specific assessment of an actor’s capability to create value by contributing to knowledge, culture and society in general. Experts use various media, including mass media, to decode and express their own views on something or someone. For example, in the fashion industry, critics who write about the introduction of a new Chanel collection can be considered experts. Experts make critique and commentary their main vocation – if not a full-time occupation (Wijnberg & Gemser, 2000) – and disseminate knowledge about a hard-to-value product, service or organization. They are generally attracted to products and services both in line with their cognitive references, and their search for novelty and avant-gardism (Slavich & Castellucci, 2016).

Relationships between expert, peer and market reputations in hard-to-value creative industries

There is empirical evidence that reputational spillovers exist at the level of an organization. Boutinot et al. (2015) suggest that one organization has and combines several mutually influenced reputations over time. Building on this idea and on research about creative sectors (e.g. Bowness, 1990; Galenson, 2005; Wijnberg & Gemser, 2000), we consider that peer and market reputations are generally established before – and positively influence – expert reputation, even in the case of an expert-based system. For example, Bowness (1990), in his study of modern painters, argued that critics cannot be aware of actors who have never sold anything and so have never received any financial support from clients. Thus, reputation among cultural elites is often based on concrete proof of achievement that has previously been provided to clients. Likewise, Galenson (2005) suggested that peers’ opinions can positively affect the opinions of experts – an actor who is highly reputed among peers is more likely than one less reputed to be promoted and remembered by a broader public. Experts seem to mediate peer reputation and to make it available to the wider public.

Following the findings from studies of creative industries (Becker, 1982; Bowness, 1990; Heinich, 1991; Lang & Lang, 1988) and of hard-to-value industries (Priem, 2007), we argue that reputation is achieved before fame in such industries. Indeed, in such sectors, if fame is achieved first, there is a high risk of being famous for only a very short time, or of lacking peer acceptance: ‘The immediacy of success is credible only if combined with a small circle of expert insiders …, while the spread of recognition among society is only credible through the mediation of time’ (Heinich, 1991, p. 215).

We develop and test several relationships between reputation and fame by identifying some reputation types that might influence fame in hard-to-value creative sectors. Detailing this will: (1) reduce some of the complexity of the fame antecedents; and (2) contribute to a refined understanding of the relationships between reputation and fame in creative sectors, and more generally in hard-to-value industries. The specific question we ask is: can fame be explained by an organization’s extant reputation in hard-to-value creative sectors? Does fame have reputational antecedents?

Hypotheses development

We have identified expert reputation as a mediating variable in the relationship between peer reputation, market reputation and fame in hard-to-value creative industries. As previously noted, this is because expert reputation seems to be positively determined by peer and market reputations, and even by fame in society at large. Indeed, experts can speak to the wider public. Their expertise is to translate specialized knowledge, creativity or events into language that makes them understandable to a non-specialized audience. This influence of experts can be potentially complementary to the role of certification (Graffin & Ward, 2010) and other third-party endorsements of quality (Rao, 1994). In contrast, market reputation is less likely to mediate between peer reputation, expert reputation and fame, as clients may not themselves diffuse information on their purchase of artwork. Rather, they rely on critics to communicate such information to the public (Heinich, 1991, 2004). Thus, we argue that the expert audience counts on the knowledge flow between organizations, clients and the public. Experts are capable of understanding the works, and of both promoting and translating them to make them accessible to the wider public. Thus, expert reputation can act as a mediator between reputations within specific audiences (market and peer) and fame. Mediation is understood here as the relationship between an independent and a dependent variable. This relationship can be broken down into two causal paths (MacKinnon, Krull, & Lockwood, 2000).

Expert reputation as a mediator between peer reputation and fame

Expert reputation reflects an assessment by experts of an actor’s capability to create value. It has often been considered as important for hard-to-value creative industries to gain greater recognition (Bowness, 1990; Heinich, 1991). The highest expert reputation occurs when most of an actor’s outputs attract regular and positive attention from the cultural elite. To an extent, in creative hard-to-value industries, peer reputation can lead to an actor being talked about by a certain number of people. Some studies on visual arts note that wide recognition comes when such actors are highly reputed among peers and when their works are relayed by the mass media (Lang & Lang, 1988). In the same vein, Bowness (1990) argues that actors need the acceptance of their circle of peers to achieve success among the public. Famous actors will often have gained a reputation among their peers before becoming known to the wider public.

However, the way actors are connected to society at large needs some clarification. Indeed, there is a big difference between how actors’ works are assessed by those working in leading-edge avant-gardism and by members of the general public, who have neither easy access to the works nor the expertise to assess them. For instance, Heinich’s study on Van Gogh’s journey to fame (Heinich, 1991) explains the difficulty of actors in communicating their art to ‘outsiders’, due to the latter’s incomprehension and the actors’ inability to find the ‘right vocabulary’. However, because other creative organizations (peers) may not be able to communicate easily about a particular organization with society at large (due to differences in expectations and a lack of common assessment criteria), we argue that peer reputation is not a direct determinant of fame in creative sectors.

Nevertheless, peer reputation can still be an indirect determinant of fame through the mediation of expert reputation. As previously noted, we consider peer reputation to be a positive determinant of expert reputation, which may itself positively influence fame. The role of cultural experts is to promote works of art and culture to society at large, and to ‘decode’ (understand and then explain) highly complex, cutting-edge and avant-garde work for broader audiences. As Mike Kelly, an American artist, explained in 2003: ‘As the story goes, the artist is uneducated but has a kind of innate gift for visual expression, which the educated and socialized critic must decode for the general population’ (Searle, 2012). Bowness’s (1990) model notes a close connection between the cultural elite and society. The elite promotes artworks to non-experts by analysing and explaining these works. These arguments yield our first hypothesis:

H1 – Expert reputation plays a mediating role between peer reputation and fame.

Expert reputation as a mediator between market reputation and fame

Market reputation is at its highest when actors achieve regular commercial success (Delmestri et al., 2005). It could be argued that fame in creative industries can be determined by market reputation. Indeed, some studies suggest that actors gain wide recognition and ‘superstar’ status after they have achieved reputation and commercial success among their clients (Lang & Lang, 1988). Bowness (1990) also argues that actors need the acceptance of clients before they can be known and talked about by the general public. Thus, famous actors may have to be already reputed among clients – especially those in business – before achieving fame.

But this relationship needs clarification, especially where the client audience is different from the general public. In such cases, the relationship is more like a business-to-business connection – as when, for instance, painters sell to art galleries (Galenson, 2005), and when architectural companies sell to state authorities or corporate clients (Boutinot, 2011). Actors who have reputations among such clients may still not necessarily be superstars, as those clients may not broadcast that they have, for example, bought particular artworks or engaged specific architectural companies. Another audience is thus needed to publicize such information to society at large. For example, in the case of visual arts, clients do not need artists’ peers – who may lack the ‘right vocabulary’ to explain their art to the wider public (Heinich, 1991) – but rather experts to act as mediators, and to promote the fact that the clients have bought such works and why they have done so, especially in the case of works by lesser-known artists (Galenson, 2005). Clients may not be able to communicate easily with society at large without such mediation. Thus, we argue that market reputation is not a direct determinant of fame in creative sectors, but that it can be a determinant via the mediation of expert reputation. We thus hypothesize as follows:

H2 – Expert reputation plays a mediating role between market reputation and fame.

Figure 1 presents an overview of our model, and shows how expert reputation may play a mediating role between peer/market reputations and fame in creative sectors.

Figure 1.

Theoretical model: Expert reputation as a mediator for a high level of fame.

Method

Sample, data collection and variables

We chose to investigate our hypotheses empirically in French architecture, a hard-to-value creative industry. With architectural companies vying to create and construct buildings around the world – and with peers, consumers and critics being audiences that confer reputation on them (Florida, 2002) – the world of architecture can also be considered to be a competitive arena that justifies the use of a selection system approach (Mol & Wijnberg, 2011). To avoid cross-cultural issues, we restricted our study population to French (rather than European or international) architectural practices. Although international (or at least European) rules exist to regulate architectural activity at a broader level, there is still some local specificity in terms of norms, issues and professional regulations. Owned by people with various backgrounds, architectural companies strike a balance between creative work and commercial constraints (Pinnington & Morris, 2002). Their work consists of suggesting solutions to societal projects by designing new buildings. Some companies promote artistic and creative works, echoing the search for distinctiveness in creative industries (Gemser & Wijnberg, 2001). The choice of companies for new projects is regulated by architectural competitions (competitive mechanisms designed to facilitate the selection of a company to design a building) that are commissioned by a state authority, or by a corporate or individual client. Such competitions can be open (meaning that any company can participate by submitting a design proposal) or restricted (meaning that the contracting client invites companies – generally four to six – to participate, based on criteria such as their previous building designs and their reputation).

According to the French National Council of the Order of Architects (Conseil National de l’Ordre des Architectes), there were 7500 architectural companies in France in 2009. We developed a theoretical sample rather than a random one, to fit better with the objectives of our study. This sample was based on three criteria: authorship, number of years of operation (so as to trace their activity, reputation and fame), and availability of information on companies.

The first selection criterion concerned the issue of authorship. Indeed, in order to be able to trace companies’ reputations and fame, and to capture the context of creative industries and what is highly valued in such domains (i.e. creation and novelty), we needed to be able to trace companies that devoted attention to avant-gardism in the concepts and forms presented in their buildings. To do this, the notion of authorship seemed crucial to us. Authorship refers to a company’s claim that it – and a fortiori its founder – created a building and made it distinctive. In line with another important attribute of creative industries, and considering that the organizational and individual levels empirically co-exist, and that the creativeness, avant-gardism and distinctive nature of artworks cannot be detached from those of the founder, we developed an approximation for authorship – the inclusion of the founder’s name in the company name. By doing this, we studied only architectural companies that value avant-gardism through their founders, and not those that produce low-budget, purely functional buildings. When we did this, the number of companies on the list dropped from 7500 to under 2000.

Second, we focused on companies’ trajectories, so as to be able to trace their activity, fame and reputation. Thus, we checked when these companies were created and when their founders were born. We needed over 10 years of activity to be able to trace their trajectories adequately. This reduced the number of companies to under 1000.

The last criterion focused on the information available about these companies. Many architectural companies provide little information about themselves and their work, and this was especially so before the late 1990s. Therefore, our sample dropped to 103 architectural companies on which all the information needed was available over the period studied. This sample seemed relevant to study our research question and to test our theoretical model.

We collected archival data about our sample architectural companies, in line with our research question and the hypotheses we developed. To understand the relationships between the various reputation types and fame, we developed a list of variables associated with the potential theoretical antecedents of reputation and fame. We collected such data from company websites, curricula vitae and books; websites about architecture; and the French architectural press and popular press going back to 1975. Architectural companies’ websites and dedicated books were particularly useful in providing information about the age of companies; non-invitation-based competitions won; market reputation (invitation-based competitions won); awards; networks; books authored; and founder’s education, age and gender. The French architectural press and the mass press were used to obtain information about peer and expert reputation, respectively. When information was missing on one or several of these points, we located it by using additional sources, such as books about architecture. We created a database from scratch, logging every aspect of each company’s existence between its creation and the end of 2008. To test our hypotheses, we aggregated our data for each variable in order to have a general picture of the activity of each company at the end of 2008.

Previous studies have argued that media coverage provides a lens through which to study the reputation-building process (Boutinot et al., 2015; Rindova et al., 2007). Indeed, journalists inform their audiences about the value and effectiveness of firms and their leaders (Pollock & Rindova, 2003). Thus, media dedicated to a particular audience (such as professional architectural journals) can reflect what is seen as valuable in that audience’s eyes (Carter & Deephouse, 1999). As we were aware from our archival study that these articles might not cover all the relevant information, we followed previous approaches to the study of reputation (Boutinot et al., 2015; Rindova et al., 2007) and fame (Ferris, 2007; Van de Rijt et al., 2013) by drawing on media coverage to develop the variables necessary to understand how the several kinds of reputation and fame might be connected or not.

We conceptualize fame in architecture as an architectural company’s position on a continuum from being talked about by a few people to being talked about by the wider public. We adopted the number of Google tags as a measure of the relative fame of each of our sample organizations. We offer three reasons to justify this step. First, in line with the definition of fame, the number of Google tags can be considered as a measure of how much companies are talked about, on a continuum from very few tags (suggesting they are little known) to a huge number of tags (suggesting they may enjoy international public acclaim). Second, the Internet represents the broadest access to information in any given domain of activity, as even non-experts can find out about architectural companies there. Third, Google reflects either negative or positive opinions about French architectural companies. We therefore measured the number of Google tags in January 2009 to see how often and how widely the 103 architectural companies were cited.

Measuring fame in this way creates various biases that must be acknowledged. First, the number of Google tags can be influenced by commercial strategies (adopted by people wanting to improve their number of tags or followers) and can be subject to considerable daily fluctuations. Second, the sources of information in Google are heterogeneous and sometimes barely traceable. For instance, companies in our sample were discussed on Wikipedia, websites dedicated to stars, and personal blogs. We argue that this reveals the ‘people talk a lot about’ component of fame. Finally, Google tags may mention companies from our sample, but may also refer to other organizations or people of the same name. To reduce the risk of counting tags about other companies, we entered the architectural companies’ names in quotes, and added the word ‘architecture’.

Our dependent variable does not reflect whether the companies were successful or indeed survived over time. Rather, it highlights companies that enjoyed a reasonable level of fame (with at least 112 Google tags) or had superstar status (reaching more than 50,000 Google tags) in 2009, reflecting the continuum associated with the definition of the term.

To measure the three types of audience-specific reputations, we did not simply adopt the indicators developed in previous studies dedicated to reputation or to creative industries (e.g. Anand & Watson, 2004; Ebbers & Wijnberg, 2011; Gemser et al., 2008). For instance, drawing on the performing arts industry, such as the field of ballet, peer reputation is often related to peer-attributed awards; market reputation to ticket sales; and expert reputation to critics’ or ballet-goers’ reviews. But architecture has no similar rankings of organizations or of their buildings, and awards tend to be made by multidisciplinary committees (and thus cannot be attributed to one specific audience); e.g. the Pritzker Prize is awarded by a set of ‘recognized professionals in their own fields of architecture, business, education, publishing and culture’ (Pritzker Prize website, 2015). We therefore used architecture-specific indicators to measure reputation (Boutinot et al., 2015).

Expert reputation

This is the mediating endogenous variable in our model. It corresponds to the assessment by critics or experts of an organization’s capability to create value for society. According to selection system theory, these actors may be neither architectural companies nor their clients, and may have only indirect links to architecture, based on their voluntary interest in this domain, for instance, by studying it (e.g. cultural journalists or sociologists). Experts have their own way of framing their arguments and visions about people and things, and use media such as The New Yorker and The Washington Post to express themselves. In collecting our data, we drew on the argument that the media inform their audience about what is valuable, and about which organizations are well-known for providing something avant-garde and useful for society. Thus, we measured expert reputation by the number of times each architectural company’s name appeared in the top five French cultural periodicals (Le Monde, Les Echos, Le Point, Libération and Télérama) between the year of their creation and the end of 2007 (rather than 2008, so as to be able to trace the impact of reputation on fame). We selected these printed sources as they: (1) had the highest number of readers for 2009–2010 (excluding those sources that did not have a column on architecture); (2) were not too politically orientated; and (3) were traceable over time and accessible. Almost no article unfavourable to our sample companies was found in such publications. These publications tend to dedicate their time and column inches to controversial and interesting topics, rather than to writing negatively about architecture. Either these cultural periodicals did not have websites at that time, or their Internet platforms and print magazines covered different topics (in the case of Télérama, for example). Thus, we felt fairly confident that the Google tags did not cover the same elements as the dedicated architectural press or as the cultural sections of periodicals that we used as indicators for the various audience-specific reputations.

For peer and market reputations, we followed the same reasoning as for expert reputation.

Peer reputation

This refers to architectural companies’ assessment of another architectural company’s capability to create value for architecture. To operationalize peer reputation in French architecture, we counted the number of times each architectural company in our sample was mentioned in the top five architectural journals (Le Moniteur, Technique et Architecture, L’Architecture d’Aujourd’hui, D’A and Architecture Créé) between the year of creation and the end of 2005 (rather than 2008, so as to be able to trace the impact of this reputation on both expert reputation and fame).

To select these architectural journals, we could not follow any readership ranking, as such data are not available for the time period studied in France for this profession. Therefore, we: (1) selected the print journals that were included in one of the very few studies of architectural journals in France, which was set up in 2007 and ranks 20 architectural journals in terms of preference among 390 French architectural companies; and (2) kept only those journals that were traceable over time and for which we could access the entire set of articles. It turned out that these journals are always listed by architectural companies on their websites, which fits with considering these publications as the top ones for the profession. Contributors to such journals are often past or practising architects themselves (e.g. Jacques-Franck Degioanni is a regular contributor to Le Moniteur), so that (as in academic journals) peers talk to peers, and the choice of whom to talk about reflects the recognition element of reputation.

Also, since the content of magazine articles is about high-quality projects, such contributions serve to recognize the quality of the selected companies’ outputs. The very few negative references deal with lawsuits and potential construction problems, news of which is not frequently relayed by peers, whose interest tends to lie in relevant and innovative projects from other companies. One article from 2003, for example, is entitled: ‘Innovative concrete: Time for architectural audacity’. Architectural journalists can thus be seen as selectors of the architectural companies’ audience, and even non-architectural contributors can be considered as ‘apparent selectors’ (Ebbers & Wijnberg, 2011, p. 375). Given that the journals concerned are dedicated to architecture, they ‘have an ability to correctly guess or predict the preferences of the party the selectors represent’ (Ebbers & Wijnberg, 2011, p. 375).

Market reputation

In French architecture, this refers to the specific assessment by clients of an architectural company’s ability to create value for the city (or, in the case of state authorities, for governments, cities etc.) or for their own businesses (in the case of private companies). Drawing on the conceptualization of the market selection system (operationalized in the movie industry, for instance, as the number of tickets sold) (e.g. Ebbers & Wijnberg, 2011; Gemser et al., 2008), we measured market reputation by the number of architectural contests that our sample companies had been invited to enter and had won between their creation and the end of 2005 (not 2008, for the reason noted above). Architectural companies are invited to enter contests because the clients organizing them have already heard their names in relation to previous works, and because they are judged to be more relevant to the clients’ projects than are their peers. It is important for architectural companies that are invited to enter competitions to try their best to win, so as to be known for their building projects. Architectural companies that have won such by-invitation competitions appear able to provide value to clients (in terms of, say, helping a city or a private company to have a good image), based on their ability to understand the clients’ needs.

Finally, a range of control variables was selected following a close look at the literature on the antecedents of reputation and fame corresponding to trajectory statistics for each company (e.g. Galenson, 2005; Graffin & Ward, 2010; Lang & Lang, 1988). All variables were measured between the years in which our sample companies were created and 2005.

National architectural contests won

Regular performance and quality markers are key antecedents of reputation. To control for architectural companies’ general performance, we counted all the architectural contests won by each company in our sample, other than those that were invitation-based.

Books written

As in the case of contests, books in which founders of our sample companies expound their views on their craft can be considered as creative outputs that can influence reputation. We measured this variable as the number of books that each founder had written.

Networks

Drawing on the importance of networks and the role of third parties in reputation building (Daskalaki, 2001; Montanari, Scapolan, & Gianecchini, 2016; Rindova, Williamson, Petkova, & Sever, 2005), we argue that collaborations with other professionals and clients can impact on architectural companies’ reputations and fame. We measured the professional network variable via a dichotomous approach, scoring 1 if the company had collaborated more than once with other companies from our sample and 0 otherwise. We measured the commercial network variable as a count of the number of repeated collaborations with the same clients (because commercial networks were more common than collaborations with architectural companies, and therefore enabled a count method).

School/educational background

The prestige of the school where founders of our sample companies were trained may influence perceptions of their ability to deliver. Since no classification existed, we split the 23 architectural schools in France into three categories. The most prestigious schools scored 3 (the Ecole Nationale Supérieure des Beaux-Arts de Paris and the Ecole Spéciale d’Architecture); the middle-ranking schools (the other Parisian schools) scored 2; and the rest (the regional schools) scored 1. We validated this measure with architectural companies from our sample.

Awards

These could be considered as potential antecedents for reputation. Sample architectural companies scored 1 if they had won at least one French or international award (e.g. the Equerre d’Argent or the Pritzker Prize), and 0 if they had not.

Age

As both the organizational and individual levels can have an impact on reputation and fame in creative industries (Godart, Maddux, Shipilov, & Galinsky, 2015), we controlled for both the company’s age and the founder’s age in each case. Company age was operationalized as the number of years each sample company had existed, between its year of creation and 2005. Founder age, measured by the number of years between the person’s birth date and 2005, was related to the fact that the organizational level is highly connected to the individual level in creative industries (Godart et al., 2015). Also, the Matthew effect (Merton, 1968) and the ‘winner-takes-all society’ effect (Frank & Cook, 1995) are prominent in architecture. The more experience and success that founder architects accumulate over time, the more successful they are likely to be in the future.

Gender

Continuing with the idea of the individual level potentially impacting reputation and fame at the organizational level, we controlled for the founders’ gender in our sample companies. This is relevant to reputation in the male-dominated field of French architecture. The gender of the founder architects was operationalized as 0 for men and 1 for women.

Data analysis

SEM analyses were used to test hypotheses about the structural relationships of our proposed model. SEM is capable of modelling multivariate relations, and estimating mediating effects in the relationship between peer/market reputations and fame.

Following the recommendation of Lei and Wu (2015), we estimated the model using the robust maximum likelihood estimator (known as MLR) available in the lavaan R package. The MLR approach uses Skinner’s (1989) pseudo maximum likelihood method, along with robust standard errors (the Huber–White procedure) and adjustment similar to that of Satorra and Bentler (1988), to deal with the relatively small sample size and to relax the multivariate normality assumption.

Our theoretical model predicts that expert reputation mediates the relationship between peer reputation, market reputation and fame. Our data analysis fits with our theoretical approach, as we followed Preacher and Hayes’ (2004) recommendation on using the simultaneous estimation method to avoid potential bias due to independent estimation, and Hayes’ guidelines (2013) to test statistically indirect effects in mediation rather than step-wise procedures (e.g. Baron & Kenny, 1986). We tested a path model that specified indirect effects of reputations on fame through expert reputation while simultaneously taking into account direct effects. Following Preacher and Hayes (2004), and Hayes (2013), the effects and confidence interval of the direct, indirect and total effects were obtained using a parametric bootstrap procedure. Control variables were included with fixed effects on expert reputation and fame, as suggested by the procedures.

Results

Correlation analysis provides an initial examination of the hypotheses linking the three reputations and fame (see Table 1). All three reputations are significantly and positively correlated with fame, and peer and market reputations are related to expert reputation.

Table 1.

Correlations between the variables.

		Mean	SD	Fame	Expert reputation	Market reputation	Peer reputation	Books written	Professional network	Competitions won	School (1)	School (2)	School (3)	Founder’s age	Awards	Company’s age	Gender	Commercial network
		Mean	SD	(1)	(2)	(3)	(4)	(5)	(6)	(7)	(8)	(9)	(10)	(11)	(12)	(13)	(14)	(15)
(1)	Fame	72.80	120.66	1.00
(2)	Expert Reputation	20.66	28.22	0.48***	1.00
(3)	Market Reputation	5.37	7.45	0.24*	0.50***	1.00
(4)	Peer Reputation	50.33	38.92	0.35***	0.72***	0.41***	1.00
(5)	Books written	2.47	6.19	0.28**	0.21*	−0.05	0.14	1.00
(6)	Professional network	0.53	0.50	0.28**	0.23*	0.18	0.26**	0.22*	1.00
(7)	Won competitions	21.81	19.24	0.04	0.31**	0.75***	0.39***	−0.11	0.16	1.00
(8)	School (1)	0.22	0.42	−0.15	−0.10	−0.25*	−0.01	−0.06	−0.15	−0.11	1.00
(9)	School (2)	0.51	0.50	−0.09	−0.25*	−0.11	−0.23*	−0.12	−0.05	−0.15	−0.55***	1.00
(10)	School (3)	0.26	0.44	0.24*	0.38***	0.36***	0.27**	0.20*	0.20*	0.27**	−0.32***	−0.61***	1.00
(11)	Founder’s age	56.90	10.89	0.21*	0.27**	0.37***	0.38***	0.27**	0.41***	0.44***	−0.26**	−0.38***	0.68***	1.00
(12)	Awards	0.77	0.92	0.05	0.31**	0.04	0.38***	−0.05	−0.20*	0.00	0.06	−0.08	0.03	−0.01	1.00
(13)	Company’s age	21.95	9.54	0.09	0.25*	0.34***	0.28**	0.02	0.16	0.45***	−0.06	−0.21*	0.29**	0.54***	0.09	1.00
(14)	Gender	0.23	0.42	−0.20*	−0.22*	−0.24*	−0.25*	−0.13	−0.31**	−0.22*	0.09	0.21*	−0.33***	−0.46***	0.01	−0.25*	1.00
(15)	Commercial network	3.77	7.83	0.22*	0.28**	0.29**	0.26**	0.11	0.33***	0.17	−0.05	−0.14	0.20*	0.39***	−0.04	0.16	−0.26**	1

N = 103; *p < 0.1; **p < 0.05; ***p < 0.01.

SD: standard deviation.

Multicollinearity between our control variables is not an issue, given the variance inflation factor, tolerance and condition index values we obtained (see Appendix 1).

In order to detail the mediating effects of expert reputation between peer reputation, market reputation and fame, and to choose the most appropriate mediation model, we built and estimated separate models to compare and test the results. The complete-mediation model (with only indirect effects) and the no-mediation model (with only direct effects) were compared to the partial-mediation model (with both direct and indirect effects of the peer and market reputations) and to the mixed-forms-of-mediating model (with all combinations of complete mediation, partial mediation and non-mediated effects).

Although the χ² difference tests are presented to compare the different models to the saturated partial-mediation model, they are potentially biased when using a small sample. To compare the goodness-of-fit of the models, we adopted the Aikaike information criterion (AIC); the Bayesian information criterion (BIC); and the AICc (consistent AIC), which performs better than the AIC when the sample size is small (West, Taylor, & Wu, 2015). The AICc is not a hypothesis test and does not refer to a significance indicator such as the p-value. As for the AIC and BIC, a lower AICc means that a model has a better fit. The difference measured by the ΔAICc compares models to the lowest AICc model. Burnham and Anderson (2002) suggest, as a rule of thumb, that a value of ΔAICc of less than 2 indicates substantial evidence for the model, and a greater value of ΔAICc indicates a model that is less well supported or even unlikely (ΔAICc > 10). The AICc was calculated using the aictab.lavaan functions in the lavaan package. Comparisons of structural models are presented in Table 2.

Table 2.

Structural model comparisons.

Structural models	AICc	AICc diff	AIC	BIC	Chisq	Chisq diff	DF diff	P-val.
M1: Complete mediation	8017.83	0	8006.43	8072.29	133.63	3.66	2	0.160
M2: Partial med. clients and complete med. peers	8019.39	1.56	8006.74	8075.25	130.59	0.62	1	0.431
M3: Partial med. peers and complete med. clients	8020.93	3.09	8008.26	8076.78	133.73	3.76	1	0.051
M4: Partial mediation	8022.42	4.59	8008.45	8079.59	129.97	0	−	−
M5: No med. clients and complete med. peers	8028.25	10.41	8016.84	8082.71	135.88	5.91	2	0.052
M6: No med. clients and partial med. peers	8031.19	13.36	8018.54	8087.04	133.28	3.31	1	0.068
M7: No med. peers and complete med. client	8064.27	46.44	8052.87	8118.73	182.84	52.87	2	<0.01
M8: No med. peers and partial med. client	8065.69	47.85	8053.04	8121.54	164.23	34.26	1	<0.01
M9: No mediation	8077.77	59.94	8067.53	8130.76	155.48	25.51	3	<0.01

N = 103.

AIC: Akaike information criterion; BIC: Bayesian information criterion; AICc: consistent Akaike information criterion. Lower AIC, BIC and AICc values reflect the better-fitting model. The AICc compares the models to the complete-mediation model reference. The χ² diff test compares the models to the saturated partial-mediation model. The χ² diff test is presented even though it is potentially biased when using a small sample. We therefore chose the AICc to compare our models. ΔAICc < 2 suggests substantial evidence for the model.

First, the difference between the no-mediation model (M9) and the complete-mediation model (M1) is significant (ΔAICc = 59.94, Δ χ² = 65.081, df = 3, p < 0.01), indicating that omitting the mediating role of expert reputation causes the complete-mediation model to deteriorate significantly. Second, two mixed (complete/partial) forms of mediating effects of expert reputation are tested, in which one of the peer and market reputations is complete when the other is partial. These models (M2 and M3) show a poorer fit compared to the complete-mediation model, and a better fit compared to the partial-mediation model. Third, four mixed forms are constituted of one mediated effect with a non-mediated effect of peer and market reputations. These models (M5, M6, M7 and M8) show poorer fit than the complete- and partial-mediation models. As a consequence, the absence of mediation through expert reputation for the peer and market reputations simultaneously is not supported by the data. Based on the lowest AICc, AIC and BIC values, the complete-mediation model (M1) seems to fit better with the data, with the fewest estimated parameters. Following the usual indicators, but potentially biased by our small sample, this model fits the data reasonably (χ²(78) = 133.63, CFI = 0.985, RMSEA = 0.089, SRMR = 0.006, GFI = 0.99).

Figure 2 provides the final results for the complete-mediation model. It shows the standardized estimated path coefficients and reports the R² measures for the four variables.

Figure 2.

Results of complete-mediation structural model.

Expert reputation appears to be a complete mediator between peer reputation and fame, confirming H1 and H2. Regarding H1, peer reputation is significantly and positively connected to expert reputation (β = .58; p < .001), which is itself also significantly and positively connected to being famous (β = .46; p < .001). Regarding H2, market reputation is significantly and positively related to expert reputation (β = .33; p < .05), while expert reputation, as previously mentioned, is also significantly and positively connected to fame. Path coefficients give information on the mediated effect of peer reputation and market reputation on fame, through expert reputation. In the complete-mediation model (M1), our results showed a positive total effect of peer reputation (tot.effect = .82, p < .01, 95% CI = [0.368, 1.269]) and of market reputation (tot.effect = 2.478, p < .05, 95% CI = [0.059, 4.898]) (see Appendix 2).

This complete-mediation relationship is influenced by several variables, as mentioned in our ‘Method’ section. Regarding fame, books written by our sample companies (β = .13; p < .1) are seen as credible signals and form the basis of organizational performance. Members of the public can buy these books if they are interested in architectural companies they have heard about from experts, and so participate in the accumulation of fame. In contrast, competitions won (β = −.14; p < .1) have a negative impact on the public at large. This counter-intuitive result can be explained by the fact that constructing too many buildings may be seen as questionable by the public. Indeed, people are educated by experts on companies’ avant-gardism, but might believe that the companies cannot be that innovative if they build in excess. In other words, if members of the public see companies winning too many competitions, this may appear to contradict what experts have told them. Regarding expert reputation, our model reveals that this reputation is positively influenced by books having been written by our sample companies (β = .15; p < .05), and by the founders having attended the most prestigious schools (β = .29; p < .01). Conversely, our model suggests that expert reputation is negatively influenced by founders’ age (β = −.36; p < .01), which shows that older founder architects are less associated with innovative and avant-garde signals than are younger ones.

Taken together, the three reputation types in the complete-mediation model explain 33% of the total variance in fame. While this implies that there may be other variables – not integrated into our model – that also impact on fame, or that the latter is self-reinforced (Van de Rijt et al., 2013), our findings indicate a close connection between reputation and fame.

To summarize, our results support our theoretical argument that expert reputation is a mediator operating between peer/market reputations and fame in the French architectural context. Experts decode, translate and interpret peer and market reputations in order to make them accessible and more comprehensible to the wider public.

Discussion and Implications

Our study contributes to the literature on reputation and fame in two ways.

Experts as sustainable ‘fame-makers’

First, our analysis confirms the role of experts in fame, and reveals some of its reputational premises. It is, of course, unlikely that experts can build fame from scratch. Reputation is one major factor of the fame status, even if it can ‘serve to strengthen reputational snowballs’ (Cowen, 2000, p. 15). Experts mediate peer and/or market reputations by choosing and decoding – on behalf of the public – evidence that has been positively assessed by peers or clients and has ‘stood the test of time’ (Becker, 1982, p. 365). By disseminating such positive assessments, experts (such as critics or analysts) can influence fame for the given actors, and even fuel (or at least help) them in their search to strike a balance between novelty and familiarity (Slavich & Castellucci, 2016). Experts may thus play a role similar to that of certification bodies in signalling quality (Graffin & Ward, 2010). However, experts need to be credible with the public in order to mediate audience-specific reputations.

More generally, our analysis complements previous arguments asserting that fame is an antecedent of reputation (Boyd et al., 2010; Brooks et al., 2003; Turban, 2001; Turban & Cable, 2003), with reputation often being treated as a single attribute. Our results pose questions for Bitektine’s theoretical scaffolding (2011) of the ideal-type sequence form of judgement, in which evaluators first develop category-based judgements (a classification around familiarity and inductive categories of organizations), and then turn to feature-based judgements (requiring more scrutiny of organizational performance or outcomes). Our study suggests a different process of judgement formation in creative hard-to-value industries. An ideal-type sequence presents broader familiarity (fame) as an antecedent of reputation. However, in creative hard-to-value industries, fame might come after reputation, because quality can be difficult to assess or judge in these industries. Prior expertise is required about a given organization’s outcomes and performance to reach broader familiarity (fame).

In addition, in such industries, judgement would depend on the level of expertise of the particular audience. In the case of architecture, people at large do not necessarily have enough knowledge to assess an architectural company and its works accurately. In order to form their opinion about a given company, they are likely to need feature-based judgements elaborated by experts. Thus, category-based judgements may come after – as opposed to before – judgement formation, as Bitektine (2011) suggested. Likewise, experts tend already to know an architectural company’s performance and other characteristics. They may thus develop a judgement about it without any available category-based judgements.

In hard-to-value creative industries, fame needs the mediation of expert reputation before it can actually be a consequence of peer and market reputations. Our findings suggest that the fame–reputation relationship is not a one-way linear process. If fame can be considered a driver for reputation (Boyd et al., 2010; Brooks et al., 2003; Turban, 2001; Turban & Cable, 2003), the reverse may also hold true, particularly when reputation is considered to be a multi-faceted construct.

Peer- and market-specific assessments ‘decoded’ by experts for the public

The second contribution deals with experts providing a level of guidance to final customers, or to the public – i.e. those who may be novices (Priem, 2007; Wijnberg & Gemser, 2000) – to help them evaluate the quality of the work. Experts’ instrumental use of the media is one important way to make peer and market reputations accessible and available to the public. Organizations can then gain recognition for their specialized competences, as assessed by peers or the market. Experts’ promotion and explanation of specialized works and achievements highlight the role of ‘talent validation’ in fame.

As our results suggest, mediation is complete for both peers and the market. Regarding the latter, complete mediation suggests that experts help the promotion of what is already valued by the market. This indicates a possible lack of communication between those who pay for buildings and those who use them or live in them. Experts provide a clearer connection between these two categories of the public. We suggest that it is the experts who act as translators between the clients who commission buildings and their users – employees, inhabitants etc. – who are part of the larger societal audience.

Meanwhile, peer reputation may be completely mediated by experts. Experts bridge two different worlds: the public and ‘insiders’ (specialist audiences). It is therefore important to understand the process of decoding and translation. In creative industries, avant-gardism may not be enough to be famous (Boorstin, 1961; Cowen, 2000). Differentiation, innovation and creativity do not ‘speak’ for themselves. Artistic works may remain obscure among members of society at large, who do not have the vocabulary, knowledge or skills to understand, appreciate or value them fully. Experts select works or actors that have stood ‘the test of time’ (Becker, 1982, p. 365), and that then need to be translated and explained for a broader audience. For example, at exhibitions, catalogues may play the role of experts. As such, experts need not only to be credible and legitimate, but also to be able to speak the language of both specialized and general audiences. It is for this reason that experts can be considered to be part of the mass media. As specialized journalists or consultants, they may be closely related to the producers – whether artists, business schools or public service organizations. As journalists, they write for and speak to the public at large, emphasizing the distinctiveness of the organization. The general public is likely to follow experts’ opinions because they have privileged access to certain information so as to be able to judge or evaluate specialized outputs. We extend recent work on reputational spillovers (Boutinot et al., 2015) and the connection among different types of reputation (Deephouse, 2000) by providing evidence for the specific role of expert reputation in its relationships with peer and market reputations in hard-to-value creative sectors.

Considering fame as being based on audience-specific reputations has several implications for further research. First, fame depends not only on the intrinsic quality of the specialized achievements that generate reputation but also on the quality of the media (Deephouse, 2000) that may be used by experts. Different media may generate different levels of reputation for famous actors (Carter & Deephouse, 1999). For example, tabloids can provide ephemeral fame, often based on controversies and scandals, while media with cultural columns (prestigious newspapers, e.g. The New York Times and the Financial Times) can shed light on the intrinsic quality of the work, and may provide longer-term fame. Future studies can expand our knowledge about the nature of media, and the degree and sustainability of fame (Van de Rijt et al., 2013).

The second implication of the role of experts is their relative degree of independence. Being famous may not always be desired or sought. Experts have their own agendas with regard to their evaluation of what they describe as new or important. While experts may select organizations with an emerging specialized reputation that they can then decode for the public, they may equally (because of their expertise) strategically select what and whom they report on – so manipulating reputations. This can lead to potential dissociation between specialized reputations (peer or market) and their exposition among experts and members of the public. How this effect might unfold is a promising avenue for research.

Third, the question of how fame is maintained over time, especially in light of reputation, needs further attention. We explain the premises of fame through reputation, and not its cumulative characteristic (Van de Rijt et al., 2013). Future work could develop a better understanding of this reinforcing process over time. In the same vein, damage to reputation may not damage fame. Indeed, reputation reflects organizations’ ability to create value, while fame reflects accumulated knowledge about something or someone. These are important avenues for research on reputation and on fame maintenance and damage, particularly in hard-to-value industries. In these industries, selection is particularly difficult: peers, clients and experts represent crucial audiences in the selection of those who can continue to stand out among others and sustain their fame over time.

Finally, we believe more work is needed on the role of creativity in the relationship between reputation and fame. While our sample focused on companies that pursue and defend avant-gardism and novelty, the antecedents to fame and the relationship between fame and reputation may be different for non-creative or less creative companies. Comparing fame antecedents for creative and non-creative companies could help refine the results of our study.

Our study has managerial implications for organizations in creative sectors. We highlight the importance of reputation among the cultural elite as a significant antecedent of fame. Mediation by the cultural elite facilitates the dissemination of the organization’s specific reputation to wider audiences, and boosts its chances of being known by a large number of people. This finding has significant implications for companies not only in creative industries (such as architecture, design and advertising), but also in professions (such as accounting and law); there, innovation, reputation and fame, as well as validation from peers, are important factors in establishing professional standing, as suggested by Greenwood, Li, Prakash, and Deephouse (2005).

Limitations

Our study has several limitations. First, our cross-sectional approach to examining the cumulative nature of reputation among various audiences is likely to affect the internal validity of our results. This approach restricts our ability to examine temporal issues of reputation evolution (such as maintaining, damaging and repairing reputation over time). A second limitation concerns companies’ search for fame. The interpretation of our results is constrained by the fact that our sample is composed of companies that accepted or sought fame by participating in important competitions and following other rules of the ‘fame game’. While fame is often welcomed, and even actively sought by many companies (for example, to attract business), some may simply not want to be famous. Our study does not provide any clue about this possibility. Third, our model explains only 33% of the variance in the fame construct. While we provide empirical evidence for how fame is impacted by previously established reputations, other dimensions (other social approval assets, or other elements such as the Matthew effect; Merton, 1968) can also impact fame. A final limitation deals with our choice of the complete-mediation model. We selected this model for its parsimony and lowest AICc, which is a useful statistic for small samples. However, the partial-mediation model (M4 in Table 2) was the best model in terms of the potentially biased chi-squared statistic. The results from this model show that: (1) 61% of the effect of market reputation is direct, while 39% is mediated by expert reputation; and (2) 74% of the effect of peer reputation is mediated by experts. In any case, the results show that experts play a central role in building fame among the public. M4 would therefore have provided a more nuanced – but still central – role of experts in mediating peer reputation, market reputation and fame, providing more space for direct influence of peers and clients over fame.

In closing, we hope our study will inspire research to shed further light on the complex relationships among different types of reputations and fame.

Footnotes

Appendices

Appendix 2.

Total effects in the complete-mediation model.

95% Confidence interval
Structural models	Estimates	Lower bound	Upper bound
M1: Complete mediation
total effect Peers (= indirect)	0.818***	0.368	1.269
total effect Market (= indirect)	2.478**	0.059	4.898

N = 103; *p < 0.1; **p < 0.05; ***p < 0.01.

Acknowledgements

We would like to thank our associate editor, Robin Holt, and the two anonymous reviewers for their very helpful feedbacks throughout the review process. We would also like to thank our colleagues for their positive and constructive feedbacks, among whom Candace Jones, Jesper P. Strandgaard and David Deephouse; the Grenoble Ecole de Management MOTI research seminar, the ISG research seminar, the Copenhagen Business School Imagine… Creative Industries research seminar and the Cass Business School research seminar for providing us with a fantastic space for presenting and discussing our paper at its early stage. All errors and omissions are ours.

Funding

This research received no specific grant from any funding agency in the public, commercial, or not-for-profit sectors.

Author biographies

Amélie Boutinot is an Associate Professor at Institut Supérieur de Gestion in Paris. She holds a PhD in Management Science from Grenoble University. Her research interests focus on social approval assets and their dynamics in creative industries, more specifically in architecture.

Iragaël Joly is an Assistant Professor at University Grenoble Alpes and researcher at Grenoble AppliedEconomics Lab. He holds a PhD in Economics from the University of Lyon. His research interests focus on the econometrics of choice modelling (structural equation models, discret choice model, duration modelling).

Vincent Mangematin is a Professor of Strategic Management and Associate Dean for Research at Grenoble Ecole de Management. He focuses on emergent phenomena and on the transformative influence of digital technologies in society. In recent years, he has focused on business models as an approach to renewing strategy.

Shaz Ansari is a Professor of Strategy at Judge Business School, University of Cambridge and Visiting Faculty at Rotterdam School of Management, Erasmus University. He holds a PhD from the University of Cambridge. His research interests include institutional processes and logics, diffusion of practices; social movements, technological and management innovations; ecosystem strategies, and reputation management.

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