The multiplicity of reputations in
innovative industries:
A conditional framework
Judith Völke 11918594 MSc Business AdministrationEntrepreneurship and Management in the Creative Industries track Amsterdam Business School – University of Amsterdam
Final version, 14th August, 2018 Supervisor: Dr. A. Tomaselli
Abstract
This thesis investigates whether the reputation of a project founder has more or less impact on performance for project founders with a mainstream market orientation versus project founders with a niche market orientation. A theoretical model is proposed, explaining the moderating role of a niche or mainstream market orientation on the relationship between a project founder’s reputation and their performance in a selection system theory setting. Selection system theory entails that there are three types of selectors, market, peer and expert. This thesis uses these types of selectors to link them to reputation, and thus the reputation of a project founder will be divided into market reputation, peer reputation and expert reputation. The empirical setting of this research is the United States music industry and the data is based on the Billboard charts. In order to test the hypotheses, a sample of 200 individual artists was taken from the Billboard charts, specifically from the years 2010 until 2015. Results confirm one of the hypotheses, the moderating role of the niche market orientation on the relationship between a project founder’s expert reputation and their performance. The findings of this thesis further the knowledge on selection system theory and the multiplicity of reputations by providing a conditional element that project founders can influence.
Statement of originality
This document is written by Judith Völke, who declares to take full responsibility for the content of this document. I declare that the text and the work presented in this document is original and that no sources other than those mentioned in the text and its references have been used in creating it. The Faculty of Economics and Business is responsible solely for the supervision of completion of the work, not for the contents.
1. Introduction ... 4
2. Theoretical background ... 7
2.1 Project Founders’ Reputation ... 7
2.2 Selection system theory ... 9
2.2.1 Market reputation ... 11
2.2.2 Peer reputation ... 12
2.2.3 Expert reputation ... 13
2.3 Niche vs. mainstream market orientation ... 14
3. Hypothesis development... 15
3.1 The effect of market, peer and expert reputation on the project founder’s performance ... 16
3.2 The moderating mechanism of a project founder’s mainstream market orientation on the relation between their market reputation and performance ... 17
3.3 The moderating mechanism of a project founder’s niche market orientation on the relation between their peer reputation and performance ... 18
3.4 The moderating mechanism of a project founder’s niche market orientation on the relation between their expert reputation and performance ... 20
4. Methodology... 22
4.1 Empirical setting ... 22
4.2 Sample and data collection ... 24
4.3 Potential biases ... 25
4.4 Variables and measures ... 26
4.4.1 Dependent variable ... 26 4.4.2 Independent variables ... 26 4.4.3 Moderator variable ... 27 4.4.4 Control variables ... 28 4.5 Method ... 29 5. Results ... 30 5.1 Descriptive statistics ... 30 5.2 Correlations... 32 5.3 Results ... 33 6. Discussion ... 37 6.1 Hypotheses testing ... 37 6.2 Theoretical contribution ... 39 6.3 Managerial implications ... 41
6.4 Limitations and future research ... 42
7. Conclusion ... 43
References ... 45
Appendix ... 50
Appendix 1 - Results H2 ... 50
1. Introduction
In business literature, reputation is known to be an important aspect to an innovative or an experience good, as consumers are not entirely aware of what the good entails until they have consumed it (Rindova, Williamson, Petkova & Sever, 2005). Reputation then serves as a market informational cue, that is, a piece of information that the market can use in order to reduce uncertainty felt about the good and thus can influence purchase decisions (Boutinot, Ansari, Belkhouja & Mangematin, 2015; Gemser, Van Oostrum & Leenders, 2006). Therefore, an organization’s reputation serves consumers to determine purchase decisions (Zhao, Ye & Zhu, 2016; Rindova et al., 2005). However, few scholars have combined reputational theory with selection system theory, and also taken the project founder’s market orientation into account.
Harvey, Tourkey, Knight and Kitchen (2017) and Ertug, Yogev, Lee and Hedström (2015) highlighted the multiplicity of reputations. Where reputation is often seen as a one-dimensional, narrow concept, Harvey et al. (2017) and Ertug et al. (2015) determine that project founders’ reputations differ among stakeholders, among categories and geographically. In this thesis, the differences between reputations among stakeholders will be discussed. This will be done according to selection system theory (Wijnberg, 1995; 2004). Selection system theory entails that the value of a product is attributed in the eyes of the relevant selector. This means that the different selectors, market, peer and expert, evaluate products differently, with differing criteria. When selection system theory is linked to reputation, the selectors are linked with the different types of reputation, and thus reputation can also be seen through the eyes of the market, peers or experts.
Several scholars have laid the groundwork in linking selection system theory to reputation (Ebbers & Wijnberg, 2012; Boutinot et al., 2015; Boutinot, Joly, Mangematin &
distinguishing how market informational cues originating from different selectors, or stakeholders, have different effects on various types of products or markets, that is, distinguishing the niche from the broad products or markets (Gemser, Leenders & Wijnberg, 2008; Pontikes, 2012). Moreover, Ertug et al. (2015) discussed the effects of actors’ audience-specific reputations on their success with different audiences. These scholars have in common that they found that there is heterogeneity in reputational effects across audiences, products, and markets. However, thus far the conditional reputational effects have been neglected in previous research. Furthermore, although different types of products have been discussed, the market orientation of the project founder, which can be either niche or mainstream, has been overlooked in current literature. This thesis will discuss the conditional reputational effects of project founders using three types of reputation, following selection system theory: market reputation, peer reputation, and expert reputation.
Therefore, the research question that will be attempted to be answered in this thesis is the following:
“What are the differences between the reputational effects for niche versus mainstream project founders across audiences?”
This thesis will re-examine literature concerning the multiplicity or reputations, reputations in the creative industries and literature about mainstream and niche products and consequently empirically test whether different types of reputations (market, peer or expert) have different effects in mainstream markets than in niche markets. The expectation is that a project founder’s mainstream orientation will strengthen the relationship between their market reputation and their performance, while a project founder’s niche orientation will strenghthen the relationship between their peer reputation and their performance, as well as their expert reputation and their performance. This research specifically builds upon earlier works of Boutinot et al. (2015), Ertug et al. (2015) and Gemser et al. (2008). It will build on the
conclusions of Ertug et al. (2015) that reputations are audience-specific and these reputations have different effects in diverse settings. It will further investigate whether the conclusions of Gemser et al. (2008) and Boutinot et al. (2015), that market informational cues are more effective in broader markets whereas peer and expert cues have a stronger effect in niche markets, will hold up concerning reputation of project founders as well. Both Boutinot et al. (2015) and Gemser et al. (2008) have used selection system and found different effects for different markets, however, no empirical work has been done in order to establish that the market orientation of the project founder (either mainstream or niche) has a moderating effect on the performance of the product, nor any other conditional effects have yet been researched. Another contribution this thesis will deliver is to complement studies of reputation multiplicity (Boutinot et al., 2015; Mishina, Block & Mannor, 2012). It will do so by showing the different reputational effects across varying markets. Moreover, multiple studies called for more research on settings of various products, as they believe there to be a difference between niche and mainstream products (Boutinot et al., 2015; Gemser et al, 2006; Gemser et al., 2008).
The empirical setting of this thesis is the United States music industry. The reputation of a project founder reduces the uncertainty felt about an experience good, which many goods in the creative industries are (Caves, 2000). Becker (1982: 23) found that the reputation of project founders and their work reinforce each other, that is, a good reputation leads to a better evaluation of the work and a good product will lead to a better reputation. Therefore reputational value can be exchanged into financial value, as products of producers with a good reputation are worth more than products of producers with a lesser reputation.
The structure of this thesis is the following: It will start by discussing the relevant literature concerning project founders’ reputation in the context of selection system. Then, it
hypotheses. Consequently, the methods that will be used in order to execute this research will be discussed, and the empirical setting will be elaborated on. Then, the results of the empirical testing will be described, after which a discussion of these results follows. The discussion includes the results, contributions, implications and limitations of this study.
2. Theoretical background
2.1 Project Founders’ Reputation
Reputation is defined as “stakeholders’ perceptions about an organization’s ability to create value relative to competitors” (Rindova et al., 2005; p.1033). Furthermore, in settings where there is incomplete and asymmetric information, the organization’s reputation can alter the incentive structure (Sorenson, 2014).
In addition, a reputation is, objectively, a prevailing collective definition based on what the relevant public knows about the firm, or individual (Lang & Lang, 1988). It further is a perceptual representation of a firm or individual’s past actions and future prospects, which makes it possible to compare the firm’s overall appeal to that of other firms or individuals (Roberts & Dowling, 2002).
Uncertainty stems from incomplete and asymmetric information (Rindova et al., 2005). Suppliers are completely aware of all facets and the quality of their offerings, whereas the consumer might not be aware of everything the product or service entails (Dolfsma, 2011). Innovative and creative work is prone to information asymmetries, as outcomes and value are difficult to assess for potential investors and buyers (Millar, Udalov & Millar, 2012). While social ties to investors may help project founders securing funds, it may not provide the investor with enough information in order to resolve these information asymmetries (Millar et al., 2012). When these social ties contain trust, the chances of securing funds from investors are higher. However, whenever there are no social ties, reputation is a signal to investors that
the project founder can be trusted (Millar et al., 2012). Agency theory dictates that a project founder’s reputation can serve as a proxy in order to reduce information asymmetries (Jensen & Meckling, 1976). Millar et al. (2012) use three types of reputation: reputation based on previous performance, reputation by association (which involves reputation created by having ties to respected others) and reputational hype (claims or forecasts that have not yet been lived up to). Where reputation based on previous performance will reduce information asymmetries, reputation by association and reputational hype will not, and will not necessarily benefit the project founder in acquiring success.
A good reputation in the corporate sense is a valuable asset that allows firms to achieve persistent profitability and superior financial performance (Roberts & Dowling, 2002). Customers value associations and transactions with high-reputation firms, because reputation serves as a signal of quality, especially in markets with much uncertainty and innovation (Roberts & Dowling, 2002).
Reputational benefits can also be transferred to the individual level (Mahto & Khanin, 2013; Dobrev & Barnett, 2005). Prior research has found that organizational characteristics are shaped by the individual characteristics of the project founder, and the role he or she plays in the organization (Dobrev & Barnett, 2005; Baron, Hannan & Burton, 1999). For example, project founder reputation is a factor that can reduce investor uncertainty and increase access to investment capital, as previous start-up experience is associated with higher performance and survival chances of subsequent ventures (Mahto & Khanin, 2013).
Reputation functions both horizontally and vertically (Dubois, 2012). On the horizontal axis, a reputation can be shared amongst a larger or smaller community and on the vertical axis, reputation orders individuals within a hierarchy. Similarly, Rindova et al. (2005) proposed that organizational reputation could be comprised of two dimensions. The first
stakeholders evaluate an organization positively on a specific attribute. The second dimension is that of prominence, capturing the degree to which an organization receives collective recognition within its organizational field.
2.2 Selection system theory
Previous research has found that reputation may not be evaluated homogeneously among stakeholders (Ertug et al., 2015; Christensen & Gornitzka, 2018; Harvey et al., 2017). Project founders interact with different audiences, each with their own concerns and uncertainties regarding projects. Where peers value others based on industry norms, a market audience has different standards, which are based on factors within the industry, as well as factors transcending the boundaries of the industry. Furthermore, in a setting of corporate reputation, the several internal and external stakeholders have different interests in the firm, and thus evaluate according to different perceptions (Harvey et al., 2017). These perceptions include reputations, which can be perceived differently from one stakeholder to the other. Therefore it is logical to measure the reputation an organization has for the different stakeholders. Selection system theory measures the perceptions of the different stakeholders by dividing the audience into market, peer and expert selectors.
The value of any product is attributed in the eyes of the relevant selector, which means that for every type of selector, the perceived value offered by the project founder can differ (Wijnberg, 1995; 2004). According to selection system theory, the selectors are market selectors, peer selectors or expert selectors. Each selector attributes value to products or services according to different standards. With market selection, consumers are the relevant selectors, peer selection refers to the system where other producers are the selectors, and with expert selection, neither consumers nor producers are selectors, that is, the selectors in an expert selection system are third party outsiders (Ebbers & Wijnberg, 2012). Selection system not only refers to the competitive processes, but it has also been linked to reputation (Ebbers
& Wijnberg, 2012; Boutinot et al., 2015). Ebbers and Wijnberg (2012) categorize types of reputation according to selection system theory, based on the sources where the reputation originates. That is, when a reputation originates from the success amongst consumers, it is qualified as market reputation, but when a reputation stems from the reception of peer-based awards, it is deemed peer reputation, and when a reputation results from expert judgments, such as critic reviews, it is categorized as expert reputation.
Reputation is a powerful cue that might influence performance outcomes (Roberts & Dowling, 2002). It might be that reputation that stems from sources similar to the self are even more powerful than reputation in general. This is because source credibility is high when the source is representative of the normal buying behavior of the consumer (Gemser et al., 2008). To superficially touch upon a more psychological surface, humans tend to believe cues from sources that are similar to themselves (Burnett, 2016). This is because they recognize the behavior, and the reasoning that precedes it seems logical. Therefore the consumer, as a market selector, will assess information cues from the market as more credible than from other sources, as it is representative of their position, and the same mechanism applies to peer and expert selectors.
As mentioned previously, reputation can function either on a horizontal axis or a vertical axis (Dubois, 2012). Selection system theory takes both axes into account, with a project founder’s market reputation being primarily a horizontal concept, as it is about the proportion of the general public being aware of the project founder’s offerings, while peer reputation is more of a vertical concept, as it is about the relative standing amongst the project founder’s peers. Expert reputation combines the two axes, as it functions to serve the general public, yet it also compares members of the industry, thus creating a hierarchy.
dimension. While all three types of reputations contain some of both dimensions, the perceived quality dimension is more important for market reputation and expert reputation, while peer reputation is more related to the prominence dimension.
2.2.1 Market reputation
Lang & Lang (1988) identified two aspects of reputation: recognition and renown. Recognition refers to the esteem held by producers within their field, thus the evaluations by professional insiders. Renown, however, is a type of recognition beyond the field the producer operates in. Renown shows the interest of the general public, and how a producer is interesting for an audience beyond the cognoscenti. Visibility is crucial for a producer in order to make the transition from recognition to renown (Lang & Lang, 1988).
Renown in Lang & Lang’s (1988) work is the equivalent of market reputation in selection system theory. Market reputation is the assessment of the consumer regarding the organization or individual’s ability to create value, thus the ability to satisfy the consumer’s needs. In order to build a good reputation with the consumer, the organization needs to signal its quality. One way to convey a reputation towards the consumer is to advertise (Sorenson, 2014). Advertising is a market informational cue that the organization is a high-quality producer, because it conveys the message that the organization produces goods of a sufficient quality that it can afford to invest in advertising. Roberts and Dowling (2002) further found that, in addition to advertising, firms often engage in reputation-building activities such as sponsorships in order to improve the value as seen by the consumer. Moreover, reputation is also associated with consumer satisfaction and trust (Park, Lee & Yin, 2014). Consumers trust high-reputation firms to be competent, socially benevolent and adhering to the moral principle of fairness and honesty. These traits increase the likelihood of purchase from these firms.
2.2.2 Peer reputation
Peer reputation refers to the assessment of fellow producers within the field on the actor’s capability to create value (Boutinot et al., 2015). Peer reputation is an important measure to validate an organization’s standing within the industry. As other producers are very aware of the context, an organization’s actions are assessed more credibly when they possess a peer reputation (Padanyi & Gainer, 2003). The effects of peer reputation are mostly researched in the context of the creative industries (architecture, Boutinot et al., 2015; film, Ebbers & Wijnberg, 2012; Gemser et al., 2008; music, Mol & Wijnberg, 2007). However, it has further been applied to a multitude of subjects, such as leadership (Bhansing, Leenders & Wijnberg, 2012), non-profit performance (Padanyi & Gainer, 2003), and funding in the biotech industry (Schoonmaker et al., 2017). Furthermore, peer reputation is a subject that is very relevant in academia, as academic articles require to be peer reviewed in order to be published.
In previous research, peer reputation has been found to affect financial performance positively (Padanyi & Gainer, 2003; Grant & Potoski, 2015). For example, in their research in the non-profit sector, Padanyi & Gainer (2003) found that peers are opinion leaders about the organizational environment, which makes them trusted and knowledgeable advisors to parties in order to make investment decisions. Therefore peer reputation leads to increased resource acquisition. This sentiment is corroborated by Grant and Potoski (2015), who looked into donor behavior in the non-profit sector. They found that donors often use observable characteristics in order to evaluate non-profits. In absence of those observable characteristics, donors often turn to peer reputation to make judgments about a non-profit’s unobservable characteristics. Schoonmaker et al. (2017) also found that peer funding is positively influenced by peer reputation, as it reduces investment uncertainty, which is critical in investment decision-making.
2.2.3 Expert reputation
Expert reputation refers to the assessment of the value the producer created by neither other producers, nor the market. Expert reputation is important, as consumers are more likely to take advice from experts than non-experts (Reyt, Wiesenfeld & Trope, 2016). In the modern day, experts in the creative industries often take the role of critics or journalists, who are valued for their independent, evaluative role (Shrum, 1991; Boutinot et al., 2015).
Critics’ roles in markets for creative goods have been of much interest to scholars. Research has been done amongst others in the domains of literature (Caves, 2000), film (Gemser et al., 2006), and theatre (Shrum, 1991). Critical reviews can play two basic roles: they either actively influence consumers in their selection process or forecast whether or not something will become a success (Gemser et al., 2006). Both roles can play an important part in the success of a producer. The first role will determine whether or not the general public will consume the product, while the second role leads to an influencer or predictor effect. The latter has been established by Eliashberg and Shugan (1997), who found that the critic is more of a predictor rather than an influencer.
Furthermore, to be selected by distributors, and ultimately consumers as well, media coverage counts more heavily than a favorable or unfavorable interpretation of the product (Gemser et al., 2006). This is due to the fact that the visibility is more important in order to be selected than the salience of the review. Also, the addition of more information is sometimes enough in order to reduce uncertainty for consumers (Lingo & O’Mahoney, 2010). These sentiments are similar to those of Shrum (1991), who found mediocre and even negative reviews to be better than no reviews at all, as the number of reviews had a stronger correlation with audience size than the contents of those reviews.
2.3 Niche vs. mainstream market orientation
Another factor that operates on the horizontal axis of reputation, and thus is concerned with the whether the reputation is shared amongst a larger or smaller community, is whether a project founder has a niche or a mainstream market orientation (Dubois, 2012). Previous research has acknowledged the importance of differentiation between audiences for different products (Ertug et al., 2015). Selection system theory has been related to reputations before, and these studies find that there should be more research on settings of various products, as there might be a difference between niche and mainstream products (Boutinot et al., 2015; Gemser et al., 2006; Gemser et al., 2008). Additionally, niche products have become more prominent in daily life, as digitization has increased the offerings in the “long tail”, further increasing chances of survival for niche products (Waldfogel, 2017). The project founder has the choice to offer either mainstream or niche products, and where mainstream products used to be the obvious choice to increase revenues, the new media environment lowers the barriers to market entry, introducing the possibility of additional sales (Elberse, 2008). Retailers are urged to broaden their assortment in order to cater to their customer’s needs, thus retailers tend to carry a wider assortment (Elberse, 2008). Moreover, social media increases the tendency for consumers to participate in discussions and the reviewing of niche products, which increases purchase intentions (Phang, Zhang & Sutano, 2013). A project founder can choose to offer products that do not match their current reputation. For example, a project founder with a market reputation can choose to offer niche products, in order to operate in a market with fewer competitors. On the other hand, a project founder with a peer or expert reputation can choose to offer mainstream products, because even though the chances of survival of niche products have increased in the new media environment, mainstream products are still often the most profitable products (Elberse, 2008).
Boutinot et al. (2015) found that organizations that focus on being reputed by peers operate in more niche, less well-defined markets, while organizations that focus on being reputed by the market are more prone to thrive in the broader, already established markets. Furthermore, Gemser et al. (2006) found that the nature of the product is an important determinant of the effect reviews have on demand. In their study conducted in the movie industry, Gemser et al. (2006) found that the number of reviews influences the demand of art house movies, whereas it does not necessarily influence the demand of mainstream movies. In addition, one of the reasons why critics’ reviews have a stronger effect on the demand of art house movies than on the demand of mainstream movies is because of the weak signaling properties of art house movies. That is, mainstream movies often possess a larger budget and thus have the ability to invest in star power and marketing efforts than niche movies.
Moreover, in a later study, Gemser et al. (2008) found similar results. Of the three types of awards studied (market, peer and expert), expert-selected awards are the most effective for niche products. They further found that awards with a jury representative of the consumers are more credible informational cues than juries that are not representative, thus market cues are more credible for market audiences.
3. Hypothesis development
Selection system theory has previously demonstrated that information originating from market, peer and expert selectors have different effects on consumer or investor behavior (Gemser et al., 2008; Ebbers & Wijnberg, 2012). However, the choices a project founder can make, and thus the influence they can exert, have been neglected in these researches. This chapter will provide hypotheses that show that factors inherent to the selected are to be taken into account when applying selection system theory. More specifically, this section will propose a moderation effect of the project founder’s market orientation on the relationship between the three different kinds of reputation and the project founder’s performance.
Some might say that reputation in itself is a factor inherent to the selected, and therefore the role of the selected has already been researched. However, according to selection system theory, the selectors are the ones who pose the reputation onto the selected, and thus the selected can influence the selector in order to gain a better reputation, but the reputation itself is not inherent to the selected.
Moreover, while gender is also a factor inherent to the project founder, it is not the focus of this study, as this research is more prone to prove that the project founder can exert influence on the relationship between their reputation and performance by making certain decisions, and thus the focus lies with factors controllable by the project founder.
3.1 The effect of market, peer and expert reputation on the project founder’s performance
Reputation is an important antecedent in the buyer-supplier relationship (Suh & Houston, 2010). When consumers are confronted with information asymmetries, they are prone to choose the offerings of suppliers with established reputations over similar offerings of
suppliers without an established reputation (Millar et al., 2012). This is likely because a good reputation signals quality of offerings and thus reduces the information asymmetries, and therefore also the uncertainty faced by the buyer (Rindova et al., 2005). Furthermore, buyers are more likely to invest in relationships with suppliers who they perceive to have a good reputation (Suh & Houston, 2010). Therefore the hypothesis is that there is a direct relationship between reputation and performance.
As discussed earlier, selection system theory explains the existence of market, peer and expert selectors, who evaluate products and services from different perspectives (Wijnberg, 1995; 2004). The three types of reputation discussed in this paper correspond to each selector. Performance can also be divided into these three categories; a project founder can perform
well in the market, among peers or in the eyes of experts. The types of reputation correspond to the same type of performance. Therefore the following direct relationship is hypothesized:
H1: When a project founder possesses a market, peer and expert reputation, only the market
reputation has a positive effect on the project founder’s market performance
3.2 The moderating mechanism of a project founder’s mainstream market orientation on the relation between their market reputation and performance
As discussed in the last chapter of the literature review, there is a difference between reputational mechanisms for niche and mainstream products (Gemser et al., 2006, Boutinot et al., 2015).
Reputation that is representative of consumers’ regular buying behavior is perceived to be more credible for consumers than reputation that comes from sources that are dissimilar to the consumer (Gemser et al., 2008). This entails that consumers are more likely to take market reputation seriously for mainstream project founders than for niche project founders. Furthermore, humans are prone to follow the herd (Gao, Hu & Bose, 2016). They often rate similarly to others’ ratings. By doing so, they create a system where popular (mainstream) project founders get even more popular and thus market reputation is more important for mainstream project founders.
Furthermore, consumers have more access to mainstream products than niche products, through the presence of these products in everyday situations. This leads to a top-of-mind awareness, which entails that consumers think of these products more quickly than of other products (Romaniuk & Sharp, 2004). If the collective audience is aware of a project founder’s product, this leads to more exposure, thus to more user-generated reviews.
Moreover, user-generated reviews are gaining more credibility in the eyes of consumers (Proserpio & Zervas, 2017). As the reach of online review platforms grows, increasingly more
consumers have access to these reviews. This is a self-reinforcing mechanism, as mentioned before, because a growing amount of positive reviews lead to more positive reviews as consumers follow the herd (Gao et al., 2016).
Additionally, as the perceived quality dimension by Rindova et al. (2005) is most important for market reputation, and Ertug et al. (2015) found that artistic quality is important for a broader audience rather than a niche audience, it can be claimed that market reputation can be linked to a mainstream audience, and thus that a mainstream market orientation strengthens the relationship between a project founder’s market reputation and their performance.
Therefore, a moderating mechanism of mainstream market orientation is hypothesized on the relationship between a project founder’s market reputation and their performance.
H2: The relation between market reputation and performance is stronger for mainstream
project founders than for niche project founders
3.3 The moderating mechanism of a project founder’s niche market orientation on the relation between their peer reputation and performance
Other producers in the field, or peers, are most aware of the context in which producers operate (Padanyi & Gainer, 2003). This raises source credibility of peers, and thus makes peer reputation a strong informational cue. Producers who focus on gaining peer reputation are also known as “market makers”, rather than “market takers” (Boutinot et al., 2015). This means that producers who focus on gaining esteem from the field are often trying to innovate and therefore appeal to other producers and cognoscenti. Ergo, these producers frequently create more niche products than producers who focus on building a strong market reputation. For niche products, consumers are more prone to informational cues from sources with more
(2006) and Boutinot et al. (2015) found, consumers who are interested in niche products often turn to industry sources, and thus peer reputation is a cue with a stronger effect on performance for niche products than for mainstream products.
Furthermore, the difference between market reputation and peer reputation also relies on the organization or individual’s objectives. Some project founders are focused on commercial success, while others are in pursuit of innovation. Bhansing et al. (2012) concluded that while the average consumer seeks entertainment in their art, peers are more oriented towards artistic innovation. Therefore, project founders generally tend to attach high value to the esteem they hold in the eyes of other producers. However, Boutinot et al. (2015) discuss how organizations’ orientations can differ, i.e. some companies are more market-oriented while others are more peer- or expert-market-oriented. They found that companies whose strategic balance is more focused on being reputed amongst peers, are often operating in more niche markets than those who are more focused on being reputed amongst the market. Thus, organizations that are seeking peer reputation are more focused on innovation, while organizations that are seeking market reputation are more determined to generate commercial success.
Moreover, niche project founders often work in a less concentrated market than mainstream project founders, with fewer players. Frenkel (2015) found that in a market with a large number of players, ratings will be more truthful than in a market with fewer players. In markets with fewer players, that is, niche markets, there will be reputation inflation. This is because the raters, in this instance the peers of a project founder, know that providing a bad rating can backfire and thus hurt their own reputation. Therefore a niche market orientation has a better ability to strengthen the relationship between peer reputation and project founder performance than a mainstream market orientation.
Therefore, a moderating mechanism of a project founder’s niche market orientation is hypothesized on the relationship between their peer reputation and performance.
H3: The relation between peer reputation and performance is stronger for niche project
founders than for mainstream project founders
3.4 The moderating mechanism of a project founder’s niche market orientation on the relation between their expert reputation and performance
As mentioned in the theory section, reviews have the strongest effect for niche, novel products, as they lack the strong signaling properties that mainstream products may have. Therefore, the consumer lacks information about the product, which increases the uncertainty and therefore the risk of buying. However, reviews often contain information that is new for the consumer, and the addition of that new information reduces the uncertainty (Lingo & O’Mahoney, 2010). The reduced uncertainty further reduces the risk of purchase for the consumer, and thus increases the likelihood of consumption. According to Gemser et al. (2006), consumers seeking to consume niche products are more likely to be affected by expert reputational cues than consumers seeking to consume mainstream products.
Similarly as discussed for H3, reputation inflation can occur with expert reputation as well, and have a stronger effect on niche markets than on mainstream markets. Expert selectors have a stronger incentive to rate mainstream products truthfully, in order to create a credible reputation for themselves (Frenkel, 2015). However, when reviewing niche products, expert selectors may be more inclined to rate more favorably, in order to create a “double reputation”, which entails that the expert selector is known by niche project founders to be a lenient rater, but the expert selector is also known by the market to be a fair rater.
reputation is more prevalent in a niche than a broad market. This is corroborated in the restaurant industry, where Luca and Servas (2016) found that reviews are less influential for mainstream chain restaurants, which already have an established reputation. Moreover, Gemser et al. (2008) found that expert-selected awards are the most effective for the independent film segment, rather than the mainstream film segment.
Additionally, reviews are found to have a stronger effect for cases with little prior information, such as novel creative products (Dempster, 2006). This is because for novel creative products, there are usually few other quality cues, such as word of mouth or star power. Moreover, in industries that are characterized by oversupply, journalists who write reviews effectively act as gatekeepers who can extract a product from the “long tail” and move it further into the spotlight (Shrum, 1991).
Therefore, a niche market orientation is hypothesized to act as a moderating mechanism between a project founder’s expert reputation and their performance.
H4: The relation between expert reputation and performance is stronger for niche project
founders than for mainstream project founders
So, in this thesis a moderation effect is proposed. Reputation is an especially valuable asset to have when dealing with experience goods in an uncertain market, where there are information asymmetries (Dolfsma, 2011; Rindova et al., 2005). Moreover, when an industry is characterized by oversupply, reputation can serve as an informational cue to help consumers make purchase decisions (Shrum, 1991). Therefore these hypotheses are especially relevant to markets with these conditions. The expectation is that, as is in line with selection system theory, of the three reputations, market, peer and expert, only the market reputation will have a positive effect on the market performance of a project founder. The peer and expert reputations will have a negative effect or no effect at all on the market performance of
the project founder. The expectation is further that a mainstream market orientation of a project founder will strengthen the effect of market reputation on performance, while a niche market orientation will strengthen the effect of peer reputation and expert reputation of performance. A conceptual framework is provided in Figure 1.
4. Methodology
4.1 Empirical setting
The empirical setting of this research will be the US music industry. The US music industry is representative of this topic, as music artists occupy the role of project founder. Since artists occupy a similar role as project founders, as they both are the face of the venture, and often the ones who started it, or at least shaped it to be as it is, the music industry is generalizable towards a broader organizational perspective.
In addition, innovation, uncertainty and oversupply are important characteristics of the creative industries, and thus of the music industry (Caves, 2000). As products in the creative industries are often experience goods, consumers must look for informational cues in order to
make a purchase decision. Reputation is such an informational cue that can convey quality and thus, reduce uncertainty in buying decisions (Rindova et al., 2005).
Furthermore, the music industry is one where reputation is an important and valuable asset, as it can help generate revenue. Ren, Shen & Kauffman (2016) found that an artist’s reputation is an important determinant for their popularity, and it may be an indicator of the artist’s ability to win awards in the field of music and increase album sales. These results are similar to the results of Gopal, Bhattacharjee & Sanders (2006), who found that past reputation of an artist has a positive effect on the rankings of the artist’s new album. As reputation plays such an important role in the music industry, it is a suitable setting for a study concerning this topic.
Moreover, an artist in the music industry can depend on multiple types of reputation. A market reputation is crucial to generate revenue in the music industry, because the consumers are ultimately the ones who will purchase the albums and visit concerts (Ren et al., 2016; Gopal et al., 2006). Therefore an artist wants to be popular amongst the market selectors. Ren et al. (2016) also write that a reputation indicates the ability to win awards in the field. Peer-based awards will indicate to the end consumer that the artist is esteemed in the music industry, and thus peer-awarded awards send a signal of quality to the end consumer. Lastly, expert reputation stems from third-party reviewers, and critics and their reviews are specifically important in the entertainment industry (Eliashberg & Shugan, 1997).
An artist in the music industry further has the option to release music directed at the mainstream audience, or at a more niche audience. Due to digitization, both mainstream and niche albums have the possibility to become “hit” albums, as fixed costs are high, but the cost of copying and sharing music is significantly lower than previously (Zhang, 2016). Furthermore, minor labels are closing the gap to major labels, in terms of profit (Bhattacharjee, Gopal, Lertwachara, Marsden & Telang, 2007). Therefore money might be a
lesser incentive to choose mainstream music over niche music. This choice by the artist may impact which reputation needs to be optimized.
The US music industry is the largest in the world, with a revenue of $8.72 billion in 2017 (Christman, 2018). This is half of the $17.3 billion revenue globally (Jones, 2018). Furthermore, it has grown 16.5% from the previous year, showing that it is a relevant, thriving industry that is also still evolving (Christman, 2018). This evolvement shows further in the fact that streaming revenue has increased a lot at the expense of downloads and thus that music consumption patterns are changing.
Moreover, the proportions of streaming, physical sales and downloads in the US market are similar to the proportions in the global market. Therefore, the US music industry is representative of the global market and thus results can be generalized globally. Artists in the US market are often popular in foreign (western) markets as well, which ensures that the results obtained from this study are in a certain sense transferrable to other western markets.
4.2 Sample and data collection
The data as used in this study will be collected from the Billboard album charts, which serves as the performance measures, databases such as Allmusic and Metacritic for both the market reputation and the expert reputation, and finally the database of the Grammy awards will be used to serve as the measure of peer reputation.
Billboard was originally an entertainment magazine, founded in 1894 (Anand & Peterson, 2008). At first, the Billboard magazine was primarily focused on advertising and all live popular entertainment. Then, when the music industry started to advertise in the magazine, Billboard shifted its focus more towards music (Anand & Peterson, 2008). From the mid-twentieth century, the music charts became a weekly feature in the magazine, and in recent years, these charts are what define Billboard. Billboard evolves its chart-making
based on physical sales, as well as streaming numbers and radio airplay. This makes Billboard a reliable source in the music industry.
The databases used for market and expert reputation measures are AllMusic and Metacritic. AllMusic is the most comprehensive database, as its mission at conception was to create an open access database that includes every recording (Wolf, 1994). It is a catalogue that encompasses most albums and songs released, not only in the US music industry, but also globally. The largest difference between AllMusic and Metacritic is that Metacritic is founded to be a rating website, rather than a catalogue containing information.
The Grammy awards are the only peer awards in the recording industry (Grammy.com, 2018). Members of The National Academy of Recording Arts and Sciences, who are artists or other professionals in the recording industry, are the ones who decide on the nominations and who cast the final votes.
4.3 Potential biases
Although ample precautions have been taken in order to reduce biases in the data, it is
impossible to rule out bias entirely. In the Billboard Hot 100, only the most popular songs at a certain time are presented. This may not give an accurate representation of the entire
catalogue of songs that are released at a certain time, as songs that are not popular enough to appear in the Billboard Hot 100 charts are not included.
Furthermore, because of the existence of gatekeepers in the creative industries (Caves, 2000), there is no pure market selection. Gatekeepers in the music industry exist of radio DJs, who decide whether or not to play the single, bookers of venues, who decide whether or not to allow an artist to take the podium and journalists, who may or may not choose to give the artist the exposure they need. However, whenever an artist advances through the gatekeeper stage, the consumers will determine market selection.
Moreover, some songs released are done so as part of a soundtrack, for a movie, TV series, advertisement or video game. This can impact the performance of a song, which has little to do with the reputation of the artist, but more so with the popularity of the movie, TV series, advertisement or video game.
Finally, there is the possibility of reverse causality. In this study, the Billboard Hot 100 was chosen specifically over the Billboard 200 in order to minimize reverse causality, because the Billboard Hot 100 has a rule that songs must not re-enter once they have left the charts. However, there is no ruling out that consumers who take a liking to a recent song will consume older music and even rate older albums. This might influence the market reputation variable. However, this is probably only a small portion of the ratings.
4.4 Variables and measures 4.4.1 Dependent variable
The dependent variable in this research is performance. Performance will be measured by analyzing the charts from the Billboard Hot 100. The Billboard Hot 100 chart ranks the most popular songs of the week, based on traditional single sales data, radio airplay and streaming data. Billboard charts are consistently used by marketers in order to denote the success of an album (Gopal et al., 2006). Performance will be measured by the sum of number of weeks an artist spent in the album charts, weighted by the ranking they occupied, similar to the method by Piazzai and Wijnberg (2017). Therefore, performance is measured by the following equation: Performance = .
4.4.2 Independent variables
Consistent with selection system theory, the independent variables in this study are divided into reputations corresponding to the selectors as described by Wijnberg (1994; 2004).
Therefore the independent variables are market reputation, peer reputation and expert reputation.
Market reputation: Market reputation will be measured by accumulating and averaging
user ratings of all previous albums of the artist. User ratings are gathered from the databases of Allmusic, Musicbrainz and Metacritic. These ratings are on a 1-5 star basis, and the average of all albums prior to the album that the song in the sample appears on will be taken.
Peer reputation: Peer reputation will be measured along the lines of Ebbers and
Wijnberg (2012). To measure peer reputation in the Dutch film industry, they took the number of awards won in the Dutch Film Festival, prior to the producer’s latest movie. In this setting, peer reputation will be measured by the number of Grammy nominations prior to the latest album. As the Grammy’s are the only awards rewarded by peers in the US music industry, they are quite exclusive (Grammy.com, 2018). Therefore it was chosen to take nominations as a measure, rather than actual wins, as that would have meant that very few artists actually have a peer reputation. By choosing the number of nominations, which are also awarded by a peer audience, it will expand the number of artists with a peer reputation.
Expert reputation: Expert reputation will be measured by critics’ reviews. As albums
are often reviewed on a 1-5 star basis, the average number of stars of the latest albums will be taken. The reviews will be extracted from music databases Allmusic, Musicbrainz and Metacritic. The reason these sources were used, is because they are large, established databases that often review music. Therefore they are a knowledgeable, reliable source. Using critics’ reviews as a measure of expert reputation is in concurrence with methods of Eliashberg and Shugan (1997) and Ebbers and Wijnberg (2012).
4.4.3 Moderator variable
Market orientation: Gemser et al. (2008) and Boutinot et al. (2015) found that expert and
effective in niche markets, while market evaluations are more effective in mainstream markets. The project founder can choose their market orientation. The market orientation refers to the type of product the project founder releases; this is either a niche product or a mainstream product in this thesis. The sample will be divided into niche and mainstream on the basis of the artist’s record label. Artists who are signed by a major record label are ones with a mainstream market orientation, while artists who are signed by an independent label will be classified as “niche”. This method was also used by Gemser et al. (2008), who, in their study in the Dutch movie industry, divided movies into “mainstream” and “independent” movies, based on whether the distributor was major or independent. The market orientation variable is constructed as a dummy variable, with 1 = mainstream market orientation, 0 = niche market orientation.
4.4.4 Control variables
In this thesis, three control variables are taken into account. These are experience, genre and gender. Previous research has shown that these might be of influence to success and therefore this research will control for these variables.
Experience: Organizational age may be positively related to reputation (Deephouse &
Carter, 2005). Therefore, experience is added as a control variable. Experience is measured by the number of years that the artist has been in the industry, that is, the years since the first release of the artists (either single, album or EP).
Genre: Throughout the years, different genres become more popular within the music
industry. Where the 60s were dominated by rock ‘n’ roll, the 70s were an era of soul, and the 80s and 90s saw an uprising of punk and indie music (Hesmondhalgh, 1999). The popularity of a genre can have an effect on the overall performance of artists in such a genre. As such, it was added as a control variable. Genres were determined by the Allmusic database. If an artist
artists could be categorized in one of seven categories: country, electronic, hiphop, latin, pop, pop/rock, or R&B. This variable is constructed as a dummy variable of K-1, where country is taken as the control group, as most artists are in this category.
Gender: A project founder’s gender can have an impact on overall performance
(Frydrych, Bock & Kinder, 2016; Greenberg & Mollick, 2015). Where women are generally less represented in the search for funds, they are more likely to succeed at raising the desired capital (Greenberg & Mollick, 2015). Furthermore, women are more likely to be represented in projects related to creative undertakings, such as dance, art and fashion (Frydrych et al., 2016). This variable is constructed as a dummy variable with male = 1, and female = 0. Whenever an artist consists of multiple people, the project founder’s gender was taken. If that is still multiple people, the most prominent member amongst them was chosen to represent the gender (that is, the front man or woman).
4.5 Method
SPSS Statistics version 25.0 was used for all computations, complemented by the Process macro of Andrew F. Hayes. The latter was used in order to test the moderation hypotheses.
In order to prepare the data, the genre variable was recoded into dummy variables. As there are 7 genres, the genre variable was coded into K-1=6 dummy variables. The “Country” genre was used as the control group, as the largest number of artists is in this group.
Then, a frequencies check was performed in order to examine any errors in the data. No errors were found. After that, descriptive statistics, skewness and kurtosis tests were performed. The item of performance has a substantial positive skewness and a positive kurtosis, indicating that performance is left skewed and leptokurtic. The items of market reputation and expert reputation have a substantial negative skewness and a positive kurtosis, indicating a right skewed, leptokurtic distribution. The item of peer reputation has an extreme positive skewness and an extreme positive kurtosis, indicating an extremely left-skewed,
leptokurtic distribution. To normalize the distributions of these variables, these items have been transformed into new variables, peer reputation by inverting, performance by log transforming and market and expert reputation by reflecting the log transformation. These transformations lead to a more acceptable skewness and kurtosis for all items. Expert reputation is now normally distributed. Although still not perfectly normal, the skewness and kurtosis of the item of performance is now between -1 and -0.5, and the items for market reputation and peer reputation were all between 0.5 and 1. Furthermore, the sample is of a sufficient size (n=200) that skewness and kurtosis will not make a substantive difference in the analysis (Tabachnick & Fidell, 2001). Consequently, a frequencies check of the standardized scores was performed in order to find outliers. No outliers were found. Furthermore, because a moderating effect will be tested, the scores for market reputation, peer reputation and expert reputation were converted into Z-scores. An interaction term was also computed by multiplying the market reputation, peer reputation and expert reputation with the “label” variable.
5. Results
5.1 Descriptive statistics
Table 1 provides a descriptive summary of all songs in the sample (n=200). The table is divided into mainstream or niche market orientation on the left, and on the right it is divided by gender. This has been done because this study focuses on the selected, and the factors inherent to those selected. As can be derived from the table, the majority of songs in the sample are performed by artists who are signed with a major label (n=154, 77%). However, as more artists are signed by a major label compared to an independent label, this is a logical outcome. We further see that male performers are more represented in the sample as well
independent labels, as the means are quite similar (6.1737 and 6.2398 respectively). However, we do see that female artists outperform their male counterparts, with a mean performance of 8.2634, compared to a mean performance of 5.3209 for male artists. For market reputation, we see small differences between the artists who have a mainstream market orientation and those who have a niche market orientation, as well as small differences between genders. However, for peer reputation as well as expert reputation, we see that the artists who are signed with a major label score quite a bit higher on these variables. This could be because artists with a mainstream market orientation are signed by labels with network connections that reach far into the industry. For peer and expert reputation, there are little differences between genders. We also see that the average experience of the artists is higher for major labels than for independent labels, as well as for male artists compared to female artists.
Total
Mainstream market
orientation Niche market orientation Female Male
N 200 154 46 59 141
Performance Mean 6.1889 6.1737 6.2398 8.2634 5.3209
Min .01 .01 .01 .01 .01
Max 41.61 41.61 38.23 41.61 38.23
Market reputation Mean 3.2880 3.3172 3.1902 3.2615 3.2991
Min 0 0 0 0 0
Max 5 4,5 5 4.5 5
Peer reputation Mean 4.57 5.23 2.37 4.29 4.69
Min 0 0 0 0 0
Max 60 60 46 46 60
Expert reputation Mean 2.8889 3.0071 2.4927 2.7466 2.9483
Min 0 0 0 0 0
Max 4.25 4.25 4.25 4.25 4.25
Experience Mean 5.81 6.34 4.04 4.92 6.18
Min 0 0 0 0 0
Max 35 35 21 22 35
5.2 Correlations
A correlational analysis was done in order to quantify the intensity and the meaning of the relationship between the variables. All variables of the model are included, as are the control variables. The results are shown in table 2.
From this analysis, it can be derived that the independent variable ‘expert reputation’ is positively related to the dependent variable performance (r = .15, p < .05). This suggests that the reception of critical acclaim by expert reviewers in the past has a positive effect on the ability to have success with a new song. The variables market reputation and peer reputation are not significantly related to performance, with a small positive correlation for market reputation (r = .73, p > .05) and a small, negative correlation for peer reputation (r = -.05, p > .05). Also control variable ‘latin’ has a significant correlation with the outcome variable ‘performance’ (r = -.21, p < .01), indicating that releasing a song of the latin genre has a negative impact on the performance of that song. Moreover, the ‘experience’ variable shows significant correlations with the ‘market reputation’, ‘peer reputation’, and ‘expert reputation’ variables (respectively r = .27, p < .01; r = -.37, p < .01; r = .27, p < .01). This indicates market audiences and expert audiences think more highly of project founders who have been in the industry longer, while peer audiences will think the opposite. Moreover, gender correlates negatively with performance (r = -.16, p < .05), indicating that female artists are performing better than male artists. Gender further correlates with the genres hiphop, in which male artists have a more dominant share (r = .25, p < .01) and pop, in which female artists are more represented (r = -.33, p < .01).
Variables M SD 1 2 3 4 5 6 7 8 9 10 11 12 1. Performance .20 .90 - 2. Market reputation .15 .26 0.73 - 3. Peer reputation .34 .36 -.05 -.12 - 4. Expert reputation -0.3 .39 .15* .60** -.25* - 5. Market orientation .77 .42 -.01 .04 -.05 .16* - 6. Experience 5.81 6.11 -.13 .27** -.37** .27** .16* - 7. Electronic .04 .18 .02 -.21** .19 -.16* -.03 -.12 - 8. Hiphop .21 .41 -.00 -.08 -.09 .08 -.07 -.08 -.10 - 9. Latin .05 .22 -.21** -.10 -.07 -.01 .07 .16* -.04 -.12 - 10. Pop .18 .39 -.07 -.00 .13 -.07 .07 -.20** -.09 -.24 -.11 - 11. Pop/Rock .15 .36 .00 .18* -.03 .11 -.04 .16* -.08 -.22 -.10 -.20** - 12. R&B .16 .37 .12 -.09 -.17 -.06 .11 -.04 -.08 -.25** -.10 -.20 -.18 - 13. Gender .71 .46 -.16* .01 .02 .07 -.02 .1 .06 .25** -.05 -.33** .03 -.05 ** Correlation is significant at the 0.01 level (2-tailed)
* Correlation is significant at the 0.05 level (2-tailed)
Table 2, Correlational matrix
5.3 Results
In order to test hypothesis H1, a regression analysis was performed. The direct linear relations between the independent variables (market reputation, peer reputation, and expert reputation) and the dependent variable performance were measured. The control variables were also regressed onto the dependent variable. The results are shown in table 3. B = unstandardized coefficients whereas b = standardized coefficients.
Moreover, a multicollinearity test was performed in order to rule out that two or more explanatory variables have a linear relationship with each other. All values are between 1 and 10, thus ruling out an issue with multicollinearity.
Variable B SE b t p VIF Market Reputation .588 .879 .080 .669 .505 2.377 Peer Reputation -.034 .082 -.049 -.419 .676 1.625 Expert Reputation 1.762 .775 .279 2.274 .025* 2.283 Experience (years) -.138 .120 -.116 1.155 .250 1.850 Electronic genre -1.632 4.035 -.041 -.404 .687 1.239 Hiphop genre .604 2.290 .031 .264 .792 1.772 Latin genre -1.659 3.727 -.045 -.445 .657 1.257 Pop genre .328 2.660 .014 .123 .902 1.717 Pop/Rock genre 1.438 2.362 .019 .163 .871 1.453 R&B genre .385 2.362 .019 .163 .871 1.617 Gender -1.589 1.753 -.092 -.907 .366 1.191 ** Correlation is significant at the 0.01 level (2-tailed)
* Correlation is significant at the 0.05 level (2-tailed)
Table 3, Regression results
The independent variables market reputation and peer reputation are not significantly correlated with performance. With the p-values of these variables being higher than .05, the relation between market reputation and performance and the relation between peer reputation and performance cannot be proven. However, the variable of expert reputation does prove to have a significant relation with performance (b = .279, p < .05). Therefore H1 is not supported, as it has been proven that when a project founder possesses a market, peer and expert reputation, only the expert reputation has a direct effect on their market performance, rather than the market reputation, which was hypothesized.
Then, a moderation analysis was performed in order to test H2, H3, and H4. To test the moderating effect of market orientation on the relationship between market, peer and expert reputation and performance, the Process macro for SPSS, written by Andrew F. Hayes was
dependent variable, X the independent variable, M the moderator and XM the interaction term.
When running the Process macro for SPSS for H2 (the moderating effect of the project founder’s market orientation on the relation between market reputation and performance), X = market reputation, M = project founder’s market orientation and XM = market reputation x project founder’s market orientation. The Process macro for SPSS performs robust standard errors by default, which ensures there are no issues concerning heteroscedasticity.
From the model summary of the moderation analysis of H2, it is found that the model is not significant with F = 1.5677 and p = .1112. However, it did find a significant interaction term for the variables “market orientation” and “market reputation”, with F = -1.9390 and p = .0409. When looking further, it turns out that the conditional effect for a niche market
orientation is significant with p = .0304, which is the opposite of hypothesized. Therefore H2 is not supported. The results of H2 can be found in appendix 1.
For H3, the moderating effect of the project founder’s market orientation on the relation between peer reputation and performance, the same procedure was followed as for H2. However, in this analysis, X = peer reputation, M = project founder’s market orientation and XM = peer reputation x project founder’s market orientation. The model summary states that this model is not significant either with F = 1.2826 and p = .2371 There is no significant interaction term, so there is no proof that H3 is supported. The results of H3 can be found in appendix 2.
H4 (the moderating effect of the project founder’s market orientation on the relation between expert reputation and performance) is tested similarly, with X = expert reputation, M = project founder’s market orientation and XM = expert reputation x project founder’s market orientation. This model did turn out to be significant at the .05 level with F = 2.24789 and p = .0137. Then, the interaction effect is examined in order to establish the evidence of moderation. The interaction effect between the variables “label type” and “expert reputation” in this model is significant at the .05 level, with p = .0348. The significant interaction indicates that there is a significant difference between the effects of expert reputation between the two different market orientations, yet it does not necessarily indicate which market orientation has the larger effect. When probing the conditional effect, we find that the label type coded 0 (niche market orientation), has a significant conditional effect on performance (p = .0010), while the label type coded 1 (mainstream market orientation) does not (p = .3241) and therefore we accept H4. An overview of the results is shown in table 4. For brevity, the control variables were left out of the table.
Variable Coeff SE t p LLCI ULCI Constant 1.1706 2.7610 .4240 .6721 -4.2759 6.6171 Market orientation 4.8307 2.8493 1.6954 .0917 -.7900 10.4514 Expert Reputation 2.5798 .7744 3.3315 .0010 1.0522 4.1073 int_1 (expert reputation x niche market orientation) -2.0094 .9453 -2.1256 .0348 -3.8742 -.1446 Table 4: Moderating effect
6. Discussion
6.1 Hypotheses testing
This study aimed at finding how different types of reputation can impact actors with different market orientations. Based on previous research in the area of reputation, three hypotheses were proposed. These hypotheses were formed in order to reflect the multiplicity of reputations. Previous research has already found that there are different types of reputations that can influence an organization, however, scholars have thus far neglected the inherent differences between these organizations. The multiplicity in reputations was represented by use of selection system theory. It was expected that the relationship between market reputation and performance would be stronger for project founders with a mainstream market orientation, while the relationship between peer- and expert reputation and performance would be stronger for project founders with a niche market orientation. This expectation was based on previous research by Boutinot et al. (2015), who connected the different types of reputation to their respective performances, and Gemser et al. (2008), who found that awards
