1
SOCIAL SUFFOCATION AND INNOVATION RESISTANCE IN
SOCIALLY DRIVEN INDUSTRIES: MAKING A
MOUNTAIN OUT OF A MOLEHILL
By
Tom Berger
University of Groningen Faculty of Economics and Business
MSc Business Administration, Strategy & Innovation
January 2013
Supervisors: dr. René van der Eijk and prof. dr. Wilfred Dolfsma
Abstract
Evolution and innovation are hot topics today. This research has empirically tested the level of innovation resistance as experienced by participants of social networks in industries that are heavily driven by social networks. The research did this by testing the relationship of the maturity level of music genres and the music genre’s participant’s innovation resistance towards innovative equipment. 225 DJs participated in an online questionnaire and two field experts are interviewed, which resulted in a quantitative as well as qualitative approach to the proposed relations. Interesting conclusions are drawn for a scientific point of view as well as a managerial point of view; the research concludes that the maturity of social networks in industries heavily driven by social networks is only of minor influence on a participant’s innovation resistance. These findings counter the suggestions of the existing literature that the maturity of social networks suffocate innovative behavior, underlining the importance for future research in this area.
Keywords: innovation resistance; decision-making; social network; aesthetics; music trajectory;
2
i. TABLE OF CONTENTS
i. TABLE OF CONTENTS ... 2 1. INTRODUCTION ... 3 2.LITERATURE REVIEW ... 10 3. METHODS ... 19 4. RESULTS ... 30 5. DISCUSSION ... 40
6. CONCLUSION, LIMITATIONSAND RESEARCH AGENDA…....………...44
7. REFERENCES LIST….………...49
3
1. INTRODUCTION
“In any moment of decision, the best thing you can do is the right thing, the second best thing is the wrong thing and the worst thing is doing nothing”- Theodore Roosevelt
1.1 INTRODUCTION
Evolution in its broadest sense is key to our existence. Basically, the evolution theory answers the question how life responds in situations where major environmental changes make existing dominant life forms ill adapted. Some of the existing life forms will adapt and stay present in small numbers. Together with their offspring they will thrive and multiply, and the poorly adapted peers will die out (Nelson, 1995). In other words: a case of survival of the fittest. The assumption that evolution is preferred over non-adoption and that people should participate in the evolution process in order to stay around in the long run, as the evolution theory suggests, is one of the largest pro-change biases that is carried along the scientific community (Rogers, 1995).
On the contrary, the field of social science shows that mankind is disproportionally biased towards a status quo alternative in decision-making (Samuelson and Zeckhauser, 1988). This implies that the current situation is preferred over the other alternative in the decision that will alter one’s status quo.
4
1.2 RESEARCH MOTIVE
Because of the presence of innovation resistance it is of prior importance for organizations to understand the process of this decision-making of potential adopters when organizations introduce an innovation.
The literature on innovation diffusion, innovation adoption and innovation resistance is extensive and entails a great variety of different perspectives (Feder and Umali, 1993). However, in the past decades relatively little research was conducted on the decisions concerning the adoption or rejection of innovations (Moreau et al., 2001; Kleijnen et al., 2009; Gatignon and Robertson, 1985; 1989). The adoption decision consists of the innovation resistance and the adoption or non-adoption/rejection. Although the adoption of an innovation and resistance to an innovation might seem like a two-edged sword, Ram (1987) has made an explicit distinction between adoption and resistance that will be used throughout this research. According to Ram (1987) the innovation adoption start after the initial resistance experienced by the consumer is overcome. If the resistance level of the potential adopter is too high, there is no adoption at all. Adoption and resistance can coexist during a lifetime of an innovation, but resistance and adoption are perceived as two separate concepts.
It seems that the rapid growth of information technology enhanced the general interest of the scientific community in innovation adoption, which started in the 1980’ (Williams et al., 2009). In line with this, large proportion of the literature on adoption or resistance of innovations is focused on the adoption of IT1.
Although a considerable part of the literature on innovation adoption and resistance was conducted empirically, none of the literature has empirically tested the level of innovation resistance of agents active in industries that are heavily driven by social networks (e.g. Gatignon and Robertson, 1989; Hoeffler, 2003; Kleijnen et al., 2009; Moreau et al., 2001; Szmigin and Foxall, 1998; Wood and Moreau, 2006). Lena and Peterson (2008) make a notice of this gap as well. They raise the question how it is possible that some participants in music genres seek innovation while other participants in music genres try to maintain traditions.
The purpose of this research is to gain an improved understanding of the mechanisms that drive an individual’s resistance to adopt a radical innovation in a socially driven environment.
A standard and common-used definition of a social network embodies the notation of all the individuals with whom one shares a social relationship. However, a social network is not necessarily just the group of people that an individual knows personally and communicates or interacts with regularly like family, friends or colleagues; These groups are examples of social networks and often are important social networks, but many other social networks can provide important information and
5
serve as an information source (Huberman et al., 2008; Potts et al., 2008). Examples of these social network information sources and the coherent decisions in practice are – the observation of the box-office totals before a person is going to see the movie, a hockey player who is not wearing a helmet because nobody does and almost every decision on financial markets (Beck, 2007; Schelling, 1973; Kirman, 1993).
Exemplary for industries that are heavily driven by social networks are creative industries. Other examples of industries that are heavily driven by social networks are the financial services industry and the scientific community (Kirman, 1993).
In this context creative industries are a set of agents and agencies in a market characterized by adoption of an infinite variety of novel ideas within social networks and consumption (Caves, 2000; Potts et al., 2008). To illustrate the size of creative industries, CBS (2011), the Dutch bureau for statistics, has stated that 2,3%2 of the entire Dutch workforce is employed in creative industries3
solely.
1.3 RESEARCH QUESTION AND SUBQUESTIONS
This research explores the relation of the maturity of social networks in creative industries and experienced innovation resistance for radical innovations of participants empirically. The research focuses on the maturity facet of a complex social network, since literature suggests that there is a relationship of the maturity of a social network and a participant’s innovation resistance (Lena and Peterson, 2008). This claim will be elaborated in detail in the theory section. This results in the following research question and sub questions for this research.
In which way does the maturity of a social network within industries that are heavily driven by social networks influence the innovation resistance of a participant of this network towards radical innovations?
In order to answer the research question a set of sub questions is composed in order to explain the different concepts and their relations. The sub questions that will be discussed throughout the theory section are found in table 1.
2 172.000 people of a total workforce of approximately 7,500,000 people.
6
Sub questions Section
What is innovation resistance? 2.1
In which way do risks drive innovation resistance? 2.2
In which way does an individual’s psychological barriers drive innovation resistance? 2.3
How can social networks be defined in the creative industry? 2.4
How can the maturity be defined of social networks in the creative industry? 2.4 How is the maturity level of social networks influencing a participant’s innovation resistance? 2.5
Table 1- Sub questions
Before heading on to the theory section, a number of focal concepts are defined and summarized. Also choices of direction of this research on macro level are explained. For innovation there are numerous definitions. A widely adopted definition is the definition by the OEDC in 1991: An innovation is “an iterative process initiated by the perception of a new market and/or new service opportunity for a technology based invention which leads to development, production, and marketing tasks striving in for the commercial success of the invention” (Garcia and Calantone, 2001, p.112).
7
Concept Definition Literature
Creative industry A set of agents and agencies in a market characterized by adoption of an infinite variety of novel ideas within social networks and consumption.
Caves, 2000 Potts et al., 2008 Innovation An iterative process initiated by the perception of a new market and/or new service
opportunity for a technology b-based invention which leads to development, production, and marketing tasks striving in for the commercial success of the invention.
Garcia and Calantone, 2002
Innovativeness Degree of newness of an innovation Garcia and Calantone, 2002
Radical innovations Innovations that result in discontinuity on macro as well as micro level and have a relatively high degree of innovativeness.
Garcia and Calantone, 2002
Social network The notation of all the people with whom one shares a social relationship and social information sources.
Huberman et al.,2008; Potts et al., 2008
Table 2 - Definitions of focal concepts
1.4 CONTRIBUTIONS, RESEARCH DOMAIN AND RESEARCH SCOPE
This research contributes to the current literature by the provision of an addition layer of theory on perceived innovation resistance and this research contributes to broader understanding of innovation resistance in a context of industries heavily driven by complex social networks. Apart from the theoretical contribution, this research will provide an additional insight for managers in industries heavily driven by social networks or related industries. This insights gained by this research aim at the improvement of the innovation diffusion’s pace as well as innovation diffusion’s spread for organizations. The additional information and insights that innovation managers in these industries gain with this research will help innovation managers to optimize the efficiency of their innovation diffusion management. Furthermore, the research contributes to the field of social sciences by its
empirical application of music genres as social entities.
8
1.5 OUTLINE OF THE PAPER
9
Article Topic Context Theory development Theory testing Theory application Review of theory
Feder and Umali
(1993) “Reviews the theoretical and empirical literature on the adoption of agricultural innovations.” Agriculture x x
Fishman (1992) “Comparison of 18 case empirical studies on IT adoption.” IT x
Gatignon and
Robertson (1989) “An empirical test of the effects of competition on the adoption of technological innovations by organizations.” Laptop computers x x
Hoeffler (2003) “This research examines techniques for incorporating both mental simulation and analogies in to an existing preference measurement technique and shows that some methods enhance and other methods hinder predictive accuracy.”
Consumer electronics
x x
Kleijnen et al.
(2009) “This paper focuses on consumer resistance to innovation. The current study presents a conceptual framework which explicates the major components of consumer resistance.”
Conceptual x x
Kuisma et al.
(2007) “Identification of reasons for consumer resistance to Internet banking.” Internet banking x
Melenhorst et
al.(2006) “This study examined older adults’ motivation to adopt technological innovation”
Email usage x
Moreau et al.
(2001) “The research uses the knowledge transfer paradigm to demonstrate that both existing knowledge and innovation continuity are major factors in a consumer's adoption process.”
Consumer electronics
x x
Oreg (2003) This research developed a resistance to change scale to measure an individual’s dispositional inclination to resist changes.”
Office move x
Ram (1987) The goal of this paper was to develop a model of innovation resistance.
conceptual x
Ram and Sheth
(1989) The objective of this paper is to explain why consumers resist innovation even though they are considered necessary and desirable.
conceptual x
Sheth (1981) This paper attempts to theorize why people resist innovations conceptual x
Szmigin and Foxall (1998)
“Innovation resistance can no longer be regarded as a potentially negative aspect of target markets for new goods and services but rather a response based on rational choices.”
Payment methods x
Williams et al. (2009)
“The aim of this paper is to provide a comprehensive and systematic review of the literature pertaining to such adoption and diffusion issues in order to observe trends.”
IT x
Wood and
Moreau (2006) “This research suggests that adoption is rarely a neutral process and that consumers can experience strong emotions in the initial use of innovations.”
conceptual x x
10
2. LITERATURE REVIEW
2.1 INNOVATION RESISTANCE
Although the field of innovation adoption and rejection has rapidly grown over the last couple of years, the concept of innovation rejection or innovation resistance is almost totally ignored (Kleijnen et al., 2009; Gatignon and Robertson, 1985; 1989)4. Innovation resistance is a response,
which is based on conscious choice on the confrontation with an innovation (Szmigin and Foxall, 1998). When a consumer is confronted with an innovation, the innovation must lead to an improvement in performance, costs or social advantages in order to minimize resistance (Ram and Sheth, 1989). Furthermore, Kleijnen et al. (2009) suggest that innovation resistance is not only the ‘resistance to innovate’, but also the ‘not-trying’ of the innovation. This is problematic, especially in the case of radical innovations, since that initial resistance could be overcome by trying the innovation to a large extent or at least reduces the experienced risks for the unknown (Kleijnen et al., 2009; Rogers, 1995; Hoeffler, 2003; Feder and Umali, 1993).
From another perspective, the degree of innovation resistance is a continuum that starts at passive resistance and ends at active resistance (Ram and Sheth, 1989; Rogers, 1994). Others, (Kleijnen et al., 2009; Szmigin and Foxall, 1988) suggest that this continuum of innovation resistance should be classified in three broad types of consumer behavior: rejection, postponement and opposition. Rejection of an innovation implies that the consumer decides to favor the status quo (Kleijnen et al., 2009). Rejection of an innovation is most of the time the case when an innovation is radical (Lee and Clark, 1997). An example of an innovation that was collectively rejected is the ’Supersmoker’. This is a device that was marketed to substitute the cigarette. But, most of the smokers preferred their status quo and continued smoking regular cigarettes (Conceptentrends, 2010).
Postponement of an innovation implies that a consumer is not unwilling to adopt the innovation in general, but just not at that moment in time (Kleijnen et al., 2009). An example is the case of VoIP-technology; the technology is recognized and appreciated, but because the technology is not the standard technology yet the innovation is collectively postponed.
Opposition of an innovation is the notation that consumers are convinced that the innovation is unsuitable or unethical. Consumers are actively protesting against the innovation in order to prevent the innovation’s success, besides the non-adoption of the innovation. This collective innovation resistance is likely to affect market mechanisms (Kleijnen et al., 2009). An example is the opposition towards the introduction of nuclear power plants (Mazur, 1975). Important to note is the composition of innovation resistance. These three forms of resistance appear at collective as well as individual
11
level. The examples given are approached from a collective resistance, which this research does not discuss, but it the examples give a general idea of the dynamics of innovation resistance. This
research will solely approach innovation resistance on the individual level.
Although this discrete classification of innovation resistance provides useful insights in the level of the experienced innovation resistance, in practice it is hard to set rigid boundaries for this classification. Therefore, in this research the level of innovation resistance will be approached as a continuum, as in line with Ram and Sheth (1989) and Rogers (1994).
In this research innovation resistance is considered to be composed of two broad groups of antecedents that drive a person’s innovation resistance according to Kleijnen et al. (2009). The (degree of) innovation resistance is a direct consequence of (1) the level of perceived risks and (2) the height of experienced psychological barriers. Kleijnen et al. (2009) states that these antecedents are equally weighted. This research adopts this approach of Kleijnen et al. (2009) and interprets the relationship of the antecedents and innovation resistance as a logic and predetermined, perfect cause-effect relationship.
2.2 RISKS AND RESISTANCE
An innovation might conflict with a consumer’s beliefs and stereotypes and will carry risk for the consumer (Ram and Sheth, 1989). The degree of innovation resistance is partially driven by the risks that a consumer perceicves when confronted with an innovation. Literature (Kleijnen et al., 2009; Ram and Sheth, 1989) has defined physical, economic, functional and social risks as antecedents for consumer resistance. Physical risk concerns the potential (physical) damage to persons or property, which might be caused by the innovation. Economic risks are related costs of an innovation for the consumer; Functional risk is characterized by the uncertainty of the level of performance of the innovation and social risk is concerned with the risk of rejection by the social environment due to the adoption of an innovation (Kleijnen et al., 2009). Table 4 provides an overview of the risk antecedents of innovation resistance.
Antecedent Definition
Physical risk Risk of damage to persons or property of an innovation. Economic risk Risk of related costs of an innovation.
Functional risk Risk of underperformance of an innovation.
12
2.3 PSYCHOLOGICAL BARRIERS
Besides risks that drive innovation resistance there are psychological oriented antecedents that drive innovation resistance (Ram and Sheth, 1989). According to the literature (Ram and Sheth, 1989; Kleijnen et al., 2009; Hirschman, 1987; Herbig and Day, 1992) the traditions and norms, the strength of existing usage patterns, the perceived image and information overload are also antecedents of the of innovation resistance. When an innovation requires a consumer to deviate from the established traditions and norms, it implies that the consumer will have a certain level of resistance. The larger the deviation is, the higher the degree of innovation resistance will be (Ram and Sheth, 1989; Hirschman, 1987; Herbig and Day, 1992). The same holds for the strength of existing usage patterns. These patterns are the habitual behavior formed when using a product frequently over a long period of time (Kleijnen et al., 2009). The perceived image of an innovation is the association that a consumer has with the innovation (e.g. a status increase or decrease for the adopter). The more unfavorable the perceived image is, the higher the level of innovation resistance will be (Ram and Sheth, 1989). This antecedent translated to the perceived negativity of the image for the sake of harmony. The last antecedent of innovation resistance is information overload, which characterizes a consumer’s response to the ever-increasing information, knowledge and innovations to which the consumer is exposed (Herbig and Day, 1992). Table 5 provides an overview.
Antecedent Definition
Traditions and norms The extent to which an innovation deviates from current traditions and norms of the consumer.
Strength of existing using patterns
The strength of habitual behavior formed over a long period of time.
Perceived negativity of the image
The association of a consumer with the innovation.
Information overload A consumer’s response to the ever-increasing information, knowledge and innovations.
Table 5 - Psychological barriers
2.4 SOCIAL NETWORK MATURITY AND THE MUSIC INDUSTRY
13
sociology of arts by critical sociologists (Latour, 2005). It seems that the current dialog between sociologists and art-historians is more open nowadays and that aesthetics gain more respect as social entities (Prior, 2011). The cultural field creates a space for social entities, groups or individuals, which are constantly in state of struggle over accumulation and distribution different resources like recognition and high evaluation (Regev, 1994). DiMaggio (1987) showed a link between social structures in creative systems, patterns of artistic consumption and production in order to come to a classification of artistic genres. Participants of artistic genres participate voluntary, because genres provide a participant with a positive extension of their identity and therefore it is in the participant’s interest to be associated with the artistic genre. (DiMaggio, 1982; Hsu and Hannan, 2005).
From sociological perspective, especially music genres are seen as a meaningful construction of identity (Roy and Dowd, 2010). Fabbri (1982) attempted to explain the collective enactment of music genres in a set of socially accepted and generic rules. His theory of music genres covered the enactment of technical aspects of the music, the semiotic, the behavior and the ideology of a genre and its participants. A drawback of Fabbri’s (1982) notion of music genres is that the classification was considered static (Roy and Dowd, 2010; Negus, 1998). Lena and Peterson (2008) applied a more dynamic approach; they distinguished four genre types that typify the maturity trajectory of music genres. These genre types are Avant-garde, Scene-based, Industry- based and Traditionalist. The genre types are constructed on a set of characteristic that define the social structure, patterns of artistic consumption and creative production. Although all kind trajectories are possible, there are in general three distinct trajectories5 through which genres mature: Avant-garde – Scene-based – Industry-based
– Traditionalist (AgSIT), Scene-based – Industry-based – Traditionalist (SIT) 6 and Industry-based –
Scene-based – Traditionalist (IST) (Lena and Peterson, 2008). The latter one, the IST-trajectory, will be excluded in this research, since this trajectory is experienced by a small part of the music genres (approximately 15%) (Lena and Peterson, 2008).
Avant-garde genre type is characterized by small groups of participants with the objective to create a new music genre. The meetings of the participants are locally organized and do not have an explicit hierarchy. A participant’s view on technology is open-minded; participants experiment with new technologies and instruments. Most of the time the genres that fit the Avant-garde genre type will be temporary; a genre will die and the social network will dissolve or the genre will evolve to a genre that could be typified as a Scene-based genre.
Scene-based genre types are world/nationwide but also decentralized. The purpose of the participants is to create a larger community. Local communities stay in touch with each other via Internet and participants actively search for new participants. The major goal from a technological perspective is to codify technical innovations in the music genre in terms of instruments used as well
5 Lena and Peterson (2007) examined 60 genres; the vast majority of the genres sampled, 40 genres (67%), had the AgSIT-trajectory, followed by 11(18%) genres which had the SIT-trajectory. 9 (15%) genres had the IST-trajectory.
14 as music structures.
Industry-based genre types are characterized by their world-wide and professional character; the ideal is to create revenues and intellectual property. Industry-based genres are often centralized and are the home of large record companies for example. For technologies that are applied in these genres the participants try to standardize formats for the applied technologies. It is regular for these genres to lose a proportion of its early participants due to the popularity. These participants have the opinion that the genre has lost it true meaning. These dissidents are often tempted to start all over again in Avant-garde genre types.
Traditionalist genre types are industry based genre types that have lost popularity of the majority, but still have a core of dedicated participants. Often there is a gap of five or more years between the downfall of an Industry-based genre and the coalescence of a traditionalist genre. The participant’s view on technology is typified as an idealized orthodoxy; there is no- or very little room for innovations in the technologies used (e.g. a certain brand or kind of amplifier is used ever since or a certain brand or kind of guitar while technological superior alternatives are at hand).
As a genre matures, the social system changes shape and the reason of existence of the social network changes as well. Lena and Peterson (2008) suggests that as a genre matures, the culture in the genre types is tempted to change from open and explorative to an idealized orthodoxy towards technical innovations. An overview of genre types and their characteristics together with the level of maturity is exposed in table 6.
Avant-garde Scene-based Industry-based Traditionalist
Organizational form Creative circle Local scene Established field Clubs / associations
Organizational scale Local Local National / worldwide Local to international
Ideal / purpose Create a new genre Create a new community Create revenue, IPRs Preserve heritage and pass it on
Technical Experimentation Codifying technical innovations Creating standardization Idealized orthodoxy
Maturity Immature Mature
15
2.5 RESEARCH FRAMEWORK
As table 6 illustrates, there is reason to suggest that there is a cause effect relationship between genre maturity and a participant’s innovation resistance when it comes to the technological aspects of the genre (Lena and Peterson, 2008). For this research, maturity levels are divided bilaterally. A genre’s maturity is considered to be (1) immature, when a genre is in the Avant-garde or in the Scene-based phase of the trajectory, and (2) mature, when a genre is in the Industry-based or in the Traditionalist phase of the trajectory. The reasoning behind this division is that oligopolistic markets characterize industry-based genres and that the innovativeness of the large record companies in these genres is considered low, although these multinational corporations apply an open system to develop and produce music (Lopes, 1992; Christianen, 1995). These large record companies inhibit musical innovations in order to sustain genres profitability. Therefore, artists are constrained to produce only slightly different content (Lena and Peterson, 2008; Peterson and Berger, 1975,). On the contrary, independent record companies dominate Scene-based genres and the innovativeness of these companies is considered relatively high (Christianen, 1995). In the trajectories of Lena and Peterson (2008) Avant-garde genres are more immature than the Scene-based genres. Traditionalist genres are typified more mature than Industry-based genres, since the Traditionalist genre type is the last stage of maturity of a genre. It should be noted that it is hard to state a solid division that industry-based genres from scene-based genres. It is reasonable that there will be genres that fit the characteristics of a mature scene-based phase as well as the early industry-based phase.
Participants that participate in one genre are not bounded to that single genre. An individual can be a participant of several different genres at the same time (Lena and Peterson, 2008). Roy and Dowd (2010) make the notation that those who adapt multiple genres can spur innovation, since they can combine disparate elements of various genres into a new fusion. For this research there is argued that individuals who participate in multiple genres are familiar with different genre doctrines and therefore less influenced by genre doctrines. These persons are considered to be more independent of the social pressures genres considered to have. This leads to an extra concept in the research framework that moderates the effect of genre maturity on a participant’s innovation resistance: genre multiplicity.
As the literature section discussed, innovation resistance is approached in the literature via eight antecedents that are grouped in two broad groups ‘Perceived Innovation Risk’ and ‘Psychological Barriers’. However, a factor analysis of the results suggested that another classification of the antecedents fitted this research in a more compelling manner.
16
backbone did not changed and all the original antecedents are still adopted, but in another order than the existing literature suggests. Table 7 provides an overview of the reordered concepts.
Antecedent Initial construct New construct
Physical risk Perceived Innovation Risk (PIR) Physical Risk (PR)
Economic risk Perceived Innovation Risk (PIR) Economic and Functional Risk (EFR)
Functional risk Perceived Innovation Risk (PIR) Economic and Functional Risk (EFR)
Social risk Perceived Innovation Risk (PIR) Social Barriers (SB)
Deviation of traditions and norms Psychological Barriers (PB) Psychological Barriers (PB)
Deviation of existing usage patterns Psychological Barriers (PB) Psychological Barriers (PB)
Negativity of the perceived image Psychological Barriers (PB) Social Barriers (SB)
Information overload. Psychological Barriers (PB) Social Barriers (SB)
Table 7 – Overview of the regrouping of the antecedents
17
Table 8 - Hypotheses
# Hypotheses Concepts + / - Supporting literature
1. The maturity of a music genre is positive related to the size of a participant’s perceived economic and functional risk concerning the adoption of a radical innovation.
Genre maturity, Economic and Functional Risk (EFR)
+ Kleijnen et al. (2009), Lena and Peterson (2008), Ram and Sheth (1989).
2. The maturity of a music genre is positive related to the size of a participant’s perceived physical risk concerning the adoption of a radical innovation.
Genre maturity, Physical Risk (PR)
+ Kleijnen et al. (2009), Lena and Peterson (2008), Ram and Sheth (1989).
3. The maturity of a music genre is positive related to the size of a participant’s experienced social barriers concerning the adoption of a radical innovation.
Genre maturity, Social Barriers (SB).
+ Herbig and Day (1992), Kleijnen et al. (2009), Lena and Peterson (2008), Ram and Sheth, (1989).
4. The maturity of a music genre is positive related to the size of a participant’s experienced psychological barriers concerning the adoption of a radical innovation.
Genre maturity, psychological barriers.
+ Herbig and Day (1992), Hirschman (1987), Kleijnen et al. (2009), Lena and Peterson (2008), Ram and Sheth, (1989).
5a. The genre multiplicity of an individual will negatively moderate the relationship of a genre’s maturity and participant’s perceived economic and functional risk.
Genre maturity, genre multiplicity, Economic and Functional Risk (EFR) - Kleijnen et al. (2009), Lena and Peterson (2008), Ram and Sheth (1989), Roy and Dowd (2010).
5b. The genre multiplicity of an individual will negatively moderate the relationship of a genre’s maturity and a participant’s perceived physical risk. Genre maturity, genre multiplicity, Physical Risk (EFR). - Kleijnen et al. (2009), Lena and Peterson (2008), Ram and Sheth (1989), Roy and Dowd (2010).
5c. The genre multiplicity of an individual will negatively moderate the relationship of a genre’s maturity and a participant’s experienced social barriers.
Genre maturity, genre multiplicity, Social Barriers (SB).
- Herbig and Day (1992), Kleijnen et al. (2009), Lena and Peterson (2008), Ram and Sheth, (1989). Roy and Dowd (2010).
5d. The genre multiplicity of an individual will negatively moderate the relationship of a genre’s maturity and a participant’s experienced psychological barriers.
Genre maturity, genre multiplicity, psychological barriers (PB).
18
All concepts and their relationships in terms of directions are modeled and presented in figure 1.
Figure 1 - Research framework
-19
3. METHODS
3.1 THE CONTEXT FOR EMPERICAL RESEARCH AND THE DATA COLLECTION 3.1.1 Research purpose
The purpose of this research is to understand the relationship of social network in industries strongly driven by social networks and innovation resistance on the level of an individual. This relationship is conducted by comparing music genres’ maturity levels with the presence of the innovation resistance’ antecedents empirically, since music genres are considered exemplary for complex social networks and social networks drive the music industry heavily. For the data collection an online questionnaire was distributed to a population of DJs in order to gain an understanding of the relationships of complex social networks and innovation resistance. This empirical application of the link of music genre characteristics as complex social networks and individual innovation resistance is, by the researcher’s best knowledge, new to the field of innovation resistance.
3.1.2 The population
The population that was targeted in the research are individuals who are disc jockeys (DJs). DJs are not limited to a single music genre (or a limited in a set of genres) that the DJs participate in (e.g. a guitarist is considered to be more limited for example because the guitar has limitations). Next to that, the DJ-industry has a considerable size. Although there is no clear definition of the boundaries of the industry at hand, the DJ-industry generates as much as $10 billion a year worldwide and employs approximately 60,000 DJs (30,000 part-time; 15,000 fulltime; 15,000 at an amateur level) in the United states of America alone (discjocky101.com, 2011; profile-america.com, 2005). Therefore, DJs are considered to be an appropriate population. DJs are entertainers who select and play recorded music since 1906 (Brewster and Broughton, 2006). The National Association of Mobile Entertainers (NAME) classifies DJs in three broad types: mobile DJ (who travel to parties to entertain), club DJs (who are employed by nightclubs and bars/lounges) and on-air Radio DJs (who are personalities and entertain the radio station listeners) (profile-america.com, 2005). The characteristics of radio DJs show too many inequalities with the other two categories’ characteristics that radio DJs are not taken in account in this research.
20
single sounds or samples (recorded over time or recorded on the spot) and air them immediately to the crowd. Also different sound effects, edit options and filters (e.g. delay, reverb and flanger) enhance the mixing of the DJ. The last decade the evolution in DJ-equipment excelled at a pace previously unseen (Norris, 2011). Next to the opportunity to provide live performances, software solutions provided a new way of playing recorded music. In this case, DJs use software solution on a laptop and control it by the use of a Midi-controller or a Time-code set up7. The laptop and controller are in ownership of the DJ and brought to the performance. These software solutions are considered to be the latest radical innovation in equipment. As with all major changes, a fierce debate8 is going on in
peer communities of DJs whether or not a DJ should perform their acts by the use of turntables (vinyl), cd-systems (CDs) or software solutions (digital content). Therefore, the population is expected to provide a strong and explicit opinion on the adoption or rejection of radical innovations in their equipment.
3.1.3 The data collection
An online questionnaire was distributed in October 2012 via social media and online forums (Dutch as well as international) that discuss DJ-related matter (e.g. upcoming EP-releases, club guide and tech-talk). An overview of the channels together with a description is exposed in table 8.
For the channel ‘Facebook’ a snowball method was used in order to distribute the questionnaire; in the case of forums permission was requested via the administrators of the forum and posts were made in the sections recommended by the administrators. As table 8 shows, there are some forums selected that target a specific music genre. The expectation was that the majority of the potential respondents are active in immature music genres since Lena and Peterson (2008) pointed out that the local communities of immature music genres stay in touch with each other by the use of digital platforms. In the aim for a balanced response number between immature and mature, there was decided to include channels that are focused on mature genres. This worked out relatively fine. Of the respondents 38,2% was solely participating in immature genres, 25,8% was solely participating in mature genres and 36% was participating in both immature and mature genres. The forum threads that contained the invitation to participate were checked on a daily basis in order to provide answers to questions of forum-members considering this research. To spur the response a coupon of €100,- was raffled among the participants.
7This is a technology that enables DJs to start, cue and mix music on a laptop via regular cd-systems and turntables.
21
Channel Description
Bax-shop.nl A Dutch forum that discusses inter alia DJ-related matters (number of members on 19/9/2012 was 9,513).
Discomusic.com An international forum that discusses inter alia DJ-related matters in the Disco genre (number of members on 19/9/2012 was 5,771).
DJresource.nl A Dutch forum that discusses inter alia DJ-related matters (number of members on 19/9/2012 was 30,560).
Djtechtools.com An international forum that discusses DJ-related matters in general (number of members on 19/9/2012 was 81,655).
GHF.info An international forum that discusses DJ-related matters in harder styles (number of members on 19/9/2012 was 45,983).
Leipeshit.nl A Dutch forum that discusses inter alia DJ-related matters in the Hip-Hop genre (number of members on 19/9/2012 was 24,056).
New-line.nl A Dutch forum that discusses inter alia DJ-related matters (number of members on 19/9/2012 was 6,014).
Table 8 - Distribution channels of the questionnaire
The sum of total of all views of the posts on the forums was 8861. It was not possible to recover the number of unique visitors of the topics posted in every case. It is assumed though, that the number of unique visitors is considerably lower, because in some of the topics an extensive discussion on the research topic started by the forum members.
A total of 225 participants completed the questionnaire, resulting in a response rate of at least 2,5%. The method used is not as direct as an offline approach or a direct online approach, however, the response count as well as the response rate is perceived as sufficient. It was not able to trace the response /views ratio of Facebook. The estimation is that this was respectively higher than on the forums.
22 97% 3% Sex Male Female 19% 65% 9% 7% Age Under 20 20 - 30 30 - 40 Over 40 0.40% 0.40% 3.60% 0.40% 2.80% 2.80% 0.80% 0.80% 0.40% 79.10% 0.40% 1.20% 6.90% 0.00% 10.00% 20.00% 30.00% 40.00% 50.00% 60.00% 70.00% 80.00% 90.00%
Origin (by country)
89.10% 0.80% 2.40% 6.90% 0.40% 0.40% 0.00% 20.00% 40.00% 60.00% 80.00% 100.00%
West Europe East Europe South Europe North America South America Pacific
Origin (by region)
23
Table 9 - Overview of frequencies of the independent- and control variables
Two field experts are interviewed in order to place the quantitative results in context and validate the outcomes of the quantitative part of this study. The experts in the field that are interviewed are mr. Z. Pillay; DJ/Producer, artist-programmer at Pand 48 and event manager at KOPJEK Creatives, mr. W. Praamstra, Chief editor at 3voor12.nl – department Groningen, Friesland, Drenthe.
Though there is no specific quantitative data of the population’s characteristics present, the field experts gave their interpretation of the match of the sample and the population based on their experiences. The field experts noticed some differences between the sample and the appointed population. They argue that it is unlikely that the vast majority of DJ’s is participating in House or Techno. Next to that, the field experts notice the skew in the origin of the respondents towards the Netherlands/west-Europe. The education level of the respondents in the sample is considered to be
46%
32% 12%
10%
Lenght of engagement
Less than 5 years 5 to 10 years 10 to 15 years Over 15 years 47% 38% 15%
Novelty of current Equipment Cdplayers and Turntables Software solution combination 38% 26% 36%
Participating in genre ( by maturity) Immature Mature Both immature and mature 16% 51% 22% 7% 4%
Participating in genre (by number) One single genre 2-3 genres 4-5 genres 6-7 genres 8 or more genres 3% 30% 19% 19% 9% 18% 63% 3% 3% 4% 16% 6% 10% 16% 7% 11% 1% 56% 22% 0% 10% 20% 30% 40% 50% 60% 70%
24
higher than the field experts experience this to be the case in practice. The field experts considered the other characteristics of the sample an honest reflection of the population. The notation should be made that the field experts base this interpretation on their experiences and this is still exposed to subjectivity.
3.2 MEASUREMENT INSTRUMENTS 3.2.1 Control variables and genre participation
The questionnaire that was distributed consists of three sections. The first section contains a set of general questions in order to gather the data on control variables and the independent variable (genre maturity) and moderating variable (multiplicity) of the research of the respondent (table 10 provides an overview of the control variables). Most of the control variables are straightforward; normative innovativeness and the domain specific innovativeness are more complex and require additional explanation.
Adoptive innovativeness is the tendency to buy new products in (Roehrich, 2004). The measure of one’s adoptive innovativeness was used in order to gain general understanding of the respondent’s normative innovativeness and served this research as a control variable. This was measured by the use of a set of questions developed by Raju (1980). Raju’s (1980) innovativeness scale is designed to measure consumer tendencies toward exploratory behavior. The author’s results of these questions show a good internal consistency (Roehrich, 2004). Others confirmed the consistency of the measure (e.g. Joachimsthaler and Lastovicka, 1984).
In order to test the innovativeness of the respondents when it comes to their equipment, a set of statements was used that are developed in order to measure one’s domain specific innovativeness. This bundle of statements is adopted from Goldsmith and Hofacker (1991) and was validated by Goldsmith et al. (1995).
3.2.2 Music genres, genre maturity and genre multiplicity
25
Altogether 26 genres were directly adopted from Lena and Peterson (2008). These genres were rearranged to 14 genres. In addition of these 14 adopted genres, 5 genres were classified for this research independent of Lena and Peterson’s (2008) classification. These 5 genres are genres in which it is expected that a large number of DJs is participating in and therefore these genres are included in this research. An overview of the classification and argumentation for the selection is found in table 11. This adds up to a total of 19 genres that were used in the survey. 12 of the genres are categorized as mature and 7 are categorized as immature. In order to validate the proposed classifications, the two experts in the field mentioned in the data collection section checked the classification. After some adjustments in the original proposed classification both field experts agreed upon the classification. An overview of all genres and their classification is show in table 12.
Control variables Distribution
Sex Male/female
Age Under 20/20-30/30-40/over 40
Origin By country / by region
Education Primary school/high school/college/university
Length of engagement Shorter than 5 years/ 5-10 years/10-15 years longer than 15 years Novelty of current equipment Turntables and/or CD-systems vs. digital solutions
Normative Innovation Statement 2.1-2.5 (see appendix A)
26
Description Genre type Maturity Source
Founded in the UK, Drum and Bass spread over the world to local communities that stay in touch via the internet.
Scene-based Immature www.futurednb.net/what-is-drum-and-bass [accessed: 24/9/2012]
Mainstream influences, recognized pop-artists use Dubstep in their songs, the founders of Dubstep left the genre to develop side trail of Dubstep.
Industry-based Mature
www.udubstep.com/the-history-of-dubstep/
[Accessed: 24/9/2012]
Harder styles became popular for a certain period of time in the year 2002. Relatively small scenes in the Netherlands, UK and France are active still today.
Traditionalist Mature www.corehistory.blogspot.nl/ [Accessed: 24/9/2012]
Founded in Latin America and now a worldwide genre in local scenes. Some tracks of the Reggaeton genre made it to the pop charts and large record companies starting to gain ground in the scene.
Industry-based Mature
hiphopisland.com/Got2know/Reggaeton /Reggaeton.html
[Accessed: 24/9/2012]
Founded in the ’90 the Trance genre took a rapid flight. At the beginning of the 21th century trance was very popular. Now Trance is not as popular anymore; many early participants became dissatisfied with the mainstream character of the genre. Still, some Trance related festivals are held each year.
Traditionalist Mature
www.voices.yahoo.com/a-history-trance-music-2064829.html/ [Accessed: 24/9/2012]
Table 11 – Classification of the additional genres
Genre Genre type Maturity
level
Drum and Bass Scene-based Immature
Dubstep Scene-based Immature
Garage Scene-based Immature
House Scene-based Immature
Jungle Scene-based Immature
Metal (Death metal, Black metal, Grindcore) Scene-based Immature
Techno Scene-based Immature
Blues (Urban Blues, Jump Blues, Delta Blues) Industry based / traditionalist Mature
Disco Traditionalist Mature
Hardcore (Hardcore, Hardstyle, Jumpstyle, Scharnz, Industrial and Terror) Traditionalist Mature Jazz (Bebop Jazz, Chicaco jazz, jazz fusion, New Orleans jazz, cool jazz) Industry-based / traditionalist Mature Rap and Hiphop (East Coast Gangsta Rap, West Coast Gangsta Rap, Humor Rap, Conscious Rap Industry-based Mature
Reggae Industry-based Mature
Reggaeton Industry-based Mature
Rock (Grundge rock, Rockability, Folk rock, Rock-n-Roll) Industry-based / traditionalist Mature
Salsa Traditionalist Mature
Soul Traditionalist Mature
Tango Industry-based Mature
Trance Industry-based Mature
27
3.2.3 Antecedents of innovation resistance
Innovation Risks - Economic and Functional Risks (EFR) and Physical Risks (PR)
The second section of the questionnaire discussed the level of perceived risks and the size of the psychological barriers. Perceived innovation risk was tested by the use of Cunningham’s (1967) two-component risk model. This model states that the overall risk is the uncertainty that comes with the innovation and the danger of the consequences of the adoption of the innovation. Therefore, for each risk type two statements are posed; one statement concerned the perceived uncertainty of an innovation, and one statement concerning the danger of the consequences of adopting an innovation. According to Mitchell’s (1998) evaluation of risk measures Cunningham’s function is best evaluated9
and the most generally useful to measure consumer risk.
Social barriers (SB)
The perceived negativity of the image of the innovation was measured with a statement originally used by Karahanna et al. (1999), which discusses the status increase or decrease that one is expecting to experience after adoption of the innovation. In the case of information overload, the statement was developed from scratch for this research. Social risk is also part of social barriers and is approached in the same manner as other perceived innovation risks.
Psychological barriers (PB)
The required deviation of traditions and norms was measured by the use of a statement adapted from Agarwal and Prasad (1998) and slightly modified in order to fit this research. The same format was used to measure one’s deviation of an existing usage pattern. Also in this case a statement was posed that shows a respondent’s deviation required from his/hers current usage patterns in order to adopt the innovation.
28
3.3 MEASUREMENT MODEL 3.3.1 Structure
First, the dependent variables were grouped by the use of a factor analysis. Then music genres were classified based on the predetermined distribution as mature or immature (or both). Also the number of genres in which a respondent was participating was extracted from the data. Dummy variables are created for all categorical variables via a comparison of the baseline category and the other categories (the baseline category was selected based on the largest n-value).
After that, a two-step multiple linear regression analysis was applied for each of the dependent variables. This resulted in four separate models that are tested. This provided the research with the results that were necessary to answer the research question.
In addition, the correlating genres in terms of selection by respondents were grouped in genre clusters by the use of a second factor analysis. Subsequently, a two-step multiple regression analyses was applied for each dependent variables with the differences in genre clusters as focal independent variable instead of genre maturity. The results of these analyses are also presented. After these analyses a comparison of the different models is made based on the squared R-values and the significant F-ratios.
After the quantitative results have been distracted from the data, the results were presented to the two field experts. By the use of a semi-structured interview the results were provided some additional explanation and context.
3.3.2 Reliability and validity precautions
A proportion of the questions and statements required some minor modification in order to fit the research, these questions are adjusted with care.
The questionnaire was pre-tested by peer researchers who filled the questionnaire out loud before the questionnaire was distributed. After this, the ambiguities were discussed and points of discussion were reconsidered, clarified or removed.
To minimize common-method variance and minimize the overall chance on type I and type II errors several variables were reversed coded. This was done to increase the reliability and validity of the content. It is common knowledge that questionnaires frequently have difficulties to assure a high content validity and reliability of questionnaires. The reversed variables were transformed back to their mirrored equivalent after removal of the cases that did not match the standards10.
In order to verify that the measurement instruments were reliable and will produce very similar outcomes in the case of repetition of the research, the vast majority of the questions and statements tested in previous research on innovation resistance/adoption or at least based on theory. In
29
30
4. RESULTS
The result section is structured in the following way. In the first part the variables are grouped based on factor analyses. In the second part the outcomes of the two-step multiple linear regression analyses are presented. In the third and final section, another perspective on the data is proposed and this new model is compared to the initial measurement model.
4.1. CLUSTERING THE ANTECEDENTS OF INNOVATION RESISTANCE
Since the conceptual model for the majority consists of broad concepts, the interrelationship of the variables was analyzed in order to group the variables. According to the literature and the research framework there are two broad groups of antecedents for innovation resistance: Perceived Innovation Risks and Psychological barriers.
However, after the execution of a factor analysis, the initial grouping of the dependent variables required a re-grouping for this research in order to apply analyses on them. The factor analysis did not show a sufficient interrelationship of the variable groups as proposed in the initial grouping. The initially proposed groups are rearranged into four new dependent variables: Physical risk (PR), Economic and functional risk (EFR), Psychological Barriers (PB) and Social Barriers (SB).
A principal component analysis was conducted on 12 items with orthogonal rotation (via varimax). The Kaiser-Meyer-Olkin measure stated KMO = .633 which is well above the bare minimum of .5 recommended by Kaiser (1974). Field (2005) considers scores between .6 and .7 as mediocre. However, the score of KMO = .633 shows that the sample size of n = 225 was adequate for factor analysis. Bartlett’s test of Sphericity shows a Chi-square of 529,847, p <.001, which indicated that the correlations between the items were sufficiently and that an identity matrix was not the case. Therefore the factor analysis was appropriate for these variables.
31
Variables EFR SB PB PR
I want to be certain about the capabilities and functionality that the gear has ,771
I want to be certain about the costs that comes with the product ,733
I consider the potential financial consequences for me in making the decision ,716
I consider potential consequences of the product lacking certain functions and capabilities ,710
I want to be certain that my peer DJs approve upon my decision to buy the new gear ,855
I consider the potential consequences that my peer DJs might disapprove of my decision to buy the new gear ,822
In my decision to cutting edge DJ equipment I’m overwhelmed with the amount of information I find about the gear ,501 ,363
Having cutting edge DJ equipment is a status symbol for me and my peer DJs ,379
For me buying or using cutting edge DJ equipment conflicts with the traditions and norms of what DJing is about ,826
In order to use cutting edge DJ equipment I have to alter the way in which I am currently performing drastically ,795
I want to be certain of the physical safety of the product ,841
I do consider potential physical consequences in the decision ,784
Eigenvalue 2,758 1,902 1,390 1,162
% of variance 22,98 15,85 11,59 9,665
Cronbach’s reliability α ,564 ,649 ,612 ,738
Notes: Only factor loadings of >.3 are included. The bold numbers are clustered
32
EFR PR SB PB
Step 1 1
Step 2 Step 1 Step 2 Step 1 Step 2 Step1 Step 2
β β β β β β β β
Sex - Female vs. male -,041 -,029 -,026 -,010 -,034 -,029 -,061 -,060
Age ,116 ,099 ,056 ,120 ,110 ,125 ,027 ,009
Region of origin -Non W-Europe vs. W-Europe ,167* ,164* -,006 ,019 -,088 -,075 -,076 -,081
Education level ,051 ,066 -,078 -,064 -,107 -,099 -,005 -,001
Length of engagement DJ -,050 -,060 -,013 -,127 -,318*** -,337*** -,129 -,111
Novelty of current gear ,010 ,004 ,093 ,101 -,067 -,075 -,421*** -,426***
Location’ s size - Bars/clubs vs. home/bars -,042 -,050 ,164* ,163* -,010 -,020 -,077 -,081
Location’ s size - Clubs/festivals vs. home/bars -,109 -,102 -,061 -,038 -,061 -,069 -,069 -,072
Location’ s size - Illegal vs. home/bars -198** -,214** ,032 ,044 ,002 ,000 ,016 ,007
Normative Innovativeness -,025 -,030 -,129 -,154* -,210** -,209** ,071 ,075
Domain Specific Innovativeness -,137* -,118 -,054 -,039 ,160* ,159** -,147* -,144*
Number of genres -,049 ,145 -,009 -,058 ,079 -,080 -,016 ,038
Number of genres * Genre maturity -,145 ,014 ,207 -,024
Genre Maturity - Both vs. Immature -,164 -,157 -,021 -,025
Genre Maturity - Mature vs. Immature -,066 ,317* ,133 -,072
R2 ,106 ,131 ,056 ,105 ,153 ,163 0,226 0,230
Adjusted R2 ,055 ,068 ,002 ,04 ,103 ,105 0,182 0,170
F 2,070* 2,075* 1,030 1,810* 3,064*** 2,673*** 5,103*** 4,114***
n 225 225 225 225 225 225 225 225
Note:
All significant values are presented in bold. (p <.05 = * ; p <.01 = ** ; p <.001 =***)
33
4.2. REGRESSION ANALYSES OF GENRE MATURITY MODEL 4.2.1 Fit of the models with independent variable genre maturity
As table 14 shows, none of the models fitted the data extremely well. The largest F-ratio of the models is 5,103 (PB, step-one). The largest amount of variance that was explained in the dependent variable was 23,0% (PB, step-two). However, all step-two models showed a significant F-value, which indicates the presence of a linear relationship. Therefore, all models are considered to fit the data sufficiently, though the fit is far from perfect. Figure 2 presents all significant relationships that the analyses showed with their beta and their significance levels.
4.2.2 Perceived economic and functional risks (EFR)
The results of the model EFR showed that there was no significant predicting effect of maturity on the perceived economic and functional risk of an innovation. Neither was there a significant moderating effect of genre multiplicity measured. This is not surprising since there is no significant predicting effect. Therefore hypothesis 1 and hypothesis 5a are both rejected. DJs that perform on illegal parties tend to perceive less economic and functional risks of innovation than DJs that play in Bars or at home do (β= -,214*). DJs that live in other regions than West-Europe perceive a higher level of
economic and functional risks than DJs from West-Europe do (β= -,164*).
4.2.3 Perceived physical risks (PR)
The model of PR showed that DJs who are solely participating in mature music genres, perceive significantly more physical risks of innovations than DJs who are solely participating in immature genres do, with a relatively large coefficient of β = 0,317*. The results did not show a significant
moderation effect by the number of genres that a DJ is participating in on the relation of genre maturity and PR. Therefore, hypothesis 2 is accepted; genre maturity is a predictor of perceived physical risks. Hypothesis 5b is rejected; the results did not show any moderating effect by the number of genres. Normative Innovativeness showed a negative relationship with PR (β= -,154*). DJs
that perform most frequently in bars and clubs tend to perceive more physical risks of innovation than DJs that play in bars or at home do (β= ,163 *).
4.2.4 Experienced social barriers (SB)
There was no significant predicting effect found of genre maturity on SB in the results. Neither did the results show a significant moderating effect. Therefore hypotheses 3 and 5c are both rejected. The results indicate that DJs that practice the hobby/occupation of a DJ for a shorter time period are expected to experience significant higher social barriers (β= -,337***) than DJs who practice the
34
Furthermore, there is a negative relationship between the normative innovativeness of a DJ and the experienced social barriers (β= -,209**) and a positive predicting effect of domain specific
innovativeness and the experienced social barriers (β= ,159 *).
4.2.5 Experienced psychological barriers (PB)
In the case of experienced psychological barriers (PB), the results did not show a significant predicting effect of genre maturity on PB. As in the case of the other models, no moderating effect was measured. Again, this is inherent to the absence of a significant predicting effect. Therefore, hypotheses 4 and 5d are therefore rejected. The results did show that DJs that have current gear that is novel in technological terms (A digital solution in combination with a midi controller and/or time-code setup) are experiencing strongly less psychological barriers in the case of a radical innovation in their equipment than DJs who perform with CDs or vinyl do (β= -,426***). The results also suggest
that there is a negative predicting effect of domain specific innovation on PB (β= -,144*).
Note: * p <0.05; ** p <0.01; *** p < 0.001 Figure 2 - Measurement model and coefficients
GENRE MATURITY
PERCEIVED ECONOMIC AND FUNCTIONAL RISKS (EFR) PSYCHOLOGICAL BARRIERS (PB) NOVELTY OF CURRENT EQUIPMENT LENGHT OF ENGAGEMENT NORMATIVE INNOVATIVENESS SOCIAL BARRIERS (SB) PERCEIVED PHYSICAL RISK
35
4.3. REGRESSION ANALYSES FOR CLUSTERED MUSIC GENRES 4.3.1 Genre clustering
In the analyzing process of the research model the data suggested a pattern in music genre selection. This provided a new perspective in addition to the initial measurement model. DJs are often
participating in multiple genres; the correlation levels suggested the relationship of genres (immature as well as mature) that are often played together by DJs. A schedule that provides an insight in the interaction of the different genres is presented in Appendix B. The pre-analyses of the correlations supported further factor analyses of the genres. This resulted in five clusters of genres in which DJs often participate at the same time. An overview of the clusters (table 15):
Cluster 1 Salsa-HipHop & Rap-Reggae-Reggaeton (SHRR)
Cluster 2 Blues-Jazz-Tango-Soul (BJTS)
Cluster 3 Metal-Rock-Disco (MRD)
Cluster 4 Dubstep-Drum & Bass-Trance-Harder Styles (DDBTH)
Cluster 5 Techno-House (TH)
Table 15 - Clustered genres
A principal component analysis (PCA) was conducted on 18 genres with orthogonal rotation (varimax). The Kaiser-Meyer-Olkin measure stated KMO = .694 which is well above the bare minimum of .5 recommended. Therefore, the score of KMO = .694 shows that the sample size of n = 225 was adequate for factor analysis. Bartlett’s test of Sphericity shows a Chi-square of 1054,942, p <.001, which indicated that the correlations between the items were sufficiently and that an identity matrix was not the case. Therefore the factor analysis was appropriate for these variables.
Six
36
Genres SHRR BJTS MRD DDBTH TH JG
Salsa ,812
Hip hop and Rap ,758
Reggae ,559 Reggaeton ,484 Blues ,833 Jazz ,716 Tango ,563 ,308 Soul ,467 ,489 Metal ,784 Rock ,731 Disco ,414 ,622 Dubstep ,754
Drum & Bass ,692 ,431
Trance ,506 Harder styles ,475 Techno ,795 House ,793 Jungle ,788 Garage ,638 Eigenvalue 3,862 2,018 1,852 1,433 1,265 1,066 % of variance 20,325 10,619 9,746 7,543 6,659 5,609 Cronbach’s reliability α reliability α ,690 ,643 ,877 ,536 ,633 ,320
Note: Only factor loadings of >.3 are included. The bold numbers are clustered
