WILL I TAKE YOUR ADVICE, OR NOT?

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WILL I TAKE YOUR ADVICE,

OR NOT?

A RESARCH OF SOCIAL INFLUENCES INVOLVED

IN THE ADOPTION PROCESS OF

HIGH-TECHNOLOGY INNOVATIONS.

Master thesis, MSc BA, specialisation Marketing Management

University of Groningen, Faculty of Economics and Business

July, 2012

ROBERT-JAN SCHRA

Student number: 1929003

Ambonstraat 15a

9715 HB Groningen

tel.: +316 308 38 953

E-mail: r.schra@student.rug.nl

Supervisor/ university

Drs. J. Berger

Drs. N. Holtrop

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Abstract

Social influence plays a very important role in the adoption process of the consumer. Due to the information sharing among consumers, the complexity, perceived uncertainty and the risks reduces. On the other hand, perceived relative advantage increases. Five adoption groups are formulated; innovators, early adopters, early majority, late majority and laggards. For the adoption of high-tech products, non-marketing sources are most influential for these adoption groups. Innovators, early adopters and early majority are most influenced by non-marketing, mass media sources like, internet (social media), virtual communities and expert endorsement. For the late majority and laggards, non-marketing and personal delivered sources like friends and family are the most influential.

Key words; Social influence, innovation, adoption group, high-technology.

Introduction

Understanding whether and why consumers will adopt new products or services is a critical insight for managers involved in marketing innovations (Arts et al., 2011). Consumers are frequently confronted with new innovations. The common thought is that innovations are an improvement of existing products and services (Ram, 1987). Nevertheless, not all innovations will be adopted successfully. Innovations require the consumer to adopt new behaviours, or discontinue past behaviours. Due to the uncertainty of unfamiliar technologies, 80 percent of innovative new products fail (Castano et al., 2008; Crawford, 1977). The consumers may adopt new technologies to obtain useful benefits (the benefits are, according to Hoeffler (2003), a key aspect of new innovations), but also to enjoy the experience of the new technologies. On the other hand, the consumers could reject the innovation (despite their potential usefulness and benefits) because their fear uncertainty of being overwhelmed by the technology (Kulviwat et al., 2007). Mick and Fournier (1988) defined this phenomenon as the ‘technology paradox’.

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mental models (Reinders et al., 2010). It is essential that many different players in the adoption network are persuaded to adapt their behaviour. If there is no support for the innovation in the adoption network, the change of failure is significant.

A negative post-purchase attitude by early adaptors can arise because early adopters by definition have high expectations of a new innovation. If these high expectations will not be met, dissatisfaction will occur once they have purchased and used the innovation. This will result in a negative word-of-mouth and negative attitude towards the innovation.

Innovation adoption can be defined as the decision of the consumer to make full use of an innovation (Rogers, 2003).

Before the consumer adopts an innovation, it will follow multiple stages, from awareness till continued use of the innovation (Rogers, 2003). During the stages of this process, the adopter gains impressions and forms perceptions of the innovation. By taking all these perceptions in considerations, choice decision will be formed (Arts et al., 2011).

In this thesis, innovation adoption will be defined as the purchase of the innovation. This is possible since the consumer has followed multiple stages before purchase (Rogers, 2003). The consumer would not purchase the innovation if they were not convinced of the benefits and advantages. It is valid to presume that consumers who purchased the innovation will fully use it, due to the multiple stages of scrutinizing the innovation before purchase. Especially in cases of high-technology innovations, the consumer scrutinizes the innovation carefully, due to the high uncertainty, high risks (Rosen et al. 1998) and usually higher costs of a high-tech innovation. Therefore, we can presume that the consumer will make full use of the innovation after purchase.

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characteristic that is far more important in the decision making of the adoption process than consumer and innovation characteristics. This characteristic is Social Influence.

Social influence stimulates social contagion and increases adoption behaviour among consumers (Goldenberg et al., 2009). Social influence may be a critical element in consumer’s decision making (Kim & Park, 2011). By consulting other consumer’s information and opinions, the innovation characteristics (relative advantage, uncertainty or risk and complexity) could be enhanced or reduced. This illustrates that social influence is indeed very important in the decision making, due to its ability to influence the attitude of consumers towards an innovation by reducing complexity, risks and uncertainties, while it also could increase relative advantage, because consumers have a better understanding of the innovation.

Social influences are more important in high-technology innovations than in low-technology innovations. A high-tech innovation is more complex and has more risks and uncertainties for the consumer than low-tech innovation. This complexity and uncertainty increases the need for social interaction and information from other individuals (Reinders et al., 2010). Consumers do not like uncertainty, so they consult other individuals in order to increase their knowledge and decrease their uncertainty (Peng et al., 2011). Therefore, in situations with high-tech innovations, the need for social interaction is more present than in situations with low-tech innovations. So, for a study that studies social influences, a study with high-tech innovations will be more applicable, than with low-tech innovations.

Considerable evidence indicates that social influence is far more important than product or consumer characteristics in de decision making process (Kim & Park, 2011). Although many studies are focused on product and consumer characteristics, very few studies have examined the role of social influence in consumer adoption of high-tech innovations (Kulviwat et al., 2009).

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This paper contributes to the existing literature as follows: Social influence is a widely studied topic (Goldenburg et al., 2009; Peng et al., 2011; Reinders et al., 2010). Like social influence, the adoption groups are a large study topic as well (Egmond et al., 2005; Muller & Yogev, 2006; Rogers, 2003). It is likely that social influence has a dissimilar effect on the several adoption groups, since the adoption groups behave differently (Robinson et al., 1992; Muller & Yogev, 2006). However, no studies were performed to measure this effect. This will be the purpose of this paper. A study will be performed, in order to research the role of social influence on the adoption process of the different adoption groups. In the existing literature, no measurement scale for adoption groups was found. The Handbook of Marketing Scales (Bearden et al., 2011) confirmed this statement. There is no scale available for the determination of the adoption groups as described by Rogers (2003).

This research is the founder of a scale which can be used in order to divide respondents into an adoption group. Since the adoption groups behave different from each other (Robinson et al., 1992; Muller & Yogev, 2006), a distinction between the groups is valuable. With more specific and detailed information about the respondents and their adoption group, research studies can provide more specific, accurate and reliable results.

So, this scale can be used as a fundament for further research about adoption groups. As will show in the ‘Result’ section of the research, there is room for improvement and development in order to create a valid scale.

In summary, the contribution of this research to the existing literature is bilateral. First; this research combines two widely researched topics into a research that is not researched in the current literature yet. Second, to accomplish this research, a new scale was created in order to divide respondents into an adoption group as described by Rogers (2003).

Research Question

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The hint of Bruner & Kumar (2007) is a very interesting hint, because normally people would expect the opposite effect. Innovators posses more knowledge about the high-tech innovation, they are less influenced by social influence, because they are the first group of adopters who experience the innovation and become familiar with the required behaviour and knowledge. As stated by Reinders et al. (2010), potential adopters experience difficulties to evaluate innovations due to the newness of the innovations and therefore consult other individuals. Innovators do not have that many possibilities to consult other individuals, because they are the first who experience the innovation. Early adopters do have more possibilities to consult other individuals because there is already a group who experienced the innovation (the innovators).

This view was the founder of an interesting research topic. As stated before, no research was conducted to the difference of social influence among the several adoption groups. Egmond et al. (2005) made a distinction between early market adopters and main market adopters. They stated that both groups differ widely in their willingness to adopt. However, no research was done to study the differences among the five group distinction of Rogers (2003).

The study of Egmond et al. (2005) and the hint of Bruner & Kumar (2007) enhanced the curiosity towards the effect of social influence on the different adoption groups. While existing literature had not study the effect of social influence on the different adoption groups yet, an interesting and new research topic occurred. Does social influence have a different effect on the five adoption groups instead of the two group distinction made by Egmond et al. (2005)? And is one type of social influence more influential than another type? This thesis is performed in order to find an answer to these questions.

Therefore, the research question for this thesis was formulated as follows:

What is the role of social influence on the different type of adopters in the adoption process with high-technology innovations?

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Theoretical background

Although the concepts; relative advantage, consumer uncertainty and perceived complexity do not play a major part in this research, they will be discussed briefly. This for clarification reasons, since these concepts are mentioned in this thesis.

Relative advantage

Arts et al. (2011) defined relative advantage as the degree to which an innovation is perceived as being better than the idea/product it supersedes. Kim & Park (2011), Kulviwat et al. (2007) and Rogers (2003) confirms this definition by stating that relative advantage is the degree to which an innovation is better than competing products. Consumers are willing to adopt new innovations more easily when they have clear advantages, than when they have little or no additional advantages over the alternatives (Kim & Park, 2011; Kulviwat et al., 2007). Consumers reflect the benefits of a new innovation over alternative offerings. This provides the potential adopter with insight in the desirability of the innovation (Arts et al., 2011). Relative advantage significantly accelerates the duration of adoption. The greater the perceived relative advantage of an innovation, the faster the consumers will adopt the innovation (Kim & Park, 2011).

Consumer uncertainty

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Perceived complexity

Arts et al. (2011) and Kim & Park (2011) define complexity as the degree to which an innovation is difficult to understand and use. When an innovation is too complex for the consumer, it does not fulfil the consumers’ expectations, which will result in unsatisfied consumers and an unsuccessful adoption process (Kleijnen et al., 2004).

The more complex an innovation is perceived, the more learning costs to adopt new behaviours will be involved (Hoeffler, 2003). The more complex the innovation and thus the higher perceived costs, the less likely it is that consumer’s change its behaviour (Arts et al., 2011).

Social influence

Social influence is defined as information by implicit or explicit pressures from individuals, groups and mass media that affect how a person behaves (Hoyer & Macinnis, 2008).

Researchers have come to realise that social structure and interactions among individuals play an important role in affecting attitude towards technology (Peng et al., 2011).

A common explanation for the importance of social influence is that potential adopters feel uncertain about innovations, because they are unfamiliar with the possibilities and

consequences. Individuals are generally uncomfortable with uncertainty, and therefore, interact with others to increase their knowledge and decrease their uncertainty (Flynn et al., 1996; Kim & Park, 2011). This statement is confirmed by Reinders et al. (2010) who declared that potential adopters experience difficulties to evaluate innovations due to the newness of the innovations and therefore consult other individuals to obtain trustworthy information (Risselada, 2012). Peng et al. (2011) stated that the influence of individuals on their network is very important. Network effects is one of the most important and powerful social

influences. Because consumers are increasingly exposed to others’ opinions, they are more likely to adopt the same technology (Tucker, 2008). Therefore, social influence stimulates the decision making process of consumers and could reduce complexity, risk and uncertainties and could increase the relative advantage due to extra knowledge of an innovation.

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Consumers may serve as ambassador or opinion leader of the innovation to stimulate social contagion. Opinion leaders not only adopt an innovation earlier, they also stimulate others to adopt the innovation as well (Goldenberg et al., 2009). Chiesa & Frattini (2011) agree, by stating that early adopters (and their developed attitude towards the innovation) are critical in influencing decisions by later adopters.

Most studies on innovation adoption investigate the role of product characteristics or customer characteristics as drivers of the consumer adoption process. But considerable evidence indicates that social influence is far more important in the decision making process (Kim & Park, 2011). There is growing agreement among researchers on the fundamental role of social networks in the way of information distribution among consumers (Goldenberg et al., 2009).

This statement is confirmed by Kulviwat et al. (2009). They suggest that adoption behaviour is established by social influence. Such behaviour can come from the desire to comply with a certain group, or to enhance one’s image within the group and avoid social disapproval (Bearden et al., 1989). The use of an innovation is sometimes perceived to enhance self-image or social status within the social group. The degree to which a consumer believes that the consumption of a product is visible for others, increase the effect of social influence on the purchase behaviour (Kulviwat et al., 2009). So if an innovation is visible for the social group, individual’s adoption process is influenced by this social group. Kulviwat et al. (2009) found that with young consumers, adoption of mobile technology services was driven by the desire for a symbol of individuality or as a social identifier.

Hoyer & Macinnis (2008) created a clear overview of the social influences, individuals could be exposed to. First, they made a distinction between marketing sources (influences delivered from a marketing source, like advertisement) and non-marketing sources (influence delivered from a source outside a marketing organization, like media of friends)

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Table 1: Sources of Influence

Marketing Source Non-Marketing Source

Mass Media Delivery

(Quadrant 1) Advertising

Sales promotions Publicity

Special events Email & websites Direct mail Cell phone (Quadrant 2) News Critiques / reviews / blogs Program content External endorsements Cultural heroes Clubs / organizations Virtual communities Personal Delivery (Quadrant 3) Salespeople Service representatives Customer service agents

(Quadrant 4) Family Friends Neighbours Casual acquaintances Classmates Co-workers

(Source: Hoyer & Macinnis, 2008)

The sources of influence differ from each other in terms of reach, credibility and two-way communication.

Hoyer & Macinnis (2008) added three characteristics to their model, which affect the amount of influence of the sources on individuals; 1) Reach 2) Credibility and 3) Two-way communication.

Mass media has a wide range. Much more consumers are reached by this type of media, than with personal delivery. An advertisement in a public place reaches far more consumers, then an advertisement, within a store.

Credibility is a difference between a marketing source and a non-marketing source. Information which is delivered through a marketing source is perceived as less reliable, more manipulative and more biased, while information for non-marketing sources is perceived as

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more credible, due to the fact, that non-marketing sources do not have any personal interest or benefit in our purchase and consumption behaviour (Hoyer & Macinnis, 2008; Rinallo & Basuroy, 2009).

Personal delivery allows a better two-way communication flow than mass media delivery. A personal conversation permits the consumer to ask questions and information. This increases the value of personal delivery. Herr et al. (1991) stated that personal information seems more vivid than mass media information, because speaking by a person makes it more ‘real’, which makes it more persuasive.

Adoption groups.

Although the distinction of five adoption groups (innovators, early adopters, early majority, late majority and laggards) is widely acknowledged, Egmond et al. (2005); Muller & Yogev (2006) and Rogers (2003) make a first distinction of two main types of adopters, before the distinction of the five adopters. 1) The early market adopters and 2) the main market adopters. The early market adopters consist of innovators and early adopters, the main market adopters consist of early majority, late majority and laggards (see table 2).

Table 2: Adoption Groups

Early Market Adopters Main Market Adopters

Innovators Early Adopters Early Majority Late Majority Laggards

The adoption starts with the early market and is followed by the main market. The two different groups differ widely in their willingness to adopt. Early market adopters have a visionary attitude, while the main market is more pragmatic (Egmond et al., 2005).

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Egmond et al. (2005) made a clear overview of the adopter characteristics for both adopter groups (see table 3).

Table 3: Adoption Characteristics

Early market adopters Main market adopters

Seek revolutionary advances (innovation and creation)

Seek evolutionary advances (maintenance and solutions)

Motivated by future opportunities Motivated by current problems

Self-referencing Stay with the herd

Risk-taking Risk-aversion

Intuitive Analytic

Contraire Conformist

Seek what is possible Pursue what is probably Will seek best technology and innovative

products

Will seek best solution or functionality to buy, focused on market leader.

Momentary, local and specific More of the same

Often curative Preventive

Fast Slow

(Source: Egmond et al, 2005)

As stated above, the distinction of five adoption groups is widely acknowledged; 1) Innovators 2) Early adopters 3) Early majority 4) Late majority 5) Laggards (Goldsmith & Hofacker, 1991; Hoyer & Macinnis, 2008; Rogers, 2003).

These groups are identified based on the timing of their adoption decisions. The first 2.5 percent of the adopters are described as the innovators, the next 13.5 percent as the early adopters, the next 34 percent is called the early majority and the following 34 percent is the late majority. The last 16 percent are the laggards (Hoyer & Macinnis, 2008).

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from the main market adopters that a different strategy is necessary for these groups, or the new product has a good chance of failing.

Early Market Adopters

Innovators:

Innovators are enthusiastic about technology and want to be the first to get a new high-tech product, even if the product is not reliable, not complete in terms of attributes or service (Hoyer & Macinnis, 2008; Muller & Yogev, 2006). They have positive attitudes towards technology and new innovations (Mattila et al., 2003). They are willing to take the risk of a failed technology, they are young in age, have a high social class, they posses financial resources are social and have affinity with science and innovations (Rogers, 2003). They are influenced by people with the same interest in technology (Muller & Yogev, 2006). Innovators are not the best opinion leaders, although they have knowledge about the technology, they have only a small feeling with the other adoption groups, which result in only a few other consumers who like to follow them (Bruner & Kumar, 2007).

Early Adopters:

Early adopters are visionaries. They admire a technologically new product not so much for its features as for its abilities to create a breakthrough in how things are done (Hoyer & Macinnis, 2008; Muller & Yogev, 2006). Difference with the innovators is that early adopters make more discrete choices. They are searching for products that make home and work life more efficient and fun (Hoyer & Macinnis, 2008) instead of just for the technology. They have intrinsic interest in certain products and are involved with the product category (Richins & Root-Shafer, 1988). They actively seek information before they adopt a new innovation (Vowles et al., 2011). They are, like the innovators, younger in age, have a higher social status, posses more financial resources and a higher level of education. They have the highest degree of opinion leadership (Rogers, 2003).

Main Market Adopters

Early Majority:

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Yogev, 2006). They do not like risk and care about the company’s reputation. They are interested in how well the innovation will fit with their lifestyle, are concerned about the reliability of the products, they are price sensitive, and are happy with competitors entering the market, so they can compare product features. (Hoyer & Macinnis, 2008). Early majority tend to be influenced mostly by other pragmatists, due to the fact that early market adopters have different demands in innovations than main market adopters. Early majority have an above average social status. They are seldom an opinion leader and have contact with the early adopters (Rogers, 2003).

Late Majority:

Late Majority consumers are more conservative, suspicious of progress, and rely on tradition. They often fear high-tech products, and their goal is to buy the innovations, when all the risks are gone and all the problems are solved. They like to buy preassembled products (Hoyer & Macinnes, 2008). They have negative technology attitudes (Matilla et al., 2003).They adopt after the average market. They are sceptical about an innovation, their social status is below average, minor financial resources, and they have contact with early majority and other people in the late majority. They have very little opinion leadership (Rogers, 2003)

Laggards:

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Hypotheses

For each of the five adoption groups a prediction will be made, concerning the social influence sources which will be most influential for each adoption group.

Innovators

As stated above, innovators are enthusiastic about technology and they possess the required knowledge of the technique. According to Muller & Yogev (2006) they are influenced by people with the same interest in technology. Because innovators possess product knowledge, influences by a marketing source are not very effective.

Innovators will be influenced best by a non-marketing source (people with the same interests). A good example of this is the website www.tweakers.net. Tweakers.net is a Dutch website for the advanced computer user and technology enthusiast, where the latest developments concerning hardware, software, games and internet are discussed.

So, it is likely that the innovators are most influenced by other technology enthusiasts. They communicate and interact mostly through mass media sources like forums, virtual communities and websites like tweakers.net. Personal delivery sources are less applied by this adoption group, because they reach their friends and other technology enthusiasts through internet.

Therefore, for the innovators, the following hypothesis is formulated;

Hypothesis 1:

Innovators will be most influenced by non-marketing, mass media sources, like websites and forums.

(This will be the second quadrant in table 1, see heading ‘Social Influence’).

Early Adopters

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According to Peng et al. (2011) consumers contact individuals within their network, in order to form an opinion about a certain technique. This fits with the high degree of opinion leadership of the early adopters. The opinion of the personal network is one of the most powerful influences (Peng et al., 2011). Because a marketing source is perceived less reliable and more manipulative than a non-marketing source (Hoyer & Macinnis, 2008), a marketing source is not very influential.

Based on the literature, two possible hypotheses could be formulated.

First, a hypothesis based on personal network. Since the personal network is one of the most powerful influence sources (Peng et al., 2011), and early adopters have a high degree of opinion leadership, it is likely that they will be influenced most by this personal network. This network consists of family, friends and other individuals in their life. Therefore the hypothesis could be formulated as follows;

Hypothesis 2a:

Early Adopters will be most influenced by non-marketing, personal delivery sources, like friends and family.

(This will be the fourth quadrant in table 1, see heading ‘Social Influence’).

However, literature suggests that early adopters are heavy users of mass media (Childers, 1986). Therefore it is plausible that a large amount of the communication and interaction between the early adopter and their personal network is through mass media sources like forums and discussion sites on Internet, but also through expert endorsement on television, radio and newspapers (Due their high degree of opinion leadership). Consequently, another hypothesis could be formulated;

Hypothesis 2b:

Early Adopters will be most influenced by non-marketing, mass media sources, like websites and forums.

(This will be the second quadrant in table 1, see heading ‘Social Influence’).

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Early Majority

According to Hoyer en Macinnis (2008), early majority is mostly influenced by other early majority through personal contact, because the majority is more pragmatic and interested in solutions and convenience, while innovators and early adopters are interested in technology and performance (Rogers, 2003). The company’s reputation is important as well. The early majority cares deeply about who is making the product and the company’s reputation (Hoyer & Macinnis, 2008).

According to the literature, both marketing and non-marketing sources have an influence on early majority. Valuing the company’s reputation is a distinctive characteristic of the early majority compared to the other majority. Therefore, like the early adopters, two hypotheses could be formulated.

Since early majority cares about the company’s reputation, it is likely that their awareness is created via advertisements in mass media, but that they will receive information from sales personnel in the store, because they do not (unlike innovators and early adopters) search much on the Internet for information.

Therefore the following hypothesis is formulated;

Hypothesis 3a:

Early Majority will be most influenced by marketing, personal delivery sources, like sales personnel and service representatives.

(This will be the third quadrant in table 1, see heading ‘Social Influence’).

However, literature suggests that early majority is most influenced by other early majority, because they have the same mentality about technology and the use of it. This group is interested in the solutions and convenience of an innovation, instead of the technology itself. They adopt technology in a later stage, when they are certain the risks are minimal. Due to this low risk attitude, it is likely that they contact other early majority in a personal way instead of through risky technology like Internet.

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Hypothesis 3b:

Early majority will be most influenced by non-marketing, personal delivery sources, like friends and family.

(This will be the fourth quadrant in table 1, see heading ‘Social Influence’).

Since both hypotheses seem plausible, both hypotheses will be discussed in the ‘Discussion’ section of this thesis.

Late Majority

Due to their conservative, sceptical nature, the late majority would not be influenced by marketing actions from marketing sources. They resist new technologies, so when a company introduces a new product / technology they react sceptical and disapprovingly (Hoyer & Macinnis, 2008). They mainly contact early majority and other late majority (Rogers, 2003). So, it is plausible that the most influence on late majority is through non-marketing, personal sources like friends and family. Therefore the following hypothesis is formulated;

Hypothesis 4:

Late Majority will be most influenced by non-marketing, personal delivery sources, like friends and family.

(This will be the fourth quadrant in table 1, see heading ‘Social Influence’).

Laggards

Like the late majority, laggards resist innovations (Hoyer & Macinnis, 2008). According to Rogers (2003) laggards have mainly contact with family and friends. So, it is likely that they are mainly influenced by this group. Therefore the following hypothesis is formulated;

Hypothesis 5:

Laggards will be most influenced by non-marketing, personal delivery sources, like friends and family.

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Methodology

The methodology will describe the development and the implementation of the survey. In order to test the stated hypotheses, a quantitative research was executed, in terms of a questionnaire. This section will explain the research population, sample size and the development of the questionnaire.

Research population

This research studies the social influence on all five groups of the adoption process. These groups differ widely from each other (Robinson et al., 1992; Muller & Yogev, 2006). For instance, the first group (innovators) is younger and has high financial resources and social status, while the last group (laggards) is older and has low financial resources and social status. Therefore, there is a very wide research population. Everybody is suitable to participate in the research. The research population is defined as all the Dutch citizens within the age of 16 and 65. This definition is chosen because people who are 16 years or older are likely to posses the financial resources to buy one of the high-tech products, while people older than 65 in general have less affinity with new technology. Because of this lack of affinity, they are likely to not adopt at all, because they do not see the need of new technology in their lives. Because they do not adopt at all, they do not fit into an adoption group and are therefore not suitable to participate in this research.

According to the Centraal Bureau voor de Statisitiek (CBS), in 2011, there were 10.922.000 Dutch citizens between 16 and 65 years old.

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Sample size

Because the research population is known, the formula with the ending population is the correct formula to determine the sample size of the questionnaire;

n>= N · z ² · p (1-p)

z ² · p (1-p) + (N-1) · F ²

n = Necessary amount of respondents

z = 1.96 (standard deviation with a 95 percent confidence interval) N = 10.922.000 (research population)

p = 0.5 (chance for specific answer) F = 0.05 (margin of error 5 percent)

So,

n> = 10.922.000 x 1.96² x 0.5(1-0.5) = 385 1.96² x 0.5(1-0.5) + (10.922.000-1) x 0.05²

The sample size of the questionnaire should be at least 385 respondents.

Data collection

To collect the data for the research, a survey will be conducted. This survey will be executed by means of quantitative research. Quantitative research was chosen because the underlying thoughts behind the choices were not relevant for this research (this would be suitable for qualitative research).

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Method

In this thesis, the distinction of five different adoption groups will be used. The reason for this choice is that five different groups are more specific than two groups. According to Robinson et al. (1992), it is critical to acknowledge the difference between the five adoption groups. If the two group distinction is used, it will not represent the many differences among the individuals within the groups. For example; there is a clear difference between the innovators and the early adopters in terms of interest in the technology. Innovators are keen for technological features of an innovation, while the early adopters are more interested in the abilities of the technology. This difference is not made by the two group distinction, which could harm the results and recommendations of the research. Therefore, the solution of the five group distinction will be applied.

However the five group distinction will be applied in this research, the distinction of two groups is important in this research as well. In the questionnaire, the first step will be to determine the adoption group in which the participant belongs. In order to detect this adoption group, the first distinction will divide the participants into an early market adopter or a main market adopter (the two group distinction). If this distinction is clear, the participants should answer some questions concerning their attitudes and opinions towards new technology, the given answers will reveal several characteristics of the participants. Based on these characteristics, the respondents can be divided into their final adoption group.

The initial idea to divide participants into adoption groups was by study the time they took to adopt the innovation after market introduction. Mahajan et al. (1990) suggested that the adoption process of high-tech products is approximately ten years. It is highly doubtful that this ten year cycle is still applicable and valid for high-tech innovations. It is very well possible that in the last decades adoption times have developed, due to increased consumer expectations and demand and the technological development. Though there is no scientific proof for this statement. According to Van Ittersum & Feinberg (2010) academic research of adoption time span measures remains scarce. The research of Mahajan et al. (1990) is still the most current research concerning the adoption time of high-tech products.

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The second phase of the questionnaire is to study the role of social influence on the adoption process of the participant. This will be conducted as follows; in this phase of the questionnaire, the respondent should take in mind their most recent high-tech purchase, or (as it applies) the high-tech product they are about to purchase. Three suggestions will be made; the mp3 player, smart phone and tablet computer. These suggestions are made because these products have a high change of being the most recent high-tech purchase, or the purchase they are about to make (these products are very popular). Another recently purchased high-tech product, or future planned purchase, is suitable as well.

The research will be conducted as follows:

The participants will receive the questionnaire. First they receive some general questions to define demographical data. Next, the respondents will be divided into early market adopters, or main market adopters (two group distinction). Following, they will receive some specific questions in order to determine in which of the five adoption groups the respondents fits best; First a distinction between innovators and early adopters (early market adopters), second a distinction between the early majority, late majority and the laggards (main market adopters). Three sub questions will be asked per adoption group.

Depending on the answers of the two group distinction, the respondents should fill in the question concerning innovators and early adopters, or the question concerning the early majority, late majority and laggards.

All the respondents will be divided into one of the five adoption groups, based on their answers in the questionnaire. As stated above, respondents have to answer three sub questions per adoption group. Each question will be answered with a number between one and seven (Likert scale, based on the research of Bearden et al., 1989). Per group, the answers will be added together and a total number (between three and twenty one) will be calculated. The respondent will be divided into the group with the highest accumulated number. The questions are designed in a way that a higher accumulates number means a better fit with the adoption group. If this method will give any difficulties, a cluster analysis will be used.

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is chosen because they are in the adoption process at that moment. The product is top of the mindset. So they can remember their social influences very well.

So, the respondents will receive some questions concerning the social influences during their adoption process.

This research will examine which of the adoption groups, is influenced most by which of the four quadrants of the sources of influence (see heading ‘Social influence’, table 1).

Measures

The questionnaire starts with four general questions to define demographical data from the respondents. This information provides insights into the research population, which could be important in the analysis and discussion phase.

The first part of the questionnaire is to determine the adoption group of the respondents. Difficult though is to examine this with prior research, because there are no empirical studies available. The principals of the five adoption groups and their characteristics, are derived from the book; Diffusion of Innovations (Rogers, 1962). Although Rogers received contributions and criticism for his diffusion of innovation theory, the five adoption groups, were accepted and acknowledged. Many studies applied the five adoption groups, in order to research other aspects of the diffusion of innovations, but the five groups themselves were not scrutinized. This is confirmed by the Handbook of Marketing Scales (Bearden et al., 2011). This handbook contains a large variety of scales used in the marketing. None of the scales were about the determination of the five adoption groups, as described by Rogers (2003). Therefore, a new scale must be developed in order to examine the adoption group of the respondents.

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efficient and adopt before the mainstream, while the main market adopters are more pragmatic and interested in the solutions an innovation offers and adopt with the mainstream or later. While the early market adopters are willing to take risks, main market adopters are risk averse. These characteristics as described by Egmond et al. (2005); Muller & Yogev (2006) and Rogers (2003) distinguish the early market adopter from the main market adopter. Therefore the following questions were developed;

- Als er een nieuwe technologie op de markt wordt gebracht ben ik meestal de eerste van mijn vrienden die het heeft.

- Ik ben geïnteresseerd in nieuwe technologie en ik ben bereid om risico’s te nemen bij het kopen van een nieuwe technologie (Doordat de technologie mogelijk nog kinderziektes heeft en nog niet optimaal werkt).

- Ik betaal liever wat meer voor een nieuwe technologie, dan dat ik wacht totdat er alternatieven op de markt komen en het product goedkoper wordt.

- Bij de komst van een nieuwe technologie ben ik vooral geïnteresseerd in de mogelijkheden van de technologie en minder in de nuttige eigenschappen.

- Ik ben geïnteresseerd in nieuwe technologieën en heb deze meestal eerder dan mijn familie en vrienden.

Innovators distinguish themselves through the fact that they are interested in technology itself, rather than the functionalities of the innovation. They admire technology for its features. When an innovation is introduced, they want to have it. They are willing to take the risk of a failed technology or a product with teething problems. This is the unique characteristic of the innovators as described by the studies of Hoyer & Macinnis (2008); Muller & Yogev (2006) and Rogers (2003). Therefore the following questions were developed to measure this unique characteristic; Note: All the questions are developed in Dutch language, due to the Dutch research population.

- Ik vind de functies van een nieuwe technologie interessanter dan de mogelijkheden die het biedt.

- Ik koop een nieuwe technologie omdat ik gek ben op technologische vernieuwing en ik op de hoogte wil zijn van de laatste technieken.

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Early adopters search for products that make their home-and working live more efficient and fun. They love products that create a breakthrough in how things are done. They actively seek information before they adopt a new technology. These characteristics are unique for the early adopters (Hoyer & Macinnis, 2008; Vowles et al., 2011) Based on these characteristics, the following questions are developed;

- Bij nieuwe technologieën kijk ik vooral naar de mogelijkheden die ze voor mij bieden. - Voordat ik een nieuwe technologie aanschaf, zoek ik veel informatie en vraag ik

andere mensen om hun mening.

- Bij de aanschaf van een nieuwe technologie let ik er vooral op hoe het mijn huidige leven verbeterd of aangenamer maakt.

The brand awareness of early majority is unique. They are brand focused when they buy a new product and care about the company’s reputation. They want predictable improvements and knowing the brand and company helps to predict what they expect from the innovation. This is the unique characteristic of the early majority as described by Hoyer & Macinnis (2008); Mulller & Yogev (2006). Based on this uniqueness, the following questions were developed;

- Ik vind het erg belangrijk dat het bedrijf die de technologie aanbied een goede reputatie heeft.

- Bij aanschaf van het product let ik altijd op het merk.

- Ik vergelijk nieuwe producten altijd met de concurrent voordat ik iets koop.

Late majority is very cautious and only willing to adopt when they are convinced the product is without any risks and problems. They like the products preassembled in order to reduce the risk (Hoyer & Macinnis, 2008; Matilla et al., 2003). Based on these described characteristics, the following questions were developed;

- Ik koop pas nieuwe technologieën als ik zeker weet dat het betrouwbaar is en vrij van problemen.

- Ik koop nieuwe technologieën als ik zeker weet dat ze nuttig voor me zijn.

- Het liefst koop in nieuwe producten kant-en-klaar, zonder dat ik nog van alles moet installeren of invullen.

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attitudes and are unwilling to change. Based on these unique characteristics described by Goldenberg & Oreg (2007); Hoyer & Macinnis (2008); Matilla et al. (2003) the following questions are developed;

- Ik houd niet van nieuwe technologieën.

- Ik ben geen liefhebber van nieuwe technologie en als ik het koop is dat omdat ik weinig andere keus meer heb.

- Ik koop de technologieën voornamelijk omdat ik er niet meer omheen kan. Bijvoorbeeld omdat mijn vertrouwde product van de markt is gehaald. (denk aan het cassettebandje en de videoband).

The questions are systematically displayed in table 4.

Table 4: Survey questions adoption groups

Question Measured construct Applied studies

Als er een nieuwe technologie op de markt wordt gebracht ben ik meestal de eerste van mijn vrienden die het heeft.

Early / main market distinction

Egmond et al. (2005) Muller & Yogev (2006) Rogers (2003)

Ik ben geïnteresseerd in nieuwe

technologie en ik ben bereid om risico’s te nemen bij het kopen van een nieuwe technologie (Doordat de technologie mogelijk nog kinderziektes heeft en nog niet optimaal werkt.)

Ik betaal liever wat meer voor een nieuwe technologie, dan dat ik wacht totdat er alternatieven op de markt komen en het product goedkoper wordt.

Bij de komst van een nieuwe technologie ben ik vooral

geïnteresseerd in de mogelijkheden van de technologie en minder in de nuttige eigenschappen.

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Ik ben geïnteresseerd in nieuwe technologieën en heb deze meestal eerder dan mijn familie en vrienden.

Ik vind de functies van een nieuwe technologie interessanter dan de mogelijkheden die het biedt.

Adoption group: Innovators

Hoyer & Macinnis (2008) Muller & Yogev (2006) Rogers (2003)

Ik koop een nieuwe technologie omdat ik gek ben op technologische

vernieuwing en ik op de hoogte wil zijn van de laatste technieken.

Ik vind nieuwe technologieën zeer interessant en koop het product het liefst zo snel mogelijk.

Bij nieuwe technologieën kijk ik vooral naar de mogelijkheden die ze voor mij bieden.

Adoption group: Early Adopters

Hoyer & Macinnis,(2008) Vowles et al. (2011)

Voordat ik een nieuwe technologie aanschaf, zoek ik veel informatie en vraag ik andere mensen om hun mening.

Bij de aanschaf van een nieuwe technologie let ik er vooral op hoe het mijn huidige leven verbeterd of aangenamer maakt.

Ik vind het erg belangrijk dat het bedrijf die de technologie aanbied een goede reputatie heeft.

Adoption group: Early Majority

Hoyer & Macinnis (2008) Muller & Yogev (2006)

Bij aanschaf van het product let ik altijd op het merk.

Hoyer & Macinnis (2008) Muller & Yogev (2006) Ik vergelijk nieuwe producten altijd met

de concurrent voordat ik iets koop.

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Ik koop pas nieuwe technologieën als ik zeker weet dat het betrouwbaar is en vrij van problemen.

Adoption group: Late Majority

Hoyer & Macinnis (2008) Matilla et al. (2003)

Ik koop nieuwe technologieën als ik zeker weet dat ze nuttig voor me zijn.

Hoyer & Macinnis (2008) Matilla et al. (2003) Het liefst koop in nieuwe producten

kant-en-klaar, zonder dat ik nog van alles moet installeren of invullen.

Ik houd niet van nieuwe technologieën. Adoption group: Laggards

Goldenberg & Oreg (2007)

Hoyer & Macinnis (2008) Matilla et al. (2003) Ik ben geen liefhebber van nieuwe

technologie en als ik

het koop is dat omdat ik weinig andere keus meer heb.

Adoption group: Laggards

Hoyer & Macinnis (2008) Matilla et al. (2003) Ik koop de technologieën voornamelijk

omdat ik er niet meer omheen kan. Bijvoorbeeld omdat mijn vertrouwde product van de markt is gehaald. (denk aan het cassettebandje en de

videoband).

Adoption group: Laggards

The questions will be tested with a sample of twenty respondents. In order to scrutinize the validity of the scale the computer program SPSS will be used.

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is expected that the questions are consistent to the construct / adoption group. To study this expectation, a pilot survey was performed. The questionnaire is split in to three different questions. First, the respondents are divided into early- or main market adopters. Second is the verification of the innovators and the early majority, while the third section determines the early majority, late majority and the laggards. The internal consistency was measured for each of the adoption groups (see table 5). Cronbach’s alpha was used to determine the internal consistency. The minimum alpha should be 0.6 or higher in order to confirm internal consistency (Malhotra & Birks, 2007).

Table 5: Internal Consistency pilot survey one

Question Cronbach’s Alpha

Early / main market distinction 0.884

Innovators 0.797

Early Adopters -0.241

Early Majority 0.785

Late Majority 0.657

Laggards 0.537

According to table 5, there are two adoption groups (early adopters and laggards) which are not internal consistent. For the early adopters, this can be explained by the fact that only six respondents filled in this question. Due to this small amount of respondents, it is very difficult to measure the internal consistency, since just a single aberrant response could significantly influence the internal consistency. Expected is that this adoption group will be internal consistent when sufficient respondents answered the questions. This is expected as the questions for this adoption group are developed in the same manner as the other adoption groups, based on unique characteristics as defined in the acknowledged literature.

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Table 6: Internal Consistency Laggards

Questions Laggards Cronbach’s Alpha if item was missing

1. Ik houd niet van nieuwe technologieën. 0.181 2. Ik schaf nieuwe technologieën

voornamelijk aan omdat ik ze nodig ben in mijn werk of dagelijks leven.

0.865

3. Ik koop de technologieën voornamelijk omdat ik er niet meer omheen kan.

Bijvoorbeeld omdat mijn vertrouwde product van de markt is gehaald. (denk aan het cassettebandje en de videoband).

- 0.159

As table 6 shows the second question is not consistent with the other two questions. If question 2 is removed, an internal consistency of 0.865 would be reached, which is sufficient. Therefore, question 2 was changed in order to improve the consistency. From;

- Ik schaf nieuwe technologieën voornamelijk aan omdat ik ze nodig ben in mijn werk of dagelijks leven.

Into;

- Ik ben geen liefhebber van nieuwe technologie en als ik het koop is dat omdat ik weinig andere keus meer heb.

The new question is in line with the characteristics, determined by multiple researchers for the laggards group.

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Table 7: Internal Consistency pilot survey two

Innovators 0.838

Early Adopters 0.475

Late Majority 0.619

Laggards 0.880

Again, for the early adopters, only five respondents filled in question six in the second pilot survey. With sufficient respondents, the internal consistency will be sufficient. The change made in the questions of the laggards, was a successful one, the internal consistency is now sufficient enough.

The second phase of the questionnaire is to examine which social influence is most influential for the respondent in their adoption process.

These questions are based on the research of Bearden et al. (1989). In the research, Bearden et al. (1989) distinguished two different types of social influence; normative influence and informative influence. Normative influence is defined as the tendency to conform to the expectations of others (Burnkrant & Cousineau, 1975). Individuals desire to enhance their self-image by association with a reference group. Informational influence is the tendency to accept information from others as evidence about reality (Deutsch & Gerard, 1955). Individuals search for information from knowledgeable others or make inferences based upon the observation of other’s behaviour (Park & Lessing, 1977).

In the research of Bearden et al. (1989) a two dimensional twelve item measurement was developed, eight normative items and four informational items.

For this thesis, the informational items of Bearden et al. (1989) are applied, because this thesis focuses on the information seeking actions of the individuals during the adoption process. Group confirmation, like with normative influences, is not a part of this research. Therefore, the questionnaire applies the four informational items of the research of Bearden et al. (1989).

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scale. To improve the consistency and the clarity of the questionnaire for the respondents, the first phase of the questionnaire will be using the seven point Likert scale as well.

The four items of Bearden et al. (1989) which are used in the questionnaire are;

1) To make sure I buy the right product or brand, I often observe what others are buying and using.

2) If I have little experience with a product. I often ask my friends about the product. 3) I often consult other people to help choose the best alternative available from a

product class.

4) I frequently gather information from friends or family about a product before I buy.

In the research of Bearden et al. (1989), the internal consistency of this scale was 0.82 for the initial sample, while three weeks later in a follow up, a value of 0.75 was measured.

In this research, a value of 0.769 was measured, which corresponds with the original research.

For all four quadrants of table 1 (see heading ‘Social influence’) the four items will be adjusted in a way that the core question remains, but the social influence will differ among the four quadrants. Example; one of the items is: To make sure I buy the right product or brand, I

often observe what others are buying and using.

So for all four different quadrants, the two words ‘what others’, are changed into a concept that represents the quadrants (For example; for quadrant one, a reference would be made to mass media, while in quadrant two, a reference would be made to independent websites or experts).

The four items of Bearden et al. (1989) would all be used for each quadrant. So, this makes sixteen items.

Table 8 shows a systematically overview of the questions.

Table 8: Survey questions social influence

Question Measured construct Applied studies

Om er zeker van te zijn dat ik het juiste high-tech product koop, kijk ik goed naar advertenties op televisie,radio en in folders.

Quadrant 1:

Marketing, mass media delivery sources.

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Ik zoek contact (via email of telefoon) met het bedrijf waar ik het high-tech product wil gaan kopen als ik het product niet goed begrijp.

Quadrant 1:

Bearden et al. (1989)

Ik kijk vaak op de websites van de producenten voor informatie voordat ik een high-tech product aanschaf.

Quadrant 1:

Ik bel of email bedrijven van high-tech producten om te vragen naar advies als ik een high-tech product wil kopen.

Quadrant 1:

Ik zoek vaak op internet bij onafhankelijke websites en forums, over een goed

koopadvies voor een high-tech product dat ik wil kopen.

Quadrant 2:

Non-marketing, mass media delivery sources.

Voordat ik een high-tech product koop, zoek ik vaak op internet bij onafhankelijke websites en forums naar informatie.

Quadrant 2:

Ik kijk goed rond op onafhankelijke websites om er zeker van te zijn dat ik het juiste high-tech product koop.

Quadrant 2:

Als ik voorafgaand aan de aankoop weinig kennis van het high-tech product zoek ik op internet bij onafhankelijke forums en experts naar advies.

Quadrant 2:

Ik ga vaak bij winkels langs om informatie te verzamelen over een high-tech product dat ik wil kopen.

Quadrant 3:

Marketing, personal delivery sources.

Door in de winkels te kijken wat er veel verkocht wordt, weet ik welke high-tech product ik moet kopen.

Quadrant 3:

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In de winkel vraag ik vaak of ze me kunnen helpen bij het kiezen van het beste high-tech product.

Quadrant 3:

Doordat ik weinig ervaring met het high-tech product heb, ga in naar de winkel voor advies, voordat ik het product aanschaf.

Quadrant 3:

Als ik weinig ervaring heb met een high-tech product, vraag ik vaak vrienden en familie om advies. Quadrant 4: Non-marketing, personal delivery sources. Bearden et al. (1989)

Ik kom vaak bij vrienden en familie om ze te vragen om te helpen met het kiezen van het beste high-tech

product. Quadrant 4: Non-marketing, personal delivery sources. Bearden et al. (1989)

Door te kijken welke high-tech producten vrienden en familie kopen, weet ik dat ik ook het goede product koop.

Quadrant 4: Non-marketing, personal delivery sources.

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Results

The data collection went as it was described in the Methodology. With the use of internet (social media and email) the respondents were reached. After the first and the second call to fill in the questionnaire, 426 people responded. Unfortunately, only 322 respondents filled in the questionnaire entirely. Because the desired amount is 385, still 63 respondents needed to fill in the questionnaire. After the third reminder and some personal contacted respondents (10 respondents), 389 respondents filled in the entire questionnaire.

For all applied tests in this thesis, a 95 percent confidence interval is used.

General information

The first four question of the questionnaire were asked to determine demographic information. The results will be discussed per item. For these questions, The Centraal Bureau voor de Statistiek (CBS) was used in order to collect information concerning the population and to compare the sample with the population.

Gender distribution

In this research, 218 of the 389 respondents (56 percent) were female, while the other 171 (44 percent) were male. This is slightly different compared to the entire research population, where the female and male are more balanced (female 50.5 percent to 49.5 percent male). With the use of a Chi-Square analysis, no significant difference was found between sample and population (significance: p= .158)

Age distribution

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Graph 1: Age distribution

Education distribution

Besides the age, there is a deviation in the education as well. In the sample, the majority of the respondents are highly educated with a bachelor (41.1 percent) or master degree (19.8 percent), while the percentage of bachelor (18.2 percent) and master degree (9.4 percent) in the population is noticeably lower (see graph 2). These differences are significant as well (p= .000).

Graph 2: Education distribution

Occupation distribution

Having a full-time job (40.1 percent) or being a student (31.6 percent) is the most common occupation of the respondents. A part-time job (17.2 percent), retired (7.2 percent) or

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unemployed (3.9 percent) complete the 100 percent occupation. 67.2 percent of the population is in the labour force, 59.1 percent is full time, while the other 40.9 percent works part time. In 2011, 34.7 percent of the population followed education.

No graph of the occupation distribution was displayed, because it is difficult to extract conclusion from these occupation numbers, since a student could also count as a part time worker. Due to the overlay between the figures it is hard to compare the sample to the population.

The age and education differences between sample and population are the most salient differences. An explanation for this result will be discussed in the ‘Discussion ‘section of this thesis.

Internal consistency

In the pilot survey, the internal consistency was used in order to test the validity of the questions. The results of the pilot survey were sufficient to distribute the questionnaire among the respondents. After the final survey of 389 respondents was performed, the internal validity was checked again, to test whether it was improved compared to the pilot survey. See table 9 for the results.

Table 9: Internal Consistency final survey

Innovators 0.765

Early Adopters 0.583

Late Majority 0.541

Laggards 0.797

Despite the two pilot surveys, which gave a promising result, the final result (as shown in table 9) is not internal consistent for three adoption groups.

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Cluster analysis for early market adopters

Cluster analysis is one of the most widely used methods, in order to divide markets into segments. It identifies homogeneous structures in the data by analyzing the similarities or dissimilarities of the objects to be clustered (Tuma et al., 2011).

Due to the fact that the respondents only answered the question for early market adopters, or answered the questions for main market adopters, two cluster analyses had to be conducted. A cluster analysis was executed for the early market adopters and a cluster analysis was executed for the main market adopters.

This whole thesis is about five adoption groups, in the stated literature, but also the hypotheses are based on the five adoption group model. Therefore, the choice has been made to regulate the amount of clusters in order to be consistent with the thesis and to provide an answer to the hypotheses. Therefore, a k-means cluster was chosen for this research.

The cluster analysis for early market adopters resulted in two different clusters (see table 10).

Table 10: Cluster Centres

Question Cluster 1 Cluster 2

Bij nieuwe technologieën kijk ik vooral naar de mogelijkheden die ze voor mij bieden.

5 5

Ik vind de functies van een nieuwe technologie interessanter dan de mogelijkheden die het biedt.

4 5

Ik koop een nieuwe technologie omdat ik gek ben op

technologische vernieuwing en ik op de hoogte wil zijn van de laatste technieken.

4 6

Voordat ik een nieuwe technologie aanschaf, zoek ik veel informatie en vraag ik andere mensen om hun mening.

6 5

Ik vind nieuwe technologieën zeer interessant en koop het product het liefst zo snel mogelijk.

4 6

Bij de aanschaf van een nieuwe technologie let ik er vooral op hoe het mijn huidige leven verbeterd of aangenamer maakt.

5 5

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Second step in this analysis is to test whether these two clusters possess the characteristics of the early market adoption groups. To test this, a discriminant analysis was performed. A discriminant analysis is a method of pattern recognition to combine or separate objects (Gau et al., 2009). As variables for the discriminant analysis, the constructs innovators and early adopters in the questionnaire were used. These constructs measure the early market adopters and their technological preferences and reveal the differences between the two clusters on the chosen variables. As a result, differences between the clusters are shown, and that gives insight in the characteristics of the clusters and whether they match with the adoption groups as described in the literature.

Table 11 shows the results of the discriminant analysis.

Table 11: Analysis early market adopters

Early market Cluster 1 Cluster 2 Significance

A. Bij nieuwe technologieën kijk ik vooral naar de mogelijkheden die ze voor mij bieden.

5.48 5.46 p= .914

B. Ik vind de functies van een nieuwe

technologie interessanter dan de mogelijkheden die het biedt.

3.78 4.85 p= .000

C. Ik koop een nieuwe technologie omdat ik gek ben op technologische vernieuwing en ik op de hoogte wil zijn van de laatste technieken.

3.68 5.76 p=.000

D. Voordat ik een nieuwe technologie aanschaf, zoek ik veel informatie en vraag ik andere mensen om hun mening.

5.58 4.57 p=.001

E. Ik vind nieuwe technologieën zeer interessant en koop het product het liefst zo snel mogelijk.

3.72 5.78 p=.000

F. Bij de aanschaf van een nieuwe technologie let ik er vooral op hoe het mijn huidige leven verbeterd of aangenamer maakt.

4.84 4.67 p=.568

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D and F. As shown in table 11, cluster two is significantly more positive towards questions B, C and E. While cluster one is significant more positive towards question D. Cluster two can be specified as the innovators, since they are more positive towards the questions B, C and E (which is in line with the literature). Cluster one is more positive towards questions D, which should be answered more positively by the early adopters. Questions A and F did not show a significant difference among the two clusters. Based on the significant differences, cluster two can be specified as the ‘innovators’, while cluster one can be specified as ‘early adopters’. A second discriminant analysis was performed in order to measure the differences of social influences among the two clusters (see table 12).

Table 12: Social influence differences per question

Social Influence Early adopters Innovators Significance

A. Om er zeker van te zijn dat ik het juiste high-tech product koop, kijk ik goed naar advertenties op televisie,radio en in folders.

4.10 3.33 p=.047

B. Ik ga vaak bij winkels langs om

informatie te verzamelen over een high-tech product dat ik wil kopen.

3.72 2.98 p=.045

C. Als ik weinig ervaring heb met een high-tech product, vraag ik vaak vrienden en familie om advies.

4.74 3.61 p=.001

D. Ik zoek vaak op internet bij

onafhankelijke websites en forums, over een goed koopadvies voor een high-tech

product dat ik wil kopen.

5.58 5.72 p=.678

E. Door in de winkels te kijken wat er veel verkocht wordt,weet ik welke high-tech product ik moet kopen.

3.14 3.07 p= .832

F. Voordat ik een high-tech product koop, zoek ik vaak op internet bij onafhankelijke websites en forums naar informatie.