1
FINDING A NEEDLE IN A HAYSTACK:
INTRODUCING A MULTI-LEVEL FRAMEWORK TO IDENTIFY LEAD USERS
by
HANS ALERS
University of Groningen Faculty of Economics and Business
MSc Strategy and Innovation August 2011
Supervisor: Thijs Broekhuizen (1st) and Florian Noseleit (2nd)
Abstract
This study integrated both field independent and field dependent factors into a multi-level framework. Several variables were found to be specific to lead users and these aid the identification process of those valuable persons. Most important results were that openness to experience and agreeableness help to explain a user‟s broadness of expertise which in turn leads to lead userness. Furthermore, lead users have high tendencies to participate in a given environment, provide solutions to other users‟ problems and communicate with different social groups. Finally, lead userness is strongly related to the early adoption of innovations and multi brand loyalty. The findings of this study provide further evidence for the importance of both field dependent and independent variables related to lead userness and the importance of these users for the diffusion of innovations.
TABLE OF CONTENTS 1. INTRODUCTION ... 3 2. LITERATURE REVIEW ... 6 3. METHODOLOGY ... 19 4. RESULTS ... 27 5. DISCUSSION ... 31 6. REFERENCES ... 35
1. INTRODUCTION
Although introducing new products is rewarding, problems occur when bringing these to the market (Griffin, 1997). While not enough dedication and financial resources might pose problems to be successful, one of the most appealing issues is that products do not match the performance level required by consumers (Lillien et al. 2002). In order to cope with this problem, companies try to integrate different kinds of users in the NPD process. When using knowledgeable users, firms try to identify user needs which apply to the rest of the market in order to introduce successful products. One of these user integration processes was introduced by Von Hippel (1986). He introduced the lead user method, where consumers are integrated in the ideation- and development phase of the NPD process; also called the fuzzy front end phase. The purpose of integrating lead users for companies is to learn from the needs and solutions of leading edge users, while collaborating with company personnel (Schreier & Prügl, 2008). This approach not only collects information from the needs of leading edge users, but simultaneously provides solutions to these needs (Lillien et al. 2002).
Moreover, lead users also can act as catalysts for the diffusion process of innovations. Following the diffusion model by Rogers (1995), lead users are the first to adopt innovations. For that reason they are also the ones that experience these new products or services in the very beginning and form the first opinions, serving as gatekeepers before even 'innovators' adopt innovations (Harrison & Waluszewski, 2008). Therefore when these users are identified and targeted, the process of the diffusion of innovations can be enhanced (Schreier & Prügl, 2008). By introducing lead users to innovative prototypes, they can be the first to adopt and tell the majority about the urge to have that product in the future.
higher forecasted sales than when not using a similar lead user process. Furthermore, research shows lead users are not only able to come up with incremental innovations, but also with more radical innovations (Lettl, 2007).
Although the importance of lead users seems obvious, more practical and methodological problems come into play when identifying them. The first one is that, in the entire population the amount of lead users tends to be small (Franke et al, 2006). Only a few people are capable of understanding products that well and, in combination with their own sets of needs, come up with successful innovations. In addition, the previously used methods for identification of lead users show problems with finding the right users. Because there are so few of them, it is hard to find common characteristics. Previous research resulted in a substantial number of characteristics that indicate or are related to lead userness (e.g. high expected benefits; being ahead of an important market trend; user expertise and opinion leadership). However, studies have shown that those variables are highly dependent on the situation in which the lead user is active. As depicted in table 1, these so called field dependent variables have been the focus of almost all lead user studies.
Franke et al. (2006) indicate that there is a need to approach lead user characteristics on an additional aggregation level, as to enlarge the number of valuable screening variables. They stress that it would be interesting to see which common personality traits apply to lead users, when using more stable and field independent factors than situation specific characteristics. In addition, Schreier & Prügl (2008) also emphasize the need for a better understanding of characteristics of lead users. They stress how valuable it might be to study additional field dependent and field-independent variables, so that more factors can be used to identify lead users.
Apart from the theoretical contribution, this research also has managerial relevance. By creating a better understanding of lead users, managers can use the results of this study to enhance their possibilities of finding lead users. When these lead users are identified, managers can contact them in order to co-create innovations (Marchi et al. 2011). Furthermore, managers can also use the results of this study to better target the consumer innovators that may stimulate the adoption of innovations.
Article Context Most important findings Field dependent variables Field independent variables Urban & Von Hippel
(1988)
PC-CAD Lead users were successfully identified and prove to have unique and useful data regarding both new product needs and solutions.
X
Morrison et al. (2000) OPAC information systems
Modifying users can be differentiated based on lead edge status and their in-house capabilities.
X
Lilien et al. (2002) 3M (longitudinal sample)
Annual sales of lead user projects generate eight times higher forecasted sales than projects without lead users.
X
Franke & Shah (2003) Sport communities Innovators often prototyping novel sports-related products, receive assistance from other users in the community and that this
assistance is freely shared.
X
Morrison et al. (2004) Libraries Establishing validity and reliability of the LES. Also there is a strong relationship between high LES and early product adoption.
X
Lüthje (2004) Four extreme sports activities
Innovations by users can be an important source of new product ideas.
X
Lüthje et al. (2005) Mountain biking User innovators rely heavily on local information to produce their innovations
X
Franke et al. (2006) Kite surfing Both components ahead of a trend and high expected benefits predict commercial attractiveness.
X
Schreier et al. (2007) Kite surfing and technical diving.
The following characteristics are specific to lead users: stronger domain specific innovativeness, lower perceived complexity, higher tendency to be opinion leader and lower opinion seeking behavior.
X
Schreier & Prügl (2008) Sailplaners, technical divers and kite surfers
Consumer knowledge, use experience, locus of control and an innovative personality explain an individual‟s lead userness. Furthermore, lead users adopt innovative products faster than other users.
Kratzer & Lettl (2008) School groups Creativity and lead userness are related. X Spann et al. (2009) VSM in movie
industry.
Virtual stock markets can help to identify lead users.
X
Jeppesen & Laursen (2009)
Role of lead users in knowledge sharing within online communities
Knowledge giving and the boundary spanning role are specific to lead users.
X
Kratzer & Lettl (2009) Children within 23 public schools
Lead users are positioned as boundary spanners, and better able to diffuse innovations as opinion leaders are bound to
2. LITERATURE REVIEW 2.1 Lead user theory
Von Hippel (1986) defines lead users as people with two characteristics that, in a given marketplace, differentiate them from normal users (Franke et al. 2006). The first component of lead userness is being ahead of an important market trend. Lead users are supposed to live on the leading edge of certain market trends, facing needs earlier than other users. Acting upon this market trend line allows them to see through the blurry view of the future other consumers have and foresee market needs for the bulk market. By doing so, the chance enhances of inventing products that are commercially attractive for manufacturers (Morrison et al. 2000). Especially in technology markets, the knowledge of the needs of tomorrow is important for companies to create successful innovative products and survive in fast moving environments (Urban & Von Hippel, 1988). The second differentiating characteristic is that lead users perceive the benefits of fulfilling their innovative needs to be high and therefore see a large incentive to innovate (Von Hippel, 1986). Schreier & Prügl (2008) emphasize that a person only puts in a high amount of effort if he sees a large potential benefit. Whether this is financial or emotional does not make a difference; users innovate when they perceive pursuing their innovations to be rewarding.
As indicated before, unfortunately for many companies, the proportion of lead users within a given population is very small. Because of difficulties identifying the small amount of lead users, recent studies have tried to come up with a more exhaustive view on what defines lead users. In addition to the
local terms. Furthermore, there is only a small overlap between
Özer (2009) Mobile camera
phones
There are theoretical and empirical distinctions between product lead-users and product experts.
X
Marchi et al. (2011) Ducati Motor community
The independent variables (willingness to collaborate, product knowledge and strategic brand alignment) are found to be crucial factors in identifying lead users in online brand communities.
X
two characteristics stemming from research done by Von Hippel, studies have focused on two additional characteristics to identify lead users.
User expertise is the first additional variable that is supposed to enhance the identification process of lead users, as it serves as a precondition for lead userness. This factor can be differentiated according to the depth and broadness of user expertise. Before a user is able to perceive future demands regarding a certain product, a large amount of deep knowledge of that specific product is needed (Lüthje, 2003; Lüthje et al. 2005; Özer, 2009). Furthermore, although filling the demand gap by innovating can be seen as highly beneficial, a large amount of additional technical knowledge is needed. Before any adjustments can be made, lead users need to know how a product can be modified in such a way that their need gap can be dissolved. While a deeper knowledge pool in one product category can enhance the probability of new ideas, innovative users tend to have a large cross knowledge base containing information about different related product categories (Lüthje, 2003). By having this broader expertise, the chance that an approach to solve problems in one product category can be used in another is increased. In order to gain this cross knowledge base, these users have frequent contact with users in other product categories (Özer, 2009).
The second proposed additional characteristic is opinion leadership. Because of the tendency of lead users to foresee market needs in combination with their high amount of user expertise, they are suited candidates to influence other users and thus serve as opinion leaders (Schreier et al. 2007; Spann et al. 2009; Özer, 2009). Lead users often form one of the appealing factors in networks around a product and their knowledge about products allows them to be gatekeepers (Harrison & Waluszewski, 2008). As lead users are often early adopters, they are the first to review products and therefore provide a window for other users to see if innovations work and are worth the trouble. They do this by expressing their opinion to others, giving advice to them or to solve problems with existing products. As a result they often become opinion leaders for less innovative users.
related knowledge it does not give a clear indication whether he or she can identify market trends before the bulk of the marketplace does. Furthermore, as Kratzer & Lettl (2009) indicate, lead users and opinion leaders are not exactly the same users. Lead users correlate higher on boundary spanning roles between different product categories than typical opinion leaders, but form less frequently the central role in one product category.
+ + + + + + + +
Figure 1: Conceptual model
2.2 Development of hypotheses
Because of different views to what extent certain characteristics can be used to identify lead users, this study introduces a framework which will help to create a comprehensive view on lead users. Based upon research done by Digman (1990), figure 1 shows that the hypotheses will be based upon three different aggregation levels. The first aggregation level describes personality traits, which are field independent, generic and stable over time. In this study, these are measured by the Five Factor model. These factors enable the development of more field specific characteristics. The most central field dependent factor is lead userness, which describes both high expected benefit and ahead of an important market trend. Furthermore, also user expertise and opinion leadership are field specific elements. In turn, these three factors influence the way people behave, accounting for the third aggregation level. This way of thinking is congruent with the approach suggested by Batra et al. (2001). They suggest that general and non-situation specific variables are causally preceding non-general, situational variables that in turn define behaviors. Joachimsthalar & Lastovicka (1984) also point to such a hierarchical model, showing that stable, fundamental traits are supposed to affect a larger amount of intervening traits.
+
+
Early adopting Multi brand loyalty
Participation Providing solutions to
other online users Communication streams User expertise depth Five Factor personality traits Opinion leadership Lead userness High expected benefits Ahead of an important
market trend
Field independent factor Field dependent factor Behavior
2.2.1 Five Factor model
The Five Factor model (FFM) is frequently used as a source for identifying personality traits. The FFM stems from a study by Fiske in the late 1940‟s, indicating a Four Factor model to describe people‟s personalities. Subsequent attention has been given to this subject, resulting in additional studies (e.g. Normal 1967; Goldberg, 1981). In the early 1990‟s, researchers came to the conclusion that five constructs could be used to describe the domain of personality traits (Digman, 1990; McCrae & John, 1992). As explained in table 2, extraversion, agreeableness, conscientiousness, neuroticism and openness form the distinctive factors. Scholars are generally positive about the FFM model because it proves to have both convergent and discriminant validity and is therefore able to describe various personality constructs (Barrick & Mount, 1991; Larson & Sachau, 2009). As shown by table 3, these different personality traits are hypothesized to explain whether users score high on lead userness.
H1a - H1e: The Five Factor model influences the amount of lead userness a person has.
In addition to the effect of the FFM on the lead userness of a person, the FFM model is hypothesized to influence the two forms of user expertise. Openness to experience and agreeableness are supposed to have the strongest effects. First of all, the more open a person is to experiences, the broader and deeper the user expertise. A person who scores high on openness to experience is curious and therefore will be more than usually interested in gaining knowledge about both one product category as well as different product categories. Furthermore, because agreeable persons appreciate trust and corporation, they are more likely to gain knowledge from different products categories. By cooperating with others users within those product categories, the chances are higher to attain a broader level of user expertise (Costa et al. 1992).
H1f: The more a person is open to experiences, the deeper and broader the level of user expertise.
Personality trait Explanation
Extraversion ‘Includes sociability, activity, dominance,
and the tendency to experience positive emotions.’
Agreeableness ‘Encompasses sympathy, trust, cooperation, and
altruism.’
Conscientiousness ‘Includes organization, persistence, scrupulousness, and need for achievement.’
Neuroticism ‘Whether a person experiences negative affects such as
anxiety, anger, and depression, and other cognitive and behavioral manifestations of emotional instability.’ Openness to experience ‘Imaginativeness, aesthetic sensitivity, depth of feeling,
Personality trait Proposed relationship Extraversion H1a - Positive:
Extravert persons are more risk taking, assertive, active and passionate. They look for novel ways of doing things (McCrae & Costa 1992; King et al. 1996; Sung & Choi, 2009).
Agreeableness H1b - Positive:
Agreeable persons appreciate corporation and trust. For those reasons contact with users across different product groups is more likely to be attained. A combination of different sorts of knowledge from these groups leads to more innovative power (Smith et al. 2006).
Conscientiousness H1c - Positive:
More conscientious people like challenges, have a sense of purpose, higher standards and a need for achievement. Therefore they are more motivated to innovate (Moutafi et al. 2004; Schreier & Prügl, 2008; Teng, 2009).
Neuroticism H1d - Positive:
Less emotional stable persons are more quickly dissatisfied with current products, leading to higher expected benefit to innovate (Franke et al. 2006).
Openness to experience H1e - Positive:
The more a person is open to the things around him the more he is able to see things ahead of him (Barrick & Mount, 1991; Schreier & Prügl, 2008). Furthermore, curiosity and fantasy are likely to lead towards innovation related activities (Franke & Shah, 2003). Divergent thinking, a characteristic which may lead to innovative behavior, and openness to experience are also related (McCrae & Ingraham, 1987).
2.2.2 User expertise
According to Schreier & Prügl (2008), user expertise directly influences lead userness. When a person has no knowledge about a specific product category he / she can hardly see ahead of the market trend, because the trend will not be known. Moreover, when using a product often and gaining knowledge about it, the chances are higher that a person will be triggered by a lacking level of performance. For that reason, a person with higher user expertise will perceive the benefits of innovating to be higher.
As outlined in section 2.1, this study differentiates user expertise according to depth and broadness. The depth of a user‟s expertise refers to knowledge in one product category, which is needed to perceive lacking performance leading to a higher expected benefit to innovate. A person with a deeper pool of knowledge becomes an information silo about a product category. As Alba & Hutchinson (1987) argue, more expertise leads to a better categorization of products. This enables a person to experience differences between products faster and see what products are needed to adopt in order to perceive and receive higher benefits. The broadness of expertise concerns the development of knowledge across different related product categories and allows people to combine existing knowledge leading to innovative ideas (Smith et al. 2006). One way of achieving a high level of broadness of user expertise is described by the boundary spanning role exhibited by lead users. By having contact with many types of users, lead users are able to gather different sorts of information (Jeppesen & Laursen, 2009; Kratzer & Lettl, 2009).
H2a: The deeper the level of user expertise, the higher the level of lead userness.
2.2.3 Opinion leadership
According to Von Hippel (1986), lead users are among the population of users that have both the need for novel products and the tendency to begin the experience with these products as they perceive the benefits of innovating to be high. As lead users are the first people to gain knowledge about innovative products they are often product opinion leaders for the bulk market. This entails that they influence other users by providing opinions and advices regarding these new products. For that reason they are considered to commence the diffusion of innovations. Accordingly, studies have shown that opinion leadership is strongly related to lead userness (Morrison et al. 2000) and some of these authors even see it as the third characteristic of lead userness (Spann et al. 2009; Özer, 2009). However, Kratzer & Lettl (2009) emphasize that opinion leaders and lead users should not be considered as being the same user. This study acknowledges the strongly related opinion leadership characteristic, but sees it as a consequence of being a lead user. The more a person is able to see ahead of the market trend and perceive high benefits to innovate, the more he is able to express potentially highly valued information which will enhance his status as an opinion leader (Schreier et al. 2007). Therefore this study proposes:
H3a: A high amount of lead userness positively influences the tendency to be an opinion leader.
Moreover, a moderating effect of the depth of user expertise on the relationship between lead userness and opinion leadership is suggested. The more knowledge a person gains about a product category, the more he is able to be a leading source of information within that field. Especially for highly innovative products, „ordinary users‟ need the expert knowledge of lead users in order to understand the benefits and use of these new products (Bilgram et al. 2008). Therefore this study proposes:
2.2.4 Behavior
This study also hypothesizes behaviors to be specific to lead users. There are five categories of behavior which will be considered in this research:
Early adoptive behavior – Early adoptive behavior arises from the need of lead users to be innovative. Although lead users often come up with their own solutions for problems and fill in their need gap by innovating, they also tend to be the ones who buy the newest available products. Because of new features and possibilities, these new products are more likely to fulfill their high needs (Lüthje, 2004; Schreier & Prügl, 2008).
H4a: A high amount of lead userness will positively influence the early adoption of innovations.
Multiple brand loyalty - In order to be ahead of an important market trend, lead users have a large knowledge pool of all available products and brands in a specific product category that make up for the current market trend. For that reason, lead users can more critically review their options regarding different brands when buying new products. Lead users will be able to reject alternatives and know the brands that generally perform well and satisfy their needs (Stokburger-Sauer & Hoyer, 2009). Rather than sticking to one brand, they look for a portfolio of high performing brands and remain loyal to those. For instance in the case of a computer, lead users will not buy a single branded computer. They rather buy the individual parts from different brands to assure the highest quality and assemble the computer themselves.
H4b: A high amount of lead userness will positively influence the level of multi brand loyalty.
Baumbach, 2010). When lead users behave according to this pattern, it becomes easier for companies to select the very few lead users that a population possesses.
H4c: A high amount of lead userness will positively influence a user’s participation in a given environment.
Providing solutions to other online users – As lead users are highly involved within their product category, they participate actively in the surrounding environment. They are showing this by innovating or helping other users solving problems they have with certain pieces of equipment (Schreier & Prügl, 2008). They can have valuable contributions as they provide solutions together with a sound knowledge base about the specific product(s). Especially within an online environment lead users are easier to identify because of their visibility considering this behavior (Spann et al. 2009). By commenting on postings of other users, participating in the topics discussed and providing solutions to problems of other users, they show themselves to every other visitor of the online community.
H4d: A high amount of lead userness will positively influence the tendency to provide solutions to other online users.
Furthermore, the tendency to provide solutions is hypothesized to be moderated by the amount of the depth and broadness of user expertise. The more expertise a person has, the more he is able to provide solutions to other users' problems.
Communication streams - As suggested by Schreier et al. (2007), there is need to study how and to whom lead users communicate. When it is clear to which users they communicate and through which medium, the diffusion of innovation processes becomes clearer. Lead users are supposed to share their opinions, serve as a source of advice and offer solutions to problems of other less knowledgeable users. However, as Schreier et al. show, lead users exhibit less opinion seeking behavior. In contrast to less leading edge users, they are supposed to rely less on information of others before they purchase new products. Additionally this study focuses on lead user's communicative behavior towards different social groups. As Kratzer & Lettl (2009) show, lead users tend to exhibit the role of boundary spanner. They reside between different kinds of social groups and communicate more often with them than the typical opinion leader. This study proposes that users with a higher amount of lead userness have the tendency to communicate more with different social groups than other users.
H4f: A high amount of lead userness will positively influence the amount of communication towards different social groups (high same and low status).
H4g: A high amount of lead userness will positively influence opinion giving behavior towards different social groups (high, same and low status).
3. METHODOLOGY
3.1 Context for empirical research
This study looked for an online community to distribute a questionnaire, as this proves to be a good method to identify the small amount of lead users in a population. Firstly, lead users exhibit a process of self selection in online environments (Spann et al. 2009). Lead users tend to actively participate in these settings, as they share their opinions and provide solutions to problems of others by commenting and posting more frequently than less leading edge users. As a result, distributing an online questionnaire on a community forum will get the attention of lead users as they are actively participating in this online environment. Furthermore, because of the public availability of most online environments, distributing the questionnaire will be more time and cost efficient than doing so in a sealed offline environments (Belz & Baumbach, 2010).
this…‟ show the innovation‟s attractiveness for the bulk market. 1
For the reasons mentioned above, the online environment of GoT was suited for the purpose of this research due the fact that it (1) has a large amount of users discussing topics concerning modifying and enhancing the performance of one‟s electronic equipment and therefore showing the need to improve and innovate and (2) concerns the latest hardware and software, with many users living on the leading edge of the market trend by reviewing the latest innovations, providing answers to innovative problems and over clocking and tweaking the newest products.
3.2 Data collection
In order to get the data to test this study‟s hypotheses, an online questionnaire was distributed on GoT in June 2011. As approximately 50% of the daily forum page views are generated in the General Forum („Stuffis Generalis‟), this forum was considered to be suited for the purpose of this research. Furthermore, as the requirement for users on „Stuffis Generalis‟ is to have least 50 forum posts, the amount of active participants is higher. Because this characteristic is specific to lead users, „Stuffis Generalis‟ was a good choice to ensure a sufficient amount of lead users.
A topic was created with the most relevant information for the participants, including a small introduction to this research and a hyperlink to the questionnaire. The topic was daily checked in order to provide answers to questions of forum considering this research. Furthermore, each day an update on the amount of participants was shared with the community. In order to motivate the community users even further, €100, - was donated to a specific charity fund chosen by Tweakers.net for the returned questionnaires.
The topic in which the questionnaire was posted generated a total of 3439 unique viewers. A total of 237 participants completed the questionnaire, resulting in a response rate of 6,9%. Although this
1
method is less direct than sending out e-mails to forum members, the numbers are quite satisfactory. The average age of the participant was 28,1 (SD = 8.00) and the sample consisted mostly of males 96.6%.
3.3 Measurement instruments
The questionnaire consisted of three independent parts. Firstly, participants were asked to fill in the Five Factor questionnaire. The Five Factor personality traits were measured through ten questions each. Secondly, the participants were handed questions about their level of lead userness. Furthermore the constructs opinion leadership and user expertise were also added as variables. Lastly, to complete the view on lead users, questions about five different behaviors were added to the questionnaire. All but one variable were measured through statements on a 5-points Likert scale, scored from (1) highly disagreeing to (5) highly agreeing.
3.3.1 Field independent factor
Five Factor Model
For the measurement of the Five Factor personality traits, the survey on http://ipip.ori.org/ipip/ was used. Goldberg (2006) shows that this test has adequate validity and reliability. Ten questions were used to describe each of the Five Factors. The different items can be found in appendix A.
3.3.2 Field dependent factors
Lead userness
computers, electronics and peripherals. Additionally, from earlier research done by Franke & Shah (2003), four questions were adapted to measure ahead of the market trend. These items completed the lead userness scale, asking whether participants (5) while making use of their computers, electronics and peripherals, are confronted with problems that cannot be solved by computers, electronics and peripherals equipment available on the market; (6) perceive the performance of their computers, electronics and peripherals stores to be sufficient for their needs; (7) experience still unresolved problems with computers, electronics and peripherals and (8) are constantly looking for improved computers, electronics and peripherals.
User expertise depth
Also based on Franke et al. (2006), this concept was measured by questioning participants whether they: (1) can repair their own computers, electronics and peripherals; (2) can help other users solve problems with their computers, electronics and peripherals; (3) can make technical changes to their computers, electronics and peripherals on their own and (4) use their computers, electronics and peripherals frequently.
User expertise broadness
The items for broadness of user expertise were derived from Franke et al. (2006) and complemented by other items. Participants were asked whether they (1) try to keep up to date with regard to the materials, innovations, and possibilities of computers, electronics and peripherals; (2) have expertise in different kinds of fields related to computers, electronics and peripherals and (3) often have contact with users in related fields to computers, electronics and peripherals.
Opinion leadership
products he or she owns; (2) the tendency of a person to be consulted by others before buying a product and (3) the tendency to convince other users to follow their opinion.
3.3.3 Behaviors
Early adopting
Early adopting was measured through two items, based on work by Özer (2009). Participants were asked if (1) they usually adopt new products earlier than other people and (2) they think it is important to own the newest computers, electronics and peripherals.
Multi brand loyalty
Based on the study conducted by Stockburger-Sauer & Hoyer (2009), multi brand loyalty was measured by asking to what extent a person (1) has positive feelings towards many different brands related to computers, electronics and peripherals, but always buys the same brand(s) and (2) is loyal to more than one brand related to computers, electronics and peripherals.
Participation
Furthermore, respondents were asked to what degree they actively participate in the environment of Gathering of Tweakers. They were asked to rate their participation from very inactive (1) to very active (5).
Providing solutions to other online users
Communication streams
Lastly, communication streams were measured. Participants were asked to what extent they (1) communicate with users with higher, lower and equal status; (2) seek advice from users with higher, lower and equal status and (3) give advice to users with higher, lower and equal status. Additional tests on these 9 items revealed that communicating, seeking advice and giving advice to different social status groups pertain to the same factor instead of three different factors. In the result section, the latent factor 'communication streams' consists of nine indicators, all pointing to communication with different social status groups.
3.3.4 Measurement model
Standard procedures were used to test the reliability and validity of the measurement items. Low loadings (< .40) and high cross-loadings (> .30) were used to drop some items of the variables in the FFM. The measurement scales for conscientiousness, agreeableness and openness to experience needed revision, while all other variables used in this study provided satisfactory measurement validity. Composite scores of the individual Five Factors were composed in order to enable model testing with Amos 18.
The final measurement model provided the following results: χ²/df = 2.31 (χ² = 1529.1; df = 663);
To minimize common-method variance, which may occur due to the use of a survey, several item scales contained reverse-coded items (Lindell & Whitney, 2001). To rule out additional method bias, a Harman's single-factor test with CFA was conducted (Podsakoff et al. 2003). 2 The results were satisfactory, showing a poor fit for the-one factor model: χ²/df = 7.04 (χ² = 5726.4; df = 819); CFI = .14;
GFI = .35; RFI = .12; TLI = .14; RMSEA = .16. Additionally, the correlations between the different constructs did not exceed 0.8 (Bagozzi, Yi & Philips, 1991).
2
26
Construct Extraversion Agreeableness Conscientiousness Neuroticism
Openness to
experience Lead userness
User expertise depth Extraversion 0.70 Agreeableness 0.32 (0.08)* 0.66 Conscientiousness 0.13 (0.07) 0.07 (0.07) 0.73 Neuroticism -0.27 (0.06)** -0.14 (0.08)* 0.09 (0.07) 0.65 Openness to experience 0.33 (0.06)** 0.10 (0.07) 0.05 (0.07) -0.29 (0.07)** 0.58 Lead userness 0.09 (0.10) 0.18 (0.12) 0.03 (0.09) 0.07 (0.10) 0.32 (0.09)** 0.64
User expertise depth 0.06 (0.07) 0.12 (0.10) 0.07 (0.08) -0.09 (0.08) 0.26 (0.09)** 0.57 (0.11)** 0.77
User expertise broadness 0.03 (0.08) 0.16 (0.09)* -0.04 (0.08) -0.06 (0.08) 0.18 (0.08)* 0.80 (0.13)** 0.75 (0.07)**
Opinion leadership 0.15 (0.07)* 0.15 (0.08)* 0.03 (0.07) 0.01 (0.07) 0.06 (0.07) 0.59 (0.12)** 0.35 (0.07)**
Early adopting -0.02 (0.08) 0.01 (0.10) -0.14 (0.09) 0.12 (0.11) 0.07 (0.09) 0.57 (0.16)** 0.32 (0.09)**
Providing solutions -0.00 (0.07) 0.03 (0.07) 0.01 (0.08) -0.09 (0.08) 0.26 (0.07)** 0.58 (0.12)** 0.43 (0.06)**
Multi brand loyalty -0.00 (0.07) 0.00 (0.08) -0.18 (0.08)* 0.08 (0.08) -0.01 (0.07) 0.18 (0.12) 0.17 (0.09)*
Communication 0.00 (0.07) 0.11 (0.08) 0.12 (0.06)* 0.09 (0.07) 0.06 (0.07) 0.26 (0.10)** 0.15 (0.07)
Participation 0.07 (0.07) 0.03 (0.06) -0.01 (0.06) -0.03 (0.06) 0.09 (0.06) 0.34 (0.09)** 0.31 (0.06)**
Construct User expertise broadness Opinion leadership Early adopting Providing solutions Multi brand Loyalty Communication Participation
Extraversion Agreeableness Conscientiousness Neuroticism Openness to experience Lead userness
User expertise depth
User expertise broadness 0.69
Opinion leadership 0.56 (0.08)** 0.76
Early adopting 0.72 (0.09)** 0.42 (0.10)** 0.62
Providing solutions 0.61 (0.07)** 0.68 (0.06)** 0.41 (0.10)** 0.82
Multi brand loyalty 0.29 (0.10)** 0.29 (0.09)** 0.46 (0.13)** 0.17 (.0.09)* 0.80
Communication 0.28 (0.07)** 0.40 (0.06)** 0.25 (0.09)** 0.44 (0.06)** 0.06 (0.08) 0.84
Participation 0.39 (0.07)** 0.33 (0.08)** 0.30 (0.09** 0.35 (0.06)** 0.14 (0.09)** 0.28 (0.07)** n.a.
Table 4: correlations and AVE’s.
The numbers below the diagonal represent the correlations between two latent constructs. The numbers in bold represent the square root of the average variance extracted (AVE). Standard errors were derived from bootstrapping with 500 replications.
27
4. RESULTS
4.1 Structural model
Figure 2 shows the regression coefficients of the structural model. The structural model provides the following results: χ²/df = 2.42 (χ² = 1785.6; df = 737); CFI = .82; GFI = .74; RFI = .70; TLI = .80;
RMSEA = .08. Although the model does not fit the data extremely well, it explains a good amount of variance in lead userness (R² = .71). Other constructs' explained variances range from .06 to .59. Furthermore, the control variables age and gender did not account for a significant difference in lead userness.
4.2 Hypotheses testing
No support could be found for H1a (β = 0.02, p>.05), H1b (β = -0.04, p>.05), H1c (β = 0.01, p>.05), H1d (β = 0.10, p>.05) and H1e (β = 0.06, p> .05) meaning that the Five Factor Model had no significant effect on the amount of lead userness. As hypothesized by H1f, openness to experience positively influences the tendency to have both higher levels of broadness and depth of user expertise (β = 0.19, p<.05; β = 0.26, p<.01). Also agreeableness (β = 0.18, p<.05) is positively related to high levels of broadness of user expertise, as suggested by hypothesis H1g.
Additionally, no empirical evidence could be found for the relationship between the depth of user expertise and the level of lead userness (H2a: β = 0.11, p>.05). However, evidence for H2b was found (β = 0.81, p<.01), proving that the amount of lead userness is strongly influenced by the broadness of user expertise. Evidence was found for a positive relationship between lead userness and the tendency to be an opinion leader (H3a: β = 0.73, p<.01).
userness has a positive effect on the degree of participation in a given environment (β = 0.86, p<.01). Moreover, lead userness is strongly related to proving solutions, as depicted by hypothesis H4d (β = 0.77, p<.01). Finally, a strong association between the amount of communication towards different social groups and lead userness is found (H4f, g & h): β = 0.43, p<.01. Lead users tend to communicate with people having different social statuses.
In sum, broadness of expertise strongly influences lead userness. In turn, broadness of expertise is explained by both openness to experience and agreeableness. Furthermore, there is strong evidence for the relationship between lead userness and opinion leadership, and there are significant relationships between the five behaviors in this research and lead userness. Unfortunately, no evidence was found for the relationship between the Five Factors and lead userness. Also the depth of user expertise did not have significant explanatory power towards lead userness.
4.3. Moderating effects
As proposed in the conceptual model, this study tested the moderating power of the depth and broadness of user expertise. In order to do so, a χ² differentiation test was conducted. Both depth and broadness of user expertise were divided into two groups based on a median split. For each moderating test the structural parameter was fixed across groups, leading to a less fitting model. A moderation effect is found when the increase in χ² with 1 degree of freedom of one group versus the other was significant (Byrne, 2010).
4.4. Mediating effects
The relationships between the Five Factor model and lead userness did not provide significant results. However, while doing the analysis for the relationship between openness to experience and agreeableness and broadness of user expertise, a significant relationship was found. Furthermore the relationship between broadness of expertise and lead userness also provided significant results. This could point towards a mediating effect and thus for these Five Factor variables mediation tests were conducted. Firstly, this study looked at Sobel (1982) test statistic for indirect effects. Furthermore, the method by Mathieu & Taylor (2006) was used to evaluate whether the effect of the Five Factor model on lead userness was fully, partially or not mediated by the level of user expertise. The Five Factor model and the level of broadness and depth of a person's user expertise were isolated in order to conduct this analysis.
Table 5 displays the direct and indirect effects of the Five Factor model on lead userness through the broadness of user expertise. The results show that the indirect effect of the broadness of user expertise on the relationship between openness to experience is significant (p<.05). The level of broadness partially mediates the relationship, as all four relationships in the different equations are significant. The relationship between agreeableness and lead userness is not considered to be fully mediated by the broadness of user expertise, because an important condition for mediation is not met: there is no significant relationship between agreeableness and lead userness in an isolated setting.
Table 5: indirect effects of the broadness of user expertise Notes:
a. In order to test the mediation effect, the relevant variables were isolated. Due to the isolation, openness to experience and agreeableness did provide significant relationships in contrast to figure 2.
b. *p<.05; **p<.01
Equation 1: Equation 2: Equation 3: Sobel test
Independent variable
Mediator = f(Independent)a
Dependent = f(Independent)
Dependent = f(Independent, Mediator)
Independent Mediator
Openness .24 (.10)** .32 (.10)** .19 (.09)* .54 (.08)*** 2.26*
30 .02 -.04 .01 .10 .06 .18* .19* .26** .73** .77** .67** .43** .35** .86** .81** .11 -0.08 0.02 .06 .55 .71 .08 .59 .45 .12 .19 .16 1 1
Figure 2. Structural model Notes:
a. *p<0.05; **p<0.01
b. Standardized coefficients are shown, however moderation effects are not. c. Numbers in bold represent the explained variance.
d. Variables in circles represent latent variables. Variables in squares manifest variables.
Opinion leadership Agreeableness Extraversion Conscientiousness Neuroticism Openness to experience Providing solutions Early adopting User expertise broadness Gender Age
Multi brand loyalty
31
5. DISCUSSION
5.1 Discussion of results and managerial implications
The purpose of this research was to contribute to the existing literature by providing a multi level analysis on lead users. The goal was finding relevant field dependent and independent factors and behaviors with regard to lead userness, so that the identification process could be simplified. While many studies have isolated antecedents and consequences of lead userness in order to find significant relationships, this study developed a comprehensive level model including 16 variables. The multi-level approach has two important advantages. First of all, such an approach shows the relative importance of variables, as previous studies have focused solely on relationships on a small amount of factors and lead userness. Secondly, a multi level analysis points out the hierarchy of effects, showing which variables should be considered first when scanning for lead users.
This research looked at the field independent factors that might influence the level of lead userness. No evidence could be found for the relationship between personality traits and lead userness, although an indirect effect of openness to experience on lead userness was found. This indirect effect aids in the identification process of lead users, which will be discussed below.
innovations is a function of combining existing knowledge with the exchange of knowledge (e.g. Smith et al. 2006). Also the moderating role of broadness of user expertise on the relationship between lead userness and the tendency to provide solutions emphasizes the importance of this concept. Managers should not focus too much on users that are experts in their own fields as lead users tend to be active in different fields related to their main product category. This role of lead users should receive more attention because it seems to be the most important characteristic next to high expected benefits and ahead of an important market trend.
For the identification of persons with a broad expertise, two field independent variables could be used. Both agreeableness and openness to experience indicate users with a broad level of user expertise. Scanning people on these two personality traits could serve as a first filter for finding useful users. Interesting about the positive effect of agreeableness is that there are also arguments that this variable inhibits innovation. Because agreeable persons are more subject to compliance they tend to do what others persons do and therefore do not exit the status quo (Costa et al. 1991; Sung & Choi, 2009). As agreeableness encompasses many elements, it seems that the corporation and trust factors are the most applicable regarding lead userness.
In addition to the factors investigated by Schreier & Prügl (2008), this study addressed more antecedents of lead userness. The behaviors called for in this research prove to be specific to lead users. Firstly, these type of users can be differentiated based on their tendencies to provide solutions and their active participation. As Spann et al. (2009) and Belz & Baumbach (2010) already indicate, this self selection process enhances the identification process of lead users. These factors provide opportunities for identification of lead users in especially online environments, as these behaviors lie on the surface. Managers can scan online communities for users that provide solutions and actively participate, as lead users often help communities to keep their information up to date.
because lead users are also opinion leaders and early adopters. This argument becomes stronger when looking at their extensive communicative behavior. Lead users communicate towards different social groups are therefore good diffusers of information about the newest products.
5.2 Limitations and future research
The findings of this study came from a community-based website on electronics, computers and peripherals where highly advanced topics are being discussed. It might be suggested that this study‟s variables are specific to these specialized markets and therefore lead to lower external validity. To deal with this problem, this study follows the reasoning by Schreier & Prügl (2008) of a general underlying mechanism which is in favor of the generalizability. People with innovative characteristics are more interested in gaining expertise in specific product fields and more importantly, in other related product categories. From that knowledge they develop a tendency to live on the leading edge of markets and there they experience high expected benefits to innovate. Together these lead user characteristics influence opinion leadership and certain behaviors that apply to a different set of markets. The approach suggested by these researchers applies to not only technology markets, but to other consumer fields as well. Although this argument in favor of external validity makes sense, many lead user studies have focused on populations consisting largely of men (e.g. Franke & Shah, 2003; Schreier et al., 2007). It might be interesting for further studies to take a look into the population of female lead users, as Costa et al. (2001) show that differences in personality exist between men and women. Therefore the screening variables that differentiate male lead users from less innovating users may be different for women. Future studies could complement lead user research by providing empirical evidence for more female-based product markets, for example cosmetics.
should include the most recent version of the FFM model in order to meet the criterion of construct validation. Because these were not entirely met, the effects of personality traits on lead userness may have led to insignificant results.
During the analysis the measurement for communication streams showed unexpected results. Instead of revealing three factors, only one factor was derived. Communication in general, opinion seeking and opinion giving were viewed as one factor describing communication. It is possible that the respondents did not see a difference between these forms of communication. Future research is invited to look for additional evidence of the existence of different forms of communication related to lead userness. That way the diffusion of innovations becomes clearer.
Also other field independent variables could be added in further research to explain lead userness, relevant characteristics and behaviors. Past studies have focused on motivational variables. For instance, Von Hippel (1986) focused on how lead users were motivated to perform an activity better than others users, while other researchers have focused on cognitive benefits and gaining reputation (Jeppesen & Frederiksen, 2006; Nambisan & Baron, 2009). However these researchers did not manage to give an exhaustive view on how lead users are motivated. Together with the distribution of the questionnaire on GoT, a discussion was started on these motivational aspects. A large amount of users responded to this discussion, by elaborating that the motivations called for by prior research did not match their own. They considered their contributions to the community be for altruistic reasons, indicating that they did not help other users solve problems in order to gain status or reputation. A suggestion would be to include different motivational aspects in a multi level study, so that lead users can be approached according to their specific motivational needs.
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APPENDIX A: MEASUREMENT ITEMS
Personality traits Scored from highly disagreeing to highly agreeing (1-5) I am...
Extraversion 1. Am the life of a party
2. Don't talk a lot
3. Feel comfortable around people 4. Keep in the background 5. Start conversations 6. Have little to say
7. Talk to a lot of different people at parties 8. Don't like to draw attention to myself 9. Don't mind being the center of attention 10. Am quiet around strangers
1. Feel little concern for others. 2. Am interested in people. 3. Insult people.
4. Sympathize with others' feelings.
5. Am not interested in other people's problems. 6. Have a soft heart.
7. Am not really interested in others. 8. Take time out for others. 9. Feel others' emotions. 10. Make people feel at ease.
1. Am exacting in my work. 2. Follow a schedule. 3. Shirk my duties. 4. Like order.
5. Often forget to put things back in their proper place. 6. Get chores done right away.
7. Make a mess of things. 8. Pay attention to details. 9. Leave my belongings around. 10. Am always prepared.
1. Get stressed out easily. 2. Am relaxed most of the time. Agreeableness
Conscientiousness
Openness to experience
3. Worry about things. 4. Seldom feel blue. 5. Am easily disturbed. 6. Get upset easily. 7. Change my mood a lot. 8. Have frequent mood swings. 9. Get irritated easily. 10. Often feel blue.
1. Have a rich vocabulary.
2. Have difficulty understanding abstract ideas. 3. Have a vivid imagination.
4. Am not interested in abstract ideas. 5. Have excellent ideas.
6. Do not have a good imagination. 7. Am quick to understand things. 8. Use difficult words.
Characteristics Scored from highly disagreeing to highly agreeing (1-5) Ahead of the market trend - adapted
from Franke et al. (2006).
1. I usually find out about new computers, electronics and peripherals earlier than others.
2. I usually find out about solutions to problems with new computers, electronics and peripherals earlier than others.
3. I have tested prototype versions of new computers, electronics and peripherals for manufacturers.
4. I have improved and /or developed new features in computers, electronics and peripherals.
1. While making use of computers, electronics and peripherals, I am often confronted with problems that cannot be solved by computers, electronics and peripherals equipment available on the market.
2. The performance of my computer(s), electronics and peripherals stores is sufficient for my needs.
3. In my opinion, there are still unresolved problems with computers, electronics and peripherals.
4. I am constantly looking for improved computers, electronics and peripherals.
1. I tell my community members about the new innovations I have purchased / obtained.
2. Before others in the community buy new products, they ask me for advice. 3. In a discussion about computers, electronics and peripherals, I would most likely convince my fellow community members of my own ideas.
1. I can repair my own computers, electronics and peripherals.
2. I can help other users solve problems with their computers, electronics and peripherals.
3. I can make technical changes to my computers, electronics and peripherals on my own.
4. I use my computers, electronics and peripherals frequently.
1. I always try to keep up to date with regard to the materials, innovations, and possibilities with regard to computers, electronics and peripherals.
2. I have expertise in different kinds of fields related to computers, electronics and peripherals.
3. I often have contact with users in related fields to computers, electronics and peripherals.
High expected benefits- adapted from
Franke et al. (2003).
Opinion leadership -adapted from
Kratzer & Lettl (2009) and Schreier et al. (2007).
User expertise depth
adapted from Franke et al. (2006).
User expertise broadness
Behavior Scored from highly disagreeing to highly agreeing (1-5) Early adopting
adapted from Özer (2009).
Multi brand loyalty
1. I usually adopt new products earlier than other people.
2. Owning the newest computers, electronics and peripherals is important to me.
1. I have positive feelings towards many different brands related to computers, electronics and peripherals, but I always buy the same brand(s).
2. I am loyal to a couple of brands related to computers, electronics and peripherals.
1. I am an active participant on Gathering of Tweakers.
1. In the online community I am participating in, I am often the one providing solutions to problems users face.
2. When a user posts a problem in the online community, I am often the first providing the solution.
1. I often communicate with users with higher status than I have. 2. I often communicate with users with lower status than I have. 3. I often communicate with users with the same status as I have. 4. I often seek advice from users with higher status than I have. 5. I often seek advice from users with lower status than I have. 6. I often seek advice from users with the same status as I have. 7. I often give advice to users with higher status than I have. 8. I often give advice to users with lower status than I have. 9. I often give advice to users with the same status as I have.
adapted from Stockburger-Sauer & Hoyer (2009).
Active participation
Providing solutions to other online users
adapted from Spann et al. (2009).
