From Motivation trough Participation
to Loyalty
The Differential Effect of product type in Online Communities
Master’s Thesis
Author: Rosa Boomsma BCom
Student id: 306444
Master Marketing
Erasmus School of Economics
Erasmus University Rotterdam
Supervisor: Dr. Remco Prins
Second supervisor: Dimitrios Tsekouras MSc
Rotterdam, 2009
From Motivation through Participation to loyalty;
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Index
Abstract ................................................................................................................................ 3
Chapter 1. Introduction................................................................................................... 4
1.1.
1.2.
1.3.
Chapter 2.
2.1.
2.2.
2.3.
2.4.
2.5.
2.6.
Chapter 3.
3.1.
3.2.
3.3.
3.4.
Chapter 4.
4.1.
4.2.
4.3.
Chapter 5.
5.1.
5.2.
5.3.
Motivation and contribution..................................................................................4
Research questions and sub research questions ..................................................5
Thesis outline...........................................................................................................7
Theoretical background and hypotheses ...................................................... 8
Introduction and contribution of this research ...................................................8
Online communities ................................................................................................9
passive vs. active participation ............................................................................11
participation as an antecedent of loyalty ............................................................12
motives for participation ......................................................................................15
Product category as a moderator ........................................................................22
Methodology ................................................................................................ 28
Approach ...............................................................................................................28
Questionnaire construct .......................................................................................28
Variables ................................................................................................................31
Regression analysis ...............................................................................................33
Results.......................................................................................................... 35
passive participation: ...........................................................................................35
active participation ...............................................................................................39
loyalty......................................................................... Error! Bookmark not defined.
Conclusion................................................................................................... 45
Discussion ..............................................................................................................45
Implications of this research ................................................................................47
Limitations of this research .................................................................................48
References ......................................................................................................................... 50
Appendix 1. Items used ................................................................................................ 52
Appendix 2. Questionnaire .......................................................................................... 55
Appendix 3. Survey invitations .................................................................................... 56
Appendix 4. Research results Thorsten Hennig-Thurau et al ................................... 58
Appendix 5. FCB Grid ................................................................................................. 59
Abstract
Members of online communities view (passive participation) or post (active participation) content
for multiple reasons. This present research will examine the moderating effect of ‘product type’
on the relationship between several ‘motives’ to participate and ‘participation’. To underline the
marketing relevance of this research, the relationship between participation and customer loyalty
is examined as well.
In order to generate data to test both the direct and moderating effects, two surveys were taken.
For the first survey, a sample was used of some 305 internet users. This survey provided data on
motives for participation, the type and level of participation and the type of product. For the
second survey, a sample was used of some 130 members from tweakers.net. This survey provided
data on the level of participation and the level of loyalty towards a certain brand.
After defining all variables, the direct effect of several motives on participation was measured,
using the linear regression model. Here, a distinction was made between motives for ‘passive’
participation and ‘active’ participation. Furthermore, there was support for two out of six motives
to have a significant effect on passive participation. However, there was no proof of a moderating
effect caused by ‘product type’. There was support for four out of five motives to have as
significant effect on active participation. For one out of five motives, there was also evidence for a
moderating effect, caused by ‘product type’. Finally, the analysis showed that passive
participation has a significant effect on brand loyalty. However, there was found no relationship
between active participation and brand loyalty.
In general, online communities try to strive for the highest participation. This present research
indicates what motives are important in both passive or active participation. Moreover, lessons
can be drawn from differences between product types. Finally, the relevance and importance of
both active and passive participation within online communities is explained.
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Chapter 1.
Introduction
With the growing importance of the internet, a new phenomenon, called web 2.0, is growing in
popularity as well. The term web 2.0 was introduced by Tim O’Reilly (2004), describing an
emerging new user-centered web. On this web, websites are using different interactive web
applications which are created for the people to use. Well-known examples of this approach are
online forums and social networking sites like Facebook or Hyves. These applications are based
on the principle of user generated content, where the content is mainly provided by the user. The
concept can differ and therefore the purposes and benefits differ among websites and applications.
Within the social context for example, the web 2.0. enables people to establish communities
online while it enables offline communities to move toward an online environment. Maintaining
and building relationships is less time consuming, and seeking information with other subject
enthusiasts becomes more efficient. Within a more knowledge based context, (online) companies
can use online user behavior and user generated content to adjust their offerings to meet specific
customers’ needs.
1.1. Motivation and contribution
Implications in the Field of Marketing
Online communities, web 2.0 and virtual worlds have been the subject of attention for many
researchers the last decade. Rightly so, because in 2009 over 67% of the global online population
visited “member communities”, including social networks and blogs (Nielsen Online; 2009).
Developing a platform for customers and potential customers to interact with each other in
relation to a certain brand or product can be an advantage in different ways (Kumar et al.; 2006)
(McWilliam; 2000). For instance, customers are an infinite source of knowledge for innovation.
Moreover, community members can be used as a database with people who share characteristics
(e.g. interests, attitude towards a brand, etc.). Members seem to be willing to interact with
producers during development, driven by interests in innovation (Füler et al.; 2008). Another
advantage is the opportunity to create a buzz by multiplying a brand’s popularity through
consumer articulations on the web. Bringing people together that have a common interest in a
brand, is a type of viral marketing that improves sustainable brand cult (Cova and Pace; 2006).
Another reason in support of using online communities as a marketing tool are the studies on
Word-of-Mouth. These communities provide a platform for sharing experiences, concerning a
brand or product, between the community members. It will add to the company’s brand equity
when more people are interested in, and are talking about, a product or brand. There is even a
good reason to maintain the negative comments.
Although bad reviews can have negative
influence, it also helps containing the trustworthiness of the community (Shang et al. 2006).
In general, an online community can only exist if sufficient members participate (Koh et al.;
2007). This can either be in the form of viewing content (passive participation), or actually post
content yourself (active participation). For company initiated communities, interaction among
participants is even more important, the participation has to lead to some extend of brand or
customer loyalty in order to be an attractive investment.
As a consequence, lot has been written about what drives people to participate and contribute to
these online communities (e.g.: Hennig-Thurau and Walsh (2003), Hennig-Thurau et al.; (2003)),
Jang et al; (2008). Or more importantly, how can this be stimulated (e.g.: Koh et al; (2007),
Beenen et al. (2004))? Although these motives and stimuli are relevant, some researchers have
been questioning whether findings on participation would differ between different kinds of
products (Hennig-Thurau and Walsh; 2003), (Shang et al.; 2006). This present research will
examine whether there is a difference between the effect that ‘motives to participate’ have on
participation for different product types. Furthermore, the relationship between participation and
customer loyalty is examined as well.
1.2. Research questions and sub research questions
Main research question
What are the differences between motives between different levels of participation and different
product types, and does this lead to loyalty intentions?
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To make assumptions about what motivates people to read information that is posted on websites,
or to actually contribute content to an online community, influences on participation have to be
examined. Consequently the following research question is formed to examine this.
Research question 1
What motives have a significant influence on passive participation and what motives tend to
evoke active participation?
As described above, it is important to see whether some motives have a stronger influence on
either passive or active participation than others. Although conclusions will be drawn from these
measures (question 1), the relationship primarily serves as a benchmark in measuring the effect of
the moderator (question 2):
Research question 2
Do motives for participation differ between product types?
However, even if there appears to be a relationship between one or both forms of participation and
loyalty intentions, the motives behind participating may be the true explanatory variable. The
attitude may already be formed before an internet user reads or posts information in the
community.
Research question 3
To what extent does motivation leading to participation explain the influence on loyalty intention?
Actual value for companies is only created if the customer grows loyalty intentions, directly or
indirectly, caused by passive or active participation. Whether participation has a significant
influence on loyalty intentions, which will be further explained in paragraph 2.5, is to be answered
by research question 3a. Although passive participation cannot exist without the presence of
consumer created content, passive participants may be more inclined to buy the product than
active participants, the other way around, or neither. Moreover, if motives differ between both
forms of participation (research question 1), it is very well possible that the attitude towards a
product, differs as well (question 3b).
Research question 3a
Is participation an antecedent of loyalty intention?
Research question 3b
What form of participation has a stronger influence on loyalty intention?
In the following research model, the three research questions are depicted.
PRODUCT TYPE
Q2
PASSIVE
PARTICIPATION
LOYALTY
MOTIVES TO
PARTICIPATE
Q
1
Q3
INTENTIONS
ACTIVE
PARTICIPATION
1.3. Thesis outline
The results of the literature review are divided into three chapters. In chapter 2, an introduction is
given on the topic online communities, web 2.0. and how these can be used for business purposes.
Furthermore, the relationship between both forms of participation and loyalty will be discussed.
The set of potential motives for participation will also be discussed in this chapter. To what extent
the relationship between motivation and participation is influenced by the type of product is
discussed at the end of this chapter. The hypotheses will formulated based on and resulting from
the theoretical background. In chapter 3 the design and methodology of the research is explained.
Research results and analyses are given and elaborated on in chapter 4. The results are discussed
in chapter 5, and finally the restrictions and implications of the research are explained.
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Chapter 2.
Theoretical background and hypotheses
2.1. Introduction and contribution of this research
In former research, different influences that encourage participation have been investigated. Some
researchers have focused on platform characteristics e.g. information quality , usefulness , size,
levels of interaction (Koh and Kim; 2003), (Jang et al.; 2008). Others have looked at the basic
motivation for participants to exchange information or communicate with each other (Gruen et al.
2005), (Hennig-Thurau et al.2004). These characteristics or motivators to participate are indeed
important to take into consideration, but may vary when other variables such as product type or
community type are taken into account as well. Mot Jang et al. (2008) for example have shown
that the characteristics, influencing community commitment, vary between consumer initiated
communities and company initiated communities. The same differences between motives to
participate could arise between different product types being the topic of a certain community.
Shang et al. (2006) discuss the influence of participation on loyalty in a virtual community of
Apple, but question whether the outcomes would be the same for different types of products.
These authors argue that computers are informational and high involvement products, and
therefore, satisfying informational needs may be the main motivation for participation. HennigThurau and Walsh (2003) indicated the same limitations to their research. They questioned
whether their conclusions on motives for viewing online content would be the same for high and
low involvement products.
To prove potential differences in member participation among product categories, a direct
influence on participation is used as a benchmark. Instead of examining how Website attributes or
characteristics affect member participation, motivation to participate will be examined. Arguing
that fulfilling a need is the main driver in becoming a member of an online community, this serves
as a basis on which the moderating effects of the type of product are tested.
Two product types are chosen in such a way that differences are most likely to occur. For each of
these product types, examples of empirical communities are gathered to serve as a background for
the research. In chapter 2, this will be described in further detail.
Both reasons for community members to read customer articulations on the internet, as to post
articulations themselves, are researched (Hennig-Thurau and Walsh; 2003) (Hennig-Thurau et al.;
2004). The former form of participation can be described as passive participation or Lurking,
while the latter is referred to as active participation or Posting. Although these authors elaborated
on the motives for both types of member behavior, these were never combined in one study. This
research aims to measure both forms of participation combined in one research.
2.2. Online communities
The definition of the term “Community” has been formulated many times, over many disciplines,
including psychology, sociology and biology. Although these definitions vary across disciplines
and authors, there is some significant overlap. There are three major criteria in order to explain
communities, which we can find in most of the definitions. 1) Members of a community tend to
come or live together, in physical or virtual spaces. 2) There has to be some interaction in order to
build relationships. 3) Community members bond through common characteristics, experiences or
values (Jang et al.; 2008), (Koh and Kim; 2003). Gusfield (1975) describes two different types of
communities. The traditional territorial or geographic community and the relational community
revolving around member relationships. Considering the absence of a physical place to meet,
virtual communities could be regarded as relational communities. However, members can become
attached to these virtual spaces which eventually can become a substitute for a geographical place.
The term “Online Communities”, as the term “Communities”, comes with multiple definitions.
What these definitions have in common, is that online communities are regarded as a computermediated space. The definition by Bagozzi and Dholakia (2002), captures the main idea: “We
view virtual communities to be mediated social spaces in the digital environment that allow
groups to form and be sustained primarily through ongoing communication processes”. This can
either serve as supplement or substitution to physical communities (Bagozzi and Dholakia; 2002).
Although it is often described as a social space, communities not always serve solely as means to
build social relationships, as will be explained.
According to Bagozzi and Dholakia (2002) communities share several characteristics. 1)
Communities often exist around a certain common interest. 2) Members from the community feel
a certain belonging to this group, which separates them from other groups. 3) Most communities
have written or unwritten rules and habits in expressing themselves. These are so called
netiquettes. 4) Unlike traditional media, content is created and published by active participants.
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This concept is in line with the core concept behind Web 2.0 mentioned earlier. Web 2.0
applications have shifted online activities from browsing to interacting and contributing. 5)
Nonverbal expressions and physical appearance is often filtered out. However, with the continues
technological developments, image supported communication becomes more easy.
Rheingold (2000) argues that although there are resemblances between online (virtual)
communities and physical communities, a large difference lies within the interaction. Outside the
virtual world, people first meet face to face, get to know one another, and possible form
relationships. Within online communities, people get to know one another, build relationships, and
possible get face to face. Another difference is whether or not participation is voluntary or not.
participation in online communities is often a matter of choice, while in the physical world
membership may be imposed by, for example, geographic location (Bagozzi and Dholakia; 2002).
For that reason the entry and exit barriers are often lower for virtual communities, which makes
motivating participation more important (Valtersson; 1996).
As mentioned earlier communities vary in purpose. Hagel and Armstrong have among others
classified online communities. According to these authors, there are four types of communities
(Armstrong and Hagel; 2000): 1) Communities of transaction facilitate the buying and selling of
products or services, often supported with information and customer reviews. Examples are
Amazon.com and ebay.com. 2) Communities of interest serve as a platform for participants to
interact about specific topics or content of interest. Examples are tweakers.net and flickr.com. 3)
Communities of relationship is a platform for building relationships, based on experiences,
interests, skills, etc. Examples are facebook.com or myspace.com. 4) Communities of fantasy
allow members to create a personality, and take on this persona, which can be different from who
they are or look like in real life. Communication often takes place between these characters in a
virtual fantasy world. Examples are secondlife.com or theworldofwarcraft.com.
Besides classifications based on the purpose that the online community serves, it can also be either
company initiated or not company initiated (Plant; 2004). It can even be classified based on
functionalities. L.Casaló et al. (2007) have defined ‘Brand community’ as: ‘a set of individuals
who voluntarily relate to each other for their interest in some brand or product’. Therefore, these
brand communities are, from a marketing perspective, an interesting kind.
In seeing whether there are differences in motives between product types, the focus of the research
will be on communities concerning a specific product group. Although opinions are spread in all
kinds of forms and ditto communities, communities of interest and communities of transaction are
the most common places for consumer articulations (Hennig-Thurau et al.; 2004). For this reason,
this study uses communities of interest and transaction as units of observation. Another reason is
the popularity of these websites. Bol.com, for example, is a Dutch community of transaction with
reviews and ratings on multimedia products and has had 80 million unique visitors last year (NRC
Handelsblad; 2009). The more popular a community is, the more likely people are familiar with
the website which will be beneficial for the research.
2.3. passive vs. active participation
As stated before, one of the characteristics of online communities is that the content is delivered
mainly by members of that community. In order to make online communities viable, attracting
people to become member and motivating these members to actively participate, are two crucial
factors.
In this research this division between active participation (posting) and passive participation
(lurking) was made (Jang et al.; 2008). is maintained for the two reasons. One, motives for
obtaining product related information can be different compared to motives for making this
information available. Two, when the antecedents are different, the level of loyalty intention is
likely to be different as well. For example; if customers are less motivated to post information
about a clothing brand, but rather read the information, the community could pick up a more
active, contributing role. Consequently, if passive participation appears to lead to loyalty
intentions, companies could consider making the information freely available instead of making
subscription obligatory.
With the evolution of the internet technology, the terms posting and viewing become rather
narrow. It often depends on the type of community, what kinds of applications are adopted.
Designing your own products in communities of transaction1 and living a second life in
communities of fantasy2 can hardly been described as posting nor viewing. Nevertheless,
contributions still come in the form of posting and viewing opinions, questions, information and
knowledge within the community (Koh and Kim; 2003). From a Marketing perspective, this
research will focus on consumers that will either articulate themselves or view articulations
concerning certain products or brands. These kind of consumer articulations are referred to as
1
2
http:// http://nikeid.nike.com; last visited June 2009
http://secondlife.com; last visited June 2009
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electronic word-of-mouth (eWOM); “any positive or negative statement made by potential,
actual, or former customers about a product or company, which is made available to a multitude
of people and institutions via the internet” (Hennig-Thurau et al.; 2004).
Many researchers have tried to discover what web-site attributes, web-site content, types of
remuneration, or other factors may influence member participation. These studies resulted in
multiple challenges for having a sustainable, attractive and effective community (Koh et al.;
2007). People not only have to be motivated to participate, but have to have the opportunity as
well. For instance, creating awareness around the social presence of other members has appeared
to be important in effective communication (Fulk et al.; 1990). Moreover, members have to be
motivated by being treated in a common need (Andrews; 2002). There has to be some leadership
to a certain extent in creating the right social climate. Equally important is the technological
infrastructure and architecture, to give the motivated members the opportunity to participate
(Godwin; 2004). Other stimulants suggested are: clear definition of members’ roles, online/offline
events, opinion leaders, basic guidelines and useful content (William and Cothrel; 2000), (Kim;
2000).
PRODUCT TYPE
PASSIVE
PARTICIPATION
LOYALTY
MOTIVES TO
PARTICIPATE
INTENTIONS
ACTIVE
PARTICIPATION
2.4. participation as an antecedent of loyalty
loyalty can be defined as “a deeply held commitment to repurchase or repatronize a preferred
product or service consistently in the future” (Oliver; 1997). loyalty is seen as one of the key
objectives of marketing managers, since it increases the level of future buying behavior which is
key in achieving success and sustainability over time (Flaviàn et al.; 2006). In order to achieve
commitment towards a certain brand (brand loyalty) or product, a relationship has to be built
between the customer and the brand or product. Communities can facilitate this relationship by
bringing customers with a mutual interest in the product together to interact (Hagel III and
Armstrong; 1997).
loyalty can be seen from two different perspectives. One perspective is behavioral loyalty, which
measures the likeliness that a customer will purchase a product once again. Attitudinal loyalty, on
the other hand, is more long term oriented and represents the commitment or preferences a
customer associates with a brand (Jacoby and Keyner; 1973). Several authors argue that attitudinal
loyalty is a better indicator of brand loyalty than actual behavioral loyalty (Füllerton; 2003)
(Shang et al.; 2006). Füllerton (2003) argues it is affective commitment that leads to purchase
behavior. Reasoning is that behavioral loyalty, possibly caused by high switching costs or
dependency, is not the kind of loyalty one would like to measure, nor achieve to increase.
Therefore, the aspects used by Füllerton (2003) to measure affective commitment will serve as a
basis in measuring attitudinal loyalty in this present paper. These aspects are the following:
forsaking the alternative, the sacrifice a consumer will give the pledge of continuity and the
resistance to change.
Several scientific articles have examined this relationship between participation within virtual
communities on customer loyalty. Although nor loyalty nor participation is always measured in
the same way, there is some overlap in the aspects that these different forms of loyalty attempt to
measure.
Shang et al. (2006) examined the effects of consumers’ lurking and posting behaviors in online
communities on brand loyalty. In line with Füllerton (2003), these authors consider attitudinal
loyalty as a better indicator of brand loyalty compared to behavioral loyalty. In this research the
authors only found support for the relationship between lurking and brand loyalty. They argue that
these results imply that the contribution by active participants have a promotional effect, on
visitors of these communities. T.W. Gruen et al. equally have made a distinction between two
forms of loyalty which is quite similar to the division mentioned by Shang et al.(2006), Jacoby
and Keyner (1973) and Füllerton (2003). On one side they describe loyalty in the form of
intention to repurchase the product; this is comparable to the behavior loyalty. On the other side
they describe the form of Word-of-Mouth, which resembles attitudinal loyalty. These authors
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found evidence for the influence of “know-how exchange” on loyalty in the form of providing
Word-of-Mouth. However, instead of measuring the frequency or the type of participation, the
quality of the content was measured. The quality was quantified by importance, usability and
trustworthiness of the information posted, valued by the respondent.
Another research that measured a more subjective aspect of participation was by L.Casaló et al.
(2007). They explored the effects of member participation on trust and loyalty towards free
software products available on the same community website. Here, participation was based on the
value of the contribution and the intrinsic motivation and enthusiasm. In contrast to findings
mentioned earlier, this study has shown that starting a virtual brand community and encouraging
member participation can lead to loyalty from a behavioral point of view. loyalty was based on
variables like repeated usage of the product but also the amount of usage.
Jang et al. (2008) found evidence for attitudinal loyalty towards the community (community
commitment) to have an influence on brand loyalty. loyalty was here measured by both brand
attachment aspects (attitudinal loyalty) and the level of repurchases (behavioral loyalty). In
addition to this, Kim et al. (2004) found a positive influence of behavioral guest loyalty on the
number of products purchased. “Guest loyalty” is another way of looking at the level or type of
participation within an online community (Kim et al.; 2004). Guest loyalty is comparable to
member participation, both attempt to measure the quantity or quality of the relationship between
user and community. For example, guest loyalty can be measured by the number of repeated visits
to the website. These findings imply that there could be a relationship between the nature of the
participation and the developed loyalty. Due to the hypothetical nature of the questions within this
present research however, it is not possible to measure the repeated visits to the site, nor the
attitude towards a specific community.
Shang et al. (2006) only found support for lurking to have an influence on loyalty; other authors
however did not make the distinction between these forms of participation (Jang et al. 2008),
(T.W. Gruen), (L.Casaló et al. 2007), (Kim et al. 2004). The quantification of participation
appeared to vary across researches as well. Kim et al. (2004) measured participation as both the
number of visits as the repetition of visits. Others however, looked at the quality aspect of
participation (Gruen et al.; 2007) (Casaló et al.; 2007). Even though the variables used may vary,
and found relationships are therefore not completely consistent, all findings support the
assumption there is a relationship between participation and (brand) loyalty. Therefore we expect
that:
H1a:
“active participation” to have a significant positive influence on loyalty intentions.
H1b:
“passive participation” to have a significant positive influence on loyalty intentions.
PRODUCT TYPE
PASSIVE
PARTICIPATION
LOYALTY
MOTIVES TO
PARTICIPATE
INTENTIONS
ACTIVE
PARTICIPATION
2.5. motives for participation
In 2003, Hennig-Thurau and Walsch researched motives for community members to read
consumer articulations. Later, in 2004, partly the same authors researched motives for community
members to actually post articulations on web sites (Hennig-Thurau et al.; 2004). Possible
motivations , formerly used in traditional Word-of-Mouth literature, were gathered and these
were tested as eWOM in an online community environment. Both studies examined the
dimensionality of the entire set of items. The underlying structure that was derived through a
principal component analysis will not be maintained to serve as a basis for the hypotheses.
However, these factors are used to give some structure (appendix 1) in explaining the theoretical
background of the different motives. It is very well possible that this present study will result in
different underlying components, however, the components found by Hennig-Thurau et al.(2003)
(2004) give a good indication of what one may expect.
Both motives for passive as for active participation were measured by Hennig-Thurau et al. (2003)
(2004), although not in one study, the significant difference was acknowledged. In addition, Koh
and Kim (2003) also found that viewing and posting require different stimuli in promoting
participation. They recommend treating both activities as separate member choices in further
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research. Comparing motives between posting and viewing is difficult in that it are two different
activities. Whether one activity has a bigger influence on loyalty, however, will be looked into in
this present research.
In order to answer research question 1, a hypothesis will be formulated for each motive, based on
former literature. Consequently, these hypotheses will be tested based on their influence on either
passive or active participation.
Some variables measure, to a large extent, the same underlying motivation for both active and
passive participation. However, some variables are only applicable for just one form of activity. In
order to learn “what products are new” or “dissonance reduction” active participation is not
required. Therefore these variables were derived within the context of passive participation. For
other motives action is needed and therefore eleven motives are formulated within the context of
active participation.
PRODUCT TYPE
PASSIVE
PARTICIPATION
LOYALTY
MOTIVES TO
PARTICIPATE
INTENTIONS
ACTIVE
PARTICIPATION
2.5.1.
2.5.1.1.
passive participation
Obtaining buying- related information
The reason for members to read articulations about a product, in order to make the right buying
decision, can be divided in two motives. On the one hand consumers want to reduce the risk of
buying the wrong product. On the other hand, the internet can be used as a medium in comparing
different products in a timely manner. This relates to consumer’s self-perceived lack of time.
These two motives are referred to as self-involvement motives (Schiffman and Kanuk; 1987).
Hennig-Thurau et al. have found these motives to be the most important in reading customer
articulations (Hennig-Thurau et al.; 2004). Therefore we expect that:
H2a:
“Risk reduction” as a motive to read customer articulations to have a significant positive
influence on passive participation.
H2b:
“Reduction of search time” as a motive to read customer articulations to have a
significant positive influence on passive participation.
2.5.1.2.
Social orientation through information
“Determination of social position” and “dissonance reduction” concern the benefits derived
through comparing evaluations, opinion and experiences with other members. A product can be
evaluated on multiple aspects, such as prestige and quality. Consumers can determine their social
position by comparing their evaluation with those of others (schiffman and kanuk). Cognitive
dissonance can be reduced by having the confirmation one made the right buying decision in case
of doubt due to contradicting messages. Opinions by others within virtual communities are
regarded as neutral and unbiased (Hennig-Thurau and Walsch; 2003). Moreover, content from
forums is thought of as more relevant, credible and is able to create more empathy amongst
readers than content from corporate websites (Schindler and Bickart; 2003). The reason for this is
that one does not benefit, unlike a company, from enhanced messages. Therefore opinions by
others are a appropriate source to recover from cognitive incongruence (Hennig-Thurau and
Walsch; 2003). Another possibility is by the comfort of knowing that others experience the same
problem as you are (Sweeney & hausknecht). Therefore we expect that:
H3a:
“Determination of social position” as a motive to read customer articulations
significant positive influence on passive participation.
H3b:
to have a
“Resonance reduction” as a motive to read customer articulations to have a
significant positive influence on passive participation.
2.5.1.3.
Community membership
Reading content on a community website may be due to a certain feeling of “belonging to the
community”. A possible antecedent is one may feel part of the community through participating in
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the experiences from other members. The feeling of belonging to a community can be achieved
when one reads and therefore experiences the consumer articulations. Therefore we expect that:
H4:
“Belonging to the community” as a motive to read customer articulations to have a
positive significant influence on passive participation.
Another motive which is not necessarily related to buying a product is “to learn what products are
new”. Opinion leaders, who are experimental and open to new experiences, are likely to seek
information about new products (Sun et al.; 2006). Curiosity and Novelty are two factors that
explain the need to learn what is new in the marketplace (Henning-Thurau et al.; 2004). In order
to learn ‘What new products or topics are in’ active participation is not required. Therefore this
variable will be considered in the context of passive participation and we expect that:
H5:
“To learn what products are new” as a motive to read customer articulations to have a
positive significant influence on passive participation.
2.5.1.4.
Top learn to consume a product
“To learn how a product is to be consumed” measures whether members participate in order to
get help in using the purchased product. actively posting a question about using a product is not
always needed. With the growing number of posts, the improving search engines and the time it
saves on waiting before the question is answered, finding written solutions is a more
accommodating alternative. In their article, Henning-Thurau et al. (2004) found that seeking
information on how to use a product had a stronger relation with visiting communities, than
posting on communities. Therefore we expect that:
H6:
“To learn how a product is to be consumed” as a motive to read customer
articulations to have a positive significant influence on passive participation.
2.5.2.
2.5.2.1.
active participation
Platform assistance
When consumers have questions or complaints addressed at the company, the community can be
used as a medium to contact the company, in seeking redress. This can be done through the
operating staff, formulated as “Problem solving through the platform operator”. The consumer
who wants to contact the company in order to file a complaint, may experience a lower barrier in
posting the complaint on the internet due to convenience or low costs. Another reason could be
the collective power of multiple members filing the same complaint, in the search for redress .
Since this research will not use the context of company-initiated communities, it is not likely
respondents declare they would post for this reason. Operators from not-company-initiated
communities do not have the responsibility to act as a mediator. Even if the community is
company-initiated, it will be managed by the company, and therefore negative eWOM may be
deleted (Jang et al.; 2008). However, since no empirical evidence was found for this reasoning,
we expect that:
H7a:
“Problem solving through the platform operator” as a motive to post articulations to have a
positive significant influence on active participation.
H7b:
“Convenience of articulation” as a motive to post articulations to have a positive
significant influence on active participation.
H7c:
“Collective power” as a motive to post articulations to have a positive significant influence
on active participation.
2.5.2.2.
Concern for other consumers
“Help others in their buying decisions” and “Save others form negative experiences” describes
the motive of helping others in making the right buying decision. Giving advice on a product, is
expected to have different motives than seeking advice. The first motive is more driven by
positive experiences, while the second motive is predominantly driven by negative experiences. In
prior research positive WOM appeared to be driven by altruistic motives and self enhancement
(Sundram et al.; 1998). Consumers distribute negative WOM however out of frustration reduction
or vengeance (Duan, Gu and Whinston; 2008). Nevertheless, one motive does not exclude the
other, and a motive may well be a combination of factors. Here, only altruistic intentions are
measured or pro-social behavior. Therefore we expect that:
H8a:
“Help others in their buying decisions” as a motive to post articulations to have a
positive significant influence on active participation.
H8b:
“Save others form negative experiences” as a motive to post articulations to have a positive
significant influence on active participation.
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2.5.2.3.
Extraversion, Positive self-enhancement & Venting negative feelings
Another type of articulating eWOM is ‘Extraversion’ or ‘Venting negative feelings’ without the
purpose of helping others. Extraversion stands for “Being predominantly concerned with and
obtaining gratification from what is outside the self” (Merriam Webster Dictionary). Venting
negative or positive feelings, makes dissonance reduction possible and therefore readers may
unintended benefit from the articulations. Nevertheless, this motive attempts to only address the
intention driven by self-interest. On one hand the participant benefits from extraversion, showing
other members their buying success and experience. In addition, Hennig-Thurau et al. (2004) have
found evidence for extraversion to have an influence on posting behavior. On the other hand, the
participant benefits from venting negative feelings about their buy or experiences. Part of venting
negative feelings is creating catharsis as a form of revenge (Hennig-Thurau et al.; 2004).
Therefore we expect that:
H9a:
“extraversion” as a motive to post articulations to have a positive significant influence on
active participation.
H9b:
“venting negative feelings” as a motive to post articulations to have a positive significant
influence on active participation.
The last motive is based on the theory of self-enhancement. Showing other members that one
understands the product. This behavior can only be gratified trough social interaction and is driven
by one’s desire for positive recognition from others (Hennig-Thurau et al.; 2004). For two
reasons, we expect the motive “self-enhancement” to have a positive influence on active
participation. First of all, the motive “social benefits” was found to be the most important
antecedent in posting. “Self-enhancement” is based on positive recognition from others (engel et
al.; 1993) (Sundram et al.; 1998) from others and is therefore related to the theory of affiliation.
Secondly, self-enhancement” in combination with “extraversion” was found to have a positive
influence on posting behavior (Hennig-Thurau et al.; 2004). Therefore we expect that:
H10:
“Self-enhancement” as a motive to post articulations to have a significant influence on
active participation.
2.5.2.4.
Social benefits
Within the context of active participation, the motivation “social benefits” is partly in line with the
motive “belonging to a virtual community”. The common need amongst these motives is the need
for affiliation; which is measured with this motivation (Hennig-Thurau et al.; 2004). Members
may want to post content in order to notify others of their presence. This way one is able to
receive social benefits from other members. Hennig-Thurau et al. (2004) have found this motive
to be the most important in posting customer articulations. Therefore we expect that:
H11:
“Social benefits” as a motive to post articulations to have a significant influence on active
participation.
2.5.2.5.
Advice seeking
“Advice seeking” measures whether members participate in order to give help in using an already
purchased product. actively posting a question concerning the product enables the members to get
more specific information on their problem (Hennig-Thurau et al.; 2004). Hennig-Thurau et al.
have found evidence for “advice seeking” to have an influence on posting behavior. Therefore we
expect that:
H12:
“Advice seeking” as a motive to post articulations to have a significant influence on active
participation.
2.5.2.6.
Helping the company
Another motive is the desire to “help the company”, by posting positive eWOM online (HennigThurau et al.; 2004). This motive is based on the same background as the first motive and is also a
form of altruism, although this time towards the company. An underlying intention is supported
by the “Equity Theory”. It argues that when customers feel their benefits to be higher than their
costs, they may feel the need to equalize this input/output ratio (Oliver and Swan; 1989). One way
of repaying the company, is spreading positive word of mouth. The results for this motive within
the research of Henning-Thurau et al. (2004) showed no significant influence. However, both ‘The
desire to help the company’ as well as ‘Positive expressions’ are a result from a positive product
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experience. Therefore we do expect for this motive to have a positive influence on active
participation.:
H13:
“Helping the company” as a motive to post articulations to have a significant influence on
active participation.
2.6. Product category as a moderator
Shang et al. (2006) mention that information searching is proposed as the main purpose for
consumers to participate in virtual communities. A consumer’s need to find information about a
certain product is driven by that consumer’s involvement in a certain product. In their research,
the hypothesis was tested whether affective or cognitive involvement has different influences on
participation. Cognitive involvement in a product is often the case when consumers are driven by
utilitarian motives. With some products consumers are more interested in comparing the benefits
with the costs, and the functional performance of a product than for example the emotional
aspects. Affective involvement on the other hand, can be reached if interests are driven by selfenhancement or by expressing one’s self-image. Cognitive involvement often corresponds with
cognitive products, also referred to as utilitarian products or informative products. Affective
involvement, in contrast, often corresponds with affective products, also referred to as symbolic
products, holistic products or hedonic products. The two product types are depicted in the “FCBgrid”, a conceptual model to reflect how consumers have a different approach to buying each of
the four product types (affective-, cognitive-, high-involvement- and low involvement products).
Buying informative products or cognitive products often requires more information than affective
products since its buyer is more concerned with its functionality and its cost. The situation can
therefore be described as learn-feel-do. Whereas the buying process for affective products follows
the sequence feel-learn-do. These products are related to one’s self-esteem and specific
information is less important (Vaughn; 1986). It goes without saying that these product categories
are not exclusive. Many products contain intangible attributes, however some products contain
these products to a greater extent, and therefore are called symbolic products (Solomon; 1983).
Examples of cognitive products are electronics and houses, while fashion apparel or music are
more affective products.
Shang et al. found that cognitive involvement had an influence on lurking, while affective
involvement did not. Although the purpose of this present research is not to measure the
difference between lurking and posting, it attempts to find support for the type of product having
effect on motives for participation. In previous research suggestions have been made to measure
whether the type of products (cognitive vs. affective) would influence the motives for
participation (Shang et al.; 2006) (Hennig-Thurau et al.; 2004).
In order to research possible differences between the two types of products, the motives for
participation discussed earlier, act as a basis. This approach serves two purposes. One, it gives us
the opportunity to see whether there is a difference between the role of virtual communities in the
buying process when it comes to different product types. Two, it enables us to sketch what the
drivers are in buying a cognitive versus an affective product.
2.6.1.
Social oriented motives
People have a certain idea of who they are, which is called the self-concept. This concept is based
on the perceptions of others, which can be communicated through social contact (Solomon; 1983).
The products we use play a important role in these perceptions because symbolic attributes of
products we use tells others who we are, what we do or what we believe in. It also works the other
way around. The social meaning inherited in symbolic attributes, determine how we behave, and
influences the social role we pursue. Likeminded people will interpret the symbolism behind a
product in the same way, and therefore will confirm one’s self-concept (Solomon; 1983). Because
of the relation between symbolic attributes and one’s social position, we expect affective products
to play more predominant role in the social behavior within online communities.
Within the context of passive participation two motives were discussed earlier in this research, in
which the emphasis is more on the social aspect in comparison to the product aspect. These are
‘Determination of social position’ and ‘Belonging to a virtual community’. The former concerns
comparing one’s opinion with those of others, the latter concerns the pleasure of being a part of a
group and its experiences. Our taste in music can represent a part of who we are, music related
opinions or experiences are therefore a mean to determine one’s social position. Equally it enables
us to enjoy belonging to a community with like-minded people. On the contrast, it is harder to
identify oneself with a more functional product like a digital camera. Within the context of active
participation the social oriented motives that were discussed earlier in this research were ‘Social
benefits’ and ‘Positive self-enhancement’. The former is comparable to ‘Belonging to a virtual
community’, with the main difference being the interactive character. The latter concerns a
behavior which can only be gratified trough social interaction and is driven by one’s desire for
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positive recognition from others (Hennig-Thurau et al.; 2004). Due to the social awareness this
motivation requires from both receptor as the messenger we expect that affective products are
more suitable in seeking positive recognition than informative products. Therefore we expect that:
H14a:
“Determination of social position” as a motive to read articulations is more important for
affective products than for informative products.
H14b:
“Belonging to a virtual community” as a motive to read articulations is more important for
affective products than for informative products.
H14c:
“Social benefits” as a motive to post articulations is more important for affective products
than for informative products.
H14d:
“Positive self-enhancement” as a motive to post articulations is more important for
affective products than for informative products.
2.6.2.
Functional oriented motives
Consumers are more concerned with the practical and functional performance when buying or
evaluating informative products. Whether or not an informative product has met its (functional)
expectation is rather objective, whilst the performance of a more affective product has more
subjective nature (Vaughn; 1986). Advice on buying a certain television based on its image
quality is often considered more valuable in making a buying decision than an opinion on what is
the best music CD available. Therefore we expect that all motives concerning using the product
after purchase or advice giving or seeking have a stronger influence within the context of
informative products.
H15a:
“Advice seeking” as a motive to post articulations is more important for informative
products than for affective products.
H15b:
“Help others in their buying decisions” as a motive to post articulations is more important
for informative products than for affective products.
Post purchase advice seeking, concerns seeking help in using the product. Learning how to watch
a movie or how to listen to music (affective products) is for the same reasons different from
seeking help in using a kitchen tool (informative/functional product). Using an affective product is
often less complex and its performance depends on one personal opinion or taste. Therefore we
expect that:
H15c:
“To learn how a product is to be consumed” as a motive to read articulations is more
important for informative products than for affective products.
2.6.3.
Word of Mouth due to positive or negative experiences
Affective or symbolic products, as compared with utilitarian products, are purchased and
evaluated largely based on emotional aspects, according to the feel-learn-do sequence (Vaugn;
1983). Pre-purchase advice giving is based on experience, and therefore resembles engaging in
word of mouth. Word of mouth can be either positive or negative and is a result of consumer
involvement in the product. Consequently, consumers will engage more easily in WoM when the
experience involves more affective elements, good or bad (Westbrook; 1987). Therefore we
expect that symbolic products are better capable of evoking emotions, positive or negative, and
therefore lead to eWoM in more cases. Moreover, Carrol and Ahuvia (2006) found that affective
products tend to evoke stronger emotional responses, and therefore consumers can develop a more
passionate and emotional attachment for a brand. Moreover, these authors found that selfexpressive brands have a greater effect on positive word-of-mouth than utilitarian products. For
these reasons, we expect that positive electronic word-of-mouth will have a stronger influence on
active participation in relation to affective products than for cognitive products.
H16a:
“Extraversion” as a motive to post articulations is more important for affective products
than for informative products.
H16b:
“Helping the company” as a motive to post articulations is more important for affective
products than for informative products.
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PRODUCT TYPE
PASSIVE
PARTICIPATION
LOYALTY
MOTIVES TO
INTENTIONS
ACTIVE
PARTICIPATE
PARTICIPATION
2.6.4.
Research model overview & hypotheses
The model below gives us an idea of the framework that will provide us information to draw the
conclusions. In addition, the hypotheses that were formulated earlier, are depicted in Table 1 and
Table 2.
PRODUCT TYPE
Informative
Affective
Table 2
PASSIVE
MOTIVES TO
PARTICIPATE
Table
1
H1a
PARTICIPATION
LOYALTY
INTENTION
ACTIVE
PARTICIPATION
H1b
S
Hypothesis
H2A
H2B
2b
H3A
2b
H3B
H
3a
H2b
4
3a
H
2b
H5
H
3
3a
H
H2b
6
H7A
3
3a
H
2b
H
3
H7B
3a
2b
H
H7C
3
3a
H
2b
H
3
H8A
3a
2b
H
H
3
H
3a
2b
H8B
H9A
3
H
3a
2b
H
H
3
H
3a
2b
H9B
H2b
3
3a
H
10
H
3
H
3a
2b
H11
H12
3
3a
H
2b
H
3
H13
3a
2b
H
H
2a
H
3
3a
H
Table 1 2b
H
3
3a
H2b
H
H2b
3
H
3a
H
H3a3
H3a
H3
Hypothesis
H3
H
H14A H2a3
motive
Risk reduction
Reduction of search time
Determination of social position
Resonance reduction
Belonging to the community
To learn what products are new
To learn how a product is to be consumed
Problem solving through the platform operator
Convenience of articulation
Collective power
Help others in their buying decisions
Save others form negative experiences
extraversion
venting negative feelings
Self-enhancement
Social benefits
Advice seeking
Helping the company
Reading
Posting
motive
Activity
Determination of social position
Belonging to a virtual community
Posting
Reading
Social benefits
Posting
Positive self-enhancement
Posting
H15A
To learn how a product is to be consumed
Reading
H15B H3
Advice seeking
Posting
H15C
Help others in their buying decisions
Posting
H16A
Helping the company
Posting
H16B
Extraversion
Posting
H14B
H14C
H14D
H2b
H3a
Moderating
effect
Affective
Informative
Affective
Table 2
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Chapter 3.
Methodology
3.1. Approach
In the first two chapters an overview is given of previous literature, which serves as a
foundation on which this present thesis will build its contribution. This foundation contains
the following aspects. Firstly the relevance of this research, as an extension on former
research, is explained. Secondly, a background is given on the phenomenon online
communities and their commercial value, viewed from a marketing perspective. Finally, the
components used in our research model are supported which lead to the formulation of the
hypotheses. For the operationalization of the research model (paragraph 2.6.4), data had to be
gathered and variables had to be defined. This was done according to the following procedure.
The items for the components from the research model had to be created in order to measure
the different variables. Then, a principal component analysis was used to reveal possible
underlying components. The underlying components were then tested on reliability, using the
Cronbach’s alpha statistic, and served as new variables. After the new variables were created
and formulated, the direct relationships between motives and participation were tested using a
linear regression model. This relationship enables us to test the moderating effect of the
product type.
3.2. Questionnaire construct
Because passive and active participation are two different activities, different items were used
to measure the motives. The items measuring ‘motives to participate’ and ‘loyalty intentions’
were already constructed in earlier research and therefore derived from three articles. The
items that were used for passive participation were derived from Hennig-Thurau et al. (2003)
and are listed in Table 20. These authors tested all the items on expert validity, criterion
validity and convergent validity. The items used for active participation were derived from a
follow up article to the first article (Hennig-Thurau et al.; 2004). Again, the items measuring
the motives for active participation were critically assessed by both experts and users and are
listed in Table 21. loyalty was measured by four items, based on items suggested by Quester
and Lim (2003) and F.Reichheld (2003). Four of the seven items measuring loyalty were
maintained due to length restrictions. An ordinal scale for visiting frequency (Lurking) and
posting frequency (Posting) were constructed. The measurement scales that were used for the
variables active and passive participation and the items that were used for loyalty are depicted
in Tabel 19.
3.2.1.
Survey one: motives
The empirical data was gathered with the use of an online survey. The website
www.studentenenquete.nl provides free use of the web based software Limesurvey version
1.81+. The original items were translated in Dutch, and subjected to several users of online
communities for their judgment, until agreement was reached on the translation.
With the use of the described software, potential participants were invited by means of an email message. Participants were found amongst family, friends and acquaintances. In order to
motivate people to complete the survey, two completed surveys were rewarded with a
voucher of € 25,- each. The address list contained 1125 e-mail addresses, resulting in 147
completed surveys after the first invitation and an additional 168 completed surveys after
sending a reminder. The survey was divided in two identical parts, each part containing
questions concerning passive and active participation. In the first part, however, the questions
concerned electronic goods (informative products) and the second part concerned music,
books and films (affective products). Although a distinction is made between posting (active
participation) and viewing (passive participation), members can still be “active” in viewing
posts. Therefore the likelihood of passive and active participation for that person was
measured. If the participant indicated that the probability of (active or passive) participating in
the community was very unlikely (“1” on a 7-point scale), the motive questions (for active or
passive participation) were then skipped.
3.2.2.
Survey two: loyalty
The second part of the data was gathered to examine the influence of active and passive
participation on loyalty intentions. In the first part of the survey the target group consisted of
anyone who is familiar with communities of interests or communities of transaction. In this
part, however, loyalty intentions can only be measured on the basis of actual behavior and
attitude. Therefore the survey was spread through ‘tweakers.net’, the largest online consumer
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electronics community in the Netherlands. A link to the survey was posted on the community
forum, were 130 participants completed the survey. The community members were first asked
to indicate their lurking and posting frequency. Lurking was formulated as number of visits
per month, and posting was described as the number of visits during which the member added
or (or changed) content to the website. Then the member was asked if they occasionally reads
or posts about a particular brand. If the answer was yes, the question was asked to state about
which brand he or she posts or reads more than other brands. To have the least possible bias in
the dataset, the cases without a certain brand name (68 cases) were deleted. Reasoning is that
without a certain brand in mind, one’s brand loyalty is impossible to measure. Finally, loyalty
was measured (Tabel 19), using the four items constructed by Quester and Lim (2003) and
F.Reichheld (2003).
In both surveys, some demographic control variables were also measured. Table 3 provides
the basic demographic distribution on both surveys.
Variable
Categories
Gender
Female
Male
Total
Primary school
High school
Intermediate Vocational Training
Higher Vocational Education
University
Other
Total
Younger that 20 years
20 - 25 years
25 - 30 years
30 - 35 years
35 - 40 years
40 years or older
Total
1 hour per day
Between 1 and 3 hours per day
Between 3 and 5 hours per day
More than 5 hours per day
I don't know
Total
1 hour per day
Between 1 and 3 hours per day
Education
Age
Hours per day
online
Hours per day
online
Percent
1st Survey
(395)
Percent
2nd Survey
(62)
48,1%
51,9%
100,0%
0,3%
4,1%
14,2%
50,1%
31,1%
0,3%
100,0%
6,1%
47,8%
27,8%
9,1%
4,1%
5,1%
100,0%
20.3%
43.3%
24.6%
11.4%
0.5%
100.0%
8%
92%
100%
0%
11%
18%
35%
34%
2%
100%
15%
42%
16%
15%
10%
3%
100%
0%
23%
Between 3 and 5 hours per day
Between 5 and 7 hours per day
Between 7 and 9 hours per day
More than 9 hours per day
Total
34%
19%
6%
18%
100%
Table 3 Demographic profile on the sample
3.3. Variables
After the data was gathered through the surveys, a principal component analysis was
conducted, using the Varimax rotation method. This analysis was performed to examine the
independence of the items that were identified for passive and active participation. Before this
analysis was performed, few measures have been taken to optimize the dataset. Firstly, all
cases that had the same values for all items, and of which the credibility was questioned, were
not selected. Secondly, all broken cases were deleted. Finally, when a participant indicated it
was “very unlikely” that one would participate (actively or passively), the survey skipped the
motivational questions (for active or passive participation). Reasoning was that participants
who indicate it is very unlikely for them to participate in the future, probably cannot relate to
any motive at all. To have the least “random” answers as possible, these cases were therefore
left out of the analysis..
To ensure the internal consistency, a reliability test was performed. This test measured the
reliability of the items within each component, with the use of the Cronbach’s alpha statistic
(α).
For passive participation, five out of seven motives showed strong correlation among the
items measured. The two items for the motive ‘Resonance reduction’ loaded high on both
‘Comparing evaluations’ and ‘Problem in common’, as Table 4 shows us. The motive ‘To
learn how a product is to be consumed’ was measured by two items, one of those appeared to
load equally high on two factors and was therefore deleted. The reliability statistic (α) scored
for four out of six motives below .7, which is a common used benchmark. However, since
these four motives only exist out of 2 items, a score above .53 is satisfying.
When looking at the underlying components (Table 4), the principal component analysis
showed us, the following theoretical reasoning was defined. The first revealed component is
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a combination of ‘Determination of social position’ with the first item for ‘Dissonance
reduction’ (for a full overview of the items see Table 20). This last item describes the comfort
one gets through reading positive evaluations about their bought product. Although
‘Determination of social position’ initially was defined as a social oriented motive, the motive
also concern comparing one’s evaluations with those of others. Therefore this new component
is called ‘Comparing evaluations’. Factor 6 is a combination of ‘Dissonance reduction’ and
‘Learn how to consume a product’. Both items address a certain problem in using the product,
and therefore this new variable is renamed into ‘Problem in common’. The items of the
remaining four variables are allocated to the remaining factors according to their initial
structure.
New Variable
Component
Item
Determination social position 2
Comparing evaluations
Determination social position 1
Resonance reduction 1
Risk Reduction
Reduction of search
time
1
,847
,734
,651
2
3
Problem in common
6
,839
,803
Risk reduction 1
Risk reduction 2
Reduction of search time 2
,376
Reduction of search time 1
,828
,700
,613
,854
,731
,422
,300
Belonging to a virtual community 2
Learn how to consume a product 1
α
,777
Belonging to a virtual community 1
Resonance reduction 2
5
,765
Learn what products are Learn about new products 1
new
Learn about new products 2
Belonging to a virtual
community
4
,442
,586
,832
,687
,532
,779
,683
,630
Table 4 Principal component analysis within the passive participation construct
For active participation five out of six factors reveal a combination of items from different
motives, as is depicted in Table 5. Therefore these items were aggregated into one separate
motive. Items that did not load highly on one distinctive factor were deleted, including the
complete motive ‘Save others from negative experiences’. The reliability statistic was
satisfying for all motives, since all motives showed a Cronbach’s alpha of above .7.
When looking at the underlying components the principal component analysis showed us, we
can define the following new variables. The first new variable combines ‘Desire to help the
company’ with ‘Extraversion’. This combination can be explained due to the fact that both
motives are a form of positive word-of-mouth, and can be linked to altruism. This new
variable is called positive expressions. The second new variable exists of ‘Social benefits’ and
‘Positive self-enhancement’. Since self-enhancement can only be gratified trough social
interaction and is driven by one’s desire for positive recognition from others (Hennig-Thurau
et al.; 2004), it is arguable that this item could correlate with the ‘Social benefits’. HennigThurau et al. (2004) found that the motives ‘Problem solving through platform operator’,
‘Collective power’ and ‘Convenience of articulation’ to be one factor, and called it ‘Power
through articulation’. This name is maintained for the third new variable. The fourth new
variable is a combination of the motives ‘Advice seeking’ and ‘Help others in their buying
decisions’, and is renamed into ‘Product advicing’. Although ‘Advice seeking’ is based on
self-benefit and ‘Help others in their buying decisions’ on altruism, both motives concern
giving or seeking advice about a certain product. The fifth last new variable consists of the
items measuring the motive ‘Venting negative feelings’, and therefore is not renamed.
To measure the relationship between participation and loyalty we used the data from the
second survey. No principal component analysis was performed for the variable ‘loyalty’,
since there was no interest in finding or testing an underlying structure. Again the reliability
was tested and showed a Cronbach’s alpha of .817, which is above .7 and therefore satisfying.
The eventual variable was created by taking the average value over all four items.
New Variable
1
,795
,597
,726
,784
2
Component
3
Desire to help the company 1
Desire to help the company 2
Positive expressions
Extraversion 1
Extraversion 3
Positive self-enhancement
,707
Social benefits 1
,679
Social benefits
Social benefits 2
,696
Social benefits 3
,708
Problem solving through operator 1
Problem solving through operator 2
Power through
articulation
Convenience of articulation 1
Collective power
Advice seeking 1
Advice seeking 2
Product advising
Help other with buying decision 1
Help other with buying decision 2
Venting negative feelings 1
Venting negative
Venting negative feelings 2
feelings
Venting negative feelings 3
Table 5 Principal component analysis within the active participation construct
4
5
,864
,829
,801
,782
,677
,562
,836
,711
,812
,598
,650
,848
,769
,811
,866
,868
3.4. Regression analysis
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After defining the variables to work with, different models are used to test the hypotheses
from chapter two. These models will be analyzed and discussed in chapter four. This chapter
is divided in three parts. Firstly, all hypotheses regarding passive participation, except for the
influence on loyalty, were tested. Secondly, these tests were repeated for all hypotheses
regarding active participation. These tests regarding both forms of participation were
performed in two steps. The first step was to look at the direct effect between motivation and
participation. Here a linear regression model was used, where all variables and control
variables were taken into account. The second step was to test for a moderating effect, caused
by the type of product. To find support for this effect, we used three types of analyses. 1)
Interaction terms were created by multiplying the motive variables with a dummy variable.
This Dummy variable contained the values one and zero. The value ‘one’ equaled Electronics
or ‘Informative Products’, ‘zero’ equaled ‘Books/Films/Music’ or ‘Affective Products’. The
moderating effect was then tested by adding the created interaction terms in a regression
model, together with the motive variables. 2) The data for informative products was separated
from the data for affective products. Then the a regression analysis was performed for each
‘Product type’. This way, both situations could be analyzed separately and independent. 3) A
one-way ANOVA analysis was performed for the relationship between motives and product
type. This analysis shows whether the mean values for each motivation significantly differs
among product types. Finally, the hypotheses regarding loyalty were tested. Again a linear
regression model was used, with loyalty as the explained variable and passive and active
participation as explaining variables.
Chapter 4.
Results
4.1. passive participation:
4.1.1.
Direct effect of Motivation on participation
In order to test whether there is a direct relationship between motives and participation, two
regression models were constructed. Both models test the relationship between motives as
independent variables and passive participation as dependent variable. However, for the
second model some control variables were added to the model. These control variables are
gender, education, age and the number of hours per day one spends on the internet. After first
creating a model with only motive variables, a second model was created where the control
variables were added to the model (Table 6). These control variables were added to see
whether it had any substantial effect on the initial results. Although the level of education and
the ‘Hours online per day” both have an influence on passive participation, they did not have
a large influence on one of the coefficients from the original model. Therefore, only the
second model is depicted in Table 6.
Model 1 indicates that a relationship exists for three out of six motives. The coefficients for
‘Risk reduction’, ‘Reduction of search time’ and ‘Belonging to a virtual community’ all three
significantly differ from zero. The variables ‘Risk reduction’ and ‘Reduction of search time’
both have a positive influence on viewing, while ‘Belonging to a virtual community’ has a
negative effect on viewing. Therefore, we found support for hypothesis H1a and H1b. This
indicates that the first two motives are better reasons for community visitors to participate.
Because both variables have an equally large standardized Beta, they both seem to have an
equally strong influence on passive participation. Since the motivation ‘Belonging to a virtual
community’ has a negative effect on passive participation, we did not find support for
hypothesis H3a. The three remaining variables do not show any significant relationship and
therefore there is no support for the hypotheses H3a, H3b, H5 and H6.
Unstandardized
Coefficients
Standardized
Coefficients
Sig.
Comparing evaluations
B
0,048
Beta
0,030
0,465
Risk Reduction
0,252
0,155
0,000*
Reduction of search time
0,268
0,165
0,000*
Model 1
From Motivation through Participation to loyalty;
The Differential Effect Of product type in Online Communities
P a g e | 35
Learn what products are new
0,033
0,021
0,612
Belonging to a virtual community
-0,208
-0,128
0,002*
Problem in common
-0,058
-0,036
0,379
Gender
-0,046
-0,014
0,736
Education
0,198
0,100
0,015**
Age
0,003
0,015
0,720
Hours online per day
0,051
0,092
0,026**
a. Dependent Variable: passive participation
Table 6 Effect of motives and control variables (*P < 0.01,**P < 0.05, ***P < 0.1)
4.1.2.
Direct & interaction effect of product type
After testing the direct effect between ‘motives’ and ‘passive participation’, the moderating
effect of ‘product type’ was tested. Again, the six motive variables were used as a basis. In
Model 2 the variable ‘product type’ was added to test the direct effect of informative products
on ‘passive participation’ In Table 9 we observe that this dummy variable, which was added
to model 1, shows support for a significant negative effect of ‘Informative products’
(Electronics) on the direct relationship. This indicates that the influence within an informative
product context differs significantly (at level p < 0.1) from the influence within an affective
product context. Implications are that in case of affective products, people tend to view
content on communities more often. The additional dummy variable did not have a large
influence on the remaining variables.
Model 2
Comparing evaluations
Risk Reduction
Reduction of search time
Learn what products are new
Belonging to a virtual community
Problem in common
Electronics
Unstandardized
Coefficients
Standardized Coefficients
B
0,052
0,307
0,272
0,007
-0,219
-0,036
-0,252
Beta
0,032
0,189
0,168
0,004
-0,135
-0,023
-0,077
Sig.
0,429
0,000*
0,000*
0,916
0,001*
0,586
0,079***
Table 7 Effect of motives and product type (*P < 0.01,**P < 0.05, ***P < 0.1)
To see whether there is a moderating effect, interaction variables were created and added to
the model. The interaction term measures the influence of the combined effect between
‘Motivation’ and ‘Informative Products’ on ‘passive participation’. Each interaction variable
was added separately to the six motives to have as little bias on the individual effect. The six
models that were created are depicted in Tabel 8. The models show whether the coefficients
significantly differed from zero. As we can see, although we added the interaction variables,
the coefficients for the motives remain more or less the same. Moreover, none of the Beta’s
from the interaction variables differ significantly from zero. Therefore, there is no support for
hypotheses H14b and H15a.
Models
Comparing evaluations
Risk Reduction
Reduction of search time
Learn what products are new
Belonging to a virtual community
Problem in common
Electronics*CE
Electronics*RR
Electronics*RST
Electronics*LNP
Electronics*BVC
Electronics*PIC
Sign
3
4
5
6
7
8
+
+
+
+
+
+
-
,470
,080
,000
,675
,002
,384
,172
,650
,000
,000
,816
,002
,335
,566
,000
,001
,785
,002
,301
,530
,000
,000
,931
,002
,334
,571
,000
,000
,789
,120
,318
,650
,000
,000
,816
,002
,335
,932
,477
,916
,521
,932
Tabel 8 (*P < 0.01,**P < 0.05, ***P < 0.1)
The next step is to test the same motive variables, but this time within the context of each
product category. Within each context, the direct relationship between the different motives
and passive participation was measured. Within the context of informative products, Table 9
shows that there is support for a significant direct relationship between the motives ‘Risk
reduction’, ‘Reduction of search time’, ‘Belonging to a virtual community’ and ‘passive
participation’. Again, ‘Risk reduction’ and ‘Reduction of search time’ both have a positive
influence on viewing, while ‘Belonging to a virtual community’ has a negative effect on
viewing. In contrast with the aggregated model (Table 6), “Risk reduction” is the strongest
relation with a standardized Beta of .219, which would indicate this motivation is even more
important within communities concerning informative products.
Unstandardized
Coefficients
Standardized
Coefficients
Sig.
Comparing evaluations
B
,050
Beta
,031
,565
Risk Reduction
,388
,219
,000*
Reduction of search time
,241
,137
,012**
Learn what products are new
,028
,016
,770
Belonging to a virtual community
-,252
-,152
,005*
Model 9
From Motivation through Participation to loyalty;
The Differential Effect Of product type in Online Communities
P a g e | 37
Problem in common
-,017
-,010
,856
a. Dependent Variable: passive participation
b. Selecting only cases for which product type = Electronics
Table 9 (*P < 0.01,**P < 0.05, ***P < 0.1)
Within the context of affective products, the model (Table 10) again shows there is support
for a direct relationship between motives ‘Risk reduction’, ‘Reduction of search time’,
‘Belonging to a virtual community’ and ‘passive participation’. In contrast to model 11
however, ‘Reduction of search time’ is the strongest relation with a standardized Beta of .217.
Moreover, ‘Belonging to a virtual community’ still has a negative influence on ‘passive
participation’, but is not as significant (P < 0.1).
Unstandardized
Coefficients
Standardized
Coefficients
Sig.
Comparing evaluations
B
,057
Beta
,034
,586
Risk Reduction
,206
,131
,040**
Reduction of search time
,321
,217
,001*
Learn what products are new
,014
,009
,882
Belonging to a virtual community
-,177
-,111
,079***
Problem in common
-,067
-,043
,498
Model 10
a. Dependent Variable: passive participation
b. Selecting only cases for which product type = books/films/music
Table 10 (*P < 0.01,**P < 0.05, ***P < 0.1)
Comparing the results for informative products with those for affective products, we find
indications of some differences. Firstly, ‘Reduction of search time’ seems be more important ,
and ‘Risk reduction’ less important, within the context of affective products. Secondly,
‘Belonging to a virtual community’ is less negative. This indicates people are less reluctant
towards this motive when it comes to affective products in comparison to informative
product.
4.1.3.
ANOVA analysis
Independent of the direct effect between motives and passive participation, a One-way
ANOVA analysis is used to see whether the mean values of the different motives significantly
differ between informative and affective products (see Table 11). Looking at the variables,
there seems to be a clear difference in means between informative and affective products.
Except for the motives ‘Learn what products are new’ and ‘Comparing evaluations’ the means
from the four other variables are significantly different between product types. Although these
results do allow for any conclusions about the ‘Level of participation’, the motives were
measured with the context of ‘passive participation’. To see which mean is higher, for
affective or informative products, the values are depicted in Table 11. For four out of six
variables the mean is higher for informative products. For the motives ‘Learn about new
products’ and ‘Belonging to a virtual community’ the means are higher for affective products.
Therefore these motives appear to be a more important factor in visiting virtual communities
for affective products than for informative products. For ‘Belonging to a virtual community’
this is in line with a lower standardized beta for this variable within the context of affective
products, compared to informative products (Table 9 & Table 10).
Means
books/films/music
One-way ANOVA
Comparing evaluations
-0.102
Risk Reduction
-0.320
Reduction of search time
-0.126
Learn what products are new
0.078
Belonging to a virtual community
0.121
Problem in common
-0.247
Means Electronics
Significance
0.075
,35
0.236
,000*
0.093
,009*
-0.058
,105
-0.089
,013**
0.182
,000*
<
<
<
>
>
<
Table 11 (*P < 0.01,**P < 0.05, ***P < 0.1)
4.2. active participation
4.2.1.
Direct effect of Motivation on participation
In order to test the direct relationship between motives and active participation, the same
models were used as for passive participation. Again the control variables ‘Gender’,
‘Education’, ‘Age’ and
the number of hours per day one spends on the internet were
measured as well. After first creating a model with only motive variables, a second model was
created where the control variables were added to the model. The control variables however,
From Motivation through Participation to loyalty;
The Differential Effect Of product type in Online Communities
P a g e | 39
did not have a noteworthy influence on one of the coefficients from the original model.
Therefore only the second model is depicted in Table 12. Moreover, the control variables do
not have a significant influence on active participation of their own.
When we look at the direct effect of the motives for active participation , we see that all
variables have positive coefficients. However, only the coefficients for ‘Positive expressions’,
‘Social benefits’, ‘Power through articulation’ and ‘Venting negative feelings’ all four
significantly differ from zero. Therefore we can state that these four motives have an
influence on posting on online communities, and therefore hypotheses H7, H8, H9a, H10,
H11, H12 and H13 are supported. The coefficient of the variable ‘Venting negative feelings’
does not significantly differs from zero, and therefore H9b is not supported.
Model 11
Unstandardized
Coefficients
Standardized
Coefficients
B
Beta
Sig.
Positive expressions
0,322
0,238
0,000*
Social benefits
0,236
0,175
0,001*
Power through articulation
0,162
0,120
0,018**
Product advising
0,174
0,129
0,012**
Venting negative feelings
0,102
0,076
0,135
Gender
-0,237
-0,088
0,102
Education
-0,127
-0,077
0,140
Age
0,011
0,054
0,300
Hours online per day
-0,016
-0,032
0,543
a. Dependent Variable: active participation
Table 12 Effect of motives and control variables (*P < 0.01,**P < 0.05, ***P < 0.1)
4.2.2.
Direct & interaction effect of product type
After testing the direct effect between ‘motives’ and ‘active participation’, the moderating
effect of ‘product type’ was tested. Again, the motive variable were used as a basis. In model
12 the variable ‘product type’ was added to the model, to test the direct effect on ‘active
participation’ In Table 13 we see that the dummy variable, which was added to the model,
does not show support for a significant negative effect of ‘Informative products’ (Electronics)
on the direct relationship. This indicates that the influence within an informative product
context does not differ significantly from the influence within an affective product context.
Moreover, the additional dummy variable did not have a large influence on the remaining
variables.
Model 12
Unstandardized
Coefficients
Standardized
Coefficients
B
Beta
Sig.
0,000*
Positive expressions
0,310
0,230
Social benefits
0,232
0,172
0,001*
Power through articulation
0,175
0,130
0,011**
Product advising
0,140
0,104
0,044**
Venting negative feelings
0,098
0,073
0,152
Electronics
0,111
0,041
0,434
a. Dependent Variable: active participation
Table 13 (*P < 0.01,**P < 0.05, ***P < 0.1)
To measure any moderating effect caused by the variable ‘product type’, each interaction
variable was separately added to the model. Noteworthy is the transition of the effect of
‘Positive Expressions’ on ‘active participation’. This variable showed a significant effect (P <
0.01) in model 12, while in Model 13 the effect is largely explained by the interaction term.
This implicates that ‘Positive expressions’ is a more important motivation within the context
of informative products compared to the context of affective products. Therefore hypotheses
H16a and H16b are not supported. All other interaction variables do not have a significant
effect on active participation. Therefore there is no support for H14a, H14c, H14d and H16.
Models
Positive expressions
Social benefits
Power through articulation
Product advising
Venting negative feelings
Electronics * PE
Electronics * SB
Electronics * PTA
Electronics * VNF
Electronics * PA
Sign
13
14
15
16
17
+
+
+
+
+
+
+
+
+
,136
,001
,015
,032
,177
,027**
,000
,004
,011
,029
,171
,000
,001
,203
,028
,122
,000
,001
,013
,030
,445
,000
,001
,012
,323
,128
,332
,533
,882
,566
Table 14 (*P < 0.01,**P < 0.05, ***P < 0.1)
The next step is to test the same motive variables, but this time within the context of each
product category. Within each context, the direct relationship between the different motives
and passive participation was measured.
From Motivation through Participation to loyalty;
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Within the context of informative products model 18 shows there is support for a direct and
significant relationship between the dependent variable ‘active participation’ and the
independent variables ‘Positive expressions’ (P < 0.01) , ‘Social benefits’ (P < 0.05), ‘Power
through articulations’(P < 0.05) and ‘Product advising’ (P < 0.1). ‘Positive expressions’ has
the strongest relationship with a standardized beta of .314. The weakest relationship is from
‘Product Advising’ with a standardized beta of .131.
Unstandardized
Coefficients
Standardized
Coefficients
Positive expressions
B
,447
Beta
,314
Sig.
,000*
Social benefits
,179
,131
,047**
Power through articulation
,213
,149
,024**
Product advising
,175
,126
,054***
Venting negative feelings
,097
,075
,253
Model 18
a. Dependent Variable: active participation
b. Selecting only cases for which product type = Electronics
Table 15 (*P < 0.01,**P < 0.05, ***P < 0.1)
When comparing the results from model 19 (Table 16) with model 18 (Table 15) we notice a
substantial difference among the coefficients. Within the context of affective products the
model shows there is only support for a direct relationship between ‘Social benefits’ and
‘active participation’. These results show that ‘Social benefits’ has a stronger influence within
the context of affective products compared to the situation depicted in Table 15. Although
model 19 does not depict the moderating effects, the result for Social benefits’ is in support of
H14c. Moreover the results show that ‘Positive expressions’, ‘Power through articulations’
and ‘Product advising’ only show a significant influence on active participation when it
comes to informative products. Regarding ‘Product advising’, these results are in support of
H15b and H15c.
Model 19
Unstandardized
Coefficients
B
Standardized
Coefficients
Beta
Sig.
Positive expressions
,141
,112
Social benefits
,329
,245
,165
,003*
Power through articulation
,138
,110
,174
Product advising
,091
,068
,397
Venting negative feelings
,048
,032
,694
a. Dependent Variable: active participation
b. Selecting only cases for which product type = books/films/music
Table 16 (*P < 0.01,**P < 0.05, ***P < 0.1)
Comparing the results for informative products with those for affective products, we find
indications for some differences. Firstly, ‘Positive expressions’ seems be more important, in
contrast to what was expected, within the context of informative products. Secondly, ‘Social
benefits’ are clearly more important when it comes to affective products, in comparison to
informative products. This is in support of what was expected (H14c).
ANOVA – Analysis
4.2.3.
Independent of the direct effect between motives and active participation, an ANOVAanalysis is used to see whether the mean values of the different motives significantly differ
between informative and affective products. Looking at the variables, there seems to be a
difference in means between informative and affective products. The differences between
product types are significant for ‘Social benefits’ ( P < 0.1), ‘Product advice’( P < 0.01) and
‘Venting negative feelings’( P < 0.01). To see which mean is higher, for affective or
informative products, the values for each variable are depicted in Table 17. “Social benefits”
is the only variable, where the mean is significantly higher for affective products. This is in
line with the results found using model 19. The mean value for ‘Product advice’ was
significantly higher for informative products, which is in line with the results found though
model 18. In using previous models, no sign was found for the difference in mean value for
‘Venting negative feelings’ though.
Variable
Means
books/films/music
Positive expressions
0.067005
Social benefits
0.111844
Power through articulation
0.084343
Product advising
-0.19173
Venting negative feelings
-0.10706
>
>
>
<
<
Means Electronics
Significance
-0.04894
,124
-0.08169
,071***
-0.0616
,143
0.140034
,006*
0.078198
,006*
From Motivation through Participation to loyalty;
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Table 17 (*P < 0.01,**P < 0.05, ***P < 0.1)
4.3. loyalty
The variable loyalty was measured with the use of four items. The average of these items was
used as a measurement for loyalty. To see whether the relationship between the form of
participation and loyalty was significant, a regression analysis was used. Table 18 shows a
significant relationship between the number of visits per month to the website, passive
participation, and the level of loyalty. Therefore hypothesis H1a is supported. The coefficient
for active participation however, did not significantly differ from zero. Therefore active
participation, the number of times the member added content, does not show any relation to
loyalty. Consequently there is no support for H1b.
Unstandardized
Coefficients
Standardized
Coefficients
B
Beta
Sig.
How many times did you visit tweakers.net during the last
month?
0,520
0,287
0,030**
How many times did you contributed to tweakers.net, by adding
adjusting content or during the last month?
0,120
0,142
0,274
Gender
0,328
0,121
0,362
Education
0,015
0,023
0,865
Age
-0,011
-0,114
0,399
Hours online per day
0,027
0,101
0,437
Model 20
a.
Dependent Variable: loyalty
Table 18 (*P < 0.01,**P < 0.05, ***P < 0.1)
Chapter 5.
Conclusion
5.1. Discussion
This research explored the impact of different motives on participation, and attempted to find
evidence for a moderating effect caused by the type of product. Moreover, in favor of the
usefulness for marketers, the relation between participation and attitudinal loyalty was
explored. Results show a direct effect for some of the motives on participation. Moreover,
when it comes to motives to participate, there are signs these differ between product types.
However, little proof has been found for a moderating effect caused by product type.
Furthermore, passive participation was proven to have a significant influence on loyalty,
while this was not the case with active participation. The purpose of this chapter is to discuss
our findings and elaborate on possible implications, based on these findings. The chapter
concludes with some limitations and suggestions for further research.
5.1.1.
passive participation
In the previous chapter, the results showed that ‘Risk reduction’ and ‘Reduction of search
time’ are motives for people to view content on communities about a certain product (Table
6). Both motives imply that the main reasons for viewing content are product related. People
want to save time and risk in preparation of buying a product. These motives were in line
with our expectations. However, the motives ‘Comparing evaluations’, ‘Belonging to a virtual
community’, ‘Learn what products are new’, and ‘Problem in common’ were not found to be
reasons to view content. The first two are both socially oriented motives, which may imply
that people are less interested in social benefits. However, social benefits may be more
difficult to achieve without interaction. This would explain why the motive ‘Social benefits’
does have an influence on active participation. For the same reason, the motivation ‘Problem
in common’ could be less accommodating if one cannot (actively) ask specific questions
about their problem.
From Motivation through Participation to loyalty;
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The motivation ‘Learn what products are new’ is a motivation that was constructed with
people like opinion leaders in mind (Sun et al.; 2006). This group could very well be
underrepresented, and therefore show little influence.
The moderating effect of the product type on the relationship between motives and viewing
was not found. This implies that however there is evidence that the motives for viewing
content about informative products differ from affective products, this could not be explained
by the level of passive participation. Reason for this inability, could be found in the construct
of the survey that was used. This will be explained when the limitations of the research are
discussed.
Looking at the motives, independently from the level of passive participation, there is
evidence that some reasons apply more to informative products than to affective products.
First of all, we find ‘Belonging to a virtual community’ to have a more positive (or less
negative) influence on viewing. This confirms that affective products are more
accommodating in assessing what kind of members are joining the community and whether
the people in the community are ‘like-minded’. Second, ‘Risk reduction’ and ‘Reduction of
search time’ appear to be more valued reasons within the context of informative Products.
Reasoning could be that informative products are easier to evaluate on the basis of consumers
articulations.
5.1.2.
active participation
In case of active participation, four out of five motives seem to evoke Posting. This is
according to what was expected in advance. However, ‘Venting negative feelings’ appeared
no reason for people to post their opinions on the internet. Possible explanation is the aspect
of catharsis as a form of revenge. People who have these kinds of emotions could merely act
out of impulsive reaction, instead of rational. The survey construction was not based on
previous experience, but on expected behavior. This could be the reason it was harder for
people to predict such impulsive behavior.
In contrast to the motives for passive participation, a moderating effect of the product type on
one of the five relationships between motives and viewing was found. However, this
moderating effect shows the exact opposite of the expected findings. ‘Positive expressions’
about affective products was expected to have a stronger influence on active participation.
The affective attachment to affective products, due to the symbolic attributes these products
often entail, was the reason for this discrepancy. The opposite result was found in Table 14. In
contrast to the moderating effect, and in favor of previous reasoning, the mean score for this
motivation was higher for affective products.
In addition to the moderating effect of ‘Positive Expressions’ there were other reasons to
believe there is a noteworthy difference between the product types. As just mentioned, in
comparing the likelihood of the different motives to occur, there was a difference between
product types. Three motives were expected to differ amongst product types. The first
motivation was ‘Positive expressions’. There was no support in favor of this expectation, as is
previously discussed. The second motive was ‘Social benefits’, which was expected to be of
greater importance within communities about affective products instead. The third motive was
‘Product advising’ which was expected to be of importance within communities about
informative products. For both of these motives, results were found in favor of the
expectations (Table 17).
5.1.3.
loyalty
Although no evidence was found for the relationship between active participation and loyalty,
evidence for passive participation to have an influence on loyalty was found. These findings
are in line with the results Shang et al. (2006) found. They reasoned that posting is more
driven by social factors, and not by personal considerations. Our findings do support this
reasoning, since ‘Risk reduction’ and ‘Reduction of search time’ were found to have the
strongest influence on viewing, while posting was strongly linked to socially oriented motives
like ‘Social benefits’ and ‘Positive expressions’. Moreover viewing comments posted by
others can have a promotional effect, and therefore evoke loyalty (Shang et al.; 2006).
5.2. Implications of this research
Possible target groups for this research are mainly researchers in the areas of community
participation, web site evaluation, web site development, commercial value of online
communities, or functionalities of online communities. Other target groups are the companies
From Motivation through Participation to loyalty;
The Differential Effect Of product type in Online Communities
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that want to catch the wave of the online communities but do not know what their customers
seek in a online community, or what kind of community fits their business.
Most companies whom have invested in web 2.0. technologies say that they are pleased with
their results (McKinsey Quarterly; 2007), however companies feel unconfident in applying
web 2.0 applications in the right way to their business (Dösinger et al. 2007). This research
aims to provide directions for companies already owning or planning to initiate an online
community. By reading this present research, lessons can be drawn from differences in
motives between products and types of participation. Whether communities concern a certain
brand or concern a certain theme or topic, in both cases the goal is to strive for the highest
participation. Therefore, knowing what drives people to view or to post content is crucial. To
give an idea of how the results could ad value, some practical implications are given. For
example, one of the implications could be that product reviews and ratings are accessible for
anyone, since they are the main reasons for lurkers to visit. active participants however, are
merely driven by social factors, and therefore emphasis could be on the social interaction.
Making members aware of the presence of other members, could stimulate the number of
postings.
Implications also concern company initiated brand communities, since the relevance and
importance of passive participation within online communities is explained. Although this
research did not show for active participation to directly have an influence on loyalty, active
participation is at least equally important. In order to have participants visiting the
community, others have to provide the content that is viewed. Therefore active participation
has to be encouraged just as much, or even more. Especially when it concerns product
experiences, reviews and ratings. These consumer articulations are more credible in
comparison to content created by the company behind the product or brand (Schindler and
Bickart; 2003). However, if passive participation has a direct influence on loyalty, this should
be encouraged as well. A possible implication could be to make it as easy as possible to enjoy
the community without signing up or paying contribution.
5.3. Limitations of this research
The main limitation of this research is the construction of the first field research. Initially
several online communities were approached to ask for incorporating actual members into this
research. This way the research could be based on actual experience instead of predictions
made by the participants from the sample. Unfortunately, no community was willing to
cooperate, and therefore the survey was taken by acquaintances, family and friends. The
questions were expressed in a hypothetical way, so even with little knowledge of communities
in general everybody could take part. The problem of this construct lies in the fact that
participation was difficult to measure. This has implications for the direct relationship, which
was used as the basis for the moderating effect.
Another difficulty was the construction of the second survey. This survey was taken by actual
members. However, the amount of participants to the survey was not large enough to measure
much variance. The largest part of the participant that volunteered, checked the highest level
of passive participation. Considering the short time frame in which the survey was taken, the
likelihood of overrepresentation of participants that visit the community quit frequently is
therefore high. Suggestion for future research would be to gather data from actual members.
This enables measuring the actual post and viewing behavior. Moreover it is advisable take
the survey over an extended period of time.
The direct relationship between motives and participation is suggested to be revised as well.
The motives that were used, which were drawn from previous research, are based on
traditional Word-of-mouth theories. Instead of deriving the motives from these theories, they
could be gathered through qualitative research instead. This way the motives are more
compatible with today’s communities.
From Motivation through Participation to loyalty;
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Appendix 1.
Items used
Items used
passive participation
Categories
Couple times per week
About once a week
About a couple of times but not every week
Maybe once this month
I did not visit the website this month
How often did you visit the community last month?
active participation
How often did you post, contribute or adjust properties on the website last
month?
Almost every time I visited the website
About half the time I visited the website
Maybe once this month
I did not contribute at all this month
loyalty
Do you read or comment about branded products ? If yes, about which
brand do you mostly read or comment?
Yes, namely
I don't know
No
It is important for me to buy <brand> over another brand
Although another brand is on sale, I still buy <brand>
I always think of <brand> over other brands when I consider buying this type of
product
I would recommend <brand> to people I know
Strongly disagree – Strongly agree
Tabel 19 Construct for the variables participation and loyalty
Viewing
HennigHennig-Thurau et al. (2003)
Previous literature
Items used
Risk reduction
 because contributions by other customers help me to make the right buying decisions
 to benefit from others’ experiences before I buy a good or use a service
Reduction of search
time
 because here I get information on the quality of products faster than elsewhere
 because one saves a great deal of time during shopping when informing oneself on such
sites before shopping
Determination of
social position
 because I can see if I am the only one who thinks of a product in a certain way
 because I like to compare my own evaluation with that of others
Dissonance
reduction
 because through reading one can get the confirmation that one made the right buying
decision
 because I feel much better when I read that I am not the only one who has a certain
problem
Belonging to a
virtual community
 because I really like being part of such a community
 because I enjoy in participating in the experiences of other community members
To learn what
products are new
 because I am interested in what is new
 because I get to know which topics are ”in”
Factor found
Obtaining
buying related
information
Social
orientation
through
information
Community
membership
To learn how a
product is to be
consumed
 because I find the right answers when I have difficulties with a product
 to find advice and solutions for my problems
To learn to
consume a
product
Table 20: Structure of motives and items used for passive participation
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Viewing
HennigHennig-Thurau et al. (2003)
Previous literature
Items used
Problem solving
through platform
operator
 because I believe the platform operator knows the person in charge within the company
and will convey my message.
 because the platform operator will stand up for me when speaking to the company.
Convenience of
articulation
 because it is more convenient than writing to or calling the company.
 because it is not that costly.
Collective Power
 because I believe companies are more accommodating when I publicize the matter.
 because one has more power together with others than writing a single letter of
complaint.
Help others in their
buying decisions
(positive WoM)
Save others form
negative
experiences(negative
WoM)
 because I want to warn others of bad products
 because I want to save others from having the same negative experiences as me
 because I want to help others with my own positive experiences
 because I want to give others the opportunity to buy the right product
Factor found
Platform
assistance
Concern for
other
consumers
Social benefits
 because I believe a chat among like-minded people is a nice thing.
 because it is fun to communicate this way with other people in the community.
 because I meet nice people this way
Social benefits
Advice seeking
 because I expect to receive tips or support from other users.
 because I hope to receive advice from others that helps me solve my problems.
Advice seeking
Helping the company
 because I am so satisfied with a product that I want to help the company to be successful.
 because in my own opinion, good companies should be supported..
Helping the
company
Extraversion
 because this way I can express my joy about a good buy.
 because I feel good when I can tell others about my buying successes
 because I can tell others about a great experience.
Positive selfenhancement
 because my contributions show others that I am a clever customer
Venting of negative
feelings




because the company harmed me, and now I will harm the company!
because I want to take vengeance upon the company.
because my contributions help me to shake off frustration about bad buys.
because I like to get anger off my chest
Table 21 Structure of motives and items used for active participation
Extraversion
/Positive selfenhancement
Venting of
negative
feelings
Appendix 2.
Questionnaire
Only hard copy
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Appendix 3.
Survey invitations
Survey 1: e-mail invitation and reminder
Hoi!
Voor mijn studie aan de Erasmus Universiteit Rotterdam houd ik een onderzoek in het kader van mijn
scriptie.
Je zou mij een groot plezier doen door deel te nemen aan dit onderzoek. Onder de deelnemers wordt
bovendien 2 x een Irischeque t.w.v. € 25 uitgereikt!
Let wel op! Je maakt alleen kans op een Irischeque wanneer je de vragenlijst volledig hebt ingevuld! Het
invullen van de vragenlijst kan tot en met morgen, winnaars worden bekend gemaakt vóór 15 juni.
Het invullen van de vragenlijst duurt ongeveer 10 minuten.
Om aan het onderzoek deel te nemen kun je op onderstaande link klikken.
Groetjes,
{ADMINNAME}
({ADMINEMAIL})
Klik hier om aan het onderzoek deel te nemen:
{SURVEYURL}
Hoi {FIRSTNAME},
Onlangs heb ik (en {ATTRIBUTE_1}) je uitgenodigd om deel te nemen aan mijn online enquête.
Nu zag ik dat je hier nog niet aan toegekomen was. Je zou me echt een groot plezier doen door me alsnog te
helpen. Bovendien maak je dan nog steeds kans op één van de twee Irischeques t.w.v. € 25 !
Let wel op! Je maakt alleen kans op een Irischeque wanneer je de vragenlijst volledig hebt ingevuld! Het
invullen van de vragenlijst kan t/m 7 juni, winnaars worden bekend gemaakt vóór 15 juni.
Het invullen van de vragenlijst duurt ongeveer 10 minuten.
Om aan het onderzoek deel te nemen kun je op onderstaande link klikken.
Groetjes,
{ADMINNAME}
({ADMINEMAIL})
Klik hier om aan het onderzoek deel te nemen:
{SURVEYURL}
Survey 2: Survey 2: Thread posted on tweakers.net
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Appendix 4.
Research results Thorsten Hennig-Thurau et al
Comment
writing
Visit frequency
problem solving through platform operator
Convenience of articulation
Ventilating negative feelings
Concern for other consumers
Extraversion/positive self-enhancement
To express positive feelings
Self-enhancement
Economic incentives
Helping the company
advice seeking
Platform assistance
-.18**
-.4
Ventilating negative feelings
Concern for other consumers
Extraversion/positive self-enhancement
-.10**
.13**
.15**
.01
.16**
.12**
Social benefits
.37**
.34**
Economic incentives
Helping the company
advice seeking
.10**
-.01
.10**
.18**
-.03
.06*
Table 1 Standardized regression coefficient (Thorsten Hennig-Thurau et al 2003)
Effect on viewing behaviour
Risk reduction
2.027
Reduction of search of time
2.155
determination of social position
Dissonance reduction
belonging to a virtual community
To learn what products are new in the
marketplace
Remuneration
To learn how a product is consumed
2.529
2.912
2.854
Obtaining buying related information
Social orientation through information
Community membership
2.954
3.253
2.579
Remuneration
To learn to consume a product
Table 2 Importance of motives: scale ranges from 1 =”fully agree” to 5 = “fully disagree” (Thorsten Hennig-Thurau et
al 2004)
Appendix 5.
FCB Grid
Figure 1 FCB Grid (Vaughn, 1980, 1986)
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