Power and Perceived Power Use by Moderators in Online Communities

Power and Perceived Power Use by Moderators in Online Communities

Gnafaki Katerina

1834952

Abstract

Online community sites, in which users interact with each other to share

knowledge, represent an interesting context to study the motivations of collective

action as well as individual ones in the form of knowledge contribution to online

community sites. We extend a model of social capital and individual motivations

based on Wasko and Faraj (2005) to incorporate and contrast the direct impact of

commitment to community, reciprocity, enjoyment in helping others and

reputation, on users’ intentions to share knowledge. In addition, taking the

approach/inhibition theory into account, we examine the moderating influence of

perceived coercive power use of moderators on users’ willingness to contribute in

online community sites. We empirically test our framework using objective data

derived from 207 respondents, all of whom are members of an online community

site. In addition to the interesting moderating effect, we find that a user’s

commitment to the community and reputation are the strongest drivers of his

intentions to share knowledge.

Keywords: Online communities, knowledge sharing, online moderation, power

1. Introduction

With the rapid growth of the Internet, online communities emerge as a new place

for individuals to interact with each other (Yang and Lai, 2008). Intuitively,

everyone seems to understand the concept of ‘online community’ but so far there

is no agreed upon definition. Sociologists define a virtual community as a group of

individuals who communicate and build social relationships with each other via

Internet-based technology, (Rheingold, 1993) while knowledge management

theory explains that an online community provides a new way for individuals to

exchange the knowledge they possess (Yang and Lai, 2008). A common definition

that is used to describe an online community is “a group of people, who come

together for a purpose online, and who are governed by norms and policies”

(Preece, 2000) and this is the one we adopt in our study.

Online communities are dynamic, evolving and constantly change (De Souza and

Preece, 2004). Understanding why people use online communities can provide

valuable information about their success. Recent theorizing on online

communities (Preece, 2004; Bagozzi and Dholakia, 2002; Ridings et al., 2002)

suggests that an important characteristic that all online communities share is text-

based communication, and that information sharing constitutes an essential

element in fostering online community use and thereby success. For example,

Yang and Lai (2008) argue that if everyone in the virtual community plays the role

of free-rider, i.e., acquiring the information without sharing, the community would

collapse.

While information sharing has been found to be a motivation for using online

communities (Wasko and Faraj, 2000), ensuring information quality or inducing

quality content, however, remains a challenge (Chen et al., 2007). Valck et al.

(2009) discuss that communities can facilitate computer-mediated interactions

between members by providing a code of conduct that specifies community

standards with regard to behavior, language or content, and that is regulated by

online community managers. For example, Slashdot has constructed a moderation

system that has been recognized for its quality of content unlike many other social

networks. On Slashdot, each comment posted by a user, receives a score ranging

from -1 to 5, indicating the quality of the comment. Once a comment is posted, it

may be checked or “moderated” by selected users who can change its score

according to the quality of information provided (Chen et al., 2007).

The scholarly literature emphasizes the importance of moderating content in

online communities. Davis (2005) argues that community moderation appears

essential for the discussions to run smoothly. In order to achieve this, moderators

are given the power and authority to remove any content that does not

correspond with the community’s policy (Johnson et al., 2004; Preece, 2001).

Several ways of power use to moderate online content have been discussed in the

past (Edwards, 2002; Wright, 2006). For instance, moderators use their power to

filter, facilitate and help online discussions by removing those that disrespect

community’s rules, as well as mediate when individuals come into conflict.

However, as observed in the literature, moderators have not always used the

power that is given to them to regulate information sharing in the right way, as

online community moderation if done incorrectly can be worse than having no

moderation at all. This is confirmed by Wright (2009) who claims that “the fear

remains, however, that the power to moderate the content of online forums may

be abused.” Wright (2009) also explains that this could be done when moderators

use their power to set overly restrictive rules or ignore ‘fair’ rules and delete

messages.

Despite the fact that online communities have existed for almost 30 years, little

research has been done on how moderators can influence user’s willingness to

share information. Interestingly, we find that there is a gap in existing literature as

theories about online communities (Ridings et al., 2002) focus on just one part of

community members, users, without taking into consideration moderators. We

also observe that past research mostly discusses that moderation is positive

(Preece and Maloney-Krichmar, 2003; De Schutter et al., 2004; Berge, 1996).

Strangely enough, negative ways of power use to achieve moderation have not

been examined thoroughly. To comprehend the concept of power that is given to

moderators, it is wise to examine the existing literature on power and authority.

According to Ba (2001) and Bahruth (2000) power is often defined as the capacity

for one social unit (e.g., the leader) to determine the behavior of another (e.g.,

followers) and the ability to control its actions. If we translate this to online

communities, power can be defined as the capacity of moderators to determine

the behavior of the users. In online community moderation, power can be used in

positive as well as negative ways. For example, Michelson (2006) considers power

as a positive force that is continually used to achieve group as well as individual

goals and that when power is used in an ethical and purposeful way there is

nothing evil about it. On the other hand, Ba (2001) points out the negative ways of

power use by stating that there are ways in which leaders, even those who are

otherwise well-intentioned, may abuse a specific type of power. Applying this

perspective to our study, we focus on the negative ways of power use by

moderators in online communities.

1.2 Contributions of the Research

Understanding various ways of power use can provide valuable information about

moderators’ role in an online community. Following the study of Chen et al, (2007)

who discuss the effective role of moderators to regulate users who otherwise

would take advantage of the anonymity in online communities, we introduce an

adverse selection problem; opportunistic moderators. Recent publications have

suggested that it may be conceptually relevant to investigate community members

by splitting them to users and moderators (Bakker et al., 2000). Therefore, it

seems necessary to refine our understanding and consider online communities

which consist of both parties; the users on one hand and the moderators on the

other, equally important for the success of the community.We hence investigate

the implications of opportunistic moderation and we address the question of how

perceived power of the moderators impacts on users’ willingness to share

information. The problem is that although declarations about the importance of

moderation are made widely in the literature, often little or no detail is given

about what happens in case online moderation is done incorrectly, either by

accident or on purpose. Research efforts to date have specifically advanced our

understanding of the effective moderation of electronic discussions, i.e., the

positive ways of power use in achieving moderation and the ways that moderation

facilitates online discussions. However, what happens in the opposite way, i.e., the

negative ways of power use and how they influence information sharing remains

obscure. Consequently, many knowledge gaps still exist and this is where our

study aims to shed light on.

Additionally, the contributions for practice can be noteworthy. The results of this

study can be very useful for online communities to sustain their websites, blogs,

wikis etc. as it attempts to address the role of moderation and how it can be more

effective by overcoming barriers concerning power use Specifically, this study can

make practical contributions by exposing problems arising from bad moderation

and therefore helping community managers to eliminate them. Additionally, by

emphasizing the dark side of moderation our study also generates practical insight

for community managers to comprehend how moderation can be improved,

showing the way to a better facilitation of online discussions, enhanced

cooperation and less disputes among members and moderators.

1.3 Thesis Outline

Our paper is organized as follows. Chapter two discusses theories about online

communities, how they stimulate information sharing and the role that

moderators play in facilitating information sharing. Furthermore we introduce the

concept of power use by moderators and we examine how perceived power use by

moderators impacts users’ willingness to share information. Additionally, we

include the development of hypotheses and the presentation of the research

model. Chapter three focus on the respondents, the design, methods and variables

that were used for our study, while chapter four presents the findings of our study.

Finally, in chapter five we conclude this paper by addressing the relevance and

implication of our findings.

2. Theoretical Framework

The first paragraph (2.1) of this theoretical framework will be focused on

introducing the history of online communities through the years as well as the

motivations to join an online community, focusing on information sharing. The

second paragraph (2.2) will shed light on information sharing, its history on the

internet and what is the role of information sharing in online communities. The

following paragraph (2.3) will discuss about moderation, what kind of roles

moderators have, and in what ways they use the power that is given to them in

online communities. In addition, section (2.4) will offer some insights on power,

reviewing power from different perspectives, introducing French and Raven’s

classification (1959) on bases of social power while highlighting the

approach/inhibition theory that will play an important role in our study. Finally,

in paragraph fifth (2.5), the last part of this chapter, the research model and an

overview of the hypotheses will be presented.

2.1 What are online communities?

Online communities have existed on the Internet for almost a quarter of a century

(Ridings and Gefen, 2004). The Well (http://www.well.com/), started in 1985, and

Usenet newsgroups, started in 1979, are widely regarded as the first virtual

communities on the Internet. Since then there has been a steady flow of new

versions and new technologies (Preece and Maloney-Krichmar, 2003) as with the

shift from the early static Web pages that appeared in the mid 1990s to highly

interactive Web pages, virtual communities have swiftly appeared on the World

Wide Web (Ridings and Gefen, 2004). The past years, more and more private

individuals clustered online with similar others to anchor themselves, support

each other, and exchange information (Bressler and Grantham, 2000).

Early descriptions of online communities were anecdotal and tended to make

comparisons with face to face communication (Preece and Maloney-Krichmar,

2003). Preece (2000) explains that the term was then hard to define is due to the

fact that it means different things to different people. In 1993, though, Rheingold

captured the essence of an online community in a way that still endures today: ‘…

virtual communities are cultural aggregations that emerge when enough people

bump into each other often in cyberspace. A virtual community is a group of

people who may or may not meet one another face-to-face, and who exchange

words and ideas through the mediation of computer bulletin boards and

networks’ (Rheingold, 1993). More interpretations of online communities have

then followed Rheingold’s definition. For example, virtual communities have been

characterized as people with shared interests or goals for whom electronic

communication is a primary form of interaction (Dennis, Pootheri, and Natarajan,

1998), as groups of people who meet regularly to discuss a subject of interest to all

members (Figallo, 1998), and groups of people brought together by shared

interests or a geographic bond (Kilsheimer, 1997). For individuals and groups,

online communities facilitate virtual collaboration among community members

with the potential of transforming the activities of off-line into an online context

(Massey et al. 2003). Finally, the definition we use in our study comes from Preece

(2000), who defines an online community as “a group of people, who come

together for a purpose online, and who are governed by norms and policies”. The

reason why we selected this definition is mirrored in the summary of De Souza

and Preece (2004) who argue that “1) it encourages a balanced view of both social

and technical issues; and 2) it is widely applicable to a range of communities both

online and physical”.

Through the years previous discussions on online communities have focused on

different aspects. Initially, for example, communities were characterized mainly by

their physical features, such as size, location and their boundaries (Preece, 2001).

The location of the virtual community, although not physical, is regarded

important because it establishes the virtual ‘place’ where the members meet

(Ridings et al., 2002). This location or mechanism may be a listserv email program,

chat room, multiuser domain or bulletin board. Listservs are one type of

community, where the members communicate through a common email program.

Chat rooms are another place where members interact. Multiuser domains

(MUDs) are programs that accept network connections from multiple

simultaneous users and provide access to a shared database of “rooms”, “exits”,

and other objects (Curtis and Nichols, 1993). Finally, bulletin boards or

newsgroups are places where members interact asynchronously.

Another facet of the definition of a virtual community is the frequency with which

its members participate in it. According to Sproull and Faraj (1997), the people in

a virtual community have a notion of membership, whether formal or informal,

and form personal relationships with others in the community while communities

often develop strong norms and expectations for behavior (Sproull and Kiesler,

1991). Consequently, people typically are attached to the communities and visit

them often (Hiltz and Wellman, 1997).

Despite the discussions about the online communities from a variety of angles,

researchers agree that online communities can be made feasible by the presence

of groups of people who interact with specific purposes, under the governance of

certain policies, and with the facilitation of computer-mediated communication

(CMC) (Lin and Lee, 2006). However, the presence of people, location, or

frequency mentioned before, as facets for the development of online communities

can be also met in the offline, traditional, face-to-face communities. Therefore,

what is exactly the difference between electronic communities from traditional

ones? Hiltz and Wellman (1997) argue that compared to communities offline,

computer-supported communities tend to be larger, more dispersed in space and

time, more densely knit, and have members with more heterogeneous social

characteristics, such as lifecycle stage, gender, ethnicity, and socioeconomic status

but with more homogeneous attitudes. According to Sproull and Faraj (1997),

there are three main differences between online and traditional communities.

First, physical location is irrelevant to participation in virtual communities.

Second, most participants in virtual communities are invisible (i.e., if an individual

only reads messages and does not post, other members may not be aware of his

presence at all). Third, the logistical and social costs to participate in virtual

communities are lower than those for participation in face-to-face communities.

Kollock and Smith (1999) also observed that virtual communities differ from

face-to-face communities in important ways such as the lack of real-world physical

cues, the ability of members to change their identities, degree of social order and

control, as well as purpose.

2.1.2 Motivations to join an online community

Research in social psychology has revealed different motivations for individuals to

join regular, non-Computer Mediated Communication (CMC) groups (Ridings and

Gefen, 2004). Humans have a need to belong and be connected with others

(Watson and Johnson, 1972). According to social identity theory (Hogg, 1996;

Tajfel, 1978), people form a social identity of values, attitudes and behavioral

intentions from the perceived membership in distinct self-inclusive real or

imagined social groups.

Moving from traditional, face-to face groups, the aforementioned motivations for

joining a community can be applied to online communities as well (Ridings and

Gefen, 2004). Rheingold (1991) describes the essence of virtual communities and

suggests motivations to use: “People in virtual communities use words as screens

to exchange pleasantries and argue, engage in intellectual discourse, conduct

commerce, exchange knowledge, share emotional support, make plans,

brainstorm, gossip, feud, fall in love, find friends and lose them, play games, flirt,

create a little high art, and a lot of idle talk.” Ridings and Gefen (2004) argue that

another possible reason why people join virtual communities is to seek

friendship. They mention that the interactivity achieved with chat rooms, instant

messaging, and bulletin boards, and the various search facilities available on the

Internet provide a way for individuals to search for and to communicate with

others for the purpose of establishing and continuing friendships. In addition, this

interactivity gives them the feeling of being together; being part of a group,

spending time together, engaging in small-talk with people around the

world (Ridings and Gefen, 2004; Wellman, 1997). According to Butler et al. (2002),

online groups can provide a place to build and maintain social ties with people

already known offline as well as those first met online.

Furthermore, recreation can also constitute another reason to join an online

community (Ridings and Gefen, 2004; Wasko and Faraj, 2000; Utz, 2000). Virtual

community participants have been found to believe that the communities are fun

and enjoyable (Wasko and Faraj, 2000). For instance, Utz (2000) proposes that the

primary motivation for individuals in MUDs is an interest in recreational role-

playing and game playing.

In addition, prior studies of online groups suggest that people often participate as

a way to gain access to otherwise obscure or inaccessible information that is

relevant to their work, hobbies, health, and other fields in which they are

personally interested (Galegher, Sproull and Kiesler, 1998; von Hippel, 2001). This

information benefit may come in the form of receiving answers to specific

questions or general knowledge arising from exposure to group communications

(Butler et al., 2002). Indeed, the most frequently cited reason for individuals to

join an online community in the literature is to access information (Jones, 1995;

Wellman et al., 1996). Ridings and Gefen (2004) discuss what makes virtual

communities unique is that most of their content is member-generated, as

opposed to other Internet information which is typically provided by the site

provider. Baxter (2007) argues that it is the member-generated content that adds

stickiness to a site, encouraging people to stay, participate and revisit.

The importance of member-generated content as a motivation to join online

communities has been discussed by Hagel and Armstrong (1997) who highlight

that “as more members generate more content, the increased content draws more

members”. Ridings et al. (2002) discuss that there are two basic modes in which

individuals can use a virtual community; to get information or give information.

This study examines information sharing in virtual communities and the effect of

moderation on this exchange. Next section will be focused on introducing a brief

history of information sharing on the internet, how do we conceptualize it and

what is the role of information sharing in online communities.

2.2 A brief history of information sharing on the internet

The earliest known versions of online information sharing environments date

back to the email-based discussion lists that predate the internet. Implemented in

the form of Listservs and other centralized hub implementers of group email,

these early interpretations leveraged collections of email addresses and allowed a

limited form of group consultation (Rafaeli and Raban, 2005). Usenet constituted

the next generation to follow. On average, in 2001 about 700,000 messages were

contributed to Usenet per day (Viegas and Smith, 2004), a number that revealed

its great popularity. Furthermore, with the emergence of WWW protocol in the

early 90s many web-based forums for information sharing were created, allowing

much more intricate and sophisticated designs while appealing to a much larger

audience (Rafaeli and Raban, 2005). Few years later, the web evolved into a new

stage, with the emergence of ‘blogs’ or weblogs. According to Drezner and Farrell

(2004) a weblog is a type of website with minimal to no external editing, providing

on-line commentary, periodically updated and presented in reverse chronological

order, with hyperlinks to other online sources. Blogs can function as personal

diaries, technical advice columns, sports chat, celebrity gossip, political

commentary, or all of the above and the process of posts commenting on posts are

a key form of information exchange in the blogosphere (Drezner and Farrell,

2004).

Among the latest innovations in online mechanisms that encourage information

sharing are the so called “Wikis”, which are server-based software systems that

allow users to freely create and edit Web page content using any Web browser.

Wikis support hyperlinks and have simple text syntax for creating new pages; they

are designed to enable ‘open editing’, encourage democratic use of the Web and

promote content composition by nontechnical users (Rafaeli and Raban, 2005).

Encyclopedias and dictionaries are a good example of wiki-powered information

collections. Finally, social networking that emerged in 2003 is another example of

online mechanism which promotes information sharing. LinkedIn.com,

Friendster.com and Facebook.com are regarded among the more heavily

populated of these sites.

As it has become clear from the discussion above the information sharing

continuum, ranging from the free flow of gossip to the highly restricted flow of

specialized and proprietary information has been studied through the years. The

plethora of available systems for information sharing discussed gives us a good

view of information sharing on the internet. However what do we mean by

information sharing and how we conceptualize it?

2.2.2 Conceptualizing information sharing

Many descriptions of information sharing have been given through the years. For

example, Sharratt and Usoro (2003) defined sharing as a process whereby a

resource is given by one party and received by another. It seems that sharing

occurs uniquely with information, in ways not replicated with other goods or

services (Rafaeli and Raban, 2005). Specifically, Rafaeli and Raban (2005) suggest

that people would rather share something intangible like information than

tangible goods e.g., their car or their house. For sharing to occur, there must be an

exchange; a resource must pass between source and recipient (Sharatt and Usoro,

2003). The term information sharing thus implies the giving and receiving of

information (Sharatt and Usoro, 2003). Information sharing is also regarded to be

“the act of providing a helpful answer in response to a request for information”

(Rafaeli and Raban, 2005). Therefore, sharing is also responsive. It depends on the

kindness of peers, friends, or complete strangers or on some intangible reward

structure. Furthermore, Hidding and Catterall (1998) also tried to conceptualize

information sharing by reasoning that knowledge has no value unless it has been

shared and used in some way. In other words, sharing knowledge is the natural

way to increase the value of knowledge (Yang and Lai, 2008). In addition,

Hendriks (1999) argued that generally knowledge-sharing presumes at least two

kinds of people to engage in; one who possess knowledge and the other who

request for acquire knowledge.1

2.2.3 Information sharing in online communities

In its current form, the World Wide Web (W3) provides a simple and effective

means for users to search, browse and retrieve information, as well as to make

information of their own available for others (Bentley et al., 1995). One of the

most popular points at which content is generated and contributed is within

online communities where people share news, information, jokes, music,

discussion, pictures, and social support (Ling et al., 2005). Although an increasing

number of online communities support interaction between participants via

multimedia applications such as video conferencing tools, Internet telephony

tools, webcams and the like, almost all rely upon the exchange of texts between

writers and readers in an ongoing discursive activity (Burnett, 2000).

Virtual communities owe their existence to information exchange between

members (Hagel and Armstrong, 1997; Rheingold, 1993). Whether members

participate in the community for its topical content or to socially connect with

1 Although it is important to distinguish between knowledge and information (Nonaka and Takeuchi, 1995), what

gets transmitted electronically is either data or information (Jarvenpaa and Staples, 2000). In particular, the terms

knowledge and information are often used interchangeably by many researchers. Kogut and Zander (1992) for

example, define information as “knowledge which can be transmitted without loss of integrity”, thus suggesting that

information is one form of knowledge. Sharatt and Usoro (2003) also discuss that information by definition is

informative and, therefore, tells us something and that knowledge is gained through the interpretation of information.

Van Beveren (2002) however states that the sharing of information covers a broad spectrum of exchanges and does

not necessarily lead to the creation of new knowledge. For the purpose of this study, we also use the term

interchangeably, since our scope is not concerned with the interpretation of information that is exchanged but with

the information itself.

other members, contact is made by producing and processing textual or graphical

member contributions (Valck et al., 2009) and members are passively informed

about noteworthy issues (Hoffman and Novak, 1996). Knowledge sharing is

enabled through mechanisms that support posting and responding to questions,

sharing stories of personal experience as well as discussing and debating issues

relevant to the community (Wasko and Faraj, 2000). According to Ridings et al.

(2002) sharing in online communities embodies both giving and getting

information. Getting information is simply reading the ongoing conversation in a

community, as well as actively soliciting information by posting questions and

comments, whereas giving information is done by posting conversation, either in

direct response to another member’s post or simply by starting a new topic in the

community (Ridings et al., 2002). For instance, in an online forum, individuals,

may post a topic to request specific knowledge while someone else who possesses

the knowledge may reply the topic by providing the knowledge they have (Yang

and Lai, 2008).

In addition, Lueg (2003) argues that members do not only get to know new

information but they also learn from others about how and where to find further

information and how to make use of this information. For example, community

members may also use other online communication channels, such as email,

mailing lists, chats, instant messengers and other newsgroups, to disseminate

information they received in a community or to search for new one. Interestingly,

both receivers and senders of information are found to presumably gain from

information exchange (Valck et al., 2009). However, this can only be achieved as

long as active participation is ensured (Butler et al., 2002). Specifically, Butler et al.

(2002) explain that participation is secured by creating and consuming content.

Creating content implies generating messages, responding to messages, organizing

discussion, and offering other online activities of interest to members. On the

other hand, consuming content is equally important because if members do not

regularly read the material that others provide, the online groups will not remain

viable (Butler et al., 2002).

Since information sharing and user-generated content have become popular

online phenomena, the quality of content has become a concern (Chen et al.,

2007). For example, in Wikipedia, readers may be provided with content that is

misleading or even incorrect and the quality of it may not be equal for all the

articles represented (Kolbitsch and Maurer, 2006). On Slashdot, commentators

may post some biased or useless comments; e.g., advertisers from companies may

post biased comments to promote their products (Chen et al., 2007). A large part

of the increase in coordination and regulation efforts in Wikipedia is due to the

need of defining quality standards and assuring the quality of content (Viégas et.

al., 2007). Therefore, it is of vital importance for the online world to secure the

dissemination of information and to communicate what information should or

should not be presented (Preece, 2001).

It appears that having clearly defined policies and rules safeguards the

dissemination of information. For example, the literature on offline organizational

communities indicates that organizations should take a proactive approach to

changing the shared social norms of sharing by instituting organizational policies

(Davenport, 1997). The policies Davenport suggested include creating a

committee or assigning responsibility to addressing information use issues and

clarifying the organization's objectives for using and sharing information. Preece

(2001) also discussed the importance of policy for securing information flow as it

is “the language and protocols that guide people’s interactions and contribute to

the development of folklore and rituals that bring a sense of history and accepted

social norms”. Studies by Preece (2001) and Wang (2002) suggest that policies can

influence who joins the community, how easy it is to get into the community, the

style of communication among participants as well as privacy and security issues.

However, despite having clearly defined policies and rules in an online

community, how these should be enforced is also a matter of discussion.

Specifically, Preece and Maloney-Krichmar (2003) emphasize that there is no

point in making rules if they are not enforced. In addition, Valck et al. (2009)

discuss that is important to enforce group norms as these will allow them to

establish and maintain an amiable ambiance in the community. So, how can these

rules be enforced in order to facilitate information sharing? The answer is given

by Lazar and Preece (2002) who state that community rules are usually enforced

by the moderator. Moderators can perform a range of different activities. There

are a number of tools and roles given to moderator depending on administration’s

aims, the technology used as wells as the context in which the discussion forum

operates (Wright, 2006). The role that moderation plays in online communities as

well as the levels of activity undertaken by community moderators are discussed

more thoroughly in the following sections.

2.3 Moderation in online communities

Moderation in online communities has existed for nearly as long as online

communities, and has been designed to combat problems that arise from the

interaction of its members (Lackaff, 2004). Lackaff (2004) suggests that some of

the most frequently acknowledged problems an online community experiences

are content overload, spam, and malice, though different online communities will

experience different problems as they increase in popularity. Content or

information overload is the state of an individual (or system) in which not all

communication inputs can be processed and utilized, leading to breakdown

(Rogers and Agarwala-Rogers 1975). In the context of CMC, researchers refer to

both “conversational overload” when too many messages are delivered, and

“information entropy” when incoming messages are not sufficiently organized to

be easily recognized as significant or as part of a conversation’s history (Jones et

al., 2004). “Spam” is the abuse of electronic messaging systems (including most

broadcast media, digital delivery systems) to send unsolicited bulk messages

indiscriminately, while “malice” refers to cases of intentional abuse, such as

“trolling”, “flaming”, and other deliberate attempts to disrupt the community.

Surprisingly, discussions in online communities are challenged by the

aforementioned problems. Therefore an effective way to cope with these problems

is to address them to moderators so that they can facilitate and maintain forward

progress in the discussions (De Loach and Greenlaw, 2007). Lackaff (2004)

distinguishes two options for community moderation; social moderation and

technical moderation. Social moderation is the process by which community

norms are maintained through social constructions and interaction, i.e.

constitutions, declarations of purpose, and education of new members (Lackaff,

2004). On the other hand, technical moderation involves two general classes; user

level moderation and post level moderation. An example of user level moderation

is the Usenet “kill file”, that allows a user to completely ignore a set of postings

based on simple criteria, such as the poster’s name or keywords in the text. In

contrast, post level moderation is a process where either all messages are only

posted after they have been explicitly approved or all messages are read after they

are posted, and inappropriate messages are deleted (Lackaff, 2004).

Apart from the aforementioned options for community moderation, it is also

important to identify the various roles that moderators perform in an online

environment. These roles have been discussed exhaustively by many researchers

(Berge, 1992; Collins and Berge, 1997; Salmon, 2000) and will be reviewed in the

following section of our study.

2.3.1 The role of moderators in online communities

Literature to date has identified that moderators are given the power to undertake

various roles within online communities. Particularly, Scott Wright detects no less

than eleven functions which may be given to the moderator. For instance, by

posting new questions and topics, the moderator assumes the role of a

conversation stimulator; he can act as a mediator when participants come into

conflict; he can facilitate debate between elected representatives and citizens by

summarizing the main points of the various messages; he can also be an open

censor by removing messages disrespecting the forums rules, whilst at the same

time providing senders with explanations concerning the censorship so that they

can reword the contentious message(Wright, 2006).

In addition, several other ways of power use to moderate online content have been

discussed by other researchers (Berge, 1992; Collins and Berge, 1997; Salmon,

2000) including:

• Facilitating, so that the group is kept focused and “on topic”

• Managing the list, e.g. archiving, deleting and adding subscribers

• Filtering messages and deciding which ones to post, e.g. removing flames,

libelous posts, spam, inappropriate jokes and generally keeping the ratio of

messages high

• Being an expert, meaning that he can answer frequently asked questions

(FAQS) or direct people to read FAQs and policies of the community

• Being an editor, s/he edits texts and format messages

• Promoting questions to generate discussions

• Being marketer, he promotes the list to others so that they join

• Helping users with general needs, and finally ,

• Being a fireman, he ensures that flaming is done offline.

An alternative approach by La Bonte et al. (2003) highlights further roles that are

mandated to moderators. Specifically, their study suggests that moderators, in

order to manage an online learning environment, they have to pay attention to the

intellectual, social as well as managerial and technical factors of the community.

For example, the moderator should encourage participation through use of

questions and probing; he should focus the discussion on critical concepts,

principles and skills; he should contribute to the creation of a friendly, social

environment, the promotion of healthy and social interactions, as well as the

creation of opportunities to sustain discussions (La Bonte et al., 2003). In addition,

their study also suggest that managerial factors require moderators to manage the

flow and direction of discussion without stifling creative opportunity, while

challenges coming from technological factors expect that moderator becomes

familiar and proficient at the use of technology (La Bonte et al., 2003).

Studies by Coleman and Gotze (2001) examine various other ways of power use to

moderate online discussions. For instance, their study distinguishes seven kinds of

moderators:

• The social host helps create an environment where the members feel

comfortable to participate.

• The moderator as manager leads the discussion and pays attention to

adherence to focus, timelines, tasks lists, commitments and process.

• The “community of practice” facilitates exchanges amongst the

participants, facilitating group interaction and highlighting points of

agreement as they emerge.

• The cybrarian participates as an expert on a specific topic, stimulating

discussions by providing relevant information as needed.

• The help desk provides simple technical pointers on using the software.

• The referee is considered probably the best-known moderator role, in that

s/he aims at making participants respect the rules of the debate and

keeping them “on topic”.

• The janitor tidies up forgotten topics by freezing and archiving and

redirects activity if it is in the wrong area (Coleman and Gotze, 2001).

Similarly, Berge and Collins (2000) detect the role of moderator as “intellectual

leader”. In particular, their study suggests that a subset of the roles and tasks of

online teachers seems to be the same or very similar to those of moderators.

Furthermore, the role of moderator as intellectual leader has also been

emphasized by Berge (1995), who suggests that some of the most important roles

of moderators revolve around their duties as “educational facilitator”. For

example, the moderator may use questions and probe for student responses that

focus discussions on critical concepts, principles and skills.

Reviewing the aforementioned roles that are assigned to moderators, we observe

that the “facilitator” role is widely discussed in the literature (Berge, 1995;

DeLoach and Greenlaw, 2007; Salmon, 2000; Wright, 2006). Interestingly,

facilitation is regarded crucial as may encourage greater participation in the

discussion, prevent domination of the discussion by a few individuals, and lead to

greater online collaboration among members (Salmon, 2000). In contrast, Wojcik

(2008) considers the “referee” as probably the best-known moderator role, in that

his actions are aimed at making participants respect the rules of the discussion

and keeping them “on topic”.

In addition, one of the common roles of moderation is also regarded to be the

“open censor” where the moderator filters the messages and intervenes when

posts violate community’s policy (Coleman and Gotze, 2001; Collins and Berge,

1997). Interestingly, it appears that in order to facilitate discussions effectively,

the moderator must have a clear understanding of why intervention is necessary

and what he hopes to accomplish with the intervention (DeLoach and Greenlaw,

2007). Thus, moderators, are considered crucial to shaping the democratic

potential of online discussion (Edwards 2002; Coleman and Gøtze 2001; Wright

2006).

There are, however, persistent fears that moderators censor rather than promote

free speech, leading to a ‘shadow of control’ (Wright, 2006). For example, Beth

Noveck (2004,) suggests that ‘to be deliberative, the conversation must be free

from censorship’ and this ‘includes any distortion or restraint of speech that

would hinder the independence of the discussion or cause participants to self-

censor’. As such, the moderator needs to know when and how to intervene

(DeLoach and Greenlaw, 2007) because an unsuccessful intervention could set

overly restrictive rules or ignore community rules and delete messages, thus

hindering freedom of discussion (Wright, 2006).

Following the study of Wright (2009), who states that “the fear remains, however,

that the power to moderate the content of online forums will be abused”, our next

section sets out, then, to examine power as a mechanism of fostering unsuccessful

moderation.

2.4 Conceptualizing Power

The idea of power is a thoroughly examined theme in existing literature.

Interestingly, it seems that there is not a general consensus about what power is

or how it operates (Cook et al., 1983). Power has long been discussed both in

sociology as well as in the offline organizational context. For example, underlying

most current definitions of power in social psychology is the idea that power is a

theoretical construct that accounts for the portion of social influence that is under

the actor’s control: “Power refers to the ability to achieve ends through influence”

(Huston, 1983, pp. 170). Similarly, Robert Bahruth (2000) defines power as the

ability to control the actions of other people as well as the ability to escape from

the control of others.

In addition, many definitions of power involve the ability of one actor to overcome

resistance in achieving a desired result (Pfeffer, 1981), or, simply, the ability to

affect outcomes or get things done (Mintzberg, 1983; Salancik and Pfeffer, 1977).

Karen Cook (Cook and Emerson, 1978) sees power coming from exchange

networks: “Power is an attribute of position in a network structure observable in

the occupant’s behavior, even though the occupant does not know what position

or what amount of power s/he possesses”.

Discussions of power also focus on the bases of power. For example, French and

Raven described five bases of power: reward power, coercive power, legitimate

power, referent power and expert power (French and Raven, 1958). In their study,

French and Raven define reward power as the agent’s ability to provide the target

with desired outcomes such as pay increases or job promotions. Coercive power is

the agent’s ability to affect negative consequences, such as a demotion or transfer

to a less desirable assignment. Legitimate power is the agent’s right to make a

request, based upon their official position in the organization, as perceived by the

target. Referent power refers to the agent’s ability to seek the target’s response,

based upon the target’s desire to please the agent. Expert power is derived from

the perceived expertise of the agent, gained by experience, education or training

(French and Raven, 1959).

Furthermore, examples of research from the behavioral perspective on power are

frequent in the organizational literature (e.g., Kipnis, Schmidt, and Wilkinson,

1980). Thompson and Luthans (1983) provided a summary of the behavioral

approach. They noted that "power is manifested through behavioral actions"; thus,

to study power empirically, researchers must ultimately study behaviors.

Likewise, Mintzberg emphasized both "will and skill": "But having a basis for

power is not enough. The individual must act" (Mintzberg, 1983). People who are

able to control relevant resources and thereby increase others' dependence on

them are in a position to acquire power (Brass and Marlene E. Burkhardt, 1993).

Following the study of Fiske (2004) we define power as “a core social motive”

(Fiske, 2004) that can be used to control over another’s valued outcomes (Dépret

and Fiske, 1993). Researchers have argued that individuals in powerful roles tend

to favor less social equality (Fiske, 1993; Sachdev and Bourhis, 1985) and

discriminate more against outgroups (Sachdev and Bourhis, 1985, 1991).

Therefore, by definition, the powerful have relative control over valued outcomes,

namely, they can act with relatively little interference or constraint from others

who lack such control (Berdahl and Marorana, 2006). This means that those low in

power, will have relatively little control over valued outcomes and are likely to

perceive threats and uncertainty in their environment (Berdahl and Marorana,

2006).

Several theories have already focused on power and how lack of power increases

the experience of negative emotions (Anderson and Berdahl, 2002; Keltner et al.,

2003; Smith and Bargh, 2003). Specifically, as relative control over others’

outcomes, power comes with opportunities to use control for one’s own

satisfaction, which might increase positive emotions (Chen, Lee-Chai and Bargh,

2001) but can also lead others to a relative dependence on them, which in turn

might increase others’ negative emotions and experiences (Berdahl and Marorana,

2006). For example, Anderson and Berdahl (2002) studied the behavior of dyads,

where each dyad was given one individual power over the outcomes of another.

The dyads had to engage in a decision-making task. Anderson and Berdahl

concluded that those with power had more influence over the groups’ decisions

than those without power.

Along similar lines, in 1972, Kipnis raised the question "Does power corrupt?" in

the title of his empirical article. The bulk of his findings suggested that the answer

to this question was "yes." For example, Kipnis found that having power was

associated with an increase in attempts to exert influence over the less powerful,

and with the devaluation of the less powerful in terms of their ability and worth

(Kipnis, 1972, 1976). Research on social participation and group dynamics has

shown that people with high power tend to speak more than people with low

power (e.g., Dovidio et al., 1988). For example, Dovidio et al. (1988) found that

people randomly assigned to high power positions in a discussion task spoke more

than twice as much as people randomly assigned to low power positions.

In addition, Steve Jones (1998a) stated that “just because the spaces with which

we are now concerned are electronic there is not a guarantee that they are

democratic, egalitarian or accessible”. Specifically, this fear comes from the fact

that power exercised from community managers “may range from force through

manipulation of symbols, information, and environment” and because “a critical

characteristic of power is the emphasis on private-goal orientation rather than

collective goal orientation” (Grimes, 1978, pp. 727). In other words, in an online

context, community managers, e.g., moderators can take advantage of the power

that is given to them to moderate the content of online discussions, either by

setting overly restrictive rules, or by ignoring community rules and delete critical

messages (Wright, 2009).

However, if community managers do not stick to these rules, or take advantage of

the power that is given to them, what would be the effect on information sharing?

2.4.1 Power and the approach/inhibition system

In 2002, Anderson and Berdahl presented a good example of an interaction

between a power holder and a powerless. They suggested: “Imagine a meeting

between a faculty advisor and his 1st-year graduate student. The advisor has a

great deal of power because he has the ability to provide or withhold resources or

administer punishments. The 1st-year student, in contrast, has control over fewer

resources and is less able to administer punishments to her advisor. When these

two people meet, how will the advisor’s power influence his behavior? How will it

affect what he says, shape the emotions he feels, or direct the focus of his

attention?” The aforementioned example derived from their study reflects the

exact intention of our study; to examine how a power holder, e.g., a moderator,

influences the behavior of a less powerful, e.g., a member, and how the power

holder will affect his attitude and intentions towards information sharing. The

research model for explaining how power use affects users’ attitudes and

intentions towards information sharing is based on the approach/inhibition

theory.

With the aim of providing a theoretical framework of the effects of power, Keltner

et al. (in press) recently proposed the approach/inhibition theory of power. The

approach system of power is activated because power holders experience

relatively little fear of reprisal from others for their actions (Berdahl and

Martorana , 2006), they are aware that they will encounter less interference from

others when approaching potential rewards (Keltner et al.,1998) and when people

have power, they have access to more material resources, such as financial

resources and physical comforts, as well as social resources, such as higher

esteem, praise, and positive attention ( French & Raven, 1959; Keltner et al.,

1998;). In contrast, those low in power have relatively little control over valued

outcomes; they must consider the reactions of the powerful before acting because

the powerful can punish them if they disapprove of their actions (Berdahl and

Martorana, 2006). Those low in power are therefore likely to perceive threats and

uncertainty in their environment (Berdahl and Martorana, 2006; Fiske, 1993).

This focus on threats helps to activate the inhibition system.

The notion that those with power are likely to experience and express relatively

positive emotions while those without power are likely to experience and express

relatively negative ones has long been discussed in the literature (Anderson and

Berdahl, 2002;Chen, Lee-Chai and Bargh, 2001). Research to date has found that a

lack of power, or relatively little control over others’ outcomes, is accompanied by

relative dependence on others, which might increase negative emotions

(Anderson and Berdahl, 2002; Keltner et al., 2003; Smith and Bargh, 2003). In

addition, recent cross-cultural research suggests that people believe the powerful

elicit anger and contempt in others (Mondillon et al., 2005).

Many findings from previous research support the approach/inhibition

framework. People in positions associated with high power (e.g., leaders, people

high in socioeconomic status) often exhibit signs of an active approach system,

and people in positions of low power (e.g., followers, people low in socioeconomic

status) often exhibit signs of an active inhibition system (Keltner et al., in press).

Thus, the approach/inhibition theory of power has shown initial promise as a

broad theoretical framework that integrates diverse findings on the effects of

power (Anderson and Berdahl, 2002).

For our specific hypotheses in the following section, we expected participants

higher in power to affect those that are lower by having an impact on their

intentions to share knowledge. We expected participants lower in power, in

contrast, to show greater inhibition in social and individual motivations. We

address each of these hypotheses in the following sections.

2.5. Research model and hypotheses

The research model for explaining how power use affects users’ intentions

towards information sharing incorporates constructs from the power literature,

relational social capital and collective action.

Previous research (Wasko and Faraj, 2005; Wiertz and Ruyter, 2007) has shown

that overall, social capital and individual characteristics are among the main

determinants of knowledge sharing. These authors have tested a theoretical

framework incorporating individual motivations and social capital to explain

voluntary behavior in computer-mediated knowledge exchange networks.

Therefore, in accordance with their study we examine the role of relational social

capital (commitment and reciprocity) as well as individual motivations

(enjoyment in helping others and reputation) as predictors of knowledge

contribution.

Figure 1 presents the model of our hypotheses. We describe each of the constructs

and their relationships to knowledge contribution in the following sections.

2.5.1 Relational Social Capital

Relational social capital refers to the affective nature of social relationships within

a collective (Wasko and Faraj 2005) and has been identified as an important

facilitator of an individual’s actions within the collective (Coleman, 1990).

Therefore, the relational dimension of social capital is expected to have a strong

influence on individual member behavior, such as knowledge contribution

(Nahapiet and Ghoshal, 1998). There are two main aspects of relational social

capital, commitment to community and reciprocity.

Commitment to community

As members have repeated positive exchange experiences, the importance of the

relationship with the community as a whole increases accordingly and members

become committed (Wiertz and Ruyter, 2007). Kollock (1999) posits that it is this

commitment that motivates members to contribute content. Prior research also

finds that when commitment to the community increases, members feel a sense of

responsibility to assist others in the collective by sharing their valuable knowledge

(Wasko and Faraj 2005). This leads to the following hypothesis

H1a: An individual’s commitment to community has a positive impact on the

intentions to share knowledge

Reciprocity

The second aspect of relational social capital is reciprocity. Reciprocity is defined

as the benefit expectancy of a future request for knowledge being met as a result

of the current contribution (Kankanhalli et al., 2005a). Research has found that

people who share knowledge in online communities believe in reciprocity (Wasko

and Farah, 2000). In addition, reciprocity is thought to exert influence on

information sharing by means of a “return-in-kind” attitude (Kolekofski and

Heminger, 2003). Thus, when the individual members of an online community

perceive that a strong norm of reciprocity governs the exchanges within the

community, they expect that their valuable knowledge contribution will be

reciprocated at some point in the future (Wiertz and Ruyter, 2007). In line with

Wasko and Faraj (2000, 2005) we derive the following hypothesis

H1b: An individual’s perception of the norm of reciprocity has a positive impact on

the intentions to share knowledge

In addition to social capital, previous research proposes that knowledge

contribution is also influenced by individual attributes of network participants

(e.g. Nahapiet and Ghoshal 1998; Wasko et al., 2004; Wasko and Faraj 2005). In

the next section, we will elaborate on the potential impact of two individual

variables that are particularly important in the context; enjoy helping others and

reputation.

2.5.2 Individual Motivations

Social capital researchers have proposed that one important reason why some

individuals build up more social capital and engage more willingly in collective

action than others are individual attributes, such as motivations and abilities

(Adler and Kwon 2002; Coleman 1990; Lakhani and von Hippel 2003; Nahapiet

and Ghoshal 1998; Putnam 1993). In line with Wasko and Faraj (2005), who

examine how an individual’s cognitive capital affects his or her level of knowledge

contribution to the network, we adopt two individual motivations. These

motivations are 1) enjoy helping others, and 2) reputation.

Enjoy helping others

In addition to individual online interaction propensity, members may also receive

intrinsic benefits from contributing knowledge. Prior research has found that

knowledge is deeply integrated in an individual’s personal character and identity

(Wasko and Faraj, 2005)., Bandura (1986) argues that individuals sometimes

engage in activities for the sake of the activity itself, rather than external rewards

due to the fact that they pursue social acceptance and intrinsic benefits. Thus,

individuals may contribute knowledge in an electronic network of practice

because they perceive that helping others with challenging problems is

interesting, and because it feels good to help other people (Kollock 1999).

Similarly, Wasko and Faraj (2000) discuss that individuals are motivated

intrinsically to contribute knowledge to others because they enjoy it. Thus, we

propose the following hypothesis

H2a: An individual’s enjoyment of helping others has a positive impact on the


Reputation

Prior research on social exchange theory (Blau 1964) argues that individuals

engage in a social interaction based on an expectation that it will lead in some way

to social rewards such as approval, status, and respect. This suggests that one

potential way an individual can benefit from active participation is the perception

that participation enhances his or her personal reputation in the network (Wasko

and Faraj, 2005). According to Hsu and Lin (2008), reputation is the degree to

which a person believes that participation could enhance personal reputation

through knowledge sharing. Thus, the perception that contributing knowledge will

enhance one’s reputation and status in the profession may motivate individuals to

contribute their valuable, personal knowledge to others in the network (Wasko

and Faraj, 2005). This leads to the following hypothesis

H2b: An individual’s reputation has a positive impact on the intentions to share

knowledge

2.5.3 Moderating Effects of perceived power use

One of the most popular frameworks for studying the effects of perceived power

use on individuals’ attitudes and behaviors has been French and Raven’s (1959)

classification of five bases of social power (i.e. reward, coercive, legitimate, expert

and referent).

In order to successfully measure our moderating variable and since we focus on

the negative ways of power use, we follow the study of Hart and Saunders (1997)

who adopt in their model one of the five bases of social power, coercive power.

Having already discussed in the previous chapter, coercive power is defined as the

agent’s ability to manipulate the attainment of valences and stems from the

expectation on the part of the individual that will be punished by the agent if he

fails to conform to influence attempt (French and Raven, 1959). Coercive power

focuses on punishment rather than benefits or inducements (Hart and Saunders,

1997). Thus, when individuals disagree, the use of coercive power by either party

makes the reestablishment of harmonious relations very difficult (Kipnis et al.,

1973). For example, in an online community the moderator can use the power to

remove posts or comments that otherwise should not be deleted while at the same

time make members feel that they will be punished in case they do not conform.

Through the years many studies have focused on the relationship between the five

leader power bases and subordinate attitudes and behaviors (Fiorelli, 1988;

Martin and Hunt; 1980). According to Elangovan and Xie (1999, pp. 320) studies

to date can be classified as focusing on “a) the relationship between supervisor

power and subordinate behavior b) the effects of supervisor power on various

facets of supervisor-subordinate relationships c) the relationship between

supervisor power and subordinate work attitudes”. Missing from this body of

research, however, are inquiries into the relationships between perceived

moderator power and member behavior not in an offline community as already

examined but in an online one.

Recent studies have suggested that the relationship between bases of social power

and subordinate variables is more complex than originally specified (Elangovan

and Xie, 2000). For example, in their study, Elangovan and Xie (2000) concluded

that there is no single base of power that is all-beneficial in influencing

subordinates or all-powerful as a predictor of employee criteria variables. They

suggested that different perceptions of supervisor power (i.e., different types of

power) might differentially affect employee motivation, satisfaction, commitment

and stress. Therefore, an alternative approach has been to consider the social

bases of power as moderators on subordinate attitudes. For example, Richmond et

al. (1980) sought to increase our understanding of the importance of supervisor-

subordinate relationship by examining the moderating impact of differential use

of supervisory power bases on satisfaction of subordinate’s perceptions. In this

way Richmond et al. could better understand the impact of each power base on

subordinate attitudes. Another example comes from Kleef et al. (2006) who study

the moderating impact of power on the interpersonal effects of anger and

happiness. The reason why they used power as a moderating variable comes from

the fact that low-power individuals can be strongly affected by their opponent’s

emotions but high power ones remain unaffected. These researchers clearly

suggest that power could also be used as a moderating variable for studying the

impact of high power individuals on low power ones. Similarly, we also consider

power as a moderating variable. The rationale is as follows.

Current research on the approach/inhibition theory shows that the behavioral

inhibition system has been equated to an alarm system (Anderson and Berdahl,

2002). Once activated by threats or potential punishments, this system triggers

affective states such as anxiety, heightened vigilance for threats in the

environment, avoidance, and response inhibition (Gray, 1982, 1987, 1991;

Higgins, 1997, 1998). Further studies highlight that people who lack power are

more attentive to threatening aspects of the social environment (Keltner et al., in

press). “If people with low power are more attentive to threats, they should

perceive the same environment as more threatening than should people with high

power” and as a consequence they inhibit themselves from speaking (Anderson

and Berdahl, 2002, pp 1365). For instance, one particularly salient threat to

people with low power is the potential for conflict with others (Operario & Fiske,

2001). Therefore, to avoid the threat of interpersonal conflict, people who lack

power might be more inhibited in what they express—they might keep

themselves from expressing their attitudes if such expression might provoke

conflict (Anderson and Berdahl, 2002). Similarly, classic research on obedience to

authority (Milgram, 1963) and social conformity (Asch, 1955) showed that people

in a presumably low power position keep their opinions to themselves.

In addition, Kipnis’ (1987, 1991) presents the argument that as people gain power

(and use influence tactics) over others they come to believe more positive things

about themselves and more negative things about their subordinates, as a result,

the increase of subordinate’s monitoring and the decrease of their participation in

decision making (Kipnis 1987, 1991).

If we translate the aforementioned findings to online discussions, moderators who

are perceived as using coercive power, communicate messages of threat or force

in an attempt to influence users. This can be done by increasing monitoring of

users, decreasing their participation in decision making, etc. Therefore, we expect

users who lack this kind of power to inhibit themselves from speaking and

keeping their opinions to themselves out of fear that they might provoke conflict

with moderators. More specifically, we expect that higher levels of perceived

power use will weaken the relationship between enjoyment in helping others, the

ability to reciprocate knowledge, the loyalty towards the community, user’s

reputation and the intentions to share knowledge. Therefore, we propose the

following hypotheses:

H3a: If an individual’s perception of coercive power use increases, the relationship

between commitment to community and intentions to share knowledge will be

weakened

H3b: If an individual’s perception of coercive power use increases, the relationship

between reciprocity and intentions to share knowledge will be weakened

H3c: If an individual’s perception of coercive power use increases, the relationship

between enjoyment in helping others and intentions to share knowledge will be

weakened

H3d: If an individual’s perception of coercive power use increases, the relationship

between reputation and intentions to share knowledge will be weakened

2.5.4 Overview of the hypotheses

H1a: An individual’s commitment to community has a positive impact on the


H1b: An individual’s perception of the norm of reciprocity has a positive impact on

the intentions to share knowledge

H2a: An individual’s enjoyment of helping others has a positive impact on the


H2b: An individual’s reputation has a positive impact on the intentions to share

knowledge

H3a: If an individual’s perception of coercive power use increases, the relationship

between commitment to community and intentions to share knowledge will be

weakened

H3b: If an individual’s perception of coercive power use increases, the relationship

between reciprocity and intentions to share knowledge will be weakened

H3c: If an individual’s perception of coercive power use increases, the relationship

between enjoyment in helping others and intentions to share knowledge will be

weakened

H3d: If an individual’s perception of coercive power use increases, the relationship

between reputation and intentions to share knowledge will be weakened

Figure 1: Conceptual model

Perceived

Coercive power

use

Social

Capital/Motivations

Commitment

to community

Reciprocity

intentions to

share knowledge Individual

Motivations

Enjoy helping

others

Reputation

3. Research Design and Method

In this chapter the research method will be described. In the first paragraph (3.1),

the design of the research is clarified and the research details are provided.

Paragraph 3.2 discusses the sample. The following paragraph (3.3) sheds light on

the research variables, while the last paragraph (3.4) focuses on the procedures

used in the research.

3.1 Research Design

In order to collect data and empirically test the hypotheses an online survey was

conducted. Online survey was selected since a survey can reach a large quantity of

people in a fast manner while the data collected from the questions can be

processed relatively easy (Van der Velde et al., 2004). This methodology was also

chosen because it enhances the generalizability of results (Dooley, 2001).

Furthermore, when conducting a survey the respondent has a greater feeling of

anonymity thus resulting in a willingness to participate (Van der Velde et al.,

2004).

An additional reason to choose a survey comes from the fact that several prior

studies have adopted this methodology (e.g., Bock et al. 2003, Constant et al. 1996,

Jarvenpaa and Staples 2000; Wasko and Faraj 2003) to successfully model and

explain contributor behavior in online communities. In the power literature,

Elangovan and Xie (2000) also adopted a survey methodology in order to examine

the effects of perceived power of the supervisor on subordinate work attitudes.

All of the questions used for this research were closed questions. A reason for

choosing closed questions for this survey comes from the study of Van der Velde et

al. (2004) who state that respondents see closed questions as more pleasant since

it takes less time to fill them in and no excessive typing takes place. The questions

were clustered around our research variables where each one of them contained

multiple items drawn from the literature.

All variables were measured using a multiple-item measurement scale. These

measures use a seven-point Likert type response format, with ‘strongly disagree’

and ‘strongly agree’ as the anchors, thus, allowing the respondents for more

selections between answers. The survey was placed on the website

http://thesistools.com/. The website allowed the respondents to fill in the survey

anonymously while making it easier for them to forward the link to their friends

so that they can also fill it in. The link to the survey was distributed mainly by

means of email so as to reach as many people as possible.

3.2 Sample

The sample of this research is regarded as a convenience sample. A convenience

sample is a sample where the respondents are selected, in part or in whole, at the

convenience of the researcher (Lunsford and Lunsford, 1995). Unlike other

samples, with a convenience sample the selection cost is minimal and the

researcher does not need to insure that the sample is an accurate presentation of

some larger group or population (Ferber, 1977; Lunsford and Lunsford, 1995).

This research focused on online communities and, as a result, the target

respondents were all members of online communities or members who at least

one time they were registered users of a community. In addition, the

questionnaire was administered in English in order to capture a wide range of

respondents and to be accessible in a variety of online community sites. The

importance of a well representative set of target group is highlighted in the study

of Van der Velde et al. (2004) who argue that a survey filled in by a relevant group

of people can obtain reliable data. Respondents were ranging from family

members and friends to students and online community users. They were

contacted mostly by emails, through social network sites like Facebook, Twitter

and LinkedIn, as well as through online discussion forums and blogs.

The results of the survey have led to a sample of 207 respondents. As we do not

know how many community members have read the threads featuring the survey,

but decided not to respond, it is difficult to estimate a precise response rate.

3.3 Research Instrument

In this paragraph the measurement of constructs (relational social capital,

individual motivations) will be described. Next to the examination of the measures

for the research variables concerning relational social capital and individual

motivations, this paragraph will also shed some light on the measurement of the

moderating variable of our study, perceived power use. Finally, the measurement

of the dependent variable of this study will be portrayed.

3.3.1 Measurement of social motivations


The items that were used to measure the influence of commitment to community

on the intentions to share knowledge were based on the research conducted by

Wiertz and Ruyter (2007). The total number of items for this research variable

was three.

Reciprocity

The research of Kankanhalli et al. (2005), Lin (2007) as well as Wiertz and Ruyter

(2007) were used to measure the influence of reciprocity on the intentions to

share knowledge. To be precise, the items “When I receive help, I feel it is only

right to give back and help others” and “The principle of give and take is important

for me in the community” came from the study of Wiertz and Ruyter (2007). The

third item of this variable, “When I share ideas, experiences and information, I

expect to receive ideas, experiences and information in return when necessary”,

was based on the research of Kankanhalli et al. (2005) and Lin (2007). The latter

item was reworded and adapted in order to be more relevant for this research.

The total number of items for this research variable was three.

3.3.2 Measurement of individual motivations

Enjoy helping others

The items measuring the enjoyment to help others in the community were

adopted by the study of Kankanhalli et al. (2005) and Wasko and Faraj (2005). In

order to get the items in line with this study, they all had to be adjusted textually.

In addition, not all the items that cover this construct were used. For example, the

item “I like helping other people” (Wasko and Faraj, 2005) was dropped since it

was already covered by the items of Kankanhalli et al. (2005). The total number of

items concerning this variable was three.

Reputation

The items to measure reputation were taken from the research of Hsu and Lin

(2008) as well as Wasko and Faraj (2005). Specifically, the items “I earn respect

from others by participating in the community” and “Participating in community's

activity enhances my personal reputation” were derived from Hsu and Lin (2008)

while the item “I feel that participating in online discussions improves my status in

the community” came from Wasko and Faraj (2005). All the items were reworded

and adjusted for the purpose of this study. The total number of items for this

research variable was three.

3.3.3 Measurement of the moderating variable

Perceived coercive power use

The research of Hinkin and Schriesheim (1989) was used to measure the

moderating impact of power on the intentions to share knowledge. Since Hinkin

and Schriesheim’s study focuses on supervisor-subordinate relationship in an

offline context, all the items for this research variable had to be adjusted textually.

For example, the item “makes being at work distasteful” from Hinkin and

Schriesheim was converted to “makes Online Community Site unattractive” while

the item “makes my work difficult for me” was changed to “makes it difficult for

me to participate in online discussions”. The total number of items for this

research variable was four.

3.3.4 Measurement of the dependent variable

Intentions to share knowledge

The items to measure the intentions to share knowledge were derived from the

study of Lin (2007). The total number of items for this research variable was

three.

Summarizing the measurement items, it can be stated that all of them were based

on prior literature. All of the items used for this study were also validated in

previous research. Nevertheless, most of them were reworded to fit the context of

this study. A detailed description of all the measurement items can be found in

Appendix A.

4. Results

In this chapter the results of the research will be presented. The first paragraph

(4.1), discusses about the demographics like age, sex and education, as well as

general output derived from the survey. The second paragraph (4.2) contains the

methods used to measure the variables for factor analysis and reliability analyses.

Finally, in the third paragraph (4.3), the results of the hypotheses testing will be

demonstrated, showing which hypotheses are supported and which have to be

rejected.

4.1 Demographics

131 of the total of 207 respondents were male with the remaining 76 to be female.

12 respondents indicated to have an age between 15 and 20 years. 52 respondents

we in the age group of 20 until 25 years old. The majority of respondents, 106 in

total, fall in the group of 25 until 30 years. 27 respondents were in the group

between 30 and 40 years, while the remaining 10 indicated to have an age

between 40-70 years, only 2 of whom were over 65 years. Furthermore, when

looking at the educational level, it can be stated that respondents were relatively

high educated. 40 percent of the respondents claim to have a master degree or

higher education. An almost equal number of respondents (41 percent) indicated

that they have a bachelor degree; while a 7 percent claim to have an HBO degree.

The remaining 12 percent have pointed one of the other educational levels (MBO,

VWO, HAVO, VMBO/ MAVO).

When analyzing the data of the survey, the results demonstrate that the majority

of the respondents (95.34 percent) are active online community users, 48 percent

of which are using it for longer than 3 years. A considerable amount of

respondents (27 percent) indicated that they have been online community site

users for 2-3 years, while a 19 percent fall in the category between 1 and 2 years.

151 respondents claim to be active users in Facebook, 150 in YouTube, 46 in

MySpace, 38 in LinkedIn, 35 in Twitter and 6 in Del.icio.us. A number of 28

respondents indicated to be active in another online community site, for example,

deviantART, Vimeo, Hyves and TVXS. In the question regarding which online

community site they visit the most, 110 respondents selected Facebook, 59

YouTube, 7 MySpace, 6 Twitter and 8 other than the aforementioned. The results

regarding the frequency of their favorite online community use is also interesting.

A 46 percent of the respondents use it more than once a day, a 33 percent daily, a

15 percent several times a week, and the remaining uses it between once a week

and less than once a week.

4.2 Validation of Measures

In order to measure the validity of our variables, construct validity has to be

checked, thus, convergent and discriminant validity is applied. “Convergent

validity determines with which comparable constructs the concepts correlates”

(Van der Velde et al., 2004, p.55). In contrast “discriminant validity indicates the

extent to which a given construct is different from other constructs” (Wasko and

Faraj, 2005, p.46). The measures of the constructs should be distinct and the

indicators should load on the appropriate construct. One criterion for adequate

discriminant validity is that the construct should share more variance with its

measures than with other constructs in the model (Barclay et al. 1995). In order to

test the data for discriminant and convergent validity, factor analyses have been

performed in SPSS.

The exploratory factor analysis (using principal axis factoring with Varimax

rotation) found a six-factor solution that explains 81.6 % of the total variance. The

six factors correspond exactly to the six constructs investigated in our study. In

addition, the factor loadings demonstrate that each indicator loads higher on the

construct of interest than on any other factor. According to Hair et al. (1998)

loadings of 0.40 and greater are considered important while if the loadings are

0.50 or greater, they are considered practically significant. Therefore, the higher

the loading, the more important it is regarded in interpreting the factor matrix

(Van der Velde et al., 2004).Moreover, as we observe the factor matrix (Appendix

B), CC3 seems to have high loadings on more than one factor. For example, in

factor 6 CC3 has a loading of .671, while in factor 2 has a loading of .416. However,

this item was not dropped because it is of importance for the content validity and

has a strong communality; 0.698.

Furthermore, the results of the factor analyses indicate that all of the items have

communalities above 0.50. According to Hair et al. (1998) communalities less than

0.50 should be identified as not having sufficient explanation. Table 1 summarizes

the results of the factor analyses presenting the communalities and factor loadings

of each item measured.

After assessing the validity of the items in the factor analyses, a Cronbach’s alpha

analysis was applied to test the items for reliability. Van der Velde et al. (2004, pp.

53) state that “Alpha is approximately equal to the mean correlation of all items

with each other”. Furthermore, the authors add that, for testing purposes, an

Alpha of o.60 is considered a minimum, 0.70 is acceptable and 0.80 or higher is

significant. Results showed significant Alpha values ranging from 0.835 to 0.936.

An extensive overview of the Cronbach’s Alpha analyses results can be found in

Appendix C.

Table 1: Results of the validity analyses

items communalities Factor

loadings

CC1 .665 .739

CC2 .613 .829

CC3 .698 .671

R1 .662 .762

R2 .759 .783

R3 .722 .845

EH1 .836 .845

EH2 .836 .831

EH3 .755 .745

REP1 .777 .811

REP2 .837 .872

REP3 .844 .866

IN1 .822 .896

IN2 .847 .919

IN3 .651 .808

PCPU1 .835 .911

PCPU2 .859 .922

PCPU3 .856 .920

PCPU4 .803 .900

4.3 Testing Hypotheses

Studies in information systems (e.g., Weill and Olson, 1989) and in other

disciplines (e.g., Jehn et al., 1999) have used moderated multiple regression to test

interaction effects. Moderated multiple regression is a hierarchical procedure that

first tests the relationship between independent constructs and the dependent

construct, and then tests the relationship between interaction terms and the

dependent construct (Stone and Hollenbeck, 1984). Interaction terms are

computed by multiplying two independent constructs. “A significant change in

explanatory power between the two steps, which can be assessed by looking at the

significance of the change in F value, indicates the presence of moderating effects”

(Kankanhalli et al., 2005a, pp.24).

Therefore, to assess the moderating effects of perceived power use a regression

analysis was conducted in which intentions to share knowledge was regressed

first onto perceived power use, commitment to community, reciprocity, enjoyment

in helping others and reputation. These variables had a satisfactory effect on

intentions to share knowledge; R² = .207; F (5, 310), p .000. The results of the

regression analysis show that commitment to community had a significant effect

on the intentions to share knowledge (β = 0, 19, p < 0.05) and reputation (β = 0.27,

p < 0.01), thus, supporting hypotheses H1a and H2b. Contrary to expectations,

reciprocity (β = 0.12, p > 0.05), and enjoy helping others (β = - 0.20, p > 0.05), had

no significant relationship with intentions to share knowledge. For this reason,

H1b and H2a were not supported.

A second regression was conducted that added four interaction terms, perceived

power use × commitment to community, perceived power use × reciprocity,

perceived power use × enjoyment in helping others and perceived power use ×

reputation, to the main-effects model. To alleviate possible collinearity problems,

the values of all constructs were centered (mean subtracted) during regression

(Aiken and West 1991). The results indicated that the change was significant (R² =

.358 and F =5, 778, p .000) in R² from the main-effects model to the full model (Δ

R2 .151, p .000) indicating that the moderating effects of perceived power use on

commitment to community, reciprocity, enjoyment in helping others and

reputation explained a significant amount of variance with respect to intentions to

share knowledge. Further, the beta coefficient for the perceived power use ×

enjoyment in helping others (standardized beta= –0.31) was significant (t = ––

2.354, p < 0 .05). Therefore, H3c was supported. Unexpectedly, the interaction

terms between perceived power use × commitment to community, perceived

power use × reciprocity and perceived power use × reputation had no influence on

the intentions to share knowledge. Hence, H3a, H3b and H3d were not supported.

Table 2 summarizes the results of hypotheses tests.

Table 2: Results of Hypotheses Testing

Intentions to share knowledge

β t-statistic

H1a commitment to community 0.19*

2.05

supported

H1b reciprocity 0.12 1.24 not supported

H2a enjoy helping others 0.078 0.771 not supported

H2b reputation 0.27** 3.02 supported

H3a PCPUCC - 0.05 -0.34 not supported

H3b PCPUR -0.11 - 0.76 not supported

H3c PCPUEH -0.31* –2.354 supported

H3d PCPUREP 0.06 0.55 not supported

*p < .05, ** p < .01

5. Discussion and Implications

The aim of this study was to identify the drivers of knowledge contribution by

users and to test the moderating effects of perceived power exercised by

moderators in online communities. To that end, we extended and empirically

tested a model of social capital and individual motivations based on Wasko and

Faraj (2005) and Wiertz and Ruyter (2007) as well as French and Raven’s

classification (1959). Given our research context, we focused our model on the

relationship between the relational dimension of social capital, individual

motivations and intentions to share knowledge, and then investigated the

moderating effects of perceived coercive power use of moderators on that

relationship. Our results clearly indicate that it is worthwhile to consider this

interaction effect, as evidenced by the significant improvement in the R² of the

intentions to share knowledge when the interaction term is added.

To begin with, contrary to Wasko and Faraj’s (2005) findings but in line with

Wiertz and Ruyter (2007) users who are committed to the online community have

greater intentions to share knowledge. This indicates that even though members

in online communities do not know each other offline, strong relationships

between individual members and to the collective as a whole develop. As a result,

users feel a relational bond with the community that encourages them to share

their information, ideas or experiences. This is even more the case in online

community sites like Facebook where users usually already know each other and

they are friends or acquainted with each other in the offline context.

Contrary to our expectations, reciprocity did not have a significant effect on the

intentions to share knowledge. This finding, even surprising, is in line with Wasko

and Faraj (2005) as well as Wiertz and Ruyter (2007). One possible explanation is

given by Wasko and Faraj (2005, pp.51) who state that “network-based

interactions may be generalized rather than dyadic, and direct reciprocity is not

necessary for sustaining collective action”. In contrast to personal exchanges

between two individuals where there is an expectation of direct reciprocity,

reciprocity in online communities may be generalized (Wasko and Teigland,

2002). Furthermore, the results from this study also provide weak evidence that

individuals who enjoy helping others have greater intentions to share knowledge,

as suggested by prior research examining electronic networks openly available on

the Internet (Kollock and Smith 1996). Our findings are in line with Wasko and

Faraj (2005) who also found a non significant relationship between intrinsic

motivations and knowledge contribution. One potential explanation of the weak

influence of intrinsic motivation and reciprocal relationships is the anonymous

nature of online communities as well as the existence of lurkers. According to

Wasko and Faraj (2005, pp. 37) “Knowledge contributors have no assurances that

those they are helping will ever return the favor, and lurkers may draw upon the

knowledge of others without contributing anything in return”. This sharply

contrasts with traditional communities and face-to-face knowledge exchanges

where people typically know one another and interact over time, creating

expectations of help and reciprocity that are enforceable through social sanctions.

Another result that deserves highlighting is the significant effect of reputation on

the intentions to share knowledge. These results are also consistent with prior

research in online settings, providing additional evidence that building reputation

is a strong motivator for active participation and knowledge contribution (Donath

1999). The above finding clearly indicates users’ perception that participation

enhances their reputation, thus, increasing their volume of contribution.

With regard to the moderating hypotheses, we find that hypotheses H3a, H3b and

H3d are not supported with the exception of hypothesis H3c. The relationship

between commitment to community, reciprocity, reputation and intentions to

share knowledge does not seem to be moderated by perceived coercive power use

even though a slight moderating effect is implied by the results. A possible reason

we came up with this finding lies in the anonymity of online communities and the

fact that the user even though is registered in the community with a specific name

and account, he can easily create a new one in case of potential conflict with the

moderator. Furthermore, another reason could lie in user’s mutual understanding

and the fact that in some online community sites they are bound together and

support each other, thus diminishing moderator’s influence. It might be the case

that in an organizational context, or in a professional electronic network of

practice, the moderating effect of perceived coercive power use is stronger than in

an online community site. In contrast, perceived coercive power use does

moderate the relationship between enjoyment in helping others and intentions to

share knowledge. As we expected, when moderators are perceived to use coercive

power, users tend to be more inhibited in what they express—they might keep

themselves from expressing their attitudes if such expression might provoke

conflict (Anderson and Berdahl, 2002). Therefore, the relationship between user’s

enjoyment in helping others and their intentions to share knowledge is weakened.

Our results have several interesting implications, both theoretical and practical.

The outcomes of this study demonstrate that the effect of perceived coercive

power use of the moderator does have a moderating effect on the relationship

between users’ individual motivations (e.g. enjoyment in helping others) and their

intentions to share knowledge. In the literature no preceding study was found that

examines this relationship in the context of online communities. Therefore, this

study has implications for other research in this field. The research model that was

developed in this study can be used to examine why people are or are not sharing

their information and what role moderators play in users’ willingness or

unwillingness to contribute to online communities. Given the demographics

presented, it can also be used to present a cultural driven approach to information

and knowledge sharing by focusing on users’ age, level of education or frequency

of online community visit. Taking the approach/inhibition theory emphasized in

this study, our model can also be a basis of an emotional driven understanding of

information sharing processes. Understanding and appreciating the role of human

emotion and its reaction to perceived power use is likely to be critical in moving

beyond information sharing to knowledge sharing because as Jarvenpaa and

Staples (2000, pp. 148) state “without people feeling that they are part of the

community that cares for them, they will not share their knowledge”.

From a practitioner standpoint, the results of this study indicate the circumstances

under which online community measures to promote knowledge contribution may

be more effective. These results offer suggestions to management about how to

promote online community sites by knowledge contributors. First, management

can raise the perceptions of commitment and reputation among valued knowledge

contributors by indicating to them that their knowledge contribution makes a

significant difference to the online community site. This can be done by

highlighting the improved community performance arising from their knowledge

contributions. Online community sites such as Amazon.com regularly recognize

their top reviewers, serving as a way to enhance their commitment and

reputation.

Furthermore, many companies launch online community sites as a marketing

channel. Thus, marketers should understand what drives people to share in the

online community context. The findings highlighted the importance of altruism

and individual reputation. Therefore, publicly praising individual participant’s

effort can enhance attitude toward online community sharing. Managers

interested in developing and sustaining knowledge exchange through online

community sites should focus attention on the creation and maintenance of a set

of core, centralized individuals by using extrinsic motivators such as enhanced

reputation to actively promote contributions to the network. As Wasko and Faraj

(2005, pp. 52) state “promoting individual reputations may also help signal the

potential quality of responses to novice participants and lurkers, making the

knowledge more accessible to all participants in the network”. Gaining status and

recognition in this way would motivate individuals to participate more (von

Hippel and von Krogh, 2003).

Community to community is important in online community sharing. Therefore,

online community-hosting service providers should promote and encourage

people to share their ideas, experiences and information or at least add comments.

Reward systems, such as keeping a billboard of top 100 posts, rewarding virtual

points for participations, etc. can also be a positive motivator. The more

information and comments posted and discussed, the longer users will stay in the

billboard. This will, in turn, establish a stronger sense of commitment to

community among participants. For example, the BlueShop community provides a

list of top knowledge contributors for each week and month, enhancing the

contributors' commitment to the community and also their reputation within the

community.

Finally, the findings underscored the importance of considering perceived power

use as a moderator, especially for intrinsic motivations on the intentions to share

knowledge. The fear of possible reprimands and punishment might prompt a user

to inhibit his attitudes towards knowledge sharing and at the same time reduce his

attachment to the online community site. In light of these effects and the

implications for moderator effectiveness, moderators should pay more attention

to how their power is perceived by users as well as carefully examine the trade-off

between short-term and long-term consequences of such perceptions.

5.2 Limitations and Directions for Future Research

Our findings can only be interpreted in the light of certain limitations. To start

with, from the findings of our sample demographics we can clearly see that most

of the respondents were in the age between 25 and 30, and the majority of them

were highly educated. This could mean that the sample could have more diversity

in age and level of education. Furthermore, while we have focused on the

relational social capital and individual attributes that seem particularly important

in the context of online communities, the structural and cognitive dimensions of

social capital and other individual difference variables are clearly important in

studying knowledge contribution. For example, several researchers have focused

on the role of generalized trust and identification with the group (e.g. Ridings et al.

2002) while Bock et al. (2005) highlight the importance of organizational climate

(e.g. fairness, affiliation, innovativeness) as a predictor of the intentions to share

knowledge.

Another limitation of this study is its focus on active users. In this research we did

not investigate individuals who read but do not post, e.g. lurkers, or members who

do not log onto online communities at all. Thus, the results may have been

impacted by self-selection bias. For example, individuals who had already ceased

to participate in online communities might have different perceptions about the

influence of moderators on their intentions to share knowledge, and so could have

been differently affected by them. For this reason, the results should be

interpreted as only explaining knowledge sharing of current knowledge

contributors of online communities.

Additionally, whether our findings could be generalized to all types of online

communities is unclear. Knowledge sharing in virtual communities of interest

might be different from that of online communities of practice or communities of

transaction. Therefore, further research is necessary to verify the generalizability

of our findings. Given these limitations, we strongly encourage others to examine

our findings through more rigorous research designs and across different national

cultures.

Finally, another limitation of this research comes from the fact that we focused

only on coercive power use from French and Raven’s classification (1959). Future

research could also examine moderators’ legitimate, reward, referent and expert

power on the intentions to share knowledge.

Overall, this study has provided useful information regarding the general

moderating effects of moderator power on user intentions to share knowledge.

Future research needs to seek a fuller understanding of how perceptions of

moderator power may influence user responses. There are a number of important

questions that remain unresolved. Are user perceptions of moderator power

influenced by critical incidents between the user and the moderator or by

observations of the moderator's dealings with others or both? How does online

community culture influence these perceptions of moderator power? Additional

empirical studies are required to address these questions and enhance our

understanding of this area.

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Appendix A

Survey

Based on a seven point Likert scale

Highly disagree

Disagree

Some disagreement

Neutral

Some agreement

Highly agree

Agree

� What is your gender?

� What is your age?

� What is your highest level of education?

� Do you make use of Online Community Sites like YouTube,

Facebook, LinkedIn or Twitter?

� On which of the following Online Communities are you active?

� What is the Online Community Site you visit the most?

� How long are you an Online Community Site user?

� What is the frequency of your Online Community Site use?


CC1: The relationship I have with the community is something to which I

am very committed

CC2: The relationship I have with the community is one I intend to maintain

indefinitely

CC3: The relationship I have with the community deserves my effort to

maintain

Reciprocity

R1: When I receive help, I feel it is only right to give back and help others

R2: When I share ideas, experiences and information, I expect to receive

ideas, experiences and information in return when necessary

R3: The principle of give and take is important for me in the community

Enjoyment in helping others

EH1: I enjoy sharing my ideas, experiences and information with others in

the community

EH2: Sharing my ideas, experiences and information with others gives me

pleasure

EH3: It feels good to help others by sharing my ideas, experiences and

information

Reputation

REP1: I earn respect from others by participating in the community

REP2: Participating in community's activity enhances my personal

reputation

REP3: I feel that participating in online discussions improves my status in

the community

Perceived Coercive Power Use

PCPU1: makes things unpleasant here

PCPU2: makes Online Community Site unattractive

PCPU3: has an undesirable impact on my willingness to contribute my

ideas, experiences and information

PCPU4: makes difficult for me to participate in online discussions

Intention to share knowledge

IN1: I intend to share my ideas, experiences and information with others

more frequently in the future

IN2: I will always make an effort to share my ideas, experiences and

information with others

IN3: I intend to share my ideas, experiences and information with members

who ask

Appendix B

Factor Analysis (Varimax Rotated):

Rotated Component Matrixa

Component

1 2 3 4 5 6

CC1 .067 .257 .295 .233 .095 .739

CC2 -.056 .168 .220 .177 -.066 .829

CC3 .081 .416 .260 .189 -.075 .671

R1 -.083 .151 .762 .240 -.061 .211

R2 -.022 .254 .783 .203 -.038 .307

R3 .073 .159 .845 .225 .036 .165

EH1 .043 .228 .260 .845 .049 .134

EH2 .002 .339 .142 .831 .063 .251

EH3 .068 .165 .375 .745 -.013 .200

REP1 -.071 .811 .280 .280 .058 .156

REP2 -.055 .872 .157 .195 .043 .229

REP3 .025 .866 .134 .202 .091 .245

IN1 .029 .107 -.003 -.005 .896 -.117

IN2 .006 .006 .014 .017 .919 -.042

IN3 .038 .026 -.049 .057 .808 .115

PCPU1 .911 -.008 .003 .024 .071 .007

PCPU2 .922 .001 -.087 .024 .022 .025

PCPU3 .920 -.065 -.039 .045 .010 .066

PCPU4 .900 .006 .111 -.004 -.019 -.053

Extraction Method: Principal Component Analysis.

Rotation Method: Varimax with Kaiser Normalization.

a. Rotation converged in 6 iterations.

Appendix C

Reliability analyses

Commitment to community:

Item-Total Statistics

Scale Mean if

Item Deleted

Scale Variance

if Item Deleted

Corrected

Item-Total

Correlation

Cronbach's

Alpha if Item

Deleted

CC1 7.48 9.465 .732 .789

CC2 7.18 10.282 .717 .802

CC3 7.20 10.218 .726 .793

Reliability Statistics

Cronbach's

Alpha N of Items

.853 3

Reciprocity:


Scale Mean if

Item Deleted

Scale Variance

if Item Deleted

Corrected

Item-Total

Correlation

Cronbach's

Alpha if Item

Deleted

R1 8.99 11.458 .727 .865

R2 9.55 10.975 .792 .809

R3 9.28 10.559 .785 .814


Cronbach's

Alpha N of Items

.880 3

Enjoyment in helping others:


Scale Mean if

Item Deleted

Scale Variance

if Item Deleted

Corrected

Item-Total

Correlation

Cronbach's

Alpha if Item

Deleted

EH1 9.33 10.483 .851 .861

EH2 9.51 10.382 .862 .851

EH3 9.24 10.634 .777 .922


Cronbach's

Alpha N of Items

.915 3

Reputation:


Scale Mean if

Item Deleted

Scale Variance

if Item Deleted

Corrected

Item-Total

Correlation

Cronbach's

Alpha if Item

Deleted

REP1 6.75 13.212 .833 .919

REP2 6.68 12.254 .881 .880

REP3 6.88 12.359 .860 .897


Cronbach's

Alpha N of Items

.931 3

Intentions to share knowledge:


Scale Mean if

Item Deleted

Scale Variance

if Item Deleted

Corrected

Item-Total

Correlation

Cronbach's

Alpha if Item

Deleted

IN1 9.33 7.990 .749 .722

IN2 9.19 7.507 .768 .699

IN3 7.89 8.727 .583 .880


Cronbach's

Alpha N of Items

.835 3

Perceived coercive power use


Scale Mean if

Item Deleted

Scale Variance

if Item Deleted

Corrected

Item-Total

Correlation

Cronbach's

Alpha if Item

Deleted

PCPU1 10.38 23.269 .851 .916

PCPU2 10.51 23.258 .862 .913

PCPU3 10.48 22.448 .859 .914

PCPU4 10.74 23.103 .825 .925


Cronbach's

Alpha N of Items

.936 4

Documents

Power and Perceived Power Use by Moderators in Online Communities