Active and passive users of customer forums and communities

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The problem of free riding
Community user types research
Motivational theories according to:
User types research
Social science theories
The influence of self-efficacy, need-to-achieve and intrinsic motivation as triggering personality characteristics
Innovativeness and identity expressiveness as main involving factors
Practical strategies and tools for motivating participants to take part in online communities
Usage of strategies and tools illustrated with «Nike» online customer community

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Active and passive users of customer forums and communities






    1. Introduction
    2. The problem of free riding
    3. Community user types research
    4. Motivational theories according to:
    1. User types research
    1. Social science theories
    2. The influence of self-efficacy, need-to-achieve and intrinsic motivation as triggering personality characteristics
    3. Innovativeness and identity expressiveness as main involving factors
    1. Practical strategies and tools for motivating participants to take part in online communities
    1. Usage of strategies and tools illustrated with «Nike» online customer community
    2. Conclusion
    3. References



1. Introduction

According to the Pew Internet research in 2007 approximately 70% of American adults used the Internet. 84% of them (about 90 millions Americans) participated in online groups and communities (Pew Internet 2007). These types of social media are used by the general public to discuss hobbies, sports, politics, finances or other topics of interest, leverage social networks, exchange technical information and social support, build collaborative artifacts, conduct business transactions or play games. By business they are necessary to exchange information with customers and suppliers, to improve operations internal by providing repositories of professional and technical information, communication spaces among employees, and platforms for new businesses (Ren and Kraut 2007).

Although many online communities are highly successful, many others fail. For example, the LV community (, which has over 7,500 members but less than 5 posts in one week, approximately 3 of which are from the community manager (R. Millington, FeverBee online community consultancy statistics 2010). This is only one illustration of great number of failing online communities. The vast majority of them have only a handful of members and no activity. Across a wide range of groups, more than 60% of the newcomers who post a message in any given month are never seen again (Arguello 2006).

The issue of passive usage is also called as a «problem of free riding». This paper explains this problem and summarise existing economic, behaviorial and social theories, which try to give an answer to one living question: «How to make passive users active?».


2. «The Problem of Free Riding»

The main problem of passive use is also called «The problem of Free Riding» (Hoisl 2007). Since information in online community is treated like public good and the users are not charged in proportion to their use, it appears rational for people to view communities without contributing. That happens because participation in an online community generates costs to a user. Therefore, it is easier for her/him to only consume the good provided (information) and not to take part in the process of generating it. So, the user gets something for free – she/he does not need to give anything in return. The only costs for free riders are charges for the Internet connection and their time spent to search for the desired information (Hoisl 2007). If all users are acting as free riders, online communities would not have any produced information, thus making this online community obsolete.

The main question of this paper is: How can users be motivated to contribute to an online community and do not only free ride? There have to be certain incentives which generate a surplus and motivate users to participate actively.


3. Community user types research

Initially not all users act passive. Community participants can be devided in several groups according to their personality, needs, topic attraction, knowledge and many other factors. All of these roles are important, because knowing the segmentation of users, their main purposes and characteristics, it might be easier to motivate them using different triggers.

In general it can be emphasized four major kinds of users (Tedjamulia, Olsen, Dean, Albrecht 2005). The first and most prevalent type of participant browses online communities and consumes information but does not contribute. The second type of participant is the one who does not find the specific type of information he or she needs and don’t dare to ask the community a specific question. These two types of participants are called “lurkers.” Several online community observations have indicated that lurkers represent 80–90% of an online communities population (Nonnecke, Preece 2001). Lurkers play a key role in the value provided by online communities by consuming useful information. Moreover, usually they ask questions that trigger contributions from others.

The third type of participant is one who not only browses and asks questions, but who is daring enough to respond to other members’ questions, engages in some social interaction, and makes some intelligent distinct contributions. The final type of participant can be considered an online community veteran who has formed strong ties to the community, is part of an established social network, makes more elaborate comments, asks thought-provoking questions, answers complex questions, and is an active participant in community activities. This type of participant is the individual responsible for making the majority of contributions and is a firm participant in the online community. His or her contributions are the primary reason lurkers become interested in the site and decide to contribute (Nonnecke, Preece 2001).

Some other authors also emphasize such types of users like newbies, who represent new community participants, spammers, who usually post the same things without sense, flamers and many others depending on type of social media (Hoisl 2007).


4. Motivation theories

From an economic point of view it can be said that to motivate a user the expectation of reward must be greater than the expected effort (Hoisl 2007). A user has to think subjectively that her/his reward will be greater than her/his effort. Every user has her/his own preferences of rewarding methods. «For a billionaire money will be less motivating than for a beggar». So besides the economic point it has to be stuck to social rewarding methods and psycology.

This chapter summarises different kinds of motivation theories that are represented in literature and articles. Considering all of them passive users may be differently motivated according to above mentioned user types research, social science theories, the influence of self-efficacy, need-to-achieve and intrinsic motivation as trigger personality characteristics and innovativeness and identity expressiveness as main involving factors.


4.1. User types research

Combining the user types research has found that lurkers are attracted to online communities because of their desire for information that is credible, relevant, and easy to find (Preece 2000). They also seek opportunities to broaden their contacts and viewpoints. Enjoyment derived from sociability and interaction with others is an additional benefit from participation. Contributors enjoy the same benefits as lurkers but are more strongly motivated to contribute, both intrinsically and extrinsically. Intrinsic motives for contribution include community citizenship, generalized reciprocity, moral obligation, and pro-social behavior (Tedjamulia, Olsen, Dean, Albrecht, 2005). In addition to altruistic motives, research has shown that in some cases, extrinsic motivation plays a role. Some studies (Tedjamulia, Olsen, Dean, Albrecht, 2005) have found that some contributors are motivated by self-interest or self-benefit, although research has not found this to be the dominant motivation in the majority of cases.

Several studies have identified stable individual differences in the extent to which people think online behavior is fun. For instance, posters enjoy online interaction more than lurkers do (Preece et al. 2004).


4.2. Social science theories

The second part of analysis is already based not only on users segmentation, but on assumption that users in the model are animated using principles derived from a set of well-established social science theories: the collective effort model of contribution to small groups, theories of group identity and interpersonal bonds as the basis of commitment to groups, information overload theory, and public goods theory from economics (Ren, Kraut 2007). Synthesizing multiple theories also enables us to examine the multiple paths through which a design choice may affect members’ motivation. It also enables us to understand the complex, reciprocal interdependencies between member behaviors and community dynamics as a community develops and evolves over time. A design choice has both immediate, first-order effects (e.g., identifying members increasing their contributions) and longer-term, second-order effects (e.g., members’ contributions increasing information overload and driving members away).

Let’s get closer to all the listed approaches. In many online communities, a small proportion of members often engage in altruistic behaviors such as answering questions, or performing community maintenance tasks such as promoting and policing the site. According to the collective effort model, social loafing in a group is greatly reduced when people perceive group tasks as interesting or when they identify with the group or like other members. Therefore, increasing the homogeneity among group members may cause some members to contribute more to help similar others whom they like. However, the collective effort model also proposes that people will contribute more to a cause they believe their efforts are needed for group success. As a result, they may contribute less in a homogeneous group because they feel their efforts are redundant.  In other words, the collective effort model suggests that members are less willing to contribute if they believe that other group members are already contributing or if the group is large. Public goods theory also suggests less contribution as group size grows (Ren, Kraut 2007).

Prior literature shows that both identification with the group as a whole (i.e., a sense of belonging) and interpersonal bonds with particular members (i.e., friendship) can lead members to become committed to groups. Social identity theory also suggests that assigning a member to a group, the presence of an out-group, and similarity among group members all lead to stronger attachment to the group.

Small groups research suggests that repeated interactions lead to interpersonal attraction; as the frequency of interaction between two persons increases, their liking for one another also increases. Moreover, getting a quick reply after posting seems to encourage members of an online community, especially newcomers, to return and participate in community discussion (Kraut et al. 2007).

One more kind of motivation that leads people to join online communities is recreational, that is, the enjoyment they derive from reading and posting online. People are also motivated to contribute to online communities by the reputation they gain by doing so. Many online communities play on this motivation by institutionalizing “leader boards” and other devices that show the most active contributor.


4.3. The influence of self-efficacy, need-to-achieve and intrinsic motivation as triggering personality characteristics

The third part of this chapter is based on Tedjamulia, Olsen, Dean, Albrecht research (2005). The purpose of the study was to assess the influence of three personality characteristics on users behaviour. First characteristics is self-efficacy. It is defined as «an individual’s perceived probability that he or she will attain a goal». Significant evidence indicates that self-efficacy is positively correlated with cooperation: people with higher self-efficacy cooperate more. Online community literature specifically mentions three forms of self-efficacy and how they influence an individual’s desire and commitment to contribute. The first type of online community efficacy is technology efficacy: individuals who are more comfortable with technology will contribute more. The second type of online community efficacy is information efficacy. Information efficacy is the belief that the information an online community member knows will be helpful to the community. People who believe they possess valuable information will contribute more. The final type of efficacy is connective efficacy, and this type of efficacy is described as the belief that content that is contributed will be received by the online community members. Members that have higher connective efficacy will contribute more.

The second characteristics is called «need-to-achieve». Psychology and organizational behavior research explain that people have different achievement needs. Researchers have found that subjects with higher achievement needs set higher goals and perform better than those with lower achievement needs. Online community members who have a greater need – to achieve consider their contributions or participation to be important, and they find it enjoyable to work hard, to be compared to a standard, and to be challenged. They feel the need to establish themselves as experts and excel above others.

Online community theorists and knowledge-management researchers have suggested that online communities should focus on individuals with a high need to achieve, since these members will dedicate the most time to helping the community through contribution and participation.

Third specification is intrinsic motivation. Intrinsic motivation refers to doing something because it is inherently interesting or enjoyable. Online community members who are intrinsically motivated are willing to work harder, are more committed, and are motivated by the act of participating and not by external controls or incentives.


4.4. Innovativeness and identity expressiveness as main involving factors

The purpose of the next study was to assess the influence of two personality characteristics, innovativeness and identity expressiveness (self-identity expressiveness and social identity expressiveness), on passive and active use of social networks (Pagani, F.Hofacker, E. Goldsmith 2011). Both constructs were hypothesized to be positively related to active social network use. The results supported these hypotheses. As levels of innovativeness for social networks increased, passive and active use increased, suggesting that innovative users are more likely to use and contribute to these sites. Likewise, it appears that as users’ motivation to express their self or social identities increases, contributions also increase.

People differ in how innovative they are with regard to new stimuli. In the case of social networks, people clearly vary in how interested they are and how eager they are to use them. Knowledge of social networks is also positively associated with use. It was found that it is those users who understand what social networks are all about, how they can be used, and what benefits they bring that are most likely to use them and, more importantly, to contribute to them. This finding is consistent with other studies of innovative consumer behavior that show that the earliest buyers of new products are unique in that they are interested in the product category, knowledgeable about it, want to try the newest things, and tend to be heavy users of the category (Goldsmith, 2000). Thus, the findings suggest that if managers can identify the more innovative users among the social network citizenry, they can encourage them to join and then actively contribute. Given the innovators’ knowledge and interest in the topic, perhaps this encouragement might take the form of providing new topic-relevant information or opportunities to contribute that the innovators can take advantage of. Topic-relevant rewards for contribution might also encourage innovators to increase their contributions. These rewards might be low in cost but meaningful if the innovators themselves suggest them. Active content production is also likely to be produced by those with high tendencies for self-expression.


5. Practical strategies and tools for motivating participants to take part in online communities

Despite all the peculiarities of users personalities prior literature highlights some general strategies, which can lead to involving more participants to active usage. The summary of these recommendations based on Waterson research (2006) is represented below.

First rule for community owners is to provide content at the launch of the community. This is one of the most important strategies. Without content, an online community is largely redundant. Content might be in the form of reports, lists of FAQs and a regular newsletter, which “kick starts” the community and helps to create at least passive use. Active use is more likely to occur when other functionality is added at a later stage.

Second rule sounds like “Stage the roll-out of the community and plan ahead”. Most of the literature on online communities mentions designing communities for later evolution and development; however, very often providing too many facilities or being too ambitious (e.g., expecting users to be active from the start) proves to be common and leads users to visit only once and then rarely return. Each phase of the community should be planned; this should cover questions such as: What extra facilities could be added? What do new users require? What has proved to be less successful than expected? Where is the most activity in the community located?

Community should be always moderated. Alongside some initial content, the community will need someone to moderate and make sure requests are answered promptly and new information is posted as soon as it becomes available. Moderating a community requires a lot of effort, however, it pays off in terms of establishing the community.

Community should be monitored and evaluated over time. Monitoring the activity within the community means more than keeping track of usage statistics and profiles. It also means regularly asking what members require, as well as how generating debate by posting topical material and/or questions on message boards, weblogs and so forth works.  Regular updates of material similarly make the site more interesting and increase the likelihood of occasional visitors becoming regular and active users.

It is also important to take account of the domain and context of use. The core domain of the community can make a big difference to the type of motivation community members have. In this case, the passive/active distinction may be important. Transforming passive users into active users may in some cases be in vain, particularly where the primary motivation of users is information retrieval. Similarly, evaluating how the community changes over time will help to determine what further strategies are appropriate in order to sustain continued use and satisfy the motivations of users.

Next rule is to encourage users to tailor their own functionality. It may be useful to encourage users to implement their own ideas for the community. This could partly be achieved by exploiting the many open-source tools.

With the help of tools owners and moderators of communities can attract passive users (Hoisl 2007). For example, “social rewarding techniques”. It can be creating an overall listing of top contributors (like a ranking of authors with the most posted articles or with the most articles edited) or credit point systems. There are many actions for which a user can receive positive or negative credit points. If a community implements a credit point system, it is obvious to show a sorted list of users with the highest amount of credit points. A hierarchical structure could be implemented, thus giving the most active users more privileges. Other tools are survey systems and recommendation systems, which pose programs which attempt to predict items that a user may be interested in based on some information about the user’s profile.

There are plenty of various tools and techniques in literature and almost all of them can be illustrated with Nike Online Community example.


7. Usage of strategies and tools. «Nike» online customer community

Nike’s approach to attract new Nike+ consumers is a social networking Web portal created for people who enjoy running and socializing with others who run. The community is aimed at enthusiasts and casual runners rather than experts, with the goal of growing the number of runners and the miles they run, with the eventual outcome of selling more shoes.

This website represents a perfect example of using tools and strategies to involve participants in contribution of information. Users are able to upload their running results to the portal. This allows them to check their own progress or compare results with friends. At the same time they get training advices and useful information. There are no conditions or payments. Runners open discussions, share results and music, take part in online competitions, get points for best attainments etc. All these interactions provided by moderators build an excellent actively using portal. Of course, mostly people themselves have high need-to-achieve and are intrinsic motivated to gain success in sport, but the environment of community is created perfectly. It has proved a very effective way to build loyalty.

Making users active has not only entertaining angle, it also yields big profit to the company. Nike+ was launched in 2006, and within a year 500,000+ runners from 160+ countries had signed on. By Aug. 2009, over 1.3 million runners had uploaded more than 150 million miles on Nike+ (D. Hambleton 2011).


7. Conclusion

Online forums and communities represent an ecology of different personality types creating and consuming content. Such networks are not homogeneous and each participant is likely to react differently. Therefore the most important goal for community owners and moderators is to create the right environment. In this paper was represented only a brief overwiev of existing tools and strategies to reach this goal, however there is still a great field for research. Taking into account the endless number of distinctions between personalities in relation with their psychological, economical, educational and many other differences it is not easy to treat all participants rightly, but with highly developing technologies and further studies it is possible to be closer to success and make more passive users active.

8. References:

  1. Patrick Waterson (2006). Motivation in Online Communities. Encyclopedia of Virtual Communities and Technologies, 334-337.
  2. Arguello, J., Butler, B., Joyce, E., Kraut R., Ling, K, Rosé, C., and Wang, X (2006). Talk to me: foundations for successful individual-group interactions in online communities. ACM Press, 959-968.
  3. Margherita Pagani, Charles F. Hofacker and Ronald E. Goldsmith (2011). The Influence of Personality on Active and Passive Use of Social Networking Sites. Psychology & Marketing, Vol. 28(5): 441–456.
  4. Satish Nambisan and Robert A. Baron (2009). Virtual Customer Environments: Testing a Model of Voluntary Participation in Value Co-creation Activities. The Journal of Product Innovation Management, 26: 388 – 406.
  5. Bernard Hoisl (2007). Motivate online community contributions using social rewarding techniques. Master Thesis.
  6. Yuqing Ren, Robert E. Kraut (2008). A Simulation for Designing Online Community: Member Motivation, Contribution, and Discussion Moderation.
  7. Steven J. J. Tedjamulia, Douglas L. Dean, David R. Olsen, Conan C. Albrecht (2005). Motivating Content Contributions to Online Communities: Toward a More Comprehensive Theory.
  8. B. Nonnecke and J. Preece (2001). "Why lurkers lurk" presented at Proceeding of Seventh Americas Conference on Information Systems, Boston.
  9. Story L. The New Advertising Outlet: Your Life. The New York Times, Oct. 14th 2007.
  10. R. Millington (2010). FeverBee online community consultancy statistics.
  11. Pew Internet statistics.

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