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Dynamic perspectives on social characteristics and sustainability in online community networks
Abstract Online community networks can help organizOnline community networks can help organizations improve collaboration. However, in spite of their potential value, there has been little empirical research into two important network factors that determine their success: social characteristics of users and changes in operations that result from network evolution. Our research addresses these deficiencies by using a cultural framework. Derived from anthropology, it extends previous system dynamics research on online community networks. The framework acts as a lens, enabling a better understanding of the effects that changes in these factors bring to online community networks. Using data collected from Wikipedia for model calibration, our findings suggest that, contrary to conventional wisdom, removing policies that focus on building group commitment does not lower performance. The results also show that online networks need structural control, otherwise their attractiveness, credibility and, subsequently, content value might all decrease. To ensure sustainability the network must be monitored, especially during the early stages of its evolution, so that rules and regulations that ensure value and validity can be selectively employed. and validity can be selectively employed.
Added by wikilit team Added on initial load  +
Collected data time dimension Longitudinal  +
Comments Research design is systems dynamics
Conclusion Our research seeks to bridge this gap by iOur research seeks to bridge this gap by integrating a cultural framework, derived from anthropology, to determine the effects of structural interventions in an online social network. The grid/group framework may also help in developing an understanding of how policy interventions affect the social dimension of the network, as well as how to align organizational characteristics with personal attributes. However, the use of a cultural typology for organizational analysis has an implicit limitation: culture, a multifaceted construct, cannot be easily captured by a two-dimensional typology, or any other simple framework for that matter (Sackmann, 1992). The grid/group typology too has only limited explanatory power. A number of tangible and timely recommendations emerge from the simulation experiments that evaluate policy options. Some insights contradict our initial expectations about policies that would help establish a sustainable online community network. For example, counter to our beliefs, policies aimed at building group commitment might not achieve the desired result. We attribute this behavior to changes in the social characteristics of the network, i.e., lowering group commitment results in losing people who look for hierarchy and group commitment, while gaining people with a high degree of self-responsibility. These two quadrants (“hierarchy” and “individualism”) represent what is known in the grid/group typology as the “stable axis” (Thompson et al., 1990). Changing the social characteristics in these two quadrants may affect the stability of the network. It is therefore suggested that an online social network focusing too much on group commitment might not achieve sustainability. On the other hand, the simulation experiments supported our proposition that online networks need structural control. Having no control decreases attractiveness, credibility and, subsequently, content volume. An implication for an actor in a real system is to carefully monitor the growth of the network in the early stages and then impose rules and regulations as soon as the network begins to grow. While an open environment accelerates the growth of an online network at the early stage, openness may negatively impact quality and subsequently the attractiveness of the network, so that users will be less inclined to join or to participate in the network. The findings of our study have practical implications that can be used in corporate settings, given that at the core of an online network are social dimensions. Network operators can use our model to assess how structural interventions shape online network growth and what policies must be in place to achieve sustainability.ust be in place to achieve sustainability.
Data source Simulation results  + , Wikipedia pages  +
Doi 10.1002/sdr.403 +
Google scholar url  +
Has author Peter Otto + , Martin Simon +
Has domain Information systems +
Has topic Community building + , Policies and governance +
Issue 3  +
Pages 321-47  +
Peer reviewed Yes  +
Publication type Journal article  +
Published in System Dynamics Review +
Research design Mathematical modeling  + , Simulation  +
Research questions Our goal is to extend previous research byOur goal is to extend previous research by integrating a social framework and to use a system dynamics (SD) model with which we can test and better understand the effects of interventions, particularly structural interventions, as organizations establish an online community. The conceptual framework we use is based on the notion that, at its core, a social network is a collection of individuals who have different motivations for participating in the online community. We build on the work of Wasko and Faraj (2000), Gu and Jarvenpaa (2003), and Subramani and Peddibhotla (2003). They suggest that altruism and reciprocity appear to drive motivation for online participation. We add the notion proposed by Thompson and Wildavsky (1986): social factors, such as beliefs and values, might also greatly determine whether and the extent to which individuals participate in online social networks. To differentiate among the many different personalities that participate in online social networks, we employ the grid/group typology (Douglas 1970, 1978). This typology groups people to four distinct categories, based on attitudes, beliefs and values (Figure 1). This enables us to assess the role of social factors in explaining how people interact and support online social networks, and how various structural interventions might influence participant attitudes and behavior. Following a description of the grid/group typology, we present a conceptual framework of a social network, which we then translate into an SD model. Our results show that, to function effectively as an online community, groups need structural parameters to adhere to but, if there is an imbalance in any one direction, i.e., too much or too little control, the network is likely to experience decay.the network is likely to experience decay.
Revid 11,256  +
Theories As stated earlier, our aim is to develop aAs stated earlier, our aim is to develop a theory of how social networks respond to interventions, and to assess whether our structural theory, derived from the literature, is adequate to replicate observed behavior. While a simulation model should replicate real-world behavior, it is, at the same time, a lens through which the modeler views the environment. Diker (2003, 2004) shows similar feedback effects in his theory of open online collaboration. For example, the positive feedback loop through which users add to the content collection and the negative loop where “density of quality problems” affects the number of users. While previous research focused on the interrelationship between a network and its host organization, and on the interaction around these structures (Kunda, 1992; Contu and Willmott, 2003; Thompson, 2005), we extend the boundary for our simulation model but also use an aggregated perspective. As we build an SD model to test theories about the dynamics of interventions in an online network, we aggregate from an individual to a group level, following the Douglas grid/group typology. Our model consists of the following clusters (or accumulations) of people: (1) administrators (people who control the content of submitted articles and maintain network quality); (2) users (people who use the network); and (3) active Wikipedians (people who contribute articles regularly to build collective knowledge). This paper is based on a dynamic theory to help develop an understanding of how structural interventions affect the sustainability of an online network. The task remains, however, to establish reliable, valid and distinctive measures for the social dimensions of the grid/group typology and to empirically assess the simulation model. Given the growing importance of online social networks to facilitate information exchange, and given the small number of system dynamics models that have addressed the dynamic nature of online networks over the years, we believe that the SD community can and must contribute to this research agenda.d must contribute to this research agenda.
Theory type Design and action  +
Title Dynamic perspectives on social characteristics and sustainability in online community networks
Unit of analysis Article  + , Edit  + , User  +
Url  +
Volume 24  +
Wikipedia coverage Sample data  +
Wikipedia data extraction Live Wikipedia  +
Wikipedia language English  +
Wikipedia page type Article  + , Collaboration and coordination  +
Year 2008  +
Creation dateThis property is a special property in this wiki. 15 March 2012 20:26:13  +
Categories Community building  + , Policies and governance  + , Information systems  + , Publications  +
Modification dateThis property is a special property in this wiki. 30 January 2014 20:23:21  +
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