Performance Management within Social Network Sites: The Social Network Intelligence Process Method

Performance Management within Social Network Sites: The Social Network Intelligence Process Method

Michel Wasmann, Marco Spruit
Copyright: © 2012 |Pages: 15
DOI: 10.4018/jbir.2012040104
OnDemand:
(Individual Articles)
Available
$37.50
No Current Special Offers
TOTAL SAVINGS: $37.50

Abstract

The huge amount of data and complexity of decisions in the current information age requires decision makers to utilize information analysis tools for supporting business decisions. This is also the case for social network sites which control huge amounts of data just waiting to be transformed from information to valuable knowledge through Business Intelligence methods. These techniques are not yet widely in use within companies whose core business revolves around user generated content. This research conducts a qualitative research to provide more knowledge and a deeper understanding of a Business Intelligence approach which supports the business model of companies exploiting a Social Network Site. Available Business Intelligence process models do not take the organizational aspects into account as continuous process improvement elements. Therefore, this work proposes the new method: the Social Network Intelligence Process (SNIP) Method. The SNIP Method and its related management information items were validated through a series of expert interviews and an in-depth single case study at the leading Dutch social network site.
Article Preview
Top

The Information Gap Within Social Network Sites

The number of social network site users is still increasing rapidly with over two-thirds (67%) of the global online population having visited a Social network site. Therefore, the amount of user generated content is increasing as well (ComScore, 2009; Nielsen, 2009). The aim of Social network sites is to share personal information, have fun and to keep in touch with friends. This paper uses the definition from Boyd and Ellison (2007) in which Social network sites are defined as web-based services that allow individuals to (1) construct a public or semi-public profile within a bounded system, (2) articulate a list of other users with whom they share a connection, and (3) view and traverse their list of connections and those made by others. A huge amount of user generated content is stored within the databases of Social network sites. Nevertheless, they are not using all the information that can be extracted from the available data because a proper overview and in-depth insight are missing. The increased information overload makes it more and more difficult and time consuming to identify relevant information for decision purposes (O'Reilly, 1980). This is a missed opportunity for Social network sites dealing with user generated content and not effectively exploiting that abundance of contextual information. The huge amount of data and complexity of decisions in the current information age, requires decision makers to utilize information analysis tools for supporting business decisions (Nemati et al., 2002; Turban et al., 2007). The need for fast decision making on the one hand, and the longer time needed to acquire the right information on the other hand causes a so-called “information gap” (Den Hamer, 2005). The data within the social network’s databases can be transformed from information to valuable knowledge with the aid of Business Intelligence (BI) to gain a competitive advantage (Porter, 1985). However, BI is not widely used within companies whose core business revolves around user generated content. Moreover, scientific literature at the intersection of social network sites and BI is only scarcely available (Punie, 2008). This paper therefore uses the definition and confirms the view of Osterwalder and Pigneur (2002) who place the business model between the strategy (strategic view) of a company and the process (operational view). They state that a business model is a “conceptual and architectural implementation (blueprint) of a business strategy [that] represents the foundation for the implementation of business processes and information systems”.

By conducting a qualitative research consisting of a literature study, interviews and a case study, this paper provides more knowledge and a deeper understanding of Business Intelligence methods to support social network site business models through the introduction of the Social Network Intelligence Process (SNIP) Method which appropriately aligns these aspects. This work is, therefore, centered around the following research question:

“In which way can Business Intelligence support the business model of companies that exploit social network sites?”

Complete Article List

Search this Journal:
Reset
Volume 15: 1 Issue (2024): Forthcoming, Available for Pre-Order
Volume 14: 1 Issue (2023)
Volume 13: 1 Issue (2022)
Volume 12: 2 Issues (2021)
Volume 11: 2 Issues (2020)
Volume 10: 2 Issues (2019)
Volume 9: 2 Issues (2018)
Volume 8: 2 Issues (2017)
Volume 7: 2 Issues (2016)
Volume 6: 2 Issues (2015)
Volume 5: 4 Issues (2014)
Volume 4: 4 Issues (2013)
Volume 3: 4 Issues (2012)
Volume 2: 4 Issues (2011)
Volume 1: 4 Issues (2010)
View Complete Journal Contents Listing