Social media has been widely adopted as a useful business tool, especially in the domain of business to consumer marketing. However, the deployment of social media tools to business processes is hindered by the lack of concrete indicators of the effects its use has on the business process. Computer based modeling has been widely used to simulate and predict business effects in other streams of study, but relatively little in the evaluation of social media impacts. This paper argues that System Dynamics and Agent-Based Modeling have been and should be utilized in measuring social media and its impacts in business context in general, as well as in the context of business ecosystems. The authors review the current state of the use of these simulation methods in the evaluation of social media business impacts by conducting a systematic literature review.
TopIntroduction
There is a body of existing scientific research on the effects of social media use in a business setting. For example, in marketing literature the biggest obstacle in deploying social media to business processes is often viewed to be the difficulty to demonstrate its effects and return on investment. According to Fisher (2009) the lack of indicators of potential benefits and expected return on investment slows down or hinders the adoption of social media as a part of a company’s marketing strategy. In addition, the ability to show measurable effects in other business functions would be beneficial. According to Jussila et al. (2014), the adoption of social media in business-to-business companies is restricted by the difficulty to show and assess the business benefits. They state that effective means and models to measure and demonstrate the benefits of social media use would be beneficial. Also Aral, Dellarocas, and Godes (2013) emphasize in their framework for the research of social media that the measuring of the effects of social media use on the individual level, platform level and company level is ranked as one of the major goals for new social media research.
This paper aims to answer how system dynamics and agent-based modeling has been used in the past to measure the effects of social media use and what possibilities could it offer for measuring social media and effects of its use in business ecosystems. Of the possible modeling methods, agent-based modeling (ABM) and system dynamics modeling (SDM) have been chosen for this review, because they are especially well suited for modeling complex social systems, and are quite well established methods for research in the scientific community. By carrying out a systematic literature review on the subject, we aim to give a comprehensive picture of the current state of modeling applications that provide various solutions to the challenges posed by the measuring and demonstrating the business effects of social media use by traditional methods.
The main research problem of this review is ”Do agent-based and system dynamics modeling offer useful ways to measure social media and effects of its use in a business context?”. This paper aims to resolve this problem by answering these research questions:
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RQ1: In which ways have ABM and SDM been used to measure the impacts of social media use?
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RQ2: Why have ABM and SDM been used and why should they be used in the evaluation of social media impacts?
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RQ3: Based on found applications, what are the direct or indirect business implications of using ABM or SDM in measuring the impacts of social media?
TopIn order to define social media accurately, one has to define the terms “web 2.0” and” User Generated Content”. Web 2.0 is a term first introduced by Tim O’Reilly in 2004 that describes the new approach of users and developers in using www-technology (O’Reilly, 2009). In the new approach the content and applications of the World Wide Web are no longer made only by individual developers. Instead, the content is constantly generated and modified communally by both the developers and users. (Kaplan & Haenlein, 2010) The term “web 2.0” includes open, interactive and communal applications that support the aforementioned communal nature of the World Wide Web. Web 2.0 applications support the formation of informal user communities and create a frame that allows the sharing of ideas and information by enabling effective creation, modification, spreading and sharing of informal information (Constantinides & Fountain, 2008).
User Generated Content (UGC) is the wide variety of publicly accessible information that exists on web 2.0 applications, and is generated by the users of that application (Kaplan & Haenlein, 2010). By combining the definitions of UGC and web 2.0, one can give a broader definition for the term “social media”. Social Media is defined as internet-based applications that utilize web 2.0 technology and principles, and enable the creation and sharing of User Generated Content (Kaplan & Haenlein, 2010).