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Introduction
The core notion of the social media returns on investment (ROI), unlike the traditional ROI, is that it should not always be measured in monetary terms (Fisher, 2009; Hoffman and Fodor, 2010; Kumar and Mirchandani, 2012; Cronin, 2014), still the social media ROI efforts are faced with the “inability to measure” syndrome. While the top management demands concrete measures on their return on social media marketing investment (Weinberg and Pehlivan, 2011), a vast majority of business managers find it hard to quantitatively measure such returns. The existing literature has suggested ways to realize social media ROI (Fisher, 2009; Hoffman and Fodor, 2010; Cronin, 2014), but such notions misalign with the fundamental philosophy of social media. It is widely understood that social media is inherently a network media where people form different types of including personal (e.g. Facebook), professional (e.g. LinkedIn) and content networks (e.g. YouTube) to create and share content, interests and expertise (Kietzmann et al., 2011). And when there is a network there is a network externality (Shapiro and Varian, 1998). Ironically, the social media ROI debate has largely overlooked the networked nature of the returns originating from social media investment. A positive comment or a Facebook like, for instance, is not just a discrete action, but a networked action with accompanying network externality. de Vries et al. (2012) showed that certain interactive brand posts and the associated positive comments affect the number of likes received by a brand (de Vries et al., 2012). Said differently, positive comments and interactive posts carry positive network externality benefiting a brand. If social media is a network media, why are the network measures then not part of the social media ROI? We argue that the social media returns are derived not only from the actions per se but also from the additional exposure that results from the network externality associated with these actions. Consequently, for a social media ROI to make sense, its core notion should be based on network theory.
Furthermore, the emerging inconclusive and possibly conflated “new media versions” of traditional media metrics (Fisher, 2009, p. 192) seem to reflect the practitioners’ insufficient attention to the underlying interconnected nature of customer behavior in the social media domain. Consequently, in this paper, our...