STUDY 2: DIGITAL DEVICES AND DISTRIBUTED CONSUMPTIONDenegri-Knott, J., Jenkins, R. and Scullion, R. (2015) Smart phones and tablets are now ubiquitous agents of information for consumer decision-making (Deloitte 2012, Econsultance 2012, Nielsen 2012). Industry forecasts see the smartphone displacing in-store staff and other sources of information in informing consumer decision-making and report an upward trend in their use for information acquisition and product comparisons (Deloitte 2012). These digital agents have amplified information points beyond marketing stimuli and WOM to include online expert reviews, social recommendations, apps and price comparison sites which allow for complex comparison between products and services (Brynjolfsson et al., 2013). As a result, the ecology of possible information sources available for decision-making has become larger and more complex. This growing complexity challenges conventional approaches to decision making and requires a different kind of intervention, which this study aims to provide. Classical decision making models (e.g. Miniard et al. 1990, Howard and Sheth 1969) and their more contemporary offshoots are all underpinned by a model of cognition that is rooted in a conception of an intracranial, individual mind. Put differently, cognitive decision-making processes unfold only in the individual, biological brain. Such approaches assume that there is a gulf between cognitive processing and external sources that is abridged via internal symbolic representations (Hollan et al. 2000, Hutchins 1994). Emphasis thereby has been placed on understanding the ways in which individual cognition drives attitude formation and change and decision-making. Here the external environment, reduced to marketing stimuli or word of mouth, is simply transformed into an internal symbolic representation that is processed. Such approach is directly or indirectly assumed in studies looking at mobile browsing (Ghose et al. 2013), mobile recommendation agents’ (Kowatsch and Maass, 2010; Lee and Benbasat, 2010; Von Reischach et al., 2009) and mobile product reviews (Von Reischach et al., 2010). In order to best understand and model decision making in a context of increased mediated networked interactions and increased information availability we draw from theoretical developments in the area of distributed cognition (DCOG) (Hollan et al. 2000, Hutchins 1994) and active externalism (AE) (Clark and Chalmers 1998, Menary 2010). Unlike existing models of cognition underpinning consumer decision models, DCOG recognizes the active role of the external environment, including artifacts, devices and other people in cognitive processing and task completion. From this vantage point, we approach cognition as a hybrid assemblage including interactions between consumers minds and the broader external environment, including sources of information, decision making tools and other people (Hollan et al.2000).
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