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Using Actor Network Theory (ANT) to investigate digital tracking technologies in the retail environment

“interaction is all that there is”  (Law 1992, p. 380)

As many socio-technological sectors, the retail industry is in a constant evolution and depends on a multiplicity of heterogeneous factors. New technologies, practices and industry players regularly attempt at challenging and redefining the established systems, pursuing economic growth and profitability. (Rigby, 2011) In this context, Omnichannel retailing appear as the ideal which many companies aspire on implementing. As recently described, “Omnichannel retailing refers to an integrated shopper experience that merges the physical store with the information rich digital environment, with the aim of providing excellent shopper experiences across all touch points.” (Brynjolfsson and al. 2013, p.655) Yet, Omnichannel strategies have taken various forms, employed different technologies and still can’t be comprehensively described in standardised practices as the speed of technological innovation makes it difficult to define in static terms. Stemming from this vision, this paper focuses on the emergence of digital tracking technologies in the retail environment and aims at evaluating the Actor-Network Theory (ANT) as a method to answer the following research question: to what extent can digital tracking technologies reevaluate the shopping experience, transform its spatial dimension and bring Omnichannel retailing closer from completion?

New media researchers are given a variety of tools and methods to undertake their studies and tackle their questions. However, what can be perceived as a convenient degree of freedom often translates into an unstable ground on which one must carefully consider the implications of every taken step. Each method or theory comes with its set of assumptions, pre-requisites, boundaries and references which must be rigorously taken into account before it can be applied. The more controversial and debated a theory is, the more perilous it can appear to adopt it, and the more relevant to answer the research question it should be. ANT undoubtedly relates to this observation and therefore always draws attention and anticipation when chosen as primary path for a research. Developed from the 1980s by Bruno Latour, John Law and Michel Callon, ANT is a particular approach to social theory originated in Science and Technology Studies (STS). (Cressman, 2009) As many scholars have come to realise, describing ANT in general terms or formulating its guidelines is unlikely to bring satisfactory results (Dankert, 2011). Most words used to describe ANT hold a specific meaning within this theory and need to be reconsidered accordingly to avoid confusion. However, I will attempt at shortly presenting key elements and concepts in this methodological account. An ANT driven research consists on exploring a socio-technical phenomenon – conceptualised as a dynamic web of relations called actor-network – focusing on the evolving relationships between its actants. The concept of actant is central to ANT which doesn’t distinguish or differentiate human actors from non-human actors, although it doesn’t consider them equal. Rather, ANT purposely ignores this contextual dimension and explores their performativity using a same vocabulary. ANT is a non-deterministic framework which leaves aside concepts such as essence, contextuality (Dankert, 2011) or intentionality (Law, 2007) to provide an essentially descriptive understanding of scientific and technological change. It is a scalable method as the researcher can and should define his own level of complexity, provided any actant can be potentially broken down into a micro-level actant-network while symmetrically any actant-network can be viewed as an actant of a macro-level actant-network— this process being often referred to as black-boxing or punctualisation in ANT literature. As Callon puts it: “the process of punctualization thus converts an entire network into a single point or node in another network”. (1991, p.153). Consecutively, ANT knows no boundaries by itself and thus potentially offers interesting perspectives and unexpected results. It requires a significant capacity of abstraction and involves undertaking in-depth fieldwork, document analysis and direct observations. The first step in the research consists on choosing an actant as starting point from which interactions with other actants will be identified until eventually constituting a chain. This preliminary choice appears crucial and must be dictated by the research question. In the context of my research field – digital tracking technologies in the retail environment – a promising initial actant could be the innovative tracking device itself. A significant study period should then be allocated in the second phase of the research to monitor and document the evolution of the actor-network. The researcher must seek for evidence of key concepts of ANT such as translation, agency, stability and power. Multiple studies have already shown the efficiency of ANT applied to various kinds of innovation (Wiskerke and al. 2007; Redwood, 2012; Harrison and Laberge, 2002). Notably, Bruno Latour performed an ANT driven research about Aramis, an innovative public transportation system which was never successfully implemented (Latour, 1996). According to Latour, ANT appear well suited when applied to science and technology in the making (1987). Also favouring ANT as “an important part of the panoply of media theory” (Couldry, 2008, p.99), Nick Couldry further argues that “ANT offers fundamental insights into the spatiality of networks and into the nature of contemporary power formations” (2008, p.104). Both statements seem to positively advocate the relevancy of ANT in the context of my research question. However, it remains necessary to acknowledge the reluctant positions of numerous scholars towards ANT and their motives. (Bloor, 1999) The two main critics address the way ANT dismisses contextuality which is central to most social studies, and ANT’s descriptive output which implies an inability to provide explanations. One could probably argue that my research question would be efficiently served by using alternative theories such as Ethnography, Material Object Analysis or Big Data Analysis but I would answer that they seem individually reductive and narrow. In fact, part of these theories will be required within the ANT research.

As I have discussed in this methodological account, ANT is a challenging road which is understandably avoided by researchers or at least rarely recommended. At the same time, it holds an intriguing and promising potential of revealing the complexities of our sociotechnical world (Cressman, 2009). Furthermore, it embeds a higher level of understanding and an external vision which I anticipate as beneficial in the intricate context of Omnichannel retailing.

I wrote this essay in the context of the Master Programme in New Media Studies & Digital Culture
I am currently following at Utrecht University.


Bloor, David. 1999. “Anti-Latour.” Stud Hist Philos Sci 30 (1): 81–112. doi:citeulike-article-id:347698\ndoi: 10.1016/S0039-3681(98)00038-7.

Brynjolfsson, Erik, Yu Jeffrey Hu, and Mohammad S Rahman. 2013. “Competing in the Age of Omnichannel Retailing.” MIT Sloan Management Review 54 (4). Massachusetts Institute of Technology: 23–29.

Callon, Michel. 1991. “Techno-Economic Networks and Irreversibility.” The Sociological Review 38 (S1): 132–61. doi:10.1111/j.1467-954X.1990.tb03351.x.

Couldry, Nick. 2008. “Actor Network Theory and Media: Do They Connect and On What Terms?”

Cressman, Darryl. 2009. “A Brief Overview of Actor-Network Theory: Punctualization, Heterogeneous Engineering & Translation.” Paper for Simon Frasier University ACT Lab/Centre for Policy Research on Science & Technology (CPROST), 1–17.

Frazer, Mariette, and Beate Elizabeth Stiehler. 2014. “Omnichannel Retailing: The Merging of the Online and off-Line Environment.” Global Conference on Business & Finance Proceedings 9 (1).

Harrisson, Denis, and Murielle Laberge. 2002. “Innovation, Identities and Resistance: The Social Construction of An Innovation Network.” Journal of Management Studies 39 (4): 497–521. doi:10.1111/1467-6486.00301.

Latour, Bruno. 1987. Science in Action: How to Follow Scientists and Engineers Through Society. Cambridge: Harvard University Press.

Latour, Bruno. 1996. Aramis, or the love of technology. Cambridge, Mass. and London: Harvard University Press.

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Wiskerke, Johannes S. C., and Dirk Roep. 2007. “Constructing a Sustainable Pork Supply Chain: A Case of Techno-Institutional Innovation.” Journal of Environmental Policy & Planning 9 (1). Routledge: 53–74. doi:10.1080/15239080701254982.


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