ANT is often accredited as the work of Michel Callon, Bruno Latour, and John Law (Callon 1986, 1999; Latour 1987, 1988, 1999; Law 1999; Sidle & Warzynski 2003; Sismondo 2004; Tatnall & Burgess 2004; Tatnall & Lepa 2003). ANT deals with (Bardini 1997):
“… progressive constitution of a network in which both human and non-human actors assume identities according to prevailing strategies of interaction. Actors’ identities and qualities are defined during negotiations between representatives of human and non-human actors. The most important of these negotiations is ‘translation‘, a multi faced interaction in which actors:
Construct common definitions and meanings
Co-opt each other in the pursuit of individual and collective objectives.”
The translation process consist of four stages (Callon 1986):
- Problematisation. Key actors attempt to define the problem and roles of other actors to fit the proposed solution, which was made by the key actors.
- Interresment. Processes that attempt to impose the identities and roles defined in problematisation on other actors.
- Enrolment. A process where one set of actors (key actors) imposes their will on others. The other actors will be persuaded to follow the identities and roles defined by the key actors. This will then lead to the establishment of a stable network of alliances.
- Mobilisation. This is where the proposed solutions gain wider acceptance. The network would grow larger with the involvement of other parties that were not involved previously. This growth is due to the influence of actors.
When using ANT to investigate IT adoption, a researcher would focus on issues such as network formation, human and non-human actors, alliance, and network build up (Sismondo 2004; Tatnall & Burgess 2004). Stronger alliances would be likely to influence the decision to adopt or reject IT. In conclusion, ANT recognises that adoption of innovation is initiated by individuals who build a network of individuals (in the form of an organisation) and nonhumans (machine, tools, etc.) to adopt innovations. ANT is different from DOI in several ways:
- It breaks the communication into stages (of translation).
- It considers the details of “resistance” (anti-program).
- It treats non-humans as actors.
- It explains success and failure with the same model.
ANT was originally developed to explain the diffusion of science into society (for example the idea of pasteurisation in Latour 1988). It is similar to Rogers’s DOI. The difference is that Rogers’s DOI viewed the diffusion as merely a communication process, while ANT viewed diffusion of innovation as involving a political game where an actor (who wants to spread the innovation) builds a network that will use the innovation.
The use of ANT in explaining the adoption of innovation is still in its early stage. Some examples are the works of McMaster (McMaster 2001; McMaster, Vidgen & Wastell 1997) and Tatnall (Tatnall & Burgess 2004; Tatnall & Lepa 2003). In those studies, the process of translation was believed to be richer and deeper in that it acknowledged the intertwining and inseparability of technical and social issues. Ciborra has also used ANT to study the management of IT infrastructure and knowledge management (Ciborra & Hanseth 1998a, 1998b; Ciborra & Patriotta 1998; Hanseth, Ciborra & Braa 2001). Development of knowledge management and management of IT infrastructure are considered to be political processes, where different stakeholders try to win power and spread their “ideology”.
ANT is an example of a theory to explain how different stakeholders in an organisation try to spread their ideas to the other stakeholders and influence them to accept the ideas. From the ANT perspective, an actor would build a network of power to overcome other networks of power so he or she could win and impose their ideas. At the end, the actors would use the network to achieve their own goals. In the context of adoption of innovation, the ANT perspective could be used to show how different actors spread their ideas (innovation) to be adopted by others through the development of a network. When their ideas (innovation) are accepted by the other stakeholders (the development of a network), the actor could use the network to achieve his or her own goals.
Bardini, T. 1997, ‘Journal of Computer-Mediated Communication’, Bridging the Gulfs: From Hypertext to Cyberspace, viewed 12 June 2004 <http://www.ascusc.org/jcmc/vol3/issue2/bardini.html>.
Callon, M. 1986, ‘Some Elements of Sociology of Translation: Domestication of The Scallops and The Fishermen of St Brieue Bay’, in J. Law (ed.), Power, Action, Belief: A New Sociology of Knowledge, Routledge& Kegan Paul, London, pp. 196-233.
Callon, M. 1999, ‘Actor-network Theory – the Market Test’, in J. Law & J. Hassard (eds), Actor Network Theory and After, Blackwell Publishers, Oxford, pp. 181-195.
Ciborra, C.U. & Hanseth, O. 1998a, ‘From Tool to Gestell Agendas for Managing The Information Infrastructure’, Information Technology and People, vol. 11, no. 4, pp. 305-327.
Ciborra, C.U. & Hanseth, O. 1998b, ‘Toward A Contingency View of Infrastructure and Knowledge: An Exploratory Study’, in Proceedings of The 19th International Conference on Information Systems, Helsinki, Finland, pp. 263-272.
Ciborra, C.U. & Patriotta, G. 1998, ‘Groupware and Teamwork in R&D: Limits to Learning and Innovation’, R&D Management, vol. 28, no. 1, pp. 43-52.
Hanseth, O., Ciborra, C.U. & Braa, K. 2001, ‘The Control Devolution: ERP and The Side Effects of Globalization’, Database for Advances in Information Systems, vol. 32, no. 4, pp. 34-46.
Latour, B. 1987, Science in Action, Open University Press, Milton Keynes.
Latour, B. 1988, The Pasteurization of France, Harvard University Press, Cambridge.
Latour, B. 1999, ‘On Recalling ANT’, in J. Law & J. Hassard (eds), Actor Network Theory and After, Blackwell Publishers, Oxford, pp. 15-25.
Law, J. 1999, ‘After ANT: Complexity, Naming, and Topology’, in J. Law & J. Hassard (eds), Actor Network Theory and After, Blackwell Publishers, Oxford, pp. 1-14.
McMaster, T. 2001, ‘The Illusion of Diffusion in Information Systems Research’, in M. Ardis & B. Marcolin (eds), Diffusing Software Products and Process Innovations, Kluwer Academic Publishers, Boston, pp. 67-85.
McMaster, T., Vidgen, R.T. & Wastell, D.G. 1997, ‘Technology Transfer — Diffusion or Translation?’, in T. McMaster, E. Mumford, E.B. Swanson, B. Warboys & D. Wastell (eds), Facilitating Technology Transfer Through Partnership – Learning from Practice and Research, Chapman and Hall, London, pp. 64-75.
Sidle, C.C. & Warzynski, C.C. 2003, ‘A New Mission for Business Schools: The Development of Actor-Network Leaders’, Journal of Education for Business, vol. 79, no. 1, pp. 40-45.
Sismondo, S. 2004, An Introduction to Science and Technology Studies, Blackwell Publishing, Malden.
Tatnall, A. & Burgess, S. 2004, ‘Using Actor-Network Theory to Identify Factors Affecting the Adoption of E-Commerce in SMEs’, in M. Singh (ed.), E-Business Innovation and Change Management, IDEA Group Publishing, Hershey, pp. 152-169.
Tatnall, A. & Lepa, J. 2003, ‘The Internet, E-Commerce, and Older People: An Actor Network Approach to Researching Reasons for Adoption and Use’, Logistics Information Management, vol. 16, no. 1, pp. 56-63.