Modelling the effects of user learning on forced innovation diffusion

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Zhang, Tao, Siebers, Peer-Olaf and Aickelin, Uwe (2012) Modelling the effects of user learning on forced innovation diffusion. In: ORS SW12 Simulation Conference, 27-28 Mar 2012, Worcestershire, England.

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Abstract

Technology adoption theories assume that users’ acceptance of an innovative technology is on a voluntary basis. However, sometimes users are force to accept an innovation. In this case users have to learn what it is useful for and how to use it. This learning process will enable users to transit from zero knowledge about the innovation to making the best use of it. So far the effects of user learning on technology adoption have received little research attention. In this paper - for the first time - we investigate the effects of user learning on forced innovation adoption by using an agent-based simulation approach using the case of forced smart metering deployments in the city of Leeds.

Item Type: Conference or Workshop Item (Paper)
RIS ID: https://nottingham-repository.worktribe.com/output/1009489
Schools/Departments: University of Nottingham, UK > Faculty of Science > School of Computer Science
Depositing User: Aickelin, Professor Uwe
Date Deposited: 19 Jul 2013 08:54
Last Modified: 04 May 2020 20:22
URI: https://eprints.nottingham.ac.uk/id/eprint/2068

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