Geomagnetic induced currents (GICs) have been considered an issue for high‐latitude power networks for some decades. More recently, GICs have been observed and studied in power networks located in lower latitude regions. This paper presents the results of a model aimed at predicting and understanding the impact of geomagnetic storms on power networks in Australia, with particular focus on the Queensland and Tasmanian networks. The model incorporates a “geoelectric field” determined using a plane wave magnetic field incident on a uniform conducting Earth, and the network model developed by Lehtinen and Pirjola (1985). Model results for two intense geomagnetic storms of solar cycle 24 are compared with transformer neutral monitors at three locations within the Queensland network and one location within the Tasmanian network. The model is then used to assess the impacts of the superintense geomagnetic storm of 29–31 October 2003 on the flow of GICs within these networks. The model results show good correlation with the observations with coefficients ranging from 0.73 to 0.96 across the observing sites. For Queensland, modeled GIC magnitudes during the superstorm of 29–31 October 2003 exceed 40 A with the larger GICs occurring in the south‐east section of the network. Modeled GICs in Tasmania for the same storm do not exceed 30 A. The larger distance spans and general east‐west alignment of the southern section of the Queensland network, in conjunction with some relatively low branch resistance values, result in larger modeled GICs despite Queensland being a lower latitude network than Tasmania.

enterprise system (ES) software is often supplemented independently by end users who develop personal solutions that establish connections between the required business practices and the ES. One solution is a type of information and communications technology workaround, a feral information system (FIS) – defined as a workaround designed to achieve certain requirements by using any information technology tool that an end user uses in conjunction with, or instead of, the mandated information system. To explore this, we conducted a case study at a large utility company. We conclude that feral information systems are not a behavioural deviance. FISs are by‐products of end users seeking operational efficiency, namely, to nullify additional transactional costs imposed by the ES. Our findings suggest that end users of ES will fall into one of four modes of operation: mode 1, where end users submit to the ES; mode 2, where they dismiss the ES; mode 3, where they develop an FIS that remains hidden from the ES proponents; and mode 4, where they operate the FIS in open defiance of the ES proponents. In this research, we deliberately take the practitioner view and, therefore, outline how different pressures help to create an FIS as a response to a poorly mandated ES. We also make a theoretical contribution by exploring issues that lead to workarounds and suggest that future research into these modes of operation can be theorized in future proposed studies.

In this chapter, the authors explore a wide mixture of economic and social concepts. At first, the reader may wonder what these diverse theories have to do with Feral Information Systems (FIS). However, the research indicates that understanding how these theoretical puzzle pieces interact with each other is important to increasing the understanding of what drives the End User to create Feral Information Systems.