Exploring the adoption and implementation of discrete and integrated IT systems: A Framework for analysis

Despite the substantial organisational benefits of integrated IT, the implementation of such systems – and particularly Enterprise Resource Planning (ERP) systems – has tended to be problematic, stimulating an extensive body of research into ERP implementation. This research has remained largely separate from the main IT implementation literature. At the same time, studies of IT implementation have generally adopted either a factor or process approach; both have major limitations. To address these imitations, factor and process perspectives are combined here in a unique model of IT implementation. We argue that • the organisational factors which determine successful implementation differ for integrated and traditional, discrete IT • failure to manage these differences is a major source of integrated IT failure. The factor/process model is used as a framework for proposing differences between discrete and integrated IT.

Implementation of Discrete and Integrated IT: The Role of Organisational Structure and Culture

ntegrated organisational IT systems, such as enterprise resource planning (ERP), supply chain management (SCM) and digital manufacturing (DM), have promised and delivered substantial performance benefits to many adopting firms. However, implementations of such systems have tended to be problematic. ERP projects, in particular, are prone to cost and time overruns, not delivering anticipated benefits and often being abandoned before completion. While research has developed around IT implementation, this has focused mainly on standalone (or discrete), as opposed to integrated, IT systems. Within this literature, organisational (i.e., structural and cultural) characteristics have been found to influence implementation success. The key aims of this research are (a) to investigate the role of organisational characteristics in determining IT implementation success; (b) to determine whether their influence differs for integrated IT and discrete IT projects; and (c) to develop specific guidelines for managers of integrated IT implementations. An in-depth comparative case study of two IT projects was conducted within a major aerospace manufacturing company.

Extending BPM Environments of Your Choice with Performance Related Decision Support

What-if Simulations have been identified as one solution for business performance related decision support. Such support is especially useful in cases where it can be automatically generated out of Business Process Management (BPM) Environments from the existing business process models and performance parameters monitored from the executed business process instances. Currently, some of the available BPM Environments offer basic-level performance prediction capabilities. However, these functionalities are normally too limited to be generally useful for performance related decision support at business process level. In this paper, an approach is presented which allows the non-intrusive integration of sophisticated tooling for what-if simulations, analytic performance prediction tools process optimizations or a combination Of Such solutions into already existing BPM environments. The approach abstracts from process modelling techniques which enable automatic decision support spanning processes across numerous BPM Environments. For instance, this enables end-to-end decision support for composite processes modelled with the Business Process Modelling Notation (BPMN) on top of existing Enterprise Resource Planning (ERP) processes modelled with proprietary languages.

The role of complexity metrics in a multi-institutional dosimetry audit of VMAT

OBJECTIVE: To demonstrate the benefit of complexity metrics such as the modulation complexity score (MCS) and monitor units (MUs) in multi-institutional audits of volumetric-modulated arc therapy (VMAT) delivery.

METHODS: 39 VMAT treatment plans were analysed using MCS and MU. A virtual phantom planning exercise was planned and independently measured using the PTW Octavius(®) phantom and seven29(®) 2D array (PTW-Freiburg GmbH, Freiburg, Germany). MCS and MU were compared with the median gamma index pass rates (2%/2 and 3%/3 mm) and plan quality. The treatment planning systems (TPS) were grouped by VMAT modelling being specifically designed for the linear accelerator manufacturer's own treatment delivery system (Type 1) or independent of vendor for VMAT delivery (Type 2). Differences in plan complexity (MCS and MU) between TPS types were compared.

RESULTS: For Varian(®) linear accelerators (Varian(®) Medical Systems, Inc., Palo Alto, CA), MCS and MU were significantly correlated with gamma pass rates. Type 2 TPS created poorer quality, more complex plans with significantly higher MUs and MCS than Type 1 TPS. Plan quality was significantly correlated with MU for Type 2 plans. A statistically significant correlation was observed between MU and MCS for all plans (R = -0.84, p < 0.01).

CONCLUSION: MU and MCS have a role in assessing plan complexity in audits along with plan quality metrics. Plan complexity metrics give some indication of plan deliverability but should be analysed with plan quality.

ADVANCES IN KNOWLEDGE: Complexity metrics were investigated for a national rotational audit involving 34 institutions and they showed value. The metrics found that more complex plans were created for planning systems which were independent of vendor for VMAT delivery.

A strategic review of electricity systems models

Electricity systems models are software tools used to manage electricity demand and the electricity systems, to trade electricity and for generation expansion planning purposes. Various portfolios and scenarios are modelled in order to compare the effects of decision making in policy and on business development plans in electricity systems so as to best advise governments and industry on the least cost economic and environmental approach to electricity supply, while maintaining a secure supply of sufficient quality electricity. The modelling techniques developed to study vertically integrated state monopolies are now applied in liberalised markets where the issues and constraints are more complex. This paper reviews the changing role of electricity systems modelling in a strategic manner, focussing on the modelling response to key developments, the move away from monopoly towards liberalised market regimes and the increasing complexity brought about by policy targets for renewable energy and emissions. The paper provides an overview of electricity systems modelling techniques, discusses a number of key proprietary electricity systems models used in the USA and Europe and provides an information resource to the electricity analyst not currently readily available in the literature on the choice of model to investigate different aspects of the electricity system.

Planning, Devolution and the Territorialisation of Wind Energy in the UK

The decarbonisation of energy systems draw a new set of stakeholders into debates over energy generation, engage a complex set of social, political, economic and environmental processes and impact at a wide range of geographical scales, including local landscape changes, national energy markets and regional infrastructure investment. This paper focusses on a particular geographic scale, that of the regions/nations of the UK (Scotland, Wales, Northern Ireland), who have been operating under devolved arrangements since the late 1990s, coinciding with the mass deployment of wind energy. The devolved administrations of the UK possess an asymmetrical set of competencies over energy policy, yet also host the majority of the UK wind resource. This context provides a useful way to consider the different ways in which geographies of "territory" are reflected in energy governance, such through techno-rational assessments of demand or infrastructure investment, but also through new spatially-defined institutions that seek to develop their own energy future, using limited regulatory competencies. By focussing on the way the devolved administrations have used their responsibilities for planning over the last decade this paper will assess the way in which the spatial politics of wind energy is giving rise to renewed forms of territorialisation of natural resources. In so doing, we aim to contribute to clarifying the questions raised by Hodson and Marvin (2013) on whether low carbon futures will reinforce or challenge dominant ways of organising relationships between the nation-state, regions, energy systems and the environment.

Exploiting Human Resource Requirements to Infer Human Movement Patterns for Use in Modelling Disease Transmission Systems: An Example from Eastern Province, Zambia

In this research, an agent-based model (ABM) was developed to generate human movement routes between homes and water resources in a rural setting, given commonly available geospatial datasets on population distribution, land cover and landscape resources. ABMs are an object-oriented computational approach to modelling a system, focusing on the interactions of autonomous agents, and aiming to assess the impact of these agents and their interactions on the system as a whole. An A* pathfinding algorithm was implemented to produce walking routes, given data on the terrain in the area. A* is an extension of Dijkstra's algorithm with an enhanced time performance through the use of heuristics. In this example, it was possible to impute daily activity movement patterns to the water resource for all villages in a 75 km long study transect across the Luangwa Valley, Zambia, and the simulated human movements were statistically similar to empirical observations on travel times to the water resource (Chi-squared, 95% confidence interval). This indicates that it is possible to produce realistic data regarding human movements without costly measurement as is commonly achieved, for example, through GPS, or retrospective or real-time diaries. The approach is transferable between different geographical locations, and the product can be useful in providing an insight into human movement patterns, and therefore has use in many human exposure-related applications, specifically epidemiological research in rural areas, where spatial heterogeneity in the disease landscape, and space-time proximity of individuals, can play a crucial role in disease spread.