Positioning hierarchy in enterprise system change

There is a widening gulf in change literature between theoretical notions of evolving organisational form and the emerging reality that old and new organisational structures coexist. This paper explores this dichotomy in Enterprise Resource Planning change. It develops a cellular hierarchy framework to explain how different types of hierarchy coexist within the same organisation during the implementation of Enterprise Resource Planning. © 2006 The Author; Journal compilation © 2006 Blackwell Publishing Ltd.

Research commentary: Information systems and conceptual modeling - A research agenda

Within the information systems field, the task of conceptual modeling involves building a representation of selected phenomena in some domain. High-quality conceptual-modeling work is important because it facilitates early detection and correction of system development errors. It also plays an increasingly important role in activities like business process reengineering and documentation of best-practice data and process models in enterprise resource planning systems. Yet little research has been undertaken on many aspects of conceptual modeling. In this paper, we propose a framework to motivate research that addresses the following fundamental question: How can we model the world to better facilitate our developing, implementing, using, and maintaining more valuable information systems? The framework comprises four elements: conceptual-modeling grammars, conceptual-modeling methods, conceptual-modeling scripts, and conceptual-modeling contexts. We provide examples of the types of research that have already been undertaken on each element and illustrate research opportunities that exist.

An analysis of changing management roles in small Australian services exporters in response to the stages in industry development

Life cycle models have become important in explaining the changing size structure of firms based on the carrying capacity of regions or industries. In particular, the population ecology model predicts stages of growth, maturity and eventually decline in the number of firms in an industry. There has been criticism of such models because of their focus on external variables as pre-determinants of the potential for enterprise development. This paper attempts to reconcile the external focus of the population ecology model with relevant internal management factors in enterprise development. A survey was conducted of Australian services exporters, and the results not only confirm the existence of four separate life cycle stages in the population ecology model, but also identify the external and internal variables that are strategically relevant at each of the stages. The findings provide potentially useful information in a range of contexts including the design of small business assistance as well a providing “guide posts” to entrepreneurs engaged in enterprise development.

Referral patterns in a global store-and-forward telemedicine system

We examined the nature of the referral patterns in the email telemedicine network operated by the Swinfen Charitable Trust with a view to informing long-term resource planning. Over the first six years of operation, 62 hospitals from 19 countries registered with the Trust in order to be able to refer cases for specialist advice; 55 of these hospitals (89%) actually referred cases during this period. During the first six years of operation, nearly 1000 referrals were submitted and answered, from a wide range of specialty areas. Between July 2002 and March 2005 the referral rate rose from 127 to 318 cases per year. The median length of time required to provide a specialist's response was 2.3 days during the first 12 months and 1.8 days during the last 12 months. Five hospitals submitted cases for more than four years (together sending a total of 493 cases). Their activity data showed a trend to declining referral rates over the four-year period, which may represent successful knowledge transfer. There is some evidence that over the last three years the growth in demand has been exponential, while the growth in resources available (i.e. specialists) has been linear, a situation which cannot continue for very long before demand outstrips supply.

Adaptive management and its role in managing Great Barrier Reef water quality

Adaptive management is the pathway to effective conservation, use and management of Australia’s coastal catchments and waterways. While the concepts of adaptive management are not new, applications involving both assessment and management responses are indeed limited at the national and regional scales. This paper outlines the components of a systematic framework for linking scientific knowledge, existing tools, planning approaches and participatory processes to achieve healthy regional partnerships between community, industry, government agencies and science providers to overcome institutional barriers and uncoordinated monitoring. The framework developed by the Coastal CRC (www.coastal.crc.org.au/amf/amf_index.htm) is hierarchical in the way it displays information to allow associated frameworks to be integrated, and represents a construct in which processes, information, decision tools and outcomes are brought together in a structured and transparent way for adaptive catchment and coastal management. This paper proposes how an adaptive management approach could be used to benefit the implementation of the Reef Water Quality Protection Plan (RWQPP).

Expansion-based algorithms for finding single pair shortest path on surface

Finding single pair shortest paths on surface is a fundamental problem in various domains, like Geographic Information Systems (GIS) 3D applications, robotic path planning system, and surface nearest neighbor query in spatial database, etc. Currently, to solve the problem, existing algorithms must traverse the entire polyhedral surface. With the rapid advance in areas like Global Positioning System (CPS), Computer Aided Design (CAD) systems and laser range scanner, surface models axe becoming more and more complex. It is not uncommon that a surface model contains millions of polygons. The single pair shortest path problem is getting harder and harder to solve. Based on the observation that the single pair shortest path is in the locality, we propose in this paper efficient methods by excluding part of the surface model without considering them in the search process. Three novel expansion-based algorithms are proposed, namely, Naive algorithm, Rectangle-based Algorithm and Ellipse-based Algorithm. Each algorithm uses a two-step approach to find the shortest path. (1) compute an initial local path. (2) use the value of this initial path to select a search region, in which the global shortest path exists. The search process terminates once the global optimum criteria are satisfied. By reducing the searching region, the performance is improved dramatically in most cases.

Classifying an opponent's behaviour in robot soccer

This paper illustrates the prediction of opponent behaviour in a competitive, highly dynamic, multi-agent and partially observableenvironment, namely RoboCup small size league robot soccer. The performance is illustrated in the context of the highly successful robot soccer team, the RoboRoos. The project is broken into three tasks; classification of behaviours, modelling and prediction of behaviours and integration of the predictions into the existing planning system. A probabilistic approach is taken to dealing with the uncertainty in the observations and with representing the uncertainty in the prediction of the behaviours. Results are shown for a classification system using a Naïve Bayesian Network that determines the opponent’s current behaviour. These results are compared to an expert designed fuzzy behaviour classification system. The paper illustrates how the modelling system will use the information from behaviour classification to produce probability distributions that model the manner with which the opponents perform their behaviours. These probability distributions are show to match well with the existing multi-agent planning system (MAPS) that forms the core of the RoboRoos system.

Achieving cooperation in a distributed multi-robot team

DMAPS (Distributed Multi-Agent Planning System) is a planning system developed for distributed multi-robot teams based on MAPS(Multi-Agent Planning System). MAPS assumes that each agent has the same global view of the environment in order to determine the most suitable actions. This assumption fails when perception is local to the agents: each agent has only a partial and unique view of the environment. DMAPS addresses this problem by creating a probabilistic global view on each agent by fusing the perceptual information from each robot. The experimental results on consuming tasks show that while the probabilistic global view is not identical on each robot, the shared view is still effective in increasing performance of the team.

Benchmarking regional planning arrangements for natural resource management 2004–05: Progress, constraints and future directions for regions

This report provides a benchmark of progress in regional planning for natural resource management in Queensland and the tropical savannas region of northern Australia during 2004. It is based on a review of regional plans and planning processes against a set of pre-defined criteria designed specifically to evaluate regional planning arrangements.

A cognitive genetic algorithm for power distribution system planning

Power systems are large scale nonlinear systems with high complexity. Various optimization techniques and expert systems have been used in power system planning. However, there are always some factors that cannot be quantified, modeled, or even expressed by expert systems. Moreover, such planning problems are often large scale optimization problems. Although computational algorithms that are capable of handling large dimensional problems can be used, the computational costs are still very high. To solve these problems, in this paper, investigation is made to explore the efficiency and effectiveness of combining mathematic algorithms with human intelligence. It had been discovered that humans can join the decision making progresses by cognitive feedback. Based on cognitive feedback and genetic algorithm, a new algorithm called cognitive genetic algorithm is presented. This algorithm can clarify and extract human's cognition. As an important application of this cognitive genetic algorithm, a practical decision method for power distribution system planning is proposed. By using this decision method, the optimal results that satisfy human expertise can be obtained and the limitations of human experts can be minimized in the mean time.