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.

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.

Objectives for multiple-species conservation planning

The first step in conservation planning is to identify objectives. Most stated objectives for conservation, such as to maximize biodiversity outcomes, are too vague to be useful within a decision-making framework. One way to clarify the issue is to define objectives in terms of the risk of extinction for multiple species. Although the assessment of extinction risk for single species is common, few researchers have formulated an objective function that combines the extinction risks of multiple species. We sought to translate the broad goal of maximizing the viability of species into explicit objectives for use in a decision-theoretic approach to conservation planning. We formulated several objective functions based on extinction risk across many species and illustrated the differences between these objectives with simple examples. Each objective function was the mathematical representation of an approach to conservation and emphasized different levels of threat Our objectives included minimizing the joint probability of one or more extinctions, minimizing the expected number of extinctions, and minimizing the increase in risk of extinction from the best-case scenario. With objective functions based on joint probabilities of extinction across species, any correlations in extinction probabilities bad to be known or the resultant decisions were potentially misleading. Additive objectives, such as the expected number of extinctions, did not produce the same anomalies. We demonstrated that the choice of objective function is central to the decision-making process because alternative objective functions can lead to a different ranking of management options. Therefore, decision makers need to think carefully in selecting and defining their conservation goals.

Conservation planning with irreplaceability: does the method matter?

A number of systematic conservation planning tools are available to aid in making land use decisions. Given the increasing worldwide use and application of reserve design tools, including measures of site irreplaceability, it is essential that methodological differences and their potential effect on conservation planning outcomes are understood. We compared the irreplaceability of sites for protecting ecosystems within the Brigalow Belt Bioregion, Queensland, Australia, using two alternative reserve system design tools, Marxan and C-Plan. We set Marxan to generate multiple reserve systems that met targets with minimal area; the first scenario ignored spatial objectives, while the second selected compact groups of areas. Marxan calculates the irreplaceability of each site as the proportion of solutions in which it occurs for each of these set scenarios. In contrast, C-Plan uses a statistical estimate of irreplaceability as the likelihood that each site is needed in all combinations of sites that satisfy the targets. We found that sites containing rare ecosystems are almost always irreplaceable regardless of the method. Importantly, Marxan and C-Plan gave similar outcomes when spatial objectives were ignored. Marxan with a compactness objective defined twice as much area as irreplaceable, including many sites with relatively common ecosystems. However, targets for all ecosystems were met using a similar amount of area in C-Plan and Marxan, even with compactness. The importance of differences in the outcomes of using the two methods will depend on the question being addressed; in general, the use of two or more complementary tools is beneficial.