What is the value of firms' prior knowledge? Building organisational knowledge capabilities

A firm's prior knowledge facilitates the absorption of new knowledge, thereby renewing a firm's systematic search, transfer and absorption capabilities. The rapidly expanding field of biotechnology is characterised by the convergence of disparate sciences and technologies. This paper, the shift from proteinbased to DNA-based diagnostic technologies, quantifies the value of a firm's prior knowledge and its relation to future knowledge development. Four dimensions of diagnostic and four dimensions of knowledge in biotechnology firms are analysed. A simple scaled matrix method is developed to quantify the positive and negative heuristic values of prior scientific and technological knowledge that is useful for the acquisition and absorption of new knowledge.

The paradox of commercialising public sector intellectual property

The juxtapositioning of government providing a public good through research and development investment on one hand and engaging in commercialisation of the research outcome on the other is a paradox. Using agricultural research as an example, we examine the nature of the paradox to determine if commercialisation potentially leads to a conflict in the role of public research institutions set up to fulfil public good responsibilities. We identify the reasons for the shift in policy towards commercialisation and greater exploitation of public sector intellectual property and how this has contributed to the emergence of the apparent inconsistency. We argue that the belief in working for public good is inherent and embedded in an organisation's history and its wider operating environment. We propose that the creation of public sector intellectual property and its commercialisation are influenced by the political, social and economic environment in which the public institutions operate. [ABSTRACT FROM AUTHOR]

Guidelines for the treatment of postmenopausal osteoporosis for general practitioners

BACKGROUND: Osteoporosis Australia has been committed to the education of general practitioners and the community with a series of updated guidelines on the management of osteoporosis. Since the last series was published in Australian Family Physician (August 2000), there have been further advances in our understanding of the treatments involved in both prevention of bone loss and the management of established osteoporosis. OBJECTIVE: This article represents updated guidelines for the treatment of postmenopausal osteoporosis to assist GPs identify those women at risk and to review current treatment strategies. DISCUSSION: Osteoporosis and its associated problems are major health concerns in Australia, especially with an aging population. While important principles of management are still considered to be maximising peak bone mass and preventing postmenopausal bone loss, new clinical trial data about drugs such as the bisphosphonates, raloxifene and oestrogen have recently become available and the relative role of various agents is gradually becoming clearer. The use of long term hormone replacement therapy has mixed risks and benefits that requires individual patient counselling.

Role of hlx1 in zebrafish brain morphogenesis

hlx1 is a related homeobox gene expressed in a dynamic spatiotemporal expression pattern during development of the zebrafish brain. The homologues of hlx1, mouse dbx1 and Xenopus Xdbx, are known to play a role in the specification of neurons in the spinal cord. However, the role of these molecules in the brain is less well known. We have used two different approaches to elucidate a putative function for hlx1 in the developing zebrafish brain. Blastomeres were injected with either synthetic hlx1 mRNA in gain-of-function experiments or with antisense morpholino oligonucleotides directed against hlx1 in loss-of-function experiments. Mis-expression of hlx1 produced severe defects in brain morphogenesis as a result of abnormal ventricle formation, a phenotype we referred to as fused-brain. These animals also showed a reduction in the size of forebrain neuronal clusters as well as abnormal axon pathfinding. hlx1 antisense morpholinos specifically perturbed hindbrain morphogenesis leading to defects in the integrity of the neuroepithelium. While hindbrain patterning was in the most part unaffected there were select disruptions to the expression pattern of the neurogenic gene Zash1B in specific rhombomeres. Our results indicate multiple roles for hlx1 during zebrafish brain morphogenesis.

An overview of APSIM, a model designed for farming systems simulation

The Agricultural Production Systems Simulator (APSIM) is a modular modelling framework that has been developed by the Agricultural Production Systems Research Unit in Australia. APSIM was developed to simulate biophysical process in farming systems, in particular where there is interest in the economic and ecological outcomes of management practice in the face of climatic risk. The paper outlines APSIM's structure and provides details of the concepts behind the different plant, soil and management modules. These modules include a diverse range of crops, pastures and trees, soil processes including water balance, N and P transformations, soil pH, erosion and a full range of management controls. Reports of APSIM testing in a diverse range of systems and environments are summarised. An example of model performance in a long-term cropping systems trial is provided. APSIM has been used in a broad range of applications, including support for on-farm decision making, farming systems design for production or resource management objectives, assessment of the value of seasonal climate forecasting, analysis of supply chain issues in agribusiness activities, development of waste management guidelines, risk assessment for government policy making and as a guide to research and education activity. An extensive citation list for these model testing and application studies is provided. Crown Copyright (C) 2002 Published by Elsevier Science B.V. All rights reserved.

The use of stochastic dynamic programming in optimal landscape reconstruction for metapopulations

A decision theory framework can be a powerful technique to derive optimal management decisions for endangered species. We built a spatially realistic stochastic metapopulation model for the Mount Lofty Ranges Southern Emu-wren (Stipiturus malachurus intermedius), a critically endangered Australian bird. Using diserete-time Markov,chains to describe the dynamics of a metapopulation and stochastic dynamic programming (SDP) to find optimal solutions, we evaluated the following different management decisions: enlarging existing patches, linking patches via corridors, and creating a new patch. This is the first application of SDP to optimal landscape reconstruction and one of the few times that landscape reconstruction dynamics have been integrated with population dynamics. SDP is a powerful tool that has advantages over standard Monte Carlo simulation methods because it can give the exact optimal strategy for every landscape configuration (combination of patch areas and presence of corridors) and pattern of metapopulation occupancy, as well as a trajectory of strategies. It is useful when a sequence of management actions can be performed over a given time horizon, as is the case for many endangered species recovery programs, where only fixed amounts of resources are available in each time step. However, it is generally limited by computational constraints to rather small networks of patches. The model shows that optimal metapopulation, management decisions depend greatly on the current state of the metapopulation,. and there is no strategy that is universally the best. The extinction probability over 30 yr for the optimal state-dependent management actions is 50-80% better than no management, whereas the best fixed state-independent sets of strategies are only 30% better than no management. This highlights the advantages of using a decision theory tool to investigate conservation strategies for metapopulations. It is clear from these results that the sequence of management actions is critical, and this can only be effectively derived from stochastic dynamic programming. The model illustrates the underlying difficulty in determining simple rules of thumb for the sequence of management actions for a metapopulation. This use of a decision theory framework extends the capacity of population viability analysis (PVA) to manage threatened species.

Voluntary disclosure of forward-looking earnings forecasts in Australia

This study examines the voluntary disclosure of future earnings information in annual reports for Australian listed companies. We find that most Australian companies in our sample do not provide quantitative earnings, forecasts in their annual reports, although more than half of the sample do disclose forward-looking information relating to earnings, without specifically disclosing point estimates for the future. These companies mostly supply qualitative information with a positive bias, while the remainder of the sample discloses no forward-looking information relating to earnings. Our findings also suggest that larger companies with less volatile earnings tend to provide more future earnings information than smaller companies with relatively volatile earnings.

SPAnDX: a process-based population dynamics model to explore management and climate change impacts on an invasive alien plant, Acacia nilotica

This paper describes a process-based metapopulation dynamics and phenology model of prickly acacia, Acacia nilotica, an invasive alien species in Australia. The model, SPAnDX, describes the interactions between riparian and upland sub-populations of A. nilotica within livestock paddocks, including the effects of extrinsic factors such as temperature, soil moisture availability and atmospheric concentrations of carbon dioxide. The model includes the effects of management events such as changing the livestock species or stocking rate, applying fire, and herbicide application. The predicted population behaviour of A. nilotica was sensitive to climate. Using 35 years daily weather datasets for five representative sites spanning the range of conditions that A. nilotica is found in Australia, the model predicted biomass levels that closely accord with expected values at each site. SPAnDX can be used as a decision-support tool in integrated weed management, and to explore the sensitivity of cultural management practices to climate change throughout the range of A. nilotica. The cohort-based DYMEX modelling package used to build and run SPAnDX provided several advantages over more traditional population modelling approaches (e.g. an appropriate specific formalism (discrete time, cohort-based, process-oriented), user-friendly graphical environment, extensible library of reusable components, and useful and flexible input/output support framework). (C) 2003 Published by Elsevier Science B.V.