Knowledge and markets

An economy is a coordinated system of distributed knowledge. Economic evolution occurs as knowledge grows and the structure of the system changes. This paper is about the role of markets in this process. Traditionally, the theory of markets has not been a central feature of evolutionary economics. This seems to be due to the orthodox view of markets as information-processing mechanisms for finding equilibria. But in economic evolution markets are actually knowledge-structuring mechanisms. What then is the relation between knowledge, information, markets and mechanisms? I argue that an evolutionary theory of markets, in the manner of Loasby (1999), requires a clear formulation of these relations. I suggest that a conception of knowledge and markets in terms of a graphical theory of complex systems furnishes precisely this.

Role of cytokine gene polymorphisms in acute rejection and renal impairment after liver transplantation

Although immunosuppressive regimens are effective, rejection occurs in up to 50% of patients after orthotopic liver transplantation (OLT), and there is concern about side effects from long-term therapy. Knowledge of clinical and immunogenetic variables may allow tailoring of immunosuppressive therapy to patients according to their potential risks. We studied the association between transforming growth factor-beta, interleukin-10, and tumor necrosis factor alpha (TNF-alpha) gene polymorphisms and graft rejection and renal impairment in 121 white liver transplant recipients. Clinical variables were collected retrospectively, and creatinine clearance was estimated using the formula of Cockcroft and Gault. Biallelic polymorphisms were detected using polymerase chain reaction-based methods. Thirty-seven of 121 patients (30.6%) developed at least 1 episode of rejection. Multivariate analysis showed that Child-Pugh score (P =.001), immune-mediated liver disease (P =.018), normal pre-OLT creatinine clearance (P =.037), and fewer HLA class 1 mismatches (P =.038) were independently associated with rejection, Renal impairment occurred in 80% of patients and was moderate or severe in 39%, Clinical variables independently associated with renal impairment were female sex (P =.001), pre-OLT renal dysfunction (P =.0001), and a diagnosis of viral hepatitis (P =.0008), There was a significant difference in the frequency of TNF-alpha -308 alleles among the primary liver diseases. After adjustment for potential confounders and a Bonferroni correction, the association between the TNF-alpha -308 polymorphism and graft rejection approached significance (P =.06). Recipient cytokine genotypes do not have a major independent role in graft rejection or renal impairment after OLT, Additional studies of immunogenetic factors require analysis of large numbers of patients with appropriate phenotypic information to avoid population stratification, which may lead to inappropriate conclusions.

Habitat complexity, spatial interference, and "minimum risk distribution": a framework for population stability

In the past century, the debate over whether or not density-dependent factors regulate populations has generally focused on changes in mean population density, ignoring the spatial variance around the mean as unimportant noise. In an attempt to provide a different framework for understanding population dynamics based on individual fitness, this paper discusses the crucial role of spatial variability itself on the stability of insect populations. The advantages of this method are the following: (1) it is founded on evolutionary principles rather than post hoc assumptions; (2) it erects hypotheses that can be tested; and (3) it links disparate ecological schools, including spatial dynamics, behavioral ecology, preference-performance, and plant apparency into an overall framework. At the core of this framework, habitat complexity governs insect spatial variance. which in turn determines population stability. First, the minimum risk distribution (MRD) is defined as the spatial distribution of individuals that results in the minimum number of premature deaths in a population given the distribution of mortality risk in the habitat (and, therefore, leading to maximized population growth). The greater the divergence of actual spatial patterns of individuals from the MRD, the greater the reduction of population growth and size from high, unstable levels. Then, based on extensive data from 29 populations of the processionary caterpillar, Ochrogaster lunifer, four steps are used to test the effect of habitat interference on population growth rates. (1) The costs (increasing the risk of scramble competition) and benefits (decreasing the risk of inverse density-dependent predation) of egg and larval aggregation are quantified. (2) These costs and benefits, along with the distribution of resources, are used to construct the MRD for each habitat. (3) The MRD is used as a benchmark against which the actual spatial pattern of individuals is compared. The degree of divergence of the actual spatial pattern from the MRD is quantified for each of the 29 habitats. (4) Finally, indices of habitat complexity are used to provide highly accurate predictions of spatial divergence from the MRD, showing that habitat interference reduces population growth rates from high, unstable levels. The reason for the divergence appears to be that high levels of background vegetation (vegetation other than host plants) interfere with female host-searching behavior. This leads to a spatial distribution of egg batches with high mortality risk, and therefore lower population growth. Knowledge of the MRD in other species should be a highly effective means of predicting trends in population dynamics. Species with high divergence between their actual spatial distribution and their MRD may display relatively stable dynamics at low population levels. In contrast, species with low divergence should experience high levels of intragenerational population growth leading to frequent habitat-wide outbreaks and unstable dynamics in the long term. Six hypotheses, erected under the framework of spatial interference, are discussed, and future tests are suggested.

Advances in application of climate prediction in agriculture

Agricultural ecosystems and their associated business and government systems are diverse and varied. They range from farms, to input supply businesses, to marketing and government policy systems, among others. These systems are dynamic and responsive to fluctuations in climate. Skill in climate prediction offers considerable opportunities to managers via its potential to realise system improvements (i.e. increased food production and profit and/or reduced risks). Realising these opportunities, however, is not straightforward as the forecasting skill is imperfect and approaches to applying the existing skill to management issues have not been developed and tested extensively. While there has been much written about impacts of climate variability, there has been relatively little done in relation to applying knowledge of climate predictions to modify actions ahead of likely impacts. However, a considerable body of effort in various parts of the world is now being focused on this issue of applying climate predictions to improve agricultural systems. In this paper, we outline the basis for climate prediction, with emphasis on the El Nino-Southern Oscillation phenomenon, and catalogue experiences at field, national and global scales in applying climate predictions to agriculture. These diverse experiences are synthesised to derive general lessons about approaches to applying climate prediction in agriculture. The case studies have been selected to represent a diversity of agricultural systems and scales of operation. They also represent the on-going activities of some of the key research and development groups in this field around the world. The case studies include applications at field/farm scale to dryland cropping systems in Australia, Zimbabwe, and Argentina. This spectrum covers resource-rich and resource-poor farming with motivations ranging from profit to food security. At national and global scale we consider possible applications of climate prediction in commodity forecasting (wheat in Australia) and examine implications on global wheat trade and price associated with global consequences of climate prediction. In cataloguing these experiences we note some general lessons. Foremost is the value of an interdisciplinary systems approach in connecting disciplinary Knowledge in a manner most suited to decision-makers. This approach often includes scenario analysis based oil simulation with credible models as a key aspect of the learning process. Interaction among researchers, analysts and decision-makers is vital in the development of effective applications all of the players learn. Issues associated with balance between information demand and supply as well as appreciation of awareness limitations of decision-makers, analysts, and scientists are highlighted. It is argued that understanding and communicating decision risks is one of the keys to successful applications of climate prediction. We consider that advances of the future will be made by better connecting agricultural scientists and practitioners with the science of climate prediction. Professions involved in decision making must take a proactive role in the development of climate forecasts if the design and use of climate predictions are to reach their full potential. (C) 2001 Elsevier Science Ltd. All rights reserved.

The future role of government in knowledge-based economies

In this article, we draw together aspects of contemporary theories of knowledge (particularly organisational knowledge) and complexity theory to demonstrate how appropriate conceptual rigor enables both the role of government and the directions of policy development in knowledge-based economies to be identified. Specifically we ask, what is the role of government in helping shape the knowledge society of the future? We argue that knowledge policy regimes must go beyond the modes of policy analysis currently used in innovation, information and technology policy because they are based in an industrial rather than post-industrial analytical framework. We also argue that if we are to develop knowledge-based economies, more encompassing images of the future than currently obtain in policy discourse are required. We therefore seek to stimulate and provoke an array of lines of thought about government and policy for such economies. Our objective is to focus on ideas more than argument and persuasion.

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 nexus of value chain integration and e-business applications on public sector agriculture R&D management

We examine the potential impact of interconnectivity of value chain partnerships through electronic means (e-business practices) on the management of Public Sector Agriculture R&D in Australia. We review the changing forms of managing research and development, the forces driving these changes, and R&D processes that are theoretically consistent with the move towards value chain involvement and the increase in active constituents in Public Sector Agriculture R&D. We then explore the potential of emerging e-business models to change the patterns of inter-connectivity, speed and omnipresence of partners in the value chain. Three e-business R&D management practices are identified that provide the prerequisite flexibility necessary to take advantage of opportunistic markets. These R&D business practices are: compressing R&D to reduce time to market, fostering co-development to enter a market at the last moment and building flexible products that allow adjustment at the last possible moment. Some fundamental reallocation of existing resources will be required to meet these markets. Implications of these e-business practices for R&D management are discussed.

The politics of reintegrating Australian Aboriginal and American Indian indigenous knowledge into resource management: The dynamics of resource appropriation and cultural revival

As the United States and Australia struggle with contemporary crises over competing uses of rapidly depleting natural resources, there are striking parallels between American Indian and Australian Aboriginal communities demanding a place at the management table and offering culturally based understandings of and solutions for the ecosystems at risk. These efforts to integrate indigenous knowledge into mainstream natural resource management are part of larger legal and political debates over land tenure, the locus of control, indigenous self-governance, and holistic ecosystems management.