Increasing profits and reducing risks in crop production using participatory systems simulation approaches

The development of cropping systems simulation capabilities world-wide combined with easy access to powerful computing has resulted in a plethora of agricultural models and consequently, model applications. Nonetheless, the scientific credibility of such applications and their relevance to farming practice is still being questioned. Our objective in this paper is to highlight some of the model applications from which benefits for farmers were or could be obtained via changed agricultural practice or policy. Changed on-farm practice due to the direct contribution of modelling, while keenly sought after, may in some cases be less achievable than a contribution via agricultural policies. This paper is intended to give some guidance for future model applications. It is not a comprehensive review of model applications, nor is it intended to discuss modelling in the context of social science or extension policy. Rather, we take snapshots around the globe to 'take stock' and to demonstrate that well-defined financial and environmental benefits can be obtained on-farm from the use of models. We highlight the importance of 'relevance' and hence the importance of true partnerships between all stakeholders (farmer, scientists, advisers) for the successful development and adoption of simulation approaches. Specifically, we address some key points that are essential for successful model applications such as: (1) issues to be addressed must be neither trivial nor obvious; (2) a modelling approach must reduce complexity rather than proliferate choices in order to aid the decision-making process (3) the cropping systems must be sufficiently flexible to allow management interventions based on insights gained from models. The pro and cons of normative approaches (e.g. decision support software that can reach a wide audience quickly but are often poorly contextualized for any individual client) versus model applications within the context of an individual client's situation will also be discussed. We suggest that a tandem approach is necessary whereby the latter is used in the early stages of model application for confidence building amongst client groups. This paper focuses on five specific regions that differ fundamentally in terms of environment and socio-economic structure and hence in their requirements for successful model applications. Specifically, we will give examples from Australia and South America (high climatic variability, large areas, low input, technologically advanced); Africa (high climatic variability, small areas, low input, subsistence agriculture); India (high climatic variability, small areas, medium level inputs, technologically progressing; and Europe (relatively low climatic variability, small areas, high input, technologically advanced). The contrast between Australia and Europe will further demonstrate how successful model applications are strongly influenced by the policy framework within which producers operate. We suggest that this might eventually lead to better adoption of fully integrated systems approaches and result in the development of resilient farming systems that are in tune with current climatic conditions and are adaptable to biophysical and socioeconomic variability and change. (C) 2001 Elsevier Science Ltd. All rights reserved.

Testing insect movement theory: empirical analysis of pest data routinely collected from agricultural crops

Observations of an insect's movement lead to theory on the insect's flight behaviour and the role of movement in the species' population dynamics. This theory leads to predictions of the way the population changes in time under different conditions. If a hypothesis on movement predicts a specific change in the population, then the hypothesis can be tested against observations of population change. Routine pest monitoring of agricultural crops provides a convenient source of data for studying movement into a region and among fields within a region. Examples of the use of statistical and computational methods for testing hypotheses with such data are presented. The types of questions that can be addressed with these methods and the limitations of pest monitoring data when used for this purpose are discussed. (C) 2002 Elsevier Science B.V. All rights reserved.

Participatory approach for the identification of dairy industry needs in the design of research, development and extension actions: Australian and Brazilian case studies

In both Australia and Brazil there are rapid changes occurring in the macroenvironment of the dairy industry. These changes are sometimes not noticed in the microenvironment of the farm, due to the labour-intensive nature of family farms, and the traditionally weak links between production and marketing. Trends in the external environment need to be discussed in a cooperative framework, to plan integrated actions for the dairy community as a whole and to demand actions from research, development and extension (R, D & E). This paper reviews the evolution of R, D & E in terms of paradigms and approaches, the present strategies used to identify dairy industry needs in Australia and Brazil, and presents a participatory strategy to design R, D & E actions for both countries. The strategy incorporates an integration of the opinions of key industry actors ( defined as members of the dairy and associated communities), especially farm suppliers ( input market), farmers, R, D & E people, milk processors and credit providers. The strategy also uses case studies with farm stays, purposive sampling, snowball interviewing techniques, semi-structured interviews, content analysis, focus group meetings, and feedback analysis, to refine the priorities for R, D & E actions in the region.

Vector Error-Correction Models in a consumer packaged goods category forecasting decision support system

A framework for developing marketing category management decision support systems (DSS) based upon the Bayesian Vector Autoregressive (BVAR) model is extended. Since the BVAR model is vulnerable to permanent and temporary shifts in purchasing patterns over time, a form that can correct for the shifts and still provide the other advantages of the BVAR is a Bayesian Vector Error-Correction Model (BVECM). We present the mechanics of extending the DSS to move from a BVAR model to the BVECM model for the category management problem. Several additional iterative steps are required in the DSS to allow the decision maker to arrive at the best forecast possible. The revised marketing DSS framework and model fitting procedures are described. Validation is conducted on a sample problem.

Minding the money: A growing responsibility for informal carers

Managing the assets of older people is a common and potentially complex task of informal care with legal, financial, cultural, political and family dimensions. Older people are increasingly recognised -as having significant assets, but the family, the state, service providers and the market have competing interests in their use. Increased policy interest in self-provision and user-charges for services underline the importance of asset management in protecting the current and future health, care and accommodation choices of older people. Although 'minding the money' has generally been included as an informal care-giving task, there is limited recognition of either its growing importance and complexity or of care-givers' involvement. The focus of both policy and practice have been primarily on substitute decision-making and abuse. This paper reports an Australian national survey and semi-structured interviews that have explored the prevalence of non-professional involvement in asset management. The findings reveal the nature and extent of involvement, the tasks that informal carers take on, the management processes that they use, and that 'minding the money' is a common informal care task and mostly undertaken in the private sphere using some risky practices. Assisting informal care-givers with asset management and protecting older people from financial risks and abuse require various strategic policy and practice responses that extend beyond substitute decision-making legislation. Policies and programmes are required: to increase the awareness of the tasks, tensions and practices surrounding asset management; to improve the financial literacy of older people, their informal care-givers and service providers; to ensure access to information, advice and support services; and to develop better accountability practices.

Science-policy in environmental and health risk assessment: if we cannot do without, can we do better?

How can empirical evidence of adverse effects from exposure to noxious agents, which is often incomplete and uncertain, be used most appropriately to protect human health? We examine several important questions on the best uses of empirical evidence in regulatory risk management decision-making raised by the US Environmental Protection Agency (EPA)'s science-policy concerning uncertainty and variability in human health risk assessment. In our view, the US EPA (and other agencies that have adopted similar views of risk management) can often improve decision-making by decreasing reliance on default values and assumptions, particularly when causation is uncertain. This can be achieved by more fully exploiting decision-theoretic methods and criteria that explicitly account for uncertain, possibly conflicting scientific beliefs and that can be fully studied by advocates and adversaries of a policy choice, in administrative decision-making involving risk assessment. The substitution of decision-theoretic frameworks for default assumption-driven policies also allows stakeholder attitudes toward risk to be incorporated into policy debates, so that the public and risk managers can more explicitly identify the roles of risk-aversion or other attitudes toward risk and uncertainty in policy recommendations. Decision theory provides a sound scientific way explicitly to account for new knowledge and its effects on eventual policy choices. Although these improvements can complicate regulatory analyses, simplifying default assumptions can create substantial costs to society and can prematurely cut off consideration of new scientific insights (e.g., possible beneficial health effects from exposure to sufficiently low 'hormetic' doses of some agents). In many cases, the administrative burden of applying decision-analytic methods is likely to be more than offset by improved effectiveness of regulations in achieving desired goals. Because many foreign jurisdictions adopt US EPA reasoning and methods of risk analysis, it may be especially valuable to incorporate decision-theoretic principles that transcend local differences among jurisdictions.

Accounting for management costs in sensitivity analyses of matrix population models

Traditional sensitivity and elasticity analyses of matrix population models have been used to p inform management decisions, but they ignore the economic costs of manipulating vital rates. For exam le, the growth rate of a population is often most sensitive to changes in adult survival rate, but this does not mean that increasing that rate is the best option for managing the population because it may be much more expensive than other options. To explore how managers should optimize their manipulation of vital rates, we incorporated the cost of changing those rates into matrix population models. We derived analytic expressions for locations in parameter space where managers should shift between management of fecundity and survival, for the balance between fecundity and survival management at those boundaries, and for the allocation of management resources to sustain that optimal balance. For simple matrices, the optimal budget allocation can often be expressed as simple functions of vital rates and the relative costs of changing them. We applied our method to management of the Helmeted Honeyeater (Lichenostomus melanops cassidix; an endangered Australian bird) and the koala (Phascolarctos cinereus) as examples. Our method showed that cost-efficient management of the Helmeted Honeyeater should focus on increasing fecundity via nest protection, whereas optimal koala management should focus on manipulating both fecundity and survival simultaneously, These findings are contrary to the cost-negligent recommendations of elasticity analysis, which would suggest focusing on managing survival in both cases. A further investigation of Helmeted Honeyeater management options, based on an individual-based model incorporating density dependence, spatial structure, and environmental stochasticity, confirmed that fecundity management was the most cost-effective strategy. Our results demonstrate that decisions that ignore economic factors will reduce management efficiency.

The influence of national culture on the level and outcome of IS decision making in the IS maintenance/redevelopment decision

Would the outcome of a Global multinational organization’s decision be the same if the same decision were to be made in different countries throughout the world? Within the same organization, we propose that national cultural differences can influence decision making in different countries and cultural clusters. While much work has been done on organizational cultural influences, this study examines the influence that national culture has on organizational decision making in respect to the evolution/redevelopment decision that organizations face when a system is believed to be entering the obsolescence phase. Building on findings from the Globe research program, we show by empirical testing of a theoretical model that national cultural dimensions are significantly associated with a) the outcome of the decision to enhance or re-develop a system, and b) the organizational level at which such decisions are made. This research is significant as a means to improve management decision making, particularly with regard to the enhancement versus re-development decision. The research suggests that a relatively uniform sub-culture exists across the global IS project level but that national cultural dimensions play a more important role in determining the organizational management level at which decisions are made.

A Research Agenda for Strategic Management Research in Developing Countries

This paper explores the extent to which it is possible to address issues pertaining to developing countries with significant socio-cultural and political interventions. Examples from the Sri Lankan tea plantations are used to illustrate the necessity to understand the context from actors’ perspectives using rigorous case study research, before making prescriptive recommendations. Current problems faced by the Sri Lankan tea industry are identified as not merely micro-institutional or managerial. We argue that their roots lie in reproduction of social struggles at the level of production. We propose a research agenda, in the doctrine of critical theory, for exploring the formation and implementation of business strategies in developing countries, using the tea plantation sector as a case. Our primary attempt here is to conceptualize strategic management in the context of political economy and to identify central issues to be addressed. Accordingly, we argue that researching historical dynamics of strategic management facilitates understanding and interpreting the articulation of modes of production in a given social formation. We further argue that a highly context specific research agenda is required to fully comprehend idiosyncratic characteristics of Sri Lankan strategy structures and organizational forms. Then, it is proposed that explaining the role of social formation in shaping and reshaping strategy relations should be at the centre of the research due to the social significance attached to ‘strategy’. Finally, methodological and epistemological necessities arising from the nature of strategy relationships are discussed.

Organizational actions in response to threats and opportunities

In this study, we tested a model in which threats and opportunities lead directly to different organizational actions and compared it to a model in which organizational characteristics moderate organizational actions taken in response to threats and opportunities. To better understand these effects, we differentiated the dimensions of threat and opportunity associated with the threat-rigidity hypothesis from the dimensions associated with prospect theory. In this study, threats had the main and moderated effects predicted from the literature, but opportunities did not.