878 resultados para Cooperative marketing of farm produce


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This article takes a critical discourse approach to one aspect of the Australian WorkChoices industrial relations legislation: the government’s major advertisement published in national newspapers in late 2005 and released simultaneously as a 16-page booklet. This strategic move was the initial stage of one of the largest ‘information’ campaigns ever mounted by an Australian government, costing more than $AUD137 million. This article analyse the semiotic (visual and graphic) elements of the advertisement to uncover what these elements contribute to the message, particularly through their construction of both an image of the legislation and a portrayal of the Australian worker. We argue for the need to fuse approaches from critical discourse studies and social semiotics to deepen understanding of industrial relations phenomena such as the ‘hard sell’ to win the hearts and minds of citizens regarding unpopular new legislation.

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The importance of agriculture in many countries has tended to reduce as their economies move from a resource base to a manufacturing industry base. Although the level of agricultural production in first world countries has increased over the past two decades, this increase has generally been at a less significant rate compared to other sectors of the economies. Despite this increase in secondary and high technology industries, developed countries have continued to encourage and support their agricultural industries. This support has been through both tariffs and price support. Following pressure from developing economies, particularly through the World Trade Organisation (WTO), GATT Uruguay round and the Cairns Group developed countries are now in various stages of winding back or de-coupling agricultural support within their economies. A major concern of farmers in protected agricultural markets is the impact of a free market trade in agricultural commodities on farm incomes, profitability and land values. This paper will analyse both the capital and income performance of the NSW rural land market over the period 1990-1999. This analysis will be based on several rural land use classifications and will compare the total return from rural properties based on the farm income generated by both the average farmer and those farmers considered to be in the top 20% of the various land use areas. The analysis will provide a comprehensive overview of rural production in a free trade economy.

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Purpose - The paper examines the benefits of further diversifying a global portfolio of financial assets with New Zealand farm real estate (FRE). ---------- Design/methodology/approach - We compare efficient sets generated with and without farm real estate using portfolio theory. ---------- Findings - The results show that given the predominantly negative correlation between FRE and financial assets, the risk-return tradeoffs of portfolios of financial assets can be improved significantly. The diversification benefits measured in terms of risk reduction, return enhancement, and improvement in the Sharpe performance ratios are robust under a number of FRE risk-return scenarios as well as under high and low inflationary periods. Using 5- and 10-year rolling periods we also find that FRE is a consistent part of risk efficient portfolios. Consistent with the results reported in Lee and Stevenson (2006) for UK real estate the risk reduction benefits of diversifying with FRE are larger than the risk enhancement benefits. ---------- Practical implication - The results suggest that FRE takes on a consistent role of risk-reducer rather than a return-enhancer in a globally diversified portfolio. FRE appears to deserve more serious consideration by investment practitioners that it has been accorded in the past. Originality/value – The study examines the role of direct real estate in a globally diversified portfolio of financial assets.

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Purpose – This paper aims to outline the challenges and tasks involved in a organising and marketing a new venture from conception to sales. It presents an interesting situation with which readers can identify and apply knowledge and skills associated with entrepreneurship and marketing and link this with the key learning objectives of a new venture marketing study unit. Design/methodology/approach – The case is constructed around key principles of marketing and entrepreneurship linked to a description of a contemporary venture written from a participant observer perspective supplemented with knowledge from interviews and archival research. Findings – The case shows how effective a diligent, creative approach to developing and selling a new venture can be. It demonstrates that effective marketing requires more than rote adoption of basic principles – it requires creative thinking and enterprising adaption of relevant principles to address the specific and well defined objectives of the venture. Research limitations/implications – The case is not intended to prescribe a particular marketing method or process; rather it is meant to stimulate creativity in the use of marketing knowledge and skills. Practical implications – The case represents an effective resource for both formal and informal teaching and learning. It demonstrates the requirement for innovative and creative adoption of marketing concepts to fit the demands of a new venture. Originality/value – The case specifically addresses an identified need for learning resources and information tailored to the area of entrepreneurial new venture marketing.

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In this paper we describe cooperative control algorithms for robots and sensor nodes in an underwater environment. Cooperative navigation is defined as the ability of a coupled system of autonomous robots to pool their resources to achieve long-distance navigation and a larger controllability space. Other types of useful cooperation in underwater environments include: exchange of information such as data download and retasking; cooperative localization and tracking; and physical connection (docking) for tasks such as deployment of underwater sensor networks, collection of nodes and rescue of damaged robots. We present experimental results obtained with an underwater system that consists of two very different robots and a number of sensor network modules. We present the hardware and software architecture of this underwater system. We then describe various interactions between the robots and sensor nodes and between the two robots, including cooperative navigation. Finally, we describe our experiments with this underwater system and present data.

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While the economic and environmental benefits of fisheries management are well accepted, the costs of effective management in low value fisheries, including the research necessary to underpin such management, may be considerable relative to the total economic benefits they may generate. Co-management is often seen as a panacea in low value fisheries. Increasing fisher participation increases legitimacy of management decision in the absence of detailed scientific input. However, where only a small number of operators exist, the potential benefits of co-management are negated by the high transaction cost to the individual fishers engaging in the management process. From an economic perspective, sole ownership has been identified as the management structure which can best achieve biological and economic sustainability. Moving low value fisheries with a small number of participants to a corporate-cooperative management model may come close to achieving these sole ownership benefits, with lower transaction costs. In this paper we look at the applicability of different management models with industry involvement to low value fisheries with a small number of participants. We provide an illustration as to how a fishery could be transitioned to a corporate-cooperative management model that captures the key benefits of sole management at a low cost and is consistent with societal objectives.

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The problem of learning correct decision rules to minimize the probability of misclassification is a long-standing problem of supervised learning in pattern recognition. The problem of learning such optimal discriminant functions is considered for the class of problems where the statistical properties of the pattern classes are completely unknown. The problem is posed as a game with common payoff played by a team of mutually cooperating learning automata. This essentially results in a probabilistic search through the space of classifiers. The approach is inherently capable of learning discriminant functions that are nonlinear in their parameters also. A learning algorithm is presented for the team and convergence is established. It is proved that the team can obtain the optimal classifier to an arbitrary approximation. Simulation results with a few examples are presented where the team learns the optimal classifier.

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A cooperative game played in a sequential manner by a pair of learning automata is investigated in this paper. The automata operate in an unknown random environment which gives a common pay-off to the automata. Necessary and sufficient conditions on the functions in the reinforcement scheme are given for absolute monotonicity which enables the expected pay-off to be monotonically increasing in any arbitrary environment. As each participating automaton operates with no information regarding the other partner, the results of the paper are relevant to decentralized control.

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This paper examines the idea that plasticity in farm management introduces resilience to change and allows farm businesses to perform when operating in highly variable environments. We also argue for the need to develop and apply more integrative assessments of farm performance that combine the use of modelling tools with deliberative processes involving farmers and researchers in a co-learning process, to more effectively identify and implement more productive and resilient farm businesses. In a plastic farming system, farm management is highly contingent on environmental conditions. In plastic farming systems farm managers constantly vary crops and inputs based on the availability of limited and variable resources (e.g. land, water, finances, labour, machinery, etc.), and signals from its operating environment (e.g. climate, markets), with the objective of maximising a number of, often competing, objectives (e.g. maximise profits, minimise risks, etc.). In contrast in more rigid farming systems farm management is more calendar driven and relatively fixed sequences of crops are regularly followed over time and across the farm. Here we describe the application of a whole farm simulation model to (i) compare, in silico, the sensitivity of two farming systems designs of contrasting levels of plasticity, operating in two contrasting environments, when exposed to a stressor in the form of climate change scenarios;(ii) investigate the presence of interactions and feedbacks at the field and farm levels capable of modifying the intensity and direction of the responses to climate signals; and (iii) discuss the need for the development and application of more integrative assessments in the analysis of impacts and adaptation options to climate change. In both environments, the more plastic farm management strategy had higher median profits and was less risky for the baseline and less intensive climate change scenarios (2030). However, for the more severe climate change scenarios (2070), the benefit of plastic strategies tended to disappear. These results suggest that, to a point, farming systems having higher levels of plasticity would enable farmers to more effectively respond to climate shifts, thus ensuring the economic viability of the farm business. Though, as the intensity of the stress increases (e.g. 2070 climate change scenario) more significant changes in the farming system might be required to adapt. We also found that in the case studies analysed here, most of the impacts from the climate change scenarios on farm profit and economic risk originated from important reductions in cropping intensity and changes in crop mix rather than from changes in the yields of individual crops. Changes in cropping intensity and crop mix were explained by the combination of reductions in the number of sowing opportunities around critical times in the cropping calendar, and to operational constraints at the whole farm level i.e. limited work capacity in an environment having fewer and more concentrated sowing opportunities. This indicates that indirect impacts from shifts in climate on farm operations can be more important than direct impacts from climate on the yield of individual crops. The results suggest that due to the complexity of farm businesses, impact assessments and opportunities for adaptation to climate change might also need to be pursued at higher integration levels than the crop or the field. We conclude that plasticity can be a desirable characteristic in farming systems operating in highly variable environments, and that integrated whole farm systems analyses of impacts and adaptation to climate change are required to identify important interactions between farm management decision rules, availability of resources, and farmer's preference.

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Formation of high value procurement networks involves a bottom-up assembly of complex production, assembly, and exchange relationships through supplier selection and contracting decisions, where suppliers are intelligent and rational agents who act strategically. In this paper we address the problem of forming procurement networks for items with value adding stages that are linearly arranged We model the problem of Procurement Network Formation (PNF) for multiple units of a single item as a cooperative game where agents cooperate to form a surplus maximizing procurement network and then share the surplus in a stable and fair manner We first investigate the stability of such networks by examining the conditions under which the core of the game is non-empty. We then present a protocol, based on the extensive form game realization of the core, for forming such networks so that the resulting network is stable. We also mention a key result when the Shapley value is applied as a solution concept.

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Dendritic cells (DCs) as sentinels of the immune system are important for eliciting both primary and secondary immune responses to a plethora of microbial pathogens. Cooperative stimulation of a complex set of pattern-recognition receptors, including TLR2 and nucleotide-binding oligomerization domain (NOD)-like receptors on DCs, acts as a rate-limiting factor in determining the initiation and mounting of the robust immune response. It underscores the need for ``decoding'' these multiple receptor interactions. In this study, we demonstrate that TLR2 and NOD receptors cooperatively regulate functional maturation of human DCs. Intriguingly, synergistic stimulation of TLR2 and NOD receptors renders enhanced refractoriness to TGF-beta- or CTLA-4-mediated impairment of human DC maturation. Signaling perturbation data suggest that NOTCH1-PI3K signaling dynamics assume critical importance in TLR2- and NOD receptor-mediated surmounting of CTLA-4- and TGF-beta -suppressed maturation of human DCs. Interestingly, the NOTCH1-PI3K signaling axis holds the capacity to regulate DC functions by virtue of PKC delta-MAPK-dependent activation of NF-kappa B. This study provides mechanistic and functional insights into TLR2-and NOD receptor-mediated regulation of DC functions and unravels NOTCH1-PI3K as a signaling cohort for TLR2 and NOD receptors. These findings serve in building a conceptual foundation for the design of improved strategies for adjuvants and immunotherapies against infectious diseases.