Determining the Rationality of Marketing Strategy on Farms

The focus of farm management, as a discipline, has reflected historically the assumption that farms are embedded in near-perfectly competitive market structures. The common validity of this assumption is plain. As open systems, farms have asymmetric relationships with their environment: they are significantly more influenced by it than influencing it. However, farmers seem often not to appreciate the implications of this for their management options. Nor, arguably, is the farm management discipline yet well equipped to analyse initiatives that farmers might contemplate to enhance their control over market outcomes, specifically, as a means of exerting greater control over business performance. In this paper a framework for the analysis of the prospects for product differentiation of farm output is presented in an attempt to fill this lacuna. Introduction As an academic discipline, historically farm management (FM) has been focused on management decision making (Charry and Parton 2002). The domain of physical agricultural production activities may have been taught within farm management qualifications, but the discipline has persistently involved analysis for decisions. Within it farms are characterised as purposeful, open, complex systems having to cope with substantial stochasticity (Dillon 1992). Economics has been the discipline used to most effect to analyse farm management decisions (Malcolm 2004).Farm Management,

One little Lebanese cucumber is not going to break the bank: Price in the choice of fresh fruits and vegetables

This paper reports on empirical research into individual consumer behaviour in the context of fresh fruit and vegetable purchases. The discussion draws on research results from two studies conducted around the actual shopping process. The findings suggest that consumers’ price response behaviour may not be consistent with that predicted by economic theory and that this could be significant at the aggregate level. The existence of ‘acceptable price ranges’ points to the presence of price thresholds within which consumers are relatively insensitive to price movements. Also of relevance is that the primary influence of the budget constraint may be at a broader level rather than at the level of choosing particular products.Demand and Price Analysis, Food Consumption/Nutrition/Food Safety,

CHARACTERISTICS OF DIFFERENT CONSUMER SEGMENTS IN THE AUSTRALIAN BEEF MARKET

Beef consumers in Australia have shown differences in their preferences for products and sensitivity to price. This can be explained by the influence on expected quality of cues related to health, production process and eating experience. Eating experience is difficult to predict as consumers generally do not have enough information to form reliable expectations. In this context, branded beef can help to signal quality and reduce the degree of uncertainty that consumers experience when shopping. Focus group research identified different segments, premiums for preferred products and potential for large-scale differentiation and branding in the Australian market.Beef Branding, Consumer Preferences, Segmentation, Focus Groups.,

PRODUCT AND BRANDING INNOVATIONS IN THE AUSTRALIAN BEEF MARKETING SYSTEM

Meat Standards Australia (MSA) represents a new beef classification system, derived from consumer preferences, which allows classifying beef in interesting ways to consumers and creates the basis for product differentiation and branding. Currently, branding of beef cuts occurs on a limited scale; however, research has revealed clear segmentation across consumers and premiums for preferred products in niche markets. The objective of this study is to identify the potential for large-scale differentiation and branding in the Australian beef marketing system and how this may best be done given the structure of the supply chain.Innovation, Branding, Australian beef marketing system, Livestock Production/Industries, Marketing,

Attitudes, Involvement and Public Support for Pest Control Methods

Public support is crucial to the widespread application of pest control methods both in the form of political support and, where people have direct agency in control methods, compliance with the demands of the methods. It is commonplace for personal behaviours reflecting political support for public policies to be presumed to depend on relevant attitudes, beliefs and values of the person. The finite amount of attention and cognitive effort each person possesses implies that attention and effort are rationed, indicating that changing behaviour requires that the targeted individual is attentive and willing to invest the required cognitive effort; that is, they are motivated to consider new information and, subsequently, to reviewing their attitudes and behaviour. We examine whether attitudes and involvement (a measure of motivation) together provide better predictions of public support for pest control methods than attitudes alone, using the distribution of baits containing sodium fluoroacetate (1080) in New Zealand to control invasive, non-native rats and possums as a case study. We found the novel combination of involvement and attitudes did provide significantly better predictions of an individual's support for using 1080 for the purpose of environmental conservation, and their pest control behaviour, than did attitudes alone

Relative advantage and complexity: Predicting the rate of adoption of agricultural innovations

The adoption of new technologies and practices is fundamental to having the capacity to adapt to climate change and ameliorate resource degradation. Consequently, having the ability to predict the scale and rate of adoption by farmers of agricultural innovations is central to gauging their adaptive capacity. It is also crucial to assessing the likely compliance of farmers with change-seeking incentives and regulations. In this paper we describe a novel approach to predicting rates of adoption with respect to agricultural technologies and practices drawing on a dual-process model of consumer decision-making and a method for describing the complexity of innovations in farm systems. We tested the approach using data collected through a survey of dairy farmers in the Waikato and Waipa regions of New Zealand. In the survey we asked 200 farmers, chosen at random, about their perceptions of the complexity and relative advantage of various agricultural and resource management practices, and collected information as to how long it took them to try, and then adopt, the practices. Our results confirm that the process of forming an intention to try or adopt a technology or practice may take several months for relatively simple technologies and practices, and several years for more complex ones. Importantly, we found that novelty in terms of the originality in the components and architecture of a technology or practice does not necessarily correlate with its complexity in terms of integrating it into farm systems. This means that apparently simple technologies and practices that are promoted to reduce resource degradation can be quite difficult to integrate into farm systems and, as a consequence, the costs of integration may act as a strong deterrent to adopting them. A logical implication of our findings is that a deep understanding of the nature of the integration task is essential to anticipating how long it might take for adoption (or compliance) to occur in agriculture and, therefore, to appreciate limits on the adaptive capacity of farmers. Such an understanding requires an intimate knowledge of the, sometimes diverse, farm systems and sub-systems in which the technology or practice is to be integrated

Motivation, Intention and Action: Wearing Masks to Prevent the Spread of COVID-19

Governments are seeking to slow the spread of COVID-19 by implementing measures that encourage, or mandate, changes in people's behaviour such as the wearing of face masks. The success of these measures depends on the willingness of individuals to change their behaviour and their commitment and capacity to translate that intention into actions. Understanding and predicting both the willingness of individuals to change their behaviour and their enthusiasm to act on that willingness are needed to assess the likely effectiveness of these measures in slowing the spread of the virus. We analysed responses to two different regional surveys about people's intentions and behaviour with respect to preventing the spread of COVID-19 in New Zealand. While motivations and intentions were largely similar across the regions, there were surprisingly large differences across the regions regarding the frequency of wearing face masks. These regional differences were not associated with regional differences in demographics (or in Alert levels) but were associated with regional differences in the number of confirmed cases of COVID-19. The results highlight the importance to policy design of distinguishing the factors that might influence the formation of behavioural intentions from those that might influence the implementation of those intentions

Compliance with Covid-19 measures: Evidence from New Zealand

Governments around the world are seeking to slow the spread of Covid-19 by implementing measures that encourage, or mandate, changes in people's behaviour. These changes include the wearing of face masks, social distancing, and testing and self-isolating when unwell. The success of these measures depends on the commitment of individuals to change their behaviour accordingly. Understanding and predicting the motivation of individuals to change their behaviour is therefore critical in assessing the likely effectiveness of these measures in slowing the spread of the virus. In this paper we draw on a novel framework, the I3 Compliance Response Framework, to understand and predict the motivation of residents in Auckland, New Zealand, to comply with measures to prevent the spread of Covid-19. The Framework is based on two concepts. The first uses the involvement construct to predict the motivation of individuals to comply. The second separates the influence of the policy measure from the influence of the policy outcome on the motivation of individuals to comply. In short, the Framework differentiates between the strength of individuals' motivation and their beliefs about the advantages and disadvantages of policy outcomes and policy measures. We found this differentiation was useful in predicting an individual's possible behavioural responses to a measure and discuss how it could assist government agencies to develop strategies to enhance compliance

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