Tahir Rehman

Using social-psychology models to understand farmers’ conservation behaviour

Abstract Research into farmers’ attitudes and motivations in the past has tended to be subjective and theoretically rather imprecise. This paper presents findings from research based on the structured social-psychology model, the Theory of Planned Behaviour, into farmers’ conservation-related behaviour. Responses from a survey of 100 Bedfordshire farmers were analysed to identify the underlying determinants of behaviour and to comprehend farmers’ attitudes. Farmers with greater environmental awareness, members of the Farming and Wildlife Advisory Group, are more influenced by conservation-related concerns and less by farm management concerns than other farmers. They appear also to be more influenced by farming and conservation referent groups, grants and conservation advice.

Typification of farming systems for constructing representative farm models: two illustrations of the application of multi-variate analyses in Chile and Pakistan

Abstract If the fundamental precepts of Farming Systems Research were to be taken literally then it would imply that for each farm ‘unique’ solutions should be sought. This is an unrealistic expectation, but it has led to the idea of a recommendation domain, implying creating a taxonomy of farms, in order to increase the general applicability of recommendations. Mathematical programming models are an established means of generating recommended solutions, but for such models to be effective they have to be constructed for ‘truly’ typical or representative situations. The multi-variate statistical techniques provide a means of creating the required typologies, particularly when an exhaustive database is available. This paper illustrates the application of this methodology in two different studies that shared the common purpose of identifying types of farming systems in their respective study areas. The issues related with the use of factor and cluster analyses for farm typification prior to building representative mathematical programming models for Chile and Pakistan are highlighted.

Logit models for identifying the factors that influence the uptake of new ‘no-tillage’ technologies by farmers in the rice–wheat and the cotton–wheat farming systems of Pakistan's Punjab

Abstract In the ‘rice–wheat’ and the ‘cotton–wheat’ farming systems of Pakistans Punjab, late planting of wheat is a perennial problem due to often delayed harvesting of the previously planted and late maturing rice and cotton crops. This leaves very limited time for land preparation for ‘on-time’ planting of wheat. ‘No-tillage’ technologies that reduce the turn-round time for wheat cultivation after rice and cotton have been developed, but their uptake has not been as expected. This paper attempts to determine the farm and farmer characteristics and other socio-economic factors that influence the adoption of ‘no-tillage’ technologies’. Logit models were developed for the analysis undertaken. In the ‘cotton–wheat’ system personal characteristics like education, tenancy status, attitude towards risk implied in the use of new technologies and contact with extension agents are the main factors that affect adoption. As regards the ‘rice–wheat’ system, resource endowments such as farm size, access to a ‘no-tillage’ drill, clayey soils and the area sown to the rice–wheat sequence along with tenancy and contact with extension agents were dominant in explaining adoption.

The application of the MCDM paradigm to the management of agricultural systems: Some basic considerations

Abstract Since the early seventies some path-breaking research, mainly in management science, has extended and developed the frontiers of mathematical programming and other similar approaches to a new paradigm for dealing with multiple-criteria in decision-making. The applications of such techniques and methods have not been particularly common in relation to agricultural systems, even though some significant theoretical and methodological contributions have emerged from the analysis of watershed management and forestry resource-use problems. This paper provides a ‘state-of-the-art’ review of the general nature of the main multiple criteria decision making methods and emphasises the theoretical and practical aspects of their use rather than the specific technicalities of individual techniques. The main purpose of this exercise is to encourage the use of multiple criteria decision making methodologies in the analysis of agricultural systems.

Multiple-criteria decision-making techniques and their role in livestock ration formulation

Abstract The livestock ration formulation problem is postulated within the framework of multiple-criteria decision-making techniques. This exercise is motivated by the fact that the ordinary least-cost approach can, and does, generate solutions that either cannot be implemented or supply nutritionally undesirable levels of various nutrients. This originates from using cost as the criterion for selecting the ingredients of the diet. But in fact, diet formulation problems involve several criteria and should, therefore, be solved using techniques designed for modelling such problems. This paper is an attempt at introducing these techniques to agricultural systems modellers and then demonstrating their use in livestock ration formulation. The multiple-criteria decision-making techniques covered include goal programming and its variants such as weighted and lexicographic approaches and multiple-objective programming.

Goal programming with penalty functions and livestock ration formulation

Abstract This paper contends that the conventional linear programming paradigm commonly used for livestock ration formulation suffers from several inherent weaknesses. One such weakness is the mathematical rigidity that must be respected to meet the minimum nutritional requirements specified in the model, thus making the paradigm inflexible and unrealistic under many situations. Goal programming techniques, on the other hand, do not impose such rigid conditions and also allow consideration of several decision criteria. This paper represents a departure from the traditional LP approach by formulating the diet formulation problem as a GP model incorporating penalty functions that make the specification of minimum levels of nutrients more flexible and realistic.

Application of multiple criteria decision making methods to farm planning: A case study

Abstract The three Multiple Criteria Decision Making (MCDM) techniques: goal programming (GP), multi-objective programming (MOP) and compromise programming (CP) are discussed in terms of their usefulness for practical farm planning. Application of these methods is illustrated by using the example of a University farm in the UK. The model is of a modest size consisting of 8 constraints and 9 activities and incorporates different objectives. These objectives include: maximization of total gross margin; maximization of permanent labour utilization; minimization of hiring of labour; minimization of annual total variable costs; and, maximization of business trading surplus. Solutions obtained by each method are compared and commented upon with regard to their relative merits in farm planning.

Farm and socio-economic characteristics of smallholder milk producers and their influence on technology adoption in Central Mexico

In order to identify the factors influencing adoption of technologies promoted by government to small-scale dairy farmers in the highlands of central Mexico, a field survey was conducted. A total of 115 farmers were grouped through cluster analysis (CA) and divided into three wealth status categories (high, medium and low) using wealth ranking. Chi-square analysis was used to examine the association of wealth status with technology adoption. Four groups of farms were differentiated in terms of farms’ dimensions, farmers’ education, sources of incomes, wealth status, management of herd, monetary support by government and technological availability. Statistical differences (p < 0.05) were observed in the milk yield per herd per year among groups. Government organizations (GO) participated little in the promotion of the 17 technologies identified, six of which focused on crop or forage production and 11 of which were related to animal husbandry. Relatives and other farmers played an important role in knowledge diffusion and technology adoption. Although wealth status had a significant association (p < 0.05) with adoption, other factors including importance of the technology to farmers, usefulness and productive benefits of innovations together with farmers’ knowledge of them, were important. It is concluded that the analysis of the information per group and wealth status was useful to identify suitable crop or forage related and animal husbandry technologies per group and wealth status of farmers. Therefore the characterizations of farmers could provide a useful starting point for the design and delivery of more appropriate and effective extension.

A linear programming formulation of the Markovian decision process approach to modelling the dairy replacement problem

Abstract In modelling the replacement decision in dairy herd management, the most common approach taken is to use dynamic programming to determine the optimal policy by comparing the future expected profitability of an animal to that of its potential replacement. It does not, however, take into account the performance of the entire herd or that of all potential replacements, which is particularly important if replacements originate from the same herd. This paper demonstrates how to overcome this inadequacy by formulating the problem as a multi-component Markovian decision process and then solving it as an associated linear programming model. The proposed methodology is illustrated by using a simple, but realistic, example for determining the optimal replacement strategy for a dairy herd over a 10-year planning horizon. The results show that replacements should be bred from heifer cows in order to increase the genetic turnover; however, no more animals than is necessary should be culled to increase this turnover. It is also shown how to include considerations such as problems of milk quota management, and other similar resource allocation decisions into the model. Additional improvements to the model could involve considering culling of animals suffering from disease.

Formulating generalised 'goal games' against nature: An illustration from decision-making under uncertainty in agriculture

Abstract The games-against-nature approach to the analysis of uncertainty in decision-making relies on the assumption that the behaviour of a decision-maker can be explained by concepts such as maximin, minimax regret, or a similarly defined criterion. In reality, however, these criteria represent a spectrum and, the actual behaviour of a decision-maker is most likely to embody a mixture of such idealisations. This paper proposes that in game-theoretic approach to decision-making under uncertainty, a more realistic representation of a decision-maker’s behaviour can be achieved by synthesising games-against-nature with goal programming into a single framework. The proposed formulation is illustrated by using a well-known example from the literature on mathematical programming models for agricultural-decision-making.