Structural heterogeneity in farm structures: a configurational approach

Purpose The purpose of this paper is to provide a multidimensional framework for the identification, description and comparative analysis of alternative farm structures and their properties for economic development. Design/methodology/approach Integrating previous typologies and considering a large set of examples, the authors identify six attributes that are necessary to characterize and compare farm structures: size; strategy; organizational form; legal form; who the owners are; and degree of separation of ownership and control. They also discuss potential complementarities between those organizational attributes and specific features of the institutions of developing and emerging countries, such as contract enforcement and property rights protection regime, and developed capital markets and corporate law. Findings Conceptually and empirically, effective farm structures can deviate from the templates traditionally considered – “small family-owned farm” or “large factory-like corporate farm,” combining structural attributes in diverse ways. The dimensionalization of farm structures also helps in revealing complementary institutional traits at the regional or larger system level that may foster development processes. Research limitations/implications The paper is limited to theory building and case-based evidence. Nevertheless, it provides dimensions that can be measured on a larger scale and by quantitative studies. Originality/value This paper sheds light on organizational diversity in agriculture and on a wider set of feasible development paths.

Factors that Influence the Rate and Intensity of Adoption of Improved Irrigation Technologies in Alberta, Canada

Despite the importance of adopting improved irrigation technologies to increase on-farm irrigation efficiency, our understanding of what determines farmers’ adoption decisions in southern Alberta remains relatively poor. The overall goals of this study are to examine the extent of adoption (proportion of all irrigators that have started the adoption process), how far along they are in the adoption process, and the intensity of adoption (percentage of irrigated land on which the technology is adopted) of improved irrigation technologies in southern Alberta, and to assess the major factors that influenced farmers’ adoption decisions. The data were collected in a farm-household survey conducted in the 12 largest irrigation districts (IDs) as well as among private irrigators in southern Alberta. Results show that adoption of improved irrigation technologies is widespread at various levels of intensity. By 2011, 81.3% of farmers had started the adoption process, are now using some kind of improved technology to apply water to their crops, and used it on 76.8% of all irrigated land. The most commonly used irrigation technology is a low pressure center pivot system. Receiving support services following the adoption decision played an important role in increasing the intensity of adoption. Obtaining information on irrigation technologies from individual farmers or farmers’ associations, and extension agencies significantly influenced farmers’ decisions to adopt. Farmers who increased their social capital through attending meetings related to agricultural production practices were more likely to adopt while farmers who participated in recreational or social organizations were less likely to adopt. Finally, the extent and intensity of adoption are higher for those with corporate farm structure, larger families, more generations of ownership and higher education.

Examination of pig farm technology by computer simulation

Agricultural production is among the riskiest production activities. Similarly to other branches of agriculture in animal breeding the finished product is the result of complex procedures. The biological technological procedure, the creation of the product is affected by an outstanding number of environmental factors which also cause uncertainties. In the North Great Plain Region of Hungary, sows, gilts and slaughter pigs are produced on a corporate farm. The reliable operation data of this company provide a stable basis for and estimating future costs and revenue and their distributions. Monte Carlo methods are one of the generally accepted tools for modeling risks. The significant independent variables, their ranges and probability distributions, and the correlation between them were inputs to the model. The values of the variables were produced using a random number generator. The computer simulation was performed using @Ris (PalisadeCorporation) software. The study concentrates on the factors affecting the number of off spring (piglets). Model inputs were the mating, mortality and farrowing rates; the costs and the income values based on these rates have been analysed as the output data of the model.

The changing face of the farming community: Lone Star Farms

Lone Star Farms, which was formed in 1996, is not a corporate farm in the classical sense, but a family farm run on corporate lines, currently comprising 10 properties throughout the South Island. Four of these properties are partially pastoral leasehold, five are freehold, and one is Puponga Farm Park at the base of Farewell Spit in NW Nelson, which is leased from the Department of Conservation. We are solely a sheep and beef cattle enterprise, with a geographic range which gives a good spread of climatic and market risk. Last winter we carried approximately 128,000 sheep and beef cattle stock units, and we are budgeted to increase next year to 140,000 su. There are nine Farm Managers and generally 20 other permanent farm staff. We have a Head Office, situated in Nelson, which, on the farming side of the business, consists of one Operations Co-ordinator and the equivalent of 2.5 administrative and clerical staff, giving a ratio of one farm staff member to 4600 su, and one support staff member to 40,000 su. The first consideration once we assume ownership of a property is to address subdivision, soil fertility, pasture species, and animal genetics, and once these are taken care of, we begin utilising our management strengths. In terms of Land, Labour, and Capital, it is the Labour component (i.e. managerial expertise regarding timing, decision-making and control) which will take us forward, once the basic building blocks of productivity are in place.