decision support systems. Furthermore, each developing country has uniquely local needs and uniquely local solutions to farm problems.

A limited number of systems appear to have been adopted for regular use in the agricultural industries of developed countries. Reasons for the poor rate of adoption have been highlighted in many studies (Parker, Campion, and Kure, 1997). In the United Kingdom, the reasons given for the lack of uptake of model-based systems are (1) lack of a computer base among the population; (2) system complexity; (3) use of inputs that the grower cannot easily provide; and (4) failure to show cost benefits. As a consequence, few DSSs launched in the United Kingdom during the 1990s made any impact on the industry (Parker, 1999).

In the Netherlands, many attempts have been made at the government level to introduce knowledge-based systems on farms, but dissemination speed is very low. Extension services tended to slow down the dissemination of DSSs, rather than promoting these products, for fear of competition from these systems. Furthermore, the use of knowledge-based systems by advisers is still quite low. Experiences (not quantified) also show that the use of these systems by farmers tends to result in extra work and a higher level of support required (Kamp, 1999).

Computer and DSS adoption studies in the United States (Ascough et al., 1999) commonly found that higher levels of farm size, farm income or sales, land ownership (tenancy), and education had positive effects on computer adoption. Increased age had a negative effect. The most frequently cited reasons for lack of adoption were high cost, lack of confidence or skill, not enough time, and small farm size. Other factors shown to have an impact on adoption were farm complexity, debt-asset ratio, exposure or perception that risk is important, and farm type (crop or livestock).

An Australian study (Lynch, Gregor, and Midmore, 2000) revealed that out of the 34 systems for which the information was maintained, only five have been in use. That is, 85 percent of the systems registered were not in use. Stubbs, Markham, and Straw (1998) examined attitudes and perceptions of farmers across five states of Australia as to how they view the computer as a tool in their decision making. Their main findings were

1. for many farmers the computers were seen as time wasters;

2. the majority of farmers are of the noncomputer generation and may see no reason to change their current habit of bookkeeping;

3. for many producers with small holdings, they could not justify the cost in terms of money and time;

4. many failed to see any benefit; and

5. determining which type of computer to buy and what software to use was a major obstacle for many farmers.

From these conclusions it appears that intelligent support systems are not particularly compatible with the current practices or attitudes of farmers.

P. T. Hayman and W. J. Easdown (personal communication) enumerated physical, economical, sociological, and farm management factors that have reinforced or hindered the adoption of WHEATMAN in the northern grain belt of Australia. These factors are also applicable to the other decision support systems. The reinforcing factors are the rapidly increasing access to powerful PCs on farms; the optimism of government agencies and willingness to substantially support DSS development and extension; development of DSSs with a team approach with active involvement of the end users; increasing ease of use of computers and development of user-friendly software; pressure on grain farmers to increase productivity as their profit margin is squeezed; and climate risk forcing careful decisions based on scientific information.

There are numerous factors on the limiting side. Of the farmers who own PCs, it is estimated that less than 22 percent are using them for farm management. The process for testing and releasing early versions of the programs leaves it open to criticism. Positive responses from naive end users create potentially unrealistic perceptions of a program's utility.

Results of surveys (Lewis, 1998; Ascough et al., 1999) suggest that individuals and organizations interested in the promotion of a DSS may enhance the success of its diffusion by

1. targeting farm businesses that already operate manual farm management information systems,

2. transferring appropriate information and knowledge to establish a farm record system that provides management information prior to DSS adoption,

3. targeting young primary industry decision makers who have a relatively high demand for management information to compensate for their relative lack of farming experience,

4. targeting those farm businesses in which spouses provide support in farm management, and

5. targeting farms with higher sales, larger acreages, and more enterprises (both cropping and livestock systems).

Such farms should experience more net benefit in DSS adoption than smaller farms. It is also suggested (Lynch, Gregor, and Midmore, 2000; Cain et al., 2003; Dorward, Galpin, and Shepherd, 2003) that in terms of software development, involvement of the end users in the decision-making process and close participation of the marketing organization are also crucial factors that can influence the acceptance and adoption of the software.

In developing countries, adoption of DSSs at the individual-farmer level is likely to remain at a slow pace until simple, rugged, dust-resistant, and low-cost devices are available. Governments can encourage the adoption of computers and decision support tools by purchasing these in bulk and then selling them to young, educated farmers at a discounted price. DSSs could also be given to village councils for use in community halls or village council offices. Agricultural extension staff could play a major role in disseminating the DSS-derived information to groups of farmers.

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