If farmers are to prosper in this turbulent economic environment they must manage their productive resources more efficiently and become more effective business managers. There appears to be wide-spread enthusiasm by rural extension services and some private organisations for promoting the effectiveness and efficiency of farm management through the use of computer-based management innovation. Innovative computer-based management tools have the potential to increase the quantity and quality of information available for decision making. Used in conjunction with modems, computers will soon provide the opportunity for remote farm businesses to access new sources of management information through connection to the Information Superhighway and the World Wide Web (MacKenzie, 1996).
Many previous studies examining the diffusion of computer innovation in the farming community investigated factors associated with the act of adoption. In reality, most farm computers become part of a management information system. It is believed that the success of diffusion programs for computer-based management innovation may be enhanced if promoters could gain a clearer understanding of the evolution, or growth in sophistication, of farm management information systems (FMIS). This study attempts to promote a clearer understanding by describing characteristics of farm businesses and their FMIS, examining the major milestones in the evolution of FMIS, and by identifying some of the factors related to the level of sophistication of FMIS.
1.1. Objectives of the study
The three main objectives of this study are:
1.
Describe the characteristics of farm businesses which provide the context for the examination of FMIS.
2.
Describe the characteristics and examine the major milestones in the evolution of FMIS.
3.
Identify factors associated with the level of sophistication of FMIS.
1.2. Background
The literature examining diffusion of innovation, and that more specifically related to the innovative behaviour of farmers, suggests several factors potentially significant to the adoption and use of computer-based management innovation within the context of FMIS. This literature also provides insight into the characteristics of farm businesses and FMIS.
1.2.1. Innovative behaviour
An innovation is a product or a methodology that an individual perceives to be new even if it has been available for some considerable length of time (Scheuing, 1989). Within the context of a farm business, both record keeping methods and computers are seen as innovations. Therefore, the adoption and use of bookkeeping/accounting methods and computer technology is interpreted as innovative behaviour. Using Rogers (1995)five adopter categories of: innovators; early adopters; early majority; late majority; and laggards as a framework several general factors related to innovative behaviour are identified in the diffusion literature. When contrasted with laggards, innovators tend to be younger, more formally educated individuals who actively seek information about new ideas (Rogers, 1995 and Scheuing, 1989). Also, it is reasonable to expect that individuals who adopt business computers would also adopt other items of office innovation. Adopter category groups tend to be normally distributed and on average there are: 2.5% innovators; 13.5% early adopters; 34% early majority; 34% late majority, and 16% laggards (Scheuing, 1989).
1.2.2. Age and length of farming experience
Age has an established correlation to computer adoption (Lazarus and Smith, 1988, Batte et al., 1990a and Huffman and Mercier, 1991), and length of farming experience has been shown to be correlated to age. No studies were located that conclusively linked the length of farming experience to adoption issues, but several suggested a correlation between farming experience and information preferences (Batte et al., 1990b and Fearne, 1990). Length of farming experience may be a hidden component in the relationship between age and farm business innovation adoption, especially computer adoption. Several studies examining the use of management information commented that older farmers do not use as many sources of information as their younger colleagues as they are more likely to rely on their experience in farming (Ford and Babb, 1989 and Batte et al., 1990b). Therefore, older more experienced farm decision makers are expected to maintain farm record systems that are comprised of a smaller number of the less complicated record types, which may reduce their demand for computer-based management innovation.
1.2.3. Spouse's involvement in farm management
There is an abundance of literature that suggests spouses make an important contribution to farm management through an involvement in farm production tasks, business decision making, farm record maintenance, and computer operation (Rosenfeld, 1985James, 1989Alston, 1990). Chamala and Crouch (1977)suggest adoption of farm innovation may have a stronger relationship with wives' rather than husbands' personal demographics. During field work they observed that some farm women played an important role in record keeping, and suggested the relative physical isolation of farming properties may increase the opportunity for the involvement of both husband and wife in farm business decision making. Sawer (1973)found a general correlation between wives' supporting role as a homemaker and mother, and their husband's acceptance of technological change. Haney (1990)stated that research traditions into work roles had: "reinforced a methodological focus on the individual" as the unit of analysis, and saw `work' and `family' as separate domains for the involvement of men and women respectively. Alston (1990)is critical of the lack of recognition traditionally given to the contribution of farm women. Only in the last one or two decades has there been any serious attempt to assess the true value of farm women's contribution to farm management. It is anticipated that the support provided by spouses in farm management will be related to the number and complexity of records comprising the farm record system, and the adoption and use of computers.
1.2.4. Characteristics of farm businesses and FMIS
Results from a number of studies indicate that farm size is related to adoption of a business computer, and to the use of information by farmers (Garcia et al., 1983Putler and Zilberman, 1988Batte et al., 1990bFearne, 1990Schnitkey et al., 1992). However, Huffman and Mercier (1991)found a significant relationship to computer adoption for their model of farming complexity which incorporated measures for both farm size and type of farming activity, while their variable for farm size alone was not significant at the 5% level. Schnitkey et al. (1991)reported that `enterprise mix' was a significant factor related to the type of accounting system operated by farmers, although only a binary variable indicating a dairy enterprise was included in their study. While they are inconclusive, these results do suggest that despite the wide support for farm size as an indicator of innovative behaviour, a combination of farm size and a count of the commodities raised by a farm business may provide a more reliable indicator of innovation adoption. Both farm size and the number of commodities are seen as relative indicators of the size or `scale' of the farm business.
Information and decision making are inseparable (Kallman and Reinharth, 1984). A system for providing information is vital to a business decision making process (Kast and Rosenweig, 1981). Farm decision makers use information from a wide range of sources, but, one of the most valuable source of specialised information about the farm operation is provided by a farm record system (FRS) (Osburn and Schneeberger, 1983 and Schnitkey et al., 1991). A FRS can include financial and production record types (Sonka, 1983). It may be as simple as a basic cash book, or so large and complex that it requires the processing capabilities of a computer to maintain it efficiently. Information provided by a FRS can be (i) passed to individuals or organisations outside the farm business, such as accountants to prepare tax returns and bankers to support loan applications, or (ii) used within the farm gate to support the business decision making process (Scudamore, 1985).
With the exception of variables representing the scale of the farming operation, variables included in the study do display an association with the three segments of farm businesses. Therefore, the concept of contiguous increase in sophistication of the FMIS is valid. Results also indicate that the three segments of farm businesses do represent the major milestones in the evolution of FMIS. Results of hypotheses tests suggest the level of sophistication of FMIS in the study population is related more to common business factors rather than factors specific to farming activities. The number and complexity of farm records incorporated into FRS are directly related to the level of sophistication of FMIS. Prime decision makers who utilise the more sophisticated forms of FMIS appear to be generally more innovative, and use a larger number of common office innovations. Younger prime decision makers' relatively high demand for management information is, at least in part, to compensate for their relative lack of farming experience. Support of farm management functions by spouses is significant, and they should be targeted as well as prime decision makers as potential users of computer-based management innovation.
In consideration of the contiguous nature of the increase in sophistication of the FMIS, the success of adoption of a computer-supported FMIS is seen to depend on the prior use of a manual FMIS, which indicates an established demand for information specifically related to the farm operation. Therefore, individuals and organisations interested in the promotion of computer-based management innovation may enhance the success of their diffusion programs by: (a) targeting farm businesses that already operate manual FMIS, or (b) transferring appropriate information and knowledge, or supplementary innovation to establish a FRS that provides management information for decision making prior to computer adoption. Further, in relation to the factors associated with computer adoption, promoters may gain increased acceptance if they package computer innovation so that it supports or promotes a strong business orientation and offers an integration of office technologies that provides a cost advantage over the purchase of separate items of office equipment.
Results can also be used to extrapolate implications for the future adoption and use of the internet. The relationship of the Internet to FMIS is depicted in Fig. 4. Again, In consideration of the contiguous nature of the increase in sophistication of the FMIS, the success of adoption and use of the internet is seen to be dependent on: (i) the operation of a FRS, which demonstrates an established demand for management information specifically related to the farm operation, and (ii) experience with computers, gained predominantly through the operation of a computer-supported FMIS.
Therefore, individuals and organisations interested in promoting the adoption and use of the Internet may improve the success of their diffusion programs by: (a) targeting farm businesses operating computer-supported FMIS, or (b) by transferring to other farm businesses appropriate information and knowledge, or supplementary innovation designed to increase the sophistication of their FMIS prior to adoption. Notwithstanding other supply-side barriers to internet use, promoters may gain increased acceptance if they can ensure that adopters are able to access management information that is currently obtained from less convenient or more expensive sources.
