Academic journal article Rural Society

Encouraging the Adoption of Decision Support Systems by Irrigators

Academic journal article Rural Society

Encouraging the Adoption of Decision Support Systems by Irrigators

Article excerpt

Introduction

Despite their potential, the uptake of many decision support systems1 (DSS) by farmers has been surprisingly slow (Lynch, Gregor & Midmore, 2000; McCown, 2002, Stephens & Middleton, 2002; Hayman, 2004; Stone & Hochman, 2004). Various reasons have been suggested to explain why uptake has been limited. Lynch, Gregor and Midmore (2000) suggested that the main problem is poor design. They contend that many DSS have not been designed using participatory approaches and as a result have not been tailored to farmers' decision making processes. McMaster et al. (2002) similarly suggest that many DSS are too difficult for farmers to use and suffer from a poor understanding of how farmers process information. Stone and Hochman (2004) suggest that there are reasons other than poor design that explain the low uptake of DSS. They argue that the primary reason for the poor rate of adoption is that, most DSS are developed and released without much, if any, reference to the basic precepts of marketing, (p.7). They advocate understanding the groups or segments of farmers within the market, what their needs and preferences are, and how to price and distribute DSS to the targeted segments. The usefulness of identifying market segments amongst farmers for the purpose of encouraging adoption of new technologies or practices has been suggested in previous studies (eg Kaine & Lees 1994; Darbyshire 1999; Watson & Pryor 2002), nonetheless there is limited evidence in the literature regarding the use of marketing approaches in the design and delivery of DSS.

Rather, models developed in the sociological and economic literatures have primarily been used to explain the diffusion of new technologies, and based on these models recommendations for improving rates of adoption have been developed. One of the first models in the sociology literature to explain the diffusion process was developed by Rogers (1962) who drew on insights from Ryan and Gross (1943). Ryan and Gross (1943) first observed that awareness and adoption of agricultural innovations (eg hybrid corn) followed bell type (or normal) distributions. Ryan and Gross, who were sociologists, explained this process of diffusion by what they described as an interaction effect. According to Rogers (1962), this is a process through which farmers who have already adopted a new technology influence those who have not yet adopted. Using data from a number of independent studies of new product adoption by farmers, Rogers (1962) divided different farmers into groups according to how quickly they adopted new technologies. Innovators are the first to adopt, and comprise about 2.5% of the farmer population. These are followed by early adopters (13.5% of the farmer population), the early majority (34%), the late majority (34%), and laggards (16%). Earlier adopters tend to be wealthier, more educated, more established, more risk preferring, more immune to social pressure, and have a greater range of contacts where they can acquire new information. Empirical evidence does support the importance of these variables in explaining adoption (eg Ervin & Ervin, 1982; Rahm & Huffman, 1984; Lynne, Shonkwiler & Rola 1988; Caffey & Kazmierczak, 1994; Zepeda & Castillo, 1997; Soule, Tegene & Wiebe, 2000; Khanna Epouhe & Hornbaker, 2001; Soule, 2001). However, other studies have demonstrated that the characteristics are not always related to early adoption (Wilkening, Tully & Presser, 1962; Goss, 1979).

An implication of the diffusion model is that more widespread adoption of new technologies can be encouraged by directly targeting and promoting to innovators and early adopters. These groups are central to encouraging diffusion amongst the majority of farmers. If these groups adopt a new technology and find it satisfactory, they will effectively market the technology to other farmers through their interaction with them. This implies that when developing a strategy for encouraging diffusion effort should be given to tailoring the product to the preferences of earlier adopters. …

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