- مبلغ: ۸۶,۰۰۰ تومان
- مبلغ: ۹۱,۰۰۰ تومان
Scientists develop decision support systems (DSSs) to make agricultural science more accessible for farmers and extension officers. Despite the growing use of participatory approaches in agricultural DSS development, reflection on this endeavour has largely focused on the ‘doing’ of participation or the ‘problem of implementation’ when DSSs have not been adopted by stakeholders. There has been little reference to relevant theoretical approaches to the social processes involved in ‘participation’ or ‘implementation’. However, if DSS use is to reach its full potential, a more conceptually informed understanding of how stakeholders collaborate in the participatory development of DSSs is required. To contribute to this conceptualisation, we developed a framework based on three concepts drawn from the field of science and technology studies: technological frames, interpretative flexibility and boundary objects. The framework highlights the importance and value of social learning for participatory DSS development, which relies upon exploring the participating parties’ different perspectives on the agricultural system represented in the DSS. Our framework provides a broad definition of success for participatory DSS development, placing greater weight on learning during the participatory process compared with subsequent use of the DSS by farmers and/or advisors. Two case studies of stakeholder collaboration to develop an irrigation scheduling DSS for sugarcane production were used to explore the relevance of the framework. The concepts in the framework were clearly displayed during the case studies. At the conclusion of the studies there were contrasting outcomes for the DSS. One group of farmers was keen to apply it in their ongoing irrigation management, while another saw little relative advantage in use of the DSS. In both instances co-learning occurred amongst case study participants, so the participatory process was clearly a success.
The declining profitability of agriculture, increasing climatic variability and growing concerns over the environmental impacts of farming pose complex challenges for farm management in Australia (Keating and Carberry, 2010). These challenges have prompted a search for ways in which scientific knowledge can be incorporated into tools that can assist farmers in making farm management decisions. These tools include decision support systems (DSSs), which help make agricultural science more accessible to and useful for farmers (McCown, 2002). Agricultural DSSs are software applications, typically based on computer models that describe various biophysical processes in farming systems and how they respond to different management practices (e.g. irrigation, fertiliser, sowing and harvesting dates) and/or climatic variability (e.g. temperature and rainfall). For example, DSSs may aid the management of cotton crops (e.g. GOSSYM/COMAX; Hodges et al., 1998), optimise nitrogen fertiliser management (e.g. SUNDIAL; Smith et al., 1996; Gibbons et al., 2005), or assess the impact of seasonal climate variability on crop production (e.g. Whopper Cropper; Nelson et al., 2002: Yield Prophet; Hochman et al., 2009).
Our framework combines the concepts of technological frames, interpretative flexibility and boundary objects from science and technology studies with social learning principles, to provide an explanation of the social processes in the participatory development of DSSs. The framework emphasises that, when deployed as a boundary object, a DSS encourages social learning between the farmers, extension officers and scientists involved in its development. Our case studies of the irrigation scheduling DSS WaterSense showed that, by acting as a boundary object, WaterSense was able to help bridge gaps between these parties through an iterative and participatory cycle of discussion and feedback. This involved acknowledging and respecting the different perspectives held by these parties (i.e. interpretative flexibility) and then taking up the opportunity to work together towards a shared understanding (i.e. arriving at more congruent technological frames). Appreciating the way in which a DSS can act as a boundary object recognises how cooperation among these multiple stakeholders can occur, despite the fact that these people can hold diverse perceptions of the DSS or the issue it is designed to address. Instead of defining the success of DSSs solely in terms of ongoing use, the participatory development of a DSS should be evaluated in terms of its ability to foster co-learning and improve practice. Our framework provides those involved in the development of agricultural technologies with new conceptual insights to reflect on their practice. In doing so, our framework contributes to enabling more effective participatory technology development and application processes, and helps DSSs be more effective in guiding sustainable farm management.