اثر یک رویکرد مشارکتی در توسعه موفقیت آمیز سیستم های پشتیبانی تصمیم کشاورزی : در مورد Pigs2win

This paper explores how a decision support system (DSS) can be developed that complies with the critical success factors of such systems. A participatory approach is used to develop Pigs2win, a DSS for Flemish pig farms. Pigs2win uses frontier analysis for comparative farm analysis. The participatory approach influences the selection of stakeholders, objective setting and evaluation of Pigs2win. Outcomes of the participatory approach result in features of Pigs2win that positively influence its compliance with critical success factors. Based on our experience with Pigs2win, we put forward points that need attention when a participatory approach is organized.

Today's decision makers need to find good solutions to increasingly complex problems [49] and [65]. Farm decision making is no exception. Due to the intensification of agricultural production and concerns relating to environmental impacts, farmers are now required to deal with a wider range of issues [19], [32] and [80]. As the complexity of decisions increases, managers increasingly lack the necessary expertise to make decisions that integrate the range of issues involved [80]. Decision support systems (DSSs) aim to help managers with their decision-making by offering information access, model analysis and supporting tools [27]. Multiple agricultural DSSs have been developed, addressing a variety of issues. These issues include measuring farm sustainability (e.g., [40], [55], [75] and [76]), improving manure management (see overview by [31]), simplifying livestock feeding decisions (e.g., [14], [23], [34] and [35]), improving crop production systems (e.g., [11], [24], [30], [66] and [70]) or subsystems like fertilizer use (e.g., [18], [22] and [69]), pest management (e.g., [36] and [56]), irrigation (e.g., [39] and [71]), yield (e.g., [6], [26] and [58]) and cultivar selection (e.g., [29] and [47]), improving pig production aspects like nutrition of growing pigs (e.g., [74]) and sows (e.g., [15]), sow productivity (e.g., [64]), disease control (e.g., [82]) and tail biting prevention (e.g., [2] and [3]). Despite the wealth of available technologies, decision support has widely failed to fulfill expectations [43], [45], [53], [57] and [80]. Many studies report on the poor uptake of agricultural DSSs (e.g., [10], [19], [20], [25], [33], [37], [42], [44], [46], [50], [51], [52], [53], [54], [58], [63] and [80]). Reasons for the low adoption rate include that the DSS is too complex, uses a terminology and logic unfamiliar to farmers, is not frequently updated, requires tedious data input, is irrelevant, unreliable and/or inflexible and is not easily accessible for users. The gap between science and practice is also often mentioned as a reason why DSSs are not implemented. The objective of this paper is to explore how a DSS can be developed that complies with the critical success factors of such tools. Multiple authors emphasize the positive impact of participatory processes involving stakeholders on DSS' success (e.g., [5], [16], [33], [38], [44], [57], [61], [63], [72] and [80]). In this paper, a participatory approach is used to develop Pigs2win, a DSS for Flemish farrow-to-finish farms. Decision making in pig farming can be considered as a typical case of simultaneously trying to improve productivity and reduce environmental pressure, mainly caused by nutrient emissions. Advice in pig farming is mainly based on the use of traditional key performance indicators (KPIs). Popular KPIs are feed conversion (kg feed per kg live weight gain), production costs (euro per kg produced live weight) and labor income (expressed per delivered pig, average finisher present, or labor unit). Traditional KPIs are easy to communicate but have shortcomings when assessing benchmarks for comparative farm analysis [73]. Compared to traditional KPIs, frontier analysis (see [8] for an introduction to frontier analysis) is more suitable for assessing farm-specific benchmarks and improvement paths [17] and [73]. Frontier methods measure technical, economic and/or environmental performance by positioning firms against a best practice frontier. Frontier methods are frequently used in management science, but they are currently not used in practice for pig farm advice, mainly because farmers and advisors are not familiar with these methods. A challenge for the participatory approach in this paper is the incorporation of frontier analysis in Pigs2win. The paper is structured as follows: Section 2 puts forward critical success factors of DSSs that can be influenced during the development process. Section 3 presents the participatory approach that is used to design and evaluate Pigs2win. Section 4 describes how the participatory method resulted in features of Pigs2win that comply with the success factors of DSSs. This section also highlights the interference between frontier analysis and success factors. Section 5 concludes and provides advice on organizing a participatory approach for building DSSs.

In this paper, a participatory approach is used to develop Pigs2win, a DSS for Flemish pig farms that uses frontier analysis for comparative farm analysis. The participatory approach influences the selection of stakeholders, objective setting and evaluation of Pigs2win, and contributes to the compliance of the DSS with its critical success factors. The approach provides an added value to the development of Pigs2win. Based on our experience, we put forward points that need attention when a participatory approach is organized. We distinguish between the selection of stakeholders, the collaboration of stakeholders and the flexibility of the participatory approach. The selection of stakeholders should be based on their possible contribution to the result of the participatory process. After all, this result directly depends on their participation. We selected stakeholders based on the objective of Pigs2win and the aim to develop a DSS that is both scientifically sound and usable in practice. Our stakeholder group initially consisted of sixteen members and was expanded during the developing process with three additional members. The diversity of stakeholders allowed us to develop a DSS that combines scientific and practical knowledge. The size and composition of the stakeholder group also enabled the creation of a broad support by the Flemish pig sector, which was also one of our goals. The three members that were added during the participatory process were farm advisors, who were identified as potential users of Pigs2win. Expanding the stakeholder group with potential users of the DSS clearly created an added value to the development process. The success of a participatory approach not only depends on the selection of appropriate stakeholders, but also on their collaboration. During the development of Pigs2win, the discussions among stakeholders were constructive and resulted in a sound progress of the developing process. Multiple reasons for this constructive collaboration can be mentioned. First, ever since the beginning of the participatory process, all stakeholders felt the need to develop something like Pigs2win, which resulted in a common objective. Second, a high level of transparency was provided to all stakeholders, as they were involved from the beginning of the development process and contributed to defining the objective, choosing modeling tools, discussing the conceptual model and testing and improving the DSS. Moreover, all important decisions were taken during plenary meetings. Consequently, all stakeholders felt involved in the process, which improved their collaboration. A third reason for the constructive collaboration is the focus on using a simple language during the participatory process. Stakeholders with a different background may use a jargon that is difficult to understand by other stakeholders. Therefore, stakeholders were instructed to avoid this jargon and use a simple language during the discussions. Other reasons for the good collaboration include the size of the stakeholder group, which enabled a smooth discussion, and the fact that all stakeholders had equal power to influence the participatory process. Finally, the fact that there were no considerable conflicts among stakeholders may also have improved the collaboration. Third, we believe that the flexibility of a participatory approach contributes to its success. The available time and defined scope must, however, be respected. The approach followed to develop Pigs2win was flexible in the sense that both the general objective and the composition of the stakeholder group were adapted during the developing process. These changes obviously contributed to the success of the process, but were only adopted because they did not compromise the available amount of time and fell within the scope of the project. Also the way of completing the developing steps put forward by Borenstein [1] was adapted to our specific case. We did not a priori provide a detailed roadmap for each step, but discussed the fulfillment with the stakeholders that were involved. Anyhow, we always kept in mind that the different developing steps had to be completed within the available amount of time. For a successful completion of a participatory approach, a balance has to be found between allowing for flexibility and respecting the available time period and defined scope. Our participatory approach resulted in the DSS Pigs2win. The ultimate aim of Pigs2win is to facilitate the selection of preferable management decisions. The DSS allows for identifying farm-specific suboptimal KPIs and assessing aggregate economic and environmental effects of improving these suboptimal KPIs. Pigs2win does not give any direct advice on which concrete management decision to take. The reason why some KPIs are suboptimal for a particular farm is after all highly farm-specific. Therefore, it is left to the user to detect preferable concrete management decisions, based on information on KPIs. Farm advisors are mainly seen as intended users of the tool, as they probably have the most knowledge of the set of available management decisions and their link with KPIs. Pigs2win allows for comparing aggregate effects of different management decisions under different scenarios (e.g. fixed or variable number of sows, fixed or variable finishing stable occupation). These scenarios are themselves part of a concrete management decision and allow for a detailed comparison. It may be interesting to use Pigs2win in combination with radio frequency identification (RFID), a technology that is increasingly being used for continuously monitoring individual pigs. This monitoring may facilitate a continuous assessment of KPIs, that can be linked to Pigs2win to analyze the evolution of farm performances. If a farm, for example, follows the weight of pigs with a RFID-based system, Pigs2win can be used to assess the effect of altering weights on the performance of the farm. A RFID-based system may also be used for analyzing the variation in performances between pigs on a farm. In that case, the effect at farm level of improving the performance of, for example, the worst performing pigs can be calculated with Pigs2win. Pigs2win has now grown into a successfully developed and evaluated DSS. A participatory development approach resulted in features of Pigs2win that contribute to the compliance with critical success factors of DSSs. The next step is to implement the system. Users who have access to data sets of pig farms can use Pigs2win as a standalone system through updating the reference set of pig farms themselves. Users who do not have access to such data sets must be frequently provided with an updated set of reference farms. This may complicate the implementation, as it requires a continuous link between the user of the DSS and the provider of the data set of reference farms. Successful implementation may also require substantial efforts for marketing the DSS and actively providing support to manage institutional barriers to adoption [80].