A Participatory Approach for Analyzing and Modeling Decision Processes: A Case Study on Cultivation Planning

A Participatory Approach for Analyzing and Modeling Decision Processes: A Case Study on Cultivation Planning

Kathrin Kirchner, Ivonne Erfurth, Sarah Möckel, Tino Gläßer, André Schmidt
DOI: 10.4018/978-1-61520-881-4.ch007
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Most decision analytic research does not focus on initial steps of modeling and mostly concentrates on selecting preexisting algorithms. In this chapter we present how we can formalize decision intensive business processes based on a case study on a Decision Support System (DSS) for cultivation planning. Decisions in this problem area depend notably on expertise and experience acquired by the farmer. As a first step the decision process of the agriculturist needs to be explored, analyzed and documented. Afterwards all information and data, which leads up to a decision, will be collected, systemized and grouped. We will apply user participative techniques that integrate the farmer as a cooperative partner into the modeling process. The outcome of this modeling leads to a formalized model later on. On account of this approach the DSS will represent the real decision process of the farmer and increases trust in the decisions suggested by the system.
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For long-term decision cultivation planning an introduction of a DSS can be helpful. The development of such a DSS needs expertise from three different research areas. The DSS is domain-driven, in our case, based on the agricultural application. Thus, information about the cultivation planning and expert knowledge of farmers will be incorporated into the DSS Analysis. Similarly knowledge from decision science (with roots in management and psychology) and requirements engineering flow directly into the DSS Analysis. Hence, we will investigate in more detail various decision and process models we can use or adapt for analyzing and modeling such a DSS (Fig. 1). In the following, we will introduce background knowledge of these three areas.

Figure 1.

Survey of related research areas


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