Water Resources Research Act Program

Details for Project ID 2019MI139B

Perceptions of decision support system success: Lessons from the North Central Region

Institute: Michigan
Year Established: 2019 Start Date: 2019-06-01 End Date: 2020-05-31
Total Federal Funds: $11,339 Total Non-Federal Funds: $15,432

Principal Investigators: Douglas Bessette

Project Summary: Decision support systems (DSS) have been utilized extensively over the last two decades to enhance problem-framing (Sandink et al., 2016), help structure decisions around complex natural resource issues (McIntosh et al., 2011), increase end-user learning (Reiter et al., 2017), and/or enrich group collaboration (Newman et al., 2017). While researchers continue to build these computer-based decision tools, rarely are these tools evaluated for their actual impact on decision-making or learning. In the limited literature that explores DSS evaluation, systems are frequently plagued by low rates of adoption (McIntosh et al., 2011; Reiter et al., 2017; Gibson et al., 2017). Additional challenges commonly encountered by DSS developers include end-user participation in DSS development and deployment, DSS sustainability in terms of technology advancements, maintenance and cost, and issues relating to the selection of success indicators and actual assessment of those measures (McIntosh et al., 2011). A recent study by Merritt et al. (2017) conducted a retrospective evaluation of water resource focused models and DSS within Australia, but the evaluation only included modelers/developers and failed to investigate the success of the tools from end-user perspectives. The proposed study seeks to answer the following questions: 1) How have DSS been deployed to address agricultural water quality and quantity issues within the North Central Region?; 2) To what extent have water-focused DSS been successfully implemented?; and 3) Do perceptions of DSS success differ between end-user and DSS developers? Results will support future DSS development and implementation endeavors and add to the limited body of research that examines environmental DSS evaluation. In this study, we will inventory and characterize water-focused DSS used in agricultural contexts in the North Central Region of the United States through an extensive literature review, examining attributes such as purpose (e.g., for research or applied use; what decisions are intended to be supported), DSS features, user audience, adoption, cost, and evaluation method (if any). To enhance and build on this effort, we will develop five case studies that explore the success of implementing water-focused using an adapted framework from prior research. Data will be collected through interviews and analysis will compare responses between and among end-users and developers