Gordon S FEMC2007

Uncovering Social and Analytical Factors Contributing to the Successful Application of Decision Support Systems for Forest Biodiversity Management

Sean N. Gordon, USDA Forest Service, PNW Research Station SDO CAP, 6th Floor, P.O. Box 3890, Portland, OR, 97208, USA, sgordon@fs.fed.us

The complexity of forest management has increased with the scope of resources of concern and the level of scrutiny from stakeholders. The design and use of specialized computer software, often referred to as decision support systems (DSS), is one method for helping managers deal with this complexity. This study investigated the utility of such DSS in relation to forest biodiversity decisions. Four in-depth case studies were conducted on how DSS were used in different problem solving situations. Participant interviews and available documentation were reviewed using a four-part, qualitative framework. First, participants were asked how they judged success of the efforts (success measures) and what factors contributed the most to the outcome (success factors). Contrary to the analytical view of DSS, the more social measures of stakeholder evaluations and contribution to consensus building were found to be the most popular measures of success. The second part of the framework compared and contrasted the applicability of success factors taken from existing analytical and social theories on these cases.

Three analytical factors were drawn from information systems theory (system quality, information quality, and service quality), and four social factors were taken from the environmental assessment literature (participation, communication, translation, and mediation). These factors covered participants explanations well and helped reveal additional aspects of the cases not directly expressed by the interviewees. Third, the cases were examined for a mutual and recursive pattern of analysis and deliberation, and, fourth, it was hypothesized that participants in less conflicted situations would use fewer social indicators of success, and that as social complexity increased, simpler tools would be more successful. Neither of these expectations was supported by this group of cases.