摘要：Site selection modeling receives much attention in the aviation biofuels literature to ensure sustainability of the aviation biofuel supply chain. These models seek to reflect the multitude of factors and conditions necessary for supply chain success. Social factors impacting that success have received increasingly greater attention but are often excluded due to difficulties in obtaining accurate and standard measures. Some of the most promising work in this arena utilizes a “community capitals approach” to create statistically grounded decision support tools (DSTs) intended to provide rapid assessment of the social characteristics of potential facility locations. Despite the value of the community capitals approach, this methodology is still marked by inconsistent predictivity due to an inability to reliably assess the cultural and historical nuances of local communities that are so vitally important to the long-term viability of these costly projects. This paper more fully examines the Community Assets and Attributes Model (CAAM) that has been developed and applied in the Pacific Northwest to incorporate social assets in site selection modeling. Based on ethnographic fieldwork in Colorado and Wyoming dealing with biomass/bioenergy facility siting, we argue that cultural capital, a key component of the CAAM, is biased to urban locations due to the measurements incorporated. As a result of this bias, current site selection modeling based on the Community Capitals Framework (CCF) does not accurately reflect rural community assets. We assert that the CAAM does not actually measure cultural capital but a product of cultural capital, namely creativity, and innovation Our mixed methods approach that combines quantitative assessment with ethnographic research highlights the limits of the CAAM by revealing that local residents in largely rural counties showed willingness to innovate in some cases but in others referred to history with similar industries that may limit support. The quantitative cultural capital measurements of the CAAM for the four counties we examine, which range in scores from −0.53 to 2, do not capture these dynamics. These scores would generally suggest moderate to high levels of support for biomass/bioenergy facilities, but the ethnographic research provides nuance for or against support that are not reflected in the quantitative capital scores. This suggests that the quantitative CAAM scores could be misleading without added qualitative context. This work demonstrates that a mixed methods approach, combining ethnographic and historical methodologies with existing quantitative community capital approaches, will produce a more effective predictive methodology for facility siting due to its heightened ability to gather critical data on place-based values, beliefs, and historical legacies relating to natural resource development in general, and the timber industry specifically.
