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Integrating human and physical systems is a daunting challenge that spans a great many problem domains, including social and economic production systems, residential behaviors, environmental exchange, and resource and land use. Because so much current research continues to be focused within rather than across these areas, our cumulative knowledge in many respects is little more than a simple summation of various disciplinary and sub-disciplinary learning curves, rather than a truly integrated, synergistic base of understanding. Indeed, a complete understanding of any subdomain may not even be possible in the absence of domain integration. Even within some subdomains, there may be very few instances of truly cumulative science, where one scholar's work adopts another's directly as the foundation for a new and tightly integrated cumulative model. If it were possible to speed the diffusion of modeling innovations and research findings within and among subdomains, the cumulative frontiers of knowledge could be expected also to advance apace.We believe that the future of research in regional science, and indeed in all social science modeling, will be based on a research infrastructure that leverages the power of networked individuals focusing their collective intellect on problem R. Jackson ( )

This study introduces and applies a modelling system that is suitable for the impact assessment of environmental innovations referred to as "Blue Economy" innovations. The paper's contribution to the literature is threefold. First, the building of a multi-sector computable general equilibrium (CGE) model, which provides the theoretical framework for studying the economic impacts of using waste as a production input. Second, the creation of an empirical methodology through which new Blue Economy technologies can be concretely accounted for in regional input-output tables. Since Blue Economy innovations are mostly built on local inputs, their effects are primarily local. Third, given that interregional spillovers of local impacts might also be significant, through interregional trade or migration, a modelling approach that can follow complex spatial processes is applied. The broader model framework chosen is the GMR-Europe model.

The authors report on the economic impacts of introducing woody biomass processing in an economically distressed, but heavily forested Central Appalachian U.S. region. Woody biomass is a readily available unconventional energy source that has the potential to boost the rural region’s economy. They use a static regional computable general equilibrium model to assess long-run economic impacts of two woody biomass processing production pathways of biomass to ethanol through fermentation and biomass to biofuel through fast pyrolysis. While the 232 to 370 jobs and $13 million to $21 million income might seem small relative to the multicounty region, the localized impact on the county in which the facility would be sited, even for the direct jobs and income impacts, would be much more substantial. The authors conclude that woody biomass processing is a viable economic development option for the study area and similar rural regions.

This paper introduces and applies a model system that is suitable for the impact assessment of Blue Economy innovations. Our contribution to the literature is threefold. First, we build a multi-sector computable general equilibrium (CGE) model, which provides the theoretical frame for studying the economic impacts of using waste as a production input. Second, we create an empirical methodology through which new technologies of Blue Economy can be concretely accounted for in regional input-output tables. Since Blue Economy innovations are largely built on local inputs, their effects are primarily local. Given that interregional spillovers of local impacts might also be significant, through interregional trade or migration, we applied a modelling approach that is able to follow complex spatial processes. The broader model framework chosen is the GMR-Europe model.