Identifying Suitable Bioeconomic Cluster Sites\u2014Combining GIS-MCDA and Operational Research Methods

Vibeke Nørstebø,Svein Olav Krøgli,Kristin T Uggen,Wenche E Dramstad,Gerardo A Perez-Valdes,Misganu Debella-Gilo

doi:10.1007/s10666-020-09694-x

Abstract

A transition to a bioeconomy implies an increased focus on efficient and sustainable use of biological resources. A common, but often neglected feature of these resources is their location dependence. To optimize their use, for example in bioeconomic industrial clusters, this spatial aspect should be integrated in analyses. Optimal design and localization of a bioeconomic cluster with respect to the various biological and non-biological resources required for the cluster, the composition of industrial facilities in the cluster, as well as the demands of the outputs of the cluster, is crucial for profitability and sustainability. We suggest that optimal design and location of bioeconomic clusters can benefit from the use of a Multicriteria Decision Analysis (MCDA) in combination with Geographic Information Systems (GIS) and Operations Research modeling. The integration of MCDA and GIS determines a set of candidate locations based on various criteria, including resource availability, accessibility, and usability. A quantitative analysis of the flow of resources between and within the different industries is then conducted based on economic Input-Output analysis. Then, the cluster locations with the highest potential profit, and their composition of industrial facilities, are identified in an optimization model. A case study on forest-based bioeconomic clusters in the Østfold county of Norway is presented to exemplify this methodology, the expectation being that further implementation of the method at the national level could help decision makers in the planning of a smoother transition from a fossil-based economy to a bioeconomy.

Highlights

A bioeconomy is “an economy where the basic building blocks for materials, chemicals and energy are derived from renewable biological resources” [1]
Overall sustainability and a holistic view of resource optimization across sectors are emphasized by a Nordic Innovation Report [7]: “bioeconomic innovations target resource-efficient use of valuable bioresources”
While forest biomass is only one example of a resource important in the bioeconomy, we found that its wide distribution, policy focus, and range of uses made it interesting for a first case study, testing the combination of Geographic Information Systems (GIS)-Multicriteria Decision Analysis (MCDA) and Operations Research (OR) optimization modeling focused on potential location of bioeconomic industrial clusters

Summary

Introduction

A bioeconomy is “an economy where the basic building blocks for materials, chemicals and energy are derived from renewable biological resources” [1]. The need and desire for a transition from a fossil-based economy to a bioeconomy is well established at the European [2, 3], Nordic [4], and Norwegian level [5, 6]. The goal is to maximize the cluster’s collective efficiency while at the same time provide economic, environmental, and social benefits, which is an expected and desired outcome from the bioeconomic transition. This offers a cross-sector perspective on renewable resources, in line with both national and international strategies

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Conclusion