Identifying Suitable Bioeconomic Cluster Sites—Combining GIS-MCDA and Operational Research Methods

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.Operations Research methods are a useful way to include costbenefit comparison in the analysis. According to Bjørndal et al. [21], "OR methods for bioeconomics" is indeed its own field of study, describing methods applied to agriculture, fishing, forestry, and mining. Despite rather different time scales of the production systems, objectives, and resources, there are commonalities, specifically, the need for multicriteria approaches, and explicit consideration of the environment.Designing eco-industrial clusters is a topic getting more and more attention. Boix et al. [22] state that most research studies focus on the optimal design of an industrial cluster network while taking into account separately water, energy, and materials. Linear and non-linear programming are used to analyze and decide on optimal design, e.g., multiobjective linear programming approach for forest management [23], optimal exploitation of fish considering environmental factors Nørstebø V. et al.

Enhancing sustainability within industrial cooperative networks through the evaluation of economically compromised entities

“…Regarding tools/techniques for practicing the CE concept through symbiosis for sustainable industrial development, Yu et al (2021) proposed an ABM approach integrating geographic information systems (GIS) to explore IS for recycling concrete aggregates to tackle the CE challenge while lacking economic incentives. Similarly, for optimal design and location of bioeconomic clusters, multicriteria decision analysis (MCDA) integrated with GIS is used to consider the quantitative analysis of the flow of resources based on economic input-output analysis (Perez-Valdes et al, 2019;Nørstebø et al, 2020). For waste material recycling and exchange decisions, Huang et al (2020) proposed a mixed-integer programming method, where the raw material price and by-product recycling are the two main cost elements of the waste material.…”

Bioeconomic Clusters—Background, Emergence, Localization and Modelling

“…Refer to [44] for a detailed mathematical description and analysis examples demonstrating model capabilities on a finer scale, the main decision variables include: Values for these variables are obtained by solving the set of equations aimed at maximizing the combined profits for all the clusters, defined as the difference between revenues and costs. The latter consists of investment, harvest, transportation, purchase and operational costs for the clusters and facilities in them, while the former assumes everything which is harvested or produced is sold for its monetary value.…”

Land Suitability Analysis for Identifying Industrial Zones in Duhok District, Kurdistan Region of Iraq

“…The geographic information system (GIS) is a powerful tool for spatial analysis that provides the functionality to capture, store, query, analyze, display, and output geographic information [6]. The capability of GIS makes it beneficial for environmental management and planning and in combination with other geoinformatics techniques have widely been used for various environmental studies such as land use/land cover change detection [7,8,9,10,11], environmental quality assessment [12,13,14,15,16], and site selection and land suitability analysis [17,18,19].…”