The design of industrial symbiosis: an input–output approach

Yazan, Devrim Murat; Romano, V.A.; Albino, Vito

doi:10.1016/j.jclepro.2016.03.160

Cited by 67 publications

(32 citation statements)

References 24 publications

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“…For the sake of simplicity, we assume that each firm can send its waste only to one firm and can receive waste only from one firm. Firms' production processes and symbiotic relationships are modeled by adopting the Enterprise Input-Output approach [48,75,76].…”

Section: Methodsmentioning

confidence: 99%

Efficacy of Landfill Tax and Subsidy Policies for the Emergence of Industrial Symbiosis Networks: An Agent-Based Simulation Study

2017

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Abstract:Despite the theoretical value of industrial symbiosis (IS), this approach appears to be underdeveloped in terms of practical applications. Different attempts to stimulate IS in practice are noticed, one of them consisting in the application of adequate policy measures. This paper explores the efficacy of two specific policies (landfill tax and economic subsidy for IS exchanges) in supporting the emergence of self-organized industrial symbiosis networks (ISNs). We frame the ISNs as complex adaptive systems and we design an agent-based model to simulate their emergence. We use a real case study and, by means of the simulation model, we assess how the two policy measures are able to enhance the formation of spontaneous IS relationships, thereby forcing the emergence of the ISN. Results show that both policy measures have a positive effect in all scenarios considered, but the extent is strictly dependent on the environmental conditions in which IS relationships occur. The economic implications for the government are finally discussed.

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Section: Methodsmentioning

confidence: 99%

Efficacy of Landfill Tax and Subsidy Policies for the Emergence of Industrial Symbiosis Networks: An Agent-Based Simulation Study

2017

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“…Lindberg et al [37] also looks at valueadded multipliers and employment effects of the bioeconomy by applying national and regional I-O models of the economy/production. A study more closely related to our work is found in Yazan et al [38], who study the concept of industrial symbiosis on industrial areas, which share characteristics with our bioeconomic industrial clusters. Environmental concerns and I-O models are successfully merged, which has led to the development of the now called environmentally extended input-output (EEIO) analysis, of which a significant body of literature already exists [39].…”

Section: Operations Research In Bioeconomics and In Clustersmentioning

confidence: 63%

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

Nørstebø

Krøgli

Debella-Gilo

et al. 2020

Environ Model Assess

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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.

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“…with: X-n × 1 vector of gross output (sales matrix) Y-n × 1 vector of final demand A-n × n matrix of input coefficients aij with n sectors in the economy (coefficient matrix) I-identity matrix The Input-Output methodology is commonly known in macroeconomic theory, and has been extensively applied to various problems and disciplines [27][28][29][30][31][32]. The main components of the methodology and data base are transactions tables, technical coefficients, and multipliers.…”

Section: Methodology and Datamentioning

confidence: 99%

Socio-Economic Implications of Drought in the Agricultural Sector and the State Economy

Ziolkowska

2016

Economies

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Abstract:In 2011, the most severe drought in Texas history caused $7.62 billion in losses in the agricultural sector alone. This paper analyzes ripple effects of the 2011 drought in Texas agriculture on the entire state economy retrospectively in an effort to foster discussion on targeted mitigation measures in the long term. By using an Input-Output and social accounting matrix model, direct effects on livestock, cotton, sorghum, wheat, corn, hay, and timber production, as well as indirect effects on other related sectors, and finally induced effects from changing consumers behavior have been estimated. According to the results, the 2011 drought caused economic losses of $16.9 billion in the entire Texas economy and increased the unemployment by around 166,895 people. The agricultural sector alone lost around 106,000 jobs. The cotton farming experienced 91% of revenue losses (as compared to 2010), while the livestock production lost 32% in revenue. The decreased production yields and limited market supply directly influence market prices for those products, which might create additional spillover effects on export and import quantities. The presented analysis can be helpful for designing policies to launch mitigation programs for drought events in the future.

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The design of industrial symbiosis: an input–output approach

Cited by 67 publications

References 24 publications

Efficacy of Landfill Tax and Subsidy Policies for the Emergence of Industrial Symbiosis Networks: An Agent-Based Simulation Study

Efficacy of Landfill Tax and Subsidy Policies for the Emergence of Industrial Symbiosis Networks: An Agent-Based Simulation Study

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

Socio-Economic Implications of Drought in the Agricultural Sector and the State Economy

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