Linear economy is a conventional model based on the "take-make-consume-waste" approach, conversely circular economy (CE) focuses on the circular approach to the energy and materials use, providing environmental, economic and social benefits for the stakeholders involved in production, distribution and consumption chains. The fundamental transition from a linear economy to a CE requires a large amount of data to increasing knowledge of consumption of natural resources and negative externalities. Among the economic sectors, agriculture strongly contributes to the consumption of resources (e.g. water and energy), to the greenhouse gas emissions and waste (e.g. wastewater) generation. The data required to optimize the transition to CE are often disaggregated, difficult to find, out of date and complex to consult by some agricultural stakeholders. The scientific literature associated with this emerging and new topic presented a shortage of papers (Klerkx, et al., 2019). To address this gap we presented this analysis regarding the third topic group, subsection (modelling and simulation). The aim of this research is to identify a data-set model in order to enable stakeholders to know the most suitable sustainability indicators and finally to implement the best CE model. We used a variety of digital sources, including bibliographic platforms, international and digital tools, EU and regional regulations. The methodological path includes the following phases: a) questionnaire administration to a sample of stakeholders for mapping the lack of data for planning the CE in the agriculture; b) manipulation and analysis of data; c) building of a set by replicable sustainability indicatorsto modelling a digital virtuous framework towards a CE. The results obtained thought the survey can be used for the definition of regional policy strategies and interventions.This new framework can improve the stakeholders’ decision-making process (Wolfert et al., 2017), achieve a CE approach, lead to a greater cooperation in the agricultural supply chain. Furthermore, the application of this CE knowledge model enables to overcome obstacles in data procurement (Newton et al., 2020). Additionally the building of a replicable framework allows to widespread a digital learning and soft culture among stakeholders, creating a virtuous network to be implemented in the Mediterranean area. Scholars, stakeholders and public administration can use this framework to design a common language of data collection, identify the information gaps to be filled and plan CE strategies in agriculture. This research is conducted for the MoDEC Apulia project in collaboration with the Agriculture Department of the Regione Puglia with the aim of strengthening the capacity building of public administrations.
Modelling digital circular economy framework in the agricultural sector. An application in Southern Italy
Crovella Tiziana
;Paiano Annarita;Lagioia Giovanni;
2021-01-01
Abstract
Linear economy is a conventional model based on the "take-make-consume-waste" approach, conversely circular economy (CE) focuses on the circular approach to the energy and materials use, providing environmental, economic and social benefits for the stakeholders involved in production, distribution and consumption chains. The fundamental transition from a linear economy to a CE requires a large amount of data to increasing knowledge of consumption of natural resources and negative externalities. Among the economic sectors, agriculture strongly contributes to the consumption of resources (e.g. water and energy), to the greenhouse gas emissions and waste (e.g. wastewater) generation. The data required to optimize the transition to CE are often disaggregated, difficult to find, out of date and complex to consult by some agricultural stakeholders. The scientific literature associated with this emerging and new topic presented a shortage of papers (Klerkx, et al., 2019). To address this gap we presented this analysis regarding the third topic group, subsection (modelling and simulation). The aim of this research is to identify a data-set model in order to enable stakeholders to know the most suitable sustainability indicators and finally to implement the best CE model. We used a variety of digital sources, including bibliographic platforms, international and digital tools, EU and regional regulations. The methodological path includes the following phases: a) questionnaire administration to a sample of stakeholders for mapping the lack of data for planning the CE in the agriculture; b) manipulation and analysis of data; c) building of a set by replicable sustainability indicatorsto modelling a digital virtuous framework towards a CE. The results obtained thought the survey can be used for the definition of regional policy strategies and interventions.This new framework can improve the stakeholders’ decision-making process (Wolfert et al., 2017), achieve a CE approach, lead to a greater cooperation in the agricultural supply chain. Furthermore, the application of this CE knowledge model enables to overcome obstacles in data procurement (Newton et al., 2020). Additionally the building of a replicable framework allows to widespread a digital learning and soft culture among stakeholders, creating a virtuous network to be implemented in the Mediterranean area. Scholars, stakeholders and public administration can use this framework to design a common language of data collection, identify the information gaps to be filled and plan CE strategies in agriculture. This research is conducted for the MoDEC Apulia project in collaboration with the Agriculture Department of the Regione Puglia with the aim of strengthening the capacity building of public administrations.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
