This study aims to analyze the dynamic sustainability of a Local Governance project for implementing Industrial Symbiosis by formulating a Business Model that can encompass its multidimensional and systemic nature. The Industrial Symbiosis (IS), known as the interaction between different industrial plants to maximize the reuse of resources usually considered as waste, is an approach that has already been successfully tested in contexts with high industrial concentration (Jacobsen, 2008) and has been analyzed from a business perspective (Fraccascia, Magno, & Albino, 2016). Industrial symbiosis is one of the approaches for the practical application of circular economy principles and consists of inter-company relationships between two or more geographically close companies that involve exchanges of energy, water, waste, and by-products. However, the Wicked Problems (Head & Alford, 2013) related to Industrial Symbiosis, already found in previous studies [(Fichtner & Tietze-Stöckinger, 2005) (Herczeg, Akkerman, & Hauschild, 2018)] are not sufficiently investigated due to an approach that is not adequately focused on Public Governance. The Business Model, according to a Good Governance perspective, identifies Area Science Park, a national Public Research Body, as the project coordinator because of its ability to intercept the needs of the various stakeholders of the local industrial ecosystem that often differ both in nature and in interests, thanks to its strong collaboration with the local industry and its ability in creating skills development through the interaction between research and industry. The research project identifies the key aspects of implementing a Decision Support System (DSS) applied to industrial symbiosis. The purpose of the DSS is to support the identification of potential and implementable industrial symbiosis good practices within a pilot project placed in the industrial retro-port area of the city of Trieste. The designed DSS is called SISSI (Informative Tools to Support Industrial Symbiosis) and consists of two software tools: a Geographic Information System (GIS) and a Business Intelligence (BI) application. Through a data lake process, the tool has been featured by secondary data collected thanks to sectoral databases (e.g., structured databases of companies, territorial data, and local waste data). Including primary data (input and output data of production processes, i.e., flows and costs of procurement of raw materials, flows and expenses related to waste and by-products management, and energy consumption and wastewater), it is possible obtaining a detailed picture of the territory and allowing the identification of potential relationships of industrial symbiosis. This study aims to find answers to questions strictly related to the operational management of SISSI, which was born and created within a public research body to improve the local industrial competitiveness, focusing on social and environmental aspects. Within this context, it was necessary to identify a methodology that allows to investigate the sustainability of the SISSI project in the long term and to set a focus on the economic-financial, social, and environmental impacts. Therefore, we have developed a business model to identify the key processes, including different governance scenarios. Therefore, according to a literature review regarding Sustainable Business Models and System Dynamics [(Sterman, 2000), (Cosenz, Rodrigues, & Rosati, 2019), (Pieroni, McAloone, & Pigosso, 2019)], we developed a preliminary qualitative model to map and to analyze the key processes (in terms of activities, stakeholders, beneficiaries, environment, etc.) involved in the SISSI project. The integration of two perspectives characterizes the development of this qualitative dynamic model: one focused on the Business Model Canvas (BMC) (Osterwalder & Pigneur, 2010) and the other on System Dynamics [(Sterman, 2000) (Cosenz & Noto, 2016)]. Starting from the BMC template, featured from a static and a managerial perspective, we decided to apply an adapted version of the sBMC framework - sustainable Business Model Canvas (Cosenz, Rodrigues, & Rosati, 2019), because it allows the dynamic assessment of the environmental, the social and the economic impacts. As BMC, sBMC is recognizable in the context of strategic management and defines the creation of the value of the product/service system through several blocks, which differ both in nature and purpose. The construction of the sBMC started firstly with collecting all the variables involved in the project processes and with their inclusion in the various framework blocks. Then we defined the Value Chain, starting from the impact on the Community (Outcomes) in a multidimensional perspective. Streaming up the value chain and considering the various key aspects of the Business Model, we have defined the variables of the other blocks of the sBMC. The model has been validated by a team of Circular Economic experts that checked the qualitative Business Model. The study included different governance scenarios despite the DSS management (public, private, or public-private partnership) and the financing system. At the end of the analysis, we included some limits of the research and future opportunities, considering the project's public relevance and the need to use a resilient system that allows addressing any operational and regulatory shocks. In particular, we expect to develop an open quantitative model to analyze the evolution of the SISSI platform according to the various scenarios. References Cosenz, F., & Noto, G. (2016). Applying System Dynamics Modelling to Strategic Management: A Literature Review. Systems Research and Behavioral Science. doi:10.1002/sres.2386 Cosenz, F., Rodrigues, V., & Rosati, F. (2019). Dynamic business modeling for sustainability: Exploring a system dynamics perspective to develop sustainable business models. Business Strategy and the Environment, 1-14. Coyle, R. G. (1996 ). System Dynamics Modelling: A practical approach. CRC Press. Fichtner, W., & Tietze-Stöckinger, I. (2005, January). Barriers of inter-organisational environmental management: two case studies on industrial symbiosis. Progress in Industrial Ecology, an International Journal, 2(1), 73-88. doi:10.1504/PIE.2005.006778 Fraccascia, L., Magno, M., & Albino, V. (2016). , Business models for industrial symbiosis: A guide for firms. Procedia Environmental Science, Engineering and Management, 3(2). Head, B., & Alford, J. (2013). Wicked Problems: Implications for Public Policy and Management. Administration & Society, 47(6), 711-739. doi:10.1177/0095399713481601 Herczeg, G., Akkerman, R., & Hauschild, M. Z. (2018, January 10). Supply chain collaboration in industrial symbiosis networks. Journal of Cleaner Production, 171, 1058-1067. doi:10.1016/j.jclepro.2017.10.046 Jacobsen, N. B. (2008, February 8). Industrial Symbiosis in Kalundborg, Denmark: A Quantitative Assessment of Economic and Environmental Aspects. Journal of Industrial Ecology, 10(1-2), 239-255. doi:10.1162/108819806775545411 Osterwalder, A., & Pigneur, Y. (2010). Business model generation. New Jersey: John Wiley & Sons. Pieroni, M. P., McAloone, T. C., & Pigosso, D. C. (2019). Business model innovation for circular economy and sustainability: A review of approaches. Journal of Cleaner Production, 215, 198-216. Sterman, J. D. (2000). Business Dynamics: Systems Thinking and Modeling for a Complex World. New York: Irwin Professional McGraw-Hill.
SISSI project - Informative Tools to Support Industrial Symbiosis. Methodological framework and development of a dynamic Business Model in an industrial retro-port area. Preliminary analysis from a qualitative point of view
Francesca Rossi
2022
Abstract
This study aims to analyze the dynamic sustainability of a Local Governance project for implementing Industrial Symbiosis by formulating a Business Model that can encompass its multidimensional and systemic nature. The Industrial Symbiosis (IS), known as the interaction between different industrial plants to maximize the reuse of resources usually considered as waste, is an approach that has already been successfully tested in contexts with high industrial concentration (Jacobsen, 2008) and has been analyzed from a business perspective (Fraccascia, Magno, & Albino, 2016). Industrial symbiosis is one of the approaches for the practical application of circular economy principles and consists of inter-company relationships between two or more geographically close companies that involve exchanges of energy, water, waste, and by-products. However, the Wicked Problems (Head & Alford, 2013) related to Industrial Symbiosis, already found in previous studies [(Fichtner & Tietze-Stöckinger, 2005) (Herczeg, Akkerman, & Hauschild, 2018)] are not sufficiently investigated due to an approach that is not adequately focused on Public Governance. The Business Model, according to a Good Governance perspective, identifies Area Science Park, a national Public Research Body, as the project coordinator because of its ability to intercept the needs of the various stakeholders of the local industrial ecosystem that often differ both in nature and in interests, thanks to its strong collaboration with the local industry and its ability in creating skills development through the interaction between research and industry. The research project identifies the key aspects of implementing a Decision Support System (DSS) applied to industrial symbiosis. The purpose of the DSS is to support the identification of potential and implementable industrial symbiosis good practices within a pilot project placed in the industrial retro-port area of the city of Trieste. The designed DSS is called SISSI (Informative Tools to Support Industrial Symbiosis) and consists of two software tools: a Geographic Information System (GIS) and a Business Intelligence (BI) application. Through a data lake process, the tool has been featured by secondary data collected thanks to sectoral databases (e.g., structured databases of companies, territorial data, and local waste data). Including primary data (input and output data of production processes, i.e., flows and costs of procurement of raw materials, flows and expenses related to waste and by-products management, and energy consumption and wastewater), it is possible obtaining a detailed picture of the territory and allowing the identification of potential relationships of industrial symbiosis. This study aims to find answers to questions strictly related to the operational management of SISSI, which was born and created within a public research body to improve the local industrial competitiveness, focusing on social and environmental aspects. Within this context, it was necessary to identify a methodology that allows to investigate the sustainability of the SISSI project in the long term and to set a focus on the economic-financial, social, and environmental impacts. Therefore, we have developed a business model to identify the key processes, including different governance scenarios. Therefore, according to a literature review regarding Sustainable Business Models and System Dynamics [(Sterman, 2000), (Cosenz, Rodrigues, & Rosati, 2019), (Pieroni, McAloone, & Pigosso, 2019)], we developed a preliminary qualitative model to map and to analyze the key processes (in terms of activities, stakeholders, beneficiaries, environment, etc.) involved in the SISSI project. The integration of two perspectives characterizes the development of this qualitative dynamic model: one focused on the Business Model Canvas (BMC) (Osterwalder & Pigneur, 2010) and the other on System Dynamics [(Sterman, 2000) (Cosenz & Noto, 2016)]. Starting from the BMC template, featured from a static and a managerial perspective, we decided to apply an adapted version of the sBMC framework - sustainable Business Model Canvas (Cosenz, Rodrigues, & Rosati, 2019), because it allows the dynamic assessment of the environmental, the social and the economic impacts. As BMC, sBMC is recognizable in the context of strategic management and defines the creation of the value of the product/service system through several blocks, which differ both in nature and purpose. The construction of the sBMC started firstly with collecting all the variables involved in the project processes and with their inclusion in the various framework blocks. Then we defined the Value Chain, starting from the impact on the Community (Outcomes) in a multidimensional perspective. Streaming up the value chain and considering the various key aspects of the Business Model, we have defined the variables of the other blocks of the sBMC. The model has been validated by a team of Circular Economic experts that checked the qualitative Business Model. The study included different governance scenarios despite the DSS management (public, private, or public-private partnership) and the financing system. At the end of the analysis, we included some limits of the research and future opportunities, considering the project's public relevance and the need to use a resilient system that allows addressing any operational and regulatory shocks. In particular, we expect to develop an open quantitative model to analyze the evolution of the SISSI platform according to the various scenarios. References Cosenz, F., & Noto, G. (2016). Applying System Dynamics Modelling to Strategic Management: A Literature Review. Systems Research and Behavioral Science. doi:10.1002/sres.2386 Cosenz, F., Rodrigues, V., & Rosati, F. (2019). Dynamic business modeling for sustainability: Exploring a system dynamics perspective to develop sustainable business models. Business Strategy and the Environment, 1-14. Coyle, R. G. (1996 ). System Dynamics Modelling: A practical approach. CRC Press. Fichtner, W., & Tietze-Stöckinger, I. (2005, January). Barriers of inter-organisational environmental management: two case studies on industrial symbiosis. Progress in Industrial Ecology, an International Journal, 2(1), 73-88. doi:10.1504/PIE.2005.006778 Fraccascia, L., Magno, M., & Albino, V. (2016). , Business models for industrial symbiosis: A guide for firms. Procedia Environmental Science, Engineering and Management, 3(2). Head, B., & Alford, J. (2013). Wicked Problems: Implications for Public Policy and Management. Administration & Society, 47(6), 711-739. doi:10.1177/0095399713481601 Herczeg, G., Akkerman, R., & Hauschild, M. Z. (2018, January 10). Supply chain collaboration in industrial symbiosis networks. Journal of Cleaner Production, 171, 1058-1067. doi:10.1016/j.jclepro.2017.10.046 Jacobsen, N. B. (2008, February 8). Industrial Symbiosis in Kalundborg, Denmark: A Quantitative Assessment of Economic and Environmental Aspects. Journal of Industrial Ecology, 10(1-2), 239-255. doi:10.1162/108819806775545411 Osterwalder, A., & Pigneur, Y. (2010). Business model generation. New Jersey: John Wiley & Sons. Pieroni, M. P., McAloone, T. C., & Pigosso, D. C. (2019). Business model innovation for circular economy and sustainability: A review of approaches. Journal of Cleaner Production, 215, 198-216. Sterman, J. D. (2000). Business Dynamics: Systems Thinking and Modeling for a Complex World. 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