Since technology, institutions and markets continuously change, business models are also dynamic configurations that evolve through micro- adaptations and/or disruptive changes. This dynamism enables economic resilience, that is, the (re)generation of system-level economic sustainability, mainly through the mechanism that in the entrepreneurship literature is called “creative destruction”. But what about social and environmental resilience? How, and under what conditions, can business model dynamics contribute to the (re)generation of environmental and social sustainability, as well? Even if business model (re)generation is today recognized as a key force to the resilience (and fragility) of social-ecological systems, we have scant understanding of how its actual contribution to sustainability could be assessed and maximized (Schaltegger & Wagner, 2011). This study contributes to addressing this challenge by developing the Common- Good DPM approach. This approach results from the cross-fertilization between Dynamic Performance Management (DPM), which is a system-thinking based method, the theory of the commons, and institutional theories. The Common-Good DPM approach is a sustainability-oriented tool for sense-making, monitoring, testing and designing around the dynamic link between business models and sustainable development models, thus leveraging business model evolution for sustainability transformations. The Common-Good DPM approach is conceived to concretely enable participatory and adaptive modelling, in which sustainability-relevant knowledge is collectively co-created through feedback based learning. In addition, the Common-Good DPM approach is data- driven, and may both enable and leverage effective big data management.

Common-Good DPM: a Tool for Co-evolving Business Models and Sustainable Development Models

Ricciardi Francesca;De Bernardi paola;Sorano Enrico
2019-01-01

Abstract

Since technology, institutions and markets continuously change, business models are also dynamic configurations that evolve through micro- adaptations and/or disruptive changes. This dynamism enables economic resilience, that is, the (re)generation of system-level economic sustainability, mainly through the mechanism that in the entrepreneurship literature is called “creative destruction”. But what about social and environmental resilience? How, and under what conditions, can business model dynamics contribute to the (re)generation of environmental and social sustainability, as well? Even if business model (re)generation is today recognized as a key force to the resilience (and fragility) of social-ecological systems, we have scant understanding of how its actual contribution to sustainability could be assessed and maximized (Schaltegger & Wagner, 2011). This study contributes to addressing this challenge by developing the Common- Good DPM approach. This approach results from the cross-fertilization between Dynamic Performance Management (DPM), which is a system-thinking based method, the theory of the commons, and institutional theories. The Common-Good DPM approach is a sustainability-oriented tool for sense-making, monitoring, testing and designing around the dynamic link between business models and sustainable development models, thus leveraging business model evolution for sustainability transformations. The Common-Good DPM approach is conceived to concretely enable participatory and adaptive modelling, in which sustainability-relevant knowledge is collectively co-created through feedback based learning. In addition, the Common-Good DPM approach is data- driven, and may both enable and leverage effective big data management.
2019
14th International Forum on Knowledge Asset Dynamics: Knowledge Ecosystems and Growth
Matera
5-7 Giugno 2019
IFKAD 2019 Knowledge Ecosystems and Growth Proceedings
Institure of Knowledge Asset Management
1670
1676
9788896687123
Business model, Sustainability, Commons, Dynamic Performance Management, System Dynamics
Ricciardi Francesca; De Bernardi paola; Sorano Enrico
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/2318/1722506
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