Business ecosystem modeling- the hybrid of system modeling and ecological modeling: an application of the smart grid

Abstract

Business ecosystem is popularly used to investigate a complex social system with the business perspective, and particularly contributes to the understanding of actors and their relations in the innovation research. However, the aspect of business ecosystem modeling is limited discussed in the literature, although the importance has emerged significantly in recent years due to the emphasis on cross-disciplinary research and digitalization with artificial intelligence. Therefore, this paper proposes a framework for business ecosystem modeling with the discussion of system engineering and ecological modeling. The domain of smart grid is selected to demonstrate how system engineering, especially standards and ontologies contribute to the business ecosystem modeling. The proposed framework of the business ecosystem modeling includes three parts and nine stages that combines theories from system engineering, ecology, and business ecosystem. Part I-Business ecosystem architecture development includes four stages which aims to identify a target business ecosystem and its elements (actors, roles, and interactions). Part II-Factor analysis includes two stages to identify potential changes (and the dimensions of the changes) in the ecosystem. Part III-Ecosystem simulation and reconfiguration aims to use simulations to investigate the transition of an ecosystem and the re-configurated ecosystem. The framework not only provides a systematic approach for modeling a business ecosystem but also provides a methodological foundation for research on the aspect of complex systems in the business ecosystem field.

Technical, Economic, Social and Regulatory Feasibility Evaluation of Dynamic Distribution Tariff Designs

“…Especially, agent-based simulations with the consideration from different stakeholders' perspectives are needed [52]. Meanwhile, besides Time-of-Use tariff, other types of dynamic distribution tariffs in the literature are recommended to be further investigated for understanding their impacts on the energy ecosystem [53]. The result can contribute to design the most suitable tariffs and justify regulations to support the sustainability and resilience of the whole energy ecosystem.…”

An overview of digitalization for the building-to-grid ecosystem

“…Meanwhile, although this paper borrows the concept of the business ecosystem, and proposes a definition for the Building-to-Grid ecosystem, the ecosystem research is far more complex and requires a systematic investigation and research design. Especially, ecosystem modeling and simulation have recently arisen attention in the energy sector with the applications of IoT, big data, and artificial intelligence, but is not much researched (Ma, 2019). The corresponding research not only requires participation from the energy or building domains with disciplines of engineering and computer science but also multi-disciplinary research is recommended in the future, especially with business and management perspectives.…”

Methodology for identifying technical details of smart energy solutions and research gaps in smart grid: an example of electric vehicles in the energy system

“…In the literature search results, all titles or abstracts including EVs are chosen to be implemented in the SGAM framework. The SGAM framework provides a smart grid architecture and illustrates the complexity of the smart grid (Ma 2019b). The SGAM framework methodology consists of seven principles: universality, localization, consistency, flexibility, scalability, extensibility, and interoperability (CEN-CENELEC-ETSI Smart Grid Coordination Group 2012).…”

“…The studies in energy flexibility based on the agent-based simulation, e.g., commercial greenhouses (Howard et al 2020a;Christensen et al 2020a;Christensen et al 2020b), water supply (Vaerbak et al 2019), and breweries (Howard et al 2020b), show that the agent-based simulation can serve this purpose, especially support the investigation of what-if scenarios (Ma et al 2019). Meanwhile, related stakeholders and their interactions can be identified with the energy ecosystem modeling methodology proposed by (Ma 2019a). Furthermore, the barriers and opportunities and barriers for adopting energy flexibility have been investigated in the literature, e.g., (Ma et al, n.d.;Billanes et al 2017).…”