A Systemic Approach to Multi-Party Relationship Modeling

Socio-economic systems exist in a wide variety of activity domains and are composed of multiple stakeholder groups. These groups pursue objectives which are often entirely motivated from within their local context. Domain specificities in the form of institutional design, for example the deregulation of Public Utility systems, can further fragment this context. Nevertheless, for these systems to be viable, a management subsystem that maintains a holistic view of the system is required. From a Systems perspective, this highlights the need to invest in methods that capture the interactions between the different stakeholders of the system. It is the understanding of the individual interactions that can help piece together a holistic view of the system thereby enabling system level discourse. In this paper we present a modeling technique that models industry interactions as a multi-party value realization process and takes a Systems approach in analyzing them. Every interaction is analyzed both from outside – system as a black box and from within – system as a white box. The design patterns that emerge from this whole/composite view of value realization provide the necessary foundation to analyze the working of multi-stakeholder systems. An explicit specification of these concepts is presented as Regulation Enabling Ontology, REGENT. As an example, we instantiate REGENT for the urban residential electricity market and demonstrate its effectiveness in identifying the requirements for time-based electricity supply systems

OVERCOMING SILOS: A REVIEW OF BUSINESS MODEL MODELING LANGUAGES FOR BUSINESS ECOSYSTEMS

Digital technologies have led to the emergence of new ways of creating value and, by enabling business ecosystems, to a change in the way businesses are organized. However, due to their non-hierarchical and complementary nature, business ecosystems are not easy to create or sustain. To support the systematic design and analysis of business ecosystems, business modeling has emerged as a valuable tool. Our structured review of the literature on business model modeling languages has found 45 potentially relevant publications. Although a preliminary analysis shows that existing modeling languages only provide limited support for business ecosystems, they can provide a useful conceptual basis to enable further research. This research-in-progress paper outlines first steps taken to identify recently developed business model modeling languages and to synthesize and organize the knowledge dispersed across disciplines. Thus, the future results of study are expected to contribute to research on business model collaboration and business ecosystems