The digital business ecosystem (DBE) is a paradigm that enables organisations and companies to develop and monitor innovative business models within collaborative business constellations. By combining digitalisation with digital collaboration, DBEs offer advantages such as cross-domain and trans-geographical collaboration, co-evolution driven by diverse interests, and adaptation through self-organising characteristics. However, to enable companies and organisations to fully benefit from DBEs, several challenges must be addressed, which include capturing, understanding, and coordinating information about individual DBE actors and their interdependencies, as well as establishing an overarching view that incorporates various perspectives on a DBE. In addition, the resilience of a DBE, in terms of its long-term viability, needs to be designed and monitored to ensure the continuity and stability of the ecosystem. Enterprise modelling has proven effective in capturing and documenting organisational designs, and can play a crucial role in overcoming these challenges by capturing and depicting abstract representations of DBEs.
The work presented in this thesis follows design science research, with the aim of establishing a modelling method for the design, analysis, and management of DBEs and their resilience. The design artefact developed here is a modelling method named DBEmap, which provides methodological support for capturing, understanding, and documenting the various perspectives on and resilience of DBEs. As a design artefact, the DBEmap modelling method targets the key actors (or “drivers”) within DBEs as users. DBEmap consists of 11 method modules that reflect critical perspectives on a DBE, along with a meta-model, a graphical language notation, and guidelines.
A systematic literature review was conducted to explicate the initial problem and explore the modelling approaches that had been previously presented in DBE-related studies. Prototyping sessions were carried out with a focus on modelling DBE resilience, alongside a survey on DBE roles using a healthcare DBE case, which also contributed to the explication of the problem. The findings highlighted the immaturity of the current state of DBE modelling and the need for a holistic modelling method.
The DBEmap modelling method was designed and developed based on data gathered from semi-structured interviews with experts and a survey analysis of DBE roles and responsibilities. These data helped to elicit the requirements for DBEmap. The design and development process involved three sub-activities: (1) developing the method modules and application guidelines using situational method engineering, (2) constructing the meta-model, and (3) creating the graphical modelling language notation.
To demonstrate and evaluate DBEmap, stakeholders from four real-world DBEs in the healthcare, higher education, and maritime domains were engaged, as well as case-independent experts from the finance and public sectors. The evaluation process followed an iterative approach using action research, semi-structured interviews, workshops, and a web-based questionnaire. The web-based questionnaire assessed experts' perceived usefulness of DBEmap in meeting the identified requirements. It included 27 statements, rated on a five-point Likert scale. The results showed similar patterns across evaluation cycles, and ex ante artificial settings were compared with ex post naturalistic ones. Qualitative feedback from semi-structured interviews indicated positive perceptions, particularly regarding the understanding of DBE concepts and constructs, visualising complexity and interconnections, and identifying gaps and balancing perspectives.
In summary, DBEmap can effectively address challenges related to integrating DBE perspectives and managing DBE resilience. This thesis also contributes to design knowledge in the field of method engineering and lays the groundwork for future research. Potential areas for further work include the integration of other Information Systems methods, extended evaluations with industrial partners over a longer timeframe, and improvements to the DBEmap tool.
Stockholm: Department of Computer and Systems Sciences, Stockholm University , 2024. , p. 110
digital business ecosystem, method engineering, enterprise modelling, resilience, ecosystem design, network organisation, organisational design
2024-12-06, L30, Nodhuset, Campus Kista, Borgarfjordsgatan 12, Kista, 09:00 (English)