In contrast to traditional business models, digital business ecosystems (DBEs) have several distinctive features—heterogeneity of involved actors, symbiosis in the exchange of resources, co-evolution of their interactions, and self-organisation. Designing DBEs is a task demanding a well-defined DBE’s scope, roles and responsibilities of the actors, their interactions and dependencies, as well as versatile technologies and data. The study focuses on two DBEs—Marispace-X and Skippo in the maritime domain to capture the tenets of the blue economy with dataspaces. Because the design approaches to DBE are scarce due to the paradigm’s novelty, the study aims to evaluate a model-based design method, DBEmap. The evaluation results concerning practitioners’ perceived usefulness of the DBEmap and its support for integrating DBE-related perspectives and benchmarking DBE resilience are presented. Reflections on the applicability of DBEmap and its implications for organisational support, highlighting the systematic guidance and actionable outcomes observed in the two case workshops, are discussed alongside the study’s limitations and directions for future research.

In alignment with the ongoing digitalization in all aspects of science and society, the legal domain is experiencing a significant growth in the volume of produced documents. Manual approaches for analysis of legal corpora, like Intellectual Property case decisions, are deemed resource-intensive, in terms of time and effort. As a response, we present the CLAIM tool, which has been developed combining Model-Driven Development with a Large Language Model. As a Design Science Research project, the tool’s development has been based on the needs of its stakeholders, which have been elicited in participatory modeling workshops. The prototype version presented in this paper includes two main phases of analysis; information extraction and semantic information retrieval. Its functionality is briefly demonstrated by analyzing trademark cancellation cases which have been filed in bad faith.

As digitalization increases its pace, the legal field produces far more text than manual analysis can keep up with. Parsing large bodies of material such as Intellectual Property rulings by hand is both slow and labor-intensive, to the point where it is considered unfeasible. In this paper, the CLAIM tool, developed to tackle this challenge by blending conceptual modeling with a large language model, is presented and evaluated. Conceived as a Design Science artifact, the tool was motivated by stakeholder requirements gathered through participatory modeling workshops. The prototype runs in two consecutive stages: automated information extraction followed by semantic querying. Its capabilities are illustrated on a corpus of EU trademark-cancellation decisions brought on grounds of bad-faith filing. CLAIM’s evaluation was based on user-testing and interviews, resulting in a set of highly positive responses.

In contrast to traditional business models, Digital Business Ecosystems (DBE) have several distinctive features - heterogeneity of involved actors, symbiosis in the exchange of resources, co-evolution of their interactions, and self-organisation. Designing DBEs is a task demanding a well-defined DBE’s scope, roles and responsibilities of the actors, their interactions and dependencies, as well as versatile technologies and data. The study focuses on two DBEs – Marispace-X and Skippo in the maritime domain to capture the tenets of the blue economy with dataspaces. Because the design approaches to DBE are scarce due to the paradigm’s novelty, the study aims to evaluate a model-based design method, DBEmap. The evaluation results concerning practitioners’ perceived usefulness of the DBEmap and its support for integrating DBE-related perspectives and designing and managing DBE resilience are presented.

The business world is nowadays characterized by complexity due to rapidly evolving market and customer requirements. As a consequence, software providers are facing the challenge of delivering products with higher pace and innovation. The agile methodology has a big impact on how software systems are developed - it should facilitate business value in short iterations. Requirements are the base of all software systems, and consequently, Requirements Engineering (RE) plays one of the most important roles in system development. Traditional elicitation techniques relying on stakeholders’ requests do not cover the increasing demands for considering unintended data from organisations' related digital sources, internal (transaction logs, sensors) or external (e.g., microblogs), amplifying thus the need for the elicitation of data-driven requirements. This study proposes a process that combines data-driven and traditional RE approaches for Agile software development, and specifically for the Scrum method. The process intends to assist Agile professionals to elicit requirements from digital sources in combination with intended data derived from the stakeholders without impacting the main Agile practices. The motivation for the research origins from the case studies carried in few companies having the challenge to include data-driven requirements into their Agile approaches. The usage of the proposal is illustrated on an enterprise software case, while several Scrum professionals were interviewed to evaluate its correctness and importance.