Digital Transformation in Public Services. Exploring Automatic Recognition of Academic Qualifications through an Ecosystem Perspective.

This study examines the digitalization of services in the education sphere through the lens of Public Service Ecosystem (PSE) theory, as proposed by Osborne et al. (2022). Its goal is to define how value is co-created across the different ecosystem levels (macro, meso, and micro). At the macro level, the study investigates the impact of societal values on the ecosystem, while at the meso level it explores inter-actor dynamics within an international, multi-actor PSE. Finally, at the micro level, it investigates how public service staff engage in value co-creation and the determinants of their (lack of) acceptance of digitalization. The empirical focus is on policies supporting the automatic recognition of foreign qualifications in the European Union and European Higher Education Area, using the Automatic Recognition Database Italia (ARDI) by CIMEA as a case study. The analysis of the macro and meso levels adopts a qualitative, document-based methodology, allowing for a deep understanding of how policies are shaped by the broader ecosystem values and how different organizations interact within it. To capture inter-actor dynamics, insights from broader business ecosystem literature are integrated with PSE theory. The analysis of the micro level is interview-based, relying on in-depth, semi-structured interviews with key stakeholders. A theory-driven thematic analysis was employed to study the data collected, using the TAM3 model as its theoretical foundation. The study shows how Osborne et al.’s PSE theory can be developed by identifying a new form of value creation (value-in-alignment) to describe the value created by interactions between the ecosystem actors at the meso level, while incorporating user-centered value creation factors (value-in-context, value-in-production, value-in-use) at the micro level. At the meso level, concepts from business ecosystem literature are shown to offer strong explanatory power for inter-actor dynamics within a PSE. At the micro level, the TAM3 model effectively illustrates how public administration staff (do not) accept technology and create or destroy value in the process. The study’s analysis of value-in-alignment at the meso level is limited, as the automatic recognition ecosystem is still evolving. Further research is needed to assess whether (and how) full alignment around automatic recognition can be achieved. At the micro level, limitations include unclear links between TAM3 factors and value-in-use, and the broader application of job crafting beyond the use of ARDI. Finally, the study is limited to credential evaluators from CIMEA, and broader insights from HEI evaluators and international students could enhance the understanding of the ecosystem. Through this research, a new model of PSE is proposed which is meant to have a wider explanatory power. While safeguarding Osborne et al.’s (2022) initial structure, the proposed updated version can be applied to the study of PSEs with multiple institutional actors, even beyond national borders, while also accounting for digitalization acceptance dynamics at the user level. Lastly, with its focus on automatic recognition policies and digital solutions for their full implementation, the study contains relevant implications for practice too.