Heidi Hietala

Dr. Heidi Hietala is a postdoctoral researcher in the Empirical Software Engineering in Software, Systems and Services (M3S) research unit. Her research focuses on the collaborative dynamics of digital transformation, particularly in digital service ecosystems. She has studied complex systems such as municipal wastewater data management and large-scale digital public service ecosystems, contributing insights into the mechanisms, antecedents, and outcomes of collective ambidexterity in such contexts. Hietala’s doctoral thesis focused on exploring how collective ambidexterity can be achieved through collaboration among public, private, and third-sector stakeholders, balancing innovation and efficiency in complex service environments.

In her current research, Hietala examines how regulation shapes AI innovation, with a particular focus on the European Union’s Artificial Intelligence Act (AI Act) and its implications for the development and use of AI in the public sector and healthcare. The research focuses on the tensions between innovation and regulatory compliance and on how organisations navigate these competing demands in an uncertain and rapidly evolving technological environment. In addition, Hietala analyses how these tensions influence organisational interpretations of regulation and shape innovation practices and decision-making.

Another core research stream focuses on software-defined vehicle (Software Defined Vehicle, SDV) ecosystems. In this work, Hietala concentrates particularly on the European automotive industry and examines the collaboration challenges within multi-actor SDV ecosystems, where vehicle manufacturers, software providers, suppliers, and other stakeholders seek to align diverse goals, values, and business logics. The research analyses how governance models, responsibility allocation, and collaboration structures influence innovation capacity and the evolution of the ecosystem in a rapidly changing technological and regulatory context.

The third research stream focuses on cognitive biases in software engineering decision-making. Hietala examines cognitive biases as a socio-technical phenomenon, in which individuals’ mental models, assumptions, prior experiences, and expectations of the future are in interaction with technological solutions and software development practices. The research analyses how these biases emerge and persist throughout the software development lifecycle and how they shape software-related decision-making and collaboration. It also examines how the negative effects of cognitive biases can be identified and mitigated as part of software development practices.

With a strong industry background in enterprise systems and digital transformation, she brings a unique perspective that bridges practical challenges with academic research, offering insights into the governance and collaboration necessary for effective digital service development. She has published in journals such as Information and Software Technology, Government Information Quarterly, and Communications of the Association for Information Systems (CAIS). She has also published her work at conferences, including the European Conference on Information Systems (ECIS) and the International Conference on Information Systems (ICIS), where her paper was recognised as Best of Track, a Best Paper nominee, and a Best Kauffman Paper nominee.