Heidi Hietala

About Me

I am Heidi Hietala, a Postdoctoral Researcher in the Software Engineering research group (M3S) within the Software Engineering and Information Systems (SEIS) research unit at the University of Oulu. My research examines collaboration, governance, and decision-making in software engineering and information systems. I am particularly interested in how organisations and individuals balance competing demands, align diverse stakeholder interests, and adapt to technological and regulatory change.

My doctoral research focused on collective ambidexterity in digital service ecosystems, exploring how public, private, and third-sector actors collaborate to balance innovation and efficiency. Through case studies of municipal wastewater data management and large-scale digital public service ecosystems, I investigated the mechanisms, antecedents, and outcomes that enable collaborative innovation and efficiency in complex multi-actor environments.

Current Research Themes

My current research focuses on four interconnected areas:

AI Regulation and Innovation. I study how regulations shape the development and adoption of artificial intelligence (AI), with a particular focus on the European Union's AI Act. My research examines how organisations address tensions between technological innovation and regulatory compliance, particularly in public sector contexts. I am interested in how these tensions influence organisational interpretations of regulation and shape innovation practices, governance, and decision-making.

Software-Defined Vehicle Ecosystems. I investigate collaboration and governance challenges in software-defined vehicle (SDV) ecosystems, particularly within the European automotive industry. My research explores how vehicle manufacturers, software providers, suppliers, and other stakeholders coordinate across organisational boundaries and how governance arrangements, responsibility allocation, and collaboration structures influence innovation capacity and ecosystem evolution.

Cognitive Biases in Software Engineering. I study software engineering decision-making through a socio-technical lens, paying particular attention to the emergence, persistence, and evolution of cognitive biases in software development. My research explores how these biased judgments develop and continue throughout the software development lifecycle, how they influence decision-making and collaboration, and ways to identify and mitigate their negative effects.

Professional Background

Before entering academia, I worked with enterprise systems and digital transformation initiatives. This industry experience provides a practical foundation for my research and enables me to bridge academic inquiry with real-world organisational challenges.

Publishing

My work has been published in leading journals, including Information and Software Technology, European Journal of Information Systems, Journal of Systems and Software, Government Information Quarterly, and Communications of the Association for Information Systems (CAIS).

I have also published at leading international conferences, including the European Conference on Information Systems (ECIS) and the International Conference on Information Systems (ICIS), where my research has been recognised with distinctions such as Best of Track, Best Paper Nominee, and Best Kauffman Paper Nominee.