Below a more detailed description of my current research focus and future research streams.

Current research (updated December 2024)
My research focuses on understanding the mechanisms and practices used by organizations in complex multi-actor collaborations to pursue ambitious goals related to digital innovation. My primary focus is conducting highly rigorous, qualitative, empirical work. For instance, I have completed two longitudinal studies on a collaboration between ‘big science’ and ‘big business’ known as Helix Nebula. In this research, I analyze how large scientific institutes (CERN, EMBL, ESA) collaborate with commercial cloud computing organizations (Atos, T-Systems) and public infrastructure providers (EGI, GÉANT) to develop a European scientific cloud computing infrastructure. In one paper, published in 2024 in the Journal of Management Studies and co-authored with Hans Berends and Philipp Tuertscher from Vrije Universiteit Amsterdam, I explore how these organizations develop a boundary infrastructure that reflects their diverse interests. My findings reveal a process where actors use the scaffolding of boundary objects and reconfiguring coalitions to align their differences and common interests. In another empirical paper, co-authored with Shaz Ansari from Cambridge Judge Business School, I examine goal dynamics within Helix Nebula. Specifically, I investigate how the organizations strive for a broad goal while managing conflicting subgoals that threaten sustained collaboration.

When I started at Warwick Business School in 2019, I became interested in the effects of AI technology on organizations. I identified an opportunity within the business school to join a funded project focused on developing an AI tool to assist lawyers in case review as part of court preparations. This has led to a published practitioner paper in MIS Quarterly Executive on how to address key challenges in developing AI for knowledge-intensive tasks. Additionally, a research paper on how organizations can align the rationalities of experts and AI during development is under review in Information Systems Research. This novel angle on AI and rationality has the potential to significantly influence future research in the field.

Broadly, my work is grounded in collaboration and technology studies, process research, and is focused on digital technology and innovation phenomena. I connect my research to various literatures, including organizational pluralism, rationality, boundary spanning, resourcing, framing, and new ways of organizing. My research consistently engages with process methodologies, and through my interest in micro-level dynamics, I have developed expertise in practice theory and its relevant methods. As a passionate qualitative researcher, I specialize in case study and ethnographic methods. My commitment to methodological rigor has led me to adopt digital methods for qualitative data as a complementary analysis technique. For example, in the second paper on Helix Nebula, I used Latent Dirichlet Allocation to extract topics from 11,000 internal text documents (e.g., emails, documents, presentations) and employed measures from communication studies and clustering methods to analyze the relationships between topics over time.

Future research (updated December 2024)
In future research, I aim to expand my work on complex multi-actor collaborations driven by digital innovation by exploring the boundaries of possibility and constraint in this field. The first direction of my future research will focus on the collaboration and ecosystem politics of digital innovation. Specifically, I will study the practices used to balance the competing interests of actors (human and non-human) in collaborative digital innovation and the coordination of the different value networks involved. To support this research, I have secured access for future longitudinal data collection at CERN, starting in 2025.

A second stream of my future research will focus on the dilemmas and tensions in fast-growing platforms and how firms manage these challenges. This work will build on a recent paper on Douyin (TikTok), which is published MIS Quarterly. Moving forward, I would like to supervise a PhD project that conducts a comparative study of fast-growing platforms over the past decade, analyzing companies such as Alibaba, TikTok, Instagram, Facebook, X, Netflix, and WhatsApp.