Susan Hilbolling

Hilbolling, Susan 2Doctoral candidate: Susan Hilbolling

Research track: Information, Logistics and Innovation

Start date: July 2014

Supervisors: Prof. dr. Marleen Huysman, Dr. ir. Hans Berends, Dr. Fleur Deken & Dr. Philipp Tuertscher

Description of research

Pushed by a challenging environment (e.g. globalisation, the advent of information technology), organizations in dynamic and competitive industries collaborate to deliver increasingly complex innovations. This project extends research on collaboration processes by investigating a topic that has received little attention so far: the time dimensions of collaborative innovation. More specifically, when we address this challenge of managing time dimensions in inter- organizational innovation processes, we refer to managing temporal complexity. This research’s specific focus on temporal complexities in inter-organizational dynamics is relevant and interesting, since a plurality of temporal structures are bound to come together in collaborative innovation efforts. Partnering organizations are rooted in different development paths, for example, start-ups are concerned with short-term survival, while established organisations need to engage on long-term planning to maintain their competitive advantage. Furthermore, the collaborating organizations may operate in multiple sectors or industries, each following their own temporal structures. For instance, research institutes are led by the semesters of the academic calendar and the four year timeline of PhD projects), while private companies organize their activities around the four quarters of the fiscal year and seasonal fluctuations in demand. We investigate particularly the role of dealing with differing temporal structures. Taken together, we argue that success or failure of collaborative innovation processes may be affected by the organizations’ ability of managing temporal complexities. Therefore, this research addresses the following question: How do organizations manage temporal complexities in collaborative innovation processes?

We will follow a qualitative theory development methodology and take an embedded, single case study approach. We will study a number of collaborative digital innovation projects, where heterogeneous partners from previous separate industries come together. For data collection and analysis we will adopt a process research methodology, which aims to understand and explain temporal progressions of evolving phenomena. Hence, the focus will be on gathering multi-level longitudinal process data; a mixture of observations (of formal and informal interactions), semi-structured interviews (both retrospective and real-time with participants from different levels of the organizations), and archival data. Unpacking time-management in this setting will advance theoretical understanding of the organizational and societal role of time.

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