The art of balance: two search dimensions of ambidexterity and spatiality
This study aims to conduct an exploratory investigation into novel knowledge combinations for innovation within high-tech cluster firms.
Project summary
This research project has received funding from the British Academy/Leverhulme Trust Small Grants SG2122\210363 Round 2021-2022.
Under immense pressure from the present wave of technological revolution, businesses, especially high-tech firms, are compelled to relentlessly pursue innovations in order to strengthen and sustain competitive advantages. To achieve this, high-tech firms must seek out and combine multiple sources of knowledge in efficient and effective ways.
However, knowledge searching is not inexpensive, with businesses on average allocating up to 19.5% of their budget on searching and other R&D activities each year (Statista, 2023). Without an effective search strategy, firms risk wasting their resources and failing on innovation and business performance targets.
This study aims to conduct an exploratory investigation into novel knowledge combinations for innovation within high-tech cluster firms. Our two-fold research question is: ‘Where and how do hi-cluster firms combine knowledge for innovation?’
Methodology
To approach potential participants, we used the list of UK high-tech clusters available on the UK Tech Cluster Group website. Then, we gathered the names of cluster member companies from the official websites of the listed high-tech clusters. Only six clusters had published their member directories: Cambridge Cluster (Silicon Fen), TechSpark, Manchester Digital, ScotlandIS, Sunderland Software City, and 91Ö±²¥ Digital. We then sent our survey directly to the senior management teams of these companies using contact information from reliable platforms – Crunchbase and Beauhurst. Over three months (March, April, and May 2024), we sent further four reminders to the senior managers. In the end, we obtained 37 complete responses, which serve as the sample for this study.
We conducted a Qualitative Comparative Analysis (QCA) on a sample of 37 high-tech cluster firms. To ensure the validity of our findings, we performed statistical tests to assess common method variance and non-response bias. Although the sample size is relatively small, the tests indicate that these biases do not significantly affect the data. Additionally, we adhered to QCA best practices by conducting multiple robustness tests, which confirmed that our results are reliable.
Results
We identify multiple knowledge-sourcing mechanisms that contribute to high innovation performance. Our findings suggest that it is essential for highly innovative cluster firms to access knowledge beyond cluster boundaries. This research project has several practical implications. First, high-tech cluster firms do not need to relocate but should adjust their knowledge-sourcing strategies to sustain high innovation performance. Second, R&D investment alone is neither a sufficient nor necessary condition for achieving high innovation performance. In fact, we found that some low-innovation performers have high levels of R&D investment but fail to integrate external knowledge into their innovation processes especially in dynamic industry environments.
