Identification and Mapping of Fintech Clustering Using a Qualitative-dominant Mixed Method

Abstract

This research delves into the complex landscape of the fintech ecosystem, specifically focusing on the Northwest City region of Ireland, employing a mixed-method approach. The study focused on the methodology used to identify and map the fintech clusters. Different methodologies have been used to map and identify clustering due to its evolving nature. In our case, due to the lack of fintech companies' records on publicly available databases, and fintech being an emerging phenomenon, our methodology relied on a combination of approaches like desk research, stakeholder engagement, geospatial analysis, and in-depth interviews which fall under the qualitative-dominant mixed method approach. Despite a diverse range of methodologies being used to identify clusters, some known studies have used mixed methods. This research aims to provide guidelines for identifying clusters by developing a database of the companies in the fintech sector and its validation in an evolving field like Fintech. It also highlights the importance of the use of geospatial analysis in clustering by mapping the fintech companies, however at the same time questions the simple agglomeration of the firms in the region. It’s not only the physical proximity that develops the clusters but the local linkages, collaborations, and networks that play a pivotal role in reaping the benefits of clusters. The detailed interviews with the fintech companies in the region and their relationship with different components of the fintech ecosystem using the triple helix model highlighted the strengths and weaknesses of the fintech ecosystem in the region. The application of mixed methods in this research highlights the value gained in exploring fintech clustering and ecosystems. This study further enhances our understanding of the emerging phenomenon of fintech clusters and ecosystems in cluster-based economies, specifically how a combination of approaches could be used to map and identify fintech clusters.  It also furthers the boundaries of knowledge in business and management methodological literature by introducing a comprehensive qualitative-dominant mixed method approach with a consolidating knowledge base on methodological approaches to clustering.