My name is Sébastien Martin, I am a PhD student working for the EINST4INE project ESR position number 9, i.e. The technological and industrial convergence and the interplay between technology-centered ecosystems. The main conceptual challenges are to better understand how the transitions do happen between distinct stages of convergence, which may be roughly defined as the blurring of boundaries between different formerly distinct domains and giving rise to the emergence of new ones or the enrichment of previously existing ones through knowledge recombination, and how these phenomena are related to the emergence and the development of ecosystems. This implies extracting the knowledge spread in the unstructured data related to the various stages of convergence, for example at the intersection between technology and industry convergence. This better understanding is mandatory to assess the feasibility of anticipating the future convergence phenomena and their implications for the different stakeholders of the ecosystems. 

Beyond the scientific excellence implied by the program, and the possibility of participating in an international project, the main reason I applied to be part of the EINST4INE project is due to its multidisciplinary nature, especially from the thesis topic on which I started to work. 

Several tracks are currently followed in parallel, and the overall achievement relies of course on the achievement of each one: 

– I am currently proceeding with a systematic review of the core component of my topic, i.e. the concept of convergence, itself framed in the broader field of technology innovation management, and from which I expect the submission of a conference paper and even a journal paper by the end of the PhD program. This will also be a valuable basis to refine the research questions and address theoretical as well as practical issues. 

– As the basic idea is to leverage the content of unstructured data, I am also reviewing how the existing literature managed to extract semantic information, considering both the papers specifically dedicated to convergence topics, but also the ones focusing on patents as large, and more generally on the methods developed by state-of-the-art NLP models dealing with semantic similarity. 

– I am also considering the relevant case studies to explore, considering at the same time the similarity with previous studies to enable fruitful comparisons with the current literature and being part of the digital transformation topic. 

– I am gathering the sources required to answer the research questions. The particularity of the research undertaken, compared to traditional approaches based on questionnaires or interviews, is that the sources exist beforehand. The positive aspect is that we are sure to have the sources and that they require a shorter collection time. The less favorable aspects are that it is hardly possible to tailor the data collected according to the research questions, which transfers the burden on data processing and the determination of valid and relevant indicators, and that most of the work involves extracting value from data through algorithms such as NLP-based methods. The sources on which this PhD is based will be patents first, then scientific publications. We do not exclude a later consideration of various complementary sources such as reports, news, or even social network data.  

From the research standpoint, consistent with my initial aspirations, I would like to contribute to extracting the best of interdisciplinary principles, to enrich our fields of research to the best of my abilities. Aside but also as part of my work, I want to highlight the transformative potential of working at the intersection of research questions specific to the field of technology and innovation management, and the development of specifically tailored data-intensive methods. By seeing myself after the end of the doctoral work, as distant as this prospect remains, I would like to continue in the field of research and continue to build on the foundations that will have been laid. 

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