Tracing university–industry knowledge transfer through a text mining approach

Woltmann, Sabrina; Alkærsig, Lars

doi:10.1007/s11192-018-2849-9

Cited by 9 publications

(6 citation statements)

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“…There are also challenges for measuring exchanges between universities and SMEs. An important current of research is based on patents and their connection to publications and other documentary sources (Woltmann & Alkaersig, 2018). There is substantial evidence about spin-off and start-up companies as they are easily identifiable and make greater use of the university resources available (Woltmann, 2012).…”

Section: An Empirical Application: the Study Of University-industry Relationships In Innovation Systemsmentioning

confidence: 99%

The use of QCA in science, technology and innovation studies: a review of the literature and an empirical application to knowledge transfer

et al. 2021

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This article analyses the use of qualitative comparative analysis (QCA) in social studies on science, technology and innovation. The goals are to address how and why the method is used, and to explore the advantages and shortcomings for this research area. A review of the literature and practical application are combined. Firstly, the article finds that the acceptance of QCA is unevenly distributed in the major research fields related to knowledge production. It is used mainly to study innovation in firms but is largely absent in science and technology studies. Second, an original study on university–industry links provides a strategic site that displays how research unfolds. Its findings demonstrate the combinations of factors that shape knowledge transfer and the configurational nature of the process. The article offers an account of challenges and directions for future research and discusses the possibilities of the method as a third way between qualitative and quantitative traditions in science, technology and innovation.

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Section: An Empirical Application: the Study Of University-industry Relationships In Innovation Systemsmentioning

confidence: 99%

The use of QCA in science, technology and innovation studies: a review of the literature and an empirical application to knowledge transfer

et al. 2021

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“…In their study, the authors employ latent Dirichlet allocation algorithm and TF-IDF term indexing to identify knowledge transfer that is typically overlooked in conventional studies by detecting connections of scientific publications and company documents. The findings of this study provide new insights into a better understanding of successful university-industry collaborations from the perspective of policymakers and other stakeholders (Woltmann and Alkaersig 2018).…”

Section: Mining Is Also Related To Other Research Fields Including Mmentioning

confidence: 84%

“…Second, this dissertation responds to the growing recognition of automated text analysis as a core method to make new theoretical and practical advancements in social science research and the academic entrepreneurship domain in particular (Buenstorf and Heinisch 2020;Hannigan et al 2019;Woltmann and Alkaersig 2018;Woo et al 2019;Wullum Nielsen and Börjeson 2019). In Chapter 5 we offer a novel (unsupervised) machine learning solution that provides (1) considerable scalability advantages compared to existing approaches, an important issue to consider when textual sources become big data, (2) after robust validation, this solution enables to generate new theoretical artefacts of studied concepts, (3) provides a solution for researchers to study USOs, high-tech start-ups and other ventures in their initial commercialisation phases to conduct a comprehensive assessment of venture potential and predict its future development scenarios using textual data such as business plans, patents, diaries, etc.…”

Section: Methodological Implicationsmentioning

confidence: 99%

“…Furthermore, authors suggest using text mining techniques on policy-level data to enhance further engagement of the public, stakeholders, and government parties . Additionally, Woltmann and Alkaersig (2018) argue that despite the increasing importance of academia to contribute to the socio-economic development, the detection of relevant knowledge transfer remains challenging. The authors, therefore, call for new methodological approaches to assess knowledge transfer of universities quantitatively.…”

Section: Mining Is Also Related To Other Research Fields Including Mmentioning

confidence: 99%

“…Our fourth main contribution is twofold and contributes new insights into two research gaps. On the one hand, we respond to the calls to replace conventional research methods with novel automated text analysis techniques (Hannigan et al 2019;Suominen et al 2017;Woltmann and Alkaersig 2018;Wullum Nielsen and Börjeson 2019), and on the other hand, we contribute new insights into conceptualisation and differentiation of USOs (see e.g. Bathelt et al 2010;Djokovic and Souitaris 2008;Mustar et al 2006;Pirnay et al 2003) and into research particularly emphasising the role of their competences (see e.g.…”

Section: Implications For Theorymentioning

confidence: 99%

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Towards an integrated understanding of university research commercialisation: a university spin-off perspective

Skute¹

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To study the impact of the early-stage USO characteristics on the likelihood to acquire funding and survive on the market (Chapter 4), and delineate different USO types based on self-perceived first-and second-order competences using unsupervised text mining techniques (Chapter 5), this dissertation uses a unique dataset from a Valorisation Grant (VG) programme managed by the Dutch Research Council (NWO; Dutch: Nederlandse Organisatie voor Wetenschappelijk Onderzoek) and previously Technology Foundation STW. NWO "ensures quality and innovation in science and facilitates its impact on society. Its main task is to fund scientific research at public research institutions in the Netherlands, especially universities. NWO focuses on all scientific disciplines and fields of research. The funds are allocated by means of a national competition on the basis of quality and independent assessment and selection procedures. NWO plays several roles as a broad, national research organisation that actively contributes to various elements of national science and innovation policy" (NWO 2020). Considering that NWO' funding instruments are primarily sponsored by the Ministry of Education, Culture and Science, and to some degree by other government ministries (e.g. Ministry of Economic Affairs, Ministry of Health, Welfare and Sport, Ministry of Foreign Affairs, Ministry of Infrastructure and the Environment), NWO aims to provide funding to the best scientific talents and the best research proposals through competition (NWO 2020). In line with the recent literature arguing about the increasing importance of university spin-offs as technology and knowledge transfer mechanisms with a potential to create new economic and societal impact (see, e.g. Bock et al. 2017; François and Philippart 2019; Muscio et al. 2016), NWO recognises the need to provide financial support to leverage the initial venturing stages of academic entrepreneurs. Through the VG programme, NWO seeks to minimise the gap between pre-organisation phase of USOs and the credibility threshold that enables USOs to signal external investors and venture capitalists about their readiness to CHAPTER 2: Mapping the field: A bibliometric analysis of the literature on university-industry collaborations This chapter is published as Skute, I., Zalewska-Kurek, K., Hatak, I., & de Weerd-Nederhof, P. (2019). Mapping the field: a bibliometric analysis of the literature on university-industry collaborations.

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Mapping of topics in DESIDOC Journal of Library and Information Technology, India: a study

Lamba

Madhusudhan

2019

Scientometrics

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This study analyzed 928 full-text research articles retrieved from DESIDOC Journal of Library and Information Technology for the period of 1981-2018 using Latent Dirichlet Allocation. The study further tagged the articles with the modeled topics. 50 core topics were identified throughout the period of 38 years whereas only 26 topics were unique in nature. Bibliometrics, ICT, information retrieval, and user studies were highly researched areas in India for the epoch. Further, Spain and Taiwan showed common research trends and areas as India whereas India has quite distinct research interests from America and China. Therefore, researchers in Library and Information Science in India should pay more attention to the topics which are under-researched. Further, it was found that there were some unique sub-fields to Indian Library and Information Science research, such as open access; online exhibition; virtual libraries; multimedia libraries; open source software; library automation; and library management system. With the passage of time topics evolve over time, new topics emerge, and old ones become obsolete. Topic modeling not only helps the researcher to determine the trending themes or related fields with respect to their field of interest but also helps them to identify new concepts and fields over time.

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Tracing university–industry knowledge transfer through a text mining approach

Cited by 9 publications

References 47 publications

The use of QCA in science, technology and innovation studies: a review of the literature and an empirical application to knowledge transfer

The use of QCA in science, technology and innovation studies: a review of the literature and an empirical application to knowledge transfer

Towards an integrated understanding of university research commercialisation: a university spin-off perspective

Mapping of topics in DESIDOC Journal of Library and Information Technology, India: a study

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