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This paper uses bibliometric methods to review the research on makerspaces. The objective of the study was to document the growth and geographic distribution of makerspace literature, identify the main authors, documents. In addition to this, the study also combined two bibliometric analysis methods, co-citation analysis and co-word analysis to identify the intellectual structure of the makerspace knowledge base and the evolution of research themes over time. A total of 654 documents related to makerspaces between 2012 and 2020 were identified from the Scopus database. The review found that research base on makerspace is starting to grow from 2017 onwards with an accelerating growth rate, however, the published studies are mainly from USA and Europe. The paper also lists the most cited documents, the influential sources of publications and the main authors working on this area. The review also identified five research clusters using co-citation analysis that have emerged over time which are “innovation and development in makerspaces”, “child development in makerspaces”, “learning and STEM education in makerspaces”, “implementation of makerspaces in education”, and “university makerspaces”. Another major finding highlighted “innovation, design, and creativity”, “engineering curriculum”, “skill development”, “computer programming knowledge”, and “learning, collaboration and community development” as the five main research themes using the co-word analysis. These findings provide a robust roadmap for further investigation in this research field.

This paper aims to identify global digital trends across industries and to map emerging business areas by co-word analysis. As the industrial landscape has become complex and dynamic due to the rapid pace of technological changes and digital transformation, identifying industrial trends can be critical for strategic planning and investment policy at the firm and regional level. For this purpose, the paper examines industry and technology profiles of top startups across four industries (i.e. education, finance, healthcare, manufacturing) using CrunchBase metadata for the period 2016–2018 and studies in which subsector early-stage firms bring digital technologies on a global level. In particular, we apply word co-occurrence analysis to reveal which subindustry and digital technology keywords/keyphrases appear together in startup company classification. We also use network analysis to visualize industry structure and to identify digitalization trends across sectors. The results obtained from the analysis show that gamification and personalization are emerging trends in the education sector. In the finance industry, digital technologies penetrate in a wide set of services such as financial transactions, payments, insurance, venture capital, stock exchange, asset and risk management. Moreover, the data analyses indicate that health diagnostics and elderly care areas are at the forefront of the healthcare industry digitalization. In the manufacturing sector, startup companies focus on automating industrial processes and creating smart interconnected manufacturing. Finally, we discuss the implications of the study for strategic planning and management.

For the analysis of doctoral dissertations in information science in the Republic of Croatia (from 1978 to 2007), keywords are used in order to get an insight into the development of information science. By the method of co-word analysis of keywords with which doctoral dissertations are indexed, a network of clusters that match following scientific disciplines is obtained: archival and documentation science, librarianship, communicology, museology, information science, information systems and lexicography. By cluster and data visualization and the overview of keywords frequency, the development of subjects and the correlation of clusters in information science, during the period of thirty years in which doctoral dissertation are made, is shown. The results of the co-word analysis about the development of information science in the Republic of Croatia are shown according to time periods, but also according to affiliation to certain disciplines inside the information science.