This research proposes an innovative data model to determine the landscape of emerging technologies. It is based on a competitive technology intelligence methodology that incorporates the assessment of scientific publications and patent analysis production, and is further supported by experts’ feedback. It enables the definition of the growth rate of scientific and technological output in terms of the top countries, institutions and journals producing knowledge within the field as well as the identification of main areas of research and development by analyzing the International Patent Classification codes including keyword clusterization and co-occurrence of patent assignees and patent codes. This model was applied to the evolving domain of 3D bioprinting. Scientific documents from the Scopus and Web of Science databases, along with patents from 27 authorities and 140 countries, were retrieved. In total, 4782 scientific publications and 706 patents were identified from 2000 to mid-2016. The number of scientific documents published and patents in the last five years showed an annual average growth of 20% and 40%, respectively. Results indicate that the most prolific nations and institutions publishing on 3D bioprinting are the USA and China, including the Massachusetts Institute of Technology (USA), Nanyang Technological University (Singapore) and Tsinghua University (China), respectively. Biomaterials and Biofabrication are the predominant journals. The most prolific patenting countries are China and the USA; while Organovo Holdings Inc. (USA) and Tsinghua University (China) are the institutions leading. International Patent Classification codes reveal that most 3D bioprinting inventions intended for medical purposes apply porous or cellular materials or biologically active materials. Knowledge clusters and expert drivers indicate that there is a research focus on tissue engineering including the fabrication of organs, bioinks and new 3D bioprinting systems. Our model offers a guide to researchers to understand the knowledge production of pioneering technologies, in this case 3D bioprinting.

This scientometric analysis of 393 original papers published from January 2000 to June 2019 describes the development and use of bioinks for 3D bioprinting. The main trends for bioink applications and the primary considerations guiding the selection and design of current bioink components (i.e., cell types, hydrogels, and additives) were reviewed. The cost, availability, practicality, and basic biological considerations (e.g., cytocompatibility and cell attachment) are the most popular parameters guiding bioink use and development. Today, extrusion bioprinting is the most widely used bioprinting technique. The most reported use of bioinks is the generic characterization of bioink formulations or bioprinting technologies (32%), followed by cartilage bioprinting applications (16%). Similarly, the cell-type choice is mostly generic, as cells are typically used as models to assess bioink formulations or new bioprinting methodologies rather than to fabricate specific tissues. The cell-binding motif arginine-glycine-aspartate is the most common bioink additive. Many articles reported the development of advanced functional bioinks for specific biomedical applications; however, most bioinks remain the basic compositions that meet the simple criteria: Manufacturability and essential biological performance. Alginate and gelatin methacryloyl are the most popular hydrogels that meet these criteria. Our analysis suggests that present-day bioinks still represent a stage of emergence of bioprinting technology.

While novel technologies have tremendous competitive potential, they also involve certain risks. Maturity assessment analyzes how well a technological development can fulfill an expected task. The technology readiness level (TRL) has been considered to be one of the most promising approaches for addressing technological maturity. Nonetheless, its assessment requires opinions of the experts, which is costly and implies the risk of personal bias. To fill this gap, this paper presents a Bibliometric Method for Assessing Technological Maturity (BIMATEM). It is a repeatable framework that assesses maturity quantitatively. Our method is based on the assumption that each technology life cycle stage can be matched to technology records contained in scientific literature, patents, and news databases. The scientific papers and patent records of mature technologies display a logistic growth behavior, while news records follow a hype-type behavior. BIMATEM determines the maturity level by curve fitting technology records to these behaviors. To test our approach, BIMATEM was applied to additive manufacturing (AM) technologies. Our results revealed that material extrusion, material jetting, powder bed fusion and vat photopolymerization are the most mature AM technologies with TRL between 6 and 7, followed by directed energy deposition with TRL between 4 and 5, and binder jetting and sheet lamination, the least mature, with TRL between 1 and 2. BIMATEM can be used by competitive technology intelligence professionals, policymakers, and further decision makers whose main interests include assessing the risk of implementing new technologies. Future research can focus on testing the method with regard to altmetrics.Electronic supplementary materialThe online version of this article (10.1007/s11192-018-2941-1) contains supplementary material, which is available to authorized users.

No abstract

Purpose The purpose of this paper is to deliver a roadmap that displays pathways to develop sustainability skills in the engineering curricula. Design/methodology/approach The selected approach to enrich engineering students with sustainability skills was active learning methodologies. First, a survey was carried out on a sample of 189 students to test the current sustainability literacy and determine the roadmap starting point. Next, a scientometric study regarding active learning methodologies was executed. A total of 2,885 articles and conference proceedings from the period 2013-2016 were retrieved from the Web of Science database. The records were then imported into text mining software to undergo a term clumping process. Annual knowledge clusters based on key terms were outputted. Finally, a roadmap was created by experts based on the annual knowledge clusters. Findings Four annual pathways were created along the roadmap to develop sustainability skills during the four-year college course in engineering. The first consisted on promoting a recycling campaign through a circular economy. The second aimed at creating educational videos regarding sustainability. The third reinforced reasoning and argumentative skills by preparing a debate on environmental issues. The last path assumed that the student is working in internship programs and prepared him/her to apply environmental management models to solve sustainability issues within the company. Research limitations/implications Roadmaps should be updated approximately every two years to reflect novelty. The proposed methodology shows an easy way to create them. Practical implications Results from this paper, as well as the proposed methodology, can be applied to any organization forming individuals: from primary school education to employee training programs in organizations. Social implications The development of sustainability skills has a direct, positive impact on professional decision-making and, ultimately, on the environment. Originality/value This paper presents a roadmapping process to develop sustainability competences throughout engineering college education.