Research on the Promotion of New Energy Vehicles Based on Multi-Source Heterogeneous Data

Under the background of green development, new energy vehicles(NEVs), as an important strategic emerging industry, play a crucial role in energy conservation and emission reduction. In the post-epidemic era, steadily promoting the promotion of NEVs will be a hot topic. Based on heterogeneous source data, combined with the Latent Dirichlet Allocation (LDA) topic model, Social Network Analysis (SNA), and econometric methods, this paper explores whether individual purchase decisions and company-level cooperative research and development will promote the promotion of new energy vehicles. The results show that whether BEV, HEV, or PHEV, users are more concerned about space dimension, power performance, and design style; Patent collaboration network analysis indicates that NEV enterprises are establishing close partnerships, which will urge the promotion of NEVs; For BEV and HEV models, new energy vehicle companies will invest more patents and R&D investment will better expedite the advancement of NEVs.

A Bibliometric Analysis of Global Fine Roots Research in Forest Ecosystems during 1992–2020

(1) Background: Fine roots (≤2 mm in diameter) play a critical role in forest ecosystem ecological processes and has been widely identified as a major research topic. This study aimed to synthesize the global literature based on the Web of Science Core Collection scientific database from 1992 to 2020 and summarize the research trends and prospects on research of fine roots in forest ecosystems. A quantitative bibliometric analysis was presented with information related to authors, countries, institutions, journals, top cited publications, research hotspots, trends, and prospects. (2) Results: The results showed that the amount of publications has increased exponentially. USA, China, and Germany were the most productive countries. Chinese Academy of Science was the most productive institution on fine roots research and also has a key position in both domestic and international cooperation networks. Leuschner C and Hertel D were the most productive authors. Six core journals were confirmed from 471 journals based on Bradford’s law. The distribution of the frequency of authors and the number of their publications were fitted with Lotka’s Law. Author collaboration network was mainly limited in the same countries/territories and institutions. Keywords analysis indicates that the hotspots are biomass, decomposition, and respiration of fine roots, especially under climate change. (3) Conclusion: Our results provide a better understanding of global characteristics and trends of fine roots that have emerged in this field, which could offer reference for future research.

A Bibliometric Analysis of Endoscopic Sedation Research: 2001–2020

Background and Aims: To evaluate endoscopic sedation research and predict research hot spots both quantitatively and qualitatively using bibliometric analysis.Methods: We extracted relevant publications from the Web of Science Core Collection (WoSCC) on 13 December 2020. We examined the retrieved data by bibliometric analysis (e.g., co-cited and cluster analysis, keyword co-occurrence) using the software CiteSpace and VOSviewer and the website of bibliometrics, the Online Analysis Platform of Literature Metrology (http://bibliometric.com/), to analyse and predict the trends and hot spots in this field.Main Results: We identified 2,879 articles and reviews on endoscopic sedation published between 2001 and 2020. Although the overall trend is increasing, with slight fluctuation in some years, there were significant increases in 2007 and 2012. In respect of the contributions on endoscopic sedation research, the United States (US) had the greatest number of publications, and it was followed by Japan and China. In addition, collaboration network analysis revealed that the most frequent collaboration was between the US and China. Six of the top ten most prolific research institutions were located in the US. The most publications on endoscopic sedation research in the past two decades were found primarily in journals on gastroenterology and hepatology. Keyword co-occurrence and co-citation cluster analysis revealed the most popular terms relating to endoscopic sedation in the manner of cluster labels; these included patient anxiety, tolerance, ketamine, propofol, hypoxia, nursing shortage, endoscopic ultrasonography, colorectal cancer, carbon dioxide insufflation, and water exchange (WE). Keyword burst detection suggested that propofol sedation, adverse event, adenoma detection rate (ADR), hypoxemia, and obesity were newly-emergent research hot spots.Conclusions: Our findings showed that hypoxia, adverse event, and ADR, along with conscious sedation and propofol sedation, have been foci of endoscopic sedation research over the past 20 years. The research focus has shifted from sedative drugs to sedative complications and endoscopy quality control, which means that there will be higher requirements and standards for sedative quality and endoscopy quality in the future.

Responsible Research and Innovation (RRI): Scientometric Analysis

Innovation and research in various fields should be done responsibly. In the last years, there is this responsibility towards different stakeholders. One of the most important stakeholders are the community and the society. In this context, the concept of social responsibility and social innovation has become very widespread. The purpose of this study was scientometric analysis of concepts in the field of responsible innovation and responsible research. R software has been used to achieve this purpose. In this study, by analyzing the information extracted from related articles (572 articles from Web of Science), the new concept of RRI and the network of researchers in this regard have been identified and analyzed. In this study, based on a systematic literature review (SLR) and scientometric methods, the evolution of the concept of “Responsible Research” and “Responsible Innovation” in the literature is investigated. Also, the selected articles identified by the SLR method from different textual dimensions regarding journals, collaboration network, co-citation network, collaboration worldmap, historical direct citation network, and emergence of new concepts are analyzed. The results of this study indicate the development of related concepts in the literature in recent years and indicate the need for further studies in this regard.

Collaborative idea generation: an experience of open creativity in the public sector

Purpose This paper aims to analyze idea generation in a public-private collaboration of a Brazilian Government Agency. The authors start from the following research question: How did the process of open creativity occur from collaboration, network relationships and creative practice in the experience of open innovation cycles of the Public Prosecutor’s Office of Pernambuco, Brazil? Design/methodology/approach The research was characterized as a case study that empirically explored a contemporary phenomenon in a specific context. The authors conducted document research and interviews and used the content analysis technique. Findings The findings showed that open creativity enabled more efficient idea generation when the public-private partnership was established in a well-structured collaboration network with the private sector of the economy; when it consisted of a heterogeneous group of external collaborators who developed a wide exchange of expertise; and when practical actions were developed to make the creative process more efficient. Research limitations/implications The study was limited to a single reality. The study was conducted in a single country and other nations may have social and institutional elements that were not considered in the analysis and that may influence the results in similar studies. Originality/value The authors investigated open creativity in the public sector, a field that still has gaps in understanding. The authors focused on social relationships for the generation and improvement of ideas among actors external to the organization involved, a niche that is still little explored in the literature.

The Differential Impact of Intrafirm Collaboration and Technological Network Centrality on Employees’ Likelihood of Leaving the Firm

How does an employee’s centrality in intrafirm research and development activities affect the employee’s propensity for outward mobility? Does this proclivity vary by the type of employment the employee seeks: moving to other firms versus founding a new venture? We maintain that, to answer these questions, we must distinguish between an employee’s centrality in the intrafirm collaboration network and the employee’s centrality in the intrafirm technological recombination network. We utilize the curricula vitae and patent data of corporate inventors at a leading semiconductor company between 1993 and 2012 to test our hypotheses. Contrary to prevailing views, our competing risk model indicates that corporate inventors who are central in the intrafirm collaboration and technological network and, thus, have the most opportunities are less likely to leave the current employer. However, when considering external employment opportunities, their preferences vary. Collaboration-central individuals are more likely to start a new venture than to move to another employer. Their skill in developing interpersonal relationships enables them to attract the tangible and intangible resources needed in a new firm. In contrast, inventors whose technological expertise is central to the firm’s technology recombination network are more likely to move to another employer than to start a new venture. In an established firm, they can leverage their technological know-how using the resources that a new venture would lack. Our theory highlights the trade-offs in employees’ attempts to take advantage of their internal and external value based on their position within the firm’s collaboration and technological networks.

Patterns of student collaborative learning in blended course designs based on their learning orientations: a student approaches to learning perspective

This study combines research methods from student approaches to learning research and social network analysis (SNA) to examine patterns of students’ collaborative learning based on their learning orientations amongst 193 postgraduates enrolled in a blended course. The study identified two distinct learning orientations, namely ‘understanding’ and ‘reproducing’, which differed in approaches to learning through inquiry, approaches to using online learning technologies, perceptions of the online workload, and academic outcomes. On the basis of students’ learning orientations and their choice of whether to collaborate and with whom to collaborate, five networks representing five patterns of collaborative learning were found. From these, two did not reveal any collaboration (Understanding Alone and Reproducing Alone networks); and three revealed collaborations (Understanding Collaboration, Mixed Collaboration, Reproducing Collaboration networks). A range of SNA measures were calculated and revealed different features of the three collaboration networks. Viewed together, the combined methodologies suggest that the Understanding Collaboration network has more desirable features of collaboration, such as the intensity of collaboration, having closely knitted groups who tended to seek out and welcome peers and who tended to engage more often in both face-to-face and online modes. The study suggests that helping students adjust their learning orientations, designing some compulsory collaborative assessment tasks, and configuring the composition of collaborative groups are productive strategies likely to improve students’ experiences of collaborative learning.

Leveraging multifaceted proximity measures among developers in predicting future collaborations to improve the social capital of software projects

Social capital is an asset earned by people through their social connections. One of the motivations among developers to contribute to open source development and maintenance tasks is to earn social capital. Recent studies suggest that the social capital of the project has an impact on the sustained participation of the developers in open source software (OSS). One way to improve the social capital of the project is to help the developers in connecting with their peers. However, to the best of our knowledge, there is no prior research which attempts to predict future collaborations among developers and establish the significance of these collaborations on improving the social capital at the project level. To address this research gap, in this paper, we model the past collaborations among developers on version control system (VCS) and issue tracking system (ITS) as homogeneous and heterogeneous developer social network (DSN). Along with the novel path count based features, defined on proposed heterogeneous DSN, multifaceted proximity features are used to generate a feature set for machine learning classifiers. Our experiments performed on 5 popular open source projects (Spark, Kafka, Flink, WildFly, Hibernate) indicate that the proposed approach can predict the future collaborations among developers on both the platforms i.e. VCS as well as ITS with a significant accuracy (AUROC up to 0.85 and 0.9 for VCS and ITS respectively). A generic metric- recall of gain in social capital is proposed to investigate the efficacy of these predicted collaborations in improving the social capital of the project. We also concretised this metric on various measures of social capital and found that collaborations predicted by our approach have significant potential to improve the social capital at project level (e.g. Recall of gain in cohesion index up to 0.98 and Recall of gain in average godfather index up to 0.99 for VCS). We also showed that structure of collaboration network has an impact on the accuracy and usefulness of predicted collaborations. Since the past research suggests that many newcomers abandon the open source project due to social barriers which they face after joining the project, our research outcomes can be used to build the recommendation systems which might help to retain such developers by improving their social ties based on similar skills/interests.