Patent research in academic literature. Landscape and trends with a focus on patent analytics.

Patent analytics is crucial for understanding innovation dynamics and technological trends. However, a comprehensive overview of this rapidly evolving field is lacking. This study presents a data-driven analysis of patent research, employing citation network analysis to categorize and examine research clusters.

How teleworking adoption is changing the labor market and workforce dynamics?

This article investigates how teleworking adoption influenced the labor market and workforce dynamic using bibliometric methods to overview 86 years of teleworking research [1936-2022]. By grouping the retrieved articles available on the Web of Science (WOS) core collection database, we revealed a holistic and topical view of teleworking literature using clustering and visualization techniques. Our results reflect the situation where the adoption of teleworking in the last three years was accelerated by the pandemic and facilitated by innovation in remote work technologies.

Employee well-being and innovativeness: A multi-level conceptual framework based on citation network analysis and data mining techniques.

This study proposes a multilevel conceptual framework for a deeper understanding of the relationship between employee well-being and innovativeness. We overview 49 years of well-being research [1972-2021] and 54 years of research on innovativeness [1967-2021] to uncover 24 dominant themes in well-being and ten primary topics in innovativeness research. Citation network analysis and text semantic similarity were used to develop a conceptual framework featuring 21 components and three levels: individual, organizational, and market.

Exploring Topics in Bibliometric Research Through Citation Networks and Semantic Analysis.

This article surveys topic distributions of the academic literature that employs the terms bibliometrics, scientometrics, and informetrics. This exploration allows informing on the adoption of those terms and publication patterns of the authors acknowledging their work to be part of bibliometric research. We retrieved 20,268 articles related to bibliometrics and applied methodologies that exploit various features of the dataset to surface different topic representations.

Exploration of Shared Themes Between Food Security and Internet of Things Research Through Literature-Based Discovery.

This paper applied a literature-based discovery methodology utilizing citation networks and text mining in order to extract and represent shared terminologies found in disjoint academic literature on food security and the Internet of Things. The topic of food security includes research on improvements in nutrition, sustainable agriculture, and a plurality of other social challenges, while the Internet of Things refers to a collection of technologies from which solutions can be drawn. Academic articles on both topics were classified into subclusters, and their text contents were compared against each other to find shared terms.

Collaborative Patterns, Productivity, and Research Impact in the Careers of Star Researchers in a Japanese Semiconductor Company.

This study analyzes how characteristics in the careers of star researchers affect the outcomes of research and development (R&D), based on a case study in a Japanese semiconductor company. By analyzing the collaboration network of patent coinventors in the company, we observe that long-term exposition and collaboration with other high-achieving researchers play a significant role in determining a successful career, that is, in terms of productivity and impact. Also, a deeper exploration of the characteristics of a selected group of star researchers in a company's R&D division helped to identify that it takes 10-15 years to generate remarkable achievements in the form of filing patents that are widely cited at a later stage.

The Academic Landscapes of Manufacturing Enterprise Performance and Environmental Sustainability: A Study of Commonalities and Differences.

This article reviews literature on manufacturing enterprise performance (MEP) and environmental sustainability (ES) to identify their commonalities and distinguishing factors; it is expected to help determine gaps and paths for future research. Topics are classified based on patterns in the citation networks of 7308 and 6275 MEP and ES articles, respectively. Additionally, a semantic linkage was computed to reveal overlap in vocabulary between the two topics.

Landscape of Research Areas for Zeolites and Metal-Organic Frameworks Using Computational Classification Based on Citation Networks.

The field of porous materials is widely spreading nowadays, and researchers need to read tremendous numbers of papers to obtain a "bird's eye" view of a given research area. However, it is difficult for researchers to obtain an objective database based on statistical data without any relation to subjective knowledge related to individual research interests. Here, citation network analysis was applied for a comparative analysis of the research areas for zeolites and metal-organic frameworks as examples for porous materials.

Computer-aided diagnosis: A survey with bibliometric analysis.

Computer-aided diagnosis (CAD) has been a promising area of research over the last two decades. However, CAD is a very complicated subject because it involves a number of medicine and engineering-related fields. To develop a research overview of CAD, we conducted a literature survey with bibliometric analysis, which we report here.

Extraction of business relationships in supply networks using statistical learning theory.

Supply chain management represents one of the most important scientific streams of operations research. The supply of energy, materials, products, and services involves millions of transactions conducted among national and local business enterprises. To deliver efficient and effective support for supply chain design and management, structural analyses and predictive models of customer-supplier relationships are expected to clarify current enterprise business conditions and to help enterprises identify innovative business partners for future success.