All posts by VPInstitute

Interdisciplinarity and collaboration: on the relationship between disciplinary diversity in departmental affiliations and reference lists

Interdisciplinarity, Research Examples

This study explores the characteristics of scientific activity patterns through co-author affiliations to obtain new insights into interdisciplinary research. To classify the interdisciplinarity in research, we explored and compared two different approaches: the diversity of disciplines reflected in the listed affiliations of the authors and the diversity of the subject categories reflected in the reference list. To assess the diversity in departmental affiliations, we developed an explorative methodology that retrieves feature words from a combination of manual work and the thesaurus function in the Thomson Data Analyzer text mining tool. To assess the diversity in references, we followed the conventional approach applied in previous work. With both approaches, we relied on diversity as the measure for assessing interdisciplinarity of 157,710 articles published in PloS One (2007–2016). Based on a comparison between the results of both approaches, our study confirms that different methodologies and indicators can produce seriously inconsistent, and even contradictory results. In addition, different indicators may capture different understandings of such a multi-faceted concept as interdisciplinarity. Our results are summarized in a schematic representation of this twofold perspective as a method of indexing the different types of interdisciplinarity commonly found in research studies.

https://doi.org/10.1007/s11192-018-2853-0

Author(s): Lin Zhang, Beibei Sun, Zaida Chinchilla-Rodríguez, Lixin Chen, Ying Huang
Organization(s): Wuhan University, North China University of Water Resources and Electric Power
Source: Scientometrics
Year: 2018

Revisiting the concept of Innovative Developing Countries (IDCs) for its relevance to health innovation and neglected tropical diseases and for the prevention and control of epidemics (Full-paper)

Network analysis, Research Examples, Research Type

Splitting countries into two groups—rich and poor; developed (the “North”) and developing (the “South”); leaders and followers—appears to us to be progressively more simplistic, unrealistic and a heritage from colonial times. Triggered by the first wave of globalization, the share of world income going to today’s wealthy nations soared from twenty to almost seventy percent between 1820 and 1990, a fact that supported and strengthened this dichotomic vision; however, the new globalization driven by information technology has propelled the rapid industrialization of several developing nations and simultaneous deindustrialization of developed nations, a phenomenon that has not yet been fully understood nor reflected in traditional economic indexes and analyses. In this article we revisit the 2005 concept of Innovative Developing Countries (IDCs) that points to the underrepresentation of IDCs in well-known innovation indexes and country ranks. Our analysis clearly shows a prominent role for IDCs in health innovation, research and development on NTDs and in epidemics preparedness, prevention and control.

Full-paper link

Author(s): Alexandre Guimarães Vasconcellos, Bruna de Paula Fonseca e Fonseca, Carlos Medicis Morel
Organization(s): National Institute of Industrial Property (INPI), Oswaldo Cruz Foundation (Fiocruz)
Source: PLoS Neglected Tropical Diseases
Year: 2018

A new model based on patent data for technology early warning research

Research Examples, Research Type, ST&I indicators, Strategic planning

As technology competition among enterprises become more intense, technical crisis occurs in enterprises, such as technological substitution and technology divulgence. Thus, it is necessary to warn enterprises of those technical crises that can be called technology early warning. As patent data contains much technology information, it becomes an efficient source to analyse technology. This paper proposes a technology early warning model based on patent data to help enterprises execute technology early warning from the perspective of its technology status. To do so, we set ten indicators from four aspects to evaluate the enterprise’s technology status at first, calculate the index of enterprise’s technical crisis with AHP, and then propose five early warning levels. China Petroleum & Chemical Corporation (Sinopec Group) and the China National Petroleum Corporation (CNPC) are taken as comparative case studies.

https://doi.org/10.1504/IJTM.2018.092969

Author(s): Ying Guo, Ganlu Sun, Lili Zhang, Fan Yang, Junfang Guo, Lin Ma
Organization(s): Beijing Institute of Technology
Source: International Journal of Technology Management
Year: 2018

Analysis of an investment by a seed capital fund using a patento-scientometric approach: the case of probiotics technology for veterinary use

Data Type, Patents, Research Examples, Research profiling, Research Type, S&T lit, ST&I policy

This article examines the potential use of scientometric and patentometric indicators as a way to instrumentalise the process of selecting projects by seed capital funds. Academic interest in high-tech companies is growing due to their ability to contribute to economic and social development. Nevertheless, the literature and documented practice reveal a certain difficulty to evaluate non-financial criteria associated with technologies by venture capital funds. We selected the case of a company that received an investment from Brazil’s largest seed capital fund to analyse the contribution of these indicators to understand the potential of the firm’s technology. We conclude that use of scientometric and patentometric can improve the process of evaluation of the following criteria: technology; market; divestment; and team.

https://doi.org/10.1504/IJBBM.2018.092749

Author(s): Gustavo Da Silva Motta, Maxwel De Azevedo-Ferreira, Rogério Hermida Quintella
Organization(s): Universidade Federal Fluminense, Universidade Federal da Bahia
Source: International Journal of Bibliometrics in Business and Management
Year: 2018

How R&D partner diversity influences innovation performance: an empirical study in the nano-biopharmaceutical field

Patents, Research Examples

R&D partner diversity is generally acknowledged to help organizations to improve innovation performance. This study investigates the influence mechanism in depth by introducing technological diversification as mediator and the structural holes of new knowledge elements from R&D partners and the degree centrality of the focal organization’s knowledge elements as two moderators. The empirical analysis is based on patent data in the emerging nano-biopharmaceutical field and includes 554 innovative organizations. Results show that partners’ organizational diversity and geographical diversity have positive effects on focal organizations’ innovation performance through improving technological diversification. The structural holes of new knowledge elements from R&D partners and the degree centrality of the focal organization’s knowledge elements moderate the process in the way that when they are at high levels, the indirect positive effects of partner diversity on innovation performance through technological diversification are strengthened.

https://doi.org/10.1007/s11192-018-2831-6

Author(s): Guiyang Zhang, Chaoying Tang
Organization(s): Chinese Academy of Sciences
Source: Scientometrics
Year: 2018

Illuminating blind spots and skewness in leadership

Biz lit, Data Type, Research Examples, Research profiling, Research Type

We explore the topic of leadership through a novel approach of analysing social science research literature called computer assisted research profiling (CARP) for ontological profiling. Our review revealed a domination by western approaches and perspectives, leading to some blind spots and skewness in understanding leadership processes, perspectives and research designs. There is a scope of organising leadership research and refining the conceptualisation of leadership in order to adequately include various differential aspects and perspectives of leadership. Often driven by existentialist positioning and unclear objectives, a synthetic integration of approaches result in more confusion. Furthermore, positivist paradigms emanating from the dominant worldview hardly leave space for indigenous approaches and perspectives. The paper suggests to bring ‘leadership research’ philosophically closer to advances in ‘fundamental research’ in physical sciences to benefit from each other. It suggests an integrative paradigm led multi-paradigmatic approach for leadership development by tapping into ancient traditions of the world.

https://doi.org/10.1504/IJTTC.2018.092644

Author(s):Puneet K. Bindlish, Sharda S. Nandram
Organization(s): Indian Institute of Technology, Nyenrode Business University
Source: International Journal of Technology Transfer and Commercialisation
Year: 2018

Discovering and forecasting interactions in big data research: A learning-enhanced bibliometric study

Research Examples, Research profiling, ST&I indicators, Tech mining

As one of the most impactful emerging technologies, big data analytics and its related applications are powering the development of information technologies and are significantly shaping thinking and behavior in today’s interconnected world. Exploring the technological evolution of big data research is an effective way to enhance technology management and create value for research and development strategies for both government and industry. This paper uses a learning-enhanced bibliometric study to discover interactions in big data research by detecting and visualizing its evolutionary pathways. Concentrating on a set of 5840 articles derived from Web of Science covering the period between 2000 and 2015, text mining and bibliometric techniques are combined to profile the hotspots in big data research and its core constituents. A learning process is used to enhance the ability to identify the interactive relationships between topics in sequential time slices, revealing technological evolution and death. The outputs include a landscape of interactions within big data research from 2000 to 2015 with a detailed map of the evolutionary pathways of specific technologies. Empirical insights for related studies in science policy, innovation management, and entrepreneurship are also provided.

https://doi.org/10.1016/j.techfore.2018.06.007

Author(s): Yi Zhang, Ying Huang, Alan L. Porter, Guangquan Zhang, Jie Lu
Organization(s): University of Technology Sydney, Hunan University
Source: Technological Forecasting and Social Change
Year: 2018

Research network emergence: societal issues in nanotechnology and the center for nanotechnology in society

Citation analysis, Network analysis, Research Examples

This article looks at the creation of a network of researchers of social issues in nanotechnology and the role of the Center for Nanotechnology in Society at Arizona State University (CNS-ASU) in the creation of this network. The extent to which CNS-ASU is associated with the development of a research network around the study of social issues in nanotechnology is examined through geographic mapping of co-authors and citations of center publications, network analysis of co-authors of papers on social issues in nanotechnology, and a disciplinary analysis of these papers. The results indicate that there is an extensive network of co-authorships among researchers studying social issues in nanotechnology with CNS-ASU at the center of this network. In addition, papers written by center members and affiliates integrate a diverse range of disciplines. Qualitative data are used to interpret some of the ways that citation occurs.

https://doi.org/10.1093/scipol/scy043

Author(s): Jan Youtie, Philip Shapira, Michael Reinsborough, Erik Fisher
Organization(s): Georgia Institute of Technology, Arizona State University
Source: Science and Public Policy
Year: 2018

A Study of Methods to Identify Industry-University-Research Institution Cooperation Partners based on Innovation Chain Theory

Network analysis, Research Examples, ST&I indicators, ST&I policy, Strategic planning

This study aims at identifying potential industry-university-research collaboration (IURC) partners effectively and analyzes the conditions and dynamics in the IURC process based on innovation chain theory.

Design/methodology/approach: The method utilizes multisource data, combining bibliometric and econometrics analyses to capture the core network of the existing collaboration networks and institution competitiveness in the innovation chain. Furthermore, a new identification method is constructed that takes into account the law of scientific research cooperation and economic factors.
Findings: Empirical analysis of the genetic engineering vaccine field shows that through the distribution characteristics of creative technologies from different institutions, the analysis based on the innovation chain can identify the more complementary capacities among organizations.Research limitations: In this study, the overall approach is shaped by the theoretical concept of an innovation chain, a linear innovation model with specific types or stages of innovation activities in each phase of the chain, and may, thus, overlook important feedback mechanisms in the innovation process.
Practical implications: Industry-university-research institution collaborations are extremely important in promoting the dissemination of innovative knowledge, enhancing the quality of innovation products, and facilitating the transformation of scientific achievements.
Originality/value: Compared to previous studies, this study emulates the real conditions of IURC. Thus, the rule of technological innovation can be better revealed, the potential partners of IURC can be identified more readily, and the conclusion has more value.

http://manu47.magtech.com.cn/Jwk3_jdis/Y2018/V3/I2/38

Author(s): Haiyun Xu, Chao Wang, Kun Dong, Rui Luo, Zenghui Yue, Hongshen Pang
Organization(s):
Source: Journal of Data and Information Science
Year: 2018

Tracing the system transformations and innovation pathways of an emerging technology: Solid lipid nanoparticles

Future-oriented technology analysis, Research Examples, Strategic planning

Accurately evaluating opportunities in new and emerging science and technologies is a growing concern. This study proposes an integrated framework for identifying a range of potential innovation pathways and commercial applications for solid lipid nanoparticles – one particularly promising contender within the field of nano-enabled drug delivery. Several text mining techniques – term clumping, SAO technique, and net effect analysis – as well as technology roadmapping, are combined with expert judgment to identify the main areas of R&D in this field, and to track their evolution over time. Through analysis, data from multiple sources, including research publications, patents, and commercial press, reveal possible future applications and commercialization opportunities for this emerging technology. We find that research is moving away from materials and delivery outcomes toward clinical applications. The most promising markets are pharmaceuticals and cosmetics; however, the “time-to-market” is much shorter for cosmetics than it is for pharmaceuticals.

The most significant contributions of this paper have been highlighted as follows. One innovation is extracting the intelligence from three kinds of data sources after in-depth considering their characteristics and matching with the features of different technology development stages to identify innovative research topics. The second one is combining SAO technique with net effect analysis to identify what the evolutionary links between research topics are, and then to use TRM to visualize the evolution of the main areas of R&D over time.

https://doi.org/10.1016/j.techfore.2018.04.026

Author(s):Xiao Zhou, Lu Huang, Alan Porter, Jose M.Vicente-Gomila
Organization(s): Xidian University, Beijing Institute or Technology
Source: Technological Forecasting and Social Change
Year: 2018