Category Archives: Research Examples

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

Innovation core, innovation semi-periphery and technology transfer: The case of wind energy patents

Citation analysis, Network analysis, Research Type, Strategic planning

Some scholars have pointed to a rise of South-South technological transfer led by emerging economies such as China, India, Brazil and South Africa while other scholars highlight that emerging economies still need to catch up with developed countries. Drawing on world system’s theory, we argue that an adapted innovation framework of ‘core – semi-periphery – periphery’ could be an important analytical framework that may help us understand the process of innovation catch up. This may help specifically to better understand how an emerging economy can at least in theory have sectors that could be defined as innovation core and source for technology transfer. We will look at wind energy as North American, European, Indian and Chinese firms dominate the market. This study used citation network analysis and patent analysis to analyse knowledge flows between wind firms and to identify and compare the position and role of each firm in the knowledge network. We argue that there is still, despite catching up, a difference between innovation core countries (US, Germany, Denmark) and innovation semi-periphery (China, India) which will limit the opportunities of knowledge transfer within the sector of wind energy.

https://doi.org/10.1016/j.enpol.2018.04.048

Author(s): Johan Nordensvard, Yuan Zhou, Xiao Zhang
Organization(s): University of Southampton, Tsinghua University
Source: Energy Policy
Year: 2018

Can resources act as capabilities foundations? A bibliometric analysis (Full-paper)

Research Examples, Research profiling

The objective of this article is to record the trends of study regarding the relationships between resources and capabilities, through a review of the literature of its definitions and typologies from 1984-2016, followed by a bibliometric analysis during the period 2001-2016. For this analysis, we used records of the Web of Science. The analysis includes indicators annual productivity, by countries and authors, most productive magazines and most cited articles. A low productivity was identified, 2010 the year with the largest number of articles published. United States leads in number of articles related to the topic. The most cited articles were published in 2003 and the most productive authors have 3 publications each. Thus, important academic gaps are evident, which is why future study paths are suggested.

Full paper PDF

Author(s): Mileidy Álvarez-Melgarejo and Martha Torres-Barreto
Organization(s): Universidad de Investigación y Desarrollo;
Source: Revista UIS Ingenierías
Year: 2018

Soft Robotics: Academic Insights and Perspectives Through Bibliometric Analysis

Research Examples, Research profiling, Research Type

Soft robotics is of growing interest in the robot community as well as in public media, and there is an increase in the quality and quantity of publications related to this topic. To formally elaborate this growth, we have used a bibliometric analysis to evaluate the publications in the field from 1990 to 2017 based on the Science Citation Index Expanded database. We present a detailed overview and discussion based on keywords, citation, h-index, year, journal, institution, country, author, and review articles. The results show that the United States takes the leading position in this research field, followed by China and Italy. Harvard University has the most publications, high average number of citations per publication and the highest h-index. IEEE Transactions on Robotics ranks first among the top 20 academic journals publishing articles related to this field, whereas Soft Robotics holds the top position in journals categorized with “ROBOTICS.” Actuator, fabrication, control, material, sensing, simulation, bionics, stiffness, modeling, power, motion, and application are the hot topics of soft robotics. Smart materials, bionics, morphological computation, and embodiment control are expected to contribute to this field in the future. Application and commercialization appear to be the initial driving force and final goal for soft robots.

http://doi.org/10.1089/soro.2017.0135

Author(s): Guanjun Bao, Hui Fang, Lingfeng Chen, Yuehua Wan, Fang Xu, Qinghua Yang, and Libin Zhang
Organization(s): Zhejiang University of Technology
Source: Soft Robotics
Year: 2018

Emergence scoring to identify frontier R&D topics and key players

Research Examples, ST&I indicators

Indicators of technological emergence promise valuable intelligence to those determining R&D priorities. We present an implemented algorithm to calculate emergence scores for topical terms from abstract record sets. We offer a family of emergence indicators deriving from those scores. Primary emergence indicators identify “hot topic” terms. We then use those to generate secondary indicators that reflect organizations, countries, or authors especially active at frontiers in a target R&D domain. We also flag abstract records (papers or patents) rich in emergent technology content, and we score research fields on relative degree of emergence. This paper presents illustrative results for example topics – Nano-Enabled Drug Delivery, Non-Linear Programming, Dye Sensitized Solar Cells, and Big Data.

https://doi.org/10.1016/j.techfore.2018.04.016

Author(s): Alan L. Porter, Jon Garner, Stephen F. Carley, Nils C. Newman
Organization: Georgia Institute of Technology
Source: Technological Forecasting and Social Change
Year: 2018

Análisis cienciométrico de la producción científica acerca de la investigación sobre la evaluación de la implementación del e-learning en el periodo 2000-2015 (Scientometric analysis e-learning research in the period 2000-2015)

Research Examples, Research profiling, Research Type

A profile is conducted on e-learning using bibliographic data from Scopus and Web of Science (WoS) from the year 2000 to 2015. A five-step scientometric analysis methodology is used: i) Recovery, ii) Migration, iii) Analysis, iv) Visualization v) Interpretation. A set of 1147 records was analyzed, finding that the countries with the greatest contribution were: United States, Spain, United Kingdom, Australia and Germany. The analysis of the profile reflects a range of topics related to e-learning and different areas of knowledge, as well as a scarce presence of research and authors of Latin American origin. This work will allow researchers to identify trends of the last fifteen years.

http://revistas.pucp.edu.pe/index.php/educacion/article/view/19283

Author(s): Diana Marcela Cardona-Román, Jenny Marcela Sánchez-Torres
Organization(s): Universidad Nacional de Colombia
Source: Educación del Departamento de Educación de la Pontificia Universidad Católica del Perú (PUCP)
Year:  2017