An integrated approach to path analysis for weighted citation networks

Lathabai, Hiran H.; George, Susan E.; Prabhakaran, Thara; Changat, Manoj

doi:10.1007/s11192-018-2917-1

Cited by 15 publications

(18 citation statements)

References 28 publications

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“…In terms of the traversal weight scheme, SPLC was used, as it aids in simulating the situation of knowledge diffusion in scientific development, not only for conveying knowledge, but also for assigning the source of knowledge itself [46]. For searching in the main path, a global standard search was conducted, which provided the overall most significant main paths in the knowledge dissemination [41,[47][48][49]. The overall flow of data collection and data analysis is shown on Figure 1.…”

Section: Data Collectionmentioning

confidence: 99%

The Role of Information Systems in the Sustainable Development of Enterprises: A Systematic Literature Network Analysis

Zeng

Lee

2020

Sustainability

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Information Systems (IS) play an important role in improving the efficiency of firms’ operations and supply chains, which links to sustainability. Therefore, this study conducted a systematic literature network analysis to review 132 articles that discuss current trends in the IS discipline. Based on a citation network analysis, this study discovered three main research domains (sustainable competitive advantage, environmental sustainability, and sustainable online social communities), and two emerging research domains (the role of IS in developing countries and sustainable information infrastructures). Furthermore, a main path analysis was conducted to understand the knowledge structure of each research domain. This addresses how different trends are reflected in the IS literature related to improving firms’ competitive advantages and environmental sustainability. The results found that the sustainable competitiveness of enterprises is improved by the synergy between IS and other recourses within in the enterprises. Green IS initiatives not only solve the issues of environmental sustainability, but also enhance sustainable competitive advantage (i.e., stock price). As social media becomes the optimal enterprise communication channel, this study discusses the factors affecting sustainable online social community, such as structural dynamics (i.e., membership size, communication activity), social dynamics (the basic nature of interactions among members), participation costs, and topic consistency. Overall, the Information System literature is highly focused on three areas—economy, environment, and society, which supports Triple Bottom Line theory.

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Section: Data Collectionmentioning

confidence: 99%

The Role of Information Systems in the Sustainable Development of Enterprises: A Systematic Literature Network Analysis

Zeng

Lee

2020

Sustainability

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“…𝑊 𝐹𝑉 𝑖 is termed as the flow vergence index by Prabhakaran et al (2015) because positive value of the index can clearly indicate works that are flow divergent and negative value of the index indicate works that are flow convergent as shown in figure 2 (right). More details about theoretical origin and rationale behind the formulation of the FV index is already covered by Prabhakaran et al (2015), Lathabai et al (2015), Lathabai et al (2017), Lathabai et al (2018) and Prabhakaran et al (2018).…”

Section: Fv Gradient Method: a Short Revisitmentioning

confidence: 99%

“…This phenomenon was termed as Flow Vergence effect or FV effect and was used to detect (Lathabai et al, 2015) and predict (Prabhakaran et al, 2018) pivot papers of paradigm shift. Computation of FV gradients of all the arcs makes the network a signed weighted network and therefore FV gradient computation can be treated as a weight assignment method that probably have the ability to highlight paths that might not be highlighted through SPX methods as shown in Lathabai et al (2018).…”

Section: Fv Gradient Method: a Short Revisitmentioning

confidence: 99%

“…Some of the previous studies have utilized these weight assignment and search schemes to get the evolutionary trajectories of knowledge flows in the citation network. For example-like in medical treatment (Mina et al, 2007;Tampuabolon & Ramlogan, 2007), human resource development (Jo et al, 2009), archaeology (Brughmans, 2013), Information technology for engineering (Prabhakaran et al, 2015;Lathabai et al, 2018) etc. All these studies utilized the important paths to understand the evolution of the specific research domain.…”

Section: Related Workmentioning

confidence: 99%

“…using the Bradford Law of scattering (Bradford, 1934;Egghe, 1990a;Oluić-Vuković, 1992), a macroscopic understanding of the field is attempted to be obtained. The study looks further into the technical evolution of knowledge of AI application domains and methodologies using Path analysis (Hummon & Doreian, 1989;Lathabai et al, 2018;Prabhakaran et al, 2018). This provides a microscopic understanding of the developments related to AI that serve as major enhancer or even has the potential to become game changer in many other areas that are closely associated with sustainable development goals.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Patterns in the growth and thematic evolution of Artificial Intelligence research: A study using Bradford distribution of productivity and Path Analysis

Gupta

Kanaujia

Lathabai

et al. 2022

Preprint

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AI Applications has led to changes in social as well as economic structure of the world and caused worldwide policy changes. AI research and applications have not only increased in volume but has also expanded across various disciplines. Newer themes of research have emerged while attention on several topics has gradually faded. Therefore, there is a need to analyse and understand the patterns of growth and thematic evolution of AI research during the last decade. Motivated by the need, Bibliometric methodologies of Bradford’s law and Path analysis are employed to develop a framework for a detailed analysis. Publication and citation data of AI for the period 2010 to 2020 obtained from Web of Science when analysed using this framework, showed an exponential growth between 2016 and 2020. An increased adoption of AI in novel domains is indicated by an increase in both concentration and dispersion of the literature. Through the analysis of evolutionary trajectories contributing to growth of AI, it was observed that applications of AI are becoming common in previously unrelated areas such as water resource management, environment management, building technology, healthcare etc. These are areas which directly relate with sustainable development and the researchers have used multiple single as well as hybrid AI tools to address their problems. The article presents useful insight along these lines which can be useful for practitioners in the field of AI.

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Artificial intelligence for Sustainable Development Goals: Bibliometric patterns and concept evolution trajectories

Singh,

Kanaujia,

Singh

et al. 2023

Sustainable Development

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The development of artificial intelligence (AI) as a field has impacted almost all aspects of human life. More recently it has found a role in addressing developmental challenges, specifically the Sustainable Development Goals (SDGs). However, there are not enough systematic studies on analysis of the role of AI research towards the SDGs. Therefore, this article attempts to bridge this gap by identifying the major bibliometric trends and concept‐evolution trajectories in the area of AI applications for sustainable‐development goals. The research publication data for the last 20 years in the areas of artificial intelligence, machine learning, deep learning, and so forth, is obtained and computationally analysed using a framework comprising bibliometrics, path analysis and content analysis. The findings show an incremental trend in overall publications on the application of AI for SDGs across the different regions of the world. SDGs 3 (good health & well‐being) and 7 (affordable and clean energy) are found as the areas with the most applications of AI. In SDG3, the literature reflects application of AI techniques such as deep learning for precision and personalised medicine while in SDG7, a number of studies have employed AI techniques for the integration of systems for efficient generation of solar power and improving the energy efficiency of a building. Furthermore, SDG 4 (quality education), SDG 13 (climate action), SDG 11 (sustainable cities and communities) and SDG 16 (peace, justice and strong institutions) are the other SDGs where AI approaches and techniques are applied. The analytical results present a detailed insight of application of AI for achieving the SDGs.

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An integrated approach to path analysis for weighted citation networks

Cited by 15 publications

References 28 publications

The Role of Information Systems in the Sustainable Development of Enterprises: A Systematic Literature Network Analysis

The Role of Information Systems in the Sustainable Development of Enterprises: A Systematic Literature Network Analysis

Patterns in the growth and thematic evolution of Artificial Intelligence research: A study using Bradford distribution of productivity and Path Analysis

Artificial intelligence for Sustainable Development Goals: Bibliometric patterns and concept evolution trajectories

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