Unraveling the capabilities that enable digital transformation: A data-driven methodology and the case of artificial intelligence

Wu, Mengjia; Çetindamar, Dilek; Min, Chao; Zhang, Yi

doi:10.1016/j.aei.2021.101368

Cited by 44 publications

(9 citation statements)

References 137 publications

(253 reference statements)

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“…The partitioned community results of each iteration constitute a topic layer of the topic tree, with the community center denoting topic labels. The finalized output is a hierarchically partitioned co-term network that represents the intellectual structure of a knowledge system (Wu et al, 2021a ; Zhang et al, 2021b ). The stepwise processes of this method are given below:…”

Section: Methodsmentioning

confidence: 99%

COVID-19 knowledge deconstruction and retrieval: an intelligent bibliometric solution

Zhang

Markley

et al. 2023

Scientometrics

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COVID-19 has been an unprecedented challenge that disruptively reshaped societies and brought a massive amount of novel knowledge to the scientific community. However, as this knowledge flood continues surging, researchers have been disadvantaged by not having access to a platform that can quickly synthesize emerging information and link the new knowledge to the latent knowledge foundation. Aiming to fill this gap, we propose a research framework and develop a dashboard that can assist scientists in identifying, retrieving, and understanding COVID-19 knowledge from the ocean of scholarly articles. Incorporating principal component decomposition (PCD), a knowledge mode-based search approach, and hierarchical topic tree (HTT) analysis, the proposed framework profiles the COVID-19 research landscape, retrieves topic-specific latent knowledge foundation, and visualizes knowledge structures. The regularly updated dashboard presents our research results. Addressing 127,971 COVID-19 research papers from PubMed, the PCD topic analysis identifies 35 research hotspots, along with their inner correlations and fluctuating trends. The HTT result segments the global knowledge landscape of COVID-19 into clinical and public health branches and reveals the deeper exploration of those studies. To supplement this analysis, we additionally built a knowledge model from research papers on the topic of vaccination and fetched 92,286 pre-Covid publications as the latent knowledge foundation for reference. The HTT analysis results on the retrieved papers show multiple relevant biomedical disciplines and four future research topics: monoclonal antibody treatments, vaccinations in diabetic patients, vaccine immunity effectiveness and durability, and vaccination-related allergic sensitization.

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Section: Methodsmentioning

confidence: 99%

COVID-19 knowledge deconstruction and retrieval: an intelligent bibliometric solution

Zhang

Markley

et al. 2023

Scientometrics

Self Cite

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“…Meanwhile, a large number of field-specific bibliometric reviews have been published. Wu et al [50] proposed a new bibliometric framework to explore the evolutionary pattern of digital transformation. Through the analysis of 10179 publications, Wu summarized the necessary capabilities of digital transformation.…”

Section: B Bibliometrics and Mbse Reviewsmentioning

confidence: 99%

Bibliometric Analysis of Model-Based Systems Engineering: Past, Current, and Future

Wang

et al. 2024

IEEE Trans. Eng. Manage.

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Model-based systems engineering (MBSE) is considered an important approach for understanding multidomain fields and is widely used in complex systems such as aerospace. In this article, a detailed survey of MBSE literature was conducted from its commencement to the present trends through bibliometric analysis. Some bibliometric tools were used to implement a visual network analysis of MBSE-related manuscripts. The results of the bibliometric study revealed the interrelationship and distribution of researchers in multidomain fields. The authorized sources of MBSE papers were also assorted. The current practices of MBSE were analyzed. The future directions for MBSE based on the current practices were discussed. We found that MBSE's research has been conducted by many research teams with distinctive characteristics, and the top publishing sources in this field have emerged. Research on MBSE focuses on system engineering, languages, system of systems, and digitalization. The development of new technologies such as next-generation modeling languages is improving current practical problems. The findings of this study may help researchers gain a faster and more comprehensive understanding of the current and future developments in MBSE.

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“…In a world where customers expect fast and fair responses, utilizing technology to enhance services is imperative [15] [16]. Neglecting the capabilities of neural networks and artificial intelligence in a data-driven landscape would be a missed opportunity [17].…”

Section: Problem Statementmentioning

confidence: 99%

Design and Creation of a Neural Network for the Classification of Bank Loan Applicants into Suitable and Non-Suitable Candidates

Márquez,

Quezada,

Robles-Gallegos

et al. 2023

IJSBT

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In the contemporary digital era, financial institutions are actively seeking ways to enhance and streamline their decision-making processes, particularly in critical areas like the approval of bank loans. Traditionally, this procedure has heavily relied on the manual examination of applicant information against predetermined criteria. However, the advent of artificial intelligence and machine learning has ushered in a new era, where neural networks are emerging as a promising tool for intelligent decision-making, aiming to significantly enhance the precision and efficiency of these crucial determinations. The system is developed using supervised artificial neural networks. This system is trained with 8 input variables to make predictions about the feasibility of granting a loan to a user. The goal is to determine whether the application is favorable, or, on the contrary, if it presents risks or disadvantages that could make granting a loan unfavorable. It is worth noting that the system has shown good performance in terms of favorable predictions.

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Unraveling the capabilities that enable digital transformation: A data-driven methodology and the case of artificial intelligence

Cited by 44 publications

References 137 publications

COVID-19 knowledge deconstruction and retrieval: an intelligent bibliometric solution

COVID-19 knowledge deconstruction and retrieval: an intelligent bibliometric solution

Bibliometric Analysis of Model-Based Systems Engineering: Past, Current, and Future

Design and Creation of a Neural Network for the Classification of Bank Loan Applicants into Suitable and Non-Suitable Candidates

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