Iskanje po katalogu digitalne knjižnice

Opis: The article analyses a multidimensional digital transformation process. Digital transformation is a change or shift in operational and strategic frameworks necessitated by the rapid advancement of digital technology. Digital transformation is more than the implementation of advanced technology, it requires a cultural shift towards constant experimentation and openness to failure. Such changes make the organization agile, efficient, and customer-orientated, with the ability to quickly integrate new, comprehensive data into the entire decision-making and innovation process. The purpose of the research was therefore to analyse the key success factors in digital transformation. The analysis serves as a basis for further theoretical research in this field and for practical implementation in organisational systems. As part of this research, a bibliometric analysis was carried out using the open-source tool VOSviewer. The analysis shows that digital transformation is particularly relevant in the fields of Computer Science; Business, Management and Accounting; and Engineering, namely in Germany, China and the Russian Federation. We have come to the conclusion that the key success factors in digital transformation are as follows: corporate organization and technology, collaboration and cultural change, holistic strategy, leadership and organizational structure, continuous learning and conformity to best practises.
Ključne besede: digital transformation, advanced technologies, key success factors, bibliometric analysis, VOSviewer
Objavljeno v DKUM: 28.08.2025; Ogledov: 0; Prenosov: 9
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Opis: Correspondence analysis (CA) is a multivariate statistical and visualization technique. CA is extremely useful in analyzing either two- or multi-way contingency tables, representing some degree of correspondence between columns and rows. The CA results are visualized in easy-to-interpret “bi–plots,” where the proximity of items (values of categorical variables) represents the degree of association between presented items. In other words, items positioned near each other are more associated than those located farther away. Each bi-plot has two dimensions, named during the analysis. The naming of dimensions adds a qualitative aspect to the analysis. Correspondence analysis may support medical professionals in finding answers to many important questions related to health, wellbeing, quality of life, and similar topics in a simpler but more informal way than by using more complex statistical or machine learning approaches. In that way, it can be used for dimension reduction and data simplification, clustering, classification, feature selection, knowledge extraction, visualization of adverse effects, or pattern detection.
Ključne besede: public health, medical research, correspondence analysis, synthetic knowledge synthesis, exploratory data analysis, bibliometric
Objavljeno v DKUM: 30.07.2025; Ogledov: 0; Prenosov: 1
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Opis: Aims: The aim of this study is to use generative artificial intelligence to perform bibliometric analysis on abstracts published at European Resuscitation Council (ERC) annual scientific congress and define trends in ERC guidelines topics over the last decade. Methods: In this bibliometric analysis, the WebHarvy software (SysNucleus, India) was used to download data from the Resuscitation journal’s website through the technique of web scraping. Next, the Chat Generative Pre-trained Transformer 4 (ChatGPT-4) application programming interface (Open AI, USA) was used to implement the multinomial classification of abstract titles following the ERC 2021 guidelines topics. Results: From 2012 to 2022 a total of 2491 abstracts have been published at ERC congresses. Published abstracts ranged from 88 (in 2020) to 368 (in 2015). On average, the most common ERC guidelines topics were Adult basic life support (50.1%), followed by Adult advanced life support (41.5%), while Newborn resuscitation and support of transition of infants at birth (2.1%) was the least common topic. The findings also highlight that the Basic Life Support and Adult Advanced Life Support ERC guidelines topics have the strongest co-occurrence to all ERC guidelines topics, where the Newborn resuscitation and support of transition of infants at birth (2.1%; 52/2491) ERC guidelines topic has the weakest co-occurrence. Conclusion: This study demonstrates the capabilities of generative artificial intelligence in the bibliometric analysis of abstract titles using the example of resuscitation medicine research over the last decade at ERC conferences using large language models.
Ključne besede: generative artificial intelligence, bibliometric analysis, congress, emergency medicine, European Resuscitation Council
Objavljeno v DKUM: 27.11.2024; Ogledov: 0; Prenosov: 2
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Opis: In our study, we are evaluating the dynamic interplay between circular cities and the circular economy, revealing connections shaped by new research insights, using Web of Science database. We have in depth analysed 671 publications from 1990 to mid- 2023, employing Leximancer and VOSviewer tools. Our analysis uncovered key themes, including buildings, waste management, value chains, and sustainable development, linking the circular cities concept and circular economy framework. Emerging research trends, such as urban metabolism, urban mining, governance models, the built environment, sustainability benchmarks, and value chain management, signify deliberate shifts towards higher circular development and implementation. These trajectories harmonise with overarching sustainable development goals. Contemporary research emphasises urban mining, circular indicators, adaptive resource reuse, and urban structure regeneration. This focus facilitates transitioning from linear models to heightened circularity within urban contexts. Research inclination is shifting from traditional economic and environmental concerns towards holistic urban configurations that prioritise social integration, communal well-being, and the dynamics of the social economy. Through this analytical expedition, we offer novel insights that enhance our understanding of the intricate symbiosis between circular cities and the circular economy. Our findings provide a scientific foundation for formulating targeted strategies by decision-makers and guiding urban landscapes towards transformative trajectories aligned with sustainable development objectives and sustainable cities.
Ključne besede: bibliometric analysis, circular city, circular economy, content analysis, Leximancer, sustainability, sustainable development goals
Objavljeno v DKUM: 29.03.2024; Ogledov: 268; Prenosov: 35
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