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This study aims to contribute to the understanding of the innovation environment of a developing nation through the Triple Helix model, revealing the existing inter-relationships between the three Helixes of Academia–Industry–Government. It sets out to find out the relationship and impact of the three Helixes on the most crucial stage of the innovation process: the commercialisation of patents, and to ascertain if there is a varying impact determined by patent ownership.

This cross-sectional study uses the survey method based on the views expressed by 220 Sri Lankan registered patent holders and categorised by organisational and individual ownership. The sample is drawn from the database of the National Intellectual Property Office of Sri Lanka and patents registered through the Patent Cooperation Treaty, extracted from the World Intellectual Property Organisation Patent Scope database. The survey was carried out in 2019 and limited to patents registered during the period 2010–2014.

The empirical findings indicate weak inter-relationship between Academia support, Industry support and patent commercial success, while the support of the Government Helix is non-significant in the commercial stage. The findings also indicate two different support standards existing in each Helix for the two ownership groups.

The study is limited to a five-year window in a relatively early period in the country’s innovation policy development. The study model is also limited by the non-inclusion of mediators such as government-backed affiliated agencies and academia technical transfer offices which if incorporated would improve the study model and be more reflective of the actual environment and their role as change agents bridging the transition to a hybrid Triple Helix.

The study findings capture the inter-relationships of the Triple Helix existing in a developing country at the most crucial stage of the innovation process. It helps policymakers identify the gaps in each Helix that stands wanting and take measures to rectify them by creating a more favourable National Innovation System. An innovative environment that will facilitate patent holders achieve higher technological transfers and commercial success rates.

The findings disclosure of two different support standards existing in each Helix for the two patent ownership groups poses a challenge for policymakers and challenges the core objective of increasing the commercial success of patents granted. The findings strengthen the need for a more robust support system to be put in place that would empower and facilitate the individual patent owner to increase the share of economic value arising from this underutilised patent group.

This study contributes by furthering the Triple Helix model in a social context and micro-setting by operationalising the theoretical practices. The study also gives insight into each Helix’s interaction and contribution during the most crucial stage of innovation management in a developing economy and its impact on the two categories of patent ownership which is scarce.

This paper aims to discuss a new source of data detailing state level occupational licensing requirements for 50 professions.

This study's research team gathered state level licensing requirements for 50 profession in all 50 states and DC from 2022 to 2023. The authors include the type of regulation, entry requirements like fees, education, training, good moral character provisions and renewal requirements. The authors include Standard Occupational Classification industry codes to allow researchers to merge it with other publicly available data sources. Finally, the authors present descriptive statistics and provide a comparison of licensing requirements for audiologists, an occupation with variation in entry requirements.

The mean number of the 50 professions licensed in states is 36. On average, these professions require a bachelor's degree, $271 in licensing fees and 26 h of continuing education to renew. For the audiologist profession, there is considerable variation between states in entry requirements like fees and education.

Despite a large body of work on occupational licensing, data limitations still exist. Most analysis focuses on whether a profession is licensed or not. However, there is considerable variation between states for the same profession, providing an avenue for work estimating the effects of specific licensing requirements. A new source of data is introduced and discussed for researchers to use in future analyses of occupational licensing.

We investigate the role of fiscal policy, through several measures of government revenues and expenditures and redistribution, on disposable and market income inequality and economic growth as well as the interaction between inequality and growth for 31 European countries from 1995 to 2019.

We use a simultaneous equations model to assess the linkage between economic growth, inequalities and fiscal policy variables.

(1) While disposable income inequality has a negative effect on all fiscal policy variables, market income inequality has a mixed effects; (2) for Eastern European countries, public consumption and direct taxation positively influence economic growth; conversely, for Western European countries, the effects are negative; (3) disposable and market income inequality have a positive effect on growth for Eastern European countries, and a negative influence on growth for Western European countries; (4) growth contributes to the increase of disposable and market income inequality for Eastern European countries; for Western European countries, the effects are opposite; and (5) fiscal policy allows for the attenuation of disposable income inequality.

The different results between the role of market and disposable income inequality levels lead us to suggest tax progressivity as an important feature to consider when analyse the trivariate relationship between inequalities, fiscal policy and growth. Furthermore, there are different dynamics between inequality and growth, and the role of fiscal policy, on both Eastern and Western European countries.

This study aims to explore the evidence-based usage patterns of higher education commission (HEC) subscribed e-journal databases in the university digital library used by the scholarly community and the academics’ online searching behaviour at a higher education institution in Pakistan.

The study used an explanatory sequential mixed methods approach. Raw transaction log data were collected for quantitative analysis, and the interview technique was used for qualitative data collection and thematic analysis.

Log analysis revealed that HEC subscribed databases were used significantly, and among those, scholarly databases covering various subjects were more frequently used than subject-specific society-based databases. Furthermore, the users frequently accessed the needed e-journal articles through search engines like Google and Google Scholar, considering them sources of free material instead of the HEC subscribed databases.

It provides practical implications for examining the evidence-based use patterns of e-journal databases. It suggests the need for improving the access management of HEC databases, keeping in view the usage statistics and the demands of the scholars. The study may also help create market venues for the publishers of scholarly databases by offering attractive and economical packages for researchers of various disciplines in developing and underdeveloped countries. The study results also guide the information professionals to arrange orientation and information literacy programs to improve the searching behaviour of their less frequent users and enhance the utilization of these subscribed databases.

The study is part of a PhD project and, to the best of the authors’ knowledge, is the first such work in the context of a developing country like Pakistan.

This article presents the results of a quantitative analysis of Ukrainian arts and humanities (A&H) research from 2012 to 2021, as observed in Scopus. The overall publication activity and the relative share of A&H publications in relation to Ukraine's total research output, comparing them with other countries. The study analyzes the diversity and total number of sources, as well as the geographic distribution of authors and citing authors, to provide insights into the internationalization level of Ukrainian A&H research. Additionally, the topical spectrum and language usage are considered to complete the overall picture.

This study uses the Scopus database as the primary data source for analyzing the general bibliometric characteristics of Ukrainian A&H research. All document types, except Erratum, were considered. A language filter was applied to compare the bibliometric characteristics of English versus non-English publications. In addition to directly imported data from Scopus, the study employs the ready-to-use SciVal tools to operate with A&H subcategories and calculate additional bibliometric characteristics, such as Citations per Publication (CPP), Field-Weighted Citation Impact (FWCI) and journal quartiles. Information on the country of journal publishers and details on delisted journals from Scopus were obtained from the official Source Title List available on the Elsevier website and the SCImago Journal and Country Rank Portal.

According to the results obtained, the publication patterns for Ukrainian A&H research exhibit dynamics comparable to those of other countries, with a gradual increase in the total number of papers and sources. However, the citedness is lower than expected, and the share of publications in top-quartile sources is lower for 2020–2021 period compared to the previous years. The impact of internationally collaborative papers, especially those in English, is higher. Nevertheless, over half of all works remain uncited, probably due to the limited readership of the journals selected for publication.

This study provides original insights into the bibliometric characteristics of Ukrainian A&H publications between 2012 and 2021, as assessed using the Scopus database. The authors’ findings reveal that Ukraine's A&H publications have higher visibility than some Asian countries with similar population sizes. However, in comparison to other countries of similar size, Ukraine's research output is smaller. The authors also discovered that cultural and historical similarities with neighboring countries play a more significant role in publication activity than population size. This study highlights the low integration of Ukrainian A&H research into the global academic community, evident through a decline in papers published in influential journals and poor citedness. These findings underscore the importance for authors to prioritize disseminating research in influential journals, rather than solely focusing on indexing in particular databases.

The study explores how Taiwan’s electronic health data systems can be used to build algorithms that reduce or eliminate medical errors and to advance precision medicine.

This study is a narrative review of the literature.

The body of medical knowledge has grown far too large for human clinicians to parse. In theory, electronic health records could augment clinical decision-making with electronic clinical decision support systems (CDSSs). However, computer scientists and clinicians have made remarkably little progress in building CDSSs, because health data tend to be siloed across many different systems that are not interoperable and cannot be linked using common identifiers. As a result, medicine in the USA is often practiced inconsistently with poor adherence to the best preventive and clinical practices. Poor information technology infrastructure contributes to medical errors and waste, resulting in suboptimal care and tens of thousands of premature deaths every year. Taiwan’s national health system, in contrast, is underpinned by a coordinated system of electronic data systems but remains underutilized. In this paper, the authors present a theoretical path toward developing artificial intelligence (AI)-driven CDSS systems using Taiwan’s National Health Insurance Research Database. Such a system could in theory not only optimize care and prevent clinical errors but also empower patients to track their progress in achieving their personal health goals.

While research teams have previously built AI systems with limited applications, this study provides a framework for building global AI-based CDSS systems using one of the world’s few unified electronic health data systems.

This study aims to provide insight into Library and Information Science (LIS) research in India using scientometric approaches. Web of Science (WoS) and SCOPUS databases were used for data retrieval. The study examines productivity in terms of source types, gender distribution, document formats, authorship and other factors. In addition, this study sought to identify trends or patterns in the research preferences of LIS scientists through text analysis.

Data were downloaded from the WoS and Scopus databases over 22 years and analysed using VOSviewer, Orange, Biblioshiny and CRExplorer softwares.

The findings reveal that 5,692 out of the 9,384 documents in both databases underwent the final examination. In total, 466 different sources produced all of those papers. Author analysis revealed that 6,603 different authors authored 5,692 documents. There were 4,209 male and 1,063 female authors. Furthermore, India shares maximum collaborations with the USA and England. The spectrogram features nine significant peaks corresponding to Lotka’s, Bradford’s and similar laws. Text analysis revealed that Indian LIS researchers have consistently investigated open access and digital or open libraries.

The findings of this study will provide readers with a better understanding of India’s contribution to LIS. In addition, the study will help academics identify research gaps and undiscovered areas in the Indian context that require further investigation.

Not many studies highlight Indian research trends and international collaboration in LIS. This study highlights research trends, collaboration and gender productivity in LIS. The most cited references and trending topics were also identified using reference publication year spectroscopy and text analysis techniques.

This study aims to explore the dissemination and evolutionary path of online public opinion from a crisis management perspective. By clarifying the influencing factors and dynamic mechanisms of online public opinion dissemination, this study provides insights into attenuating the negative impact of online public opinion and creating a favorable ecological space for online public opinion.

This research employs bibliometric analysis and CiteSpace software to analyze 302 Chinese articles published from 2006 to 2023 in the China National Knowledge Infrastructure (CNKI) database and 276 English articles published from 1994 to 2023 in the Web of Science core set database. Through literature keyword clustering, co-citation analysis and burst terms analysis, this paper summarizes the core scientific research institutions, scholars, hot topics and evolutionary paths of online public opinion crisis management research from both Chinese and international academic communities.

The results show that the study of online public opinion crisis management in China and internationally is centered on the life cycle theory, which integrates knowledge from information, computer and system sciences. Although there are differences in political interaction and stage evolution, the overall evolutionary path is similar, and it develops dynamically in the “benign conflict” between the expansion of the research perspective and the gradual refinement of research granularity.

This study summarizes the research results of online public opinion crisis management from China and the international academic community and identifies current research hotspots and theoretical evolution paths. Future research can focus on deepening the basic theories of public opinion crisis management under the influence of frontier technologies, exploring the subjectivity and emotionality of web users using fine algorithms and promoting the international development of network public opinion crisis management theory through transnational comparison and international cooperation.

An increasing number of images are generated daily, and images are gradually becoming a search target. Content-based image retrieval (CBIR) is helpful for users to express their requirements using an image query. Nevertheless, determining whether the retrieval system can provide convenient operation and relevant retrieval results is challenging. A CBIR system based on deep learning features was proposed in this study to effectively search and navigate images in digital articles.

Convolutional neural networks (CNNs) were used as the feature extractors in the author's experiments. Using pretrained parameters, the training time and retrieval time were reduced. Different CNN features were extracted from the constructed image databases consisting of images taken from the National Palace Museum Journals Archive and were compared in the CBIR system.

DenseNet201 achieved the best performance, with a top-10 mAP of 89% and a query time of 0.14 s.

The CBIR homepage displayed image categories showing the content of the database and provided the default query images. After retrieval, the result showed the metadata of the retrieved images and links back to the original pages.

With the interface and retrieval demonstration, a novel image-based reading mode can be established via the CBIR and links to the original images and contextual descriptions.

In the context of the digital age, this study aims to investigate the impact of citizens' digital participation on the scientific and democratic decision-making processes of the government. Specifically, the authors focus on the factors influencing citizens' digital participation, with a particular emphasis on their digital skills.

Exploring the influence of citizens' digital skills on their digital participation is of great practical significance for eliminating the digital divide and for promoting a life characterized by enriched digital interactions with the public. This study selected the social consciousness survey database of Chinese netizens in 2017, used ordered Probit and OLS models, and comprehensively used the instrumental variable method (IV), causal stepwise regression method and bootstrap method to empirically verify and construct a mechanism model of the influence of digital skills on citizens' digital participation.

The empirical findings indicate a noteworthy positive association between citizens' proficiency in digital skills and their active engagement in digital activities. This relationship is positively mediated by factors such as political interest and attention to social issues, underscoring their role in encouraging greater digital participation. Conversely, national identity exhibits a counteractive influence on this mechanism, potentially discouraging digital engagement. Notably, the impact of digital skill mastery on digital participation is more pronounced among non-elderly individuals and those residing in metropolitan areas, highlighting the significance of demographic characteristics in this context.

These research results can help the government and other organizations make better decisions and facilitate improvement of citizens' digital participation by promoting their mastery of digital skills.