Publications

10 pages, 188 KiB

Open AccessArticle

A Study on the Current Status and Driving Force of Library Marketing in the Digital Age

by Jianping Wang, Senqiang Wang and Yanan Liu

Publications 2025, 13(2), 21; https://doi.org/10.3390/publications13020021 - 27 Apr 2025

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In the context of the rapid evolution of digital technology and the growing demand for user-centered services, the question of how to effectively implement marketing strategies in libraries has become important in research. This article introduces the theoretical background and development process of [...] Read more.

In the context of the rapid evolution of digital technology and the growing demand for user-centered services, the question of how to effectively implement marketing strategies in libraries has become important in research. This article introduces the theoretical background and development process of domestic and international research on library marketing in the digital era, systematically combs through the current situation of domestic library marketing research, and puts forward the existing deficiencies and problems. Based on the discovery of library marketing strategy research insufficiency and other problems, this paper uses STP theory (segmentation, targeting, and positioning) to conduct a systematic strategy analysis of library operation and management and puts forward countermeasure suggestions for the cross-integration of disciplines, the improvement and optimization of the new theory of library marketing, the integration of STP theory and public library strategy, and the innovation of the research direction. Full article

23 pages, 1601 KiB

Open AccessArticle

Unequal Access, Unequal Impact? The Role of Open Access Policies in Publishing and Citation Trends Across Three Countries

by Shlomit Hadad, Daphne R. Raban and Noa Aharony

Publications 2025, 13(2), 20; https://doi.org/10.3390/publications13020020 - 16 Apr 2025

Viewed by 710

Abstract

This bibliometric study investigates Open Access (OA) publication and citation trends in Austria, Israel, and Mexico from 2010 to 2020—three countries with comparable research output but differing OA infrastructures. (1) Background: The study examines how national OA policies, funding mechanisms, and transformative agreements [...] Read more.

This bibliometric study investigates Open Access (OA) publication and citation trends in Austria, Israel, and Mexico from 2010 to 2020—three countries with comparable research output but differing OA infrastructures. (1) Background: The study examines how national OA policies, funding mechanisms, and transformative agreements (TAs) shape publication and citation patterns across disciplines. (2) Methods: Using Scopus data, the analysis focuses on four broad subject areas (health, physical, life, and social sciences), applying both three-way ANOVA and a Weighted OA Citation Impact index that adjusts citation shares based on the proportional representation of each subject area in national research output. An OA Engagement Score was also developed to assess each country’s policy and infrastructure support. (3) Results: OA publications consistently receive more citations than closed-access ones, confirming a robust OA citation advantage. Austria leads in both OA publication volume and weighted impact, reflecting its strong policy frameworks and TA coverage. Israel, while publishing fewer OA articles, achieves high citation visibility in specific disciplines. Mexico demonstrates strengths in repositories and Diamond OA journals but lags in transformative agreements. (4) Conclusions: National differences in OA policy maturity, infrastructure, and publishing models shape both visibility and citation impact. Structural limitations and indexing disparities may further affect how research from different regions and disciplines is represented globally, emphasizing the need for inclusive and context-sensitive frameworks for evaluating OA engagement. Full article

(This article belongs to the Special Issue Bias in Indexing: Effects on Visibility and Equity)

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19 pages, 2890 KiB

Open AccessArticle

Publication Trends on the Varying Coefficients Model: Estimating the Actual (Under)Utilization of a Highly Acclaimed Method for Studying Statistical Interactions

by Assaf Botzer

Publications 2025, 13(2), 19; https://doi.org/10.3390/publications13020019 - 7 Apr 2025

Viewed by 347

Abstract

Numerous papers have demonstrated that by using a varying coefficients model (VCM), researchers can unveil patterns of interactions between variables that could otherwise remain hidden if using the more popular regression model with an interaction term. Hence, one would expect high acceptance of [...] Read more.

Numerous papers have demonstrated that by using a varying coefficients model (VCM), researchers can unveil patterns of interactions between variables that could otherwise remain hidden if using the more popular regression model with an interaction term. Hence, one would expect high acceptance of the VCM as a tool for studying statistical interactions in datasets. Yet, the current paper shows that the VCM is still struggling to migrate from journals in which methods are presented to journals in which methods are utilized. First, a search in Google Scholar with the phrase “varying coefficients” returned ~79,200 results in comparison to returning ~2,710,000 results with the phrase “interaction term”. Second, a bibliometric analysis of publications with the VCM showed that in many research domains, there were more publications with the VCM in journals on methods than publications with the VCM in journals for empirical investigations. Economics and environmental studies stood out with many more publications with the VCM in empirical journals than in journals on statistical methods. The gap between the high acclaims of the VCM in the statistical literature and its low utilization rate in practice should be of concern to the research community. The possible reasons for this gap and its potential remedies are discussed. Full article

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28 pages, 365 KiB

Open AccessArticle

Tailoring Scientific Knowledge: How Generative AI Personalizes Academic Reading Experiences

by Anna Małgorzata Kamińska

Publications 2025, 13(2), 18; https://doi.org/10.3390/publications13020018 - 2 Apr 2025

Viewed by 434

Abstract

The scientific literature is expanding at an unprecedented pace, making it increasingly difficult for researchers, students, and professionals to extract relevant insights efficiently. Traditional academic publishing offers static, one-size-fits-all content that does not cater to the diverse backgrounds, expertise levels, and interests of [...] Read more.

The scientific literature is expanding at an unprecedented pace, making it increasingly difficult for researchers, students, and professionals to extract relevant insights efficiently. Traditional academic publishing offers static, one-size-fits-all content that does not cater to the diverse backgrounds, expertise levels, and interests of readers. This paper explores how generative AI can dynamically personalize scholarly content by tailoring summaries and key takeaways to individual user profiles. Nine scientific articles from a single journal issue were used to create the dataset, and prompt engineering was applied to generate tailored insights for exemplary personas: a digital humanities and open science researcher, and a mining and raw materials industry specialist. The effectiveness of AI-generated content modifications in enhancing readability, comprehension, and relevance was evaluated. The results indicate that generative AI can successfully emphasize different aspects of an article, making it more accessible and engaging to specific audiences. However, challenges such as content oversimplification, potential biases, and ethical considerations remain. The implications of AI-powered personalization in scholarly communication are discussed, and future research directions are proposed to refine and optimize AI-driven adaptive reading experiences. Full article

(This article belongs to the Special Issue AI in Open Access)

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21 pages, 1577 KiB

Open AccessArticle

Does Publisher Volume Matter? A Cross-Sectional Analysis of Scopus Journal Publishing Patterns

by Eungi Kim

Publications 2025, 13(2), 17; https://doi.org/10.3390/publications13020017 - 1 Apr 2025

Viewed by 1240

Abstract

The objective of this study is to examine the relationship between publisher volume—the number of journals a publisher produces—and journal publishing patterns in Scopus, including various journal metrics such as the h-index, SCImago Journal Rank (SJR), and journal quartiles. The SCImago database, which [...] Read more.

The objective of this study is to examine the relationship between publisher volume—the number of journals a publisher produces—and journal publishing patterns in Scopus, including various journal metrics such as the h-index, SCImago Journal Rank (SJR), and journal quartiles. The SCImago database, which is derived from Scopus data, serves as a proxy for journal impact and influence. The analysis also considered factors such as Open Access (OA) status, geographical location, and subject areas. Using the 2023 SJR dataset, publishers were classified into four categories: V1 (single journal), V2 (2–9 journals), V3 (10–99 journals), and V4 (100+ journals). The findings showed that V4 publishers accounted for 44.5% of Scopus-indexed journals despite comprising only 0.3% of all publishers, whereas V1 publishers represented 78.6% of all publishers but contributed only 21.3% of journals. High-volume publishers had more journals ranked in Q1 and Q2, while lower-volume publishers were more concentrated in Q3 and Q4. Results from the linear mixed-effects model indicated that publisher volume was associated with journal metrics, with higher-volume publishers generally achieving higher h-index and SJR scores. Western Europe and North America had the highest number of V4 publishers, whereas China, Spain, and Italy exhibited strong journal production but had fewer publishers in the highest-volume category. These results illustrate the dominance of a small group of high-volume (V4) publishers and the challenges smaller publishers face in gaining visibility and impact. They also underscore the need to consider policies that foster a more balanced and equitable scholarly publishing environment, particularly for underrepresented regions and subject areas. Full article

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12 pages, 247 KiB

Open AccessArticle

From Fees to Free: Comparing APC-Based and Diamond Open Access Journals in Engineering

by Luís Eduardo Pilatti, Luiz Alberto Pilatti, Gustavo Dambiski Gomes de Carvalho and Luis Mauricio Martins de Resende

Publications 2025, 13(2), 16; https://doi.org/10.3390/publications13020016 - 1 Apr 2025

Viewed by 600

Abstract

This study analyzes the impact of different Open Access (OA) publication models in engineering, comparing journals that charge Article Processing Charges (APCs) with those operating under the Diamond OA model. A total of 757 engineering OA journals, comprising 504 APC-based and 253 Diamond [...] Read more.

This study analyzes the impact of different Open Access (OA) publication models in engineering, comparing journals that charge Article Processing Charges (APCs) with those operating under the Diamond OA model. A total of 757 engineering OA journals, comprising 504 APC-based and 253 Diamond OA journals, were examined using bibliometric data from 2020 to 2023. The analysis focused on four key metrics: CiteScore, total citations, number of published articles, and the percentage of cited articles. The results indicate that APC-based journals dominate the upper quartiles (Q1 and Q2) regarding absolute citation counts, primarily driven by high-volume mega-journals such as IEEE Access. However, Diamond OA journals exhibit a higher proportion of cited articles (88.8% compared to 83.4% in APC-based journals) within the top 10% category. Despite their benefits in providing cost-free dissemination, Diamond OA journals account for only 8.4% of the 3012 active engineering journals indexed in Scopus, highlighting sustainability and visibility challenges. The findings suggest that, while APC-based journals achieve higher absolute citation counts, editorial reputation and visibility strategies significantly influence citation performance. This study contributes to the ongoing discussion on the financial sustainability and equity of OA publishing in engineering. Full article

(This article belongs to the Special Issue Diamond Open Access)

25 pages, 7710 KiB

Open AccessArticle

Top2Vec Topic Modeling to Analyze the Dynamics of Publication Activity Related to Environmental Monitoring Using Unmanned Aerial Vehicles

by Vladimir Albrekht, Ravil I. Mukhamediev, Yelena Popova, Elena Muhamedijeva and Asset Botaibekov

Publications 2025, 13(2), 15; https://doi.org/10.3390/publications13020015 - 25 Mar 2025

Viewed by 407

Abstract

Unmanned aerial vehicles (UAVs) play a key role in the process of contemporary environmental monitoring, enabling more frequent and detailed observations of various environmental parameters. With the rapid growth of scientific publications on this topic, it is important to identify the key trends [...] Read more.

Unmanned aerial vehicles (UAVs) play a key role in the process of contemporary environmental monitoring, enabling more frequent and detailed observations of various environmental parameters. With the rapid growth of scientific publications on this topic, it is important to identify the key trends and directions. This study uses the Top2Vec algorithm for topic modeling algorithm aimed at analyzing abstracts of more than 556 thousand scientific articles published on the arXiv platform from 2010 to 2023. The analysis was conducted in five key domains: air, water, and surface pollution monitoring; causes of pollution; and challenges in the use of UAVs. The research method included data collection and pre-processing, topic modeling, and quantitative analysis of publication activity using indicators of the rate (D1) and acceleration (D2) of change in the number of publications. The study allows concluding that the main challenge for the researchers is the task of processing data obtained in the course of monitoring. The second most important factor is the reduction in restrictions on the UAV flight duration. Among the causes of pollution, agricultural activities will be considered as a priority. Research in monitoring greenhouse gas emissions will be the most topical in air quality monitoring, while erosion and sedimentation—in the area of land surface control. Thermal pollution, microplastics, and chemical pollution are most relevant in the field of water quality control. On the other hand, the interest of the scientific community in topics related to soil pollution, particulate matter, sensor calibration, and volatile organic compounds is decreasing. Full article

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25 pages, 747 KiB

Open AccessArticle

Generative AI vs. Traditional Databases: Insights from Industrial Engineering Applications

by Jose E. Naranjo, Maria M. Llumiquinga, Washington D. Vaca and Cristian X. Espin

Publications 2025, 13(2), 14; https://doi.org/10.3390/publications13020014 - 25 Mar 2025

Viewed by 472

Abstract

This study evaluates the efficiency and accuracy of Generative AI (GAI) tools, specifically ChatGPT and Gemini, in comparison with traditional academic databases for industrial engineering research. It was conducted in two phases. First, a survey was administered to 101 students to assess their [...] Read more.

This study evaluates the efficiency and accuracy of Generative AI (GAI) tools, specifically ChatGPT and Gemini, in comparison with traditional academic databases for industrial engineering research. It was conducted in two phases. First, a survey was administered to 101 students to assess their familiarity with GAIs and the most commonly used tools in their academic field. Second, an assessment of the quality of the information provided by GAIs was carried out, in which 11 industrial engineering professors participated as evaluators. The study focuses on the query process, response times, and information accuracy, using a structured methodology that includes predefined prompts, expert validation, and statistical analysis. A comparative assessment was conducted through standardized search workflows developed using the Bizagi tool, ensuring consistency in the evaluation of both approaches. Results demonstrate that GAIs significantly reduce query response times compared to conventional databases, although the accuracy and completeness of responses require careful validation. A Chi-Square analysis was performed to statistically assess accuracy differences, revealing no significant disparities between the two AI tools. While GAIs offer efficiency advantages, conventional databases remain essential for in-depth literature searches requiring high levels of precision. These findings highlight the potential and limitations of GAIs in academic research, providing insights into their optimal application in industrial engineering education. Full article

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