Public Sources Research Articles

Topics and Trends of Health Informatics Education Research: Scientometric Analysis.

Academic and educational institutions are making significant contributions toward training health informatics professionals. As research in health informatics education (HIE) continues to grow, it is useful to have a clearer understanding of this research field. This study aims to comprehensively explore the research topics and trends of HIE from 2014 to 2023. Specifically, it aims to explore (1) the trends of annual articles, (2) the prolific countries/regions, institutions, and publication sources, (3) the scientific collaborations of countries/regions and institutions, and (4) the major research themes and their developmental tendencies. Using publications in Web of Science Core Collection, a scientometric analysis of 575 articles related to the field of HIE was conducted. The structural topic model was used to identify topics discussed in the literature and to reveal the topic structure and evolutionary trends of HIE research. Research interest in HIE has clearly increased from 2014 to 2023, and is continually expanding. The United States was found to be the most prolific country in this field. Harvard University was found to be the leading institution with the highest publication productivity. Journal of Medical Internet Research, Journal of The American Medical Informatics Association, and Applied Clinical Informatics were the top 3 journals with the highest articles in this field. Countries/regions and institutions having higher levels of international collaboration were more impactful. Research on HIE could be modeled into 7 topics related to the following areas: clinical (130/575, 22.6%), mobile application (123/575, 21.4%), consumer (99/575, 17.2%), teaching (61/575, 10.6%), public health (56/575, 9.7%), discipline (55/575, 9.6%), and nursing (51/575, 8.9%). The results clearly indicate the unique foci for each year, depicting the process of development for health informatics research. This is believed to be the first scientometric analysis exploring the research topics and trends in HIE. This study provides useful insights and implications, and the findings could be used as a guide for HIE contributors.

Exploring the Intersection of Brands and Linguistics: A Comprehensive Bibliometric Study

Branding has emerged as a multidiscipline with complication, conveyed by integrated digital technologies, AI, and rich linguistic approaches. This paper depicts the research landscape at the juncture of branding and linguistics, supported by VOSviewer, Biblioshiny, and CiteSpace in pinpointing key trends, themes, and collaboration networks. Drawing on data collected from Scopus, this study investigates the shifts in traditional branding strategies caused by technologies of machine learning, sentiment analysis, and social media platforms. It highlights the contributions made by leading authors, major publication sources, and patterns of international collaboration in influential works. Finally, thematic and co-occurrence analysis shows significant movement into data-based and computational approaches. This also points out some research gaps in the field of digital branding’s long- term effects, ethical considerations of AI-photo strategies, and multilingual branding approaches that provide a useful basis for future research and practical application innovation in the field of branding.

Financial Sustainability Through Literacy and Retirement Preparedness

This study discusses financial sustainability in retirement via a comprehensive bibliometric and content analysis on financial literacy and retirement preparedness for 1970–October 2024. Data for this study are extracted from the Scopus database. In line with the PRISMA guideline, the inclusion and exclusion criteria were applied, and the final corpus of articles used in the analysis is 518 articles. These articles are analyzed using the bibliometric methods: Bibliometrix R-package (Biblioshiny) version 4.0 and VOSviewer 1.6.20. The descriptive analysis identified the publication trends, prominent authors, articles, sources, country collaboration, and quadrant analysis. Based on the bibliographic coupling, the following themes were identified: (1) financial literacy and retirement planning, (2) behavioral finance and psychological determinants of retirement planning and preparedness, (3) financial risk, decision making, and retirement preparedness, and (4) gender, socioeconomic factors, and financial literacy disparities. This study has consolidated and enriched the understanding of how financial literacy, education, psychology and behaviors, and financial risk play a pivotal and central role in shaping long-term financial sustainability, as well as retirement planning and preparedness. From a practical perspective, an all-inclusive understanding of the above is essential for guiding regulators and policymakers in designing policies, targeted interventions, and programs that empower individuals towards retirement preparedness, considering regional, socioeconomic, and gender-related factors.

EXAMINING CARBON QUANTUM DOTS RESEARCH IN TURKEY: A SCIENTIFIC MAPPING ANALYSIS

The bibliometric analysis presented in this work is thorough and comprehensive, carefully examining the wide range of contributions related to "carbon dots" and "carbon quantum dots" in Turkish research from 2014 to 2023. Using Biblioshiny as the major analytical tool and the Web of Science database, this study methodically breaks down the annual trends, regional spreads, institutional ties, authorship trends, and the complex clusters of keywords in this field. After a comprehensive analysis of international and local citations, the research identifies a noteworthy yearly growth rate of 14.72% for Turkey's carbon dot project. Starting with one manuscript in 2014, the research output increased rapidly, reaching sixty critical documents by the end of May 2024. This thorough study clarifies important publication sources; in particular, it emphasizes ChemistrySelect and the publication of Fluorescence as two of the field's top contributors. This thorough evaluation significantly contributes to our knowledge of the state of carbon studies in Turkey, providing priceless insights and a guide to advise and set the direction for future research projects in this continuously developing field, especially for researchers and academics connected with "carbon dots".

Assessing the Impact of Tourism on Country Brand Value

This research explores the connection between tourism statistics and country brand value, as well as the impact tourism has on it, by utilizing public data sources and employing statistical techniques. A country's brand reflects its image as perceived by foreign audiences, representing the nation's reputation and standing internationally. This perception is mirrored in the influx of tourists visiting the country. While brand value is typically not measured by the number of arrivals, but rather by the country's tourism image, prior studies have shown that higher brand value leads to an increase in foreign visitors. However, fewer investigations have focused on whether the volume of tourists directly influences the country's brand value. The findings of this study demonstrate a significant link between the two, revealing a causal relationship. Nevertheless, there is some uncertainty surrounding the causality, which future research aims to clarify. The goal of this preliminary study was to explore whether this question could be effectively addressed.

European Firms’ Delisting Around Major Regulatory Shocks: The Cost-Benefit Tradeoff of the Financial Services Action Plan

ABSTRACT Between 1999 and 2005, the EU adopted the Financial Services Action Plan (FSAP) to reshape its financial markets. In this paper, we examine the firm-level effect of this major regulatory shock. In pre/post-2005 analyses, we compare the probabilities of companies voluntarily or involuntarily delisting in seven European economies that strongly commit to implementing regulations and seven economies that apply regulations more leniently. Our findings indicate an increased probability of delisting after 2005, primarily due to involuntary delistings in economies that implement regulations strictly. Furthermore, we examine a core element of the FSAP, the International Financial Reporting Standards (IFRS) mandate, which aimed to improve public firms’ reporting and disclosure quality. IFRS continued to undergo rapid changes after 2005, and we document an incremental association between delisting and the post-2005 changes. Our results highlight the firm-level consequences of the FSAP across jurisdictions with varying institutional environments. Data Availability: Data are available from the public sources cited in the text. JEL Classifications: G15; G18; G38; K22; M48.

Utilizing Deep Learning for Field-Level Information Extraction from German Real Estate Tax Notices

ABSTRACT Document processing and related tasks such as information extraction represent a large portion of business workloads and therefore offer high potential for efficiency improvements and process automation. Although semistructured documents such as invoices and receipts have been extensively studied, tax notices represent a largely unexplored area due to their information richness and layout complexity. This article presents a study investigating the potential of deep learning-based information extraction for German real estate tax notices. We propose a hybrid approach based on the LayoutLM transformer model that uses textual, positional, and visual information as well as a rule-based information extraction. We show how such a system can be developed and integrated into the business workflow of organizations on the example of a German tax consulting firm. We also discuss the implications and key challenges that organizations face when planning to adopt such technologies. Data Availability: Custom data and code are not publicly available. Relevant public source code is cited in the text. JEL Classifications: M15; M40; M41.

Private Equity Fund Reporting Quality, External Monitors, and Third-Party Service Providers

ABSTRACT We describe variation in the reporting quality (i.e., accuracy and bias of reported net asset values (NAVs)) of private equity (PE) funds across types of external monitors (investors and auditors) and third-party service providers (valuation specialists, marketers, and administrators). In contrast to public markets, we find only limited evidence that reporting quality varies with the composition and types of investors in PE funds. We observe, however, that reporting quality varies with auditor involvement and the use of third-party service providers; these associations often differ across buyout (BO) and venture capital (VC) funds and from those observed in public markets. Our evidence is important to investors and regulators, especially now that PE supersedes public markets as the main vehicle to raise capital and as regulators increase their focus on private markets. Data Availability: Data used in this study are available from public sources listed in the paper. JEL Classifications: G1; G14; G30; M4; M41.

Identifying the Relationship between Earnings and Prices

ABSTRACT The relationships between accounting earnings and stock prices, as well as between unexpected earnings and returns, have received substantial attention in the empirical literature. Several theoretical models predict the shapes of these relationships. However, a comprehensive empirical description that could be used to evaluate these predictions is lacking. By integrating recent advances in statistics and machine learning with findings in the accounting literature, we develop an empirical method to identify the relationships, which is consistent with the firm-specific and nonlinear features of the theoretical models. Our approach provides a clear description of stylized and robust patterns in the relationships that are relevant to distinguish between existing models and to aid future theory development. The findings are consistent with recently proposed dynamic option models for both the earnings-price and unexpected earnings-returns relationships. Data availability: Data are available from the public sources cited in the text. A summary of the R code used in the article is available in Starica and Marton (2024). JEL Classifications: G10; G30; M41.

ANALISIS STRATEGI PEMULIHAN EKONOMI INDONESIA PASCA PANDEMI BERBASIS TRANSFORMASI DIGITAL

This research aims to identify strategies and implementation results carried out by the Indonesian government to restore economic conditions during and especially after the pandemic. This type of research is included in quantitative-qualitative research with the qualitative variables in this research being the level of achievement of economic growth and economic recovery strategies, respectively. Primary data is data from interviews and secondary data is existing publication sources. The results show that the strategy implemented by the government, namely protecting, implementing PEN, capital participation, placing funds, and guarantee schemes has succeeded in restoring the condition of the Indonesian economy, especially entering the digitalization of the post-pandemic economy.

Does Disclosure Regulation Affect Mutual Fund Families’ Proxy Voting?

ABSTRACT Nonactivist investors that own more than 5 percent of a firm must report their holdings by filing a 13G in which they must commit to not influencing control of the firm. Mutual fund families are the most common investors filing 13Gs. I study whether the 13G requirement affects mutual fund families’ voting in proxy contests. I find mutual fund families that file the form are less likely to vote for activist proposals than are those that do not, suggesting that the requirement discourages mutual fund families from supporting activists who seek to influence control of the firm. The effects strengthen when vote outcomes directly affect the firm’s control and when activists pose a higher threat to the firm. I further document that the aggregate voting power of 13G-filing mutual fund families correlates with management winning contested votes and retaining board seats during proxy contests. Data Availability: Data are available from the public sources cited in the text. JEL Classifications: G34; G23; G38; K22; L51; M12.

Technical insights of clean and sustainable photocatalytic concrete: A scientometric analysis-aided review.

Air quality has deteriorated rapidly in recent decades due to exponential economic growth, necessitating effective solutions to mitigate pollution. One promising approach is the use of photocatalytic concrete containing TiO2, which, when activated by sunlight, can degrade various contaminants. This study provides a comprehensive scientometric-based review of research on photocatalytic concrete, focusing on literature published between 1997 and 2024. The review employs a scientometric analysis to identify the key trends, frequent keywords, publication sources, and leading nations. Furthermore, comprehensive review was conducted to evaluate various properties of photocatalytic concrete, highlighting research gaps, field project assessments, challenges and life-cycle cost evaluations. The findings reveal that while photocatalytic concrete demonstrates significant pollutant degradation under laboratory conditions, there is a notable scarcity of data on its real-world applications. The review underscores the need for more extensive field studies to verify its effectiveness and to expand research on its properties and applications. Overall, this review offers valuable insights into the current state of photocatalytic concrete technology, its limitations, and the opportunities for its advancement in sustainable construction practices.

Ideal Madrasah Diniyah Takmiliyah Leadership Strategy

To examine the optimal leadership approach of Madrasah Diniyah Takmiliyah, this study uses a qualitative methodology through literature review. Literature reviews from various sources of books, scientific publications, and scientific journals, as well as the results of interviews with specialists relevant to leadership at Madrasah Diniyah Takmiliyah, are the source of data for this research. The findings are as follows: 1) A number of elements, such as leadership style, members' desires and desires, internal and external influences, and self-development, affect how effective leadership is in Madrasah Diniyah Takmiliyah. 2) According to research, madrasah leaders with an adaptive leadership style can adapt to the environment and the demands of their students. These methods include the development of efficient communication, the improvement of joint competence, the implementation of joint activities, the provision of feedback, and the creation of a supportive environment.

Econophysics, State of the Science and Bibliographic Production: a Bibliometric Analysis

Objective: This article aims to investigate the state of the art regarding the scientific production of Econophysics as a field of study. The aim is to map the annual production of articles, types of documents, most relevant authors, most productive countries, institutions, journals, scientific collaboration networks, and associated themes and trends. Theoretical Framework: Econophysics applies physics procedures to analyze financial markets and solve economic problems, using tools such as fractal theory and Brownian motion. The term Econophysics was created by H. Eugene Stanley in 1995. Bibliometric mapping, conducted with software such as Bibliometrix and R-Project, is essential for understanding trends in the academic literature on Econophysics. Method: Bibliometric analysis was used to map the existing scientific literature on the field of Econophysics. This science is described as a method that employs the resources of mathematics, statistics, and computing to bring the scientific memory of a specific area of knowledge. The Scopus database was used to collect data on the main publications during the period from 1996 to 2024. The Bibliometrix and R-Project software produced keyword co-occurrence maps, citation analysis, and collaboration networks between authors and institutions. The main metrics analyzed include the number of publications per year, the main thematic areas, the sources of publications, the most cited authors, and the geographical distribution of scientific contributions. Results and Discussion: A total of 1,805 publications between 1996 and 2024 (June), of which 1,450 are scientific articles related to Econophysics. The data suggest a consistent increase in article publications until 2006, after which there was stability between 80 to 100 articles published annually. The percentage of international collaboration is 20.83%, highlighting the collaborative aspect among various countries. The average number of citations of the articles is 22.41%. When analyzing the co-occurrence of keywords, the three main thematic groups were identified—finance, physics, and economics—and the most frequently used terms were trade and financial markets. 793 articles were published by the journal Physica A, which leads the publication ranking. Zhou, Stanley, and Mantegna are the most productive and highly referenced writers. And the nations that contribute the most to the development of Econophysics are China, the United States of America, and Japan. Research Implications: It is a broader view of the evolution of Econophysics, the main trends, and the areas of research that have emerged in recent decades. It helps understand how physics algorithms can be used to solve economic problems, promoting a more equitable economy. Originality/Value: This study pioneers the conducting of a comprehensive bibliometric analysis of the literature on econophysics, a relatively new field that combines physical science and economics. The originality lies in the application of various analysis methods through the Bibliometrix and R-Project software to map and analyze the scientific production in this area, providing a better understanding of the evolution and current state of the research. This work contributes to the literature by providing a detailed overview of research trends, main contributions, and gaps in knowledge.

Toward Integration of Blockchain, Cryptocurrencies into Forensic Accounting Education

ABSTRACT Blockchain and cryptocurrency knowledge and skills are important for forensic accountants. We examine the integration of blockchain and cryptocurrency topics into forensic accounting education by (1) reviewing the literature to identify a list of blockchain and cryptocurrency topics that could be incorporated into forensic accounting education, (2) investigating the forensic accounting curriculum of universities worldwide in their coverage of blockchain and cryptocurrencies topics, and (3) presenting important topics in blockchain and cryptocurrencies that could be taught in related courses with a keen focus on the module approach. Among 20 universities with forensic accounting programs in China, only four provide stand-alone blockchain and cryptocurrency courses compared with 25 out of 58 forensic accounting programs in the United States that offer stand-alone blockchain and cryptocurrency courses. Our results highlight the importance of integrating blockchain and cryptocurrency content into forensic accounting education to provide the skills to deter, detect, and prevent fraud. Data Availability: Data are available from the public sources. JEL Classifications: M41; M42.

An Examination of Management Tone in the MD&A in the Context of Fraud Pentagon

ABSTRACT We examine the association between management tone in management discussion and analysis (MD&A) and five elements of the fraud pentagon model of incentives, opportunity, rationalization, capability, and arrogance. Management tone is measured using a biased tone, and several proxies for fraud are constructed. Using a sample of 586 public companies listed on the Teheran Stock Exchange from 2013 to 2022, we find (1) auditor’s opinion, current ratio, capital expenditure, earnings management, and tax evasion as proxies for fraud incentives; (2) internal control weakness as a proxy for fraud opportunity; (3) CEO tenure and ability as proxies for fraud capability; (4) competition in the product market, industry tax evasion, and lack of political communication as proxies for fraud rationalization; and (5) narcissism and overconfidence as proxies for fraud arrogance are associated with management abnormal tone. We contribute to literature by examining relationships between fraud elements and the abnormal tone in MD&A. Data Availability: Data used in this paper are available from the public sources identified in the text and upon request from authors. JEL Classifications: M41; M42; M48.

Mapping Authentic Marketing Research Trends through Bibliometric Analysis (2013-2023)

Authentic marketing is a widely debated subject in several industries, including gastronomy, tourism, and culture. This study utilizes bibliometric analysis to identify the current state of the art in authentic marketing themes across multiple scientific disciplines. Bibliometric research analyzes the progress of research on authentic marketing from 2013 to 2023 by examining data from the past 10 years. Bibliometric analysis is to identify and analyze research trends across time, with the goal of generating new research ideas for future studies. Bibliometric research analyzes the progress of research on authentic marketing from 2013 to 2023 by examining data from the past 10 years. Based on bibliometric study, it is evident that the United States has a predominant presence in publications about legitimate marketing. In addition, the most commonly published type of article is the article, and the Journal of Business Research has the highest scientific influence in terms of publication sources, as it has the largest number of citations. Bibliometric analysis aims to identify and map the evolving trends in authentic marketing research, such as perception, sustainability, brand authenticity, social media, influencer marketing, purchase intention, and online social networking. This analysis can provide valuable insights and research ideas for future studies.

Accurate and transferable drug-target interaction prediction with DrugLAMP.

Accurate prediction of drug-target interactions (DTIs), especially for novel targets or drugs, is crucial for accelerating drug discovery. Recent advances in pretrained language models (PLMs) and multi-modal learning present new opportunities to enhance DTI prediction by leveraging vast unlabeled molecular data and integrating complementary information from multiple modalities. We introduce DrugLAMP (PLM-assisted multi-modal prediction), a PLM-based multi-modal framework for accurate and transferable DTI prediction. DrugLAMP integrates molecular graph and protein sequence features extracted by PLMs and traditional feature extractors. We introduce two novel multi-modal fusion modules: (i) pocket-guided co-attention (PGCA), which uses protein pocket information to guide the attention mechanism on drug features, and (ii) paired multi-modal attention (PMMA), which enables effective cross-modal interactions between drug and protein features. These modules work together to enhance the model's ability to capture complex drug-protein interactions. Moreover, the contrastive compound-protein pre-training (2C2P) module enhances the model's generalization to real-world scenarios by aligning features across modalities and conditions. Comprehensive experiments demonstrate DrugLAMP's state-of-the-art performance on both standard benchmarks and challenging settings simulating real-world drug discovery, where test drugs/targets are unseen during training. Visualizations of attention maps and application to predict cryptic pockets and drug side effects further showcase DrugLAMP's strong interpretability and generalizability. Ablation studies confirm the contributions of the proposed modules. Source code and datasets are freely available at https://github.com/Lzcstan/DrugLAMP. All data originate from public sources.

Equity of financial protection for health in high-income countries: scoping review protocol

IntroductionFinancial protection (FP) is a central function of health systems to enhance access to essential care and improve health equity. We aim to characterise evidence on the distribution of FP...

A dataset of venture capitalist types in China (1978–2021): A machine-human hybrid approach

Despite escalating interest in distinguishing among various types of venture capitalists (VCs) and their roles in shaping entrepreneurship and innovation, such research remains sparse in the world’s second-largest VC market, i.e., China. To address this important gap, we have devised a machine-human hybrid approach to perform the classification task for VC types. Specifically, we have compiled a list of 49,187 VCs that made investments in China before 2021 from CVSource database, collected VC ownership information from other public sources, developed machine-learning algorithms to predict VC types, and used human coders when machine-learning failed to produce a prediction. Utilizing this hybrid approach, we have classified VCs into one of the following types: GVC (public agency-affiliated, state-owned enterprise-affiliated), CVC (corporate VC), IVC (independent VC), BVC (bank-affiliated VC), FVC (financial/non-bank-affiliated VC), UVC (university-affiliated VC), and PenVC (pension-fund-affiliated VC). We not only provide the most up-to-date database for VC types in the Chinese setting but also demonstrate how to leverage machine-learning algorithms to devise a transparent coding approach for VC-type classifications.