Transparent Data Research Articles

Open Science in Agricultural Economics

Abstract We provide a ‘big picture’ of what Open Science is and what benefits, limitations, and risks it entails for agricultural economists. We show that Open Science comprises various aspects, such as, the accessibility of science, transparency of scientific processes, open and FAIR research data and code, and openness in teaching and education. We identify potential benefits of Open Science for individual researchers and the public, as well as adoption barriers. We highlight that public benefits of a wide-spread uptake of Open Science practices still remain unexplored. We share best practice examples for key aspects of agricultural economic research, i.e., primary data collection and analysis, optimization and simulation models, use of replication packages and an Open Science Community. Assessing the author guidelines of twelve Agricultural Economics journals for their Open Science practices, we find that data citation and transparency are considered important in many journals already, whereas replication, pre-registration or results-blind review are encouraged but rarely enforced. It also becomes evident that the journals differ in terms of how strictly they enforce their open-science guidelines. We close by providing recommendations for researchers, journal editors, policy makers, universities, research institutes and funding agencies to better align public benefits with private incentives.

Evolving trends, limitations, and ethical considerations in AI-driven conversational interfaces: assessing ChatGPT's impact on healthcare, financial services, and educational sectors

ABSTRACT This study presents a comprehensive bibliometric analysis of ChatGPT's impact on three critical sectors: healthcare, financial services, and education, covering the period from 2022 to 2024. The research aimed to explore the evolving trends, limitations, and ethical considerations associated with the deployment of ChatGPT and similar AI-driven conversational interfaces. The findings reveal that while ChatGPT offers significant potential in enhancing efficiency and decision-making processes, it also faces substantial challenges in data privacy, integration with existing systems, and the need for improved emotional intelligence. The study highlights the inherent biases in AI models, raising concerns about the accuracy and fairness of AI-driven outputs. Ethical considerations, including data privacy, transparency, accountability, and equity in AI applications, are identified as crucial areas requiring urgent attention and development. Additionally, the research underscores the importance of developing robust regulatory frameworks and ethical guidelines to govern AI deployment in these sectors. Successful integration of ChatGPT and similar technologies depends on addressing these challenges and ethical considerations through collaborative efforts among AI developers, industry professionals, policymakers, and ethicists. Future research should focus on improving AI's data security, emotional intelligence, bias reduction, human-AI collaboration, and assessing long-term impacts across diverse settings.

Public views on open data health research in Switzerland: Implications for research and policy

Abstract Background The increasing volume of publicly available data offers health researchers opportunities to explore public sentiment through open data research on issues such as vaccination hesitancy and fake news propagation. To ensure ethical conduct and maintain public trust, assessing public perceptions of open data research in healthcare is crucial. Methods We conducted 10 focus groups across the German, French, and Italian-speaking regions of Switzerland. We presented participants with real-world examples of open data research in healthcare and guided discussions using a semi-structured format. The topic areas were: (1) using Twitter data to assess public opinion on gene-editing technology, (2) assessment of health policy documents, (3) using Twitter data to predict individual health status and (4) using YouTube data to assess public sentiment on health policies. We assessed our findings using a thematic analysis approach. Results Gathering insights from 75 citizens, four major themes emerged: (1) Expectations towards actors and open data research, such as using research findings for societal benefit, and ensuring transparency in data use through informed consent; (2) Supportive measures including communication strategies to raise awareness and inform the public about the use of publicly available data for health research; (3) Concerns about data reuse for purposes beyond the study’s objectives, especially for financial gain, and about data validity and privacy, particularly for sensitive health data; and (4) Mitigative measures to minimize harm, such as through the involvement of external oversight committees. Conclusions Our findings indicate public support for open data research in healthcare, provided that specific expectations are met. Developing a guiding framework for legitimate open data research in healthcare is a valuable next step, with a focus on enhancing public awareness through communication campaigns and providing oversight measures to foster public trust. Key messages • Open data research in healthcare relies on public data use without explicit consent, which can disconnect the research community from society. • We found that public support for open data research in healthcare is generally present, however it is also conditional on communication and policy efforts addressing their concerns.

The physician-AI relationship: partnering for precision medicine via clinical decision support

Abstract Background Clinical decision support systems (CDSSs) can enhance physician decision-making, but successful adoption depends on positive user attitudes. Understanding Israeli physicians’ attitudes toward CDSSs is crucial for overcoming implementation barriers and refining training. Methods Semi-structured interviews explored knowledge, experiences, perceived benefits/drawbacks, and potential barriers/facilitators to CDSS use among 25 Israeli physicians across specialties, roles, settings, and experience levels selected via stratified sampling. Individual 45-minute video interviews were conducted in January-July 2023. Results Familiarity and CDSS experience varied substantially across medical specialties. While risk calculators, information systems, and expert systems disseminating contemporary research insights are widespread, AI-based system adoption is relatively low outside radiology. Physicians expressed positive attitudes, recognizing CDSSs’ potential to enhance clinical work, reduce errors, and alleviate burdens. However, concerns included AI systems’ impact on workload, patient relationships, skill erosion, and overreliance. Key implementation barriers involved technological infrastructure, organizational processes, physician perceptions, and system features. Facilitating factors included tailored design, focused training, continuous accuracy/reliability validation, and clear autonomy/liability guidelines. Conclusions Addressing key concerns around transparency, trustworthiness and responsible use is crucial for AI-CDSS to fulfill its promise of enhancing quality and outcomes. Insights from Israeli clinicians provide guidance on priorities like transparency of data and algorithms as well as ensuring AI behaves ethically. Collaboration among technology designers, healthcare professionals and stakeholders can help develop systems that physicians trust to improve care while safeguarding patients. Ongoing evaluation is also needed to optimize AI-CDSS over time. Key messages • Understanding physician attitudes is key to overcoming barriers to clinical decision support system adoption and optimizing training protocols. • Addressing transparency, trustworthiness, and ethical considerations around AI clinical decision support systems is crucial for enhancing quality care.

Cloud Computing in Insurance: Emerging Trends and Transformative Technologies

This article examines the transformative impact of emerging cloud computing trends on the insurance industry. As insurers increasingly adopt cloud-based solutions, several key technologies are poised to revolutionize operations, customer experiences, and business models. The integration of artificial intelligence and machine learning is enhancing underwriting accuracy, claims processing efficiency, and fraud detection capabilities. Edge computing is enabling real-time data analysis and decision-making, while serverless architectures are optimizing resource allocation and reducing costs. Blockchain technology is improving data security, transparency, and trust in transactions. Additionally, hybrid and multi-cloud strategies are providing insurers with greater flexibility and regulatory compliance. This comprehensive analysis explores these trends, their interconnections, and their potential to drive innovation in insurance. The article concludes by discussing the implications of these advancements for insurers, policyholders, and the broader financial services ecosystem, offering insights into future research directions and industry adaptations.

A global adoption of cryptocurrency and blockchain technology into the healthcare system

Abstract Background/Objectives Blockchain technology is revolutionizing various industries by enhancing security, transparency, and efficiency. In healthcare, its small-scale application demonstrates the potential to transform healthcare. This study explores how cryptocurrency and blockchain technology enhance healthcare financial stability, secure medical information exchange, increase payment recovery and interoperability. Methods Guided by the Diffusion of Innovations (DOI) Theory, this study reviews 34 articles on blockchain and cryptocurrency adoption in healthcare. We performed a thematic analysis focusing on empirical data, theoretical analyses, and existing implementations. Data were categorized by DOI elements: relative advantage, compatibility, complexity, trialability, observability, and social system. The findings were synthesized into a detailed framework for adopting these technologies in healthcare. Results Our analysis shows that cryptocurrency offers a secure, decentralized payment platform, eliminating the need for third-party intermediaries. Blockchain adoption enhances payment and patient record protection. Cryptographic methods ensure data integrity, transparency, and security, preventing modifications once recorded. Altering data requires consensus from the network majority, protecting healthcare providers from ransomware attacks. Conclusions Evidence suggests that cryptocurrency and blockchain will disrupt healthcare payments, data management, and accommodate interoperability within the next decade. These technologies promise improved security, improved public health research, and increased trust in the healthcare system. Key messages • Our research will be assessing the challenges of integrating digital coins and blockchain technology into the healthcare system. • Examine the potential benefits and risks of implementing blockchain technology in healthcare settings.

Review of Blockchain Technology on Data Security and Privacy: Recommendations for Advancing Tanzania's ICT Sector

The rapid growth of the ICT sector has led to increased global data exchange and innovation opportunities. The increased use of technology has brought about concerns regarding data security and privacy which triggered a rising interest in blockchain technology as a potential solution to security challenges. This research endeavours to comprehensively examine the influence of blockchain on data security and privacy inside and outside Tanzanian, filling the gap that exists. The blended approach was used to analyse blockchain's effects while focusing on ethical considerations. The review emphasizes the benefits of blockchain in enhancing data security, trust, and transparency, along with its various applications. The research highlights blockchain technology's potential to offer robust data protection and improve transparency while identifying the challenges that must be addressed for successful implementation. The study investigates the role of blockchain in securing information systems in global and Tanzanian settings, focusing on sectors such as healthcare, banking, education, and land registration. The study emphasises the significant potential of blockchain technology to impact various industries in Tanzania profoundly. It offers valuable insights for professionals, policymakers, and researchers, highlighting the need to investigate how blockchain can be applied explicitly within different sectors. Additionally, it suggests practical strategies for seamlessly integrating this technology, considering the unique challenges the Tanzanian ICT sector encounters.

Trustworthiness of EHRs: Key Factors from a User-Centered Study in Germany

Abstract Background The integration of digital technologies, particularly Electronic Health Records (EHRs), promises substantial improvements in patient care and cost reductions. However, the success of EHRs depends heavily on patient trust and usage, which are influenced by their control over data visibility, storage, and sharing. Identifying the factors that enhance the perceived trustworthiness of EHRs is essential for increasing their reliability and acceptance in healthcare settings. Methods Participants (N = 30) first interacted with an interactive EHR prototype, then evaluated its trustworthiness and suggested improvements during semi-structured interviews. These interviews were transcribed and analyzed using thematic analysis to identify key themes affecting perceptions of the EHR’s trustworthiness. Results Through thematic analysis, we developed a categorical system encompassing five principal themes: provider reputation, information quality, system characteristics, user control, and user feedback. The analysis revealed that deficiencies in design and usability indirectly affect perceptions of privacy and data security. Conclusions Our study underscores the critical role of contextual factors-including provider reputation, strategic IT partnerships, and user feedback-in cultivating trust in Electronic Health Record (EHR) systems. Addressing privacy concerns and bolstering user trust necessitates not only a professional approach to design and usability but also clear communication about adherence to rigorous data privacy and security standards. In Germany’s tightly regulated environment, clearly communicating EHR security standards is crucial. Enhancing trust also involves robust customer support, user control over their data, and leveraging social proof like high download rates or positive reviews. These approaches could significantly improve EHR acceptance and trust in digital health across the country. Key messages • The perceived trustworthiness of EHRs is essential for increasing their reliability and acceptance in healthcare settings. • Effective communication and design are critical for building trust in digital health technologies. Trust in EHRs grows with transparent data policies and empowering user controls.

Research on the Impact and Solution Strategies of Blockchain Technology on Data Security and Transparency in Enterprise Digital Transformation

Abstract: This research delves into the profound impact of blockchain technology on enhancing data security and transparency during enterprises digital transformation. By dissecting blockchains core attributesdecentralization, immutability, and advanced securitythis study elucidates how it offers pragmatic solutions to prevalent challenges such as data breaches and opaque information processing. Leveraging an extensive literature review, meticulous case analysis, and expert insights, the article comprehensively illustrates blockchains diverse applications in ensuring data integrity and enhancing transparency across critical sectors, including financial services, supply chain management, and healthcare. Furthermore, the study identifies and deliberates on existing research gaps in blockchain technologys application within digital transformation, proposing a systematic framework to deepen comprehension of its role in this process. Moreover, it conducts an in-depth analysis of the technical, operational, and environmental hurdles hindering blockchain adoption, offering a series of action strategies to enable enterprises to harness their potential effectively amidst the swiftly evolving digital landscape. Through this comprehensive inquiry, the article underscores the strategic significance of blockchain technology in augmenting corporate operational transparency and data security. Additionally, it elucidates how blockchain can bolster corporate governance, compliance, and stakeholder trust. Overall, this synthesis provides a thorough review and profound insights into research findings, underscoring blockchains pivotal role in addressing contemporary digital challenges while furnishing invaluable strategic guidance for industry innovation and advancement. The research outcomes hold substantial implications for practitioners and researchers, signaling the transformative potential of blockchain technology in reshaping enterprise operations and charting a course for future exploration in this pivotal domain.

On the Suitability of Process Mining for Enhancing Transparency of Blockchain Applications

AbstractBlockchain technology is known for its transparency properties due to its publicly available, immutable data. Yet, as data availability does not inherently ensure transparency, further analytical methods may be required for human interpretation of data traces. Process mining has emerged as a popular toolbox for understanding processes and how they are executed in practice. The paper studies process mining as a method to enhance the transparency of blockchain data. To this end, two popular Ethereum applications were analyzed using process mining: the prediction and betting marketplace Augur and the network marketing platform Forsage. Observations from the process-mining analyses are used to discuss if process mining can serve as a method to establish transparency of a blockchain. For both applications, new insights are generated for usage scenarios such as application redesign, security analysis, user behavior analysis, and revealing blind spots in Augur’s and Forsage’s documentation. The paper concludes that there is evidence that process mining can serve as a method to enhance transparency in blockchains at the cost of technical setup and knowledge acquisition.

Blockchain in Healthcare: Overview of Applications, Challenges, and Future Directions

There are numerous healthcare issues which show the potential of blockchain technology such as transparency, interoperability and security of data. Through this study, it tries to offer a very deep explanation of where the Blockchain applications today stand for in the healthcare domain emphasising on possible benefits from the technology and some known challenges that are being faced while actuating those. We then use blockchain applications in the above-mentioned aspects to explain different aspects of use of Blockchain in healthcare like supply chain management, clinical trials, secure medical data exchange and patient empowerment. We also talk about Blockchain from implementation point of view – smart contracts, consensus methods and data privacy. In this publication, we determine whether deploying Blockchain in healthcare raises ethical and legal issues and how existing issues can be addressed. In conclusion, we describe future directions for research and opportunities to use Blockchain to improve healthcare delivery and outcomes.

The Role of Blockchain Technology in Supply Chain Management

In the rapidly evolving digital era, efficiency and transparency are key to gaining a competitive edge in business. Blockchain technology has emerged as a revolutionary solution with the potential to enhance transparency, security, and efficiency in the supply chain. While many large companies have adopted it for various benefits, challenges such as scalability, interoperability, and legal uncertainties still hinder the widespread adoption of blockchain. This research utilizes a literature review to explore the challenges and benefits of implementing blockchain in the supply chain, as well as strategies to enhance data security, transparency, and efficiency. The findings indicate that blockchain can improve transparency, security, and efficiency in the supply chain, but there are still challenges to be addressed. Nonetheless, with proper investment and development, the potential benefits of blockchain in supply chain management (SCM) are significant.

The Impact and Challenges of Digital Transformation on Supply Chain Resilience in Physical Enterprises

Abstract: In the digital era, supply chain resilience (SCR) has become a key pillar of the real economy. Enterprises face various challenges, including cybersecurity threats, market volatility, technological change and changing global conditions. A strong SCR not only ensures continued business operations but also maintains market stability and consumer well-being. Digital transformation helps businesses anticipate market changes, optimize inventory management, improve operational efficiency, and assist in management decisions when necessary by providing unprecedented data transparency and real-time insights. The purpose of this paper is to examine the extent of digital transformation in the supply chains of physical firms globally through a literature review, to identify the factors influencing the resilience of digital transformation in the supply chains of physical firms, and to discover the barriers to digital transformation in the supply chains of physical firms. The study finds that the digital transformation of physical firms' supply chains is still in its infancy, and there are barriers at both managerial and physical levels. Solutions to address these barriers include enhancing employee training, correctly introducing appropriate digital technologies, and improving information security.

Enhancing Medical Information Security Through Blockchain Technology

Healthcare data management systems today face pressing challenges in maintaining data transparency, traceability, immutability, and security. Additionally, the centralized framework of many current healthcare systems raises concerns over potential catastrophic failures at single points. Blockchain technology stands out as a transformative solution, offering a decentralized and innovative approach with the potential to redefine healthcare data management. This paper investigates the transformative impact of blockchain in the realm of healthcare data management. It underscores how blockchain can drive revolutionary progress and substantial improvements in the sector. The paper examines the key features and benefits of blockchain, shedding light on the vast opportunities it opens up for healthcare. We provide an in-depth look at current projects and case studies, illustrating the practical application of blockchain in various healthcare contexts. Moreover, we address the significant research challenges hindering the full integration of blockchain into healthcare systems. The paper concludes by outlining future research directions that could further the advancement of blockchain in healthcare, paving the way for a new standard of excellence in data management.

THE ROLE OF BLOCKCHAIN TECHNOLOGY IN SECURING BANKING TRANSACTIONS IN AFRICA

<p>The rise of digital financial services in Africa has highlighted the growing need for secure and efficient banking systems. Blockchain technology, with its decentralized and immutable nature, offers promising solutions to address the security challenges inherent in traditional banking infrastructures across the continent. This study explores the potential of blockchain technology in enhancing the security of banking transactions in Africa by minimizing fraud, ensuring data transparency, and facilitating cross-border payments. The research examines how blockchain can revolutionize banking in Africa by providing secure transaction validation, improved customer privacy, and increased trust in financial institutions. Furthermore, it addresses the current barriers to blockchain adoption in African banks, such as regulatory challenges, technological infrastructure, and financial inclusion issues. The study concludes with strategic recommendations for integrating blockchain into the banking sector, emphasizing its capacity to foster financial innovation, increase transaction security, and drive economic growth across Africa.</p><p><strong>JEL:</strong> K24, L86</p><p> </p><p><strong> Article visualizations:</strong></p><p><img src="/-counters-/soc/0799/a.php" alt="Hit counter" /></p>

Role of artificial intelligence in predicting neurological outcomes in post cardiac resuscitation

Being an extremely high mortality rate condition, cardiac arrest cases have rightfully been evaluated via various studies and scoring factors for effective resuscitative practices and neurological outcomes post resuscitation. This narrative review aims to explore the role of Artificial Intelligence (AI) in predicting neurological outcomes post cardiac resuscitation. Methodology involved detailed review of all relevant recent studies of AI, different machine learning algorithms, prediction tools and assessing their benefit in predicting neurological outcomes in post cardiac resuscitation cases as compared to more traditional prognostic scoring systems and tools. Previously, outcome determining clinical, blood and radiological factors were prone to other influencing factors like limited accuracy and time constraints. Studies conducted also emphasized that to predict poor neurological outcomes, a more multimodal approach helped adjust for confounding factors, interpret diverse datasets and provide a reliable prognosis which only demonstrates need for AI to help overcome challenges faced. Advanced machine learning algorithms like Artificial Neural Networks (ANN) using supervised learning by AI have improved accuracy of prognostic models outperforming conventional models. Several real-world cases of effective AI powered algorithm models have been cited here. Studies comparing machine learning tools like XGBoost, AI Watson, hyperspectral imaging, ChatGPT-4 and AI based gradient boosting have noted their beneficial uses. AI could help reduce workload, healthcare costs and help personalize care, process vast genetic and lifestyle data and help reduce side effects from treatments. Limitations of AI have been covered extensively in this article including data quality, bias, privacy issues and transparency. Our objectives should be to use more diverse data sources, use interpretable data output giving process explanation, validation method and implement policies to safeguard patient data. Despite the limitations, the advancements already made by AI and its potential in predicting neurological outcomes in post cardiac resuscitation cases has been quite promising and boosts a continually improving system, albeit requiring close human supervision with training and improving models, with plans to educate clinicians, the public and sharing collected data.

PENGGUNAAN APLIKASI E-KINERJA SEBAGAI INSTRUMEN PENINGKATAN SASARAN KINERJA PEGAWAI PADA BADAN KEPEGAWAIAN DAN PENGEMBANGAN SDM KOTA KENDARI

This study aims to evaluate the use of the E-Kinerja application as an instrument for improving Employee Performance Targets (SKP) at the Regional Personnel and Human Resource Development Agency (BKPSDM) of Kendari City. The methodology employed is qualitative, with data collected through semi-structured interviews and observations of the application usage process. Respondents were selected using purposive sampling, specifically, employees actively involved in the E-Kinerja application. The results indicate that the application enhances the effectiveness of performance assessment, with both leadership and employees experiencing benefits in terms of accuracy, transparency, and ease of data access. However, challenges such as technical issues and the need for ongoing training for employees persist. Additionally, other important indicators such as timely reporting, data transparency, accuracy in assessment, and employee satisfaction were identified as contributing factors to the effectiveness of the system. Recommendations include improving technological infrastructure, providing continuous training, and developing strategies to enhance the balance between quantitative and qualitative assessments. These steps are expected to further improve accountability and bureaucratic efficiency at BKPSDM Kendari City.

Q-ensemble learning for customer churn prediction with blockchain-enabled data transparency

Q-ensemble learning for customer churn prediction with blockchain-enabled data transparency

Investigating Dark Patterns on Social Media: Implications for User Engagement and Impulse Buying Behavior

With the increasing use of social media and the proliferation of digital applications, dark patterns have become a significant concern due to their potential impact on user behavior. These patterns aim to influence user engagement and impulse buying in ways that are often subtle and undesired. Despite the importance of this issue, there is a lack of research examining the effects of dark patterns on engagement and impulse buying behavior, particularly in the Middle East. This study investigates key factors associated with dark patterns on social media that impact user engagement and influence impulse buying behavior. A Google Forms survey was conducted with 492 participants from PSUT in Jordan, and SEM was employed for hypothesis testing. The study found that time, effort, pleasure, and social acceptance significantly positively influence user engagement, while non-routine behavior exerts a negative influence. Furthermore, engagement demonstrated a significant positive effect on impulse buying behavior. Marketers should prioritize genuine connections and ethical practices to maintain trust and respect user autonomy. Dark patterns can erode trust and harm long-term relationships, emphasizing the need for transparency, social proof, and ethical data handling. This research addresses a significant gap in understanding the influence of dark patterns on consumer behavior.

The Dual Nature of AI in Information Dissemination: Ethical Considerations.

Infodemics pose significant dangers to public health and to the societal fabric, as the spread of misinformation can have far-reaching consequences. While artificial intelligence (AI) systems have the potential to craft compelling and valuable information campaigns with positive repercussions for public health and democracy, concerns have arisen regarding the potential use of AI systems to generate convincing disinformation. The consequences of this dual nature of AI, capable of both illuminating and obscuring the information landscape, are complex and multifaceted. We contend that the rapid integration of AI into society demands a comprehensive understanding of its ethical implications and the development of strategies to harness its potential for the greater good while mitigating harm. Thus, in this paper we explore the ethical dimensions of AI's role in information dissemination and impact on public health, arguing that potential strategies to deal with AI and disinformation encompass generating regulated and transparent data sets used to train AI models, regulating content outputs, and promoting information literacy.