Effects of Swanson theory-based auricular acupressure on chemotherapy-induced peripheral neuropathy, and broader health-related outcomes in patients with breast cancer: A randomized controlled trial.

Since the arrival of ChatGPT in November 2022, many Generative AI chatbots have appeared in the marketplace. Some of these tools like Consensus, Scholar GPT and Scholar AI are specifically designed to facilitate access to research and scholarly information. Also, research database aggregators and vendors like Scopus, Clarivate and JSTOR have introduced their version of Gen AI applications for use on their databases. Will the widespread use of these tools change the ways people seek, access and use information? How can the contemporary, and future, information science research contribute to the sustainability of the Gen AI-augmented information systems and services, especially in the context of research and scholarly information? By critically analysing a diverse range of research papers, and industry and institutional reports and documents, this article discusses various issues associated with the social, economic and environmental sustainability of research and scholarly information systems and services in the era of Gen AI. It proposes a model for sustainability of the information ecosystem in the era of Gen AI, focusing particularly on access to research and scholarly information using LLM-based chatbots, and proposes a research agenda to achieve the social, economic and environmental sustainability of information.

Purpose This study investigates the temporary discontinuance of social media. Building on stimulus-response binding and priming mechanisms, we propose a research model illustrating how compulsive social media use–through hedonic consumption, social interaction and content sharing–shapes temporary discontinuance. We argue that compulsive use can be modulated by cognition-based priming effects (cognitive dissonance and attitudes toward discontinuance) and affect-based priming effects (somatic and self-evaluative mood states), with exposure to cues (e.g. social media apps on smartphones) acting as a potential moderator. Design/methodology/approach We tested our model through a field study and quantitative analysis of Facebook users who voluntarily took a break from the platform. An objective assessment of participants’ temporary discontinuance was used to validate the model. Structural equation modeling was employed to analyze relationships between compulsive social media use, priming effects and discontinuance behaviors. Findings The results indicate that compulsive social media use can both directly and indirectly influence temporary discontinuance. Cognition-based priming (cognitive dissonance and attitudes) and affect-based priming (mood states) significantly shape discontinuance behavior, while exposure to cues moderates these relationships. The findings highlight the complex mechanisms underlying social media disengagement. Originality/value This study extends discontinuance behavior research in information systems (IS) by identifying priming effects as key mechanisms influencing temporary disengagement. The findings offer practical insights for users seeking to manage social media use, service providers designing interventions and policymakers addressing digital well-being.

Artificial intelligence (AI) is reshaping strategic corporate finance by enhancing firms’ ability to interpret market signals, optimize financial structures, and pursue sustainability-oriented growth. This paper reviews the emerging literature on the integration of AI-driven market intelligence with capital structuring to achieve sustainable market leadership. It explores how predictive analytics, natural language processing, and machine learning models enable corporate leaders to interpret complex financial environments, anticipate market shifts, and optimize debt–equity configurations in alignment with long-term strategic objectives. Drawing from interdisciplinary research in finance, strategy, and information systems, the paper argues that AI-driven market intelligence strengthens financial agility and risk management by transforming unstructured data into actionable insights for capital allocation. The integration of AI with capital structuring supports firms’ pursuit of sustainable leadership by aligning financing strategies with dynamic market expectations, investor sentiment, and regulatory trends. Furthermore, AI facilitates continuous learning loops in financial decision-making, allowing for adaptive leverage and funding strategies that balance profitability with environmental and social responsibility.

An early step in designing information systems (IS) is eliciting design requirements. Traditionally, these requirements focus on product characteristics, such as desired functionalities. However, this technology-centered approach often neglects the broader context of IS design, which significantly influences project outcomes. While IS scholars emphasize the importance of context awareness, clear guidance on achieving it remains lacking-particularly for marginalized communities, where the context differs substantially from that of typically non-marginalized researchers and developers. Marginalized communities, such as the Deaf community, possess distinct cultural identities shaped by histories of discrimination and exclusion. Successfully conducting IS research and design in these contexts demands profound context awareness. We derive our argument for the importance of context awareness from the theory of Value Sensitive Design and the principles of sociotechnical design. We propose that context awareness is essential for the project to be perceived as legitimate by the marginalized community, which is crucial for the project's success. To help researchers become more context-aware, we present 42 design requirements resulting from a two-year iterative design science research project conducted in collaboration with the Deaf community. These design requirements encompass the research project, the IS design process, and the final product. This article contributes to the literature on inclusive IS design, Value Sensitive Design, and the development of assistive technologies.

ABSTRACT Introduction: The Roma minority in Poland has been struggling with systemic educational exclusion for years, which affects their social and economic situation as well as their mental health. This article analyzes three key systemic issues in the Polish education system concerning Roma children: overrepresentation in special schools, a shortage of Roma education assistants, and a high dropout rate after primary school. Methodology and results: Based on data from the Educational Information System (SIO) and scientific research, the article highlights the mismatch of diagnostic tests to the linguistic and cultural needs of Roma children, leading to misdiagnoses and stigmatization. There are significant differences in the percentage of Roma children in special schools between Polish provinces. The lack of support from Roma education assistants and insufficient promotion of education within the Roma community exacerbate the problem. Discussion: The article provides recommendations for implementing tailored diagnostic tests, increasing the number of Roma education assistants, organizing anti-discrimination training, and supporting programs to guide Roma children in choosing educational paths. It emphasizes the importance of inclusive education in improving the mental well-being of Roma children and calls for collaboration among state institutions, NGOs, and the Roma community. Implementing these actions could reduce educational inequalities, enhance social integration, and support the Roma minority in Poland.

Decentralized autonomous organizations (DAOs) represent an innovation in the design of organizations by creating blockchain-based human-machine systems that are governed based on the collective decisions of their participants. Although this new form of organizing promises to sustain participation and foster decentralized governance, many existing DAOs have failed to achieve the intended degrees of decentralization. This study aims to understand how DAOs can fulfill their potential for decentralization by empowering individuals to participate in governance. Using an abductive approach guided by the empowerment theory, this research identifies three key practices underpinning empowerment in DAOs: promoting autonomy, ensuring transparency, and fostering communication. A configurational approach is used to identify complementarities among these practices that lead to three distinct governance archetypes associated with varying degrees of decentralization. Based on fuzzy-set qualitative comparative analysis (fsQCA) of 30 DAO cases, we introduce “deliberative democracy” as a DAO governance archetype that allows for increasingly decentralized governance. Our findings demonstrate that, although a high degree of autonomy is needed to sustain decentralization, there needs to be sufficient communication among autonomous actors to facilitate the collective management of DAOs. These findings advance the understanding of decentralization in information systems research and highlight the governance mechanisms that foster decentralization in blockchain-based systems.

Purpose As sustainability regulations tighten, Regulatory Technologies (RegTech) solutions have become more crucial, enabling real-time monitoring, predictive risk analytics, automated reporting and data-driven decision-making to support compliance. The purpose of this study is to synthesize the existing body of knowledge from academic and gray literature – including insights from researchers, industry and governing authorities – to assess the capabilities enabled, challenges and limitations of using RegTech solutions for sustainability compliance. Design/methodology/approach A multivocal literature review approach was applied to synthesize insights from academic literature and gray literature. We adopt an information systems capabilities lens to assess how RegTech supports sustainability-related compliance needs. Given that RegTech is an emerging field where much of the practical development and discussions about RegTech and compliance technologies occur outside academia, a multivocal literature review approach bridges the gap between academia and industry and ensures a comprehensive and holistic analysis. Findings The findings reveal that RegTech enables automated compliance monitoring, and environmental, social and governance (ESG) risk management, enhances transparency in reporting and offers tools to mitigate greenwashing risks while also supporting sustainable investment and digital finance. In additon, varying maturity levels across platforms, high implementation costs and cybersecurity risks present further adoption challenges. Practical implications To fully harness RegTech’s potential, interdisciplinary collaboration is crucial. Researchers in sustainability, finance, law, management and information systems should work together to develop frameworks, empirical studies and policy recommendations that address the operational, ethical and technical dimensions of RegTech. Strengthening partnerships between academia, industry and policymakers can help bridge the gap between conceptual research and practical implementation, ensuring that RegTech solutions are both effective and ethically sound. For industry, the integration of RegTech solutions presents a significant opportunity to improve sustainability compliance while reducing regulatory burden. Financial institutions, corporations and technology providers should prioritize investments in scalable and interoperable RegTech solutions that align with emerging regulatory and sustainability reporting standards such as the Corporate Sustainability Reporting Directive, Sustainable Finance Disclosure Regulation and global ESG disclosure standards. Originality/value This study’s originality lies in its comprehensive synthesis of academic and gray literature to evaluate the role of RegTech in sustainability compliance, a critical yet unexplored topic. Moreover, the study provides valuable insights for researchers, policymakers, regulators and practitioners on advancing standardized terminology across disciplines regarding the RegTech phenomenon and offers strategies and insights to enhance RegTech’s potential in driving sustainability compliance.

Research visibility has become a critical issue for universities, yet the institutional conditions that shape it remain underexplored. While Current Research Information Systems (CRISs) provide essential infrastructure for managing publications and researcher profiles, their impact depends on broader governance and cultural factors. This study compares four universities—two in Peru, one in Chile, and one in Spain—that have adopted the Pure CRIS platform. Data were manually extracted from institutional portals and analyzed descriptively, using normalized indicators such as publications per researcher, Sustainable Development Goal (SDG) alignment, and collaboration networks. Although based on a limited sample, the analysis highlights substantial contrasts: European institutions show consolidated integration of CRIS into national evaluation systems, while Latin American universities remain at earlier stages of adoption, with fragmented policies and limited international reach. The findings suggest that technological platforms alone are insufficient; institutional commitment, coherent policies, and academic cultures that value dissemination are decisive. These insights contribute a comparative framework to guide universities, particularly in Latin America, seeking to strengthen their global research visibility.

Information Systems (ISs) research frequently relies on digital trace data, often using simple activity counts as proxies for complex latent constructs like ‘experience’. However, the validity of such proxies is often assumed rather than critically scrutinized. This study problematizes this practice by treating a common proxy—a creator’s prior project count on Kickstarter—not as a measure of experience, but as a focal signal whose meaning is inherently ambiguous and context-dependent. By analyzing large-scale data (N ≈ 16,407 projects), we uncover a nuanced ‘experience paradox.’ The proxy exhibits a significant inverted-U association with backer mobilization and non-linearly moderates the value of other positive signals. Strikingly, it also maintains a persistent negative direct association with total funding, with its meaning varying significantly across project categories. These findings reveal the profound ambiguity of seemingly objective digital traces. Our primary contribution is methodological and theoretical: we provide a robust empirical critique of naive proxy use and refine signaling theory for digital contexts by integrating it with cognitive limitations and contextual factors. We urge IS scholars to develop more sophisticated measurement models and offer specific, evidence-based cautions for platform managers against the simplistic use of activity metrics in the digital economy.

Press releases covering novel scientific developments play an important role in science communication. Their number has increased in the past years, making them a valuable object of quantitative analysis in science communication research. However, large-scale research on academic press releases is limited, likely due to the lack of comprehensive and open datasets. In this data paper, we describe how we created a dataset of press releases published on EurekAlert!, an online science news service. The dataset consists of the metadata of a total of 566,566 press releases. We describe how we extracted the data, transformed it into a relational database, and made the code and data openly available to the research community. Next to that, we explain the structure of the dataset and how it can be accessed and propose potential integrations into other research information systems.

Booking cancellations have a significant impact in demand-management decisions in the hospitality industry. These cancellations often limit the production of accurate forecast which is a significant tool in terms of revenue management performance. In order to curb these booking cancellation problems, hotels tend to employ rigid cancellation policies and overbooking strategies which could be detrimental to revenue generation and reputation of the hotel. This study is aimed at creating a machine learning model that could, with very high accuracy and precision, predict hotel booking cancellations. The dataset used is based on the individual bookings drawn from a hotel reservation system from a resort hotel in Portugal. The model was built using random forest algorithm with the dataset being split into 80% for the training set and 20% for the test dataset. By addressing booking cancellation prediction as a classification problem in data science context, the findings showed that it is possible to build models for predicting booking cancellations with an accuracy result of over 88%. This allows hotel managers accurately predict net demand and build better forecasts, improve cancellation policies, define better overbooking strategies and hence come up with more realistic and profitable pricing and resources allocation strategies. Keyword: Machine Learning, Hotel Booking Cancellation, Random Forest Algorithm, Prediction. CISDI Journal Reference Format Afolorunso, A.A., Aimuel, B.E., Abiodun, A.O., Adesina, A.O. & Ajagbe, S.A. (2025): Development of a Machine Learning–Enabled Decision Support Framework for Hotel Booking Cancellation Prediction. Computing, Information Systems, Development Informatics and Allied Research Journal. Vol 16 No 3, Pp 23-36. Available online at www.isteams.net/cisdijournal. dx.doi.org/10.22624/AIMS/CISDI/V16N3P2

This study discusses the development of the Research and Community Service Management Information System (Simpeka) at the Institute for Research and Community Service (LPPM) of the University of Timor to optimize the submission process for research and community service proposals. This web-based system was developed using PHP 5.6, MySQL 5.7, HTML5, CSS3, and JavaScript ES6. Testing involved the LPPM and relevant stakeholders to ensure the system met user requirements. The implementation results show an increase in the number of proposals from 150 in 2023 to 169 in the current year (an increase of 12.67%), a reduction in the average review time from 14 days to 7 days (50% efficiency), and a decrease in funding validation time from 7 days to 2 days (71.4% efficiency). The percentage of proposals validated according to the budget increased from 80% to 95% (an accuracy improvement of 18.75%). Technically, the Simpeka dashboard has an average load time of 1.8 seconds and a database query response time of 0.35 seconds. These improvements demonstrate that Simpeka can accelerate administrative processes, enhance transparency, and strengthen accountability in the management of research and community service at the University of Timor

Utilising influenza monitoring data from Sichuan Province, descriptive research and geographic information systems (GIS) were employed to examine the epidemiological features and spatiotemporal patterns of influenza in the province from 2015 to 2024. From 2015 to 2024, Sichuan Province reported a total of 2,105,900 influenza cases, exhibiting a general rising trend in incidence, notably marked by high rises in 2019 and 2023. Global geographic autocorrelation study indicated substantial positive spatial autocorrelation in influenza incidence from 2019 to 2024 (Moran's I > 0, P < 0.05). Local spatial autocorrelation study identified clustering patterns throughout Sichuan Province, with high-high clustering mostly in the centre region and low-low clustering mainly in the western and eastern parts. Hotspot study indicated a progressive rise in the quantity of influenza hotspots, predominantly located in the central region, namely within urban areas of the plains. Analysis of the standard deviational ellipse of the movement trajectory of influenza outbreak centres indicated a shift in influenza transmission within the province from central urban areas to the southern regions, accompanied by a gradual dissemination. Our findings demonstrate that influenza prevention and control continues to be a significant public health concern in Sichuan Province. Region-specific influenza prevention and control strategies must be formulated, emphasising enhanced surveillance of low-incidence influenza clusters and preferential resource allocation to areas with elevated influenza incidence, to effectively address potential future influenza pandemics and mitigate the influenza burden.

ABSTRACT This paper is designed to enhance accounting researchers’ understanding of neurophysiological research methods. Our methodological guide presents the latest innovations in this realm, including pupillometry, facial expression analysis, electroencephalography, electrocardiography, functional magnetic resonance imaging, electrodermal activity assessment, and functional near-infrared spectroscopy. The paper introduces readers to uses of neurophysiological research techniques by identifying key themes in the recent AIS literature and assessing the potential value of a spectrum of neurophysiological techniques for advancing these research themes. In essence, this paper serves as a foundational guide for researchers aspiring to harness the potential of neurophysiological techniques in accounting contexts.

ABSTRACT This study addresses the persistent challenge of social inclusion faced by senior citizens, a group frequently marginalised in an increasingly digital society. While existing Information Systems (IS) research has documented the barriers seniors encounter in digital engagement, limited knowledge exists on effectively translating these insights into actionable design practices. Approaching social inclusion as a design challenge, we conducted an Action Design Research (ADR) project with a large international humanitarian organisation to co-design a digital gateway artefact to support seniors in achieving relevant, independent, and meaningful use of digital technologies. Drawing from this experience, we introduce the concept of socially inclusive design and articulate three prescriptive design principles that explicitly embed the core social needs of trust, agency, and belonging into IS artefact design, fostering meaningful integration of digital tools into seniors’ everyday social lives. In doing so, we challenge prevailing assumptions that improvements in technological usability alone sufficiently achieve meaningful digital integration, emphasising instead the necessity of intentionally addressing users’ underlying social needs through artefact-level design decisions. Our research advances IS design knowledge by providing actionable guidance for aligning artefact design with broader societal objectives, facilitating deeper digital engagement and consequently, greater social participation among socially excluded groups.

Abstract The use of social media across all demographic groups has brought the harmful nature of cyberbullying into sharper focus. Detecting cyberbullying on social media platforms has become widely researched in Information Systems (IS) research. However, previous literature has primarily focused on designing technical detection tools to classify cyberbullying, overlooking connected contextual, social, and psychological dynamics between users. Therefore, this research summarizes existing cyberbullying analysis methods, focusing on social and technical aspects. It evaluates existing approaches from a systematic literature review to identify suitable strategies to improve cyberbullying detection. We identified thirty-one fundamental articles in this context. We extracted three categories to address improvement potential: detection methods and technologies, socio-behavioural perspectives for cyberbullying, and regulatory and contextual influences. Based on our findings, we provide a research agenda and recommendations for designing strategies to detect cyberbullying.

The new management logic of digital megaprojects: An agenda for information systems research

This study investigates trends in the incidence and clinical management of self-harm among adolescents and young adults in Catalonia from 2013 to 2022, using data from the Information System for Research in Primary Care (SIDIAP). A population-based cohort analysis was conducted to examine temporal trends, demographic inequalities, and clinical care patterns. The study population comprised 1,707,471 eligible individuals aged 10 to 24, contributing 8,868,472 person-years of observation. The incidence of self-harm increased significantly over the study period (Incidence Rate Ratio [IRR] 2022 vs. 2013 for the total cohort: 2.67; 95% CI: 2.31-3.10), particularly during the COVID-19 pandemic (IRR 2022 vs. 2019: 2.06; 95 CI: 1.81-2.35), with rates in girls approximately three times higher than in boys. Socioeconomic deprivation emerged as a major risk factor, with individuals from deprived areas demonstrating elevated self-harm rates. Comorbid mental health disorders, notably anxiety and depression, were highly prevalent among individuals engaging in self-harm. Clinical management strategies differed by age and sex; girls were more frequently referred to mental health services, while psychotropic medication was commonly prescribed for both sexes. The incidence of self-harm has steadily increased reaching unprecedented levels during the pandemic, with significant disparities by sex, age, and socioeconomic status. The findings underscore the need for an appropriate healthcare response addressing the social determinants of health. Monitoring incidence trends and implementing targeted strategies are essential to support youth mental health in the post-pandemic context.

ABSTRACTDigital innovation offers significant societal, economic and environmental benefits but is also a source of profound harms. Prior information systems (IS) research has often overlooked the ethical tensions involved, framing harms as ‘unintended consequences’ rather than symptoms of deeper systemic problems. In response, this paper presents a problematization review that critiques and revises three widely held assumptions about digital innovations: (1) that they generate net benefits that outweigh the associated harm; (2) that their ethicality can be calculated through utility and (3) that their harms can be mitigated through technological, corporate or regulatory intervention. We argue that compassion provides a pluralistic ethical foundation that integrates the strengths of consequentialism, deontology, and virtue ethics. This framework prioritises serving all stakeholders, especially the most vulnerable, while avoiding harm. It sets a research agenda focused on addressing structural dysfunctions, amplifying marginalised voices, and fostering sustainable systems. By reimagining digital innovation as a force for the common good, this paper contributes to a more just and equitable digital future for all.