When participants on transaction platforms harm others (e.g. fraud, misconduct), it typically takes time before platform sponsors tighten their membership conditions. Although anecdotal evidence exists, platform governance literature does not cover the microlevel processes through which negative network externalities lead to actions to protect the platform. This paper employs an institutional legitimacy lens to theorise how governance processes unfold as platforms encounter negative network externalities. We study PayNow, a payment platform whose governance practices evolved over time as legitimacy pressures accumulated, leading to progressively stricter onboarding and fraud-prevention measures. The study provides exploratory insights into microlevel processes of materialising and spotting externalities, perceiving legitimacy challenges, questioning internal assumptions, trading off legitimacy and growth, and safeguarding the platform. We contribute to platform governance literature by illustrating how governance actions are driven by moral and regulatory legitimacy challenges that stem from diverse forms of negative network externalities.

Background: The transition from adolescence to young adulthood (age 10‐25 years) constitutes a sensitive developmental period marked by rapid biological, psychological, and social change, during which preventive health interventions can shape long-term outcomes. Mobile health tools offer accessible opportunities for tailored support for this population, but often adapt poorly to dynamic contexts, resulting in inconsistent engagement and effects. Just-in-time adaptive interventions (JITAIs), which tailor support in real time using ongoing data, are increasingly explored as precision health strategies. However, how these mechanisms are designed, implemented, and evaluated for adolescents and young adults (AYAs) has not been systematically reviewed. Objective: This review aimed to synthesize the evidence on JITAIs developed for AYAs, examine how their adaptive mechanisms have been designed to support specific health goals and changing AYA contexts, and assess methodological reporting quality to inform future precision health intervention development. Methods: We conducted a systematic review in accordance with PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) and SWiM (Synthesis Without Meta-Analysis) reporting guidelines. Twelve databases were searched for peer-reviewed studies published from 2013 to 2025. Eligible studies focused on participants aged 10 to 25 years and reported real-time adaptive mobile health interventions consistent with JITAI design principles. Two reviewers independently conducted screening, data extraction, and methodological quality appraisal using the Joanna Briggs Institute checklists. AYA coauthors contributed to all phases. Due to substantial heterogeneity in study populations, intervention content, adaptive mechanisms, comparators, and outcome measurements, findings were synthesized narratively, and no meta-analysis was conducted. Results: A total of 61 unique interventions were included. JITAIs for AYAs addressed substance use (n=24, 39.3%), mental health (n=23, 37.7%), and physical health or chronic conditions (n=14, 23%). JITAI tailoring mechanisms relied predominantly on self-reported behavioral data. Decision rules were typically symptom threshold–based, and decision points were commonly daily or event-triggered. Methodological concerns with reporting on intervention administration, participant selection, and outcome measurement reliability were pervasive across all studies, limiting the interpretability of observed effects and cross-study comparisons. Ethical considerations, including researcher positioning and reflexivity, alongside the depth of reporting around participatory AYA engagement in design and implementation, were also inconsistent. Conclusions: This review contributes a novel perspective to AYA digital health by moving beyond intervention outcomes to examine how core adaptive mechanisms are operationalized for AYAs across multiple health domains, while also integrating AYA perspectives into the interpretation of findings and recommendations. Unlike prior reviews focused primarily on adults or specific conditions, it identifies broader contextual, methodological, and ethical considerations relevant to AYA precision health. These findings highlight the need for more transparent, contextually responsive, and youth-centered adaptive interventions, alongside more rigorous designs for evaluating adaptive intervention components in daily life contexts.

Youth are increasingly using large language models (LLMs) for well-being support, yet existing governance guidelines provide limited interaction-level requirements and empirical work rarely centers lived experience from youth and the communities that support them. We report a participatory study with 38 stakeholders (youth, parents, youth care workers). Using reflexive thematic analysis, we identify three stakeholder-derived governance domains for youth-facing LLM support: Interaction, Context, and Escalation. Stakeholders aligned on Governance of Interaction and Context but diverged on Escalation, particularly acceptable transitions to external support, with youth proposing intermediary peer referral mechanisms via personalized information retrieval. We translate these stakeholder accounts into preliminary normative requirements and dialogue inspection examples that can be used to guide model fine-tuning and post hoc evaluation. We further discuss how our formative findings expand upon major artificial intelligence guidelines by surfacing where existing frameworks remain underspecified for conversational governance and evaluation.

Large language model (LLM)-based conversational systems are increasingly proposed as personalized digital well-being tools (DWTs) for youth, yet current personalization approaches often fail to reflect heterogeneous lived experiences. We present a participatory approach for eliciting personalization requirements for LLM-based DWTs, with youth well-being as a case study. In a multi-stage co-creation study with youth, parents, and youth care professionals (N=38), we combined data-driven personas with participatory persona co-creation and follow-up stakeholder interviews to examine what meaningful LLM-based DWT personalization should entail. Our preliminary findings suggest that stakeholders prioritize person-centered personalization beyond demographic or clinical labels, emphasizing identity, relational dynamics, routines, literacy needs, and changing lived context. Participants also highlighted the importance of dialogic mechanisms, particularly reflective questioning and ongoing updating of contextual representations over time. We argue that participatory personas can serve as reflexive scaffolds for surfacing community-grounded personalization needs and translating them into emerging design requirements for adaptive LLM systems. These findings position personalization in DWTs as an ongoing dialogic, person-centered process that warrants further investigation in research on human-AI personalization.

Background: Women face unique and diverse mental health challenges and therefore require tailored interventions that address their specific needs and lived realities. Research has shown a lack of digital interventions designed for and with women from marginalized backgrounds, such as minority racial/ethnic backgrounds or with low socioeconomic status. If Digital Mental Health Interventions (DMHI) are not designed with active involvement of women from diverse backgrounds, they may fail to reach their public health objectives, which potentially exacerbates existing health disparities. How Human-Centered design methods are applied and reported, and whether women from diverse backgrounds are involved in the design and development of Digital Mental Health Interventions (DMHI), is under-researched. Objective: This study examined the methods and frameworks used in the design and development processes of DMHIs, whether and how studies include women from diverse backgrounds, and whether they tailor to their diverse needs related to intersectional identities (e.g., race/ethnicity, socioeconomic status, age) in the design and development process. Methods: We conducted a scoping review following the PRISMA-ScR guidelines. The databases included are Scopus, PubMed and IEEE Xplore, and the databases are searched from the inception until the 31st of May 2026. We included 77 articles that described the design process of digital mental health solutions for women. Results: Among the 77 reviewed studies, 18 (23.4%) did not explicitly state their design methods, and most of them provided limited information on the characteristics of the included populations. Only 16 (20.8%) studies consistently involved users across all design stages. Intersectional identities were considered in only 26 (33.8%) studies. We observed an overrepresentation of research in higher-income countries, an underrepresentation of women from racial/ethnic minority backgrounds, a narrow age range of participants, and a lack of consideration of intersectional identities. Conclusions: Our findings reveal critical gaps in the development of DMHIs for women, including the superficial reporting and application of Human-Centered Design methods in the design process, limited user involvement, and a lack of consideration of diversity, inclusivity and intersectionality. Future research should emphasize active involvement of end-users from the earliest design phases onwards and adopting an intersectional lens in their design processes. We propose a research agenda for better reporting and applying HCD methods in future DMHI research, towards designing diverse, inclusive and equitable digital solutions for all women. Registry and registry number for systematic reviews or meta-analyses: A protocol of this study is pre-registered at Open Science Framework (DOI 10.17605/OSF.IO/WC79P).

As privacy concerns grow, organizations and policy makers promote the use of privacy-enhancing technologies (PETs) to improve user trust and data-sharing behaviors. However, privacy-enhancing technologies (PETs) are often technologically complex and opaque to lay users. It is challenging to understand and effectively communicate the functionality of complex PETs to the users, such as Secure Multi-Party Computation (MPC). Studies typically assess the impact of new PETs by presenting users with a high-level description of the technology before measuring how this treatment changed their attitude or behavior. These results influence business and regulatory decisions (see Gartner's Hype Cycle for Emerging Technology [123]). In the present study, we question this approach. We assess whether naming specific PETs and providing generic descriptions impact users' willingness to put trust in service providers and share their data. Our survey presented three randomized controlled trials with 1,457 participants in a data marketplace scenario. The first group was treated with a PET (MPC), the second group with a fictional PET, and the third with a non-PET, serving as a control group. Our findings reveal that user trust and data-sharing willingness increased with MPC and the fictional PET, indicating that the high-level description, rather than the technology name, shapes user perception. We conclude that claiming the use of a PET is not an effective method to measure the impact of actually using this technology. However, given their mental model, lay users cannot verify the privacy claims of such descriptions presented in studies or by service providers. This increases the risks of users being deceived into a false sense of privacy, leading them to expose more private data than they otherwise would.

During an executive meeting, the senior vice president of a large technology firm discussed recent sustainability developments with the managing director of a global implementation firm. They concluded that sustainability is gaining traction and significantly impacts data collection, analysis, and reporting. They agreed to jointly invest in developing a sustainability module to integrate into the technology firm’s digital platform. By reaching out to a client interested in becoming a “launching customer,” they established a digital platform ecosystem and created the sustainability module. This case outlines the real design challenges faced by the ecosystem partners. Seven (7) design challenges have been identified, ranging from selecting and importing data tracking metrics against goals and targets to creating a dashboard. Three environmentoriented features (e.g., decarbonization, travel emissions, energy consumption) were launched as a minimum viable product and rolled out to the client. This teaching case consists of two parts: the first part introduces the concept of sustainability, digital platform ecosystems, a case description, and the design framework, while the second part discusses the seven identified design challenges.

Data platforms enable actors to exchange personal and business data. While data is relevant for any digital platform, data platforms exclusively revolve around data artifacts. This paper argues that the specific characteristics of data artifacts challenge the authors’ understanding of platform openness. Specifically, it is argued that data artifacts are editable, interactive and distributable, which means that the consequences of opening up a data platform extend far beyond the focal platform and its context. From this, the study infers that the scope of platform openness extends beyond the data platform on which data artifacts originate. At the same time, the very nature of data artifacts afford new mechanisms to realize and reduce the risks of openness. New avenues are suggested to study platform openness in the realm of data platforms. These avenues include (1) exploring and incorporating novel consequences of platform openness in a data platform setting, (2) examining new arenas for defining openness beyond a focal platform’s confines, and (3) theorizing the implications of new mechanisms for realizing openness while maintaining apparent control over data artifacts.

In the data economy, data sovereignty is often conceptualized as data providers’ ability to control their shared data. While control is essential, the current literature overlooks how this facet interrelates with other sovereignty facets and contextual conditions. Drawing from social contract theory and insights from 31 expert interviews, we propose a data sovereignty conceptual framework encompassing protection, participation, and provision facets. The protection facets establish data sharing foundations by emphasizing baseline rights, such as data ownership. Building on this foundation, the participation facet, through responsibility divisions, steers the provision facets. Provision comprises facets such as control, security, and compliance mechanisms, thus ensuring that foundational rights are preserved during and after data sharing. Contextual conditions (data type, organizational size, and business data sharing setting) determine the level of difficulty in realizing sovereignty facets. For instance, if personal data is shared, privacy becomes a relevant protection facet, leading to challenges of ownership between data providers and data subjects, compliance demands, and control enforcement. Our novel conceptualization paves the way for coherent and comprehensive theory development concerning data sovereignty as a complex, multi-faceted construct.

The concept of Environmental, Social, and Governance (ESG), has captivated the attention of firms and academics, driven by an EU directive for firms to report ESG. Digital platforms fulfill an essential role to support organizations to manage their ESG initiatives. Since ESG disclosure standards are ambiguous, designing a digital platform for ESG is challenging. The design of ESG platform functionality is hindered as essential knowledge is fragmented across various stakeholders. In this paper, we show how a platform owner, complementor, and platform user co-design ESG platform module features by applying an ecosystem approach. Situated in a socio-technical context, we apply Action Based Research (ADR) that includes a cyclic process of design iterations in an actual real-life setting. We identified ten challenges that may occur in the design process, and we explain which strategies have been applied to overcome the challenges.

Purpose: Digital platforms are essential for fostering innovation in first-line healthcare. These platforms require openness, allowing external parties to utilize, enhance, or profit from them. Yet, knowledge about barriers to realizing platform openness is lacking. This research investigates the barriers to realizing platform openness in first-line healthcare. Method: This research employed a qualitative exploratory approach. We collected data through thirteen semi-structured interviews with platform experts, application developers, and healthcare practitioners. As a study setting, we focused on Dutch first-line healthcare. We then analyzed the data using thematic analysis. Result: We identify barriers in three main categories that hinder platform openness: technology-related (e.g., redundancy in development work), business-related (e.g., profit-maximizing strategy), and healthcare-related (e.g., reluctance to change). Scientific contribution: We contribute to the platform literature in medical informatics by being among the first to examine openness barriers that hinder platform-based innovation. We thus explain why platform implementations often do not result in substantial improvements in healthcare delivery despite their transformative impact in other industries.

Introduction Health behaviours such as exercise and diet strongly influence well-being and disease risk, providing the opportunity for interventions tailored to diverse individual contexts. Precise behaviour interventions are critical during adolescence and young adulthood (ages 10-25), a formative period shaping lifelong well-being. We will conduct a systematic review of just-in-time adaptive interventions (JITAIs) for health behaviour and well-being in adolescents and young adults (AYAs). A JITAI is an emerging digital health design that provides precise health support by monitoring and adjusting to individual, specific and evolving contexts in real time. Despite demonstrated potential, no published reviews have explored how JITAIs can dynamically adapt to intersectional health factors of diverse AYAs. We will identify the JITAIs' distal and proximal outcomes and their tailoring mechanisms, and report their effectiveness. We will also explore studies' considerations of health equity. This will form a comprehensive assessment of JITAIs and their role in promoting health behaviours of AYAs. We will integrate evidence to guide the development and implementation of precise, effective and equitable digital health interventions for AYAs. Methods and analysis In adherence to Preferred Reporting Items for Systematic Review and Meta-Analysis guidelines, we will conduct a systematic search across multiple databases, including CENTRAL, MEDLINE and WHO Global Index Medicus. We will include peer-reviewed studies on JITAIs targeting health of AYAs in multiple languages. Two independent reviewers will conduct screening and data extraction of study and participant characteristics, JITAI designs, health outcome measures and equity considerations. We will provide a narrative synthesis of findings and, if data allows, conduct a meta-analysis. Ethics and dissemination As we will not collect primary data, we do not require ethical approval. We will disseminate the review findings through peer-reviewed journal publication, conferences and stakeholder meetings to inform participatory research. PROSPERO registration number CRD42023473117.

This paper analyses strategies for platform owners to increase complementor participation on the platform. Specifically, it draws on open innovation (OI) and the resource-based view (RBV) to isolate three drivers of complementor participation, namely breadth of content offerings and boundary resources (related to OI), and exclusive content (associated with RBV). We hypothesize that higher levels of each of these drivers increase the platform's attractiveness to future complementors and increase complementor participation. Based on negative binomial fixed effects regressions in the context of video game consoles, we find that boundary resources and exclusive content, but not breadth of content offerings, are positively related to complementor participation. This shows that drivers from both OI and RBV relate to complementor participation. The results have implications for the orchestration of platform ecosystems.