Online retailers increasingly offer reusable express packaging, but adoption remains difficult because sustainable options can conflict with the convenience expectations that define online retailing. This article examines reusable packaging adoption as a circular retail service conversion problem. Across three studies with adult online shoppers, we test how digital service nudges and responsibility framing influence adoption through perceived service friction, perceived environmental efficacy, and sustainable service trust, and how these effects depend on return convenience. Study 1 uses a quota-based, post-stratification-weighted survey to show that decision-relevant service nudges reduce perceived service friction and increase adoption intention, while responsibility framing increases perceived environmental efficacy and sustainable service trust. Study 2 uses a discrete choice experiment to estimate trade-offs among nudge timing, return convenience, deposit/refund rules, delivery delay, environmental benefit visibility, and responsibility framing. Study 3 uses an incentivized simulated checkout task to test behaviorally consequential reusable-packaging choice at the decision point. The results show that return convenience and deposit clarity are stronger adoption drivers than generic environmental claims, and that consumers penalize delivery delay more strongly than they reward verified environmental-benefit information. Decision-point nudges increase reusable-packaging checkout choice more than post-checkout reminders, especially when return convenience is high. The findings contribute to retail service convenience, digital nudging, and circular retailing research by showing that sustainable retail adoption depends on service-touchpoint design, not only on environmental attitudes. We position the model as a middle-range service-conversion framework grounded in service convenience, limited-attention decision-making, and sustainable-consumption efficacy and trust.

Chronic health information seeking is vital for patient well-being and self-management, yet how AI aids this process remains unclear. To explore how users interact with Gen AI tools when seeking and evaluating chronic health information, this study conducted an experiment involving 60 participants, collecting 757 user-generated dialogues related to three chronic conditions. We developed a complementary coding framework integrating analysis of user behavior and AI’s response to understand user-AI interactions and their impact on chronic disease information seeking, evaluation and adoption. The results show that while user interactions with Gen AI share similarities with traditional searches, they also exhibit distinct characteristics: 1) User-input prompts are more detailed, with longer sentences and more terms to specify information needs. Users also adopt more diverse reformulation strategies, often informed or inspired by AI feedback. 2) Some users communicate with AI as if interacting with a human, and the AI often responds with emotionally supportive, human-like replies. 3) Users spend less time but engage in more conversation turns, as the AI provides clear, well-structured responses that maintain dialogue flow and adapt to user intent, thereby enhancing retrieval efficiency and encouraging continued interaction. 4) While most users evaluate AI-generated content heuristically and rarely seek external verification, encountering factual inaccuracies or low-credibility responses can reduce their willingness to adopt the AI's output. These findings offer a more holistic understanding of human-AI interaction in online health information seeking and provide valuable guidance for optimizing system design, enhancing algorithm literacy, and improving health management practices.

The design studio is a unique environment typically situated at the center of design education. This study explores the transition from a conventional design studio to a real-life design context and examines the changes in the design process adopted by students in such a setting. For this study, 25 interior design undergraduates were included through a convenience sampling technique. The students were exposed to a real-life context where they could engage with contextual scenarios and collaborate with end users whom they encountered in a workplace setting. In the architectural design process, end users are the individuals who will benefit from the design once it has been constructed. The Manin Market in Peliyagoda, Sri Lanka, was selected as the real-life context for this study. Action research methodology was employed, with data collected through naturalistic observation, focus group interviews, and photographs. The data were analysed by using a six-phased thematic analysis. The findings reveal the emergence of the empathizing phase as a critical component, interwoven with all major design thinking phases. Additionally, the study identifies the use of information and communication technology (ICT) tools as essential mediums for design communication throughout the students’ design process in a real-life context.

Passenger trust is key to acceptance and reliance in autonomous eVTOL aircraft, especially during low-altitude risk scenarios such as obstacle avoidance. Grounded in situation awareness theory and human–automation trust research, this study examines passenger trust formation, focusing on explanatory information and its spatial layout. A passenger-centered framework is proposed in which trust is mediated by visual attention, cognitive workload, perceived usability, and situation awareness. A simulated experiment compared three interface configurations: full head-down display, full head-up display, and split-screen. Subjective measures and eye-tracking data capture perceptual and cognitive processes. Results indicate that full head-up display enhances situation awareness, usability, and trust by supporting efficient attention allocation and cognitive coherence. Split-screen layouts increase integration demands and limit trust development. Findings clarify passenger trust mechanisms and highlight the importance of integrated, low-friction interface design under dynamic low-altitude risk conditions.

Wilderness search and rescue (WiSAR) often involves asymmetric information accessibility and role responsibilities that shape decision-making pathways. This study investigates how information-sharing strategies shape human–drone collaboration under asymmetric information in WiSAR. A controlled indoor laboratory simulation with 26 dyads compared no sharing, full sharing, and adaptive sharing. Compared with no sharing, both full and adaptive sharing improved subjective experience, whereas no consistent reductions in task completion time were observed. Differences between full and adaptive sharing were generally nonsignificant across most subjective measures. Behavioral, subjective, and eye-tracking data suggest that both sharing strategies support coordination under asymmetry by facilitating information alignment and reducing uncertainty. Adaptive sharing introduced more structured interaction patterns but did not consistently outperform full sharing. These findings suggest that information sharing primarily mitigates asymmetric constraints rather than demonstrating the superiority of adaptive mechanisms, highlighting the need to balance informativeness and coordination support in human–AI collaboration design.

Although social media extensively captures user preferences and aesthetic intentions, its highly unstructured and emotionally expressive semantics have long been regarded as noise that is difficult to translate into reliable generative cues. Here we show that social media semantics contain stable patterns that can be systematically abstracted and validated, and that these patterns exert interpretable effects on the structural quality and semantic consistency of three-dimensional (3D) generation. Using 60,500 real-world social media posts, we validate this finding through CoX-3D, an explainable generative framework that introduces an Explainable Mediation Layer to bridge macroscopic social computing with microscopic physical rendering. Incorporating these stable semantic patterns reduces structural reconstruction error by over 50% and improves semantic consistency, measured by CLIP similarity, by 13.1%. Semantic activation and attribution analyses further reveal differentiated roles of semantic factors in geometric and stylistic decisions. These results demonstrate that social media semantics constitute a systematically modelable and interpretable cognitive resource, establishing a generalizable paradigm for socially informed generative 3D design.

Purpose – Collaboration has become increasingly common in modern life, study and work and group discussion is vital for exchanging ideas and promoting collaboration. This study aims to explore how groups with consistent and inconsistent initial attitudes negotiate meaning and build knowledge together by analyzing verbal interaction in face-to-face discussion settings.

Design/methodology/approach – This study conducted a qualitative inquiry of 19 group discussions in which students were asked to discuss a certain topic to produce arguments supporting a thesis statement they agreed with. Ten groups are composed of attitude-consistent members, and the other ten of attitude-inconsistent members. This study recorded, transcribed and coded the discussion process, using a codebook built upon prior research on collaborative knowledge building.

Findings – This study found that 1) attitude-consistent groups reached consensus quickly and focused on refining shared arguments with minimal conflict; 2) attitude-inconsistent groups engaged in more questioning, explanation and defense, reflecting deeper negotiation and reasoning; 3) initial attitude composition influenced how groups interacted, negotiated conflicts and moved toward consensus and 4) the ability to influence group outcomes was linked less to majority opinion and more to members’ communication and persuasion skills.

Originality/value – This study offers process-level insights into how group-level attitudinal composition shapes collaborative knowledge building in in-person educational settings. The findings inform the design of collaborative learning environments that balance efficiency with cognitive depth and foster productive engagement with diverse perspectives.

Amid platform-based collaboration, expanding digital government interfaces, and the commoditisation of data, corporate digital innovation increasingly depends on the interoperability and coordination of cross-organisational data and information systems. However, governance interface mismatches and interoperability failures often generate systemic conversion losses between data restructuring and innovation outputs. The organisational mechanisms through which such losses are mitigated remain insufficiently understood. Drawing on boundary-spanning theory and extending it to the information systems context, this study conceptualises the Chief Information Officer (CIO) as an institutionalised information boundary-spanning capability grounded in information systems orchestration and governance. By identifying, integrating, and orchestrating data resources, information systems, and cross-boundary interfaces, CIO-enabled IS orchestration enhances the governability and reusability of digital resources, thereby improving digital innovation efficiency. Using firm-year panel data from Chinese A-share listed firms between 2014 and 2024 (approximately 50,000 observations), we treat a firm’s first CIO appointment as a staggered institutional event and employ propensity score matching combined with a staggered difference-in-differences approach for causal identification. The results show that the initial appointment of a CIO significantly increases digital innovation output. Mechanism analyses indicate that information systems orchestration capability serves as a key mediating channel. Further analyses reveal that open innovation ecosystem maturity and governance interface configurations shaped by public and firm-level digital governance significantly strengthen CIOs’ boundary-spanning effects. From an information management perspective, this study demonstrates that digital innovation returns in open innovation contexts are not technologically self-generating, but depend critically on the alignment between governance interfaces and information systems orchestration.

Purpose – This study aimed to uncover the themes and types of information shared among parents of children with autism spectrum disorder (ASD) in an online community and to elucidate the relationship between them.

Design/methodology/approach – Utilizing Houyi Crawler software, this study initially gathered 8,575 posts from the designated “Autism Bar” section within Baidu Tieba, a popular Chinese online community, after which 3,673 relevant posts were retained. The posts underwent rigorous qualitative analysis using open coding to precisely identify the themes and subthemes related to information sharing among parents of children with ASD.

Findings – First, the study identified 10 major themes and 37 subthemes that encapsulated the intricate nature of information sharing among Chinese parents of children with ASD in an online community. Second, these parents predominantly shared experiential information rich in cognitive–affective insights, although other types of information such as facts and descriptions were also shared to a lesser degree. Third, a specific correlation was identified between themes and types of information shared within this community.

Originality/value – The study is among the first to characterize empirically the themes and types of information shared by parents of children with ASD through examining the articulations of online discussants.

This review maps the intellectual base and evolution of Search as Learning using a reproducible workflow that combines a Web of Science corpus, Python screening, and VOSviewer, yielding 95 studies. Keyword co-occurrence, temporal overlays, co-citation, and country and journal mappings reveal eight thematic clusters and a shift from cognitive and exploratory themes to measurable learning outcomes and emerging AI mediated support. The co-citation results indicate a three part foundation: conceptual framing, operational measurement and prediction of knowledge gain, and log based behavioral methods. Collaboration concentrates in the United States and Northwestern Europe, with outlets centered on Conference on Human Information Interaction and Retrieval (CHIIR) and strong citation impact for the Journal of Information Science. Building on these findings, the review articulates an extended definition that unites user centered, interaction centered, and system centered perspectives, and proposes a simple prompt framework that operationalizes the system centered view in generative AI based SAL support.