Digital ecosystems are essential for enabling circular economy practices. Yet, little is known about how they emerge in segmented markets where voluntary coordination repeatedly fails, and no single actor can impose standards. This study examines the formation of a digital ecosystem through an in-depth case of the Battery Pass consortium, which developed a digital product passport in response to the European Union’s New Batteries Regulation. Based on 14 interviews across 17 organisations and an inductive case study design, we show that market-driven coordination challenges alone did not trigger ecosystem formation. Instead, regulatory enforcement created a shared imperative, while the consortium acted as an institutional facilitator by translating regulatory ambiguity into actionable standards, aligning heterogeneous actors, and fostering trust and interoperability. We identify a third pathway of ecosystem emergence, i.e. policy-catalysed, consortium-orchestrated formation, that arises when regulatory mandates intersect with fragmented markets lacking a focal orchestrator. The findings extend ecosystem emergence theory and offer guidance for policymakers and industry stakeholders in designing regulatory and collaborative structures that support transparent, trustworthy, and interoperable data-sharing infrastructures.

Generative artificial intelligence (AI) is increasingly utilized in business model innovation (BMI). Large language models support ideation and problem-solving but face challenges such as hallucination and complex reasoning. This study develops ChatBMI, an IT artifact that integrates generative AI into business model development tools (BMDTs) using structured prompts to enhance BMI processes. Following the design science research methodology, we assess existing BMDTs, identify AI leverage points, and implement a structured prompt system. ChatBMI improves business model development by enhancing creativity and reducing reliance on prompt engineering expertise. Our research contributes to innovation literature by demonstrating that structured prompts improve AI performance. We also present a structured approach for BMI prompt generation to guide business model designers in generative AI integration. This study advances AI-driven business model innovation, providing practical insights for academia and industry. Future research should explore AI's evolving capabilities and broader implications for digital transformation and strategic innovation.

In an era of data-driven decision-making, organizations increasingly build data ecosystems to share and capitalize on data within their ecosystem. With the advent of various initiatives with different goals, architectures, and governance structures, understanding the possible configurations that lead to vibrant data ecosystems is crucial for enhancing innovation and collaboration. This study investigates these configurations, focusing on the interplay between technical and social boundary resources, centralization, domain specialization, and the number of developing partners. Based on data from 26 data ecosystem initiatives, we use fuzzy-set Qualitative Comparative Analysis to identify three configurations of vibrant data ecosystems and derive two configurations associated with less success. Our findings contribute to understanding how different elements' combinations impact data ecosystems' performance, offering insights for practitioners aiming to enhance data sharing, innovation, and collaboration within their ecosystems.

Artificial intelligence (AI) offers transformative opportunities across industries, but poses new challenges related to fairness, safety, and compliance. Despite the urgent need for governing AI development projects systematically, there is a research gap regarding practical frameworks. Established development frameworks, such as agile development or CRISP-ML(Q), either lack AI-specific aspects or are incompatible with firms' stringent governance needs. Therefore, we designed and evaluated a phase model to govern and manage AI development projects, drawing on extant literature and close collaboration with AUDI AG, a leading car manufacturer. The resulting artifact defines six incremental phases to support procedural governance and specifies key activities and project checkpoints. The study contributes a rigorously developed artifact and additional recommendations to support firm-specific adaptations of the model. The results provide actionable guidance for practitioners to foster business/AI alignment, formalize responsible AI practices, and mitigate project risks.

The Metaverse has emerged as a prominent topic of discussion within the technology industry, presenting a wide array of opportunities for value creation across various businesses. Nevertheless, its value potential remains uncertain due to its early development stage. Our research analyzes 29 cases to address this gap and identify key value drivers for business models of complementors in Metaverse ecosystems. We identified five primary Metaverse-enabled value drivers for complementors (immersive customer engagement, massively scaled user innovation, virtual business efficiency, digital exclusivity, and extended ecosystem collaboration.). We illustrate how these drivers enhance those of ebusiness models, exploring their broader implications for business model innovation and value creation. Our findings provide valuable insights into value-creation opportunities that companies can leverage in the Metaverse, contributing to a better understanding of fundamental value drivers and enabling businesses to navigate this emerging landscape more effectively.

Transitioning to a circular economy requires innovative tools to ensure transparency, resource efficiency, and lifecycle management. Digital product passports (DPPs) have emerged as a key enabler, providing stakeholders across value chains with actionable product lifecycle data. While technical and regulatory frameworks for DPPs are advancing, limited attention has been given to their socio-technical design-balancing functionality with usability, accessibility, and stakeholder engagement. This research-in-progress addresses this gap by exploring how to design DPPs that effectively support sustainable practices in the furniture sector, a high-impact industry facing significant challenges in material traceability and end-of-life management. Adopting a Design Science Research methodology, this study develops a DPP prototype tailored to the furniture sector, integrating centralized lifecycle data modules, real-time condition monitoring, repair guidance, and environmental context analysis. Grounded in socio-technical theory, this research derives five actionable design principles to guide DPP development, emphasizing transparency, adaptability, security, and stakeholder collaboration. Preliminary findings indicate contributions both theoretically, by advancing socio-technical design frameworks, and practically, by offering a scalable and user-friendly approach to DPP development. By aligning technical functionality with social dynamics, this research aims to provide innovative solutions to drive sustainable production and consumption practices.

Objectives Healthcare providers employ heuristic and analytical decision-making to navigate the high-stakes environment of the emergency department (ED). Despite the increasing integration of information systems (ISs), research on their efficacy is conflicting. Drawing on related fields, we investigate how timing and mode of delivery influence IS effectiveness. Our objective is to reconcile previous contradictory findings, shedding light on optimal IS design in the ED.Materials and methods We conducted a systematic review following PRISMA across PubMed, Scopus, and Web of Science. We coded the ISs' timing as heuristic or analytical, their mode of delivery as active for automatic alerts and passive when requiring user-initiated information retrieval, and their effect on process, economic, and clinical outcomes.Results Our analysis included 83 studies. During early heuristic decision-making, most active interventions were ineffective, while passive interventions generally improved outcomes. In the analytical phase, the effects were reversed. Passive interventions that facilitate information extraction consistently improved outcomes.Discussion Our findings suggest that the effectiveness of active interventions negatively correlates with the amount of information received during delivery. During early heuristic decision-making, when information overload is high, physicians are unresponsive to alerts and proactively consult passive resources. In the later analytical phases, physicians show increased receptivity to alerts due to decreased diagnostic uncertainty and information quantity. Interventions that limit information lead to positive outcomes, supporting our interpretation.Conclusion We synthesize our findings into an integrated model that reveals the underlying reasons for conflicting findings from previous reviews and can guide practitioners in designing ISs in the ED.

A Circular Economy's (CE) adoption and continuation depend on various success factors, such as suitable collaboration between value chain stakeholders to enable circular material flows. Using digital platforms appears promising, as various CE use cases show. However, a differentiated view of the underlying mechanisms, i.e., the inherent characteristics and functionalities of digital platforms, is required to understand how these impact CE success factors and constitute the foundation for practical applications. Through a systematic literature review, we identified 15 digital platform mechanisms that impact 20 success factors for CE adoption and continuation. We conceptualized two CE platform types, each characterized by specific mechanisms: CE transaction brokers serve as marketplaces for resource trading. CE operating systems form technical supply chain infrastructures for collaboration alongside material flows. Our findings expand the theoretical understanding of the relationship between digital platforms and CE success, thus facilitating informed decisions about their practical use.

When presented with the latest statistics on global warming, it becomes evident that ecological sustainability will be equally important as economic sustainability for companies. A new wave of start-ups shows that ecological sustainability can be integral to a business model (BM) without compromising economic success. Like start-ups that designed their BMs to be ecologically and economically sustainable, incumbents also need to undergo two fundamental transformations in parallel: digital and sustainable BM transformation. While each transformation alone is considered demanding, we examined 31 start-ups to develop a taxonomy of digital sustainable BMs to understand how companies can master these complementary challenges and provide guidelines on achieving ecological and economic sustainability by implementing digital BMs. We use this taxonomy to derive four distinct archetypes of how sustainability can be an integral part of the BM: Sustainable Software Solutions, Sustainable Product-Service Systems, Sustainability Intelligence, and Digital Sustainable Platforms. For each archetype, we reveal the role of digital technology in creating ecological BMs and how these BMs create sustainable value from an ecological, economic, and technological perspective. Therefore, we go beyond using digital technology to optimise production or logistics or enable remote work and implement sustainability as an integral part of the core logic of the organisation and its identity. For practice, our strategy guidelines contribute to creating a sustainable reality based on digital technology implemented in the BMs.