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Phenomenon-driven research (PDR) establishes when a phenomenon warrants investigation but offers little structured guidance on diagnosing why a state change occurred or which aspect of the phenomenon drove it. We address this by introducing a framework based on the Belief-Action-Outcome (BAO) framework and meme theory, positioned after a state change is detected but before full-scale theorising begins. By separating institutional beliefs, concrete interventions, and realised and unrealised outcomes into distinct analytical layers, the framework allows researchers to identify which aspect of a phenomenon produced the change and why. We demonstrate its usefulness through the Maritime Single Window (MSW), a digital platform mandated across EU Member States, where the replacement of Directive 2010/65/EU by Regulation (EU) 2019/1239 represents such a state change. Our contribution equips IS researchers with an analytical structure that helps bridge the gap between rigour and relevance.

Municipalities face increasing pressure to deliver efficient and secure digital solutions. While this challenges all municipalities to engage in digital transformation (DT), resource disparities contribute to digital inequality as smaller actors struggle to allocate financial means and secure competency. Inter-municipal collaboration is crucial for addressing these challenges, yet research on its role in DT remains limited. This paper examines how DT unfolds in inter-municipal collaboration through a case study of two Swedish municipalities striving for equal welfare as a human right. Using longitudinal data and a collective social action perspective, we identify the trajectories of different types of DT, enabling mechanisms and sub-mechanisms that facilitate progress, and their role at various stages of collaboration. By extending existing frameworks, this research deepens the understanding of inter-municipal DT and provides valuable insights for practitioners working to enhance digital public services through collaboration.

Retrieval-augmented generation (RAG) architecture enhances large language models (LLMs) by incorporating external, domain-specific data sources, thereby reducing hallucinations and improving response accuracy. This approach departs from purely generative systems and offers a scalable, cost-efficient alternative for enhancing LLMs. However, the construction of ground truth to enable evolvability (ability to integrate new data continuously) and adaptability (ability to adjust responses to user context and intents dynamically) remains challenging. This study investigates how the challenges of establishing ground truth manifest at the organizational, unit, team, and individual levels within a countywide Swedish healthcare organization. Our analysis reveals that the main challenges stem from the heterogeneity of knowledge practices, which complicate the creation of reliable retrieval from the knowledge base. Furthermore, we identify a trade-off between attempts to enhance accuracy and maintain contextual relevance. These findings contribute practical insights into the micro-foundations of evolvability and adaptability in RAG-based chatbot development.

Digital innovation is increasingly shaped by the blurred boundaries between physical and digital realities. However, digital innovation scholarship has primarily focused on artificial objects, largely overlooking the role of natural objects in digital innovation processes. To address this knowledge gap, we report a qualitative case study of a Swedish forestry firm’s efforts to digitally represent natural objects and offer news forms of value to their customers. Our findings indicate that three key characteristics of natural objects – locus of control, pace, and multi-functionality – shape digital innovation processes.

Increasingly connected vehicles offer drivers benefits related to safety, navigation, and maintenance. They also provide policymakers new opportunities to trace and modify behavior using data insights. For such efforts to be effective, policymakers need access to policy instruments. These instruments must also be adopted by regulated entities such as technology providers, vehicle manufacturers, and drivers. Reuse and scaling across jurisdictional boundaries are crucial for the efficient development, adoption, and use of these digital tools. However, establishing digital tools that scale across diverse contexts requires navigating trade-offs between generalization to meet global demands and specialization to provide desired functionality. Using digital trace data and interviews, we conducted a longitudinal study of the development of the Mobility Data Specification standard for, freefloating e-scooters, over three years. We identified four key instrument tensions related to privacy, scope, richness, and the pace of evolution. We detail the nature of these tensions, analyze how they were mitigated, and suggest implications for the development of digital regulatory tools that span jurisdictional boundaries.

Digital options theory explains how investments in digital technology enable competitive responses. While prior research on digital options focuses on exogenous changes, such as environmental dynamism, it largely neglects endogenous changes within organizations. This study introduces organizational dynamism as a concept to capture endogenous change, distinguishing it from environmental dynamism and examining its impact on the relationship between digital options and market performance. Using a 15-year panel dataset from 103 geographically dispersed organizations, we find that organizational and environmental dynamism act as critical boundary conditions for digital options' performance implications. Specifically, organizational dynamism generally diminishes the performance benefits of digital options, though this negative impact is reduced for digital reach options under high environmental dynamism. These findings highlight the complex interplay between endogenous and exogenous change in shaping digital options' outcomes. We make three contributions. First, we expand digital options theory by introducing organizational dynamism as a lens to differentiate endogenous and exogenous change. Second, we explain how organizational dynamism influences digital options through mechanisms of digital debt and attrition. Third, we reconcile conflicting findings by demonstrating the combined effects of organizational and environmental dynamism on digital options' performance implications. These insights offer valuable guidance for managing digital investments in dynamic environments.

Multi-purpose ports' efficient and sustainable operation relies on seamless coordination and decision-making among multiple organizations. This paper underscores the critical importance of forecasting resource and infrastructure utilization for informed operational, tactical, and strategic decision-making. The proposed approach draws on digital twin technology to enable collaborative decision-making by modeling complex port environments to enable shared situational awareness among stakeholders. Illustrated through a collaborative project involving the RISE Research Institutes of Sweden, National University of Singapore, Grieg Connect, Umeå University, Kvarken Ports Umeå, and INAB, we propose a digital twin design to empower the port as a decision- maker in multi-organizational settings to proactively plan and optimize its utilization of present and future resources.

Maritime transports play a vital role for several industries in enabling efficient and sustainable transportation of goods. Ports are central hubs in the transport chain since they connect the maritime and land-based transport systems. The central position of ports makes them critical enablers of efficiency through digital connectivity but also implies that they need to consider many types of participating agents with whom they form episodic tight couplings. However, the industry's digitalization level remains relatively low, and we know little of the challenges facing ports in increasing it. Through a case study of digitalization in Swedish small- and medium-sized ports handling different types of cargo and serving different types of transport modes, we identify key objectives and critical challenges underlying digitalization processes in ports.

Connected vehicles generate new data streams that present promising opportunities for policymakers to monitor and learn from events and behavior. To explore what we can learn from how public entities leverage ubiquitous data streams for policy development and enforcement, we draw on a case study of the standard Mobility Data Specification (MDS) and its use by cities to regulate E-scooter operators. Our findings suggest that (1) the richness of real-time data changes the speed of policy revision, (2) data access enables moving some micro-decisions to the edge, and (3) policy will be formulated as fixed or flexible with different amendment rules.