This editorial outlines the critical challenges and research directions associated with managing and sustaining digital transformations within the Information Systems field. It discusses the gap between short-term adoption studies and long-term organizational normalization, providing a framework for future scholarly inquiry. Additionally, it introduces four selected papers from the Special Issue that explore leadership, theoretical metaphors, scaling tensions, and small business readiness. Problem Although initiating a digital transformation is widely emphasized, organizations face high failure rates because sustaining long-term transformation remains difficult and under-researched. Existing Information Systems literature often focuses on short timeframes and successful case studies, creating a disconnect with real-world complexities, cultural barriers, and structural obstacles. Outcome - Emphasizes the need for longitudinal research designs to observe how digital transformations unfold, normalize, and sustain over extended periods.
- Identifies key research challenges, including the misuse of terminology, unexamined assumptions, root causes of failure, and the dark side of digital transformations.
- Introduces the concept of an 'execution engine' to fundamentally adapt decision-making processes and performance rhythms for long-term transformation success.
- Showcases four special issue papers focusing on healthcare value landscapes, CIO-CDO role alignment, prototype ambiguity in scaling, and microbusiness owner-manager mindsets.

This paper proposes a creative evolution process philosophy perspective for information systems (IS) research, grounded in the philosophical works of Henri Bergson and Alfred North Whitehead. It establishes a set of five core principles to shift the research paradigm from viewing reality as static entities to seeing it as continuous processes and conscious experiences. The authors demonstrate the practical utility of this perspective by re-examining the challenges and failures in large-scale requirements engineering. Problem Traditional information systems development and research predominantly rely on entitative worldviews that treat reality as composed of fixed, static objects and discrete time steps. This static perspective fails to capture the complex, evolving nature of human experience and temporal flow, which frequently leads to project failures in large-scale IT implementations. Furthermore, the IS literature lacks formal principles and criteria for conducting research anchored in process philosophy that accounts for human consciousness and free will. Outcome - Formulated five foundational principles for process philosophy in IS research: heterogeneous multiplicity, immanence in a process, experience over abstraction, consciousness in duration, and relational ontology.
- Identified entitative abstractions in traditional requirements engineering as a major contributor to large-scale IT project failures.
- Emphasized the critical role of human consciousness, inner time, and free will in co-creating technology systems that adapt to evolving organizational contexts.

This study introduces a memory analysis framework based on Patanjali's Yoga Sutra to evaluate information systems implementation. It incorporates core concepts such as Samskara (subliminal impressions) and Alambana (external triggers) to understand how accumulated stakeholder experiences influence technology engagement. The framework is applied to an existing case study of an agricultural marketing information system in India. Problem Current information systems research predominantly focuses on team memory within Western organizational contexts, overlooking individual cognitive variations and Eastern philosophical perspectives. Additionally, existing studies rarely theorize memory per se, leaving a gap in understanding how subliminal impressions and past negative experiences impact stakeholder trust and behavioral responses. Outcome - The Yoga Sutra framework demonstrates that subliminal impressions (Samskara) formed by past unfair trade practices deeply influence stakeholder behaviors and technology adoption.
- Contextual factors and research interviews function as triggers (Alambana) that evoke unpleasant memories, reinforcing distrust between system users, government boards, and private vendors.
- Information system failures in developing contexts often result from a lack of adherence to core ethical and behavioral values rather than culture acting as a barrier.

This study proposes an ethics-based ontology for Information and Communication Technology for Development (ICT4D) research by combining Heidegger's existential phenomenology with Hans Jonas's ethics of responsibility. The paper examines how technology impacts lived experiences, human identity, and moral agency, applying this theoretical framework to re-analyze two One Laptop per Child (OLPC) case studies in Nepal and Peru. Problem Current ICT4D research predominantly relies on realist and idealist ontologies that view technology primarily as functional tools for systemic or economic growth. This narrow focus creates an ethical gap, neglecting how technological interventions affect human dignity, local agency, cultural integrity, and long-term intergenerational justice. Outcome - Establishes an ethics-based ontology in ICT4D that shifts focus from instrumental views of technology to lived human experience and moral responsibility.
- Demonstrates through the OLE Nepal case study how embedding technology into local educational ecosystems, national curricula, and teacher practices leads to sustainable success.
- Reveals through the OLPC Peru case study how top-down, context-unaware technological implementations erode local agency and lead to project failure.
- Highlights key implementation challenges, including translating abstract philosophical concepts into practical design metrics and addressing Eurocentric biases in technology evaluation.

This short paper proposes a conceptual research model to investigate the factors influencing the adoption and sustained usage of gamified location-based applications for community building. The framework integrates ten core factors across technology characteristics, gamification elements, and social dimensions to explain user engagement. The authors present a quantitative research methodology involving a survey of active Pokémon GO players to empirically test and validate eleven proposed hypotheses. Problem While gamification and location-based games like Pokémon GO have achieved widespread popularity, existing research primarily focuses on short-term individual user behavior or educational outcomes. Little is understood about the long-term sociopsychological mechanisms and 'stickiness' factors that enable location-based games to foster sustainable, real-world community engagement and social bonds. Outcome - Formulates a novel theoretical framework connecting technology adoption, gamification mechanics, external social influences, and intrinsic motivations to app stickiness and community engagement.
- Identifies key drivers such as location incentives, perceived ease of use, reward value, achievement, network influence, herd behavior, social motive, and sense of belonging.
- Establishes an empirical research design targeting over 1,000 active Pokémon GO players using Partial Least Squares Structural Equation Modeling (PLS-SEM).
- Provides preliminary theoretical grounding for designing mobile gamified systems that promote social sustainability and persistent physical-world social interactions.

This study investigates social commerce (s-commerce) adoption, consumer characteristics, and platform preferences in Qatar. Utilizing a quantitative survey of 441 Qatari residents, the research analyzes demographical trends, internet usage habits, and online shopping frequencies within the country's unique socio-cultural context. Problem Despite rapid growth in social media usage and e-commerce across the GCC region, research on social commerce adoption specifically in Qatar remains very limited. Furthermore, there is a lack of empirical understanding regarding how local socio-cultural factors and demographic profiles shape consumer engagement and purchase behaviors in Qatar's digital landscape. Outcome - Most social commerce users in Qatar engage in s-commerce purchases 1-3 times per month (82%), with an additional 18% purchasing 4-7 times monthly.
- Instagram emerged as the leading platform for s-commerce in Qatar (46%), followed by WhatsApp (20%), TikTok (14%), and Facebook (9%).
- Female consumers (56%) and younger demographics aged 20-24 (48%) constitute the largest user segments engaging in social commerce.
- The findings highlight the significant impact of local culture, digital infrastructure, and localized content preferences in driving social commerce diffusion.

This study explores the current state, challenges, and opportunities for integrating location analytics into Information Systems (IS) research and education. Drawing on insights from an academic panel, it outlines how spatial methodologies can enrich IS theories, enhance research rigor, and better prepare students for data-driven business roles. Problem Despite the critical role of location analytics in modern industry decision-making and strategic planning, its presence in academic IS research and business school curricula remains remarkably sparse. This gap leaves researchers overlooking spatial dimensions in complex problems and leaves graduates lacking essential geospatial skills required by the modern workforce. Outcome - Demonstrates how incorporating spatial methodologies (such as spatial autocorrelation and geographically weighted regression) can address complex societal 'wicked problems' like climate change, network disruption, and privacy.
- Provides a strategic roadmap for integrating location analytics into undergraduate and graduate IS curricula to prepare students for high-demand business roles.
- Outlines actionable steps to bridge academia and industry, including collaborative case study development, special journal issues, and enhanced faculty training in geospatial tools.

This study presents a threat-centric security analysis that maps adversarial techniques across a five-layer reference architecture for generative AI systems. The authors combine architectural decomposition and threat taxonomy mapping with a comparative analysis of EU and US governance frameworks to evaluate security controls. Problem Generative AI systems introduce security risks that fundamentally differ from traditional software due to probabilistic outputs, emergent failure modes, and expanded attack surfaces from tool and retrieval integration. Conventional perimeter-based and policy-only controls are insufficient because many GenAI vulnerabilities are structural rather than configurable. Outcome - High-impact generative AI risks are structural properties inherent to architectural design rather than isolated, patchable bugs.
- Effective risk mitigation requires a layered defense-in-depth model that combines traditional cybersecurity controls with AI-specific mechanisms such as context separation and tool sandboxing.
- Transatlantic regulatory divergence establishes EU frameworks as the de facto technical baseline for multinational deployments, driving global architectural convergence.

This paper investigates how scenario-based learning using AI-powered storytelling chatbots can engage university students in learning social engineering concepts. Utilizing a design thinking methodology with co-creation, an interactive chatbot powered by GPT-4 Turbo was developed to simulate real-world cybersecurity scenarios. The study evaluates the chatbot's effectiveness in delivering active learning experiences and providing dynamic feedback to students. Problem Traditional instruction methods in Information Systems often struggle to effectively engage students or illustrate the subtle tactics used in social engineering attacks. Although AI-driven interactive storytelling holds great potential for experiential education, research into designing AI chatbots as role-playing storytellers remains in its infancy. Outcome - The study demonstrated that co-designing AI chatbot prompts with students created effective 'teachable moments' for understanding social engineering tactics and data governance.
- Analysis of student interactions revealed diverse engagement approaches, ranging from friendly small talk to strategic IT troubleshooting and phishing tactics.
- Key strategies were established for integrating a storytelling culture in higher education, including establishing a shared language, providing appropriate digital resources, and fostering collaborative environments.
- Essential ethical guidelines were identified, emphasizing the necessity of robust data privacy, algorithmic bias mitigation, and content boundaries in educational AI applications.

This study investigates how information systems (IS) support open innovation networks among small and medium-sized enterprises (SMEs). Through a three-year case study of an inter-organizational medical device project developing a cardiovascular stent graft, the authors examine the key IS functionalities required across the open innovation process. Problem Developing complex products increasingly requires open innovation networks where independent firms pool their specialized expertise and resources. However, conventional enterprise applications are not designed for open innovation, creating a gap in understanding how to select, configure, and maintain a shared IS infrastructure across diverse network partners. Outcome - Identifies five key IS functionalities critical for innovation networks: collaborative work environments, knowledge maps, knowledge spaces, innovation procedure toolkits, and social media platforms.
- Reveals that network success stems from pragmatically using a diverse set of accessible IS tools to form a shared infrastructure rather than relying on a single complex system.
- Delivers nine practical guidelines for CIOs to manage IS infrastructure across the co-shaping, co-performing, and co-opting phases of open innovation networks.

This study examines how small and medium-sized enterprises use inter-organizational information systems to facilitate new product development within multi-firm innovation networks. Through an in-depth qualitative analysis of three case studies, the paper explores how information systems enable networking capabilities that allow partners to align their physical, human, and organizational resources. Problem Existing theories like the Resource-Based View primarily explain competitive advantage at the individual firm level, leaving a research gap regarding how network-level resources are developed and reconfigured across organizational boundaries. Consequently, firms in collaborative innovation networks struggle to systematically identify partner capabilities, align complementary assets, and manage shared inter-organizational processes. Outcome - Inter-organizational information systems are essential for enabling networking capabilities and constructing unique, shared resource constellations at the network level.
- Four core informational purposes of information systems—representation, sharing, architecture, and reach—facilitate the cross-boundary resource alignment process.
- Creating IS-embedded network resources enables collaborating firms to establish sustainable competitive advantages that extend beyond individual firm boundaries.

This paper examines the integration of location analytics into Information Systems research and education based on a panel discussion at AMCIS 2022. It outlines how spatial methodologies can enhance research rigor and provides strategies for incorporating location intelligence into academic curricula. Problem Despite the growing strategic importance of location analytics in industry, its adoption within academic Information Systems research and teaching remains minimal. As a result, spatial problem-solving is rarely addressed in business curricula, leading to a disconnect between graduate competencies and industry demand. Outcome - Highlights key research opportunities where location analytics can address complex, multidisciplinary problems such as climate change, network disruptions, and location privacy.
- Proposes a stepwise framework for business schools to integrate location analytics into IS courses, concentrations, and interdisciplinary programs.
- Recommends action steps to strengthen industry-academic partnerships, train faculty, and promote spatial methodologies in leading IS journals.

This study investigates how digital ventures create and adapt their internal business processes to support rapid firm growth. Utilizing a qualitative multiple case study design across seven digital ventures, the authors analyze process changes in key operational areas such as sales, recruitment, and product management. Problem Although business process management literature recognizes that digital technology can facilitate business process changes, the specific technology characteristics that enable these adaptations remain underexplored. Moreover, fast-growing digital ventures face severe operational scaling challenges that require continuous process flexibility and structure. Outcome - Identified four distinct patterns of business process change in digital ventures: creating minimum viable processes, creating encapsulated processes, creating centralized control flow integrations, and creating centralized data flow integrations.
- Revealed that digital ventures typically start with flexible, human-orchestrated processes supported by low-specificity tools before migrating to specialized enterprise systems to boost efficiency.
- Showed how proxy communication tools and centralized analytics systems are used to reduce system complexity and eliminate data silos in maturing ventures.

This study evaluates the depth and quality of domain-specific knowledge in ChatGPT (GPT-3.5) within the field of Information Systems (IS). Using an established IS competency framework, the researchers analyzed ChatGPT's performance on over 3,000 questions gathered from university IS courses and professional certification exams. Problem While Generative AI tools demonstrate impressive general academic abilities, their specific knowledge accuracy across specialized fields like Information Systems remains uncertain. Educators and industry professionals lack clear benchmarks regarding whether ChatGPT can reliably produce accurate IS content, pass professional certifications, or answer complex technical queries without hallucinating. Outcome - ChatGPT answered 65% to 85% of Information Systems queries correctly across all core framework areas, performing roughly at the level of an average student.
- The model performed significantly better on university course exams than on professional certification exams, failing to reach passing scores for the PMP and Microsoft Azure Administrator tests.
- ChatGPT achieved higher relative accuracy against class averages on closed-book exams compared to open-book or online exam environments where students had external resource access.
- While ChatGPT displayed broad coverage across diverse IS topics, its responses favored listing structured information over demonstrating expert-level critical thinking or complex problem-solving.

This study investigates how public sector organizations can build and leverage dynamic capabilities to effectively adopt and continuously adapt artificial intelligence (AI) technologies. The researchers utilized a qualitative multiple-case study design, gathering semi-structured interview data and secondary documentation across five German public sector organizations. Problem Public sector organizations face significant barriers when adopting AI, driven by complex technological, regulatory, and organizational uncertainties. Existing literature frequently takes a static approach to technology adoption and primarily focuses on private sector environments, leaving public sector managers without clear frameworks to handle ongoing socio-technical shifts. Outcome - The study empirically supports that AI adoption in public organizations is hindered by high levels of technological, regulatory, and organizational uncertainties, which require proactive management.
- The research empirically identifies and supports a framework of specific organizational microfoundations across three key dimensions: sensing (e.g., tracing employee expectations and monitoring regulatory landscapes), seizing (e.g., establishing AI governance and launching pilot projects), and transforming (e.g., active change management and promoting AI literacy).
- The findings empirically show that employee representation bodies (such as staff councils) often play a critical, gatekeeping role that can delay or hinder AI implementation decisions.
- The study acknowledges limitations, including its geographical focus on the German public sector and a limited observation timeframe from April 2024 to October 2025.

This study examines the economic impact of cryptocurrency regulation by analyzing Binance's February 2024 delisting of the privacy coin Monero. Utilizing the synthetic control method, the researchers construct a counterfactual scenario to evaluate short- and medium-term price effects. They complement this quantitative analysis with qualitative, semi-structured interviews with community stewards. Problem Regulators are placing strict compliance pressures on centralized exchanges to delist anonymity-enhancing coins, yet it remains highly debated whether these regulatory actions effectively reduce the value of these privacy-centric assets. Additionally, there has been limited empirical evidence on how such delisting events alter consumer choices and asset valuations over time. Outcome - Hypothesis 1 (delisting will cause an immediate negative price impact) was STATISTICALLY SUPPORTED: Monero's price was significantly lower (estimated at 63% to 72% lower) post-delisting compared to its synthetic counterfactual.\n- Hypothesis 2 (the negative price impact will diminish over time) was NOT SUPPORTED: Rather than recovering, the negative price impact intensified when longer time lags of up to 200 days were examined.\n- Limitations: The findings are restricted to a single delisting event of one specific privacy coin (Monero) and use trading price as an imperfect proxy for perceived value.

This study examines how providers of generative artificial intelligence systems manage system autonomy post-deployment. Utilizing an exploratory multiple-case study methodology, the researchers analyze seven active systems deployed in business-to-business, business-to-consumer, and internal organizational contexts. The analysis integrates qualitative data from 14 semi-structured interviews and direct system testing to model autonomy management practices. Problem Generative artificial intelligence systems can autonomously generate content and orchestrate workflows, but managing this autonomy introduces risks like hallucinations, security vulnerabilities, and operational errors. Although literature emphasizes the necessity of managing AI systems, there is a lack of empirical research showing how system providers balance control and autonomy in live environments. This leaves practitioners with limited guidance on managing post-deployment risks without losing system utility. Outcome - The study conceptualizes AI autonomy as consisting of two dimensions: generative autonomy (content creation) and workflow autonomy (process and system interaction), which is qualitatively supported by the case analysis.
- The research identifies 20 distinct post-deployment practices categorized under either harnessing value-adding autonomy (such as real-time auditing and semantic resource enrichment) or reducing unproductive autonomy (such as architectural weaving and resource circuit breakers), which is qualitatively supported by the case analysis.
- The analysis identifies 'averting effects' where efforts to manage one dimension of autonomy require maintaining the other, which is qualitatively supported by the case analysis.
- The study identifies a 'potential' relationship where reducing workflow autonomy creates a structural foundation that allows providers to further restrict generative autonomy, which is qualitatively supported by the case analysis.
- The findings are limited by the exploratory, qualitative nature of the seven cases, which does not quantitatively measure the operational efficiency, safety, or economic impacts of the individual practices, as well as the limited temporal autonomy of current systems.

This qualitative case study utilizes Actor-Network Theory to investigate how corporate actors shape and negotiate digital sustainability initiatives. By examining a specialized working group within a German insurance company, the researchers analyze the interactions and power relations between sustainability and IT/IS departments across four translation moments. The study provides practical insights on governance mechanisms to stabilize collaborative actor networks. Problem Organizations struggle to manage digital sustainability initiatives because they require aligning the distinct strategies, competencies, and interests of IT and sustainability departments. This tension often leads to misalignment, inefficiencies, and competing demands that hinder successful project implementation. Additionally, there is a lack of empirical understanding regarding how these diverse actors negotiate and shape digital sustainability governance in practice. Outcome - The case study supported that sustainability management acts as a stabilizer by establishing structural frameworks, securing senior executive backing, and fostering interdepartmental knowledge sharing.
- The analysis supported that IT/IS management often acts as a destabilizing force by imposing resource limitations, prioritizing short-term operational goals, and withholding full active engagement.
- The research demonstrated that the corporate digital sustainability actor-network remains unstable due to unresolved conflicts between sustainability goals and IT efficiency metrics.
- A limitation of these findings is their reliance on a single-case study of a German insurance company with an interview sample dominated by IT-department stakeholders.