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Exploring Digital Sustainability: A Multidimensional Framework for IS Scholarship
AI Processed Human Approved

How can organizations use digital technology to improve environmental performance and achieve economic benefits?

Dina Jill Maya Mertens, Thomas Haskamp, Jan vom Brocke
Exploring Digital Sustainability: A Multidimensional Framework for IS Scholarship
International Conference on Information Systems (ICIS) · 2025
Key findings
  • Synthesized literature into a multidimensional framework detailing the antecedents, moderators, and outcomes of digital sustainability.
  • Identified 14 sustainability-enabling logics showing how digital technology drives value creation, such as automatization, prediction, tokenization, and servitization.
  • Categorized consequences into economic benefits, enhanced green employee/customer behavior, and improved environmental performance, alongside critical considerations like digital energy consumption.
  • Proposed a research agenda around three main avenues: organizational transformation, product-level value creation mechanisms, and managing the duality/paradox of digital sustainability.
What it means for you
  • CIO / IT Executive: On Monday morning, initiate a review of your organization's current digital infrastructure against the 'antecedents' dimension of the digital sustainability framework. Prioritize identifying at least one area where technology can be leveraged for 'automatization' to reduce physical resource consumption (e.g., paperless workflows, virtual meetings replacing travel).
  • IT Manager: On Monday morning, identify one specific digital tool or process currently in use (e.g., cloud storage, software updates) and evaluate its potential 'digital energy consumption.' Research and propose to your team one tangible step to optimize its energy efficiency, such as scheduling software updates during off-peak hours or reviewing cloud storage policies for unused data.
  • Business Strategist: On Monday morning, examine your current product or service offerings and identify an opportunity to apply one of the 'sustainability-enabling logics' presented in the research. For example, explore how 'servitization' (offering a service instead of a product) could reduce material waste and extend product lifespan.
  • Researcher: On Monday morning, focus on the 'product-level value creation mechanisms' research agenda. Select one of the 14 identified logics (e.g., 'prediction') and brainstorm how it could be applied to develop a testable hypothesis related to reducing a specific environmental impact within an organizational context. Outline the initial steps for designing a pilot study.
  • Policymaker: On Monday morning, review existing digital infrastructure policies and identify areas where incentives can be introduced or strengthened to encourage 'enhanced green employee/customer behavior' through digital means. For example, consider proposing a policy that rewards teams who demonstrably reduce their digital carbon footprint through technology adoption.
Digital Sustainability, Digital Technology, Green IS, Green IT, Sustainable Value Creation, Literature Review
Using a Process Philosophy Perspective in Information Systems Research: Principles of Creative Evolution
AI Processed Human Approved

Why do traditional approaches to defining requirements cause large-scale IT projects to fail?

David Kreps, Frantz Rowe
Using a Process Philosophy Perspective in Information Systems Research: Principles of Creative Evolution
Journal of the Association for Information Systems · 2024
Key findings
  • 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.
What it means for you
  • CIO / IT Executive: On Monday morning, schedule a 30-minute "process thinking" brainstorming session with your heads of engineering and product development to discuss a recent project that faced significant challenges, focusing on how evolving user needs and unforeseen contextual shifts, rather than static requirements, might have been the root cause.
  • IT Manager: On Monday morning, initiate a 15-minute stand-up with your development team to specifically ask them to articulate one instance from the past week where a change in the team's understanding or a user's evolving need led to a necessary adaptation of their work, and how they managed that 'flow'.
  • Business Strategist: On Monday morning, review the 'success metrics' for your current key strategic initiatives and identify one metric that relies heavily on a static, predefined outcome. Then, draft a brief proposal to reframe that metric to capture ongoing adaptability and emergent value rather than just initial adherence to a plan.
  • Researcher: On Monday morning, dedicate an hour to re-reading your current research proposal, specifically highlighting any language that treats concepts as fixed entities. Then, rewrite one paragraph to emphasize the dynamic, experiential, and relational aspects of your subject matter, incorporating the principles of creative evolution.
  • Policymaker: On Monday morning, identify one current policy or regulation within your domain that is narrowly defined by static criteria or historical precedents. Then, draft a one-page memo outlining how an update to this policy could incorporate principles of ongoing adaptation and feedback loops to account for emergent technological and societal shifts.
process philosophy, ontology, duration, consciousness, free will, requirements engineering
Yoga Sutra-Based Memory Analysis of Information Systems Implementation
AI Processed Human Approved

How do stakeholders' past negative experiences affect their trust and adoption of new technology?

Ranjan Vaidya
Yoga Sutra-Based Memory Analysis of Information Systems Implementation
Communications of the Association for Information Systems · 2026
Key findings
  • 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.
What it means for you
  • CIO / IT Executive: On Monday morning, schedule a 30-minute discovery call with your Head of User Experience and your Chief Ethics Officer to brainstorm how to proactively identify and mitigate potential 'Samskara' (subliminal impressions) in upcoming system implementations by focusing on past negative stakeholder experiences.
  • IT Manager: On Monday morning, review the last three system user feedback reports for any recurring themes related to distrust or negative past experiences, and flag the top two recurring issues to investigate further for potential 'Alambana' (external triggers) in your current system.
  • Business Strategist: On Monday morning, draft a brief (one-page) internal memo to your team outlining the concept of 'Samskara' and its potential impact on technology adoption, and request them to identify one instance in recent projects where past negative impressions might have influenced user behavior.
  • Researcher: On Monday morning, begin drafting the introduction to your next research paper by clearly articulating the gap in current information systems research regarding the lack of focus on individual cognitive variations and Eastern philosophical perspectives on memory, using the Yoga Sutra framework as your proposed solution.
  • Policymaker: On Monday morning, initiate a discussion with your advisory board regarding the importance of embedding ethical and behavioral values into the design and implementation guidelines for all new government information systems, referencing the finding that failures often stem from a lack of adherence to these values, not culture.
Yoga, Information Systems, Memory, Behavioural Analysis, Samskara, ICT4D
Ethics-based ontology in ICT4D
AI Processed Human Approved

How do technology projects affect local communities, and what determines whether they succeed or fail?

Devinder Thapa
Ethics-based ontology in ICT4D
2025
Key findings
  • 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.
What it means for you
  • CIO / IT Executive: On Monday morning, schedule a 30-minute meeting with your ICT4D project leads to introduce the concept of an 'ethics-based ontology' and ask them to identify one project where technology is deeply integrated into user workflows and cultural practices. Assign them to bring initial thoughts on how the project's impact on lived experience and moral agency could be assessed in the next project review.
  • IT Manager: On Monday morning, review the support tickets and user feedback logs from the last quarter for your current ICT4D deployment. Specifically, look for recurring issues that are not purely technical but seem to relate to user frustration, resistance to adoption, or a perception of technology not fitting their daily routines. Flag these for further investigation with your team.
  • Business Strategist: On Monday morning, identify your organization's most critical ICT4D initiative. Draft a brief memo outlining how you plan to evaluate its success not just on efficiency metrics but also on its impact on the dignity, agency, and cultural integrity of the end-users. Prepare to discuss this revised evaluation framework with your team by the end of the week.
  • Researcher: On Monday morning, revisit the 'implementation challenges' section of the research paper and select ONE challenge (e.g., translating abstract concepts into practical design metrics). Begin drafting a short (1-page) proposal for how you might operationalize this concept for a future ICT4D project you are involved in, focusing on a tangible measurement.
  • Policymaker: On Monday morning, review existing national or organizational guidelines for technology procurement and deployment in development contexts. Identify sections that address user impact, cultural sensitivity, or long-term sustainability. Draft a short list of questions to investigate how these existing guidelines could be strengthened to incorporate considerations of lived experience and moral responsibility for technology's impact.
ICT4D, being-in-the-World, ethics of responsibility, ontology, development, philosophy
Gamification for Community Building: Click to Shake Hands
AI Processed Human Approved

What drives users to stay engaged with location-based games and build real-world communities?

Faisal Al Thani, Chadi Aoun, Savanid Vatanasakdakul
Gamification for Community Building: Click to Shake Hands
Pacific Asia Conference on Information Systems (PACIS) · 2025
Key findings
  • 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.
What it means for you
  • CIO / IT Executive: On Monday morning, allocate budget to pilot a location-based gamified application in one of our company's facilities, specifically focusing on fostering cross-departmental collaboration by integrating 'location incentives' for shared project spaces.
  • IT Manager: On Monday morning, schedule a meeting with your development team to discuss how to integrate elements like 'reward value' and 'achievement' into our existing internal communication platform to encourage more active participation and knowledge sharing.
  • Business Strategist: On Monday morning, initiate a brainstorming session with your marketing and product teams to identify opportunities to leverage 'network influence' and 'herd behavior' in upcoming product launches or community outreach initiatives, perhaps by creating exclusive early-access groups.
  • Researcher: On Monday morning, refine the survey instrument to include questions specifically measuring 'sense of belonging' and 'social motive' as distinct constructs, and prepare to recruit participants from diverse community groups for your next study.
  • Policymaker: On Monday morning, direct your staff to research successful public policy initiatives that have used location-based incentives or gamification to encourage citizen engagement with local services or community events, and identify potential applications for our jurisdiction.
Community Engagement, Gamification, Location-based games, Stickiness, Technology Adoption, Social Interaction
An Empirical Investigation of Cloud Computing and Environmental Performance of Nations: Implications for Shared Responsibility in Cloud Computing
AI Processed Human Approved

How does cloud computing affect energy use and carbon emissions across host and user countries?

Jooho Kim, Jiyong Park, Jason Dedrick
An Empirical Investigation of Cloud Computing and Environmental Performance of Nations: Implications for Shared Responsibility in Cloud Computing
Journal of the Association for Information Systems · 2025
Key findings
  • Access to cloud services generally enhances environmental efficiency by reducing national energy and carbon intensities associated with IT services.
  • Countries hosting cloud data centers experience higher local energy and carbon intensities due to heavy physical infrastructure demands.
  • Neighboring countries benefit from green cloud IT services without incurring adverse environmental costs on their local IT capital.
  • A shared responsibility model based on multilayered technology architecture is proposed to divide environmental accountability between cloud providers and users.
What it means for you
  • CIO / IT Executive: On Monday morning, initiate a review of our current cloud infrastructure's geographical distribution and identify which of our cloud services are hosted in countries that are net importers of cloud services (i.e., benefiting from efficiency gains) versus countries that are net hosts of data centers. Then, begin drafting an internal memo to your team outlining the need to assess the environmental footprint of our chosen cloud providers, specifically focusing on the geographical location of their data centers.
  • IT Manager: On Monday morning, compile a list of all cloud services currently utilized by your department and identify the primary cloud provider(s) for each. Then, locate and review the public documentation of these providers regarding their data center locations and any publicly available environmental sustainability reports or initiatives.
  • Business Strategist: On Monday morning, begin by identifying which key business processes or customer-facing services are heavily reliant on cloud computing. Then, investigate if these services are currently being delivered from cloud infrastructure located in countries that are significant importers of cloud services or from countries that are major hosts of data centers, and flag this for further cost-benefit analysis that includes potential environmental externalities.
  • Researcher: On Monday morning, start by drafting an email to your colleagues or supervisor proposing a follow-up study that quantifies the specific cross-border environmental impacts for a subset of countries using the methodologies outlined in this paper. Include a brief outline of the data you would need to gather, such as national IT service import/export data and detailed data center location information for key cloud providers.
  • Policymaker: On Monday morning, draft a preliminary policy brief for your relevant committee or ministry that summarizes the key findings of this research regarding the uneven distribution of environmental burdens from cloud computing. Specifically, highlight the need for international dialogue on shared responsibility and propose an initial step to investigate incorporating environmental footprint data into public procurement policies for cloud services.
Cloud Computing, IT Capital, IT Services, Digital Responsibility, Shared Responsibility, Sustainability
Role of Information Systems in Empowering Innovation Networks
AI Processed Human Approved

How can leaders set up and manage shared technology tools to support collaborative innovation across partner companies?

Sven-Volker Rehm, Lakshmi Goel, Iris Junglas
Role of Information Systems in Empowering Innovation Networks
MIS Quarterly Executive · 2015
Key findings
  • 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.
What it means for you
  • CIO / IT Executive: On Monday morning, initiate a review of our existing IS tools to identify at least three readily accessible platforms (e.g., cloud-based project management, secure file sharing, internal wiki) that can be quickly configured to support a collaborative work environment for our next cross-company project, prioritizing ease of adoption for all partners.
  • IT Manager: On Monday morning, assess the user-friendliness and integration capabilities of our current knowledge management system and identify any gaps. Then, plan a quick training session for a pilot group of users demonstrating how to tag and categorize project-related documents to build a rudimentary 'knowledge map' for our innovation network.
  • Business Strategist: On Monday morning, draft a brief outline of key innovation challenges and opportunities for our next external collaboration, and then identify which of the five identified IS functionalities (collaborative work environments, knowledge maps, knowledge spaces, innovation procedure toolkits, and social media platforms) would be most impactful in addressing these specific challenges, focusing on pragmatic tool selection.
  • Researcher: On Monday morning, begin cataloging and categorizing the publicly available 'innovation procedure toolkits' or best practice guides that could be shared or adapted for our current project, focusing on those with clear, step-by-step instructions that can be easily integrated into a shared digital space.
  • Policymaker: On Monday morning, draft a short proposal for an initiative that encourages or provides resources for SMEs to adopt cloud-based collaborative platforms, specifically highlighting how these platforms can support cross-organizational knowledge sharing and innovation within their respective industries.
Open Innovation, Innovation Networks, Information Systems Infrastructure, Small and Medium Enterprises, Collaborative Work Environments, Medical Device Industry
Using Information Systems in Innovation Networks: Uncovering Network Resources
AI Processed Human Approved

How can collaborating companies use shared information systems to align resources and develop new products?

Sven-Volker Rehm, Lakshmi Goel, Iris Junglas
Using Information Systems in Innovation Networks: Uncovering Network Resources
Journal of the Association for Information Systems · 2017
Key findings
  • 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.
What it means for you
  • CIO / IT Executive: On Monday morning, schedule a meeting with key innovation network partners to initiate discussions on standardizing or enhancing inter-organizational information system capabilities for resource visibility and alignment. Identify one critical shared process in an ongoing innovation project and task your team with exploring how a new information system feature could better represent and share partner resources for that process.
  • IT Manager: On Monday morning, review the existing inter-organizational information systems used by your company in innovation networks. Identify one area where information sharing or representation of partner capabilities is currently fragmented or manual, and develop a concrete proposal for a pilot project to improve this using a specific IS feature (e.g., a shared dashboard for resource availability).
  • Business Strategist: On Monday morning, identify one ongoing collaborative innovation project and map out the key physical, human, and organizational resources currently being leveraged from your network partners. Then, identify specific gaps in visibility or alignment of these resources and brainstorm one practical way an inter-organizational information system could be adapted or enhanced to address these gaps.
  • Researcher: On Monday morning, begin drafting a qualitative interview guide for your next set of case studies, focusing on questions that explore how specific inter-organizational information system features (representation, sharing, architecture, reach) enable or hinder the alignment of physical, human, and organizational resources for new product development.
  • Policymaker: On Monday morning, research existing government grants or incentives that support the adoption and development of inter-organizational information systems for small and medium-sized enterprises involved in collaborative innovation. Draft a one-page summary of potential policy interventions to encourage such adoption for a discussion with relevant industry stakeholders.
Network Resource, Dynamic Capability, Networking Capability, Resource-based View, Innovation Network, New Product Development
Artificial Normality: How Conversational Agents’ Perceived Humanness Inhibits Error Attribution and Preserves Satisfaction
AI Processed Human Approved

How does making conversational agents appear more human affect customer reactions when errors occur?

Alfred Benedikt Brendel, Sascha Lichtenberg, Fabian Hildebrandt & Alan R. Dennis
Artificial Normality: How Conversational Agents’ Perceived Humanness Inhibits Error Attribution and Preserves Satisfaction
Journal of Management Information Systems · 2026
Key findings
  • Greater perceived humanness in conversational agents preserves perceptions of situational normality when minor errors occur.
  • Preserved situational normality reduces users' tendency to attribute error cause to the agent, thereby safeguarding overall service satisfaction.
  • Errors made by humanlike conversational agents are processed similarly to errors made by human service agents, demonstrating that humanlike design can alleviate algorithm aversion.
What it means for you
  • CIO / IT Executive: On Monday morning, allocate budget to pilot the integration of more human-centric design principles (e.g., nuanced language, empathetic phrasing) into our core customer-facing conversational agent, focusing on areas where process errors are most common, to preemptively reduce user error attribution and maintain satisfaction.
  • IT Manager: On Monday morning, task your development team to review our current conversational agent's dialogue logs for instances of process errors and identify the top 3 most frequent error types to begin redesigning their responses with more humanlike cues (e.g., slight pauses, conversational fillers) to normalize the situation for users.
  • Business Strategist: On Monday morning, initiate a cross-functional workshop with marketing and product development to explore how to strategically position our conversational agents' perceived humanness in customer communications, emphasizing its role in creating a seamless experience even when minor technical glitches occur.
  • Researcher: On Monday morning, begin designing a follow-up study that experimentally manipulates specific humanlike conversational features (e.g., varying levels of politeness, acknowledgment of difficulty) within a simulated error scenario to quantify their direct impact on error attribution and situational normality, building upon the findings of Artificial Normality.
  • Policymaker: On Monday morning, convene a small working group to draft guidelines for the ethical development of conversational agents, recommending that AI design standards encourage the incorporation of humanlike qualities to enhance user experience and mitigate negative reactions to inevitable system errors, rather than solely focusing on pure efficiency.
Chatbot, Chatbot errors, situational normality, anthropomorphism, humanness, error attribution, user satisfaction
TIME TO TURN OFF THE LIGHTS: A SUCCESS FACTOR FRAMEWORK FOR ADVANCING HYPERAUTOMATION IN ORGANIZATIONS
AI Processed Human Approved

What are the key factors needed to successfully scale automation across an organization?

Lisa Straub, Christian Zeiß, Ulvi Ibrahimli, Christoph Tomitza, Benedikt Wirsing, Axel Winkelmann
TIME TO TURN OFF THE LIGHTS: A SUCCESS FACTOR FRAMEWORK FOR ADVANCING HYPERAUTOMATION IN ORGANIZATIONS
ECIS 2026 · 2026
Key findings
  • The survey results statistically supported all 15 success factors within the framework, achieving a high average agreement score of 6.05 out of 7, with 93.2% of respondents selecting positive agreement.
  • 'Leadership Commitment' (SF3) and 'Communication and Trust Building' (SF4) received the highest levels of overall agreement, indicating strong statistical support.
  • 'Strategic Partner Collaboration' (SF15) and 'Customer Integration' (SF13) received statistically supported relevance, although they had comparatively lower overall agreement scores.
  • The study's generalizability is limited by the German context of the initial qualitative interviews, a modest quantitative survey sample size (n = 103), and its reliance on subjective assessments rather than objective performance metrics.
What it means for you
  • CIO / IT Executive: On Monday morning, schedule a 30-minute alignment meeting with business unit heads to establish a joint 'Hyperautomation Governance Board' to audit all active shadow-IT automation tools (like RPA and low-code apps) and map them against your long-term IT integration roadmap to prevent fragmented technical debt.
  • IT Manager: On Monday morning, block out two hours to audit your current automation deployment backlog and draft a standardized 'API-First Integration Checklist' that your development team must use to ensure new automations do not bypass APIs and create system incompatibilities.
  • Business Strategist: On Monday morning, select one high-volume customer-facing workflow and schedule a scoping call with a key strategic partner to co-design an integrated, automated data-sharing process, directly applying the 'Customer Integration' (SF13) and 'Strategic Partner Collaboration' (SF15) success factors.
  • Researcher: On Monday morning, draft a research proposal and outreach email to target three non-German, US-based enterprises to secure pilot sites for a comparative case study that measures objective operational KPIs (such as transaction error rates and processing speed) to validate the subjective findings of the 15-factor framework.
  • Policymaker: On Monday morning, draft an amendment to your organization's IT Procurement Policy mandating that any new business unit purchasing low-code or RPA tools must submit a 'Systemic Compatibility and Trust Impact Assessment' addressing how the tool aligns with the enterprise IT architecture and employee trust-building guidelines.
Hyperautomation, Transformation Management, Organizational Change, Success Factor Framework, Affordance Theory
ARE THE REGULATORS WINNING THE FIGHT WITH ANONYMITY-ENHANCING COINS? STUDYING BINANCE’S EUROPEAN DELISTING OF MONERO AS A NATURAL EXPERIMENT
AI Processed Human Approved

How does delisting a privacy coin from a major exchange impact its price over time?

Robin Renwick, Rob Gleasure
ARE THE REGULATORS WINNING THE FIGHT WITH ANONYMITY-ENHANCING COINS? STUDYING BINANCE’S EUROPEAN DELISTING OF MONERO AS A NATURAL EXPERIMENT
ECIS 2026 · 2026
Key findings
  • 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.
What it means for you
  • CIO / IT Executive: Audit our organization's digital asset holdings and treasury to identify any exposure to privacy coins like Monero, and immediately initiate a migration plan to convert these assets to compliant, liquid cryptocurrencies to avoid permanent valuation loss from regulatory delistings.
  • IT Manager: Update network monitoring tools and firewall rules to detect and block any Monero nodes, mining scripts, or wallet connections on company-owned infrastructure to prevent compliance violations arising from tightening centralized exchange regulations.
  • Business Strategist: Review our payment gateway integrations and product roadmap to remove Monero or other privacy coins as accepted payment methods, and pivot our privacy-focused initiatives toward compliant layer-2 scaling solutions (like Zero-Knowledge rollups) that satisfy regulators.
  • Researcher: Draft a new research proposal to apply the synthetic control method to other privacy-centric assets (like Zcash or Dash) across different geographic regions, incorporating decentralized exchange (DEX) trading volumes to test if the value shifted off centralized order books.
  • Policymaker: Draft an amendment to the national crypto-asset regulatory framework to mandate that all registered centralized exchanges delist anonymity-enhancing coins, citing this empirical evidence that exchange-level bans are highly effective at permanently reducing these assets' market value and liquidity.
Cryptocurrencies, Monero, Privacy, Regulation, Natural Experiment, Synthetic Control Method
ACTOR-NETWORKS IN CORPORATE DIGITAL SUSTAINABILITY INITIATIVES
AI Processed

How do IT and sustainability departments interact to shape corporate digital sustainability initiatives?

David Stanlein, Lea Püchel, Enni Alina Juntunen, Tobias Brandt
ACTOR-NETWORKS IN CORPORATE DIGITAL SUSTAINABILITY INITIATIVES
ECIS 2026 · 2026
Key findings
  • 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.
What it means for you
  • CIO / IT Executive: Schedule a 30-minute meeting with the Head of Sustainability to co-design and integrate a 'sustainability impact score' directly into the IT department's project prioritization framework, ensuring green metrics are evaluated alongside traditional cost and efficiency KPIs.
  • IT Manager: Review your team's current project backlog and formally assign a senior systems engineer as the dedicated 'Green IT Liaison' to attend the sustainability working group's bi-weekly meetings, ensuring technical resource constraints are communicated early.
  • Business Strategist: Draft a charter for a joint IT-Sustainability Steering Committee that outlines a shared governance model, specifically defining a conflict-resolution protocol for when short-term IT cost-cutting clashes with long-term carbon reduction targets.
  • Researcher: Draft a research proposal for a multi-case study targeting non-financial sectors (such as manufacturing or retail) that intentionally oversamples sustainability managers to address the IT-biased, single-case limitation of the existing literature.
  • Policymaker: Initiate a draft for a voluntary corporate digital sustainability reporting template that requires firms to disclose how their IT infrastructure procurement policies align with national green transition targets.
digital sustainability, actor-network theory, case study, IT/IS alignment, IT/IS management
STRUCTURING READINESS FOR AI INNOVATION: THE ROLE OF THE DESIGN CHALLENGE BRIEF AS A COORDINATION AND GATEKEEPING ARTEFACT
AI Processed Human Approved

How can teams evaluate whether an artificial intelligence project is ready to launch?

Jennifer Hehn, Franziska Anna Röckel, Benjamin van Giffen
STRUCTURING READINESS FOR AI INNOVATION: THE ROLE OF THE DESIGN CHALLENGE BRIEF AS A COORDINATION AND GATEKEEPING ARTEFACT
ECIS 2026 · 2026
Key findings
  • The study outlines a preliminary three-phase qualitative model for establishing AI project readiness: divergent exploration, negotiation/translation, and convergent alignment, though these findings are descriptive and lack statistical testing.
  • The Design Challenge Brief is shown to act as a gatekeeping artifact that structures readiness reviews and allows teams to selectively revisit earlier project assumptions without resetting the entire process.
  • The study is limited by its small qualitative sample of five projects and its setting within a structured, university-led innovation lab, which may restrict generalizability to less-structured corporate settings.
What it means for you
  • CIO / IT Executive: Draft and mandate a standard 'Design Challenge Brief' template that all AI project champions must complete and get approved before receiving formal project launch funding.
  • IT Manager: Gather your AI project team for a 1-hour workshop to map your current pre-project planning stage to the three phases of divergent exploration, negotiation/translation, and convergent alignment, explicitly documenting how you will handle fluid data availability.
  • Business Strategist: Audit your pipeline of proposed AI initiatives and flag any project that has not yet completed a collaborative 'Design Challenge Brief' to prevent launching projects with high uncertainty around non-deterministic outcomes.
  • Researcher: Draft a research proposal and survey instrument to test the generalizability of the three-phase AI readiness model across a quantitative sample of 100+ corporate AI projects outside of academic lab settings.
  • Policymaker: Integrate a 'Design Challenge Brief' gatekeeping requirement into your public sector AI procurement and funding frameworks to ensure public agencies evaluate data readiness and outcome uncertainties before awarding AI contracts.
AI innovation, readiness work, design challenge brief, boundary objects, gatekeeping
FROM BROWN TO GREEN: HOW AI-DRIVEN TRANSFORMATION ENABLES BUSINESS MODEL RECONFIGURATION IN THE TWIN TRANSITION
AI Processed Human Approved

How can businesses use artificial intelligence to transition their business models toward sustainability?

Elaine Mosconi, Marie-Claude Boudreau
FROM BROWN TO GREEN: HOW AI-DRIVEN TRANSFORMATION ENABLES BUSINESS MODEL RECONFIGURATION IN THE TWIN TRANSITION
ECIS 2026 · 2026
Key findings
  • The AI-enabled platform qualitatively supported a business model shift from transactional, time-based billing to recurring, outcome-based services focused on asset durability and lifecycle performance.
  • A strategic alignment gap was identified: executives framed the AI and sustainability transformation as radical, whereas operational managers experienced it as incremental.
  • Successful scaling of the AI initiative qualitatively depended on adaptive governance (looser decision-making, rapid experimentation), pre-requisite capability building in data engineering, and strong leadership support.
  • Key organizational trade-offs and barriers emerged, specifically related to skills gaps, legacy system integration, high energy consumption of AI models, and delayed financial return on investment.
  • Limitation: The findings of this study are based on a single qualitative case study of a Canadian engineering firm, which may limit the direct generalizability of the results to other industries or regions.
What it means for you
  • CIO / IT Executive: Initiate an audit of legacy data pipelines to identify bottlenecks for AI integration, and establish a 'green sandbox' environment with relaxed governance rules to allow developers to experiment with asset-durability algorithms while tracking model energy consumption.
  • IT Manager: Hold a 30-minute team sync to map out existing data engineering skill gaps and assign one developer to clean and structure a single historical dataset of asset lifecycle performance to prepare it for future AI model training.
  • Business Strategist: Draft a pilot proposal to transition one high-trust client from hourly billing to a recurring, outcome-based pricing model focused on extending their asset lifecycle, and schedule a meeting with operational managers to align on realistic, incremental milestones.
  • Researcher: Design a survey instrument targeting business and IT leaders across multiple industries to quantitatively test whether the perceptual gap between executive (radical) and operational (incremental) views on AI-driven green transitions exists outside of the engineering sector.
  • Policymaker: Draft a policy brief proposing a targeted grant program that subsidizes data-engineering upskilling and offsets energy-efficiency auditing costs for mid-sized firms adopting AI-enabled, sustainable business models.
Twin Transition, Artificial Intelligence, Sustainability, Business Model, Dynamic Capabilities
THE AI-ENABLED CIRCULAR ECONOMY: EXTRACTING AND SYNTHESIZING DESIGN KNOWLEDGE
AI Processed

How can organizations design and use artificial intelligence to support circular economy practices?

Linda Sagnier Eckert, Christoph Hoppe-Ludwig, Timo Strohmann, Anne Ixmeier, Daniel Heinz
THE AI-ENABLED CIRCULAR ECONOMY: EXTRACTING AND SYNTHESIZING DESIGN KNOWLEDGE
ECIS 2026 · 2026
Key findings
  • Synthesized design knowledge from 99 empirically grounded studies supported four distinct meta-principles for AI-enabled circular economies.
  • Meta-Principle 1 (AI for slowing resource loops) is supported by 15 empirical studies showing predictive AI models successfully forecast asset degradation to trigger life-extending actions.
  • Meta-Principle 2 (AI for closing resource loops) is supported by 29 empirical studies showing integrated computer vision and robotic sorting systems reliably classify and separate materials.
  • Meta-Principle 3 (AI for narrowing resource loops) is supported by 18 empirical studies showing hybrid optimization models successfully reduce resource and energy consumption.
  • Meta-Principle 4 (AI for socio-technical orchestration) is supported by 37 empirical studies demonstrating that AI can drive the organizational dynamic capabilities needed to coordinate circular workflows.
  • A recognized limitation is that the corpus is restricted to English-language, peer-reviewed publications from the last five years, and the synthesized principles have not been longitudinally tested in new field environments.
What it means for you
  • CIO / IT Executive: Schedule a 9:00 AM workshop with your Enterprise Architecture and Sustainability teams to map your organization's existing data infrastructure against the study's two-layered framework, explicitly linking your micro-level AI model choices with macro-level organizational capabilities to support circular workflows.
  • IT Manager: Initiate a pilot project on your team's backlog to deploy a predictive maintenance model on a single class of high-wear manufacturing assets, using telemetry data to forecast asset degradation and automatically trigger life-extending maintenance tickets.
  • Business Strategist: Conduct a value-chain audit to identify where materials are lost, and draft a business case for integrating computer vision and robotic sorting systems at your primary waste-handling facility to automate material classification and close resource loops.
  • Researcher: Draft a research proposal for a 12-month longitudinal field study in partnership with a local electronics manufacturer to empirically validate the paper's four synthesized meta-principles in a real-world operational environment, addressing the literature's lack of longitudinal testing.
  • Policymaker: Draft a policy memo proposing a targeted grant program that provides R&D tax credits to industrial recycling facilities that implement integrated computer vision and automated sorting systems to improve regional material recycling rates.
Circular economy, Artificial intelligence, Design knowledge, Meta-Synthesis, Design science research, Dynamic capabilities
ORCHESTRATION PARADOXES IN NATIONAL QUANTUM COMPUTING INNOVATION ECOSYSTEMS
AI Processed Human Approved

What competing tensions and trade-offs do leaders face when guiding national quantum computing ecosystems?

Jori Taipale, Olli Tyrväinen, Tuure Tuunanen, Joel Mero, Teiko Heinosaari
ORCHESTRATION PARADOXES IN NATIONAL QUANTUM COMPUTING INNOVATION ECOSYSTEMS
ECIS 2026 · 2026
Key findings
  • Organizing tensions were identified as the most frequent paradox, specifically focusing on the trade-offs between collaboration vs. resource competition and guidance vs. flexibility.
  • Performance tensions emerged regarding resource allocation between software vs. hardware development and building a shared vision vs. individual firm survival.
  • Belonging tensions highlighted a 'godfather' paradox, where the ecosystem must balance the state's role as a major supportive funder and customer with the ultimate goal of corporate independence.
  • Learning tensions were characterized by the challenge of managing multi-talent knowledge development versus narrow technology specialization.
  • The study is limited by its single qualitative case context in Finland with a small sample of 15 informants, requiring caution when applying these findings to other national contexts.
What it means for you
  • CIO / IT Executive: Schedule a 9:00 AM meeting with your lead enterprise architect to audit your current quantum-readiness roadmap, establishing a formal policy that divides software development and hardware access investments 50/50 to hedge against the performance tension of committing prematurely to a single unproven hardware stack.
  • IT Manager: Create a bi-weekly 1-hour 'Quantum Cross-Training' slot in your team's calendar starting this Friday, pairing your specialized quantum physics PhDs with your generalist cloud engineers to address the learning tension between narrow technical specialization and broad-based systems integration.
  • Business Strategist: Perform a revenue dependency audit to calculate the percentage of your quantum business unit's funding derived from state grants versus commercial clients, and draft a pitch deck for two private-sector pilots to actively transition away from 'godfather' state-funding reliance.
  • Researcher: Draft a pre-competitive collaboration agreement template to send to a peer researcher at a competing institution, outlining a shared framework for baseline algorithm testing while clearly defining IP boundaries to manage the tension of collaboration versus resource competition.
  • Policymaker: Draft a revision for the upcoming national quantum funding round guidelines that introduces a 'co-investment requirement,' mandating that state-funded consortia secure at least 25% of their budget from private corporate buyers to counter the 'godfather' dependency paradox.
Ecosystem orchestration, Paradox theory, Quantum computing innovation ecosystem, Explorative case study, Interpretive qualitative research
A CONTEXT-AWARE URBAN HEAT COMPANION FOR PROSUMER PARTICIPATORY SENSING AND JUST-IN-TIME ADAPTIVE INTERVENTION
AI Processed Human Approved

Can real-time advice keep citizens engaged in collecting local heat data using wearable sensors?

Niklas von Heyden, Florian Onur Kuhlmeier, Jeffrey Parsons, Alexander Maedche
A CONTEXT-AWARE URBAN HEAT COMPANION FOR PROSUMER PARTICIPATORY SENSING AND JUST-IN-TIME ADAPTIVE INTERVENTION
ECIS 2026 · 2026
Key findings
  • The Heat Companion system demonstrated technical reliability, capturing micro-climate variations with an average temperature deviation of +1.9 °C and relative-humidity deviation of -6.9% compared to the nearest official weather stations.
  • High system engagement was observed during the field study, with participants opening 93% of the 690 generated recommendations and responding with a median time of 14.2 seconds.
  • Engagement and compliance varied across recommendation domains, with short, actionable prompts like 'Hydration & Cooling' achieving a 33.6% follow rate, while broader domains like 'Social Care' had a 5% follow rate.
  • Perceived relevance of feedback was higher during warmer afternoon hours (median rating of 4.0 out of 5) than in the morning (median rating of 2.0 out of 5), suggesting relevance aligns with actual heat exposure.
  • Due to the small sample size (8 participants) and exploratory feasibility design, no inferential statistical tests were conducted to confirm the statistical significance of the behavioral changes, which remains a key limitation.
What it means for you
  • CIO / IT Executive: Authorize a pilot project to integrate on-device, context-aware processing capabilities into the company's mobile application roadmap, shifting away from centralized cloud polling to enable low-latency, real-time push notifications driven by on-device sensor data.
  • IT Manager: Update the push-notification system's scheduling logic to restrict alerts to high-relevance afternoon windows (12:00 PM to 4:00 PM) and truncate copy to short, single-action prompts like 'Hydration & Cooling' to maximize user compliance rates.
  • Business Strategist: Redesign the incentive structure of our data-collection app to offer immediate, personalized 'micro-utility' benefits—such as real-time local comfort scores—directly to the user upon data submission, mitigating long-term participation fatigue.
  • Researcher: Draft a research proposal and power analysis for a randomized controlled trial (RCT) with a target sample size of at least 150 participants to statistically validate the behavioral impacts and compliance rates of the Heat Companion's adaptive interventions.
  • Policymaker: Draft a municipal initiative to equip outdoor public-sector employees (such as postal or sanitation workers) with wearable micro-climate sensors to map urban heat islands where official weather stations lack coverage.
Citizen-Centric Green IS, Participatory Sensing, Context-Aware Computing, Just-In-Time Adaptive Interventions, Urban Climate Adaptation
TOWARDS DESIGN PRINCIPLES FOR TEACHING INDUSTRY 4.0 COMPETENCIES TO CS/IS STUDENTS
AI Processed

How can educators effectively teach modern industrial software skills without expensive physical equipment?

Felix Salcher
TOWARDS DESIGN PRINCIPLES FOR TEACHING INDUSTRY 4.0 COMPETENCIES TO CS/IS STUDENTS
ECIS 2026 · 2026
Key findings
  • Eight design principles were established, emphasizing virtualization, containerization, and problem-based learning cases as alternatives to expensive learning factories.\n- Preliminary course evaluation yielded positive descriptive feedback, with a mean rating of 4.43 out of 5 across satisfaction categories.\n- No formal statistical significance tests were performed due to the pilot nature of the study and the small, specific evaluation sample.\n- The pilot is limited by a very small sample size (9 respondents from a single cohort) and relies on subjective student perceptions rather than objective competency-based assessments.\n- Students noted difficulty adapting to the course's fast pace and programming requirements, highlighting a need for aligned prerequisites.
What it means for you
  • CIO / IT Executive: Direct your enterprise architecture team to draft a transition plan to replace physical IT hardware training labs with virtualized, containerized sandbox environments (e.g., Docker/Kubernetes) to reduce infrastructure costs and align onboarding with modern Industry 4.0 software architectures.
  • IT Manager: Review the programming prerequisites of your junior developers and assign them a structured, hands-on troubleshooting task using a containerized microservice mock-up on Monday morning to assess their readiness for complex Industry 4.0 integration projects.
  • Business Strategist: Reallocate a portion of next quarter's talent development budget away from high-cost physical equipment training and toward scalable, software-based virtual simulators to cost-effectively build digital twin and data architecture competencies.
  • Researcher: Draft a research proposal to conduct a multi-institution comparative study on these eight design principles, incorporating objective pre- and post-intervention technical testing rather than relying on subjective student feedback to measure competency gains.
  • Policymaker: Create a state-level educational grant initiative that incentivizes higher education institutions to update computer science curricula with virtualization-based Industry 4.0 frameworks, shifting funding priority away from physical learning factories.
Design Principles, Design Science Research, Industry 4.0, Smart Manufacturing
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