AIS Logo

Got a research question instead? Ask AIS Insights

Browse the library 43 papers

All Artificial Intelligence & Automation Information Systems & Management Human-Computer Interaction Data Analytics & Big Data Digital Transformation & Strategy Cybersecurity & Privacy Cloud & Infrastructure E-Commerce & Digital Platforms Operations & Supply Chain Sustainability & Green IS
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
SUPPORT OR SUBSTITUTION: HOW CHATGPT AFFECTS COGNITIVE LOAD, OWNERSHIP, AND PERFORMANCE IN PROBLEM-SOLVING
AI Processed

How does using ChatGPT affect worker performance, workload, and their sense of ownership over problem-solving tasks?

Leonie Rebecca Freise, Josephine Mago Moritz
SUPPORT OR SUBSTITUTION: HOW CHATGPT AFFECTS COGNITIVE LOAD, OWNERSHIP, AND PERFORMANCE IN PROBLEM-SOLVING
ECIS 2026 · 2026
Key findings
  • Both ChatGPT-only access and ChatGPT with a prompting guide significantly improved task performance compared to the control group (Supported).\n- ChatGPT access significantly reduced temporal demand, but neither ChatGPT condition significantly reduced mental demand, and there was no significant effect of cognitive load on task performance (Partially Supported).\n- Both experimental conditions significantly reduced psychological ownership of the task outcome (Supported).\n- Reduced psychological ownership did not significantly impair task performance in this study (Not Supported).\n- Higher AI literacy significantly moderated and weakened the negative effects of AI access on temporal demand, and partially weakened the negative effect of the prompting guide on psychological ownership (Partially Supported).\n- The study's limitations include a modest sample size of 136 participants, a single-session experimental setting, and a reliance on self-reported measures.
What it means for you
  • CIO / IT Executive: Sign off on the procurement and scheduling of a mandatory 'AI Literacy and Collaborative Prompting' training program for all departments currently using generative AI, rather than just distributing licenses, to actively counter the erosion of psychological ownership and help staff manage cognitive load.
  • IT Manager: Schedule a 30-minute team meeting to establish a 'Human-in-the-Loop' workflow review protocol, requiring team members to explicitly document, edit, and present their personal contributions to any ChatGPT-generated deliverables to re-establish psychological ownership over their outcomes.
  • Business Strategist: Draft a proposal to revise departmental key performance indicators (KPIs), shifting the metrics of success from speed and volume (temporal savings) to qualitative, human-curated excellence to prevent employees from disengaging and treating their roles as outsourced, low-ownership tasks.
  • Researcher: Write a research proposal for a multi-week longitudinal field study with a cohort of at least 250 participants to track whether the observed short-term reduction in psychological ownership from AI usage leads to long-term employee disengagement or performance declines over time.
  • Policymaker: Publish a revised corporate governance policy that defines a 'Responsible Authorship' standard, mandating that the human employee remains 100% accountable for the accuracy and quality of AI-assisted outputs to prevent the dilution of organizational responsibility.
Generative Artificial Intelligence, Human-AI Collaboration, Cognitive Load, Psychological Ownership, AI Literacy, Task Performance
THE ANATOMY OF A DESIGN CHALLENGE FOR INITIATING AI INNOVATION
AI Processed Human Approved

How should teams structure initial challenges to successfully launch AI projects?

Franziska Anna Röckel, Benjamin van Giffen, Andreas Janson, Jennifer Hehn
THE ANATOMY OF A DESIGN CHALLENGE FOR INITIATING AI INNOVATION
ECIS 2026 · 2026
Key findings
  • The study empirically validated a structural anatomy for the Design Challenge consisting of four robust elements (verb, object of innovation, target group, context) and three plastic elements (internal data, technology, potential), which was supported across all 42 cases analyzed.
  • The robust elements were validated to successfully create a stable, shared identity and common direction among diverse team members, acting as a center of authority.
  • The plastic elements were shown to successfully absorb technological uncertainty, providing a flexible framework for teams to negotiate and adapt to AI's emergent capabilities over time.
  • The qualitative analysis identified three distinct nuances in shaping the 'object of innovation' (modular, abstract, and space) that guide teams toward either incremental or more radical innovation pathways.
What it means for you
  • CIO / IT Executive: Mandate that all upcoming AI project proposals use a standardized 'Design Challenge' charter template structured around the 4 robust elements (verb, object of innovation, target group, context) and 3 plastic elements (internal data, technology, potential), explicitly forbidding teams from locking in a rigid technical architecture in their initial pitch.
  • IT Manager: Gather your interdisciplinary project team for a 60-minute workshop on Monday morning to co-create a 'Design Challenge' statement, explicitly defining the stable 'robust' elements to align the business and tech members, while leaving the 'plastic' elements (like specific data sources and AI models) open as flexible targets to be negotiated as the project progresses.
  • Business Strategist: Review your company's AI project portfolio on Monday morning and intentionally rewrite the 'object of innovation' for each project: frame them as 'modular' if you need predictable, incremental improvements, or rewrite them as 'space-based' (e.g., focused on broad capabilities) if you want to push the team toward radical, disruptive business model innovation.
  • Researcher: Update your qualitative coding scheme for ongoing field studies of AI adoption to track how frequently and at what project stages teams modify the 'plastic' elements (internal data, technology, potential) versus the 'robust' elements of their project charters to measure the empirical threshold where technological uncertainty triggers project misalignment.
  • Policymaker: Revise the application guidelines for the upcoming public AI innovation grant cycle to replace rigid 'technical specifications' requirements with a mandatory 'Design Challenge' framework, scoring applicants on the clarity of their robust elements (target group, context) and the adaptive flexibility of their plastic elements (data and technology integration plans).
Design Challenge, AI Innovation, Boundary Object, Anatomy, Interdisciplinary Collaboration, Problem Formulation
WHEN WE CANNOT STOP THE DATA FLOW: THE EMOTIONAL LIFE OF DATA IN A CHILDREN’S DAYCARE CENTER
AI Processed

How does continuous digital reporting affect emotional pressure, trust, and staff autonomy in childcare centers?

Lea Püchel, Tobias Brandt
WHEN WE CANNOT STOP THE DATA FLOW: THE EMOTIONAL LIFE OF DATA IN A CHILDREN’S DAYCARE CENTER
ECIS 2026 · 2026
Key findings
  • This is a qualitative, ethnographic case study, meaning it does not test quantitative hypotheses or report statistical significance values.
  • The qualitative data supports a sequential three-stage framework showing how digital opportunity transitions into perceived control and safety, data reassurance dependency, and ultimately internalized data-driven surveillance.
  • In the highly digitalized center, continuous digital updates successfully provided a feeling of safety but created an addictive loop where any absence of data was interpreted as a signal of risk.
  • Educators did not openly resist the system but instead practiced adaptive, situated compliance, adjusting their timing, tone, and messaging to meet platform expectations.
  • The comparative boundary case with lower-intensity digital reporting demonstrated that a slower communication rhythm can temper the emergence of the full data-dependency cycle.
What it means for you
  • CIO / IT Executive: On Monday morning, reconfigure your enterprise communication and tracking platforms to aggregate non-critical status updates into a single daily digest at 4:00 PM, rather than allowing real-time push notifications, to actively break the expectation of continuous monitoring.
  • IT Manager: On Monday morning, audit the daycare platform's dashboard interface and replace all default automatic 'No Data' warning flags or empty progress bars with a neutral status indicator to eliminate the false perception of operational risk during quiet hours.
  • Business Strategist: On Monday morning, draft and distribute a 'Communication Cadence Agreement' to clients that explicitly sets the expectation of only two digital updates per day, actively framing this slower rhythm as a premium service feature that ensures staff are focused on active care rather than screens.
  • Researcher: On Monday morning, draft a research proposal to conduct a comparative diary study of frontline workers in relationship-heavy sectors like eldercare, specifically measuring the psychological friction and time spent on 'situated compliance' tasks versus actual patient care.
  • Policymaker: On Monday morning, draft a policy amendment for child and eldercare labor standards that prohibits the use of real-time telemetry and continuous digital logging frequency as metrics for assessing staff performance and regulatory compliance.
Data work, future of work, reporting systems, relational data, data dependency
UNPACKING THE ROLE OF INDIVIDUALS IN PROCESS MINING: A LITERATURE REVIEW AND RESEARCH FRAMEWORK
AI Processed

How do individual user behaviors and attitudes impact the business value generated from process mining?

Julian Dyong, Sandro Franzoi, Jan vom Brocke
UNPACKING THE ROLE OF INDIVIDUALS IN PROCESS MINING: A LITERATURE REVIEW AND RESEARCH FRAMEWORK
ECIS 2026 · 2026
Key findings
  • The review identifies and establishes user behavior, usage patterns, and affect (such as uncertainty and trust) as the three core elements constituting the individual level of process mining, supported by the synthesized literature.
  • The analysis reveals that technical, individual, and organizational contingency factors systematically influence user behavior and affect; for example, data inaccuracies undermine user trust, while formal training and methodological guidance support correct execution.
  • Individual behaviors and affective states are shown to directly impact value outcomes, with structured behaviors like hypothesis testing decreasing analysis duration and increasing the quality of insights.
  • Key limitations of the study include its reliance on a limited sample of 23 reviewed papers, a static framework that does not capture sequential or temporal dynamics, and a lack of true inter-coder reliability during the qualitative coding process.
What it means for you
  • CIO / IT Executive: Initiate a data audit of the source pipelines feeding your enterprise process mining tools to eliminate data discrepancies, directly addressing the research finding that data inaccuracies severely undermine user trust and derail tool adoption.
  • IT Manager: Add a mandatory 'Hypothesis-First' template to your team's process mining workflow on Monday morning, requiring analysts to document their specific diagnostic hypothesis before running queries to enforce structured behavior and reduce analysis duration.
  • Business Strategist: Redesign the process mining ROI dashboard to measure actual business value outcomes (e.g., cost savings from process changes) rather than user log-in frequency, linking individual analytical insights directly to operational KPIs.
  • Researcher: Draft a research design for a longitudinal study tracking 20 process mining analysts over six months to capture the sequential and temporal dynamics of user affect and trust, directly addressing the static limitations of current literature.
  • Policymaker: Establish an internal organizational standard mandating that no department may deploy process mining software without integrating a formal training and methodological guidance program, ensuring compliant and high-quality data execution.
Process Mining, Individual Level, Literature Review, Research Framework, Value Creation, User Behavior
Corporate Nomads: Working at the Boundary Between Corporate Work and Digital Nomadism
AI Processed Human Approved

How can companies and employees successfully negotiate a nomadic lifestyle alongside permanent corporate employment?

Julian Marx, Milad Mirbabaie, Stefan Stieglitz
Corporate Nomads: Working at the Boundary Between Corporate Work and Digital Nomadism
Journal of the Association for Information Systems · 2025
Key findings
  • The study develops a three-phase process model (splintering, calibrating, and harmonizing) that explains how corporate nomads and their organizations successfully negotiate this new work arrangement.
  • The integration of corporate nomads is not a one-sided decision but a mutual process of 'boundary work' requiring engagement, negotiation, and trade-offs from both the employee and the company.
  • Corporate nomads operate as individual outliers who change their personal work boundaries (e.g., location and time) without transforming the entire organization's structure.
  • Information Technology (IT) is crucial in managing the inherent tensions of this lifestyle, helping to balance organizational control with employee autonomy and enabling integration from a distance.
Corporate Nomads, Digital Nomads, Boundary Work, Digital Work, Information Systems
REGULATING EMERGING TECHNOLOGIES: PROSPECTIVE SENSEMAKING THROUGH ABSTRACTION AND ELABORATION
AI Processed

How can governments and industry leaders create effective rules for emerging technologies without stifling innovation?

Stefan Seidel, Christoph J. Frick, Jan vom Brocke
REGULATING EMERGING TECHNOLOGIES: PROSPECTIVE SENSEMAKING THROUGH ABSTRACTION AND ELABORATION
MIS Quarterly · 2025
Key findings
  • Creating effective regulation for new technologies is a process of 'collective prospective sensemaking,' where diverse stakeholders build a shared understanding over time.
  • This process relies on two interrelated activities: 'abstraction' and 'elaboration'. Abstraction involves generalizing the essential properties of a technology to create flexible, technology-neutral rules that encourage innovation.
  • Elaboration involves specifying details and requirements to provide legal certainty and protect users.
  • Through this process, the regulatory target can evolve significantly, as seen in the case study's shift from regulating 'blockchain/cryptocurrency' to a broader, more durable law for the 'token economy' and 'trustworthy technology'.
Technology regulation, prospective sensemaking, sensemaking, institutional construction, emerging technology, blockchain, token economy
Showing all 43 podcasts