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AI Processed Human Approved

How can organizations turn digital activity data into actionable solutions for improving their business processes?

Jan vom Brocke, Sandro Franzoi, Sophie Hartl, Thomas Grisold

The Process of Process Science – Generating Actionable Insights from Digital Trace Data

2026

Key findings

Defines three core methodological principles for process science: contextual grounding, iterative reasoning, and the integration of computational and human sense-making.
Proposes three interconnected, recursive cycles of inquiry: a descriptive cycle (from scope via data to description), an explanatory cycle (from analysis via pattern to explanation), and a prescriptive cycle (from intervention via evaluation to prescription).
Demonstrates the practical execution of these cycles through a real-world case study of a financial institution's digital customer onboarding process.
Provides concrete guidance for researchers and practitioners on combining qualitative insights with computational techniques to move from descriptive analytics to actionable organizational interventions.

What it means for you

CIO / IT Executive: Schedule a 30-minute meeting with your IT Manager for Monday morning to initiate the 'descriptive cycle' by identifying a specific digital process (e.g., customer support ticket resolution) and confirming the availability of its digital trace data for analysis.
IT Manager: On Monday morning, begin by downloading and organizing the raw digital trace data logs (e.g., timestamps, event names, user IDs) for the chosen IT process from your systems and prepare to import them into a process mining tool.
Business Strategist: On Monday morning, prepare a concise list of 3-5 key business questions you want to understand about a specific digital process (e.g., 'Why is our customer onboarding taking so long?') to inform the 'explanatory cycle'.
Researcher: On Monday morning, review the provided case study from the research paper and begin to outline a potential scope for a process science study based on a digital process you have access to data for, focusing on defining the initial research questions.
Policymaker: On Monday morning, request a brief overview from your IT Executive and Business Strategist regarding the current state of understanding and identified inefficiencies within a key digital customer-facing process, preparing to guide future intervention strategies.

Process Science, Methodology, Iteration, Process Mining, Digital Trace Data, Socio-Technical Processes

AI Processed Human Approved

How can AI governance be adapted to fit local cultural and ethical values around the world?

Dimitrios Symeonidis, Johannes Schneider, Anastasija Nikiforova

TOWARD CULTURAL–ETHICAL FIT IN AI GOVERNANCE: A GLOBAL TYPOLOGY OF GOVERNANCE PROFILES

ECIS 2026 · 2026

Key findings

Identified eight distinct ideal-type AI governance profiles reflecting specific cultural and ethical alignments: group fairness, individual fairness, market-led growth, value-led growth, human oversight fortress, autonomous growth, individual control, and collective security.
Demonstrated that global AI governance is structured by two key meta-tensions: social justice versus economic competitiveness, and autonomy versus security and control.
Formulated three theoretical propositions outlining how cultural alignment determines governance legitimacy, shapes patterns of societal resistance, and guides regulatory evolution over time.
Offered a diagnostic decision framework for policymakers to adapt international AI guidelines to local socio-cultural contexts without sacrificing core safety requirements.

What it means for you

CIO / IT Executive: On Monday morning, schedule a 30-minute deep dive with your legal and ethics teams to identify which of the eight AI governance profiles identified in the research most closely aligns with your organization's current AI development and deployment practices, and flag any immediate misalignments.
IT Manager: On Monday morning, initiate a review of your team's current AI project documentation and development methodologies, specifically looking for instances where decisions about fairness, transparency, or accountability might have been implicitly influenced by a single cultural perspective (e.g., U.S.-centric) and note them for further discussion.
Business Strategist: On Monday morning, begin analyzing your organization's key international markets and identify the primary cultural value orientations that characterize them, then cross-reference this with the meta-tensions (social justice vs. economic competitiveness, autonomy vs. security) to anticipate potential governance friction for upcoming AI initiatives.
Researcher: On Monday morning, begin drafting a short literature review outline focusing on how cultural value orientations (e.g., individualism vs. collectivism) have historically shaped the adoption and regulation of other transformative technologies (e.g., the internet, biotechnology) to draw parallels with AI governance.
Policymaker: On Monday morning, review the 'diagnostic decision framework' mentioned in the research, and identify one specific AI guideline (e.g., data privacy regulations) that your jurisdiction currently applies universally, then brainstorm how to adapt its interpretation to better fit the dominant cultural value orientations of your primary constituent groups.

AI governance, cultural values, governance typology, ethical AI, regulatory design

AI Processed Human Approved

What roles can generative AI play in data quality management, and how should leaders govern them?

Karen Roht, Anastasija Nikiforova, Hippolyte Lefebvre

A Typology For Responsible Delegation Of Data Quality Management To Generative AI

ECIS 2026 · 2026

Key findings

Formulated a four-role typology for GenAI in DQM: Translator (natural language to rule logic), Explainer (narrative summaries of anomalies and metadata), Resolver (data correction suggestions), and Integrator (cross-system schema alignment).
Revealed that current GenAI adoption in commercial DQM tools remains nascent (~17%), functioning largely as an interpretive co-pilot rather than an autonomous decision-maker.
Proposed five theoretical governance guidelines highlighting task decomposability appraisal, mandatory human validation for high-impact actions, reverse delegation protocols, explainability standards, and retained human accountability.

What it means for you

CIO / IT Executive: On Monday morning, initiate a review of your organization's current DQM tool landscape to identify which, if any, are actively experimenting with or have integrated GenAI capabilities, and schedule a follow-up meeting with the IT Manager to discuss initial findings and potential pilot opportunities based on the 'Translator' role.
IT Manager: On Monday morning, dedicate an hour to review the existing data quality rulebooks and documentation within your team's purview, noting down specific areas where natural language descriptions of data quality issues or desired rules are prevalent, to prepare for a discussion with the CIO/IT Executive about the potential application of the 'Translator' GenAI role.
Business Strategist: On Monday morning, identify one critical business process that is currently hampered by data quality issues and then, using the 'Explainer' GenAI role as a conceptual framework, draft three potential narrative-style questions you would ask an AI about the root causes and impact of these data quality problems to present to stakeholders.
Researcher: On Monday morning, begin by outlining a research proposal to investigate the effectiveness and potential biases of GenAI 'Resolver' roles in correcting common data anomalies within a specific industry domain, drawing upon the governance guidelines related to mandatory human validation for high-impact actions.
Policymaker: On Monday morning, begin drafting a preliminary policy document that outlines the principle of 'retained human accountability' for any data quality decisions made or influenced by GenAI within the organization, focusing on the need for clear audit trails and oversight for 'Resolver' and 'Integrator' roles.

Data Quality Management, Generative AI, Human-AI Collaboration, AI Governance, Task Delegation, Agentic IS

AI Processed Human Approved

How does adopting smart speakers change how consumers search for, buy, and consume digital content?

Yoonseock Son, Wonseok Oh, Il Im

THE VOICE OF COMMERCE: HOW SMART SPEAKERS RESHAPE DIGITAL CONTENT CONSUMPTION AND PREFERENCES

MIS Quarterly · 2023

Key findings

Smart speaker adoption led to a 21.5% increase in monthly VOD content expenditures, alongside a 3.0% decrease in average content completion rates.
The increase in purchases is driven by lowered search friction, resulting in more search incidences, higher conversion rates, and less labor-intensive evaluation of content.
Using smart speakers for conversational purposes beyond simple informational queries amplifies the positive impact of device adoption on sales.

What it means for you

CIO / IT Executive: On Monday morning, task your team with investigating integration points between existing VOD platforms and major smart speaker voice assistant APIs (e.g., Alexa, Google Assistant) to enable seamless content discovery and playback via voice commands.
IT Manager: On Monday morning, analyze the current VOD platform's data infrastructure to identify how to track and log voice-initiated search queries and content playback events, distinguishing them from traditional remote control interactions.
Business Strategist: On Monday morning, initiate a brainstorm session to explore new content promotion strategies that leverage voice-activated search, considering how to make titles more discoverable through natural language queries and conversational recommendations.
Researcher: On Monday morning, begin outlining a follow-up study to quantify the correlation between specific conversational voice interactions (beyond simple search) and increased VOD content consumption, perhaps through A/B testing of voice-guided discovery features.
Policymaker: On Monday morning, convene a working group to assess the potential implications of increased voice-activated content consumption on digital accessibility standards and to explore how to ensure equitable access to content across all user interfaces.

Voice channel, search, smart speaker, digital content, econometrics

AI Processed Human Approved

How can organizations effectively design and implement artificial intelligence to support business decision-making?

Savindu Herath Pathirannehelage, Yash Raj Shrestha, Georg von Krogh

Design principles for artificial intelligence-augmented decision making: An action design research study

European Journal of Information Systems · 2024

Key findings

Formulate a strategic data roadmap aligning AIADM use cases with business model requirements, resources, and capabilities.
Ensure synergy across input data, AI models, and visual outputs to demonstrate tangible business value.
Implement ethical AI governance frameworks and auditing mechanisms to ensure compliance and build stakeholder trust.
Maintain human involvement in design and execution to integrate domain expertise and retain decision accountability.
Embrace an iterative design mindset focused on continuous learning, adaptation, and system improvement over time.
Utilize open-source tools and external expert partnerships to mitigate talent and resource limitations.

What it means for you

CIO / IT Executive: On Monday morning, schedule a 30-minute kickoff meeting with your heads of data science, infrastructure, and business intelligence to review the company's current AIADM initiatives and identify one high-priority business model requirement for AIADM to address within the next quarter.
IT Manager: On Monday morning, initiate a preliminary audit of existing data pipelines and AI model repositories, specifically noting any inconsistencies or gaps in documentation that hinder synergy between input data, AI models, and visual outputs.
Business Strategist: On Monday morning, draft a concise one-page document outlining at least two specific AIADM use cases that directly align with the company's current strategic objectives, identifying the key data inputs and desired decision outcomes for each.
Researcher: On Monday morning, review the internal documentation for the AIADM system currently in use, and identify one specific instance where human domain expertise could have significantly improved the AI's output or decision recommendation.
Policymaker: On Monday morning, begin drafting a preliminary checklist of essential components for an ethical AI governance framework, focusing on elements relevant to data privacy, bias detection, and clear lines of decision accountability for AI-augmented decisions.

AI-augmented decision making, artificial intelligence, decision support systems, design principles, action design research, human-AI ensemble

AI Processed Human Approved

How can organizations turn responsible artificial intelligence principles into practical governance practices?

Emmanouil Papagiannidis, Patrick Mikalef, Kieran Conboy

Responsible artificial intelligence governance: A review and research framework

2025

Key findings

Synthesizes prior research on responsible AI into seven core principles: accountability, diversity and fairness, human agency and oversight, privacy and data governance, technical robustness and safety, transparency, and social and environmental well-being.
Establishes a tripartite framework for responsible AI governance comprising structural (roles and authority), procedural (processes and evaluation), and relational (collaboration and literacy) practices.
Maps the contextual antecedents of AI governance, including evolving societal norms and organizational values, as well as its effects on business value and social assessment.
Formulates a detailed research agenda with key questions to guide future academic inquiry and practical implementation.

What it means for you

CIO / IT Executive: On Monday morning, initiate a review of your organization's current AI project lifecycle documentation to identify where the seven core responsible AI principles (accountability, diversity & fairness, human agency & oversight, privacy & data governance, technical robustness & safety, transparency, and social & environmental well-being) are explicitly addressed and where gaps exist, preparing to assign ownership for these areas.
IT Manager: On Monday morning, schedule a 30-minute meeting with your team responsible for AI development or deployment to collaboratively identify one specific AI project that could benefit from enhanced procedural practices (e.g., implementing a new risk assessment checklist based on transparency principles) and assign a team member to draft this enhancement by Friday.
Business Strategist: On Monday morning, dedicate an hour to researching how responsible AI governance (structural, procedural, and relational practices) could directly contribute to your organization's stated business objectives and competitive advantage, identifying at least one concrete opportunity to explore further.
Researcher: On Monday morning, select one of the seven core responsible AI principles that you find most underdeveloped in current practice and spend two hours identifying three specific research questions from the provided framework that directly address operationalizing this principle, preparing to draft a short proposal for investigation.
Policymaker: On Monday morning, dedicate an hour to identifying which of the seven core responsible AI principles your current regulatory framework or internal policies address most weakly, and then draft a one-page summary of potential areas for future policy development or amendment, focusing on bridging the gap between abstract principles and actionable practices.

Artificial intelligence, Responsible AI governance, Governance practices, AI implementation, AI lifecycle, Trustworthy AI

AI Processed Human Approved

How does collaborative course redesign affect student performance, teaching consistency, and instructor confidence?

John Michael Muraski, Donald H. Heath, Michael A. Eierman, Michael Patton

Efficacy Beliefs and Outcomes: Socio-Cognitive Perspectives on a Faculty-Led coP

AIS SIGED International Conference on Information Systems Education and Research (SIGED) · 2023

Key findings

Student performance showed consistent, measurable gains across multiple semesters following the course redesign, as demonstrated by improved pre- and post-test assessment deltas.
Participation in the community of practice positively impacted instructors' self-efficacy beliefs, with vicarious learning and peer verbal persuasion emerging as key drivers of confidence.
The collaborative approach established high course consistency across sections while creating a durable, supportive framework for peer mentoring and ongoing curriculum enhancement.

What it means for you

CIO / IT Executive: On Monday morning, schedule a 30-minute meeting with your IT academic technology support lead to explore a pilot program implementing a Communities of Practice model for a high-enrollment introductory course, using the provided research as a framework for discussion on potential student outcome improvements and faculty development.
IT Manager: On Monday morning, gather the instructors for the introductory information systems course for a 45-minute session. Share the key findings of this research, specifically highlighting the gains in student performance and instructor self-efficacy. Then, collaboratively brainstorm one small, concrete change to the course syllabus or assessment that can be implemented next semester as a collective first step towards greater consistency.
Business Strategist: On Monday morning, analyze the current onboarding and ongoing professional development process for new faculty teaching foundational courses. Identify any gaps in collaborative support and informal learning opportunities, and consider how principles from this research, such as vicarious learning and peer persuasion, could be integrated into existing programs to improve faculty confidence and course consistency.
Researcher: On Monday morning, begin drafting a proposal for a follow-up study. Focus on investigating the specific mechanisms of vicarious learning and peer verbal persuasion within the identified Community of Practice, perhaps through targeted surveys or observation protocols, to quantify their impact on instructor self-efficacy and to better understand how to scale these findings.
Policymaker: On Monday morning, initiate a discussion with the Provost's office and the Faculty Senate leadership to present the findings of this research. Propose the development of a university-wide framework or grant program that incentivizes and supports the formation of faculty Communities of Practice for foundational courses, emphasizing the potential for improved student learning outcomes and faculty development.

Community of Practice, Self-Efficacy, Course Redesign, Social Cognitive Theory, Information Systems Education, Participatory Action Research

AI Processed Human Approved

How can practitioner researchers overcome the divide between academia and industry to create real-world impact?

Stephen McCarthy, Hendrik Scholta, Geir Inge Hausvik, Peter André Busch

Boundary Spanning and Practical Impact in IS Research: A Bourdieusian Analysis

Information Systems Journal (ISJ) · 2025

Key findings

IS practitioner doctorates facilitate knowledge exchange through boundary-spanning activities including research design adaptation, multi-channel dissemination, and creating symbolic discourse.
Practical impact progresses through proof-of-concept, proof-of-value, and proof-of-use stages, each requiring different combinations of social, cultural, economic, and symbolic capital.
Environmental forces such as academic vs. practice doxa (institutional norms) and habitus (professional dispositions) create positional conflicts that require active negotiation and tailored incentives to sustain engagement.

What it means for you

CIO / IT Executive: On Monday morning, schedule a 30-minute meeting with your direct reports to initiate a 'practice impact review' focused on one ongoing IS project. Ask each person to identify one specific academic insight or research finding from a recent external study or internal research initiative that could be directly applied to improve that project's current proof-of-concept or proof-of-value stage, and assign them to explore this application by end of week.
IT Manager: On Monday morning, identify one specific, recent academic paper or conference proceeding relevant to a current team challenge. Forward this paper to your team with a concise note asking for a brief, 1-2 sentence summary of its most practical takeaway and how it *might* apply to your current proof-of-value stage objective by Tuesday afternoon.
Business Strategist: On Monday morning, review the key performance indicators (KPIs) of one strategic business initiative currently underway. Identify which KPIs are not meeting expectations and, using the 'proof-of-value' framework, draft a one-page hypothesis on how a novel IS application or process, potentially informed by academic research, could demonstrably improve these specific KPIs within the next quarter.
Researcher: On Monday morning, select one recent academic publication where you are the lead author and identify its 'proof-of-use' stage potential. Draft a single-slide executive summary that articulates the core problem addressed, the practical solution proposed, and one tangible benefit for a specific industry practitioner role (e.g., IT manager, business analyst), and share it with three relevant practitioner contacts for feedback by Wednesday.
Policymaker: On Monday morning, review the current grant application criteria for technology innovation funding. Identify if and how 'demonstrable practical impact' is explicitly assessed, and draft a brief proposal to incorporate a specific requirement for applicants to detail their strategy for achieving 'proof-of-value' or 'proof-of-use' within a defined timeframe, alongside theoretical contributions.

academia-practice gap, boundary spanning, design science research, engaged IS scholarship, practical impact, theory of practice

AI Processed Human Approved

How can digital data be used to understand and guide ongoing changes involving people and technology?

Jan vom Brocke, Wil M. P. van der Aalst, Nicholas Berente, Boudewijn van Dongen, Thomas Grisold, Waldemar Kremser, Jan Mendling, Brian T. Pentland, Maximilian Roeglinger, Michael Rosemann, Barbara Weber

Process science: the interdisciplinary study of socio-technical change

Process Science · 2024

Key findings

Defines process science as an interdisciplinary domain aimed at capturing, understanding, and intervening in socio-technical change across multiple levels of abstraction.
Categorizes key activities of process science into discovery (detecting patterns via event data), explanation (identifying cause-effect relations), and intervention (shaping process trajectories).
Advocates for shifting from an 'entity-first' to a 'process-first' perspective to identify analogies across diverse domains and support computationally intensive theory building.
Introduces a research framework that integrates digital trace data from practice with theoretical foundations to solve real-world problems and drive societal impact.

What it means for you

CIO / IT Executive: On Monday morning, initiate a review of your organization's current digital infrastructure and data collection capabilities to identify which systems generate 'digital trace data' relevant to socio-technical processes. Prioritize understanding the flow of this data and its potential for analysis.
IT Manager: On Monday morning, investigate your team's current methods for logging and tracking user interactions with key IT systems. Identify specific 'events' that could be captured and analyzed to reveal patterns of socio-technical change within your department.
Business Strategist: On Monday morning, schedule a brainstorming session with your core team to identify one specific business process currently undergoing significant change (e.g., customer onboarding, product development). Brainstorm what digital 'trace data' this process generates and how understanding its dynamics could inform strategy.
Researcher: On Monday morning, start cataloging existing datasets within your research domain that represent 'digital traces' of human-technology interaction. Begin exploring computational tools that can analyze event sequences rather than just static entities.
Policymaker: On Monday morning, identify a specific public policy area (e.g., digital inclusion, citizen engagement) that is experiencing rapid socio-technical evolution. Begin researching existing digital platforms and services that generate trace data related to this policy area.

Process Science, Socio-Technical Processes, Digital Trace Data, Process Mining, Organizational Change, Interdisciplinary Research

AI Processed Human Approved

How do virtual worlds help people with lifelong disabilities move from social isolation to social inclusion?

Karen Stendal, Maung K. Sein, Devinder Thapa

Affordance-Based Pathway Model of Social Inclusion: A Case Study of Virtual Worlds and People With Lifelong Disability

Journal of the Association for Information Systems · 2026

Key findings

Identified three functional affordances (communicability, mobility, and personalizability) and two social affordances (engageability and self-actualizability) crucial for social inclusion.
Established that the actualization of functional affordances enables and dynamically interacts with social affordances to foster interpersonal relationships and community participation.
Discovered that outcomes achieved by actualizing specific affordances serve as facilitating conditions that support the perception and realization of additional affordances.
Extended affordance theory by demonstrating a feedback loop where social engagement refines and enhances the perception and use of basic functional capabilities.

What it means for you

CIO / IT Executive: On Monday morning, task your accessibility team to conduct an initial assessment of our current platform's 'communicability' features (e.g., real-time chat, group messaging, avatar-based interaction quality) against the research's identified functional affordances to understand potential barriers and opportunities for individuals with disabilities.
IT Manager: On Monday morning, schedule a 30-minute working session with your frontline support staff to review existing user feedback logs for mentions of difficulty with navigation, communication, or customization within our virtual environment, specifically looking for patterns that might align with limitations in perceived 'mobility' or 'personalizability' affordances.
Business Strategist: On Monday morning, initiate a competitive analysis focusing on how emerging virtual platforms or digital communities are leveraging 'engageability' and 'self-actualizability' affordances to foster user connection and content creation, particularly noting any strategies that might appeal to or benefit users with disabilities.
Researcher: On Monday morning, begin drafting a protocol for a pilot study within our organization's virtual world that focuses on measuring the impact of enhanced 'communicability' features on user-reported feelings of 'engageability' and 'self-actualizability' among a diverse user group, potentially including participants with disabilities.
Policymaker: On Monday morning, convene a brief meeting with your advisory committee to discuss how current digital inclusion policies might be strengthened by explicitly incorporating the research's identified 'functional affordances' (communicability, mobility, personalizability) and 'social affordances' (engageability, self-actualizability) as measurable criteria for assessing technological accessibility and support for social participation.

Social Inclusion, Virtual Worlds, People With Lifelong Disability, Affordances, Second Life, ICT

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

AI Processed Human Approved

How do people experience and make sense of their bodies in immersive virtual reality?

Amir Haj-Bolouri

The Philosopher’s Corner: The “Immersed Flesh”: A Phenomenological Conceptualization of Immersive Virtual Reality Embodiment

ACM SIGMIS Database: the DATABASE for Advances in Information Systems · 2025

Key findings

Conceptualizes IVR embodiment through the new concept of 'Immersed Flesh', defined as a dynamic matrix that merges physical and virtual worlds into a co-extensive reality.
Adapts Merleau-Ponty's ontology of the Flesh into key structural elements for IS, including Actual Grip, Apparent Grip, Circuit, Chiasma, Interworld, Measuring Body, and Reversibility.
Illustrates the practical and theoretical value of the framework through three distinct IVR scenarios: expressing the living body (e.g., IVR dancing), intersubjective perspective-taking (e.g., embodying a tree), and experiencing the objective body of passing entities (e.g., avatars of deceased relatives).
Generates research questions for future IS inquiry into user self-agency, bodily empathy, and ethical considerations surrounding virtual presence.

What it means for you

CIO / IT Executive: On Monday morning, schedule a 30-minute briefing for your senior IT team to introduce the concept of 'Immersed Flesh' as a potential lens for evaluating our next-generation immersive technology investments, specifically focusing on how it moves beyond purely functional metrics to consider user experience and embodiment.
IT Manager: On Monday morning, gather your team responsible for VR development or deployment and ask them to review our current IVR platforms and identify one specific feature or interaction where users might be experiencing something akin to 'Actual Grip' or 'Apparent Grip' as described in the 'Immersed Flesh' concept.
Business Strategist: On Monday morning, dedicate one hour to brainstorm three hypothetical business use cases where fostering 'bodily empathy' or enhancing 'user self-agency' through IVR, inspired by the 'Immersed Flesh' framework, could provide a competitive advantage or solve a current business challenge.
Researcher: On Monday morning, draft a preliminary research proposal outline that incorporates at least two of the structural elements from the 'Immersed Flesh' framework (e.g., Chiasma, Interworld) to investigate user embodiment in a specific IVR application relevant to our field.
Policymaker: On Monday morning, request a brief (1-page) summary of the 'Immersed Flesh' concept from your policy research unit, specifically asking them to highlight any potential ethical implications or policy considerations related to virtual presence and user embodiment in immersive technologies.

Immersive Virtual Reality, Embodiment, Phenomenology, Information Systems, Merleau-Ponty

AI Processed Human Approved

How can organizations successfully manage and sustain digital transformations over the long term?

Noel Carroll, Nik Rushdi Hassan, Iris Junglas, Thomas Hess, Lorraine Morgan

Transform or be transformed: the importance of research on managing and sustaining digital transformations

European Journal of Information Systems · 2023

Key findings

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.

What it means for you

CIO / IT Executive: On Monday morning, schedule a 30-minute meeting with your direct reports to discuss the 'execution engine' concept and brainstorm one specific process within your IT department that needs fundamental adaptation for long-term digital transformation success. Assign one person to draft a brief proposal by end-of-week.
IT Manager: On Monday morning, identify one digital initiative currently underway that is showing signs of slowing adoption or unexpected friction. Gather the project team for a 1-hour 'root cause analysis' session, focusing specifically on potential cultural or structural obstacles, not just technical issues, and document the top 2-3 hypothesized causes.
Business Strategist: On Monday morning, review your organization's current digital transformation roadmap and flag any objectives that are solely focused on short-term adoption metrics. Draft a list of 3-5 questions to explore how these objectives will be sustained and normalized over the next 1-3 years, and schedule a preliminary discussion with your team by Wednesday.
Researcher: On Monday morning, analyze your current research project's data collection plan. Identify if it allows for longitudinal observation of digital transformation normalization (beyond initial adoption) and, if not, sketch out one modification to incorporate this perspective in future data gathering or analysis.
Policymaker: On Monday morning, review existing public funding guidelines or incentives for digital transformation. Identify one specific criterion or reporting requirement that might unintentionally discourage longitudinal sustainability efforts and draft a brief memo suggesting a minor amendment to encourage long-term impact.

Digital Transformation, Managing, Sustaining, Research Agenda, Socio-technical Factors, Citizen Development

AI Processed Human Approved

What makes security risk management programs effective, and how do priorities differ between managers and staff?

Jason A. Williams, Humayun Zafar, Saurabh Gupta

Critical Success Factors for an Effective Security Risk Management Program: An Exploratory Case Study

2026

Key findings

Confirmed six initial Critical Success Factors (CSFs) from existing literature: Executive Management Support, Organizational Maturity, Open Communication, Risk Management Stakeholders, Team Member Empowerment, and Holistic View of an Organization.
Identified three newly extracted CSFs from empirical evidence: Security Maintenance, Corporate Security Strategy, and Human Resource Development.
Discovered key perception differences across organizational levels, with management prioritizing Executive Management Support and staff ranking Open Communication as most essential.
Emphasized that effective SRM programs require continuous policy updates, joint management-staff governance committees, and alignment between security goals and overall business strategy.

What it means for you

CIO / IT Executive: On Monday morning, schedule a 15-minute call with your direct reports, specifically the heads of IT Security and IT Operations, to review the 'Corporate Security Strategy' CSF and discuss how the current IT security roadmap directly supports two specific, measurable business objectives for Q3. Ask them to come prepared with one example for each.
IT Manager: On Monday morning, initiate a 'lunch and learn' session invitation for your team scheduled for next week, focusing on a specific, practical aspect of 'Human Resource Development' related to security, such as a short demo on identifying and reporting phishing emails securely. Request that team members bring one question they have about our current security policies.
Business Strategist: On Monday morning, identify and document two specific business processes within your department that currently have the weakest security controls, using the 'Holistic View of an Organization' CSF as a lens. Draft a brief, one-paragraph summary of the potential risks associated with these weaknesses to share with the IT Security team by end-of-day.
Researcher: On Monday morning, begin a systematic review of the interview transcripts from your case study, specifically tagging every instance where participants mention 'Open Communication' or 'Team Member Empowerment'. Note the organizational level of the speaker for each tag to facilitate your analysis of perception differences.
Policymaker: On Monday morning, draft an agenda for a joint management-staff governance committee meeting focused on reviewing and proposing updates to one specific security policy (e.g., password complexity, data handling). Identify two key areas within that policy that have historically seen low compliance and propose specific, actionable changes to address them.

Information Security, Security Risk Management, Critical Success Factors, Case Study, Q-Sort, Security Governance

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

AI Processed Human Approved

How can artificial intelligence simplify complex privacy policies while maintaining their essential legal accuracy?

Al Maha Al Jabor, Shahad Adnan Astaneh, Manoranjan Mohanty, Chadi Aoun

Automated Privacy Policy Simplification through a GPT-Powered Chrome Extension

International Conference on Information Systems (ICIS) · 2025

Key findings

The audience-adjusted rewriting prompt ('rewrite so a 10th-grade student can understand while maintaining legal accuracy') produced the highest readability improvements while preserving core legal content.
Readability metrics improved substantially after simplification, with Flesch Reading Ease increasing significantly and complexity indices like Flesch-Kincaid Grade Level dropping sharply.
ROUGE content evaluation metrics (ROUGE-1 Precision = 0.8862, ROUGE-L Precision = 0.6025) confirmed strong textual overlap and high fidelity to original legal terms.
A prototype Chrome extension was created, enabling real-time policy summarization and context-aware Q&A capabilities grounded in the APCO theoretical framework.

What it means for you

CIO / IT Executive: On Monday morning, initiate a pilot program to evaluate the integration of a GPT-powered privacy policy simplification Chrome extension across a select department, focusing on user adoption and feedback regarding usability and perceived value.
IT Manager: On Monday morning, prepare a technical feasibility assessment for deploying the developed Chrome extension across the organization's standard user workstations, outlining any necessary infrastructure changes or security considerations.
Business Strategist: On Monday morning, analyze how the real-time privacy policy simplification and Q&A features of the Chrome extension can be leveraged to enhance user trust and potentially create a competitive differentiator for our online services.
Researcher: On Monday morning, begin designing an experiment to test the effectiveness of the audience-adjusted rewriting prompt ('rewrite so a 10th-grade student can understand while maintaining legal accuracy') with a new set of privacy policies from a different industry sector.
Policymaker: On Monday morning, review the research findings on improved readability and content preservation to draft talking points for discussions on enhancing consumer understanding of digital service terms and conditions.

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

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

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